Datasets:

mtpti5iD
/

redhat-docs_dataset

Dataset card Data Studio Files Files and versions Community

Split (2)

train · 44.6k rows

Subsets and Splits

No saved queries yet

Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.

title stringlengths 4 168	content stringlengths 7 1.74M	commands sequencelengths 1 5.62k ⌀	url stringlengths 79 342
Chapter 3. Installing Data Grid Operator	Chapter 3. Installing Data Grid Operator Install Data Grid Operator into a OpenShift namespace to create and manage Data Grid clusters. 3.1. Installing Data Grid Operator on Red Hat OpenShift Create subscriptions to Data Grid Operator on OpenShift so you can install different Data Grid versions and receive automatic updates. Automatic updates apply to Data Grid Operator first and then for each Data Grid node. Data Grid Operator updates clusters one node at a time, gracefully shutting down each node and then bringing it back online with the updated version before going on to the node. Prerequisites Access to OperatorHub running on OpenShift. Some OpenShift environments, such as OpenShift Container Platform, can require administrator credentials. Have an OpenShift project for Data Grid Operator if you plan to install it into a specific namespace. Procedure Log in to the OpenShift Web Console. Navigate to OperatorHub . Find and select Data Grid Operator. Select Install and continue to Create Operator Subscription . Specify options for your subscription. Installation Mode You can install Data Grid Operator into a Specific namespace or All namespaces. Update Channel Get updates for Data Grid Operator 8.4.x. Approval Strategies Automatically install updates from the 8.4.x channel or require approval before installation. Select Subscribe to install Data Grid Operator. Navigate to Installed Operators to verify the Data Grid Operator installation. 3.2. Installing Data Grid Operator with the native CLI plugin Install Data Grid Operator with the native Data Grid CLI plugin, kubectl-infinispan . Prerequisites Have kubectl-infinispan on your PATH . Procedure Run the oc infinispan install command to create Data Grid Operator subscriptions, for example: Verify the installation. Tip Use oc infinispan install --help for command options and descriptions. 3.3. Installing Data Grid Operator with an OpenShift client You can use the oc client to create Data Grid Operator subscriptions as an alternative to installing through the OperatorHub or with the native Data Grid CLI. Prerequisites Have an oc client. Procedure Set up projects. Create a project for Data Grid Operator. If you want Data Grid Operator to control a specific Data Grid cluster only, create a project for that cluster. 1 Creates a project into which you install Data Grid Operator. 2 Optionally creates a project for a specific Data Grid cluster if you do not want Data Grid Operator to watch all projects. Create an OperatorGroup resource. Control all Data Grid clusters Control a specific Data Grid cluster Create a subscription for Data Grid Operator. Note If you want to manually approve updates from the 8.4.x channel, change the value of the spec.installPlanApproval field to Manual . Verify the installation.	[ "infinispan install --channel=8.4.x --source=redhat-operators --source-namespace=openshift-marketplace", "get pods -n openshift-operators \| grep infinispan-operator NAME READY STATUS infinispan-operator-<id> 1/1 Running", "new-project USD{INSTALL_NAMESPACE} 1 new-project USD{WATCH_NAMESPACE} 2", "apply -f - << EOF apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: datagrid namespace: USD{INSTALL_NAMESPACE} EOF", "apply -f - << EOF apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: datagrid namespace: USD{INSTALL_NAMESPACE} spec: targetNamespaces: - USD{WATCH_NAMESPACE} EOF", "apply -f - << EOF apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: datagrid-operator namespace: USD{INSTALL_NAMESPACE} spec: channel: 8.4.x installPlanApproval: Automatic name: datagrid source: redhat-operators sourceNamespace: openshift-marketplace EOF", "get pods -n USD{INSTALL_NAMESPACE} NAME READY STATUS infinispan-operator-<id> 1/1 Running" ]	https://docs.redhat.com/en/documentation/red_hat_data_grid/8.4/html/data_grid_operator_guide/installation
Installing on a single node	Installing on a single node OpenShift Container Platform 4.15 Installing OpenShift Container Platform on a single node Red Hat OpenShift Documentation Team	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.15/html/installing_on_a_single_node/index
Chapter 4. Configuring the instrumentation	Chapter 4. Configuring the instrumentation The Red Hat build of OpenTelemetry Operator uses an Instrumentation custom resource that defines the configuration of the instrumentation. 4.1. Auto-instrumentation in the Red Hat build of OpenTelemetry Operator Auto-instrumentation in the Red Hat build of OpenTelemetry Operator can automatically instrument an application without manual code changes. Developers and administrators can monitor applications with minimal effort and changes to the existing codebase. Auto-instrumentation runs as follows: The Red Hat build of OpenTelemetry Operator injects an init-container, or a sidecar container for Go, to add the instrumentation libraries for the programming language of the instrumented application. The Red Hat build of OpenTelemetry Operator sets the required environment variables in the application's runtime environment. These variables configure the auto-instrumentation libraries to collect traces, metrics, and logs and send them to the appropriate OpenTelemetry Collector or another telemetry backend. The injected libraries automatically instrument your application by connecting to known frameworks and libraries, such as web servers or database clients, to collect telemetry data. The source code of the instrumented application is not modified. Once the application is running with the injected instrumentation, the application automatically generates telemetry data, which is sent to a designated OpenTelemetry Collector or an external OTLP endpoint for further processing. Auto-instrumentation enables you to start collecting telemetry data quickly without having to manually integrate the OpenTelemetry SDK into your application code. However, some applications might require specific configurations or custom manual instrumentation. 4.2. OpenTelemetry instrumentation configuration options The Red Hat build of OpenTelemetry can inject and configure the OpenTelemetry auto-instrumentation libraries into your workloads. Currently, the project supports injection of the instrumentation libraries from Go, Java, Node.js, Python, .NET, and the Apache HTTP Server ( httpd ). Important The Red Hat build of OpenTelemetry Operator only supports the injection mechanism of the instrumentation libraries but does not support instrumentation libraries or upstream images. Customers can build their own instrumentation images or use community images. 4.2.1. Instrumentation options Instrumentation options are specified in an Instrumentation custom resource (CR). Sample Instrumentation CR apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation metadata: name: java-instrumentation spec: env: - name: OTEL_EXPORTER_OTLP_TIMEOUT value: "20" exporter: endpoint: http://production-collector.observability.svc.cluster.local:4317 propagators: - w3c sampler: type: parentbased_traceidratio argument: "0.25" java: env: - name: OTEL_JAVAAGENT_DEBUG value: "true" Table 4.1. Parameters used by the Operator to define the Instrumentation Parameter Description Values env Common environment variables to define across all the instrumentations. exporter Exporter configuration. propagators Propagators defines inter-process context propagation configuration. tracecontext , baggage , b3 , b3multi , jaeger , ottrace , none resource Resource attributes configuration. sampler Sampling configuration. apacheHttpd Configuration for the Apache HTTP Server instrumentation. dotnet Configuration for the .NET instrumentation. go Configuration for the Go instrumentation. java Configuration for the Java instrumentation. nodejs Configuration for the Node.js instrumentation. python Configuration for the Python instrumentation. Table 4.2. Default protocol for auto-instrumentation Auto-instrumentation Default protocol Java 1.x otlp/grpc Java 2.x otlp/http Python otlp/http .NET otlp/http Go otlp/http Apache HTTP Server otlp/grpc 4.2.2. Configuration of the OpenTelemetry SDK variables You can use the instrumentation.opentelemetry.io/inject-sdk annotation in the OpenTelemetry Collector custom resource to instruct the Red Hat build of OpenTelemetry Operator to inject some of the following OpenTelemetry SDK environment variables, depending on the Instrumentation CR, into your pod: OTEL_SERVICE_NAME OTEL_TRACES_SAMPLER OTEL_TRACES_SAMPLER_ARG OTEL_PROPAGATORS OTEL_RESOURCE_ATTRIBUTES OTEL_EXPORTER_OTLP_ENDPOINT OTEL_EXPORTER_OTLP_CERTIFICATE OTEL_EXPORTER_OTLP_CLIENT_CERTIFICATE OTEL_EXPORTER_OTLP_CLIENT_KEY Table 4.3. Values for the instrumentation.opentelemetry.io/inject-sdk annotation Value Description "true" Injects the Instrumentation resource with the default name from the current namespace. "false" Injects no Instrumentation resource. "<instrumentation_name>" Specifies the name of the Instrumentation resource to inject from the current namespace. "<namespace>/<instrumentation_name>" Specifies the name of the Instrumentation resource to inject from another namespace. 4.2.3. Exporter configuration Although the Instrumentation custom resource supports setting up one or more exporters per signal, auto-instrumentation configures only the OTLP Exporter. So you must configure the endpoint to point to the OTLP Receiver on the Collector. Sample exporter TLS CA configuration using a config map apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation # ... spec # ... exporter: endpoint: https://production-collector.observability.svc.cluster.local:4317 1 tls: configMapName: ca-bundle 2 ca_file: service-ca.crt 3 # ... 1 Specifies the OTLP endpoint using the HTTPS scheme and TLS. 2 Specifies the name of the config map. The config map must already exist in the namespace of the pod injecting the auto-instrumentation. 3 Points to the CA certificate in the config map or the absolute path to the certificate if the certificate is already present in the workload file system. Sample exporter mTLS configuration using a Secret apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation # ... spec # ... exporter: endpoint: https://production-collector.observability.svc.cluster.local:4317 1 tls: secretName: serving-certs 2 ca_file: service-ca.crt 3 cert_file: tls.crt 4 key_file: tls.key 5 # ... 1 Specifies the OTLP endpoint using the HTTPS scheme and TLS. 2 Specifies the name of the Secret for the ca_file , cert_file , and key_file values. The Secret must already exist in the namespace of the pod injecting the auto-instrumentation. 3 Points to the CA certificate in the Secret or the absolute path to the certificate if the certificate is already present in the workload file system. 4 Points to the client certificate in the Secret or the absolute path to the certificate if the certificate is already present in the workload file system. 5 Points to the client key in the Secret or the absolute path to a key if the key is already present in the workload file system. Note You can provide the CA certificate in a config map or Secret. If you provide it in both, the config map takes higher precedence than the Secret. Example configuration for CA bundle injection by using a config map and Instrumentation CR apiVersion: v1 kind: ConfigMap metadata: name: otelcol-cabundle namespace: tutorial-application annotations: service.beta.openshift.io/inject-cabundle: "true" # ... --- apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation metadata: name: my-instrumentation spec: exporter: endpoint: https://simplest-collector.tracing-system.svc.cluster.local:4317 tls: configMapName: otelcol-cabundle ca: service-ca.crt # ... 4.2.4. Configuration of the Apache HTTP Server auto-instrumentation Important The Apache HTTP Server auto-instrumentation 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 . Table 4.4. Parameters for the .spec.apacheHttpd field Name Description Default attrs Attributes specific to the Apache HTTP Server. configPath Location of the Apache HTTP Server configuration. /usr/local/apache2/conf env Environment variables specific to the Apache HTTP Server. image Container image with the Apache SDK and auto-instrumentation. resourceRequirements The compute resource requirements. version Apache HTTP Server version. 2.4 The PodSpec annotation to enable injection instrumentation.opentelemetry.io/inject-apache-httpd: "true" 4.2.5. Configuration of the .NET auto-instrumentation Important The .NET auto-instrumentation 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 . Important By default, this feature injects unsupported, upstream instrumentation libraries. Name Description env Environment variables specific to .NET. image Container image with the .NET SDK and auto-instrumentation. resourceRequirements The compute resource requirements. For the .NET auto-instrumentation, the required OTEL_EXPORTER_OTLP_ENDPOINT environment variable must be set if the endpoint of the exporters is set to 4317 . The .NET autoinstrumentation uses http/proto by default, and the telemetry data must be set to the 4318 port. The PodSpec annotation to enable injection instrumentation.opentelemetry.io/inject-dotnet: "true" 4.2.6. Configuration of the Go auto-instrumentation Important The Go auto-instrumentation 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 . Important By default, this feature injects unsupported, upstream instrumentation libraries. Name Description env Environment variables specific to Go. image Container image with the Go SDK and auto-instrumentation. resourceRequirements The compute resource requirements. The PodSpec annotation to enable injection instrumentation.opentelemetry.io/inject-go: "true" Additional permissions required for the Go auto-instrumentation in the OpenShift cluster apiVersion: security.openshift.io/v1 kind: SecurityContextConstraints metadata: name: otel-go-instrumentation-scc allowHostDirVolumePlugin: true allowPrivilegeEscalation: true allowPrivilegedContainer: true allowedCapabilities: - "SYS_PTRACE" fsGroup: type: RunAsAny runAsUser: type: RunAsAny seLinuxContext: type: RunAsAny seccompProfiles: - '*' supplementalGroups: type: RunAsAny Tip The CLI command for applying the permissions for the Go auto-instrumentation in the OpenShift cluster is as follows: USD oc adm policy add-scc-to-user otel-go-instrumentation-scc -z <service_account> 4.2.7. Configuration of the Java auto-instrumentation Important The Java auto-instrumentation 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 . Important By default, this feature injects unsupported, upstream instrumentation libraries. Name Description env Environment variables specific to Java. image Container image with the Java SDK and auto-instrumentation. resourceRequirements The compute resource requirements. The PodSpec annotation to enable injection instrumentation.opentelemetry.io/inject-java: "true" 4.2.8. Configuration of the Node.js auto-instrumentation Important The Node.js auto-instrumentation 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 . Important By default, this feature injects unsupported, upstream instrumentation libraries. Name Description env Environment variables specific to Node.js. image Container image with the Node.js SDK and auto-instrumentation. resourceRequirements The compute resource requirements. The PodSpec annotations to enable injection instrumentation.opentelemetry.io/inject-nodejs: "true" instrumentation.opentelemetry.io/otel-go-auto-target-exe: "/path/to/container/executable" The instrumentation.opentelemetry.io/otel-go-auto-target-exe annotation sets the value for the required OTEL_GO_AUTO_TARGET_EXE environment variable. 4.2.9. Configuration of the Python auto-instrumentation Important The Python auto-instrumentation 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 . Important By default, this feature injects unsupported, upstream instrumentation libraries. Name Description env Environment variables specific to Python. image Container image with the Python SDK and auto-instrumentation. resourceRequirements The compute resource requirements. For Python auto-instrumentation, the OTEL_EXPORTER_OTLP_ENDPOINT environment variable must be set if the endpoint of the exporters is set to 4317 . Python auto-instrumentation uses http/proto by default, and the telemetry data must be set to the 4318 port. The PodSpec annotation to enable injection instrumentation.opentelemetry.io/inject-python: "true" 4.2.10. Multi-container pods The instrumentation is run on the first container that is available by default according to the pod specification. In some cases, you can also specify target containers for injection. Pod annotation instrumentation.opentelemetry.io/container-names: "<container_1>,<container_2>" Note The Go auto-instrumentation does not support multi-container auto-instrumentation injection. 4.2.11. Multi-container pods with multiple instrumentations Injecting instrumentation for an application language to one or more containers in a multi-container pod requires the following annotation: instrumentation.opentelemetry.io/<application_language>-container-names: "<container_1>,<container_2>" 1 1 You can inject instrumentation for only one language per container. For the list of supported <application_language> values, see the following table. Table 4.5. Supported values for the <application_language> Language Value for <application_language> ApacheHTTPD apache DotNet dotnet Java java NGINX inject-nginx NodeJS nodejs Python python SDK sdk 4.2.12. Using the instrumentation CR with Service Mesh When using the instrumentation custom resource (CR) with Red Hat OpenShift Service Mesh, you must use the b3multi propagator.	[ "apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation metadata: name: java-instrumentation spec: env: - name: OTEL_EXPORTER_OTLP_TIMEOUT value: \"20\" exporter: endpoint: http://production-collector.observability.svc.cluster.local:4317 propagators: - w3c sampler: type: parentbased_traceidratio argument: \"0.25\" java: env: - name: OTEL_JAVAAGENT_DEBUG value: \"true\"", "apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation spec exporter: endpoint: https://production-collector.observability.svc.cluster.local:4317 1 tls: configMapName: ca-bundle 2 ca_file: service-ca.crt 3", "apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation spec exporter: endpoint: https://production-collector.observability.svc.cluster.local:4317 1 tls: secretName: serving-certs 2 ca_file: service-ca.crt 3 cert_file: tls.crt 4 key_file: tls.key 5", "apiVersion: v1 kind: ConfigMap metadata: name: otelcol-cabundle namespace: tutorial-application annotations: service.beta.openshift.io/inject-cabundle: \"true\" --- apiVersion: opentelemetry.io/v1alpha1 kind: Instrumentation metadata: name: my-instrumentation spec: exporter: endpoint: https://simplest-collector.tracing-system.svc.cluster.local:4317 tls: configMapName: otelcol-cabundle ca: service-ca.crt", "instrumentation.opentelemetry.io/inject-apache-httpd: \"true\"", "instrumentation.opentelemetry.io/inject-dotnet: \"true\"", "instrumentation.opentelemetry.io/inject-go: \"true\"", "apiVersion: security.openshift.io/v1 kind: SecurityContextConstraints metadata: name: otel-go-instrumentation-scc allowHostDirVolumePlugin: true allowPrivilegeEscalation: true allowPrivilegedContainer: true allowedCapabilities: - \"SYS_PTRACE\" fsGroup: type: RunAsAny runAsUser: type: RunAsAny seLinuxContext: type: RunAsAny seccompProfiles: - '*' supplementalGroups: type: RunAsAny", "oc adm policy add-scc-to-user otel-go-instrumentation-scc -z <service_account>", "instrumentation.opentelemetry.io/inject-java: \"true\"", "instrumentation.opentelemetry.io/inject-nodejs: \"true\" instrumentation.opentelemetry.io/otel-go-auto-target-exe: \"/path/to/container/executable\"", "instrumentation.opentelemetry.io/inject-python: \"true\"", "instrumentation.opentelemetry.io/container-names: \"<container_1>,<container_2>\"", "instrumentation.opentelemetry.io/<application_language>-container-names: \"<container_1>,<container_2>\" 1" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.16/html/red_hat_build_of_opentelemetry/otel-configuration-of-instrumentation
8.79. java-1.6.0-openjdk	8.79. java-1.6.0-openjdk 8.79.1. RHBA-2013:1741 - java-1.6.0-openjdk bug fix and enhancement update Updated java-1.6.0-openjdk packages that fix several bugs and add various enhancements are now available for Red Hat Enterprise Linux 6. The java-1.6.0-openjdk packages provide the OpenJDK 6 Java Runtime Environment and the OpenJDK 6 Java Software Development Kit. Note The java-1.6.0-openjdk packages have been upgraded to upstream IcedTea version 1.13.0, which provides a number of bug fixes and enhancements over the version. (BZ# 983411 ) Bug Fix BZ# 976897 Previously, int[] objects allocated by instances of the com.sun.imageio.plugins.jpeg.JPEGImageWriter class were consuming extensive amounts of memory, which was consequently not released. With this update, the underlying stream processing logic has been modified to ensure correct releasing of such memory, and extensive memory consumption no longer occurs. Users of java-1.6.0-openjdk are advised to upgrade to these updated packages, which fix these bugs and add these enhancements. All running instances of OpenJDK Java must be restarted for the update to take effect.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.5_technical_notes/java-1.6.0-openjdk
7.289. xorg-x11-xkb-utils	7.289. xorg-x11-xkb-utils 7.289.1. RHBA-2013:0305 - xorg-x11-xkb-utils bug fix and enhancement update Updated xorg-x11-xkb-utils packages that fix several bugs and add various enhancements are now available. The x11-xkb-utils packages provide a set of client-side utilities for XKB, the X11 keyboard extension. Note The x11-xkb-utils packages have been upgraded to upstream version 7.7, which provides a number of bug fixes and enhancements over the version. (BZ# 835282 , BZ# 872057 ) All users of x11-xkb-utils are advised to upgrade to these updated packages, which fix these bugs and add these enhancements.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.4_technical_notes/xorg-x11-xkb-utils
Chapter 6. Installing and preparing the Operators	Chapter 6. Installing and preparing the Operators You install the Red Hat OpenStack Services on OpenShift (RHOSO) OpenStack Operator ( openstack-operator ) and create the RHOSO control plane on an operational Red Hat OpenShift Container Platform (RHOCP) cluster. You install the OpenStack Operator by using the RHOCP web console. You perform the control plane installation tasks and all data plane creation tasks on a workstation that has access to the RHOCP cluster. 6.1. Prerequisites An operational RHOCP cluster, version 4.16. For the RHOCP system requirements, see Red Hat OpenShift Container Platform cluster requirements in Planning your deployment . The oc command line tool is installed on your workstation. You are logged in to the RHOCP cluster as a user with cluster-admin privileges. 6.2. Installing the OpenStack Operator You use OperatorHub on the Red Hat OpenShift Container Platform (RHOCP) web console to install the OpenStack Operator ( openstack-operator ) on your RHOCP cluster. Procedure Log in to the RHOCP web console as a user with cluster-admin permissions. Select Operators OperatorHub . In the Filter by keyword field, type OpenStack . Click the OpenStack Operator tile with the Red Hat source label. Read the information about the Operator and click Install . On the Install Operator page, select "Operator recommended Namespace: openstack-operators" from the Installed Namespace list. Click Install to make the Operator available to the openstack-operators namespace. The Operators are deployed and ready when the Status of the OpenStack Operator is Succeeded .	null	https://docs.redhat.com/en/documentation/red_hat_openstack_services_on_openshift/18.0/html/deploying_a_network_functions_virtualization_environment/assembly_installing-and-preparing-the-operators
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
3.0 Release Notes	3.0 Release Notes Red Hat Software Collections 3.0 Release Notes for Red Hat Software Collections 3.0 Lenka Spackova Red Hat Customer Content Services [email protected] Jaromir Hradilek Red Hat Customer Content Services [email protected] Eliska Slobodova Red Hat Customer Content Services	null	https://docs.redhat.com/en/documentation/red_hat_software_collections/3/html/3.0_release_notes/index
Chapter 24. Storage	Chapter 24. Storage e2fsprogs component The e4defrag utility in the e2fsprogs package is not supported in Red Hat Enterprise Linux 7.0, and is scheduled to be removed in Red Hat Enterprise Linux 7.1. xfsprogs component If XFS metadata checksums are enabled specifying the -m crc=1 option to the mkfs.xfs command, the kernel prints the following warning message when the file system is mounted: Note that this CRC functionality is available for testing in Red Hat Enterprise Linux 7.0 and is planned to be fully supported in Red Hat Enterprise Linux 7.1. cryptsetup component, BZ#883941 When the systemd daemon parses the crypttab file in case of a non-LUKS device for swap with a random key, it uses the ripemd160 hash by default, which is not allowed in FIPS mode. To work around this problem, add the hash= setting with an algorithm approved for FIPS to the particular crypttab line. For example: swap /dev/sda7 /dev/urandom swap,hash=sha1 . lvm2 component, BZ# 1083633 If the kernel thin provisioning code detects a device failure or runs out of metadata space, it sets a flag on the device to indicate that it needs to be checked. Currently, LVM tools do not perform this check automatically. To work around this problem, execute the thin_check --clear-needs-check-flag command to perform the check and remove the flag. Then run the thin_repair command if necessary. Alternatively, you can add --clear-needs-check-flag to thin_check_options in the global section of the /etc/lvm.conf configuration file to run the check automatically. device-mapper-multipath component, BZ#1066264 In Red Hat Enterprise Linux 7, the behavior of the kpartx utility has been changed, so it no longer adds the letter p as a delimiter between a device name and a partition suffix unless the device name ends with a digit. When a device is renamed using the multipath utility, the device name is simply replaced by a new name while the suffix stays unchanged, regardless of the delimiter. Consequently, the kpartx behavior is not followed, and changing device names ending in a digit to names ending in a letter, or the other way round, works incorrectly when using multipath to rename devices. To work around this problem, choose one of the following three options: Remove the multipathd daemon and add the devices again; Remove the devices manually by using the kpartx -d command and then add them by running the partx -a command; Rename the devices by using the kpartx -p p command for device names that are supposed to contain the delimiter and they do not, and the kpartx -p "" command in cases when the delimiter is used redundantly. snapper component, BZ# 1071973 The empty-pre-post cleanup algorithm, which is used for deleting pre-post pairs of file system snapshots with empty diffs, does not work in Red Hat Enterprise Linux 7. To work around this problem, remove empty pre-post snapshot couples manually by using the delete command. kernel component, BZ#1084859 The bigalloc feature for the ext4 file systems, which enables ext4 to use clustered allocation, is not supported in Red Hat Enterprise Linux 7. lvm2 component, BZ#1083835 Placing the /boot partition on an LVM volume is not supported. Placing the /boot partition on a Btrfs subvolume is not supported either. nfs-utils component, BZ#1082746 While the rpc.svcgssd binary is included in the nfs-utils package in Red Hat Enterprise Linux 7.0, its use in new deployments is discouraged in favor of gssproxy . The rpc.svcgssd binary may be removed in later Red Hat Enterprise Linux 7 releases. kernel component, BZ#1061871, BZ#1201247 When a storage array returns a CHECK CONDITION status but the sense data is invalid, the Small Computer Systems Interface (SCSI) mid-layer code retries the I/O operation. If subsequent I/O operations receive the same result, I/O operations are retried indefinitely. For this bug, no workaround is currently available.	[ "Version 5 superblock detected. This kernel has EXPERIMENTAL support enabled! Use of these features in this kernel is at your own risk!" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/7.0_release_notes/known-issues-storage
Chapter 7. Configure Network Bonding	Chapter 7. Configure Network Bonding Red Hat Enterprise Linux 7 allows administrators to bind multiple network interfaces together into a single, bonded, channel. Channel bonding enables two or more network interfaces to act as one, simultaneously increasing the bandwidth and providing redundancy. Warning The use of direct cable connections without network switches is not supported for bonding. The failover mechanisms described here will not work as expected without the presence of network switches. See the Red Hat Knowledgebase article Why is bonding in not supported with direct connection using crossover cables? for more information. Note The active-backup, balance-tlb and balance-alb modes do not require any specific configuration of the switch. Other bonding modes require configuring the switch to aggregate the links. For example, a Cisco switch requires EtherChannel for Modes 0, 2, and 3, but for Mode 4 LACP and EtherChannel are required. See the documentation supplied with your switch and see https://www.kernel.org/doc/Documentation/networking/bonding.txt 7.1. Understanding the Default Behavior of Controller and Port Interfaces When controlling bonded port interfaces using the NetworkManager daemon, and especially when fault finding, keep the following in mind: Starting the controller interface does not automatically start the port interfaces. Starting a port interface always starts the controller interface. Stopping the controller interface also stops the port interfaces. A controller without ports can start static IP connections. A controller without ports waits for ports when starting DHCP connections. A controller with a DHCP connection waiting for ports completes when a port with a carrier is added. A controller with a DHCP connection waiting for ports continues waiting when a port without a carrier is added.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/networking_guide/ch-configure_network_bonding
Part I. Viewing and managing your subscription inventory	Part I. Viewing and managing your subscription inventory The Subscription Inventory page on the Red Hat Hybrid Cloud Console provides information and resources to help you manage the account-level subscriptions in your inventory. Specifically, you can view details and status information about each subscription, learn more about subscriptions and how to manage them, and explore purchasing and no-cost trial options. Subscription-level details (name, SKU, quantity, and service level) about each subscription in your inventory are presented in the All subscriptions table. These details, plus the account support type and subscription capacity, are also presented in a list on the subscription details page. The account number is displayed in the table title. The subscription status types (Active, Expired, Expiring soon, and Future dated) and the number of subscriptions in your inventory with each status are displayed in a set of tiles on the Subscription inventory page. There are multiple ways to view and organize the subscription information in the All subscriptions table. You can use the table to sort the subscriptions alphabetically or numerically by name, SKU, quantity, or service level. You can use the tiles to filter your subscriptions by status (active, expired, expiring soon, or future dated). You can use the search bar to filter your subscriptions by name or SKU. Authorized users can use the Subscription Inventory page to manage your subscriptions and interact with your Red Hat account team, as needed, to maintain adequate subscription quantities and types for your account.	null	https://docs.redhat.com/en/documentation/subscription_central/1-latest/html/viewing_and_managing_your_subscription_inventory_on_the_hybrid_cloud_console/assembly-viewing-managing-sub-inventory
Removing OpenShift Serverless	Removing OpenShift Serverless Red Hat OpenShift Serverless 1.35 Removing Serverless from your cluster Red Hat OpenShift Documentation Team	[ "oc delete knativeeventings.operator.knative.dev knative-eventing -n knative-eventing", "oc delete namespace knative-eventing", "oc delete knativeservings.operator.knative.dev knative-serving -n knative-serving", "oc delete namespace knative-serving", "oc get crd -oname \| grep 'knative.dev' \| xargs oc delete" ]	https://docs.redhat.com/en/documentation/red_hat_openshift_serverless/1.35/html-single/removing_openshift_serverless/index
Chapter 9. Server Message Block (SMB)	Chapter 9. Server Message Block (SMB) The Server Message Block (SMB) protocol implements an application-layer network protocol used to access resources on a server, such as file shares and shared printers. On Microsoft Windows, SMB is implemented by default. If you run Red Hat Enterprise Linux, use Samba to provide SMB shares and the cifs-utils utility to mount SMB shares from a remote server. Note In the context of SMB, you sometimes read about the Common Internet File System (CIFS) protocol, which is a dialect of SMB. Both the SMB and CIFS protocol are supported and the kernel module and utilities involved in mounting SMB and CIFS shares both use the name cifs . 9.1. Providing SMB Shares See the Samba section in the Red Hat System Administrator's Guide .	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/storage_administration_guide/ch-server_message_block-smb
