Datasets:

mtpti5iD
/

redhat-docs_dataset

Dataset card Data Studio Files Files and versions Community

Split (2)

train · 44.6k rows

Subsets and Splits

title stringlengths 4 168	content stringlengths 7 1.74M	commands sequencelengths 1 5.62k ⌀	url stringlengths 79 342
Chapter 2. New features and enhancements	Chapter 2. New features and enhancements Red Hat JBoss Web Server 6.0 Service Pack 1 includes the following new features and enhancements. 2.1. Location changes for tomcat-websocket-chat quick start application This release includes the following changes to the location of the example tomcat-websocket-chat quick start application that you can use with JWS for OpenShift: The URL for the quick start has changed from https://github.com/jboss-openshift/openshift-quickstarts to https://github.com/web-servers/tomcat-websocket-chat-quickstart . The git repository for the quick start has changed from https://github.com/jboss-openshift/openshift-quickstarts.git to https://github.com/web-servers/tomcat-websocket-chat-quickstart.git . The directory path for the quick start has changed from openshift-quickstarts/tomcat-websocket-chat to tomcat-websocket-chat-quickstart/tomcat-websocket-chat .	null	https://docs.redhat.com/en/documentation/red_hat_jboss_web_server/6.0/html/red_hat_jboss_web_server_6.0_service_pack_1_release_notes/new_features_and_enhancements
9.9. Securing Server Connections	9.9. Securing Server Connections After designing the authentication scheme for identified users and the access control scheme for protecting information in the directory, the step is to design a way to protect the integrity of the information as it passes between servers and client applications. For both server to client connections and server to server connections, the Directory Server supports a variety of secure connection types: Transport Layer Security (TLS) . To provide secure communications over the network, the Directory Server can use LDAP over the Transport Layer Security (TLS). TLS can be used in conjunction with encryption algorithms from RSA. The encryption method selected for a particular connection is the result of a negotiation between the client application and Directory Server. Start TLS . Directory Server also supports Start TLS, a method of initiating a Transport Layer Security (TLS) connection over a regular, unencrypted LDAP port. Simple Authentication and Security Layer (SASL) . SASL is a security framework, meaning that it sets up a system that allows different mechanisms to authenticate a user to the server, depending on what mechanism is enabled in both client and server applications. It can also establish an encrypted session between the client and a server. In Directory Server, SASL is used with GSS-API to enable Kerberos logins and can be used for almost all server to server connections, including replication, chaining, and pass-through authentication. (SASL cannot be used with Windows Sync.) Secure connections are recommended for any operations which handle sensitive information, like replication, and are required for some operations, like Windows password synchronization. Directory Server can support TLS connections, SASL, and non-secure connections simultaneously. Both SASL authentication and TLS connections can be configured at the same time. For example, the Directory Server instance can be configured to require TLS connections to the server and also support SASL authentication for replication connections. This means it is not necessary to choose whether to use TLS or SASL in a network environment; you can use both. It is also possible to set a minimum level of security for connections to the server. The security strength factor measures, in key strength, how strong a secure connection is. An ACI can be set that requires certain operations (like password changes) only occur if the connection is of a certain strength or higher. It is also possible to set a minimum SSF, which can essentially disable standard connections and requires TLS, Start TLS, or SASL for every connection. The Directory Server supports TLS and SASL simultaneously, and the server calculates the SSF of all available connection types and selects the strongest. For more information about using TLS, Start TLS, and SASL, check out the Administration Guide .	null	https://docs.redhat.com/en/documentation/red_hat_directory_server/11/html/deployment_guide/Designing_a_Secure_Directory-Securing_Connections_with_TLS_and_Start_TLS
Provisioning APIs	Provisioning APIs OpenShift Container Platform 4.17 Reference guide for provisioning APIs Red Hat OpenShift Documentation Team	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.17/html-single/provisioning_apis/index
Chapter 6. Configure Host Names	Chapter 6. Configure Host Names 6.1. Understanding Host Names There are three classes of hostname : static, pretty, and transient. The " static " host name is the traditional hostname , which can be chosen by the user, and is stored in the /etc/hostname file. The " transient " hostname is a dynamic host name maintained by the kernel. It is initialized to the static host name by default, whose value defaults to " localhost " . It can be changed by DHCP or mDNS at runtime. The " pretty " hostname is a free-form UTF8 host name for presentation to the user. Note A host name can be a free-form string up to 64 characters in length. However, Red Hat recommends that both static and transient names match the fully-qualified domain name ( FQDN ) used for the machine in DNS , such as host.example.com . It is also recommended that the static and transient names consists only of 7 bit ASCII lower-case characters, no spaces or dots, and limits itself to the format allowed for DNS domain name labels, even though this is not a strict requirement. Older specifications do not permit the underscore, and so their use is not recommended. The hostnamectl tool will enforce the following: Static and transient host names to consist of a-z , A-Z , 0-9 , " - " , " _ " and " . " only, to not begin or end in a dot, and to not have two dots immediately following each other. The size limit of 64 characters is enforced. 6.1.1. Recommended Naming Practices The Internet Corporation for Assigned Names and Numbers (ICANN) sometimes adds previously unregistered Top-Level Domains (such as .yourcompany ) to the public register. Therefore, Red Hat strongly recommends that you do not use a domain name that is not delegated to you, even on a private network, as this can result in a domain name that resolves differently depending on network configuration. As a result, network resources can become unavailable. Using domain names that are not delegated to you also makes DNSSEC more difficult to deploy and maintain, as domain name collisions require manual configuration to enable DNSSEC validation. See the ICANN FAQ on domain name collision for more information on this issue.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/networking_guide/ch-configure_host_names
2.3. LVM Logical Volumes	2.3. LVM Logical Volumes In LVM, a volume group is divided up into logical volumes. The following sections describe the different types of logical volumes. 2.3.1. Linear Volumes A linear volume aggregates space from one or more physical volumes into one logical volume. For example, if you have two 60GB disks, you can create a 120GB logical volume. The physical storage is concatenated. Creating a linear volume assigns a range of physical extents to an area of a logical volume in order. For example, as shown in Figure 2.2, "Extent Mapping" logical extents 1 to 99 could map to one physical volume and logical extents 100 to 198 could map to a second physical volume. From the point of view of the application, there is one device that is 198 extents in size. Figure 2.2. Extent Mapping The physical volumes that make up a logical volume do not have to be the same size. Figure 2.3, "Linear Volume with Unequal Physical Volumes" shows volume group VG1 with a physical extent size of 4MB. This volume group includes 2 physical volumes named PV1 and PV2 . The physical volumes are divided into 4MB units, since that is the extent size. In this example, PV1 is 200 extents in size (800MB) and PV2 is 100 extents in size (400MB). You can create a linear volume any size between 1 and 300 extents (4MB to 1200MB). In this example, the linear volume named LV1 is 300 extents in size. Figure 2.3. Linear Volume with Unequal Physical Volumes You can configure more than one linear logical volume of whatever size you require from the pool of physical extents. Figure 2.4, "Multiple Logical Volumes" shows the same volume group as in Figure 2.3, "Linear Volume with Unequal Physical Volumes" , but in this case two logical volumes have been carved out of the volume group: LV1 , which is 250 extents in size (1000MB) and LV2 which is 50 extents in size (200MB). Figure 2.4. Multiple Logical Volumes 2.3.2. Striped Logical Volumes When you write data to an LVM logical volume, the file system lays the data out across the underlying physical volumes. You can control the way the data is written to the physical volumes by creating a striped logical volume. For large sequential reads and writes, this can improve the efficiency of the data I/O. Striping enhances performance by writing data to a predetermined number of physical volumes in round-robin fashion. With striping, I/O can be done in parallel. In some situations, this can result in near-linear performance gain for each additional physical volume in the stripe. The following illustration shows data being striped across three physical volumes. In this figure: the first stripe of data is written to the first physical volume the second stripe of data is written to the second physical volume the third stripe of data is written to the third physical volume the fourth stripe of data is written to the first physical volume In a striped logical volume, the size of the stripe cannot exceed the size of an extent. Figure 2.5. Striping Data Across Three PVs Striped logical volumes can be extended by concatenating another set of devices onto the end of the first set. In order to extend a striped logical volume, however, there must be enough free space on the set of underlying physical volumes that make up the volume group to support the stripe. For example, if you have a two-way stripe that uses up an entire volume group, adding a single physical volume to the volume group will not enable you to extend the stripe. Instead, you must add at least two physical volumes to the volume group. For more information on extending a striped volume, see Section 4.4.17, "Extending a Striped Volume" . 2.3.3. RAID Logical Volumes LVM supports RAID0/1/4/5/6/10. An LVM RAID volume has the following characteristics: RAID logical volumes created and managed by means of LVM leverage the MD kernel drivers. RAID1 images can be temporarily split from the array and merged back into the array later. LVM RAID volumes support snapshots. For information on creating RAID logical volumes, see Section 4.4.3, "RAID Logical Volumes" . Note RAID logical volumes are not cluster-aware. While RAID logical volumes can be created and activated exclusively on one machine, they cannot be activated simultaneously on more than one machine. 2.3.4. Thinly-Provisioned Logical Volumes (Thin Volumes) Logical volumes can be thinly provisioned. This allows you to create logical volumes that are larger than the available extents. Using thin provisioning, you can manage a storage pool of free space, known as a thin pool, which can be allocated to an arbitrary number of devices when needed by applications. You can then create devices that can be bound to the thin pool for later allocation when an application actually writes to the logical volume. The thin pool can be expanded dynamically when needed for cost-effective allocation of storage space. Note Thin volumes are not supported across the nodes in a cluster. The thin pool and all its thin volumes must be exclusively activated on only one cluster node. By using thin provisioning, a storage administrator can overcommit the physical storage, often avoiding the need to purchase additional storage. For example, if ten users each request a 100GB file system for their application, the storage administrator can create what appears to be a 100GB file system for each user but which is backed by less actual storage that is used only when needed. Note When using thin provisioning, it is important that the storage administrator monitor the storage pool and add more capacity if it starts to become full. To make sure that all available space can be used, LVM supports data discard. This allows for re-use of the space that was formerly used by a discarded file or other block range. For information on creating thin volumes, see Section 4.4.5, "Creating Thinly-Provisioned Logical Volumes" . Thin volumes provide support for a new implementation of copy-on-write (COW) snapshot logical volumes, which allow many virtual devices to share the same data in the thin pool. For information on thin snapshot volumes, see Section 2.3.6, "Thinly-Provisioned Snapshot Volumes" . 2.3.5. Snapshot Volumes The LVM snapshot feature provides the ability to create virtual images of a device at a particular instant without causing a service interruption. When a change is made to the original device (the origin) after a snapshot is taken, the snapshot feature makes a copy of the changed data area as it was prior to the change so that it can reconstruct the state of the device. Note LVM supports thinly-provisioned snapshots. For information on thinly provisioned snapshot volumes, see Section 2.3.6, "Thinly-Provisioned Snapshot Volumes" . Note LVM snapshots are not supported across the nodes in a cluster. You cannot create a snapshot volume in a clustered volume group. Because a snapshot copies only the data areas that change after the snapshot is created, the snapshot feature requires a minimal amount of storage. For example, with a rarely updated origin, 3-5 % of the origin's capacity is sufficient to maintain the snapshot. Note Snapshot copies of a file system are virtual copies, not an actual media backup for a file system. Snapshots do not provide a substitute for a backup procedure. The size of the snapshot governs the amount of space set aside for storing the changes to the origin volume. For example, if you made a snapshot and then completely overwrote the origin the snapshot would have to be at least as big as the origin volume to hold the changes. You need to dimension a snapshot according to the expected level of change. So for example a short-lived snapshot of a read-mostly volume, such as /usr , would need less space than a long-lived snapshot of a volume that sees a greater number of writes, such as /home . If a snapshot runs full, the snapshot becomes invalid, since it can no longer track changes on the origin volume. You should regularly monitor the size of the snapshot. Snapshots are fully resizable, however, so if you have the storage capacity you can increase the size of the snapshot volume to prevent it from getting dropped. Conversely, if you find that the snapshot volume is larger than you need, you can reduce the size of the volume to free up space that is needed by other logical volumes. When you create a snapshot file system, full read and write access to the origin stays possible. If a chunk on a snapshot is changed, that chunk is marked and never gets copied from the original volume. There are several uses for the snapshot feature: Most typically, a snapshot is taken when you need to perform a backup on a logical volume without halting the live system that is continuously updating the data. You can execute the fsck command on a snapshot file system to check the file system integrity and determine whether the original file system requires file system repair. Because the snapshot is read/write, you can test applications against production data by taking a snapshot and running tests against the snapshot, leaving the real data untouched. You can create LVM volumes for use with Red Hat Virtualization. LVM snapshots can be used to create snapshots of virtual guest images. These snapshots can provide a convenient way to modify existing guests or create new guests with minimal additional storage. For information on creating LVM-based storage pools with Red Hat Virtualization, see the Virtualization Administration Guide . For information on creating snapshot volumes, see Section 4.4.6, "Creating Snapshot Volumes" . You can use the --merge option of the lvconvert command to merge a snapshot into its origin volume. One use for this feature is to perform system rollback if you have lost data or files or otherwise need to restore your system to a state. After you merge the snapshot volume, the resulting logical volume will have the origin volume's name, minor number, and UUID and the merged snapshot is removed. For information on using this option, see Section 4.4.9, "Merging Snapshot Volumes" . 2.3.6. Thinly-Provisioned Snapshot Volumes Red Hat Enterprise Linux provides support for thinly-provisioned snapshot volumes. Thin snapshot volumes allow many virtual devices to be stored on the same data volume. This simplifies administration and allows for the sharing of data between snapshot volumes. As for all LVM snapshot volumes, as well as all thin volumes, thin snapshot volumes are not supported across the nodes in a cluster. The snapshot volume must be exclusively activated on only one cluster node. Thin snapshot volumes provide the following benefits: A thin snapshot volume can reduce disk usage when there are multiple snapshots of the same origin volume. If there are multiple snapshots of the same origin, then a write to the origin will cause one COW operation to preserve the data. Increasing the number of snapshots of the origin should yield no major slowdown. Thin snapshot volumes can be used as a logical volume origin for another snapshot. This allows for an arbitrary depth of recursive snapshots (snapshots of snapshots of snapshots...). A snapshot of a thin logical volume also creates a thin logical volume. This consumes no data space until a COW operation is required, or until the snapshot itself is written. A thin snapshot volume does not need to be activated with its origin, so a user may have only the origin active while there are many inactive snapshot volumes of the origin. When you delete the origin of a thinly-provisioned snapshot volume, each snapshot of that origin volume becomes an independent thinly-provisioned volume. This means that instead of merging a snapshot with its origin volume, you may choose to delete the origin volume and then create a new thinly-provisioned snapshot using that independent volume as the origin volume for the new snapshot. Although there are many advantages to using thin snapshot volumes, there are some use cases for which the older LVM snapshot volume feature may be more appropriate to your needs: You cannot change the chunk size of a thin pool. If the thin pool has a large chunk size (for example, 1MB) and you require a short-living snapshot for which a chunk size that large is not efficient, you may elect to use the older snapshot feature. You cannot limit the size of a thin snapshot volume; the snapshot will use all of the space in the thin pool, if necessary. This may not be appropriate for your needs. In general, you should consider the specific requirements of your site when deciding which snapshot format to use. Note When using thin provisioning, it is important that the storage administrator monitor the storage pool and add more capacity if it starts to become full. For information on configuring and displaying information on thinly-provisioned snapshot volumes, see Section 4.4.7, "Creating Thinly-Provisioned Snapshot Volumes" . 2.3.7. Cache Volumes As of the Red Hat Enterprise Linux 7.1 release, LVM supports the use of fast block devices (such as SSD drives) as write-back or write-through caches for larger slower block devices. Users can create cache logical volumes to improve the performance of their existing logical volumes or create new cache logical volumes composed of a small and fast device coupled with a large and slow device. For information on creating LVM cache volumes, see Section 4.4.8, "Creating LVM Cache Logical Volumes" .	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/logical_volume_manager_administration/lv_overview
3.6. Do You Have Enough Disk Space?	3.6. Do You Have Enough Disk Space? Nearly every modern-day operating system (OS) uses disk partitions , and Red Hat Enterprise Linux is no exception. When you install Red Hat Enterprise Linux, you may have to work with disk partitions. If you have not worked with disk partitions before (or need a quick review of the basic concepts), refer to Appendix A, An Introduction to Disk Partitions before proceeding. The disk space used by Red Hat Enterprise Linux must be separate from the disk space used by other OSes you may have installed on your system, such as Windows, OS/2, or even a different version of Linux. For x86, AMD64, and Intel 64 systems, at least two partitions ( / and swap ) must be dedicated to Red Hat Enterprise Linux. Before you start the installation process, you must have enough unpartitioned [1] disk space for the installation of Red Hat Enterprise Linux, or have one or more partitions that may be deleted, thereby freeing up enough disk space to install Red Hat Enterprise Linux. To gain a better sense of how much space you really need, refer to the recommended partitioning sizes discussed in Section 9.15.5, "Recommended Partitioning Scheme" . If you are not sure that you meet these conditions, or if you want to know how to create free disk space for your Red Hat Enterprise Linux installation, refer to Appendix A, An Introduction to Disk Partitions . [1] Unpartitioned disk space means that available disk space on the hard drives you are installing to has not been divided into sections for data. When you partition a disk, each partition behaves like a separate disk drive.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/installation_guide/Disk_Space-x86
Chapter 4. Configuration information for Red Hat Quay	Chapter 4. Configuration information for Red Hat Quay Checking a configuration YAML can help identify and resolve various issues related to the configuration of Red Hat Quay. Checking the configuration YAML can help you address the following issues: Incorrect Configuration Parameters : If the database is not functioning as expected or is experiencing performance issues, your configuration parameters could be at fault. By checking the configuration YAML, administrators can ensure that all the required parameters are set correctly and match the intended settings for the database. Resource Limitations : The configuration YAML might specify resource limits for the database, such as memory and CPU limits. If the database is running into resource constraints or experiencing contention with other services, adjusting these limits can help optimize resource allocation and improve overall performance. Connectivity Issues : Incorrect network settings in the configuration YAML can lead to connectivity problems between the application and the database. Ensuring that the correct network configurations are in place can resolve issues related to connectivity and communication. Data Storage and Paths : The configuration YAML may include paths for storing data and logs. If the paths are misconfigured or inaccessible, the database may encounter errors while reading or writing data, leading to operational issues. Authentication and Security : The configuration YAML may contain authentication settings, including usernames, passwords, and access controls. Verifying these settings is crucial for maintaining the security of the database and ensuring only authorized users have access. Plugin and Extension Settings : Some databases support extensions or plugins that enhance functionality. Issues may arise if these plugins are misconfigured or not loaded correctly. Checking the configuration YAML can help identify any problems with plugin settings. Replication and High Availability Settings : In clustered or replicated database setups, the configuration YAML may define replication settings and high availability configurations. Incorrect settings can lead to data inconsistency and system instability. Backup and Recovery Options : The configuration YAML might include backup and recovery options, specifying how data backups are performed and how data can be recovered in case of failures. Validating these settings can ensure data safety and successful recovery processes. By checking your configuration YAML, Red Hat Quay administrators can detect and resolve these issues before they cause significant disruptions to the application or service relying on the database. 4.1. Obtaining configuration information for Red Hat Quay Configuration information can be obtained for all types of Red Hat Quay deployments, include standalone, Operator, and geo-replication deployments. Obtaining configuration information can help you resolve issues with authentication and authorization, your database, object storage, and repository mirroring. After you have obtained the necessary configuration information, you can update your config.yaml file, search the Red Hat Knowledgebase for a solution, or file a support ticket with the Red Hat Support team. Procedure To obtain configuration information on Red Hat Quay Operator deployments, you can use oc exec , oc cp , or oc rsync . To use the oc exec command, enter the following command: USD oc exec -it <quay_pod_name> -- cat /conf/stack/config.yaml This command returns your config.yaml file directly to your terminal. To use the oc copy command, enter the following commands: USD oc cp <quay_pod_name>:/conf/stack/config.yaml /tmp/config.yaml To display this information in your terminal, enter the following command: USD cat /tmp/config.yaml To use the oc rsync command, enter the following commands: oc rsync <quay_pod_name>:/conf/stack/ /tmp/local_directory/ To display this information in your terminal, enter the following command: USD cat /tmp/local_directory/config.yaml Example output DISTRIBUTED_STORAGE_CONFIG: local_us: - RHOCSStorage - access_key: redacted bucket_name: lht-quay-datastore-68fff7b8-1b5e-46aa-8110-c4b7ead781f5 hostname: s3.openshift-storage.svc.cluster.local is_secure: true port: 443 secret_key: redacted storage_path: /datastorage/registry DISTRIBUTED_STORAGE_DEFAULT_LOCATIONS: - local_us DISTRIBUTED_STORAGE_PREFERENCE: - local_us To obtain configuration information on standalone Red Hat Quay deployments, you can use podman cp or podman exec . To use the podman copy command, enter the following commands: USD podman cp <quay_container_id>:/conf/stack/config.yaml /tmp/local_directory/ To display this information in your terminal, enter the following command: USD cat /tmp/local_directory/config.yaml To use podman exec , enter the following commands: USD podman exec -it <quay_container_id> cat /conf/stack/config.yaml Example output BROWSER_API_CALLS_XHR_ONLY: false ALLOWED_OCI_ARTIFACT_TYPES: application/vnd.oci.image.config.v1+json: - application/vnd.oci.image.layer.v1.tar+zstd application/vnd.sylabs.sif.config.v1+json: - application/vnd.sylabs.sif.layer.v1+tar AUTHENTICATION_TYPE: Database AVATAR_KIND: local BUILDLOGS_REDIS: host: quay-server.example.com password: strongpassword port: 6379 DATABASE_SECRET_KEY: 05ee6382-24a6-43c0-b30f-849c8a0f7260 DB_CONNECTION_ARGS: {} --- 4.2. Obtaining database configuration information You can obtain configuration information about your database by using the following procedure. Warning Interacting with the PostgreSQL database is potentially destructive. It is highly recommended that you perform the following procedure with the help of a Red Hat Quay Support Specialist. Procedure If you are using the Red Hat Quay Operator on OpenShift Container Platform, enter the following command: USD oc exec -it <database_pod> -- cat /var/lib/pgsql/data/userdata/postgresql.conf If you are using a standalone deployment of Red Hat Quay, enter the following command: USD podman exec -it <database_container> cat /var/lib/pgsql/data/userdata/postgresql.conf	[ "oc exec -it <quay_pod_name> -- cat /conf/stack/config.yaml", "oc cp <quay_pod_name>:/conf/stack/config.yaml /tmp/config.yaml", "cat /tmp/config.yaml", "rsync <quay_pod_name>:/conf/stack/ /tmp/local_directory/", "cat /tmp/local_directory/config.yaml", "DISTRIBUTED_STORAGE_CONFIG: local_us: - RHOCSStorage - access_key: redacted bucket_name: lht-quay-datastore-68fff7b8-1b5e-46aa-8110-c4b7ead781f5 hostname: s3.openshift-storage.svc.cluster.local is_secure: true port: 443 secret_key: redacted storage_path: /datastorage/registry DISTRIBUTED_STORAGE_DEFAULT_LOCATIONS: - local_us DISTRIBUTED_STORAGE_PREFERENCE: - local_us", "podman cp <quay_container_id>:/conf/stack/config.yaml /tmp/local_directory/", "cat /tmp/local_directory/config.yaml", "podman exec -it <quay_container_id> cat /conf/stack/config.yaml", "BROWSER_API_CALLS_XHR_ONLY: false ALLOWED_OCI_ARTIFACT_TYPES: application/vnd.oci.image.config.v1+json: - application/vnd.oci.image.layer.v1.tar+zstd application/vnd.sylabs.sif.config.v1+json: - application/vnd.sylabs.sif.layer.v1+tar AUTHENTICATION_TYPE: Database AVATAR_KIND: local BUILDLOGS_REDIS: host: quay-server.example.com password: strongpassword port: 6379 DATABASE_SECRET_KEY: 05ee6382-24a6-43c0-b30f-849c8a0f7260 DB_CONNECTION_ARGS: {} ---", "oc exec -it <database_pod> -- cat /var/lib/pgsql/data/userdata/postgresql.conf", "podman exec -it <database_container> cat /var/lib/pgsql/data/userdata/postgresql.conf" ]	https://docs.redhat.com/en/documentation/red_hat_quay/3.9/html/troubleshooting_red_hat_quay/obtaining-quay-config-information
Chapter 12. Updating managed clusters with the Topology Aware Lifecycle Manager	Chapter 12. Updating managed clusters with the Topology Aware Lifecycle Manager You can use the Topology Aware Lifecycle Manager (TALM) to manage the software lifecycle of multiple clusters. TALM uses Red Hat Advanced Cluster Management (RHACM) policies to perform changes on the target clusters. Important Using PolicyGenerator resources with GitOps ZTP is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . 12.1. About the Topology Aware Lifecycle Manager configuration The Topology Aware Lifecycle Manager (TALM) manages the deployment of Red Hat Advanced Cluster Management (RHACM) policies for one or more OpenShift Container Platform clusters. Using TALM in a large network of clusters allows the phased rollout of policies to the clusters in limited batches. This helps to minimize possible service disruptions when updating. With TALM, you can control the following actions: The timing of the update The number of RHACM-managed clusters The subset of managed clusters to apply the policies to The update order of the clusters The set of policies remediated to the cluster The order of policies remediated to the cluster The assignment of a canary cluster For single-node OpenShift, the Topology Aware Lifecycle Manager (TALM) offers pre-caching images for clusters with limited bandwidth. TALM supports the orchestration of the OpenShift Container Platform y-stream and z-stream updates, and day-two operations on y-streams and z-streams. 12.2. About managed policies used with Topology Aware Lifecycle Manager The Topology Aware Lifecycle Manager (TALM) uses RHACM policies for cluster updates. TALM can be used to manage the rollout of any policy CR where the remediationAction field is set to inform . Supported use cases include the following: Manual user creation of policy CRs Automatically generated policies from the PolicyGenerator or PolicyGentemplate custom resource definition (CRD) For policies that update an Operator subscription with manual approval, TALM provides additional functionality that approves the installation of the updated Operator. For more information about managed policies, see Policy Overview in the RHACM documentation. Additional resources About the PolicyGenerator CRD 12.3. Installing the Topology Aware Lifecycle Manager by using the web console You can use the OpenShift Container Platform web console to install the Topology Aware Lifecycle Manager. Prerequisites Install the latest version of the RHACM Operator. TALM requires RHACM 2.9 or later. Set up a hub cluster with a disconnected registry. Log in as a user with cluster-admin privileges. Procedure In the OpenShift Container Platform web console, navigate to Operators OperatorHub . Search for the Topology Aware Lifecycle Manager from the list of available Operators, and then click Install . Keep the default selection of Installation mode ["All namespaces on the cluster (default)"] and Installed Namespace ("openshift-operators") to ensure that the Operator is installed properly. Click Install . Verification To confirm that the installation is successful: Navigate to the Operators Installed Operators page. Check that the Operator is installed in the All Namespaces namespace and its status is Succeeded . If the Operator is not installed successfully: Navigate to the Operators Installed Operators page and inspect the Status column for any errors or failures. Navigate to the Workloads Pods page and check the logs in any containers in the cluster-group-upgrades-controller-manager pod that are reporting issues. 12.4. Installing the Topology Aware Lifecycle Manager by using the CLI You can use the OpenShift CLI ( oc ) to install the Topology Aware Lifecycle Manager (TALM). Prerequisites Install the OpenShift CLI ( oc ). Install the latest version of the RHACM Operator. TALM requires RHACM 2.9 or later. Set up a hub cluster with disconnected registry. Log in as a user with cluster-admin privileges. Procedure Create a Subscription CR: Define the Subscription CR and save the YAML file, for example, talm-subscription.yaml : apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-topology-aware-lifecycle-manager-subscription namespace: openshift-operators spec: channel: "stable" name: topology-aware-lifecycle-manager source: redhat-operators sourceNamespace: openshift-marketplace Create the Subscription CR by running the following command: USD oc create -f talm-subscription.yaml Verification Verify that the installation succeeded by inspecting the CSV resource: USD oc get csv -n openshift-operators Example output NAME DISPLAY VERSION REPLACES PHASE topology-aware-lifecycle-manager.4.18.x Topology Aware Lifecycle Manager 4.18.x Succeeded Verify that the TALM is up and running: USD oc get deploy -n openshift-operators Example output NAMESPACE NAME READY UP-TO-DATE AVAILABLE AGE openshift-operators cluster-group-upgrades-controller-manager 1/1 1 1 14s 12.5. About the ClusterGroupUpgrade CR The Topology Aware Lifecycle Manager (TALM) builds the remediation plan from the ClusterGroupUpgrade CR for a group of clusters. You can define the following specifications in a ClusterGroupUpgrade CR: Clusters in the group Blocking ClusterGroupUpgrade CRs Applicable list of managed policies Number of concurrent updates Applicable canary updates Actions to perform before and after the update Update timing You can control the start time of an update using the enable field in the ClusterGroupUpgrade CR. For example, if you have a scheduled maintenance window of four hours, you can prepare a ClusterGroupUpgrade CR with the enable field set to false . You can set the timeout by configuring the spec.remediationStrategy.timeout setting as follows: spec remediationStrategy: maxConcurrency: 1 timeout: 240 You can use the batchTimeoutAction to determine what happens if an update fails for a cluster. You can specify continue to skip the failing cluster and continue to upgrade other clusters, or abort to stop policy remediation for all clusters. Once the timeout elapses, TALM removes all enforce policies to ensure that no further updates are made to clusters. To apply the changes, you set the enabled field to true . For more information see the "Applying update policies to managed clusters" section. As TALM works through remediation of the policies to the specified clusters, the ClusterGroupUpgrade CR can report true or false statuses for a number of conditions. Note After TALM completes a cluster update, the cluster does not update again under the control of the same ClusterGroupUpgrade CR. You must create a new ClusterGroupUpgrade CR in the following cases: When you need to update the cluster again When the cluster changes to non-compliant with the inform policy after being updated 12.5.1. Selecting clusters TALM builds a remediation plan and selects clusters based on the following fields: The clusterLabelSelector field specifies the labels of the clusters that you want to update. This consists of a list of the standard label selectors from k8s.io/apimachinery/pkg/apis/meta/v1 . Each selector in the list uses either label value pairs or label expressions. Matches from each selector are added to the final list of clusters along with the matches from the clusterSelector field and the cluster field. The clusters field specifies a list of clusters to update. The canaries field specifies the clusters for canary updates. The maxConcurrency field specifies the number of clusters to update in a batch. The actions field specifies beforeEnable actions that TALM takes as it begins the update process, and afterCompletion actions that TALM takes as it completes policy remediation for each cluster. You can use the clusters , clusterLabelSelector , and clusterSelector fields together to create a combined list of clusters. The remediation plan starts with the clusters listed in the canaries field. Each canary cluster forms a single-cluster batch. Sample ClusterGroupUpgrade CR with the enabled field set to false apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: creationTimestamp: '2022-11-18T16:27:15Z' finalizers: - ran.openshift.io/cleanup-finalizer generation: 1 name: talm-cgu namespace: talm-namespace resourceVersion: '40451823' uid: cca245a5-4bca-45fa-89c0-aa6af81a596c Spec: actions: afterCompletion: 1 addClusterLabels: upgrade-done: "" deleteClusterLabels: upgrade-running: "" deleteObjects: true beforeEnable: 2 addClusterLabels: upgrade-running: "" clusters: 3 - spoke1 enable: false 4 managedPolicies: 5 - talm-policy preCaching: false remediationStrategy: 6 canaries: 7 - spoke1 maxConcurrency: 2 8 timeout: 240 clusterLabelSelectors: 9 - matchExpressions: - key: label1 operator: In values: - value1a - value1b batchTimeoutAction: 10 status: 11 computedMaxConcurrency: 2 conditions: - lastTransitionTime: '2022-11-18T16:27:15Z' message: All selected clusters are valid reason: ClusterSelectionCompleted status: 'True' type: ClustersSelected 12 - lastTransitionTime: '2022-11-18T16:27:15Z' message: Completed validation reason: ValidationCompleted status: 'True' type: Validated 13 - lastTransitionTime: '2022-11-18T16:37:16Z' message: Not enabled reason: NotEnabled status: 'False' type: Progressing managedPoliciesForUpgrade: - name: talm-policy namespace: talm-namespace managedPoliciesNs: talm-policy: talm-namespace remediationPlan: - - spoke1 - - spoke2 - spoke3 status: 1 Specifies the action that TALM takes when it completes policy remediation for each cluster. 2 Specifies the action that TALM takes as it begins the update process. 3 Defines the list of clusters to update. 4 The enable field is set to false . 5 Lists the user-defined set of policies to remediate. 6 Defines the specifics of the cluster updates. 7 Defines the clusters for canary updates. 8 Defines the maximum number of concurrent updates in a batch. The number of remediation batches is the number of canary clusters, plus the number of clusters, except the canary clusters, divided by the maxConcurrency value. The clusters that are already compliant with all the managed policies are excluded from the remediation plan. 9 Displays the parameters for selecting clusters. 10 Controls what happens if a batch times out. Possible values are abort or continue . If unspecified, the default is continue . 11 Displays information about the status of the updates. 12 The ClustersSelected condition shows that all selected clusters are valid. 13 The Validated condition shows that all selected clusters have been validated. Note Any failures during the update of a canary cluster stops the update process. When the remediation plan is successfully created, you can you set the enable field to true and TALM starts to update the non-compliant clusters with the specified managed policies. Note You can only make changes to the spec fields if the enable field of the ClusterGroupUpgrade CR is set to false . 12.5.2. Validating TALM checks that all specified managed policies are available and correct, and uses the Validated condition to report the status and reasons as follows: true Validation is completed. false Policies are missing or invalid, or an invalid platform image has been specified. 12.5.3. Pre-caching Clusters might have limited bandwidth to access the container image registry, which can cause a timeout before the updates are completed. On single-node OpenShift clusters, you can use pre-caching to avoid this. The container image pre-caching starts when you create a ClusterGroupUpgrade CR with the preCaching field set to true . TALM compares the available disk space with the estimated OpenShift Container Platform image size to ensure that there is enough space. If a cluster has insufficient space, TALM cancels pre-caching for that cluster and does not remediate policies on it. TALM uses the PrecacheSpecValid condition to report status information as follows: true The pre-caching spec is valid and consistent. false The pre-caching spec is incomplete. TALM uses the PrecachingSucceeded condition to report status information as follows: true TALM has concluded the pre-caching process. If pre-caching fails for any cluster, the update fails for that cluster but proceeds for all other clusters. A message informs you if pre-caching has failed for any clusters. false Pre-caching is still in progress for one or more clusters or has failed for all clusters. For more information see the "Using the container image pre-cache feature" section. 12.5.4. Updating clusters TALM enforces the policies following the remediation plan. Enforcing the policies for subsequent batches starts immediately after all the clusters of the current batch are compliant with all the managed policies. If the batch times out, TALM moves on to the batch. The timeout value of a batch is the spec.timeout field divided by the number of batches in the remediation plan. TALM uses the Progressing condition to report the status and reasons as follows: true TALM is remediating non-compliant policies. false The update is not in progress. Possible reasons for this are: All clusters are compliant with all the managed policies. The update timed out as policy remediation took too long. Blocking CRs are missing from the system or have not yet completed. The ClusterGroupUpgrade CR is not enabled. Note The managed policies apply in the order that they are listed in the managedPolicies field in the ClusterGroupUpgrade CR. One managed policy is applied to the specified clusters at a time. When a cluster complies with the current policy, the managed policy is applied to it. Sample ClusterGroupUpgrade CR in the Progressing state apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: creationTimestamp: '2022-11-18T16:27:15Z' finalizers: - ran.openshift.io/cleanup-finalizer generation: 1 name: talm-cgu namespace: talm-namespace resourceVersion: '40451823' uid: cca245a5-4bca-45fa-89c0-aa6af81a596c Spec: actions: afterCompletion: deleteObjects: true beforeEnable: {} clusters: - spoke1 enable: true managedPolicies: - talm-policy preCaching: true remediationStrategy: canaries: - spoke1 maxConcurrency: 2 timeout: 240 clusterLabelSelectors: - matchExpressions: - key: label1 operator: In values: - value1a - value1b batchTimeoutAction: status: clusters: - name: spoke1 state: complete computedMaxConcurrency: 2 conditions: - lastTransitionTime: '2022-11-18T16:27:15Z' message: All selected clusters are valid reason: ClusterSelectionCompleted status: 'True' type: ClustersSelected - lastTransitionTime: '2022-11-18T16:27:15Z' message: Completed validation reason: ValidationCompleted status: 'True' type: Validated - lastTransitionTime: '2022-11-18T16:37:16Z' message: Remediating non-compliant policies reason: InProgress status: 'True' type: Progressing 1 managedPoliciesForUpgrade: - name: talm-policy namespace: talm-namespace managedPoliciesNs: talm-policy: talm-namespace remediationPlan: - - spoke1 - - spoke2 - spoke3 status: currentBatch: 2 currentBatchRemediationProgress: spoke2: state: Completed spoke3: policyIndex: 0 state: InProgress currentBatchStartedAt: '2022-11-18T16:27:16Z' startedAt: '2022-11-18T16:27:15Z' 1 The Progressing fields show that TALM is in the process of remediating policies. 12.5.5. Update status TALM uses the Succeeded condition to report the status and reasons as follows: true All clusters are compliant with the specified managed policies. false Policy remediation failed as there were no clusters available for remediation, or because policy remediation took too long for one of the following reasons: The current batch contains canary updates and the cluster in the batch does not comply with all the managed policies within the batch timeout. Clusters did not comply with the managed policies within the timeout value specified in the remediationStrategy field. Sample ClusterGroupUpgrade CR in the Succeeded state apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-upgrade-complete namespace: default spec: clusters: - spoke1 - spoke4 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: 1 clusters: - name: spoke1 state: complete - name: spoke4 state: complete conditions: - message: All selected clusters are valid reason: ClusterSelectionCompleted status: "True" type: ClustersSelected - message: Completed validation reason: ValidationCompleted status: "True" type: Validated - message: All clusters are compliant with all the managed policies reason: Completed status: "False" type: Progressing 2 - message: All clusters are compliant with all the managed policies reason: Completed status: "True" type: Succeeded 3 managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default remediationPlan: - - spoke1 - - spoke4 status: completedAt: '2022-11-18T16:27:16Z' startedAt: '2022-11-18T16:27:15Z' 2 In the Progressing fields, the status is false as the update has completed; clusters are compliant with all the managed policies. 3 The Succeeded fields show that the validations completed successfully. 1 The status field includes a list of clusters and their respective statuses. The status of a cluster can be complete or timedout . Sample ClusterGroupUpgrade CR in the timedout state apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: creationTimestamp: '2022-11-18T16:27:15Z' finalizers: - ran.openshift.io/cleanup-finalizer generation: 1 name: talm-cgu namespace: talm-namespace resourceVersion: '40451823' uid: cca245a5-4bca-45fa-89c0-aa6af81a596c spec: actions: afterCompletion: deleteObjects: true beforeEnable: {} clusters: - spoke1 - spoke2 enable: true managedPolicies: - talm-policy preCaching: false remediationStrategy: maxConcurrency: 2 timeout: 240 status: clusters: - name: spoke1 state: complete - currentPolicy: 1 name: talm-policy status: NonCompliant name: spoke2 state: timedout computedMaxConcurrency: 2 conditions: - lastTransitionTime: '2022-11-18T16:27:15Z' message: All selected clusters are valid reason: ClusterSelectionCompleted status: 'True' type: ClustersSelected - lastTransitionTime: '2022-11-18T16:27:15Z' message: Completed validation reason: ValidationCompleted status: 'True' type: Validated - lastTransitionTime: '2022-11-18T16:37:16Z' message: Policy remediation took too long reason: TimedOut status: 'False' type: Progressing - lastTransitionTime: '2022-11-18T16:37:16Z' message: Policy remediation took too long reason: TimedOut status: 'False' type: Succeeded 2 managedPoliciesForUpgrade: - name: talm-policy namespace: talm-namespace managedPoliciesNs: talm-policy: talm-namespace remediationPlan: - - spoke1 - spoke2 status: startedAt: '2022-11-18T16:27:15Z' completedAt: '2022-11-18T20:27:15Z' 1 If a cluster's state is timedout , the currentPolicy field shows the name of the policy and the policy status. 2 The status for succeeded is false and the message indicates that policy remediation took too long. 12.5.6. Blocking ClusterGroupUpgrade CRs You can create multiple ClusterGroupUpgrade CRs and control their order of application. For example, if you create ClusterGroupUpgrade CR C that blocks the start of ClusterGroupUpgrade CR A, then ClusterGroupUpgrade CR A cannot start until the status of ClusterGroupUpgrade CR C becomes UpgradeComplete . One ClusterGroupUpgrade CR can have multiple blocking CRs. In this case, all the blocking CRs must complete before the upgrade for the current CR can start. Prerequisites Install the Topology Aware Lifecycle Manager (TALM). Provision one or more managed clusters. Log in as a user with cluster-admin privileges. Create RHACM policies in the hub cluster. Procedure Save the content of the ClusterGroupUpgrade CRs in the cgu-a.yaml , cgu-b.yaml , and cgu-c.yaml files. apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-a namespace: default spec: blockingCRs: 1 - name: cgu-c namespace: default clusters: - spoke1 - spoke2 - spoke3 enable: false managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy remediationStrategy: canaries: - spoke1 maxConcurrency: 2 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR is not enabled reason: UpgradeNotStarted status: "False" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default placementBindings: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy placementRules: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy remediationPlan: - - spoke1 - - spoke2 1 Defines the blocking CRs. The cgu-a update cannot start until cgu-c is complete. apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-b namespace: default spec: blockingCRs: 1 - name: cgu-a namespace: default clusters: - spoke4 - spoke5 enable: false managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR is not enabled reason: UpgradeNotStarted status: "False" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy placementRules: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy remediationPlan: - - spoke4 - - spoke5 status: {} 1 The cgu-b update cannot start until cgu-a is complete. apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-c namespace: default spec: 1 clusters: - spoke6 enable: false managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR is not enabled reason: UpgradeNotStarted status: "False" type: Ready managedPoliciesCompliantBeforeUpgrade: - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy placementRules: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy remediationPlan: - - spoke6 status: {} 1 The cgu-c update does not have any blocking CRs. TALM starts the cgu-c update when the enable field is set to true . Create the ClusterGroupUpgrade CRs by running the following command for each relevant CR: USD oc apply -f <name>.yaml Start the update process by running the following command for each relevant CR: USD oc --namespace=default patch clustergroupupgrade.ran.openshift.io/<name> \ --type merge -p '{"spec":{"enable":true}}' The following examples show ClusterGroupUpgrade CRs where the enable field is set to true : Example for cgu-a with blocking CRs apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-a namespace: default spec: blockingCRs: - name: cgu-c namespace: default clusters: - spoke1 - spoke2 - spoke3 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy remediationStrategy: canaries: - spoke1 maxConcurrency: 2 timeout: 240 status: conditions: - message: 'The ClusterGroupUpgrade CR is blocked by other CRs that have not yet completed: [cgu-c]' 1 reason: UpgradeCannotStart status: "False" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default placementBindings: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy placementRules: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy remediationPlan: - - spoke1 - - spoke2 status: {} 1 Shows the list of blocking CRs. Example for cgu-b with blocking CRs apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-b namespace: default spec: blockingCRs: - name: cgu-a namespace: default clusters: - spoke4 - spoke5 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: 'The ClusterGroupUpgrade CR is blocked by other CRs that have not yet completed: [cgu-a]' 1 reason: UpgradeCannotStart status: "False" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy placementRules: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy remediationPlan: - - spoke4 - - spoke5 status: {} 1 Shows the list of blocking CRs. Example for cgu-c with blocking CRs apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-c namespace: default spec: clusters: - spoke6 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR has upgrade policies that are still non compliant 1 reason: UpgradeNotCompleted status: "False" type: Ready managedPoliciesCompliantBeforeUpgrade: - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy placementRules: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy remediationPlan: - - spoke6 status: currentBatch: 1 remediationPlanForBatch: spoke6: 0 1 The cgu-c update does not have any blocking CRs. 12.6. Update policies on managed clusters The Topology Aware Lifecycle Manager (TALM) remediates a set of inform policies for the clusters specified in the ClusterGroupUpgrade custom resource (CR). TALM remediates inform policies by controlling the remediationAction specification in a Policy CR through the bindingOverrides.remediationAction and subFilter specifications in the PlacementBinding CR. Each policy has its own corresponding RHACM placement rule and RHACM placement binding. One by one, TALM adds each cluster from the current batch to the placement rule that corresponds with the applicable managed policy. If a cluster is already compliant with a policy, TALM skips applying that policy on the compliant cluster. TALM then moves on to applying the policy to the non-compliant cluster. After TALM completes the updates in a batch, all clusters are removed from the placement rules associated with the policies. Then, the update of the batch starts. If a spoke cluster does not report any compliant state to RHACM, the managed policies on the hub cluster can be missing status information that TALM needs. TALM handles these cases in the following ways: If a policy's status.compliant field is missing, TALM ignores the policy and adds a log entry. Then, TALM continues looking at the policy's status.status field. If a policy's status.status is missing, TALM produces an error. If a cluster's compliance status is missing in the policy's status.status field, TALM considers that cluster to be non-compliant with that policy. The ClusterGroupUpgrade CR's batchTimeoutAction determines what happens if an upgrade fails for a cluster. You can specify continue to skip the failing cluster and continue to upgrade other clusters, or specify abort to stop the policy remediation for all clusters. Once the timeout elapses, TALM removes all the resources it created to ensure that no further updates are made to clusters. Example upgrade policy apiVersion: policy.open-cluster-management.io/v1 kind: Policy metadata: name: ocp-4.4.18.4 namespace: platform-upgrade spec: disabled: false policy-templates: - objectDefinition: apiVersion: policy.open-cluster-management.io/v1 kind: ConfigurationPolicy metadata: name: upgrade spec: namespaceselector: exclude: - kube-* include: - '' object-templates: - complianceType: musthave objectDefinition: apiVersion: config.openshift.io/v1 kind: ClusterVersion metadata: name: version spec: channel: stable-4.18 desiredUpdate: version: 4.4.18.4 upstream: https://api.openshift.com/api/upgrades_info/v1/graph status: history: - state: Completed version: 4.4.18.4 remediationAction: inform severity: low remediationAction: inform For more information about RHACM policies, see Policy overview . Additional resources About the PolicyGenerator CRD 12.6.1. Configuring Operator subscriptions for managed clusters that you install with TALM Topology Aware Lifecycle Manager (TALM) can only approve the install plan for an Operator if the Subscription custom resource (CR) of the Operator contains the status.state.AtLatestKnown field. Procedure Add the status.state.AtLatestKnown field to the Subscription CR of the Operator: Example Subscription CR apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: cluster-logging namespace: openshift-logging annotations: ran.openshift.io/ztp-deploy-wave: "2" spec: channel: "stable" name: cluster-logging source: redhat-operators sourceNamespace: openshift-marketplace installPlanApproval: Manual status: state: AtLatestKnown 1 1 The status.state: AtLatestKnown field is used for the latest Operator version available from the Operator catalog. Note When a new version of the Operator is available in the registry, the associated policy becomes non-compliant. Apply the changed Subscription policy to your managed clusters with a ClusterGroupUpgrade CR. 12.6.2. Applying update policies to managed clusters You can update your managed clusters by applying your policies. Prerequisites Install the Topology Aware Lifecycle Manager (TALM). TALM requires RHACM 2.9 or later. Provision one or more managed clusters. Log in as a user with cluster-admin privileges. Create RHACM policies in the hub cluster. Procedure Save the contents of the ClusterGroupUpgrade CR in the cgu-1.yaml file. apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-1 namespace: default spec: managedPolicies: 1 - policy1-common-cluster-version-policy - policy2-common-nto-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy enable: false clusters: 2 - spoke1 - spoke2 - spoke5 - spoke6 remediationStrategy: maxConcurrency: 2 3 timeout: 240 4 batchTimeoutAction: 5 1 The name of the policies to apply. 2 The list of clusters to update. 3 The maxConcurrency field signifies the number of clusters updated at the same time. 4 The update timeout in minutes. 5 Controls what happens if a batch times out. Possible values are abort or continue . If unspecified, the default is continue . Create the ClusterGroupUpgrade CR by running the following command: USD oc create -f cgu-1.yaml Check if the ClusterGroupUpgrade CR was created in the hub cluster by running the following command: USD oc get cgu --all-namespaces Example output NAMESPACE NAME AGE STATE DETAILS default cgu-1 8m55 NotEnabled Not Enabled Check the status of the update by running the following command: USD oc get cgu -n default cgu-1 -ojsonpath='{.status}' \| jq Example output { "computedMaxConcurrency": 2, "conditions": [ { "lastTransitionTime": "2022-02-25T15:34:07Z", "message": "Not enabled", 1 "reason": "NotEnabled", "status": "False", "type": "Progressing" } ], "managedPoliciesContent": { "policy1-common-cluster-version-policy": "null", "policy2-common-nto-sub-policy": "[{\"kind\":\"Subscription\",\"name\":\"node-tuning-operator\",\"namespace\":\"openshift-cluster-node-tuning-operator\"}]", "policy3-common-ptp-sub-policy": "[{\"kind\":\"Subscription\",\"name\":\"ptp-operator-subscription\",\"namespace\":\"openshift-ptp\"}]", "policy4-common-sriov-sub-policy": "[{\"kind\":\"Subscription\",\"name\":\"sriov-network-operator-subscription\",\"namespace\":\"openshift-sriov-network-operator\"}]" }, "managedPoliciesForUpgrade": [ { "name": "policy1-common-cluster-version-policy", "namespace": "default" }, { "name": "policy2-common-nto-sub-policy", "namespace": "default" }, { "name": "policy3-common-ptp-sub-policy", "namespace": "default" }, { "name": "policy4-common-sriov-sub-policy", "namespace": "default" } ], "managedPoliciesNs": { "policy1-common-cluster-version-policy": "default", "policy2-common-nto-sub-policy": "default", "policy3-common-ptp-sub-policy": "default", "policy4-common-sriov-sub-policy": "default" }, "placementBindings": [ "cgu-policy1-common-cluster-version-policy", "cgu-policy2-common-nto-sub-policy", "cgu-policy3-common-ptp-sub-policy", "cgu-policy4-common-sriov-sub-policy" ], "placementRules": [ "cgu-policy1-common-cluster-version-policy", "cgu-policy2-common-nto-sub-policy", "cgu-policy3-common-ptp-sub-policy", "cgu-policy4-common-sriov-sub-policy" ], "remediationPlan": [ [ "spoke1", "spoke2" ], [ "spoke5", "spoke6" ] ], "status": {} } 1 The spec.enable field in the ClusterGroupUpgrade CR is set to false . Change the value of the spec.enable field to true by running the following command: USD oc --namespace=default patch clustergroupupgrade.ran.openshift.io/cgu-1 \ --patch '{"spec":{"enable":true}}' --type=merge Verification Check the status of the update by running the following command: USD oc get cgu -n default cgu-1 -ojsonpath='{.status}' \| jq Example output { "computedMaxConcurrency": 2, "conditions": [ 1 { "lastTransitionTime": "2022-02-25T15:33:07Z", "message": "All selected clusters are valid", "reason": "ClusterSelectionCompleted", "status": "True", "type": "ClustersSelected" }, { "lastTransitionTime": "2022-02-25T15:33:07Z", "message": "Completed validation", "reason": "ValidationCompleted", "status": "True", "type": "Validated" }, { "lastTransitionTime": "2022-02-25T15:34:07Z", "message": "Remediating non-compliant policies", "reason": "InProgress", "status": "True", "type": "Progressing" } ], "managedPoliciesContent": { "policy1-common-cluster-version-policy": "null", "policy2-common-nto-sub-policy": "[{\"kind\":\"Subscription\",\"name\":\"node-tuning-operator\",\"namespace\":\"openshift-cluster-node-tuning-operator\"}]", "policy3-common-ptp-sub-policy": "[{\"kind\":\"Subscription\",\"name\":\"ptp-operator-subscription\",\"namespace\":\"openshift-ptp\"}]", "policy4-common-sriov-sub-policy": "[{\"kind\":\"Subscription\",\"name\":\"sriov-network-operator-subscription\",\"namespace\":\"openshift-sriov-network-operator\"}]" }, "managedPoliciesForUpgrade": [ { "name": "policy1-common-cluster-version-policy", "namespace": "default" }, { "name": "policy2-common-nto-sub-policy", "namespace": "default" }, { "name": "policy3-common-ptp-sub-policy", "namespace": "default" }, { "name": "policy4-common-sriov-sub-policy", "namespace": "default" } ], "managedPoliciesNs": { "policy1-common-cluster-version-policy": "default", "policy2-common-nto-sub-policy": "default", "policy3-common-ptp-sub-policy": "default", "policy4-common-sriov-sub-policy": "default" }, "placementBindings": [ "cgu-policy1-common-cluster-version-policy", "cgu-policy2-common-nto-sub-policy", "cgu-policy3-common-ptp-sub-policy", "cgu-policy4-common-sriov-sub-policy" ], "placementRules": [ "cgu-policy1-common-cluster-version-policy", "cgu-policy2-common-nto-sub-policy", "cgu-policy3-common-ptp-sub-policy", "cgu-policy4-common-sriov-sub-policy" ], "remediationPlan": [ [ "spoke1", "spoke2" ], [ "spoke5", "spoke6" ] ], "status": { "currentBatch": 1, "currentBatchRemediationProgress": { "spoke1": { "policyIndex": 1, "state": "InProgress" }, "spoke2": { "policyIndex": 1, "state": "InProgress" } }, "currentBatchStartedAt": "2022-02-25T15:54:16Z", "startedAt": "2022-02-25T15:54:16Z" } } 1 Reflects the update progress of the current batch. Run this command again to receive updated information about the progress. Check the status of the policies by running the following command: oc get policies -A Example output NAMESPACE NAME REMEDIATION ACTION COMPLIANCE STATE AGE spoke1 default.policy1-common-cluster-version-policy enforce Compliant 18m spoke1 default.policy2-common-nto-sub-policy enforce NonCompliant 18m spoke2 default.policy1-common-cluster-version-policy enforce Compliant 18m spoke2 default.policy2-common-nto-sub-policy enforce NonCompliant 18m spoke5 default.policy3-common-ptp-sub-policy inform NonCompliant 18m spoke5 default.policy4-common-sriov-sub-policy inform NonCompliant 18m spoke6 default.policy3-common-ptp-sub-policy inform NonCompliant 18m spoke6 default.policy4-common-sriov-sub-policy inform NonCompliant 18m default policy1-common-ptp-sub-policy inform Compliant 18m default policy2-common-sriov-sub-policy inform NonCompliant 18m default policy3-common-ptp-sub-policy inform NonCompliant 18m default policy4-common-sriov-sub-policy inform NonCompliant 18m The spec.remediationAction value changes to enforce for the child policies applied to the clusters from the current batch. The spec.remedationAction value remains inform for the child policies in the rest of the clusters. After the batch is complete, the spec.remediationAction value changes back to inform for the enforced child policies. If the policies include Operator subscriptions, you can check the installation progress directly on the single-node cluster. Export the KUBECONFIG file of the single-node cluster you want to check the installation progress for by running the following command: USD export KUBECONFIG=<cluster_kubeconfig_absolute_path> Check all the subscriptions present on the single-node cluster and look for the one in the policy you are trying to install through the ClusterGroupUpgrade CR by running the following command: USD oc get subs -A \| grep -i <subscription_name> Example output for cluster-logging policy NAMESPACE NAME PACKAGE SOURCE CHANNEL openshift-logging cluster-logging cluster-logging redhat-operators stable If one of the managed policies includes a ClusterVersion CR, check the status of platform updates in the current batch by running the following command against the spoke cluster: USD oc get clusterversion Example output NAME VERSION AVAILABLE PROGRESSING SINCE STATUS version 4.4.18.5 True True 43s Working towards 4.4.18.7: 71 of 735 done (9% complete) Check the Operator subscription by running the following command: USD oc get subs -n <operator-namespace> <operator-subscription> -ojsonpath="{.status}" Check the install plans present on the single-node cluster that is associated with the desired subscription by running the following command: USD oc get installplan -n <subscription_namespace> Example output for cluster-logging Operator NAMESPACE NAME CSV APPROVAL APPROVED openshift-logging install-6khtw cluster-logging.5.3.3-4 Manual true 1 1 The install plans have their Approval field set to Manual and their Approved field changes from false to true after TALM approves the install plan. Note When TALM is remediating a policy containing a subscription, it automatically approves any install plans attached to that subscription. Where multiple install plans are needed to get the operator to the latest known version, TALM might approve multiple install plans, upgrading through one or more intermediate versions to get to the final version. Check if the cluster service version for the Operator of the policy that the ClusterGroupUpgrade is installing reached the Succeeded phase by running the following command: USD oc get csv -n <operator_namespace> Example output for OpenShift Logging Operator NAME DISPLAY VERSION REPLACES PHASE cluster-logging.5.4.2 Red Hat OpenShift Logging 5.4.2 Succeeded 12.7. Using the container image pre-cache feature Single-node OpenShift clusters might have limited bandwidth to access the container image registry, which can cause a timeout before the updates are completed. Note The time of the update is not set by TALM. You can apply the ClusterGroupUpgrade CR at the beginning of the update by manual application or by external automation. The container image pre-caching starts when the preCaching field is set to true in the ClusterGroupUpgrade CR. TALM uses the PrecacheSpecValid condition to report status information as follows: true The pre-caching spec is valid and consistent. false The pre-caching spec is incomplete. TALM uses the PrecachingSucceeded condition to report status information as follows: true TALM has concluded the pre-caching process. If pre-caching fails for any cluster, the update fails for that cluster but proceeds for all other clusters. A message informs you if pre-caching has failed for any clusters. false Pre-caching is still in progress for one or more clusters or has failed for all clusters. After a successful pre-caching process, you can start remediating policies. The remediation actions start when the enable field is set to true . If there is a pre-caching failure on a cluster, the upgrade fails for that cluster. The upgrade process continues for all other clusters that have a successful pre-cache. The pre-caching process can be in the following statuses: NotStarted This is the initial state all clusters are automatically assigned to on the first reconciliation pass of the ClusterGroupUpgrade CR. In this state, TALM deletes any pre-caching namespace and hub view resources of spoke clusters that remain from incomplete updates. TALM then creates a new ManagedClusterView resource for the spoke pre-caching namespace to verify its deletion in the PrecachePreparing state. PreparingToStart Cleaning up any remaining resources from incomplete updates is in progress. Starting Pre-caching job prerequisites and the job are created. Active The job is in "Active" state. Succeeded The pre-cache job succeeded. PrecacheTimeout The artifact pre-caching is partially done. UnrecoverableError The job ends with a non-zero exit code. 12.7.1. Using the container image pre-cache filter The pre-cache feature typically downloads more images than a cluster needs for an update. You can control which pre-cache images are downloaded to a cluster. This decreases download time, and saves bandwidth and storage. You can see a list of all images to be downloaded using the following command: USD oc adm release info <ocp-version> The following ConfigMap example shows how you can exclude images using the excludePrecachePatterns field. apiVersion: v1 kind: ConfigMap metadata: name: cluster-group-upgrade-overrides data: excludePrecachePatterns: \| azure 1 aws vsphere alibaba 1 TALM excludes all images with names that include any of the patterns listed here. 12.7.2. Creating a ClusterGroupUpgrade CR with pre-caching For single-node OpenShift, the pre-cache feature allows the required container images to be present on the spoke cluster before the update starts. Note For pre-caching, TALM uses the spec.remediationStrategy.timeout value from the ClusterGroupUpgrade CR. You must set a timeout value that allows sufficient time for the pre-caching job to complete. When you enable the ClusterGroupUpgrade CR after pre-caching has completed, you can change the timeout value to a duration that is appropriate for the update. Prerequisites Install the Topology Aware Lifecycle Manager (TALM). Provision one or more managed clusters. Log in as a user with cluster-admin privileges. Procedure Save the contents of the ClusterGroupUpgrade CR with the preCaching field set to true in the clustergroupupgrades-group-du.yaml file: apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: du-upgrade-4918 namespace: ztp-group-du-sno spec: preCaching: true 1 clusters: - cnfdb1 - cnfdb2 enable: false managedPolicies: - du-upgrade-platform-upgrade remediationStrategy: maxConcurrency: 2 timeout: 240 1 The preCaching field is set to true , which enables TALM to pull the container images before starting the update. When you want to start pre-caching, apply the ClusterGroupUpgrade CR by running the following command: USD oc apply -f clustergroupupgrades-group-du.yaml Verification Check if the ClusterGroupUpgrade CR exists in the hub cluster by running the following command: USD oc get cgu -A Example output NAMESPACE NAME AGE STATE DETAILS ztp-group-du-sno du-upgrade-4918 10s InProgress Precaching is required and not done 1 1 The CR is created. Check the status of the pre-caching task by running the following command: USD oc get cgu -n ztp-group-du-sno du-upgrade-4918 -o jsonpath='{.status}' Example output { "conditions": [ { "lastTransitionTime": "2022-01-27T19:07:24Z", "message": "Precaching is required and not done", "reason": "InProgress", "status": "False", "type": "PrecachingSucceeded" }, { "lastTransitionTime": "2022-01-27T19:07:34Z", "message": "Pre-caching spec is valid and consistent", "reason": "PrecacheSpecIsWellFormed", "status": "True", "type": "PrecacheSpecValid" } ], "precaching": { "clusters": [ "cnfdb1" 1 "cnfdb2" ], "spec": { "platformImage": "image.example.io"}, "status": { "cnfdb1": "Active" "cnfdb2": "Succeeded"} } } 1 Displays the list of identified clusters. Check the status of the pre-caching job by running the following command on the spoke cluster: USD oc get jobs,pods -n openshift-talo-pre-cache Example output NAME COMPLETIONS DURATION AGE job.batch/pre-cache 0/1 3m10s 3m10s NAME READY STATUS RESTARTS AGE pod/pre-cache--1-9bmlr 1/1 Running 0 3m10s Check the status of the ClusterGroupUpgrade CR by running the following command: USD oc get cgu -n ztp-group-du-sno du-upgrade-4918 -o jsonpath='{.status}' Example output "conditions": [ { "lastTransitionTime": "2022-01-27T19:30:41Z", "message": "The ClusterGroupUpgrade CR has all clusters compliant with all the managed policies", "reason": "UpgradeCompleted", "status": "True", "type": "Ready" }, { "lastTransitionTime": "2022-01-27T19:28:57Z", "message": "Precaching is completed", "reason": "PrecachingCompleted", "status": "True", "type": "PrecachingSucceeded" 1 } 1 The pre-cache tasks are done. 12.8. Troubleshooting the Topology Aware Lifecycle Manager The Topology Aware Lifecycle Manager (TALM) is an OpenShift Container Platform Operator that remediates RHACM policies. When issues occur, use the oc adm must-gather command to gather details and logs and to take steps in debugging the issues. For more information about related topics, see the following documentation: Red Hat Advanced Cluster Management for Kubernetes 2.4 Support Matrix Red Hat Advanced Cluster Management Troubleshooting The "Troubleshooting Operator issues" section 12.8.1. General troubleshooting You can determine the cause of the problem by reviewing the following questions: Is the configuration that you are applying supported? Are the RHACM and the OpenShift Container Platform versions compatible? Are the TALM and RHACM versions compatible? Which of the following components is causing the problem? Section 12.8.3, "Managed policies" Section 12.8.4, "Clusters" Section 12.8.5, "Remediation Strategy" Section 12.8.6, "Topology Aware Lifecycle Manager" To ensure that the ClusterGroupUpgrade configuration is functional, you can do the following: Create the ClusterGroupUpgrade CR with the spec.enable field set to false . Wait for the status to be updated and go through the troubleshooting questions. If everything looks as expected, set the spec.enable field to true in the ClusterGroupUpgrade CR. Warning After you set the spec.enable field to true in the ClusterUpgradeGroup CR, the update procedure starts and you cannot edit the CR's spec fields anymore. 