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Chapter 7. Rule Audit	Chapter 7. Rule Audit Rule audit allows the auditing of rules which have been triggered by all the rules that were activated at some point. The Rule Audit list view shows you a list of every time an event came in that matched a condition within a rulebook and triggered an action. The list shows you rules within your rulebook and each heading matches up to a rule that has been executed. 7.1. Viewing rule audit details From the Rule Audit list view you can check the event that triggered specific actions. Procedure From the navigation panel select Rule Audit . Select the desired rule, this brings you to the Details tab. From here you can view when it was created, when it was last fired, and the rulebook activation that it corresponds to. 7.2. Viewing rule audit events Procedure From the navigation panel select Rule Audit . Select the desired rule, this brings you to the Details tab. To view all the events that triggered an action, select the Events tab. This shows you the event that triggered actions. Select an event to view the Event log , along with the Source type and Timestamp . 7.3. Viewing rule audit actions Procedure From the navigation panel select Rule Audit . Select the desired rule, this brings you to the Actions tab. From here you can view executed actions that were taken. Some actions are linked out to automation controller where you can view the output.	null	https://docs.redhat.com/en/documentation/red_hat_ansible_automation_platform/2.4/html/event-driven_ansible_controller_user_guide/eda-rule-audit
2.5.4. SELinux: Avoid SELinux on GFS2	2.5.4. SELinux: Avoid SELinux on GFS2 Security Enhanced Linux (SELinux) is highly recommended for security reasons in most situations, but it is not supported for use with GFS2. SELinux stores information using extended attributes about every file system object, and SELinux labels on GFS2 file systems can get out of sync between cluster nodes because of how they are cached in memory. When mounting a GFS2 file system, you must ensure that SELinux will not attempt to read the seclabel element on each file system object by using one of the context options as described on the mount (8) man page; SELinux will assume that all content in the file system is labeled with the seclabel element provided in the context mount options. This will also speed up processing as it avoids another disk read of the extended attribute block that could contain seclabel elements. For example, on a system with SELinux in enforcing mode, you can use the following mount command to mount the GFS2 file system if the file system is going to contain Apache content. This label will apply to the entire file system; it remains in memory and is not written to disk. If you are not sure whether the file system will contain Apache content, you can use the labels public_content_rw_t or public_content_t , or you could define a new label altogether and define a policy around it. Note that in a Pacemaker cluster you should always use Pacemaker to manage a GFS2 file system. You can specify the mount options when you create a GFS2 file system resource, as described in Chapter 6, Configuring a GFS2 File System in a Pacemaker Cluster .	[ "mount -t gfs2 -o context=system_u:object_r:httpd_sys_content_t:s0 /dev/mapper/xyz/mnt/gfs2", "mount -t gfs2 -o context=system_u:object_r:httpd_sys_content_t:s0 /dev/mapper/xyz/mnt/gfs2" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/global_file_system_2/s2-selinux-gfs2-gfs2
Preface	Preface These release notes list new features, features in technology preview, known issues, and issues fixed in Red Hat Decision Manager 7.13.	null	https://docs.redhat.com/en/documentation/red_hat_decision_manager/7.13/html/release_notes_for_red_hat_decision_manager_7.13/pr01
Chapter 4. Configuring user workload monitoring	Chapter 4. Configuring user workload monitoring 4.1. Preparing to configure the user workload monitoring stack This section explains which user-defined monitoring components can be configured, how to enable user workload monitoring, and how to prepare for configuring the user workload monitoring stack. Important Not all configuration parameters for the monitoring stack are exposed. Only the parameters and fields listed in the Config map reference for the Cluster Monitoring Operator are supported for configuration. The monitoring stack imposes additional resource requirements. Consult the computing resources recommendations in Scaling the Cluster Monitoring Operator and verify that you have sufficient resources. 4.1.1. Configurable monitoring components This table shows the monitoring components you can configure and the keys used to specify the components in the user-workload-monitoring-config config map. Table 4.1. Configurable monitoring components for user-defined projects Component user-workload-monitoring-config config map key Prometheus Operator prometheusOperator Prometheus prometheus Alertmanager alertmanager Thanos Ruler thanosRuler Warning Different configuration changes to the ConfigMap object result in different outcomes: The pods are not redeployed. Therefore, there is no service outage. The affected pods are redeployed: For single-node clusters, this results in temporary service outage. For multi-node clusters, because of high-availability, the affected pods are gradually rolled out and the monitoring stack remains available. Configuring and resizing a persistent volume always results in a service outage, regardless of high availability. Each procedure that requires a change in the config map includes its expected outcome. 4.1.2. Enabling monitoring for user-defined projects In OpenShift Container Platform, you can enable monitoring for user-defined projects in addition to the default platform monitoring. You can monitor your own projects in OpenShift Container Platform without the need for an additional monitoring solution. Using this feature centralizes monitoring for core platform components and user-defined projects. Note Versions of Prometheus Operator installed using Operator Lifecycle Manager (OLM) are not compatible with user-defined monitoring. Therefore, custom Prometheus instances installed as a Prometheus custom resource (CR) managed by the OLM Prometheus Operator are not supported in OpenShift Container Platform. 4.1.2.1. Enabling monitoring for user-defined projects Cluster administrators can enable monitoring for user-defined projects by setting the enableUserWorkload: true field in the cluster monitoring ConfigMap object. Important You must remove any custom Prometheus instances before enabling monitoring for user-defined projects. Note You must have access to the cluster as a user with the cluster-admin cluster role to enable monitoring for user-defined projects in OpenShift Container Platform. Cluster administrators can then optionally grant users permission to configure the components that are responsible for monitoring user-defined projects. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have installed the OpenShift CLI ( oc ). You have created the cluster-monitoring-config ConfigMap object. You have optionally created and configured the user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring project. You can add configuration options to this ConfigMap object for the components that monitor user-defined projects. Note Every time you save configuration changes to the user-workload-monitoring-config ConfigMap object, the pods in the openshift-user-workload-monitoring project are redeployed. It might sometimes take a while for these components to redeploy. Procedure Edit the cluster-monitoring-config ConfigMap object: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add enableUserWorkload: true under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: \| enableUserWorkload: true 1 1 When set to true , the enableUserWorkload parameter enables monitoring for user-defined projects in a cluster. Save the file to apply the changes. Monitoring for user-defined projects is then enabled automatically. Note If you enable monitoring for user-defined projects, the user-workload-monitoring-config ConfigMap object is created by default. Verify that the prometheus-operator , prometheus-user-workload , and thanos-ruler-user-workload pods are running in the openshift-user-workload-monitoring project. It might take a short while for the pods to start: USD oc -n openshift-user-workload-monitoring get pod Example output NAME READY STATUS RESTARTS AGE prometheus-operator-6f7b748d5b-t7nbg 2/2 Running 0 3h prometheus-user-workload-0 4/4 Running 1 3h prometheus-user-workload-1 4/4 Running 1 3h thanos-ruler-user-workload-0 3/3 Running 0 3h thanos-ruler-user-workload-1 3/3 Running 0 3h Additional resources User workload monitoring first steps 4.1.2.2. Granting users permission to configure monitoring for user-defined projects As a cluster administrator, you can assign the user-workload-monitoring-config-edit role to a user. This grants permission to configure and manage monitoring for user-defined projects without giving them permission to configure and manage core OpenShift Container Platform monitoring components. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. The user account that you are assigning the role to already exists. You have installed the OpenShift CLI ( oc ). Procedure Assign the user-workload-monitoring-config-edit role to a user in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring adm policy add-role-to-user \ user-workload-monitoring-config-edit <user> \ --role-namespace openshift-user-workload-monitoring Verify that the user is correctly assigned to the user-workload-monitoring-config-edit role by displaying the related role binding: USD oc describe rolebinding <role_binding_name> -n openshift-user-workload-monitoring Example command USD oc describe rolebinding user-workload-monitoring-config-edit -n openshift-user-workload-monitoring Example output Name: user-workload-monitoring-config-edit Labels: <none> Annotations: <none> Role: Kind: Role Name: user-workload-monitoring-config-edit Subjects: Kind Name Namespace ---- ---- --------- User user1 1 1 In this example, user1 is assigned to the user-workload-monitoring-config-edit role. 4.1.3. Enabling alert routing for user-defined projects In OpenShift Container Platform, an administrator can enable alert routing for user-defined projects. This process consists of the following steps: Enable alert routing for user-defined projects: Use the default platform Alertmanager instance. Use a separate Alertmanager instance only for user-defined projects. Grant users permission to configure alert routing for user-defined projects. After you complete these steps, developers and other users can configure custom alerts and alert routing for their user-defined projects. Additional resources Understanding alert routing for user-defined projects 4.1.3.1. Enabling the platform Alertmanager instance for user-defined alert routing You can allow users to create user-defined alert routing configurations that use the main platform instance of Alertmanager. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config ConfigMap object: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add enableUserAlertmanagerConfig: true in the alertmanagerMain section under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: \| # ... alertmanagerMain: enableUserAlertmanagerConfig: true 1 # ... 1 Set the enableUserAlertmanagerConfig value to true to allow users to create user-defined alert routing configurations that use the main platform instance of Alertmanager. Save the file to apply the changes. The new configuration is applied automatically. 4.1.3.2. Enabling a separate Alertmanager instance for user-defined alert routing In some clusters, you might want to deploy a dedicated Alertmanager instance for user-defined projects, which can help reduce the load on the default platform Alertmanager instance and can better separate user-defined alerts from default platform alerts. In these cases, you can optionally enable a separate instance of Alertmanager to send alerts for user-defined projects only. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config ConfigMap object: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add enabled: true and enableAlertmanagerConfig: true in the alertmanager section under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: enabled: true 1 enableAlertmanagerConfig: true 2 1 Set the enabled value to true to enable a dedicated instance of the Alertmanager for user-defined projects in a cluster. Set the value to false or omit the key entirely to disable the Alertmanager for user-defined projects. If you set this value to false or if the key is omitted, user-defined alerts are routed to the default platform Alertmanager instance. 2 Set the enableAlertmanagerConfig value to true to enable users to define their own alert routing configurations with AlertmanagerConfig objects. Save the file to apply the changes. The dedicated instance of Alertmanager for user-defined projects starts automatically. Verification Verify that the user-workload Alertmanager instance has started: # oc -n openshift-user-workload-monitoring get alertmanager Example output NAME VERSION REPLICAS AGE user-workload 0.24.0 2 100s 4.1.3.3. Granting users permission to configure alert routing for user-defined projects You can grant users permission to configure alert routing for user-defined projects. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have enabled monitoring for user-defined projects. The user account that you are assigning the role to already exists. You have installed the OpenShift CLI ( oc ). Procedure Assign the alert-routing-edit cluster role to a user in the user-defined project: USD oc -n <namespace> adm policy add-role-to-user alert-routing-edit <user> 1 1 For <namespace> , substitute the namespace for the user-defined project, such as ns1 . For <user> , substitute the username for the account to which you want to assign the role. Additional resources Configuring alert notifications 4.1.4. Granting users permissions for monitoring for user-defined projects As a cluster administrator, you can monitor all core OpenShift Container Platform and user-defined projects. You can also grant developers and other users different permissions: Monitoring user-defined projects Configuring the components that monitor user-defined projects Configuring alert routing for user-defined projects Managing alerts and silences for user-defined projects You can grant the permissions by assigning one of the following monitoring roles or cluster roles: Table 4.2. Monitoring roles Role name Description Project user-workload-monitoring-config-edit Users with this role can edit the user-workload-monitoring-config ConfigMap object to configure Prometheus, Prometheus Operator, Alertmanager, and Thanos Ruler for user-defined workload monitoring. openshift-user-workload-monitoring monitoring-alertmanager-api-reader Users with this role have read access to the user-defined Alertmanager API for all projects, if the user-defined Alertmanager is enabled. openshift-user-workload-monitoring monitoring-alertmanager-api-writer Users with this role have read and write access to the user-defined Alertmanager API for all projects, if the user-defined Alertmanager is enabled. openshift-user-workload-monitoring Table 4.3. Monitoring cluster roles Cluster role name Description Project monitoring-rules-view Users with this cluster role have read access to PrometheusRule custom resources (CRs) for user-defined projects. They can also view the alerts and silences in the Developer perspective of the OpenShift Container Platform web console. Can be bound with RoleBinding to any user project. monitoring-rules-edit Users with this cluster role can create, modify, and delete PrometheusRule CRs for user-defined projects. They can also manage alerts and silences in the Developer perspective of the OpenShift Container Platform web console. Can be bound with RoleBinding to any user project. monitoring-edit Users with this cluster role have the same privileges as users with the monitoring-rules-edit cluster role. Additionally, users can create, read, modify, and delete ServiceMonitor and PodMonitor resources to scrape metrics from services and pods. Can be bound with RoleBinding to any user project. alert-routing-edit Users with this cluster role can create, update, and delete AlertmanagerConfig CRs for user-defined projects. Can be bound with RoleBinding to any user project. Additional resources Granting users permission to configure monitoring for user-defined projects Granting users permission to configure alert routing for user-defined projects 4.1.4.1. Granting user permissions by using the web console You can grant users permissions for the openshift-monitoring project or their own projects, by using the OpenShift Container Platform web console. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. The user account that you are assigning the role to already exists. Procedure In the Administrator perspective of the OpenShift Container Platform web console, go to User Management RoleBindings Create binding . In the Binding Type section, select the Namespace Role Binding type. In the Name field, enter a name for the role binding. In the Namespace field, select the project where you want to grant the access. Important The monitoring role or cluster role permissions that you grant to a user by using this procedure apply only to the project that you select in the Namespace field. Select a monitoring role or cluster role from the Role Name list. In the Subject section, select User . In the Subject Name field, enter the name of the user. Select Create to apply the role binding. 4.1.4.2. Granting user permissions by using the CLI You can grant users permissions for the openshift-monitoring project or their own projects, by using the OpenShift CLI ( oc ). Important Whichever role or cluster role you choose, you must bind it against a specific project as a cluster administrator. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. The user account that you are assigning the role to already exists. You have installed the OpenShift CLI ( oc ). Procedure To assign a monitoring role to a user for a project, enter the following command: USD oc adm policy add-role-to-user <role> <user> -n <namespace> --role-namespace <namespace> 1 1 Substitute <role> with the wanted monitoring role, <user> with the user to whom you want to assign the role, and <namespace> with the project where you want to grant the access. To assign a monitoring cluster role to a user for a project, enter the following command: USD oc adm policy add-cluster-role-to-user <cluster-role> <user> -n <namespace> 1 1 Substitute <cluster-role> with the wanted monitoring cluster role, <user> with the user to whom you want to assign the cluster role, and <namespace> with the project where you want to grant the access. 4.1.5. Excluding a user-defined project from monitoring Individual user-defined projects can be excluded from user workload monitoring. To do so, add the openshift.io/user-monitoring label to the project's namespace with a value of false . Procedure Add the label to the project namespace: USD oc label namespace my-project 'openshift.io/user-monitoring=false' To re-enable monitoring, remove the label from the namespace: USD oc label namespace my-project 'openshift.io/user-monitoring-' Note If there were any active monitoring targets for the project, it may take a few minutes for Prometheus to stop scraping them after adding the label. 4.1.6. Disabling monitoring for user-defined projects After enabling monitoring for user-defined projects, you can disable it again by setting enableUserWorkload: false in the cluster monitoring ConfigMap object. Note Alternatively, you can remove enableUserWorkload: true to disable monitoring for user-defined projects. Procedure Edit the cluster-monitoring-config ConfigMap object: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Set enableUserWorkload: to false under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: \| enableUserWorkload: false Save the file to apply the changes. Monitoring for user-defined projects is then disabled automatically. Check that the prometheus-operator , prometheus-user-workload and thanos-ruler-user-workload pods are terminated in the openshift-user-workload-monitoring project. This might take a short while: USD oc -n openshift-user-workload-monitoring get pod Example output No resources found in openshift-user-workload-monitoring project. Note The user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring project is not automatically deleted when monitoring for user-defined projects is disabled. This is to preserve any custom configurations that you may have created in the ConfigMap object. 4.2. Configuring performance and scalability for user workload monitoring You can configure the monitoring stack to optimize the performance and scale of your clusters. The following documentation provides information about how to distribute the monitoring components and control the impact of the monitoring stack on CPU and memory resources. 4.2.1. Controlling the placement and distribution of monitoring components You can move the monitoring stack components to specific nodes: Use the nodeSelector constraint with labeled nodes to move any of the monitoring stack components to specific nodes. Assign tolerations to enable moving components to tainted nodes. By doing so, you control the placement and distribution of the monitoring components across a cluster. By controlling placement and distribution of monitoring components, you can optimize system resource use, improve performance, and separate workloads based on specific requirements or policies. Additional resources Using node selectors to move monitoring components 4.2.1.1. Moving monitoring components to different nodes You can move any of the components that monitor workloads for user-defined projects to specific worker nodes. Warning It is not permitted to move components to control plane or infrastructure nodes. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure If you have not done so yet, add a label to the nodes on which you want to run the monitoring components: USD oc label nodes <node_name> <node_label> 1 1 Replace <node_name> with the name of the node where you want to add the label. Replace <node_label> with the name of the wanted label. Edit the user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Specify the node labels for the nodeSelector constraint for the component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| # ... <component>: 1 nodeSelector: <node_label_1> 2 <node_label_2> 3 # ... 1 Substitute <component> with the appropriate monitoring stack component name. 2 Substitute <node_label_1> with the label you added to the node. 3 Optional: Specify additional labels. If you specify additional labels, the pods for the component are only scheduled on the nodes that contain all of the specified labels. Note If monitoring components remain in a Pending state after configuring the nodeSelector constraint, check the pod events for errors relating to taints and tolerations. Save the file to apply the changes. The components specified in the new configuration are automatically moved to the new nodes, and the pods affected by the new configuration are redeployed. Additional resources Enabling monitoring for user-defined projects Understanding how to update labels on nodes Placing pods on specific nodes using node selectors nodeSelector (Kubernetes documentation) 4.2.1.2. Assigning tolerations to monitoring components You can assign tolerations to the components that monitor user-defined projects, to enable moving them to tainted worker nodes. Scheduling is not permitted on control plane or infrastructure nodes. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Specify tolerations for the component: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: tolerations: <toleration_specification> Substitute <component> and <toleration_specification> accordingly. For example, oc adm taint nodes node1 key1=value1:NoSchedule adds a taint to node1 with the key key1 and the value value1 . This prevents monitoring components from deploying pods on node1 unless a toleration is configured for that taint. The following example configures the thanosRuler component to tolerate the example taint: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: tolerations: - key: "key1" operator: "Equal" value: "value1" effect: "NoSchedule" Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources Enabling monitoring for user-defined projects Controlling pod placement using node taints Taints and Tolerations (Kubernetes documentation) 4.2.2. Managing CPU and memory resources for monitoring components You can ensure that the containers that run monitoring components have enough CPU and memory resources by specifying values for resource limits and requests for those components. You can configure these limits and requests for monitoring components that monitor user-defined projects in the openshift-user-workload-monitoring namespace. 4.2.2.1. Specifying limits and requests To configure CPU and memory resources, specify values for resource limits and requests in the user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring namespace. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add values to define resource limits and requests for each component you want to configure. Important Ensure that the value set for a limit is always higher than the value set for a request. Otherwise, an error will occur, and the container will not run. Example of setting resource limits and requests apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheus: resources: limits: cpu: 500m memory: 3Gi requests: cpu: 200m memory: 500Mi thanosRuler: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources About specifying limits and requests for monitoring components Kubernetes requests and limits documentation (Kubernetes documentation) 4.2.3. Controlling the impact of unbound metrics attributes in user-defined projects Cluster administrators can use the following measures to control the impact of unbound metrics attributes in user-defined projects: Limit the number of samples that can be accepted per target scrape in user-defined projects Limit the number of scraped labels, the length of label names, and the length of label values Create alerts that fire when a scrape sample threshold is reached or when the target cannot be scraped Note Limiting scrape samples can help prevent the issues caused by adding many unbound attributes to labels. Developers can also prevent the underlying cause by limiting the number of unbound attributes that they define for metrics. Using attributes that are bound to a limited set of possible values reduces the number of potential key-value pair combinations. Additional resources Controlling the impact of unbound metrics attributes in user-defined projects Enabling monitoring for user-defined projects Determining why Prometheus is consuming a lot of disk space 4.2.3.1. Setting scrape sample and label limits for user-defined projects You can limit the number of samples that can be accepted per target scrape in user-defined projects. You can also limit the number of scraped labels, the length of label names, and the length of label values. Warning If you set sample or label limits, no further sample data is ingested for that target scrape after the limit is reached. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add the enforcedSampleLimit configuration to data/config.yaml to limit the number of samples that can be accepted per target scrape in user-defined projects: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: enforcedSampleLimit: 50000 1 1 A value is required if this parameter is specified. This enforcedSampleLimit example limits the number of samples that can be accepted per target scrape in user-defined projects to 50,000. Add the enforcedLabelLimit , enforcedLabelNameLengthLimit , and enforcedLabelValueLengthLimit configurations to data/config.yaml to limit the number of scraped labels, the length of label names, and the length of label values in user-defined projects: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: enforcedLabelLimit: 500 1 enforcedLabelNameLengthLimit: 50 2 enforcedLabelValueLengthLimit: 600 3 1 Specifies the maximum number of labels per scrape. The default value is 0 , which specifies no limit. 2 Specifies the maximum length in characters of a label name. The default value is 0 , which specifies no limit. 3 Specifies the maximum length in characters of a label value. The default value is 0 , which specifies no limit. Save the file to apply the changes. The limits are applied automatically. 4.2.3.2. Creating scrape sample alerts You can create alerts that notify you when: The target cannot be scraped or is not available for the specified for duration A scrape sample threshold is reached or is exceeded for the specified for duration Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have limited the number of samples that can be accepted per target scrape in user-defined projects, by using enforcedSampleLimit . You have installed the OpenShift CLI ( oc ). Procedure Create a YAML file with alerts that inform you when the targets are down and when the enforced sample limit is approaching. The file in this example is called monitoring-stack-alerts.yaml : apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: labels: prometheus: k8s role: alert-rules name: monitoring-stack-alerts 1 namespace: ns1 2 spec: groups: - name: general.rules rules: - alert: TargetDown 3 annotations: message: '{{ printf "%.4g" USDvalue }}% of the {{ USDlabels.job }}/{{ USDlabels.service }} targets in {{ USDlabels.namespace }} namespace are down.' 4 expr: 100 * (count(up == 0) BY (job, namespace, service) / count(up) BY (job, namespace, service)) > 10 for: 10m 5 labels: severity: warning 6 - alert: ApproachingEnforcedSamplesLimit 7 annotations: message: '{{ USDlabels.container }} container of the {{ USDlabels.pod }} pod in the {{ USDlabels.namespace }} namespace consumes {{ USDvalue \| humanizePercentage }} of the samples limit budget.' 8 expr: scrape_samples_scraped/50000 > 0.8 9 for: 10m 10 labels: severity: warning 11 1 Defines the name of the alerting rule. 2 Specifies the user-defined project where the alerting rule will be deployed. 3 The TargetDown alert will fire if the target cannot be scraped or is not available for the for duration. 4 The message that will be output when the TargetDown alert fires. 5 The conditions for the TargetDown alert must be true for this duration before the alert is fired. 6 Defines the severity for the TargetDown alert. 7 The ApproachingEnforcedSamplesLimit alert will fire when the defined scrape sample threshold is reached or exceeded for the specified for duration. 8 The message that will be output when the ApproachingEnforcedSamplesLimit alert fires. 9 The threshold for the ApproachingEnforcedSamplesLimit alert. In this example the alert will fire when the number of samples per target scrape has exceeded 80% of the enforced sample limit of 50000 . The for duration must also have passed before the alert will fire. The <number> in the expression scrape_samples_scraped/<number> > <threshold> must match the enforcedSampleLimit value defined in the user-workload-monitoring-config ConfigMap object. 10 The conditions for the ApproachingEnforcedSamplesLimit alert must be true for this duration before the alert is fired. 11 Defines the severity for the ApproachingEnforcedSamplesLimit alert. Apply the configuration to the user-defined project: USD oc apply -f monitoring-stack-alerts.yaml 4.2.4. Configuring pod topology spread constraints You can configure pod topology spread constraints for all the pods for user-defined monitoring to control how pod replicas are scheduled to nodes across zones. This ensures that the pods are highly available and run more efficiently, because workloads are spread across nodes in different data centers or hierarchical infrastructure zones. You can configure pod topology spread constraints for monitoring pods by using the user-workload-monitoring-config config map. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add the following settings under the data/config.yaml field to configure pod topology spread constraints: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 topologySpreadConstraints: - maxSkew: <n> 2 topologyKey: <key> 3 whenUnsatisfiable: <value> 4 labelSelector: 5 <match_option> 1 Specify a name of the component for which you want to set up pod topology spread constraints. 2 Specify a numeric value for maxSkew , which defines the degree to which pods are allowed to be unevenly distributed. 3 Specify a key of node labels for topologyKey . Nodes that have a label with this key and identical values are considered to be in the same topology. The scheduler tries to put a balanced number of pods into each domain. 4 Specify a value for whenUnsatisfiable . Available options are DoNotSchedule and ScheduleAnyway . Specify DoNotSchedule if you want the maxSkew value to define the maximum difference allowed between the number of matching pods in the target topology and the global minimum. Specify ScheduleAnyway if you want the scheduler to still schedule the pod but to give higher priority to nodes that might reduce the skew. 5 Specify labelSelector to find matching pods. Pods that match this label selector are counted to determine the number of pods in their corresponding topology domain. Example configuration for Thanos Ruler apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: topologySpreadConstraints: - maxSkew: 1 topologyKey: monitoring whenUnsatisfiable: ScheduleAnyway labelSelector: matchLabels: app.kubernetes.io/name: thanos-ruler Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources About pod topology spread constraints for monitoring Controlling pod placement by using pod topology spread constraints Pod Topology Spread Constraints (Kubernetes documentation) 4.3. Storing and recording data for user workload monitoring Store and record your metrics and alerting data, configure logs to specify which activities are recorded, control how long Prometheus retains stored data, and set the maximum amount of disk space for the data. These actions help you protect your data and use them for troubleshooting. 4.3.1. Configuring persistent storage Run cluster monitoring with persistent storage to gain the following benefits: Protect your metrics and alerting data from data loss by storing them in a persistent volume (PV). As a result, they can survive pods being restarted or recreated. Avoid getting duplicate notifications and losing silences for alerts when the Alertmanager pods are restarted. For production environments, it is highly recommended to configure persistent storage. Important In multi-node clusters, you must configure persistent storage for Prometheus, Alertmanager, and Thanos Ruler to ensure high availability. 4.3.1.1. Persistent storage prerequisites Dedicate sufficient persistent storage to ensure that the disk does not become full. Use Filesystem as the storage type value for the volumeMode parameter when you configure the persistent volume. Important Do not use a raw block volume, which is described with volumeMode: Block in the PersistentVolume resource. Prometheus cannot use raw block volumes. Prometheus does not support file systems that are not POSIX compliant. For example, some NFS file system implementations are not POSIX compliant. If you want to use an NFS file system for storage, verify with the vendor that their NFS implementation is fully POSIX compliant. 4.3.1.2. Configuring a persistent volume claim To use a persistent volume (PV) for monitoring components, you must configure a persistent volume claim (PVC). Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add your PVC configuration for the component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 volumeClaimTemplate: spec: storageClassName: <storage_class> 2 resources: requests: storage: <amount_of_storage> 3 1 Specify the monitoring component for which you want to configure the PVC. 2 Specify an existing storage class. If a storage class is not specified, the default storage class is used. 3 Specify the amount of required storage. The following example configures a PVC that claims persistent storage for Thanos Ruler: Example PVC configuration apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: volumeClaimTemplate: spec: storageClassName: my-storage-class resources: requests: storage: 10Gi Note Storage requirements for the thanosRuler component depend on the number of rules that are evaluated and how many samples each rule generates. Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed and the new storage configuration is applied. Warning When you update the config map with a PVC configuration, the affected StatefulSet object is recreated, resulting in a temporary service outage. Additional resources Understanding persistent storage PersistentVolumeClaims (Kubernetes documentation) 4.3.1.3. Resizing a persistent volume You can resize a persistent volume (PV) for the instances of Prometheus, Thanos Ruler, and Alertmanager. You need to manually expand a persistent volume claim (PVC), and then update the config map in which the component is configured. Important You can only expand the size of the PVC. Shrinking the storage size is not possible. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have configured at least one PVC for components that monitor user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Manually expand a PVC with the updated storage request. For more information, see "Expanding persistent volume claims (PVCs) with a file system" in Expanding persistent volumes . Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add a new storage size for the PVC configuration for the component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 volumeClaimTemplate: spec: resources: requests: storage: <amount_of_storage> 2 1 The component for which you want to change the storage size. 2 Specify the new size for the storage volume. It must be greater than the value. The following example sets the new PVC request to 20 gigabytes for Thanos Ruler: Example storage configuration for thanosRuler apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: volumeClaimTemplate: spec: resources: requests: storage: 20Gi Note Storage requirements for the thanosRuler component depend on the number of rules that are evaluated and how many samples each rule generates. Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Warning When you update the config map with a new storage size, the affected StatefulSet object is recreated, resulting in a temporary service outage. Additional resources Prometheus database storage requirements Expanding persistent volume claims (PVCs) with a file system 4.3.2. Modifying retention time and size for Prometheus metrics data By default, Prometheus retains metrics data for 24 hours for monitoring for user-defined projects. You can modify the retention time for the Prometheus instance to change when the data is deleted. You can also set the maximum amount of disk space the retained metrics data uses. Note Data compaction occurs every two hours. Therefore, a persistent volume (PV) might fill up before compaction, potentially exceeding the retentionSize limit. In such cases, the KubePersistentVolumeFillingUp alert fires until the space on a PV is lower than the retentionSize limit. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add the retention time and size configuration under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: retention: <time_specification> 1 retentionSize: <size_specification> 2 1 The retention time: a number directly followed by ms (milliseconds), s (seconds), m (minutes), h (hours), d (days), w (weeks), or y (years). You can also combine time values for specific times, such as 1h30m15s . 2 The retention size: a number directly followed by B (bytes), KB (kilobytes), MB (megabytes), GB (gigabytes), TB (terabytes), PB (petabytes), and EB (exabytes). The following example sets the retention time to 24 hours and the retention size to 10 gigabytes for the Prometheus instance: Example of setting retention time for Prometheus apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: retention: 24h retentionSize: 10GB Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. 