Chapter 4. Configuring persistent storage	Chapter 4. Configuring persistent storage 4.1. Persistent storage using AWS Elastic Block Store OpenShift Container Platform supports AWS Elastic Block Store volumes (EBS). You can provision your OpenShift Container Platform cluster with persistent storage by using Amazon EC2 . Some familiarity with Kubernetes and AWS is assumed. The Kubernetes persistent volume framework allows administrators to provision a cluster with persistent storage and gives users a way to request those resources without having any knowledge of the underlying infrastructure. AWS Elastic Block Store volumes can be provisioned dynamically. Persistent volumes are not bound to a single project or namespace; they can be shared across the OpenShift Container Platform cluster. Persistent volume claims are specific to a project or namespace and can be requested by users. Important High-availability of storage in the infrastructure is left to the underlying storage provider. 4.1.1. Additional resources See AWS Elastic Block Store CSI Driver Operator for information about accessing additional storage options, such as volume snapshots, that are not possible with in-tree volume plug-ins. 4.1.2. Creating the EBS storage class Storage classes are used to differentiate and delineate storage levels and usages. By defining a storage class, users can obtain dynamically provisioned persistent volumes. Procedure In the OpenShift Container Platform console, click Storage Storage Classes . In the storage class overview, click Create Storage Class . Define the desired options on the page that appears. Enter a name to reference the storage class. Enter an optional description. Select the reclaim policy. Select kubernetes.io/aws-ebs from the drop-down list. Note To create the storage class with the equivalent CSI driver, select ebs.csi.aws.com from the drop-down list. For more details, see AWS Elastic Block Store CSI Driver Operator . Enter additional parameters for the storage class as desired. Click Create to create the storage class. 4.1.3. Creating the persistent volume claim Prerequisites Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. Procedure In the OpenShift Container Platform console, click Storage Persistent Volume Claims . In the persistent volume claims overview, click Create Persistent Volume Claim . Define the desired options on the page that appears. Select the storage class created previously from the drop-down menu. Enter a unique name for the storage claim. Select the access mode. This determines the read and write access for the created storage claim. Define the size of the storage claim. Click Create to create the persistent volume claim and generate a persistent volume. 4.1.4. Volume format Before OpenShift Container Platform mounts the volume and passes it to a container, it checks that it contains a file system as specified by the fsType parameter in the persistent volume definition. If the device is not formatted with the file system, all data from the device is erased and the device is automatically formatted with the given file system. This allows using unformatted AWS volumes as persistent volumes, because OpenShift Container Platform formats them before the first use. 4.1.5. Maximum number of EBS volumes on a node By default, OpenShift Container Platform supports a maximum of 39 EBS volumes attached to one node. This limit is consistent with the AWS volume limits . The volume limit depends on the instance type. Important As a cluster administrator, you must use either in-tree or Container Storage Interface (CSI) volumes and their respective storage classes, but never both volume types at the same time. The maximum attached EBS volume number is counted separately for in-tree and CSI volumes. 4.1.6. Additional resources See AWS Elastic Block Store CSI Driver Operator for information about accessing additional storage options, such as volume snapshots, that are not possible with in-tree volume plug-ins. 4.2. Persistent storage using Azure OpenShift Container Platform supports Microsoft Azure Disk volumes. You can provision your OpenShift Container Platform cluster with persistent storage using Azure. Some familiarity with Kubernetes and Azure is assumed. The Kubernetes persistent volume framework allows administrators to provision a cluster with persistent storage and gives users a way to request those resources without having any knowledge of the underlying infrastructure. Azure Disk volumes can be provisioned dynamically. Persistent volumes are not bound to a single project or namespace; they can be shared across the OpenShift Container Platform cluster. Persistent volume claims are specific to a project or namespace and can be requested by users. Important High availability of storage in the infrastructure is left to the underlying storage provider. Additional resources Microsoft Azure Disk 4.2.1. Creating the Azure storage class Storage classes are used to differentiate and delineate storage levels and usages. By defining a storage class, users can obtain dynamically provisioned persistent volumes. Procedure In the OpenShift Container Platform console, click Storage Storage Classes . In the storage class overview, click Create Storage Class . Define the desired options on the page that appears. Enter a name to reference the storage class. Enter an optional description. Select the reclaim policy. Select kubernetes.io/azure-disk from the drop down list. Enter the storage account type. This corresponds to your Azure storage account SKU tier. Valid options are Premium_LRS , Standard_LRS , StandardSSD_LRS , and UltraSSD_LRS . Enter the kind of account. Valid options are shared , dedicated, and managed . Important Red Hat only supports the use of kind: Managed in the storage class. With Shared and Dedicated , Azure creates unmanaged disks, while OpenShift Container Platform creates a managed disk for machine OS (root) disks. But because Azure Disk does not allow the use of both managed and unmanaged disks on a node, unmanaged disks created with Shared or Dedicated cannot be attached to OpenShift Container Platform nodes. Enter additional parameters for the storage class as desired. Click Create to create the storage class. Additional resources Azure Disk Storage Class 4.2.2. Creating the persistent volume claim Prerequisites Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. Procedure In the OpenShift Container Platform console, click Storage Persistent Volume Claims . In the persistent volume claims overview, click Create Persistent Volume Claim . Define the desired options on the page that appears. Select the storage class created previously from the drop-down menu. Enter a unique name for the storage claim. Select the access mode. This determines the read and write access for the created storage claim. Define the size of the storage claim. Click Create to create the persistent volume claim and generate a persistent volume. 4.2.3. Volume format Before OpenShift Container Platform mounts the volume and passes it to a container, it checks that it contains a file system as specified by the fsType parameter in the persistent volume definition. If the device is not formatted with the file system, all data from the device is erased and the device is automatically formatted with the given file system. This allows using unformatted Azure volumes as persistent volumes, because OpenShift Container Platform formats them before the first use. 4.3. Persistent storage using Azure File OpenShift Container Platform supports Microsoft Azure File volumes. You can provision your OpenShift Container Platform cluster with persistent storage using Azure. Some familiarity with Kubernetes and Azure is assumed. The Kubernetes persistent volume framework allows administrators to provision a cluster with persistent storage and gives users a way to request those resources without having any knowledge of the underlying infrastructure. You can provision Azure File volumes dynamically. Persistent volumes are not bound to a single project or namespace, and you can share them across the OpenShift Container Platform cluster. Persistent volume claims are specific to a project or namespace, and can be requested by users for use in applications. Important High availability of storage in the infrastructure is left to the underlying storage provider. Important Azure File volumes use Server Message Block. Additional resources Azure Files 4.3.1. Create the Azure File share persistent volume claim To create the persistent volume claim, you must first define a Secret object that contains the Azure account and key. This secret is used in the PersistentVolume definition, and will be referenced by the persistent volume claim for use in applications. Prerequisites An Azure File share exists. The credentials to access this share, specifically the storage account and key, are available. Procedure Create a Secret object that contains the Azure File credentials: USD oc create secret generic <secret-name> --from-literal=azurestorageaccountname=<storage-account> \ 1 --from-literal=azurestorageaccountkey=<storage-account-key> 2 1 The Azure File storage account name. 2 The Azure File storage account key. Create a PersistentVolume object that references the Secret object you created: apiVersion: "v1" kind: "PersistentVolume" metadata: name: "pv0001" 1 spec: capacity: storage: "5Gi" 2 accessModes: - "ReadWriteOnce" storageClassName: azure-file-sc azureFile: secretName: <secret-name> 3 shareName: share-1 4 readOnly: false 1 The name of the persistent volume. 2 The size of this persistent volume. 3 The name of the secret that contains the Azure File share credentials. 4 The name of the Azure File share. Create a PersistentVolumeClaim object that maps to the persistent volume you created: apiVersion: "v1" kind: "PersistentVolumeClaim" metadata: name: "claim1" 1 spec: accessModes: - "ReadWriteOnce" resources: requests: storage: "5Gi" 2 storageClassName: azure-file-sc 3 volumeName: "pv0001" 4 1 The name of the persistent volume claim. 2 The size of this persistent volume claim. 3 The name of the storage class that is used to provision the persistent volume. Specify the storage class used in the PersistentVolume definition. 4 The name of the existing PersistentVolume object that references the Azure File share. 4.3.2. Mount the Azure File share in a pod After the persistent volume claim has been created, it can be used inside by an application. The following example demonstrates mounting this share inside of a pod. Prerequisites A persistent volume claim exists that is mapped to the underlying Azure File share. Procedure Create a pod that mounts the existing persistent volume claim: apiVersion: v1 kind: Pod metadata: name: pod-name 1 spec: containers: ... volumeMounts: - mountPath: "/data" 2 name: azure-file-share volumes: - name: azure-file-share persistentVolumeClaim: claimName: claim1 3 1 The name of the pod. 2 The path to mount the Azure File share inside the pod. Do not mount to the container root, / , or any path that is the same in the host and the container. This can corrupt your host system if the container is sufficiently privileged, such as the host /dev/pts files. It is safe to mount the host by using /host . 3 The name of the PersistentVolumeClaim object that has been previously created. 4.4. Persistent storage using Cinder OpenShift Container Platform supports OpenStack Cinder. Some familiarity with Kubernetes and OpenStack is assumed. Cinder volumes can be provisioned dynamically. Persistent volumes are not bound to a single project or namespace; they can be shared across the OpenShift Container Platform cluster. Persistent volume claims are specific to a project or namespace and can be requested by users. Additional resources For more information about how OpenStack Block Storage provides persistent block storage management for virtual hard drives, see OpenStack Cinder . 4.4.1. Manual provisioning with Cinder Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. Prerequisites OpenShift Container Platform configured for Red Hat OpenStack Platform (RHOSP) Cinder volume ID 4.4.1.1. Creating the persistent volume You must define your persistent volume (PV) in an object definition before creating it in OpenShift Container Platform: Procedure Save your object definition to a file. cinder-persistentvolume.yaml apiVersion: "v1" kind: "PersistentVolume" metadata: name: "pv0001" 1 spec: capacity: storage: "5Gi" 2 accessModes: - "ReadWriteOnce" cinder: 3 fsType: "ext3" 4 volumeID: "f37a03aa-6212-4c62-a805-9ce139fab180" 5 1 The name of the volume that is used by persistent volume claims or pods. 2 The amount of storage allocated to this volume. 3 Indicates cinder for Red Hat OpenStack Platform (RHOSP) Cinder volumes. 4 The file system that is created when the volume is mounted for the first time. 5 The Cinder volume to use. Important Do not change the fstype parameter value after the volume is formatted and provisioned. Changing this value can result in data loss and pod failure. Create the object definition file you saved in the step. USD oc create -f cinder-persistentvolume.yaml 4.4.1.2. Persistent volume formatting You can use unformatted Cinder volumes as PVs because OpenShift Container Platform formats them before the first use. Before OpenShift Container Platform mounts the volume and passes it to a container, the system checks that it contains a file system as specified by the fsType parameter in the PV definition. If the device is not formatted with the file system, all data from the device is erased and the device is automatically formatted with the given file system. 4.4.1.3. Cinder volume security If you use Cinder PVs in your application, configure security for their deployment configurations. Prerequisites An SCC must be created that uses the appropriate fsGroup strategy. Procedure Create a service account and add it to the SCC: USD oc create serviceaccount <service_account> USD oc adm policy add-scc-to-user <new_scc> -z <service_account> -n <project> In your application's deployment configuration, provide the service account name and securityContext : apiVersion: v1 kind: ReplicationController metadata: name: frontend-1 spec: replicas: 1 1 selector: 2 name: frontend template: 3 metadata: labels: 4 name: frontend 5 spec: containers: - image: openshift/hello-openshift name: helloworld ports: - containerPort: 8080 protocol: TCP restartPolicy: Always serviceAccountName: <service_account> 6 securityContext: fsGroup: 7777 7 1 The number of copies of the pod to run. 2 The label selector of the pod to run. 3 A template for the pod that the controller creates. 4 The labels on the pod. They must include labels from the label selector. 5 The maximum name length after expanding any parameters is 63 characters. 6 Specifies the service account you created. 7 Specifies an fsGroup for the pods. 4.5. Persistent storage using Fibre Channel OpenShift Container Platform supports Fibre Channel, allowing you to provision your OpenShift Container Platform cluster with persistent storage using Fibre channel volumes. Some familiarity with Kubernetes and Fibre Channel is assumed. The Kubernetes persistent volume framework allows administrators to provision a cluster with persistent storage and gives users a way to request those resources without having any knowledge of the underlying infrastructure. Persistent volumes are not bound to a single project or namespace; they can be shared across the OpenShift Container Platform cluster. Persistent volume claims are specific to a project or namespace and can be requested by users. Important High availability of storage in the infrastructure is left to the underlying storage provider. Additional resources Using Fibre Channel devices 4.5.1. Provisioning To provision Fibre Channel volumes using the PersistentVolume API the following must be available: The targetWWNs (array of Fibre Channel target's World Wide Names). A valid LUN number. The filesystem type. A persistent volume and a LUN have a one-to-one mapping between them. Prerequisites Fibre Channel LUNs must exist in the underlying infrastructure. PersistentVolume object definition apiVersion: v1 kind: PersistentVolume metadata: name: pv0001 spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce fc: wwids: [scsi-3600508b400105e210000900000490000] 1 targetWWNs: ['500a0981891b8dc5', '500a0981991b8dc5'] 2 lun: 2 3 fsType: ext4 1 World wide identifiers (WWIDs). Either FC wwids or a combination of FC targetWWNs and lun must be set, but not both simultaneously. The FC WWID identifier is recommended over the WWNs target because it is guaranteed to be unique for every storage device, and independent of the path that is used to access the device. The WWID identifier can be obtained by issuing a SCSI Inquiry to retrieve the Device Identification Vital Product Data ( page 0x83 ) or Unit Serial Number ( page 0x80 ). FC WWIDs are identified as /dev/disk/by-id/ to reference the data on the disk, even if the path to the device changes and even when accessing the device from different systems. 2 3 Fibre Channel WWNs are identified as /dev/disk/by-path/pci-<IDENTIFIER>-fc-0x<WWN>-lun-<LUN#> , but you do not need to provide any part of the path leading up to the WWN , including the 0x , and anything after, including the - (hyphen). Important Changing the value of the fstype parameter after the volume has been formatted and provisioned can result in data loss and pod failure. 4.5.1.1. Enforcing disk quotas Use LUN partitions to enforce disk quotas and size constraints. Each LUN is mapped to a single persistent volume, and unique names must be used for persistent volumes. Enforcing quotas in this way allows the end user to request persistent storage by a specific amount, such as 10Gi, and be matched with a corresponding volume of equal or greater capacity. 4.5.1.2. Fibre Channel volume security Users request storage with a persistent volume claim. This claim only lives in the user's namespace, and can only be referenced by a pod within that same namespace. Any attempt to access a persistent volume across a namespace causes the pod to fail. Each Fibre Channel LUN must be accessible by all nodes in the cluster. 4.6. Persistent storage using FlexVolume OpenShift Container Platform supports FlexVolume, an out-of-tree plug-in that uses an executable model to interface with drivers. To use storage from a back-end that does not have a built-in plug-in, you can extend OpenShift Container Platform through FlexVolume drivers and provide persistent storage to applications. Pods interact with FlexVolume drivers through the flexvolume in-tree plugin. Additional resources Expanding persistent volumes 4.6.1. About FlexVolume drivers A FlexVolume driver is an executable file that resides in a well-defined directory on all nodes in the cluster. OpenShift Container Platform calls the FlexVolume driver whenever it needs to mount or unmount a volume represented by a PersistentVolume object with flexVolume as the source. Important Attach and detach operations are not supported in OpenShift Container Platform for FlexVolume. 4.6.2. FlexVolume driver example The first command-line argument of the FlexVolume driver is always an operation name. Other parameters are specific to each operation. Most of the operations take a JavaScript Object Notation (JSON) string as a parameter. This parameter is a complete JSON string, and not the name of a file with the JSON data. The FlexVolume driver contains: All flexVolume.options . Some options from flexVolume prefixed by kubernetes.io/ , such as fsType and readwrite . The content of the referenced secret, if specified, prefixed by kubernetes.io/secret/ . FlexVolume driver JSON input example { "fooServer": "192.168.0.1:1234", 1 "fooVolumeName": "bar", "kubernetes.io/fsType": "ext4", 2 "kubernetes.io/readwrite": "ro", 3 "kubernetes.io/secret/<key name>": "<key value>", 4 "kubernetes.io/secret/<another key name>": "<another key value>", } 1 All options from flexVolume.options . 2 The value of flexVolume.fsType . 3 ro / rw based on flexVolume.readOnly . 4 All keys and their values from the secret referenced by flexVolume.secretRef . OpenShift Container Platform expects JSON data on standard output of the driver. When not specified, the output describes the result of the operation. FlexVolume driver default output example { "status": "<Success/Failure/Not supported>", "message": "<Reason for success/failure>" } Exit code of the driver should be 0 for success and 1 for error. Operations should be idempotent, which means that the mounting of an already mounted volume should result in a successful operation. 4.6.3. Installing FlexVolume drivers FlexVolume drivers that are used to extend OpenShift Container Platform are executed only on the node. To implement FlexVolumes, a list of operations to call and the installation path are all that is required. Prerequisites FlexVolume drivers must implement these operations: init Initializes the driver. It is called during initialization of all nodes. Arguments: none Executed on: node Expected output: default JSON mount Mounts a volume to directory. This can include anything that is necessary to mount the volume, including finding the device and then mounting the device. Arguments: <mount-dir> <json> Executed on: node Expected output: default JSON unmount Unmounts a volume from a directory. This can include anything that is necessary to clean up the volume after unmounting. Arguments: <mount-dir> Executed on: node Expected output: default JSON mountdevice Mounts a volume's device to a directory where individual pods can then bind mount. This call-out does not pass "secrets" specified in the FlexVolume spec. If your driver requires secrets, do not implement this call-out. Arguments: <mount-dir> <json> Executed on: node Expected output: default JSON unmountdevice Unmounts a volume's device from a directory. Arguments: <mount-dir> Executed on: node Expected output: default JSON All other operations should return JSON with {"status": "Not supported"} and exit code 1 . Procedure To install the FlexVolume driver: Ensure that the executable file exists on all nodes in the cluster. Place the executable file at the volume plug-in path: /etc/kubernetes/kubelet-plugins/volume/exec/<vendor>~<driver>/<driver> . For example, to install the FlexVolume driver for the storage foo , place the executable file at: /etc/kubernetes/kubelet-plugins/volume/exec/openshift.com~foo/foo . 4.6.4. Consuming storage using FlexVolume drivers Each PersistentVolume object in OpenShift Container Platform represents one storage asset in the storage back-end, such as a volume. Procedure Use the PersistentVolume object to reference the installed storage. Persistent volume object definition using FlexVolume drivers example apiVersion: v1 kind: PersistentVolume metadata: name: pv0001 1 spec: capacity: storage: 1Gi 2 accessModes: - ReadWriteOnce flexVolume: driver: openshift.com/foo 3 fsType: "ext4" 4 secretRef: foo-secret 5 readOnly: true 6 options: 7 fooServer: 192.168.0.1:1234 fooVolumeName: bar 1 The name of the volume. This is how it is identified through persistent volume claims or from pods. This name can be different from the name of the volume on back-end storage. 2 The amount of storage allocated to this volume. 3 The name of the driver. This field is mandatory. 4 The file system that is present on the volume. This field is optional. 5 The reference to a secret. Keys and values from this secret are provided to the FlexVolume driver on invocation. This field is optional. 6 The read-only flag. This field is optional. 7 The additional options for the FlexVolume driver. In addition to the flags specified by the user in the options field, the following flags are also passed to the executable: Note Secrets are passed only to mount or unmount call-outs. 4.7. Persistent storage using GCE Persistent Disk OpenShift Container Platform supports GCE Persistent Disk volumes (gcePD). You can provision your OpenShift Container Platform cluster with persistent storage using GCE. Some familiarity with Kubernetes and GCE is assumed. The Kubernetes persistent volume framework allows administrators to provision a cluster with persistent storage and gives users a way to request those resources without having any knowledge of the underlying infrastructure. GCE Persistent Disk volumes can be provisioned dynamically. Persistent volumes are not bound to a single project or namespace; they can be shared across the OpenShift Container Platform cluster. Persistent volume claims are specific to a project or namespace and can be requested by users. Important High availability of storage in the infrastructure is left to the underlying storage provider. Additional resources GCE Persistent Disk 4.7.1. Creating the GCE storage class Storage classes are used to differentiate and delineate storage levels and usages. By defining a storage class, users can obtain dynamically provisioned persistent volumes. Procedure In the OpenShift Container Platform console, click Storage Storage Classes . In the storage class overview, click Create Storage Class . Define the desired options on the page that appears. Enter a name to reference the storage class. Enter an optional description. Select the reclaim policy. Select kubernetes.io/gce-pd from the drop-down list. Enter additional parameters for the storage class as desired. Click Create to create the storage class. 4.7.2. Creating the persistent volume claim Prerequisites Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. Procedure In the OpenShift Container Platform console, click Storage Persistent Volume Claims . In the persistent volume claims overview, click Create Persistent Volume Claim . Define the desired options on the page that appears. Select the storage class created previously from the drop-down menu. Enter a unique name for the storage claim. Select the access mode. This determines the read and write access for the created storage claim. Define the size of the storage claim. Click Create to create the persistent volume claim and generate a persistent volume. 4.7.3. Volume format Before OpenShift Container Platform mounts the volume and passes it to a container, it checks that it contains a file system as specified by the fsType parameter in the persistent volume definition. If the device is not formatted with the file system, all data from the device is erased and the device is automatically formatted with the given file system. This allows using unformatted GCE volumes as persistent volumes, because OpenShift Container Platform formats them before the first use. 4.8. Persistent storage using hostPath A hostPath volume in an OpenShift Container Platform cluster mounts a file or directory from the host node's filesystem into your pod. Most pods will not need a hostPath volume, but it does offer a quick option for testing should an application require it. Important The cluster administrator must configure pods to run as privileged. This grants access to pods in the same node. 4.8.1. Overview OpenShift Container Platform supports hostPath mounting for development and testing on a single-node cluster. In a production cluster, you would not use hostPath. Instead, a cluster administrator would provision a network resource, such as a GCE Persistent Disk volume, an NFS share, or an Amazon EBS volume. Network resources support the use of storage classes to set up dynamic provisioning. A hostPath volume must be provisioned statically. Important Do not mount to the container root, / , or any path that is the same in the host and the container. This can corrupt your host system if the container is sufficiently privileged. It is safe to mount the host by using /host . The following example shows the / directory from the host being mounted into the container at /host . apiVersion: v1 kind: Pod metadata: name: test-host-mount spec: containers: - image: registry.access.redhat.com/ubi8/ubi name: test-container command: ['sh', '-c', 'sleep 3600'] volumeMounts: - mountPath: /host name: host-slash volumes: - name: host-slash hostPath: path: / type: '' 4.8.2. Statically provisioning hostPath volumes A pod that uses a hostPath volume must be referenced by manual (static) provisioning. Procedure Define the persistent volume (PV). Create a file, pv.yaml , with the PersistentVolume object definition: apiVersion: v1 kind: PersistentVolume metadata: name: task-pv-volume 1 labels: type: local spec: storageClassName: manual 2 capacity: storage: 5Gi accessModes: - ReadWriteOnce 3 persistentVolumeReclaimPolicy: Retain hostPath: path: "/mnt/data" 4 1 The name of the volume. This name is how it is identified by persistent volume claims or pods. 2 Used to bind persistent volume claim requests to this persistent volume. 3 The volume can be mounted as read-write by a single node. 4 The configuration file specifies that the volume is at /mnt/data on the cluster's node. Do not mount to the container root, / , or any path that is the same in the host and the container. This can corrupt your host system. It is safe to mount the host by using /host . Create the PV from the file: USD oc create -f pv.yaml Define the persistent volume claim (PVC). Create a file, pvc.yaml , with the PersistentVolumeClaim object definition: apiVersion: v1 kind: PersistentVolumeClaim metadata: name: task-pvc-volume spec: accessModes: - ReadWriteOnce resources: requests: storage: 1Gi storageClassName: manual Create the PVC from the file: USD oc create -f pvc.yaml 4.8.3. Mounting the hostPath share in a privileged pod After the persistent volume claim has been created, it can be used inside by an application. The following example demonstrates mounting this share inside of a pod. Prerequisites A persistent volume claim exists that is mapped to the underlying hostPath share. Procedure Create a privileged pod that mounts the existing persistent volume claim: apiVersion: v1 kind: Pod metadata: name: pod-name 1 spec: containers: ... securityContext: privileged: true 2 volumeMounts: - mountPath: /data 3 name: hostpath-privileged ... securityContext: {} volumes: - name: hostpath-privileged persistentVolumeClaim: claimName: task-pvc-volume 4 1 The name of the pod. 2 The pod must run as privileged to access the node's storage. 3 The path to mount the host path share inside the privileged pod. Do not mount to the container root, / , or any path that is the same in the host and the container. This can corrupt your host system if the container is sufficiently privileged, such as the host /dev/pts files. It is safe to mount the host by using /host . 4 The name of the PersistentVolumeClaim object that has been previously created. 4.9. Persistent storage using iSCSI You can provision your OpenShift Container Platform cluster with persistent storage using iSCSI . Some familiarity with Kubernetes and iSCSI is assumed. The Kubernetes persistent volume framework allows administrators to provision a cluster with persistent storage and gives users a way to request those resources without having any knowledge of the underlying infrastructure. Important High-availability of storage in the infrastructure is left to the underlying storage provider. Important When you use iSCSI on Amazon Web Services, you must update the default security policy to include TCP traffic between nodes on the iSCSI ports. By default, they are ports 860 and 3260 . Important Users must ensure that the iSCSI initiator is already configured on all OpenShift Container Platform nodes by installing the iscsi-initiator-utils package and configuring their initiator name in /etc/iscsi/initiatorname.iscsi . The iscsi-initiator-utils package is already installed on deployments that use Red Hat Enterprise Linux CoreOS (RHCOS). For more information, see Managing Storage Devices . 4.9.1. Provisioning Verify that the storage exists in the underlying infrastructure before mounting it as a volume in OpenShift Container Platform. All that is required for the iSCSI is the iSCSI target portal, a valid iSCSI Qualified Name (IQN), a valid LUN number, the filesystem type, and the PersistentVolume API. PersistentVolume object definition apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.16.154.81:3260 iqn: iqn.2014-12.example.server:storage.target00 lun: 0 fsType: 'ext4' 4.9.2. Enforcing disk quotas Use LUN partitions to enforce disk quotas and size constraints. Each LUN is one persistent volume. Kubernetes enforces unique names for persistent volumes. Enforcing quotas in this way allows the end user to request persistent storage by a specific amount (for example, 10Gi ) and be matched with a corresponding volume of equal or greater capacity. 4.9.3. iSCSI volume security Users request storage with a PersistentVolumeClaim object. This claim only lives in the user's namespace and can only be referenced by a pod within that same namespace. Any attempt to access a persistent volume claim across a namespace causes the pod to fail. Each iSCSI LUN must be accessible by all nodes in the cluster. 4.9.3.1. Challenge Handshake Authentication Protocol (CHAP) configuration Optionally, OpenShift can use CHAP to authenticate itself to iSCSI targets: apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.0.0.1:3260 iqn: iqn.2016-04.test.com:storage.target00 lun: 0 fsType: ext4 chapAuthDiscovery: true 1 chapAuthSession: true 2 secretRef: name: chap-secret 3 1 Enable CHAP authentication of iSCSI discovery. 2 Enable CHAP authentication of iSCSI session. 3 Specify name of Secrets object with user name + password. This Secret object must be available in all namespaces that can use the referenced volume. 4.9.4. iSCSI multipathing For iSCSI-based storage, you can configure multiple paths by using the same IQN for more than one target portal IP address. Multipathing ensures access to the persistent volume when one or more of the components in a path fail. To specify multi-paths in the pod specification, use the portals field. For example: apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.0.0.1:3260 portals: ['10.0.2.16:3260', '10.0.2.17:3260', '10.0.2.18:3260'] 1 iqn: iqn.2016-04.test.com:storage.target00 lun: 0 fsType: ext4 readOnly: false 1 Add additional target portals using the portals field. 4.9.5. iSCSI custom initiator IQN Configure the custom initiator iSCSI Qualified Name (IQN) if the iSCSI targets are restricted to certain IQNs, but the nodes that the iSCSI PVs are attached to are not guaranteed to have these IQNs. To specify a custom initiator IQN, use initiatorName field. apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.0.0.1:3260 portals: ['10.0.2.16:3260', '10.0.2.17:3260', '10.0.2.18:3260'] iqn: iqn.2016-04.test.com:storage.target00 lun: 0 initiatorName: iqn.2016-04.test.com:custom.iqn 1 fsType: ext4 readOnly: false 1 Specify the name of the initiator. 4.10. Persistent storage using local volumes OpenShift Container Platform can be provisioned with persistent storage by using local volumes. Local persistent volumes allow you to access local storage devices, such as a disk or partition, by using the standard persistent volume claim interface. Local volumes can be used without manually scheduling pods to nodes because the system is aware of the volume node constraints. However, local volumes are still subject to the availability of the underlying node and are not suitable for all applications. Note Local volumes can only be used as a statically created persistent volume. 