12.8.2. Cannot modify the ClusterUpgradeGroup CR Issue You cannot edit the ClusterUpgradeGroup CR after enabling the update. Resolution Restart the procedure by performing the following steps: Remove the old ClusterGroupUpgrade CR by running the following command: USD oc delete cgu -n <ClusterGroupUpgradeCR_namespace> <ClusterGroupUpgradeCR_name> Check and fix the existing issues with the managed clusters and policies. Ensure that all the clusters are managed clusters and available. Ensure that all the policies exist and have the spec.remediationAction field set to inform . Create a new ClusterGroupUpgrade CR with the correct configurations. USD oc apply -f <ClusterGroupUpgradeCR_YAML> 12.8.3. Managed policies Checking managed policies on the system Issue You want to check if you have the correct managed policies on the system. Resolution Run the following command: USD oc get cgu lab-upgrade -ojsonpath='{.spec.managedPolicies}' Example output ["group-du-sno-validator-du-validator-policy", "policy2-common-nto-sub-policy", "policy3-common-ptp-sub-policy"] Checking remediationAction mode Issue You want to check if the remediationAction field is set to inform in the spec of the managed policies. Resolution Run the following command: USD oc get policies --all-namespaces Example output NAMESPACE NAME REMEDIATION ACTION COMPLIANCE STATE AGE default policy1-common-cluster-version-policy inform NonCompliant 5d21h default policy2-common-nto-sub-policy inform Compliant 5d21h default policy3-common-ptp-sub-policy inform NonCompliant 5d21h default policy4-common-sriov-sub-policy inform NonCompliant 5d21h Checking policy compliance state Issue You want to check the compliance state of policies. Resolution Run the following command: USD oc get policies --all-namespaces Example output NAMESPACE NAME REMEDIATION ACTION COMPLIANCE STATE AGE default policy1-common-cluster-version-policy inform NonCompliant 5d21h default policy2-common-nto-sub-policy inform Compliant 5d21h default policy3-common-ptp-sub-policy inform NonCompliant 5d21h default policy4-common-sriov-sub-policy inform NonCompliant 5d21h 12.8.4. Clusters Checking if managed clusters are present Issue You want to check if the clusters in the ClusterGroupUpgrade CR are managed clusters. Resolution Run the following command: USD oc get managedclusters Example output NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE local-cluster true https://api.hub.example.com:6443 True Unknown 13d spoke1 true https://api.spoke1.example.com:6443 True True 13d spoke3 true https://api.spoke3.example.com:6443 True True 27h Alternatively, check the TALM manager logs: Get the name of the TALM manager by running the following command: USD oc get pod -n openshift-operators Example output NAME READY STATUS RESTARTS AGE cluster-group-upgrades-controller-manager-75bcc7484d-8k8xp 2/2 Running 0 45m Check the TALM manager logs by running the following command: USD oc logs -n openshift-operators \ cluster-group-upgrades-controller-manager-75bcc7484d-8k8xp -c manager Example output ERROR controller-runtime.manager.controller.clustergroupupgrade Reconciler error {"reconciler group": "ran.openshift.io", "reconciler kind": "ClusterGroupUpgrade", "name": "lab-upgrade", "namespace": "default", "error": "Cluster spoke5555 is not a ManagedCluster"} 1 sigs.k8s.io/controller-runtime/pkg/internal/controller.(Controller).processNextWorkItem 1 The error message shows that the cluster is not a managed cluster. Checking if managed clusters are available Issue You want to check if the managed clusters specified in the ClusterGroupUpgrade CR are available. Resolution Run the following command: USD oc get managedclusters Example output NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE local-cluster true https://api.hub.testlab.com:6443 True Unknown 13d spoke1 true https://api.spoke1.testlab.com:6443 True True 13d 1 spoke3 true https://api.spoke3.testlab.com:6443 True True 27h 2 1 2 The value of the AVAILABLE field is True for the managed clusters. Checking clusterLabelSelector Issue You want to check if the clusterLabelSelector field specified in the ClusterGroupUpgrade CR matches at least one of the managed clusters. Resolution Run the following command: USD oc get managedcluster --selector=upgrade=true 1 1 The label for the clusters you want to update is upgrade:true . Example output NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE spoke1 true https://api.spoke1.testlab.com:6443 True True 13d spoke3 true https://api.spoke3.testlab.com:6443 True True 27h Checking if canary clusters are present Issue You want to check if the canary clusters are present in the list of clusters. Example ClusterGroupUpgrade CR spec: remediationStrategy: canaries: - spoke3 maxConcurrency: 2 timeout: 240 clusterLabelSelectors: - matchLabels: upgrade: true Resolution Run the following commands: USD oc get cgu lab-upgrade -ojsonpath='{.spec.clusters}' Example output ["spoke1", "spoke3"] Check if the canary clusters are present in the list of clusters that match clusterLabelSelector labels by running the following command: USD oc get managedcluster --selector=upgrade=true Example output NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE spoke1 true https://api.spoke1.testlab.com:6443 True True 13d spoke3 true https://api.spoke3.testlab.com:6443 True True 27h Note A cluster can be present in spec.clusters and also be matched by the spec.clusterLabelSelector label. Checking the pre-caching status on spoke clusters Check the status of pre-caching by running the following command on the spoke cluster: USD oc get jobs,pods -n openshift-talo-pre-cache 12.8.5. Remediation Strategy Checking if remediationStrategy is present in the ClusterGroupUpgrade CR Issue You want to check if the remediationStrategy is present in the ClusterGroupUpgrade CR. Resolution Run the following command: USD oc get cgu lab-upgrade -ojsonpath='{.spec.remediationStrategy}' Example output {"maxConcurrency":2, "timeout":240} Checking if maxConcurrency is specified in the ClusterGroupUpgrade CR Issue You want to check if the maxConcurrency is specified in the ClusterGroupUpgrade CR. Resolution Run the following command: USD oc get cgu lab-upgrade -ojsonpath='{.spec.remediationStrategy.maxConcurrency}' Example output 2 12.8.6. Topology Aware Lifecycle Manager Checking condition message and status in the ClusterGroupUpgrade CR Issue You want to check the value of the status.conditions field in the ClusterGroupUpgrade CR. Resolution Run the following command: USD oc get cgu lab-upgrade -ojsonpath='{.status.conditions}' Example output {"lastTransitionTime":"2022-02-17T22:25:28Z", "message":"Missing managed policies:[policyList]", "reason":"NotAllManagedPoliciesExist", "status":"False", "type":"Validated"} Checking if status.remediationPlan was computed Issue You want to check if status.remediationPlan is computed. Resolution Run the following command: USD oc get cgu lab-upgrade -ojsonpath='{.status.remediationPlan}' Example output [["spoke2", "spoke3"]] Errors in the TALM manager container Issue You want to check the logs of the manager container of TALM. Resolution Run the following command: USD oc logs -n openshift-operators \ cluster-group-upgrades-controller-manager-75bcc7484d-8k8xp -c manager Example output ERROR controller-runtime.manager.controller.clustergroupupgrade Reconciler error {"reconciler group": "ran.openshift.io", "reconciler kind": "ClusterGroupUpgrade", "name": "lab-upgrade", "namespace": "default", "error": "Cluster spoke5555 is not a ManagedCluster"} 1 sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).processNextWorkItem 1 Displays the error. Clusters are not compliant to some policies after a ClusterGroupUpgrade CR has completed Issue The policy compliance status that TALM uses to decide if remediation is needed has not yet fully updated for all clusters. This may be because: The CGU was run too soon after a policy was created or updated. The remediation of a policy affects the compliance of subsequent policies in the ClusterGroupUpgrade CR. Resolution Create and apply a new ClusterGroupUpdate CR with the same specification. Auto-created ClusterGroupUpgrade CR in the GitOps ZTP workflow has no managed policies Issue If there are no policies for the managed cluster when the cluster becomes Ready , a ClusterGroupUpgrade CR with no policies is auto-created. Upon completion of the ClusterGroupUpgrade CR, the managed cluster is labeled as ztp-done . If the PolicyGenerator or PolicyGenTemplate CRs were not pushed to the Git repository within the required time after SiteConfig resources were pushed, this might result in no policies being available for the target cluster when the cluster became Ready . Resolution Verify that the policies you want to apply are available on the hub cluster, then create a ClusterGroupUpgrade CR with the required policies. You can either manually create the ClusterGroupUpgrade CR or trigger auto-creation again. To trigger auto-creation of the ClusterGroupUpgrade CR, remove the ztp-done label from the cluster and delete the empty ClusterGroupUpgrade CR that was previously created in the zip-install namespace. Pre-caching has failed Issue Pre-caching might fail for one of the following reasons: There is not enough free space on the node. For a disconnected environment, the pre-cache image has not been properly mirrored. There was an issue when creating the pod. Resolution To check if pre-caching has failed due to insufficient space, check the log of the pre-caching pod in the node. Find the name of the pod using the following command: USD oc get pods -n openshift-talo-pre-cache Check the logs to see if the error is related to insufficient space using the following command: USD oc logs -n openshift-talo-pre-cache <pod name> If there is no log, check the pod status using the following command: USD oc describe pod -n openshift-talo-pre-cache <pod name> If the pod does not exist, check the job status to see why it could not create a pod using the following command: USD oc describe job -n openshift-talo-pre-cache pre-cache Additional resources OpenShift Container Platform Troubleshooting Operator Issues Updating managed policies with Topology Aware Lifecycle Manager About the PolicyGenerator CRD	[ "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-topology-aware-lifecycle-manager-subscription namespace: openshift-operators spec: channel: \"stable\" name: topology-aware-lifecycle-manager source: redhat-operators sourceNamespace: openshift-marketplace", "oc create -f talm-subscription.yaml", "oc get csv -n openshift-operators", "NAME DISPLAY VERSION REPLACES PHASE topology-aware-lifecycle-manager.4.18.x Topology Aware Lifecycle Manager 4.18.x Succeeded", "oc get deploy -n openshift-operators", "NAMESPACE NAME READY UP-TO-DATE AVAILABLE AGE openshift-operators cluster-group-upgrades-controller-manager 1/1 1 1 14s", "spec remediationStrategy: maxConcurrency: 1 timeout: 240", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: creationTimestamp: '2022-11-18T16:27:15Z' finalizers: - ran.openshift.io/cleanup-finalizer generation: 1 name: talm-cgu namespace: talm-namespace resourceVersion: '40451823' uid: cca245a5-4bca-45fa-89c0-aa6af81a596c Spec: actions: afterCompletion: 1 addClusterLabels: upgrade-done: \"\" deleteClusterLabels: upgrade-running: \"\" deleteObjects: true beforeEnable: 2 addClusterLabels: upgrade-running: \"\" clusters: 3 - spoke1 enable: false 4 managedPolicies: 5 - talm-policy preCaching: false remediationStrategy: 6 canaries: 7 - spoke1 maxConcurrency: 2 8 timeout: 240 clusterLabelSelectors: 9 - matchExpressions: - key: label1 operator: In values: - value1a - value1b batchTimeoutAction: 10 status: 11 computedMaxConcurrency: 2 conditions: - lastTransitionTime: '2022-11-18T16:27:15Z' message: All selected clusters are valid reason: ClusterSelectionCompleted status: 'True' type: ClustersSelected 12 - lastTransitionTime: '2022-11-18T16:27:15Z' message: Completed validation reason: ValidationCompleted status: 'True' type: Validated 13 - lastTransitionTime: '2022-11-18T16:37:16Z' message: Not enabled reason: NotEnabled status: 'False' type: Progressing managedPoliciesForUpgrade: - name: talm-policy namespace: talm-namespace managedPoliciesNs: talm-policy: talm-namespace remediationPlan: - - spoke1 - - spoke2 - spoke3 status:", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: creationTimestamp: '2022-11-18T16:27:15Z' finalizers: - ran.openshift.io/cleanup-finalizer generation: 1 name: talm-cgu namespace: talm-namespace resourceVersion: '40451823' uid: cca245a5-4bca-45fa-89c0-aa6af81a596c Spec: actions: afterCompletion: deleteObjects: true beforeEnable: {} clusters: - spoke1 enable: true managedPolicies: - talm-policy preCaching: true remediationStrategy: canaries: - spoke1 maxConcurrency: 2 timeout: 240 clusterLabelSelectors: - matchExpressions: - key: label1 operator: In values: - value1a - value1b batchTimeoutAction: status: clusters: - name: spoke1 state: complete computedMaxConcurrency: 2 conditions: - lastTransitionTime: '2022-11-18T16:27:15Z' message: All selected clusters are valid reason: ClusterSelectionCompleted status: 'True' type: ClustersSelected - lastTransitionTime: '2022-11-18T16:27:15Z' message: Completed validation reason: ValidationCompleted status: 'True' type: Validated - lastTransitionTime: '2022-11-18T16:37:16Z' message: Remediating non-compliant policies reason: InProgress status: 'True' type: Progressing 1 managedPoliciesForUpgrade: - name: talm-policy namespace: talm-namespace managedPoliciesNs: talm-policy: talm-namespace remediationPlan: - - spoke1 - - spoke2 - spoke3 status: currentBatch: 2 currentBatchRemediationProgress: spoke2: state: Completed spoke3: policyIndex: 0 state: InProgress currentBatchStartedAt: '2022-11-18T16:27:16Z' startedAt: '2022-11-18T16:27:15Z'", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-upgrade-complete namespace: default spec: clusters: - spoke1 - spoke4 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: 1 clusters: - name: spoke1 state: complete - name: spoke4 state: complete conditions: - message: All selected clusters are valid reason: ClusterSelectionCompleted status: \"True\" type: ClustersSelected - message: Completed validation reason: ValidationCompleted status: \"True\" type: Validated - message: All clusters are compliant with all the managed policies reason: Completed status: \"False\" type: Progressing 2 - message: All clusters are compliant with all the managed policies reason: Completed status: \"True\" type: Succeeded 3 managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default remediationPlan: - - spoke1 - - spoke4 status: completedAt: '2022-11-18T16:27:16Z' startedAt: '2022-11-18T16:27:15Z'", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: creationTimestamp: '2022-11-18T16:27:15Z' finalizers: - ran.openshift.io/cleanup-finalizer generation: 1 name: talm-cgu namespace: talm-namespace resourceVersion: '40451823' uid: cca245a5-4bca-45fa-89c0-aa6af81a596c spec: actions: afterCompletion: deleteObjects: true beforeEnable: {} clusters: - spoke1 - spoke2 enable: true managedPolicies: - talm-policy preCaching: false remediationStrategy: maxConcurrency: 2 timeout: 240 status: clusters: - name: spoke1 state: complete - currentPolicy: 1 name: talm-policy status: NonCompliant name: spoke2 state: timedout computedMaxConcurrency: 2 conditions: - lastTransitionTime: '2022-11-18T16:27:15Z' message: All selected clusters are valid reason: ClusterSelectionCompleted status: 'True' type: ClustersSelected - lastTransitionTime: '2022-11-18T16:27:15Z' message: Completed validation reason: ValidationCompleted status: 'True' type: Validated - lastTransitionTime: '2022-11-18T16:37:16Z' message: Policy remediation took too long reason: TimedOut status: 'False' type: Progressing - lastTransitionTime: '2022-11-18T16:37:16Z' message: Policy remediation took too long reason: TimedOut status: 'False' type: Succeeded 2 managedPoliciesForUpgrade: - name: talm-policy namespace: talm-namespace managedPoliciesNs: talm-policy: talm-namespace remediationPlan: - - spoke1 - spoke2 status: startedAt: '2022-11-18T16:27:15Z' completedAt: '2022-11-18T20:27:15Z'", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-a namespace: default spec: blockingCRs: 1 - name: cgu-c namespace: default clusters: - spoke1 - spoke2 - spoke3 enable: false managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy remediationStrategy: canaries: - spoke1 maxConcurrency: 2 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR is not enabled reason: UpgradeNotStarted status: \"False\" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default placementBindings: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy placementRules: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy remediationPlan: - - spoke1 - - spoke2", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-b namespace: default spec: blockingCRs: 1 - name: cgu-a namespace: default clusters: - spoke4 - spoke5 enable: false managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR is not enabled reason: UpgradeNotStarted status: \"False\" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy placementRules: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy remediationPlan: - - spoke4 - - spoke5 status: {}", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-c namespace: default spec: 1 clusters: - spoke6 enable: false managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR is not enabled reason: UpgradeNotStarted status: \"False\" type: Ready managedPoliciesCompliantBeforeUpgrade: - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy placementRules: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy remediationPlan: - - spoke6 status: {}", "oc apply -f <name>.yaml", "oc --namespace=default patch clustergroupupgrade.ran.openshift.io/<name> --type merge -p '{\"spec\":{\"enable\":true}}'", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-a namespace: default spec: blockingCRs: - name: cgu-c namespace: default clusters: - spoke1 - spoke2 - spoke3 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy remediationStrategy: canaries: - spoke1 maxConcurrency: 2 timeout: 240 status: conditions: - message: 'The ClusterGroupUpgrade CR is blocked by other CRs that have not yet completed: [cgu-c]' 1 reason: UpgradeCannotStart status: \"False\" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default placementBindings: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy placementRules: - cgu-a-policy1-common-cluster-version-policy - cgu-a-policy2-common-pao-sub-policy - cgu-a-policy3-common-ptp-sub-policy remediationPlan: - - spoke1 - - spoke2 status: {}", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-b namespace: default spec: blockingCRs: - name: cgu-a namespace: default clusters: - spoke4 - spoke5 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: 'The ClusterGroupUpgrade CR is blocked by other CRs that have not yet completed: [cgu-a]' 1 reason: UpgradeCannotStart status: \"False\" type: Ready managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy2-common-pao-sub-policy namespace: default - name: policy3-common-ptp-sub-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy placementRules: - cgu-b-policy1-common-cluster-version-policy - cgu-b-policy2-common-pao-sub-policy - cgu-b-policy3-common-ptp-sub-policy - cgu-b-policy4-common-sriov-sub-policy remediationPlan: - - spoke4 - - spoke5 status: {}", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-c namespace: default spec: clusters: - spoke6 enable: true managedPolicies: - policy1-common-cluster-version-policy - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy remediationStrategy: maxConcurrency: 1 timeout: 240 status: conditions: - message: The ClusterGroupUpgrade CR has upgrade policies that are still non compliant 1 reason: UpgradeNotCompleted status: \"False\" type: Ready managedPoliciesCompliantBeforeUpgrade: - policy2-common-pao-sub-policy - policy3-common-ptp-sub-policy managedPoliciesForUpgrade: - name: policy1-common-cluster-version-policy namespace: default - name: policy4-common-sriov-sub-policy namespace: default placementBindings: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy placementRules: - cgu-c-policy1-common-cluster-version-policy - cgu-c-policy4-common-sriov-sub-policy remediationPlan: - - spoke6 status: currentBatch: 1 remediationPlanForBatch: spoke6: 0", "apiVersion: policy.open-cluster-management.io/v1 kind: Policy metadata: name: ocp-4.4.18.4 namespace: platform-upgrade spec: disabled: false policy-templates: - objectDefinition: apiVersion: policy.open-cluster-management.io/v1 kind: ConfigurationPolicy metadata: name: upgrade spec: namespaceselector: exclude: - kube-* include: - '' object-templates: - complianceType: musthave objectDefinition: apiVersion: config.openshift.io/v1 kind: ClusterVersion metadata: name: version spec: channel: stable-4.18 desiredUpdate: version: 4.4.18.4 upstream: https://api.openshift.com/api/upgrades_info/v1/graph status: history: - state: Completed version: 4.4.18.4 remediationAction: inform severity: low remediationAction: inform", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: cluster-logging namespace: openshift-logging annotations: ran.openshift.io/ztp-deploy-wave: \"2\" spec: channel: \"stable\" name: cluster-logging source: redhat-operators sourceNamespace: openshift-marketplace installPlanApproval: Manual status: state: AtLatestKnown 1", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: cgu-1 namespace: default spec: managedPolicies: 1 - policy1-common-cluster-version-policy - policy2-common-nto-sub-policy - policy3-common-ptp-sub-policy - policy4-common-sriov-sub-policy enable: false clusters: 2 - spoke1 - spoke2 - spoke5 - spoke6 remediationStrategy: maxConcurrency: 2 3 timeout: 240 4 batchTimeoutAction: 5", "oc create -f cgu-1.yaml", "oc get cgu --all-namespaces", "NAMESPACE NAME AGE STATE DETAILS default cgu-1 8m55 NotEnabled Not Enabled", "oc get cgu -n default cgu-1 -ojsonpath='{.status}' \| jq", "{ \"computedMaxConcurrency\": 2, \"conditions\": [ { \"lastTransitionTime\": \"2022-02-25T15:34:07Z\", \"message\": \"Not enabled\", 1 \"reason\": \"NotEnabled\", \"status\": \"False\", \"type\": \"Progressing\" } ], \"managedPoliciesContent\": { \"policy1-common-cluster-version-policy\": \"null\", \"policy2-common-nto-sub-policy\": \"[{\\\"kind\\\":\\\"Subscription\\\",\\\"name\\\":\\\"node-tuning-operator\\\",\\\"namespace\\\":\\\"openshift-cluster-node-tuning-operator\\\"}]\", \"policy3-common-ptp-sub-policy\": \"[{\\\"kind\\\":\\\"Subscription\\\",\\\"name\\\":\\\"ptp-operator-subscription\\\",\\\"namespace\\\":\\\"openshift-ptp\\\"}]\", \"policy4-common-sriov-sub-policy\": \"[{\\\"kind\\\":\\\"Subscription\\\",\\\"name\\\":\\\"sriov-network-operator-subscription\\\",\\\"namespace\\\":\\\"openshift-sriov-network-operator\\\"}]\" }, \"managedPoliciesForUpgrade\": [ { \"name\": \"policy1-common-cluster-version-policy\", \"namespace\": \"default\" }, { \"name\": \"policy2-common-nto-sub-policy\", \"namespace\": \"default\" }, { \"name\": \"policy3-common-ptp-sub-policy\", \"namespace\": \"default\" }, { \"name\": \"policy4-common-sriov-sub-policy\", \"namespace\": \"default\" } ], \"managedPoliciesNs\": { \"policy1-common-cluster-version-policy\": \"default\", \"policy2-common-nto-sub-policy\": \"default\", \"policy3-common-ptp-sub-policy\": \"default\", \"policy4-common-sriov-sub-policy\": \"default\" }, \"placementBindings\": [ \"cgu-policy1-common-cluster-version-policy\", \"cgu-policy2-common-nto-sub-policy\", \"cgu-policy3-common-ptp-sub-policy\", \"cgu-policy4-common-sriov-sub-policy\" ], \"placementRules\": [ \"cgu-policy1-common-cluster-version-policy\", \"cgu-policy2-common-nto-sub-policy\", \"cgu-policy3-common-ptp-sub-policy\", \"cgu-policy4-common-sriov-sub-policy\" ], \"remediationPlan\": [ [ \"spoke1\", \"spoke2\" ], [ \"spoke5\", \"spoke6\" ] ], \"status\": {} }", "oc --namespace=default patch clustergroupupgrade.ran.openshift.io/cgu-1 --patch '{\"spec\":{\"enable\":true}}' --type=merge", "oc get cgu -n default cgu-1 -ojsonpath='{.status}' \| jq", "{ \"computedMaxConcurrency\": 2, \"conditions\": [ 1 { \"lastTransitionTime\": \"2022-02-25T15:33:07Z\", \"message\": \"All selected clusters are valid\", \"reason\": \"ClusterSelectionCompleted\", \"status\": \"True\", \"type\": \"ClustersSelected\" }, { \"lastTransitionTime\": \"2022-02-25T15:33:07Z\", \"message\": \"Completed validation\", \"reason\": \"ValidationCompleted\", \"status\": \"True\", \"type\": \"Validated\" }, { \"lastTransitionTime\": \"2022-02-25T15:34:07Z\", \"message\": \"Remediating non-compliant policies\", \"reason\": \"InProgress\", \"status\": \"True\", \"type\": \"Progressing\" } ], \"managedPoliciesContent\": { \"policy1-common-cluster-version-policy\": \"null\", \"policy2-common-nto-sub-policy\": \"[{\\\"kind\\\":\\\"Subscription\\\",\\\"name\\\":\\\"node-tuning-operator\\\",\\\"namespace\\\":\\\"openshift-cluster-node-tuning-operator\\\"}]\", \"policy3-common-ptp-sub-policy\": \"[{\\\"kind\\\":\\\"Subscription\\\",\\\"name\\\":\\\"ptp-operator-subscription\\\",\\\"namespace\\\":\\\"openshift-ptp\\\"}]\", \"policy4-common-sriov-sub-policy\": \"[{\\\"kind\\\":\\\"Subscription\\\",\\\"name\\\":\\\"sriov-network-operator-subscription\\\",\\\"namespace\\\":\\\"openshift-sriov-network-operator\\\"}]\" }, \"managedPoliciesForUpgrade\": [ { \"name\": \"policy1-common-cluster-version-policy\", \"namespace\": \"default\" }, { \"name\": \"policy2-common-nto-sub-policy\", \"namespace\": \"default\" }, { \"name\": \"policy3-common-ptp-sub-policy\", \"namespace\": \"default\" }, { \"name\": \"policy4-common-sriov-sub-policy\", \"namespace\": \"default\" } ], \"managedPoliciesNs\": { \"policy1-common-cluster-version-policy\": \"default\", \"policy2-common-nto-sub-policy\": \"default\", \"policy3-common-ptp-sub-policy\": \"default\", \"policy4-common-sriov-sub-policy\": \"default\" }, \"placementBindings\": [ \"cgu-policy1-common-cluster-version-policy\", \"cgu-policy2-common-nto-sub-policy\", \"cgu-policy3-common-ptp-sub-policy\", \"cgu-policy4-common-sriov-sub-policy\" ], \"placementRules\": [ \"cgu-policy1-common-cluster-version-policy\", \"cgu-policy2-common-nto-sub-policy\", \"cgu-policy3-common-ptp-sub-policy\", \"cgu-policy4-common-sriov-sub-policy\" ], \"remediationPlan\": [ [ \"spoke1\", \"spoke2\" ], [ \"spoke5\", \"spoke6\" ] ], \"status\": { \"currentBatch\": 1, \"currentBatchRemediationProgress\": { \"spoke1\": { \"policyIndex\": 1, \"state\": \"InProgress\" }, \"spoke2\": { \"policyIndex\": 1, \"state\": \"InProgress\" } }, \"currentBatchStartedAt\": \"2022-02-25T15:54:16Z\", \"startedAt\": \"2022-02-25T15:54:16Z\" } }", "get policies -A", "NAMESPACE NAME REMEDIATION ACTION COMPLIANCE STATE AGE spoke1 default.policy1-common-cluster-version-policy enforce Compliant 18m spoke1 default.policy2-common-nto-sub-policy enforce NonCompliant 18m spoke2 default.policy1-common-cluster-version-policy enforce Compliant 18m spoke2 default.policy2-common-nto-sub-policy enforce NonCompliant 18m spoke5 default.policy3-common-ptp-sub-policy inform NonCompliant 18m spoke5 default.policy4-common-sriov-sub-policy inform NonCompliant 18m spoke6 default.policy3-common-ptp-sub-policy inform NonCompliant 18m spoke6 default.policy4-common-sriov-sub-policy inform NonCompliant 18m default policy1-common-ptp-sub-policy inform Compliant 18m default policy2-common-sriov-sub-policy inform NonCompliant 18m default policy3-common-ptp-sub-policy inform NonCompliant 18m default policy4-common-sriov-sub-policy inform NonCompliant 18m", "export KUBECONFIG=<cluster_kubeconfig_absolute_path>", "oc get subs -A \| grep -i <subscription_name>", "NAMESPACE NAME PACKAGE SOURCE CHANNEL openshift-logging cluster-logging cluster-logging redhat-operators stable", "oc get clusterversion", "NAME VERSION AVAILABLE PROGRESSING SINCE STATUS version 4.4.18.5 True True 43s Working towards 4.4.18.7: 71 of 735 done (9% complete)", "oc get subs -n <operator-namespace> <operator-subscription> -ojsonpath=\"{.status}\"", "oc get installplan -n <subscription_namespace>", "NAMESPACE NAME CSV APPROVAL APPROVED openshift-logging install-6khtw cluster-logging.5.3.3-4 Manual true 1", "oc get csv -n <operator_namespace>", "NAME DISPLAY VERSION REPLACES PHASE cluster-logging.5.4.2 Red Hat OpenShift Logging 5.4.2 Succeeded", "oc adm release info <ocp-version>", "apiVersion: v1 kind: ConfigMap metadata: name: cluster-group-upgrade-overrides data: excludePrecachePatterns: \| azure 1 aws vsphere alibaba", "apiVersion: ran.openshift.io/v1alpha1 kind: ClusterGroupUpgrade metadata: name: du-upgrade-4918 namespace: ztp-group-du-sno spec: preCaching: true 1 clusters: - cnfdb1 - cnfdb2 enable: false managedPolicies: - du-upgrade-platform-upgrade remediationStrategy: maxConcurrency: 2 timeout: 240", "oc apply -f clustergroupupgrades-group-du.yaml", "oc get cgu -A", "NAMESPACE NAME AGE STATE DETAILS ztp-group-du-sno du-upgrade-4918 10s InProgress Precaching is required and not done 1", "oc get cgu -n ztp-group-du-sno du-upgrade-4918 -o jsonpath='{.status}'", "{ \"conditions\": [ { \"lastTransitionTime\": \"2022-01-27T19:07:24Z\", \"message\": \"Precaching is required and not done\", \"reason\": \"InProgress\", \"status\": \"False\", \"type\": \"PrecachingSucceeded\" }, { \"lastTransitionTime\": \"2022-01-27T19:07:34Z\", \"message\": \"Pre-caching spec is valid and consistent\", \"reason\": \"PrecacheSpecIsWellFormed\", \"status\": \"True\", \"type\": \"PrecacheSpecValid\" } ], \"precaching\": { \"clusters\": [ \"cnfdb1\" 1 \"cnfdb2\" ], \"spec\": { \"platformImage\": \"image.example.io\"}, \"status\": { \"cnfdb1\": \"Active\" \"cnfdb2\": \"Succeeded\"} } }", "oc get jobs,pods -n openshift-talo-pre-cache", "NAME COMPLETIONS DURATION AGE job.batch/pre-cache 0/1 3m10s 3m10s NAME READY STATUS RESTARTS AGE pod/pre-cache--1-9bmlr 1/1 Running 0 3m10s", "oc get cgu -n ztp-group-du-sno du-upgrade-4918 -o jsonpath='{.status}'", "\"conditions\": [ { \"lastTransitionTime\": \"2022-01-27T19:30:41Z\", \"message\": \"The ClusterGroupUpgrade CR has all clusters compliant with all the managed policies\", \"reason\": \"UpgradeCompleted\", \"status\": \"True\", \"type\": \"Ready\" }, { \"lastTransitionTime\": \"2022-01-27T19:28:57Z\", \"message\": \"Precaching is completed\", \"reason\": \"PrecachingCompleted\", \"status\": \"True\", \"type\": \"PrecachingSucceeded\" 1 }", "oc delete cgu -n <ClusterGroupUpgradeCR_namespace> <ClusterGroupUpgradeCR_name>", "oc apply -f <ClusterGroupUpgradeCR_YAML>", "oc get cgu lab-upgrade -ojsonpath='{.spec.managedPolicies}'", "[\"group-du-sno-validator-du-validator-policy\", \"policy2-common-nto-sub-policy\", \"policy3-common-ptp-sub-policy\"]", "oc get policies --all-namespaces", "NAMESPACE NAME REMEDIATION ACTION COMPLIANCE STATE AGE default policy1-common-cluster-version-policy inform NonCompliant 5d21h default policy2-common-nto-sub-policy inform Compliant 5d21h default policy3-common-ptp-sub-policy inform NonCompliant 5d21h default policy4-common-sriov-sub-policy inform NonCompliant 5d21h", "oc get policies --all-namespaces", "NAMESPACE NAME REMEDIATION ACTION COMPLIANCE STATE AGE default policy1-common-cluster-version-policy inform NonCompliant 5d21h default policy2-common-nto-sub-policy inform Compliant 5d21h default policy3-common-ptp-sub-policy inform NonCompliant 5d21h default policy4-common-sriov-sub-policy inform NonCompliant 5d21h", "oc get managedclusters", "NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE local-cluster true https://api.hub.example.com:6443 True Unknown 13d spoke1 true https://api.spoke1.example.com:6443 True True 13d spoke3 true https://api.spoke3.example.com:6443 True True 27h", "oc get pod -n openshift-operators", "NAME READY STATUS RESTARTS AGE cluster-group-upgrades-controller-manager-75bcc7484d-8k8xp 2/2 Running 0 45m", "oc logs -n openshift-operators cluster-group-upgrades-controller-manager-75bcc7484d-8k8xp -c manager", "ERROR controller-runtime.manager.controller.clustergroupupgrade Reconciler error {\"reconciler group\": \"ran.openshift.io\", \"reconciler kind\": \"ClusterGroupUpgrade\", \"name\": \"lab-upgrade\", \"namespace\": \"default\", \"error\": \"Cluster spoke5555 is not a ManagedCluster\"} 1 sigs.k8s.io/controller-runtime/pkg/internal/controller.(Controller).processNextWorkItem", "oc get managedclusters", "NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE local-cluster true https://api.hub.testlab.com:6443 True Unknown 13d spoke1 true https://api.spoke1.testlab.com:6443 True True 13d 1 spoke3 true https://api.spoke3.testlab.com:6443 True True 27h 2", "oc get managedcluster --selector=upgrade=true 1", "NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE spoke1 true https://api.spoke1.testlab.com:6443 True True 13d spoke3 true https://api.spoke3.testlab.com:6443 True True 27h", "spec: remediationStrategy: canaries: - spoke3 maxConcurrency: 2 timeout: 240 clusterLabelSelectors: - matchLabels: upgrade: true", "oc get cgu lab-upgrade -ojsonpath='{.spec.clusters}'", "[\"spoke1\", \"spoke3\"]", "oc get managedcluster --selector=upgrade=true", "NAME HUB ACCEPTED MANAGED CLUSTER URLS JOINED AVAILABLE AGE spoke1 true https://api.spoke1.testlab.com:6443 True True 13d spoke3 true https://api.spoke3.testlab.com:6443 True True 27h", "oc get jobs,pods -n openshift-talo-pre-cache", "oc get cgu lab-upgrade -ojsonpath='{.spec.remediationStrategy}'", "{\"maxConcurrency\":2, \"timeout\":240}", "oc get cgu lab-upgrade -ojsonpath='{.spec.remediationStrategy.maxConcurrency}'", "2", "oc get cgu lab-upgrade -ojsonpath='{.status.conditions}'", "{\"lastTransitionTime\":\"2022-02-17T22:25:28Z\", \"message\":\"Missing managed policies:[policyList]\", \"reason\":\"NotAllManagedPoliciesExist\", \"status\":\"False\", \"type\":\"Validated\"}", "oc get cgu lab-upgrade -ojsonpath='{.status.remediationPlan}'", "[[\"spoke2\", \"spoke3\"]]", "oc logs -n openshift-operators cluster-group-upgrades-controller-manager-75bcc7484d-8k8xp -c manager", "ERROR controller-runtime.manager.controller.clustergroupupgrade Reconciler error {\"reconciler group\": \"ran.openshift.io\", \"reconciler kind\": \"ClusterGroupUpgrade\", \"name\": \"lab-upgrade\", \"namespace\": \"default\", \"error\": \"Cluster spoke5555 is not a ManagedCluster\"} 1 sigs.k8s.io/controller-runtime/pkg/internal/controller.(*Controller).processNextWorkItem", "oc get pods -n openshift-talo-pre-cache", "oc logs -n openshift-talo-pre-cache <pod name>", "oc describe pod -n openshift-talo-pre-cache <pod name>", "oc describe job -n openshift-talo-pre-cache pre-cache" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.18/html/edge_computing/cnf-talm-for-cluster-updates
GitOps	GitOps Red Hat Advanced Cluster Management for Kubernetes 2.11 GitOps Red Hat Advanced Cluster Management for Kubernetes Team	[ "apiVersion: apps.open-cluster-management.io/v1beta1 kind: GitOpsCluster metadata: name: gitops-cluster-sample namespace: dev spec: argoServer: cluster: local-cluster argoNamespace: openshift-gitops placementRef: kind: Placement apiVersion: cluster.open-cluster-management.io/v1beta1 name: all-openshift-clusters 1", "apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: application-set-admin rules: - apiGroups: - argoproj.io resources: - applicationsets verbs: - get - list - watch - update - delete - deletecollection - patch", "apiVersion: cluster.open-cluster-management.io/v1beta1 kind: Placement metadata: name: placement namespace: ns1 spec: tolerations: - key: cluster.open-cluster-management.io/unreachable operator: Exists - key: cluster.open-cluster-management.io/unavailable operator: Exists", "cannot create resource \"services\" in API group \"\" in the namespace \"mortgage\",deployments.apps is forbidden: User \"system:serviceaccount:openshift-gitops:openshift-gitops-Argo CD-application-controller\"", "kind: ClusterRoleBinding apiVersion: rbac.authorization.k8s.io/v1 metadata: name: argo-admin subjects: - kind: ServiceAccount name: openshift-gitops-argocd-application-controller namespace: openshift-gitops roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: cluster-admin", "apiVersion: v1 kind: Namespace metadata: name: mortgage2 labels: argocd.argoproj.io/managed-by: openshift-gitops", "apiVersion: argoproj.io/v1alpha1 kind: `ApplicationSet` metadata: name: guestbook-allclusters-app-set namespace: openshift-gitops spec: generators: - clusterDecisionResource: configMapRef: ocm-placement-generator labelSelector: matchLabels: cluster.open-cluster-management.io/placement: aws-app-placement requeueAfterSeconds: 30 template: metadata: annotations: apps.open-cluster-management.io/ocm-managed-cluster: '{{name}}' 1 apps.open-cluster-management.io/ocm-managed-cluster-app-namespace: openshift-gitops argocd.argoproj.io/skip-reconcile: \"true\" 2 labels: apps.open-cluster-management.io/pull-to-ocm-managed-cluster: \"true\" 3 name: '{{name}}-guestbook-app' spec: destination: namespace: guestbook server: https://kubernetes.default.svc project: default sources: [ { repoURL: https://github.com/argoproj/argocd-example-apps.git targetRevision: main path: guestbook } ] syncPolicy: automated: {} syncOptions: - CreateNamespace=true", "NAMESPACE NAME READY STATUS open-cluster-management multicluster-integrations-7c46498d9-fqbq4 3/3 Running", "apiVersion: apps.open-cluster-management.io/v1alpha1 kind: MulticlusterApplicationSetReport metadata: labels: apps.open-cluster-management.io/hosting-applicationset: openshift-gitops.guestbook-allclusters-app-set name: guestbook-allclusters-app-set namespace: openshift-gitops statuses: clusterConditions: - cluster: cluster1 conditions: - message: 'Failed sync attempt: one or more objects failed to apply, reason: services is forbidden: User \"system:serviceaccount:openshift-gitops:openshift-gitops-Argo CD-application-controller\" cannot create resource \"services\" in API group \"\" in the namespace \"guestbook\",deployments.apps is forbidden: User <name> cannot create resource \"deployments\" in API group \"apps\" in the namespace \"guestboo...' type: SyncError healthStatus: Missing syncStatus: OutOfSync - cluster: pcluster1 healthStatus: Progressing syncStatus: Synced - cluster: pcluster2 healthStatus: Progressing syncStatus: Synced summary: clusters: \"3\" healthy: \"0\" inProgress: \"2\" notHealthy: \"3\" notSynced: \"1\" synced: \"2\"", "kind: ClusterRole apiVersion: rbac.authorization.k8s.io/v1 metadata: name: openshift-gitops-policy-admin rules: - verbs: - get - list - watch - create - update - patch - delete apiGroups: - policy.open-cluster-management.io resources: - policies - policysets - placementbindings - verbs: - get - list - watch - create - update - patch - delete apiGroups: - apps.open-cluster-management.io resources: - placementrules - verbs: - get - list - watch - create - update - patch - delete apiGroups: - cluster.open-cluster-management.io resources: - placements - placements/status - placementdecisions - placementdecisions/status", "kind: ClusterRoleBinding apiVersion: rbac.authorization.k8s.io/v1 metadata: name: openshift-gitops-policy-admin subjects: - kind: ServiceAccount name: openshift-gitops-argocd-application-controller namespace: openshift-gitops roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: openshift-gitops-policy-admin", "-n openshift-gitops edit argocd openshift-gitops", "apiVersion: argoproj.io/v1beta1 kind: ArgoCD metadata: name: openshift-gitops namespace: openshift-gitops spec: kustomizeBuildOptions: --enable-alpha-plugins repo: env: - name: KUSTOMIZE_PLUGIN_HOME value: /etc/kustomize/plugin initContainers: - args: - -c - cp /policy-generator/PolicyGenerator-not-fips-compliant /policy-generator-tmp/PolicyGenerator command: - /bin/bash image: registry.redhat.io/rhacm2/multicluster-operators-subscription-rhel9:v<version> name: policy-generator-install volumeMounts: - mountPath: /policy-generator-tmp name: policy-generator volumeMounts: - mountPath: /etc/kustomize/plugin/policy.open-cluster-management.io/v1/policygenerator name: policy-generator volumes: - emptyDir: {} name: policy-generator", "image: '{{ (index (lookup \"apps/v1\" \"Deployment\" \"open-cluster-management\" \"multicluster-operators-hub-subscription\").spec.template.spec.containers 0).image }}'", "env: - name: POLICY_GEN_ENABLE_HELM value: \"true\"", "kind: ClusterRoleBinding apiVersion: rbac.authorization.k8s.io/v1 metadata: name: openshift-gitops-policy-admin subjects: - kind: ServiceAccount name: openshift-gitops-argocd-application-controller namespace: openshift-gitops roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: openshift-gitops-policy-admin", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-gitops-operator namespace: openshift-operators spec: channel: stable name: openshift-gitops-operator source: redhat-operators sourceNamespace: openshift-marketplace", "apiVersion: policy.open-cluster-management.io/v1 kind: PolicyGenerator metadata: name: install-openshift-gitops policyDefaults: namespace: policies placement: clusterSelectors: vendor: \"OpenShift\" remediationAction: enforce policies: - name: install-openshift-gitops manifests: - path: openshift-gitops-subscription.yaml", "generators: - policy-generator-config.yaml", "apiVersion: apps.open-cluster-management.io/v1 kind: PlacementRule metadata: name: placement-install-openshift-gitops namespace: policies spec: clusterConditions: - status: \"True\" type: ManagedClusterConditionAvailable clusterSelector: matchExpressions: - key: vendor operator: In values: - OpenShift --- apiVersion: policy.open-cluster-management.io/v1 kind: PlacementBinding metadata: name: binding-install-openshift-gitops namespace: policies placementRef: apiGroup: apps.open-cluster-management.io kind: PlacementRule name: placement-install-openshift-gitops subjects: - apiGroup: policy.open-cluster-management.io kind: Policy name: install-openshift-gitops --- apiVersion: policy.open-cluster-management.io/v1 kind: Policy metadata: annotations: policy.open-cluster-management.io/categories: CM Configuration Management policy.open-cluster-management.io/controls: CM-2 Baseline Configuration policy.open-cluster-management.io/standards: NIST SP 800-53 policy.open-cluster-management.io/description: name: install-openshift-gitops namespace: policies spec: disabled: false policy-templates: - objectDefinition: apiVersion: policy.open-cluster-management.io/v1 kind: ConfigurationPolicy metadata: name: install-openshift-gitops spec: object-templates: - complianceType: musthave objectDefinition: apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-gitops-operator namespace: openshift-operators spec: channel: stable name: openshift-gitops-operator source: redhat-operators sourceNamespace: openshift-marketplace remediationAction: enforce severity: low", "apiVersion: rbac.open-cluster-management.io/v1alpha1 kind: ClusterPermission metadata: name: <clusterpermission-msa-subject-sample> namespace: <managed cluster> spec: roles: - namespace: default rules: - apiGroups: [\"apps\"] resources: [\"deployments\"] verbs: [\"get\", \"list\", \"create\", \"update\", \"delete\", \"patch\"] - apiGroups: [\"\"] resources: [\"configmaps\", \"secrets\", \"pods\", \"podtemplates\", \"persistentvolumeclaims\", \"persistentvolumes\"] verbs: [\"get\", \"update\", \"list\", \"create\", \"delete\", \"patch\"] - apiGroups: [\"storage.k8s.io\"] resources: [\"\"] verbs: [\"list\"] - namespace: mortgage rules: - apiGroups: [\"apps\"] resources: [\"deployments\"] verbs: [\"get\", \"list\", \"create\", \"update\", \"delete\", \"patch\"] - apiGroups: [\"\"] resources: [\"configmaps\", \"secrets\", \"pods\", \"services\", \"namespace\"] verbs: [\"get\", \"update\", \"list\", \"create\", \"delete\", \"patch\"] clusterRole: rules: - apiGroups: [\"\"] resources: [\"\"] verbs: [\"get\", \"list\"] roleBindings: - namespace: default roleRef: kind: Role subject: apiGroup: authentication.open-cluster-management.io kind: ManagedServiceAccount name: <managed-sa-sample> - namespace: mortgage roleRef: kind: Role subject: apiGroup: authentication.open-cluster-management.io kind: ManagedServiceAccount name: <managed-sa-sample> clusterRoleBinding: subject: apiGroup: authentication.open-cluster-management.io kind: ManagedServiceAccount name: <managed-sa-sample>", "--- apiVersion: apps.open-cluster-management.io/v1beta1 metadata: name: argo-acm-importer namespace: openshift-gitops spec: managedServiceAccountRef: <managed-sa-sample> argoServer: cluster: notused argoNamespace: openshift-gitops placementRef: kind: Placement apiVersion: cluster.open-cluster-management.io/v1beta1 name: all-openshift-clusters namespace: openshift-gitops", "% oc get secrets -n openshift-gitops <managed cluster-managed-sa-sample-cluster-secret> NAME TYPE DATA AGE <managed cluster-managed-sa-sample-cluster-secret> Opaque 3 4m2s", "When the GitOpsCluster resource is updated with the `managedServiceAccountRef`, each managed cluster in the placement of this GitOpsCluster needs to have the service account. If you have several managed clusters, it becomes tedious for you to create the managed service account and cluster permission for each managed cluster. You can simply this process by using a policy to create the managed service account and cluster permission for all your managed clusters", "apiVersion: policy.open-cluster-management.io/v1 kind: Policy metadata: name: policy-gitops namespace: openshift-gitops annotations: policy.open-cluster-management.io/standards: NIST-CSF policy.open-cluster-management.io/categories: PR.PT Protective Technology policy.open-cluster-management.io/controls: PR.PT-3 Least Functionality spec: remediationAction: enforce disabled: false policy-templates: - objectDefinition: apiVersion: policy.open-cluster-management.io/v1 kind: ConfigurationPolicy metadata: name: policy-gitops-sub spec: pruneObjectBehavior: None remediationAction: enforce severity: low object-templates-raw: \| {{ range USDplacedec := (lookup \"cluster.open-cluster-management.io/v1beta1\" \"PlacementDecision\" \"openshift-gitops\" \"\" \"cluster.open-cluster-management.io/placement=aws-app-placement\").items }} {{ range USDclustdec := USDplacedec.status.decisions }} - complianceType: musthave objectDefinition: apiVersion: authentication.open-cluster-management.io/v1alpha1 kind: ManagedServiceAccount metadata: name: <managed-sa-sample> namespace: {{ USDclustdec.clusterName }} spec: rotation: {} - complianceType: musthave objectDefinition: apiVersion: rbac.open-cluster-management.io/v1alpha1 kind: ClusterPermission metadata: name: <clusterpermission-msa-subject-sample> namespace: {{ USDclustdec.clusterName }} spec: roles: - namespace: default rules: - apiGroups: [\"apps\"] resources: [\"deployments\"] verbs: [\"get\", \"list\", \"create\", \"update\", \"delete\"] - apiGroups: [\"\"] resources: [\"configmaps\", \"secrets\", \"pods\", \"podtemplates\", \"persistentvolumeclaims\", \"persistentvolumes\"] verbs: [\"get\", \"update\", \"list\", \"create\", \"delete\"] - apiGroups: [\"storage.k8s.io\"] resources: [\"\"] verbs: [\"list\"] - namespace: mortgage rules: - apiGroups: [\"apps\"] resources: [\"deployments\"] verbs: [\"get\", \"list\", \"create\", \"update\", \"delete\"] - apiGroups: [\"\"] resources: [\"configmaps\", \"secrets\", \"pods\", \"services\", \"namespace\"] verbs: [\"get\", \"update\", \"list\", \"create\", \"delete\"] clusterRole: rules: - apiGroups: [\"\"] resources: [\"\"] verbs: [\"get\", \"list\"] roleBindings: - namespace: default roleRef: kind: Role subject: apiGroup: authentication.open-cluster-management.io kind: ManagedServiceAccount name: <managed-sa-sample> - namespace: mortgage roleRef: kind: Role subject: apiGroup: authentication.open-cluster-management.io kind: ManagedServiceAccount name: <managed-sa-sample> clusterRoleBinding: subject: apiGroup: authentication.open-cluster-management.io kind: ManagedServiceAccount name: <managed-sa-sample> {{ end }} {{ end }} --- apiVersion: policy.open-cluster-management.io/v1 kind: PlacementBinding metadata: name: binding-policy-gitops namespace: openshift-gitops placementRef: name: lc-app-placement kind: Placement apiGroup: cluster.open-cluster-management.io subjects: - name: policy-gitops kind: Policy apiGroup: policy.open-cluster-management.io --- apiVersion: cluster.open-cluster-management.io/v1beta1 kind: Placement metadata: name: lc-app-placement namespace: openshift-gitops spec: numberOfClusters: 1 predicates: - requiredClusterSelector: labelSelector: matchLabels: name: local-cluster" ]	https://docs.redhat.com/en/documentation/red_hat_advanced_cluster_management_for_kubernetes/2.11/html-single/gitops/index
Part III. Post deployment operations	Part III. Post deployment operations	null	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/16.0/html/director_installation_and_usage/post_deployment_operations
Chapter 6. Network Configuration	Chapter 6. Network Configuration This chapter provides an introduction to the common networking configurations used by libvirt-based guest virtual machines. Red Hat Enterprise Linux 7 supports the following networking setups for virtualization: virtual networks using Network Address Translation ( NAT ) directly allocated physical devices using PCI device assignment directly allocated virtual functions using PCIe SR-IOV bridged networks You must enable NAT, network bridging or directly assign a PCI device to allow external hosts access to network services on guest virtual machines. 6.1. Network Address Translation (NAT) with libvirt One of the most common methods for sharing network connections is to use Network Address Translation (NAT) forwarding (also known as virtual networks). Host Configuration Every standard libvirt installation provides NAT-based connectivity to virtual machines as the default virtual network. Verify that it is available with the virsh net-list --all command. If it is missing, the following can be used in the XML configuration file (such as /etc/libvirtd/qemu/myguest.xml) for the guest: The default network is defined from /etc/libvirt/qemu/networks/default.xml Mark the default network to automatically start: Start the default network: Once the libvirt default network is running, you will see an isolated bridge device. This device does not have any physical interfaces added. The new device uses NAT and IP forwarding to connect to the physical network. Do not add new interfaces. libvirt adds iptables rules which allow traffic to and from guest virtual machines attached to the virbr0 device in the INPUT , FORWARD , OUTPUT and POSTROUTING chains. libvirt then attempts to enable the ip_forward parameter. Some other applications may disable ip_forward , so the best option is to add the following to /etc/sysctl.conf . Guest Virtual Machine Configuration Once the host configuration is complete, a guest virtual machine can be connected to the virtual network based on its name. To connect a guest to the 'default' virtual network, the following can be used in the XML configuration file (such as /etc/libvirtd/qemu/myguest.xml ) for the guest: Note Defining a MAC address is optional. If you do not define one, a MAC address is automatically generated and used as the MAC address of the bridge device used by the network. Manually setting the MAC address may be useful to maintain consistency or easy reference throughout your environment, or to avoid the very small chance of a conflict.	[ "virsh net-list --all Name State Autostart ----------------------------------------- default active yes", "ll /etc/libvirt/qemu/ total 12 drwx------. 3 root root 4096 Nov 7 23:02 networks -rw-------. 1 root root 2205 Nov 20 01:20 r6.4.xml -rw-------. 1 root root 2208 Nov 8 03:19 r6.xml", "virsh net-autostart default Network default marked as autostarted", "virsh net-start default Network default started", "brctl show bridge name bridge id STP enabled interfaces virbr0 8000.000000000000 yes", "net.ipv4.ip_forward = 1", "<interface type='network'> <source network='default'/> </interface>", "<interface type='network'> <source network='default'/> <mac address='00:16:3e:1a:b3:4a'/> </interface>" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/virtualization_deployment_and_administration_guide/chap-network_configuration
Appendix B. Image configuration parameters	Appendix B. Image configuration parameters You can use the following keys with the --property option for the glance image-create , glance image-create-via-import , and glance image-update commands. Table B.1. Property keys Specific to Key Description Supported values All architecture The CPU architecture that must be supported by the hypervisor. For example, x86_64 , arm , or ppc64 . Run uname -m to get the architecture of a machine. aarch - ARM 64-bit alpha - DEC 64-bit RISC armv7l - ARM Cortex-A7 MPCore cris - Ethernet, Token Ring, AXis-Code Reduced Instruction Set i686 - Intel sixth-generation x86 (P6 micro architecture) ia64 - Itanium lm32 - Lattice Micro32 m68k - Motorola 68000 microblaze - Xilinx 32-bit FPGA (Big Endian) microblazeel - Xilinx 32-bit FPGA (Little Endian) mips - MIPS 32-bit RISC (Big Endian) mipsel - MIPS 32-bit RISC (Little Endian) mips64 - MIPS 64-bit RISC (Big Endian) mips64el - MIPS 64-bit RISC (Little Endian) openrisc - OpenCores RISC parisc - HP Precision Architecture RISC parisc64 - HP Precision Architecture 64-bit RISC ppc - PowerPC 32-bit ppc64 - PowerPC 64-bit ppcemb - PowerPC (Embedded 32-bit) s390 - IBM Enterprise Systems Architecture/390 s390x - S/390 64-bit sh4 - SuperH SH-4 (Little Endian) sh4eb - SuperH SH-4 (Big Endian) sparc - Scalable Processor Architecture, 32-bit sparc64 - Scalable Processor Architecture, 64-bit unicore32 - Microprocessor Research and Development Center RISC Unicore32 x86_64 - 64-bit extension of IA-32 xtensa - Tensilica Xtensa configurable microprocessor core xtensaeb - Tensilica Xtensa configurable microprocessor core (Big Endian) All hypervisor_type The hypervisor type. kvm , vmware All instance_uuid For snapshot images, this is the UUID of the server used to create this image. Valid server UUID All kernel_id The ID of an image stored in the Image Service that should be used as the kernel when booting an AMI-style image. Valid image ID All os_distro The common name of the operating system distribution in lowercase. arch - Arch Linux. Do not use archlinux or org.archlinux . centos - Community Enterprise Operating System. Do not use org.centos or CentOS . debian - Debian. Do not use Debian or org.debian . fedora - Fedora. Do not use Fedora , org.fedora , or org.fedoraproject . freebsd - FreeBSD. Do not use org.freebsd , freeBSD , or FreeBSD . gentoo - Gentoo Linux. Do not use Gentoo or org.gentoo . mandrake - Mandrakelinux (MandrakeSoft) distribution. Do not use mandrakelinux or MandrakeLinux . mandriva - Mandriva Linux. Do not use mandrivalinux . mes - Mandriva Enterprise Server. Do not use mandrivaent or mandrivaES . msdos - Microsoft Disc Operating System. Do not use ms-dos . netbsd - NetBSD. Do not use NetBSD or org.netbsd . netware - Novell NetWare. Do not use novell or NetWare . openbsd - OpenBSD. Do not use OpenBSD or org.openbsd . opensolaris - OpenSolaris. Do not use OpenSolaris or org.opensolaris . opensuse - openSUSE. Do not use suse , SuSE , or org.opensuse . rhel - Red Hat Enterprise Linux. Do not use redhat , RedHat , or com.redhat . sled - SUSE Linux Enterprise Desktop. Do not use com.suse . ubuntu - Ubuntu. Do not use Ubuntu , com.ubuntu , org.ubuntu , or canonical . windows - Microsoft Windows. Do not use com.microsoft.server . All os_version The operating system version as specified by the distributor. Version number (for example, "11.10") All ramdisk_id The ID of image stored in the Image Service that should be used as the ramdisk when booting an AMI-style image. Valid image ID All vm_mode The virtual machine mode. This represents the host/guest ABI (application binary interface) used for the virtual machine. hvm -Fully virtualized. This is the mode used by QEMU and KVM. libvirt API driver hw_cdrom_bus Specifies the type of disk controller to attach CD-ROM devices to. scsi , virtio , ide , or usb . If you specify iscsi , you must set the hw_scsi_model parameter to virtio-scsi . libvirt API driver hw_disk_bus Specifies the type of disk controller to attach disk devices to. scsi , virtio , ide , or usb . Note that if using iscsi , the hw_scsi_model needs to be set to virtio-scsi . libvirt API driver hw_firmware_type Specifies the type of firmware to use to boot the instance. Set to one of the following valid values: bios uefi libvirt API driver hw_machine_type Enables booting an ARM system using the specified machine type. If an ARM image is used and its machine type is not explicitly specified, then Compute uses the virt machine type as the default for ARMv7 and AArch64. Valid types can be viewed by using the virsh capabilities command. The machine types are displayed in the machine tag. libvirt API driver hw_numa_nodes Number of NUMA nodes to expose to the instance (does not override flavor definition). Integer. libvirt API driver hw_numa_cpus.0 Mapping of vCPUs N-M to NUMA node 0 (does not override flavor definition). Comma-separated list of integers. libvirt API driver hw_numa_cpus.1 Mapping of vCPUs N-M to NUMA node 1 (does not override flavor definition). Comma-separated list of integers. libvirt API driver hw_numa_mem.0 Mapping N MB of RAM to NUMA node 0 (does not override flavor definition). Integer libvirt API driver hw_numa_mem.1 Mapping N MB of RAM to NUMA node 1 (does not override flavor definition). Integer libvirt API driver hw_pci_numa_affinity_policy Specifies the NUMA affinity policy for PCI passthrough devices and SR-IOV interfaces. Set to one of the following valid values: required : The Compute service creates an instance that requests a PCI device only when at least one of the NUMA nodes of the instance has affinity with the PCI device. This option provides the best performance. preferred : The Compute service attempts a best effort selection of PCI devices based on NUMA affinity. If affinity is not possible, then the Compute service schedules the instance on a NUMA node that has no affinity with the PCI device. legacy : (Default) The Compute service creates instances that request a PCI device in one of the following cases: The PCI device has affinity with at least one of the NUMA nodes. The PCI devices do not provide information about their NUMA affinities. libvirt API driver hw_qemu_guest_agent Guest agent support. If set to yes , and if qemu-ga is also installed, file systems can be quiesced (frozen) and snapshots created automatically. yes / no libvirt API driver hw_rng_model Adds a random number generator (RNG) device to instances launched with this image. The instance flavor enables the RNG device by default. To disable the RNG device, the cloud administrator must set hw_rng:allowed to False on the flavor. The default entropy source is /dev/random . To specify a hardware RNG device, set rng_dev_path to /dev/hwrng in your Compute environment file. virtio , or other supported device. libvirt API driver hw_scsi_model Enables the use of VirtIO SCSI (virtio-scsi) to provide block device access for compute instances; by default, instances use VirtIO Block (virtio-blk). VirtIO SCSI is a para-virtualized SCSI controller device that provides improved scalability and performance, and supports advanced SCSI hardware. virtio-scsi libvirt API driver hw_tpm_model Set to the model of TPM device to use. Ignored if hw:tpm_version is not configured. tpm-tis : (Default) TPM Interface Specification. tpm-crb : Command-Response Buffer. Compatible only with TPM version 2.0. libvirt API driver hw_tpm_version Set to the version of TPM to use. TPM version 2.0 is the only supported version. 2.0 libvirt API driver hw_video_model The video device driver for the display device to use in virtual machine instances. Set to one of the following values to specify the supported driver to use: virtio - (Default) Recommended Driver for the virtual machine display device, supported by most architectures. The VirtIO GPU driver is included in RHEL-7 and later, and Linux kernel versions 4.4 and later. If an instance kernel has the VirtIO GPU driver, then the instance can use all the VirtIO GPU features. If an instance kernel does not have the VirtIO GPU driver, the VirtIO GPU device gracefully falls back to VGA compatibility mode, which provides a working display for the instance. qxl - Deprecated Driver for Spice or noVNC environments that is no longer maintained. cirrus - Legacy driver, supported only for backward compatibility. Do not use for new instances. vga - Use this driver for IBM Power environments. gop - Not supported for QEMU/KVM environments. xen - Not supported for KVM environments. vmvga - Legacy driver, do not use. none - Use this value to disable emulated graphics or video in virtual GPU (vGPU) instances where the driver is configured separately. libvirt API driver hw_video_ram Maximum RAM for the video image. Used only if a hw_video:ram_max_mb value has been set in the flavor's extra_specs and that value is higher than the value set in hw_video_ram . Integer in MB (for example, 64 ) libvirt API driver hw_watchdog_action Enables a virtual hardware watchdog device that carries out the specified action if the server hangs. The watchdog uses the i6300esb device (emulating a PCI Intel 6300ESB). If hw_watchdog_action is not specified, the watchdog is disabled. disabled-The device is not attached. Allows the user to disable the watchdog for the image, even if it has been enabled using the image's flavor. The default value for this parameter is disabled. reset-Forcefully reset the guest. poweroff-Forcefully power off the guest. pause-Pause the guest. none-Only enable the watchdog; do nothing if the server hangs. libvirt API driver os_command_line The kernel command line to be used by the libvirt driver, instead of the default. For Linux Containers(LXC), the value is used as arguments for initialization. This key is valid only for Amazon kernel, ramdisk, or machine images (aki, ari, or ami). libvirt API driver os_secure_boot Use to create an instance that is protected with UEFI Secure Boot. Set to one of the following valid values: required : Enables Secure Boot for instances launched with this image. The instance is only launched if the Compute service locates a host that can support Secure Boot. If no host is found, the Compute service returns a "No valid host" error. disabled : Disables Secure Boot for instances launched with this image. Disabled by default. optional : Enables Secure Boot for instances launched with this image only when the Compute service determines that the host can support Secure Boot. libvirt API driver and VMware API driver hw_vif_model Specifies the model of virtual network interface device to use. The valid options depend on the configured hypervisor. KVM and QEMU: e1000, ne2k_pci, pcnet, rtl8139, and virtio. VMware: e1000, e1000e, VirtualE1000, VirtualE1000e, VirtualPCNet32, VirtualSriovEthernetCard, and VirtualVmxnet. Xen: e1000, netfront, ne2k_pci, pcnet, and rtl8139. VMware API driver vmware_adaptertype The virtual SCSI or IDE controller used by the hypervisor. lsiLogic , busLogic , or ide VMware API driver vmware_ostype A VMware GuestID which describes the operating system installed in the image. This value is passed to the hypervisor when creating a virtual machine. If not specified, the key defaults to otherGuest . For more information, see Images with VMware vSphere . VMware API driver vmware_image_version Currently unused. 1 XenAPI driver auto_disk_config If true, the root partition on the disk is automatically resized before the instance boots. This value is only taken into account by the Compute service when using a Xen-based hypervisor with the XenAPI driver. The Compute service will only attempt to resize if there is a single partition on the image, and only if the partition is in ext3 or ext4 format. true / false libvirt API driver and XenAPI driver os_type The operating system installed on the image. The XenAPI driver contains logic that takes different actions depending on the value of the os_type parameter of the image. For example, for os_type=windows images, it creates a FAT32-based swap partition instead of a Linux swap partition, and it limits the injected host name to less than 16 characters. linux or windows	null	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/17.1/html/creating_and_managing_images/assembly_image-config-parameters_glance-creating-images
Chapter 8. Working with clusters	Chapter 8. Working with clusters 8.1. Viewing system event information in an OpenShift Container Platform cluster Events in OpenShift Container Platform are modeled based on events that happen to API objects in an OpenShift Container Platform cluster. 8.1.1. Understanding events Events allow OpenShift Container Platform to record information about real-world events in a resource-agnostic manner. They also allow developers and administrators to consume information about system components in a unified way. 8.1.2. Viewing events using the CLI You can get a list of events in a given project using the CLI. Procedure To view events in a project use the following command: USD oc get events [-n <project>] 1 1 The name of the project. For example: USD oc get events -n openshift-config Example output LAST SEEN TYPE REASON OBJECT MESSAGE 97m Normal Scheduled pod/dapi-env-test-pod Successfully assigned openshift-config/dapi-env-test-pod to ip-10-0-171-202.ec2.internal 97m Normal Pulling pod/dapi-env-test-pod pulling image "gcr.io/google_containers/busybox" 97m Normal Pulled pod/dapi-env-test-pod Successfully pulled image "gcr.io/google_containers/busybox" 97m Normal Created pod/dapi-env-test-pod Created container 9m5s Warning FailedCreatePodSandBox pod/dapi-volume-test-pod Failed create pod sandbox: rpc error: code = Unknown desc = failed to create pod network sandbox k8s_dapi-volume-test-pod_openshift-config_6bc60c1f-452e-11e9-9140-0eec59c23068_0(748c7a40db3d08c07fb4f9eba774bd5effe5f0d5090a242432a73eee66ba9e22): Multus: Err adding pod to network "openshift-sdn": cannot set "openshift-sdn" ifname to "eth0": no netns: failed to Statfs "/proc/33366/ns/net": no such file or directory 8m31s Normal Scheduled pod/dapi-volume-test-pod Successfully assigned openshift-config/dapi-volume-test-pod to ip-10-0-171-202.ec2.internal To view events in your project from the OpenShift Container Platform console. Launch the OpenShift Container Platform console. Click Home Events and select your project. Move to resource that you want to see events. For example: Home Projects <project-name> <resource-name>. Many objects, such as pods and deployments, have their own Events tab as well, which shows events related to that object. 8.1.3. List of events This section describes the events of OpenShift Container Platform. Table 8.1. Configuration events Name Description FailedValidation Failed pod configuration validation. Table 8.2. Container events Name Description BackOff Back-off restarting failed the container. Created Container created. Failed Pull/Create/Start failed. Killing Killing the container. Started Container started. Preempting Preempting other pods. ExceededGracePeriod Container runtime did not stop the pod within specified grace period. Table 8.3. Health events Name Description Unhealthy Container is unhealthy. Table 8.4. Image events Name Description BackOff Back off Ctr Start, image pull. ErrImageNeverPull The image's NeverPull Policy is violated. Failed Failed to pull the image. InspectFailed Failed to inspect the image. Pulled Successfully pulled the image or the container image is already present on the machine. Pulling Pulling the image. Table 8.5. Image Manager events Name Description FreeDiskSpaceFailed Free disk space failed. InvalidDiskCapacity Invalid disk capacity. Table 8.6. Node events Name Description FailedMount Volume mount failed. HostNetworkNotSupported Host network not supported. HostPortConflict Host/port conflict. KubeletSetupFailed Kubelet setup failed. NilShaper Undefined shaper. NodeNotReady Node is not ready. NodeNotSchedulable Node is not schedulable. NodeReady Node is ready. NodeSchedulable Node is schedulable. NodeSelectorMismatching Node selector mismatch. OutOfDisk Out of disk. Rebooted Node rebooted. Starting Starting kubelet. FailedAttachVolume Failed to attach volume. FailedDetachVolume Failed to detach volume. VolumeResizeFailed Failed to expand/reduce volume. VolumeResizeSuccessful Successfully expanded/reduced volume. FileSystemResizeFailed Failed to expand/reduce file system. FileSystemResizeSuccessful Successfully expanded/reduced file system. FailedUnMount Failed to unmount volume. FailedMapVolume Failed to map a volume. FailedUnmapDevice Failed unmaped device. AlreadyMountedVolume Volume is already mounted. SuccessfulDetachVolume Volume is successfully detached. SuccessfulMountVolume Volume is successfully mounted. SuccessfulUnMountVolume Volume is successfully unmounted. ContainerGCFailed Container garbage collection failed. ImageGCFailed Image garbage collection failed. FailedNodeAllocatableEnforcement Failed to enforce System Reserved Cgroup limit. NodeAllocatableEnforced Enforced System Reserved Cgroup limit. UnsupportedMountOption Unsupported mount option. SandboxChanged Pod sandbox changed. FailedCreatePodSandBox Failed to create pod sandbox. FailedPodSandBoxStatus Failed pod sandbox status. Table 8.7. Pod worker events Name Description FailedSync Pod sync failed. Table 8.8. System Events Name Description SystemOOM There is an OOM (out of memory) situation on the cluster. Table 8.9. Pod events Name Description FailedKillPod Failed to stop a pod. FailedCreatePodContainer Failed to create a pod container. Failed Failed to make pod data directories. NetworkNotReady Network is not ready. FailedCreate Error creating: <error-msg> . SuccessfulCreate Created pod: <pod-name> . FailedDelete Error deleting: <error-msg> . SuccessfulDelete Deleted pod: <pod-id> . Table 8.10. Horizontal Pod AutoScaler events Name Description SelectorRequired Selector is required. InvalidSelector Could not convert selector into a corresponding internal selector object. FailedGetObjectMetric HPA was unable to compute the replica count. InvalidMetricSourceType Unknown metric source type. ValidMetricFound HPA was able to successfully calculate a replica count. FailedConvertHPA Failed to convert the given HPA. FailedGetScale HPA controller was unable to get the target's current scale. SucceededGetScale HPA controller was able to get the target's current scale. FailedComputeMetricsReplicas Failed to compute desired number of replicas based on listed metrics. FailedRescale New size: <size> ; reason: <msg> ; error: <error-msg> . SuccessfulRescale New size: <size> ; reason: <msg> . FailedUpdateStatus Failed to update status. Table 8.11. Network events (openshift-sdn) Name Description Starting Starting OpenShift SDN. NetworkFailed The pod's network interface has been lost and the pod will be stopped. Table 8.12. Network events (kube-proxy) Name Description NeedPods The service-port <serviceName>:<port> needs pods. Table 8.13. Volume events Name Description FailedBinding There are no persistent volumes available and no storage class is set. VolumeMismatch Volume size or class is different from what is requested in claim. VolumeFailedRecycle Error creating recycler pod. VolumeRecycled Occurs when volume is recycled. RecyclerPod Occurs when pod is recycled. VolumeDelete Occurs when volume is deleted. VolumeFailedDelete Error when deleting the volume. ExternalProvisioning Occurs when volume for the claim is provisioned either manually or via external software. ProvisioningFailed Failed to provision volume. ProvisioningCleanupFailed Error cleaning provisioned volume. ProvisioningSucceeded Occurs when the volume is provisioned successfully. WaitForFirstConsumer Delay binding until pod scheduling. Table 8.14. Lifecycle hooks Name Description FailedPostStartHook Handler failed for pod start. FailedPreStopHook Handler failed for pre-stop. UnfinishedPreStopHook Pre-stop hook unfinished. Table 8.15. Deployments Name Description DeploymentCancellationFailed Failed to cancel deployment. DeploymentCancelled Canceled deployment. DeploymentCreated Created new replication controller. IngressIPRangeFull No available Ingress IP to allocate to service. Table 8.16. Scheduler events Name Description FailedScheduling Failed to schedule pod: <pod-namespace>/<pod-name> . This event is raised for multiple reasons, for example: AssumePodVolumes failed, Binding rejected etc. Preempted By <preemptor-namespace>/<preemptor-name> on node <node-name> . Scheduled Successfully assigned <pod-name> to <node-name> . Table 8.17. Daemon set events Name Description SelectingAll This daemon set is selecting all pods. A non-empty selector is required. FailedPlacement Failed to place pod on <node-name> . FailedDaemonPod Found failed daemon pod <pod-name> on node <node-name> , will try to kill it. Table 8.18. LoadBalancer service events Name Description CreatingLoadBalancerFailed Error creating load balancer. DeletingLoadBalancer Deleting load balancer. EnsuringLoadBalancer Ensuring load balancer. EnsuredLoadBalancer Ensured load balancer. UnAvailableLoadBalancer There are no available nodes for LoadBalancer service. LoadBalancerSourceRanges Lists the new LoadBalancerSourceRanges . For example, <old-source-range> <new-source-range> . LoadbalancerIP Lists the new IP address. For example, <old-ip> <new-ip> . ExternalIP Lists external IP address. For example, Added: <external-ip> . UID Lists the new UID. For example, <old-service-uid> <new-service-uid> . ExternalTrafficPolicy Lists the new ExternalTrafficPolicy . For example, <old-policy> <new-policy> . HealthCheckNodePort Lists the new HealthCheckNodePort . For example, <old-node-port> new-node-port> . UpdatedLoadBalancer Updated load balancer with new hosts. LoadBalancerUpdateFailed Error updating load balancer with new hosts. DeletingLoadBalancer Deleting load balancer. DeletingLoadBalancerFailed Error deleting load balancer. DeletedLoadBalancer Deleted load balancer. 8.2. Estimating the number of pods your OpenShift Container Platform nodes can hold As a cluster administrator, you can use the OpenShift Cluster Capacity Tool to view the number of pods that can be scheduled to increase the current resources before they become exhausted, and to ensure any future pods can be scheduled. This capacity comes from an individual node host in a cluster, and includes CPU, memory, disk space, and others. 8.2.1. Understanding the OpenShift Cluster Capacity Tool The OpenShift Cluster Capacity Tool simulates a sequence of scheduling decisions to determine how many instances of an input pod can be scheduled on the cluster before it is exhausted of resources to provide a more accurate estimation. Note The remaining allocatable capacity is a rough estimation, because it does not count all of the resources being distributed among nodes. It analyzes only the remaining resources and estimates the available capacity that is still consumable in terms of a number of instances of a pod with given requirements that can be scheduled in a cluster. Also, pods might only have scheduling support on particular sets of nodes based on its selection and affinity criteria. As a result, the estimation of which remaining pods a cluster can schedule can be difficult. You can run the OpenShift Cluster Capacity Tool as a stand-alone utility from the command line, or as a job in a pod inside an OpenShift Container Platform cluster. Running the tool as job inside of a pod enables you to run it multiple times without intervention. 8.2.2. Running the OpenShift Cluster Capacity Tool on the command line You can run the OpenShift Cluster Capacity Tool from the command line to estimate the number of pods that can be scheduled onto your cluster. You create a sample pod spec file, which the tool uses for estimating resource usage. The pod spec specifies its resource requirements as limits or requests . The cluster capacity tool takes the pod's resource requirements into account for its estimation analysis. Prerequisites Run the OpenShift Cluster Capacity Tool , which is available as a container image from the Red Hat Ecosystem Catalog. Create a sample pod spec file: Create a YAML file similar to the following: apiVersion: v1 kind: Pod metadata: name: small-pod labels: app: guestbook tier: frontend spec: containers: - name: php-redis image: gcr.io/google-samples/gb-frontend:v4 imagePullPolicy: Always resources: limits: cpu: 150m memory: 100Mi requests: cpu: 150m memory: 100Mi Create the cluster role: USD oc create -f <file_name>.yaml For example: USD oc create -f pod-spec.yaml Procedure To use the cluster capacity tool on the command line: From the terminal, log in to the Red Hat Registry: USD podman login registry.redhat.io Pull the cluster capacity tool image: USD podman pull registry.redhat.io/openshift4/ose-cluster-capacity Run the cluster capacity tool: USD podman run -v USDHOME/.kube:/kube:Z -v USD(pwd):/cc:Z ose-cluster-capacity \ /bin/cluster-capacity --kubeconfig /kube/config --<pod_spec>.yaml /cc/<pod_spec>.yaml \ --verbose where: <pod_spec>.yaml Specifies the pod spec to use. verbose Outputs a detailed description of how many pods can be scheduled on each node in the cluster. Example output small-pod pod requirements: - CPU: 150m - Memory: 100Mi The cluster can schedule 88 instance(s) of the pod small-pod. Termination reason: Unschedulable: 0/5 nodes are available: 2 Insufficient cpu, 3 node(s) had taint {node-role.kubernetes.io/master: }, that the pod didn't tolerate. Pod distribution among nodes: small-pod - 192.168.124.214: 45 instance(s) - 192.168.124.120: 43 instance(s) In the above example, the number of estimated pods that can be scheduled onto the cluster is 88. 