4.3.2.1. Modifying the retention time for Thanos Ruler metrics data By default, for user-defined projects, Thanos Ruler automatically retains metrics data for 24 hours. You can modify the retention time to change how long this data is retained by specifying a time value in the user-workload-monitoring-config config map in the openshift-user-workload-monitoring namespace. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add the retention time configuration under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: retention: <time_specification> 1 1 Specify the retention time in the following format: a number directly followed by ms (milliseconds), s (seconds), m (minutes), h (hours), d (days), w (weeks), or y (years). You can also combine time values for specific times, such as 1h30m15s . The default is 24h . The following example sets the retention time to 10 days for Thanos Ruler data: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: retention: 10d Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources Retention time and size for Prometheus metrics Enabling monitoring for user-defined projects Prometheus database storage requirements Recommended configurable storage technology Understanding persistent storage Optimizing storage 4.3.3. Setting log levels for monitoring components You can configure the log level for Alertmanager, Prometheus Operator, Prometheus, and Thanos Ruler. The following log levels can be applied to the relevant component in the user-workload-monitoring-config ConfigMap object: debug . Log debug, informational, warning, and error messages. info . Log informational, warning, and error messages. warn . Log warning and error messages only. error . Log error messages only. The default log level is info . Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add logLevel: <log_level> for a component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 logLevel: <log_level> 2 1 The monitoring stack component for which you are setting a log level. Available component values are prometheus , alertmanager , prometheusOperator , and thanosRuler . 2 The log level to set for the component. The available values are error , warn , info , and debug . The default value is info . Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Confirm that the log level has been applied by reviewing the deployment or pod configuration in the related project. The following example checks the log level for the prometheus-operator deployment: USD oc -n openshift-user-workload-monitoring get deploy prometheus-operator -o yaml \| grep "log-level" Example output - --log-level=debug Check that the pods for the component are running. The following example lists the status of pods: USD oc -n openshift-user-workload-monitoring get pods Note If an unrecognized logLevel value is included in the ConfigMap object, the pods for the component might not restart successfully. 4.3.4. Enabling the query log file for Prometheus You can configure Prometheus to write all queries that have been run by the engine to a log file. Important Because log rotation is not supported, only enable this feature temporarily when you need to troubleshoot an issue. After you finish troubleshooting, disable query logging by reverting the changes you made to the ConfigMap object to enable the feature. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add the queryLogFile parameter for Prometheus under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: queryLogFile: <path> 1 1 Add the full path to the file in which queries will be logged. Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Verify that the pods for the component are running. The following sample command lists the status of pods: USD oc -n openshift-user-workload-monitoring get pods Example output ... prometheus-operator-776fcbbd56-2nbfm 2/2 Running 0 132m prometheus-user-workload-0 5/5 Running 1 132m prometheus-user-workload-1 5/5 Running 1 132m thanos-ruler-user-workload-0 3/3 Running 0 132m thanos-ruler-user-workload-1 3/3 Running 0 132m ... Read the query log: USD oc -n openshift-user-workload-monitoring exec prometheus-user-workload-0 -- cat <path> Important Revert the setting in the config map after you have examined the logged query information. Additional resources Enabling monitoring for user-defined projects 4.4. Configuring metrics for user workload monitoring Configure the collection of metrics to monitor how cluster components and your own workloads are performing. You can send ingested metrics to remote systems for long-term storage and add cluster ID labels to the metrics to identify the data coming from different clusters. Additional resources Understanding metrics 4.4.1. Configuring remote write storage You can configure remote write storage to enable Prometheus to send ingested metrics to remote systems for long-term storage. Doing so has no impact on how or for how long Prometheus stores metrics. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). You have set up a remote write compatible endpoint (such as Thanos) and know the endpoint URL. See the Prometheus remote endpoints and storage documentation for information about endpoints that are compatible with the remote write feature. Important Red Hat only provides information for configuring remote write senders and does not offer guidance on configuring receiver endpoints. Customers are responsible for setting up their own endpoints that are remote-write compatible. Issues with endpoint receiver configurations are not included in Red Hat production support. You have set up authentication credentials in a Secret object for the remote write endpoint. You must create the secret in the openshift-user-workload-monitoring namespace. Warning To reduce security risks, use HTTPS and authentication to send metrics to an endpoint. Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add a remoteWrite: section under data/config.yaml/prometheus , as shown in the following example: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" 1 <endpoint_authentication_credentials> 2 1 The URL of the remote write endpoint. 2 The authentication method and credentials for the endpoint. Currently supported authentication methods are AWS Signature Version 4, authentication using HTTP in an Authorization request header, Basic authentication, OAuth 2.0, and TLS client. See Supported remote write authentication settings for sample configurations of supported authentication methods. Add write relabel configuration values after the authentication credentials: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" <endpoint_authentication_credentials> writeRelabelConfigs: - <your_write_relabel_configs> 1 1 Add configuration for metrics that you want to send to the remote endpoint. Example of forwarding a single metric called my_metric apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" writeRelabelConfigs: - sourceLabels: [__name__] regex: 'my_metric' action: keep Example of forwarding metrics called my_metric_1 and my_metric_2 in my_namespace namespace apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" writeRelabelConfigs: - sourceLabels: [__name__,namespace] regex: '(my_metric_1\|my_metric_2);my_namespace' action: keep Save the file to apply the changes. The new configuration is applied automatically. 4.4.1.1. Supported remote write authentication settings You can use different methods to authenticate with a remote write endpoint. Currently supported authentication methods are AWS Signature Version 4, basic authentication, authorization, OAuth 2.0, and TLS client. The following table provides details about supported authentication methods for use with remote write. Authentication method Config map field Description AWS Signature Version 4 sigv4 This method uses AWS Signature Version 4 authentication to sign requests. You cannot use this method simultaneously with authorization, OAuth 2.0, or Basic authentication. Basic authentication basicAuth Basic authentication sets the authorization header on every remote write request with the configured username and password. authorization authorization Authorization sets the Authorization header on every remote write request using the configured token. OAuth 2.0 oauth2 An OAuth 2.0 configuration uses the client credentials grant type. Prometheus fetches an access token from tokenUrl with the specified client ID and client secret to access the remote write endpoint. You cannot use this method simultaneously with authorization, AWS Signature Version 4, or Basic authentication. TLS client tlsConfig A TLS client configuration specifies the CA certificate, the client certificate, and the client key file information used to authenticate with the remote write endpoint server using TLS. The sample configuration assumes that you have already created a CA certificate file, a client certificate file, and a client key file. 4.4.1.2. Example remote write authentication settings The following samples show different authentication settings you can use to connect to a remote write endpoint. Each sample also shows how to configure a corresponding Secret object that contains authentication credentials and other relevant settings. Each sample configures authentication for use with monitoring for user-defined projects in the openshift-user-workload-monitoring namespace. 4.4.1.2.1. Sample YAML for AWS Signature Version 4 authentication The following shows the settings for a sigv4 secret named sigv4-credentials in the openshift-user-workload-monitoring namespace. apiVersion: v1 kind: Secret metadata: name: sigv4-credentials namespace: openshift-user-workload-monitoring stringData: accessKey: <AWS_access_key> 1 secretKey: <AWS_secret_key> 2 type: Opaque 1 The AWS API access key. 2 The AWS API secret key. The following shows sample AWS Signature Version 4 remote write authentication settings that use a Secret object named sigv4-credentials in the openshift-user-workload-monitoring namespace: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://authorization.example.com/api/write" sigv4: region: <AWS_region> 1 accessKey: name: sigv4-credentials 2 key: accessKey 3 secretKey: name: sigv4-credentials 4 key: secretKey 5 profile: <AWS_profile_name> 6 roleArn: <AWS_role_arn> 7 1 The AWS region. 2 4 The name of the Secret object containing the AWS API access credentials. 3 The key that contains the AWS API access key in the specified Secret object. 5 The key that contains the AWS API secret key in the specified Secret object. 6 The name of the AWS profile that is being used to authenticate. 7 The unique identifier for the Amazon Resource Name (ARN) assigned to your role. 4.4.1.2.2. Sample YAML for Basic authentication The following shows sample Basic authentication settings for a Secret object named rw-basic-auth in the openshift-user-workload-monitoring namespace: apiVersion: v1 kind: Secret metadata: name: rw-basic-auth namespace: openshift-user-workload-monitoring stringData: user: <basic_username> 1 password: <basic_password> 2 type: Opaque 1 The username. 2 The password. The following sample shows a basicAuth remote write configuration that uses a Secret object named rw-basic-auth in the openshift-user-workload-monitoring namespace. It assumes that you have already set up authentication credentials for the endpoint. apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://basicauth.example.com/api/write" basicAuth: username: name: rw-basic-auth 1 key: user 2 password: name: rw-basic-auth 3 key: password 4 1 3 The name of the Secret object that contains the authentication credentials. 2 The key that contains the username in the specified Secret object. 4 The key that contains the password in the specified Secret object. 4.4.1.2.3. Sample YAML for authentication with a bearer token using a Secret Object The following shows bearer token settings for a Secret object named rw-bearer-auth in the openshift-user-workload-monitoring namespace: apiVersion: v1 kind: Secret metadata: name: rw-bearer-auth namespace: openshift-user-workload-monitoring stringData: token: <authentication_token> 1 type: Opaque 1 The authentication token. The following shows sample bearer token config map settings that use a Secret object named rw-bearer-auth in the openshift-user-workload-monitoring namespace: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| enableUserWorkload: true prometheus: remoteWrite: - url: "https://authorization.example.com/api/write" authorization: type: Bearer 1 credentials: name: rw-bearer-auth 2 key: token 3 1 The authentication type of the request. The default value is Bearer . 2 The name of the Secret object that contains the authentication credentials. 3 The key that contains the authentication token in the specified Secret object. 4.4.1.2.4. Sample YAML for OAuth 2.0 authentication The following shows sample OAuth 2.0 settings for a Secret object named oauth2-credentials in the openshift-user-workload-monitoring namespace: apiVersion: v1 kind: Secret metadata: name: oauth2-credentials namespace: openshift-user-workload-monitoring stringData: id: <oauth2_id> 1 secret: <oauth2_secret> 2 type: Opaque 1 The Oauth 2.0 ID. 2 The OAuth 2.0 secret. The following shows an oauth2 remote write authentication sample configuration that uses a Secret object named oauth2-credentials in the openshift-user-workload-monitoring namespace: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://test.example.com/api/write" oauth2: clientId: secret: name: oauth2-credentials 1 key: id 2 clientSecret: name: oauth2-credentials 3 key: secret 4 tokenUrl: https://example.com/oauth2/token 5 scopes: 6 - <scope_1> - <scope_2> endpointParams: 7 param1: <parameter_1> param2: <parameter_2> 1 3 The name of the corresponding Secret object. Note that ClientId can alternatively refer to a ConfigMap object, although clientSecret must refer to a Secret object. 