4.10.1. Installing the Local Storage Operator The Local Storage Operator is not installed in OpenShift Container Platform by default. Use the following procedure to install and configure this Operator to enable local volumes in your cluster. Prerequisites Access to the OpenShift Container Platform web console or command-line interface (CLI). Procedure Create the openshift-local-storage project: USD oc adm new-project openshift-local-storage Optional: Allow local storage creation on infrastructure nodes. You might want to use the Local Storage Operator to create volumes on infrastructure nodes in support of components such as logging and monitoring. You must adjust the default node selector so that the Local Storage Operator includes the infrastructure nodes, and not just worker nodes. To block the Local Storage Operator from inheriting the cluster-wide default selector, enter the following command: USD oc annotate project openshift-local-storage openshift.io/node-selector='' From the UI To install the Local Storage Operator from the web console, follow these steps: Log in to the OpenShift Container Platform web console. Navigate to Operators OperatorHub . Type Local Storage into the filter box to locate the Local Storage Operator. Click Install . On the Install Operator page, select A specific namespace on the cluster . Select openshift-local-storage from the drop-down menu. Adjust the values for Update Channel and Approval Strategy to the values that you want. Click Install . Once finished, the Local Storage Operator will be listed in the Installed Operators section of the web console. From the CLI Install the Local Storage Operator from the CLI. Run the following command to get the OpenShift Container Platform major and minor version. It is required for the channel value in the step. USD OC_VERSION=USD(oc version -o yaml \| grep openshiftVersion \| \ grep -o '[0-9][.][0-9]' \| head -1) Create an object YAML file to define an Operator group and subscription for the Local Storage Operator, such as openshift-local-storage.yaml : Example openshift-local-storage.yaml apiVersion: operators.coreos.com/v1alpha2 kind: OperatorGroup metadata: name: local-operator-group namespace: openshift-local-storage spec: targetNamespaces: - openshift-local-storage --- apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: local-storage-operator namespace: openshift-local-storage spec: channel: "USD{OC_VERSION}" installPlanApproval: Automatic 1 name: local-storage-operator source: redhat-operators sourceNamespace: openshift-marketplace 1 The user approval policy for an install plan. Create the Local Storage Operator object by entering the following command: USD oc apply -f openshift-local-storage.yaml At this point, the Operator Lifecycle Manager (OLM) is now aware of the Local Storage Operator. A ClusterServiceVersion (CSV) for the Operator should appear in the target namespace, and APIs provided by the Operator should be available for creation. Verify local storage installation by checking that all pods and the Local Storage Operator have been created: Check that all the required pods have been created: USD oc -n openshift-local-storage get pods Example output NAME READY STATUS RESTARTS AGE local-storage-operator-746bf599c9-vlt5t 1/1 Running 0 19m Check the ClusterServiceVersion (CSV) YAML manifest to see that the Local Storage Operator is available in the openshift-local-storage project: USD oc get csvs -n openshift-local-storage Example output NAME DISPLAY VERSION REPLACES PHASE local-storage-operator.4.2.26-202003230335 Local Storage 4.2.26-202003230335 Succeeded After all checks have passed, the Local Storage Operator is installed successfully. 4.10.2. Provisioning local volumes by using the Local Storage Operator Local volumes cannot be created by dynamic provisioning. Instead, persistent volumes can be created by the Local Storage Operator. The local volume provisioner looks for any file system or block volume devices at the paths specified in the defined resource. Prerequisites The Local Storage Operator is installed. You have a local disk that meets the following conditions: It is attached to a node. It is not mounted. It does not contain partitions. Procedure Create the local volume resource. This resource must define the nodes and paths to the local volumes. Note Do not use different storage class names for the same device. Doing so will create multiple persistent volumes (PVs). Example: Filesystem apiVersion: "local.storage.openshift.io/v1" kind: "LocalVolume" metadata: name: "local-disks" namespace: "openshift-local-storage" 1 spec: nodeSelector: 2 nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-140-183 - ip-10-0-158-139 - ip-10-0-164-33 storageClassDevices: - storageClassName: "local-sc" 3 volumeMode: Filesystem 4 fsType: xfs 5 devicePaths: 6 - /path/to/device 7 1 The namespace where the Local Storage Operator is installed. 2 Optional: A node selector containing a list of nodes where the local storage volumes are attached. This example uses the node hostnames, obtained from oc get node . If a value is not defined, then the Local Storage Operator will attempt to find matching disks on all available nodes. 3 The name of the storage class to use when creating persistent volume objects. The Local Storage Operator automatically creates the storage class if it does not exist. Be sure to use a storage class that uniquely identifies this set of local volumes. 4 The volume mode, either Filesystem or Block , that defines the type of local volumes. 5 The file system that is created when the local volume is mounted for the first time. 6 The path containing a list of local storage devices to choose from. 7 Replace this value with your actual local disks filepath to the LocalVolume resource by-id , such as /dev/disk/by-id/wwn . PVs are created for these local disks when the provisioner is deployed successfully. Note A raw block volume ( volumeMode: block ) is not formatted with a file system. You should use this mode only if any application running on the pod can use raw block devices. Example: Block apiVersion: "local.storage.openshift.io/v1" kind: "LocalVolume" metadata: name: "local-disks" namespace: "openshift-local-storage" 1 spec: nodeSelector: 2 nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-136-143 - ip-10-0-140-255 - ip-10-0-144-180 storageClassDevices: - storageClassName: "localblock-sc" 3 volumeMode: Block 4 devicePaths: 5 - /path/to/device 6 1 The namespace where the Local Storage Operator is installed. 2 Optional: A node selector containing a list of nodes where the local storage volumes are attached. This example uses the node hostnames, obtained from oc get node . If a value is not defined, then the Local Storage Operator will attempt to find matching disks on all available nodes. 3 The name of the storage class to use when creating persistent volume objects. 4 The volume mode, either Filesystem or Block , that defines the type of local volumes. 5 The path containing a list of local storage devices to choose from. 6 Replace this value with your actual local disks filepath to the LocalVolume resource by-id , such as dev/disk/by-id/wwn . PVs are created for these local disks when the provisioner is deployed successfully. Create the local volume resource in your OpenShift Container Platform cluster. Specify the file you just created: USD oc create -f <local-volume>.yaml Verify that the provisioner was created and that the corresponding daemon sets were created: USD oc get all -n openshift-local-storage Example output NAME READY STATUS RESTARTS AGE pod/local-disks-local-provisioner-h97hj 1/1 Running 0 46m pod/local-disks-local-provisioner-j4mnn 1/1 Running 0 46m pod/local-disks-local-provisioner-kbdnx 1/1 Running 0 46m pod/local-disks-local-diskmaker-ldldw 1/1 Running 0 46m pod/local-disks-local-diskmaker-lvrv4 1/1 Running 0 46m pod/local-disks-local-diskmaker-phxdq 1/1 Running 0 46m pod/local-storage-operator-54564d9988-vxvhx 1/1 Running 0 47m NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/local-storage-operator ClusterIP 172.30.49.90 <none> 60000/TCP 47m NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE daemonset.apps/local-disks-local-provisioner 3 3 3 3 3 <none> 46m daemonset.apps/local-disks-local-diskmaker 3 3 3 3 3 <none> 46m NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/local-storage-operator 1/1 1 1 47m NAME DESIRED CURRENT READY AGE replicaset.apps/local-storage-operator-54564d9988 1 1 1 47m Note the desired and current number of daemon set processes. A desired count of 0 indicates that the label selectors were invalid. Verify that the persistent volumes were created: USD oc get pv Example output NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE local-pv-1cec77cf 100Gi RWO Delete Available local-sc 88m local-pv-2ef7cd2a 100Gi RWO Delete Available local-sc 82m local-pv-3fa1c73 100Gi RWO Delete Available local-sc 48m Important Editing the LocalVolume object does not change the fsType or volumeMode of existing persistent volumes because doing so might result in a destructive operation. 4.10.3. Provisioning local volumes without the Local Storage Operator Local volumes cannot be created by dynamic provisioning. Instead, persistent volumes can be created by defining the persistent volume (PV) in an object definition. The local volume provisioner looks for any file system or block volume devices at the paths specified in the defined resource. Important Manual provisioning of PVs includes the risk of potential data leaks across PV reuse when PVCs are deleted. The Local Storage Operator is recommended for automating the life cycle of devices when provisioning local PVs. Prerequisites Local disks are attached to the OpenShift Container Platform nodes. Procedure Define the PV. Create a file, such as example-pv-filesystem.yaml or example-pv-block.yaml , with the PersistentVolume object definition. This resource must define the nodes and paths to the local volumes. Note Do not use different storage class names for the same device. Doing so will create multiple PVs. example-pv-filesystem.yaml apiVersion: v1 kind: PersistentVolume metadata: name: example-pv-filesystem spec: capacity: storage: 100Gi volumeMode: Filesystem 1 accessModes: - ReadWriteOnce persistentVolumeReclaimPolicy: Delete storageClassName: local-storage 2 local: path: /dev/xvdf 3 nodeAffinity: required: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - example-node 1 The volume mode, either Filesystem or Block , that defines the type of PVs. 2 The name of the storage class to use when creating PV resources. Use a storage class that uniquely identifies this set of PVs. 3 The path containing a list of local storage devices to choose from. Note A raw block volume ( volumeMode: block ) is not formatted with a file system. Use this mode only if any application running on the pod can use raw block devices. example-pv-block.yaml apiVersion: v1 kind: PersistentVolume metadata: name: example-pv-block spec: capacity: storage: 100Gi volumeMode: Block 1 accessModes: - ReadWriteOnce persistentVolumeReclaimPolicy: Delete storageClassName: local-storage 2 local: path: /dev/xvdf 3 nodeAffinity: required: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - example-node 1 The volume mode, either Filesystem or Block , that defines the type of PVs. 2 The name of the storage class to use when creating PV resources. Be sure to use a storage class that uniquely identifies this set of PVs. 3 The path containing a list of local storage devices to choose from. Create the PV resource in your OpenShift Container Platform cluster. Specify the file you just created: USD oc create -f <example-pv>.yaml Verify that the local PV was created: USD oc get pv Example output NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE example-pv-filesystem 100Gi RWO Delete Available local-storage 3m47s example-pv1 1Gi RWO Delete Bound local-storage/pvc1 local-storage 12h example-pv2 1Gi RWO Delete Bound local-storage/pvc2 local-storage 12h example-pv3 1Gi RWO Delete Bound local-storage/pvc3 local-storage 12h 4.10.4. Creating the local volume persistent volume claim Local volumes must be statically created as a persistent volume claim (PVC) to be accessed by the pod. Prerequisites Persistent volumes have been created using the local volume provisioner. Procedure Create the PVC using the corresponding storage class: kind: PersistentVolumeClaim apiVersion: v1 metadata: name: local-pvc-name 1 spec: accessModes: - ReadWriteOnce volumeMode: Filesystem 2 resources: requests: storage: 100Gi 3 storageClassName: local-sc 4 1 Name of the PVC. 2 The type of the PVC. Defaults to Filesystem . 3 The amount of storage available to the PVC. 4 Name of the storage class required by the claim. Create the PVC in the OpenShift Container Platform cluster, specifying the file you just created: USD oc create -f <local-pvc>.yaml 4.10.5. Attach the local claim After a local volume has been mapped to a persistent volume claim it can be specified inside of a resource. Prerequisites A persistent volume claim exists in the same namespace. Procedure Include the defined claim in the resource spec. The following example declares the persistent volume claim inside a pod: apiVersion: v1 kind: Pod spec: ... containers: volumeMounts: - name: local-disks 1 mountPath: /data 2 volumes: - name: localpvc persistentVolumeClaim: claimName: local-pvc-name 3 1 The name of the volume to mount. 2 The path inside the pod where the volume is mounted. Do not mount to the container root, / , or any path that is the same in the host and the container. This can corrupt your host system if the container is sufficiently privileged, such as the host /dev/pts files. It is safe to mount the host by using /host . 3 The name of the existing persistent volume claim to use. Create the resource in the OpenShift Container Platform cluster, specifying the file you just created: USD oc create -f <local-pod>.yaml 4.10.6. Automating discovery and provisioning for local storage devices The Local Storage Operator automates local storage discovery and provisioning. With this feature, you can simplify installation when dynamic provisioning is not available during deployment, such as with bare metal, VMware, or AWS store instances with attached devices. Important Automatic discovery and provisioning 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 https://access.redhat.com/support/offerings/techpreview/ . Use the following procedure to automatically discover local devices, and to automatically provision local volumes for selected devices. Warning Use the LocalVolumeSet object with caution. When you automatically provision persistent volumes (PVs) from local disks, the local PVs might claim all devices that match. If you are using a LocalVolumeSet object, make sure the Local Storage Operator is the only entity managing local devices on the node. Prerequisites You have cluster administrator permissions. You have installed the Local Storage Operator. You have attached local disks to OpenShift Container Platform nodes. You have access to the OpenShift Container Platform web console and the oc command-line interface (CLI). Procedure To enable automatic discovery of local devices from the web console: In the Administrator perspective, navigate to Operators Installed Operators and click on the Local Volume Discovery tab. Click Create Local Volume Discovery . Select either All nodes or Select nodes , depending on whether you want to discover available disks on all or specific nodes. Note Only worker nodes are available, regardless of whether you filter using All nodes or Select nodes . Click Create . A local volume discovery instance named auto-discover-devices is displayed. To display a continuous list of available devices on a node: Log in to the OpenShift Container Platform web console. Navigate to Compute Nodes . Click the node name that you want to open. The "Node Details" page is displayed. Select the Disks tab to display the list of the selected devices. The device list updates continuously as local disks are added or removed. You can filter the devices by name, status, type, model, capacity, and mode. To automatically provision local volumes for the discovered devices from the web console: Navigate to Operators Installed Operators and select Local Storage from the list of Operators. Select Local Volume Set Create Local Volume Set . Enter a volume set name and a storage class name. Choose All nodes or Select nodes to apply filters accordingly. Note Only worker nodes are available, regardless of whether you filter using All nodes or Select nodes . Select the disk type, mode, size, and limit you want to apply to the local volume set, and click Create . A message displays after several minutes, indicating that the "Operator reconciled successfully." Alternatively, to provision local volumes for the discovered devices from the CLI: Create an object YAML file to define the local volume set, such as local-volume-set.yaml , as shown in the following example: apiVersion: local.storage.openshift.io/v1alpha1 kind: LocalVolumeSet metadata: name: example-autodetect spec: nodeSelector: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - worker-0 - worker-1 storageClassName: example-storageclass 1 volumeMode: Filesystem fsType: ext4 maxDeviceCount: 10 deviceInclusionSpec: deviceTypes: 2 - disk - part deviceMechanicalProperties: - NonRotational minSize: 10G maxSize: 100G models: - SAMSUNG - Crucial_CT525MX3 vendors: - ATA - ST2000LM 1 Determines the storage class that is created for persistent volumes that are provisioned from discovered devices. The Local Storage Operator automatically creates the storage class if it does not exist. Be sure to use a storage class that uniquely identifies this set of local volumes. 2 When using the local volume set feature, the Local Storage Operator does not support the use of logical volume management (LVM) devices. Create the local volume set object: USD oc apply -f local-volume-set.yaml Verify that the local persistent volumes were dynamically provisioned based on the storage class: USD oc get pv Example output NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE local-pv-1cec77cf 100Gi RWO Delete Available example-storageclass 88m local-pv-2ef7cd2a 100Gi RWO Delete Available example-storageclass 82m local-pv-3fa1c73 100Gi RWO Delete Available example-storageclass 48m Note Results are deleted after they are removed from the node. Symlinks must be manually removed. 4.10.7. Using tolerations with Local Storage Operator pods Taints can be applied to nodes to prevent them from running general workloads. To allow the Local Storage Operator to use tainted nodes, you must add tolerations to the Pod or DaemonSet definition. This allows the created resources to run on these tainted nodes. You apply tolerations to the Local Storage Operator pod through the LocalVolume resource and apply taints to a node through the node specification. A taint on a node instructs the node to repel all pods that do not tolerate the taint. Using a specific taint that is not on other pods ensures that the Local Storage Operator pod can also run on that node. Important Taints and tolerations consist of a key, value, and effect. As an argument, it is expressed as key=value:effect . An operator allows you to leave one of these parameters empty. Prerequisites The Local Storage Operator is installed. Local disks are attached to OpenShift Container Platform nodes with a taint. Tainted nodes are expected to provision local storage. Procedure To configure local volumes for scheduling on tainted nodes: Modify the YAML file that defines the Pod and add the LocalVolume spec, as shown in the following example: apiVersion: "local.storage.openshift.io/v1" kind: "LocalVolume" metadata: name: "local-disks" namespace: "openshift-local-storage" spec: tolerations: - key: localstorage 1 operator: Equal 2 value: "localstorage" 3 storageClassDevices: - storageClassName: "localblock-sc" volumeMode: Block 4 devicePaths: 5 - /dev/xvdg 1 Specify the key that you added to the node. 2 Specify the Equal operator to require the key / value parameters to match. If operator is Exists , the system checks that the key exists and ignores the value. If operator is Equal , then the key and value must match. 3 Specify the value local of the tainted node. 4 The volume mode, either Filesystem or Block , defining the type of the local volumes. 5 The path containing a list of local storage devices to choose from. Optional: To create local persistent volumes on only tainted nodes, modify the YAML file and add the LocalVolume spec, as shown in the following example: spec: tolerations: - key: node-role.kubernetes.io/master operator: Exists The defined tolerations will be passed to the resulting daemon sets, allowing the diskmaker and provisioner pods to be created for nodes that contain the specified taints. 4.10.8. Deleting the Local Storage Operator resources 4.10.8.1. Removing a local volume or local volume set Occasionally, local volumes and local volume sets must be deleted. While removing the entry in the resource and deleting the persistent volume is typically enough, if you want to reuse the same device path or have it managed by a different storage class, then additional steps are needed. Note The following procedure outlines an example for removing a local volume. The same procedure can also be used to remove symlinks for a local volume set custom resource. Prerequisites The persistent volume must be in a Released or Available state. Warning Deleting a persistent volume that is still in use can result in data loss or corruption. Procedure Edit the previously created local volume to remove any unwanted disks. Edit the cluster resource: USD oc edit localvolume <name> -n openshift-local-storage Navigate to the lines under devicePaths , and delete any representing unwanted disks. Delete any persistent volumes created. USD oc delete pv <pv-name> Delete any symlinks on the node. Warning The following step involves accessing a node as the root user. Modifying the state of the node beyond the steps in this procedure could result in cluster instability. Create a debug pod on the node: USD oc debug node/<node-name> Change your root directory to the host: USD chroot /host Navigate to the directory containing the local volume symlinks. USD cd /mnt/openshift-local-storage/<sc-name> 1 1 The name of the storage class used to create the local volumes. Delete the symlink belonging to the removed device. USD rm <symlink> 4.10.8.2. Uninstalling the Local Storage Operator To uninstall the Local Storage Operator, you must remove the Operator and all created resources in the openshift-local-storage project. Warning Uninstalling the Local Storage Operator while local storage PVs are still in use is not recommended. While the PVs will remain after the Operator's removal, there might be indeterminate behavior if the Operator is uninstalled and reinstalled without removing the PVs and local storage resources. Prerequisites Access to the OpenShift Container Platform web console. Procedure Delete any local volume resources installed in the project, such as localvolume , localvolumeset , and localvolumediscovery : USD oc delete localvolume --all --all-namespaces USD oc delete localvolumeset --all --all-namespaces USD oc delete localvolumediscovery --all --all-namespaces Uninstall the Local Storage Operator from the web console. Log in to the OpenShift Container Platform web console. Navigate to Operators Installed Operators . Type Local Storage into the filter box to locate the Local Storage Operator. Click the Options menu at the end of the Local Storage Operator. Click Uninstall Operator . Click Remove in the window that appears. The PVs created by the Local Storage Operator will remain in the cluster until deleted. Once these volumes are no longer in use, delete them by running the following command: USD oc delete pv <pv-name> Delete the openshift-local-storage project: USD oc delete project openshift-local-storage 4.11. Persistent storage using NFS OpenShift Container Platform clusters can be provisioned with persistent storage using NFS. Persistent volumes (PVs) and persistent volume claims (PVCs) provide a convenient method for sharing a volume across a project. While the NFS-specific information contained in a PV definition could also be defined directly in a Pod definition, doing so does not create the volume as a distinct cluster resource, making the volume more susceptible to conflicts. Additional resources Network File System (NFS) 4.11.1. Provisioning Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. To provision NFS volumes, a list of NFS servers and export paths are all that is required. Procedure Create an object definition for the PV: apiVersion: v1 kind: PersistentVolume metadata: name: pv0001 1 spec: capacity: storage: 5Gi 2 accessModes: - ReadWriteOnce 3 nfs: 4 path: /tmp 5 server: 172.17.0.2 6 persistentVolumeReclaimPolicy: Retain 7 1 The name of the volume. This is the PV identity in various oc <command> pod commands. 2 The amount of storage allocated to this volume. 3 Though this appears to be related to controlling access to the volume, it is actually used similarly to labels and used to match a PVC to a PV. Currently, no access rules are enforced based on the accessModes . 4 The volume type being used, in this case the nfs plug-in. 5 The path that is exported by the NFS server. 6 The hostname or IP address of the NFS server. 7 The reclaim policy for the PV. This defines what happens to a volume when released. Note Each NFS volume must be mountable by all schedulable nodes in the cluster. Verify that the PV was created: USD oc get pv Example output NAME LABELS CAPACITY ACCESSMODES STATUS CLAIM REASON AGE pv0001 <none> 5Gi RWO Available 31s Create a persistent volume claim that binds to the new PV: apiVersion: v1 kind: PersistentVolumeClaim metadata: name: nfs-claim1 spec: accessModes: - ReadWriteOnce 1 resources: requests: storage: 5Gi 2 volumeName: pv0001 storageClassName: "" 1 The access modes do not enforce security, but rather act as labels to match a PV to a PVC. 2 This claim looks for PVs offering 5Gi or greater capacity. Verify that the persistent volume claim was created: USD oc get pvc Example output NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE nfs-claim1 Bound pv0001 5Gi RWO 2m 4.11.2. Enforcing disk quotas You can use disk partitions to enforce disk quotas and size constraints. Each partition can be its own export. Each export is one PV. OpenShift Container Platform enforces unique names for PVs, but the uniqueness of the NFS volume's server and path is up to the administrator. Enforcing quotas in this way allows the developer to request persistent storage by a specific amount, such as 10Gi, and be matched with a corresponding volume of equal or greater capacity. 4.11.3. NFS volume security This section covers NFS volume security, including matching permissions and SELinux considerations. The user is expected to understand the basics of POSIX permissions, process UIDs, supplemental groups, and SELinux. Developers request NFS storage by referencing either a PVC by name or the NFS volume plug-in directly in the volumes section of their Pod definition. The /etc/exports file on the NFS server contains the accessible NFS directories. The target NFS directory has POSIX owner and group IDs. The OpenShift Container Platform NFS plug-in mounts the container's NFS directory with the same POSIX ownership and permissions found on the exported NFS directory. However, the container is not run with its effective UID equal to the owner of the NFS mount, which is the desired behavior. As an example, if the target NFS directory appears on the NFS server as: USD ls -lZ /opt/nfs -d Example output drwxrws---. nfsnobody 5555 unconfined_u:object_r:usr_t:s0 /opt/nfs USD id nfsnobody Example output uid=65534(nfsnobody) gid=65534(nfsnobody) groups=65534(nfsnobody) Then the container must match SELinux labels, and either run with a UID of 65534 , the nfsnobody owner, or with 5555 in its supplemental groups to access the directory. Note The owner ID of 65534 is used as an example. Even though NFS's root_squash maps root , uid 0 , to nfsnobody , uid 65534 , NFS exports can have arbitrary owner IDs. Owner 65534 is not required for NFS exports. 4.11.3.1. Group IDs The recommended way to handle NFS access, assuming it is not an option to change permissions on the NFS export, is to use supplemental groups. Supplemental groups in OpenShift Container Platform are used for shared storage, of which NFS is an example. In contrast, block storage such as iSCSI uses the fsGroup SCC strategy and the fsGroup value in the securityContext of the pod. Note To gain access to persistent storage, it is generally preferable to use supplemental group IDs versus user IDs. Because the group ID on the example target NFS directory is 5555 , the pod can define that group ID using supplementalGroups under the securityContext definition of the pod. For example: spec: containers: - name: ... securityContext: 1 supplementalGroups: [5555] 2 1 securityContext must be defined at the pod level, not under a specific container. 2 An array of GIDs defined for the pod. In this case, there is one element in the array. Additional GIDs would be comma-separated. Assuming there are no custom SCCs that might satisfy the pod requirements, the pod likely matches the restricted SCC. This SCC has the supplementalGroups strategy set to RunAsAny , meaning that any supplied group ID is accepted without range checking. As a result, the above pod passes admissions and is launched. However, if group ID range checking is desired, a custom SCC is the preferred solution. A custom SCC can be created such that minimum and maximum group IDs are defined, group ID range checking is enforced, and a group ID of 5555 is allowed. Note To use a custom SCC, you must first add it to the appropriate service account. For example, use the default service account in the given project unless another has been specified on the Pod specification. 4.11.3.2. User IDs User IDs can be defined in the container image or in the Pod definition. Note It is generally preferable to use supplemental group IDs to gain access to persistent storage versus using user IDs. In the example target NFS directory shown above, the container needs its UID set to 65534 , ignoring group IDs for the moment, so the following can be added to the Pod definition: spec: containers: 1 - name: ... securityContext: runAsUser: 65534 2 1 Pods contain a securityContext definition specific to each container and a pod's securityContext which applies to all containers defined in the pod. 2 65534 is the nfsnobody user. Assuming that the project is default and the SCC is restricted , the user ID of 65534 as requested by the pod is not allowed. Therefore, the pod fails for the following reasons: It requests 65534 as its user ID. All SCCs available to the pod are examined to see which SCC allows a user ID of 65534 . While all policies of the SCCs are checked, the focus here is on user ID. Because all available SCCs use MustRunAsRange for their runAsUser strategy, UID range checking is required. 65534 is not included in the SCC or project's user ID range. It is generally considered a good practice not to modify the predefined SCCs. The preferred way to fix this situation is to create a custom SCC A custom SCC can be created such that minimum and maximum user IDs are defined, UID range checking is still enforced, and the UID of 65534 is allowed. Note To use a custom SCC, you must first add it to the appropriate service account. For example, use the default service account in the given project unless another has been specified on the Pod specification. 4.11.3.3. SELinux Red Hat Enterprise Linux (RHEL) and Red Hat Enterprise Linux CoreOS (RHCOS) systems are configured to use SELinux on remote NFS servers by default. For non-RHEL and non-RHCOS systems, SELinux does not allow writing from a pod to a remote NFS server. The NFS volume mounts correctly but it is read-only. You will need to enable the correct SELinux permissions by using the following procedure. Prerequisites The container-selinux package must be installed. This package provides the virt_use_nfs SELinux boolean. Procedure Enable the virt_use_nfs boolean using the following command. The -P option makes this boolean persistent across reboots. # setsebool -P virt_use_nfs 1 4.11.3.4. Export settings To enable arbitrary container users to read and write the volume, each exported volume on the NFS server should conform to the following conditions: Every export must be exported using the following format: /<example_fs> *(rw,root_squash) The firewall must be configured to allow traffic to the mount point. For NFSv4, configure the default port 2049 ( nfs ). NFSv4 # iptables -I INPUT 1 -p tcp --dport 2049 -j ACCEPT For NFSv3, there are three ports to configure: 2049 ( nfs ), 20048 ( mountd ), and 111 ( portmapper ). NFSv3 # iptables -I INPUT 1 -p tcp --dport 2049 -j ACCEPT # iptables -I INPUT 1 -p tcp --dport 20048 -j ACCEPT # iptables -I INPUT 1 -p tcp --dport 111 -j ACCEPT The NFS export and directory must be set up so that they are accessible by the target pods. Either set the export to be owned by the container's primary UID, or supply the pod group access using supplementalGroups , as shown in the group IDs above. 