8.2.3. Running the OpenShift Cluster Capacity Tool as a job inside a pod Running the OpenShift Cluster Capacity Tool as a job inside of a pod allows you to run the tool multiple times without needing user intervention. You run the OpenShift Cluster Capacity Tool as a job by using a ConfigMap object. Prerequisites Download and install OpenShift Cluster Capacity Tool . Procedure To run the cluster capacity tool: Create the cluster role: Create a YAML file similar to the following: kind: ClusterRole apiVersion: rbac.authorization.k8s.io/v1 metadata: name: cluster-capacity-role rules: - apiGroups: [""] resources: ["pods", "nodes", "persistentvolumeclaims", "persistentvolumes", "services", "replicationcontrollers"] verbs: ["get", "watch", "list"] - apiGroups: ["apps"] resources: ["replicasets", "statefulsets"] verbs: ["get", "watch", "list"] - apiGroups: ["policy"] resources: ["poddisruptionbudgets"] verbs: ["get", "watch", "list"] - apiGroups: ["storage.k8s.io"] resources: ["storageclasses"] verbs: ["get", "watch", "list"] Create the cluster role by running the following command: USD oc create -f <file_name>.yaml For example: USD oc create sa cluster-capacity-sa Create the service account: USD oc create sa cluster-capacity-sa -n default Add the role to the service account: USD oc adm policy add-cluster-role-to-user cluster-capacity-role \ system:serviceaccount:<namespace>:cluster-capacity-sa where: <namespace> Specifies the namespace where the pod is located. Define and create the pod spec: Create a YAML file similar to the following: apiVersion: v1 kind: Pod metadata: name: small-pod labels: app: guestbook tier: frontend spec: containers: - name: php-redis image: gcr.io/google-samples/gb-frontend:v4 imagePullPolicy: Always resources: limits: cpu: 150m memory: 100Mi requests: cpu: 150m memory: 100Mi Create the pod by running the following command: USD oc create -f <file_name>.yaml For example: USD oc create -f pod.yaml Created a config map object by running the following command: USD oc create configmap cluster-capacity-configmap \ --from-file=pod.yaml=pod.yaml The cluster capacity analysis is mounted in a volume using a config map object named cluster-capacity-configmap to mount the input pod spec file pod.yaml into a volume test-volume at the path /test-pod . Create the job using the below example of a job specification file: Create a YAML file similar to the following: apiVersion: batch/v1 kind: Job metadata: name: cluster-capacity-job spec: parallelism: 1 completions: 1 template: metadata: name: cluster-capacity-pod spec: containers: - name: cluster-capacity image: openshift/origin-cluster-capacity imagePullPolicy: "Always" volumeMounts: - mountPath: /test-pod name: test-volume env: - name: CC_INCLUSTER 1 value: "true" command: - "/bin/sh" - "-ec" - \| /bin/cluster-capacity --podspec=/test-pod/pod.yaml --verbose restartPolicy: "Never" serviceAccountName: cluster-capacity-sa volumes: - name: test-volume configMap: name: cluster-capacity-configmap 1 A required environment variable letting the cluster capacity tool know that it is running inside a cluster as a pod. The pod.yaml key of the ConfigMap object is the same as the Pod spec file name, though it is not required. By doing this, the input pod spec file can be accessed inside the pod as /test-pod/pod.yaml . Run the cluster capacity image as a job in a pod by running the following command: USD oc create -f cluster-capacity-job.yaml Verification Check the job logs to find the number of pods that can be scheduled in the cluster: USD oc logs jobs/cluster-capacity-job Example output small-pod pod requirements: - CPU: 150m - Memory: 100Mi The cluster can schedule 52 instance(s) of the pod small-pod. Termination reason: Unschedulable: No nodes are available that match all of the following predicates:: Insufficient cpu (2). Pod distribution among nodes: small-pod - 192.168.124.214: 26 instance(s) - 192.168.124.120: 26 instance(s) 8.3. Restrict resource consumption with limit ranges By default, containers run with unbounded compute resources on an OpenShift Container Platform cluster. With limit ranges, you can restrict resource consumption for specific objects in a project: pods and containers: You can set minimum and maximum requirements for CPU and memory for pods and their containers. Image streams: You can set limits on the number of images and tags in an ImageStream object. Images: You can limit the size of images that can be pushed to an internal registry. Persistent volume claims (PVC): You can restrict the size of the PVCs that can be requested. If a pod does not meet the constraints imposed by the limit range, the pod cannot be created in the namespace. 8.3.1. About limit ranges A limit range, defined by a LimitRange object, restricts resource consumption in a project. In the project you can set specific resource limits for a pod, container, image, image stream, or persistent volume claim (PVC). All requests to create and modify resources are evaluated against each LimitRange object in the project. If the resource violates any of the enumerated constraints, the resource is rejected. The following shows a limit range object for all components: pod, container, image, image stream, or PVC. You can configure limits for any or all of these components in the same object. You create a different limit range object for each project where you want to control resources. Sample limit range object for a container apiVersion: "v1" kind: "LimitRange" metadata: name: "resource-limits" spec: limits: - type: "Container" max: cpu: "2" memory: "1Gi" min: cpu: "100m" memory: "4Mi" default: cpu: "300m" memory: "200Mi" defaultRequest: cpu: "200m" memory: "100Mi" maxLimitRequestRatio: cpu: "10" 8.3.1.1. About component limits The following examples show limit range parameters for each component. The examples are broken out for clarity. You can create a single LimitRange object for any or all components as necessary. 8.3.1.1.1. Container limits A limit range allows you to specify the minimum and maximum CPU and memory that each container in a pod can request for a specific project. If a container is created in the project, the container CPU and memory requests in the Pod spec must comply with the values set in the LimitRange object. If not, the pod does not get created. The container CPU or memory request and limit must be greater than or equal to the min resource constraint for containers that are specified in the LimitRange object. The container CPU or memory request and limit must be less than or equal to the max resource constraint for containers that are specified in the LimitRange object. If the LimitRange object defines a max CPU, you do not need to define a CPU request value in the Pod spec. But you must specify a CPU limit value that satisfies the maximum CPU constraint specified in the limit range. The ratio of the container limits to requests must be less than or equal to the maxLimitRequestRatio value for containers that is specified in the LimitRange object. If the LimitRange object defines a maxLimitRequestRatio constraint, any new containers must have both a request and a limit value. OpenShift Container Platform calculates the limit-to-request ratio by dividing the limit by the request . This value should be a non-negative integer greater than 1. For example, if a container has cpu: 500 in the limit value, and cpu: 100 in the request value, the limit-to-request ratio for cpu is 5 . This ratio must be less than or equal to the maxLimitRequestRatio . If the Pod spec does not specify a container resource memory or limit, the default or defaultRequest CPU and memory values for containers specified in the limit range object are assigned to the container. Container LimitRange object definition apiVersion: "v1" kind: "LimitRange" metadata: name: "resource-limits" 1 spec: limits: - type: "Container" max: cpu: "2" 2 memory: "1Gi" 3 min: cpu: "100m" 4 memory: "4Mi" 5 default: cpu: "300m" 6 memory: "200Mi" 7 defaultRequest: cpu: "200m" 8 memory: "100Mi" 9 maxLimitRequestRatio: cpu: "10" 10 1 The name of the LimitRange object. 2 The maximum amount of CPU that a single container in a pod can request. 3 The maximum amount of memory that a single container in a pod can request. 4 The minimum amount of CPU that a single container in a pod can request. 5 The minimum amount of memory that a single container in a pod can request. 6 The default amount of CPU that a container can use if not specified in the Pod spec. 7 The default amount of memory that a container can use if not specified in the Pod spec. 8 The default amount of CPU that a container can request if not specified in the Pod spec. 9 The default amount of memory that a container can request if not specified in the Pod spec. 10 The maximum limit-to-request ratio for a container. 8.3.1.1.2. Pod limits A limit range allows you to specify the minimum and maximum CPU and memory limits for all containers across a pod in a given project. To create a container in the project, the container CPU and memory requests in the Pod spec must comply with the values set in the LimitRange object. If not, the pod does not get created. If the Pod spec does not specify a container resource memory or limit, the default or defaultRequest CPU and memory values for containers specified in the limit range object are assigned to the container. Across all containers in a pod, the following must hold true: The container CPU or memory request and limit must be greater than or equal to the min resource constraints for pods that are specified in the LimitRange object. The container CPU or memory request and limit must be less than or equal to the max resource constraints for pods that are specified in the LimitRange object. The ratio of the container limits to requests must be less than or equal to the maxLimitRequestRatio constraint specified in the LimitRange object. Pod LimitRange object definition apiVersion: "v1" kind: "LimitRange" metadata: name: "resource-limits" 1 spec: limits: - type: "Pod" max: cpu: "2" 2 memory: "1Gi" 3 min: cpu: "200m" 4 memory: "6Mi" 5 maxLimitRequestRatio: cpu: "10" 6 1 The name of the limit range object. 2 The maximum amount of CPU that a pod can request across all containers. 3 The maximum amount of memory that a pod can request across all containers. 4 The minimum amount of CPU that a pod can request across all containers. 5 The minimum amount of memory that a pod can request across all containers. 6 The maximum limit-to-request ratio for a container. 8.3.1.1.3. Image limits A LimitRange object allows you to specify the maximum size of an image that can be pushed to an OpenShift image registry. When pushing images to an OpenShift image registry, the following must hold true: The size of the image must be less than or equal to the max size for images that is specified in the LimitRange object. Image LimitRange object definition apiVersion: "v1" kind: "LimitRange" metadata: name: "resource-limits" 1 spec: limits: - type: openshift.io/Image max: storage: 1Gi 2 1 The name of the LimitRange object. 2 The maximum size of an image that can be pushed to an OpenShift image registry. Note To prevent blobs that exceed the limit from being uploaded to the registry, the registry must be configured to enforce quotas. Warning The image size is not always available in the manifest of an uploaded image. This is especially the case for images built with Docker 1.10 or higher and pushed to a v2 registry. If such an image is pulled with an older Docker daemon, the image manifest is converted by the registry to schema v1 lacking all the size information. No storage limit set on images prevent it from being uploaded. The issue is being addressed. 8.3.1.1.4. Image stream limits A LimitRange object allows you to specify limits for image streams. For each image stream, the following must hold true: The number of image tags in an ImageStream specification must be less than or equal to the openshift.io/image-tags constraint in the LimitRange object. The number of unique references to images in an ImageStream specification must be less than or equal to the openshift.io/images constraint in the limit range object. Imagestream LimitRange object definition apiVersion: "v1" kind: "LimitRange" metadata: name: "resource-limits" 1 spec: limits: - type: openshift.io/ImageStream max: openshift.io/image-tags: 20 2 openshift.io/images: 30 3 1 The name of the LimitRange object. 2 The maximum number of unique image tags in the imagestream.spec.tags parameter in imagestream spec. 3 The maximum number of unique image references in the imagestream.status.tags parameter in the imagestream spec. The openshift.io/image-tags resource represents unique image references. Possible references are an ImageStreamTag , an ImageStreamImage and a DockerImage . Tags can be created using the oc tag and oc import-image commands. No distinction is made between internal and external references. However, each unique reference tagged in an ImageStream specification is counted just once. It does not restrict pushes to an internal container image registry in any way, but is useful for tag restriction. The openshift.io/images resource represents unique image names recorded in image stream status. It allows for restriction of a number of images that can be pushed to the OpenShift image registry. Internal and external references are not distinguished. 8.3.1.1.5. Persistent volume claim limits A LimitRange object allows you to restrict the storage requested in a persistent volume claim (PVC). Across all persistent volume claims in a project, the following must hold true: The resource request in a persistent volume claim (PVC) must be greater than or equal the min constraint for PVCs that is specified in the LimitRange object. The resource request in a persistent volume claim (PVC) must be less than or equal the max constraint for PVCs that is specified in the LimitRange object. PVC LimitRange object definition apiVersion: "v1" kind: "LimitRange" metadata: name: "resource-limits" 1 spec: limits: - type: "PersistentVolumeClaim" min: storage: "2Gi" 2 max: storage: "50Gi" 3 1 The name of the LimitRange object. 2 The minimum amount of storage that can be requested in a persistent volume claim. 3 The maximum amount of storage that can be requested in a persistent volume claim. 8.3.2. Creating a Limit Range To apply a limit range to a project: Create a LimitRange object with your required specifications: apiVersion: "v1" kind: "LimitRange" metadata: name: "resource-limits" 1 spec: limits: - type: "Pod" 2 max: cpu: "2" memory: "1Gi" min: cpu: "200m" memory: "6Mi" - type: "Container" 3 max: cpu: "2" memory: "1Gi" min: cpu: "100m" memory: "4Mi" default: 4 cpu: "300m" memory: "200Mi" defaultRequest: 5 cpu: "200m" memory: "100Mi" maxLimitRequestRatio: 6 cpu: "10" - type: openshift.io/Image 7 max: storage: 1Gi - type: openshift.io/ImageStream 8 max: openshift.io/image-tags: 20 openshift.io/images: 30 - type: "PersistentVolumeClaim" 9 min: storage: "2Gi" max: storage: "50Gi" 1 Specify a name for the LimitRange object. 2 To set limits for a pod, specify the minimum and maximum CPU and memory requests as needed. 3 To set limits for a container, specify the minimum and maximum CPU and memory requests as needed. 4 Optional. For a container, specify the default amount of CPU or memory that a container can use, if not specified in the Pod spec. 5 Optional. For a container, specify the default amount of CPU or memory that a container can request, if not specified in the Pod spec. 6 Optional. For a container, specify the maximum limit-to-request ratio that can be specified in the Pod spec. 7 To set limits for an Image object, set the maximum size of an image that can be pushed to an OpenShift image registry. 8 To set limits for an image stream, set the maximum number of image tags and references that can be in the ImageStream object file, as needed. 9 To set limits for a persistent volume claim, set the minimum and maximum amount of storage that can be requested. Create the object: USD oc create -f <limit_range_file> -n <project> 1 1 Specify the name of the YAML file you created and the project where you want the limits to apply. 8.3.3. Viewing a limit You can view any limits defined in a project by navigating in the web console to the project's Quota page. You can also use the CLI to view limit range details: Get the list of LimitRange object defined in the project. For example, for a project called demoproject : USD oc get limits -n demoproject NAME CREATED AT resource-limits 2020-07-15T17:14:23Z Describe the LimitRange object you are interested in, for example the resource-limits limit range: USD oc describe limits resource-limits -n demoproject Name: resource-limits Namespace: demoproject Type Resource Min Max Default Request Default Limit Max Limit/Request Ratio ---- -------- --- --- --------------- ------------- ----------------------- Pod cpu 200m 2 - - - Pod memory 6Mi 1Gi - - - Container cpu 100m 2 200m 300m 10 Container memory 4Mi 1Gi 100Mi 200Mi - openshift.io/Image storage - 1Gi - - - openshift.io/ImageStream openshift.io/image - 12 - - - openshift.io/ImageStream openshift.io/image-tags - 10 - - - PersistentVolumeClaim storage - 50Gi - - - 8.3.4. Deleting a Limit Range To remove any active LimitRange object to no longer enforce the limits in a project: Run the following command: USD oc delete limits <limit_name> 8.4. Configuring cluster memory to meet container memory and risk requirements As a cluster administrator, you can help your clusters operate efficiently through managing application memory by: Determining the memory and risk requirements of a containerized application component and configuring the container memory parameters to suit those requirements. Configuring containerized application runtimes (for example, OpenJDK) to adhere optimally to the configured container memory parameters. Diagnosing and resolving memory-related error conditions associated with running in a container. 8.4.1. Understanding managing application memory It is recommended to fully read the overview of how OpenShift Container Platform manages Compute Resources before proceeding. For each kind of resource (memory, CPU, storage), OpenShift Container Platform allows optional request and limit values to be placed on each container in a pod. Note the following about memory requests and memory limits: Memory request The memory request value, if specified, influences the OpenShift Container Platform scheduler. The scheduler considers the memory request when scheduling a container to a node, then fences off the requested memory on the chosen node for the use of the container. If a node's memory is exhausted, OpenShift Container Platform prioritizes evicting its containers whose memory usage most exceeds their memory request. In serious cases of memory exhaustion, the node OOM killer may select and kill a process in a container based on a similar metric. The cluster administrator can assign quota or assign default values for the memory request value. The cluster administrator can override the memory request values that a developer specifies, to manage cluster overcommit. Memory limit The memory limit value, if specified, provides a hard limit on the memory that can be allocated across all the processes in a container. If the memory allocated by all of the processes in a container exceeds the memory limit, the node Out of Memory (OOM) killer will immediately select and kill a process in the container. If both memory request and limit are specified, the memory limit value must be greater than or equal to the memory request. The cluster administrator can assign quota or assign default values for the memory limit value. The minimum memory limit is 12 MB. If a container fails to start due to a Cannot allocate memory pod event, the memory limit is too low. Either increase or remove the memory limit. Removing the limit allows pods to consume unbounded node resources. 8.4.1.1. Managing application memory strategy The steps for sizing application memory on OpenShift Container Platform are as follows: Determine expected container memory usage Determine expected mean and peak container memory usage, empirically if necessary (for example, by separate load testing). Remember to consider all the processes that may potentially run in parallel in the container: for example, does the main application spawn any ancillary scripts? Determine risk appetite Determine risk appetite for eviction. If the risk appetite is low, the container should request memory according to the expected peak usage plus a percentage safety margin. If the risk appetite is higher, it may be more appropriate to request memory according to the expected mean usage. Set container memory request Set container memory request based on the above. The more accurately the request represents the application memory usage, the better. If the request is too high, cluster and quota usage will be inefficient. If the request is too low, the chances of application eviction increase. Set container memory limit, if required Set container memory limit, if required. Setting a limit has the effect of immediately killing a container process if the combined memory usage of all processes in the container exceeds the limit, and is therefore a mixed blessing. On the one hand, it may make unanticipated excess memory usage obvious early ("fail fast"); on the other hand it also terminates processes abruptly. Note that some OpenShift Container Platform clusters may require a limit value to be set; some may override the request based on the limit; and some application images rely on a limit value being set as this is easier to detect than a request value. If the memory limit is set, it should not be set to less than the expected peak container memory usage plus a percentage safety margin. Ensure application is tuned Ensure application is tuned with respect to configured request and limit values, if appropriate. This step is particularly relevant to applications which pool memory, such as the JVM. The rest of this page discusses this. Additional resources Understanding compute resources and containers 8.4.2. Understanding OpenJDK settings for OpenShift Container Platform The default OpenJDK settings do not work well with containerized environments. As a result, some additional Java memory settings must always be provided whenever running the OpenJDK in a container. The JVM memory layout is complex, version dependent, and describing it in detail is beyond the scope of this documentation. However, as a starting point for running OpenJDK in a container, at least the following three memory-related tasks are key: Overriding the JVM maximum heap size. Encouraging the JVM to release unused memory to the operating system, if appropriate. Ensuring all JVM processes within a container are appropriately configured. Optimally tuning JVM workloads for running in a container is beyond the scope of this documentation, and may involve setting multiple additional JVM options. 8.4.2.1. Understanding how to override the JVM maximum heap size For many Java workloads, the JVM heap is the largest single consumer of memory. Currently, the OpenJDK defaults to allowing up to 1/4 (1/ -XX:MaxRAMFraction ) of the compute node's memory to be used for the heap, regardless of whether the OpenJDK is running in a container or not. It is therefore essential to override this behavior, especially if a container memory limit is also set. There are at least two ways the above can be achieved: If the container memory limit is set and the experimental options are supported by the JVM, set -XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap . Note The UseCGroupMemoryLimitForHeap option has been removed in JDK 11. Use -XX:+UseContainerSupport instead. This sets -XX:MaxRAM to the container memory limit, and the maximum heap size ( -XX:MaxHeapSize / -Xmx ) to 1/ -XX:MaxRAMFraction (1/4 by default). Directly override one of -XX:MaxRAM , -XX:MaxHeapSize or -Xmx . This option involves hard-coding a value, but has the advantage of allowing a safety margin to be calculated. 8.4.2.2. Understanding how to encourage the JVM to release unused memory to the operating system By default, the OpenJDK does not aggressively return unused memory to the operating system. This may be appropriate for many containerized Java workloads, but notable exceptions include workloads where additional active processes co-exist with a JVM within a container, whether those additional processes are native, additional JVMs, or a combination of the two. Java-based agents can use the following JVM arguments to encourage the JVM to release unused memory to the operating system: -XX:+UseParallelGC -XX:MinHeapFreeRatio=5 -XX:MaxHeapFreeRatio=10 -XX:GCTimeRatio=4 -XX:AdaptiveSizePolicyWeight=90. These arguments are intended to return heap memory to the operating system whenever allocated memory exceeds 110% of in-use memory ( -XX:MaxHeapFreeRatio ), spending up to 20% of CPU time in the garbage collector ( -XX:GCTimeRatio ). At no time will the application heap allocation be less than the initial heap allocation (overridden by -XX:InitialHeapSize / -Xms ). Detailed additional information is available Tuning Java's footprint in OpenShift (Part 1) , Tuning Java's footprint in OpenShift (Part 2) , and at OpenJDK and Containers . 8.4.2.3. Understanding how to ensure all JVM processes within a container are appropriately configured In the case that multiple JVMs run in the same container, it is essential to ensure that they are all configured appropriately. For many workloads it will be necessary to grant each JVM a percentage memory budget, leaving a perhaps substantial additional safety margin. Many Java tools use different environment variables ( JAVA_OPTS , GRADLE_OPTS , and so on) to configure their JVMs and it can be challenging to ensure that the right settings are being passed to the right JVM. The JAVA_TOOL_OPTIONS environment variable is always respected by the OpenJDK, and values specified in JAVA_TOOL_OPTIONS will be overridden by other options specified on the JVM command line. By default, to ensure that these options are used by default for all JVM workloads run in the Java-based agent image, the OpenShift Container Platform Jenkins Maven agent image sets: JAVA_TOOL_OPTIONS="-XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap -Dsun.zip.disableMemoryMapping=true" Note The UseCGroupMemoryLimitForHeap option has been removed in JDK 11. Use -XX:+UseContainerSupport instead. This does not guarantee that additional options are not required, but is intended to be a helpful starting point. 8.4.3. Finding the memory request and limit from within a pod An application wishing to dynamically discover its memory request and limit from within a pod should use the Downward API. Procedure Configure the pod to add the MEMORY_REQUEST and MEMORY_LIMIT stanzas: Create a YAML file similar to the following: apiVersion: v1 kind: Pod metadata: name: test spec: containers: - name: test image: fedora:latest command: - sleep - "3600" env: - name: MEMORY_REQUEST 1 valueFrom: resourceFieldRef: containerName: test resource: requests.memory - name: MEMORY_LIMIT 2 valueFrom: resourceFieldRef: containerName: test resource: limits.memory resources: requests: memory: 384Mi limits: memory: 512Mi 1 Add this stanza to discover the application memory request value. 2 Add this stanza to discover the application memory limit value. Create the pod by running the following command: USD oc create -f <file-name>.yaml Verification Access the pod using a remote shell: USD oc rsh test Check that the requested values were applied: USD env \| grep MEMORY \| sort Example output MEMORY_LIMIT=536870912 MEMORY_REQUEST=402653184 Note The memory limit value can also be read from inside the container by the /sys/fs/cgroup/memory/memory.limit_in_bytes file. 8.4.4. Understanding OOM kill policy OpenShift Container Platform can kill a process in a container if the total memory usage of all the processes in the container exceeds the memory limit, or in serious cases of node memory exhaustion. When a process is Out of Memory (OOM) killed, this might result in the container exiting immediately. If the container PID 1 process receives the SIGKILL , the container will exit immediately. Otherwise, the container behavior is dependent on the behavior of the other processes. For example, a container process exited with code 137, indicating it received a SIGKILL signal. If the container does not exit immediately, an OOM kill is detectable as follows: Access the pod using a remote shell: # oc rsh test Run the following command to see the current OOM kill count in /sys/fs/cgroup/memory/memory.oom_control : USD grep '^oom_kill ' /sys/fs/cgroup/memory/memory.oom_control Example output oom_kill 0 Run the following command to provoke an OOM kill: USD sed -e '' </dev/zero Example output Killed Run the following command to view the exit status of the sed command: USD echo USD? Example output 137 The 137 code indicates the container process exited with code 137, indicating it received a SIGKILL signal. Run the following command to see that the OOM kill counter in /sys/fs/cgroup/memory/memory.oom_control incremented: USD grep '^oom_kill ' /sys/fs/cgroup/memory/memory.oom_control Example output oom_kill 1 If one or more processes in a pod are OOM killed, when the pod subsequently exits, whether immediately or not, it will have phase Failed and reason OOMKilled . An OOM-killed pod might be restarted depending on the value of restartPolicy . If not restarted, controllers such as the replication controller will notice the pod's failed status and create a new pod to replace the old one. Use the follwing command to get the pod status: USD oc get pod test Example output NAME READY STATUS RESTARTS AGE test 0/1 OOMKilled 0 1m If the pod has not restarted, run the following command to view the pod: USD oc get pod test -o yaml Example output ... status: containerStatuses: - name: test ready: false restartCount: 0 state: terminated: exitCode: 137 reason: OOMKilled phase: Failed If restarted, run the following command to view the pod: USD oc get pod test -o yaml Example output ... status: containerStatuses: - name: test ready: true restartCount: 1 lastState: terminated: exitCode: 137 reason: OOMKilled state: running: phase: Running 8.4.5. Understanding pod eviction OpenShift Container Platform may evict a pod from its node when the node's memory is exhausted. Depending on the extent of memory exhaustion, the eviction may or may not be graceful. Graceful eviction implies the main process (PID 1) of each container receiving a SIGTERM signal, then some time later a SIGKILL signal if the process has not exited already. Non-graceful eviction implies the main process of each container immediately receiving a SIGKILL signal. An evicted pod has phase Failed and reason Evicted . It will not be restarted, regardless of the value of restartPolicy . However, controllers such as the replication controller will notice the pod's failed status and create a new pod to replace the old one. USD oc get pod test Example output NAME READY STATUS RESTARTS AGE test 0/1 Evicted 0 1m USD oc get pod test -o yaml Example output ... status: message: 'Pod The node was low on resource: [MemoryPressure].' phase: Failed reason: Evicted 8.5. Configuring your cluster to place pods on overcommitted nodes In an overcommitted state, the sum of the container compute resource requests and limits exceeds the resources available on the system. For example, you might want to use overcommitment in development environments where a trade-off of guaranteed performance for capacity is acceptable. Containers can specify compute resource requests and limits. Requests are used for scheduling your container and provide a minimum service guarantee. Limits constrain the amount of compute resource that can be consumed on your node. The scheduler attempts to optimize the compute resource use across all nodes in your cluster. It places pods onto specific nodes, taking the pods' compute resource requests and nodes' available capacity into consideration. OpenShift Container Platform administrators can control the level of overcommit and manage container density on developer containers by using the ClusterResourceOverride Operator . Note In OpenShift Container Platform, you must enable cluster-level overcommit. Node overcommitment is enabled by default. See Disabling overcommitment for a node . 8.5.1. Resource requests and overcommitment For each compute resource, a container may specify a resource request and limit. Scheduling decisions are made based on the request to ensure that a node has enough capacity available to meet the requested value. If a container specifies limits, but omits requests, the requests are defaulted to the limits. A container is not able to exceed the specified limit on the node. The enforcement of limits is dependent upon the compute resource type. If a container makes no request or limit, the container is scheduled to a node with no resource guarantees. In practice, the container is able to consume as much of the specified resource as is available with the lowest local priority. In low resource situations, containers that specify no resource requests are given the lowest quality of service. Scheduling is based on resources requested, while quota and hard limits refer to resource limits, which can be set higher than requested resources. The difference between request and limit determines the level of overcommit; for instance, if a container is given a memory request of 1Gi and a memory limit of 2Gi, it is scheduled based on the 1Gi request being available on the node, but could use up to 2Gi; so it is 100% overcommitted. 8.5.2. Cluster-level overcommit using the Cluster Resource Override Operator The Cluster Resource Override Operator is an admission webhook that allows you to control the level of overcommit and manage container density across all the nodes in your cluster. The Operator controls how nodes in specific projects can exceed defined memory and CPU limits. The Operator modifies the ratio between the requests and limits that are set on developer containers. In conjunction with a per-project limit range that specifies limits and defaults, you can achieve the desired level of overcommit. You must install the Cluster Resource Override Operator by using the OpenShift Container Platform console or CLI as shown in the following sections. After you deploy the Cluster Resource Override Operator, the Operator modifies all new pods in specific namespaces. The Operator does not edit pods that existed before you deployed the Operator. During the installation, you create a ClusterResourceOverride custom resource (CR), where you set the level of overcommit, as shown in the following example: apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster 1 spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 2 cpuRequestToLimitPercent: 25 3 limitCPUToMemoryPercent: 200 4 # ... 1 The name must be cluster . 2 Optional. If a container memory limit has been specified or defaulted, the memory request is overridden to this percentage of the limit, between 1-100. The default is 50. 3 Optional. If a container CPU limit has been specified or defaulted, the CPU request is overridden to this percentage of the limit, between 1-100. The default is 25. 4 Optional. If a container memory limit has been specified or defaulted, the CPU limit is overridden to a percentage of the memory limit, if specified. Scaling 1Gi of RAM at 100 percent is equal to 1 CPU core. This is processed prior to overriding the CPU request (if configured). The default is 200. Note The Cluster Resource Override Operator overrides have no effect if limits have not been set on containers. Create a LimitRange object with default limits per individual project or configure limits in Pod specs for the overrides to apply. When configured, you can enable overrides on a per-project basis by applying the following label to the Namespace object for each project where you want the overrides to apply. For example, you can configure override so that infrastructure components are not subject to the overrides. apiVersion: v1 kind: Namespace metadata: # ... labels: clusterresourceoverrides.admission.autoscaling.openshift.io/enabled: "true" # ... The Operator watches for the ClusterResourceOverride CR and ensures that the ClusterResourceOverride admission webhook is installed into the same namespace as the operator. For example, a pod has the following resources limits: apiVersion: v1 kind: Pod metadata: name: my-pod namespace: my-namespace # ... spec: containers: - name: hello-openshift image: openshift/hello-openshift resources: limits: memory: "512Mi" cpu: "2000m" # ... The Cluster Resource Override Operator intercepts the original pod request, then overrides the resources according to the configuration set in the ClusterResourceOverride object. apiVersion: v1 kind: Pod metadata: name: my-pod namespace: my-namespace # ... spec: containers: - image: openshift/hello-openshift name: hello-openshift resources: limits: cpu: "1" 1 memory: 512Mi requests: cpu: 250m 2 memory: 256Mi # ... 1 The CPU limit has been overridden to 1 because the limitCPUToMemoryPercent parameter is set to 200 in the ClusterResourceOverride object. As such, 200% of the memory limit, 512Mi in CPU terms, is 1 CPU core. 2 The CPU request is now 250m because the cpuRequestToLimit is set to 25 in the ClusterResourceOverride object. As such, 25% of the 1 CPU core is 250m. 8.5.2.1. Installing the Cluster Resource Override Operator using the web console You can use the OpenShift Container Platform web console to install the Cluster Resource Override Operator to help control overcommit in your cluster. Prerequisites The Cluster Resource Override Operator has no effect if limits have not been set on containers. You must specify default limits for a project using a LimitRange object or configure limits in Pod specs for the overrides to apply. Procedure To install the Cluster Resource Override Operator using the OpenShift Container Platform web console: In the OpenShift Container Platform web console, navigate to Home Projects Click Create Project . Specify clusterresourceoverride-operator as the name of the project. Click Create . Navigate to Operators OperatorHub . Choose ClusterResourceOverride Operator from the list of available Operators and click Install . On the Install Operator page, make sure A specific Namespace on the cluster is selected for Installation Mode . Make sure clusterresourceoverride-operator is selected for Installed Namespace . Select an Update Channel and Approval Strategy . Click Install . On the Installed Operators page, click ClusterResourceOverride . On the ClusterResourceOverride Operator details page, click Create ClusterResourceOverride . On the Create ClusterResourceOverride page, click YAML view and edit the YAML template to set the overcommit values as needed: apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster 1 spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 2 cpuRequestToLimitPercent: 25 3 limitCPUToMemoryPercent: 200 4 # ... 1 The name must be cluster . 2 Optional. Specify the percentage to override the container memory limit, if used, between 1-100. The default is 50. 3 Optional. Specify the percentage to override the container CPU limit, if used, between 1-100. The default is 25. 4 Optional. Specify the percentage to override the container memory limit, if used. Scaling 1Gi of RAM at 100 percent is equal to 1 CPU core. This is processed prior to overriding the CPU request, if configured. The default is 200. Click Create . Check the current state of the admission webhook by checking the status of the cluster custom resource: On the ClusterResourceOverride Operator page, click cluster . On the ClusterResourceOverride Details page, click YAML . The mutatingWebhookConfigurationRef section appears when the webhook is called. apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: annotations: kubectl.kubernetes.io/last-applied-configuration: \| {"apiVersion":"operator.autoscaling.openshift.io/v1","kind":"ClusterResourceOverride","metadata":{"annotations":{},"name":"cluster"},"spec":{"podResourceOverride":{"spec":{"cpuRequestToLimitPercent":25,"limitCPUToMemoryPercent":200,"memoryRequestToLimitPercent":50}}}} creationTimestamp: "2019-12-18T22:35:02Z" generation: 1 name: cluster resourceVersion: "127622" selfLink: /apis/operator.autoscaling.openshift.io/v1/clusterresourceoverrides/cluster uid: 978fc959-1717-4bd1-97d0-ae00ee111e8d spec: podResourceOverride: spec: cpuRequestToLimitPercent: 25 limitCPUToMemoryPercent: 200 memoryRequestToLimitPercent: 50 status: # ... mutatingWebhookConfigurationRef: 1 apiVersion: admissionregistration.k8s.io/v1 kind: MutatingWebhookConfiguration name: clusterresourceoverrides.admission.autoscaling.openshift.io resourceVersion: "127621" uid: 98b3b8ae-d5ce-462b-8ab5-a729ea8f38f3 # ... 1 Reference to the ClusterResourceOverride admission webhook. 8.5.2.2. Installing the Cluster Resource Override Operator using the CLI You can use the OpenShift Container Platform CLI to install the Cluster Resource Override Operator to help control overcommit in your cluster. Prerequisites The Cluster Resource Override Operator has no effect if limits have not been set on containers. You must specify default limits for a project using a LimitRange object or configure limits in Pod specs for the overrides to apply. Procedure To install the Cluster Resource Override Operator using the CLI: Create a namespace for the Cluster Resource Override Operator: Create a Namespace object YAML file (for example, cro-namespace.yaml ) for the Cluster Resource Override Operator: apiVersion: v1 kind: Namespace metadata: name: clusterresourceoverride-operator Create the namespace: USD oc create -f <file-name>.yaml For example: USD oc create -f cro-namespace.yaml Create an Operator group: Create an OperatorGroup object YAML file (for example, cro-og.yaml) for the Cluster Resource Override Operator: apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: clusterresourceoverride-operator namespace: clusterresourceoverride-operator spec: targetNamespaces: - clusterresourceoverride-operator Create the Operator Group: USD oc create -f <file-name>.yaml For example: USD oc create -f cro-og.yaml Create a subscription: Create a Subscription object YAML file (for example, cro-sub.yaml) for the Cluster Resource Override Operator: apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: clusterresourceoverride namespace: clusterresourceoverride-operator spec: channel: "stable" name: clusterresourceoverride source: redhat-operators sourceNamespace: openshift-marketplace Create the subscription: USD oc create -f <file-name>.yaml For example: USD oc create -f cro-sub.yaml Create a ClusterResourceOverride custom resource (CR) object in the clusterresourceoverride-operator namespace: Change to the clusterresourceoverride-operator namespace. USD oc project clusterresourceoverride-operator Create a ClusterResourceOverride object YAML file (for example, cro-cr.yaml) for the Cluster Resource Override Operator: apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster 1 spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 2 cpuRequestToLimitPercent: 25 3 limitCPUToMemoryPercent: 200 4 1 The name must be cluster . 2 Optional. Specify the percentage to override the container memory limit, if used, between 1-100. The default is 50. 3 Optional. Specify the percentage to override the container CPU limit, if used, between 1-100. The default is 25. 4 Optional. Specify the percentage to override the container memory limit, if used. Scaling 1Gi of RAM at 100 percent is equal to 1 CPU core. This is processed prior to overriding the CPU request, if configured. The default is 200. Create the ClusterResourceOverride object: USD oc create -f <file-name>.yaml For example: USD oc create -f cro-cr.yaml Verify the current state of the admission webhook by checking the status of the cluster custom resource. USD oc get clusterresourceoverride cluster -n clusterresourceoverride-operator -o yaml The mutatingWebhookConfigurationRef section appears when the webhook is called. Example output apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: annotations: kubectl.kubernetes.io/last-applied-configuration: \| {"apiVersion":"operator.autoscaling.openshift.io/v1","kind":"ClusterResourceOverride","metadata":{"annotations":{},"name":"cluster"},"spec":{"podResourceOverride":{"spec":{"cpuRequestToLimitPercent":25,"limitCPUToMemoryPercent":200,"memoryRequestToLimitPercent":50}}}} creationTimestamp: "2019-12-18T22:35:02Z" generation: 1 name: cluster resourceVersion: "127622" selfLink: /apis/operator.autoscaling.openshift.io/v1/clusterresourceoverrides/cluster uid: 978fc959-1717-4bd1-97d0-ae00ee111e8d spec: podResourceOverride: spec: cpuRequestToLimitPercent: 25 limitCPUToMemoryPercent: 200 memoryRequestToLimitPercent: 50 status: # ... mutatingWebhookConfigurationRef: 1 apiVersion: admissionregistration.k8s.io/v1 kind: MutatingWebhookConfiguration name: clusterresourceoverrides.admission.autoscaling.openshift.io resourceVersion: "127621" uid: 98b3b8ae-d5ce-462b-8ab5-a729ea8f38f3 # ... 1 Reference to the ClusterResourceOverride admission webhook. 8.5.2.3. Configuring cluster-level overcommit The Cluster Resource Override Operator requires a ClusterResourceOverride custom resource (CR) and a label for each project where you want the Operator to control overcommit. Prerequisites The Cluster Resource Override Operator has no effect if limits have not been set on containers. You must specify default limits for a project using a LimitRange object or configure limits in Pod specs for the overrides to apply. Procedure To modify cluster-level overcommit: Edit the ClusterResourceOverride CR: apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 1 cpuRequestToLimitPercent: 25 2 limitCPUToMemoryPercent: 200 3 # ... 1 Optional. Specify the percentage to override the container memory limit, if used, between 1-100. The default is 50. 2 Optional. Specify the percentage to override the container CPU limit, if used, between 1-100. The default is 25. 3 Optional. Specify the percentage to override the container memory limit, if used. Scaling 1Gi of RAM at 100 percent is equal to 1 CPU core. This is processed prior to overriding the CPU request, if configured. The default is 200. Ensure the following label has been added to the Namespace object for each project where you want the Cluster Resource Override Operator to control overcommit: apiVersion: v1 kind: Namespace metadata: # ... labels: clusterresourceoverrides.admission.autoscaling.openshift.io/enabled: "true" 1 # ... 1 Add this label to each project. 8.5.3. Node-level overcommit You can use various ways to control overcommit on specific nodes, such as quality of service (QOS) guarantees, CPU limits, or reserve resources. You can also disable overcommit for specific nodes and specific projects. 8.5.3.1. Understanding compute resources and containers The node-enforced behavior for compute resources is specific to the resource type. 8.5.3.1.1. Understanding container CPU requests A container is guaranteed the amount of CPU it requests and is additionally able to consume excess CPU available on the node, up to any limit specified by the container. If multiple containers are attempting to use excess CPU, CPU time is distributed based on the amount of CPU requested by each container. For example, if one container requested 500m of CPU time and another container requested 250m of CPU time, then any extra CPU time available on the node is distributed among the containers in a 2:1 ratio. If a container specified a limit, it will be throttled not to use more CPU than the specified limit. CPU requests are enforced using the CFS shares support in the Linux kernel. By default, CPU limits are enforced using the CFS quota support in the Linux kernel over a 100ms measuring interval, though this can be disabled. 8.5.3.1.2. Understanding container memory requests A container is guaranteed the amount of memory it requests. A container can use more memory than requested, but once it exceeds its requested amount, it could be terminated in a low memory situation on the node. If a container uses less memory than requested, it will not be terminated unless system tasks or daemons need more memory than was accounted for in the node's resource reservation. If a container specifies a limit on memory, it is immediately terminated if it exceeds the limit amount. 8.5.3.2. Understanding overcommitment and quality of service classes A node is overcommitted when it has a pod scheduled that makes no request, or when the sum of limits across all pods on that node exceeds available machine capacity. In an overcommitted environment, it is possible that the pods on the node will attempt to use more compute resource than is available at any given point in time. When this occurs, the node must give priority to one pod over another. The facility used to make this decision is referred to as a Quality of Service (QoS) Class. A pod is designated as one of three QoS classes with decreasing order of priority: Table 8.19. Quality of Service Classes Priority Class Name Description 1 (highest) Guaranteed If limits and optionally requests are set (not equal to 0) for all resources and they are equal, then the pod is classified as Guaranteed . 2 Burstable If requests and optionally limits are set (not equal to 0) for all resources, and they are not equal, then the pod is classified as Burstable . 3 (lowest) BestEffort If requests and limits are not set for any of the resources, then the pod is classified as BestEffort . Memory is an incompressible resource, so in low memory situations, containers that have the lowest priority are terminated first: Guaranteed containers are considered top priority, and are guaranteed to only be terminated if they exceed their limits, or if the system is under memory pressure and there are no lower priority containers that can be evicted. Burstable containers under system memory pressure are more likely to be terminated once they exceed their requests and no other BestEffort containers exist. BestEffort containers are treated with the lowest priority. Processes in these containers are first to be terminated if the system runs out of memory. 8.5.3.2.1. Understanding how to reserve memory across quality of service tiers You can use the qos-reserved parameter to specify a percentage of memory to be reserved by a pod in a particular QoS level. This feature attempts to reserve requested resources to exclude pods from lower OoS classes from using resources requested by pods in higher QoS classes. OpenShift Container Platform uses the qos-reserved parameter as follows: A value of qos-reserved=memory=100% will prevent the Burstable and BestEffort QoS classes from consuming memory that was requested by a higher QoS class. This increases the risk of inducing OOM on BestEffort and Burstable workloads in favor of increasing memory resource guarantees for Guaranteed and Burstable workloads. A value of qos-reserved=memory=50% will allow the Burstable and BestEffort QoS classes to consume half of the memory requested by a higher QoS class. A value of qos-reserved=memory=0% will allow a Burstable and BestEffort QoS classes to consume up to the full node allocatable amount if available, but increases the risk that a Guaranteed workload will not have access to requested memory. This condition effectively disables this feature. 8.5.3.3. Understanding swap memory and QOS You can disable swap by default on your nodes to preserve quality of service (QOS) guarantees. Otherwise, physical resources on a node can oversubscribe, affecting the resource guarantees the Kubernetes scheduler makes during pod placement. For example, if two guaranteed pods have reached their memory limit, each container could start using swap memory. Eventually, if there is not enough swap space, processes in the pods can be terminated due to the system being oversubscribed. Failing to disable swap results in nodes not recognizing that they are experiencing MemoryPressure , resulting in pods not receiving the memory they made in their scheduling request. As a result, additional pods are placed on the node to further increase memory pressure, ultimately increasing your risk of experiencing a system out of memory (OOM) event. Important If swap is enabled, any out-of-resource handling eviction thresholds for available memory will not work as expected. Take advantage of out-of-resource handling to allow pods to be evicted from a node when it is under memory pressure, and rescheduled on an alternative node that has no such pressure. 8.5.3.4. Understanding nodes overcommitment In an overcommitted environment, it is important to properly configure your node to provide best system behavior. When the node starts, it ensures that the kernel tunable flags for memory management are set properly. The kernel should never fail memory allocations unless it runs out of physical memory. To ensure this behavior, OpenShift Container Platform configures the kernel to always overcommit memory by setting the vm.overcommit_memory parameter to 1 , overriding the default operating system setting. OpenShift Container Platform also configures the kernel not to panic when it runs out of memory by setting the vm.panic_on_oom parameter to 0 . A setting of 0 instructs the kernel to call oom_killer in an Out of Memory (OOM) condition, which kills processes based on priority You can view the current setting by running the following commands on your nodes: USD sysctl -a \|grep commit Example output #... vm.overcommit_memory = 0 #... USD sysctl -a \|grep panic Example output #... vm.panic_on_oom = 0 #... Note The above flags should already be set on nodes, and no further action is required. You can also perform the following configurations for each node: Disable or enforce CPU limits using CPU CFS quotas Reserve resources for system processes Reserve memory across quality of service tiers 8.5.3.5. Disabling or enforcing CPU limits using CPU CFS quotas Nodes by default enforce specified CPU limits using the Completely Fair Scheduler (CFS) quota support in the Linux kernel. If you disable CPU limit enforcement, it is important to understand the impact on your node: If a container has a CPU request, the request continues to be enforced by CFS shares in the Linux kernel. If a container does not have a CPU request, but does have a CPU limit, the CPU request defaults to the specified CPU limit, and is enforced by CFS shares in the Linux kernel. If a container has both a CPU request and limit, the CPU request is enforced by CFS shares in the Linux kernel, and the CPU limit has no impact on the node. Prerequisites Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command: USD oc edit machineconfigpool <name> For example: USD oc edit machineconfigpool worker Example output apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: "2022-11-16T15:34:25Z" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: "" 1 name: worker 1 The label appears under Labels. Tip If the label is not present, add a key/value pair such as: USD oc label machineconfigpool worker custom-kubelet=small-pods Procedure Create a custom resource (CR) for your configuration change. Sample configuration for a disabling CPU limits apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: disable-cpu-units 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 2 kubeletConfig: cpuCfsQuota: false 3 1 Assign a name to CR. 2 Specify the label from the machine config pool. 3 Set the cpuCfsQuota parameter to false . Run the following command to create the CR: USD oc create -f <file_name>.yaml 8.5.3.6. Reserving resources for system processes To provide more reliable scheduling and minimize node resource overcommitment, each node can reserve a portion of its resources for use by system daemons that are required to run on your node for your cluster to function. In particular, it is recommended that you reserve resources for incompressible resources such as memory. Procedure To explicitly reserve resources for non-pod processes, allocate node resources by specifying resources available for scheduling. For more details, see Allocating Resources for Nodes. 8.5.3.7. Disabling overcommitment for a node When enabled, overcommitment can be disabled on each node. Procedure To disable overcommitment in a node run the following command on that node: USD sysctl -w vm.overcommit_memory=0 8.5.4. Project-level limits To help control overcommit, you can set per-project resource limit ranges, specifying memory and CPU limits and defaults for a project that overcommit cannot exceed. For information on project-level resource limits, see Additional resources. Alternatively, you can disable overcommitment for specific projects. 8.5.4.1. Disabling overcommitment for a project When enabled, overcommitment can be disabled per-project. For example, you can allow infrastructure components to be configured independently of overcommitment. Procedure To disable overcommitment in a project: Create or edit the namespace object file. Add the following annotation: apiVersion: v1 kind: Namespace metadata: annotations: quota.openshift.io/cluster-resource-override-enabled: "false" 1 # ... 1 Setting this annotation to false disables overcommit for this namespace. 8.5.5. Additional resources Setting deployment resources . Allocating resources for nodes . 8.6. Configuring the Linux cgroup version on your nodes By default, OpenShift Container Platform uses Linux control group version 1 (cgroup v1) in your cluster. You can switch to Linux control group version 2 (cgroup v2), if needed, by editing the node.config object. Enabling cgroup v2 in OpenShift Container Platform disables all cgroup version 1 controllers and hierarchies in your cluster. cgroup v2 is the current version of the Linux cgroup API. cgroup v2 offers several improvements over cgroup v1, including a unified hierarchy, safer sub-tree delegation, new features such as Pressure Stall Information , and enhanced resource management and isolation. However, cgroup v2 has different CPU, memory, and I/O management characteristics than cgroup v1. Therefore, some workloads might experience slight differences in memory or CPU usage on clusters that run cgroup v2. Note If you run third-party monitoring and security agents that depend on the cgroup file system, update the agents to a version that supports cgroup v2. If you have configured cgroup v2 and run cAdvisor as a stand-alone daemon set for monitoring pods and containers, update cAdvisor to v0.43.0 or later. If you deploy Java applications, use versions that fully support cgroup v2, such as the following packages: OpenJDK / HotSpot: jdk8u372, 11.0.16, 15 and later IBM Semeru Runtimes: jdk8u345-b01, 11.0.16.0, 17.0.4.0, 18.0.2.0 and later IBM SDK Java Technology Edition Version (IBM Java): 8.0.7.15 and later 8.6.1. Configuring Linux cgroup You can enable Linux control group version 1 (cgroup v1) or Linux control group version 2 (cgroup v2) by editing the node.config object. The default is cgroup v1. Note Currently, disabling CPU load balancing is not supported by cgroup v2. As a result, you might not get the desired behavior from performance profiles if you have cgroup v2 enabled. Enabling cgroup v2 is not recommended if you are using performance profiles. Prerequisites You have a running OpenShift Container Platform cluster that uses version 4.12 or later. You are logged in to the cluster as a user with administrative privileges. Procedure Enable cgroup v2 on nodes: Edit the node.config object: USD oc edit nodes.config/cluster Edit the spec.cgroupMode parameter: Example node.config object apiVersion: config.openshift.io/v1 kind: Node metadata: annotations: include.release.openshift.io/ibm-cloud-managed: "true" include.release.openshift.io/self-managed-high-availability: "true" include.release.openshift.io/single-node-developer: "true" release.openshift.io/create-only: "true" creationTimestamp: "2022-07-08T16:02:51Z" generation: 1 name: cluster ownerReferences: - apiVersion: config.openshift.io/v1 kind: ClusterVersion name: version uid: 36282574-bf9f-409e-a6cd-3032939293eb resourceVersion: "1865" uid: 0c0f7a4c-4307-4187-b591-6155695ac85b spec: cgroupMode: "v2" 1 ... 1 Specify v2 to enable cgroup v2 or v1 for cgroup v1. Verification Check the machine configs to see that the new machine configs were added: USD oc get mc Example output NAME GENERATEDBYCONTROLLER IGNITIONVERSION AGE 00-master 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 00-worker 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 97-master-generated-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-generated-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-ssh 3.2.0 40m 99-worker-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-ssh 3.2.0 40m rendered-master-23d4317815a5f854bd3553d689cfe2e9 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 10s 1 rendered-master-23e785de7587df95a4b517e0647e5ab7 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-5d596d9293ca3ea80c896a1191735bb1 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-dcc7f1b92892d34db74d6832bcc9ccd4 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 10s 1 New machine configs are created, as expected. Check that the new kernelArguments were added to the new machine configs: USD oc describe mc <name> Example output for cgroup v1 apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker name: 05-worker-kernelarg-selinuxpermissive spec: kernelArguments: systemd.unified_cgroup_hierarchy=0 1 systemd.legacy_systemd_cgroup_controller=1 2 1 Enables cgroup v1 in systemd. 2 Disables cgroup v2. Example output for cgroup v2 apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker name: 05-worker-kernelarg-selinuxpermissive spec: kernelArguments: - systemd_unified_cgroup_hierarchy=1 1 - cgroup_no_v1="all" 2 - psi=1 3 1 Enables cgroup v2 in systemd. 2 Disables cgroup v1. 3 Enables the Linux Pressure Stall Information (PSI) feature. Check the nodes to see that scheduling on the nodes is disabled. This indicates that the change is being applied: USD oc get nodes Example output NAME STATUS ROLES AGE VERSION ci-ln-fm1qnwt-72292-99kt6-master-0 Ready,SchedulingDisabled master 58m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-master-1 Ready master 58m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-master-2 Ready master 58m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-worker-a-h5gt4 Ready,SchedulingDisabled worker 48m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-worker-b-7vtmd Ready worker 48m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-worker-c-rhzkv Ready worker 48m v1.26.0 After a node returns to the Ready state, start a debug session for that node: USD oc debug node/<node_name> Set /host as the root directory within the debug shell: sh-4.4# chroot /host Check that the sys/fs/cgroup/cgroup2fs or sys/fs/cgroup/tmpfs file is present on your nodes: USD stat -c %T -f /sys/fs/cgroup Example output for cgroup v1 tmp2fs Example output for cgroup v2 cgroup2fs Additional resources OpenShift Container Platform installation overview 8.7. Enabling features using feature gates As an administrator, you can use feature gates to enable features that are not part of the default set of features. 8.7.1. Understanding feature gates You can use the FeatureGate custom resource (CR) to enable specific feature sets in your cluster. A feature set is a collection of OpenShift Container Platform features that are not enabled by default. You can activate the following feature set by using the FeatureGate CR: TechPreviewNoUpgrade . This feature set is a subset of the current Technology Preview features. This feature set allows you to enable these Technology Preview features on test clusters, where you can fully test them, while leaving the features disabled on production clusters. Warning Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters. The following Technology Preview features are enabled by this feature set: External cloud providers. Enables support for external cloud providers for clusters on vSphere, AWS, Azure, and GCP. Support for OpenStack is GA. This is an internal feature that most users do not need to interact with. ( ExternalCloudProvider ) Shared Resources CSI Driver and Build CSI Volumes in OpenShift Builds. Enables the Container Storage Interface (CSI). ( CSIDriverSharedResource ) CSI volumes. Enables CSI volume support for the OpenShift Container Platform build system. ( BuildCSIVolumes ) Swap memory on nodes. Enables swap memory use for OpenShift Container Platform workloads on a per-node basis. ( NodeSwap ) OpenStack Machine API Provider. This gate has no effect and is planned to be removed from this feature set in a future release. ( MachineAPIProviderOpenStack ) Insights Operator. Enables the InsightsDataGather CRD, which allows users to configure some Insights data gathering options. Pod topology spread constraints. Enables the matchLabelKeys parameter for pod topology constraints. The parameter is list of pod label keys to select the pods over which spreading will be calculated. ( MatchLabelKeysInPodTopologySpread ) Retroactive Default Storage Class. Enables OpenShift Container Platform to retroactively assign the default storage class to PVCs if there was no default storage class when the PVC was created.( RetroactiveDefaultStorageClass ) Pod disruption budget (PDB) unhealthy pod eviction policy. Enables support for specifying how unhealthy pods are considered for eviction when using PDBs. ( PDBUnhealthyPodEvictionPolicy ) Dynamic Resource Allocation API. Enables a new API for requesting and sharing resources between pods and containers. This is an internal feature that most users do not need to interact with. ( DynamicResourceAllocation ) Pod security admission enforcement. Enables the restricted enforcement mode for pod security admission. Instead of only logging a warning, pods are rejected if they violate pod security standards. ( OpenShiftPodSecurityAdmission ) For more information about the features activated by the TechPreviewNoUpgrade feature gate, see the following topics: Shared Resources CSI Driver and Build CSI Volumes in OpenShift Builds CSI inline ephemeral volumes Swap memory on nodes Disabling the Insights Operator gather operations Enabling the Insights Operator gather operations Managing machines with the Cluster API Controlling pod placement by using pod topology spread constraints Managing the default storage class Specifying the eviction policy for unhealthy pods Pod security admission enforcement . 8.7.2. Enabling feature sets at installation You can enable feature sets for all nodes in the cluster by editing the install-config.yaml file before you deploy the cluster. Prerequisites You have an install-config.yaml file. Procedure Use the featureSet parameter to specify the name of the feature set you want to enable, such as TechPreviewNoUpgrade : Warning Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters. Sample install-config.yaml file with an enabled feature set compute: - hyperthreading: Enabled name: worker platform: aws: rootVolume: iops: 2000 size: 500 type: io1 metadataService: authentication: Optional type: c5.4xlarge zones: - us-west-2c replicas: 3 featureSet: TechPreviewNoUpgrade Save the file and reference it when using the installation program to deploy the cluster. Verification You can verify that the feature gates are enabled by looking at the kubelet.conf file on a node after the nodes return to the ready state. From the Administrator perspective in the web console, navigate to Compute Nodes . Select a node. In the Node details page, click Terminal . In the terminal window, change your root directory to /host : sh-4.2# chroot /host View the kubelet.conf file: sh-4.2# cat /etc/kubernetes/kubelet.conf Sample output # ... featureGates: InsightsOperatorPullingSCA: true, LegacyNodeRoleBehavior: false # ... The features that are listed as true are enabled on your cluster. Note The features listed vary depending upon the OpenShift Container Platform version. 8.7.3. Enabling feature sets using the web console You can use the OpenShift Container Platform web console to enable feature sets for all of the nodes in a cluster by editing the FeatureGate custom resource (CR). Procedure To enable feature sets: In the OpenShift Container Platform web console, switch to the Administration Custom Resource Definitions page. On the Custom Resource Definitions page, click FeatureGate . On the Custom Resource Definition Details page, click the Instances tab. Click the cluster feature gate, then click the YAML tab. Edit the cluster instance to add specific feature sets: Warning Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters. Sample Feature Gate custom resource apiVersion: config.openshift.io/v1 kind: FeatureGate metadata: name: cluster 1 # ... spec: featureSet: TechPreviewNoUpgrade 2 1 The name of the FeatureGate CR must be cluster . 2 Add the feature set that you want to enable: TechPreviewNoUpgrade enables specific Technology Preview features. After you save the changes, new machine configs are created, the machine config pools are updated, and scheduling on each node is disabled while the change is being applied. Verification You can verify that the feature gates are enabled by looking at the kubelet.conf file on a node after the nodes return to the ready state. From the Administrator perspective in the web console, navigate to Compute Nodes . Select a node. In the Node details page, click Terminal . In the terminal window, change your root directory to /host : sh-4.2# chroot /host View the kubelet.conf file: sh-4.2# cat /etc/kubernetes/kubelet.conf Sample output # ... featureGates: InsightsOperatorPullingSCA: true, LegacyNodeRoleBehavior: false # ... The features that are listed as true are enabled on your cluster. Note The features listed vary depending upon the OpenShift Container Platform version. 8.7.4. Enabling feature sets using the CLI You can use the OpenShift CLI ( oc ) to enable feature sets for all of the nodes in a cluster by editing the FeatureGate custom resource (CR). Prerequisites You have installed the OpenShift CLI ( oc ). Procedure To enable feature sets: Edit the FeatureGate CR named cluster : USD oc edit featuregate cluster Warning Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters. Sample FeatureGate custom resource apiVersion: config.openshift.io/v1 kind: FeatureGate metadata: name: cluster 1 # ... spec: featureSet: TechPreviewNoUpgrade 2 1 The name of the FeatureGate CR must be cluster . 2 Add the feature set that you want to enable: TechPreviewNoUpgrade enables specific Technology Preview features. After you save the changes, new machine configs are created, the machine config pools are updated, and scheduling on each node is disabled while the change is being applied. Verification You can verify that the feature gates are enabled by looking at the kubelet.conf file on a node after the nodes return to the ready state. From the Administrator perspective in the web console, navigate to Compute Nodes . Select a node. In the Node details page, click Terminal . In the terminal window, change your root directory to /host : sh-4.2# chroot /host View the kubelet.conf file: sh-4.2# cat /etc/kubernetes/kubelet.conf Sample output # ... featureGates: InsightsOperatorPullingSCA: true, LegacyNodeRoleBehavior: false # ... The features that are listed as true are enabled on your cluster. Note The features listed vary depending upon the OpenShift Container Platform version. 8.8. Improving cluster stability in high latency environments using worker latency profiles If the cluster administrator has performed latency tests for platform verification, they can discover the need to adjust the operation of the cluster to ensure stability in cases of high latency. The cluster administrator need change only one parameter, recorded in a file, which controls four parameters affecting how supervisory processes read status and interpret the health of the cluster. Changing only the one parameter provides cluster tuning in an easy, supportable manner. The Kubelet process provides the starting point for monitoring cluster health. The Kubelet sets status values for all nodes in the OpenShift Container Platform cluster. The Kubernetes Controller Manager ( kube controller ) reads the status values every 10 seconds, by default. If the kube controller cannot read a node status value, it loses contact with that node after a configured period. The default behavior is: The node controller on the control plane updates the node health to Unhealthy and marks the node Ready condition`Unknown`. In response, the scheduler stops scheduling pods to that node. The Node Lifecycle Controller adds a node.kubernetes.io/unreachable taint with a NoExecute effect to the node and schedules any pods on the node for eviction after five minutes, by default. This behavior can cause problems if your network is prone to latency issues, especially if you have nodes at the network edge. In some cases, the Kubernetes Controller Manager might not receive an update from a healthy node due to network latency. The Kubelet evicts pods from the node even though the node is healthy. To avoid this problem, you can use worker latency profiles to adjust the frequency that the Kubelet and the Kubernetes Controller Manager wait for status updates before taking action. These adjustments help to ensure that your cluster runs properly if network latency between the control plane and the worker nodes is not optimal. These worker latency profiles contain three sets of parameters that are pre-defined with carefully tuned values to control the reaction of the cluster to increased latency. No need to experimentally find the best values manually. You can configure worker latency profiles when installing a cluster or at any time you notice increased latency in your cluster network. 