2 4 The key that contains the OAuth 2.0 credentials in the specified Secret object. 5 The URL used to fetch a token with the specified clientId and clientSecret . 6 The OAuth 2.0 scopes for the authorization request. These scopes limit what data the tokens can access. 7 The OAuth 2.0 authorization request parameters required for the authorization server. 4.4.1.2.5. Sample YAML for TLS client authentication The following shows sample TLS client settings for a tls Secret object named mtls-bundle in the openshift-user-workload-monitoring namespace. apiVersion: v1 kind: Secret metadata: name: mtls-bundle namespace: openshift-user-workload-monitoring data: ca.crt: <ca_cert> 1 client.crt: <client_cert> 2 client.key: <client_key> 3 type: tls 1 The CA certificate in the Prometheus container with which to validate the server certificate. 2 The client certificate for authentication with the server. 3 The client key. The following sample shows a tlsConfig remote write authentication configuration that uses a TLS Secret object named mtls-bundle . apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" tlsConfig: ca: secret: name: mtls-bundle 1 key: ca.crt 2 cert: secret: name: mtls-bundle 3 key: client.crt 4 keySecret: name: mtls-bundle 5 key: client.key 6 1 3 5 The name of the corresponding Secret object that contains the TLS authentication credentials. Note that ca and cert can alternatively refer to a ConfigMap object, though keySecret must refer to a Secret object. 2 The key in the specified Secret object that contains the CA certificate for the endpoint. 4 The key in the specified Secret object that contains the client certificate for the endpoint. 6 The key in the specified Secret object that contains the client key secret. 4.4.1.3. Example remote write queue configuration You can use the queueConfig object for remote write to tune the remote write queue parameters. The following example shows the queue parameters with their default values for monitoring for user-defined projects in the openshift-user-workload-monitoring namespace. Example configuration of remote write parameters with default values apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" <endpoint_authentication_credentials> queueConfig: capacity: 10000 1 minShards: 1 2 maxShards: 50 3 maxSamplesPerSend: 2000 4 batchSendDeadline: 5s 5 minBackoff: 30ms 6 maxBackoff: 5s 7 retryOnRateLimit: false 8 1 The number of samples to buffer per shard before they are dropped from the queue. 2 The minimum number of shards. 3 The maximum number of shards. 4 The maximum number of samples per send. 5 The maximum time for a sample to wait in buffer. 6 The initial time to wait before retrying a failed request. The time gets doubled for every retry up to the maxbackoff time. 7 The maximum time to wait before retrying a failed request. 8 Set this parameter to true to retry a request after receiving a 429 status code from the remote write storage. Additional resources Prometheus REST API reference for remote write Setting up remote write compatible endpoints (Prometheus documentation) Tuning remote write settings (Prometheus documentation) Understanding secrets 4.4.2. Creating cluster ID labels for metrics You can create cluster ID labels for metrics by adding the write_relabel settings for remote write storage in the user-workload-monitoring-config config map in the openshift-user-workload-monitoring namespace. Note When Prometheus scrapes user workload targets that expose a namespace label, the system stores this label as exported_namespace . This behavior ensures that the final namespace label value is equal to the namespace of the target pod. You cannot override this default configuration by setting the value of the honorLabels field to true for PodMonitor or ServiceMonitor objects. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role, or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). You have configured remote write storage. Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config In the writeRelabelConfigs: section under data/config.yaml/prometheus/remoteWrite , add cluster ID relabel configuration values: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" <endpoint_authentication_credentials> writeRelabelConfigs: 1 - <relabel_config> 2 1 Add a list of write relabel configurations for metrics that you want to send to the remote endpoint. 2 Substitute the label configuration for the metrics sent to the remote write endpoint. The following sample shows how to forward a metric with the cluster ID label cluster_id : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: "https://remote-write-endpoint.example.com" writeRelabelConfigs: - sourceLabels: - __tmp_openshift_cluster_id__ 1 targetLabel: cluster_id 2 action: replace 3 1 The system initially applies a temporary cluster ID source label named __tmp_openshift_cluster_id__ . This temporary label gets replaced by the cluster ID label name that you specify. 2 Specify the name of the cluster ID label for metrics sent to remote write storage. If you use a label name that already exists for a metric, that value is overwritten with the name of this cluster ID label. For the label name, do not use __tmp_openshift_cluster_id__ . The final relabeling step removes labels that use this name. 3 The replace write relabel action replaces the temporary label with the target label for outgoing metrics. This action is the default and is applied if no action is specified. Save the file to apply the changes. The new configuration is applied automatically. Additional resources Adding cluster ID labels to metrics Obtaining your cluster ID 4.4.3. Setting up metrics collection for user-defined projects You can create a ServiceMonitor resource to scrape metrics from a service endpoint in a user-defined project. This assumes that your application uses a Prometheus client library to expose metrics to the /metrics canonical name. This section describes how to deploy a sample service in a user-defined project and then create a ServiceMonitor resource that defines how that service should be monitored. 4.4.3.1. Deploying a sample service To test monitoring of a service in a user-defined project, you can deploy a sample service. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with administrative permissions for the namespace. Procedure Create a YAML file for the service configuration. In this example, it is called prometheus-example-app.yaml . Add the following deployment and service configuration details to the file: apiVersion: v1 kind: Namespace metadata: name: ns1 --- apiVersion: apps/v1 kind: Deployment metadata: labels: app: prometheus-example-app name: prometheus-example-app namespace: ns1 spec: replicas: 1 selector: matchLabels: app: prometheus-example-app template: metadata: labels: app: prometheus-example-app spec: containers: - image: ghcr.io/rhobs/prometheus-example-app:0.4.2 imagePullPolicy: IfNotPresent name: prometheus-example-app --- apiVersion: v1 kind: Service metadata: labels: app: prometheus-example-app name: prometheus-example-app namespace: ns1 spec: ports: - port: 8080 protocol: TCP targetPort: 8080 name: web selector: app: prometheus-example-app type: ClusterIP This configuration deploys a service named prometheus-example-app in the user-defined ns1 project. This service exposes the custom version metric. Apply the configuration to the cluster: USD oc apply -f prometheus-example-app.yaml It takes some time to deploy the service. You can check that the pod is running: USD oc -n ns1 get pod Example output NAME READY STATUS RESTARTS AGE prometheus-example-app-7857545cb7-sbgwq 1/1 Running 0 81m 4.4.3.2. Specifying how a service is monitored To use the metrics exposed by your service, you must configure OpenShift Container Platform monitoring to scrape metrics from the /metrics endpoint. You can do this using a ServiceMonitor custom resource definition (CRD) that specifies how a service should be monitored, or a PodMonitor CRD that specifies how a pod should be monitored. The former requires a Service object, while the latter does not, allowing Prometheus to directly scrape metrics from the metrics endpoint exposed by a pod. This procedure shows you how to create a ServiceMonitor resource for a service in a user-defined project. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or the monitoring-edit cluster role. You have enabled monitoring for user-defined projects. For this example, you have deployed the prometheus-example-app sample service in the ns1 project. Note The prometheus-example-app sample service does not support TLS authentication. Procedure Create a new YAML configuration file named example-app-service-monitor.yaml . Add a ServiceMonitor resource to the YAML file. The following example creates a service monitor named prometheus-example-monitor to scrape metrics exposed by the prometheus-example-app service in the ns1 namespace: apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 1 spec: endpoints: - interval: 30s port: web 2 scheme: http selector: 3 matchLabels: app: prometheus-example-app 1 Specify a user-defined namespace where your service runs. 2 Specify endpoint ports to be scraped by Prometheus. 3 Configure a selector to match your service based on its metadata labels. Note A ServiceMonitor resource in a user-defined namespace can only discover services in the same namespace. That is, the namespaceSelector field of the ServiceMonitor resource is always ignored. Apply the configuration to the cluster: USD oc apply -f example-app-service-monitor.yaml It takes some time to deploy the ServiceMonitor resource. Verify that the ServiceMonitor resource is running: USD oc -n <namespace> get servicemonitor Example output NAME AGE prometheus-example-monitor 81m 4.4.3.3. Example service endpoint authentication settings You can configure authentication for service endpoints for user-defined project monitoring by using ServiceMonitor and PodMonitor custom resource definitions (CRDs). The following samples show different authentication settings for a ServiceMonitor resource. Each sample shows how to configure a corresponding Secret object that contains authentication credentials and other relevant settings. 4.4.3.3.1. Sample YAML authentication with a bearer token The following sample shows bearer token settings for a Secret object named example-bearer-auth in the ns1 namespace: Example bearer token secret apiVersion: v1 kind: Secret metadata: name: example-bearer-auth namespace: ns1 stringData: token: <authentication_token> 1 1 Specify an authentication token. The following sample shows bearer token authentication settings for a ServiceMonitor CRD. The example uses a Secret object named example-bearer-auth : Example bearer token authentication settings apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 spec: endpoints: - authorization: credentials: key: token 1 name: example-bearer-auth 2 port: web selector: matchLabels: app: prometheus-example-app 1 The key that contains the authentication token in the specified Secret object. 2 The name of the Secret object that contains the authentication credentials. Important Do not use bearerTokenFile to configure bearer token. If you use the bearerTokenFile configuration, the ServiceMonitor resource is rejected. 4.4.3.3.2. Sample YAML for Basic authentication The following sample shows Basic authentication settings for a Secret object named example-basic-auth in the ns1 namespace: Example Basic authentication secret apiVersion: v1 kind: Secret metadata: name: example-basic-auth namespace: ns1 stringData: user: <basic_username> 1 password: <basic_password> 2 1 Specify a username for authentication. 2 Specify a password for authentication. The following sample shows Basic authentication settings for a ServiceMonitor CRD. The example uses a Secret object named example-basic-auth : Example Basic authentication settings apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 spec: endpoints: - basicAuth: username: key: user 1 name: example-basic-auth 2 password: key: password 3 name: example-basic-auth 4 port: web selector: matchLabels: app: prometheus-example-app 1 The key that contains the username in the specified Secret object. 2 4 The name of the Secret object that contains the Basic authentication. 3 The key that contains the password in the specified Secret object. 4.4.3.3.3. Sample YAML authentication with OAuth 2.0 The following sample shows OAuth 2.0 settings for a Secret object named example-oauth2 in the ns1 namespace: Example OAuth 2.0 secret apiVersion: v1 kind: Secret metadata: name: example-oauth2 namespace: ns1 stringData: id: <oauth2_id> 1 secret: <oauth2_secret> 2 1 Specify an Oauth 2.0 ID. 2 Specify an Oauth 2.0 secret. The following sample shows OAuth 2.0 authentication settings for a ServiceMonitor CRD. The example uses a Secret object named example-oauth2 : Example OAuth 2.0 authentication settings apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 spec: endpoints: - oauth2: clientId: secret: key: id 1 name: example-oauth2 2 clientSecret: key: secret 3 name: example-oauth2 4 tokenUrl: https://example.com/oauth2/token 5 port: web selector: matchLabels: app: prometheus-example-app 1 The key that contains the OAuth 2.0 ID in the specified Secret object. 