4.11.4. Reclaiming resources NFS implements the OpenShift Container Platform Recyclable plug-in interface. Automatic processes handle reclamation tasks based on policies set on each persistent volume. By default, PVs are set to Retain . Once claim to a PVC is deleted, and the PV is released, the PV object should not be reused. Instead, a new PV should be created with the same basic volume details as the original. For example, the administrator creates a PV named nfs1 : apiVersion: v1 kind: PersistentVolume metadata: name: nfs1 spec: capacity: storage: 1Mi accessModes: - ReadWriteMany nfs: server: 192.168.1.1 path: "/" The user creates PVC1 , which binds to nfs1 . The user then deletes PVC1 , releasing claim to nfs1 . This results in nfs1 being Released . If the administrator wants to make the same NFS share available, they should create a new PV with the same NFS server details, but a different PV name: apiVersion: v1 kind: PersistentVolume metadata: name: nfs2 spec: capacity: storage: 1Mi accessModes: - ReadWriteMany nfs: server: 192.168.1.1 path: "/" Deleting the original PV and re-creating it with the same name is discouraged. Attempting to manually change the status of a PV from Released to Available causes errors and potential data loss. 4.11.5. Additional configuration and troubleshooting Depending on what version of NFS is being used and how it is configured, there may be additional configuration steps needed for proper export and security mapping. The following are some that may apply: NFSv4 mount incorrectly shows all files with ownership of nobody:nobody Could be attributed to the ID mapping settings, found in /etc/idmapd.conf on your NFS. See this Red Hat Solution . Disabling ID mapping on NFSv4 On both the NFS client and server, run: # echo 'Y' > /sys/module/nfsd/parameters/nfs4_disable_idmapping 4.12. Red Hat OpenShift Container Storage Red Hat OpenShift Container Storage is a provider of agnostic persistent storage for OpenShift Container Platform supporting file, block, and object storage, either in-house or in hybrid clouds. As a Red Hat storage solution, Red Hat OpenShift Container Storage is completely integrated with OpenShift Container Platform for deployment, management, and monitoring. Red Hat OpenShift Container Storage provides its own documentation library. The complete set of Red Hat OpenShift Container Storage documentation identified below is available at https://access.redhat.com/documentation/en-us/red_hat_openshift_container_storage/4.7/ Important OpenShift Container Storage on top of Red Hat Hyperconverged Infrastructure (RHHI) for Virtualization, which uses hyperconverged nodes that host virtual machines installed with OpenShift Container Platform, is not a supported configuration. For more information about supported platforms, see the Red Hat OpenShift Container Storage Supportability and Interoperability Guide . If you are looking for Red Hat OpenShift Container Storage information about... See the following Red Hat OpenShift Container Storage documentation: Planning What's new, known issues, notable bug fixes, and Technology Previews Red Hat OpenShift Container Storage 4.7 Release Notes Supported workloads, layouts, hardware and software requirements, sizing and scaling recommendations Planning your Red Hat OpenShift Container Storage 4.7 deployment Deploying Deploying Red Hat OpenShift Container Storage using Amazon Web Services for local or cloud storage Deploying OpenShift Container Storage 4.7 using Amazon Web Services Deploying Red Hat OpenShift Container Storage to local storage on bare metal infrastructure Deploying OpenShift Container Storage 4.7 using bare metal infrastructure Deploying Red Hat OpenShift Container Storage to use an external Red Hat Ceph Storage cluster Deploying OpenShift Container Storage 4.7 in external mode Deploying and managing Red Hat OpenShift Container Storage on existing Google Cloud clusters Deploying and managing OpenShift Container Storage 4.7 using Google Cloud Deploying Red Hat OpenShift Container Storage to use local storage on IBM Z infrastructure Deploying OpenShift Container Storage using IBM Z Deploying Red Hat OpenShift Container Storage on IBM Power Systems Deploying OpenShift Container Storage using IBM Power Systems Deploying Red Hat OpenShift Container Storage on IBM Cloud Deploying OpenShift Container Storage using IBM Cloud Deploying and managing Red Hat OpenShift Container Storage on Red Hat OpenStack Platform (RHOSP) Deploying and managing OpenShift Container Storage 4.7 using Red Hat OpenStack Platform Deploying and managing Red Hat OpenShift Container Storage on Red Hat Virtualization (RHV) Deploying and managing OpenShift Container Storage 4.7 using Red Hat Virtualization Platform Deploying Red Hat OpenShift Container Storage on VMware vSphere clusters Deploying OpenShift Container Storage 4.7 on VMware vSphere Updating Red Hat OpenShift Container Storage to the latest version Updating OpenShift Container Storage Managing Allocating storage to core services and hosted applications in Red Hat OpenShift Container Storage, including snapshot and clone Managing and allocating resources Managing storage resources across a hybrid cloud or multicloud environment using the Multicloud Object Gateway (NooBaa) Managing hybrid and multicloud resources Safely replacing storage devices for Red Hat OpenShift Container Storage Replacing devices Safely replacing a node in a Red Hat OpenShift Container Storage cluster Replacing nodes Scaling operations in Red Hat OpenShift Container Storage Scaling storage Monitoring a Red Hat OpenShift Container Storage 4.7 cluster Monitoring OpenShift Container Storage 4.7 Troubleshooting errors and issues Troubleshooting OpenShift Container Storage 4.7 Migrating your OpenShift Container Platform cluster from version 3 to version 4 Migration Toolkit for Containers 4.13. Persistent storage using VMware vSphere volumes OpenShift Container Platform allows use of VMware vSphere's Virtual Machine Disk (VMDK) volumes. You can provision your OpenShift Container Platform cluster with persistent storage using VMware vSphere. Some familiarity with Kubernetes and VMware vSphere is assumed. VMware vSphere volumes can be provisioned dynamically. OpenShift Container Platform creates the disk in vSphere and attaches this disk to the correct image. Note OpenShift Container Platform provisions new volumes as independent persistent disks that can freely attach and detach the volume on any node in the cluster. Consequently, you cannot back up volumes that use snapshots, or restore volumes from snapshots. See Snapshot Limitations for more information. The Kubernetes persistent volume framework allows administrators to provision a cluster with persistent storage and gives users a way to request those resources without having any knowledge of the underlying infrastructure. Persistent volumes are not bound to a single project or namespace; they can be shared across the OpenShift Container Platform cluster. Persistent volume claims are specific to a project or namespace and can be requested by users. Additional resources VMware vSphere 4.13.1. Dynamically provisioning VMware vSphere volumes Dynamically provisioning VMware vSphere volumes is the recommended method. 4.13.2. Prerequisites An OpenShift Container Platform cluster installed on a VMware vSphere version that meets the requirements for the components that you use. See Installing a cluster on vSphere for information about vSphere version support. You can use either of the following procedures to dynamically provision these volumes using the default storage class. 4.13.2.1. Dynamically provisioning VMware vSphere volumes using the UI OpenShift Container Platform installs a default storage class, named thin , that uses the thin disk format for provisioning volumes. Prerequisites Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. Procedure In the OpenShift Container Platform console, click Storage Persistent Volume Claims . In the persistent volume claims overview, click Create Persistent Volume Claim . Define the required options on the resulting page. Select the thin storage class. Enter a unique name for the storage claim. Select the access mode to determine the read and write access for the created storage claim. Define the size of the storage claim. Click Create to create the persistent volume claim and generate a persistent volume. 4.13.2.2. Dynamically provisioning VMware vSphere volumes using the CLI OpenShift Container Platform installs a default StorageClass, named thin , that uses the thin disk format for provisioning volumes. Prerequisites Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. Procedure (CLI) You can define a VMware vSphere PersistentVolumeClaim by creating a file, pvc.yaml , with the following contents: kind: PersistentVolumeClaim apiVersion: v1 metadata: name: pvc 1 spec: accessModes: - ReadWriteOnce 2 resources: requests: storage: 1Gi 3 1 A unique name that represents the persistent volume claim. 2 The access mode of the persistent volume claim. With ReadWriteOnce , the volume can be mounted with read and write permissions by a single node. 3 The size of the persistent volume claim. Create the PersistentVolumeClaim object from the file: USD oc create -f pvc.yaml 4.13.3. Statically provisioning VMware vSphere volumes To statically provision VMware vSphere volumes you must create the virtual machine disks for reference by the persistent volume framework. Prerequisites Storage must exist in the underlying infrastructure before it can be mounted as a volume in OpenShift Container Platform. Procedure Create the virtual machine disks. Virtual machine disks (VMDKs) must be created manually before statically provisioning VMware vSphere volumes. Use either of the following methods: Create using vmkfstools . Access ESX through Secure Shell (SSH) and then use following command to create a VMDK volume: USD vmkfstools -c <size> /vmfs/volumes/<datastore-name>/volumes/<disk-name>.vmdk Create using vmware-diskmanager : USD shell vmware-vdiskmanager -c -t 0 -s <size> -a lsilogic <disk-name>.vmdk Create a persistent volume that references the VMDKs. Create a file, pv1.yaml , with the PersistentVolume object definition: apiVersion: v1 kind: PersistentVolume metadata: name: pv1 1 spec: capacity: storage: 1Gi 2 accessModes: - ReadWriteOnce persistentVolumeReclaimPolicy: Retain vsphereVolume: 3 volumePath: "[datastore1] volumes/myDisk" 4 fsType: ext4 5 1 The name of the volume. This name is how it is identified by persistent volume claims or pods. 2 The amount of storage allocated to this volume. 3 The volume type used, with vsphereVolume for vSphere volumes. The label is used to mount a vSphere VMDK volume into pods. The contents of a volume are preserved when it is unmounted. The volume type supports VMFS and VSAN datastore. 4 The existing VMDK volume to use. If you used vmkfstools , you must enclose the datastore name in square brackets, [] , in the volume definition, as shown previously. 5 The file system type to mount. For example, ext4, xfs, or other file systems. Important Changing the value of the fsType parameter after the volume is formatted and provisioned can result in data loss and pod failure. Create the PersistentVolume object from the file: USD oc create -f pv1.yaml Create a persistent volume claim that maps to the persistent volume you created in the step. Create a file, pvc1.yaml , with the PersistentVolumeClaim object definition: apiVersion: v1 kind: PersistentVolumeClaim metadata: name: pvc1 1 spec: accessModes: - ReadWriteOnce 2 resources: requests: storage: "1Gi" 3 volumeName: pv1 4 1 A unique name that represents the persistent volume claim. 2 The access mode of the persistent volume claim. With ReadWriteOnce, the volume can be mounted with read and write permissions by a single node. 3 The size of the persistent volume claim. 4 The name of the existing persistent volume. Create the PersistentVolumeClaim object from the file: USD oc create -f pvc1.yaml 4.13.3.1. Formatting VMware vSphere volumes Before OpenShift Container Platform mounts the volume and passes it to a container, it checks that the volume contains a file system that is specified by the fsType parameter value in the PersistentVolume (PV) definition. If the device is not formatted with the file system, all data from the device is erased, and the device is automatically formatted with the specified file system. Because OpenShift Container Platform formats them before the first use, you can use unformatted vSphere volumes as PVs.	[ "oc create secret generic <secret-name> --from-literal=azurestorageaccountname=<storage-account> \\ 1 --from-literal=azurestorageaccountkey=<storage-account-key> 2", "apiVersion: \"v1\" kind: \"PersistentVolume\" metadata: name: \"pv0001\" 1 spec: capacity: storage: \"5Gi\" 2 accessModes: - \"ReadWriteOnce\" storageClassName: azure-file-sc azureFile: secretName: <secret-name> 3 shareName: share-1 4 readOnly: false", "apiVersion: \"v1\" kind: \"PersistentVolumeClaim\" metadata: name: \"claim1\" 1 spec: accessModes: - \"ReadWriteOnce\" resources: requests: storage: \"5Gi\" 2 storageClassName: azure-file-sc 3 volumeName: \"pv0001\" 4", "apiVersion: v1 kind: Pod metadata: name: pod-name 1 spec: containers: volumeMounts: - mountPath: \"/data\" 2 name: azure-file-share volumes: - name: azure-file-share persistentVolumeClaim: claimName: claim1 3", "apiVersion: \"v1\" kind: \"PersistentVolume\" metadata: name: \"pv0001\" 1 spec: capacity: storage: \"5Gi\" 2 accessModes: - \"ReadWriteOnce\" cinder: 3 fsType: \"ext3\" 4 volumeID: \"f37a03aa-6212-4c62-a805-9ce139fab180\" 5", "oc create -f cinder-persistentvolume.yaml", "oc create serviceaccount <service_account>", "oc adm policy add-scc-to-user <new_scc> -z <service_account> -n <project>", "apiVersion: v1 kind: ReplicationController metadata: name: frontend-1 spec: replicas: 1 1 selector: 2 name: frontend template: 3 metadata: labels: 4 name: frontend 5 spec: containers: - image: openshift/hello-openshift name: helloworld ports: - containerPort: 8080 protocol: TCP restartPolicy: Always serviceAccountName: <service_account> 6 securityContext: fsGroup: 7777 7", "apiVersion: v1 kind: PersistentVolume metadata: name: pv0001 spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce fc: wwids: [scsi-3600508b400105e210000900000490000] 1 targetWWNs: ['500a0981891b8dc5', '500a0981991b8dc5'] 2 lun: 2 3 fsType: ext4", "{ \"fooServer\": \"192.168.0.1:1234\", 1 \"fooVolumeName\": \"bar\", \"kubernetes.io/fsType\": \"ext4\", 2 \"kubernetes.io/readwrite\": \"ro\", 3 \"kubernetes.io/secret/<key name>\": \"<key value>\", 4 \"kubernetes.io/secret/<another key name>\": \"<another key value>\", }", "{ \"status\": \"<Success/Failure/Not supported>\", \"message\": \"<Reason for success/failure>\" }", "apiVersion: v1 kind: PersistentVolume metadata: name: pv0001 1 spec: capacity: storage: 1Gi 2 accessModes: - ReadWriteOnce flexVolume: driver: openshift.com/foo 3 fsType: \"ext4\" 4 secretRef: foo-secret 5 readOnly: true 6 options: 7 fooServer: 192.168.0.1:1234 fooVolumeName: bar", "\"fsType\":\"<FS type>\", \"readwrite\":\"<rw>\", \"secret/key1\":\"<secret1>\" \"secret/keyN\":\"<secretN>\"", "apiVersion: v1 kind: Pod metadata: name: test-host-mount spec: containers: - image: registry.access.redhat.com/ubi8/ubi name: test-container command: ['sh', '-c', 'sleep 3600'] volumeMounts: - mountPath: /host name: host-slash volumes: - name: host-slash hostPath: path: / type: ''", "apiVersion: v1 kind: PersistentVolume metadata: name: task-pv-volume 1 labels: type: local spec: storageClassName: manual 2 capacity: storage: 5Gi accessModes: - ReadWriteOnce 3 persistentVolumeReclaimPolicy: Retain hostPath: path: \"/mnt/data\" 4", "oc create -f pv.yaml", "apiVersion: v1 kind: PersistentVolumeClaim metadata: name: task-pvc-volume spec: accessModes: - ReadWriteOnce resources: requests: storage: 1Gi storageClassName: manual", "oc create -f pvc.yaml", "apiVersion: v1 kind: Pod metadata: name: pod-name 1 spec: containers: securityContext: privileged: true 2 volumeMounts: - mountPath: /data 3 name: hostpath-privileged securityContext: {} volumes: - name: hostpath-privileged persistentVolumeClaim: claimName: task-pvc-volume 4", "apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.16.154.81:3260 iqn: iqn.2014-12.example.server:storage.target00 lun: 0 fsType: 'ext4'", "apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.0.0.1:3260 iqn: iqn.2016-04.test.com:storage.target00 lun: 0 fsType: ext4 chapAuthDiscovery: true 1 chapAuthSession: true 2 secretRef: name: chap-secret 3", "apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.0.0.1:3260 portals: ['10.0.2.16:3260', '10.0.2.17:3260', '10.0.2.18:3260'] 1 iqn: iqn.2016-04.test.com:storage.target00 lun: 0 fsType: ext4 readOnly: false", "apiVersion: v1 kind: PersistentVolume metadata: name: iscsi-pv spec: capacity: storage: 1Gi accessModes: - ReadWriteOnce iscsi: targetPortal: 10.0.0.1:3260 portals: ['10.0.2.16:3260', '10.0.2.17:3260', '10.0.2.18:3260'] iqn: iqn.2016-04.test.com:storage.target00 lun: 0 initiatorName: iqn.2016-04.test.com:custom.iqn 1 fsType: ext4 readOnly: false", "oc adm new-project openshift-local-storage", "oc annotate project openshift-local-storage openshift.io/node-selector=''", "OC_VERSION=USD(oc version -o yaml \| grep openshiftVersion \| grep -o '[0-9][.][0-9]' \| head -1)", "apiVersion: operators.coreos.com/v1alpha2 kind: OperatorGroup metadata: name: local-operator-group namespace: openshift-local-storage spec: targetNamespaces: - openshift-local-storage --- apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: local-storage-operator namespace: openshift-local-storage spec: channel: \"USD{OC_VERSION}\" installPlanApproval: Automatic 1 name: local-storage-operator source: redhat-operators sourceNamespace: openshift-marketplace", "oc apply -f openshift-local-storage.yaml", "oc -n openshift-local-storage get pods", "NAME READY STATUS RESTARTS AGE local-storage-operator-746bf599c9-vlt5t 1/1 Running 0 19m", "oc get csvs -n openshift-local-storage", "NAME DISPLAY VERSION REPLACES PHASE local-storage-operator.4.2.26-202003230335 Local Storage 4.2.26-202003230335 Succeeded", "apiVersion: \"local.storage.openshift.io/v1\" kind: \"LocalVolume\" metadata: name: \"local-disks\" namespace: \"openshift-local-storage\" 1 spec: nodeSelector: 2 nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-140-183 - ip-10-0-158-139 - ip-10-0-164-33 storageClassDevices: - storageClassName: \"local-sc\" 3 volumeMode: Filesystem 4 fsType: xfs 5 devicePaths: 6 - /path/to/device 7", "apiVersion: \"local.storage.openshift.io/v1\" kind: \"LocalVolume\" metadata: name: \"local-disks\" namespace: \"openshift-local-storage\" 1 spec: nodeSelector: 2 nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - ip-10-0-136-143 - ip-10-0-140-255 - ip-10-0-144-180 storageClassDevices: - storageClassName: \"localblock-sc\" 3 volumeMode: Block 4 devicePaths: 5 - /path/to/device 6", "oc create -f <local-volume>.yaml", "oc get all -n openshift-local-storage", "NAME READY STATUS RESTARTS AGE pod/local-disks-local-provisioner-h97hj 1/1 Running 0 46m pod/local-disks-local-provisioner-j4mnn 1/1 Running 0 46m pod/local-disks-local-provisioner-kbdnx 1/1 Running 0 46m pod/local-disks-local-diskmaker-ldldw 1/1 Running 0 46m pod/local-disks-local-diskmaker-lvrv4 1/1 Running 0 46m pod/local-disks-local-diskmaker-phxdq 1/1 Running 0 46m pod/local-storage-operator-54564d9988-vxvhx 1/1 Running 0 47m NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/local-storage-operator ClusterIP 172.30.49.90 <none> 60000/TCP 47m NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE daemonset.apps/local-disks-local-provisioner 3 3 3 3 3 <none> 46m daemonset.apps/local-disks-local-diskmaker 3 3 3 3 3 <none> 46m NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/local-storage-operator 1/1 1 1 47m NAME DESIRED CURRENT READY AGE replicaset.apps/local-storage-operator-54564d9988 1 1 1 47m", "oc get pv", "NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE local-pv-1cec77cf 100Gi RWO Delete Available local-sc 88m local-pv-2ef7cd2a 100Gi RWO Delete Available local-sc 82m local-pv-3fa1c73 100Gi RWO Delete Available local-sc 48m", "apiVersion: v1 kind: PersistentVolume metadata: name: example-pv-filesystem spec: capacity: storage: 100Gi volumeMode: Filesystem 1 accessModes: - ReadWriteOnce persistentVolumeReclaimPolicy: Delete storageClassName: local-storage 2 local: path: /dev/xvdf 3 nodeAffinity: required: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - example-node", "apiVersion: v1 kind: PersistentVolume metadata: name: example-pv-block spec: capacity: storage: 100Gi volumeMode: Block 1 accessModes: - ReadWriteOnce persistentVolumeReclaimPolicy: Delete storageClassName: local-storage 2 local: path: /dev/xvdf 3 nodeAffinity: required: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - example-node", "oc create -f <example-pv>.yaml", "oc get pv", "NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE example-pv-filesystem 100Gi RWO Delete Available local-storage 3m47s example-pv1 1Gi RWO Delete Bound local-storage/pvc1 local-storage 12h example-pv2 1Gi RWO Delete Bound local-storage/pvc2 local-storage 12h example-pv3 1Gi RWO Delete Bound local-storage/pvc3 local-storage 12h", "kind: PersistentVolumeClaim apiVersion: v1 metadata: name: local-pvc-name 1 spec: accessModes: - ReadWriteOnce volumeMode: Filesystem 2 resources: requests: storage: 100Gi 3 storageClassName: local-sc 4", "oc create -f <local-pvc>.yaml", "apiVersion: v1 kind: Pod spec: containers: volumeMounts: - name: local-disks 1 mountPath: /data 2 volumes: - name: localpvc persistentVolumeClaim: claimName: local-pvc-name 3", "oc create -f <local-pod>.yaml", "apiVersion: local.storage.openshift.io/v1alpha1 kind: LocalVolumeSet metadata: name: example-autodetect spec: nodeSelector: nodeSelectorTerms: - matchExpressions: - key: kubernetes.io/hostname operator: In values: - worker-0 - worker-1 storageClassName: example-storageclass 1 volumeMode: Filesystem fsType: ext4 maxDeviceCount: 10 deviceInclusionSpec: deviceTypes: 2 - disk - part deviceMechanicalProperties: - NonRotational minSize: 10G maxSize: 100G models: - SAMSUNG - Crucial_CT525MX3 vendors: - ATA - ST2000LM", "oc apply -f local-volume-set.yaml", "oc get pv", "NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE local-pv-1cec77cf 100Gi RWO Delete Available example-storageclass 88m local-pv-2ef7cd2a 100Gi RWO Delete Available example-storageclass 82m local-pv-3fa1c73 100Gi RWO Delete Available example-storageclass 48m", "apiVersion: \"local.storage.openshift.io/v1\" kind: \"LocalVolume\" metadata: name: \"local-disks\" namespace: \"openshift-local-storage\" spec: tolerations: - key: localstorage 1 operator: Equal 2 value: \"localstorage\" 3 storageClassDevices: - storageClassName: \"localblock-sc\" volumeMode: Block 4 devicePaths: 5 - /dev/xvdg", "spec: tolerations: - key: node-role.kubernetes.io/master operator: Exists", "oc edit localvolume <name> -n openshift-local-storage", "oc delete pv <pv-name>", "oc debug node/<node-name>", "chroot /host", "cd /mnt/openshift-local-storage/<sc-name> 1", "rm <symlink>", "oc delete localvolume --all --all-namespaces oc delete localvolumeset --all --all-namespaces oc delete localvolumediscovery --all --all-namespaces", "oc delete pv <pv-name>", "oc delete project openshift-local-storage", "apiVersion: v1 kind: PersistentVolume metadata: name: pv0001 1 spec: capacity: storage: 5Gi 2 accessModes: - ReadWriteOnce 3 nfs: 4 path: /tmp 5 server: 172.17.0.2 6 persistentVolumeReclaimPolicy: Retain 7", "oc get pv", "NAME LABELS CAPACITY ACCESSMODES STATUS CLAIM REASON AGE pv0001 <none> 5Gi RWO Available 31s", "apiVersion: v1 kind: PersistentVolumeClaim metadata: name: nfs-claim1 spec: accessModes: - ReadWriteOnce 1 resources: requests: storage: 5Gi 2 volumeName: pv0001 storageClassName: \"\"", "oc get pvc", "NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE nfs-claim1 Bound pv0001 5Gi RWO 2m", "ls -lZ /opt/nfs -d", "drwxrws---. nfsnobody 5555 unconfined_u:object_r:usr_t:s0 /opt/nfs", "id nfsnobody", "uid=65534(nfsnobody) gid=65534(nfsnobody) groups=65534(nfsnobody)", "spec: containers: - name: securityContext: 1 supplementalGroups: [5555] 2", "spec: containers: 1 - name: securityContext: runAsUser: 65534 2", "setsebool -P virt_use_nfs 1", "/<example_fs> *(rw,root_squash)", "iptables -I INPUT 1 -p tcp --dport 2049 -j ACCEPT", "iptables -I INPUT 1 -p tcp --dport 2049 -j ACCEPT", "iptables -I INPUT 1 -p tcp --dport 20048 -j ACCEPT", "iptables -I INPUT 1 -p tcp --dport 111 -j ACCEPT", "apiVersion: v1 kind: PersistentVolume metadata: name: nfs1 spec: capacity: storage: 1Mi accessModes: - ReadWriteMany nfs: server: 192.168.1.1 path: \"/\"", "apiVersion: v1 kind: PersistentVolume metadata: name: nfs2 spec: capacity: storage: 1Mi accessModes: - ReadWriteMany nfs: server: 192.168.1.1 path: \"/\"", "echo 'Y' > /sys/module/nfsd/parameters/nfs4_disable_idmapping", "kind: PersistentVolumeClaim apiVersion: v1 metadata: name: pvc 1 spec: accessModes: - ReadWriteOnce 2 resources: requests: storage: 1Gi 3", "oc create -f pvc.yaml", "vmkfstools -c <size> /vmfs/volumes/<datastore-name>/volumes/<disk-name>.vmdk", "shell vmware-vdiskmanager -c -t 0 -s <size> -a lsilogic <disk-name>.vmdk", "apiVersion: v1 kind: PersistentVolume metadata: name: pv1 1 spec: capacity: storage: 1Gi 2 accessModes: - ReadWriteOnce persistentVolumeReclaimPolicy: Retain vsphereVolume: 3 volumePath: \"[datastore1] volumes/myDisk\" 4 fsType: ext4 5", "oc create -f pv1.yaml", "apiVersion: v1 kind: PersistentVolumeClaim metadata: name: pvc1 1 spec: accessModes: - ReadWriteOnce 2 resources: requests: storage: \"1Gi\" 3 volumeName: pv1 4", "oc create -f pvc1.yaml" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.7/html/storage/configuring-persistent-storage
2.2.8.4. Disable Sendmail Network Listening	2.2.8.4. Disable Sendmail Network Listening By default, Sendmail is set up to only listen to the local loopback address. You can verify this by viewing the file /etc/mail/sendmail.mc to ensure that the following line appears: This ensures that Sendmail only accepts mail messages (such as cron job reports) from the local system and not from the network. This is the default setting and protects Sendmail from a network attack. For removal of the localhost restriction, the Addr=127.0.0.1 string needs to be removed. Changing Sendmail's configuration requires installing the sendmail-cf package, then editing the .mc file, running /etc/mail/make and finally restarting sendmail . The .cf configuration file will be regenerated. Note that the system clock must be correct and working and that there must not be any system clock time shifts between these actions in order for the configuration file to be automatically regenerated.	[ "DAEMON_OPTIONS(`Port=smtp,Addr=127.0.0.1, Name=MTA')dnl" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/security_guide/sect-security_guide-disable_sendmail_network_listening
3.3. Converting a virtual machine	3.3. Converting a virtual machine Once you have prepared to convert the virtual machines, use virt-v2v to perform the actual conversions. This section provides the steps to convert the virtual machines, and the command syntax for virt-v2v . Note that conversions are resource intensive processes that require copying the whole disk image for a virtual machine. In typical environments, converting a single virtual machine takes approximately 5-10 minutes. In Example 3.4, "Typical virt-v2v conversion time" a virtual machine with a single 8GB disk is copied over SSH on a 1GigE network on three-year-old consumer hardware: Example 3.4. Typical virt-v2v conversion time The size of the disk to be copied is the major factor in determining conversion time. For a virtual machine on average hardware with a single disk of 20GB or less, a conversion usually takes less than 10 minutes. 3.3.1. Converting a local virtual machine using virt-v2v virt-v2v converts virtual machines from a foreign hypervisor to run on KVM, managed by libvirt. The general command syntax for converting machines to run on KVM, managed by libvirt is: For a list of virt-v2v parameters, refer to Chapter 7, References .	[ "win2k3r2-pv-32.img: 100% [===========================================]D 0h02m57s virt-v2v: win2k3r2-pv-32 configured with virtio drivers.", "virt-v2v -i libvirtxml -op pool --bridge bridge_name guest_name.xml virt-v2v -op pool --network netname guest_name virt-v2v -ic esx://esx.example.com/?no_verify=1 -op pool --bridge bridge_name guest_name" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/v2v_guide/sect-converting-a-virtual-machine
Chapter 1. Enhancements	Chapter 1. Enhancements ENTMQIC-2455 - Allow AMQP open properties to be supplemented from connector configuration With this release you can now add metadata when connecting routers, as described in Adding metadata to connections . ENTMQIC-2448 - Allow defining address prefix shared by different multitenant listeners With this release a multitenant prefix specified by a vhost policy can be shared among several hostnames with a pattern specified in the aliases parameter as described in Creating vhost policies .	null	https://docs.redhat.com/en/documentation/red_hat_amq/2020.q4/html/release_notes_for_amq_interconnect_1.9/enhancements
14.9.5. Forcing a Guest Virtual Machine to Stop	14.9.5. Forcing a Guest Virtual Machine to Stop Force a guest virtual machine to stop with the virsh destroy command: This command does an immediate ungraceful shutdown and stops the specified guest virtual machine. Using virsh destroy can corrupt guest virtual machine file systems. Use the destroy option only when the guest virtual machine is unresponsive. If you want to initiate a graceful shutdown, use the virsh destroy --graceful command.	[ "virsh destroy {domain-id, domain-name or domain-uuid} [--graceful]" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/virtualization_administration_guide/sub-sect-shutting_down_rebooting_and_force_shutdown_of_a_guest_virtual_machine-forcing_a_guest_virtual_machine_to_stop
A.3. Capturing Trace Data on a Constant Basis Using the Systemtap Flight Recorder	A.3. Capturing Trace Data on a Constant Basis Using the Systemtap Flight Recorder You can capture QEMU trace data all the time using a systemtap initscript provided in the qemu-kvm package. This package uses SystemTap's flight recorder mode to trace all running guest virtual machines and to save the results to a fixed-size buffer on the host. Old trace entries are overwritten by new entries when the buffer is filled. Procedure A.1. Configuring and running systemtap Install the package Install the systemtap-initscript package by running the following command: Copy the configuration file Copy the systemtap scripts and the configuration files to the systemtap directory by running the following commands: The set of trace events to enable is given in qemu_kvm.stp. This SystemTap script can be customized to add or remove trace events provided in /usr/share/systemtap/tapset/qemu-kvm-simpletrace.stp . SystemTap customizations can be made to qemu_kvm.conf to control the flight recorder buffer size and whether to store traces in memory only or in the disk as well. Start the service Start the systemtap service by running the following command: Make systemtap enabled to run at boot time Enable the systemtap service to run at boot time by running the following command: Confirmation the service is running Confirm that the service is working by running the following command: Procedure A.2. Inspecting the trace buffer Create a trace buffer dump file Create a trace buffer dump file called trace.log and place it in the tmp directory by running the following command: You can change the file name and location to something else. Start the service As the step stops the service, start it again by running the following command: Convert the trace contents into a readable format To convert the trace file contents into a more readable format, enter the following command: Note The following notes and limitations should be noted: The systemtap service is disabled by default. There is a small performance penalty when this service is enabled, but it depends on which events are enabled in total. There is a README file located in /usr/share/doc/qemu-kvm-*/README.systemtap .	[ "yum install systemtap-initscript", "cp /usr/share/qemu-kvm/systemtap/script.d/qemu_kvm.stp /etc/systemtap/script.d/ cp /usr/share/qemu-kvm/systemtap/conf.d/qemu_kvm.conf /etc/systemtap/conf.d/", "systemctl start systemtap qemu_kvm", "systemctl enable systemtap qemu_kvm", "systemctl status systemtap qemu_kvm qemu_kvm is running", "staprun -A qemu_kvm >/tmp/trace.log", "systemctl start systemtap qemu_kvm", "/usr/share/qemu-kvm/simpletrace.py --no-header /usr/share/qemu-kvm/trace-events /tmp/trace.log" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/virtualization_deployment_and_administration_guide/sect-troubleshooting-systemtaptrace
Manage Secrets with OpenStack Key Manager	Manage Secrets with OpenStack Key Manager Red Hat OpenStack Platform 16.2 How to integrate OpenStack Key Manager (barbican) with your OpenStack deployment. OpenStack Documentation Team [email protected]	null	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/16.2/html/manage_secrets_with_openstack_key_manager/index
Chapter 14. Configuring audit logging	Chapter 14. Configuring audit logging Red Hat Advanced Cluster Security for Kubernetes provides audit logging features that you can use to check all the changes made in Red Hat Advanced Cluster Security for Kubernetes. The audit log captures all the PUT and POST events, which are modifications to Red Hat Advanced Cluster Security for Kubernetes. Use this information to troubleshoot a problem or to keep a record of important events, such as changes to roles and permissions. With audit logging you get a complete picture of all normal and abnormal events that happened on Red Hat Advanced Cluster Security for Kubernetes. Note Audit logging is not enabled by default. You must enable audit logging manually. Warning Currently there is no message delivery guarantee for audit log messages. 14.1. Enabling audit logging When you enable audit logging, every time there is a modification, Red Hat Advanced Cluster Security for Kubernetes sends an HTTP POST message (in JSON format) to the configured system. Prerequisites Configure Splunk or another webhook receiver to handle Red Hat Advanced Cluster Security for Kubernetes log messages. You must have write permission enabled on the Notifiers resource for your role. Procedure In the RHACS portal, go to Platform Configuration Integrations . Scroll down to the Notifier Integrations section and select Generic Webhook or Splunk . Fill in the required information and turn on the Enable Audit Logging toggle. 14.2. Sample audit log message The log message has the following format: { "headers": { "Accept-Encoding": [ "gzip" ], "Content-Length": [ "586" ], "Content-Type": [ "application/json" ], "User-Agent": [ "Go-http-client/1.1" ] }, "data": { "audit": { "interaction": "CREATE", "method": "UI", "request": { "endpoint": "/v1/notifiers", "method": "POST", "source": { "requestAddr": "10.131.0.7:58276", "xForwardedFor": "8.8.8.8", }, "sourceIp": "8.8.8.8", "payload": { "@type": "storage.Notifier", "enabled": true, "generic": { "auditLoggingEnabled": true, "endpoint": "http://samplewebhookserver.com:8080" }, "id": "b53232ee-b13e-47e0-b077-1e383c84aa07", "name": "Webhook", "type": "generic", "uiEndpoint": "https://localhost:8000" } }, "status": "REQUEST_SUCCEEDED", "time": "2019-05-28T16:07:05.500171300Z", "user": { "friendlyName": "John Doe", "role": { "globalAccess": "READ_WRITE_ACCESS", "name": "Admin" }, "username": "[email protected]" } } } } The source IP address of the request is displayed in the source parameters, which makes it easier for you to investigate audit log requests and identify their origin. To determine the source IP address of a request, RHACS uses the following parameters: xForwardedFor : The X-Forwarded-For header. requestAddr : The remote address header. sourceIp : The IP address of the HTTP request. Important The determination of the source IP address depends on how you expose Central externally. You can consider the following options: If you expose Central behind a load balancer, for example, if you are running Central on Google Kubernetes Engine (GKE) or Amazon Elastic Kubernetes Service (Amazon EKS) by using the Kubernetes External Load Balancer service type, see Preserving the client source IP . If you expose Central behind an Ingress Controller that forwards requests by using the X-Forwarded-For header , you do not need to make any configuration changes. If you expose Central with a TLS passthrough route, you cannot determine the source IP address of the client. A cluster-internal IP address is displayed in the source parameters as the source IP address of the client.	[ "{ \"headers\": { \"Accept-Encoding\": [ \"gzip\" ], \"Content-Length\": [ \"586\" ], \"Content-Type\": [ \"application/json\" ], \"User-Agent\": [ \"Go-http-client/1.1\" ] }, \"data\": { \"audit\": { \"interaction\": \"CREATE\", \"method\": \"UI\", \"request\": { \"endpoint\": \"/v1/notifiers\", \"method\": \"POST\", \"source\": { \"requestAddr\": \"10.131.0.7:58276\", \"xForwardedFor\": \"8.8.8.8\", }, \"sourceIp\": \"8.8.8.8\", \"payload\": { \"@type\": \"storage.Notifier\", \"enabled\": true, \"generic\": { \"auditLoggingEnabled\": true, \"endpoint\": \"http://samplewebhookserver.com:8080\" }, \"id\": \"b53232ee-b13e-47e0-b077-1e383c84aa07\", \"name\": \"Webhook\", \"type\": \"generic\", \"uiEndpoint\": \"https://localhost:8000\" } }, \"status\": \"REQUEST_SUCCEEDED\", \"time\": \"2019-05-28T16:07:05.500171300Z\", \"user\": { \"friendlyName\": \"John Doe\", \"role\": { \"globalAccess\": \"READ_WRITE_ACCESS\", \"name\": \"Admin\" }, \"username\": \"[email protected]\" } } } }" ]	https://docs.redhat.com/en/documentation/red_hat_advanced_cluster_security_for_kubernetes/4.7/html/configuring/configure-audit-logging