8.8.1. Understanding worker latency profiles Worker latency profiles are four different categories of carefully-tuned parameters. The four parameters which implement these values are node-status-update-frequency , node-monitor-grace-period , default-not-ready-toleration-seconds and default-unreachable-toleration-seconds . These parameters can use values which allow you control the reaction of the cluster to latency issues without needing to determine the best values using manual methods. Important Setting these parameters manually is not supported. Incorrect parameter settings adversely affect cluster stability. All worker latency profiles configure the following parameters: node-status-update-frequency Specifies how often the kubelet posts node status to the API server. node-monitor-grace-period Specifies the amount of time in seconds that the Kubernetes Controller Manager waits for an update from a kubelet before marking the node unhealthy and adding the node.kubernetes.io/not-ready or node.kubernetes.io/unreachable taint to the node. default-not-ready-toleration-seconds Specifies the amount of time in seconds after marking a node unhealthy that the Kube API Server Operator waits before evicting pods from that node. default-unreachable-toleration-seconds Specifies the amount of time in seconds after marking a node unreachable that the Kube API Server Operator waits before evicting pods from that node. The following Operators monitor the changes to the worker latency profiles and respond accordingly: The Machine Config Operator (MCO) updates the node-status-update-frequency parameter on the worker nodes. The Kubernetes Controller Manager updates the node-monitor-grace-period parameter on the control plane nodes. The Kubernetes API Server Operator updates the default-not-ready-toleration-seconds and default-unreachable-toleration-seconds parameters on the control plane nodes. Although the default configuration works in most cases, OpenShift Container Platform offers two other worker latency profiles for situations where the network is experiencing higher latency than usual. The three worker latency profiles are described in the following sections: Default worker latency profile With the Default profile, each Kubelet updates it's status every 10 seconds ( node-status-update-frequency ). The Kube Controller Manager checks the statuses of Kubelet every 5 seconds ( node-monitor-grace-period ). The Kubernetes Controller Manager waits 40 seconds for a status update from Kubelet before considering the Kubelet unhealthy. If no status is made available to the Kubernetes Controller Manager, it then marks the node with the node.kubernetes.io/not-ready or node.kubernetes.io/unreachable taint and evicts the pods on that node. If a pod on that node has the NoExecute taint, the pod is run according to tolerationSeconds . If the pod has no taint, it will be evicted in 300 seconds ( default-not-ready-toleration-seconds and default-unreachable-toleration-seconds settings of the Kube API Server ). Profile Component Parameter Value Default kubelet node-status-update-frequency 10s Kubelet Controller Manager node-monitor-grace-period 40s Kubernetes API Server Operator default-not-ready-toleration-seconds 300s Kubernetes API Server Operator default-unreachable-toleration-seconds 300s Medium worker latency profile Use the MediumUpdateAverageReaction profile if the network latency is slightly higher than usual. The MediumUpdateAverageReaction profile reduces the frequency of kubelet updates to 20 seconds and changes the period that the Kubernetes Controller Manager waits for those updates to 2 minutes. The pod eviction period for a pod on that node is reduced to 60 seconds. If the pod has the tolerationSeconds parameter, the eviction waits for the period specified by that parameter. The Kubernetes Controller Manager waits for 2 minutes to consider a node unhealthy. In another minute, the eviction process starts. Profile Component Parameter Value MediumUpdateAverageReaction kubelet node-status-update-frequency 20s Kubelet Controller Manager node-monitor-grace-period 2m Kubernetes API Server Operator default-not-ready-toleration-seconds 60s Kubernetes API Server Operator default-unreachable-toleration-seconds 60s Low worker latency profile Use the LowUpdateSlowReaction profile if the network latency is extremely high. The LowUpdateSlowReaction profile reduces the frequency of kubelet updates to 1 minute and changes the period that the Kubernetes Controller Manager waits for those updates to 5 minutes. The pod eviction period for a pod on that node is reduced to 60 seconds. If the pod has the tolerationSeconds parameter, the eviction waits for the period specified by that parameter. The Kubernetes Controller Manager waits for 5 minutes to consider a node unhealthy. In another minute, the eviction process starts. Profile Component Parameter Value LowUpdateSlowReaction kubelet node-status-update-frequency 1m Kubelet Controller Manager node-monitor-grace-period 5m Kubernetes API Server Operator default-not-ready-toleration-seconds 60s Kubernetes API Server Operator default-unreachable-toleration-seconds 60s 8.8.2. Using and changing worker latency profiles To change a worker latency profile to deal with network latency, edit the node.config object to add the name of the profile. You can change the profile at any time as latency increases or decreases. You must move one worker latency profile at a time. For example, you cannot move directly from the Default profile to the LowUpdateSlowReaction worker latency profile. You must move from the Default worker latency profile to the MediumUpdateAverageReaction profile first, then to LowUpdateSlowReaction . Similarly, when returning to the Default profile, you must move from the low profile to the medium profile first, then to Default . Note You can also configure worker latency profiles upon installing an OpenShift Container Platform cluster. Procedure To move from the default worker latency profile: Move to the medium worker latency profile: Edit the node.config object: USD oc edit nodes.config/cluster Add spec.workerLatencyProfile: MediumUpdateAverageReaction : Example node.config object apiVersion: config.openshift.io/v1 kind: Node metadata: annotations: include.release.openshift.io/ibm-cloud-managed: "true" include.release.openshift.io/self-managed-high-availability: "true" include.release.openshift.io/single-node-developer: "true" release.openshift.io/create-only: "true" creationTimestamp: "2022-07-08T16:02:51Z" generation: 1 name: cluster ownerReferences: - apiVersion: config.openshift.io/v1 kind: ClusterVersion name: version uid: 36282574-bf9f-409e-a6cd-3032939293eb resourceVersion: "1865" uid: 0c0f7a4c-4307-4187-b591-6155695ac85b spec: workerLatencyProfile: MediumUpdateAverageReaction 1 # ... 1 Specifies the medium worker latency policy. Scheduling on each worker node is disabled as the change is being applied. Optional: Move to the low worker latency profile: Edit the node.config object: USD oc edit nodes.config/cluster Change the spec.workerLatencyProfile value to LowUpdateSlowReaction : Example node.config object apiVersion: config.openshift.io/v1 kind: Node metadata: annotations: include.release.openshift.io/ibm-cloud-managed: "true" include.release.openshift.io/self-managed-high-availability: "true" include.release.openshift.io/single-node-developer: "true" release.openshift.io/create-only: "true" creationTimestamp: "2022-07-08T16:02:51Z" generation: 1 name: cluster ownerReferences: - apiVersion: config.openshift.io/v1 kind: ClusterVersion name: version uid: 36282574-bf9f-409e-a6cd-3032939293eb resourceVersion: "1865" uid: 0c0f7a4c-4307-4187-b591-6155695ac85b spec: workerLatencyProfile: LowUpdateSlowReaction 1 # ... 1 Specifies use of the low worker latency policy. Scheduling on each worker node is disabled as the change is being applied. Verification When all nodes return to the Ready condition, you can use the following command to look in the Kubernetes Controller Manager to ensure it was applied: USD oc get KubeControllerManager -o yaml \| grep -i workerlatency -A 5 -B 5 Example output # ... - lastTransitionTime: "2022-07-11T19:47:10Z" reason: ProfileUpdated status: "False" type: WorkerLatencyProfileProgressing - lastTransitionTime: "2022-07-11T19:47:10Z" 1 message: all static pod revision(s) have updated latency profile reason: ProfileUpdated status: "True" type: WorkerLatencyProfileComplete - lastTransitionTime: "2022-07-11T19:20:11Z" reason: AsExpected status: "False" type: WorkerLatencyProfileDegraded - lastTransitionTime: "2022-07-11T19:20:36Z" status: "False" # ... 1 Specifies that the profile is applied and active. To change the medium profile to default or change the default to medium, edit the node.config object and set the spec.workerLatencyProfile parameter to the appropriate value.	[ "oc get events [-n <project>] 1", "oc get events -n openshift-config", "LAST SEEN TYPE REASON OBJECT MESSAGE 97m Normal Scheduled pod/dapi-env-test-pod Successfully assigned openshift-config/dapi-env-test-pod to ip-10-0-171-202.ec2.internal 97m Normal Pulling pod/dapi-env-test-pod pulling image \"gcr.io/google_containers/busybox\" 97m Normal Pulled pod/dapi-env-test-pod Successfully pulled image \"gcr.io/google_containers/busybox\" 97m Normal Created pod/dapi-env-test-pod Created container 9m5s Warning FailedCreatePodSandBox pod/dapi-volume-test-pod Failed create pod sandbox: rpc error: code = Unknown desc = failed to create pod network sandbox k8s_dapi-volume-test-pod_openshift-config_6bc60c1f-452e-11e9-9140-0eec59c23068_0(748c7a40db3d08c07fb4f9eba774bd5effe5f0d5090a242432a73eee66ba9e22): Multus: Err adding pod to network \"openshift-sdn\": cannot set \"openshift-sdn\" ifname to \"eth0\": no netns: failed to Statfs \"/proc/33366/ns/net\": no such file or directory 8m31s Normal Scheduled pod/dapi-volume-test-pod Successfully assigned openshift-config/dapi-volume-test-pod to ip-10-0-171-202.ec2.internal", "apiVersion: v1 kind: Pod metadata: name: small-pod labels: app: guestbook tier: frontend spec: containers: - name: php-redis image: gcr.io/google-samples/gb-frontend:v4 imagePullPolicy: Always resources: limits: cpu: 150m memory: 100Mi requests: cpu: 150m memory: 100Mi", "oc create -f <file_name>.yaml", "oc create -f pod-spec.yaml", "podman login registry.redhat.io", "podman pull registry.redhat.io/openshift4/ose-cluster-capacity", "podman run -v USDHOME/.kube:/kube:Z -v USD(pwd):/cc:Z ose-cluster-capacity /bin/cluster-capacity --kubeconfig /kube/config --<pod_spec>.yaml /cc/<pod_spec>.yaml --verbose", "small-pod pod requirements: - CPU: 150m - Memory: 100Mi The cluster can schedule 88 instance(s) of the pod small-pod. Termination reason: Unschedulable: 0/5 nodes are available: 2 Insufficient cpu, 3 node(s) had taint {node-role.kubernetes.io/master: }, that the pod didn't tolerate. Pod distribution among nodes: small-pod - 192.168.124.214: 45 instance(s) - 192.168.124.120: 43 instance(s)", "kind: ClusterRole apiVersion: rbac.authorization.k8s.io/v1 metadata: name: cluster-capacity-role rules: - apiGroups: [\"\"] resources: [\"pods\", \"nodes\", \"persistentvolumeclaims\", \"persistentvolumes\", \"services\", \"replicationcontrollers\"] verbs: [\"get\", \"watch\", \"list\"] - apiGroups: [\"apps\"] resources: [\"replicasets\", \"statefulsets\"] verbs: [\"get\", \"watch\", \"list\"] - apiGroups: [\"policy\"] resources: [\"poddisruptionbudgets\"] verbs: [\"get\", \"watch\", \"list\"] - apiGroups: [\"storage.k8s.io\"] resources: [\"storageclasses\"] verbs: [\"get\", \"watch\", \"list\"]", "oc create -f <file_name>.yaml", "oc create sa cluster-capacity-sa", "oc create sa cluster-capacity-sa -n default", "oc adm policy add-cluster-role-to-user cluster-capacity-role system:serviceaccount:<namespace>:cluster-capacity-sa", "apiVersion: v1 kind: Pod metadata: name: small-pod labels: app: guestbook tier: frontend spec: containers: - name: php-redis image: gcr.io/google-samples/gb-frontend:v4 imagePullPolicy: Always resources: limits: cpu: 150m memory: 100Mi requests: cpu: 150m memory: 100Mi", "oc create -f <file_name>.yaml", "oc create -f pod.yaml", "oc create configmap cluster-capacity-configmap --from-file=pod.yaml=pod.yaml", "apiVersion: batch/v1 kind: Job metadata: name: cluster-capacity-job spec: parallelism: 1 completions: 1 template: metadata: name: cluster-capacity-pod spec: containers: - name: cluster-capacity image: openshift/origin-cluster-capacity imagePullPolicy: \"Always\" volumeMounts: - mountPath: /test-pod name: test-volume env: - name: CC_INCLUSTER 1 value: \"true\" command: - \"/bin/sh\" - \"-ec\" - \| /bin/cluster-capacity --podspec=/test-pod/pod.yaml --verbose restartPolicy: \"Never\" serviceAccountName: cluster-capacity-sa volumes: - name: test-volume configMap: name: cluster-capacity-configmap", "oc create -f cluster-capacity-job.yaml", "oc logs jobs/cluster-capacity-job", "small-pod pod requirements: - CPU: 150m - Memory: 100Mi The cluster can schedule 52 instance(s) of the pod small-pod. Termination reason: Unschedulable: No nodes are available that match all of the following predicates:: Insufficient cpu (2). Pod distribution among nodes: small-pod - 192.168.124.214: 26 instance(s) - 192.168.124.120: 26 instance(s)", "apiVersion: \"v1\" kind: \"LimitRange\" metadata: name: \"resource-limits\" spec: limits: - type: \"Container\" max: cpu: \"2\" memory: \"1Gi\" min: cpu: \"100m\" memory: \"4Mi\" default: cpu: \"300m\" memory: \"200Mi\" defaultRequest: cpu: \"200m\" memory: \"100Mi\" maxLimitRequestRatio: cpu: \"10\"", "apiVersion: \"v1\" kind: \"LimitRange\" metadata: name: \"resource-limits\" 1 spec: limits: - type: \"Container\" max: cpu: \"2\" 2 memory: \"1Gi\" 3 min: cpu: \"100m\" 4 memory: \"4Mi\" 5 default: cpu: \"300m\" 6 memory: \"200Mi\" 7 defaultRequest: cpu: \"200m\" 8 memory: \"100Mi\" 9 maxLimitRequestRatio: cpu: \"10\" 10", "apiVersion: \"v1\" kind: \"LimitRange\" metadata: name: \"resource-limits\" 1 spec: limits: - type: \"Pod\" max: cpu: \"2\" 2 memory: \"1Gi\" 3 min: cpu: \"200m\" 4 memory: \"6Mi\" 5 maxLimitRequestRatio: cpu: \"10\" 6", "apiVersion: \"v1\" kind: \"LimitRange\" metadata: name: \"resource-limits\" 1 spec: limits: - type: openshift.io/Image max: storage: 1Gi 2", "apiVersion: \"v1\" kind: \"LimitRange\" metadata: name: \"resource-limits\" 1 spec: limits: - type: openshift.io/ImageStream max: openshift.io/image-tags: 20 2 openshift.io/images: 30 3", "apiVersion: \"v1\" kind: \"LimitRange\" metadata: name: \"resource-limits\" 1 spec: limits: - type: \"PersistentVolumeClaim\" min: storage: \"2Gi\" 2 max: storage: \"50Gi\" 3", "apiVersion: \"v1\" kind: \"LimitRange\" metadata: name: \"resource-limits\" 1 spec: limits: - type: \"Pod\" 2 max: cpu: \"2\" memory: \"1Gi\" min: cpu: \"200m\" memory: \"6Mi\" - type: \"Container\" 3 max: cpu: \"2\" memory: \"1Gi\" min: cpu: \"100m\" memory: \"4Mi\" default: 4 cpu: \"300m\" memory: \"200Mi\" defaultRequest: 5 cpu: \"200m\" memory: \"100Mi\" maxLimitRequestRatio: 6 cpu: \"10\" - type: openshift.io/Image 7 max: storage: 1Gi - type: openshift.io/ImageStream 8 max: openshift.io/image-tags: 20 openshift.io/images: 30 - type: \"PersistentVolumeClaim\" 9 min: storage: \"2Gi\" max: storage: \"50Gi\"", "oc create -f <limit_range_file> -n <project> 1", "oc get limits -n demoproject", "NAME CREATED AT resource-limits 2020-07-15T17:14:23Z", "oc describe limits resource-limits -n demoproject", "Name: resource-limits Namespace: demoproject Type Resource Min Max Default Request Default Limit Max Limit/Request Ratio ---- -------- --- --- --------------- ------------- ----------------------- Pod cpu 200m 2 - - - Pod memory 6Mi 1Gi - - - Container cpu 100m 2 200m 300m 10 Container memory 4Mi 1Gi 100Mi 200Mi - openshift.io/Image storage - 1Gi - - - openshift.io/ImageStream openshift.io/image - 12 - - - openshift.io/ImageStream openshift.io/image-tags - 10 - - - PersistentVolumeClaim storage - 50Gi - - -", "oc delete limits <limit_name>", "-XX:+UseParallelGC -XX:MinHeapFreeRatio=5 -XX:MaxHeapFreeRatio=10 -XX:GCTimeRatio=4 -XX:AdaptiveSizePolicyWeight=90.", "JAVA_TOOL_OPTIONS=\"-XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap -Dsun.zip.disableMemoryMapping=true\"", "apiVersion: v1 kind: Pod metadata: name: test spec: containers: - name: test image: fedora:latest command: - sleep - \"3600\" env: - name: MEMORY_REQUEST 1 valueFrom: resourceFieldRef: containerName: test resource: requests.memory - name: MEMORY_LIMIT 2 valueFrom: resourceFieldRef: containerName: test resource: limits.memory resources: requests: memory: 384Mi limits: memory: 512Mi", "oc create -f <file-name>.yaml", "oc rsh test", "env \| grep MEMORY \| sort", "MEMORY_LIMIT=536870912 MEMORY_REQUEST=402653184", "oc rsh test", "grep '^oom_kill ' /sys/fs/cgroup/memory/memory.oom_control", "oom_kill 0", "sed -e '' </dev/zero", "Killed", "echo USD?", "137", "grep '^oom_kill ' /sys/fs/cgroup/memory/memory.oom_control", "oom_kill 1", "oc get pod test", "NAME READY STATUS RESTARTS AGE test 0/1 OOMKilled 0 1m", "oc get pod test -o yaml", "status: containerStatuses: - name: test ready: false restartCount: 0 state: terminated: exitCode: 137 reason: OOMKilled phase: Failed", "oc get pod test -o yaml", "status: containerStatuses: - name: test ready: true restartCount: 1 lastState: terminated: exitCode: 137 reason: OOMKilled state: running: phase: Running", "oc get pod test", "NAME READY STATUS RESTARTS AGE test 0/1 Evicted 0 1m", "oc get pod test -o yaml", "status: message: 'Pod The node was low on resource: [MemoryPressure].' phase: Failed reason: Evicted", "apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster 1 spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 2 cpuRequestToLimitPercent: 25 3 limitCPUToMemoryPercent: 200 4", "apiVersion: v1 kind: Namespace metadata: labels: clusterresourceoverrides.admission.autoscaling.openshift.io/enabled: \"true\"", "apiVersion: v1 kind: Pod metadata: name: my-pod namespace: my-namespace spec: containers: - name: hello-openshift image: openshift/hello-openshift resources: limits: memory: \"512Mi\" cpu: \"2000m\"", "apiVersion: v1 kind: Pod metadata: name: my-pod namespace: my-namespace spec: containers: - image: openshift/hello-openshift name: hello-openshift resources: limits: cpu: \"1\" 1 memory: 512Mi requests: cpu: 250m 2 memory: 256Mi", "apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster 1 spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 2 cpuRequestToLimitPercent: 25 3 limitCPUToMemoryPercent: 200 4", "apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: annotations: kubectl.kubernetes.io/last-applied-configuration: \| {\"apiVersion\":\"operator.autoscaling.openshift.io/v1\",\"kind\":\"ClusterResourceOverride\",\"metadata\":{\"annotations\":{},\"name\":\"cluster\"},\"spec\":{\"podResourceOverride\":{\"spec\":{\"cpuRequestToLimitPercent\":25,\"limitCPUToMemoryPercent\":200,\"memoryRequestToLimitPercent\":50}}}} creationTimestamp: \"2019-12-18T22:35:02Z\" generation: 1 name: cluster resourceVersion: \"127622\" selfLink: /apis/operator.autoscaling.openshift.io/v1/clusterresourceoverrides/cluster uid: 978fc959-1717-4bd1-97d0-ae00ee111e8d spec: podResourceOverride: spec: cpuRequestToLimitPercent: 25 limitCPUToMemoryPercent: 200 memoryRequestToLimitPercent: 50 status: mutatingWebhookConfigurationRef: 1 apiVersion: admissionregistration.k8s.io/v1 kind: MutatingWebhookConfiguration name: clusterresourceoverrides.admission.autoscaling.openshift.io resourceVersion: \"127621\" uid: 98b3b8ae-d5ce-462b-8ab5-a729ea8f38f3", "apiVersion: v1 kind: Namespace metadata: name: clusterresourceoverride-operator", "oc create -f <file-name>.yaml", "oc create -f cro-namespace.yaml", "apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: clusterresourceoverride-operator namespace: clusterresourceoverride-operator spec: targetNamespaces: - clusterresourceoverride-operator", "oc create -f <file-name>.yaml", "oc create -f cro-og.yaml", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: clusterresourceoverride namespace: clusterresourceoverride-operator spec: channel: \"stable\" name: clusterresourceoverride source: redhat-operators sourceNamespace: openshift-marketplace", "oc create -f <file-name>.yaml", "oc create -f cro-sub.yaml", "oc project clusterresourceoverride-operator", "apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster 1 spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 2 cpuRequestToLimitPercent: 25 3 limitCPUToMemoryPercent: 200 4", "oc create -f <file-name>.yaml", "oc create -f cro-cr.yaml", "oc get clusterresourceoverride cluster -n clusterresourceoverride-operator -o yaml", "apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: annotations: kubectl.kubernetes.io/last-applied-configuration: \| {\"apiVersion\":\"operator.autoscaling.openshift.io/v1\",\"kind\":\"ClusterResourceOverride\",\"metadata\":{\"annotations\":{},\"name\":\"cluster\"},\"spec\":{\"podResourceOverride\":{\"spec\":{\"cpuRequestToLimitPercent\":25,\"limitCPUToMemoryPercent\":200,\"memoryRequestToLimitPercent\":50}}}} creationTimestamp: \"2019-12-18T22:35:02Z\" generation: 1 name: cluster resourceVersion: \"127622\" selfLink: /apis/operator.autoscaling.openshift.io/v1/clusterresourceoverrides/cluster uid: 978fc959-1717-4bd1-97d0-ae00ee111e8d spec: podResourceOverride: spec: cpuRequestToLimitPercent: 25 limitCPUToMemoryPercent: 200 memoryRequestToLimitPercent: 50 status: mutatingWebhookConfigurationRef: 1 apiVersion: admissionregistration.k8s.io/v1 kind: MutatingWebhookConfiguration name: clusterresourceoverrides.admission.autoscaling.openshift.io resourceVersion: \"127621\" uid: 98b3b8ae-d5ce-462b-8ab5-a729ea8f38f3", "apiVersion: operator.autoscaling.openshift.io/v1 kind: ClusterResourceOverride metadata: name: cluster spec: podResourceOverride: spec: memoryRequestToLimitPercent: 50 1 cpuRequestToLimitPercent: 25 2 limitCPUToMemoryPercent: 200 3", "apiVersion: v1 kind: Namespace metadata: labels: clusterresourceoverrides.admission.autoscaling.openshift.io/enabled: \"true\" 1", "sysctl -a \|grep commit", "# vm.overcommit_memory = 0 #", "sysctl -a \|grep panic", "# vm.panic_on_oom = 0 #", "oc edit machineconfigpool <name>", "oc edit machineconfigpool worker", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: \"2022-11-16T15:34:25Z\" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 1 name: worker", "oc label machineconfigpool worker custom-kubelet=small-pods", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: disable-cpu-units 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 2 kubeletConfig: cpuCfsQuota: false 3", "oc create -f <file_name>.yaml", "sysctl -w vm.overcommit_memory=0", "apiVersion: v1 kind: Namespace metadata: annotations: quota.openshift.io/cluster-resource-override-enabled: \"false\" 1", "oc edit nodes.config/cluster", "apiVersion: config.openshift.io/v1 kind: Node metadata: annotations: include.release.openshift.io/ibm-cloud-managed: \"true\" include.release.openshift.io/self-managed-high-availability: \"true\" include.release.openshift.io/single-node-developer: \"true\" release.openshift.io/create-only: \"true\" creationTimestamp: \"2022-07-08T16:02:51Z\" generation: 1 name: cluster ownerReferences: - apiVersion: config.openshift.io/v1 kind: ClusterVersion name: version uid: 36282574-bf9f-409e-a6cd-3032939293eb resourceVersion: \"1865\" uid: 0c0f7a4c-4307-4187-b591-6155695ac85b spec: cgroupMode: \"v2\" 1", "oc get mc", "NAME GENERATEDBYCONTROLLER IGNITIONVERSION AGE 00-master 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 00-worker 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 97-master-generated-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-generated-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-ssh 3.2.0 40m 99-worker-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-ssh 3.2.0 40m rendered-master-23d4317815a5f854bd3553d689cfe2e9 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 10s 1 rendered-master-23e785de7587df95a4b517e0647e5ab7 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-5d596d9293ca3ea80c896a1191735bb1 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-dcc7f1b92892d34db74d6832bcc9ccd4 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 10s", "oc describe mc <name>", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker name: 05-worker-kernelarg-selinuxpermissive spec: kernelArguments: systemd.unified_cgroup_hierarchy=0 1 systemd.legacy_systemd_cgroup_controller=1 2", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker name: 05-worker-kernelarg-selinuxpermissive spec: kernelArguments: - systemd_unified_cgroup_hierarchy=1 1 - cgroup_no_v1=\"all\" 2 - psi=1 3", "oc get nodes", "NAME STATUS ROLES AGE VERSION ci-ln-fm1qnwt-72292-99kt6-master-0 Ready,SchedulingDisabled master 58m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-master-1 Ready master 58m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-master-2 Ready master 58m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-worker-a-h5gt4 Ready,SchedulingDisabled worker 48m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-worker-b-7vtmd Ready worker 48m v1.26.0 ci-ln-fm1qnwt-72292-99kt6-worker-c-rhzkv Ready worker 48m v1.26.0", "oc debug node/<node_name>", "sh-4.4# chroot /host", "stat -c %T -f /sys/fs/cgroup", "tmp2fs", "cgroup2fs", "compute: - hyperthreading: Enabled name: worker platform: aws: rootVolume: iops: 2000 size: 500 type: io1 metadataService: authentication: Optional type: c5.4xlarge zones: - us-west-2c replicas: 3 featureSet: TechPreviewNoUpgrade", "sh-4.2# chroot /host", "sh-4.2# cat /etc/kubernetes/kubelet.conf", "featureGates: InsightsOperatorPullingSCA: true, LegacyNodeRoleBehavior: false", "apiVersion: config.openshift.io/v1 kind: FeatureGate metadata: name: cluster 1 spec: featureSet: TechPreviewNoUpgrade 2", "sh-4.2# chroot /host", "sh-4.2# cat /etc/kubernetes/kubelet.conf", "featureGates: InsightsOperatorPullingSCA: true, LegacyNodeRoleBehavior: false", "oc edit featuregate cluster", "apiVersion: config.openshift.io/v1 kind: FeatureGate metadata: name: cluster 1 spec: featureSet: TechPreviewNoUpgrade 2", "sh-4.2# chroot /host", "sh-4.2# cat /etc/kubernetes/kubelet.conf", "featureGates: InsightsOperatorPullingSCA: true, LegacyNodeRoleBehavior: false", "oc edit nodes.config/cluster", "apiVersion: config.openshift.io/v1 kind: Node metadata: annotations: include.release.openshift.io/ibm-cloud-managed: \"true\" include.release.openshift.io/self-managed-high-availability: \"true\" include.release.openshift.io/single-node-developer: \"true\" release.openshift.io/create-only: \"true\" creationTimestamp: \"2022-07-08T16:02:51Z\" generation: 1 name: cluster ownerReferences: - apiVersion: config.openshift.io/v1 kind: ClusterVersion name: version uid: 36282574-bf9f-409e-a6cd-3032939293eb resourceVersion: \"1865\" uid: 0c0f7a4c-4307-4187-b591-6155695ac85b spec: workerLatencyProfile: MediumUpdateAverageReaction 1", "oc edit nodes.config/cluster", "apiVersion: config.openshift.io/v1 kind: Node metadata: annotations: include.release.openshift.io/ibm-cloud-managed: \"true\" include.release.openshift.io/self-managed-high-availability: \"true\" include.release.openshift.io/single-node-developer: \"true\" release.openshift.io/create-only: \"true\" creationTimestamp: \"2022-07-08T16:02:51Z\" generation: 1 name: cluster ownerReferences: - apiVersion: config.openshift.io/v1 kind: ClusterVersion name: version uid: 36282574-bf9f-409e-a6cd-3032939293eb resourceVersion: \"1865\" uid: 0c0f7a4c-4307-4187-b591-6155695ac85b spec: workerLatencyProfile: LowUpdateSlowReaction 1", "oc get KubeControllerManager -o yaml \| grep -i workerlatency -A 5 -B 5", "- lastTransitionTime: \"2022-07-11T19:47:10Z\" reason: ProfileUpdated status: \"False\" type: WorkerLatencyProfileProgressing - lastTransitionTime: \"2022-07-11T19:47:10Z\" 1 message: all static pod revision(s) have updated latency profile reason: ProfileUpdated status: \"True\" type: WorkerLatencyProfileComplete - lastTransitionTime: \"2022-07-11T19:20:11Z\" reason: AsExpected status: \"False\" type: WorkerLatencyProfileDegraded - lastTransitionTime: \"2022-07-11T19:20:36Z\" status: \"False\"" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.13/html/nodes/working-with-clusters
Project APIs	Project APIs OpenShift Container Platform 4.17 Reference guide for project APIs Red Hat OpenShift Documentation Team	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.17/html-single/project_apis/index
Chapter 4. Installing Hosts for Red Hat Virtualization	Chapter 4. Installing Hosts for Red Hat Virtualization Red Hat Virtualization supports two types of hosts: Red Hat Virtualization Hosts (RHVH) and Red Hat Enterprise Linux hosts . Depending on your environment, you may want to use one type only, or both. At least two hosts are required for features such as migration and high availability. See Section 4.3, "Recommended Practices for Configuring Host Networks" for networking information. Important SELinux is in enforcing mode upon installation. To verify, run getenforce . SELinux must be in enforcing mode on all hosts and Managers for your Red Hat Virtualization environment to be supported. Table 4.1. Host Types Host Type Other Names Description Red Hat Virtualization Host RHVH, thin host This is a minimal operating system based on Red Hat Enterprise Linux. It is distributed as an ISO file from the Customer Portal and contains only the packages required for the machine to act as a host. Red Hat Enterprise Linux host RHEL host, thick host Red Hat Enterprise Linux systems with the appropriate subscriptions attached can be used as hosts. Host Compatibility When you create a new data center, you can set the compatibility version. Select the compatibility version that suits all the hosts in the data center. Once set, version regression is not allowed. For a fresh Red Hat Virtualization installation, the latest compatibility version is set in the default data center and default cluster; to use an earlier compatibility version, you must create additional data centers and clusters. For more information about compatibility versions see Red Hat Virtualization Manager Compatibility in Red Hat Virtualization Life Cycle . 4.1. Red Hat Virtualization Hosts 4.1.1. Installing Red Hat Virtualization Hosts Red Hat Virtualization Host (RHVH) is a minimal operating system based on Red Hat Enterprise Linux that is designed to provide a simple method for setting up a physical machine to act as a hypervisor in a Red Hat Virtualization environment. The minimal operating system contains only the packages required for the machine to act as a hypervisor, and features a Cockpit web interface for monitoring the host and performing administrative tasks. See http://cockpit-project.org/running.html for the minimum browser requirements. RHVH supports NIST 800-53 partitioning requirements to improve security. RHVH uses a NIST 800-53 partition layout by default. The host must meet the minimum host requirements . Procedure Download the RHVH ISO image from the Customer Portal: Log in to the Customer Portal at https://access.redhat.com . Click Downloads in the menu bar. Click Red Hat Virtualization . Scroll up and click Download Latest to access the product download page. Go to Hypervisor Image for RHV 4.3 and and click Download Now . Create a bootable media device. See Making Media in the Red Hat Enterprise Linux Installation Guide for more information. Start the machine on which you are installing RHVH, booting from the prepared installation media. From the boot menu, select Install RHVH 4.3 and press Enter . Note You can also press the Tab key to edit the kernel parameters. Kernel parameters must be separated by a space, and you can boot the system using the specified kernel parameters by pressing the Enter key. Press the Esc key to clear any changes to the kernel parameters and return to the boot menu. Select a language, and click Continue . Select a time zone from the Date & Time screen and click Done . Select a keyboard layout from the Keyboard screen and click Done . Select the device on which to install RHVH from the Installation Destination screen. Optionally, enable encryption. Click Done . Important Red Hat strongly recommends using the Automatically configure partitioning option. Select a network from the Network & Host Name screen and click Configure... to configure the connection details. Note To use the connection every time the system boots, select the Automatically connect to this network when it is available check box. For more information, see Edit Network Connections in the Red Hat Enterprise Linux 7 Installation Guide . Enter a host name in the Host name field, and click Done . Optionally configure Language Support , Security Policy , and Kdump . See Installing Using Anaconda in the Red Hat Enterprise Linux 7 Installation Guide for more information on each of the sections in the Installation Summary screen. Click Begin Installation . Set a root password and, optionally, create an additional user while RHVH installs. Warning Red Hat strongly recommends not creating untrusted users on RHVH, as this can lead to exploitation of local security vulnerabilities. Click Reboot to complete the installation. Note When RHVH restarts, nodectl check performs a health check on the host and displays the result when you log in on the command line. The message node status: OK or node status: DEGRADED indicates the health status. Run nodectl check to get more information. The service is enabled by default. 4.1.2. Enabling the Red Hat Virtualization Host Repository Register the system to receive updates. Red Hat Virtualization Host only requires one repository. This section provides instructions for registering RHVH with the Content Delivery Network , or with Red Hat Satellite 6 . Registering RHVH with the Content Delivery Network Log in to the Cockpit web interface at https:// HostFQDNorIP :9090 . Navigate to Subscriptions , click Register System , and enter your Customer Portal user name and password. The Red Hat Virtualization Host subscription is automatically attached to the system. Click Terminal . Enable the Red Hat Virtualization Host 7 repository to allow later updates to the Red Hat Virtualization Host: Registering RHVH with Red Hat Satellite 6 Log in to the Cockpit web interface at https:// HostFQDNorIP :9090 . Click Terminal . Register RHVH with Red Hat Satellite 6: 4.1.3. Advanced Installation 4.1.3.1. Custom Partitioning Custom partitioning on Red Hat Virtualization Host (RHVH) is not recommended. Red Hat strongly recommends using the Automatically configure partitioning option in the Installation Destination window. If your installation requires custom partitioning, select the I will configure partitioning option during the installation, and note that the following restrictions apply: Ensure the default LVM Thin Provisioning option is selected in the Manual Partitioning window. The following directories are required and must be on thin provisioned logical volumes: root ( / ) /home /tmp /var /var/crash /var/log /var/log/audit Important Do not create a separate partition for /usr . Doing so will cause the installation to fail. /usr must be on a logical volume that is able to change versions along with RHVH, and therefore should be left on root ( / ). For information about the required storage sizes for each partition, see Section 2.2.3, "Storage Requirements" . The /boot directory should be defined as a standard partition. The /var directory must be on a separate volume or disk. Only XFS or Ext4 file systems are supported. Configuring Manual Partitioning in a Kickstart File The following example demonstrates how to configure manual partitioning in a Kickstart file. Note If you use logvol --thinpool --grow , you must also include volgroup --reserved-space or volgroup --reserved-percent to reserve space in the volume group for the thin pool to grow. 4.1.3.2. Automating Red Hat Virtualization Host Deployment You can install Red Hat Virtualization Host (RHVH) without a physical media device by booting from a PXE server over the network with a Kickstart file that contains the answers to the installation questions. General instructions for installing from a PXE server with a Kickstart file are available in the Red Hat Enterprise Linux Installation Guide , as RHVH is installed in much the same way as Red Hat Enterprise Linux. RHVH-specific instructions, with examples for deploying RHVH with Red Hat Satellite, are described below. The automated RHVH deployment has 3 stages: Section 4.1.3.2.1, "Preparing the Installation Environment" Section 4.1.3.2.2, "Configuring the PXE Server and the Boot Loader" Section 4.1.3.2.3, "Creating and Running a Kickstart File" 4.1.3.2.1. Preparing the Installation Environment Log in to the Customer Portal . Click Downloads in the menu bar. Click Red Hat Virtualization . Scroll up and click Download Latest to access the product download page. Go to Hypervisor Image for RHV 4.3 and and click Download Now . Make the RHVH ISO image available over the network. See Installation Source on a Network in the Red Hat Enterprise Linux Installation Guide . Extract the squashfs.img hypervisor image file from the RHVH ISO: Note This squashfs.img file, located in the /tmp/usr/share/redhat-virtualization-host/image/ directory, is called redhat-virtualization-host- version_number _version.squashfs.img . It contains the hypervisor image for installation on the physical machine. It should not be confused with the /LiveOS/squashfs.img file, which is used by the Anaconda inst.stage2 option. 4.1.3.2.2. Configuring the PXE Server and the Boot Loader Configure the PXE server. See Preparing for a Network Installation in the Red Hat Enterprise Linux Installation Guide . Copy the RHVH boot images to the /tftpboot directory: Create a rhvh label specifying the RHVH boot images in the boot loader configuration: RHVH Boot Loader Configuration Example for Red Hat Satellite If you are using information from Red Hat Satellite to provision the host, you must create a global or host group level parameter called rhvh_image and populate it with the directory URL where the ISO is mounted or extracted: Make the content of the RHVH ISO locally available and export it to the network, for example, using an HTTPD server: 4.1.3.2.3. Creating and Running a Kickstart File Create a Kickstart file and make it available over the network. See Kickstart Installations in the Red Hat Enterprise Linux Installation Guide . Ensure that the Kickstart file meets the following RHV-specific requirements: The %packages section is not required for RHVH. Instead, use the liveimg option and specify the redhat-virtualization-host- version_number _version.squashfs.img file from the RHVH ISO image: Autopartitioning is highly recommended: Note Thin provisioning must be used with autopartitioning. The --no-home option does not work in RHVH because /home is a required directory. If your installation requires manual partitioning, see Section 4.1.3.1, "Custom Partitioning" for a list of limitations that apply to partitions and an example of manual partitioning in a Kickstart file. A %post section that calls the nodectl init command is required: Kickstart Example for Deploying RHVH on Its Own This Kickstart example shows you how to deploy RHVH. You can include additional commands and options as required. Kickstart Example for Deploying RHVH with Registration and Network Configuration from Satellite This Kickstart example uses information from Red Hat Satellite to configure the host network and register the host to the Satellite server. You must create a global or host group level parameter called rhvh_image and populate it with the directory URL to the squashfs.img file. ntp_server1 is also a global or host group level variable. Add the Kickstart file location to the boot loader configuration file on the PXE server: Install RHVH following the instructions in Booting from the Network Using PXE in the Red Hat Enterprise Linux Installation Guide . 4.2. Red Hat Enterprise Linux hosts 4.2.1. Installing Red Hat Enterprise Linux hosts A Red Hat Enterprise Linux host is based on a standard basic installation of Red Hat Enterprise Linux 7 on a physical server, with the Red Hat Enterprise Linux Server and Red Hat Virtualization subscriptions attached. For detailed installation instructions, see the Performing a standard {enterprise-linux-shortname} installation . The host must meet the minimum host requirements . Important Virtualization must be enabled in your host's BIOS settings. For information on changing your host's BIOS settings, refer to your host's hardware documentation. Important Third-party watchdogs should not be installed on Red Hat Enterprise Linux hosts, as they can interfere with the watchdog daemon provided by VDSM. 4.2.2. Enabling the Red Hat Enterprise Linux host Repositories To use a Red Hat Enterprise Linux machine as a host, you must register the system with the Content Delivery Network, attach the Red Hat Enterprise Linux Server and Red Hat Virtualization subscriptions, and enable the host repositories. Procedure Register your system with the Content Delivery Network, entering your Customer Portal user name and password when prompted: Find the Red Hat Enterprise Linux Server and Red Hat Virtualization subscription pools and record the pool IDs: Use the pool IDs to attach the subscriptions to the system: Note To view currently attached subscriptions: To list all enabled repositories: Configure the repositories: For Red Hat Enterprise Linux 7 hosts, little endian, on IBM POWER8 hardware: For Red Hat Enterprise Linux 7 hosts, little endian, on IBM POWER9 hardware: Ensure that all packages currently installed are up to date: Reboot the machine. 4.2.3. Installing Cockpit on Red Hat Enterprise Linux hosts You can install Cockpit for monitoring the host's resources and performing administrative tasks. Procedure Install the dashboard packages: Enable and start the cockpit.socket service: Check if Cockpit is an active service in the firewall: You should see cockpit listed. If it is not, enter the following with root permissions to add cockpit as a service to your firewall: The --permanent option keeps the cockpit service active after rebooting. You can log in to the Cockpit web interface at https:// HostFQDNorIP :9090 . 4.3. Recommended Practices for Configuring Host Networks If your network environment is complex, you may need to configure a host network manually before adding the host to the Red Hat Virtualization Manager. Red Hat recommends the following practices for configuring a host network: Configure the network with Cockpit. Alternatively, you can use nmtui or nmcli . If a network is not required for a self-hosted engine deployment or for adding a host to the Manager, configure the network in the Administration Portal after adding the host to the Manager. See Creating a New Logical Network in a Data Center or Cluster . Use the following naming conventions: VLAN devices: VLAN_NAME_TYPE_RAW_PLUS_VID_NO_PAD VLAN interfaces: physical_device . VLAN_ID (for example, eth0.23 , eth1.128 , enp3s0.50 ) Bond interfaces: bond number (for example, bond0 , bond1 ) VLANs on bond interfaces: bond number . VLAN_ID (for example, bond0.50 , bond1.128 ) Use network bonding . Networking teaming is not supported in Red Hat Virtualization and will cause errors if the host is used to deploy a self-hosted engine or added to the Manager. Use recommended bonding modes: If the ovirtmgmt network is not used by virtual machines, the network may use any supported bonding mode. If the ovirtmgmt network is used by virtual machines, see Which bonding modes work when used with a bridge that virtual machine guests or containers connect to? . Red Hat Virtualization's default bonding mode is (Mode 4) Dynamic Link Aggregation . If your switch does not support Link Aggregation Control Protocol (LACP), use (Mode 1) Active-Backup . See Bonding Modes for details. Configure a VLAN on a physical NIC as in the following example (although nmcli is used, you can use any tool): Configure a VLAN on a bond as in the following example (although nmcli is used, you can use any tool): Do not disable firewalld . Customize the firewall rules in the Administration Portal after adding the host to the Manager. See Configuring Host Firewall Rules . Important When creating a management bridge that uses a static IPv6 address, disable network manager control in its interface configuration (ifcfg) file before adding a host. See https://access.redhat.com/solutions/3981311 for more information. 4.4. Adding Standard Hosts to the Red Hat Virtualization Manager Adding a host to your Red Hat Virtualization environment can take some time, as the following steps are completed by the platform: virtualization checks, installation of packages, and creation of a bridge. Important When creating a management bridge that uses a static IPv6 address, disable network manager control in its interface configuration (ifcfg) file before adding a host. See https://access.redhat.com/solutions/3981311 for more information. Procedure From the Administration Portal, click Compute Hosts . Click New . Use the drop-down list to select the Data Center and Host Cluster for the new host. Enter the Name and the Address of the new host. The standard SSH port, port 22, is auto-filled in the SSH Port field. Select an authentication method to use for the Manager to access the host. Enter the root user's password to use password authentication. Alternatively, copy the key displayed in the SSH PublicKey field to /root/.ssh/authorized_keys on the host to use public key authentication. Optionally, click the Advanced Parameters button to change the following advanced host settings: Disable automatic firewall configuration. Add a host SSH fingerprint to increase security. You can add it manually, or fetch it automatically. Optionally configure power management, where the host has a supported power management card. For information on power management configuration, see Host Power Management Settings Explained in the Administration Guide . Click OK . The new host displays in the list of hosts with a status of Installing , and you can view the progress of the installation in the Events section of the Notification Drawer ( ). After a brief delay the host status changes to Up .	[ "subscription-manager repos --enable=rhel-7-server-rhvh-4-rpms", "rpm -Uvh http://satellite.example.com/pub/katello-ca-consumer-latest.noarch.rpm # subscription-manager register --org=\" org_id \" # subscription-manager list --available # subscription-manager attach --pool= pool_id # subscription-manager repos --disable='' --enable=rhel-7-server-rhvh-4-rpms", "clearpart --all part /boot --fstype xfs --size=1000 --ondisk=sda part pv.01 --size=42000 --grow volgroup HostVG pv.01 --reserved-percent=20 logvol swap --vgname=HostVG --name=swap --fstype=swap --recommended logvol none --vgname=HostVG --name=HostPool --thinpool --size=40000 --grow logvol / --vgname=HostVG --name=root --thin --fstype=ext4 --poolname=HostPool --fsoptions=\"defaults,discard\" --size=6000 --grow logvol /var --vgname=HostVG --name=var --thin --fstype=ext4 --poolname=HostPool --fsoptions=\"defaults,discard\" --size=15000 logvol /var/crash --vgname=HostVG --name=var_crash --thin --fstype=ext4 --poolname=HostPool --fsoptions=\"defaults,discard\" --size=10000 logvol /var/log --vgname=HostVG --name=var_log --thin --fstype=ext4 --poolname=HostPool --fsoptions=\"defaults,discard\" --size=8000 logvol /var/log/audit --vgname=HostVG --name=var_audit --thin --fstype=ext4 --poolname=HostPool --fsoptions=\"defaults,discard\" --size=2000 logvol /home --vgname=HostVG --name=home --thin --fstype=ext4 --poolname=HostPool --fsoptions=\"defaults,discard\" --size=1000 logvol /tmp --vgname=HostVG --name=tmp --thin --fstype=ext4 --poolname=HostPool --fsoptions=\"defaults,discard\" --size=1000", "mount -o loop /path/to/RHVH-ISO /mnt/rhvh cp /mnt/rhvh/Packages/redhat-virtualization-host-image-update /tmp cd /tmp rpm2cpio redhat-virtualization-host-image-update* \| cpio -idmv", "cp mnt/rhvh/images/pxeboot/{vmlinuz,initrd.img} /var/lib/tftpboot/pxelinux/", "LABEL rhvh MENU LABEL Install Red Hat Virtualization Host KERNEL /var/lib/tftpboot/pxelinux/vmlinuz APPEND initrd=/var/lib/tftpboot/pxelinux/initrd.img inst.stage2= URL/to/RHVH-ISO", "<%# kind: PXELinux name: RHVH PXELinux %> Created for booting new hosts # DEFAULT rhvh LABEL rhvh KERNEL <%= @kernel %> APPEND initrd=<%= @initrd %> inst.ks=<%= foreman_url(\"provision\") %> inst.stage2=<%= @host.params[\"rhvh_image\"] %> intel_iommu=on console=tty0 console=ttyS1,115200n8 ssh_pwauth=1 local_boot_trigger=<%= foreman_url(\"built\") %> IPAPPEND 2", "cp -a /mnt/rhvh/ /var/www/html/rhvh-install curl URL/to/RHVH-ISO /rhvh-install", "liveimg --url= example.com /tmp/usr/share/redhat-virtualization-host/image/redhat-virtualization-host- version_number _version.squashfs.img", "autopart --type=thinp", "%post nodectl init %end", "liveimg --url=http:// FQDN /tmp/usr/share/redhat-virtualization-host/image/redhat-virtualization-host- version_number _version.squashfs.img clearpart --all autopart --type=thinp rootpw --plaintext ovirt timezone --utc America/Phoenix zerombr text reboot %post --erroronfail nodectl init %end", "<%# kind: provision name: RHVH Kickstart default oses: - RHVH %> install liveimg --url=<%= @host.params['rhvh_image'] %>squashfs.img network --bootproto static --ip=<%= @host.ip %> --netmask=<%= @host.subnet.mask %> --gateway=<%= @host.subnet.gateway %> --nameserver=<%= @host.subnet.dns_primary %> --hostname <%= @host.name %> zerombr clearpart --all autopart --type=thinp rootpw --iscrypted <%= root_pass %> installation answers lang en_US.UTF-8 timezone <%= @host.params['time-zone'] \|\| 'UTC' %> keyboard us firewall --service=ssh services --enabled=sshd text reboot %post --log=/root/ks.post.log --erroronfail nodectl init <%= snippet 'subscription_manager_registration' %> <%= snippet 'kickstart_networking_setup' %> /usr/sbin/ntpdate -sub <%= @host.params['ntp_server1'] \|\| '0.fedora.pool.ntp.org' %> /usr/sbin/hwclock --systohc /usr/bin/curl <%= foreman_url('built') %> sync systemctl reboot %end", "APPEND initrd=/var/tftpboot/pxelinux/initrd.img inst.stage2= URL/to/RHVH-ISO inst.ks= URL/to/RHVH-ks .cfg", "subscription-manager register", "subscription-manager list --available", "subscription-manager attach --pool= poolid", "subscription-manager list --consumed", "yum repolist", "subscription-manager repos --disable='' --enable=rhel-7-server-rpms --enable=rhel-7-server-rhv-4-mgmt-agent-rpms --enable=rhel-7-server-ansible-2.9-rpms", "subscription-manager repos --disable='' --enable=rhel-7-server-rhv-4-mgmt-agent-for-power-le-rpms --enable=rhel-7-for-power-le-rpms", "subscription-manager repos --disable='*' --enable=rhel-7-server-rhv-4-mgmt-agent-for-power-9-rpms --enable=rhel-7-for-power-9-rpms", "yum update", "yum install cockpit-ovirt-dashboard", "systemctl enable cockpit.socket systemctl start cockpit.socket", "firewall-cmd --list-services", "firewall-cmd --permanent --add-service=cockpit", "nmcli connection add type vlan con-name vlan50 ifname eth0.50 dev eth0 id 50 nmcli con mod vlan50 +ipv4.dns 8.8.8.8 +ipv4.addresses 123.123 .0.1/24 +ivp4.gateway 123.123 .0.254", "nmcli connection add type bond con-name bond0 ifname bond0 bond.options \"mode=active-backup,miimon=100\" ipv4.method disabled ipv6.method ignore nmcli connection add type ethernet con-name eth0 ifname eth0 master bond0 slave-type bond nmcli connection add type ethernet con-name eth1 ifname eth1 master bond0 slave-type bond nmcli connection add type vlan con-name vlan50 ifname bond0.50 dev bond0 id 50 nmcli con mod vlan50 +ipv4.dns 8.8.8.8 +ipv4.addresses 123.123 .0.1/24 +ivp4.gateway 123.123 .0.254" ]	https://docs.redhat.com/en/documentation/red_hat_virtualization/4.3/html/installing_red_hat_virtualization_as_a_standalone_manager_with_remote_databases/installing_hosts_for_rhv_sm_remotedb_deploy
Chapter 10. Managing Ceph OSDs on the dashboard	Chapter 10. Managing Ceph OSDs on the dashboard As a storage administrator, you can monitor and manage OSDs on the Red Hat Ceph Storage Dashboard. Some of the capabilities of the Red Hat Ceph Storage Dashboard are: List OSDs, their status, statistics, information such as attributes, metadata, device health, performance counters and performance details. Mark OSDs down, in, out, lost, purge, reweight, scrub, deep-scrub, destroy, delete, and select profiles to adjust backfilling activity. List all drives associated with an OSD. Set and change the device class of an OSD. Deploy OSDs on new drives and hosts. Prerequisites A running Red Hat Ceph Storage cluster cluster-manager level of access on the Red Hat Ceph Storage dashboard 10.1. Managing the OSDs on the Ceph dashboard You can carry out the following actions on a Ceph OSD on the Red Hat Ceph Storage Dashboard: Create a new OSD. Edit the device class of the OSD. Mark the Flags as No Up , No Down , No In , or No Out . Scrub and deep-scrub the OSDs. Reweight the OSDs. Mark the OSDs Out , In , Down , or Lost . Purge the OSDs. Destroy the OSDs. Delete the OSDs. Prerequisites A running Red Hat Ceph Storage cluster. Dashboard is installed. Hosts, Monitors and Manager Daemons are added to the storage cluster. Procedure Log in to the Dashboard. From the Cluster drop-down menu, select OSDs . Creating an OSD To create the OSD, click Create . Figure 10.1. Add device for OSDs Note Ensure you have an available host and a few available devices. You can check for available devices in Physical Disks under the Cluster drop-down menu. In the Create OSDs window, from Deployment Options, select one of the below options: Cost/Capacity-optimized : The cluster gets deployed with all available HDDs. Throughput-optimized : Slower devices are used to store data and faster devices are used to store journals/WALs. IOPS-optmized : All the available NVMEs are used to deploy OSDs. From the Advanced Mode, you can add primary, WAL and DB devices by clicking +Add . Primary devices : Primary storage devices contain all OSD data. WAL devices : Write-Ahead-Log devices are used for BlueStore's internal journal and are used only if the WAL device is faster than the primary device. For example, NVMEs or SSDs. DB devices : DB devices are used to store BlueStore's internal metadata and are used only if the DB device is faster than the primary device. For example, NVMEs or SSDs ). If you want to encrypt your data for security purposes, under Features , select encryption . Click the Preview button and in the OSD Creation Preview dialog box, Click Create . In the OSD Creation Preview dialog box, Click Create . You get a notification that the OSD was created successfully. The OSD status changes from in and down to in and up . Editing an OSD To edit an OSD, select the row. From Edit drop-down menu, select Edit . Edit the device class. Click Edit OSD . Figure 10.2. Edit an OSD You get a notification that the OSD was updated successfully. Marking the Flags of OSDs To mark the flag of the OSD, select the row. From Edit drop-down menu, select Flags . Mark the Flags with No Up , No Down , No In , or No Out . Click Update . Figure 10.3. Marking Flags of an OSD You get a notification that the flags of the OSD was updated successfully. Scrubbing the OSDs To scrub the OSD, select the row. From Edit drop-down menu, select Scrub . In the OSDs Scrub dialog box, click Update . Figure 10.4. Scrubbing an OSD You get a notification that the scrubbing of the OSD was initiated successfully. Deep-scrubbing the OSDs To deep-scrub the OSD, select the row. From Edit drop-down menu, select Deep scrub . In the OSDs Deep Scrub dialog box, click Update . Figure 10.5. Deep-scrubbing an OSD You get a notification that the deep scrubbing of the OSD was initiated successfully. Reweighting the OSDs To reweight the OSD, select the row. From Edit drop-down menu, select Reweight . In the Reweight OSD dialog box, enter a value between zero and one. Click Reweight . Figure 10.6. Reweighting an OSD Marking OSDs Out To mark the OSD out, select the row. From Edit drop-down menu, select Mark Out . In the Mark OSD out dialog box, click Mark Out . Figure 10.7. Marking OSDs out The status of the OSD will change to out . Marking OSDs In To mark the OSD in, select the OSD row that is in out status. From Edit drop-down menu, select Mark In . In the Mark OSD in dialog box, click Mark In . Figure 10.8. Marking OSDs in The status of the OSD will change to in . Marking OSDs Down To mark the OSD down, select the row. From Edit drop-down menu, select Mark Down . In the Mark OSD down dialog box, click Mark Down . Figure 10.9. Marking OSDs down The status of the OSD will change to down . Marking OSDs Lost To mark the OSD lost, select the OSD in out and down status. From Edit drop-down menu, select Mark Lost . In the Mark OSD Lost dialog box, check Yes, I am sure option, and click Mark Lost . Figure 10.10. Marking OSDs Lost Purging OSDs To purge the OSD, select the OSD in down status. From Edit drop-down menu, select Purge . In the Purge OSDs dialog box, check Yes, I am sure option, and click Purge OSD . Figure 10.11. Purging OSDs All the flags are reset and the OSD is back in in and up status. Destroying OSDs To destroy the OSD, select the OSD in down status. From Edit drop-down menu, select Destroy . In the Destroy OSDs dialog box, check Yes, I am sure option, and click Destroy OSD . Figure 10.12. Destroying OSDs The status of the OSD changes to destroyed . Deleting OSDs To delete the OSD, select the OSD in down status. From Edit drop-down menu, select Delete . In the Destroy OSDs dialog box, check Yes, I am sure option, and click Delete OSD . Note You can preserve the OSD_ID when you have to to replace the failed OSD. Figure 10.13. Deleting OSDs 10.2. Replacing the failed OSDs on the Ceph dashboard You can replace the failed OSDs in a Red Hat Ceph Storage cluster with the cluster-manager level of access on the dashboard. One of the highlights of this feature on the dashboard is that the OSD IDs can be preserved while replacing the failed OSDs. Prerequisites A running Red Hat Ceph Storage cluster. At least cluster-manager level of access to the Ceph Dashboard. At least one of the OSDs is down Procedure On the dashboard, you can identify the failed OSDs in the following ways: Dashboard AlertManager pop-up notifications. Dashboard landing page showing HEALTH_WARN status. Dashboard landing page showing failed OSDs. Dashboard OSD page showing failed OSDs. In this example, you can see that one of the OSDs is down on the landing page of the dashboard. Apart from this, on the physical drive, you can view the LED lights blinking if one of the OSDs is down. Click OSDs . Select the out and down OSD: From the Edit drop-down menu, select Flags and select No Up and click Update . From the Edit drop-down menu, select Delete . In the Delete OSD dialog box, select the Preserve OSD ID(s) for replacement and Yes, I am sure check boxes. Click Delete OSD . Wait till the status of the OSD changes to out and destroyed status. Optional: If you want to change the No Up Flag for the entire cluster, in the Cluster-wide configuration drop-down menu, select Flags . In Cluster-wide OSDs Flags dialog box, select No Up and click Update. Optional: If the OSDs are down due to a hard disk failure, replace the physical drive: If the drive is hot-swappable, replace the failed drive with a new one. If the drive is not hot-swappable and the host contains multiple OSDs, you might have to shut down the whole host and replace the physical drive. Consider preventing the cluster from backfilling. See the Stopping and Starting Rebalancing chapter in the Red Hat Ceph Storage Troubleshooting Guide for details. When the drive appears under the /dev/ directory, make a note of the drive path. If you want to add the OSD manually, find the OSD drive and format the disk. If the new disk has data, zap the disk: Syntax Example From the Create drop-down menu, select Create . In the Create OSDs window, click +Add for Primary devices. In the Primary devices dialog box, from the Hostname drop-down list, select any one filter. From Any drop-down list, select the respective option. Note You have to select the Hostname first and then at least one filter to add the devices. For example, from Hostname list, select Type and from Any list select hdd . Select Vendor and from Any list, select ATA Click Add . In the Create OSDs window , click the Preview button. In the OSD Creation Preview dialog box, Click Create . You will get a notification that the OSD is created. The OSD will be in out and down status. Select the newly created OSD that has out and down status. In the Edit drop-down menu, select Mark-in . In the Mark OSD in window, select Mark in . In the Edit drop-down menu, select Flags . Uncheck No Up and click Update . Optional: If you have changed the No Up Flag before for cluster-wide configuration, in the Cluster-wide configuration menu, select Flags . In Cluster-wide OSDs Flags dialog box, uncheck No Up and click Update . Verification Verify that the OSD that was destroyed is created on the device and the OSD ID is preserved. Additional Resources For more information on Down OSDs, see the Down OSDs section in the Red Hat Ceph Storage Troubleshooting Guide . For additional assistance see the Red Hat Support for service section in the Red Hat Ceph Storage Troubleshooting Guide . For more information on system roles, see the Managing roles on the Ceph dashboard section in the Red Hat Ceph Storage Dashboard Guide .	[ "ceph orch device zap HOST_NAME PATH --force", "ceph orch device zap ceph-adm2 /dev/sdc --force" ]	https://docs.redhat.com/en/documentation/red_hat_ceph_storage/6/html/dashboard_guide/management-of-ceph-osds-on-the-dashboard
8.55. glusterfs	8.55. glusterfs 8.55.1. RHBA-2013:1641 - glusterfs bug fix and enhancement update Updated glusterfs packages that fix several bugs and add one enhancement are now available for Red Hat Enterprise Linux 6. Red Hat Storage is software only, scale-out storage that provides flexible and affordable unstructured data storage for the enterprise. GlusterFS, a key building block of Red Hat Storage, is based on a stackable user-space design and can deliver exceptional performance for diverse workloads. GlusterFS aggregates various storage servers over network interconnects into one large, parallel network file system. Bug Fixes BZ# 998778 Previously, the "errno" value was not set correctly during an API failure. Consequently, applications using API could behave unpredictably. With this update, the value is set properly during API failures and the applications work as expected. BZ# 998832 Previously, the glusterfs-api library handled all signals that were sent to applications using glusterfs-api. As a consequence, glusterfs-api interpreted incorrectly all the the signals that were not used by this library. With this update, glusterfs-api no longer handles the signals that it does not use so that such signals are now interpreted properly. BZ# 1017014 Previously, the glfs_fini() function did not return NULL, even if the libgfapi library successfully cleaned up all resources. Consequently, an attempt to use the "qemu-img create" command, which used libgfapi, failed. The underlying source code has been modified so that the function returns NULL when the libgfapi cleanup is successful, and the command now works as expected. Enhancement BZ# 916645 Native Support for GlusterFS in QEMU has been included to glusterfs packages. This support allows native access to GlusterFS volumes using the libgfapi library instead of through a locally mounted FUSE file system. This native approach offers considerable performance improvements. Users of glusterfs are advised to upgrade to these updated packages, which fix these bugs and add this enhancement.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.5_technical_notes/glusterfs
Making open source more inclusive	Making open source more inclusive Red Hat is committed to replacing problematic language in our code, documentation, and web properties. We are beginning with these four terms: master, slave, blacklist, and whitelist. Because of the enormity of this endeavor, these changes will be implemented gradually over several upcoming releases. For more details, see our CTO Chris Wright's message .	null	https://docs.redhat.com/en/documentation/red_hat_data_grid/8.5/html/data_grid_cross-site_replication/making-open-source-more-inclusive_datagrid
Chapter 6. Managing applications with MTA	Chapter 6. Managing applications with MTA You can use the Migration Toolkit for Applications (MTA) user interface to perform the following tasks: Add applications Assign application credentials Import a list of applications Download a CSV template for importing application lists Create application migration waves Create Jira issues for migration waves MTA user interface applications have the following attributes: Name (free text) Description (optional, free text) Business service (optional, chosen from a list) Tags (optional, chosen from a list) Owner (optional, chosen from a list) Contributors (optional, chosen from a list) Source code (a path entered by the user) Binary (a path entered by the user) 6.1. Adding a new application You can add a new application to the Application Inventory for subsequent assessment and analysis. Tip Before creating an application, set up business services, check tags and tag categories, and create additions as needed. Prerequisites You are logged in to an MTA server. Procedure In the Migration view, click Application Inventory . Click Create new . Under Basic information , enter the following fields: Name : A unique name for the new application. Description : A short description of the application (optional). Business service : A purpose of the application (optional). Manual tags : Software tags that characterize the application (optional, one or more). Owner : A registered software owner from the drop-down list (optional). Contributors : Contributors from the drop-down list (optional, one or more). Comments : Relevant comments on the application (optional). Click Source Code and enter the following fields: Repository type : Git or Subversion . Source repository : A URL of the repository where the software code is saved. For Subversion: this must be either the URL to the root of the repository or a fully qualified URL which (optionally) includes the branch and nested directory. When fully qualified, the Branch and Root path must be blank. Branch : An application code branch in the repository (optional). For Git: this may be any reference; commit-hash , branch or tag . For Subversion: this may be a fully qualified path to a branch or tag, for example, branches/stable or tags/stable . This must be blank when the Source repository URL includes the branch. Root path : A root path inside the repository for the target application (optional). For Subversion: this must be blank when the Source Repository URL includes the root path. NOTE: If you enter any value in either the Branch or Root path fields, the Source repository field becomes mandatory. Optional: Click Binary and enter the following fields: Group : The Maven group for the application artifact. Artifact : The Maven artifact for the application. Version : A software version of the application. Packaging : The packaging for the application artifact, for example, JAR , WAR , or EAR . NOTE: If you enter any value in any of the Binary section fields, all fields automatically become mandatory. Click Create . The new application appears in the list of defined applications. Automated Tasks After adding a new application to the Application Inventory , you can set your cursor to hover over the application name to see the automated tasks spawned by adding the application. The language discovery task identifies the programming languages in the application. The technology discovery task identifies specific technologies in the application. The tasks automatically add appropriate tags to the application, reducing the effort involved in manually assigning tags to the application. After these tasks are complete, the number of tags added to the application will appear under the Tags column. To view the tags: Click on the application's row entry. A side pane opens. Click the Tags tab. The tags attached to the application are displayed. You can add additional tags manually as needed. When MTA analyzes the application, it can add additional tags to the application automatically. 6.2. Editing an application You can edit an existing application in the Application Inventory and re-run an assessment or analysis for this application. Prerequisites You are logged in to an MTA server. Procedure In the Migration view, click Application Inventory . Select the Migration working mode. Click Application Inventory in the left menu bar. A list of available applications appears in the main pane. Click Edit ( ) to open the application settings. Review the application settings. For a list of application settings, see Adding an application . If you changed any application settings, click Save . Note After editing an application, MTA re-spawns the language discovery and technology discovery tasks. 6.3. Assigning credentials to an application You can assign credentials to one or more applications. Procedure In the Migration view, click Application inventory . Click the Options menu ( ) to the right of Analyze and select Manage credentials . Select one credential from the Source credentials list and from the Maven settings list. Click Save . 6.4. Importing a list of applications You can import a .csv file that contains a list of applications and their attributes to the Migration Toolkit for Applications (MTA) user interface. Note Importing a list of applications does not overwrite any of the existing applications. Procedure Review the import file to ensure it contains all the required information in the required format. In the Migration view, click Application Inventory . Click the Options menu ( ). Click Import . Select the desired file and click Open . Optional: Select Enable automatic creation of missing entities . This option is selected by default. Verify that the import has completed and check the number of accepted or rejected rows. Review the imported applications by clicking the arrow to the left of the checkbox. Important Accepted rows might not match the number of applications in the Application inventory list because some rows are dependencies. To verify, check the Record Type column of the CSV file for applications defined as 1 and dependencies defined as 2 . 6.5. Downloading a CSV template You can download a CSV template for importing application lists by using the Migration Toolkit for Applications (MTA) user interface. Procedure In the Migration view, click Application inventory . Click the Options menu ( ) to the right of Review . Click Manage imports to open the Application imports page. Click the Options menu ( ) to the right of Import . Click Download CSV template . 6.6. Creating a migration wave A migration wave is a group applications that you can migrate on a given schedule. You can track each migration by exporting a list of the wave's applications to the Jira issue management system. This automatically creates a separate Jira issue for each application of the migration wave. Procedure In the Migration view, click Migration waves . Click Create new . The New migration wave window opens. Enter the following information: Name (optional). If the name is not given, you can use the start and end dates to identify migration waves. Potential start date . This date must be later than the current date. Potential end date . This date must be later than the start date. Stakeholders (optional) Stakeholder groups (optional) Click Create . The new migration wave appears in the list of existing migration waves. To assign applications to the migration wave, click the Options menu ( ) to the right of the migration wave and select Manage applications . The Manage applications window opens that displays the list of applications that are not assigned to any other migration wave. Select the checkboxes of the applications that you want to assign to the migration wave. Click Save . Note The owner and the contributors of each application associated with the migration wave are automatically added to the migration wave's list of stakeholders. Optional: To update a migration wave, select Update from the migration wave's Options menu ( ). The Update migration wave window opens. 6.7. Creating Jira issues for a migration wave You can use a migration wave to create Jira issues automatically for each application assigned to the migration wave. A separate Jira issue is created for each application associated with the migration wave. The following fields of each issue are filled in automatically: Title: Migrate <application name> Reporter: Username of the token owner. Description: Created by Konveyor Note You cannot delete an application if it is linked to a Jira ticket or is associated with a migration wave. To unlink the application from the Jira ticket, click the Unlink from Jira icon in the details view of the application or in the details view of a migration wave. Prerequisites You configured Jira connection. For more information, see Creating and configuring a Jira connection . Procedure In the Migration view, click Migration waves . Click the Options menu ( ) to the right of the migration wave for which you want to create Jira issues and select Export to Issue Manager . The Export to Issue Manager window opens. Select the Jira Cloud or Jira Server/Datacenter instance type. Select the instance, project, and issue type from the lists. Click Export . The status of the migration wave on the Migration waves page changes to Issues Created . Optional: To see the status of each individual application of a migration wave, click the Status column. Optional: To see if any particular application is associated with a migration wave, open the application's Details tab on the Application inventory page.	null	https://docs.redhat.com/en/documentation/migration_toolkit_for_applications/7.2/html/user_interface_guide/working-with-applications-in-the-ui