2 4 The name of the Secret object that contains the OAuth 2.0 credentials. 3 The key that contains the OAuth 2.0 secret in the specified Secret object. 5 The URL used to fetch a token with the specified clientId and clientSecret . Additional resources Enabling monitoring for user-defined projects Scrape Prometheus metrics using TLS in ServiceMonitor configuration (Red Hat Customer Portal article) PodMonitor API ServiceMonitor API 4.5. Configuring alerts and notifications for user workload monitoring You can configure a local or external Alertmanager instance to route alerts from Prometheus to endpoint receivers. You can also attach custom labels to all time series and alerts to add useful metadata information. 4.5.1. Configuring external Alertmanager instances The OpenShift Container Platform monitoring stack includes a local Alertmanager instance that routes alerts from Prometheus. You can add external Alertmanager instances to route alerts for user-defined projects. If you add the same external Alertmanager configuration for multiple clusters and disable the local instance for each cluster, you can then manage alert routing for multiple clusters by using a single external Alertmanager instance. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add an additionalAlertmanagerConfigs section with configuration details under data/config.yaml/<component> : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 additionalAlertmanagerConfigs: - <alertmanager_specification> 2 2 Substitute <alertmanager_specification> with authentication and other configuration details for additional Alertmanager instances. Currently supported authentication methods are bearer token ( bearerToken ) and client TLS ( tlsConfig ). 1 Substitute <component> for one of two supported external Alertmanager components: prometheus or thanosRuler . The following sample config map configures an additional Alertmanager for Thanos Ruler by using a bearer token with client TLS authentication: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: additionalAlertmanagerConfigs: - scheme: https pathPrefix: / timeout: "30s" apiVersion: v1 bearerToken: name: alertmanager-bearer-token key: token tlsConfig: key: name: alertmanager-tls key: tls.key cert: name: alertmanager-tls key: tls.crt ca: name: alertmanager-tls key: tls.ca staticConfigs: - external-alertmanager1-remote.com - external-alertmanager1-remote2.com Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. 4.5.2. Configuring secrets for Alertmanager The OpenShift Container Platform monitoring stack includes Alertmanager, which routes alerts from Prometheus to endpoint receivers. If you need to authenticate with a receiver so that Alertmanager can send alerts to it, you can configure Alertmanager to use a secret that contains authentication credentials for the receiver. For example, you can configure Alertmanager to use a secret to authenticate with an endpoint receiver that requires a certificate issued by a private Certificate Authority (CA). You can also configure Alertmanager to use a secret to authenticate with a receiver that requires a password file for Basic HTTP authentication. In either case, authentication details are contained in the Secret object rather than in the ConfigMap object. 4.5.2.1. Adding a secret to the Alertmanager configuration You can add secrets to the Alertmanager configuration by editing the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project. After you add a secret to the config map, the secret is mounted as a volume at /etc/alertmanager/secrets/<secret_name> within the alertmanager container for the Alertmanager pods. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have created the secret to be configured in Alertmanager in the openshift-user-workload-monitoring project. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Add a secrets: section under data/config.yaml/alertmanager with the following configuration: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: secrets: 1 - <secret_name_1> 2 - <secret_name_2> 1 This section contains the secrets to be mounted into Alertmanager. The secrets must be located within the same namespace as the Alertmanager object. 2 The name of the Secret object that contains authentication credentials for the receiver. If you add multiple secrets, place each one on a new line. The following sample config map settings configure Alertmanager to use two Secret objects named test-secret-basic-auth and test-secret-api-token : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: secrets: - test-secret-basic-auth - test-secret-api-token Save the file to apply the changes. The new configuration is applied automatically. 4.5.3. Attaching additional labels to your time series and alerts You can attach custom labels to all time series and alerts leaving Prometheus by using the external labels feature of Prometheus. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or as a user with the user-workload-monitoring-config-edit role in the openshift-user-workload-monitoring project. A cluster administrator has enabled monitoring for user-defined projects. You have installed the OpenShift CLI ( oc ). Procedure Edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring project: USD oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config Define labels you want to add for every metric under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: externalLabels: <key>: <value> 1 1 Substitute <key>: <value> with key-value pairs where <key> is a unique name for the new label and <value> is its value. Warning Do not use prometheus or prometheus_replica as key names, because they are reserved and will be overwritten. Do not use cluster or managed_cluster as key names. Using them can cause issues where you are unable to see data in the developer dashboards. Note In the openshift-user-workload-monitoring project, Prometheus handles metrics and Thanos Ruler handles alerting and recording rules. Setting externalLabels for prometheus in the user-workload-monitoring-config ConfigMap object will only configure external labels for metrics and not for any rules. For example, to add metadata about the region and environment to all time series and alerts, use the following example: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: externalLabels: region: eu environment: prod Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources Enabling monitoring for user-defined projects 4.5.4. Configuring alert notifications In OpenShift Container Platform, an administrator can enable alert routing for user-defined projects with one of the following methods: Use the default platform Alertmanager instance. Use a separate Alertmanager instance only for user-defined projects. Developers and other users with the alert-routing-edit cluster role can configure custom alert notifications for their user-defined projects by configuring alert receivers. Note Review the following limitations of alert routing for user-defined projects: User-defined alert routing is scoped to the namespace in which the resource is defined. For example, a routing configuration in namespace ns1 only applies to PrometheusRules resources in the same namespace. When a namespace is excluded from user-defined monitoring, AlertmanagerConfig resources in the namespace cease to be part of the Alertmanager configuration. Additional resources Understanding alert routing for user-defined projects Sending notifications to external systems PagerDuty (PagerDuty official site) Prometheus Integration Guide (PagerDuty official site) Support version matrix for monitoring components Enabling alert routing for user-defined projects 4.5.4.1. Configuring alert routing for user-defined projects If you are a non-administrator user who has been given the alert-routing-edit cluster role, you can create or edit alert routing for user-defined projects. Prerequisites A cluster administrator has enabled monitoring for user-defined projects. A cluster administrator has enabled alert routing for user-defined projects. You are logged in as a user that has the alert-routing-edit cluster role for the project for which you want to create alert routing. You have installed the OpenShift CLI ( oc ). Procedure Create a YAML file for alert routing. The example in this procedure uses a file called example-app-alert-routing.yaml . Add an AlertmanagerConfig YAML definition to the file. For example: apiVersion: monitoring.coreos.com/v1beta1 kind: AlertmanagerConfig metadata: name: example-routing namespace: ns1 spec: route: receiver: default groupBy: [job] receivers: - name: default webhookConfigs: - url: https://example.org/post Save the file. Apply the resource to the cluster: USD oc apply -f example-app-alert-routing.yaml The configuration is automatically applied to the Alertmanager pods. 4.5.4.2. Configuring alert routing for user-defined projects with the Alertmanager secret If you have enabled a separate instance of Alertmanager that is dedicated to user-defined alert routing, you can customize where and how the instance sends notifications by editing the alertmanager-user-workload secret in the openshift-user-workload-monitoring namespace. Note All features of a supported version of upstream Alertmanager are also supported in an OpenShift Container Platform Alertmanager configuration. To check all the configuration options of a supported version of upstream Alertmanager, see Alertmanager configuration (Prometheus documentation). Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have enabled a separate instance of Alertmanager for user-defined alert routing. You have installed the OpenShift CLI ( oc ). Procedure Print the currently active Alertmanager configuration into the file alertmanager.yaml : USD oc -n openshift-user-workload-monitoring get secret alertmanager-user-workload --template='{{ index .data "alertmanager.yaml" }}' \| base64 --decode > alertmanager.yaml Edit the configuration in alertmanager.yaml : route: receiver: Default group_by: - name: Default routes: - matchers: - "service = prometheus-example-monitor" 1 receiver: <receiver> 2 receivers: - name: Default - name: <receiver> <receiver_configuration> 3 1 Specify labels to match your alerts. This example targets all alerts that have the service="prometheus-example-monitor" label. 2 Specify the name of the receiver to use for the alerts group. 3 Specify the receiver configuration. Apply the new configuration in the file: USD oc -n openshift-user-workload-monitoring create secret generic alertmanager-user-workload --from-file=alertmanager.yaml --dry-run=client -o=yaml \| oc -n openshift-user-workload-monitoring replace secret --filename=- 4.5.4.3. Configuring different alert receivers for default platform alerts and user-defined alerts You can configure different alert receivers for default platform alerts and user-defined alerts to ensure the following results: All default platform alerts are sent to a receiver owned by the team in charge of these alerts. All user-defined alerts are sent to another receiver so that the team can focus only on platform alerts. You can achieve this by using the openshift_io_alert_source="platform" label that is added by the Cluster Monitoring Operator to all platform alerts: Use the openshift_io_alert_source="platform" matcher to match default platform alerts. Use the openshift_io_alert_source!="platform" or 'openshift_io_alert_source=""' matcher to match user-defined alerts. Note This configuration does not apply if you have enabled a separate instance of Alertmanager dedicated to user-defined alerts.	[ "oc -n openshift-monitoring edit configmap cluster-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: \| enableUserWorkload: true 1", "oc -n openshift-user-workload-monitoring get pod", "NAME READY STATUS RESTARTS AGE prometheus-operator-6f7b748d5b-t7nbg 2/2 Running 0 3h prometheus-user-workload-0 4/4 Running 1 3h prometheus-user-workload-1 4/4 Running 1 3h thanos-ruler-user-workload-0 3/3 Running 0 3h thanos-ruler-user-workload-1 3/3 Running 0 3h", "oc -n openshift-user-workload-monitoring adm policy add-role-to-user user-workload-monitoring-config-edit <user> --role-namespace openshift-user-workload-monitoring", "oc describe rolebinding <role_binding_name> -n openshift-user-workload-monitoring", "oc describe rolebinding user-workload-monitoring-config-edit -n openshift-user-workload-monitoring", "Name: user-workload-monitoring-config-edit Labels: <none> Annotations: <none> Role: Kind: Role Name: user-workload-monitoring-config-edit Subjects: Kind Name Namespace ---- ---- --------- User user1 1", "oc -n openshift-monitoring edit configmap cluster-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: \| # alertmanagerMain: enableUserAlertmanagerConfig: true 1 #", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: enabled: true 1 enableAlertmanagerConfig: true 2", "oc -n openshift-user-workload-monitoring get alertmanager", "NAME VERSION REPLICAS AGE user-workload 0.24.0 2 100s", "oc -n <namespace> adm policy add-role-to-user alert-routing-edit <user> 1", "oc adm policy add-role-to-user <role> <user> -n <namespace> --role-namespace <namespace> 1", "oc adm policy add-cluster-role-to-user <cluster-role> <user> -n <namespace> 1", "oc label namespace my-project 'openshift.io/user-monitoring=false'", "oc label namespace my-project 'openshift.io/user-monitoring-'", "oc -n openshift-monitoring edit configmap cluster-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: \| enableUserWorkload: false", "oc -n openshift-user-workload-monitoring get pod", "No resources found in openshift-user-workload-monitoring project.", "oc label nodes <node_name> <node_label> 1", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| # <component>: 1 nodeSelector: <node_label_1> 2 <node_label_2> 3 #", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: tolerations: <toleration_specification>", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: tolerations: - key: \"key1\" operator: \"Equal\" value: \"value1\" effect: \"NoSchedule\"", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheus: resources: limits: cpu: 500m memory: 3Gi requests: cpu: 200m memory: 500Mi thanosRuler: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: enforcedSampleLimit: 50000 1", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: enforcedLabelLimit: 500 1 enforcedLabelNameLengthLimit: 50 2 enforcedLabelValueLengthLimit: 600 3", "apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: labels: prometheus: k8s role: alert-rules name: monitoring-stack-alerts 1 namespace: ns1 2 spec: groups: - name: general.rules rules: - alert: TargetDown 3 annotations: message: '{{ printf \"%.4g\" USDvalue }}% of the {{ USDlabels.job }}/{{ USDlabels.service }} targets in {{ USDlabels.namespace }} namespace are down.' 4 expr: 100 * (count(up == 0) BY (job, namespace, service) / count(up) BY (job, namespace, service)) > 10 for: 10m 5 labels: severity: warning 6 - alert: ApproachingEnforcedSamplesLimit 7 annotations: message: '{{ USDlabels.container }} container of the {{ USDlabels.pod }} pod in the {{ USDlabels.namespace }} namespace consumes {{ USDvalue \| humanizePercentage }} of the samples limit budget.' 