Chapter 6. Managing Satellite with Ansible collections	Chapter 6. Managing Satellite with Ansible collections Satellite Ansible Collections is a set of Ansible modules that interact with the Satellite API. You can manage and automate many aspects of Satellite with Satellite Ansible collections. 6.1. Installing the Satellite Ansible modules Use this procedure to install the Satellite Ansible modules. Procedure Install the package using the following command: 6.2. Viewing the Satellite Ansible modules You can view the installed Satellite Ansible modules by running: Alternatively, you can also see the complete list of Satellite Ansible modules and other related information at Red Hat Ansible Automation Platform . All modules are in the redhat.satellite namespace and can be referred to in the format redhat.satellite._module_name_ . For example, to display information about the activation_key module, enter the following command:	[ "satellite-maintain packages install ansible-collection-redhat-satellite", "ansible-doc -l redhat.satellite", "ansible-doc redhat.satellite.activation_key" ]	https://docs.redhat.com/en/documentation/red_hat_satellite/6.15/html/administering_red_hat_satellite/managing_project_with_ansible_collections_admin
Part I. Preparing the RHEL installation	Part I. Preparing the RHEL installation Essential steps for preparing a RHEL installation environment addresses system requirements, supported architectures, and offers customization options for installation media. Additionally, it covers methods for creating bootable installation media, setting up network-based repositories, and configuring UEFI HTTP or PXE installation sources. Guidance is also included for systems using UEFI Secure Boot and for installing RHEL on 64-bit IBM Z architecture.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/9/html/automatically_installing_rhel/preparing-the-rhel-installation
Providing feedback on Red Hat build of OpenJDK documentation	Providing feedback on Red Hat build of OpenJDK documentation To report an error or to improve our documentation, log in to your Red Hat Jira account and submit an issue. If you do not have a Red Hat Jira account, then you will be prompted to create an account. Procedure Click the following link to create a ticket . Enter a brief description of the issue in the Summary . Provide a detailed description of the issue or enhancement in the Description . Include a URL to where the issue occurs in the documentation. Clicking Submit creates and routes the issue to the appropriate documentation team.	null	https://docs.redhat.com/en/documentation/red_hat_build_of_openjdk/11/html/release_notes_for_red_hat_build_of_openjdk_11.0.18/proc-providing-feedback-on-redhat-documentation
Chapter 91. workflow	Chapter 91. workflow This chapter describes the commands under the workflow command. 91.1. workflow create Create new workflow. Usage: Table 91.1. Positional arguments Value Summary definition Workflow definition file. Table 91.2. Command arguments Value Summary -h, --help Show this help message and exit --marker [MARKER] The last execution uuid of the page, displays list of executions after "marker". --limit [LIMIT] Maximum number of entries to return in a single result. --sort_keys [SORT_KEYS] Comma-separated list of sort keys to sort results by. Default: created_at. Example: mistral execution-list --sort_keys=id,description --sort_dirs [SORT_DIRS] Comma-separated list of sort directions. default: asc. Example: mistral execution-list --sort_keys=id,description --sort_dirs=asc,desc --filter FILTERS Filters. can be repeated. --namespace [NAMESPACE] Namespace to create the workflow within. --public With this flag workflow will be marked as "public". Table 91.3. Output formatter options Value Summary -f {csv,json,table,value,yaml}, --format {csv,json,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns --sort-column SORT_COLUMN Specify the column(s) to sort the data (columns specified first have a priority, non-existing columns are ignored), can be repeated --sort-ascending Sort the column(s) in ascending order --sort-descending Sort the column(s) in descending order Table 91.4. CSV formatter options Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 91.5. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.6. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.2. workflow definition show Show workflow definition. Usage: Table 91.7. Positional arguments Value Summary identifier Workflow id or name. Table 91.8. Command arguments Value Summary -h, --help Show this help message and exit --namespace [NAMESPACE] Namespace to get the workflow from. 91.3. workflow delete Delete workflow. Usage: Table 91.9. Positional arguments Value Summary workflow Name or id of workflow(s). Table 91.10. Command arguments Value Summary -h, --help Show this help message and exit --namespace [NAMESPACE] Namespace to delete the workflow from. 91.4. workflow engine service list List all services. Usage: Table 91.11. Command arguments Value Summary -h, --help Show this help message and exit --marker [MARKER] The last execution uuid of the page, displays list of executions after "marker". --limit [LIMIT] Maximum number of entries to return in a single result. --sort_keys [SORT_KEYS] Comma-separated list of sort keys to sort results by. Default: created_at. Example: mistral execution-list --sort_keys=id,description --sort_dirs [SORT_DIRS] Comma-separated list of sort directions. default: asc. Example: mistral execution-list --sort_keys=id,description --sort_dirs=asc,desc --filter FILTERS Filters. can be repeated. Table 91.12. Output formatter options Value Summary -f {csv,json,table,value,yaml}, --format {csv,json,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns --sort-column SORT_COLUMN Specify the column(s) to sort the data (columns specified first have a priority, non-existing columns are ignored), can be repeated --sort-ascending Sort the column(s) in ascending order --sort-descending Sort the column(s) in descending order Table 91.13. CSV formatter options Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 91.14. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.15. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.5. workflow env create Create new environment. Usage: Table 91.16. Positional arguments Value Summary file Environment configuration file in json or yaml Table 91.17. Command arguments Value Summary -h, --help Show this help message and exit Table 91.18. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.19. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.20. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.21. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.6. workflow env delete Delete environment. Usage: Table 91.22. Positional arguments Value Summary environment Name of environment(s). Table 91.23. Command arguments Value Summary -h, --help Show this help message and exit 91.7. workflow env list List all environments. Usage: Table 91.24. Command arguments Value Summary -h, --help Show this help message and exit --marker [MARKER] The last execution uuid of the page, displays list of executions after "marker". --limit [LIMIT] Maximum number of entries to return in a single result. --sort_keys [SORT_KEYS] Comma-separated list of sort keys to sort results by. Default: created_at. Example: mistral execution-list --sort_keys=id,description --sort_dirs [SORT_DIRS] Comma-separated list of sort directions. default: asc. Example: mistral execution-list --sort_keys=id,description --sort_dirs=asc,desc --filter FILTERS Filters. can be repeated. Table 91.25. Output formatter options Value Summary -f {csv,json,table,value,yaml}, --format {csv,json,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns --sort-column SORT_COLUMN Specify the column(s) to sort the data (columns specified first have a priority, non-existing columns are ignored), can be repeated --sort-ascending Sort the column(s) in ascending order --sort-descending Sort the column(s) in descending order Table 91.26. CSV formatter options Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 91.27. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.28. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.8. workflow env show Show specific environment. Usage: Table 91.29. Positional arguments Value Summary environment Environment name Table 91.30. Command arguments Value Summary -h, --help Show this help message and exit --export Export the environment suitable for import Table 91.31. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.32. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.33. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.34. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.9. workflow env update Update environment. Usage: Table 91.35. Positional arguments Value Summary file Environment configuration file in json or yaml Table 91.36. Command arguments Value Summary -h, --help Show this help message and exit Table 91.37. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.38. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.39. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.40. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.10. workflow execution create Create new execution. Usage: Table 91.41. Positional arguments Value Summary workflow_identifier Workflow id or name workflow_input Workflow input params Workflow additional parameters Table 91.42. Command arguments Value Summary -h, --help Show this help message and exit --namespace [NAMESPACE] Workflow namespace. -d DESCRIPTION, --description DESCRIPTION Execution description -s [SOURCE_EXECUTION_ID] Workflow execution id which will allow operators to create a new workflow execution based on the previously successful executed workflow. Example: mistral execution-create -s 123e4567-e89b-12d3-a456-426655440000 Table 91.43. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.44. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.45. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.46. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.11. workflow execution delete Delete execution. Usage: Table 91.47. Positional arguments Value Summary execution Id of execution identifier(s). Table 91.48. Command arguments Value Summary -h, --help Show this help message and exit --force Force the deletion of an execution. might cause a cascade of errors if used for running executions. 91.12. workflow execution input show Show execution input data. Usage: Table 91.49. Positional arguments Value Summary id Execution id Table 91.50. Command arguments Value Summary -h, --help Show this help message and exit 91.13. workflow execution list List all executions. Usage: Table 91.51. Command arguments Value Summary -h, --help Show this help message and exit --marker [MARKER] The last execution uuid of the page, displays list of executions after "marker". --limit [LIMIT] Maximum number of entries to return in a single result. --sort_keys [SORT_KEYS] Comma-separated list of sort keys to sort results by. Default: created_at. Example: mistral execution-list --sort_keys=id,description --sort_dirs [SORT_DIRS] Comma-separated list of sort directions. default: asc. Example: mistral execution-list --sort_keys=id,description --sort_dirs=asc,desc --filter FILTERS Filters. can be repeated. --oldest Display the executions starting from the oldest entries instead of the newest --task [TASK] Parent task execution id associated with workflow execution list. --rootsonly Return only root executions Table 91.52. Output formatter options Value Summary -f {csv,json,table,value,yaml}, --format {csv,json,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns --sort-column SORT_COLUMN Specify the column(s) to sort the data (columns specified first have a priority, non-existing columns are ignored), can be repeated --sort-ascending Sort the column(s) in ascending order --sort-descending Sort the column(s) in descending order Table 91.53. CSV formatter options Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 91.54. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.55. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.14. workflow execution output show Show execution output data. Usage: Table 91.56. Positional arguments Value Summary id Execution id Table 91.57. Command arguments Value Summary -h, --help Show this help message and exit 91.15. workflow execution published show Show workflow global published variables. Usage: Table 91.58. Positional arguments Value Summary id Workflow id Table 91.59. Command arguments Value Summary -h, --help Show this help message and exit 91.16. workflow execution report show Print execution report. Usage: Table 91.60. Positional arguments Value Summary id Execution id Table 91.61. Command arguments Value Summary -h, --help Show this help message and exit --errors-only Only error paths will be included. --statistics-only Only the statistics will be included. --no-errors-only Not only error paths will be included. --max-depth [MAX_DEPTH] Maximum depth of the workflow execution tree. if 0, only the root workflow execution and its tasks will be included 91.17. workflow execution show Show specific execution. Usage: Table 91.62. Positional arguments Value Summary execution Execution identifier Table 91.63. Command arguments Value Summary -h, --help Show this help message and exit Table 91.64. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.65. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.66. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.67. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.18. workflow execution update Update execution. Usage: Table 91.68. Positional arguments Value Summary id Execution identifier Table 91.69. Command arguments Value Summary -h, --help Show this help message and exit -s {RUNNING,PAUSED,SUCCESS,ERROR,CANCELLED}, --state {RUNNING,PAUSED,SUCCESS,ERROR,CANCELLED} Execution state -e ENV, --env ENV Environment variables -d DESCRIPTION, --description DESCRIPTION Execution description Table 91.70. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.71. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.72. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.73. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.19. workflow list List all workflows. Usage: Table 91.74. Command arguments Value Summary -h, --help Show this help message and exit --marker [MARKER] The last execution uuid of the page, displays list of executions after "marker". --limit [LIMIT] Maximum number of entries to return in a single result. --sort_keys [SORT_KEYS] Comma-separated list of sort keys to sort results by. Default: created_at. Example: mistral execution-list --sort_keys=id,description --sort_dirs [SORT_DIRS] Comma-separated list of sort directions. default: asc. Example: mistral execution-list --sort_keys=id,description --sort_dirs=asc,desc --filter FILTERS Filters. can be repeated. Table 91.75. Output formatter options Value Summary -f {csv,json,table,value,yaml}, --format {csv,json,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns --sort-column SORT_COLUMN Specify the column(s) to sort the data (columns specified first have a priority, non-existing columns are ignored), can be repeated --sort-ascending Sort the column(s) in ascending order --sort-descending Sort the column(s) in descending order Table 91.76. CSV formatter options Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 91.77. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.78. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.20. workflow show Show specific workflow. Usage: Table 91.79. Positional arguments Value Summary workflow Workflow id or name. Table 91.80. Command arguments Value Summary -h, --help Show this help message and exit --namespace [NAMESPACE] Namespace to get the workflow from. Table 91.81. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.82. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.83. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.84. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.21. workflow update Update workflow. Usage: Table 91.85. Positional arguments Value Summary definition Workflow definition Table 91.86. Command arguments Value Summary -h, --help Show this help message and exit --marker [MARKER] The last execution uuid of the page, displays list of executions after "marker". --limit [LIMIT] Maximum number of entries to return in a single result. --sort_keys [SORT_KEYS] Comma-separated list of sort keys to sort results by. Default: created_at. Example: mistral execution-list --sort_keys=id,description --sort_dirs [SORT_DIRS] Comma-separated list of sort directions. default: asc. Example: mistral execution-list --sort_keys=id,description --sort_dirs=asc,desc --filter FILTERS Filters. can be repeated. --id ID Workflow id. --namespace [NAMESPACE] Namespace of the workflow. --public With this flag workflow will be marked as "public". Table 91.87. Output formatter options Value Summary -f {csv,json,table,value,yaml}, --format {csv,json,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns --sort-column SORT_COLUMN Specify the column(s) to sort the data (columns specified first have a priority, non-existing columns are ignored), can be repeated --sort-ascending Sort the column(s) in ascending order --sort-descending Sort the column(s) in descending order Table 91.88. CSV formatter options Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 91.89. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.90. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 91.22. workflow validate Validate workflow. Usage: Table 91.91. Positional arguments Value Summary definition Workflow definition file Table 91.92. Command arguments Value Summary -h, --help Show this help message and exit Table 91.93. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 91.94. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 91.95. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 91.96. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show.	[ "openstack workflow create [-h] [-f {csv,json,table,value,yaml}] [-c COLUMN] [--quote {all,minimal,none,nonnumeric}] [--noindent] [--max-width <integer>] [--fit-width] [--print-empty] [--sort-column SORT_COLUMN] [--sort-ascending \| --sort-descending] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS] [--namespace [NAMESPACE]] [--public] definition", "openstack workflow definition show [-h] [--namespace [NAMESPACE]] identifier", "openstack workflow delete [-h] [--namespace [NAMESPACE]] workflow [workflow ...]", "openstack workflow engine service list [-h] [-f {csv,json,table,value,yaml}] [-c COLUMN] [--quote {all,minimal,none,nonnumeric}] [--noindent] [--max-width <integer>] [--fit-width] [--print-empty] [--sort-column SORT_COLUMN] [--sort-ascending \| --sort-descending] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS]", "openstack workflow env create [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] file", "openstack workflow env delete [-h] environment [environment ...]", "openstack workflow env list [-h] [-f {csv,json,table,value,yaml}] [-c COLUMN] [--quote {all,minimal,none,nonnumeric}] [--noindent] [--max-width <integer>] [--fit-width] [--print-empty] [--sort-column SORT_COLUMN] [--sort-ascending \| --sort-descending] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS]", "openstack workflow env show [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] [--export] environment", "openstack workflow env update [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] file", "openstack workflow execution create [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] [--namespace [NAMESPACE]] [-d DESCRIPTION] [-s [SOURCE_EXECUTION_ID]] [workflow_identifier] [workflow_input] [params]", "openstack workflow execution delete [-h] [--force] execution [execution ...]", "openstack workflow execution input show [-h] id", "openstack workflow execution list [-h] [-f {csv,json,table,value,yaml}] [-c COLUMN] [--quote {all,minimal,none,nonnumeric}] [--noindent] [--max-width <integer>] [--fit-width] [--print-empty] [--sort-column SORT_COLUMN] [--sort-ascending \| --sort-descending] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS] [--oldest] [--task [TASK]] [--rootsonly]", "openstack workflow execution output show [-h] id", "openstack workflow execution published show [-h] id", "openstack workflow execution report show [-h] [--errors-only] [--statistics-only] [--no-errors-only] [--max-depth [MAX_DEPTH]] id", "openstack workflow execution show [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] execution", "openstack workflow execution update [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] [-s {RUNNING,PAUSED,SUCCESS,ERROR,CANCELLED}] [-e ENV] [-d DESCRIPTION] id", "openstack workflow list [-h] [-f {csv,json,table,value,yaml}] [-c COLUMN] [--quote {all,minimal,none,nonnumeric}] [--noindent] [--max-width <integer>] [--fit-width] [--print-empty] [--sort-column SORT_COLUMN] [--sort-ascending \| --sort-descending] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS]", "openstack workflow show [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] [--namespace [NAMESPACE]] workflow", "openstack workflow update [-h] [-f {csv,json,table,value,yaml}] [-c COLUMN] [--quote {all,minimal,none,nonnumeric}] [--noindent] [--max-width <integer>] [--fit-width] [--print-empty] [--sort-column SORT_COLUMN] [--sort-ascending \| --sort-descending] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS] [--id ID] [--namespace [NAMESPACE]] [--public] definition", "openstack workflow validate [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] definition" ]	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/17.1/html/command_line_interface_reference/workflow
Chapter 18. Common administrative networking tasks	Chapter 18. Common administrative networking tasks Sometimes you might need to perform administration tasks on the Red Hat OpenStack Platform Networking service (neutron) such as configuring the Layer 2 Population driver or specifying the name assigned to ports by the internal DNS. 18.1. Configuring the L2 population driver The L2 Population driver enables broadcast, multicast, and unicast traffic to scale out on large overlay networks. By default, Open vSwitch GRE and VXLAN replicate broadcasts to every agent, including those that do not host the destination network. This design requires the acceptance of significant network and processing overhead. The alternative design introduced by the L2 Population driver implements a partial mesh for ARP resolution and MAC learning traffic; it also creates tunnels for a particular network only between the nodes that host the network. This traffic is sent only to the necessary agent by encapsulating it as a targeted unicast. To enable the L2 Population driver, complete the following steps: 1. Enable the L2 population driver by adding it to the list of mechanism drivers. You also must enable at least one tunneling driver: either GRE, VXLAN, or both. Add the appropriate configuration options to the ml2_conf.ini file: Note Neutron's Linux Bridge ML2 driver and agent were deprecated in Red Hat OpenStack Platform 11. The Open vSwitch (OVS) plugin OpenStack Platform director default, and is recommended by Red Hat for general usage. 2. Enable L2 population in the openvswitch_agent.ini file. Enable it on each node that contains the L2 agent: Note To install ARP reply flows, configure the arp_responder flag: 18.2. Tuning keepalived to avoid VRRP packet loss If the number of highly available (HA) routers on a single host is high, when an HA router fail over occurs, the Virtual Router Redundancy Protocol (VRRP) messages might overflow the IRQ queues. This overflow stops Open vSwitch (OVS) from responding and forwarding those VRRP messages. To avoid VRRP packet overload, you must increase the VRRP advertisement interval using the ha_vrrp_advert_int parameter in the ExtraConfig section for the Controller role. Procedure Log in to the undercloud as the stack user, and source the stackrc file to enable the director command line tools. Example Create a custom YAML environment file. Example Tip The Red Hat OpenStack Platform Orchestration service (heat) uses a set of plans called templates to install and configure your environment. You can customize aspects of the overcloud with a custom environment file , which is a special type of template that provides customization for your heat templates. In the YAML environment file, increase the VRRP advertisement interval using the ha_vrrp_advert_int argument with a value specific for your site. (The default is 2 seconds.) You can also set values for gratuitous ARP messages: ha_vrrp_garp_master_repeat The number of gratuitous ARP messages to send at one time after the transition to the master state. (The default is 5 messages.) ha_vrrp_garp_master_delay The delay for second set of gratuitous ARP messages after the lower priority advert is received in the master state. (The default is 5 seconds.) Example Run the openstack overcloud deploy command and include the core heat templates, environment files, and this new custom environment file. Important The order of the environment files is important because the parameters and resources defined in subsequent environment files take precedence. Example Additional resources 2.1.2 Data Forwarding Rules, Subsection 2 in RFC 4541 Environment files in the Director Installation and Usage guide Including environment files in overcloud creation in the Director Installation and Usage guide 18.3. Specifying the name that DNS assigns to ports You can specify the name assigned to ports by the internal DNS when you enable the Red Hat OpenStack Platform (RHOSP) Networking service (neutron) dns_domain for ports extension ( dns_domain_ports ). You enable the dns_domain for ports extension by declaring the RHOSP Orchestration (heat) NeutronPluginExtensions parameter in a YAML-formatted environment file. Using a corresponding parameter, NeutronDnsDomain , you specify your domain name, which overrides the default value, openstacklocal . After redeploying your overcloud, you can use the OpenStack Client port commands, port set or port create , with --dns-name to assign a port name. Also, when the dns_domain for ports extension is enabled, the Compute service automatically populates the dns_name attribute with the hostname attribute of the instance during the boot of VM instances. At the end of the boot process, dnsmasq recognizes the allocated ports by their instance hostname. Procedure Log in to the undercloud as the stack user, and source the stackrc file to enable the director command line tools. Example Create a custom YAML environment file ( my-neutron-environment.yaml ). Note Values inside parentheses are sample values that are used in the example commands in this procedure. Substitute these sample values with ones that are appropriate for your site. Example Tip The undercloud includes a set of Orchestration service templates that form the plan for your overcloud creation. You can customize aspects of the overcloud with environment files, which are YAML-formatted files that override parameters and resources in the core Orchestration service template collection. You can include as many environment files as necessary. In the environment file, add a parameter_defaults section. Under this section, add the dns_domain for ports extension, dns_domain_ports . Example Note If you set dns_domain_ports , ensure that the deployment does not also use dns_domain , the DNS Integration extension. These extensions are incompatible, and both extensions cannot be defined simultaneously. Also in the parameter_defaults section, add your domain name ( example.com ) using the NeutronDnsDomain parameter. Example Run the openstack overcloud deploy command and include the core Orchestration templates, environment files, and this new environment file. Important The order of the environment files is important because the parameters and resources defined in subsequent environment files take precedence. Example Verification Log in to the overcloud, and create a new port ( new_port ) on a network ( public ). Assign a DNS name ( my_port ) to the port. Example Display the details for your port ( new_port ). Example Output Under dns_assignment , the fully qualified domain name ( fqdn ) value for the port contains a concatenation of the DNS name ( my_port ) and the domain name ( example.com ) that you set earlier with NeutronDnsDomain . Create a new VM instance ( my_vm ) using the port ( new_port ) that you just created. Example Display the details for your port ( new_port ). Example Output Note that the Compute service changes the dns_name attribute from its original value ( my_port ) to the name of the instance with which the port is associated ( my_vm ). Additional resources Environment files in the Director Installation and Usage guide Including environment files in overcloud creation in the Director Installation and Usage guide port in the Command Line Interface Reference server create in the Command Line Interface Reference 18.4. Assigning DHCP attributes to ports You can use Red Hat Openstack Plaform (RHOSP) Networking service (neutron) extensions to add networking functions. You can use the extra DHCP option extension ( extra_dhcp_opt ) to configure ports of DHCP clients with DHCP attributes. For example, you can add a PXE boot option such as tftp-server , server-ip-address , or bootfile-name to a DHCP client port. The value of the extra_dhcp_opt attribute is an array of DHCP option objects, where each object contains an opt_name and an opt_value . IPv4 is the default version, but you can change this to IPv6 by including a third option, ip-version=6 . When a VM instance starts, the RHOSP Networking service supplies port information to the instance using DHCP protocol. If you add DHCP information to a port already connected to a running instance, the instance only uses the new DHCP port information when the instance is restarted. Some of the more common DHCP port attributes are: bootfile-name , dns-server , domain-name , mtu , server-ip-address , and tftp-server . For the complete set of acceptable values for opt_name , refer to the DHCP specification. Prerequisites You must have RHOSP administrator privileges. Procedure Log in to the undercloud host as the stack user. Source the undercloud credentials file: Create a custom YAML environment file. Example Your environment file must contain the keywords parameter_defaults . Under these keywords, add the extra DHCP option extension, extra_dhcp_opt . Example Run the deployment command and include the core heat templates, environment files, and this new custom environment file. Important The order of the environment files is important because the parameters and resources defined in subsequent environment files take precedence. Example Verification Source your credentials file. Example Create a new port ( new_port ) on a network ( public ). Assign a valid attribute from the DHCP specification to the new port. Example Display the details for your port ( new_port ). Example Sample output Additional resources OVN supported DHCP options Dynamic Host Configuration Protocol (DHCP) and Bootstrap Protocol (BOOTP) Parameters Environment files in the Director Installation and Usage guide Including environment files in overcloud creation in the Director Installation and Usage guide port create in the Command Line Interface Reference port show in the Command Line Interface Reference 18.5. Enabling NUMA affinity on ports To enable users to create instances with NUMA affinity on the port, you must load the Red Hat Openstack Plaform (RHOSP) Networking service (neutron) extension, port_numa_affinity_policy . Prerequisites Access to the undercloud host and credentials for the stack user. Procedure Log in to the undercloud host as the stack user. Source the undercloud credentials file: To enable the port_numa_affinity_policy extension, open the environment file where the NeutronPluginExtensions parameter is defined, and add port_numa_affinity_policy to the list: Add the environment file that you modified to the stack with your other environment files, and redeploy the overcloud: Important The order of the environment files is important because the parameters and resources defined in subsequent environment files take precedence. Verification Source your credentials file. Example Create a new port. When you create a port, use one of the following options to specify the NUMA affinity policy to apply to the port: --numa-policy-required - NUMA affinity policy required to schedule this port. --numa-policy-preferred - NUMA affinity policy preferred to schedule this port. --numa-policy-legacy - NUMA affinity policy using legacy mode to schedule this port. Example Display the details for your port. Example Sample output When the extension is loaded, the Value column should read, legacy , preferred or required . If the extension has failed to load, Value reads None : Additional resources Environment files in the Director Installation and Usage guide Including environment files in overcloud creation in the Director Installation and Usage guide Creating an instance with NUMA affinity on the port in the Creating and Managing Instances guide 18.6. Loading kernel modules Some features in Red Hat OpenStack Platform (RHOSP) require certain kernel modules to be loaded. For example, the OVS firewall driver requires you to load the nf_conntrack_proto_gre kernel module to support GRE tunneling between two VM instances. By using a special Orchestration service (heat) parameter, ExtraKernelModules , you can ensure that heat stores configuration information about the required kernel modules needed for features like GRE tunneling. Later, during normal module management, these required kernel modules are loaded. Procedure On the undercloud host, logged in as the stack user, create a custom YAML environment file. Example Tip Heat uses a set of plans called templates to install and configure your environment. You can customize aspects of the overcloud with a custom environment file , which is a special type of template that provides customization for your heat templates. In the YAML environment file under parameter_defaults , set ExtraKernelModules to the name of the module that you want to load. Example Run the openstack overcloud deploy command and include the core heat templates, environment files, and this new custom environment file. Important The order of the environment files is important as the parameters and resources defined in subsequent environment files take precedence. Example Verification If heat has properly loaded the module, you should see output when you run the lsmod command on the Compute node: Example Additional resources Environment files in the Director Installation and Usage guide Including environment files in overcloud creation in the Director Installation and Usage guide 18.7. Configuring shared security groups When you want one or more Red Hat OpenStack Platform (RHOSP) projects to be able to share data, you can use the RHOSP Networking service (neutron) RBAC policy feature to share a security group. You create security groups and Networking service role-based access control (RBAC) policies using the OpenStack Client. You can apply a security group directly to an instance during instance creation, or to a port on the running instance. Note You cannot apply a role-based access control (RBAC)-shared security group directly to an instance during instance creation. To apply an RBAC-shared security group to an instance you must first create the port, apply the shared security group to that port, and then assign that port to the instance. See Adding a security group to a port . Prerequisites You have at least two RHOSP projects that you want to share. In one of the projects, the current project , you have created a security group that you want to share with another project, the target project . In this example, the ping_ssh security group is created: Example Procedure Log in to the overcloud for the current project that contains the security group. Obtain the name or ID of the target project. Obtain the name or ID of the security group that you want to share between RHOSP projects. Using the identifiers from the steps, create an RBAC policy using the openstack network rbac create command. In this example, the ID of the target project is 32016615de5d43bb88de99e7f2e26a1e . The ID of the security group is 5ba835b7-22b0-4be6-bdbe-e0722d1b5f24 : Example --target-project specifies the project that requires access to the security group. Tip You can share data between all projects by using the --target-all-projects argument instead of --target-project <target-project> . By default, only the admin user has this privilege. --action access_as_shared specifies what the project is allowed to do. --type indicates that the target object is a security group. 