Chapter 4. Controlling pod placement onto nodes (scheduling)	Chapter 4. Controlling pod placement onto nodes (scheduling) 4.1. Controlling pod placement using the scheduler Pod scheduling is an internal process that determines placement of new pods onto nodes within the cluster. The scheduler code has a clean separation that watches new pods as they get created and identifies the most suitable node to host them. It then creates bindings (pod to node bindings) for the pods using the master API. Default pod scheduling OpenShift Container Platform comes with a default scheduler that serves the needs of most users. The default scheduler uses both inherent and customization tools to determine the best fit for a pod. Advanced pod scheduling In situations where you might want more control over where new pods are placed, the OpenShift Container Platform advanced scheduling features allow you to configure a pod so that the pod is required or has a preference to run on a particular node or alongside a specific pod. You can control pod placement by using the following scheduling features: Scheduler profiles Pod affinity and anti-affinity rules Node affinity Node selectors Taints and tolerations Node overcommitment 4.1.1. About the default scheduler The default OpenShift Container Platform pod scheduler is responsible for determining the placement of new pods onto nodes within the cluster. It reads data from the pod and finds a node that is a good fit based on configured profiles. It is completely independent and exists as a standalone solution. It does not modify the pod; it creates a binding for the pod that ties the pod to the particular node. 4.1.1.1. Understanding default scheduling The existing generic scheduler is the default platform-provided scheduler engine that selects a node to host the pod in a three-step operation: Filters the nodes The available nodes are filtered based on the constraints or requirements specified. This is done by running each node through the list of filter functions called predicates , or filters . Prioritizes the filtered list of nodes This is achieved by passing each node through a series of priority , or scoring , functions that assign it a score between 0 - 10, with 0 indicating a bad fit and 10 indicating a good fit to host the pod. The scheduler configuration can also take in a simple weight (positive numeric value) for each scoring function. The node score provided by each scoring function is multiplied by the weight (default weight for most scores is 1) and then combined by adding the scores for each node provided by all the scores. This weight attribute can be used by administrators to give higher importance to some scores. Selects the best fit node The nodes are sorted based on their scores and the node with the highest score is selected to host the pod. If multiple nodes have the same high score, then one of them is selected at random. 4.1.2. Scheduler use cases One of the important use cases for scheduling within OpenShift Container Platform is to support flexible affinity and anti-affinity policies. 4.1.2.1. Infrastructure topological levels Administrators can define multiple topological levels for their infrastructure (nodes) by specifying labels on nodes. For example: region=r1 , zone=z1 , rack=s1 . These label names have no particular meaning and administrators are free to name their infrastructure levels anything, such as city/building/room. Also, administrators can define any number of levels for their infrastructure topology, with three levels usually being adequate (such as: regions zones racks ). Administrators can specify affinity and anti-affinity rules at each of these levels in any combination. 4.1.2.2. Affinity Administrators should be able to configure the scheduler to specify affinity at any topological level, or even at multiple levels. Affinity at a particular level indicates that all pods that belong to the same service are scheduled onto nodes that belong to the same level. This handles any latency requirements of applications by allowing administrators to ensure that peer pods do not end up being too geographically separated. If no node is available within the same affinity group to host the pod, then the pod is not scheduled. If you need greater control over where the pods are scheduled, see Controlling pod placement on nodes using node affinity rules and Placing pods relative to other pods using affinity and anti-affinity rules . These advanced scheduling features allow administrators to specify which node a pod can be scheduled on and to force or reject scheduling relative to other pods. 4.1.2.3. Anti-affinity Administrators should be able to configure the scheduler to specify anti-affinity at any topological level, or even at multiple levels. Anti-affinity (or 'spread') at a particular level indicates that all pods that belong to the same service are spread across nodes that belong to that level. This ensures that the application is well spread for high availability purposes. The scheduler tries to balance the service pods across all applicable nodes as evenly as possible. If you need greater control over where the pods are scheduled, see Controlling pod placement on nodes using node affinity rules and Placing pods relative to other pods using affinity and anti-affinity rules . These advanced scheduling features allow administrators to specify which node a pod can be scheduled on and to force or reject scheduling relative to other pods. 4.2. Scheduling pods using a scheduler profile You can configure OpenShift Container Platform to use a scheduling profile to schedule pods onto nodes within the cluster. 4.2.1. About scheduler profiles You can specify a scheduler profile to control how pods are scheduled onto nodes. The following scheduler profiles are available: LowNodeUtilization This profile attempts to spread pods evenly across nodes to get low resource usage per node. This profile provides the default scheduler behavior. HighNodeUtilization This profile attempts to place as many pods as possible on to as few nodes as possible. This minimizes node count and has high resource usage per node. Note Switching to the HighNodeUtilization scheduler profile will result in all pods of a ReplicaSet object being scheduled on the same node. This will add an increased risk for pod failure if the node fails. NoScoring This is a low-latency profile that strives for the quickest scheduling cycle by disabling all score plugins. This might sacrifice better scheduling decisions for faster ones. 4.2.2. Configuring a scheduler profile You can configure the scheduler to use a scheduler profile. Prerequisites Access to the cluster as a user with the cluster-admin role. Procedure Edit the Scheduler object: USD oc edit scheduler cluster Specify the profile to use in the spec.profile field: apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster #... spec: mastersSchedulable: false profile: HighNodeUtilization 1 #... 1 Set to LowNodeUtilization , HighNodeUtilization , or NoScoring . Save the file to apply the changes. 4.3. Placing pods relative to other pods using affinity and anti-affinity rules Affinity is a property of pods that controls the nodes on which they prefer to be scheduled. Anti-affinity is a property of pods that prevents a pod from being scheduled on a node. In OpenShift Container Platform, pod affinity and pod anti-affinity allow you to constrain which nodes your pod is eligible to be scheduled on based on the key-value labels on other pods. 4.3.1. Understanding pod affinity Pod affinity and pod anti-affinity allow you to constrain which nodes your pod is eligible to be scheduled on based on the key/value labels on other pods. Pod affinity can tell the scheduler to locate a new pod on the same node as other pods if the label selector on the new pod matches the label on the current pod. Pod anti-affinity can prevent the scheduler from locating a new pod on the same node as pods with the same labels if the label selector on the new pod matches the label on the current pod. For example, using affinity rules, you could spread or pack pods within a service or relative to pods in other services. Anti-affinity rules allow you to prevent pods of a particular service from scheduling on the same nodes as pods of another service that are known to interfere with the performance of the pods of the first service. Or, you could spread the pods of a service across nodes, availability zones, or availability sets to reduce correlated failures. Note A label selector might match pods with multiple pod deployments. Use unique combinations of labels when configuring anti-affinity rules to avoid matching pods. There are two types of pod affinity rules: required and preferred . Required rules must be met before a pod can be scheduled on a node. Preferred rules specify that, if the rule is met, the scheduler tries to enforce the rules, but does not guarantee enforcement. Note Depending on your pod priority and preemption settings, the scheduler might not be able to find an appropriate node for a pod without violating affinity requirements. If so, a pod might not be scheduled. To prevent this situation, carefully configure pod affinity with equal-priority pods. You configure pod affinity/anti-affinity through the Pod spec files. You can specify a required rule, a preferred rule, or both. If you specify both, the node must first meet the required rule, then attempts to meet the preferred rule. The following example shows a Pod spec configured for pod affinity and anti-affinity. In this example, the pod affinity rule indicates that the pod can schedule onto a node only if that node has at least one already-running pod with a label that has the key security and value S1 . The pod anti-affinity rule says that the pod prefers to not schedule onto a node if that node is already running a pod with label having key security and value S2 . Sample Pod config file with pod affinity apiVersion: v1 kind: Pod metadata: name: with-pod-affinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: 2 - labelSelector: matchExpressions: - key: security 3 operator: In 4 values: - S1 5 topologyKey: topology.kubernetes.io/zone containers: - name: with-pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] 1 Stanza to configure pod affinity. 2 Defines a required rule. 3 5 The key and value (label) that must be matched to apply the rule. 4 The operator represents the relationship between the label on the existing pod and the set of values in the matchExpression parameters in the specification for the new pod. Can be In , NotIn , Exists , or DoesNotExist . Sample Pod config file with pod anti-affinity apiVersion: v1 kind: Pod metadata: name: with-pod-antiaffinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAntiAffinity: 1 preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 100 3 podAffinityTerm: labelSelector: matchExpressions: - key: security 4 operator: In 5 values: - S2 topologyKey: kubernetes.io/hostname containers: - name: with-pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] 1 Stanza to configure pod anti-affinity. 2 Defines a preferred rule. 3 Specifies a weight for a preferred rule. The node with the highest weight is preferred. 4 Description of the pod label that determines when the anti-affinity rule applies. Specify a key and value for the label. 5 The operator represents the relationship between the label on the existing pod and the set of values in the matchExpression parameters in the specification for the new pod. Can be In , NotIn , Exists , or DoesNotExist . Note If labels on a node change at runtime such that the affinity rules on a pod are no longer met, the pod continues to run on the node. 4.3.2. Configuring a pod affinity rule The following steps demonstrate a simple two-pod configuration that creates pod with a label and a pod that uses affinity to allow scheduling with that pod. Note You cannot add an affinity directly to a scheduled pod. Procedure Create a pod with a specific label in the pod spec: Create a YAML file with the following content: apiVersion: v1 kind: Pod metadata: name: security-s1 labels: security: S1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: security-s1 image: docker.io/ocpqe/hello-pod securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault Create the pod. USD oc create -f <pod-spec>.yaml When creating other pods, configure the following parameters to add the affinity: Create a YAML file with the following content: apiVersion: v1 kind: Pod metadata: name: security-s1-east # ... spec: affinity: 1 podAffinity: requiredDuringSchedulingIgnoredDuringExecution: 2 - labelSelector: matchExpressions: - key: security 3 values: - S1 operator: In 4 topologyKey: topology.kubernetes.io/zone 5 # ... 1 Adds a pod affinity. 2 Configures the requiredDuringSchedulingIgnoredDuringExecution parameter or the preferredDuringSchedulingIgnoredDuringExecution parameter. 3 Specifies the key and values that must be met. If you want the new pod to be scheduled with the other pod, use the same key and values parameters as the label on the first pod. 4 Specifies an operator . The operator can be In , NotIn , Exists , or DoesNotExist . For example, use the operator In to require the label to be in the node. 5 Specify a topologyKey , which is a prepopulated Kubernetes label that the system uses to denote such a topology domain. Create the pod. USD oc create -f <pod-spec>.yaml 4.3.3. Configuring a pod anti-affinity rule The following steps demonstrate a simple two-pod configuration that creates pod with a label and a pod that uses an anti-affinity preferred rule to attempt to prevent scheduling with that pod. Note You cannot add an affinity directly to a scheduled pod. Procedure Create a pod with a specific label in the pod spec: Create a YAML file with the following content: apiVersion: v1 kind: Pod metadata: name: security-s1 labels: security: S1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: security-s1 image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] Create the pod. USD oc create -f <pod-spec>.yaml When creating other pods, configure the following parameters: Create a YAML file with the following content: apiVersion: v1 kind: Pod metadata: name: security-s2-east # ... spec: # ... affinity: 1 podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 100 3 podAffinityTerm: labelSelector: matchExpressions: - key: security 4 values: - S1 operator: In 5 topologyKey: kubernetes.io/hostname 6 # ... 1 Adds a pod anti-affinity. 2 Configures the requiredDuringSchedulingIgnoredDuringExecution parameter or the preferredDuringSchedulingIgnoredDuringExecution parameter. 3 For a preferred rule, specifies a weight for the node, 1-100. The node that with highest weight is preferred. 4 Specifies the key and values that must be met. If you want the new pod to not be scheduled with the other pod, use the same key and values parameters as the label on the first pod. 5 Specifies an operator . The operator can be In , NotIn , Exists , or DoesNotExist . For example, use the operator In to require the label to be in the node. 6 Specifies a topologyKey , which is a prepopulated Kubernetes label that the system uses to denote such a topology domain. Create the pod. USD oc create -f <pod-spec>.yaml 4.3.4. Sample pod affinity and anti-affinity rules The following examples demonstrate pod affinity and pod anti-affinity. 4.3.4.1. Pod Affinity The following example demonstrates pod affinity for pods with matching labels and label selectors. The pod team4 has the label team:4 . apiVersion: v1 kind: Pod metadata: name: team4 labels: team: "4" # ... spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: ocp image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... The pod team4a has the label selector team:4 under podAffinity . apiVersion: v1 kind: Pod metadata: name: team4a # ... spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: team operator: In values: - "4" topologyKey: kubernetes.io/hostname containers: - name: pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... The team4a pod is scheduled on the same node as the team4 pod. 4.3.4.2. Pod Anti-affinity The following example demonstrates pod anti-affinity for pods with matching labels and label selectors. The pod pod-s1 has the label security:s1 . apiVersion: v1 kind: Pod metadata: name: pod-s1 labels: security: s1 # ... spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: ocp image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... The pod pod-s2 has the label selector security:s1 under podAntiAffinity . apiVersion: v1 kind: Pod metadata: name: pod-s2 # ... spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAntiAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: security operator: In values: - s1 topologyKey: kubernetes.io/hostname containers: - name: pod-antiaffinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... The pod pod-s2 cannot be scheduled on the same node as pod-s1 . 4.3.4.3. Pod Affinity with no Matching Labels The following example demonstrates pod affinity for pods without matching labels and label selectors. The pod pod-s1 has the label security:s1 . apiVersion: v1 kind: Pod metadata: name: pod-s1 labels: security: s1 # ... spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: ocp image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... The pod pod-s2 has the label selector security:s2 . apiVersion: v1 kind: Pod metadata: name: pod-s2 # ... spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: security operator: In values: - s2 topologyKey: kubernetes.io/hostname containers: - name: pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... The pod pod-s2 is not scheduled unless there is a node with a pod that has the security:s2 label. If there is no other pod with that label, the new pod remains in a pending state: Example output NAME READY STATUS RESTARTS AGE IP NODE pod-s2 0/1 Pending 0 32s <none> 4.3.5. Using pod affinity and anti-affinity to control where an Operator is installed By default, when you install an Operator, OpenShift Container Platform installs the Operator pod to one of your worker nodes randomly. However, there might be situations where you want that pod scheduled on a specific node or set of nodes. The following examples describe situations where you might want to schedule an Operator pod to a specific node or set of nodes: If an Operator requires a particular platform, such as amd64 or arm64 If an Operator requires a particular operating system, such as Linux or Windows If you want Operators that work together scheduled on the same host or on hosts located on the same rack If you want Operators dispersed throughout the infrastructure to avoid downtime due to network or hardware issues You can control where an Operator pod is installed by adding a pod affinity or anti-affinity to the Operator's Subscription object. The following example shows how to use pod anti-affinity to prevent the installation the Custom Metrics Autoscaler Operator from any node that has pods with a specific label: Pod affinity example that places the Operator pod on one or more specific nodes apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: podAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: app operator: In values: - test topologyKey: kubernetes.io/hostname #... 1 A pod affinity that places the Operator's pod on a node that has pods with the app=test label. Pod anti-affinity example that prevents the Operator pod from one or more specific nodes apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: podAntiAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: cpu operator: In values: - high topologyKey: kubernetes.io/hostname #... 1 A pod anti-affinity that prevents the Operator's pod from being scheduled on a node that has pods with the cpu=high label. Procedure To control the placement of an Operator pod, complete the following steps: Install the Operator as usual. If needed, ensure that your nodes are labeled to properly respond to the affinity. Edit the Operator Subscription object to add an affinity: apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: podAntiAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: podAffinityTerm: labelSelector: matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-185-229.ec2.internal topologyKey: topology.kubernetes.io/zone #... 1 Add a podAffinity or podAntiAffinity . Verification To ensure that the pod is deployed on the specific node, run the following command: USD oc get pods -o wide Example output NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES custom-metrics-autoscaler-operator-5dcc45d656-bhshg 1/1 Running 0 50s 10.131.0.20 ip-10-0-185-229.ec2.internal <none> <none> 4.4. Controlling pod placement on nodes using node affinity rules Affinity is a property of pods that controls the nodes on which they prefer to be scheduled. In OpenShift Container Platform node affinity is a set of rules used by the scheduler to determine where a pod can be placed. The rules are defined using custom labels on the nodes and label selectors specified in pods. 4.4.1. Understanding node affinity Node affinity allows a pod to specify an affinity towards a group of nodes it can be placed on. The node does not have control over the placement. For example, you could configure a pod to only run on a node with a specific CPU or in a specific availability zone. There are two types of node affinity rules: required and preferred . Required rules must be met before a pod can be scheduled on a node. Preferred rules specify that, if the rule is met, the scheduler tries to enforce the rules, but does not guarantee enforcement. Note If labels on a node change at runtime that results in an node affinity rule on a pod no longer being met, the pod continues to run on the node. You configure node affinity through the Pod spec file. You can specify a required rule, a preferred rule, or both. If you specify both, the node must first meet the required rule, then attempts to meet the preferred rule. The following example is a Pod spec with a rule that requires the pod be placed on a node with a label whose key is e2e-az-NorthSouth and whose value is either e2e-az-North or e2e-az-South : Example pod configuration file with a node affinity required rule apiVersion: v1 kind: Pod metadata: name: with-node-affinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: nodeAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: 2 nodeSelectorTerms: - matchExpressions: - key: e2e-az-NorthSouth 3 operator: In 4 values: - e2e-az-North 5 - e2e-az-South 6 containers: - name: with-node-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... 1 The stanza to configure node affinity. 2 Defines a required rule. 3 5 6 The key/value pair (label) that must be matched to apply the rule. 4 The operator represents the relationship between the label on the node and the set of values in the matchExpression parameters in the Pod spec. This value can be In , NotIn , Exists , or DoesNotExist , Lt , or Gt . The following example is a node specification with a preferred rule that a node with a label whose key is e2e-az-EastWest and whose value is either e2e-az-East or e2e-az-West is preferred for the pod: Example pod configuration file with a node affinity preferred rule apiVersion: v1 kind: Pod metadata: name: with-node-affinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: nodeAffinity: 1 preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 1 3 preference: matchExpressions: - key: e2e-az-EastWest 4 operator: In 5 values: - e2e-az-East 6 - e2e-az-West 7 containers: - name: with-node-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] # ... 1 The stanza to configure node affinity. 2 Defines a preferred rule. 3 Specifies a weight for a preferred rule. The node with highest weight is preferred. 4 6 7 The key/value pair (label) that must be matched to apply the rule. 5 The operator represents the relationship between the label on the node and the set of values in the matchExpression parameters in the Pod spec. This value can be In , NotIn , Exists , or DoesNotExist , Lt , or Gt . There is no explicit node anti-affinity concept, but using the NotIn or DoesNotExist operator replicates that behavior. Note If you are using node affinity and node selectors in the same pod configuration, note the following: If you configure both nodeSelector and nodeAffinity , both conditions must be satisfied for the pod to be scheduled onto a candidate node. If you specify multiple nodeSelectorTerms associated with nodeAffinity types, then the pod can be scheduled onto a node if one of the nodeSelectorTerms is satisfied. If you specify multiple matchExpressions associated with nodeSelectorTerms , then the pod can be scheduled onto a node only if all matchExpressions are satisfied. 4.4.2. Configuring a required node affinity rule Required rules must be met before a pod can be scheduled on a node. Procedure The following steps demonstrate a simple configuration that creates a node and a pod that the scheduler is required to place on the node. Add a label to a node using the oc label node command: USD oc label node node1 e2e-az-name=e2e-az1 Tip You can alternatively apply the following YAML to add the label: kind: Node apiVersion: v1 metadata: name: <node_name> labels: e2e-az-name: e2e-az1 #... Create a pod with a specific label in the pod spec: Create a YAML file with the following content: Note You cannot add an affinity directly to a scheduled pod. Example output apiVersion: v1 kind: Pod metadata: name: s1 spec: affinity: 1 nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: 2 nodeSelectorTerms: - matchExpressions: - key: e2e-az-name 3 values: - e2e-az1 - e2e-az2 operator: In 4 #... 1 Adds a pod affinity. 2 Configures the requiredDuringSchedulingIgnoredDuringExecution parameter. 3 Specifies the key and values that must be met. If you want the new pod to be scheduled on the node you edited, use the same key and values parameters as the label in the node. 4 Specifies an operator . The operator can be In , NotIn , Exists , or DoesNotExist . For example, use the operator In to require the label to be in the node. Create the pod: USD oc create -f <file-name>.yaml 4.4.3. Configuring a preferred node affinity rule Preferred rules specify that, if the rule is met, the scheduler tries to enforce the rules, but does not guarantee enforcement. Procedure The following steps demonstrate a simple configuration that creates a node and a pod that the scheduler tries to place on the node. Add a label to a node using the oc label node command: USD oc label node node1 e2e-az-name=e2e-az3 Create a pod with a specific label: Create a YAML file with the following content: Note You cannot add an affinity directly to a scheduled pod. apiVersion: v1 kind: Pod metadata: name: s1 spec: affinity: 1 nodeAffinity: preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 3 preference: matchExpressions: - key: e2e-az-name 4 values: - e2e-az3 operator: In 5 #... 1 Adds a pod affinity. 2 Configures the preferredDuringSchedulingIgnoredDuringExecution parameter. 3 Specifies a weight for the node, as a number 1-100. The node with highest weight is preferred. 4 Specifies the key and values that must be met. If you want the new pod to be scheduled on the node you edited, use the same key and values parameters as the label in the node. 5 Specifies an operator . The operator can be In , NotIn , Exists , or DoesNotExist . For example, use the operator In to require the label to be in the node. Create the pod. USD oc create -f <file-name>.yaml 4.4.4. Sample node affinity rules The following examples demonstrate node affinity. 4.4.4.1. Node affinity with matching labels The following example demonstrates node affinity for a node and pod with matching labels: The Node1 node has the label zone:us : USD oc label node node1 zone=us Tip You can alternatively apply the following YAML to add the label: kind: Node apiVersion: v1 metadata: name: <node_name> labels: zone: us #... The pod-s1 pod has the zone and us key/value pair under a required node affinity rule: USD cat pod-s1.yaml Example output apiVersion: v1 kind: Pod metadata: name: pod-s1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - image: "docker.io/ocpqe/hello-pod" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: "zone" operator: In values: - us #... The pod-s1 pod can be scheduled on Node1: USD oc get pod -o wide Example output NAME READY STATUS RESTARTS AGE IP NODE pod-s1 1/1 Running 0 4m IP1 node1 4.4.4.2. Node affinity with no matching labels The following example demonstrates node affinity for a node and pod without matching labels: The Node1 node has the label zone:emea : USD oc label node node1 zone=emea Tip You can alternatively apply the following YAML to add the label: kind: Node apiVersion: v1 metadata: name: <node_name> labels: zone: emea #... The pod-s1 pod has the zone and us key/value pair under a required node affinity rule: USD cat pod-s1.yaml Example output apiVersion: v1 kind: Pod metadata: name: pod-s1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - image: "docker.io/ocpqe/hello-pod" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: "zone" operator: In values: - us #... The pod-s1 pod cannot be scheduled on Node1: USD oc describe pod pod-s1 Example output ... Events: FirstSeen LastSeen Count From SubObjectPath Type Reason --------- -------- ----- ---- ------------- -------- ------ 1m 33s 8 default-scheduler Warning FailedScheduling No nodes are available that match all of the following predicates:: MatchNodeSelector (1). 4.4.5. Using node affinity to control where an Operator is installed By default, when you install an Operator, OpenShift Container Platform installs the Operator pod to one of your worker nodes randomly. However, there might be situations where you want that pod scheduled on a specific node or set of nodes. The following examples describe situations where you might want to schedule an Operator pod to a specific node or set of nodes: If an Operator requires a particular platform, such as amd64 or arm64 If an Operator requires a particular operating system, such as Linux or Windows If you want Operators that work together scheduled on the same host or on hosts located on the same rack If you want Operators dispersed throughout the infrastructure to avoid downtime due to network or hardware issues You can control where an Operator pod is installed by adding a node affinity constraints to the Operator's Subscription object. The following examples show how to use node affinity to install an instance of the Custom Metrics Autoscaler Operator to a specific node in the cluster: Node affinity example that places the Operator pod on a specific node apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: nodeAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-163-94.us-west-2.compute.internal #... 1 A node affinity that requires the Operator's pod to be scheduled on a node named ip-10-0-163-94.us-west-2.compute.internal . Node affinity example that places the Operator pod on a node with a specific platform apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: nodeAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/arch operator: In values: - arm64 - key: kubernetes.io/os operator: In values: - linux #... 1 A node affinity that requires the Operator's pod to be scheduled on a node with the kubernetes.io/arch=arm64 and kubernetes.io/os=linux labels. Procedure To control the placement of an Operator pod, complete the following steps: Install the Operator as usual. If needed, ensure that your nodes are labeled to properly respond to the affinity. Edit the Operator Subscription object to add an affinity: apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: 1 nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-185-229.ec2.internal #... 1 Add a nodeAffinity . Verification To ensure that the pod is deployed on the specific node, run the following command: USD oc get pods -o wide Example output NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES custom-metrics-autoscaler-operator-5dcc45d656-bhshg 1/1 Running 0 50s 10.131.0.20 ip-10-0-185-229.ec2.internal <none> <none> 4.4.6. Additional resources Understanding how to update labels on nodes 4.5. Placing pods onto overcommited nodes In an overcommited state, the sum of the container compute resource requests and limits exceeds the resources available on the system. Overcommitment might be desirable in development environments where a trade-off of guaranteed performance for capacity is acceptable. Requests and limits enable administrators to allow and manage the overcommitment of resources on a node. The scheduler uses requests for scheduling your container and providing a minimum service guarantee. Limits constrain the amount of compute resource that may be consumed on your node. 4.5.1. Understanding overcommitment Requests and limits enable administrators to allow and manage the overcommitment of resources on a node. The scheduler uses requests for scheduling your container and providing a minimum service guarantee. Limits constrain the amount of compute resource that may be consumed on your node. OpenShift Container Platform administrators can control the level of overcommit and manage container density on nodes by configuring masters to override the ratio between request and limit set on developer containers. In conjunction with a per-project LimitRange object specifying limits and defaults, this adjusts the container limit and request to achieve the desired level of overcommit. Note That these overrides have no effect if no limits have been set on containers. Create a LimitRange object with default limits, per individual project, or in the project template, to ensure that the overrides apply. After these overrides, the container limits and requests must still be validated by any LimitRange object in the project. It is possible, for example, for developers to specify a limit close to the minimum limit, and have the request then be overridden below the minimum limit, causing the pod to be forbidden. This unfortunate user experience should be addressed with future work, but for now, configure this capability and LimitRange objects with caution. 4.5.2. Understanding nodes overcommitment In an overcommitted environment, it is important to properly configure your node to provide best system behavior. When the node starts, it ensures that the kernel tunable flags for memory management are set properly. The kernel should never fail memory allocations unless it runs out of physical memory. To ensure this behavior, OpenShift Container Platform configures the kernel to always overcommit memory by setting the vm.overcommit_memory parameter to 1 , overriding the default operating system setting. OpenShift Container Platform also configures the kernel not to panic when it runs out of memory by setting the vm.panic_on_oom parameter to 0 . A setting of 0 instructs the kernel to call oom_killer in an Out of Memory (OOM) condition, which kills processes based on priority. You can view the current setting by running the following commands on your nodes: USD sysctl -a \|grep commit Example output #... vm.overcommit_memory = 0 #... USD sysctl -a \|grep panic Example output #... vm.panic_on_oom = 0 #... Note The above flags should already be set on nodes, and no further action is required. You can also perform the following configurations for each node: Disable or enforce CPU limits using CPU CFS quotas Reserve resources for system processes Reserve memory across quality of service tiers 4.6. Controlling pod placement using node taints Taints and tolerations allow the node to control which pods should (or should not) be scheduled on them. 4.6.1. Understanding taints and tolerations A taint allows a node to refuse a pod to be scheduled unless that pod has a matching toleration . You apply taints to a node through the Node specification ( NodeSpec ) and apply tolerations to a pod through the Pod specification ( PodSpec ). When you apply a taint to a node, the scheduler cannot place a pod on that node unless the pod can tolerate the taint. Example taint in a node specification apiVersion: v1 kind: Node metadata: name: my-node #... spec: taints: - effect: NoExecute key: key1 value: value1 #... Example toleration in a Pod spec apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key1" operator: "Equal" value: "value1" effect: "NoExecute" tolerationSeconds: 3600 #... Taints and tolerations consist of a key, value, and effect. Table 4.1. Taint and toleration components Parameter Description key The key is any string, up to 253 characters. The key must begin with a letter or number, and may contain letters, numbers, hyphens, dots, and underscores. value The value is any string, up to 63 characters. The value must begin with a letter or number, and may contain letters, numbers, hyphens, dots, and underscores. effect The effect is one of the following: NoSchedule [1] New pods that do not match the taint are not scheduled onto that node. Existing pods on the node remain. PreferNoSchedule New pods that do not match the taint might be scheduled onto that node, but the scheduler tries not to. Existing pods on the node remain. NoExecute New pods that do not match the taint cannot be scheduled onto that node. Existing pods on the node that do not have a matching toleration are removed. operator Equal The key / value / effect parameters must match. This is the default. Exists The key / effect parameters must match. You must leave a blank value parameter, which matches any. If you add a NoSchedule taint to a control plane node, the node must have the node-role.kubernetes.io/master=:NoSchedule taint, which is added by default. For example: apiVersion: v1 kind: Node metadata: annotations: machine.openshift.io/machine: openshift-machine-api/ci-ln-62s7gtb-f76d1-v8jxv-master-0 machineconfiguration.openshift.io/currentConfig: rendered-master-cdc1ab7da414629332cc4c3926e6e59c name: my-node #... spec: taints: - effect: NoSchedule key: node-role.kubernetes.io/master #... A toleration matches a taint: If the operator parameter is set to Equal : the key parameters are the same; the value parameters are the same; the effect parameters are the same. If the operator parameter is set to Exists : the key parameters are the same; the effect parameters are the same. The following taints are built into OpenShift Container Platform: node.kubernetes.io/not-ready : The node is not ready. This corresponds to the node condition Ready=False . node.kubernetes.io/unreachable : The node is unreachable from the node controller. This corresponds to the node condition Ready=Unknown . node.kubernetes.io/memory-pressure : The node has memory pressure issues. This corresponds to the node condition MemoryPressure=True . node.kubernetes.io/disk-pressure : The node has disk pressure issues. This corresponds to the node condition DiskPressure=True . node.kubernetes.io/network-unavailable : The node network is unavailable. node.kubernetes.io/unschedulable : The node is unschedulable. node.cloudprovider.kubernetes.io/uninitialized : When the node controller is started with an external cloud provider, this taint is set on a node to mark it as unusable. After a controller from the cloud-controller-manager initializes this node, the kubelet removes this taint. node.kubernetes.io/pid-pressure : The node has pid pressure. This corresponds to the node condition PIDPressure=True . Important OpenShift Container Platform does not set a default pid.available evictionHard . 4.6.1.1. Understanding how to use toleration seconds to delay pod evictions You can specify how long a pod can remain bound to a node before being evicted by specifying the tolerationSeconds parameter in the Pod specification or MachineSet object. If a taint with the NoExecute effect is added to a node, a pod that does tolerate the taint, which has the tolerationSeconds parameter, the pod is not evicted until that time period expires. Example output apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key1" operator: "Equal" value: "value1" effect: "NoExecute" tolerationSeconds: 3600 #... Here, if this pod is running but does not have a matching toleration, the pod stays bound to the node for 3,600 seconds and then be evicted. If the taint is removed before that time, the pod is not evicted. 4.6.1.2. Understanding how to use multiple taints You can put multiple taints on the same node and multiple tolerations on the same pod. OpenShift Container Platform processes multiple taints and tolerations as follows: Process the taints for which the pod has a matching toleration. The remaining unmatched taints have the indicated effects on the pod: If there is at least one unmatched taint with effect NoSchedule , OpenShift Container Platform cannot schedule a pod onto that node. If there is no unmatched taint with effect NoSchedule but there is at least one unmatched taint with effect PreferNoSchedule , OpenShift Container Platform tries to not schedule the pod onto the node. If there is at least one unmatched taint with effect NoExecute , OpenShift Container Platform evicts the pod from the node if it is already running on the node, or the pod is not scheduled onto the node if it is not yet running on the node. Pods that do not tolerate the taint are evicted immediately. Pods that tolerate the taint without specifying tolerationSeconds in their Pod specification remain bound forever. Pods that tolerate the taint with a specified tolerationSeconds remain bound for the specified amount of time. For example: Add the following taints to the node: USD oc adm taint nodes node1 key1=value1:NoSchedule USD oc adm taint nodes node1 key1=value1:NoExecute USD oc adm taint nodes node1 key2=value2:NoSchedule The pod has the following tolerations: apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key1" operator: "Equal" value: "value1" effect: "NoSchedule" - key: "key1" operator: "Equal" value: "value1" effect: "NoExecute" #... In this case, the pod cannot be scheduled onto the node, because there is no toleration matching the third taint. The pod continues running if it is already running on the node when the taint is added, because the third taint is the only one of the three that is not tolerated by the pod. 4.6.1.3. Understanding pod scheduling and node conditions (taint node by condition) The Taint Nodes By Condition feature, which is enabled by default, automatically taints nodes that report conditions such as memory pressure and disk pressure. If a node reports a condition, a taint is added until the condition clears. The taints have the NoSchedule effect, which means no pod can be scheduled on the node unless the pod has a matching toleration. The scheduler checks for these taints on nodes before scheduling pods. If the taint is present, the pod is scheduled on a different node. Because the scheduler checks for taints and not the actual node conditions, you configure the scheduler to ignore some of these node conditions by adding appropriate pod tolerations. To ensure backward compatibility, the daemon set controller automatically adds the following tolerations to all daemons: node.kubernetes.io/memory-pressure node.kubernetes.io/disk-pressure node.kubernetes.io/unschedulable (1.10 or later) node.kubernetes.io/network-unavailable (host network only) You can also add arbitrary tolerations to daemon sets. Note The control plane also adds the node.kubernetes.io/memory-pressure toleration on pods that have a QoS class. This is because Kubernetes manages pods in the Guaranteed or Burstable QoS classes. The new BestEffort pods do not get scheduled onto the affected node. 4.6.1.4. Understanding evicting pods by condition (taint-based evictions) The Taint-Based Evictions feature, which is enabled by default, evicts pods from a node that experiences specific conditions, such as not-ready and unreachable . When a node experiences one of these conditions, OpenShift Container Platform automatically adds taints to the node, and starts evicting and rescheduling the pods on different nodes. Taint Based Evictions have a NoExecute effect, where any pod that does not tolerate the taint is evicted immediately and any pod that does tolerate the taint will never be evicted, unless the pod uses the tolerationSeconds parameter. The tolerationSeconds parameter allows you to specify how long a pod stays bound to a node that has a node condition. If the condition still exists after the tolerationSeconds period, the taint remains on the node and the pods with a matching toleration are evicted. If the condition clears before the tolerationSeconds period, pods with matching tolerations are not removed. If you use the tolerationSeconds parameter with no value, pods are never evicted because of the not ready and unreachable node conditions. Note OpenShift Container Platform evicts pods in a rate-limited way to prevent massive pod evictions in scenarios such as the master becoming partitioned from the nodes. By default, if more than 55% of nodes in a given zone are unhealthy, the node lifecycle controller changes that zone's state to PartialDisruption and the rate of pod evictions is reduced. For small clusters (by default, 50 nodes or less) in this state, nodes in this zone are not tainted and evictions are stopped. For more information, see Rate limits on eviction in the Kubernetes documentation. OpenShift Container Platform automatically adds a toleration for node.kubernetes.io/not-ready and node.kubernetes.io/unreachable with tolerationSeconds=300 , unless the Pod configuration specifies either toleration. apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: node.kubernetes.io/not-ready operator: Exists effect: NoExecute tolerationSeconds: 300 1 - key: node.kubernetes.io/unreachable operator: Exists effect: NoExecute tolerationSeconds: 300 #... 1 These tolerations ensure that the default pod behavior is to remain bound for five minutes after one of these node conditions problems is detected. You can configure these tolerations as needed. For example, if you have an application with a lot of local state, you might want to keep the pods bound to node for a longer time in the event of network partition, allowing for the partition to recover and avoiding pod eviction. Pods spawned by a daemon set are created with NoExecute tolerations for the following taints with no tolerationSeconds : node.kubernetes.io/unreachable node.kubernetes.io/not-ready As a result, daemon set pods are never evicted because of these node conditions. 4.6.1.5. Tolerating all taints You can configure a pod to tolerate all taints by adding an operator: "Exists" toleration with no key and values parameters. Pods with this toleration are not removed from a node that has taints. Pod spec for tolerating all taints apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - operator: "Exists" #... 4.6.2. Adding taints and tolerations You add tolerations to pods and taints to nodes to allow the node to control which pods should or should not be scheduled on them. For existing pods and nodes, you should add the toleration to the pod first, then add the taint to the node to avoid pods being removed from the node before you can add the toleration. Procedure Add a toleration to a pod by editing the Pod spec to include a tolerations stanza: Sample pod configuration file with an Equal operator apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key1" 1 value: "value1" operator: "Equal" effect: "NoExecute" tolerationSeconds: 3600 2 #... 1 The toleration parameters, as described in the Taint and toleration components table. 2 The tolerationSeconds parameter specifies how long a pod can remain bound to a node before being evicted. For example: Sample pod configuration file with an Exists operator apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key1" operator: "Exists" 1 effect: "NoExecute" tolerationSeconds: 3600 #... 1 The Exists operator does not take a value . This example places a taint on node1 that has key key1 , value value1 , and taint effect NoExecute . Add a taint to a node by using the following command with the parameters described in the Taint and toleration components table: USD oc adm taint nodes <node_name> <key>=<value>:<effect> For example: USD oc adm taint nodes node1 key1=value1:NoExecute This command places a taint on node1 that has key key1 , value value1 , and effect NoExecute . Note If you add a NoSchedule taint to a control plane node, the node must have the node-role.kubernetes.io/master=:NoSchedule taint, which is added by default. For example: apiVersion: v1 kind: Node metadata: annotations: machine.openshift.io/machine: openshift-machine-api/ci-ln-62s7gtb-f76d1-v8jxv-master-0 machineconfiguration.openshift.io/currentConfig: rendered-master-cdc1ab7da414629332cc4c3926e6e59c name: my-node #... spec: taints: - effect: NoSchedule key: node-role.kubernetes.io/master #... The tolerations on the pod match the taint on the node. A pod with either toleration can be scheduled onto node1 . 4.6.2.1. Adding taints and tolerations using a compute machine set You can add taints to nodes using a compute machine set. All nodes associated with the MachineSet object are updated with the taint. Tolerations respond to taints added by a compute machine set in the same manner as taints added directly to the nodes. Procedure Add a toleration to a pod by editing the Pod spec to include a tolerations stanza: Sample pod configuration file with Equal operator apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key1" 1 value: "value1" operator: "Equal" effect: "NoExecute" tolerationSeconds: 3600 2 #... 1 The toleration parameters, as described in the Taint and toleration components table. 2 The tolerationSeconds parameter specifies how long a pod is bound to a node before being evicted. For example: Sample pod configuration file with Exists operator apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key1" operator: "Exists" effect: "NoExecute" tolerationSeconds: 3600 #... Add the taint to the MachineSet object: Edit the MachineSet YAML for the nodes you want to taint or you can create a new MachineSet object: USD oc edit machineset <machineset> Add the taint to the spec.template.spec section: Example taint in a compute machine set specification apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: my-machineset #... spec: #... template: #... spec: taints: - effect: NoExecute key: key1 value: value1 #... This example places a taint that has the key key1 , value value1 , and taint effect NoExecute on the nodes. Scale down the compute machine set to 0: USD oc scale --replicas=0 machineset <machineset> -n openshift-machine-api Tip You can alternatively apply the following YAML to scale the compute machine set: apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: <machineset> namespace: openshift-machine-api spec: replicas: 0 Wait for the machines to be removed. Scale up the compute machine set as needed: USD oc scale --replicas=2 machineset <machineset> -n openshift-machine-api Or: USD oc edit machineset <machineset> -n openshift-machine-api Wait for the machines to start. The taint is added to the nodes associated with the MachineSet object. 4.6.2.2. Binding a user to a node using taints and tolerations If you want to dedicate a set of nodes for exclusive use by a particular set of users, add a toleration to their pods. Then, add a corresponding taint to those nodes. The pods with the tolerations are allowed to use the tainted nodes or any other nodes in the cluster. If you want ensure the pods are scheduled to only those tainted nodes, also add a label to the same set of nodes and add a node affinity to the pods so that the pods can only be scheduled onto nodes with that label. Procedure To configure a node so that users can use only that node: Add a corresponding taint to those nodes: For example: USD oc adm taint nodes node1 dedicated=groupName:NoSchedule Tip You can alternatively apply the following YAML to add the taint: kind: Node apiVersion: v1 metadata: name: my-node #... spec: taints: - key: dedicated value: groupName effect: NoSchedule #... Add a toleration to the pods by writing a custom admission controller. 4.6.2.3. Creating a project with a node selector and toleration You can create a project that uses a node selector and toleration, which are set as annotations, to control the placement of pods onto specific nodes. Any subsequent resources created in the project are then scheduled on nodes that have a taint matching the toleration. Prerequisites A label for node selection has been added to one or more nodes by using a compute machine set or editing the node directly. A taint has been added to one or more nodes by using a compute machine set or editing the node directly. Procedure Create a Project resource definition, specifying a node selector and toleration in the metadata.annotations section: Example project.yaml file kind: Project apiVersion: project.openshift.io/v1 metadata: name: <project_name> 1 annotations: openshift.io/node-selector: '<label>' 2 scheduler.alpha.kubernetes.io/defaultTolerations: >- [{"operator": "Exists", "effect": "NoSchedule", "key": "<key_name>"} 3 ] 1 The project name. 2 The default node selector label. 3 The toleration parameters, as described in the Taint and toleration components table. This example uses the NoSchedule effect, which allows existing pods on the node to remain, and the Exists operator, which does not take a value. Use the oc apply command to create the project: USD oc apply -f project.yaml Any subsequent resources created in the <project_name> namespace should now be scheduled on the specified nodes. Additional resources Adding taints and tolerations manually to nodes or with compute machine sets Creating project-wide node selectors Pod placement of Operator workloads 4.6.2.4. Controlling nodes with special hardware using taints and tolerations In a cluster where a small subset of nodes have specialized hardware, you can use taints and tolerations to keep pods that do not need the specialized hardware off of those nodes, leaving the nodes for pods that do need the specialized hardware. You can also require pods that need specialized hardware to use specific nodes. You can achieve this by adding a toleration to pods that need the special hardware and tainting the nodes that have the specialized hardware. Procedure To ensure nodes with specialized hardware are reserved for specific pods: Add a toleration to pods that need the special hardware. For example: apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "disktype" value: "ssd" operator: "Equal" effect: "NoSchedule" tolerationSeconds: 3600 #... Taint the nodes that have the specialized hardware using one of the following commands: USD oc adm taint nodes <node-name> disktype=ssd:NoSchedule Or: USD oc adm taint nodes <node-name> disktype=ssd:PreferNoSchedule Tip You can alternatively apply the following YAML to add the taint: kind: Node apiVersion: v1 metadata: name: my_node #... spec: taints: - key: disktype value: ssd effect: PreferNoSchedule #... 4.6.3. Removing taints and tolerations You can remove taints from nodes and tolerations from pods as needed. You should add the toleration to the pod first, then add the taint to the node to avoid pods being removed from the node before you can add the toleration. Procedure To remove taints and tolerations: To remove a taint from a node: USD oc adm taint nodes <node-name> <key>- For example: USD oc adm taint nodes ip-10-0-132-248.ec2.internal key1- Example output node/ip-10-0-132-248.ec2.internal untainted To remove a toleration from a pod, edit the Pod spec to remove the toleration: apiVersion: v1 kind: Pod metadata: name: my-pod #... spec: tolerations: - key: "key2" operator: "Exists" effect: "NoExecute" tolerationSeconds: 3600 #... 4.7. Placing pods on specific nodes using node selectors A node selector specifies a map of key/value pairs that are defined using custom labels on nodes and selectors specified in pods. For the pod to be eligible to run on a node, the pod must have the same key/value node selector as the label on the node. 4.7.1. About node selectors You can use node selectors on pods and labels on nodes to control where the pod is scheduled. With node selectors, OpenShift Container Platform schedules the pods on nodes that contain matching labels. You can use a node selector to place specific pods on specific nodes, cluster-wide node selectors to place new pods on specific nodes anywhere in the cluster, and project node selectors to place new pods in a project on specific nodes. For example, as a cluster administrator, you can create an infrastructure where application developers can deploy pods only onto the nodes closest to their geographical location by including a node selector in every pod they create. In this example, the cluster consists of five data centers spread across two regions. In the U.S., label the nodes as us-east , us-central , or us-west . In the Asia-Pacific region (APAC), label the nodes as apac-east or apac-west . The developers can add a node selector to the pods they create to ensure the pods get scheduled on those nodes. A pod is not scheduled if the Pod object contains a node selector, but no node has a matching label. Important If you are using node selectors and node affinity in the same pod configuration, the following rules control pod placement onto nodes: If you configure both nodeSelector and nodeAffinity , both conditions must be satisfied for the pod to be scheduled onto a candidate node. If you specify multiple nodeSelectorTerms associated with nodeAffinity types, then the pod can be scheduled onto a node if one of the nodeSelectorTerms is satisfied. If you specify multiple matchExpressions associated with nodeSelectorTerms , then the pod can be scheduled onto a node only if all matchExpressions are satisfied. Node selectors on specific pods and nodes You can control which node a specific pod is scheduled on by using node selectors and labels. To use node selectors and labels, first label the node to avoid pods being descheduled, then add the node selector to the pod. Note You cannot add a node selector directly to an existing scheduled pod. You must label the object that controls the pod, such as deployment config. For example, the following Node object has the region: east label: Sample Node object with a label kind: Node apiVersion: v1 metadata: name: ip-10-0-131-14.ec2.internal selfLink: /api/v1/nodes/ip-10-0-131-14.ec2.internal uid: 7bc2580a-8b8e-11e9-8e01-021ab4174c74 resourceVersion: '478704' creationTimestamp: '2019-06-10T14:46:08Z' labels: kubernetes.io/os: linux topology.kubernetes.io/zone: us-east-1a node.openshift.io/os_version: '4.5' node-role.kubernetes.io/worker: '' topology.kubernetes.io/region: us-east-1 node.openshift.io/os_id: rhcos node.kubernetes.io/instance-type: m4.large kubernetes.io/hostname: ip-10-0-131-14 kubernetes.io/arch: amd64 region: east 1 type: user-node #... 1 Labels to match the pod node selector. A pod has the type: user-node,region: east node selector: Sample Pod object with node selectors apiVersion: v1 kind: Pod metadata: name: s1 #... spec: nodeSelector: 1 region: east type: user-node #... 1 Node selectors to match the node label. The node must have a label for each node selector. When you create the pod using the example pod spec, it can be scheduled on the example node. Default cluster-wide node selectors With default cluster-wide node selectors, when you create a pod in that cluster, OpenShift Container Platform adds the default node selectors to the pod and schedules the pod on nodes with matching labels. For example, the following Scheduler object has the default cluster-wide region=east and type=user-node node selectors: Example Scheduler Operator Custom Resource apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster #... spec: defaultNodeSelector: type=user-node,region=east #... A node in that cluster has the type=user-node,region=east labels: Example Node object apiVersion: v1 kind: Node metadata: name: ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 #... labels: region: east type: user-node #... Example Pod object with a node selector apiVersion: v1 kind: Pod metadata: name: s1 #... spec: nodeSelector: region: east #... When you create the pod using the example pod spec in the example cluster, the pod is created with the cluster-wide node selector and is scheduled on the labeled node: Example pod list with the pod on the labeled node NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-s1 1/1 Running 0 20s 10.131.2.6 ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 <none> <none> Note If the project where you create the pod has a project node selector, that selector takes preference over a cluster-wide node selector. Your pod is not created or scheduled if the pod does not have the project node selector. Project node selectors With project node selectors, when you create a pod in this project, OpenShift Container Platform adds the node selectors to the pod and schedules the pods on a node with matching labels. If there is a cluster-wide default node selector, a project node selector takes preference. For example, the following project has the region=east node selector: Example Namespace object apiVersion: v1 kind: Namespace metadata: name: east-region annotations: openshift.io/node-selector: "region=east" #... The following node has the type=user-node,region=east labels: Example Node object apiVersion: v1 kind: Node metadata: name: ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 #... labels: region: east type: user-node #... When you create the pod using the example pod spec in this example project, the pod is created with the project node selectors and is scheduled on the labeled node: Example Pod object apiVersion: v1 kind: Pod metadata: namespace: east-region #... spec: nodeSelector: region: east type: user-node #... Example pod list with the pod on the labeled node NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-s1 1/1 Running 0 20s 10.131.2.6 ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 <none> <none> A pod in the project is not created or scheduled if the pod contains different node selectors. For example, if you deploy the following pod into the example project, it is not created: Example Pod object with an invalid node selector apiVersion: v1 kind: Pod metadata: name: west-region #... spec: nodeSelector: region: west #... 4.7.2. Using node selectors to control pod placement You can use node selectors on pods and labels on nodes to control where the pod is scheduled. With node selectors, OpenShift Container Platform schedules the pods on nodes that contain matching labels. You add labels to a node, a compute machine set, or a machine config. Adding the label to the compute machine set ensures that if the node or machine goes down, new nodes have the label. Labels added to a node or machine config do not persist if the node or machine goes down. To add node selectors to an existing pod, add a node selector to the controlling object for that pod, such as a ReplicaSet object, DaemonSet object, StatefulSet object, Deployment object, or DeploymentConfig object. Any existing pods under that controlling object are recreated on a node with a matching label. If you are creating a new pod, you can add the node selector directly to the pod spec. If the pod does not have a controlling object, you must delete the pod, edit the pod spec, and recreate the pod. Note You cannot add a node selector directly to an existing scheduled pod. Prerequisites To add a node selector to existing pods, determine the controlling object for that pod. For example, the router-default-66d5cf9464-m2g75 pod is controlled by the router-default-66d5cf9464 replica set: USD oc describe pod router-default-66d5cf9464-7pwkc Example output kind: Pod apiVersion: v1 metadata: # ... Name: router-default-66d5cf9464-7pwkc Namespace: openshift-ingress # ... Controlled By: ReplicaSet/router-default-66d5cf9464 # ... The web console lists the controlling object under ownerReferences in the pod YAML: apiVersion: v1 kind: Pod metadata: name: router-default-66d5cf9464-7pwkc # ... ownerReferences: - apiVersion: apps/v1 kind: ReplicaSet name: router-default-66d5cf9464 uid: d81dd094-da26-11e9-a48a-128e7edf0312 controller: true blockOwnerDeletion: true # ... Procedure Add labels to a node by using a compute machine set or editing the node directly: Use a MachineSet object to add labels to nodes managed by the compute machine set when a node is created: Run the following command to add labels to a MachineSet object: USD oc patch MachineSet <name> --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"<key>"="<value>","<key>"="<value>"}}]' -n openshift-machine-api For example: USD oc patch MachineSet abc612-msrtw-worker-us-east-1c --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"type":"user-node","region":"east"}}]' -n openshift-machine-api Tip You can alternatively apply the following YAML to add labels to a compute machine set: apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: xf2bd-infra-us-east-2a namespace: openshift-machine-api spec: template: spec: metadata: labels: region: "east" type: "user-node" # ... Verify that the labels are added to the MachineSet object by using the oc edit command: For example: USD oc edit MachineSet abc612-msrtw-worker-us-east-1c -n openshift-machine-api Example MachineSet object apiVersion: machine.openshift.io/v1beta1 kind: MachineSet # ... spec: # ... template: metadata: # ... spec: metadata: labels: region: east type: user-node # ... Add labels directly to a node: Edit the Node object for the node: USD oc label nodes <name> <key>=<value> For example, to label a node: USD oc label nodes ip-10-0-142-25.ec2.internal type=user-node region=east Tip You can alternatively apply the following YAML to add labels to a node: kind: Node apiVersion: v1 metadata: name: hello-node-6fbccf8d9 labels: type: "user-node" region: "east" # ... Verify that the labels are added to the node: USD oc get nodes -l type=user-node,region=east Example output NAME STATUS ROLES AGE VERSION ip-10-0-142-25.ec2.internal Ready worker 17m v1.30.3 Add the matching node selector to a pod: To add a node selector to existing and future pods, add a node selector to the controlling object for the pods: Example ReplicaSet object with labels kind: ReplicaSet apiVersion: apps/v1 metadata: name: hello-node-6fbccf8d9 # ... spec: # ... template: metadata: creationTimestamp: null labels: ingresscontroller.operator.openshift.io/deployment-ingresscontroller: default pod-template-hash: 66d5cf9464 spec: nodeSelector: kubernetes.io/os: linux node-role.kubernetes.io/worker: '' type: user-node 1 # ... 1 Add the node selector. To add a node selector to a specific, new pod, add the selector to the Pod object directly: Example Pod object with a node selector apiVersion: v1 kind: Pod metadata: name: hello-node-6fbccf8d9 # ... spec: nodeSelector: region: east type: user-node # ... Note You cannot add a node selector directly to an existing scheduled pod. 4.7.3. Creating default cluster-wide node selectors You can use default cluster-wide node selectors on pods together with labels on nodes to constrain all pods created in a cluster to specific nodes. With cluster-wide node selectors, when you create a pod in that cluster, OpenShift Container Platform adds the default node selectors to the pod and schedules the pod on nodes with matching labels. You configure cluster-wide node selectors by editing the Scheduler Operator custom resource (CR). You add labels to a node, a compute machine set, or a machine config. Adding the label to the compute machine set ensures that if the node or machine goes down, new nodes have the label. Labels added to a node or machine config do not persist if the node or machine goes down. Note You can add additional key/value pairs to a pod. But you cannot add a different value for a default key. Procedure To add a default cluster-wide node selector: Edit the Scheduler Operator CR to add the default cluster-wide node selectors: USD oc edit scheduler cluster Example Scheduler Operator CR with a node selector apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster ... spec: defaultNodeSelector: type=user-node,region=east 1 mastersSchedulable: false 1 Add a node selector with the appropriate <key>:<value> pairs. After making this change, wait for the pods in the openshift-kube-apiserver project to redeploy. This can take several minutes. The default cluster-wide node selector does not take effect until the pods redeploy. Add labels to a node by using a compute machine set or editing the node directly: Use a compute machine set to add labels to nodes managed by the compute machine set when a node is created: Run the following command to add labels to a MachineSet object: USD oc patch MachineSet <name> --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"<key>"="<value>","<key>"="<value>"}}]' -n openshift-machine-api 1 1 Add a <key>/<value> pair for each label. For example: USD oc patch MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"type":"user-node","region":"east"}}]' -n openshift-machine-api Tip You can alternatively apply the following YAML to add labels to a compute machine set: apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: <machineset> namespace: openshift-machine-api spec: template: spec: metadata: labels: region: "east" type: "user-node" Verify that the labels are added to the MachineSet object by using the oc edit command: For example: USD oc edit MachineSet abc612-msrtw-worker-us-east-1c -n openshift-machine-api Example MachineSet object apiVersion: machine.openshift.io/v1beta1 kind: MachineSet ... spec: ... template: metadata: ... spec: metadata: labels: region: east type: user-node ... Redeploy the nodes associated with that compute machine set by scaling down to 0 and scaling up the nodes: For example: USD oc scale --replicas=0 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api USD oc scale --replicas=1 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api When the nodes are ready and available, verify that the label is added to the nodes by using the oc get command: USD oc get nodes -l <key>=<value> For example: USD oc get nodes -l type=user-node Example output NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-c-vmqzp Ready worker 61s v1.30.3 Add labels directly to a node: Edit the Node object for the node: USD oc label nodes <name> <key>=<value> For example, to label a node: USD oc label nodes ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 type=user-node region=east Tip You can alternatively apply the following YAML to add labels to a node: kind: Node apiVersion: v1 metadata: name: <node_name> labels: type: "user-node" region: "east" Verify that the labels are added to the node using the oc get command: USD oc get nodes -l <key>=<value>,<key>=<value> For example: USD oc get nodes -l type=user-node,region=east Example output NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 Ready worker 17m v1.30.3 4.7.4. Creating project-wide node selectors You can use node selectors in a project together with labels on nodes to constrain all pods created in that project to the labeled nodes. When you create a pod in this project, OpenShift Container Platform adds the node selectors to the pods in the project and schedules the pods on a node with matching labels in the project. If there is a cluster-wide default node selector, a project node selector takes preference. You add node selectors to a project by editing the Namespace object to add the openshift.io/node-selector parameter. You add labels to a node, a compute machine set, or a machine config. Adding the label to the compute machine set ensures that if the node or machine goes down, new nodes have the label. Labels added to a node or machine config do not persist if the node or machine goes down. A pod is not scheduled if the Pod object contains a node selector, but no project has a matching node selector. When you create a pod from that spec, you receive an error similar to the following message: Example error message Error from server (Forbidden): error when creating "pod.yaml": pods "pod-4" is forbidden: pod node label selector conflicts with its project node label selector Note You can add additional key/value pairs to a pod. But you cannot add a different value for a project key. Procedure To add a default project node selector: Create a namespace or edit an existing namespace to add the openshift.io/node-selector parameter: USD oc edit namespace <name> Example output apiVersion: v1 kind: Namespace metadata: annotations: openshift.io/node-selector: "type=user-node,region=east" 1 openshift.io/description: "" openshift.io/display-name: "" openshift.io/requester: kube:admin openshift.io/sa.scc.mcs: s0:c30,c5 openshift.io/sa.scc.supplemental-groups: 1000880000/10000 openshift.io/sa.scc.uid-range: 1000880000/10000 creationTimestamp: "2021-05-10T12:35:04Z" labels: kubernetes.io/metadata.name: demo name: demo resourceVersion: "145537" uid: 3f8786e3-1fcb-42e3-a0e3-e2ac54d15001 spec: finalizers: - kubernetes 1 Add the openshift.io/node-selector with the appropriate <key>:<value> pairs. Add labels to a node by using a compute machine set or editing the node directly: Use a MachineSet object to add labels to nodes managed by the compute machine set when a node is created: Run the following command to add labels to a MachineSet object: USD oc patch MachineSet <name> --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"<key>"="<value>","<key>"="<value>"}}]' -n openshift-machine-api For example: USD oc patch MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"type":"user-node","region":"east"}}]' -n openshift-machine-api Tip You can alternatively apply the following YAML to add labels to a compute machine set: apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: <machineset> namespace: openshift-machine-api spec: template: spec: metadata: labels: region: "east" type: "user-node" Verify that the labels are added to the MachineSet object by using the oc edit command: For example: USD oc edit MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api Example output apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: ... spec: ... template: metadata: ... spec: metadata: labels: region: east type: user-node Redeploy the nodes associated with that compute machine set: For example: USD oc scale --replicas=0 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api USD oc scale --replicas=1 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api When the nodes are ready and available, verify that the label is added to the nodes by using the oc get command: USD oc get nodes -l <key>=<value> For example: USD oc get nodes -l type=user-node,region=east Example output NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-c-vmqzp Ready worker 61s v1.30.3 Add labels directly to a node: Edit the Node object to add labels: USD oc label <resource> <name> <key>=<value> For example, to label a node: USD oc label nodes ci-ln-l8nry52-f76d1-hl7m7-worker-c-tgq49 type=user-node region=east Tip You can alternatively apply the following YAML to add labels to a node: kind: Node apiVersion: v1 metadata: name: <node_name> labels: type: "user-node" region: "east" Verify that the labels are added to the Node object using the oc get command: USD oc get nodes -l <key>=<value> For example: USD oc get nodes -l type=user-node,region=east Example output NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 Ready worker 17m v1.30.3 Additional resources Creating a project with a node selector and toleration 4.8. Controlling pod placement by using pod topology spread constraints You can use pod topology spread constraints to provide fine-grained control over the placement of your pods across nodes, zones, regions, or other user-defined topology domains. Distributing pods across failure domains can help to achieve high availability and more efficient resource utilization. 4.8.1. Example use cases As an administrator, I want my workload to automatically scale between two to fifteen pods. I want to ensure that when there are only two pods, they are not placed on the same node, to avoid a single point of failure. As an administrator, I want to distribute my pods evenly across multiple infrastructure zones to reduce latency and network costs. I want to ensure that my cluster can self-heal if issues arise. 4.8.2. Important considerations Pods in an OpenShift Container Platform cluster are managed by workload controllers such as deployments, stateful sets, or daemon sets. These controllers define the desired state for a group of pods, including how they are distributed and scaled across the nodes in the cluster. You should set the same pod topology spread constraints on all pods in a group to avoid confusion. When using a workload controller, such as a deployment, the pod template typically handles this for you. Mixing different pod topology spread constraints can make OpenShift Container Platform behavior confusing and troubleshooting more difficult. You can avoid this by ensuring that all nodes in a topology domain are consistently labeled. OpenShift Container Platform automatically populates well-known labels, such as kubernetes.io/hostname . This helps avoid the need for manual labeling of nodes. These labels provide essential topology information, ensuring consistent node labeling across the cluster. Only pods within the same namespace are matched and grouped together when spreading due to a constraint. You can specify multiple pod topology spread constraints, but you must ensure that they do not conflict with each other. All pod topology spread constraints must be satisfied for a pod to be placed. 4.8.3. Understanding skew and maxSkew Skew refers to the difference in the number of pods that match a specified label selector across different topology domains, such as zones or nodes. The skew is calculated for each domain by taking the absolute difference between the number of pods in that domain and the number of pods in the domain with the lowest amount of pods scheduled. Setting a maxSkew value guides the scheduler to maintain a balanced pod distribution. 4.8.3.1. Example skew calculation You have three zones (A, B, and C), and you want to distribute your pods evenly across these zones. If zone A has 5 pods, zone B has 3 pods, and zone C has 2 pods, to find the skew, you can subtract the number of pods in the domain with the lowest amount of pods scheduled from the number of pods currently in each zone. This means that the skew for zone A is 3, the skew for zone B is 1, and the skew for zone C is 0. 4.8.3.2. The maxSkew parameter The maxSkew parameter defines the maximum allowable difference, or skew, in the number of pods between any two topology domains. If maxSkew is set to 1 , the number of pods in any topology domain should not differ by more than 1 from any other domain. If the skew exceeds maxSkew , the scheduler attempts to place new pods in a way that reduces the skew, adhering to the constraints. Using the example skew calculation, the skew values exceed the default maxSkew value of 1 . The scheduler places new pods in zone B and zone C to reduce the skew and achieve a more balanced distribution, ensuring that no topology domain exceeds the skew of 1. 4.8.4. Example configurations for pod topology spread constraints You can specify which pods to group together, which topology domains they are spread among, and the acceptable skew. The following examples demonstrate pod topology spread constraint configurations. Example to distribute pods that match the specified labels based on their zone apiVersion: v1 kind: Pod metadata: name: my-pod labels: region: us-east spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault topologySpreadConstraints: - maxSkew: 1 1 topologyKey: topology.kubernetes.io/zone 2 whenUnsatisfiable: DoNotSchedule 3 labelSelector: 4 matchLabels: region: us-east 5 matchLabelKeys: - my-pod-label 6 containers: - image: "docker.io/ocpqe/hello-pod" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] 1 The maximum difference in number of pods between any two topology domains. The default is 1 , and you cannot specify a value of 0 . 2 The key of a node label. Nodes with this key and identical value are considered to be in the same topology. 3 How to handle a pod if it does not satisfy the spread constraint. The default is DoNotSchedule , which tells the scheduler not to schedule the pod. Set to ScheduleAnyway to still schedule the pod, but the scheduler prioritizes honoring the skew to not make the cluster more imbalanced. 4 Pods that match this label selector are counted and recognized as a group when spreading to satisfy the constraint. Be sure to specify a label selector, otherwise no pods can be matched. 5 Be sure that this Pod spec also sets its labels to match this label selector if you want it to be counted properly in the future. 