8 expr: scrape_samples_scraped/50000 > 0.8 9 for: 10m 10 labels: severity: warning 11", "oc apply -f monitoring-stack-alerts.yaml", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 topologySpreadConstraints: - maxSkew: <n> 2 topologyKey: <key> 3 whenUnsatisfiable: <value> 4 labelSelector: 5 <match_option>", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: topologySpreadConstraints: - maxSkew: 1 topologyKey: monitoring whenUnsatisfiable: ScheduleAnyway labelSelector: matchLabels: app.kubernetes.io/name: thanos-ruler", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 volumeClaimTemplate: spec: storageClassName: <storage_class> 2 resources: requests: storage: <amount_of_storage> 3", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: volumeClaimTemplate: spec: storageClassName: my-storage-class resources: requests: storage: 10Gi", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 volumeClaimTemplate: spec: resources: requests: storage: <amount_of_storage> 2", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: volumeClaimTemplate: spec: resources: requests: storage: 20Gi", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: retention: <time_specification> 1 retentionSize: <size_specification> 2", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: retention: 24h retentionSize: 10GB", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: retention: <time_specification> 1", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: retention: 10d", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 logLevel: <log_level> 2", "oc -n openshift-user-workload-monitoring get deploy prometheus-operator -o yaml \| grep \"log-level\"", "- --log-level=debug", "oc -n openshift-user-workload-monitoring get pods", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: queryLogFile: <path> 1", "oc -n openshift-user-workload-monitoring get pods", "prometheus-operator-776fcbbd56-2nbfm 2/2 Running 0 132m prometheus-user-workload-0 5/5 Running 1 132m prometheus-user-workload-1 5/5 Running 1 132m thanos-ruler-user-workload-0 3/3 Running 0 132m thanos-ruler-user-workload-1 3/3 Running 0 132m", "oc -n openshift-user-workload-monitoring exec prometheus-user-workload-0 -- cat <path>", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" 1 <endpoint_authentication_credentials> 2", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" <endpoint_authentication_credentials> writeRelabelConfigs: - <your_write_relabel_configs> 1", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" writeRelabelConfigs: - sourceLabels: [__name__] regex: 'my_metric' action: keep", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" writeRelabelConfigs: - sourceLabels: [__name__,namespace] regex: '(my_metric_1\|my_metric_2);my_namespace' action: keep", "apiVersion: v1 kind: Secret metadata: name: sigv4-credentials namespace: openshift-user-workload-monitoring stringData: accessKey: <AWS_access_key> 1 secretKey: <AWS_secret_key> 2 type: Opaque", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://authorization.example.com/api/write\" sigv4: region: <AWS_region> 1 accessKey: name: sigv4-credentials 2 key: accessKey 3 secretKey: name: sigv4-credentials 4 key: secretKey 5 profile: <AWS_profile_name> 6 roleArn: <AWS_role_arn> 7", "apiVersion: v1 kind: Secret metadata: name: rw-basic-auth namespace: openshift-user-workload-monitoring stringData: user: <basic_username> 1 password: <basic_password> 2 type: Opaque", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://basicauth.example.com/api/write\" basicAuth: username: name: rw-basic-auth 1 key: user 2 password: name: rw-basic-auth 3 key: password 4", "apiVersion: v1 kind: Secret metadata: name: rw-bearer-auth namespace: openshift-user-workload-monitoring stringData: token: <authentication_token> 1 type: Opaque", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| enableUserWorkload: true prometheus: remoteWrite: - url: \"https://authorization.example.com/api/write\" authorization: type: Bearer 1 credentials: name: rw-bearer-auth 2 key: token 3", "apiVersion: v1 kind: Secret metadata: name: oauth2-credentials namespace: openshift-user-workload-monitoring stringData: id: <oauth2_id> 1 secret: <oauth2_secret> 2 type: Opaque", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://test.example.com/api/write\" oauth2: clientId: secret: name: oauth2-credentials 1 key: id 2 clientSecret: name: oauth2-credentials 3 key: secret 4 tokenUrl: https://example.com/oauth2/token 5 scopes: 6 - <scope_1> - <scope_2> endpointParams: 7 param1: <parameter_1> param2: <parameter_2>", "apiVersion: v1 kind: Secret metadata: name: mtls-bundle namespace: openshift-user-workload-monitoring data: ca.crt: <ca_cert> 1 client.crt: <client_cert> 2 client.key: <client_key> 3 type: tls", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" tlsConfig: ca: secret: name: mtls-bundle 1 key: ca.crt 2 cert: secret: name: mtls-bundle 3 key: client.crt 4 keySecret: name: mtls-bundle 5 key: client.key 6", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" <endpoint_authentication_credentials> queueConfig: capacity: 10000 1 minShards: 1 2 maxShards: 50 3 maxSamplesPerSend: 2000 4 batchSendDeadline: 5s 5 minBackoff: 30ms 6 maxBackoff: 5s 7 retryOnRateLimit: false 8", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" <endpoint_authentication_credentials> writeRelabelConfigs: 1 - <relabel_config> 2", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: remoteWrite: - url: \"https://remote-write-endpoint.example.com\" writeRelabelConfigs: - sourceLabels: - __tmp_openshift_cluster_id__ 1 targetLabel: cluster_id 2 action: replace 3", "apiVersion: v1 kind: Namespace metadata: name: ns1 --- apiVersion: apps/v1 kind: Deployment metadata: labels: app: prometheus-example-app name: prometheus-example-app namespace: ns1 spec: replicas: 1 selector: matchLabels: app: prometheus-example-app template: metadata: labels: app: prometheus-example-app spec: containers: - image: ghcr.io/rhobs/prometheus-example-app:0.4.2 imagePullPolicy: IfNotPresent name: prometheus-example-app --- apiVersion: v1 kind: Service metadata: labels: app: prometheus-example-app name: prometheus-example-app namespace: ns1 spec: ports: - port: 8080 protocol: TCP targetPort: 8080 name: web selector: app: prometheus-example-app type: ClusterIP", "oc apply -f prometheus-example-app.yaml", "oc -n ns1 get pod", "NAME READY STATUS RESTARTS AGE prometheus-example-app-7857545cb7-sbgwq 1/1 Running 0 81m", "apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 1 spec: endpoints: - interval: 30s port: web 2 scheme: http selector: 3 matchLabels: app: prometheus-example-app", "oc apply -f example-app-service-monitor.yaml", "oc -n <namespace> get servicemonitor", "NAME AGE prometheus-example-monitor 81m", "apiVersion: v1 kind: Secret metadata: name: example-bearer-auth namespace: ns1 stringData: token: <authentication_token> 1", "apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 spec: endpoints: - authorization: credentials: key: token 1 name: example-bearer-auth 2 port: web selector: matchLabels: app: prometheus-example-app", "apiVersion: v1 kind: Secret metadata: name: example-basic-auth namespace: ns1 stringData: user: <basic_username> 1 password: <basic_password> 2", "apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 spec: endpoints: - basicAuth: username: key: user 1 name: example-basic-auth 2 password: key: password 3 name: example-basic-auth 4 port: web selector: matchLabels: app: prometheus-example-app", "apiVersion: v1 kind: Secret metadata: name: example-oauth2 namespace: ns1 stringData: id: <oauth2_id> 1 secret: <oauth2_secret> 2", "apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: prometheus-example-monitor namespace: ns1 spec: endpoints: - oauth2: clientId: secret: key: id 1 name: example-oauth2 2 clientSecret: key: secret 3 name: example-oauth2 4 tokenUrl: https://example.com/oauth2/token 5 port: web selector: matchLabels: app: prometheus-example-app", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| <component>: 1 additionalAlertmanagerConfigs: - <alertmanager_specification> 2", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| thanosRuler: additionalAlertmanagerConfigs: - scheme: https pathPrefix: / timeout: \"30s\" apiVersion: v1 bearerToken: name: alertmanager-bearer-token key: token tlsConfig: key: name: alertmanager-tls key: tls.key cert: name: alertmanager-tls key: tls.crt ca: name: alertmanager-tls key: tls.ca staticConfigs: - external-alertmanager1-remote.com - external-alertmanager1-remote2.com", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: secrets: 1 - <secret_name_1> 2 - <secret_name_2>", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| alertmanager: secrets: - test-secret-basic-auth - test-secret-api-token", "oc -n openshift-user-workload-monitoring edit configmap user-workload-monitoring-config", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: externalLabels: <key>: <value> 1", "apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: \| prometheus: externalLabels: region: eu environment: prod", "apiVersion: monitoring.coreos.com/v1beta1 kind: AlertmanagerConfig metadata: name: example-routing namespace: ns1 spec: route: receiver: default groupBy: [job] receivers: - name: default webhookConfigs: - url: https://example.org/post", "oc apply -f example-app-alert-routing.yaml", "oc -n openshift-user-workload-monitoring get secret alertmanager-user-workload --template='{{ index .data \"alertmanager.yaml\" }}' \| base64 --decode > alertmanager.yaml", "route: receiver: Default group_by: - name: Default routes: - matchers: - \"service = prometheus-example-monitor\" 1 receiver: <receiver> 2 receivers: - name: Default - name: <receiver> <receiver_configuration> 3", "oc -n openshift-user-workload-monitoring create secret generic alertmanager-user-workload --from-file=alertmanager.yaml --dry-run=client -o=yaml \| oc -n openshift-user-workload-monitoring replace secret --filename=-" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.14/html/monitoring/configuring-user-workload-monitoring
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/21/html/release_notes_for_red_hat_build_of_openjdk_21.0.1/providing-direct-documentation-feedback_openjdk