5ba835b7-22b0-4be6-bdbe-e0722d1b5f24 is the ID of the particular security group which is being granted access to. The target project is able to access the security group when running the OpenStack Client security group commands, in addition to being able to bind to its ports. No other users (other than administrators and the owner) are able to access the security group. Tip To remove access for the target project, delete the RBAC policy that allows it using the openstack network rbac delete command. Additional resources Creating a security group in the Creating and Managing Instances guide security group create in the Command Line Interface Reference network rbac create in the Command Line Interface Reference	[ "[ml2] type_drivers = local,flat,vlan,gre,vxlan,geneve mechanism_drivers = l2population", "[agent] l2_population = True", "[agent] l2_population = True arp_responder = True", "source ~/stackrc", "vi /home/stack/templates/my-neutron-environment.yaml", "parameter_defaults: ControllerExtraConfig: neutron::agents::l3::ha_vrrp_advert_int: 7 neutron::config::l3_agent_config: DEFAULT/ha_vrrp_garp_master_repeat: value: 5 DEFAULT/ha_vrrp_garp_master_delay: value: 5", "openstack overcloud deploy --templates -e [your-environment-files] -e /usr/share/openstack-tripleo-heat-templates/environments/services/my-neutron-environment.yaml", "source ~/stackrc", "vi /home/stack/templates/my-neutron-environment.yaml", "parameter_defaults: NeutronPluginExtensions: \"qos,port_security,dns_domain_ports\"", "parameter_defaults: NeutronPluginExtensions: \"qos,port_security,dns_domain_ports\" NeutronDnsDomain: \"example.com\"", "openstack overcloud deploy --templates -e [your-environment-files] -e /usr/share/openstack-tripleo-heat-templates/environments/services/my-neutron-environment.yaml", "source ~/overcloudrc openstack port create --network public --dns-name my_port new_port", "openstack port show -c dns_assignment -c dns_domain -c dns_name -c name new_port", "+-------------------------+----------------------------------------------+ \| Field \| Value \| +-------------------------+----------------------------------------------+ \| dns_assignment \| fqdn='my_port.example.com', \| \| \| hostname='my_port', \| \| \| ip_address='10.65.176.113' \| \| dns_domain \| example.com \| \| dns_name \| my_port \| \| name \| new_port \| +-------------------------+----------------------------------------------+", "openstack server create --image rhel --flavor m1.small --port new_port my_vm", "openstack port show -c dns_assignment -c dns_domain -c dns_name -c name new_port", "+-------------------------+----------------------------------------------+ \| Field \| Value \| +-------------------------+----------------------------------------------+ \| dns_assignment \| fqdn='my_vm.example.com', \| \| \| hostname='my_vm', \| \| \| ip_address='10.65.176.113' \| \| dns_domain \| example.com \| \| dns_name \| my_vm \| \| name \| new_port \| +-------------------------+----------------------------------------------+", "source ~/stackrc", "vi /home/stack/templates/my-octavia-environment.yaml", "parameter_defaults: NeutronPluginExtensions: \"qos,port_security,extra_dhcp_opt\"", "openstack overcloud deploy --templates -e <your_environment_files> -e /usr/share/openstack-tripleo-heat-templates/environments/services/octavia.yaml -e /home/stack/templates/my-octavia-environment.yaml", "source ~/overcloudrc", "openstack port create --extra-dhcp-option name=domain-name,value=test.domain --extra-dhcp-option name=ntp-server,value=192.0.2.123 --network public new_port", "openstack port show new_port -c extra_dhcp_opts", "+-----------------+-----------------------------------------------------------------+ \| Field \| Value \| +-----------------+-----------------------------------------------------------------+ \| extra_dhcp_opts \| ip_version='4', opt_name='domain-name', opt_value='test.domain' \| \| \| ip_version='4', opt_name='ntp-server', opt_value='192.0.2.123' \| +-----------------+-----------------------------------------------------------------+", "source ~/stackrc", "parameter_defaults: NeutronPluginExtensions: \"qos,port_numa_affinity_policy\"", "openstack overcloud deploy --templates -e <your_environment_files> -e /home/stack/templates/<custom_environment_file>.yaml", "source ~/overcloudrc", "openstack port create --network public --numa-policy-legacy myNUMAAffinityPort", "openstack port show myNUMAAffinityPort -c numa_affinity_policy", "+----------------------+--------+ \| Field \| Value \| +----------------------+--------+ \| numa_affinity_policy \| legacy \| +----------------------+--------+", "vi /home/stack/templates/my-modules-environment.yaml", "ComputeParameters: ExtraKernelModules: nf_conntrack_proto_gre: {} ControllerParameters: ExtraKernelModules: nf_conntrack_proto_gre: {}", "openstack overcloud deploy --templates -e [your-environment-files] -e /usr/share/openstack-tripleo-heat-templates/environments/services/my-modules-environment.yaml", "sudo lsmod \| grep nf_conntrack_proto_gre", "openstack security group create ping_ssh", "openstack project list", "openstack security group list", "openstack network rbac create --target-project 32016615de5d43bb88de99e7f2e26a1e --action access_as_shared --type security_group 5ba835b7-22b0-4be6-bdbe-e0722d1b5f24" ]	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/17.0/html/networking_guide/common-network-tasks_rhosp-network
Developing C and C++ applications in RHEL 8	Developing C and C++ applications in RHEL 8 Red Hat Enterprise Linux 8 Setting up a developer workstation, and developing and debugging C and C++ applications in Red Hat Enterprise Linux 8 Red Hat Customer Content Services	[ "subscription-manager repos --enable rhel-8-for-USD(uname -i)-baseos-debug-rpms subscription-manager repos --enable rhel-8-for-USD(uname -i)-baseos-source-rpms subscription-manager repos --enable rhel-8-for-USD(uname -i)-appstream-debug-rpms subscription-manager repos --enable rhel-8-for-USD(uname -i)-appstream-source-rpms", "yum install git", "git config --global user.name \" Full Name \" git config --global user.email \" [email protected] \"", "git config --global core.editor command", "man git man gittutorial man gittutorial-2", "yum group install \"Development Tools\"", "yum install llvm-toolset", "yum install gcc-gfortran", "yum install gdb valgrind systemtap ltrace strace", "yum install yum-utils", "stap-prep", "yum install perf papi pcp-zeroconf valgrind strace sysstat systemtap", "stap-prep", "systemctl enable pmcd && systemctl start pmcd", "man gcc", "gcc -c source.c another_source.c", "gcc ... -g", "man gcc", "man gcc", "gcc ... -O2 -g -Wall -Wl,-z,now,-z,relro -fstack-protector-strong -fstack-clash-protection -D_FORTIFY_SOURCE=2", "gcc ... -Walloc-zero -Walloca-larger-than -Wextra -Wformat-security -Wvla-larger-than", "gcc ... objfile.o another_object.o ... -o executable-file", "mkdir hello-c cd hello-c", "#include <stdio.h> int main() { printf(\"Hello, World!\\n\"); return 0; }", "gcc hello.c -o helloworld", "./helloworld Hello, World!", "mkdir hello-c cd hello-c", "#include <stdio.h> int main() { printf(\"Hello, World!\\n\"); return 0; }", "gcc -c hello.c", "gcc hello.o -o helloworld", "./helloworld Hello, World!", "mkdir hello-cpp cd hello-cpp", "#include <iostream> int main() { std::cout << \"Hello, World!\\n\"; return 0; }", "g++ hello.cpp -o helloworld", "./helloworld Hello, World!", "mkdir hello-cpp cd hello-cpp", "#include <iostream> int main() { std::cout << \"Hello, World!\\n\"; return 0; }", "g++ -c hello.cpp", "g++ hello.o -o helloworld", "./helloworld Hello, World!", "gcc ... -l foo", "gcc ... -I include_path", "gcc ... -L library_path -l foo", "gcc ... -I header_path -c", "gcc ... -L library_path -l foo", "./program", "gcc ... -L library_path -l foo", "gcc ... -L library_path -l foo -Wl,-rpath= library_path", "./program", "export LD_LIBRARY_PATH= library_path :USDLD_LIBRARY_PATH ./program", "man ld.so", "cat /etc/ld.so.conf", "ldconfig -v", "gcc ... path/to/libfoo.a", "gcc ... -Wl,-Bstatic -l first -Wl,-Bdynamic -l second", "gcc ... -l foo", "objdump -p somelibrary \| grep SONAME", "gcc ... -c -fPIC some_file.c", "gcc -shared -o libfoo.so.x.y -Wl,-soname, libfoo.so.x some_file.o", "cp libfoo.so.x.y /usr/lib64", "ln -s libfoo.so.x.y libfoo.so.x ln -s libfoo.so.x libfoo.so", "gcc -c source_file.c", "ar rcs lib foo .a source_file.o", "nm libfoo.a", "gcc ... -l foo", "man ar", "all: hello hello: hello.o gcc hello.o -o hello hello.o: hello.c gcc -c hello.c -o hello.o", "CC=gcc CFLAGS=-c -Wall SOURCE=hello.c OBJ=USD(SOURCE:.c=.o) EXE=hello all: USD(SOURCE) USD(EXE) USD(EXE): USD(OBJ) USD(CC) USD(OBJ) -o USD@ %.o: %.c USD(CC) USD(CFLAGS) USD< -o USD@ clean: rm -rf USD(OBJ) USD(EXE)", "mkdir hellomake cd hellomake", "#include <stdio.h> int main(int argc, char argv[]) { printf(\"Hello, World!\\n\"); return 0; }", "CC=gcc CFLAGS=-c -Wall SOURCE=hello.c OBJ=USD(SOURCE:.c=.o) EXE=hello all: USD(SOURCE) USD(EXE) USD(EXE): USD(OBJ) USD(CC) USD(OBJ) -o USD@ %.o: %.c USD(CC) USD(CFLAGS) USD< -o USD@ clean: rm -rf USD(OBJ) USD(EXE)", "make gcc -c -Wall hello.c -o hello.o gcc hello.o -o hello", "./hello Hello, World!", "make clean rm -rf hello.o hello", "man make info make", "man gcc", "gcc ... -g", "man gcc", "gdb -q /bin/ls Reading symbols from /bin/ls...Reading symbols from .gnu_debugdata for /usr/bin/ls...(no debugging symbols found)...done. (no debugging symbols found)...done. Missing separate debuginfos, use: dnf debuginfo-install coreutils-8.30-6.el8.x86_64 (gdb)", "(gdb) q", "dnf debuginfo-install coreutils-8.30-6.el8.x86_64", "which less /usr/bin/less", "locate libz \| grep so /usr/lib64/libz.so.1 /usr/lib64/libz.so.1.2.11", "yum install mlocate updatedb", "rpm -qf /usr/lib64/libz.so.1.2.7 zlib-1.2.11-10.el8.x86_64", "debuginfo-install zlib-1.2.11-10.el8.x86_64", "gdb program", "ps -C program -o pid h pid", "gdb -p pid", "(gdb) shell ps -C program -o pid h pid", "(gdb) attach pid", "(gdb) file path/to/program", "(gdb) help info", "(gdb) br file:line", "(gdb) br line", "(gdb) br function_name", "(gdb) br file:line if condition", "(gdb) info br", "(gdb) delete number", "(gdb) clear file:line", "(gdb) watch expression", "(gdb) rwatch expression", "(gdb) awatch expression", "(gdb) info br", "(gdb) delete num", "strace -fvttTyy -s 256 -e trace= call program", "ps -C program (...) strace -fvttTyy -s 256 -e trace= call -p pid", "strace ... \|& tee your_log_file.log", "man strace", "ltrace -f -l library -e function program", "ps -C program (...) ltrace -f -l library -e function program -p pid", "ltrace ... \|& tee your_log_file.log", "man ltrace", "ps -aux", "stap /usr/share/systemtap/examples/process/strace.stp -x pid", "(gdb) catch syscall syscall-name", "(gdb) r", "(gdb) c", "(gdb) catch signal signal-type", "(gdb) r", "(gdb) c", "ulimit -a", "DumpCore=yes DefaultLimitCORE=infinity", "systemctl daemon-reexec", "ulimit -c unlimited", "yum install sos", "sosreport", "coredumpctl list executable-name coredumpctl dump executable-name > /path/to/file-for-export", "eu-unstrip -n --core= ./core.9814 0x400000+0x207000 2818b2009547f780a5639c904cded443e564973e@0x400284 /usr/bin/sleep /usr/lib/debug/bin/sleep.debug [exe] 0x7fff26fff000+0x1000 1e2a683b7d877576970e4275d41a6aaec280795e@0x7fff26fff340 . - linux-vdso.so.1 0x35e7e00000+0x3b6000 374add1ead31ccb449779bc7ee7877de3377e5ad@0x35e7e00280 /usr/lib64/libc-2.14.90.so /usr/lib/debug/lib64/libc-2.14.90.so.debug libc.so.6 0x35e7a00000+0x224000 3ed9e61c2b7e707ce244816335776afa2ad0307d@0x35e7a001d8 /usr/lib64/ld-2.14.90.so /usr/lib/debug/lib64/ld-2.14.90.so.debug ld-linux-x86-64.so.2", "eu-readelf -n executable_file", "gdb -e executable_file -c core_file", "(gdb) symbol-file program.debug", "sysctl kernel.core_pattern", "kernel.core_pattern = \|/usr/lib/systemd/systemd-coredump", "pgrep -a executable-name-fragment", "PID command-line", "pgrep -a bc 5459 bc", "kill -ABRT PID", "coredumpctl list PID", "coredumpctl list 5459 TIME PID UID GID SIG COREFILE EXE Thu 2019-11-07 15:14:46 CET 5459 1000 1000 6 present /usr/bin/bc", "coredumpctl info PID", "coredumpctl debug PID", "Missing separate debuginfos, use: dnf debuginfo-install bc-1.07.1-5.el8.x86_64", "coredumpctl dump PID > /path/to/file_for_export", "ps -C some-program", "gcore -o filename pid", "sosreport", "(gdb) set use-coredump-filter off", "(gdb) set dump-excluded-mappings on", "(gdb) gcore core-file", "gdbserver --multi :1234 gdb -batch -ex 'target extended-remote :1234' -ex 'set remote exec-file /bin/echo' -ex 'file /bin/echo' -ex 'run /' /", "gdbserver --multi :1234 gdb -batch -ex 'target extended-remote :1234' -ex 'set remote exec-file /bin/echo' -ex 'file /bin/echo' -ex 'run /' /bin /boot (...) /tmp /usr /var", "(gdb) maintenance print symbols /tmp/out main.c", "maint print symbols [-pc address ] [--] [ filename ] maint print symbols [-objfile objfile ] [-source source ] [--] [ filename ] maint print psymbols [-objfile objfile ] [-pc address ] [--] [ filename ] maint print psymbols [-objfile objfile ] [-source source ] [--] [ filename ] maint print msymbols [-objfile objfile ] [--] [ filename ]", "debuginfo-install coreutils gdb -batch -ex 'file echo' -ex start -ex 'add-inferior' -ex 'inferior 2' -ex 'file echo' -ex start -ex 'info threads' -ex 'pring USD_thread' -ex 'inferior 1' -ex 'pring USD_thread' (...) Id Target Id Frame * 2 process 203923 \"echo\" main (argc=1, argv=0x7fffffffdb88) at src/echo.c:109 1 process 203914 \"echo\" main (argc=1, argv=0x7fffffffdb88) at src/echo.c:109 USD1 = 2 (...) USD2 = 1", "dnf debuginfo-install coreutils gdb -batch -ex 'file echo' -ex start -ex 'add-inferior' -ex 'inferior 2' -ex 'file echo' -ex start -ex 'info threads' -ex 'pring USD_thread' -ex 'inferior 1' -ex 'pring USD_thread' (...) Id Target Id Frame 1.1 process 4106488 \"echo\" main (argc=1, argv=0x7fffffffce58) at ../src/echo.c:109 * 2.1 process 4106494 \"echo\" main (argc=1, argv=0x7fffffffce58) at ../src/echo.c:109 USD1 = 1 (...) USD2 = 1", "yum install gcc-toolset- N", "yum list available gcc-toolset- N -\\", "yum install package_name", "yum install gcc-toolset-13-annobin-annocheck gcc-toolset-13-binutils-devel", "yum remove gcc-toolset- N \\", "scl enable gcc-toolset- N tool", "scl enable gcc-toolset- N bash", "scl enable gcc-toolset-9 'gcc -lsomelib objfile.o'", "scl enable gcc-toolset-9 'gcc objfile.o -lsomelib'", "scl enable gcc-toolset-9 'ld -lsomelib objfile.o'", "scl enable gcc-toolset-9 'ld objfile.o -lsomelib'", "scl enable gcc-toolset-10 'gcc -lsomelib objfile.o'", "scl enable gcc-toolset-10 'gcc objfile.o -lsomelib'", "scl enable gcc-toolset-10 'ld -lsomelib objfile.o'", "scl enable gcc-toolset-10 'ld objfile.o -lsomelib'", "scl enable gcc-toolset-11 'gcc -lsomelib objfile.o'", "scl enable gcc-toolset-11 'gcc objfile.o -lsomelib'", "scl enable gcc-toolset-11 'ld -lsomelib objfile.o'", "scl enable gcc-toolset-11 'ld objfile.o -lsomelib'", "scl enable gcc-toolset-12 'gcc -lsomelib objfile.o'", "scl enable gcc-toolset-12 'gcc objfile.o -lsomelib'", "scl enable gcc-toolset-12 'ld -lsomelib objfile.o'", "scl enable gcc-toolset-12 'ld objfile.o -lsomelib'", "cc1: fatal error: inaccessible plugin file opt/rh/gcc-toolset-12/root/usr/lib/gcc/ architecture -linux-gnu/12/plugin/gcc-annobin.so expanded from short plugin name gcc-annobin: No such file or directory", "cd /opt/rh/gcc-toolset-12/root/usr/lib/gcc/ architecture -linux-gnu/12/plugin ln -s annobin.so gcc-annobin.so", "scl enable gcc-toolset-13 'gcc -lsomelib objfile.o'", "scl enable gcc-toolset-13 'gcc objfile.o -lsomelib'", "scl enable gcc-toolset-13 'ld -lsomelib objfile.o'", "scl enable gcc-toolset-13 'ld objfile.o -lsomelib'", "cc1: fatal error: inaccessible plugin file opt/rh/gcc-toolset-13/root/usr/lib/gcc/ architecture -linux-gnu/13/plugin/gcc-annobin.so expanded from short plugin name gcc-annobin: No such file or directory", "cd /opt/rh/gcc-toolset-13/root/usr/lib/gcc/ architecture -linux-gnu/13/plugin ln -s annobin.so gcc-annobin.so", "scl enable gcc-toolset-14 'gcc -lsomelib objfile.o'", "scl enable gcc-toolset-14 'gcc objfile.o -lsomelib'", "scl enable gcc-toolset-14 'ld -lsomelib objfile.o'", "scl enable gcc-toolset-14 'ld objfile.o -lsomelib'", "cc1: fatal error: inaccessible plugin file opt/rh/gcc-toolset-14/root/usr/lib/gcc/ architecture -linux-gnu/14/plugin/gcc-annobin.so expanded from short plugin name gcc-annobin: No such file or directory", "cd /opt/rh/gcc-toolset-14/root/usr/lib/gcc/ architecture -linux-gnu/14/plugin ln -s annobin.so gcc-annobin.so", "podman login registry.redhat.io Username: username Password: ******", "podman pull registry.redhat.io/rhel8/gcc-toolset- <toolset_version> -toolchain", "podman images", "podman run -it image_name /bin/bash", "podman login registry.redhat.io Username: username Password: ******", "podman pull registry.redhat.io/rhel8/gcc-toolset-14-toolchain", "podman run -it registry.redhat.io/rhel8/gcc-toolset-14-toolchain /bin/bash", "bash-4.4USD gcc -v gcc version 14.2.1 20240801 (Red Hat 14.2.1-1) (GCC)", "bash-4.4USD rpm -qa", "gcc -fplugin=annobin", "gcc -iplugindir= /path/to/directory/containing/annobin/", "gcc --print-file-name=plugin", "clang -fplugin= /path/to/directory/containing/annobin/", "gcc -fplugin=annobin -fplugin-arg-annobin- option file-name", "gcc -fplugin=annobin -fplugin-arg-annobin-verbose file-name", "clang -fplugin= /path/to/directory/containing/annobin/ -Xclang -plugin-arg-annobin -Xclang option file-name", "clang -fplugin=/usr/lib64/clang/10/lib/annobin.so -Xclang -plugin-arg-annobin -Xclang verbose file-name", "annocheck file-name", "annocheck directory-name", "annocheck rpm-package-name", "annocheck rpm-package-name --debug-rpm debuginfo-rpm", "annocheck --enable-built-by", "annocheck --enable-notes", "annocheck --section-size= name", "annocheck --enable-notes --disable-hardened file-name", "objcopy --merge-notes file-name", "cc1: fatal error: inaccessible plugin file opt/rh/gcc-toolset-12/root/usr/lib/gcc/ architecture -linux-gnu/12/plugin/gcc-annobin.so expanded from short plugin name gcc-annobin: No such file or directory", "cd /opt/rh/gcc-toolset-12/root/usr/lib/gcc/ architecture -linux-gnu/12/plugin ln -s annobin.so gcc-annobin.so" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/8/html-single/developing_c_and_cpp_applications_in_rhel_8/index
Chapter 137. AutoRestartStatus schema reference	Chapter 137. AutoRestartStatus schema reference Used in: KafkaConnectorStatus , KafkaMirrorMaker2Status Property Property type Description count integer The number of times the connector or task is restarted. connectorName string The name of the connector being restarted. lastRestartTimestamp string The last time the automatic restart was attempted. The required format is 'yyyy-MM-ddTHH:mm:ssZ' in the UTC time zone.	null	https://docs.redhat.com/en/documentation/red_hat_streams_for_apache_kafka/2.7/html/streams_for_apache_kafka_api_reference/type-AutoRestartStatus-reference
7.138. man-pages	7.138. man-pages 7.138.1. RHBA-2013:0447 - man-pages bug fix and enhancement update An updated man-pages package that fixes numerous bugs and add two enhancements is now available for Red Hat Enterprise Linux 6. The man-pages package provides man (manual) pages from the Linux Documentation Project (LDP). Bug Fixes BZ# 714073 Prior to this update, a manual page for the fattach() function was missing. This update adds the fattach(2) manual page. BZ# 714074 Prior to this update, a manual page for the recvmmsg() call was missing. This update adds the recvmmsg(2) manual page. BZ# 714075 Prior to this update, manual pages for the cciss and hpsa utilities were missing. This update adds the cciss(4) and hpsa(4) manual pages. BZ# 714078 The host.conf(5) manual page contained a description for the unsupported order keyword. This update removes the incorrect description. BZ# 735789 Prior to this update, the clock_gettime(2) , clock_getres(2) , and clock_nanosleep(2) manual pages did not mention the -lrt option. With this update, the description of the -lrt option has been added to the aforementioned manual pages. BZ# 745152 This update adds the description of the single-request-reopen to the resolv.conf(5) manual page. BZ# 745501 With this update, usage of SSSD in the nsswitch.conf file is now described in the nsswitch.conf(5) manual page. BZ# 745521 With this update, the new UMOUNT_NOFOLLOW flag is described in the umount(2) manual page. BZ#745733 Previously, a manual page for the sendmmsg() function was missing. This update adds the sendmmsg(2) manual page. BZ# 752778 Previously, the db(3) manual page was pointing to the non-existent dbopen(3) manual page. When the man db command was issued, the following error message was returned: With this update, the db(3) manual page is removed. BZ#771540 This update adds the missing description of the TCP_CONGESTION socket option to the tcp(7) manual page. BZ# 804003 Descriptions of some socket options were missing in the ip(7) manual page. This update adds these descriptions to the ip(7) manual page. BZ#809564 Prior to this update, the shmat(2) manual page was missing the description for the EIDRM error code. With this update, this description has been added to the shmat(2) manual page. BZ# 822317 The bdflush(2) system call manual page was missing information that this system call is obsolete. This update adds this information to the bdflush(2) manual page. BZ#835679 The nscd.conf(5) manual page was not listing " services " among valid services. With this update, " services " are listed in the nscd.conf(5) manual page as expected. BZ#840791 Previously, the nsswitch.conf(5) manual page lacked information on the search mechanism, particularly about the notfound status. This update provides an improved manual page with added description of notfound . BZ#840796 Prior to this update, the behavior of the connect() call with the local address set to the INADDR_ANY wildcard address was insufficiently described in the ip(7) manual page. Possible duplication of the local port after the call was not acknowledged. With this update, the documentation has been reworked in order to reflect the behavior of the connect() call correctly. BZ#840798 Due to the vague description of the getdents() function in the getdents(2) manual page, the risk of using this function directly was not clear enough. The description has been extended with a warning to prevent incorrect usage of the getdents() function. BZ#840805 The nscd.conf(5) manual page was missing descriptions and contained several duplicate entries. With this update, the text has been clarified and redundant entries have been removed. BZ#857163 Previously, the tzset(3) manual page contained an incorrect interval in the description of the start and end format for Daylight Saving Time. Consequently, users thought the number was 1-based rather than 0-based when not using the J option. With this update, the manual page has been corrected. The Julian day can be specified with an interval of 0 to 365 and February 29 is counted in leap years when the J option is not used. BZ# 857962 The description of the /proc/sys/fs/file-nr file in the proc(5) manual page was outdated. This update adds the current information to this manual page. BZ# 858278 The connect(2) manual page in the Error section listed EAGAIN error code instead of EADDRNOTAVAIL error code. This update amends the manual page with correct information. Enhancements BZ# 857162 An update in the close(2) man page explains the interaction between system calls close() and recv() in different threads. BZ# 858240 This update adds the description of the --version switch to the zdump(8) manual page. All users of man-pages are advised to upgrade to this updated package, which fixes these bugs and add these enhancements.	[ "fopen: No such file or directory." ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.4_technical_notes/man-pages
1.5. Starting and Stopping a Directory Server Instance	1.5. Starting and Stopping a Directory Server Instance 1.5.1. Starting and Stopping a Directory Server Instance Using the Command Line Use the dsctl utility to start, stop, or restart an instance: To start the instance: To stop the instance: To restart the instance: Optionally, you can enable Directory Server instances to automatically start when the system boots: For a single instance: For all instances on a server: For further details, see the Managing System Services section in the Red Hat System Administrator's Guide . 1.5.2. Starting and Stopping a Directory Server Instance Using the Web Console As an alternative to command line, you can use the web console to start, stop, or restart instances. To start, stop, or restart a Directory Server instance: Open the Directory Server user interface in the web console. See Section 1.4, "Logging Into Directory Server Using the Web Console" . Select the instance. Click the Actions button and select the action to execute: Start Instance Stop Instance Restart Instance	[ "dsctl instance_name start", "dsctl instance_name stop", "dsctl instance_name restart", "systemctl enable dirsrv@ instance_name", "systemctl enable dirsrv.target" ]	https://docs.redhat.com/en/documentation/red_hat_directory_server/11/html/administration_guide/starting_and_stopping-ds
Providing Feedback on Red Hat Documentation	Providing Feedback on Red Hat Documentation We appreciate your input on our documentation. Please let us know how we could make it better. You can submit feedback by filing a ticket in Bugzilla: Navigate to the Bugzilla website. In the Component field, use Documentation . In the Description field, enter your suggestion for improvement. Include a link to the relevant parts of the documentation. Click Submit Bug .	null	https://docs.redhat.com/en/documentation/red_hat_satellite/6.11/html/configuring_red_hat_satellite_to_use_ansible/providing-feedback-on-red-hat-documentation_ansible
Monitoring	Monitoring OpenShift Container Platform 4.12 Configuring and using the monitoring stack in OpenShift Container Platform Red Hat OpenShift Documentation Team	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.12/html/monitoring/index
4.4. Results Translation Extension	4.4. Results Translation Extension The JDBCExecutionFactory provides several methods to modify the java.sql.Statement and java.sql.ResultSet interactions, including: Overriding the createXXXExecution to subclass the corresponding JDBCXXXExecution. The JDBCBaseExecution has protected methods to get the appropriate statement (getStatement, getPreparedStatement, getCallableStatement) and to bind prepared statement values bindPreparedStatementValues. Retrieve values from the JDBC ResultSet or CallableStatement - see the retrieveValue methods.	null	https://docs.redhat.com/en/documentation/red_hat_jboss_data_virtualization/6.4/html/development_guide_volume_4_server_development/results_translation_extension
Chapter 21. Ensuring the presence of host-based access control rules in IdM using Ansible playbooks	Chapter 21. Ensuring the presence of host-based access control rules in IdM using Ansible playbooks Ansible is an automation tool used to configure systems, deploy software, and perform rolling updates. It includes support for Identity Management (IdM). Learn more about Identity Management (IdM) host-based access policies and how to define them using Ansible . 21.1. Host-based access control rules in IdM Host-based access control (HBAC) rules define which users or user groups can access which hosts or host groups by using which services or services in a service group. As a system administrator, you can use HBAC rules to achieve the following goals: Limit access to a specified system in your domain to members of a specific user group. Allow only a specific service to be used to access systems in your domain. By default, IdM is configured with a default HBAC rule named allow_all , which means universal access to every host for every user via every relevant service in the entire IdM domain. You can fine-tune access to different hosts by replacing the default allow_all rule with your own set of HBAC rules. For centralized and simplified access control management, you can apply HBAC rules to user groups, host groups, or service groups instead of individual users, hosts, or services. 21.2. Ensuring the presence of an HBAC rule in IdM using an Ansible playbook Follow this procedure to ensure the presence of a host-based access control (HBAC) rule in Identity Management (IdM) using an Ansible playbook. Prerequisites You have configured your Ansible control node to meet the following requirements: You are using Ansible version 2.13 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. The users and user groups you want to use for your HBAC rule exist in IdM. See Managing user accounts using Ansible playbooks and Ensuring the presence of IdM groups and group members using Ansible playbooks for details. The hosts and host groups to which you want to apply your HBAC rule exist in IdM. See Managing hosts using Ansible playbooks and Managing host groups using Ansible playbooks for details. Procedure Create an inventory file, for example inventory.file , and define ipaserver in it: Create your Ansible playbook file that defines the HBAC policy whose presence you want to ensure. To simplify this step, you can copy and modify the example in the /usr/share/doc/ansible-freeipa/playbooks/hbacrule/ensure-hbacrule-allhosts-present.yml file: Run the playbook: Verification Log in to the IdM Web UI as administrator. Navigate to Policy Host-Based-Access-Control HBAC Test . In the Who tab, select idm_user. In the Accessing tab, select client.idm.example.com . In the Via service tab, select sshd . In the Rules tab, select login . In the Run test tab, click the Run test button. If you see ACCESS GRANTED, the HBAC rule is implemented successfully. Additional resources See the README-hbacsvc.md , README-hbacsvcgroup.md , and README-hbacrule.md files in the /usr/share/doc/ansible-freeipa directory. See the playbooks in the subdirectories of the /usr/share/doc/ansible-freeipa/playbooks directory.	[ "[ipaserver] server.idm.example.com", "--- - name: Playbook to handle hbacrules hosts: ipaserver vars_files: - /home/user_name/MyPlaybooks/secret.yml tasks: # Ensure idm_user can access client.idm.example.com via the sshd service - ipahbacrule: ipaadmin_password: \"{{ ipaadmin_password }}\" name: login user: idm_user host: client.idm.example.com hbacsvc: - sshd state: present", "ansible-playbook --vault-password-file=password_file -v -i path_to_inventory_directory/inventory.file path_to_playbooks_directory/ensure-new-hbacrule-present.yml" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/8/html/using_ansible_to_install_and_manage_identity_management/ensuring-the-presence-of-host-based-access-control-rules-in-idm-using-ansible-playbooks_using-ansible-to-install-and-manage-idm
7.17. bridge-utils	7.17. bridge-utils 7.17.1. RHEA-2013:0322 - bridge-utils enhancement update Updated bridge-utils packages that add two enhancements are now available for Red Hat Enterprise Linux 6. The bridge-utils packages contain utilities for configuration of the Linux Ethernet bridge. The Linux Ethernet bridge can be used to connect multiple Ethernet devices together. This connection is fully transparent: hosts connected to one Ethernet device see hosts connected to the other Ethernet devices directly. Enhancements BZ# 676355 The man page was missing the multicast option descriptions. This update adds that information to the man page. BZ#690529 This enhancement adds the missing feature described in the BRCTL(8) man page, that allows the user to get the bridge information for a simple bridge using the "brctl show USDBRIDGE" command. All users of bridge-utils are advise to upgrade to these updated packages, which add these enhancements.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.4_technical_notes/bridge-utils