6 A list of pod label keys to select which pods to calculate spreading over. Example demonstrating a single pod topology spread constraint kind: Pod apiVersion: v1 metadata: name: my-pod labels: region: us-east spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault topologySpreadConstraints: - maxSkew: 1 topologyKey: topology.kubernetes.io/zone whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: region: us-east containers: - image: "docker.io/ocpqe/hello-pod" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] The example defines a Pod spec with a one pod topology spread constraint. It matches on pods labeled region: us-east , distributes among zones, specifies a skew of 1 , and does not schedule the pod if it does not meet these requirements. Example demonstrating multiple pod topology spread constraints kind: Pod apiVersion: v1 metadata: name: my-pod-2 labels: region: us-east spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault topologySpreadConstraints: - maxSkew: 1 topologyKey: node whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: region: us-east - maxSkew: 1 topologyKey: rack whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: region: us-east containers: - image: "docker.io/ocpqe/hello-pod" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] The example defines a Pod spec with two pod topology spread constraints. Both match on pods labeled region: us-east , specify a skew of 1 , and do not schedule the pod if it does not meet these requirements. The first constraint distributes pods based on a user-defined label node , and the second constraint distributes pods based on a user-defined label rack . Both constraints must be met for the pod to be scheduled. 4.8.5. Additional resources Understanding how to update labels on nodes 4.9. Descheduler 4.9.1. Descheduler overview While the scheduler is used to determine the most suitable node to host a new pod, the descheduler can be used to evict a running pod so that the pod can be rescheduled onto a more suitable node. 4.9.1.1. About the descheduler You can use the descheduler to evict pods based on specific strategies so that the pods can be rescheduled onto more appropriate nodes. You can benefit from descheduling running pods in situations such as the following: Nodes are underutilized or overutilized. Pod and node affinity requirements, such as taints or labels, have changed and the original scheduling decisions are no longer appropriate for certain nodes. Node failure requires pods to be moved. New nodes are added to clusters. Pods have been restarted too many times. Important The descheduler does not schedule replacement of evicted pods. The scheduler automatically performs this task for the evicted pods. When the descheduler decides to evict pods from a node, it employs the following general mechanism: Pods in the openshift-* and kube-system namespaces are never evicted. Critical pods with priorityClassName set to system-cluster-critical or system-node-critical are never evicted. Static, mirrored, or stand-alone pods that are not part of a replication controller, replica set, deployment, or job are never evicted because these pods will not be recreated. Pods associated with daemon sets are never evicted. Pods with local storage are never evicted. Best effort pods are evicted before burstable and guaranteed pods. All types of pods with the descheduler.alpha.kubernetes.io/evict annotation are eligible for eviction. This annotation is used to override checks that prevent eviction, and the user can select which pod is evicted. Users should know how and if the pod will be recreated. Pods subject to pod disruption budget (PDB) are not evicted if descheduling violates its pod disruption budget (PDB). The pods are evicted by using eviction subresource to handle PDB. 4.9.1.2. Descheduler profiles The following descheduler profiles are available: AffinityAndTaints This profile evicts pods that violate inter-pod anti-affinity, node affinity, and node taints. It enables the following strategies: RemovePodsViolatingInterPodAntiAffinity : removes pods that are violating inter-pod anti-affinity. RemovePodsViolatingNodeAffinity : removes pods that are violating node affinity. RemovePodsViolatingNodeTaints : removes pods that are violating NoSchedule taints on nodes. Pods with a node affinity type of requiredDuringSchedulingIgnoredDuringExecution are removed. TopologyAndDuplicates This profile evicts pods in an effort to evenly spread similar pods, or pods of the same topology domain, among nodes. It enables the following strategies: RemovePodsViolatingTopologySpreadConstraint : finds unbalanced topology domains and tries to evict pods from larger ones when DoNotSchedule constraints are violated. RemoveDuplicates : ensures that there is only one pod associated with a replica set, replication controller, deployment, or job running on same node. If there are more, those duplicate pods are evicted for better pod distribution in a cluster. Warning Do not enable TopologyAndDuplicates with any of the following profiles: SoftTopologyAndDuplicates or CompactAndScale . Enabling these profiles together results in a conflict. LifecycleAndUtilization This profile evicts long-running pods and balances resource usage between nodes. It enables the following strategies: RemovePodsHavingTooManyRestarts : removes pods whose containers have been restarted too many times. Pods where the sum of restarts over all containers (including Init Containers) is more than 100. LowNodeUtilization : finds nodes that are underutilized and evicts pods, if possible, from overutilized nodes in the hope that recreation of evicted pods will be scheduled on these underutilized nodes. A node is considered underutilized if its usage is below 20% for all thresholds (CPU, memory, and number of pods). A node is considered overutilized if its usage is above 50% for any of the thresholds (CPU, memory, and number of pods). Optionally, you can adjust these underutilized/overutilized threshold percentages by setting the Technology Preview field devLowNodeUtilizationThresholds to one the following values: Low for 10%/30%, Medium for 20%/50%, or High for 40%/70%. The default value is Medium . PodLifeTime : evicts pods that are too old. By default, pods that are older than 24 hours are removed. You can customize the pod lifetime value. Warning Do not enable LifecycleAndUtilization with any of the following profiles: LongLifecycle or CompactAndScale . Enabling these profiles together results in a conflict. SoftTopologyAndDuplicates This profile is the same as TopologyAndDuplicates , except that pods with soft topology constraints, such as whenUnsatisfiable: ScheduleAnyway , are also considered for eviction. Warning Do not enable both SoftTopologyAndDuplicates and TopologyAndDuplicates . Enabling both results in a conflict. EvictPodsWithLocalStorage This profile allows pods with local storage to be eligible for eviction. EvictPodsWithPVC This profile allows pods with persistent volume claims to be eligible for eviction. If you are using Kubernetes NFS Subdir External Provisioner , you must add an excluded namespace for the namespace where the provisioner is installed. CompactAndScale This profile enables the HighNodeUtilization strategy, which attempts to evict pods from underutilized nodes to allow a workload to run on a smaller set of nodes. A node is considered underutilized if its usage is below 20% for all thresholds (CPU, memory, and number of pods). Optionally, you can adjust the underutilized percentage by setting the Technology Preview field devHighNodeUtilizationThresholds to one the following values: Minimal for 10%, Modest for 20%, or Moderate for 30%. The default value is Modest . Warning Do not enable CompactAndScale with any of the following profiles: LifecycleAndUtilization , LongLifecycle , or TopologyAndDuplicates . Enabling these profiles together results in a conflict. LongLifecycle This profile balances resource usage between nodes and enables the following strategies: RemovePodsHavingTooManyRestarts : removes pods whose containers have been restarted too many times and pods where the sum of restarts over all containers (including Init Containers) is more than 100. Restarting the VM guest operating system does not increase this count. LowNodeUtilization : evicts pods from overutilized nodes when there are any underutilized nodes. The destination node for the evicted pod will be determined by the scheduler. A node is considered underutilized if its usage is below 20% for all thresholds (CPU, memory, and number of pods). A node is considered overutilized if its usage is above 50% for any of the thresholds (CPU, memory, and number of pods). Warning Do not enable LongLifecycle with any of the following profiles: LifecycleAndUtilization or CompactAndScale . Enabling these profiles together results in a conflict. 4.9.2. Kube Descheduler Operator release notes The Kube Descheduler Operator allows you to evict pods so that they can be rescheduled on more appropriate nodes. These release notes track the development of the Kube Descheduler Operator. For more information, see About the descheduler . 4.9.2.1. Release notes for Kube Descheduler Operator 5.1.1 Issued: 2 December 2024 The following advisory is available for the Kube Descheduler Operator 5.1.1: RHEA-2024:10118 4.9.2.1.1. New features and enhancements This release of the Kube Descheduler Operator updates the Kubernetes version to 1.31. 4.9.2.1.2. Bug fixes This release of the Kube Descheduler Operator addresses several Common Vulnerabilities and Exposures (CVEs). 4.9.2.2. Release notes for Kube Descheduler Operator 5.1.0 Issued: 23 October 2024 The following advisory is available for the Kube Descheduler Operator 5.1.0: RHSA-2024:6341 4.9.2.2.1. New features and enhancements Two new descheduler profiles are now available: CompactAndScale : This profile attempts to evict pods from underutilized nodes to allow a workload to run on a smaller set of nodes. LongLifecycle : This profile balances resource usage between nodes and enables the RemovePodsHavingTooManyRestarts and LowNodeUtilization strategies. For the CompactAndScale profile, you can use the Technology Preview field devHighNodeUtilizationThresholds to adjust the underutilized threshold value. 4.9.2.2.2. Bug fixes This release of the Kube Descheduler Operator addresses several Common Vulnerabilities and Exposures (CVEs). 4.9.3. Evicting pods using the descheduler You can run the descheduler in OpenShift Container Platform by installing the Kube Descheduler Operator and setting the desired profiles and other customizations. 4.9.3.1. Installing the descheduler The descheduler is not available by default. To enable the descheduler, you must install the Kube Descheduler Operator from OperatorHub and enable one or more descheduler profiles. By default, the descheduler runs in predictive mode, which means that it only simulates pod evictions. You must change the mode to automatic for the descheduler to perform the pod evictions. Important If you have enabled hosted control planes in your cluster, set a custom priority threshold to lower the chance that pods in the hosted control plane namespaces are evicted. Set the priority threshold class name to hypershift-control-plane , because it has the lowest priority value ( 100000000 ) of the hosted control plane priority classes. Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. Access to the OpenShift Container Platform web console. Procedure Log in to the OpenShift Container Platform web console. Create the required namespace for the Kube Descheduler Operator. Navigate to Administration Namespaces and click Create Namespace . Enter openshift-kube-descheduler-operator in the Name field, enter openshift.io/cluster-monitoring=true in the Labels field to enable descheduler metrics, and click Create . Install the Kube Descheduler Operator. Navigate to Operators OperatorHub . Type Kube Descheduler Operator into the filter box. Select the Kube Descheduler Operator and click Install . On the Install Operator page, select A specific namespace on the cluster . Select openshift-kube-descheduler-operator from the drop-down menu. Adjust the values for the Update Channel and Approval Strategy to the desired values. Click Install . Create a descheduler instance. From the Operators Installed Operators page, click the Kube Descheduler Operator . Select the Kube Descheduler tab and click Create KubeDescheduler . Edit the settings as necessary. To evict pods instead of simulating the evictions, change the Mode field to Automatic . 4.9.3.2. Configuring descheduler profiles You can configure which profiles the descheduler uses to evict pods. Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. Procedure Edit the KubeDescheduler object: USD oc edit kubedeschedulers.operator.openshift.io cluster -n openshift-kube-descheduler-operator Specify one or more profiles in the spec.profiles section. apiVersion: operator.openshift.io/v1 kind: KubeDescheduler metadata: name: cluster namespace: openshift-kube-descheduler-operator spec: deschedulingIntervalSeconds: 3600 logLevel: Normal managementState: Managed operatorLogLevel: Normal mode: Predictive 1 profileCustomizations: namespaces: 2 excluded: - my-namespace podLifetime: 48h 3 thresholdPriorityClassName: my-priority-class-name 4 evictionLimits: total: 20 5 profiles: 6 - AffinityAndTaints - TopologyAndDuplicates - LifecycleAndUtilization - EvictPodsWithLocalStorage - EvictPodsWithPVC 1 Optional: By default, the descheduler does not evict pods. To evict pods, set mode to Automatic . 2 Optional: Set a list of user-created namespaces to include or exclude from descheduler operations. Use excluded to set a list of namespaces to exclude or use included to set a list of namespaces to include. Note that protected namespaces ( openshift-* , kube-system , hypershift ) are excluded by default. 3 Optional: Enable a custom pod lifetime value for the LifecycleAndUtilization profile. Valid units are s , m , or h . The default pod lifetime is 24 hours. 4 Optional: Specify a priority threshold to consider pods for eviction only if their priority is lower than the specified level. Use the thresholdPriority field to set a numerical priority threshold (for example, 10000 ) or use the thresholdPriorityClassName field to specify a certain priority class name (for example, my-priority-class-name ). If you specify a priority class name, it must already exist or the descheduler will throw an error. Do not set both thresholdPriority and thresholdPriorityClassName . 5 Optional: Set the maximum number of pods to evict during each descheduler run. 6 Add one or more profiles to enable. Available profiles: AffinityAndTaints , TopologyAndDuplicates , LifecycleAndUtilization , SoftTopologyAndDuplicates , EvictPodsWithLocalStorage , EvictPodsWithPVC , CompactAndScale , and LongLifecycle . Ensure that you do not enable profiles that conflict with each other. You can enable multiple profiles; the order that the profiles are specified in is not important. Save the file to apply the changes. 4.9.3.3. Configuring the descheduler interval You can configure the amount of time between descheduler runs. The default is 3600 seconds (one hour). Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. Procedure Edit the KubeDescheduler object: USD oc edit kubedeschedulers.operator.openshift.io cluster -n openshift-kube-descheduler-operator Update the deschedulingIntervalSeconds field to the desired value: apiVersion: operator.openshift.io/v1 kind: KubeDescheduler metadata: name: cluster namespace: openshift-kube-descheduler-operator spec: deschedulingIntervalSeconds: 3600 1 ... 1 Set the number of seconds between descheduler runs. A value of 0 in this field runs the descheduler once and exits. Save the file to apply the changes. 4.9.4. Uninstalling the Kube Descheduler Operator You can remove the Kube Descheduler Operator from OpenShift Container Platform by uninstalling the Operator and removing its related resources. 4.9.4.1. Uninstalling the descheduler You can remove the descheduler from your cluster by removing the descheduler instance and uninstalling the Kube Descheduler Operator. This procedure also cleans up the KubeDescheduler CRD and openshift-kube-descheduler-operator namespace. Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. Access to the OpenShift Container Platform web console. Procedure Log in to the OpenShift Container Platform web console. Delete the descheduler instance. From the Operators Installed Operators page, click Kube Descheduler Operator . Select the Kube Descheduler tab. Click the Options menu to the cluster entry and select Delete KubeDescheduler . In the confirmation dialog, click Delete . Uninstall the Kube Descheduler Operator. Navigate to Operators Installed Operators . Click the Options menu to the Kube Descheduler Operator entry and select Uninstall Operator . In the confirmation dialog, click Uninstall . Delete the openshift-kube-descheduler-operator namespace. Navigate to Administration Namespaces . Enter openshift-kube-descheduler-operator into the filter box. Click the Options menu to the openshift-kube-descheduler-operator entry and select Delete Namespace . In the confirmation dialog, enter openshift-kube-descheduler-operator and click Delete . Delete the KubeDescheduler CRD. Navigate to Administration Custom Resource Definitions . Enter KubeDescheduler into the filter box. Click the Options menu to the KubeDescheduler entry and select Delete CustomResourceDefinition . In the confirmation dialog, click Delete . 4.10. Secondary scheduler 4.10.1. Secondary scheduler overview You can install the Secondary Scheduler Operator to run a custom secondary scheduler alongside the default scheduler to schedule pods. 4.10.1.1. About the Secondary Scheduler Operator The Secondary Scheduler Operator for Red Hat OpenShift provides a way to deploy a custom secondary scheduler in OpenShift Container Platform. The secondary scheduler runs alongside the default scheduler to schedule pods. Pod configurations can specify which scheduler to use. The custom scheduler must have the /bin/kube-scheduler binary and be based on the Kubernetes scheduling framework . Important You can use the Secondary Scheduler Operator to deploy a custom secondary scheduler in OpenShift Container Platform, but Red Hat does not directly support the functionality of the custom secondary scheduler. The Secondary Scheduler Operator creates the default roles and role bindings required by the secondary scheduler. You can specify which scheduling plugins to enable or disable by configuring the KubeSchedulerConfiguration resource for the secondary scheduler. 4.10.2. Secondary Scheduler Operator for Red Hat OpenShift release notes The Secondary Scheduler Operator for Red Hat OpenShift allows you to deploy a custom secondary scheduler in your OpenShift Container Platform cluster. These release notes track the development of the Secondary Scheduler Operator for Red Hat OpenShift. For more information, see About the Secondary Scheduler Operator . 4.10.2.1. Release notes for Secondary Scheduler Operator for Red Hat OpenShift 1.3.1 Issued: 3 October 2024 The following advisory is available for the Secondary Scheduler Operator for Red Hat OpenShift 1.3.1: RHEA-2024:7073 4.10.2.1.1. New features and enhancements This release of the Secondary Scheduler Operator adds support for IBM Z(R) and IBM Power(R). 4.10.2.1.2. Bug fixes This release of the Secondary Scheduler Operator addresses several Common Vulnerabilities and Exposures (CVEs). 4.10.2.1.3. Known issues Currently, you cannot deploy additional resources, such as config maps, CRDs, or RBAC policies through the Secondary Scheduler Operator. Any resources other than roles and role bindings that are required by your custom secondary scheduler must be applied externally. ( WRKLDS-645 ) 4.10.2.2. Release notes for Secondary Scheduler Operator for Red Hat OpenShift 1.3.0 Issued: 1 July 2024 The following advisory is available for the Secondary Scheduler Operator for Red Hat OpenShift 1.3.0: RHSA-2024:3637 4.10.2.2.1. New features and enhancements You can now install and use the Secondary Scheduler Operator in an OpenShift Container Platform cluster running in FIPS mode. Important To enable FIPS mode for your cluster, you must run the installation program from a Red Hat Enterprise Linux (RHEL) computer configured to operate in FIPS mode. For more information about configuring FIPS mode on RHEL, see Switching RHEL to FIPS mode . When running Red Hat Enterprise Linux (RHEL) or Red Hat Enterprise Linux CoreOS (RHCOS) booted in FIPS mode, OpenShift Container Platform core components use the RHEL cryptographic libraries that have been submitted to NIST for FIPS 140-2/140-3 Validation on only the x86_64, ppc64le, and s390x architectures. 4.10.2.2.2. Bug fixes This release of the Secondary Scheduler Operator addresses several Common Vulnerabilities and Exposures (CVEs). 4.10.2.2.3. Known issues Currently, you cannot deploy additional resources, such as config maps, CRDs, or RBAC policies through the Secondary Scheduler Operator. Any resources other than roles and role bindings that are required by your custom secondary scheduler must be applied externally. ( WRKLDS-645 ) 4.10.3. Scheduling pods using a secondary scheduler You can run a custom secondary scheduler in OpenShift Container Platform by installing the Secondary Scheduler Operator, deploying the secondary scheduler, and setting the secondary scheduler in the pod definition. 4.10.3.1. Installing the Secondary Scheduler Operator You can use the web console to install the Secondary Scheduler Operator for Red Hat OpenShift. Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. You have access to the OpenShift Container Platform web console. Procedure Log in to the OpenShift Container Platform web console. Create the required namespace for the Secondary Scheduler Operator for Red Hat OpenShift. Navigate to Administration Namespaces and click Create Namespace . Enter openshift-secondary-scheduler-operator in the Name field and click Create . Install the Secondary Scheduler Operator for Red Hat OpenShift. Navigate to Operators OperatorHub . Enter Secondary Scheduler Operator for Red Hat OpenShift into the filter box. Select the Secondary Scheduler Operator for Red Hat OpenShift and click Install . On the Install Operator page: The Update channel is set to stable , which installs the latest stable release of the Secondary Scheduler Operator for Red Hat OpenShift. Select A specific namespace on the cluster and select openshift-secondary-scheduler-operator from the drop-down menu. Select an Update approval strategy. The Automatic strategy allows Operator Lifecycle Manager (OLM) to automatically update the Operator when a new version is available. The Manual strategy requires a user with appropriate credentials to approve the Operator update. Click Install . Verification Navigate to Operators Installed Operators . Verify that Secondary Scheduler Operator for Red Hat OpenShift is listed with a Status of Succeeded . 4.10.3.2. Deploying a secondary scheduler After you have installed the Secondary Scheduler Operator, you can deploy a secondary scheduler. Prerequisities You are logged in to OpenShift Container Platform as a user with the cluster-admin role. You have access to the OpenShift Container Platform web console. The Secondary Scheduler Operator for Red Hat OpenShift is installed. Procedure Log in to the OpenShift Container Platform web console. Create config map to hold the configuration for the secondary scheduler. Navigate to Workloads ConfigMaps . Click Create ConfigMap . In the YAML editor, enter the config map definition that contains the necessary KubeSchedulerConfiguration configuration. For example: apiVersion: v1 kind: ConfigMap metadata: name: "secondary-scheduler-config" 1 namespace: "openshift-secondary-scheduler-operator" 2 data: "config.yaml": \| apiVersion: kubescheduler.config.k8s.io/v1 kind: KubeSchedulerConfiguration 3 leaderElection: leaderElect: false profiles: - schedulerName: secondary-scheduler 4 plugins: 5 score: disabled: - name: NodeResourcesBalancedAllocation - name: NodeResourcesLeastAllocated 1 The name of the config map. This is used in the Scheduler Config field when creating the SecondaryScheduler CR. 2 The config map must be created in the openshift-secondary-scheduler-operator namespace. 3 The KubeSchedulerConfiguration resource for the secondary scheduler. For more information, see KubeSchedulerConfiguration in the Kubernetes API documentation. 4 The name of the secondary scheduler. Pods that set their spec.schedulerName field to this value are scheduled with this secondary scheduler. 5 The plugins to enable or disable for the secondary scheduler. For a list default scheduling plugins, see Scheduling plugins in the Kubernetes documentation. Click Create . Create the SecondaryScheduler CR: Navigate to Operators Installed Operators . Select Secondary Scheduler Operator for Red Hat OpenShift . Select the Secondary Scheduler tab and click Create SecondaryScheduler . The Name field defaults to cluster ; do not change this name. The Scheduler Config field defaults to secondary-scheduler-config . Ensure that this value matches the name of the config map created earlier in this procedure. In the Scheduler Image field, enter the image name for your custom scheduler. Important Red Hat does not directly support the functionality of your custom secondary scheduler. Click Create . 4.10.3.3. Scheduling a pod using the secondary scheduler To schedule a pod using the secondary scheduler, set the schedulerName field in the pod definition. Prerequisities You are logged in to OpenShift Container Platform as a user with the cluster-admin role. You have access to the OpenShift Container Platform web console. The Secondary Scheduler Operator for Red Hat OpenShift is installed. A secondary scheduler is configured. Procedure Log in to the OpenShift Container Platform web console. Navigate to Workloads Pods . Click Create Pod . In the YAML editor, enter the desired pod configuration and add the schedulerName field: apiVersion: v1 kind: Pod metadata: name: nginx namespace: default spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: nginx image: nginx:1.14.2 ports: - containerPort: 80 securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] schedulerName: secondary-scheduler 1 1 The schedulerName field must match the name that is defined in the config map when you configured the secondary scheduler. Click Create . Verification Log in to the OpenShift CLI. Describe the pod using the following command: USD oc describe pod nginx -n default Example output Name: nginx Namespace: default Priority: 0 Node: ci-ln-t0w4r1k-72292-xkqs4-worker-b-xqkxp/10.0.128.3 ... Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 12s secondary-scheduler Successfully assigned default/nginx to ci-ln-t0w4r1k-72292-xkqs4-worker-b-xqkxp ... In the events table, find the event with a message similar to Successfully assigned <namespace>/<pod_name> to <node_name> . In the "From" column, verify that the event was generated from the secondary scheduler and not the default scheduler. Note You can also check the secondary-scheduler-* pod logs in the openshift-secondary-scheduler-namespace to verify that the pod was scheduled by the secondary scheduler. 4.10.4. Uninstalling the Secondary Scheduler Operator You can remove the Secondary Scheduler Operator for Red Hat OpenShift from OpenShift Container Platform by uninstalling the Operator and removing its related resources. 4.10.4.1. Uninstalling the Secondary Scheduler Operator You can uninstall the Secondary Scheduler Operator for Red Hat OpenShift by using the web console. Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. You have access to the OpenShift Container Platform web console. The Secondary Scheduler Operator for Red Hat OpenShift is installed. Procedure Log in to the OpenShift Container Platform web console. Uninstall the Secondary Scheduler Operator for Red Hat OpenShift Operator. Navigate to Operators Installed Operators . Click the Options menu to the Secondary Scheduler Operator entry and click Uninstall Operator . In the confirmation dialog, click Uninstall . 4.10.4.2. Removing Secondary Scheduler Operator resources Optionally, after uninstalling the Secondary Scheduler Operator for Red Hat OpenShift, you can remove its related resources from your cluster. Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. You have access to the OpenShift Container Platform web console. Procedure Log in to the OpenShift Container Platform web console. Remove CRDs that were installed by the Secondary Scheduler Operator: Navigate to Administration CustomResourceDefinitions . Enter SecondaryScheduler in the Name field to filter the CRDs. Click the Options menu to the SecondaryScheduler CRD and select Delete Custom Resource Definition : Remove the openshift-secondary-scheduler-operator namespace. Navigate to Administration Namespaces . Click the Options menu to the openshift-secondary-scheduler-operator and select Delete Namespace . In the confirmation dialog, enter openshift-secondary-scheduler-operator in the field and click Delete .	[ "oc edit scheduler cluster", "apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster # spec: mastersSchedulable: false profile: HighNodeUtilization 1 #", "apiVersion: v1 kind: Pod metadata: name: with-pod-affinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: 2 - labelSelector: matchExpressions: - key: security 3 operator: In 4 values: - S1 5 topologyKey: topology.kubernetes.io/zone containers: - name: with-pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: with-pod-antiaffinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAntiAffinity: 1 preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 100 3 podAffinityTerm: labelSelector: matchExpressions: - key: security 4 operator: In 5 values: - S2 topologyKey: kubernetes.io/hostname containers: - name: with-pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: security-s1 labels: security: S1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: security-s1 image: docker.io/ocpqe/hello-pod securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault", "oc create -f <pod-spec>.yaml", "apiVersion: v1 kind: Pod metadata: name: security-s1-east spec: affinity: 1 podAffinity: requiredDuringSchedulingIgnoredDuringExecution: 2 - labelSelector: matchExpressions: - key: security 3 values: - S1 operator: In 4 topologyKey: topology.kubernetes.io/zone 5", "oc create -f <pod-spec>.yaml", "apiVersion: v1 kind: Pod metadata: name: security-s1 labels: security: S1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: security-s1 image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "oc create -f <pod-spec>.yaml", "apiVersion: v1 kind: Pod metadata: name: security-s2-east spec: affinity: 1 podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 100 3 podAffinityTerm: labelSelector: matchExpressions: - key: security 4 values: - S1 operator: In 5 topologyKey: kubernetes.io/hostname 6", "oc create -f <pod-spec>.yaml", "apiVersion: v1 kind: Pod metadata: name: team4 labels: team: \"4\" spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: ocp image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: team4a spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: team operator: In values: - \"4\" topologyKey: kubernetes.io/hostname containers: - name: pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: pod-s1 labels: security: s1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: ocp image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: pod-s2 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAntiAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: security operator: In values: - s1 topologyKey: kubernetes.io/hostname containers: - name: pod-antiaffinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: pod-s1 labels: security: s1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: ocp image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: pod-s2 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: podAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: security operator: In values: - s2 topologyKey: kubernetes.io/hostname containers: - name: pod-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "NAME READY STATUS RESTARTS AGE IP NODE pod-s2 0/1 Pending 0 32s <none>", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: podAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: app operator: In values: - test topologyKey: kubernetes.io/hostname #", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: podAntiAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchExpressions: - key: cpu operator: In values: - high topologyKey: kubernetes.io/hostname #", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: podAntiAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: podAffinityTerm: labelSelector: matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-185-229.ec2.internal topologyKey: topology.kubernetes.io/zone #", "oc get pods -o wide", "NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES custom-metrics-autoscaler-operator-5dcc45d656-bhshg 1/1 Running 0 50s 10.131.0.20 ip-10-0-185-229.ec2.internal <none> <none>", "apiVersion: v1 kind: Pod metadata: name: with-node-affinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: nodeAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: 2 nodeSelectorTerms: - matchExpressions: - key: e2e-az-NorthSouth 3 operator: In 4 values: - e2e-az-North 5 - e2e-az-South 6 containers: - name: with-node-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "apiVersion: v1 kind: Pod metadata: name: with-node-affinity spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault affinity: nodeAffinity: 1 preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 1 3 preference: matchExpressions: - key: e2e-az-EastWest 4 operator: In 5 values: - e2e-az-East 6 - e2e-az-West 7 containers: - name: with-node-affinity image: docker.io/ocpqe/hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "oc label node node1 e2e-az-name=e2e-az1", "kind: Node apiVersion: v1 metadata: name: <node_name> labels: e2e-az-name: e2e-az1 #", "apiVersion: v1 kind: Pod metadata: name: s1 spec: affinity: 1 nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: 2 nodeSelectorTerms: - matchExpressions: - key: e2e-az-name 3 values: - e2e-az1 - e2e-az2 operator: In 4 #", "oc create -f <file-name>.yaml", "oc label node node1 e2e-az-name=e2e-az3", "apiVersion: v1 kind: Pod metadata: name: s1 spec: affinity: 1 nodeAffinity: preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 3 preference: matchExpressions: - key: e2e-az-name 4 values: - e2e-az3 operator: In 5 #", "oc create -f <file-name>.yaml", "oc label node node1 zone=us", "kind: Node apiVersion: v1 metadata: name: <node_name> labels: zone: us #", "cat pod-s1.yaml", "apiVersion: v1 kind: Pod metadata: name: pod-s1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - image: \"docker.io/ocpqe/hello-pod\" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: \"zone\" operator: In values: - us #", "oc get pod -o wide", "NAME READY STATUS RESTARTS AGE IP NODE pod-s1 1/1 Running 0 4m IP1 node1", "oc label node node1 zone=emea", "kind: Node apiVersion: v1 metadata: name: <node_name> labels: zone: emea #", "cat pod-s1.yaml", "apiVersion: v1 kind: Pod metadata: name: pod-s1 spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - image: \"docker.io/ocpqe/hello-pod\" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: \"zone\" operator: In values: - us #", "oc describe pod pod-s1", "Events: FirstSeen LastSeen Count From SubObjectPath Type Reason --------- -------- ----- ---- ------------- -------- ------ 1m 33s 8 default-scheduler Warning FailedScheduling No nodes are available that match all of the following predicates:: MatchNodeSelector (1).", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: nodeAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-163-94.us-west-2.compute.internal #", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: nodeAffinity: 1 requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/arch operator: In values: - arm64 - key: kubernetes.io/os operator: In values: - linux #", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-custom-metrics-autoscaler-operator namespace: openshift-keda spec: name: my-package source: my-operators sourceNamespace: operator-registries config: affinity: 1 nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-185-229.ec2.internal #", "oc get pods -o wide", "NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES custom-metrics-autoscaler-operator-5dcc45d656-bhshg 1/1 Running 0 50s 10.131.0.20 ip-10-0-185-229.ec2.internal <none> <none>", "sysctl -a \|grep commit", "# vm.overcommit_memory = 0 #", "sysctl -a \|grep panic", "# vm.panic_on_oom = 0 #", "apiVersion: v1 kind: Node metadata: name: my-node # spec: taints: - effect: NoExecute key: key1 value: value1 #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key1\" operator: \"Equal\" value: \"value1\" effect: \"NoExecute\" tolerationSeconds: 3600 #", "apiVersion: v1 kind: Node metadata: annotations: machine.openshift.io/machine: openshift-machine-api/ci-ln-62s7gtb-f76d1-v8jxv-master-0 machineconfiguration.openshift.io/currentConfig: rendered-master-cdc1ab7da414629332cc4c3926e6e59c name: my-node # spec: taints: - effect: NoSchedule key: node-role.kubernetes.io/master #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key1\" operator: \"Equal\" value: \"value1\" effect: \"NoExecute\" tolerationSeconds: 3600 #", "oc adm taint nodes node1 key1=value1:NoSchedule", "oc adm taint nodes node1 key1=value1:NoExecute", "oc adm taint nodes node1 key2=value2:NoSchedule", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key1\" operator: \"Equal\" value: \"value1\" effect: \"NoSchedule\" - key: \"key1\" operator: \"Equal\" value: \"value1\" effect: \"NoExecute\" #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: node.kubernetes.io/not-ready operator: Exists effect: NoExecute tolerationSeconds: 300 1 - key: node.kubernetes.io/unreachable operator: Exists effect: NoExecute tolerationSeconds: 300 #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - operator: \"Exists\" #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key1\" 1 value: \"value1\" operator: \"Equal\" effect: \"NoExecute\" tolerationSeconds: 3600 2 #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key1\" operator: \"Exists\" 1 effect: \"NoExecute\" tolerationSeconds: 3600 #", "oc adm taint nodes <node_name> <key>=<value>:<effect>", "oc adm taint nodes node1 key1=value1:NoExecute", "apiVersion: v1 kind: Node metadata: annotations: machine.openshift.io/machine: openshift-machine-api/ci-ln-62s7gtb-f76d1-v8jxv-master-0 machineconfiguration.openshift.io/currentConfig: rendered-master-cdc1ab7da414629332cc4c3926e6e59c name: my-node # spec: taints: - effect: NoSchedule key: node-role.kubernetes.io/master #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key1\" 1 value: \"value1\" operator: \"Equal\" effect: \"NoExecute\" tolerationSeconds: 3600 2 #", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key1\" operator: \"Exists\" effect: \"NoExecute\" tolerationSeconds: 3600 #", "oc edit machineset <machineset>", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: my-machineset # spec: # template: # spec: taints: - effect: NoExecute key: key1 value: value1 #", "oc scale --replicas=0 machineset <machineset> -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: <machineset> namespace: openshift-machine-api spec: replicas: 0", "oc scale --replicas=2 machineset <machineset> -n openshift-machine-api", "oc edit machineset <machineset> -n openshift-machine-api", "oc adm taint nodes node1 dedicated=groupName:NoSchedule", "kind: Node apiVersion: v1 metadata: name: my-node # spec: taints: - key: dedicated value: groupName effect: NoSchedule #", "kind: Project apiVersion: project.openshift.io/v1 metadata: name: <project_name> 1 annotations: openshift.io/node-selector: '<label>' 2 scheduler.alpha.kubernetes.io/defaultTolerations: >- [{\"operator\": \"Exists\", \"effect\": \"NoSchedule\", \"key\": \"<key_name>\"} 3 ]", "oc apply -f project.yaml", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"disktype\" value: \"ssd\" operator: \"Equal\" effect: \"NoSchedule\" tolerationSeconds: 3600 #", "oc adm taint nodes <node-name> disktype=ssd:NoSchedule", "oc adm taint nodes <node-name> disktype=ssd:PreferNoSchedule", "kind: Node apiVersion: v1 metadata: name: my_node # spec: taints: - key: disktype value: ssd effect: PreferNoSchedule #", "oc adm taint nodes <node-name> <key>-", "oc adm taint nodes ip-10-0-132-248.ec2.internal key1-", "node/ip-10-0-132-248.ec2.internal untainted", "apiVersion: v1 kind: Pod metadata: name: my-pod # spec: tolerations: - key: \"key2\" operator: \"Exists\" effect: \"NoExecute\" tolerationSeconds: 3600 #", "kind: Node apiVersion: v1 metadata: name: ip-10-0-131-14.ec2.internal selfLink: /api/v1/nodes/ip-10-0-131-14.ec2.internal uid: 7bc2580a-8b8e-11e9-8e01-021ab4174c74 resourceVersion: '478704' creationTimestamp: '2019-06-10T14:46:08Z' labels: kubernetes.io/os: linux topology.kubernetes.io/zone: us-east-1a node.openshift.io/os_version: '4.5' node-role.kubernetes.io/worker: '' topology.kubernetes.io/region: us-east-1 node.openshift.io/os_id: rhcos node.kubernetes.io/instance-type: m4.large kubernetes.io/hostname: ip-10-0-131-14 kubernetes.io/arch: amd64 region: east 1 type: user-node #", "apiVersion: v1 kind: Pod metadata: name: s1 # spec: nodeSelector: 1 region: east type: user-node #", "apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster # spec: defaultNodeSelector: type=user-node,region=east #", "apiVersion: v1 kind: Node metadata: name: ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 # labels: region: east type: user-node #", "apiVersion: v1 kind: Pod metadata: name: s1 # spec: nodeSelector: region: east #", "NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-s1 1/1 Running 0 20s 10.131.2.6 ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 <none> <none>", "apiVersion: v1 kind: Namespace metadata: name: east-region annotations: openshift.io/node-selector: \"region=east\" #", "apiVersion: v1 kind: Node metadata: name: ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 # labels: region: east type: user-node #", "apiVersion: v1 kind: Pod metadata: namespace: east-region # spec: nodeSelector: region: east type: user-node #", "NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES pod-s1 1/1 Running 0 20s 10.131.2.6 ci-ln-qg1il3k-f76d1-hlmhl-worker-b-df2s4 <none> <none>", "apiVersion: v1 kind: Pod metadata: name: west-region # spec: nodeSelector: region: west #", "oc describe pod router-default-66d5cf9464-7pwkc", "kind: Pod apiVersion: v1 metadata: Name: router-default-66d5cf9464-7pwkc Namespace: openshift-ingress Controlled By: ReplicaSet/router-default-66d5cf9464", "apiVersion: v1 kind: Pod metadata: name: router-default-66d5cf9464-7pwkc ownerReferences: - apiVersion: apps/v1 kind: ReplicaSet name: router-default-66d5cf9464 uid: d81dd094-da26-11e9-a48a-128e7edf0312 controller: true blockOwnerDeletion: true", "oc patch MachineSet <name> --type='json' -p='[{\"op\":\"add\",\"path\":\"/spec/template/spec/metadata/labels\", \"value\":{\"<key>\"=\"<value>\",\"<key>\"=\"<value>\"}}]' -n openshift-machine-api", "oc patch MachineSet abc612-msrtw-worker-us-east-1c --type='json' -p='[{\"op\":\"add\",\"path\":\"/spec/template/spec/metadata/labels\", \"value\":{\"type\":\"user-node\",\"region\":\"east\"}}]' -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: xf2bd-infra-us-east-2a namespace: openshift-machine-api spec: template: spec: metadata: labels: region: \"east\" type: \"user-node\"", "oc edit MachineSet abc612-msrtw-worker-us-east-1c -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet spec: template: metadata: spec: metadata: labels: region: east type: user-node", "oc label nodes <name> <key>=<value>", "oc label nodes ip-10-0-142-25.ec2.internal type=user-node region=east", "kind: Node apiVersion: v1 metadata: name: hello-node-6fbccf8d9 labels: type: \"user-node\" region: \"east\"", "oc get nodes -l type=user-node,region=east", "NAME STATUS ROLES AGE VERSION ip-10-0-142-25.ec2.internal Ready worker 17m v1.30.3", "kind: ReplicaSet apiVersion: apps/v1 metadata: name: hello-node-6fbccf8d9 spec: template: metadata: creationTimestamp: null labels: ingresscontroller.operator.openshift.io/deployment-ingresscontroller: default pod-template-hash: 66d5cf9464 spec: nodeSelector: kubernetes.io/os: linux node-role.kubernetes.io/worker: '' type: user-node 1", "apiVersion: v1 kind: Pod metadata: name: hello-node-6fbccf8d9 spec: nodeSelector: region: east type: user-node", "oc edit scheduler cluster", "apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster spec: defaultNodeSelector: type=user-node,region=east 1 mastersSchedulable: false", "oc patch MachineSet <name> --type='json' -p='[{\"op\":\"add\",\"path\":\"/spec/template/spec/metadata/labels\", \"value\":{\"<key>\"=\"<value>\",\"<key>\"=\"<value>\"}}]' -n openshift-machine-api 1", "oc patch MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c --type='json' -p='[{\"op\":\"add\",\"path\":\"/spec/template/spec/metadata/labels\", \"value\":{\"type\":\"user-node\",\"region\":\"east\"}}]' -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: <machineset> namespace: openshift-machine-api spec: template: spec: metadata: labels: region: \"east\" type: \"user-node\"", "oc edit MachineSet abc612-msrtw-worker-us-east-1c -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet spec: template: metadata: spec: metadata: labels: region: east type: user-node", "oc scale --replicas=0 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api", "oc scale --replicas=1 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api", "oc get nodes -l <key>=<value>", "oc get nodes -l type=user-node", "NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-c-vmqzp Ready worker 61s v1.30.3", "oc label nodes <name> <key>=<value>", "oc label nodes ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 type=user-node region=east", "kind: Node apiVersion: v1 metadata: name: <node_name> labels: type: \"user-node\" region: \"east\"", "oc get nodes -l <key>=<value>,<key>=<value>", "oc get nodes -l type=user-node,region=east", "NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 Ready worker 17m v1.30.3", "Error from server (Forbidden): error when creating \"pod.yaml\": pods \"pod-4\" is forbidden: pod node label selector conflicts with its project node label selector", "oc edit namespace <name>", "apiVersion: v1 kind: Namespace metadata: annotations: openshift.io/node-selector: \"type=user-node,region=east\" 1 openshift.io/description: \"\" openshift.io/display-name: \"\" openshift.io/requester: kube:admin openshift.io/sa.scc.mcs: s0:c30,c5 openshift.io/sa.scc.supplemental-groups: 1000880000/10000 openshift.io/sa.scc.uid-range: 1000880000/10000 creationTimestamp: \"2021-05-10T12:35:04Z\" labels: kubernetes.io/metadata.name: demo name: demo resourceVersion: \"145537\" uid: 3f8786e3-1fcb-42e3-a0e3-e2ac54d15001 spec: finalizers: - kubernetes", "oc patch MachineSet <name> --type='json' -p='[{\"op\":\"add\",\"path\":\"/spec/template/spec/metadata/labels\", \"value\":{\"<key>\"=\"<value>\",\"<key>\"=\"<value>\"}}]' -n openshift-machine-api", "oc patch MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c --type='json' -p='[{\"op\":\"add\",\"path\":\"/spec/template/spec/metadata/labels\", \"value\":{\"type\":\"user-node\",\"region\":\"east\"}}]' -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: <machineset> namespace: openshift-machine-api spec: template: spec: metadata: labels: region: \"east\" type: \"user-node\"", "oc edit MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: spec: template: metadata: spec: metadata: labels: region: east type: user-node", "oc scale --replicas=0 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api", "oc scale --replicas=1 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api", "oc get nodes -l <key>=<value>", "oc get nodes -l type=user-node,region=east", "NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-c-vmqzp Ready worker 61s v1.30.3", "oc label <resource> <name> <key>=<value>", "oc label nodes ci-ln-l8nry52-f76d1-hl7m7-worker-c-tgq49 type=user-node region=east", "kind: Node apiVersion: v1 metadata: name: <node_name> labels: type: \"user-node\" region: \"east\"", "oc get nodes -l <key>=<value>", "oc get nodes -l type=user-node,region=east", "NAME STATUS ROLES AGE VERSION ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 Ready worker 17m v1.30.3", "apiVersion: v1 kind: Pod metadata: name: my-pod labels: region: us-east spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault topologySpreadConstraints: - maxSkew: 1 1 topologyKey: topology.kubernetes.io/zone 2 whenUnsatisfiable: DoNotSchedule 3 labelSelector: 4 matchLabels: region: us-east 5 matchLabelKeys: - my-pod-label 6 containers: - image: \"docker.io/ocpqe/hello-pod\" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "kind: Pod apiVersion: v1 metadata: name: my-pod labels: region: us-east spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault topologySpreadConstraints: - maxSkew: 1 topologyKey: topology.kubernetes.io/zone whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: region: us-east containers: - image: \"docker.io/ocpqe/hello-pod\" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "kind: Pod apiVersion: v1 metadata: name: my-pod-2 labels: region: us-east spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault topologySpreadConstraints: - maxSkew: 1 topologyKey: node whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: region: us-east - maxSkew: 1 topologyKey: rack whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: region: us-east containers: - image: \"docker.io/ocpqe/hello-pod\" name: hello-pod securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL]", "oc edit kubedeschedulers.operator.openshift.io cluster -n openshift-kube-descheduler-operator", "apiVersion: operator.openshift.io/v1 kind: KubeDescheduler metadata: name: cluster namespace: openshift-kube-descheduler-operator spec: deschedulingIntervalSeconds: 3600 logLevel: Normal managementState: Managed operatorLogLevel: Normal mode: Predictive 1 profileCustomizations: namespaces: 2 excluded: - my-namespace podLifetime: 48h 3 thresholdPriorityClassName: my-priority-class-name 4 evictionLimits: total: 20 5 profiles: 6 - AffinityAndTaints - TopologyAndDuplicates - LifecycleAndUtilization - EvictPodsWithLocalStorage - EvictPodsWithPVC", "oc edit kubedeschedulers.operator.openshift.io cluster -n openshift-kube-descheduler-operator", "apiVersion: operator.openshift.io/v1 kind: KubeDescheduler metadata: name: cluster namespace: openshift-kube-descheduler-operator spec: deschedulingIntervalSeconds: 3600 1", "apiVersion: v1 kind: ConfigMap metadata: name: \"secondary-scheduler-config\" 1 namespace: \"openshift-secondary-scheduler-operator\" 2 data: \"config.yaml\": \| apiVersion: kubescheduler.config.k8s.io/v1 kind: KubeSchedulerConfiguration 3 leaderElection: leaderElect: false profiles: - schedulerName: secondary-scheduler 4 plugins: 5 score: disabled: - name: NodeResourcesBalancedAllocation - name: NodeResourcesLeastAllocated", "apiVersion: v1 kind: Pod metadata: name: nginx namespace: default spec: securityContext: runAsNonRoot: true seccompProfile: type: RuntimeDefault containers: - name: nginx image: nginx:1.14.2 ports: - containerPort: 80 securityContext: allowPrivilegeEscalation: false capabilities: drop: [ALL] schedulerName: secondary-scheduler 1", "oc describe pod nginx -n default", "Name: nginx Namespace: default Priority: 0 Node: ci-ln-t0w4r1k-72292-xkqs4-worker-b-xqkxp/10.0.128.3 Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 12s secondary-scheduler Successfully assigned default/nginx to ci-ln-t0w4r1k-72292-xkqs4-worker-b-xqkxp" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.17/html/nodes/controlling-pod-placement-onto-nodes-scheduling
function::user_string2_utf32	function::user_string2_utf32 Name function::user_string2_utf32 - Retrieves UTF-32 string from user memory with alternative error string Synopsis Arguments addr The user address to retrieve the string from err_msg The error message to return when data isn't available Description This function returns a null terminated UTF-8 string converted from the UTF-32 string at a given user memory address. Reports the given error message on string copy fault or conversion error.	[ "user_string2_utf32:string(addr:long,err_msg:string)" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/systemtap_tapset_reference/api-user-string2-utf32
Appendix A. Fuse Console Configuration Properties	Appendix A. Fuse Console Configuration Properties By default, the Fuse Console configuration is defined in the hawtconfig.json file. You can customize the Fuse Console configuration information, such as title, logo, and login page information. Table A.1, "Fuse Console Configuration Properties" provides a description of the properties and lists whether or not each property requires a value. Table A.1. Fuse Console Configuration Properties Section Property Name Default Value Description Required? About Title Red Hat Fuse Management Console The title that shows on the About page of the Fuse Console. Required productInfo Empty value Product information that shows on the About page of the Fuse Console. Optional additionalInfo Empty value Any additional information that shows on the About page of the Fuse Console. Optional	null	https://docs.redhat.com/en/documentation/red_hat_fuse/7.13/html/managing_fuse_on_jboss_eap_standalone/r_fuse-console-configuration
Chapter 132. SSH	Chapter 132. SSH Since Camel 2.10 Both producer and consumer are supported The SSH component enables access to SSH servers so that you can send an SSH command and process the response. 132.1. Dependencies When using camel-ssh with Red Hat build of Camel Spring Boot, add the following Maven dependency to your pom.xml to have support for auto configuration: <dependency> <groupId>org.apache.camel.springboot</groupId> <artifactId>camel-ssh-starter</artifactId> </dependency> 132.2. URI format 132.3. Configuring Options Camel components are configured on two levels: Component level Endpoint level 132.3.1. Component Level Options The component level is the highest level. The configurations you define at this level are inherited by all the endpoints. For example, a component can have security settings, credentials for authentication, urls for network connection, and so on. Since components typically have pre-configured defaults for the most common cases, you may need to only configure a few component options, or maybe none at all. You can configure components with Component DSL in a configuration file (application.properties\|yaml), or directly with Java code. 132.3.2. Endpoint Level Options At the Endpoint level you have many options, which you can use to configure what you want the endpoint to do. The options are categorized according to whether the endpoint is used as a consumer (from) or as a producer (to) or used for both. You can configure endpoints directly in the endpoint URI as path and query parameters. You can also use Endpoint DSL and DataFormat DSL as type safe ways of configuring endpoints and data formats in Java. When configuring options, use Property Placeholders for urls, port numbers, sensitive information, and other settings. Placeholders allows you to externalize the configuration from your code, giving you more flexible and reusable code. 132.4. Component Options The SSH component supports 25 options, which are listed below. Name Description Default Type failOnUnknownHost (common) Specifies whether a connection to an unknown host should fail or not. This value is only checked when the property knownHosts is set. false boolean knownHostsResource (common) Sets the resource path for a known_hosts file. String timeout (common) Sets the timeout in milliseconds to wait in establishing the remote SSH server connection. Defaults to 30000 milliseconds. 30000 long bridgeErrorHandler (consumer) Allows for bridging the consumer to the Camel routing Error Handler, which mean any exceptions (if possible) occurred while the Camel consumer is trying to pickup incoming messages, or the likes, will now be processed as a message and handled by the routing Error Handler. Important: This is only possible if the 3rd party component allows Camel to be alerted if an exception was thrown. Some components handle this internally only, and therefore bridgeErrorHandler is not possible. In other situations we may improve the Camel component to hook into the 3rd party component and make this possible for future releases. By default the consumer will use the org.apache.camel.spi.ExceptionHandler to deal with exceptions, that will be logged at WARN or ERROR level and ignored. false boolean pollCommand (consumer) Sets the command string to send to the remote SSH server during every poll cycle. Only works with camel-ssh component being used as a consumer, i.e. from(ssh://... ) You may need to end your command with a newline, and that must be URL encoded %0A. String lazyStartProducer (producer) Whether the producer should be started lazy (on the first message). By starting lazy you can use this to allow CamelContext and routes to startup in situations where a producer may otherwise fail during starting and cause the route to fail being started. By deferring this startup to be lazy then the startup failure can be handled during routing messages via Camel's routing error handlers. Beware that when the first message is processed then creating and starting the producer may take a little time and prolong the total processing time of the processing. false boolean autowiredEnabled (advanced) Whether autowiring is enabled. This is used for automatic autowiring options (the option must be marked as autowired) by looking up in the registry to find if there is a single instance of matching type, which then gets configured on the component. This can be used for automatic configuring JDBC data sources, JMS connection factories, AWS Clients, etc. true boolean channelType (advanced) Sets the channel type to pass to the Channel as part of command execution. Defaults to exec. exec String clientBuilder (advanced) Autowired Instance of ClientBuilder used by the producer or consumer to create a new SshClient. ClientBuilder compressions (advanced) Whether to use compression, and if so which. String configuration (advanced) Component configuration. SshConfiguration shellPrompt (advanced) Sets the shellPrompt to be dropped when response is read after command execution. String sleepForShellPrompt (advanced) Sets the sleep period in milliseconds to wait reading response from shell prompt. Defaults to 100 milliseconds. 100 long healthCheckConsumerEnabled (health) Used for enabling or disabling all consumer based health checks from this component. true boolean healthCheckProducerEnabled (health) Used for enabling or disabling all producer based health checks from this component. Note By default all producer based health-checks are disabled. You can turn on producer checks globally by setting camel.health.producersEnabled=true . true boolean certResource (security) Sets the resource path of the certificate to use for Authentication. Will use ResourceHelperKeyPairProvider to resolve file based certificate, and depends on keyType setting. String certResourcePassword (security) Sets the password to use in loading certResource, if certResource is an encrypted key. String ciphers (security) Comma-separated list of allowed/supported ciphers in their order of preference. String kex (security) Comma-separated list of allowed/supported key exchange algorithms in their order of preference. String keyPairProvider (security) Sets the KeyPairProvider reference to use when connecting using Certificates to the remote SSH Server. KeyPairProvider keyType (security) Sets the key type to pass to the KeyPairProvider as part of authentication. KeyPairProvider.loadKey(... ) will be passed this value. From Camel 3.0.0 / 2.25.0, by default Camel will select the first available KeyPair that is loaded. Prior to this, a KeyType of 'ssh-rsa' was enforced by default. String macs (security) Comma-separated list of allowed/supported message authentication code algorithms in their order of preference. The MAC algorithm is used for data integrity protection. String password (security) Sets the password to use in connecting to remote SSH server. Requires keyPairProvider to be set to null. String signatures (security) Comma-separated list of allowed/supported signature algorithms in their order of preference. String username (security) Sets the username to use in logging into the remote SSH server. String 132.5. Endpoint Options The SSH endpoint is configured using URI syntax: With the following path and query parameters: 132.5.1. Path Parameters (2 parameters) Name Description Default Type host (common) Required Sets the hostname of the remote SSH server. String port (common) Sets the port number for the remote SSH server. 22 int 132.5.2. Query Parameters (39 parameters) Name Description Default Type failOnUnknownHost (common) Specifies whether a connection to an unknown host should fail or not. This value is only checked when the property knownHosts is set. false boolean knownHostsResource (common) Sets the resource path for a known_hosts file. String timeout (common) Sets the timeout in milliseconds to wait in establishing the remote SSH server connection. Defaults to 30000 milliseconds. 30000 long pollCommand (consumer) Sets the command string to send to the remote SSH server during every poll cycle. Only works with camel-ssh component being used as a consumer, i.e. from(ssh://... ) You may need to end your command with a newline, and that must be URL encoded %0A. String sendEmptyMessageWhenIdle (consumer) If the polling consumer did not poll any files, you can enable this option to send an empty message (no body) instead. false boolean bridgeErrorHandler (consumer (advanced)) Allows for bridging the consumer to the Camel routing Error Handler, which mean any exceptions (if possible) occurred while the Camel consumer is trying to pickup incoming messages, or the likes, will now be processed as a message and handled by the routing Error Handler. Important: This is only possible if the 3rd party component allows Camel to be alerted if an exception was thrown. Some components handle this internally only, and therefore bridgeErrorHandler is not possible. In other situations we may improve the Camel component to hook into the 3rd party component and make this possible for future releases. By default the consumer will use the org.apache.camel.spi.ExceptionHandler to deal with exceptions, that will be logged at WARN or ERROR level and ignored. false boolean exceptionHandler (consumer (advanced)) To let the consumer use a custom ExceptionHandler. Notice if the option bridgeErrorHandler is enabled then this option is not in use. By default the consumer will deal with exceptions, that will be logged at WARN or ERROR level and ignored. ExceptionHandler exchangePattern (consumer (advanced)) Sets the exchange pattern when the consumer creates an exchange. Enum values: InOnly InOut ExchangePattern pollStrategy (consumer (advanced)) A pluggable org.apache.camel.PollingConsumerPollingStrategy allowing you to provide your custom implementation to control error handling usually occurred during the poll operation before an Exchange have been created and being routed in Camel. PollingConsumerPollStrategy lazyStartProducer (producer (advanced)) Whether the producer should be started lazy (on the first message). By starting lazy you can use this to allow CamelContext and routes to startup in situations where a producer may otherwise fail during starting and cause the route to fail being started. By deferring this startup to be lazy then the startup failure can be handled during routing messages via Camel's routing error handlers. Beware that when the first message is processed then creating and starting the producer may take a little time and prolong the total processing time of the processing. false boolean channelType (advanced) Sets the channel type to pass to the Channel as part of command execution. Defaults to exec. exec String clientBuilder (advanced) Autowired Instance of ClientBuilder used by the producer or consumer to create a new SshClient. ClientBuilder compressions (advanced) Whether to use compression, and if so which. String shellPrompt (advanced) Sets the shellPrompt to be dropped when response is read after command execution. String sleepForShellPrompt (advanced) Sets the sleep period in milliseconds to wait reading response from shell prompt. Defaults to 100 milliseconds. 100 long backoffErrorThreshold (scheduler) The number of subsequent error polls (failed due some error) that should happen before the backoffMultipler should kick-in. int backoffIdleThreshold (scheduler) The number of subsequent idle polls that should happen before the backoffMultipler should kick-in. int backoffMultiplier (scheduler) To let the scheduled polling consumer backoff if there has been a number of subsequent idles/errors in a row. The multiplier is then the number of polls that will be skipped before the actual attempt is happening again. When this option is in use then backoffIdleThreshold and/or backoffErrorThreshold must also be configured. int delay (scheduler) Milliseconds before the poll. 500 long greedy (scheduler) If greedy is enabled, then the ScheduledPollConsumer will run immediately again, if the run polled 1 or more messages. false boolean initialDelay (scheduler) Milliseconds before the first poll starts. 1000 long repeatCount (scheduler) Specifies a maximum limit of number of fires. So if you set it to 1, the scheduler will only fire once. If you set it to 5, it will only fire five times. A value of zero or negative means fire forever. 0 long runLoggingLevel (scheduler) The consumer logs a start/complete log line when it polls. This option allows you to configure the logging level for that. Enum values: TRACE DEBUG INFO WARN ERROR OFF TRACE LoggingLevel scheduledExecutorService (scheduler) Allows for configuring a custom/shared thread pool to use for the consumer. By default each consumer has its own single threaded thread pool. ScheduledExecutorService scheduler (scheduler) To use a cron scheduler from either camel-spring or camel-quartz component. Use value spring or quartz for built in scheduler. none Object schedulerProperties (scheduler) To configure additional properties when using a custom scheduler or any of the Quartz, Spring based scheduler. Map startScheduler (scheduler) Whether the scheduler should be auto started. true boolean timeUnit (scheduler) Time unit for initialDelay and delay options. Enum values: NANOSECONDS MICROSECONDS MILLISECONDS SECONDS MINUTES HOURS DAYS MILLISECONDS TimeUnit useFixedDelay (scheduler) Controls if fixed delay or fixed rate is used. See ScheduledExecutorService in JDK for details. true boolean certResource (security) Sets the resource path of the certificate to use for Authentication. Will use ResourceHelperKeyPairProvider to resolve file based certificate, and depends on keyType setting. String certResourcePassword (security) Sets the password to use in loading certResource, if certResource is an encrypted key. String ciphers (security) Comma-separated list of allowed/supported ciphers in their order of preference. String kex (security) Comma-separated list of allowed/supported key exchange algorithms in their order of preference. String keyPairProvider (security) Sets the KeyPairProvider reference to use when connecting using Certificates to the remote SSH Server. KeyPairProvider keyType (security) Sets the key type to pass to the KeyPairProvider as part of authentication. KeyPairProvider.loadKey(... ) will be passed this value. From Camel 3.0.0 / 2.25.0, by default Camel will select the first available KeyPair that is loaded. Prior to this, a KeyType of 'ssh-rsa' was enforced by default. String macs (security) Comma-separated list of allowed/supported message authentication code algorithms in their order of preference. The MAC algorithm is used for data integrity protection. String password (security) Sets the password to use in connecting to remote SSH server. Requires keyPairProvider to be set to null. String signatures (security) Comma-separated list of allowed/supported signature algorithms in their order of preference. String username (security) Sets the username to use in logging into the remote SSH server. String 132.6. Message Headers The SSH component supports 4 message header(s), which is/are listed below: Name Description Default Type CamelSshUsername (common) Constant: USERNAME_HEADER The user name. String CamelSshPassword (common) Constant: PASSWORD_HEADER The password. String CamelSshStderr (common) Constant: STDERR The value of this header is a InputStream with the standard error stream of the executable. InputStream CamelSshExitValue (common) Constant: EXIT_VALUE The value of this header is the exit value that is returned, after the execution. By convention a non-zero status exit value indicates abnormal termination. Note that the exit value is OS dependent. Integer 132.7. Usage as a Producer endpoint When the SSH Component is used as a Producer (`.to("ssh://... ")`), it sends the message body as the command to execute on the remote SSH server. XML DSL example Note that the command has an XML encoded newline (` `). <route id="camel-example-ssh-producer"> <from uri="direct:exampleSshProducer"/> <setBody> <constant>features:list </constant> </setBody> <to uri="ssh://karaf:karaf@localhost:8101"/> <log message="USD{body}"/> </route> 132.8. Authentication The SSH Component can authenticate against the remote SSH server using one of two mechanisms: Public Key certificate Username/password Configuring how the SSH Component does authentication is based on how and which options are set. First, it will look to see if the certResource option has been set, and if so, use it to locate the referenced Public Key certificate and use that for authentication. If certResource is not set, it will look to see if a keyPairProvider has been set, and if so, it will use that for certificate-based authentication. If neither certResource nor keyPairProvider are set, it will use the username and password options for authentication. Even though the username and password are provided in the endpoint configuration and headers set with SshConstants.USERNAME_HEADER ( CamelSshUsername ) and SshConstants.PASSWORD_HEADER ( CamelSshPassword ), the endpoint configuration is surpassed and credentials set in the headers are used. The following route fragment shows an SSH polling consumer using a certificate from the classpath. XML DSL <route> <from uri="ssh://scott@localhost:8101?certResource=classpath:test_rsa&useFixedDelay=true&delay=5000&pollCommand=features:list%0A"/> <log message="USD{body}"/> </route> Java DSL from("ssh://scott@localhost:8101?certResource=classpath:test_rsa&useFixedDelay=true&delay=5000&pollCommand=features:list%0A") .log("USD{body}"); An example of using Public Key authentication is provided in examples/camel-example-ssh-security . 132.9. Certificate Dependencies You need to add some additional runtime dependencies if you use certificate-based authentication. You may need to use later versions depending on what version of Camel you are using. The component uses sshd-core library which is based on either bouncycastle or eddsa security providers. camel-ssh is picking explicitly bouncycastle as security provider. <dependency> <groupId>org.apache.sshd</groupId> <artifactId>sshd-core</artifactId> <version>2.8.0</version> </dependency> <dependency> <groupId>org.bouncycastle</groupId> <artifactId>bcpg-jdk18on</artifactId> <version>1.71</version> </dependency> <dependency> <groupId>org.bouncycastle</groupId> <artifactId>bcpkix-jdk18on</artifactId> <version>1.71</version> </dependency> 132.10. Spring Boot Auto-Configuration The component supports 26 options, which are listed below. Name Description Default Type camel.component.ssh.autowired-enabled Whether autowiring is enabled. This is used for automatic autowiring options (the option must be marked as autowired) by looking up in the registry to find if there is a single instance of matching type, which then gets configured on the component. This can be used for automatic configuring JDBC data sources, JMS connection factories, AWS Clients, etc. true Boolean camel.component.ssh.bridge-error-handler Allows for bridging the consumer to the Camel routing Error Handler, which mean any exceptions (if possible) occurred while the Camel consumer is trying to pickup incoming messages, or the likes, will now be processed as a message and handled by the routing Error Handler. Important: This is only possible if the 3rd party component allows Camel to be alerted if an exception was thrown. Some components handle this internally only, and therefore bridgeErrorHandler is not possible. In other situations we may improve the Camel component to hook into the 3rd party component and make this possible for future releases. By default the consumer will use the org.apache.camel.spi.ExceptionHandler to deal with exceptions, that will be logged at WARN or ERROR level and ignored. false Boolean camel.component.ssh.cert-resource Sets the resource path of the certificate to use for Authentication. Will use ResourceHelperKeyPairProvider to resolve file based certificate, and depends on keyType setting. String camel.component.ssh.cert-resource-password Sets the password to use in loading certResource, if certResource is an encrypted key. String camel.component.ssh.channel-type Sets the channel type to pass to the Channel as part of command execution. Defaults to exec. exec String camel.component.ssh.ciphers Comma-separated list of allowed/supported ciphers in their order of preference. String camel.component.ssh.client-builder Instance of ClientBuilder used by the producer or consumer to create a new SshClient. The option is a org.apache.sshd.client.ClientBuilder type. ClientBuilder camel.component.ssh.compressions Whether to use compression, and if so which. String camel.component.ssh.configuration Component configuration. The option is a org.apache.camel.component.ssh.SshConfiguration type. SshConfiguration camel.component.ssh.enabled Whether to enable auto configuration of the ssh component. This is enabled by default. Boolean camel.component.ssh.fail-on-unknown-host Specifies whether a connection to an unknown host should fail or not. This value is only checked when the property knownHosts is set. false Boolean camel.component.ssh.health-check-consumer-enabled Used for enabling or disabling all consumer based health checks from this component. true Boolean camel.component.ssh.health-check-producer-enabled Used for enabling or disabling all producer based health checks from this component. Notice: Camel has by default disabled all producer based health-checks. You can turn on producer checks globally by setting camel.health.producersEnabled=true. true Boolean camel.component.ssh.kex Comma-separated list of allowed/supported key exchange algorithms in their order of preference. String camel.component.ssh.key-pair-provider Sets the KeyPairProvider reference to use when connecting using Certificates to the remote SSH Server. The option is a org.apache.sshd.common.keyprovider.KeyPairProvider type. KeyPairProvider camel.component.ssh.key-type Sets the key type to pass to the KeyPairProvider as part of authentication. KeyPairProvider.loadKey(... ) will be passed this value. From Camel 3.0.0 / 2.25.0, by default Camel will select the first available KeyPair that is loaded. Prior to this, a KeyType of 'ssh-rsa' was enforced by default. String camel.component.ssh.known-hosts-resource Sets the resource path for a known_hosts file. String camel.component.ssh.lazy-start-producer Whether the producer should be started lazy (on the first message). By starting lazy you can use this to allow CamelContext and routes to startup in situations where a producer may otherwise fail during starting and cause the route to fail being started. By deferring this startup to be lazy then the startup failure can be handled during routing messages via Camel's routing error handlers. Beware that when the first message is processed then creating and starting the producer may take a little time and prolong the total processing time of the processing. false Boolean camel.component.ssh.macs Comma-separated list of allowed/supported message authentication code algorithms in their order of preference. The MAC algorithm is used for data integrity protection. String camel.component.ssh.password Sets the password to use in connecting to remote SSH server. Requires keyPairProvider to be set to null. String camel.component.ssh.poll-command Sets the command string to send to the remote SSH server during every poll cycle. Only works with camel-ssh component being used as a consumer, i.e. from(ssh://... ) You may need to end your command with a newline, and that must be URL encoded %0A. String camel.component.ssh.shell-prompt Sets the shellPrompt to be dropped when response is read after command execution. String camel.component.ssh.signatures Comma-separated list of allowed/supported signature algorithms in their order of preference. String camel.component.ssh.sleep-for-shell-prompt Sets the sleep period in milliseconds to wait reading response from shell prompt. Defaults to 100 milliseconds. 100 Long camel.component.ssh.timeout Sets the timeout in milliseconds to wait in establishing the remote SSH server connection. Defaults to 30000 milliseconds. 30000 Long camel.component.ssh.username Sets the username to use in logging into the remote SSH server. String	[ "<dependency> <groupId>org.apache.camel.springboot</groupId> <artifactId>camel-ssh-starter</artifactId> </dependency>", "ssh:[username[:password]@]host[:port][?options]", "ssh:host:port", "<route id=\"camel-example-ssh-producer\"> <from uri=\"direct:exampleSshProducer\"/> <setBody> <constant>features:list </constant> </setBody> <to uri=\"ssh://karaf:karaf@localhost:8101\"/> <log message=\"USD{body}\"/> </route>", "<route> <from uri=\"ssh://scott@localhost:8101?certResource=classpath:test_rsa&useFixedDelay=true&delay=5000&pollCommand=features:list%0A\"/> <log message=\"USD{body}\"/> </route>", "from(\"ssh://scott@localhost:8101?certResource=classpath:test_rsa&useFixedDelay=true&delay=5000&pollCommand=features:list%0A\") .log(\"USD{body}\");", "<dependency> <groupId>org.apache.sshd</groupId> <artifactId>sshd-core</artifactId> <version>2.8.0</version> </dependency> <dependency> <groupId>org.bouncycastle</groupId> <artifactId>bcpg-jdk18on</artifactId> <version>1.71</version> </dependency> <dependency> <groupId>org.bouncycastle</groupId> <artifactId>bcpkix-jdk18on</artifactId> <version>1.71</version> </dependency>" ]	https://docs.redhat.com/en/documentation/red_hat_build_of_apache_camel/4.4/html/red_hat_build_of_apache_camel_for_spring_boot_reference/csb-camel-ssh-component-starter