Chapter 32. JPA	Chapter 32. JPA Since Camel 1.0 Both producer and consumer are supported. The JPA component enables you to store and retrieve Java objects from persistent storage using EJB 3's Java Persistence Architecture (JPA). Java Persistence Architecture (JPA) is a standard interface layer that wraps Object/Relational Mapping (ORM) products such as OpenJPA, Hibernate, TopLink. Add the following dependency to your pom.xml for this component: <dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-jpa</artifactId> <version>3.20.1.redhat-00056</version> <!-- use the same version as your Camel core version --> </dependency> 32.1. Sending to the endpoint You can store a Java entity bean in a database by sending it to a JPA producer endpoint. The body of the In message is assumed to be an entity bean (that is, a POJO with an @Entity annotation on it) or a collection or array of entity beans. If the body is a List of entities, use entityType=java.util.List as a configuration passed to the producer endpoint. If the body does not contain one of the listed types, put a Message Translator before the endpoint to perform the necessary conversion first. You can use query , namedQuery or nativeQuery for the producer as well. For the value of the parameters , you can use the Simple expression which allows you to retrieve parameter values from Message body, header and etc. Those query can be used for retrieving a set of data with using SELECT JPQL/SQL statement as well as executing bulk update/delete with using UPDATE / DELETE JPQL/SQL statement. Please note that you need to specify useExecuteUpdate to true if you execute UPDATE / DELETE with namedQuery as camel doesn't look into the named query unlike query and nativeQuery . 32.2. Consuming from the endpoint Consuming messages from a JPA consumer endpoint removes (or updates) entity beans in the database. This allows you to use a database table as a logical queue: consumers take messages from the queue and then delete/update them to logically remove them from the queue. If you do not wish to delete the entity bean when it has been processed (and when routing is done), you can specify consumeDelete=false on the URI. This will result in the entity being processed each poll. If you would rather perform some update on the entity to mark it as processed (such as to exclude it from a future query) then you can annotate a method with @Consumed which will be invoked on your entity bean when the entity bean when it has been processed (and when routing is done). You can use @PreConsumed which will be invoked on your entity bean before it has been processed (before routing). If you are consuming a lot (100K+) of rows and experience OutOfMemory problems you should set the maximumResults to sensible value. 32.3. URI format For sending to the endpoint, the entityClassName is optional. If specified, it helps the Type Converter to ensure the body is of the correct type. For consuming, the entityClassName is mandatory. 32.4. Configuring Options Camel components are configured on two separate levels: component level endpoint level 32.4.1. Configuring Component Options The component level is the highest level which holds general and common configurations that are inherited by the endpoints. For example a component may have security settings, credentials for authentication, urls for network connection and so forth. Some components only have a few options, and others may have many. Because components typically have pre configured defaults that are commonly used, then you may often only need to configure a few options on a component; or none at all. Configuring components can be done with the Component DSL , in a configuration file (application.properties\|yaml), or directly with Java code. 32.4.2. Configuring Endpoint Options Where you find yourself configuring the most is on endpoints, as endpoints often have many options, which allows you to configure what you need the endpoint to do. The options are also categorized into whether the endpoint is used as consumer (from) or as a producer (to), or used for both. Configuring endpoints is most often done directly in the endpoint URI as path and query parameters. You can also use the Endpoint DSL as a type safe way of configuring endpoints. A good practice when configuring options is to use Property Placeholders , which allows to not hardcode urls, port numbers, sensitive information, and other settings. In other words placeholders allows to externalize the configuration from your code, and gives more flexibility and reuse. The following two sections lists all the options, firstly for the component followed by the endpoint. 32.4.3. Component Options The JPA component supports 9 options, which are listed below. Name Description Default Type aliases (common) Maps an alias to a JPA entity class. The alias can then be used in the endpoint URI (instead of the fully qualified class name). Map entityManagerFactory (common) To use the EntityManagerFactory. This is strongly recommended to configure. EntityManagerFactory joinTransaction (common) The camel-jpa component will join transaction by default. You can use this option to turn this off, for example if you use LOCAL_RESOURCE and join transaction doesn't work with your JPA provider. This option can also be set globally on the JpaComponent, instead of having to set it on all endpoints. true boolean sharedEntityManager (common) Whether to use Spring's SharedEntityManager for the consumer/producer. Note in most cases joinTransaction should be set to false as this is not an EXTENDED EntityManager. false boolean transactionManager (common) To use the PlatformTransactionManager for managing transactions. PlatformTransactionManager transactionStrategy (common) To use the TransactionStrategy for running the operations in a transaction. TransactionStrategy bridgeErrorHandler (consumer) Allows for bridging the consumer to the Camel routing Error Handler, which mean any exceptions occurred while the consumer is trying to pickup incoming messages, or the likes, will now be processed as a message and handled by the routing Error Handler. 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 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 32.4.4. Endpoint Options The JPA endpoint is configured using URI syntax: with the following path and query parameters: 32.4.4.1. Path Parameters (1 parameters) Name Description Default Type entityType (common) Required Entity class name. Class 32.4.4.2. Query Parameters (44 parameters) Name Description Default Type joinTransaction (common) The camel-jpa component will join transaction by default. You can use this option to turn this off, for example if you use LOCAL_RESOURCE and join transaction doesn't work with your JPA provider. This option can also be set globally on the JpaComponent, instead of having to set it on all endpoints. true boolean maximumResults (common) Set the maximum number of results to retrieve on the Query. -1 int namedQuery (common) To use a named query. String nativeQuery (common) To use a custom native query. You may want to use the option resultClass also when using native queries. String persistenceUnit (common) Required The JPA persistence unit used by default. camel String query (common) To use a custom query. String resultClass (common) Defines the type of the returned payload (we will call entityManager.createNativeQuery(nativeQuery, resultClass) instead of entityManager.createNativeQuery(nativeQuery)). Without this option, we will return an object array. Only has an affect when using in conjunction with native query when consuming data. Class consumeDelete (consumer) If true, the entity is deleted after it is consumed; if false, the entity is not deleted. true boolean consumeLockEntity (consumer) Specifies whether or not to set an exclusive lock on each entity bean while processing the results from polling. true boolean deleteHandler (consumer) To use a custom DeleteHandler to delete the row after the consumer is done processing the exchange. DeleteHandler lockModeType (consumer) To configure the lock mode on the consumer. Enum values: READ WRITE OPTIMISTIC OPTIMISTIC_FORCE_INCREMENT PESSIMISTIC_READ PESSIMISTIC_WRITE PESSIMISTIC_FORCE_INCREMENT NONE PESSIMISTIC_WRITE LockModeType maxMessagesPerPoll (consumer) An integer value to define the maximum number of messages to gather per poll. By default, no maximum is set. Can be used to avoid polling many thousands of messages when starting up the server. Set a value of 0 or negative to disable. int preDeleteHandler (consumer) To use a custom Pre-DeleteHandler to delete the row after the consumer has read the entity. DeleteHandler 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 skipLockedEntity (consumer) To configure whether to use NOWAIT on lock and silently skip the entity. false boolean transacted (consumer) Whether to run the consumer in transacted mode, by which all messages will either commit or rollback, when the entire batch has been processed. The default behavior (false) is to commit all the previously successfully processed messages, and only rollback the last failed message. false boolean bridgeErrorHandler (consumer (advanced)) Allows for bridging the consumer to the Camel routing Error Handler, which mean any exceptions occurred while the consumer is trying to pickup incoming messages, or the likes, will now be processed as a message and handled by the routing Error Handler. 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 InOptionalOut ExchangePattern parameters (consumer (advanced)) This key/value mapping is used for building the query parameters. It is expected to be of the generic type java.util.Map where the keys are the named parameters of a given JPA query and the values are their corresponding effective values you want to select for. When it's used for producer, Simple expression can be used as a parameter value. It allows you to retrieve parameter values from the message body, header and etc. Map 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 findEntity (producer) If enabled then the producer will find a single entity by using the message body as key and entityType as the class type. This can be used instead of a query to find a single entity. false boolean flushOnSend (producer) Flushes the EntityManager after the entity bean has been persisted. true boolean remove (producer) Indicates to use entityManager.remove(entity). false boolean useExecuteUpdate (producer) To configure whether to use executeUpdate() when producer executes a query. When you use INSERT, UPDATE or DELETE statement as a named query, you need to specify this option to 'true'. Boolean usePersist (producer) Indicates to use entityManager.persist(entity) instead of entityManager.merge(entity). Note: entityManager.persist(entity) doesn't work for detached entities (where the EntityManager has to execute an UPDATE instead of an INSERT query)!. false boolean 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 usePassedInEntityManager (producer (advanced)) If set to true, then Camel will use the EntityManager from the header JpaConstants.ENTITY_MANAGER instead of the configured entity manager on the component/endpoint. This allows end users to control which entity manager will be in use. false boolean entityManagerProperties (advanced) Additional properties for the entity manager to use. Map sharedEntityManager (advanced) Whether to use Spring's SharedEntityManager for the consumer/producer. Note in most cases joinTransaction should be set to false as this is not an EXTENDED EntityManager. false boolean 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 32.5. Message Headers The JPA component supports 2 message header(s), which are listed below: Name Description Default Type CamelEntityManager (common) Constant: ENTITY_MANAGER The JPA EntityManager object. EntityManager CamelJpaParameters (producer) Constant: link: JPA_PARAMETERS_HEADER Alternative way for passing query parameters as an Exchange header. Map 32.6. Configuring EntityManagerFactory It is recommended to configure the JPA component to use a specific EntityManagerFactory instance. If failed to do so each JpaEndpoint will auto create their own instance of EntityManagerFactory which most often is not what you want. For example, you can instantiate a JPA component that references the myEMFactory entity manager factory, as follows: <bean id="jpa" class="org.apache.camel.component.jpa.JpaComponent"> <property name="entityManagerFactory" ref="myEMFactory"/> </bean> The JpaComponent automatically looks up the EntityManagerFactory from the Registry which means you do not need to configure this on the JpaComponent as shown above. You only need to do so if there is ambiguity, in which case Camel will log a WARN. 32.7. Configuring TransactionManager The JpaComponent automatically looks up the TransactionManager from the Registry. If Camel won't find any TransactionManager instance registered, it will also look up for the TransactionTemplate and try to extract TransactionManager from it. If none TransactionTemplate is available in the registry, JpaEndpoint will auto create their own instance of TransactionManager which most often is not what you want. If more than single instance of the TransactionManager is found, Camel will log a WARN. In such cases you might want to instantiate and explicitly configure a JPA component that references the myTransactionManager transaction manager, as follows: <bean id="jpa" class="org.apache.camel.component.jpa.JpaComponent"> <property name="entityManagerFactory" ref="myEMFactory"/> <property name="transactionManager" ref="myTransactionManager"/> </bean> 32.8. Using a consumer with a named query For consuming only selected entities, you can use the namedQuery URI query option. First, you have to define the named query in the JPA Entity class: @Entity @NamedQuery(name = "step1", query = "select x from MultiSteps x where x.step = 1") public class MultiSteps { ... } After that you can define a consumer uri as shown below: from("jpa://org.apache.camel.examples.MultiSteps?namedQuery=step1") .to("bean:myBusinessLogic"); 32.9. Using a consumer with a query For consuming only selected entities, you can use the query URI query option. You only have to define the query option: from("jpa://org.apache.camel.examples.MultiSteps?query=select o from org.apache.camel.examples.MultiSteps o where o.step = 1") .to("bean:myBusinessLogic"); 32.10. Using a consumer with a native query For consuming only selected entities, you can use the nativeQuery URI query option. You only have to define the native query option: from("jpa://org.apache.camel.examples.MultiSteps?nativeQuery=select * from MultiSteps where step = 1") .to("bean:myBusinessLogic"); If you use the native query option, you will receive an object array in the message body. 32.11. Using a producer with a named query For retrieving selected entities or execute bulk update/delete, you can use the namedQuery URI query option. First, you have to define the named query in the JPA Entity class: @Entity @NamedQuery(name = "step1", query = "select x from MultiSteps x where x.step = 1") public class MultiSteps { ... } After that you can define a producer uri as shown below: from("direct:namedQuery") .to("jpa://org.apache.camel.examples.MultiSteps?namedQuery=step1"); Note that you need to specify useExecuteUpdate option to true to execute UPDATE / DELETE statement as a named query. 32.12. Using a producer with a query For retrieving selected entities or execute bulk update/delete, you can use the query URI query option. You only have to define the query option: from("direct:query") .to("jpa://org.apache.camel.examples.MultiSteps?query=select o from org.apache.camel.examples.MultiSteps o where o.step = 1"); 32.13. Using a producer with a native query For retrieving selected entities or execute bulk update/delete, you can use the nativeQuery URI query option. You only have to define the native query option: from("direct:nativeQuery") .to("jpa://org.apache.camel.examples.MultiSteps?resultClass=org.apache.camel.examples.MultiSteps&nativeQuery=select * from MultiSteps where step = 1"); If you use the native query option without specifying resultClass , you will receive an object array in the message body. 32.14. Using the JPA-Based Idempotent Repository The Idempotent Consumer from the EIP patterns is used to filter out duplicate messages. A JPA-based idempotent repository is provided. To use the JPA based idempotent repository. Procedure Set up a persistence-unit in the persistence.xml file. Set up a org.springframework.orm.jpa.JpaTemplate which is used by the org.apache.camel.processor.idempotent.jpa.JpaMessageIdRepository . Configure the error formatting macro: snippet: java.lang.IndexOutOfBoundsException: Index: 20, Size: 20 Configure the idempotent repository as org.apache.camel.processor.idempotent.jpa.JpaMessageIdRepository . Create the JPA idempotent repository in the Spring XML file as shown below: <camelContext xmlns="http://camel.apache.org/schema/spring"> <route id="JpaMessageIdRepositoryTest"> <from uri="direct:start" /> <idempotentConsumer idempotentRepository="jpaStore"> <header>messageId</header> <to uri="mock:result" /> </idempotentConsumer> </route> </camelContext> When running this Camel component tests inside your IDE If you run the tests of this component directly inside your IDE, and not through Maven, then you could see exceptions like these: The problem here is that the source has been compiled or recompiled through your IDE and not through Maven, which would enhance the byte-code at build time . To overcome this you need to enable dynamic byte-code enhancement of OpenJPA . For example, assuming the current OpenJPA version being used in Camel is 2.2.1, to run the tests inside your IDE you would need to pass the following argument to the JVM: 32.15. Spring Boot Auto-Configuration When using jpa with Spring Boot make sure to use the following Maven dependency to have support for auto configuration: <dependency> <groupId>org.apache.camel.springboot</groupId> <artifactId>camel-jpa-starter</artifactId> </dependency> The component supports 10 options, which are listed below. Name Description Default Type camel.component.jpa.aliases Maps an alias to a JPA entity class. The alias can then be used in the endpoint URI (instead of the fully qualified class name). Map camel.component.jpa.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.jpa.bridge-error-handler Allows for bridging the consumer to the Camel routing Error Handler, which mean any exceptions occurred while the consumer is trying to pickup incoming messages, or the likes, will now be processed as a message and handled by the routing Error Handler. 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.jpa.enabled Whether to enable auto configuration of the jpa component. This is enabled by default. Boolean camel.component.jpa.entity-manager-factory To use the EntityManagerFactory. This is strongly recommended to configure. The option is a javax.persistence.EntityManagerFactory type. EntityManagerFactory camel.component.jpa.join-transaction The camel-jpa component will join transaction by default. You can use this option to turn this off, for example if you use LOCAL_RESOURCE and join transaction doesn't work with your JPA provider. This option can also be set globally on the JpaComponent, instead of having to set it on all endpoints. true Boolean camel.component.jpa.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.jpa.shared-entity-manager Whether to use Spring's SharedEntityManager for the consumer/producer. Note in most cases joinTransaction should be set to false as this is not an EXTENDED EntityManager. false Boolean camel.component.jpa.transaction-manager To use the PlatformTransactionManager for managing transactions. The option is a org.springframework.transaction.PlatformTransactionManager type. PlatformTransactionManager camel.component.jpa.transaction-strategy To use the TransactionStrategy for running the operations in a transaction. The option is a org.apache.camel.component.jpa.TransactionStrategy type. TransactionStrategy	[ "<dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-jpa</artifactId> <version>3.20.1.redhat-00056</version> <!-- use the same version as your Camel core version --> </dependency>", "jpa:entityClassName[?options]", "jpa:entityType", "<bean id=\"jpa\" class=\"org.apache.camel.component.jpa.JpaComponent\"> <property name=\"entityManagerFactory\" ref=\"myEMFactory\"/> </bean>", "<bean id=\"jpa\" class=\"org.apache.camel.component.jpa.JpaComponent\"> <property name=\"entityManagerFactory\" ref=\"myEMFactory\"/> <property name=\"transactionManager\" ref=\"myTransactionManager\"/> </bean>", "@Entity @NamedQuery(name = \"step1\", query = \"select x from MultiSteps x where x.step = 1\") public class MultiSteps { }", "from(\"jpa://org.apache.camel.examples.MultiSteps?namedQuery=step1\") .to(\"bean:myBusinessLogic\");", "from(\"jpa://org.apache.camel.examples.MultiSteps?query=select o from org.apache.camel.examples.MultiSteps o where o.step = 1\") .to(\"bean:myBusinessLogic\");", "from(\"jpa://org.apache.camel.examples.MultiSteps?nativeQuery=select * from MultiSteps where step = 1\") .to(\"bean:myBusinessLogic\");", "@Entity @NamedQuery(name = \"step1\", query = \"select x from MultiSteps x where x.step = 1\") public class MultiSteps { }", "from(\"direct:namedQuery\") .to(\"jpa://org.apache.camel.examples.MultiSteps?namedQuery=step1\");", "from(\"direct:query\") .to(\"jpa://org.apache.camel.examples.MultiSteps?query=select o from org.apache.camel.examples.MultiSteps o where o.step = 1\");", "from(\"direct:nativeQuery\") .to(\"jpa://org.apache.camel.examples.MultiSteps?resultClass=org.apache.camel.examples.MultiSteps&nativeQuery=select * from MultiSteps where step = 1\");", "<camelContext xmlns=\"http://camel.apache.org/schema/spring\"> <route id=\"JpaMessageIdRepositoryTest\"> <from uri=\"direct:start\" /> <idempotentConsumer idempotentRepository=\"jpaStore\"> <header>messageId</header> <to uri=\"mock:result\" /> </idempotentConsumer> </route> </camelContext>", "org.springframework.transaction.CannotCreateTransactionException: Could not open JPA EntityManager for transaction; nested exception is <openjpa-2.2.1-r422266:1396819 nonfatal user error> org.apache.openjpa.persistence.ArgumentException: This configuration disallows runtime optimization, but the following listed types were not enhanced at build time or at class load time with a javaagent: \"org.apache.camel.examples.SendEmail\". at org.springframework.orm.jpa.JpaTransactionManager.doBegin(JpaTransactionManager.java:427) at org.springframework.transaction.support.AbstractPlatformTransactionManager.getTransaction(AbstractPlatformTransactionManager.java:371) at org.springframework.transaction.support.TransactionTemplate.execute(TransactionTemplate.java:127) at org.apache.camel.processor.jpa.JpaRouteTest.cleanupRepository(JpaRouteTest.java:96) at org.apache.camel.processor.jpa.JpaRouteTest.createCamelContext(JpaRouteTest.java:67) at org.apache.camel.test.junit5.CamelTestSupport.doSetUp(CamelTestSupport.java:238) at org.apache.camel.test.junit5.CamelTestSupport.setUp(CamelTestSupport.java:208)", "-javaagent:<path_to_your_local_m2_cache>/org/apache/openjpa/openjpa/2.2.1/openjpa-2.2.1.jar", "<dependency> <groupId>org.apache.camel.springboot</groupId> <artifactId>camel-jpa-starter</artifactId> </dependency>" ]	https://docs.redhat.com/en/documentation/red_hat_build_of_apache_camel_for_spring_boot/3.20/html/camel_spring_boot_reference/csb-camel-jpa-component-starter
Chapter 98. Managing DNS records in IdM	Chapter 98. Managing DNS records in IdM This chapter describes how to manage DNS records in Identity Management (IdM). As an IdM administrator, you can add, modify and delete DNS records in IdM. The chapter contains the following sections: DNS records in IdM Adding DNS resource records from the IdM Web UI Adding DNS resource records from the IdM CLI Common ipa dnsrecord-add options Deleting DNS records in the IdM Web UI Deleting an entire DNS record in the IdM Web UI Deleting DNS records in the IdM CLI Prerequisites Your IdM deployment contains an integrated DNS server. For information how to install IdM with integrated DNS, see one of the following links: Installing an IdM server: With integrated DNS, with an integrated CA as the root CA . Installing an IdM server: With integrated DNS, with an external CA as the root CA . 98.1. DNS records in IdM Identity Management (IdM) supports many different DNS record types. The following four are used most frequently: A This is a basic map for a host name and an IPv4 address. The record name of an A record is a host name, such as www . The IP Address value of an A record is an IPv4 address, such as 192.0.2.1 . For more information about A records, see RFC 1035 . AAAA This is a basic map for a host name and an IPv6 address. The record name of an AAAA record is a host name, such as www . The IP Address value is an IPv6 address, such as 2001:DB8::1111 . For more information about AAAA records, see RFC 3596 . SRV Service (SRV) resource records map service names to the DNS name of the server that is providing that particular service. For example, this record type can map a service like an LDAP directory to the server which manages it. The record name of an SRV record has the format _service . _protocol , such as _ldap._tcp . The configuration options for SRV records include priority, weight, port number, and host name for the target service. For more information about SRV records, see RFC 2782 . PTR A pointer record (PTR) adds a reverse DNS record, which maps an IP address to a domain name. Note All reverse DNS lookups for IPv4 addresses use reverse entries that are defined in the in-addr.arpa. domain. The reverse address, in human-readable form, is the exact reverse of the regular IP address, with the in-addr.arpa. domain appended to it. For example, for the network address 192.0.2.0/24 , the reverse zone is 2.0.192.in-addr.arpa . The record name of a PTR must be in the standard format specified in RFC 1035 , extended in RFC 2317 , and RFC 3596 . The host name value must be a canonical host name of the host for which you want to create the record. Note Reverse zones can also be configured for IPv6 addresses, with zones in the .ip6.arpa. domain. For more information about IPv6 reverse zones, see RFC 3596 . When adding DNS resource records, note that many of the records require different data. For example, a CNAME record requires a host name, while an A record requires an IP address. In the IdM Web UI, the fields in the form for adding a new record are updated automatically to reflect what data is required for the currently selected type of record. 98.2. Adding DNS resource records in the IdM Web UI Follow this procedure to add DNS resource records in the Identity Management (IdM) Web UI. Prerequisites The DNS zone to which you want to add a DNS record exists and is managed by IdM. For more information about creating a DNS zone in IdM DNS, see Managing DNS zones in IdM . You are logged in as IdM administrator. Procedure In the IdM Web UI, click Network Services DNS DNS Zones . Click the DNS zone to which you want to add a DNS record. In the DNS Resource Records section, click Add to add a new record. Figure 98.1. Adding a New DNS Resource Record Select the type of record to create and fill out the other fields as required. Figure 98.2. Defining a New DNS Resource Record Click Add to confirm the new record. 98.3. Adding DNS resource records from the IdM CLI Follow this procedure to add a DNS resource record of any type from the command-line interface (CLI). Prerequisites The DNS zone to which you want to add a DNS records exists. For more information about creating a DNS zone in IdM DNS, see Managing DNS zones in IdM . You are logged in as IdM administrator. Procedure To add a DNS resource record, use the ipa dnsrecord-add command. The command follows this syntax: In the command above: The zone_name is the name of the DNS zone to which the record is being added. The record_name is an identifier for the new DNS resource record. For example, to add an A type DNS record of host1 to the idm.example.com zone, enter: 98.4. Common ipa dnsrecord-* options You can use the following options when adding, modifying and deleting the most common DNS resource record types in Identity Management (IdM): A (IPv4) AAAA (IPv6) SRV PTR In Bash , you can define multiple entries by listing the values in a comma-separated list inside curly braces, such as --option={val1,val2,val3} . Table 98.1. General Record Options Option Description --ttl = number Sets the time to live for the record. --structured Parses the raw DNS records and returns them in a structured format. Table 98.2. "A" record options Option Description Examples --a-rec = ARECORD Passes a single A record or a list of A records. ipa dnsrecord-add idm.example.com host1 --a-rec=192.168.122.123 Can create a wildcard A record with a given IP address. ipa dnsrecord-add idm.example.com "*" --a-rec=192.168.122.123 [a] --a-ip-address = string Gives the IP address for the record. When creating a record, the option to specify the A record value is --a-rec . However, when modifying an A record, the --a-rec option is used to specify the current value for the A record. The new value is set with the --a-ip-address option. ipa dnsrecord-mod idm.example.com --a-rec 192.168.122.123 --a-ip-address 192.168.122.124 [a] The example creates a wildcard A record with the IP address of 192.0.2.123. Table 98.3. "AAAA" record options Option Description Example --aaaa-rec = AAAARECORD Passes a single AAAA (IPv6) record or a list of AAAA records. ipa dnsrecord-add idm.example.com www --aaaa-rec 2001:db8::1231:5675 --aaaa-ip-address = string Gives the IPv6 address for the record. When creating a record, the option to specify the A record value is --aaaa-rec . However, when modifying an A record, the --aaaa-rec option is used to specify the current value for the A record. The new value is set with the --a-ip-address option. ipa dnsrecord-mod idm.example.com --aaaa-rec 2001:db8::1231:5675 --aaaa-ip-address 2001:db8::1231:5676 Table 98.4. "PTR" record options Option Description Example --ptr-rec = PTRRECORD Passes a single PTR record or a list of PTR records. When adding the reverse DNS record, the zone name used with the ipa dnsrecord-add command is reversed, compared to the usage for adding other DNS records. Typically, the host IP address is the last octet of the IP address in a given network. The first example on the right adds a PTR record for server4.idm.example.com with IPv4 address 192.168.122.4. The second example adds a reverse DNS entry to the 0.0.0.0.0.0.0.0.8.b.d.0.1.0.0.2.ip6.arpa. IPv6 reverse zone for the host server2.example.com with the IP address 2001:DB8::1111 . ipa dnsrecord-add 122.168.192.in-addr.arpa 4 --ptr-rec server4.idm.example.com. USD ipa dnsrecord-add 0.0.0.0.0.0.0.0.8.b.d.0.1.0.0.2.ip6.arpa. 1.1.1.0.0.0.0.0.0.0.0.0.0.0.0 --ptr-rec server2.idm.example.com. --ptr-hostname = string Gives the host name for the record. Table 98.5. "SRV" Record Options Option Description Example --srv-rec = SRVRECORD Passes a single SRV record or a list of SRV records. In the examples on the right, _ldap._tcp defines the service type and the connection protocol for the SRV record. The --srv-rec option defines the priority, weight, port, and target values. The weight values of 51 and 49 in the examples add up to 100 and represent the probability, in percentages, that a particular record is used. # ipa dnsrecord-add idm.example.com _ldap._tcp --srv-rec="0 51 389 server1.idm.example.com." # ipa dnsrecord-add server.idm.example.com _ldap._tcp --srv-rec="1 49 389 server2.idm.example.com." --srv-priority = number Sets the priority of the record. There can be multiple SRV records for a service type. The priority (0 - 65535) sets the rank of the record; the lower the number, the higher the priority. A service has to use the record with the highest priority first. # ipa dnsrecord-mod server.idm.example.com _ldap._tcp --srv-rec="1 49 389 server2.idm.example.com." --srv-priority=0 --srv-weight = number Sets the weight of the record. This helps determine the order of SRV records with the same priority. The set weights should add up to 100, representing the probability (in percentages) that a particular record is used. # ipa dnsrecord-mod server.idm.example.com _ldap._tcp --srv-rec="0 49 389 server2.idm.example.com." --srv-weight=60 --srv-port = number Gives the port for the service on the target host. # ipa dnsrecord-mod server.idm.example.com _ldap._tcp --srv-rec="0 60 389 server2.idm.example.com." --srv-port=636 --srv-target = string Gives the domain name of the target host. This can be a single period (.) if the service is not available in the domain. Additional resources Run ipa dnsrecord-add --help . 98.5. Deleting DNS records in the IdM Web UI Follow this procedure to delete DNS records in Identity Management (IdM) using the IdM Web UI. Prerequisites You are logged in as IdM administrator. Procedure In the IdM Web UI, click Network Services DNS DNS Zones . Click the zone from which you want to delete a DNS record, for example example.com. . In the DNS Resource Records section, click the name of the resource record. Figure 98.3. Selecting a DNS Resource Record Select the check box by the name of the record type to delete. Click Delete . Figure 98.4. Deleting a DNS Resource Record The selected record type is now deleted. The other configuration of the resource record is left intact. Additional resources Deleting an entire DNS record in the IdM Web UI 98.6. Deleting an entire DNS record in the IdM Web UI Follow this procedure to delete all the records for a particular resource in a zone using the Identity Management (IdM) Web UI. Prerequisites You are logged in as IdM administrator. Procedure In the IdM Web UI, click Network Services DNS DNS Zones . Click the zone from which you want to delete a DNS record, for example zone.example.com. . In the DNS Resource Records section, select the check box of the resource record to delete. Click Delete . Figure 98.5. Deleting an Entire Resource Record The entire resource record is now deleted. 98.7. Deleting DNS records in the IdM CLI Follow this procedure to remove DNS records from a zone managed by the Identity Management (IdM) DNS. Prerequisites You are logged in as IdM administrator. Procedure To remove records from a zone, use the ipa dnsrecord-del command and add the -- recordType -rec option together with the record value. For example, to remove an A type record: If you run ipa dnsrecord-del without any options, the command prompts for information about the record to delete. Note that passing the --del-all option with the command removes all associated records for the zone. Additional resources Run the ipa dnsrecord-del --help command. 98.8. Additional resources See Using Ansible to manage DNS records in IdM .	[ "ipa dnsrecord-add zone_name record_name -- record_type_option=data", "ipa dnsrecord-add idm.example.com host1 --a-rec=192.168.122.123", "ipa dnsrecord-del example.com www --a-rec 192.0.2.1" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/8/html/configuring_and_managing_identity_management/managing-dns-records-in-idm_configuring-and-managing-idm
Chapter 6. Managing image streams	Chapter 6. Managing image streams Image streams provide a means of creating and updating container images in an on-going way. As improvements are made to an image, tags can be used to assign new version numbers and keep track of changes. This document describes how image streams are managed. 6.1. Why use imagestreams An image stream and its associated tags provide an abstraction for referencing container images from within OpenShift Container Platform. The image stream and its tags allow you to see what images are available and ensure that you are using the specific image you need even if the image in the repository changes. Image streams do not contain actual image data, but present a single virtual view of related images, similar to an image repository. You can configure builds and deployments to watch an image stream for notifications when new images are added and react by performing a build or deployment, respectively. For example, if a deployment is using a certain image and a new version of that image is created, a deployment could be automatically performed to pick up the new version of the image. However, if the image stream tag used by the deployment or build is not updated, then even if the container image in the container image registry is updated, the build or deployment continues using the , presumably known good image. The source images can be stored in any of the following: OpenShift Container Platform's integrated registry. An external registry, for example registry.redhat.io or quay.io. Other image streams in the OpenShift Container Platform cluster. When you define an object that references an image stream tag, such as a build or deployment configuration, you point to an image stream tag and not the repository. When you build or deploy your application, OpenShift Container Platform queries the repository using the image stream tag to locate the associated ID of the image and uses that exact image. The image stream metadata is stored in the etcd instance along with other cluster information. Using image streams has several significant benefits: You can tag, rollback a tag, and quickly deal with images, without having to re-push using the command line. You can trigger builds and deployments when a new image is pushed to the registry. Also, OpenShift Container Platform has generic triggers for other resources, such as Kubernetes objects. You can mark a tag for periodic re-import. If the source image has changed, that change is picked up and reflected in the image stream, which triggers the build or deployment flow, depending upon the build or deployment configuration. You can share images using fine-grained access control and quickly distribute images across your teams. If the source image changes, the image stream tag still points to a known-good version of the image, ensuring that your application does not break unexpectedly. You can configure security around who can view and use the images through permissions on the image stream objects. Users that lack permission to read or list images on the cluster level can still retrieve the images tagged in a project using image streams. 6.2. Configuring image streams An ImageStream object file contains the following elements. Imagestream object definition apiVersion: image.openshift.io/v1 kind: ImageStream metadata: annotations: openshift.io/generated-by: OpenShiftNewApp labels: app: ruby-sample-build template: application-template-stibuild name: origin-ruby-sample 1 namespace: test spec: {} status: dockerImageRepository: 172.30.56.218:5000/test/origin-ruby-sample 2 tags: - items: - created: 2017-09-02T10:15:09Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d 3 generation: 2 image: sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 4 - created: 2017-09-01T13:40:11Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 generation: 1 image: sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d tag: latest 5 1 The name of the image stream. 2 Docker repository path where new images can be pushed to add or update them in this image stream. 3 The SHA identifier that this image stream tag currently references. Resources that reference this image stream tag use this identifier. 4 The SHA identifier that this image stream tag previously referenced. Can be used to rollback to an older image. 5 The image stream tag name. 6.3. Image stream images An image stream image points from within an image stream to a particular image ID. Image stream images allow you to retrieve metadata about an image from a particular image stream where it is tagged. Image stream image objects are automatically created in OpenShift Container Platform whenever you import or tag an image into the image stream. You should never have to explicitly define an image stream image object in any image stream definition that you use to create image streams. The image stream image consists of the image stream name and image ID from the repository, delimited by an @ sign: To refer to the image in the ImageStream object example, the image stream image looks like: 6.4. Image stream tags An image stream tag is a named pointer to an image in an image stream. It is abbreviated as istag . An image stream tag is used to reference or retrieve an image for a given image stream and tag. Image stream tags can reference any local or externally managed image. It contains a history of images represented as a stack of all images the tag ever pointed to. Whenever a new or existing image is tagged under particular image stream tag, it is placed at the first position in the history stack. The image previously occupying the top position is available at the second position. This allows for easy rollbacks to make tags point to historical images again. The following image stream tag is from an ImageStream object: Image stream tag with two images in its history kind: ImageStream apiVersion: image.openshift.io/v1 metadata: name: my-image-stream # ... tags: - items: - created: 2017-09-02T10:15:09Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d generation: 2 image: sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 - created: 2017-09-01T13:40:11Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 generation: 1 image: sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d tag: latest # ... Image stream tags can be permanent tags or tracking tags. Permanent tags are version-specific tags that point to a particular version of an image, such as Python 3.5. Tracking tags are reference tags that follow another image stream tag and can be updated to change which image they follow, like a symlink. These new levels are not guaranteed to be backwards-compatible. For example, the latest image stream tags that ship with OpenShift Container Platform are tracking tags. This means consumers of the latest image stream tag are updated to the newest level of the framework provided by the image when a new level becomes available. A latest image stream tag to v3.10 can be changed to v3.11 at any time. It is important to be aware that these latest image stream tags behave differently than the Docker latest tag. The latest image stream tag, in this case, does not point to the latest image in the Docker repository. It points to another image stream tag, which might not be the latest version of an image. For example, if the latest image stream tag points to v3.10 of an image, when the 3.11 version is released, the latest tag is not automatically updated to v3.11 , and remains at v3.10 until it is manually updated to point to a v3.11 image stream tag. Note Tracking tags are limited to a single image stream and cannot reference other image streams. You can create your own image stream tags for your own needs. The image stream tag is composed of the name of the image stream and a tag, separated by a colon: For example, to refer to the sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d image in the ImageStream object example earlier, the image stream tag would be: 6.5. Image stream change triggers Image stream triggers allow your builds and deployments to be automatically invoked when a new version of an upstream image is available. For example, builds and deployments can be automatically started when an image stream tag is modified. This is achieved by monitoring that particular image stream tag and notifying the build or deployment when a change is detected. 6.6. Image stream mapping When the integrated registry receives a new image, it creates and sends an image stream mapping to OpenShift Container Platform, providing the image's project, name, tag, and image metadata. Note Configuring image stream mappings is an advanced feature. This information is used to create a new image, if it does not already exist, and to tag the image into the image stream. OpenShift Container Platform stores complete metadata about each image, such as commands, entry point, and environment variables. Images in OpenShift Container Platform are immutable and the maximum name length is 63 characters. The following image stream mapping example results in an image being tagged as test/origin-ruby-sample:latest : Image stream mapping object definition apiVersion: image.openshift.io/v1 kind: ImageStreamMapping metadata: creationTimestamp: null name: origin-ruby-sample namespace: test tag: latest image: dockerImageLayers: - name: sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef size: 0 - name: sha256:ee1dd2cb6df21971f4af6de0f1d7782b81fb63156801cfde2bb47b4247c23c29 size: 196634330 - name: sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef size: 0 - name: sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef size: 0 - name: sha256:ca062656bff07f18bff46be00f40cfbb069687ec124ac0aa038fd676cfaea092 size: 177723024 - name: sha256:63d529c59c92843c395befd065de516ee9ed4995549f8218eac6ff088bfa6b6e size: 55679776 - name: sha256:92114219a04977b5563d7dff71ec4caa3a37a15b266ce42ee8f43dba9798c966 size: 11939149 dockerImageMetadata: Architecture: amd64 Config: Cmd: - /usr/libexec/s2i/run Entrypoint: - container-entrypoint Env: - RACK_ENV=production - OPENSHIFT_BUILD_NAMESPACE=test - OPENSHIFT_BUILD_SOURCE=https://github.com/openshift/ruby-hello-world.git - EXAMPLE=sample-app - OPENSHIFT_BUILD_NAME=ruby-sample-build-1 - PATH=/opt/app-root/src/bin:/opt/app-root/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin - STI_SCRIPTS_URL=image:///usr/libexec/s2i - STI_SCRIPTS_PATH=/usr/libexec/s2i - HOME=/opt/app-root/src - BASH_ENV=/opt/app-root/etc/scl_enable - ENV=/opt/app-root/etc/scl_enable - PROMPT_COMMAND=. /opt/app-root/etc/scl_enable - RUBY_VERSION=2.2 ExposedPorts: 8080/tcp: {} Labels: build-date: 2015-12-23 io.k8s.description: Platform for building and running Ruby 2.2 applications io.k8s.display-name: 172.30.56.218:5000/test/origin-ruby-sample:latest io.openshift.build.commit.author: Ben Parees <[email protected]> io.openshift.build.commit.date: Wed Jan 20 10:14:27 2016 -0500 io.openshift.build.commit.id: 00cadc392d39d5ef9117cbc8a31db0889eedd442 io.openshift.build.commit.message: 'Merge pull request #51 from php-coder/fix_url_and_sti' io.openshift.build.commit.ref: master io.openshift.build.image: centos/ruby-22-centos7@sha256:3a335d7d8a452970c5b4054ad7118ff134b3a6b50a2bb6d0c07c746e8986b28e io.openshift.build.source-location: https://github.com/openshift/ruby-hello-world.git io.openshift.builder-base-version: 8d95148 io.openshift.builder-version: 8847438ba06307f86ac877465eadc835201241df io.openshift.s2i.scripts-url: image:///usr/libexec/s2i io.openshift.tags: builder,ruby,ruby22 io.s2i.scripts-url: image:///usr/libexec/s2i license: GPLv2 name: CentOS Base Image vendor: CentOS User: "1001" WorkingDir: /opt/app-root/src Container: 86e9a4a3c760271671ab913616c51c9f3cea846ca524bf07c04a6f6c9e103a76 ContainerConfig: AttachStdout: true Cmd: - /bin/sh - -c - tar -C /tmp -xf - && /usr/libexec/s2i/assemble Entrypoint: - container-entrypoint Env: - RACK_ENV=production - OPENSHIFT_BUILD_NAME=ruby-sample-build-1 - OPENSHIFT_BUILD_NAMESPACE=test - OPENSHIFT_BUILD_SOURCE=https://github.com/openshift/ruby-hello-world.git - EXAMPLE=sample-app - PATH=/opt/app-root/src/bin:/opt/app-root/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin - STI_SCRIPTS_URL=image:///usr/libexec/s2i - STI_SCRIPTS_PATH=/usr/libexec/s2i - HOME=/opt/app-root/src - BASH_ENV=/opt/app-root/etc/scl_enable - ENV=/opt/app-root/etc/scl_enable - PROMPT_COMMAND=. /opt/app-root/etc/scl_enable - RUBY_VERSION=2.2 ExposedPorts: 8080/tcp: {} Hostname: ruby-sample-build-1-build Image: centos/ruby-22-centos7@sha256:3a335d7d8a452970c5b4054ad7118ff134b3a6b50a2bb6d0c07c746e8986b28e OpenStdin: true StdinOnce: true User: "1001" WorkingDir: /opt/app-root/src Created: 2016-01-29T13:40:00Z DockerVersion: 1.8.2.fc21 Id: 9d7fd5e2d15495802028c569d544329f4286dcd1c9c085ff5699218dbaa69b43 Parent: 57b08d979c86f4500dc8cad639c9518744c8dd39447c055a3517dc9c18d6fccd Size: 441976279 apiVersion: "1.0" kind: DockerImage dockerImageMetadataVersion: "1.0" dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d 6.7. Working with image streams The following sections describe how to use image streams and image stream tags. 6.7.1. Getting information about image streams You can get general information about the image stream and detailed information about all the tags it is pointing to. Procedure Get general information about the image stream and detailed information about all the tags it is pointing to: USD oc describe is/<image-name> For example: USD oc describe is/python Example output Name: python Namespace: default Created: About a minute ago Labels: <none> Annotations: openshift.io/image.dockerRepositoryCheck=2017-10-02T17:05:11Z Docker Pull Spec: docker-registry.default.svc:5000/default/python Image Lookup: local=false Unique Images: 1 Tags: 1 3.5 tagged from centos/python-35-centos7 * centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 About a minute ago Get all the information available about particular image stream tag: USD oc describe istag/<image-stream>:<tag-name> For example: USD oc describe istag/python:latest Example output Image Name: sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 Docker Image: centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 Name: sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 Created: 2 minutes ago Image Size: 251.2 MB (first layer 2.898 MB, last binary layer 72.26 MB) Image Created: 2 weeks ago Author: <none> Arch: amd64 Entrypoint: container-entrypoint Command: /bin/sh -c USDSTI_SCRIPTS_PATH/usage Working Dir: /opt/app-root/src User: 1001 Exposes Ports: 8080/tcp Docker Labels: build-date=20170801 Note More information is output than shown. 6.7.2. Adding tags to an image stream You can add additional tags to image streams. Procedure Add a tag that points to one of the existing tags by using the `oc tag`command: USD oc tag <image-name:tag1> <image-name:tag2> For example: USD oc tag python:3.5 python:latest Example output Tag python:latest set to python@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25. Confirm the image stream has two tags, one, 3.5 , pointing at the external container image and another tag, latest , pointing to the same image because it was created based on the first tag. USD oc describe is/python Example output Name: python Namespace: default Created: 5 minutes ago Labels: <none> Annotations: openshift.io/image.dockerRepositoryCheck=2017-10-02T17:05:11Z Docker Pull Spec: docker-registry.default.svc:5000/default/python Image Lookup: local=false Unique Images: 1 Tags: 2 latest tagged from python@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 * centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 About a minute ago 3.5 tagged from centos/python-35-centos7 * centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 5 minutes ago 6.7.3. Adding tags for an external image You can add tags for external images. Procedure Add tags pointing to internal or external images, by using the oc tag command for all tag-related operations: USD oc tag <repository/image> <image-name:tag> For example, this command maps the docker.io/python:3.6.0 image to the 3.6 tag in the python image stream. USD oc tag docker.io/python:3.6.0 python:3.6 Example output Tag python:3.6 set to docker.io/python:3.6.0. If the external image is secured, you must create a secret with credentials for accessing that registry. 6.7.4. Updating image stream tags You can update a tag to reflect another tag in an image stream. Procedure Update a tag: USD oc tag <image-name:tag> <image-name:latest> For example, the following updates the latest tag to reflect the 3.6 tag in an image stream: USD oc tag python:3.6 python:latest Example output Tag python:latest set to python@sha256:438208801c4806548460b27bd1fbcb7bb188273d13871ab43f. 6.7.5. Removing image stream tags You can remove old tags from an image stream. Procedure Remove old tags from an image stream: USD oc tag -d <image-name:tag> For example: USD oc tag -d python:3.6 Example output Deleted tag default/python:3.6 See Removing deprecated image stream tags from the Cluster Samples Operator for more information on how the Cluster Samples Operator handles deprecated image stream tags. 6.7.6. Configuring periodic importing of image stream tags When working with an external container image registry, to periodically re-import an image, for example to get latest security updates, you can use the --scheduled flag. Procedure Schedule importing images: USD oc tag <repository/image> <image-name:tag> --scheduled For example: USD oc tag docker.io/python:3.6.0 python:3.6 --scheduled Example output Tag python:3.6 set to import docker.io/python:3.6.0 periodically. This command causes OpenShift Container Platform to periodically update this particular image stream tag. This period is a cluster-wide setting set to 15 minutes by default. Remove the periodic check, re-run above command but omit the --scheduled flag. This will reset its behavior to default. USD oc tag <repositiory/image> <image-name:tag> 6.8. Importing images and image streams from private registries An image stream can be configured to import tag and image metadata from private image registries requiring authentication. This procedures applies if you change the registry that the Cluster Samples Operator uses to pull content from to something other than registry.redhat.io . Note When importing from insecure or secure registries, the registry URL defined in the secret must include the :80 port suffix or the secret is not used when attempting to import from the registry. Procedure You must create a secret object that is used to store your credentials by entering the following command: USD oc create secret generic <secret_name> --from-file=.dockerconfigjson=<file_absolute_path> --type=kubernetes.io/dockerconfigjson After the secret is configured, create the new image stream or enter the oc import-image command: USD oc import-image <imagestreamtag> --from=<image> --confirm During the import process, OpenShift Container Platform picks up the secrets and provides them to the remote party. 6.8.1. Allowing pods to reference images from other secured registries To pull a secured container from other private or secured registries, you must create a pull secret from your container client credentials, such as Docker or Podman, and add it to your service account. Both Docker and Podman use a configuration file to store authentication details to log in to secured or insecure registry: Docker : By default, Docker uses USDHOME/.docker/config.json . Podman : By default, Podman uses USDHOME/.config/containers/auth.json . These files store your authentication information if you have previously logged in to a secured or insecure registry. Note Both Docker and Podman credential files and the associated pull secret can contain multiple references to the same registry if they have unique paths, for example, quay.io and quay.io/<example_repository> . However, neither Docker nor Podman support multiple entries for the exact same registry path. Example config.json file { "auths":{ "cloud.openshift.com":{ "auth":"b3Blb=", "email":"[email protected]" }, "quay.io":{ "auth":"b3Blb=", "email":"[email protected]" }, "quay.io/repository-main":{ "auth":"b3Blb=", "email":"[email protected]" } } } Example pull secret apiVersion: v1 data: .dockerconfigjson: ewogICAiYXV0aHMiOnsKICAgICAgIm0iOnsKICAgICAgIsKICAgICAgICAgImF1dGgiOiJiM0JsYj0iLAogICAgICAgICAiZW1haWwiOiJ5b3VAZXhhbXBsZS5jb20iCiAgICAgIH0KICAgfQp9Cg== kind: Secret metadata: creationTimestamp: "2021-09-09T19:10:11Z" name: pull-secret namespace: default resourceVersion: "37676" uid: e2851531-01bc-48ba-878c-de96cfe31020 type: Opaque Procedure Create a secret from an existing authentication file: For Docker clients using .docker/config.json , enter the following command: USD oc create secret generic <pull_secret_name> \ --from-file=.dockerconfigjson=<path/to/.docker/config.json> \ --type=kubernetes.io/dockerconfigjson For Podman clients using .config/containers/auth.json , enter the following command: USD oc create secret generic <pull_secret_name> \ --from-file=<path/to/.config/containers/auth.json> \ --type=kubernetes.io/podmanconfigjson If you do not already have a Docker credentials file for the secured registry, you can create a secret by running: USD oc create secret docker-registry <pull_secret_name> \ --docker-server=<registry_server> \ --docker-username=<user_name> \ --docker-password=<password> \ --docker-email=<email> To use a secret for pulling images for pods, you must add the secret to your service account. The name of the service account in this example should match the name of the service account the pod uses. The default service account is default : USD oc secrets link default <pull_secret_name> --for=pull 6.9. Importing a manifest list through ImageStreamImport You can use the ImageStreamImport resource to find and import image manifests from other container image registries into the cluster. Individual images or an entire image repository can be imported. Use the following procedure to import a manifest list through the ImageStreamImport object with the importMode value. Procedure Create an ImageStreamImport YAML file and set the importMode parameter to PreserveOriginal on the tags that you will import as a manifest list: apiVersion: image.openshift.io/v1 kind: ImageStreamImport metadata: name: app namespace: myapp spec: import: true images: - from: kind: DockerImage name: <registry>/<user_name>/<image_name> to: name: latest referencePolicy: type: Source importPolicy: importMode: "PreserveOriginal" Create the ImageStreamImport by running the following command: USD oc create -f <your_imagestreamimport.yaml> 6.9.1. importMode configuration fields The following table describes the configuration fields available for the importMode value: Parameter Description Legacy The default value for importMode . When active, the manifest list is discarded, and a single sub-manifest is imported. The platform is chosen in the following order of priority: Tag annotations Control plane architecture Linux/AMD64 The first manifest in the list PreserveOriginal When active, the original manifest is preserved. For manifest lists, the manifest list and all of its sub-manifests are imported.	[ "apiVersion: image.openshift.io/v1 kind: ImageStream metadata: annotations: openshift.io/generated-by: OpenShiftNewApp labels: app: ruby-sample-build template: application-template-stibuild name: origin-ruby-sample 1 namespace: test spec: {} status: dockerImageRepository: 172.30.56.218:5000/test/origin-ruby-sample 2 tags: - items: - created: 2017-09-02T10:15:09Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d 3 generation: 2 image: sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 4 - created: 2017-09-01T13:40:11Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 generation: 1 image: sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d tag: latest 5", "<image-stream-name>@<image-id>", "origin-ruby-sample@sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d", "kind: ImageStream apiVersion: image.openshift.io/v1 metadata: name: my-image-stream tags: - items: - created: 2017-09-02T10:15:09Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d generation: 2 image: sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 - created: 2017-09-01T13:40:11Z dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:909de62d1f609a717ec433cc25ca5cf00941545c83a01fb31527771e1fab3fc5 generation: 1 image: sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d tag: latest", "<imagestream name>:<tag>", "origin-ruby-sample:latest", "apiVersion: image.openshift.io/v1 kind: ImageStreamMapping metadata: creationTimestamp: null name: origin-ruby-sample namespace: test tag: latest image: dockerImageLayers: - name: sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef size: 0 - name: sha256:ee1dd2cb6df21971f4af6de0f1d7782b81fb63156801cfde2bb47b4247c23c29 size: 196634330 - name: sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef size: 0 - name: sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef size: 0 - name: sha256:ca062656bff07f18bff46be00f40cfbb069687ec124ac0aa038fd676cfaea092 size: 177723024 - name: sha256:63d529c59c92843c395befd065de516ee9ed4995549f8218eac6ff088bfa6b6e size: 55679776 - name: sha256:92114219a04977b5563d7dff71ec4caa3a37a15b266ce42ee8f43dba9798c966 size: 11939149 dockerImageMetadata: Architecture: amd64 Config: Cmd: - /usr/libexec/s2i/run Entrypoint: - container-entrypoint Env: - RACK_ENV=production - OPENSHIFT_BUILD_NAMESPACE=test - OPENSHIFT_BUILD_SOURCE=https://github.com/openshift/ruby-hello-world.git - EXAMPLE=sample-app - OPENSHIFT_BUILD_NAME=ruby-sample-build-1 - PATH=/opt/app-root/src/bin:/opt/app-root/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin - STI_SCRIPTS_URL=image:///usr/libexec/s2i - STI_SCRIPTS_PATH=/usr/libexec/s2i - HOME=/opt/app-root/src - BASH_ENV=/opt/app-root/etc/scl_enable - ENV=/opt/app-root/etc/scl_enable - PROMPT_COMMAND=. /opt/app-root/etc/scl_enable - RUBY_VERSION=2.2 ExposedPorts: 8080/tcp: {} Labels: build-date: 2015-12-23 io.k8s.description: Platform for building and running Ruby 2.2 applications io.k8s.display-name: 172.30.56.218:5000/test/origin-ruby-sample:latest io.openshift.build.commit.author: Ben Parees <[email protected]> io.openshift.build.commit.date: Wed Jan 20 10:14:27 2016 -0500 io.openshift.build.commit.id: 00cadc392d39d5ef9117cbc8a31db0889eedd442 io.openshift.build.commit.message: 'Merge pull request #51 from php-coder/fix_url_and_sti' io.openshift.build.commit.ref: master io.openshift.build.image: centos/ruby-22-centos7@sha256:3a335d7d8a452970c5b4054ad7118ff134b3a6b50a2bb6d0c07c746e8986b28e io.openshift.build.source-location: https://github.com/openshift/ruby-hello-world.git io.openshift.builder-base-version: 8d95148 io.openshift.builder-version: 8847438ba06307f86ac877465eadc835201241df io.openshift.s2i.scripts-url: image:///usr/libexec/s2i io.openshift.tags: builder,ruby,ruby22 io.s2i.scripts-url: image:///usr/libexec/s2i license: GPLv2 name: CentOS Base Image vendor: CentOS User: \"1001\" WorkingDir: /opt/app-root/src Container: 86e9a4a3c760271671ab913616c51c9f3cea846ca524bf07c04a6f6c9e103a76 ContainerConfig: AttachStdout: true Cmd: - /bin/sh - -c - tar -C /tmp -xf - && /usr/libexec/s2i/assemble Entrypoint: - container-entrypoint Env: - RACK_ENV=production - OPENSHIFT_BUILD_NAME=ruby-sample-build-1 - OPENSHIFT_BUILD_NAMESPACE=test - OPENSHIFT_BUILD_SOURCE=https://github.com/openshift/ruby-hello-world.git - EXAMPLE=sample-app - PATH=/opt/app-root/src/bin:/opt/app-root/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin - STI_SCRIPTS_URL=image:///usr/libexec/s2i - STI_SCRIPTS_PATH=/usr/libexec/s2i - HOME=/opt/app-root/src - BASH_ENV=/opt/app-root/etc/scl_enable - ENV=/opt/app-root/etc/scl_enable - PROMPT_COMMAND=. /opt/app-root/etc/scl_enable - RUBY_VERSION=2.2 ExposedPorts: 8080/tcp: {} Hostname: ruby-sample-build-1-build Image: centos/ruby-22-centos7@sha256:3a335d7d8a452970c5b4054ad7118ff134b3a6b50a2bb6d0c07c746e8986b28e OpenStdin: true StdinOnce: true User: \"1001\" WorkingDir: /opt/app-root/src Created: 2016-01-29T13:40:00Z DockerVersion: 1.8.2.fc21 Id: 9d7fd5e2d15495802028c569d544329f4286dcd1c9c085ff5699218dbaa69b43 Parent: 57b08d979c86f4500dc8cad639c9518744c8dd39447c055a3517dc9c18d6fccd Size: 441976279 apiVersion: \"1.0\" kind: DockerImage dockerImageMetadataVersion: \"1.0\" dockerImageReference: 172.30.56.218:5000/test/origin-ruby-sample@sha256:47463d94eb5c049b2d23b03a9530bf944f8f967a0fe79147dd6b9135bf7dd13d", "oc describe is/<image-name>", "oc describe is/python", "Name: python Namespace: default Created: About a minute ago Labels: <none> Annotations: openshift.io/image.dockerRepositoryCheck=2017-10-02T17:05:11Z Docker Pull Spec: docker-registry.default.svc:5000/default/python Image Lookup: local=false Unique Images: 1 Tags: 1 3.5 tagged from centos/python-35-centos7 * centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 About a minute ago", "oc describe istag/<image-stream>:<tag-name>", "oc describe istag/python:latest", "Image Name: sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 Docker Image: centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 Name: sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 Created: 2 minutes ago Image Size: 251.2 MB (first layer 2.898 MB, last binary layer 72.26 MB) Image Created: 2 weeks ago Author: <none> Arch: amd64 Entrypoint: container-entrypoint Command: /bin/sh -c USDSTI_SCRIPTS_PATH/usage Working Dir: /opt/app-root/src User: 1001 Exposes Ports: 8080/tcp Docker Labels: build-date=20170801", "oc tag <image-name:tag1> <image-name:tag2>", "oc tag python:3.5 python:latest", "Tag python:latest set to python@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25.", "oc describe is/python", "Name: python Namespace: default Created: 5 minutes ago Labels: <none> Annotations: openshift.io/image.dockerRepositoryCheck=2017-10-02T17:05:11Z Docker Pull Spec: docker-registry.default.svc:5000/default/python Image Lookup: local=false Unique Images: 1 Tags: 2 latest tagged from python@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 * centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 About a minute ago 3.5 tagged from centos/python-35-centos7 * centos/python-35-centos7@sha256:49c18358df82f4577386404991c51a9559f243e0b1bdc366df25 5 minutes ago", "oc tag <repository/image> <image-name:tag>", "oc tag docker.io/python:3.6.0 python:3.6", "Tag python:3.6 set to docker.io/python:3.6.0.", "oc tag <image-name:tag> <image-name:latest>", "oc tag python:3.6 python:latest", "Tag python:latest set to python@sha256:438208801c4806548460b27bd1fbcb7bb188273d13871ab43f.", "oc tag -d <image-name:tag>", "oc tag -d python:3.6", "Deleted tag default/python:3.6", "oc tag <repository/image> <image-name:tag> --scheduled", "oc tag docker.io/python:3.6.0 python:3.6 --scheduled", "Tag python:3.6 set to import docker.io/python:3.6.0 periodically.", "oc tag <repositiory/image> <image-name:tag>", "oc create secret generic <secret_name> --from-file=.dockerconfigjson=<file_absolute_path> --type=kubernetes.io/dockerconfigjson", "oc import-image <imagestreamtag> --from=<image> --confirm", "{ \"auths\":{ \"cloud.openshift.com\":{ \"auth\":\"b3Blb=\", \"email\":\"[email protected]\" }, \"quay.io\":{ \"auth\":\"b3Blb=\", \"email\":\"[email protected]\" }, \"quay.io/repository-main\":{ \"auth\":\"b3Blb=\", \"email\":\"[email protected]\" } } }", "apiVersion: v1 data: .dockerconfigjson: ewogICAiYXV0aHMiOnsKICAgICAgIm0iOnsKICAgICAgIsKICAgICAgICAgImF1dGgiOiJiM0JsYj0iLAogICAgICAgICAiZW1haWwiOiJ5b3VAZXhhbXBsZS5jb20iCiAgICAgIH0KICAgfQp9Cg== kind: Secret metadata: creationTimestamp: \"2021-09-09T19:10:11Z\" name: pull-secret namespace: default resourceVersion: \"37676\" uid: e2851531-01bc-48ba-878c-de96cfe31020 type: Opaque", "oc create secret generic <pull_secret_name> --from-file=.dockerconfigjson=<path/to/.docker/config.json> --type=kubernetes.io/dockerconfigjson", "oc create secret generic <pull_secret_name> --from-file=<path/to/.config/containers/auth.json> --type=kubernetes.io/podmanconfigjson", "oc create secret docker-registry <pull_secret_name> --docker-server=<registry_server> --docker-username=<user_name> --docker-password=<password> --docker-email=<email>", "oc secrets link default <pull_secret_name> --for=pull", "apiVersion: image.openshift.io/v1 kind: ImageStreamImport metadata: name: app namespace: myapp spec: import: true images: - from: kind: DockerImage name: <registry>/<user_name>/<image_name> to: name: latest referencePolicy: type: Source importPolicy: importMode: \"PreserveOriginal\"", "oc create -f <your_imagestreamimport.yaml>" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.12/html/images/managing-image-streams
Chapter 48. Storage	Chapter 48. Storage Multi-queue I/O scheduling for SCSI Red Hat Enterprise Linux 7 includes a new multiple-queue I/O scheduling mechanism for block devices known as blk-mq. The scsi-mq package allows the Small Computer System Interface (SCSI) subsystem to make use of this new queuing mechanism. This functionality is provided as a Technology Preview and is not enabled by default. To enable it, add scsi_mod.use_blk_mq=Y to the kernel command line. Although blk-mq is intended to offer improved performance, particularly for low-latency devices, it is not guaranteed to always provide better performance. In particular, in some cases, enabling scsi-mq can result in significantly worse performance, especially on systems with many CPUs. (BZ#1109348) Targetd plug-in from the libStorageMgmt API Since Red Hat Enterprise Linux 7.1, storage array management with libStorageMgmt, a storage array independent API, has been fully supported. The provided API is stable, consistent, and allows developers to programmatically manage different storage arrays and utilize the hardware-accelerated features provided. System administrators can also use libStorageMgmt to manually configure storage and to automate storage management tasks with the included command-line interface. The Targetd plug-in is not fully supported and remains a Technology Preview. (BZ#1119909) SCSI-MQ as a Technology Preview in the qla2xxx and lpfc drivers The qla2xxx driver updated in Red Hat Enterprise Linux 7.4 can enable the use of SCSI-MQ (multiqueue) with the ql2xmqsupport=1 module parameter. The default value is 0 (disabled). The SCSI-MQ functionality is provided as a Technology Preview when used with the qla2xxx or the lpfc drivers. Note that a recent performance testing at Red Hat with async IO over Fibre Channel adapters using SCSI-MQ has shown significant performance degradation under certain conditions. (BZ#1414957) NVMe/FC available as a Technology Preview in Qlogic adapters using the qla2xxx driver The NVMe over Fibre Channel (NVMe/FC) transport type is available as a Technology Preview in Qlogic adapters using the qla2xxx driver. NVMe/FC is an additional fabric transport type for the Nonvolatile Memory Express (NVMe) protocol, in addition to the Remote Direct Memory Access (RDMA) protocol that was previously introduced in Red Hat Enterprise Linux. NVMe/FC provides a higher-performance, lower-latency I/O protocol over existing Fibre Channel infrastructure. This is especially important with solid-state storage arrays, because it allows the performance benefits of NVMe storage to be passed through the fabric transport, rather than being encapsulated in a different protocol, SCSI. Note that since Red Hat Enterprise Linux 7.6, NVMe/FC is fully supported with Broadcom Emulex Fibre Channel 32Gbit adapters using the lpfc driver. See the restrictions listed in the New Features part. (BZ# 1387768 , BZ#1454386)	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/7.6_release_notes/technology_previews_storage
Providing feedback on Red Hat documentation	Providing feedback on Red Hat documentation We appreciate and prioritize your feedback regarding our documentation. Provide as much detail as possible, so that your request can be quickly addressed. Prerequisites You are logged in to the Red Hat Customer Portal. Procedure To provide feedback, perform the following steps: Click the following link: Create Issue Describe the issue or enhancement in the Summary text box. Provide details about the issue or requested enhancement in the Description text box. Type your name in the Reporter text box. Click the Create button. This action creates a documentation ticket and routes it to the appropriate documentation team. Thank you for taking the time to provide feedback.	null	https://docs.redhat.com/en/documentation/red_hat_insights/1-latest/html/generating_advisor_service_reports_with_fedramp/proc-providing-feedback-on-redhat-documentation