Chapter 7. Viewing the status of the QuayRegistry object	Chapter 7. Viewing the status of the QuayRegistry object Lifecycle observability for a given Red Hat Quay deployment is reported in the status section of the corresponding QuayRegistry object. The Red Hat Quay Operator constantly updates this section, and this should be the first place to look for any problems or state changes in Red Hat Quay or its managed dependencies. 7.1. Viewing the registry endpoint Once Red Hat Quay is ready to be used, the status.registryEndpoint field will be populated with the publicly available hostname of the registry. 7.2. Viewing the config editor endpoint Access Red Hat Quay's UI-based config editor using status.configEditorEndpoint . 7.3. Viewing the config editor credentials secret The username and password for the config editor UI will be stored in a Secret in the same namespace as the QuayRegistry referenced by status.configEditorCredentialsSecret . 7.4. Viewing the version of Red Hat Quay in use The current version of Red Hat Quay that is running will be reported in status.currentVersion . 7.5. Viewing the conditions of your Red Hat Quay deployment Certain conditions will be reported in status.conditions .	null	https://docs.redhat.com/en/documentation/red_hat_quay/3.9/html/deploying_the_red_hat_quay_operator_on_openshift_container_platform/operator-quayregistry-status
Chapter 19. Task filtering in Business Central	Chapter 19. Task filtering in Business Central Business Central provides built-in filters to help you search tasks. You can filter tasks by attributes such as Status , Filter By , Process Definition Id , and Created On . It is also possible to create custom task filters using the Advanced Filters option. The newly created custom filter is added to the Saved Filters pane, which is accessible by clicking on the star icon on the left of the Task Inbox page. 19.1. Managing task list columns In the task list on the Task Inbox and Manage Tasks windows, you can specify what columns to view and you can change the order of columns to better manage task information. Note Only users with the process-admin role can view the task list on the Manage Tasks page. Users with the admin role can access the Manage Tasks page, however they see only an empty task list. Procedure In Business Central, go to Menu Manage Tasks or Menu Track Task Inbox . On the Manage Task or Task Inbox page, click the Show/hide columns icon to the right of Bulk Actions . Select or deselect columns to display. As you make changes to the list, columns in the task list appear or disappear. To rearrange the columns, drag the column heading to a new position. Note that your pointer must change to the icon shown in the following illustration before you can drag the column: To save your changes as a filter, click Save Filters , enter a name, and click Save . To use your new filter, click the Saved Filters icon (star) on the left of the screen and select your filter from the list. 19.2. Filtering tasks using basic filters Business Central provides basic filters for filtering and searching through tasks based on their attributes such as Status , Filter By , Process Definition Id , and Created On . Procedure In Business Central, go to Menu Track Task Inbox . On the Task Inbox page, click the filter icon on the left of the page to expand the Filters pane and select the filters you want to use: Status : Filter tasks based on their status. Filter By : Filter tasks based on Id , Task , Correlation Key , Actual Owner , or Process Instance Description attribute. Process Definition Id : Filter tasks based on process definition ids. Created On : Filter tasks based on their creation date. You can use the Advanced Filters option to create custom filters in Business Central. 19.3. Filtering tasks using advanced filters You can create custom task filters using the Advanced Filters option in Business Central. Procedure In Business Central, go to Menu Track Task Inbox . On the Task Inbox page, click the advanced filters icon on the left of the page to expand the Advanced Filters panel. In the Advanced Filters panel, enter the filter name and description, and click Add New . Select an attribute from the Select column drop-down list, such as Name . The content of the drop-down changes to Name != value1 . Click the drop-down again and choose the required logical query. For the Name attribute, choose equals to . Change the value of the text field to the name of the task you want to filter. Note The name must match the value defined in the business process of the project. Click Save and the tasks are filtered according to the filter definition. Click the star icon to open the Saved Filters pane. In the Saved Filters pane, you can view the saved advanced filters. 19.4. Managing tasks using default filter You can set a task filter as a default filter using the Saved Filter option in Business Central. A default filter will be executed every time when the page is open by the user. Procedure In Business Central, go to Menu Track Task Inbox or go to Menu Manage Tasks . On the Task Inbox page or the Manage Tasks page, click the star icon on the left of the page to expand the Saved Filters panel. In the Saved Filters panel, you can view the saved advanced filters. Default filter selection for Tasks or Task Inbox In the Saved Filters panel, set a saved task filter as the default filter. 19.5. Viewing task variables using basic filters Business Central provides basic filters to view task variables in Manage Tasks and Task Inbox . You can view the task variables of the task as columns using Show/hide columns . Procedure In Business Central, go to Menu Manage Tasks or go to Menu Track Task Inbox . On the Task Inbox page, click the filter icon on the left of the page to expand the Filters panel In the Filters panel, select the Task Name . The filter is applied to the current task list. Click Show/hide columns on the upper right of the tasks list and the task variables of the specified task id will be displayed. Click the star icon to open the Saved Filters panel. In the Saved Filters panel, you can view all the saved advanced filters. 19.6. Viewing task variables using advanced filters You can use the Advanced Filters option in Business Central to view task variables in Manage Tasks and Task Inbox . When you create a filter with the task defined, you can view the task variables of the task as columns using Show/hide columns . Procedure In Business Central, go to Menu Manage Tasks or go to Menu Track Task Inbox . On the Manage Tasks page or the Task Inbox page, click the advanced filters icon to expand the Advanced Filters panel. In the Advanced Filters panel, enter the name and description of the filter, and click Add New . From the Select column list, select the name attribute. The value will change to name != value1 . From the Select column list, select equals to for the logical query. In the text field, enter the name of the task. Click Save and the filter is applied on the current task list. Click Show/hide columns on the upper right of the tasks list and the task variables of the specified task id will be displayed. Click the star icon to open the Saved Filters panel. In the Saved Filters panel, you can view all the saved advanced filters.	null	https://docs.redhat.com/en/documentation/red_hat_process_automation_manager/7.13/html/developing_process_services_in_red_hat_process_automation_manager/interacting-with-processes-filter-tasks-con
Chapter 30. Managing DNS forwarding in IdM	Chapter 30. Managing DNS forwarding in IdM Follow these procedures to configure DNS global forwarders and DNS forward zones in the Identity Management (IdM) Web UI, the IdM CLI, and using Ansible: The two roles of an IdM DNS server DNS forward policies in IdM Adding a global forwarder in the IdM Web UI Adding a global forwarder in the CLI Adding a DNS Forward Zone in the IdM Web UI Adding a DNS Forward Zone in the CLI Establishing a DNS Global Forwarder in IdM using Ansible Ensuring the presence of a DNS global forwarder in IdM using Ansible Ensuring the absence of a DNS global forwarder in IdM using Ansible Ensuring DNS Global Forwarders are disabled in IdM using Ansible Ensuring the presence of a DNS Forward Zone in IdM using Ansible Ensuring a DNS Forward Zone has multiple forwarders in IdM using Ansible Ensuring a DNS Forward Zone is disabled in IdM using Ansible Ensuring the absence of a DNS Forward Zone in IdM using Ansible 30.1. The two roles of an IdM DNS server DNS forwarding affects how a DNS service answers DNS queries. By default, the Berkeley Internet Name Domain (BIND) service integrated with IdM acts as both an authoritative and a recursive DNS server: Authoritative DNS server When a DNS client queries a name belonging to a DNS zone for which the IdM server is authoritative, BIND replies with data contained in the configured zone. Authoritative data always takes precedence over any other data. Recursive DNS server When a DNS client queries a name for which the IdM server is not authoritative, BIND attempts to resolve the query using other DNS servers. If forwarders are not defined, BIND asks the root servers on the Internet and uses a recursive resolution algorithm to answer the DNS query. In some cases, it is not desirable to let BIND contact other DNS servers directly and perform the recursion based on data available on the Internet. You can configure BIND to use another DNS server, a forwarder , to resolve the query. When you configure BIND to use a forwarder, queries and answers are forwarded back and forth between the IdM server and the forwarder, and the IdM server acts as the DNS cache for non-authoritative data. 30.2. DNS forward policies in IdM IdM supports the first and only standard BIND forward policies, as well as the none IdM-specific forward policy. Forward first (default) The IdM BIND service forwards DNS queries to the configured forwarder. If a query fails because of a server error or timeout, BIND falls back to the recursive resolution using servers on the Internet. The forward first policy is the default policy, and it is suitable for optimizing DNS traffic. Forward only The IdM BIND service forwards DNS queries to the configured forwarder. If a query fails because of a server error or timeout, BIND returns an error to the client. The forward only policy is recommended for environments with split DNS configuration. None (forwarding disabled) DNS queries are not forwarded with the none forwarding policy. Disabling forwarding is only useful as a zone-specific override for global forwarding configuration. This option is the IdM equivalent of specifying an empty list of forwarders in BIND configuration. Note You cannot use forwarding to combine data in IdM with data from other DNS servers. You can only forward queries for specific subzones of the primary zone in IdM DNS. By default, the BIND service does not forward queries to another server if the queried DNS name belongs to a zone for which the IdM server is authoritative. In such a situation, if the queried DNS name cannot be found in the IdM database, the NXDOMAIN answer is returned. Forwarding is not used. Example 30.1. Example Scenario The IdM server is authoritative for the test.example. DNS zone. BIND is configured to forward queries to the DNS server with the 192.0.2.254 IP address. When a client sends a query for the nonexistent.test.example. DNS name, BIND detects that the IdM server is authoritative for the test.example. zone and does not forward the query to the 192.0.2.254. server. As a result, the DNS client receives the NXDomain error message, informing the user that the queried domain does not exist. 30.3. Adding a global forwarder in the IdM Web UI Follow this procedure to add a global DNS forwarder in the Identity Management (IdM) Web UI. Prerequisites You are logged in to the IdM WebUI as IdM administrator. You know the Internet Protocol (IP) address of the DNS server to forward queries to. Procedure In the IdM Web UI, select Network Services DNS Global Configuration DNS . In the DNS Global Configuration section, click Add . Specify the IP address of the DNS server that will receive forwarded DNS queries. Select the Forward policy . Click Save at the top of the window. Verification Select Network Services DNS Global Configuration DNS . Verify that the global forwarder, with the forward policy you specified, is present and enabled in the IdM Web UI. 30.4. Adding a global forwarder in the CLI Follow this procedure to add a global DNS forwarder by using the command line (CLI). Prerequisites You are logged in as IdM administrator. You know the Internet Protocol (IP) address of the DNS server to forward queries to. Procedure Use the ipa dnsconfig-mod command to add a new global forwarder. Specify the IP address of the DNS forwarder with the --forwarder option. Verification Use the dnsconfig-show command to display global forwarders. 30.5. Adding a DNS Forward Zone in the IdM Web UI Follow this procedure to add a DNS forward zone in the Identity Management (IdM) Web UI. Important Do not use forward zones unless absolutely required. Forward zones are not a standard solution, and using them can lead to unexpected and problematic behavior. If you must use forward zones, limit their use to overriding a global forwarding configuration. When creating a new DNS zone, Red Hat recommends to always use standard DNS delegation using nameserver (NS) records and to avoid forward zones. In most cases, using a global forwarder is sufficient, and forward zones are not necessary. Prerequisites You are logged in to the IdM WebUI as IdM administrator. You know the Internet Protocol (IP) address of the DNS server to forward queries to. Procedure In the IdM Web UI, select Network Services DNS Forward Zones DNS . In the DNS Forward Zones section, click Add . In the Add DNS forward zone window, specify the forward zone name. Click the Add button and specify the IP address of a DNS server to receive the forwarding request. You can specify multiple forwarders per forward zone. Select the Forward policy . Click Add at the bottom of the window to add the new forward zone. Verification In the IdM Web UI, select Network Services DNS Forward Zones DNS . Verify that the forward zone you created, with the forwarders and forward policy you specified, is present and enabled in the IdM Web UI. 30.6. Adding a DNS Forward Zone in the CLI Follow this procedure to add a DNS forward zone by using the command line (CLI). Important Do not use forward zones unless absolutely required. Forward zones are not a standard solution, and using them can lead to unexpected and problematic behavior. If you must use forward zones, limit their use to overriding a global forwarding configuration. When creating a new DNS zone, Red Hat recommends to always use standard DNS delegation using nameserver (NS) records and to avoid forward zones. In most cases, using a global forwarder is sufficient, and forward zones are not necessary. Prerequisites You are logged in as IdM administrator. You know the Internet Protocol (IP) address of the DNS server to forward queries to. Procedure Use the dnsforwardzone-add command to add a new forward zone. Specify at least one forwarder with the --forwarder option if the forward policy is not none , and specify the forward policy with the --forward-policy option. Verification Use the dnsforwardzone-show command to display the DNS forward zone you just created. 30.7. Establishing a DNS Global Forwarder in IdM using Ansible Follow this procedure to use an Ansible playbook to establish a DNS Global Forwarder in IdM. In the example procedure below, the IdM administrator creates a DNS global forwarder to a DNS server with an Internet Protocol (IP) v4 address of 8.8.6.6 and IPv6 address of 2001:4860:4860::8800 on port 53 . Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Make a copy of the set-configuration.yml Ansible playbook file. For example: Open the establish-global-forwarder.yml file for editing. Adapt the file by setting the following variables: Change the name variable for the playbook to Playbook to establish a global forwarder in IdM DNS . In the tasks section, change the name of the task to Create a DNS global forwarder to 8.8.6.6 and 2001:4860:4860::8800 . In the forwarders section of the ipadnsconfig portion: Change the first ip_address value to the IPv4 address of the global forwarder: 8.8.6.6 . Change the second ip_address value to the IPv6 address of the global forwarder: 2001:4860:4860::8800 . Verify the port value is set to 53 . Change the forward_policy to first . This the modified Ansible playbook file for the current example: Save the file. Run the playbook: Additional resources The README-dnsconfig.md file in the /usr/share/doc/ansible-freeipa/ directory 30.8. Ensuring the presence of a DNS global forwarder in IdM using Ansible Follow this procedure to use an Ansible playbook to ensure the presence of a DNS global forwarder in IdM. In the example procedure below, the IdM administrator ensures the presence of a DNS global forwarder to a DNS server with an Internet Protocol (IP) v4 address of 7.7.9.9 and IP v6 address of 2001:db8::1:0 on port 53 . Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Make a copy of the forwarders-absent.yml Ansible playbook file. For example: Open the ensure-presence-of-a-global-forwarder.yml file for editing. Adapt the file by setting the following variables: Change the name variable for the playbook to Playbook to ensure the presence of a global forwarder in IdM DNS . In the tasks section, change the name of the task to Ensure the presence of a DNS global forwarder to 7.7.9.9 and 2001:db8::1:0 on port 53 . In the forwarders section of the ipadnsconfig portion: Change the first ip_address value to the IPv4 address of the global forwarder: 7.7.9.9 . Change the second ip_address value to the IPv6 address of the global forwarder: 2001:db8::1:0 . Verify the port value is set to 53 . Change the state to present . This the modified Ansible playbook file for the current example: Save the file. Run the playbook: Additional resources The README-dnsconfig.md file in the /usr/share/doc/ansible-freeipa/ directory 30.9. Ensuring the absence of a DNS global forwarder in IdM using Ansible Follow this procedure to use an Ansible playbook to ensure the absence of a DNS global forwarder in IdM. In the example procedure below, the IdM administrator ensures the absence of a DNS global forwarder with an Internet Protocol (IP) v4 address of 8.8.6.6 and IP v6 address of 2001:4860:4860::8800 on port 53 . Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Make a copy of the forwarders-absent.yml Ansible playbook file. For example: Open the ensure-absence-of-a-global-forwarder.yml file for editing. Adapt the file by setting the following variables: Change the name variable for the playbook to Playbook to ensure the absence of a global forwarder in IdM DNS . In the tasks section, change the name of the task to Ensure the absence of a DNS global forwarder to 8.8.6.6 and 2001:4860:4860::8800 on port 53 . In the forwarders section of the ipadnsconfig portion: Change the first ip_address value to the IPv4 address of the global forwarder: 8.8.6.6 . Change the second ip_address value to the IPv6 address of the global forwarder: 2001:4860:4860::8800 . Verify the port value is set to 53 . Set the action variable to member . Verify the state is set to absent . This the modified Ansible playbook file for the current example: Important If you only use the state: absent option in your playbook without also using action: member , the playbook fails. Save the file. Run the playbook: Additional resources The README-dnsconfig.md file in the /usr/share/doc/ansible-freeipa/ directory The action: member option in ipadnsconfig ansible-freeipa modules 30.10. Ensuring DNS Global Forwarders are disabled in IdM using Ansible Follow this procedure to use an Ansible playbook to ensure DNS Global Forwarders are disabled in IdM. In the example procedure below, the IdM administrator ensures that the forwarding policy for the global forwarder is set to none , which effectively disables the global forwarder. Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Verify the contents of the disable-global-forwarders.yml Ansible playbook file which is already configured to disable all DNS global forwarders. For example: Run the playbook: Additional resources The README-dnsconfig.md file in the /usr/share/doc/ansible-freeipa/ directory 30.11. Ensuring the presence of a DNS Forward Zone in IdM using Ansible Follow this procedure to use an Ansible playbook to ensure the presence of a DNS Forward Zone in IdM. In the example procedure below, the IdM administrator ensures the presence of a DNS forward zone for example.com to a DNS server with an Internet Protocol (IP) address of 8.8.8.8 . Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Make a copy of the forwarders-absent.yml Ansible playbook file. For example: Open the ensure-presence-forwardzone.yml file for editing. Adapt the file by setting the following variables: Change the name variable for the playbook to Playbook to ensure the presence of a dnsforwardzone in IdM DNS . In the tasks section, change the name of the task to Ensure presence of a dnsforwardzone for example.com to 8.8.8.8 . In the tasks section, change the ipadnsconfig heading to ipadnsforwardzone . In the ipadnsforwardzone section: Add the ipaadmin_password variable and set it to your IdM administrator password. Add the name variable and set it to example.com . In the forwarders section: Remove the ip_address and port lines. Add the IP address of the DNS server to receive forwarded requests by specifying it after a dash: Add the forwardpolicy variable and set it to first . Add the skip_overlap_check variable and set it to true . Change the state variable to present . This the modified Ansible playbook file for the current example: Save the file. Run the playbook: Additional resources See the README-dnsforwardzone.md file in the /usr/share/doc/ansible-freeipa/ directory. 30.12. Ensuring a DNS Forward Zone has multiple forwarders in IdM using Ansible Follow this procedure to use an Ansible playbook to ensure a DNS Forward Zone in IdM has multiple forwarders. In the example procedure below, the IdM administrator ensures the DNS forward zone for example.com is forwarding to 8.8.8.8 and 4.4.4.4 . Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Make a copy of the forwarders-absent.yml Ansible playbook file. For example: Open the ensure-presence-multiple-forwarders.yml file for editing. Adapt the file by setting the following variables: Change the name variable for the playbook to Playbook to ensure the presence of multiple forwarders in a dnsforwardzone in IdM DNS . In the tasks section, change the name of the task to Ensure presence of 8.8.8.8 and 4.4.4.4 forwarders in dnsforwardzone for example.com . In the tasks section, change the ipadnsconfig heading to ipadnsforwardzone . In the ipadnsforwardzone section: Add the ipaadmin_password variable and set it to your IdM administrator password. Add the name variable and set it to example.com . In the forwarders section: Remove the ip_address and port lines. Add the IP address of the DNS servers you want to ensure are present, preceded by a dash: Change the state variable to present. This the modified Ansible playbook file for the current example: Save the file. Run the playbook: Additional resources See the README-dnsforwardzone.md file in the /usr/share/doc/ansible-freeipa/ directory. 30.13. Ensuring a DNS Forward Zone is disabled in IdM using Ansible Follow this procedure to use an Ansible playbook to ensure a DNS Forward Zone is disabled in IdM. In the example procedure below, the IdM administrator ensures the DNS forward zone for example.com is disabled. Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Make a copy of the forwarders-absent.yml Ansible playbook file. For example: Open the ensure-disabled-forwardzone.yml file for editing. Adapt the file by setting the following variables: Change the name variable for the playbook to Playbook to ensure a dnsforwardzone is disabled in IdM DNS . In the tasks section, change the name of the task to Ensure a dnsforwardzone for example.com is disabled . In the tasks section, change the ipadnsconfig heading to ipadnsforwardzone . In the ipadnsforwardzone section: Add the ipaadmin_password variable and set it to your IdM administrator password. Add the name variable and set it to example.com . Remove the entire forwarders section. Change the state variable to disabled . This the modified Ansible playbook file for the current example: Save the file. Run the playbook: Additional resources See the README-dnsforwardzone.md file in the /usr/share/doc/ansible-freeipa/ directory. 30.14. Ensuring the absence of a DNS Forward Zone in IdM using Ansible Follow this procedure to use an Ansible playbook to ensure the absence of a DNS Forward Zone in IdM. In the example procedure below, the IdM administrator ensures the absence of a DNS forward zone for example.com . Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.14 or later. You have installed the ansible-freeipa package. The example assumes that in the ~/ MyPlaybooks / directory, you have created an Ansible inventory file with the fully-qualified domain name (FQDN) of the IdM server. The example assumes that the secret.yml Ansible vault stores your ipaadmin_password . The target node, that is the node on which the ansible-freeipa module is executed, is part of the IdM domain as an IdM client, server or replica. You know the IdM administrator password. Procedure Navigate to the /usr/share/doc/ansible-freeipa/playbooks/dnsconfig directory: Open your inventory file and make sure that the IdM server that you want to configure is listed in the [ipaserver] section. For example, to instruct Ansible to configure server.idm.example.com , enter: Make a copy of the forwarders-absent.yml Ansible playbook file. For example: Open the ensure-absence-forwardzone.yml file for editing. Adapt the file by setting the following variables: Change the name variable for the playbook to Playbook to ensure the absence of a dnsforwardzone in IdM DNS . In the tasks section, change the name of the task to Ensure the absence of a dnsforwardzone for example.com . In the tasks section, change the ipadnsconfig heading to ipadnsforwardzone . In the ipadnsforwardzone section: Add the ipaadmin_password variable and set it to your IdM administrator password. Add the name variable and set it to example.com . Remove the entire forwarders section. Leave the state variable as absent . This the modified Ansible playbook file for the current example: Save the file. Run the playbook: Additional resources See the README-dnsforwardzone.md file in the /usr/share/doc/ansible-freeipa/ directory.	[ "[user@server ~]USD ipa dnsconfig-mod --forwarder= 10.10.0.1 Server will check DNS forwarder(s). This may take some time, please wait Global forwarders: 10.10.0.1 IPA DNS servers: server.example.com", "[user@server ~]USD ipa dnsconfig-show Global forwarders: 10.10.0.1 IPA DNS servers: server.example.com", "[user@server ~]USD ipa dnsforwardzone-add forward.example.com. --forwarder= 10.10.0.14 --forwarder= 10.10.1.15 --forward-policy=first Zone name: forward.example.com. Zone forwarders: 10.10.0.14, 10.10.1.15 Forward policy: first", "[user@server ~]USD ipa dnsforwardzone-show forward.example.com. Zone name: forward.example.com. Zone forwarders: 10.10.0.14, 10.10.1.15 Forward policy: first", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cp set-configuration.yml establish-global-forwarder.yml", "--- - name: Playbook to establish a global forwarder in IdM DNS hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Create a DNS global forwarder to 8.8.6.6 and 2001:4860:4860::8800 ipadnsconfig: forwarders: - ip_address: 8.8.6.6 - ip_address: 2001:4860:4860::8800 port: 53 forward_policy: first allow_sync_ptr: true", "ansible-playbook --vault-password-file=password_file -v -i inventory.file establish-global-forwarder.yml", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cp forwarders-absent.yml ensure-presence-of-a-global-forwarder.yml", "--- - name: Playbook to ensure the presence of a global forwarder in IdM DNS hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Ensure the presence of a DNS global forwarder to 7.7.9.9 and 2001:db8::1:0 on port 53 ipadnsconfig: forwarders: - ip_address: 7.7.9.9 - ip_address: 2001:db8::1:0 port: 53 state: present", "ansible-playbook --vault-password-file=password_file -v -i inventory.file ensure-presence-of-a-global-forwarder.yml", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cp forwarders-absent.yml ensure-absence-of-a-global-forwarder.yml", "--- - name: Playbook to ensure the absence of a global forwarder in IdM DNS hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Ensure the absence of a DNS global forwarder to 8.8.6.6 and 2001:4860:4860::8800 on port 53 ipadnsconfig: forwarders: - ip_address: 8.8.6.6 - ip_address: 2001:4860:4860::8800 port: 53 action: member state: absent", "ansible-playbook --vault-password-file=password_file -v -i inventory.file ensure-absence-of-a-global-forwarder.yml", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cat disable-global-forwarders.yml --- - name: Playbook to disable global DNS forwarders hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Disable global forwarders. ipadnsconfig: forward_policy: none", "ansible-playbook --vault-password-file=password_file -v -i inventory.file disable-global-forwarders.yml", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cp forwarders-absent.yml ensure-presence-forwardzone.yml", "- 8.8.8.8", "--- - name: Playbook to ensure the presence of a dnsforwardzone in IdM DNS hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Ensure the presence of a dnsforwardzone for example.com to 8.8.8.8 ipadnsforwardzone: ipaadmin_password: \"{{ ipaadmin_password }}\" name: example.com forwarders: - 8.8.8.8 forwardpolicy: first skip_overlap_check: true state: present", "ansible-playbook --vault-password-file=password_file -v -i inventory.file ensure-presence-forwardzone.yml", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cp forwarders-absent.yml ensure-presence-multiple-forwarders.yml", "- 8.8.8.8 - 4.4.4.4", "--- - name: name: Playbook to ensure the presence of multiple forwarders in a dnsforwardzone in IdM DNS hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Ensure presence of 8.8.8.8 and 4.4.4.4 forwarders in dnsforwardzone for example.com ipadnsforwardzone: ipaadmin_password: \"{{ ipaadmin_password }}\" name: example.com forwarders: - 8.8.8.8 - 4.4.4.4 state: present", "ansible-playbook --vault-password-file=password_file -v -i inventory.file ensure-presence-multiple-forwarders.yml", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cp forwarders-absent.yml ensure-disabled-forwardzone.yml", "--- - name: Playbook to ensure a dnsforwardzone is disabled in IdM DNS hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Ensure a dnsforwardzone for example.com is disabled ipadnsforwardzone: ipaadmin_password: \"{{ ipaadmin_password }}\" name: example.com state: disabled", "ansible-playbook --vault-password-file=password_file -v -i inventory.file ensure-disabled-forwardzone.yml", "cd /usr/share/doc/ansible-freeipa/playbooks/dnsconfig", "[ipaserver] server.idm.example.com", "cp forwarders-absent.yml ensure-absence-forwardzone.yml", "--- - name: Playbook to ensure the absence of a dnsforwardzone in IdM DNS hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: - name: Ensure the absence of a dnsforwardzone for example.com ipadnsforwardzone: ipaadmin_password: \"{{ ipaadmin_password }}\" name: example.com state: absent", "ansible-playbook --vault-password-file=password_file -v -i inventory.file ensure-absence-forwardzone.yml" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/9/html/using_ansible_to_install_and_manage_identity_management/managing-dns-forwarding-in-idm_using-ansible-to-install-and-manage-identity-management
9.16. Write Changes to Disk	9.16. Write Changes to Disk The installer prompts you to confirm the partitioning options that you selected. Click Write changes to disk to allow the installer to partition your hard drive and install Red Hat Enterprise Linux. Figure 9.47. Writing storage configuration to disk If you are certain that you want to proceed, click Write changes to disk . Warning Up to this point in the installation process, the installer has made no lasting changes to your computer. When you click Write changes to disk , the installer will allocate space on your hard drive and start to transfer Red Hat Enterprise Linux into this space. Depending on the partitioning option that you chose, this process might include erasing data that already exists on your computer. To revise any of the choices that you made up to this point, click Go back . To cancel installation completely, switch off your computer. To switch off most computers at this stage, press the power button and hold it down for a few seconds. After you click Write changes to disk , allow the installation process to complete. If the process is interrupted (for example, by you switching off or resetting the computer, or by a power outage) you will probably not be able to use your computer until you restart and complete the Red Hat Enterprise Linux installation process, or install a different operating system.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/installation_guide/Write_changes_to_disk-x86
Chapter 6. Managing user passwords in IdM	Chapter 6. Managing user passwords in IdM 6.1. Who can change IdM user passwords and how Regular users without the permission to change other users' passwords can change only their own personal password. The new password must meet the IdM password policies applicable to the groups of which the user is a member. For details on configuring password policies, see Defining IdM password policies . Administrators and users with password change rights can set initial passwords for new users and reset passwords for existing users. These passwords: Do not have to meet the IdM password policies. Expire after the first successful login. When this happens, IdM prompts the user to change the expired password immediately. To disable this behavior, see Enabling password reset in IdM without prompting the user for a password change at the login . Note The LDAP Directory Manager (DM) user can change user passwords using LDAP tools. The new password can override any IdM password policies. Passwords set by DM do not expire after the first login. 6.2. Changing your user password in the IdM Web UI As an Identity Management (IdM) user, you can change your user password in the IdM Web UI. Prerequisites You are logged in to the IdM Web UI. Procedure In the upper right corner, click User name Change password . Figure 6.1. Resetting Password Enter the current and new passwords. 6.3. Resetting another user's password in the IdM Web UI As an administrative user of Identity Management (IdM), you can change passwords for other users in the IdM Web UI. Prerequisites You are logged in to the IdM Web UI as an administrative user. Procedure Select Identity Users . Click the name of the user to edit. Click Actions Reset password . Figure 6.2. Resetting Password Enter the new password, and click Reset Password . Figure 6.3. Confirming New Password 6.4. Resetting the Directory Manager user password If you lose the Identity Management (IdM) Directory Manager password, you can reset it. Prerequisites You have root access to an IdM server. Procedure Generate a new password hash by using the pwdhash command. For example: By specifying the path to the Directory Server configuration, you automatically use the password storage scheme set in the nsslapd-rootpwstoragescheme attribute to encrypt the new password. On every IdM server in your topology, execute the following steps: Stop all IdM services installed on the server: Edit the /etc/dirsrv/IDM-EXAMPLE-COM/dse.ldif file and set the nsslapd-rootpw attribute to the value generated by the pwdhash command: Start all IdM services installed on the server: 6.5. Changing your user password or resetting another user's password in IdM CLI You can change your user password using the Identity Management (IdM) command-line interface (CLI). If you are an administrative user, you can use the CLI to reset another user's password. Prerequisites You have obtained a ticket-granting ticket (TGT) for an IdM user. If you are resetting another user's password, you must have obtained a TGT for an administrative user in IdM. Procedure Enter the ipa user-mod command with the name of the user and the --password option. The command will prompt you for the new password. Note You can also use the ipa passwd idm_user command instead of ipa user-mod . 6.6. Enabling password reset in IdM without prompting the user for a password change at the login By default, when an administrator resets another user's password, the password expires after the first successful login. As IdM Directory Manager, you can specify the following privileges for individual IdM administrators: They can perform password change operations without requiring users to change their passwords subsequently on their first login. They can bypass the password policy so that no strength or history enforcement is applied. Warning Bypassing the password policy can be a security threat. Exercise caution when selecting users to whom you grant these additional privileges. Prerequisites You know the Directory Manager password. Procedure On every Identity Management (IdM) server in the domain, make the following changes: Enter the ldapmodify command to modify LDAP entries. Specify the name of the IdM server and the 389 port and press Enter: Enter the Directory Manager password. Enter the distinguished name for the ipa_pwd_extop password synchronization entry and press Enter: Specify the modify type of change and press Enter: Specify what type of modification you want LDAP to execute and to which attribute. Press Enter: Specify the administrative user accounts in the passSyncManagersDNs attribute. The attribute is multi-valued. For example, to grant the admin user the password resetting powers of Directory Manager: Press Enter twice to stop editing the entry. The whole procedure looks as follows: The admin user, listed under passSyncManagerDNs , now has the additional privileges. 6.7. Checking if an IdM user's account is locked As an Identity Management (IdM) administrator, you can check if an IdM user's account is locked. For that, you must compare a user's maximum allowed number of failed login attempts with the number of the user's actual failed logins. Prerequisites You have obtained the ticket-granting ticket (TGT) of an administrative user in IdM. Procedure Display the status of the user account to see the number of failed logins: Display the number of allowed login attempts for a particular user: Log in to the IdM Web UI as IdM administrator. Open the Identity Users Active users tab. Click the user name to open the user settings. In the Password policy section, locate the Max failures item. Compare the number of failed logins as displayed in the output of the ipa user-status command with the Max failures number displayed in the IdM Web UI. If the number of failed logins equals that of maximum allowed login attempts, the user account is locked. Additional resources Unlocking user accounts after password failures in IdM 6.8. Unlocking user accounts after password failures in IdM If a user attempts to log in using an incorrect password a certain number of times, Identity Management (IdM) locks the user account, which prevents the user from logging in. For security reasons, IdM does not display any warning message that the user account has been locked. Instead, the CLI prompt might continue asking the user for a password again and again. IdM automatically unlocks the user account after a specified amount of time has passed. Alternatively, you can unlock the user account manually with the following procedure. Prerequisites You have obtained the ticket-granting ticket of an IdM administrative user. Procedure To unlock a user account, use the ipa user-unlock command. After this, the user can log in again. Additional resources Checking if an IdM user's account is locked 6.9. Enabling the tracking of last successful Kerberos authentication for users in IdM For performance reasons, Identity Management (IdM) running in Red Hat Enterprise Linux 8 does not store the time stamp of the last successful Kerberos authentication of a user. As a consequence, certain commands, such as ipa user-status , do not display the time stamp. Prerequisites You have obtained the ticket-granting ticket (TGT) of an administrative user in IdM. You have root access to the IdM server on which you are executing the procedure. Procedure Display the currently enabled password plug-in features: The output shows that the KDC:Disable Last Success plug-in is enabled. The plug-in hides the last successful Kerberos authentication attempt from being visible in the ipa user-status output. Add the --ipaconfigstring= feature parameter for every feature to the ipa config-mod command that is currently enabled, except for KDC:Disable Last Success : This command enables only the AllowNThash plug-in. To enable multiple features, specify the --ipaconfigstring= feature parameter separately for each feature. Restart IdM:	[ "pwdhash -D /etc/dirsrv/slapd-IDM-EXAMPLE-COM password {PBKDF2_SHA256}AAAgABU0bKhyjY53NcxY33ueoPjOUWtl4iyYN5uW", "ipactl stop", "nsslapd-rootpw: {PBKDF2_SHA256}AAAgABU0bKhyjY53NcxY33ueoPjOUWtl4iyYN5uW", "ipactl start", "ipa user-mod idm_user --password Password: Enter Password again to verify: -------------------- Modified user \"idm_user\" --------------------", "ldapmodify -x -D \"cn=Directory Manager\" -W -h server.idm.example.com -p 389 Enter LDAP Password:", "dn: cn=ipa_pwd_extop,cn=plugins,cn=config", "changetype: modify", "add: passSyncManagersDNs", "passSyncManagersDNs: uid=admin,cn=users,cn=accounts,dc=example,dc=com", "ldapmodify -x -D \"cn=Directory Manager\" -W -h server.idm.example.com -p 389 Enter LDAP Password: dn: cn=ipa_pwd_extop,cn=plugins,cn=config changetype: modify add: passSyncManagersDNs passSyncManagersDNs: uid=admin,cn=users,cn=accounts,dc=example,dc=com", "ipa user-status example_user ----------------------- Account disabled: False ----------------------- Server: idm.example.com Failed logins: 8 Last successful authentication: N/A Last failed authentication: 20220229080317Z Time now: 2022-02-29T08:04:46Z ---------------------------- Number of entries returned 1 ----------------------------", "ipa user-unlock idm_user ----------------------- Unlocked account \"idm_user\" -----------------------", "ipa config-show \| grep \"Password plugin features\" Password plugin features: AllowNThash , KDC:Disable Last Success", "ipa config-mod --ipaconfigstring='AllowNThash'", "ipactl restart" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/9/html/managing_idm_users_groups_hosts_and_access_control_rules/managing-user-passwords-in-idm_managing-users-groups-hosts
13.5. Migrating from NIS to IdM	13.5. Migrating from NIS to IdM There is no direct migration path from NIS to Identity Management. This is a manual process with three major steps: setting up netgroup entries in IdM, exporting the existing data from NIS, and importing that data into IdM. There are several options for how to set up the IdM environment and how to export data; the best option depends on the type of data and the overall network environment that you have. 13.5.1. Preparing Netgroup Entries in IdM The first step is to identify what kinds of identities are being managed by NIS. Frequently, a NIS server is used for either user entries or host entries, but not for both, which can simplify the data migration process. For user entries Determine what applications are using the user information in the NIS server. While some clients (like sudo ) require NIS netgroups, many clients can use Unix groups instead. If no netgroups are required, then simply create corresponding user accounts in IdM and delete the netgroups entirely. Otherwise, create the user entries in IdM and then create an IdM-managed netgroup and add those users as members. This is described in Section 13.3, "Creating Netgroups" . For host entries Whenever a host group is created in IdM, a corresponding shadow NIS group is automatically created. These netgroups can then be managed using the ipa-host-net-manage command. For a direct conversion It may be necessary to have an exact conversion, with every NIS user and host having an exact corresponding entry in IdM. In that case, each entry can be created using the original NIS names: Create an entry for every user referenced in a netgroup. Create an entry for every host referenced in a netgroup. Create a netgroup with the same name as the original netgroup. Add the users and hosts as direct members of the netgroup. Alternatively, add the users and hosts into IdM groups or other netgroups, and then add those groups as members to the netgroup. 13.5.2. Enabling the NIS Listener in Identity Management The IdM Directory Server can function as a limited NIS server. The slapi-nis plug-in sets up a special NIS listener that receives incoming NIS requests and manages the NIS maps within the Directory Server. Identity Management uses three NIS maps: passwd group netgroup Using IdM as an intermediate NIS server offers a reasonable way to handle NIS requests while migrating NIS clients and data. The slapi-nis plug-in is not enabled by default. To enable NIS for Identity Management: Obtain new Kerberos credentials as an IdM admin user. Enable the NIS listener and compatibility plug-ins: Restart the DNS and Directory Server service: 13.5.3. Exporting and Importing the Existing NIS Data NIS can contain information for users, groups, DNS and hosts, netgroups, and automount maps. Any of these entry types can be migrated over to the IdM server. Migration is performed by exporting the data using ypcat and then looping through that output and creating the IdM entries with the corresponding ipa -add commands. While this could be done manually, it is easiest to script it. These examples use a shell script. 13.5.3.1. Importing User Entries The /etc/passwd file contains all of the NIS user information. These entries can be used to create IdM user accounts with UID, GID, gecos, shell, home directory, and name attributes that mirror the NIS entries. For example, this is nis-user.sh : #!/bin/sh # 1 is the nis domain, 2 is the nis master server ypcat -d USD1 -h USD2 passwd > /dev/shm/nis-map.passwd 2>&1 IFS=USD'\n' for line in USD(cat /dev/shm/nis-map.passwd); do IFS=' ' username=USD(echo USDline\|cut -f1 -d:) # Not collecting encrypted password because we need cleartext password to create kerberos key uid=USD(echo USDline\|cut -f3 -d:) gid=USD(echo USDline\|cut -f4 -d:) gecos=USD(echo USDline\|cut -f5 -d:) homedir=USD(echo USDline\|cut -f6 -d:) shell=USD(echo USDline\|cut -f7 -d:) # Now create this entry echo passw0rd1\|ipa user-add USDusername --first=NIS --last=USER --password --gidnumber=USDgid --uid=USDuid --gecos=USDgecos --homedir=USDhomedir --shell=USDshell ipa user-show USDusername done This can be run for a given NIS domain: Note This script does not migrate user passwords. Rather, it creates a temporary password which users are then prompted to change when they log in. 13.5.3.2. Importing Group Entries The /etc/group file contains all of the NIS group information. These entries can be used to create IdM user group accounts with the GID, gecos, shell, home directory, and name attributes that mirror the NIS entries. For example, this is nis-group.sh : #!/bin/sh # 1 is the nis domain, 2 is the nis master server ypcat -d USD1 -h USD2 group > /dev/shm/nis-map.group 2>&1 IFS=USD'\n' for line in USD(cat /dev/shm/nis-map.group); do IFS=' ' groupname=USD(echo USDline\|cut -f1 -d:) # Not collecting encrypted password because we need cleartext password to create kerberos key gid=USD(echo USDline\|cut -f3 -d:) members=USD(echo USDline\|cut -f4 -d:) # Now create this entry ipa group-add USDgroupname --desc=NIS_GROUP_USDgroupname --gid=USDgid if [ -n "USDmembers" ]; then ipa group-add-member USDgroupname --users=USDmembers fi ipa group-show USDgroupname done This can be run for a given NIS domain: 13.5.3.3. Importing Host Entries The /etc/hosts file contains all of the NIS host information. These entries can be used to create IdM host accounts that mirror the NIS entries. For example, this is nis-hosts.sh : #!/bin/sh # 1 is the nis domain, 2 is the nis master server ypcat -d USD1 -h USD2 hosts \| egrep -v "localhost\|127.0.0.1" > /dev/shm/nis-map.hosts 2>&1 IFS=USD'\n' for line in USD(cat /dev/shm/nis-map.hosts); do IFS=' ' ipaddress=USD(echo USDline\|awk '{print USD1}') hostname=USD(echo USDline\|awk '{print USD2}') master=USD(ipa env xmlrpc_uri \|tr -d '[:space:]'\|cut -f3 -d:\|cut -f3 -d/) domain=USD(ipa env domain\|tr -d '[:space:]'\|cut -f2 -d:) if [ USD(echo USDhostname\|grep "\." \|wc -l) -eq 0 ]; then hostname=USD(echo USDhostname.USDdomain) fi zone=USD(echo USDhostname\|cut -f2- -d.) if [ USD(ipa dnszone-show USDzone 2>/dev/null \| wc -l) -eq 0 ]; then ipa dnszone-add --name-server=USDmaster --admin-email=root.USDmaster fi ptrzone=USD(echo USDipaddress\|awk -F. '{print USD3 "." USD2 "." USD1 ".in-addr.arpa."}') if [ USD(ipa dnszone-show USDptrzone 2>/dev/null\|wc -l) -eq 0 ]; then ipa dnszone-add USDptrzone --name-server=USDmaster --admin-email=root.USDmaster fi # Now create this entry ipa host-add USDhostname --ip-address=USDipaddress ipa host-show USDhostname done This can be run for a given NIS domain: Note This script example does not account for special host scenarios, such as using aliases. 13.5.3.4. Importing Netgroup Entries The /etc/netgroup file contains all of the NIS netgroup information. These entries can be used to create IdM netgroup accounts that mirror the NIS entries. For example, this is nis-netgroup.sh : #!/bin/sh # 1 is the nis domain, 2 is the nis master server ypcat -k -d USD1 -h USD2 netgroup > /dev/shm/nis-map.netgroup 2>&1 IFS=USD'\n' for line in USD(cat /dev/shm/nis-map.netgroup); do IFS=' ' netgroupname=USD(echo USDline\|awk '{print USD1}') triples=USD(echo USDline\|sed "s/^USDnetgroupname //") echo "ipa netgroup-add USDnetgroupname --desc=NIS_NG_USDnetgroupname" if [ USD(echo USDline\|grep "(,"\|wc -l) -gt 0 ]; then echo "ipa netgroup-mod USDnetgroupname --hostcat=all" fi if [ USD(echo USDline\|grep ",,"\|wc -l) -gt 0 ]; then echo "ipa netgroup-mod USDnetgroupname --usercat=all" fi for triple in USDtriples; do triple=USD(echo USDtriple\|sed -e 's/-//g' -e 's/(//' -e 's/)//') if [ USD(echo USDtriple\|grep ",.,"\|wc -l) -gt 0 ]; then hostname=USD(echo USDtriple\|cut -f1 -d,) username=USD(echo USDtriple\|cut -f2 -d,) domain=USD(echo USDtriple\|cut -f3 -d,) hosts=""; users=""; doms=""; [ -n "USDhostname" ] && hosts="--hosts=USDhostname" [ -n "USDusername" ] && users="--users=USDusername" [ -n "USDdomain" ] && doms="--nisdomain=USDdomain" echo "ipa netgroup-add-member USDhosts USDusers USDdoms" else netgroup=USDtriple echo "ipa netgroup-add USDnetgroup --desc=NIS_NG_USDnetgroup" fi done done As explained briefly in Section 13.1, "About NIS and Identity Management" , NIS entries exist in a set of three values, called a triple. The triple is host,user,domain , but not every component is required; commonly, a triple only defines a host and domain or user and domain. The way this script is written, the ipa netgroup-add-member command always adds a host, user, and domain triple to the netgroup. if [ USD(echo USDtriple\|grep ",.,"\|wc -l) -gt 0 ]; then hostname=USD(echo USDtriple\|cut -f1 -d,) username=USD(echo USDtriple\|cut -f2 -d,) domain=USD(echo USDtriple\|cut -f3 -d,) hosts=""; users=""; doms=""; [ -n "USDhostname" ] && hosts="--hosts=USDhostname" [ -n "USDusername" ] && users="--users=USDusername" [ -n "USDdomain" ] && doms="--nisdomain=USDdomain" echo "ipa netgroup-add-member USDhosts USDusers USDdoms" Any missing element is added as a blank, so the triple is properly migrated. For example, for the triple server,,domain the options with the member add command are --hosts=server --users="" --nisdomain=domain . This can be run for a given NIS domain by specifying the NIS domain and NIS server: 13.5.3.5. Importing Automount Maps Automount maps are actually a series of nested and inter-related entries that define the location (the parent entry), and then associated keys and maps. While the data are the same in the NIS and IdM entries, the way that data are defined is different. The NIS information is exported and then used to construct an LDAP entry for the automount location and associated map; it then creates an entry for every configured key for the map. Unlike the other NIS migration script examples, this script takes options to create an automount location and a map name, along with the migrated NIS domain and server. #!/bin/sh # 1 is for the automount entry in ipa ipa automountlocation-add USD1 # 2 is the nis domain, 3 is the nis master server, 4 is the map name ypcat -k -d USD2 -h USD3 USD4 > /dev/shm/nis-map.USD4 2>&1 ipa automountmap-add USD1 USD4 basedn=USD(ipa env basedn\|tr -d '[:space:]'\|cut -f2 -d:) cat > /tmp/amap.ldif <<EOF dn: nis-domain=nisdomain.example.com+nis-map=USD4,cn=NIS Server,cn=plugins,cn=config objectClass: extensibleObject nis-domain: USD3 nis-map: USD4 nis-base: automountmapname=USD4,cn=nis,cn=automount,USDbasedn nis-filter: (objectclass=) nis-key-format: %{automountKey} nis-value-format: %{automountInformation} EOF ldapadd -x -h USD3 -D "cn=directory manager" -w secret -f /tmp/amap.ldif IFS=USD'\n' for line in USD(cat /dev/shm/nis-map.USD4); do IFS=" " key=USD(echo "USDline" \| awk '{print USD1}') info=USD(echo "USDline" \| sed -e "s#^USDkey[ \t]*##") ipa automountkey-add nis USD4 --key="USDkey" --info="USDinfo" done This can be run for a given NIS domain: 13.5.4. Setting Weak Password Encryption for NIS User Authentication to IdM A NIS server can handle CRYPT password hashes. Once an existing NIS server is migrated to IdM (and its underlying LDAP database), it may still be necessary to preserve the NIS-supported CRYPT passwords. However, the LDAP server does not use CRYPT hashes by default. It uses salted SHA (SSHA) or SSHA-256. If the 389 Directory Server password hash is not changed, then NIS users cannot authenticate to the IdM domain, and kinit fails with password failures. To set the underlying 389 Directory Server to use CRYPT as the password hash, change the passwordStorageScheme attribute using ldapmodify : Note Changing the password storage scheme only applies the scheme to new passwords; it does not retroactively change the encryption method used for existing passwords. If weak crypto is required for password hashes, it is better to change the setting as early as possible so that more user passwords use the weaker password hash.	[ "kinit admin", "ipa-nis-manage enable ipa-compat-manage enable", "service rpcbind restart service dirsrv restart", "#!/bin/sh 1 is the nis domain, 2 is the nis master server ypcat -d USD1 -h USD2 passwd > /dev/shm/nis-map.passwd 2>&1 IFS=USD'\\n' for line in USD(cat /dev/shm/nis-map.passwd); do IFS=' ' username=USD(echo USDline\|cut -f1 -d:) # Not collecting encrypted password because we need cleartext password to create kerberos key uid=USD(echo USDline\|cut -f3 -d:) gid=USD(echo USDline\|cut -f4 -d:) gecos=USD(echo USDline\|cut -f5 -d:) homedir=USD(echo USDline\|cut -f6 -d:) shell=USD(echo USDline\|cut -f7 -d:) # Now create this entry echo passw0rd1\|ipa user-add USDusername --first=NIS --last=USER --password --gidnumber=USDgid --uid=USDuid --gecos=USDgecos --homedir=USDhomedir --shell=USDshell ipa user-show USDusername done", "kinit admin ./nis-user.sh nisdomain nis-master.example.com", "#!/bin/sh 1 is the nis domain, 2 is the nis master server ypcat -d USD1 -h USD2 group > /dev/shm/nis-map.group 2>&1 IFS=USD'\\n' for line in USD(cat /dev/shm/nis-map.group); do IFS=' ' groupname=USD(echo USDline\|cut -f1 -d:) # Not collecting encrypted password because we need cleartext password to create kerberos key gid=USD(echo USDline\|cut -f3 -d:) members=USD(echo USDline\|cut -f4 -d:) # Now create this entry ipa group-add USDgroupname --desc=NIS_GROUP_USDgroupname --gid=USDgid if [ -n \"USDmembers\" ]; then ipa group-add-member USDgroupname --users=USDmembers fi ipa group-show USDgroupname done", "kinit admin ./nis-group.sh nisdomain nis-master.example.com", "#!/bin/sh 1 is the nis domain, 2 is the nis master server ypcat -d USD1 -h USD2 hosts \| egrep -v \"localhost\|127.0.0.1\" > /dev/shm/nis-map.hosts 2>&1 IFS=USD'\\n' for line in USD(cat /dev/shm/nis-map.hosts); do IFS=' ' ipaddress=USD(echo USDline\|awk '{print USD1}') hostname=USD(echo USDline\|awk '{print USD2}') master=USD(ipa env xmlrpc_uri \|tr -d '[:space:]'\|cut -f3 -d:\|cut -f3 -d/) domain=USD(ipa env domain\|tr -d '[:space:]'\|cut -f2 -d:) if [ USD(echo USDhostname\|grep \"\\.\" \|wc -l) -eq 0 ]; then hostname=USD(echo USDhostname.USDdomain) fi zone=USD(echo USDhostname\|cut -f2- -d.) if [ USD(ipa dnszone-show USDzone 2>/dev/null \| wc -l) -eq 0 ]; then ipa dnszone-add --name-server=USDmaster --admin-email=root.USDmaster fi ptrzone=USD(echo USDipaddress\|awk -F. '{print USD3 \".\" USD2 \".\" USD1 \".in-addr.arpa.\"}') if [ USD(ipa dnszone-show USDptrzone 2>/dev/null\|wc -l) -eq 0 ]; then ipa dnszone-add USDptrzone --name-server=USDmaster --admin-email=root.USDmaster fi # Now create this entry ipa host-add USDhostname --ip-address=USDipaddress ipa host-show USDhostname done", "kinit admin ./nis-hosts.sh nisdomain nis-master.example.com", "#!/bin/sh 1 is the nis domain, 2 is the nis master server ypcat -k -d USD1 -h USD2 netgroup > /dev/shm/nis-map.netgroup 2>&1 IFS=USD'\\n' for line in USD(cat /dev/shm/nis-map.netgroup); do IFS=' ' netgroupname=USD(echo USDline\|awk '{print USD1}') triples=USD(echo USDline\|sed \"s/^USDnetgroupname //\") echo \"ipa netgroup-add USDnetgroupname --desc=NIS_NG_USDnetgroupname\" if [ USD(echo USDline\|grep \"(,\"\|wc -l) -gt 0 ]; then echo \"ipa netgroup-mod USDnetgroupname --hostcat=all\" fi if [ USD(echo USDline\|grep \",,\"\|wc -l) -gt 0 ]; then echo \"ipa netgroup-mod USDnetgroupname --usercat=all\" fi for triple in USDtriples; do triple=USD(echo USDtriple\|sed -e 's/-//g' -e 's/(//' -e 's/)//') if [ USD(echo USDtriple\|grep \",.,\"\|wc -l) -gt 0 ]; then hostname=USD(echo USDtriple\|cut -f1 -d,) username=USD(echo USDtriple\|cut -f2 -d,) domain=USD(echo USDtriple\|cut -f3 -d,) hosts=\"\"; users=\"\"; doms=\"\"; [ -n \"USDhostname\" ] && hosts=\"--hosts=USDhostname\" [ -n \"USDusername\" ] && users=\"--users=USDusername\" [ -n \"USDdomain\" ] && doms=\"--nisdomain=USDdomain\" echo \"ipa netgroup-add-member USDhosts USDusers USDdoms\" else netgroup=USDtriple echo \"ipa netgroup-add USDnetgroup --desc=NIS_NG_USDnetgroup\" fi done done", "if [ USD(echo USDtriple\|grep \",.,\"\|wc -l) -gt 0 ]; then hostname=USD(echo USDtriple\|cut -f1 -d,) username=USD(echo USDtriple\|cut -f2 -d,) domain=USD(echo USDtriple\|cut -f3 -d,) hosts=\"\"; users=\"\"; doms=\"\"; [ -n \"USDhostname\" ] && hosts=\"--hosts=USDhostname\" [ -n \"USDusername\" ] && users=\"--users=USDusername\" [ -n \"USDdomain\" ] && doms=\"--nisdomain=USDdomain\" echo \"ipa netgroup-add-member USDhosts USDusers USDdoms\"", "kinit admin ./nis-hosts.sh nisdomain nis-master.example.com", "#!/bin/sh 1 is for the automount entry in ipa ipa automountlocation-add USD1 2 is the nis domain, 3 is the nis master server, 4 is the map name ypcat -k -d USD2 -h USD3 USD4 > /dev/shm/nis-map.USD4 2>&1 ipa automountmap-add USD1 USD4 basedn=USD(ipa env basedn\|tr -d '[:space:]'\|cut -f2 -d:) cat > /tmp/amap.ldif <<EOF dn: nis-domain=nisdomain.example.com+nis-map=USD4,cn=NIS Server,cn=plugins,cn=config objectClass: extensibleObject nis-domain: USD3 nis-map: USD4 nis-base: automountmapname=USD4,cn=nis,cn=automount,USDbasedn nis-filter: (objectclass=) nis-key-format: %{automountKey} nis-value-format: %{automountInformation} EOF ldapadd -x -h USD3 -D \"cn=directory manager\" -w secret -f /tmp/amap.ldif IFS=USD'\\n' for line in USD(cat /dev/shm/nis-map.USD4); do IFS=\" \" key=USD(echo \"USDline\" \| awk '{print USD1}') info=USD(echo \"USDline\" \| sed -e \"s#^USDkey[ \\t]##\") ipa automountkey-add nis USD4 --key=\"USDkey\" --info=\"USDinfo\" done", "kinit admin ./nis-hosts.sh location nisdomain nis-master.example.com map", "ldapmodify -D \"cn=directory server\" -w secret -p 389 -h ipaserver.example.com dn: cn=config changetype: modify replace: passwordStorageScheme passwordStorageScheme: crypt" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/identity_management_guide/migrating-from-nis
Making open source more inclusive	Making open source more inclusive Red Hat is committed to replacing problematic language in our code, documentation, and web properties. We are beginning with these four terms: master, slave, blacklist, and whitelist. Because of the enormity of this endeavor, these changes will be implemented gradually over several upcoming releases. For more details, see our CTO Chris Wright's message .	null	https://docs.redhat.com/en/documentation/red_hat_fuse/7.13/html/migration_guide/making-open-source-more-inclusive
Chapter 8. Interoperability	Chapter 8. Interoperability This chapter discusses how to use AMQ Ruby in combination with other AMQ components. For an overview of the compatibility of AMQ components, see the product introduction . 8.1. Interoperating with other AMQP clients AMQP messages are composed using the AMQP type system . This common format is one of the reasons AMQP clients in different languages are able to interoperate with each other. When sending messages, AMQ Ruby automatically converts language-native types to AMQP-encoded data. When receiving messages, the reverse conversion takes place. Note More information about AMQP types is available at the interactive type reference maintained by the Apache Qpid project. Table 8.1. AMQP types AMQP type Description null An empty value boolean A true or false value char A single Unicode character string A sequence of Unicode characters binary A sequence of bytes byte A signed 8-bit integer short A signed 16-bit integer int A signed 32-bit integer long A signed 64-bit integer ubyte An unsigned 8-bit integer ushort An unsigned 16-bit integer uint An unsigned 32-bit integer ulong An unsigned 64-bit integer float A 32-bit floating point number double A 64-bit floating point number array A sequence of values of a single type list A sequence of values of variable type map A mapping from distinct keys to values uuid A universally unique identifier symbol A 7-bit ASCII string from a constrained domain timestamp An absolute point in time Table 8.2. AMQ Ruby types before encoding and after decoding AMQP type AMQ Ruby type before encoding AMQ Ruby type after decoding null nil nil boolean true, false true, false char - String string String String binary - String byte - Integer short - Integer int - Integer long Integer Integer ubyte - Integer ushort - Integer uint - Integer ulong - Integer float - Float double Float Float array - Array list Array Array map Hash Hash symbol Symbol Symbol timestamp Date, Time Time Table 8.3. AMQ Ruby and other AMQ client types (1 of 2) AMQ Ruby type before encoding AMQ C++ type AMQ JavaScript type nil nullptr null true, false bool boolean String std::string string Integer int64_t number Float double number Array std::vector Array Hash std::map object Symbol proton::symbol string Date, Time proton::timestamp number Table 8.4. AMQ Ruby and other AMQ client types (2 of 2) AMQ Ruby type before encoding AMQ .NET type AMQ Python type nil null None true, false System.Boolean bool String System.String unicode Integer System.Int64 long Float System.Double float Array Amqp.List list Hash Amqp.Map dict Symbol Amqp.Symbol str Date, Time System.DateTime long 8.2. Interoperating with AMQ JMS AMQP defines a standard mapping to the JMS messaging model. This section discusses the various aspects of that mapping. For more information, see the AMQ JMS Interoperability chapter. JMS message types AMQ Ruby provides a single message type whose body type can vary. By contrast, the JMS API uses different message types to represent different kinds of data. The table below indicates how particular body types map to JMS message types. For more explicit control of the resulting JMS message type, you can set the x-opt-jms-msg-type message annotation. See the AMQ JMS Interoperability chapter for more information. Table 8.5. AMQ Ruby and JMS message types AMQ Ruby body type JMS message type String TextMessage nil TextMessage - BytesMessage Any other type ObjectMessage 8.3. Connecting to AMQ Broker AMQ Broker is designed to interoperate with AMQP 1.0 clients. Check the following to ensure the broker is configured for AMQP messaging: Port 5672 in the network firewall is open. The AMQ Broker AMQP acceptor is enabled. See Default acceptor settings . The necessary addresses are configured on the broker. See Addresses, Queues, and Topics . The broker is configured to permit access from your client, and the client is configured to send the required credentials. See Broker Security . 8.4. Connecting to AMQ Interconnect AMQ Interconnect works with any AMQP 1.0 client. Check the following to ensure the components are configured correctly: Port 5672 in the network firewall is open. The router is configured to permit access from your client, and the client is configured to send the required credentials. See Securing network connections .	null	https://docs.redhat.com/en/documentation/red_hat_amq/2020.q4/html/using_the_amq_ruby_client/interoperability
Chapter 2. BMCEventSubscription [metal3.io/v1alpha1]	Chapter 2. BMCEventSubscription [metal3.io/v1alpha1] Description BMCEventSubscription is the Schema for the fast eventing API Type object 2.1. Specification Property Type Description apiVersion string APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#resources kind string Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds metadata ObjectMeta Standard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata spec object status object 2.1.1. .spec Description Type object Property Type Description context string Arbitrary user-provided context for the event destination string A webhook URL to send events to hostName string A reference to a BareMetalHost httpHeadersRef object A secret containing HTTP headers which should be passed along to the Destination when making a request 2.1.2. .spec.httpHeadersRef Description A secret containing HTTP headers which should be passed along to the Destination when making a request Type object Property Type Description name string name is unique within a namespace to reference a secret resource. namespace string namespace defines the space within which the secret name must be unique. 2.1.3. .status Description Type object Property Type Description error string subscriptionID string 2.2. API endpoints The following API endpoints are available: /apis/metal3.io/v1alpha1/bmceventsubscriptions GET : list objects of kind BMCEventSubscription /apis/metal3.io/v1alpha1/namespaces/{namespace}/bmceventsubscriptions DELETE : delete collection of BMCEventSubscription GET : list objects of kind BMCEventSubscription POST : create a BMCEventSubscription /apis/metal3.io/v1alpha1/namespaces/{namespace}/bmceventsubscriptions/{name} DELETE : delete a BMCEventSubscription GET : read the specified BMCEventSubscription PATCH : partially update the specified BMCEventSubscription PUT : replace the specified BMCEventSubscription /apis/metal3.io/v1alpha1/namespaces/{namespace}/bmceventsubscriptions/{name}/status GET : read status of the specified BMCEventSubscription PATCH : partially update status of the specified BMCEventSubscription PUT : replace status of the specified BMCEventSubscription 2.2.1. /apis/metal3.io/v1alpha1/bmceventsubscriptions Table 2.1. Global query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. pretty string If 'true', then the output is pretty printed. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. HTTP method GET Description list objects of kind BMCEventSubscription Table 2.2. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscriptionList schema 401 - Unauthorized Empty 2.2.2. /apis/metal3.io/v1alpha1/namespaces/{namespace}/bmceventsubscriptions Table 2.3. Global path parameters Parameter Type Description namespace string object name and auth scope, such as for teams and projects Table 2.4. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method DELETE Description delete collection of BMCEventSubscription Table 2.5. Query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. Table 2.6. HTTP responses HTTP code Reponse body 200 - OK Status schema 401 - Unauthorized Empty HTTP method GET Description list objects of kind BMCEventSubscription Table 2.7. Query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. Table 2.8. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscriptionList schema 401 - Unauthorized Empty HTTP method POST Description create a BMCEventSubscription Table 2.9. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields, provided that the ServerSideFieldValidation feature gate is also enabled. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23 and is the default behavior when the ServerSideFieldValidation feature gate is disabled. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default when the ServerSideFieldValidation feature gate is enabled. - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 2.10. Body parameters Parameter Type Description body BMCEventSubscription schema Table 2.11. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscription schema 201 - Created BMCEventSubscription schema 202 - Accepted BMCEventSubscription schema 401 - Unauthorized Empty 2.2.3. /apis/metal3.io/v1alpha1/namespaces/{namespace}/bmceventsubscriptions/{name} Table 2.12. Global path parameters Parameter Type Description name string name of the BMCEventSubscription namespace string object name and auth scope, such as for teams and projects Table 2.13. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method DELETE Description delete a BMCEventSubscription Table 2.14. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed gracePeriodSeconds integer The duration in seconds before the object should be deleted. Value must be non-negative integer. The value zero indicates delete immediately. If this value is nil, the default grace period for the specified type will be used. Defaults to a per object value if not specified. zero means delete immediately. orphanDependents boolean Deprecated: please use the PropagationPolicy, this field will be deprecated in 1.7. Should the dependent objects be orphaned. If true/false, the "orphan" finalizer will be added to/removed from the object's finalizers list. Either this field or PropagationPolicy may be set, but not both. propagationPolicy string Whether and how garbage collection will be performed. Either this field or OrphanDependents may be set, but not both. The default policy is decided by the existing finalizer set in the metadata.finalizers and the resource-specific default policy. Acceptable values are: 'Orphan' - orphan the dependents; 'Background' - allow the garbage collector to delete the dependents in the background; 'Foreground' - a cascading policy that deletes all dependents in the foreground. Table 2.15. Body parameters Parameter Type Description body DeleteOptions schema Table 2.16. HTTP responses HTTP code Reponse body 200 - OK Status schema 202 - Accepted Status schema 401 - Unauthorized Empty HTTP method GET Description read the specified BMCEventSubscription Table 2.17. Query parameters Parameter Type Description resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset Table 2.18. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscription schema 401 - Unauthorized Empty HTTP method PATCH Description partially update the specified BMCEventSubscription Table 2.19. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields, provided that the ServerSideFieldValidation feature gate is also enabled. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23 and is the default behavior when the ServerSideFieldValidation feature gate is disabled. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default when the ServerSideFieldValidation feature gate is enabled. - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 2.20. Body parameters Parameter Type Description body Patch schema Table 2.21. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscription schema 401 - Unauthorized Empty HTTP method PUT Description replace the specified BMCEventSubscription Table 2.22. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields, provided that the ServerSideFieldValidation feature gate is also enabled. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23 and is the default behavior when the ServerSideFieldValidation feature gate is disabled. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default when the ServerSideFieldValidation feature gate is enabled. - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 2.23. Body parameters Parameter Type Description body BMCEventSubscription schema Table 2.24. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscription schema 201 - Created BMCEventSubscription schema 401 - Unauthorized Empty 2.2.4. /apis/metal3.io/v1alpha1/namespaces/{namespace}/bmceventsubscriptions/{name}/status Table 2.25. Global path parameters Parameter Type Description name string name of the BMCEventSubscription namespace string object name and auth scope, such as for teams and projects Table 2.26. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method GET Description read status of the specified BMCEventSubscription Table 2.27. Query parameters Parameter Type Description resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset Table 2.28. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscription schema 401 - Unauthorized Empty HTTP method PATCH Description partially update status of the specified BMCEventSubscription Table 2.29. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields, provided that the ServerSideFieldValidation feature gate is also enabled. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23 and is the default behavior when the ServerSideFieldValidation feature gate is disabled. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default when the ServerSideFieldValidation feature gate is enabled. - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 2.30. Body parameters Parameter Type Description body Patch schema Table 2.31. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscription schema 401 - Unauthorized Empty HTTP method PUT Description replace status of the specified BMCEventSubscription Table 2.32. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields, provided that the ServerSideFieldValidation feature gate is also enabled. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23 and is the default behavior when the ServerSideFieldValidation feature gate is disabled. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default when the ServerSideFieldValidation feature gate is enabled. - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 2.33. Body parameters Parameter Type Description body BMCEventSubscription schema Table 2.34. HTTP responses HTTP code Reponse body 200 - OK BMCEventSubscription schema 201 - Created BMCEventSubscription schema 401 - Unauthorized Empty	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.12/html/provisioning_apis/bmceventsubscription-metal3-io-v1alpha1
Chapter 13. The Apache HTTP Server	Chapter 13. The Apache HTTP Server The Apache HTTP Server provides an open-source HTTP server with the current HTTP standards. [14] In Red Hat Enterprise Linux, the httpd package provides the Apache HTTP Server. Enter the following command to see if the httpd package is installed: If it is not installed and you want to use the Apache HTTP Server, use the yum utility as the root user to install it: 13.1. The Apache HTTP Server and SELinux When SELinux is enabled, the Apache HTTP Server ( httpd ) runs confined by default. Confined processes run in their own domains, and are separated from other confined processes. If a confined process is compromised by an attacker, depending on SELinux policy configuration, an attacker's access to resources and the possible damage they can do is limited. The following example demonstrates the httpd processes running in their own domain. This example assumes the httpd , setroubleshoot , setroubleshoot-server and policycoreutils-python packages are installed: Run the getenforce command to confirm SELinux is running in enforcing mode: The command returns Enforcing when SELinux is running in enforcing mode. Enter the following command as root to start httpd : Confirm that the service is running. The output should include the information below (only the time stamp will differ): To view the httpd processes, execute the following command: The SELinux context associated with the httpd processes is system_u:system_r:httpd_t:s0 . The second last part of the context, httpd_t , is the type. A type defines a domain for processes and a type for files. In this case, the httpd processes are running in the httpd_t domain. SELinux policy defines how processes running in confined domains (such as httpd_t ) interact with files, other processes, and the system in general. Files must be labeled correctly to allow httpd access to them. For example, httpd can read files labeled with the httpd_sys_content_t type, but cannot write to them, even if Linux (DAC) permissions allow write access. Booleans must be enabled to allow certain behavior, such as allowing scripts network access, allowing httpd access to NFS and CIFS volumes, and httpd being allowed to execute Common Gateway Interface (CGI) scripts. When the /etc/httpd/conf/httpd.conf file is configured so httpd listens on a port other than TCP ports 80, 443, 488, 8008, 8009, or 8443, the semanage port command must be used to add the new port number to SELinux policy configuration. The following example demonstrates configuring httpd to listen on a port that is not already defined in SELinux policy configuration for httpd , and, as a consequence, httpd failing to start. This example also demonstrates how to then configure the SELinux system to allow httpd to successfully listen on a non-standard port that is not already defined in the policy. This example assumes the httpd package is installed. Run each command in the example as the root user: Enter the following command to confirm httpd is not running: If the output differs, stop the process: Use the semanage utility to view the ports SELinux allows httpd to listen on: Edit the /etc/httpd/conf/httpd.conf file as root. Configure the Listen option so it lists a port that is not configured in SELinux policy configuration for httpd . In this example, httpd is configured to listen on port 12345: Enter the following command to start httpd : An SELinux denial message similar to the following is logged: For SELinux to allow httpd to listen on port 12345, as used in this example, the following command is required: Start httpd again and have it listen on the new port: Now that SELinux has been configured to allow httpd to listen on a non-standard port (TCP 12345 in this example), httpd starts successfully on this port. To prove that httpd is listening and communicating on TCP port 12345, open a telnet connection to the specified port and issue a HTTP GET command, as follows: [14] For more information, see the section named The Apache HTTP Sever in the System Administrator's Guide .	[ "~]USD rpm -q httpd package httpd is not installed", "~]# yum install httpd", "~]USD getenforce Enforcing", "~]# systemctl start httpd.service", "~]# systemctl status httpd.service httpd.service - The Apache HTTP Server Loaded: loaded (/usr/lib/systemd/system/httpd.service; disabled) Active: active (running) since Mon 2013-08-05 14:00:55 CEST; 8s ago", "~]USD ps -eZ \| grep httpd system_u:system_r:httpd_t:s0 19780 ? 00:00:00 httpd system_u:system_r:httpd_t:s0 19781 ? 00:00:00 httpd system_u:system_r:httpd_t:s0 19782 ? 00:00:00 httpd system_u:system_r:httpd_t:s0 19783 ? 00:00:00 httpd system_u:system_r:httpd_t:s0 19784 ? 00:00:00 httpd system_u:system_r:httpd_t:s0 19785 ? 00:00:00 httpd", "~]# systemctl status httpd.service httpd.service - The Apache HTTP Server Loaded: loaded (/usr/lib/systemd/system/httpd.service; disabled) Active: inactive (dead)", "~]# systemctl stop httpd.service", "~]# semanage port -l \| grep -w http_port_t http_port_t tcp 80, 443, 488, 8008, 8009, 8443", "Change this to Listen on specific IP addresses as shown below to prevent Apache from glomming onto all bound IP addresses (0.0.0.0) # #Listen 12.34.56.78:80 Listen 127.0.0.1:12345", "~]# systemctl start httpd.service Job for httpd.service failed. See 'systemctl status httpd.service' and 'journalctl -xn' for details.", "setroubleshoot: SELinux is preventing the httpd (httpd_t) from binding to port 12345. For complete SELinux messages. run sealert -l f18bca99-db64-4c16-9719-1db89f0d8c77", "~]# semanage port -a -t http_port_t -p tcp 12345", "~]# systemctl start httpd.service", "~]# telnet localhost 12345 Trying 127.0.0.1 Connected to localhost. Escape character is '^]'. GET / HTTP/1.0 HTTP/1.1 200 OK Date: Wed, 02 Dec 2009 14:36:34 GMT Server: Apache/2.2.13 (Red Hat) Accept-Ranges: bytes Content-Length: 3985 Content-Type: text/html; charset=UTF-8 [...continues...]" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/selinux_users_and_administrators_guide/chap-managing_confined_services-the_apache_http_server
10.3. Removing a Guest Virtual Machine Entry	10.3. Removing a Guest Virtual Machine Entry If the guest virtual machine is running, unregister the system, by running the following command in a terminal window as root on the guest: If the system has been deleted, however, the virtual service cannot tell whether the service is deleted or paused. In that case, you must manually remove the system from the server side, using the following steps: Login to the Subscription Manager The Subscription Manager is located on the Red Hat Customer Portal . Login to the Customer Portal using your user name and password, by clicking the login icon at the top of the screen. Click the Subscriptions tab Click the Subscriptions tab. Click the Systems link Scroll down the page and click the Systems link. Delete the system To delete the system profile, locate the specified system's profile in the table, select the check box beside its name and click Delete .	[ "subscription-manager unregister" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/virtualization_deployment_and_administration_guide/virt-who-remove-guest
function::proc_mem_data_pid	function::proc_mem_data_pid Name function::proc_mem_data_pid - Program data size (data + stack) in pages Synopsis Arguments pid The pid of process to examine Description Returns the given process data size (data + stack) in pages, or zero when the process doesn't exist or the number of pages couldn't be retrieved.	[ "proc_mem_data_pid:long(pid:long)" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/systemtap_tapset_reference/api-proc-mem-data-pid
Chapter 2. Installing the Integration Test Suite (tempest)	Chapter 2. Installing the Integration Test Suite (tempest) To manually install the Integration Test Suite, Installing the Integration Test Suite manually . 2.1. Prerequisites An undercloud installation. For more information, see Installing the undercloud . An overcloud deployment. For more information, see Creating a basic overcloud with CLI tools . 2.2. Installing the Integration Test Suite manually If you do not want to install the Integration Test Suite (tempest) automatically with director, you can perform the installation manually later. You must ensure that you have a basic network configuration, install the Integration Test Suite packages, and create a configuration file that contains details about your OpenStack services and other testing behaviour switches. Procedure Ensure that the following networks are available within your Red Hat OpenStack Platform (RHOSP) environment: An external network that can provide a floating IP. A private network. Connect these networks through a router. To create the private network, specify the following options according to your network deployment: To create the public network, specify the following options according to your network deployment: Install the packages related to the Integration Test Suite: This command does not install any tempest plugins. You must install the plugins manually, depending on your RHOSP installation. Install the appropriate tempest plugin for each component in your environment. For example, enter the following command to install the keystone, neutron, cinder, and telemetry plugins: For a full list of packages, see Integration Test Suite packages . Note You can also install the openstack-tempest-all package. This package contains all of the tempest plugins. 2.2.1. Integration Test Suite packages Use dnf search to retrieve a list of tempest test packages: Component Package Name barbican python3-barbican-tests-tempest cinder python3-cinder-tests-tempest designate python3-designate-tests-tempest ec2-api python3-ec2api-tests-tempest heat python3-heat-tests-tempest ironic python3-ironic-tests-tempest keystone python3-keystone-tests-tempest kuryr python3-kuryr-tests-tempest manila python3-manila-tests-tempest mistral python3-mistral-tests-tempest networking-bgvpn python3-networking-bgpvpn-tests-tempest networking-l2gw python3-networking-l2gw-tests-tempest neutron python3-neutron-tests-tempest nova-join python3-novajoin-tests-tempest octavia python3-octavia-tests-tempest patrole python3-patrole-tests-tempest telemetry python3-telemetry-tests-tempest tripleo-common python3-tripleo-common-tests-tempest zaqar python3-zaqar-tests-tempest Note The python3-telemetry-tests-tempest package contains plugins for aodh, panko, gnocchi, and ceilometer tests. The python3-ironic-tests-tempest package contains plugins for ironic and ironic-inspector.	[ "openstack network create <network_name> --share openstack subnet create <subnet_name> --subnet-range <address/prefix> --network <network_name> openstack router create <router_name> openstack router add subnet <router_name> <subnet_name>", "openstack network create <network_name> --external --provider-network-type flat --provider-physical-network datacentre openstack subnet create <subnet_name> --subnet-range <address/prefix> --gateway <default_gateway> --no-dhcp --network <network_name> openstack router set <router_name> --external-gateway <public_network_name>", "sudo dnf -y install openstack-tempest", "sudo dnf install python3-keystone-tests-tempest python3-neutron-tests-tempest python3-cinder-tests-tempest python3-telemetry-tests-tempest", "sudo dnf search USD(openstack service list -c Name -f value) 2>/dev/null \| grep test \| awk '{print USD1}'" ]	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/17.1/html/validating_your_cloud_with_the_red_hat_openstack_platform_integration_test_suite/assembly_installing-the-integration-test-suite-tempest_tempest
function::usymname	function::usymname Name function::usymname - Return the symbol of an address in the current task. EXPERIMENTAL! Synopsis Arguments addr The address to translate. Description Returns the (function) symbol name associated with the given address if known. If not known it will return the hex string representation of addr.	[ "function usymname:string(addr:long)" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/systemtap_tapset_reference/api-usymname
Chapter 2. Preparing to install a cluster that uses SR-IOV or OVS-DPDK on OpenStack	Chapter 2. Preparing to install a cluster that uses SR-IOV or OVS-DPDK on OpenStack Before you install a OpenShift Container Platform cluster that uses single-root I/O virtualization (SR-IOV) or Open vSwitch with the Data Plane Development Kit (OVS-DPDK) on Red Hat OpenStack Platform (RHOSP), you must understand the requirements for each technology and then perform preparatory tasks. 2.1. Requirements for clusters on RHOSP that use either SR-IOV or OVS-DPDK If you use SR-IOV or OVS-DPDK with your deployment, you must meet the following requirements: RHOSP compute nodes must use a flavor that supports huge pages. 2.1.1. Requirements for clusters on RHOSP that use SR-IOV To use single-root I/O virtualization (SR-IOV) with your deployment, you must meet the following requirements: Plan your Red Hat OpenStack Platform (RHOSP) SR-IOV deployment . OpenShift Container Platform must support the NICs that you use. For a list of supported NICs, see "About Single Root I/O Virtualization (SR-IOV) hardware networks" in the "Hardware networks" subsection of the "Networking" documentation. For each node that will have an attached SR-IOV NIC, your RHOSP cluster must have: One instance from the RHOSP quota One port attached to the machines subnet One port for each SR-IOV Virtual Function A flavor with at least 16 GB memory, 4 vCPUs, and 25 GB storage space SR-IOV deployments often employ performance optimizations, such as dedicated or isolated CPUs. For maximum performance, configure your underlying RHOSP deployment to use these optimizations, and then run OpenShift Container Platform compute machines on the optimized infrastructure. For more information about configuring performant RHOSP compute nodes, see Configuring Compute nodes for performance . 2.1.2. Requirements for clusters on RHOSP that use OVS-DPDK To use Open vSwitch with the Data Plane Development Kit (OVS-DPDK) with your deployment, you must meet the following requirements: Plan your Red Hat OpenStack Platform (RHOSP) OVS-DPDK deployment by referring to Planning your OVS-DPDK deployment in the Network Functions Virtualization Planning and Configuration Guide. Configure your RHOSP OVS-DPDK deployment according to Configuring an OVS-DPDK deployment in the Network Functions Virtualization Planning and Configuration Guide. 2.2. Preparing to install a cluster that uses SR-IOV You must configure RHOSP before you install a cluster that uses SR-IOV on it. When installing a cluster using SR-IOV, you must deploy clusters using cgroup v1. For more information, Enabling Linux control group version 1 (cgroup v1) . Important cgroup v1 is a deprecated feature. Deprecated functionality is still included in OpenShift Container Platform and continues to be supported; however, it will be removed in a future release of this product and is not recommended for new deployments. For the most recent list of major functionality that has been deprecated or removed within OpenShift Container Platform, refer to the Deprecated and removed features section of the OpenShift Container Platform release notes. 2.2.1. Creating SR-IOV networks for compute machines If your Red Hat OpenStack Platform (RHOSP) deployment supports single root I/O virtualization (SR-IOV) , you can provision SR-IOV networks that compute machines run on. Note The following instructions entail creating an external flat network and an external, VLAN-based network that can be attached to a compute machine. Depending on your RHOSP deployment, other network types might be required. Prerequisites Your cluster supports SR-IOV. Note If you are unsure about what your cluster supports, review the OpenShift Container Platform SR-IOV hardware networks documentation. You created radio and uplink provider networks as part of your RHOSP deployment. The names radio and uplink are used in all example commands to represent these networks. Procedure On a command line, create a radio RHOSP network: USD openstack network create radio --provider-physical-network radio --provider-network-type flat --external Create an uplink RHOSP network: USD openstack network create uplink --provider-physical-network uplink --provider-network-type vlan --external Create a subnet for the radio network: USD openstack subnet create --network radio --subnet-range <radio_network_subnet_range> radio Create a subnet for the uplink network: USD openstack subnet create --network uplink --subnet-range <uplink_network_subnet_range> uplink 2.3. Preparing to install a cluster that uses OVS-DPDK You must configure RHOSP before you install a cluster that uses SR-IOV on it. Complete Creating a flavor and deploying an instance for OVS-DPDK before you install a cluster on RHOSP. After you perform preinstallation tasks, install your cluster by following the most relevant OpenShift Container Platform on RHOSP installation instructions. Then, perform the tasks under " steps" on this page. 2.4. steps For either type of deployment: Configure the Node Tuning Operator with huge pages support . To complete SR-IOV configuration after you deploy your cluster: Install the SR-IOV Operator . Configure your SR-IOV network device . Create SR-IOV compute machines . Consult the following references after you deploy your cluster to improve its performance: A test pod template for clusters that use OVS-DPDK on OpenStack . A test pod template for clusters that use SR-IOV on OpenStack . A performance profile template for clusters that use OVS-DPDK on OpenStack	[ "openstack network create radio --provider-physical-network radio --provider-network-type flat --external", "openstack network create uplink --provider-physical-network uplink --provider-network-type vlan --external", "openstack subnet create --network radio --subnet-range <radio_network_subnet_range> radio", "openstack subnet create --network uplink --subnet-range <uplink_network_subnet_range> uplink" ]	https://docs.redhat.com/en/documentation/openshift_container_platform_installation/4.16/html/installing_on_openstack/installing-openstack-nfv-preparing
Chapter 7. Deprecated functionality	Chapter 7. Deprecated functionality Deprecated devices are fully supported, which means that they are tested and maintained, and their support status remains unchanged within Red Hat Enterprise Linux 9. However, these devices will likely not be supported in the major version release, and are not recommended for new deployments on the current or future major versions of RHEL. For the most recent list of deprecated functionality within a particular major release, see the latest version of release documentation. For information about the length of support, see Red Hat Enterprise Linux Life Cycle and Red Hat Enterprise Linux Application Streams Life Cycle . A package can be deprecated and not recommended for further use. Under certain circumstances, a package can be removed from the product. Product documentation then identifies more recent packages that offer functionality similar, identical, or more advanced to the one deprecated, and provides further recommendations. For information regarding functionality that is present in RHEL 8 but has been removed in RHEL 9, see Considerations in adopting RHEL 9 . 7.1. Installer and image creation Deprecated Kickstart commands The following Kickstart commands have been deprecated: timezone --ntpservers timezone --nontp logging --level %packages --excludeWeakdeps %packages --instLangs %anaconda pwpolicy Note that where only specific options are listed, the base command and its other options are still available and not deprecated. Using the deprecated commands in Kickstart files prints a warning in the logs. You can turn the deprecated command warnings into errors with the inst.ksstrict boot option. (BZ#1899167) 7.2. Shells and command-line tools Setting the TMPDIR variable in the ReaR configuration file is deprecated Setting the TMPDIR environment variable in the /etc/rear/local.conf or /etc/rear/site.conf ReaR configuration file), by using a statement such as export TMPDIR=... , does not work and is deprecated. To specify a custom directory for ReaR temporary files, export the variable in the shell environment before executing ReaR. For example, execute the export TMPDIR=... statement and then execute the rear command in the same shell session or script. Jira:RHELDOCS-18049 7.3. Security SHA-1 is deprecated for cryptographic purposes The usage of the SHA-1 message digest for cryptographic purposes has been deprecated in RHEL 9. The digest produced by SHA-1 is not considered secure because of many documented successful attacks based on finding hash collisions. The RHEL core crypto components no longer create signatures using SHA-1 by default. Applications in RHEL 9 have been updated to avoid using SHA-1 in security-relevant use cases. Among the exceptions, the HMAC-SHA1 message authentication code and the Universal Unique Identifier (UUID) values can still be created using SHA-1 because these use cases do not currently pose security risks. SHA-1 also can be used in limited cases connected with important interoperability and compatibility concerns, such as Kerberos and WPA-2. See the List of RHEL applications using cryptography that is not compliant with FIPS 140-3 section in the RHEL 9 Security hardening document for more details. If your scenario requires the use of SHA-1 for verifying existing or third-party cryptographic signatures, you can enable it by entering the following command: Alternatively, you can switch the system-wide crypto policies to the LEGACY policy. Note that LEGACY also enables many other algorithms that are not secure. (JIRA:RHELPLAN-110763) SCP is deprecated in RHEL 9 The secure copy protocol (SCP) is deprecated because it has known security vulnerabilities. The SCP API remains available for the RHEL 9 lifecycle but using it reduces system security. In the scp utility, SCP is replaced by the SSH File Transfer Protocol (SFTP) by default. The OpenSSH suite does not use SCP in RHEL 9. SCP is deprecated in the libssh library. (JIRA:RHELPLAN-99136) Digest-MD5 in SASL is deprecated The Digest-MD5 authentication mechanism in the Simple Authentication Security Layer (SASL) framework is deprecated, and it might be removed from the cyrus-sasl packages in a future major release. (BZ#1995600) OpenSSL deprecates MD2, MD4, MDC2, Whirlpool, RIPEMD160, Blowfish, CAST, DES, IDEA, RC2, RC4, RC5, SEED, and PBKDF1 The OpenSSL project has deprecated a set of cryptographic algorithms because they are insecure, uncommonly used, or both. Red Hat also discourages the use of those algorithms, and RHEL 9 provides them for migrating encrypted data to use new algorithms. Users must not depend on those algorithms for the security of their systems. The implementations of the following algorithms have been moved to the legacy provider in OpenSSL: MD2, MD4, MDC2, Whirlpool, RIPEMD160, Blowfish, CAST, DES, IDEA, RC2, RC4, RC5, SEED, and PBKDF1. See the /etc/pki/tls/openssl.cnf configuration file for instructions on how to load the legacy provider and enable support for the deprecated algorithms. ( BZ#1975836 ) /etc/system-fips is now deprecated Support for indicating FIPS mode through the /etc/system-fips file has been removed, and the file will not be included in future versions of RHEL. To install RHEL in FIPS mode, add the fips=1 parameter to the kernel command line during the system installation. You can check whether RHEL operates in FIPS mode by using the fips-mode-setup --check command. (JIRA:RHELPLAN-103232) libcrypt.so.1 is now deprecated The libcrypt.so.1 library is now deprecated, and it might be removed in a future version of RHEL. ( BZ#2034569 ) fapolicyd.rules is deprecated The /etc/fapolicyd/rules.d/ directory for files containing allow and deny execution rules replaces the /etc/fapolicyd/fapolicyd.rules file. The fagenrules script now merges all component rule files in this directory to the /etc/fapolicyd/compiled.rules file. Rules in /etc/fapolicyd/fapolicyd.trust are still processed by the fapolicyd framework but only for ensuring backward compatibility. ( BZ#2054740 ) 7.4. Networking ipset and iptables-nft have been deprecated The ipset and iptables-nft packages have been deprecated in RHEL. The iptables-nft package contains different tools such as iptables , ip6tables , ebtables and arptables . These tools will no longer receive new features and using them for new deployments is not recommended. As a replacement, prefer using the nft command-line tool provided by the nftables package. Existing setups should migrate to nft if possible. When you load the iptables , ip6tables , ebtables , arptables , nft_compat , or ipset module, the module logs the following warning to the /var/log/messages file: For more information on migrating to nftables, see Migrating from iptables to nftables , as well as the iptables-translate(8) and ip6tables-translate(8) man pages. ( BZ#1945151 ) Network teams are deprecated in RHEL 9 The teamd service and the libteam library are deprecated in Red Hat Enterprise Linux 9 and will be removed in the major release. As a replacement, configure a bond instead of a network team. Red Hat focuses its efforts on kernel-based bonding to avoid maintaining two features, bonds and teams, that have similar functions. The bonding code has a high customer adoption, is robust, and has an active community development. As a result, the bonding code receives enhancements and updates. For details about how to migrate a team to a bond, see Migrating a network team configuration to network bond . (BZ#1935544) NetworkManager connection profiles in ifcfg format are deprecated In RHEL 9.0 and later, connection profiles in ifcfg format are deprecated. The major RHEL release will remove the support for this format. However, in RHEL 9, NetworkManager still processes and updates existing profiles in this format if you modify them. By default, NetworkManager now stores connection profiles in keyfile format in the /etc/NetworkManager/system-connections/ directory. Unlike the ifcfg format, the keyfile format supports all connection settings that NetworkManager provides. For further details about the keyfile format and how to migrate profiles, see NetworkManager connection profiles in keyfile format . (BZ#1894877) The iptables back end in firewalld is deprecated In RHEL 9, the iptables framework is deprecated. As a consequence, the iptables backend and the direct interface in firewalld are also deprecated. Instead of the direct interface you can use the native features in firewalld to configure the required rules. ( BZ#2089200 ) 7.5. Kernel ATM encapsulation is deprecated in RHEL 9 Asynchronous Transfer Mode (ATM) encapsulation enables Layer-2 (Point-to-Point Protocol, Ethernet) or Layer-3 (IP) connectivity for the ATM Adaptation Layer 5 (AAL-5). Red Hat has not been providing support for ATM NIC drivers since RHEL 7. The support for ATM implementation is being dropped in RHEL 9. These protocols are currently used only in chipsets, which support the ADSL technology and are being phased out by manufacturers. Therefore, ATM encapsulation is deprecated in Red Hat Enterprise Linux 9. For more information, see PPP Over AAL5 , Multiprotocol Encapsulation over ATM Adaptation Layer 5 , and Classical IP and ARP over ATM . ( BZ#2058153 ) v4l/dvb television and video capture devices are no longer supported With RHEL 9, Red Hat no longer supports Video4Linux ( v4l ) and Linux DVB ( DVB ) devices that consist of various television tuner cards and miscellaneous video capture cards and Red Hat no longer provides their associated drivers. ( BZ#2074598 ) 7.6. File systems and storage lvm2-activation-generator and its generated services removed in RHEL 9.0 The lvm2-activation-generator program and its generated services lvm2-activation , lvm2-activation-early , and lvm2-activation-net are removed in RHEL 9.0. The lvm.conf event_activation setting, used to activate the services, is no longer functional. The only method for auto activating volume groups is event based activation. ( BZ#2038183 ) 7.7. Dynamic programming languages, web and database servers libdb has been deprecated RHEL 8 and RHEL 9 currently provide Berkeley DB ( libdb ) version 5.3.28, which is distributed under the LGPLv2 license. The upstream Berkeley DB version 6 is available under the AGPLv3 license, which is more restrictive. The libdb package is deprecated as of RHEL 9 and might not be available in future major RHEL releases. In addition, cryptographic algorithms have been removed from libdb in RHEL 9 and multiple libdb dependencies have been removed from RHEL 9. Users of libdb are advised to migrate to a different key-value database. For more information, see the Knowledgebase article Available replacements for the deprecated Berkeley DB (libdb) in RHEL . (BZ#1927780, BZ#1974657 , JIRA:RHELPLAN-80695) 7.8. Identity Management SHA-1 in OpenDNSSec is now deprecated OpenDNSSec supports exporting Digital Signatures and authentication records using the SHA-1 algorithm. The use of the SHA-1 algorithm is no longer supported. With the RHEL 9 release, SHA-1 in OpenDNSSec is deprecated and it might be removed in a future minor release. Additionally, OpenDNSSec support is limited to its integration with Red Hat Identity Management. OpenDNSSec is not supported standalone. ( BZ#1979521 ) The SSSD implicit files provider domain is disabled by default The SSSD implicit files provider domain, which retrieves user information from local files such as /etc/shadow and group information from /etc/groups , is now disabled by default. To retrieve user and group information from local files with SSSD: Configure SSSD. Choose one of the following options: Explicitly configure a local domain with the id_provider=files option in the sssd.conf configuration file. Enable the files provider by setting enable_files_domain=true in the sssd.conf configuration file. Configure the name services switch. (JIRA:RHELPLAN-100639) The SMB1 protocol is deprecated in Samba Starting with Samba 4.11, the insecure Server Message Block version 1 (SMB1) protocol is deprecated and will be removed in a future release. To improve the security, by default, SMB1 is disabled in the Samba server and client utilities. Jira:RHELDOCS-16612 7.9. Graphics infrastructures X.org Server is now deprecated The X.org display server is deprecated, and will be removed in a future major RHEL release. The default desktop session is now the Wayland session in most cases. The X11 protocol remains fully supported using the XWayland back end. As a result, applications that require X11 can run in the Wayland session. Red Hat is working on resolving the remaining problems and gaps in the Wayland session. For the outstanding problems in Wayland , see the Known issues section. You can switch your user session back to the X.org back end. For more information, see Selecting GNOME environment and display protocol . (JIRA:RHELPLAN-121048) Motif has been deprecated The Motif widget toolkit has been deprecated in RHEL, because development in the upstream Motif community is inactive. The following Motif packages have been deprecated, including their development and debugging variants: motif openmotif openmotif21 openmotif22 Additionally, the motif-static package has been removed. Red Hat recommends using the GTK toolkit as a replacement. GTK is more maintainable and provides new features compared to Motif. (JIRA:RHELPLAN-98983) 7.10. Red Hat Enterprise Linux system roles The networking system role displays a deprecation warning when configuring teams on RHEL 9 nodes The network teaming capabilities have been deprecated in RHEL 9. As a result, using the networking RHEL system role on an RHEL 8 controller to configure a network team on RHEL 9 nodes, shows a warning about its deprecation. ( BZ#1999770 ) 7.11. Virtualization SecureBoot image verification using SHA1-based signatures is deprecated Performing SecureBoot image verification using SHA1-based signatures on UEFI (PE/COFF) executables has become deprecated. Instead, Red Hat recommends using signatures based on the SHA2 algorithm, or later. (BZ#1935497) Limited support for virtual machine snapshots Creating snapshots of virtual machines (VMs) is currently only supported for VMs not using the UEFI firmware. In addition, during the snapshot operation, the QEMU monitor may become blocked, which negatively impacts the hypervisor performance for certain workloads. Also note that the current mechanism of creating VM snapshots has been deprecated, and Red Hat does not recommend using VM snapshots in a production environment. However, a new VM snapshot mechanism is under development and is planned to be fully implemented in a future minor release of RHEL 9. (JIRA:RHELPLAN-15509, BZ#1621944) virt-manager has been deprecated The Virtual Machine Manager application, also known as virt-manager , has been deprecated. The RHEL web console, also known as Cockpit , is intended to become its replacement in a subsequent release. It is, therefore, recommended that you use the web console for managing virtualization in a GUI. Note, however, that some features available in virt-manager may not be yet available in the RHEL web console. (JIRA:RHELPLAN-10304) libvirtd has become deprecated The monolithic libvirt daemon, libvirtd , has been deprecated in RHEL 9, and will be removed in a future major release of RHEL. Note that you can still use libvirtd for managing virtualization on your hypervisor, but Red Hat recommends switching to the newly introduced modular libvirt daemons. For instructions and details, see the RHEL 9 Configuring and Managing Virtualization document. (JIRA:RHELPLAN-113995) The virtual floppy driver has become deprecated The isa-fdc driver, which controls virtual floppy disk devices, is now deprecated, and will become unsupported in a future release of RHEL. Therefore, to ensure forward compatibility with migrated virtual machines (VMs), Red Hat discourages using floppy disk devices in VMs hosted on RHEL 9. ( BZ#1965079 ) qcow2-v2 image format is deprecated With RHEL 9, the qcow2-v2 format for virtual disk images has become deprecated, and will become unsupported in a future major release of RHEL. In addition, the RHEL 9 Image Builder cannot create disk images in the qcow2-v2 format. Instead of qcow2-v2, Red Hat strongly recommends using qcow2-v3. To convert a qcow2-v2 image to a later format version, use the qemu-img amend command. ( BZ#1951814 ) 7.12. Containers Running RHEL 9 containers on a RHEL 7 host is not supported Running RHEL 9 containers on a RHEL 7 host is not supported. It might work, but it is not guaranteed. For more information, see Red Hat Enterprise Linux Container Compatibility Matrix . (JIRA:RHELPLAN-100087) SHA1 hash algorithm within Podman has been deprecated The SHA1 algorithm used to generate the filename of the rootless network namespace is no longer supported in Podman. Therefore, rootless containers started before updating to Podman 4.1.1 from the RHBA-2022:5951 advisory have to be restarted if they are joined to a network (and not just using slirp4netns ) to ensure they can connect to containers started after the upgrade. (BZ#2069279) rhel9/pause has been deprecated The rhel9/pause container image has been deprecated. ( BZ#2106816 ) 7.13. Deprecated packages This section lists packages that have been deprecated and will probably not be included in a future major release of Red Hat Enterprise Linux. For changes to packages between RHEL 8 and RHEL 9, see Changes to packages in the Considerations in adopting RHEL 9 document. Important The support status of deprecated packages remains unchanged within RHEL 9. For more information about the length of support, see Red Hat Enterprise Linux Life Cycle and Red Hat Enterprise Linux Application Streams Life Cycle . The following packages have been deprecated in RHEL 9: iptables-devel iptables-libs iptables-nft iptables-nft-services iptables-utils libdb mcpp python3-pytz	[ "update-crypto-policies --set DEFAULT:SHA1", "Warning: <module_name> - this driver is not recommended for new deployments. It continues to be supported in this RHEL release, but it is likely to be removed in the next major release. Driver updates and fixes will be limited to critical issues. Please contact Red Hat Support for additional information.", "[domain/local] id_provider=files", "[sssd] enable_files_domain = true", "authselect enable-feature with-files-provider" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/9/html/9.0_release_notes/deprecated_functionality
Chapter 3. Deploying AMQ Broker on OpenShift Container Platform using the AMQ Broker Operator	Chapter 3. Deploying AMQ Broker on OpenShift Container Platform using the AMQ Broker Operator 3.1. Prerequisites Before you install the Operator and use it to create a broker deployment, you should consult the Operator deployment notes in Section 2.7, "Operator deployment notes" . 3.2. Installing the Operator using the CLI Note Each Operator release requires that you download the latest AMQ Broker 7.11.7 Operator Installation and Example Files as described below. The procedures in this section show how to use the OpenShift command-line interface (CLI) to install and deploy the latest version of the Operator for AMQ Broker 7.11 in a given OpenShift project. In subsequent procedures, you use this Operator to deploy some broker instances. For an alternative method of installing the AMQ Broker Operator that uses the OperatorHub graphical interface, see Section 3.3, "Installing the Operator using OperatorHub" . To learn about upgrading existing Operator-based broker deployments, see Chapter 6, Upgrading an Operator-based broker deployment . 3.2.1. Preparing to deploy the Operator Before you deploy the Operator using the CLI, you must download the Operator installation files and prepare the deployment. Procedure In your web browser, navigate to the Software Downloads page for AMQ Broker 7.11.7 releases . Ensure that the value of the Version drop-down list is set to 7.11.7 and the Patches tab is selected. to the latest AMQ Broker 7.11.7 Operator Installation and Example Files , click Download . Download of the amq-broker-operator-7.11.7-ocp-install-examples.zip compressed archive automatically begins. Move the archive to your chosen directory. The following example moves the archive to a directory called ~/broker/operator . USD mkdir ~/broker/operator USD mv amq-broker-operator-7.11.7-ocp-install-examples.zip ~/broker/operator In your chosen directory, extract the contents of the archive. For example: USD cd ~/broker/operator USD unzip amq-broker-operator-7.11.7-ocp-install-examples.zip Switch to the directory that was created when you extracted the archive. For example: USD cd amq-broker-operator-7.11.7-ocp-install-examples Log in to OpenShift Container Platform as a cluster administrator. For example: USD oc login -u system:admin Specify the project in which you want to install the Operator. You can create a new project or switch to an existing one. Create a new project: USD oc new-project <project_name> Or, switch to an existing project: USD oc project <project_name> Specify a service account to use with the Operator. In the deploy directory of the Operator archive that you extracted, open the service_account.yaml file. Ensure that the kind element is set to ServiceAccount . If you want to change the default service account name, in the metadata section, replace amq-broker-controller-manager with a custom name. Create the service account in your project. USD oc create -f deploy/service_account.yaml Specify a role name for the Operator. Open the role.yaml file. This file specifies the resources that the Operator can use and modify. Ensure that the kind element is set to Role . If you want to change the default role name, in the metadata section, replace amq-broker-operator-role with a custom name. Create the role in your project. USD oc create -f deploy/role.yaml Specify a role binding for the Operator. The role binding binds the previously-created service account to the Operator role, based on the names you specified. Open the role_binding.yaml file. Ensure that the name values for ServiceAccount and Role match those specified in the service_account.yaml and role.yaml files. For example: metadata: name: amq-broker-operator-rolebinding subjects: kind: ServiceAccount name: amq-broker-controller-manager roleRef: kind: Role name: amq-broker-operator-role Create the role binding in your project. USD oc create -f deploy/role_binding.yaml Specify a leader election role binding for the Operator. The role binding binds the previously-created service account to the leader election role, based on the names you specified. Create a leader election role for the Operator. USD oc create -f deploy/election_role.yaml Create the leader election role binding in your project. USD oc create -f deploy/election_role_binding.yaml (Optional) If you want the Operator to watch multiple namespaces, complete the following steps: Note If the OpenShift Container Platform cluster already contains installed Operators for AMQ Broker, you must ensure the new Operator does not watch any of the same namespaces as existing Operators. For information on how to identify the namespaces that are watched by existing Operators, see, Identifying namespaces watched by existing Operators . In the deploy directory of the Operator archive that you downloaded and extracted, open the operator_yaml file. If you want the Operator to watch all namespaces in the cluster, in the WATCH_NAMESPACE section, add a value attribute and set the value to an asterisk. Comment out the existing attributes in the WATCH_NAMESPACE section. For example: - name: WATCH_NAMESPACE value: "*" # valueFrom: # fieldRef: # fieldPath: metadata.namespace Note To avoid conflicts, ensure that multiple Operators do not watch the same namespace. For example, if you deploy an Operator to watch all namespaces on the cluster, you cannot deploy another Operator to watch individual namespaces. If Operators are already deployed on the cluster, you can specify a list of namespaces that the new Operator watches, as described in the following step. If you want the Operator to watch multiple, but not all, namespaces on the cluster, in the WATCH_NAMESPACE section, specify a list of namespaces. Ensure that you exclude any namespaces that are watched by existing Operators. For example: - name: WATCH_NAMESPACE value: "namespace1, namespace2"`. In the deploy directory of the Operator archive that you downloaded and extracted, open the cluster_role_binding.yaml file. In the Subjects section, specify a namespace that corresponds to the OpenShift Container Platform project to which you are deploying the Operator. For example: Subjects: - kind: ServiceAccount name: amq-broker-controller-manager namespace: operator-project Note If you previously deployed brokers using an earlier version of the Operator, and you want to deploy the Operator to watch multiple namespaces, see Before you upgrade . Create a cluster role in your project. USD oc create -f deploy/cluster_role.yaml Create a cluster role binding in your project. USD oc create -f deploy/cluster_role_binding.yaml In the procedure that follows, you deploy the Operator in your project. 3.2.2. Deploying the Operator using the CLI The procedure in this section shows how to use the OpenShift command-line interface (CLI) to deploy the latest version of the Operator for AMQ Broker 7.11 in your OpenShift project. Prerequisites You must have already prepared your OpenShift project for the Operator deployment. See Section 3.2.1, "Preparing to deploy the Operator" . Starting in AMQ Broker 7.3, you use a new version of the Red Hat Ecosystem Catalog to access container images. This new version of the registry requires you to become an authenticated user before you can access images. Before you can follow the procedure in this section, you must first complete the steps described in Red Hat Container Registry Authentication . If you intend to deploy brokers with persistent storage and do not have container-native storage in your OpenShift cluster, you need to manually provision Persistent Volumes (PVs) and ensure that they are available to be claimed by the Operator. For example, if you want to create a cluster of two brokers with persistent storage (that is, by setting persistenceEnabled=true in your Custom Resource), you need to have two PVs available. By default, each broker instance requires storage of 2 GiB. If you specify persistenceEnabled=false in your Custom Resource, the deployed brokers uses ephemeral storage. Ephemeral storage means that that every time you restart the broker Pods, any existing data is lost. For more information about provisioning persistent storage, see: Understanding persistent storage Procedure In the OpenShift command-line interface (CLI), log in to OpenShift as a cluster administrator. For example: USD oc login -u system:admin Switch to the project that you previously prepared for the Operator deployment. For example: USD oc project <project_name> Switch to the directory that was created when you previously extracted the Operator installation archive. For example: USD cd ~/broker/operator/amq-broker-operator-7.11.7-ocp-install-examples Deploy the CRDs that are included with the Operator. You must install the CRDs in your OpenShift cluster before deploying and starting the Operator. Deploy the main broker CRD. USD oc create -f deploy/crds/broker_activemqartemis_crd.yaml Deploy the address CRD. USD oc create -f deploy/crds/broker_activemqartemisaddress_crd.yaml Deploy the scaledown controller CRD. USD oc create -f deploy/crds/broker_activemqartemisscaledown_crd.yaml Deploy the security CRD: USD oc create -f deploy/crds/broker_activemqartemissecurity_crd.yaml Link the pull secret associated with the account used for authentication in the Red Hat Ecosystem Catalog with the default , deployer , and builder service accounts for your OpenShift project. USD oc secrets link --for=pull default <secret_name> USD oc secrets link --for=pull deployer <secret_name> USD oc secrets link --for=pull builder <secret_name> In the deploy directory of the Operator archive that you downloaded and extracted, open the operator.yaml file. Ensure that the value of the spec.containers.image property corresponds to version 7.11.7-opr-2 of the Operator, as shown below. spec: template: spec: containers: #image: registry.redhat.io/amq7/amq-broker-rhel8-operator:7.10 image: registry.redhat.io/amq7/amq-broker-rhel8-operator@sha256:d5c10ee9a342d7fd59bdd3cfae25029548f5081c985c9bdf5656dbd5e8877e0e Note In the operator.yaml file, the Operator uses an image that is represented by a Secure Hash Algorithm (SHA) value. The comment line, which begins with a number sign ( # ) symbol, denotes that the SHA value corresponds to a specific container image tag. Deploy the Operator. USD oc create -f deploy/operator.yaml In your OpenShift project, the Operator starts in a new Pod. In the OpenShift Container Platform web console, the information on the Events tab of the Operator Pod confirms that OpenShift has deployed the Operator image that you specified, has assigned a new container to a node in your OpenShift cluster, and has started the new container. In addition, if you click the Logs tab within the Pod, the output should include lines resembling the following: The preceding output confirms that the newly-deployed Operator is communicating with Kubernetes, that the controllers for the broker and addressing are running, and that these controllers have started some workers. Note It is recommended that you deploy only a single instance of the AMQ Broker Operator in a given OpenShift project. Setting the spec.replicas property of your Operator deployment to a value greater than 1 , or deploying the Operator more than once in the same project is not recommended. Additional resources For an alternative method of installing the AMQ Broker Operator that uses the OperatorHub graphical interface, see Section 3.3, "Installing the Operator using OperatorHub" . 3.3. Installing the Operator using OperatorHub 3.3.1. Overview of the Operator Lifecycle Manager In OpenShift Container Platform 4.5 and later, the Operator Lifecycle Manager (OLM) helps users install, update, and generally manage the lifecycle of all Operators and their associated services running across their clusters. It is part of the Operator Framework, an open source toolkit designed to manage Kubernetes-native applications (Operators) in an effective, automated, and scalable way. The OLM runs by default in OpenShift Container Platform 4.5 and later, which aids cluster administrators in installing, upgrading, and granting access to Operators running on their cluster. The OpenShift Container Platform web console provides management screens for cluster administrators to install Operators, as well as grant specific projects access to use the catalog of Operators available on the cluster. OperatorHub is the graphical interface that OpenShift cluster administrators use to discover, install, and upgrade Operators using the OLM. With one click, these Operators can be pulled from OperatorHub, installed on the cluster, and managed by the OLM, ready for engineering teams to self-service manage the software in development, test, and production environments. When you have deployed the Operator, you can use Custom Resource (CR) instances to create broker deployments such as standalone and clustered brokers. 3.3.2. Deploying the Operator from OperatorHub This procedure shows how to use OperatorHub to deploy the latest version of the Operator for AMQ Broker to a specified OpenShift project. Note In OperatorHub, you can install only the latest Operator version that is provided in each channel. If you want to install an earlier version of an Operator, you must install the Operator by using the CLI. For more information, see Section 3.2, "Installing the Operator using the CLI" . Prerequisites The Red Hat Integration - AMQ Broker for RHEL 8 (Multiarch) Operator must be available in OperatorHub. You have cluster administrator privileges. Procedure Log in to the OpenShift Container Platform web console as a cluster administrator. In left navigation menu, click Operators OperatorHub . On the Project drop-down menu at the top of the OperatorHub page, select the project in which you want to deploy the Operator. On the OperatorHub page, use the Filter by keyword... box to find the Red Hat Integration - AMQ Broker for RHEL 8 (Multiarch) Operator. Note In OperatorHub, you might find more than one Operator than includes AMQ Broker in its name. Ensure that you click the Red Hat Integration - AMQ Broker for RHEL 8 (Multiarch) Operator. When you click this Operator, review the information pane that opens. For AMQ Broker 7.11, the latest minor version tag of this Operator is 7.11.7-opr-2 . Click the Red Hat Integration - AMQ Broker for RHEL 8 (Multiarch) Operator. On the dialog box that appears, click Install . On the Install Operator page: Under Update Channel , select the 7.11.x channel to receive updates for version 7.11 only. The 7.11.x channel is a Long Term Support (LTS) channel. Depending on when your OpenShift Container Platform cluster was installed, you may also see channels for older versions of AMQ Broker. The only other supported channel is 7.10.x , which is also an LTS channel. Under Installation Mode , choose which namespaces the Operator watches: A specific namespace on the cluster - The Operator is installed in that namespace and only monitors that namespace for CR changes. All namespaces - The Operator monitors all namespaces for CR changes. Note If you previously deployed brokers using an earlier version of the Operator, and you want deploy the Operator to watch many namespaces, see Before you upgrade . From the Installed Namespace drop-down menu, select the project in which you want to install the Operator. Under Approval Strategy , ensure that the radio button entitled Automatic is selected. This option specifies that updates to the Operator do not require manual approval for installation to take place. Click Install . When the Operator installation is complete, the Installed Operators page opens. You should see that the Red Hat Integration - AMQ Broker for RHEL 8 (Multiarch) Operator is installed in the project namespace that you specified. Additional resources To learn how to create a broker deployment in a project that has the Operator for AMQ Broker installed, see Section 3.4.1, "Deploying a basic broker instance" . 3.4. Creating Operator-based broker deployments 3.4.1. Deploying a basic broker instance The following procedure shows how to use a Custom Resource (CR) instance to create a basic broker deployment. Note While you can create more than one broker deployment in a given OpenShift project by deploying multiple Custom Resource (CR) instances, typically, you create a single broker deployment in a project, and then deploy multiple CR instances for addresses. Red Hat recommends you create broker deployments in separate projects. In AMQ Broker 7.11, if you want to configure the following items, you must add the appropriate configuration to the main broker CR instance before deploying the CR for the first time. The size and storage class of the Persistent Volume Claim (PVC) required by each broker in a deployment for persistent storage Limits and requests for memory and CPU for each broker in a deployment Prerequisites You must have already installed the AMQ Broker Operator. To use the OpenShift command-line interface (CLI) to install the AMQ Broker Operator, see Section 3.2, "Installing the Operator using the CLI" . To use the OperatorHub graphical interface to install the AMQ Broker Operator, see Section 3.3, "Installing the Operator using OperatorHub" . You should understand how the Operator chooses a broker container image to use for your broker deployment. For more information, see Section 2.6, "How the Operator chooses container images" . Starting in AMQ Broker 7.3, you use a new version of the Red Hat Ecosystem Catalog to access container images. This new version of the registry requires you to become an authenticated user before you can access images. Before you can follow the procedure in this section, you must first complete the steps described in Red Hat Container Registry Authentication . Procedure When you have successfully installed the Operator, the Operator is running and listening for changes related to your CRs. This example procedure shows how to use a CR instance to deploy a basic broker in your project. Start configuring a Custom Resource (CR) instance for the broker deployment. Using the OpenShift command-line interface: Log in to OpenShift as a user that has privileges to deploy CRs in the project in which you are creating the deployment. Open the sample CR file called broker_activemqartemis_cr.yaml that was included in the deploy/crs directory of the Operator installation archive that you downloaded and extracted. Using the OpenShift Container Platform web console: Log in to the console as a user that has privileges to deploy CRs in the project in which you are creating the deployment. Start a new CR instance based on the main broker CRD. In the left pane, click Administration Custom Resource Definitions . Click the ActiveMQArtemis CRD. Click the Instances tab. Click Create ActiveMQArtemis . Within the console, a YAML editor opens, enabling you to configure a CR instance. For a basic broker deployment, a configuration might resemble that shown below. apiVersion: broker.amq.io/v1beta1 kind: ActiveMQArtemis metadata: name: ex-aao spec: deploymentPlan: size: 1 image: placeholder requireLogin: false persistenceEnabled: true journalType: nio messageMigration: true Observe that in the broker_activemqartemis_cr.yaml sample CR file, the image property is set to a default value of placeholder . This value indicates that, by default, the image property does not specify a broker container image to use for the deployment. To learn how the Operator determines the appropriate broker container image to use, see Section 2.6, "How the Operator chooses container images" . Note The broker_activemqartemis_cr.yaml sample CR uses a naming convention of ex-aao . This naming convention denotes that the CR is an example resource for the AMQ Broker Operator . AMQ Broker is based on the ActiveMQ Artemis project. When you deploy this sample CR, the resulting StatefulSet uses the name ex-aao-ss . Furthermore, broker Pods in the deployment are directly based on the StatefulSet name, for example, ex-aao-ss-0 , ex-aao-ss-1 , and so on. The application name in the CR appears in the deployment as a label on the StatefulSet. You might use this label in a Pod selector, for example. The size property specifies the number of brokers to deploy. A value of 2 or greater specifies a clustered broker deployment. However, to deploy a single broker instance, ensure that the value is set to 1 . Deploy the CR instance. Using the OpenShift command-line interface: Save the CR file. Switch to the project in which you are creating the broker deployment. Create the CR instance. Using the OpenShift web console: When you have finished configuring the CR, click Create . In the OpenShift Container Platform web console, click Workloads StatefulSets . You see a new StatefulSet called ex-aao-ss . Click the ex-aao-ss StatefulSet. You see that there is one Pod, corresponding to the single broker that you defined in the CR. Within the StatefulSet, click the Pods tab. Click the ex-aao-ss Pod. On the Events tab of the running Pod, you see that the broker container has started. The Logs tab shows that the broker itself is running. To test that the broker is running normally, access a shell on the broker Pod to send some test messages. Using the OpenShift Container Platform web console: Click Workloads Pods . Click the ex-aao-ss Pod. Click the Terminal tab. Using the OpenShift command-line interface: Get the Pod names and internal IP addresses for your project. Access the shell for the broker Pod. From the shell, use the artemis command to send some test messages. Specify the internal IP address of the broker Pod in the URL. For example: The preceding command automatically creates a queue called demoQueue on the broker and sends a default quantity of 1000 messages to the queue. You should see output that resembles the following: Additional resources For a complete configuration reference for the main broker Custom Resource (CR), see Section 8.1, "Custom Resource configuration reference" . To learn how to connect a running broker to AMQ Management Console, see Chapter 5, Connecting to AMQ Management Console for an Operator-based broker deployment . 3.4.2. Deploying clustered brokers If there are two or more broker Pods running in your project, the Pods automatically form a broker cluster. A clustered configuration enables brokers to connect to each other and redistribute messages as needed, for load balancing. The following procedure shows you how to deploy clustered brokers. By default, the brokers in this deployment use on demand load balancing, meaning that brokers will forward messages only to other brokers that have matching consumers. Prerequisites A basic broker instance is already deployed. See Section 3.4.1, "Deploying a basic broker instance" . Procedure Open the CR file that you used for your basic broker deployment. For a clustered deployment, ensure that the value of deploymentPlan.size is 2 or greater. For example: apiVersion: broker.amq.io/v1beta1 kind: ActiveMQArtemis metadata: name: ex-aao spec: deploymentPlan: size: 4 image: placeholder ... Note In the metadata section, you need to include the namespace property and specify a value only if you are using the OpenShift Container Platform web console to create your CR instance. The value that you should specify is the name of the OpenShift project for your broker deployment. Save the modified CR file. Log in to OpenShift as a user that has privileges to deploy CRs in the project in which you previously created your basic broker deployment. Switch to the project in which you previously created your basic broker deployment. At the command line, apply the change: USD oc apply -f <path/to/custom_resource_instance> .yaml In the OpenShift Container Platform web console, additional broker Pods starts in your project, according to the number specified in your CR. By default, the brokers running in the project are clustered. Open the Logs tab of each Pod. The logs show that OpenShift has established a cluster connection bridge on each broker. Specifically, the log output includes a line like the following: 3.4.3. Applying Custom Resource changes to running broker deployments The following are some important things to note about applying Custom Resource (CR) changes to running broker deployments: You cannot dynamically update the persistenceEnabled attribute in your CR. To change this attribute, scale your cluster down to zero brokers. Delete the existing CR. Then, recreate and redeploy the CR with your changes, also specifying a deployment size. As described in Section 3.2.2, "Deploying the Operator using the CLI" , if you create a broker deployment with persistent storage (that is, by setting persistenceEnabled=true in your CR), you might need to provision Persistent Volumes (PVs) for the AMQ Broker Operator to claim for your broker Pods. If you scale down the size of your broker deployment, the Operator releases any PVs that it previously claimed for the broker Pods that are now shut down. However, if you remove your broker deployment by deleting your CR, AMQ Broker Operator does not release Persistent Volume Claims (PVCs) for any broker Pods that are still in the deployment when you remove it. In addition, these unreleased PVs are unavailable to any new deployment. In this case, you need to manually release the volumes. For more information, see Release a persistent volume in the OpenShift documentation. In AMQ Broker 7.11, if you want to configure the following items, you must add the appropriate configuration to the main CR instance before deploying the CR for the first time. The size and storage class of the Persistent Volume Claim (PVC) required by each broker in a deployment for persistent storage . Limits and requests for memory and CPU for each broker in a deployment . During an active scaling event, any further changes that you apply are queued by the Operator and executed only when scaling is complete. For example, suppose that you scale the size of your deployment down from four brokers to one. Then, while scaledown is taking place, you also change the values of the broker administrator user name and password. In this case, the Operator queues the user name and password changes until the deployment is running with one active broker. All CR changes - apart from changing the size of your deployment, or changing the value of the expose attribute for acceptors, connectors, or the console - cause existing brokers to be restarted. If you have multiple brokers in your deployment, only one broker restarts at a time. 3.5. Changing the logging level for the Operator The default logging level for AMQ Broker Operator is info , which logs information and error messages. You can change the default logging level to increase or decrease the detail that is written to the Operator logs. If you use the OpenShift Container Platform command-line interface to install the Operator, you can set the new logging level in the Operator configuration file, operator.yaml , either before or after you install the Operator. If you use Operator Hub, you can use the OpenShift Container Platform web console to set the logging level in the Operator subscription after you install the Operator. The other available logging levels for the Operator are: error Writes error messages only to the log. debug Write all messages to the log including debugging messages. Procedure Using the OpenShift Container Platform command-line interface: Log in as a cluster administrator. For example: USD oc login -u system:admin If the Operator is not installed, complete the following steps to change the logging level. In the deploy directory of the Operator archive that you downloaded and extracted, open the operator.yaml file. Change the value of the zap-log-level attribute to debug or error . For example: apiVersion: apps/v1 kind: Deployment metadata: labels: control-plane: controller-manager name: amq-broker-controller-manager spec: containers: - args: - --zap-log-level=error ... Save the operator.yaml file. Install the Operator. If the Operator is already installed, use the sed command to change the logging level in the deploy/operator.yaml file and redeploy the Operator. For example, the following command changes the logging level from info to error and redeploys the Operator: USD sed 's/--zap-log-level=info/--zap-log-level=error/' deploy/operator.yaml \| oc apply -f - Using the OpenShift Container Platform web console: Log in to the OpenShift Container Platform as a cluster administrator. In the left pane, click Operators Installed Operators . Click the Red Hat Integration - AMQ Broker for RHEL 8 (Multiarch) Operator. Click the Subscriptions tab. Click Actions . Click Edit Subscription . Click the YAML tab. Within the console, a YAML editor opens, enabling you to edit the subscription. In the config element, add an environment variable called ARGS and specify a logging level of info , debug or error . In the following example, an ARGS environment variable that specifies a logging level of debug is passed to the Operator container. apiVersion: operators.coreos.com/v1alpha1 kind: Subscription spec: ... config: env: - name: ARGS value: "--zap-log-level=debug" ... Click Save. 3.6. Viewing status information for your broker deployment You can view the status of a series of standard conditions reported by OpenShift Container Platform for your broker deployment. You can also view additional status information provided in the Custom Resource (CR) for your broker deployment. Procedure Open the CR instance for the broker deployment. Using the OpenShift command-line interface: Log in to OpenShift Container Platform as a user that has privileges to view CRs in the project for the broker deployment. View the CR for your deployment. Using the OpenShift Container Platform web console: Log in to the console as a user that has privileges to deploy CRs in the project for the broker deployment. In the left pane, click Operators Installed Operator . Click the Red Hat Integration - AMQ Broker for RHEL 8 (Multiarch) operator. Click the ActiveMQ Artemis tab. Click the name of the ActiveMQ Artemis instance. View the status of the OpenShift Container Platform conditions for your broker deployment. Using the OpenShift command-line interface: Go to the status section of the CR and view the conditions details. Using the OpenShift Container Platform web console: In the Details tab, scroll down to the Conditions section. A condition has a status and a type. It might also have a reason, a message and other details. A condition has a status value of True if the condition is met, False if the condition is not met, or Unknown if the status of the condition cannot be determined. Note The Valid condition also has a status of Unknown if the CR does not comply with the recommended use of the spec.deploymentPlan.image , spec.deploymentPlan.initImage and the spec.version attribute in a CR. For more information, see Section 6.4.3, "Validation of restrictions applied to automatic upgrades" . Status information is provided for the following conditions: Condition name Displays the status of... Valid The validation of the CR. If the status of the Valid condition is False , the Operator does not complete the reconciliation and update the StatefulSet until you first resolve the issue that caused the false status. Deployed The availability of the StatefulSet, Pods and other resources. Ready A top-level condition which summarizes the other more detailed conditions. The Ready condition has a status of True only if none of the other conditions have a status of False . BrokerPropertiesApplied The properties configured in the CR that use the brokerProperties attribute. For more information about the BrokerPropertiesApplied condition, see Section 4.17, "Configuring items not exposed in the Custom Resource Definition" . JaasPropertiesApplied The Java Authentication and Authorization Service (JAAS) login modules configured in the CR. For more information about the JaasPropertiesApplied condition, see Section 4.3.1, "Configuring JAAS login modules in a secret" . View additional status information for your broker deployment in the status section of the CR. The following additional status information is displayed: deploymentPlanSize The number of broker Pods in the deployment. podstatus The status and name of each broker Pod in the deployment. version The version of the broker and the registry URLs of the broker and init container images that are deployed. upgrade The ability of the Operator to apply major, minor, patch and security updates to the deployment, which is determined by the values of the spec.deploymentPlan.image and spec.version attributes in the CR. If the spec.deploymentPlan.image attribute specifies the registry URL of a broker container image, the status of all upgrade types is False , which means that the Operator cannot upgrade the existing container images. If the spec.deploymentPlan.image attribute is not in the CR or has a value of placeholder , the configuration of the spec.version attribute affects the upgrade status as follows: The status of securityUpdates is True , irrespective of whether the spec.version attribute is configured or its value. The status of patchUpdates is True if the value of the spec.version attribute has only a major and a minor version, for example, '7.10', so the Operator can upgrade to the latest patch version of the container images. The status of minorUpdates is True if the value of the spec.version attribute has only a major version, for example, '7', so the Operator can upgrade to the latest minor and patch versions of the container images. The status of majorUpdates is True if the spec.version attribute is not in the CR, so any available upgrades can be deployed, including an upgrade from 7.x.x to 8.x.x, if this version is available.	[ "mkdir ~/broker/operator mv amq-broker-operator-7.11.7-ocp-install-examples.zip ~/broker/operator", "cd ~/broker/operator unzip amq-broker-operator-7.11.7-ocp-install-examples.zip", "cd amq-broker-operator-7.11.7-ocp-install-examples", "oc login -u system:admin", "oc new-project <project_name>", "oc project <project_name>", "oc create -f deploy/service_account.yaml", "oc create -f deploy/role.yaml", "metadata: name: amq-broker-operator-rolebinding subjects: kind: ServiceAccount name: amq-broker-controller-manager roleRef: kind: Role name: amq-broker-operator-role", "oc create -f deploy/role_binding.yaml", "oc create -f deploy/election_role.yaml", "oc create -f deploy/election_role_binding.yaml", "- name: WATCH_NAMESPACE value: \"*\" valueFrom: fieldRef: fieldPath: metadata.namespace", "- name: WATCH_NAMESPACE value: \"namespace1, namespace2\"`.", "Subjects: - kind: ServiceAccount name: amq-broker-controller-manager namespace: operator-project", "oc create -f deploy/cluster_role.yaml", "oc create -f deploy/cluster_role_binding.yaml", "oc login -u system:admin", "oc project <project_name>", "cd ~/broker/operator/amq-broker-operator-7.11.7-ocp-install-examples", "oc create -f deploy/crds/broker_activemqartemis_crd.yaml", "oc create -f deploy/crds/broker_activemqartemisaddress_crd.yaml", "oc create -f deploy/crds/broker_activemqartemisscaledown_crd.yaml", "oc create -f deploy/crds/broker_activemqartemissecurity_crd.yaml", "oc secrets link --for=pull default <secret_name> oc secrets link --for=pull deployer <secret_name> oc secrets link --for=pull builder <secret_name>", "spec: template: spec: containers: #image: registry.redhat.io/amq7/amq-broker-rhel8-operator:7.10 image: registry.redhat.io/amq7/amq-broker-rhel8-operator@sha256:d5c10ee9a342d7fd59bdd3cfae25029548f5081c985c9bdf5656dbd5e8877e0e", "oc create -f deploy/operator.yaml", "{\"level\":\"info\",\"ts\":1553619035.8302743,\"logger\":\"kubebuilder.controller\",\"msg\":\"Starting Controller\",\"controller\":\"activemqartemisaddress-controller\"} {\"level\":\"info\",\"ts\":1553619035.830541,\"logger\":\"kubebuilder.controller\",\"msg\":\"Starting Controller\",\"controller\":\"activemqartemis-controller\"} {\"level\":\"info\",\"ts\":1553619035.9306898,\"logger\":\"kubebuilder.controller\",\"msg\":\"Starting workers\",\"controller\":\"activemqartemisaddress-controller\",\"worker count\":1} {\"level\":\"info\",\"ts\":1553619035.9311671,\"logger\":\"kubebuilder.controller\",\"msg\":\"Starting workers\",\"controller\":\"activemqartemis-controller\",\"worker count\":1}", "login -u <user> -p <password> --server= <host:port>", "apiVersion: broker.amq.io/v1beta1 kind: ActiveMQArtemis metadata: name: ex-aao spec: deploymentPlan: size: 1 image: placeholder requireLogin: false persistenceEnabled: true journalType: nio messageMigration: true", "oc project <project_name>", "oc create -f <path/to/custom_resource_instance> .yaml", "oc get pods -o wide NAME STATUS IP amq-broker-operator-54d996c Running 10.129.2.14 ex-aao-ss-0 Running 10.129.2.15", "oc rsh ex-aao-ss-0", "sh-4.2USD ./amq-broker/bin/artemis producer --url tcp://10.129.2.15:61616 --destination queue://demoQueue", "Connection brokerURL = tcp://10.129.2.15:61616 Producer ActiveMQQueue[demoQueue], thread=0 Started to calculate elapsed time Producer ActiveMQQueue[demoQueue], thread=0 Produced: 1000 messages Producer ActiveMQQueue[demoQueue], thread=0 Elapsed time in second : 3 s Producer ActiveMQQueue[demoQueue], thread=0 Elapsed time in milli second : 3492 milli seconds", "apiVersion: broker.amq.io/v1beta1 kind: ActiveMQArtemis metadata: name: ex-aao spec: deploymentPlan: size: 4 image: placeholder", "oc login -u <user> -p <password> --server= <host:port>", "oc project <project_name>", "oc apply -f <path/to/custom_resource_instance> .yaml", "targetConnector=ServerLocatorImpl (identity=(Cluster-connection-bridge::ClusterConnectionBridge@6f13fb88", "oc login -u system:admin", "apiVersion: apps/v1 kind: Deployment metadata: labels: control-plane: controller-manager name: amq-broker-controller-manager spec: containers: - args: - --zap-log-level=error", "sed 's/--zap-log-level=info/--zap-log-level=error/' deploy/operator.yaml \| oc apply -f -", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription spec: config: env: - name: ARGS value: \"--zap-log-level=debug\"", "get ActiveMQArtemis < CR instance name > -n < namespace > -o yaml" ]	https://docs.redhat.com/en/documentation/red_hat_amq_broker/7.11/html/deploying_amq_broker_on_openshift/deploying-broker-on-ocp-using-operator_broker-ocp