Chapter 2. Common Vulnerabilities and Exposures (CVEs)	Chapter 2. Common Vulnerabilities and Exposures (CVEs) Common Vulnerabilities and Exposures (CVEs) are security vulnerabilities identified in publicly released software packages. CVEs are identified and listed by the National Cybersecurity FFRDC (NCF), the federally funded research and development center operated by the Mitre Corporation, with funding from the National Cyber Security Division of the United States Department of Homeland Security. The complete list of CVEs is available at https://cve.mitre.org . By highlighting CVEs with publicly known exploits and security rules associated with CVEs, the vulnerability service surfaces enhanced threat intelligence to aid in determining which CVEs pose the greatest potential risk to RHEL environments, enabling our users to effectively prioritize and address their most critical issues first. Important The vulnerability service does not contain every CVE included in the list of entries at https://cve.mitre.org . Only Red Hat CVEs, those CVEs for which Red Hat issues security advisories (RHSAs), are included in the vulnerability service. The vulnerability service identifies CVEs impacting your RHEL systems, indicates the severity and enables you to efficiently triage the exposures that are most critical to resolve. The dashbar will alert you to the following types of CVEs: Known exploits Security rules Critical severity Important severity 2.1. Red Hat Security Advisories (RHSAs) Red Hat Security Advisory (RHSA) errata document security vulnerabilities in Red Hat products for which there are remediations or mitigations available. The Red Hat Insights for Red Hat Enterprise Linux vulnerability service displays the advisory identifier tied to each system exposed to a CVE. View this information by selecting a CVE and selecting the Filter by affected systems link in the security rule card. If an advisory exists for the system, the RHSA ID is visible as a link to the system in the Exposed systems list, Advisory column. When there are no such advisories, the Advisory column is not visible, or will show "Not available." When an advisory exists for a system, users can view more information about the RHSA, including a list of affected systems. In the patch service, users can select systems to create an Ansible Playbook to apply the remediation. 2.2. Security rules Security rules are CVEs given additional visibility due to the elevated risk and exposure associated with them. These are security flaws that may receive significant media coverage and have been scrutinized by the Red Hat Product Security team, using the Product Security Incident Response Plan workflow to help determine your RHEL environment exposure. These security rules enable you to take the appropriate action to protect your organization. Security rules provide deep threat intelligence, beyond analyzing the version of RHEL running on a system. Security rules are manually curated to determine whether you are susceptible to a security threat by analyzing system metadata collected by the Insights client. If the vulnerability service identifies a system as exposed to a security rule, there is the potential for elevated security risk and issues should be addressed with urgency. Important Addressing security rules on exposed systems should be your highest priority. Finally, not all systems exposed to a CVE are also exposed to a security rule associated with that CVE. Even though you may be running a vulnerable version of software, other environmental conditions may mitigate the threat; for example, a specific port is closed or if you are running SELinux. 2.2.1. Identifying security rules in the Insights for RHEL dashboard Use the following steps to view your infrastructure exposure to security rules. Procedure Navigate to the Red Hat Insights for Red Hat Enterprise Linux dashboard . Note For simplicity, panels for services not related to security vulnerability assessment are minimized in the following screenshot. : View the Latest critical notifications on your systems panel. These are security rules with an elevated severity rating of "Important" or "Critical." These are potentially your most critical issues and should be prioritized for remediation. To the right of each notification, click the Expand button to see associated CVEs and the number of systems exposed in your infrastructure. Note You may see security rules in your critical notifications but have zero systems exposed. In this case, even though the CVE is present in your infrastructure, the security rule conditions may not exist. Below the name of the security rule, and under Associated CVEs, click the CVE ID link. View which of your systems is impacted by the security rule CVE and optionally select exposed systems to create playbooks. , view the information in the vulnerability card. Note the number of "CVEs with security rules impacting systems." This number includes security rules of any severity impacting at least one system. Click View CVEs . Consider lesser-severity security rules your second highest priority for remediation, following high-severity security rules. 2.3. Known exploits Red Hat analyzes Cybersecurity and Infrastructure Security Agency (CISA) data, to determine whether code exists publicly to exploit a CVE, or a CVE has already been exploited publicly. The vulnerability service applies the "Known exploits" label to CVEs that meet that criteria. This enhanced threat assessment can help users identify and address those CVEs that pose the most critical risks first. Red Hat recommends users review any CVEs with the "Known exploit" label with high priority and work towards remediating those issues. Important The vulnerability service makes you aware that the known-exploit CVE exists on systems in your infrastructure. The "Known exploits" label does not mean that the vulnerability was exploited on your RHEL systems; the vulnerability service does not make that determination. 2.4. Common Vulnerabilities and Exposures provide deep threat intelligence with triage feature The vulnerability service provides you with data about individual Common Vulnerabilities and Exposures (CVEs) and their effect on your systems registered to Insights. CVEs are categorized as vulnerable or affected but not vulnerable. This level of threat intelligence is available for CVEs that have the Security Rule label or for those that have gone through Red Hat Product Security's rigorous analysis. This increased threat intelligence enables you to triage issues and address the most urgent ones first. When managing a large fleet of servers, this translates into expedited protection and significant efficiencies. An affected but not vulnerable CVE status indicates that you are running software that has a vulnerability in it but is not currently exploitable. This system will need remediation but does not require immediate attention. A vulnerable CVE status indicates flawed code with an open path to exploitation. An open path could be a port or an OS version that permits one of the following: confidential information to be leaked, the integrity of the system to be compromised or availability of the system to be hindered. Let us look at an example of a vulnerable server versus an affected but not vulnerable server: Suppose that Server A is running vulnerable software that allows root access to the system. Server A would be considered vulnerable and require immediate patching. In contrast, suppose that Server B's current configuration prevents the vulnerability from manifesting, even when present in the affected code. Server B would be considered affected but not vulnerable . This would mean that Server B could be relegated to the to-do list, so that the more immediate threat, Server A could be remediated. Important You should patch Server B once Server A has been addressed since it is running potentially vulnerable code. Version updates and other events could render it vulnerable in the future. 2.4.1. Identifying known-exploit CVEs in the Red Hat Insights for RHEL dashboard Use the following steps to identify known-exploit CVEs in the Insights for Red Hat Enterprise Linux dashboard vulnerability card. Procedure Navigate to the Red Hat Insights for Red Hat Enterprise Linux dashboard . Note For simplicity, panels for services not related to security vulnerability assessment are minimized in the following screenshot. : On the Vulnerability card, note the CVEs with Known exploits impacting 1 or more systems and the number displayed . Click View Known exploits . View the filtered list of Known-exploit CVEs in the CVEs list.	null	https://docs.redhat.com/en/documentation/red_hat_insights/1-latest/html/assessing_and_monitoring_security_vulnerabilities_on_rhel_systems/vuln-cves_vuln-overview
3.2. Load Balancer Using Direct Routing	3.2. Load Balancer Using Direct Routing Direct routing allows real servers to process and route packets directly to a requesting user rather than passing outgoing packets through the LVS router. Direct routing requires that the real servers be physically connected to a network segment with the LVS router and be able to process and direct outgoing packets as well. Network Layout In a direct routing Load Balancer setup, the LVS router needs to receive incoming requests and route them to the proper real server for processing. The real servers then need to directly route the response to the client. So, for example, if the client is on the Internet, and sends the packet through the LVS router to a real server, the real server must be able to connect directly to the client through the Internet. This can be done by configuring a gateway for the real server to pass packets to the Internet. Each real server in the server pool can have its own separate gateway (and each gateway with its own connection to the Internet), allowing for maximum throughput and scalability. For typical Load Balancer setups, however, the real servers can communicate through one gateway (and therefore one network connection). Hardware The hardware requirements of a Load Balancer system using direct routing is similar to other Load Balancer topologies. While the LVS router needs to be running Red Hat Enterprise Linux to process the incoming requests and perform load-balancing for the real servers, the real servers do not need to be Linux machines to function correctly. The LVS routers need one or two NICs each (depending on if there is a backup router). You can use two NICs for ease of configuration and to distinctly separate traffic; incoming requests are handled by one NIC and routed packets to real servers on the other. Since the real servers bypass the LVS router and send outgoing packets directly to a client, a gateway to the Internet is required. For maximum performance and availability, each real server can be connected to its own separate gateway which has its own dedicated connection to the network to which the client is connected (such as the Internet or an intranet). Software There is some configuration outside of keepalived that needs to be done, especially for administrators facing ARP issues when using Load Balancer by means of direct routing. Refer to Section 3.2.1, "Direct Routing Using arptables" or Section 3.2.3, "Direct Routing Using iptables" for more information. 3.2.1. Direct Routing Using arptables In order to configure direct routing using arptables , each real server must have their virtual IP address configured, so they can directly route packets. ARP requests for the VIP are ignored entirely by the real servers, and any ARP packets that might otherwise be sent containing the VIPs are mangled to contain the real server's IP instead of the VIPs. Using the arptables method, applications may bind to each individual VIP or port that the real server is servicing. For example, the arptables method allows multiple instances of Apache HTTP Server to be running and bound explicitly to different VIPs on the system. However, using the arptables method, VIPs cannot be configured to start on boot using standard Red Hat Enterprise Linux system configuration tools. To configure each real server to ignore ARP requests for each virtual IP addresses, perform the following steps: Create the ARP table entries for each virtual IP address on each real server (the real_ip is the IP the director uses to communicate with the real server; often this is the IP bound to eth0 ): This will cause the real servers to ignore all ARP requests for the virtual IP addresses, and change any outgoing ARP responses which might otherwise contain the virtual IP so that they contain the real IP of the server instead. The only node that should respond to ARP requests for any of the VIPs is the current active LVS node. Once this has been completed on each real server, save the ARP table entries by typing the following commands on each real server: arptables-save > /etc/sysconfig/arptables systemctl enable arptables.service The systemctl enable command will cause the system to reload the arptables configuration on bootup before the network is started. Configure the virtual IP address on all real servers using ip addr to create an IP alias. For example: Configure Keepalived for Direct Routing. This can be done by adding lb_kind DR to the keepalived.conf file. Refer to Chapter 4, Initial Load Balancer Configuration with Keepalived for more information. 3.2.2. Direct Routing Using firewalld You may also work around the ARP issue using the direct routing method by creating firewall rules using firewalld . To configure direct routing using firewalld , you must add rules that create a transparent proxy so that a real server will service packets sent to the VIP address, even though the VIP address does not exist on the system. The firewalld method is simpler to configure than the arptables method. This method also circumvents the LVS ARP issue entirely, because the virtual IP address or addresses exist only on the active LVS director. However, there are performance issues using the firewalld method compared to arptables , as there is overhead in forwarding every return packet. You also cannot reuse ports using the firewalld method. For example, it is not possible to run two separate Apache HTTP Server services bound to port 80, because both must bind to INADDR_ANY instead of the virtual IP addresses. To configure direct routing using the firewalld method, perform the following steps on every real server: Ensure that firewalld is running. Ensure that firewalld is enabled to start at system start. Enter the following command for every VIP, port, and protocol (TCP or UDP) combination intended to be serviced for the real server. This command will cause the real servers to process packets destined for the VIP and port that they are given. Reload the firewall rules and keep the state information. The current permanent configuration will become the new firewalld runtime configuration as well as the configuration at the system start. 3.2.3. Direct Routing Using iptables You may also work around the ARP issue using the direct routing method by creating iptables firewall rules. To configure direct routing using iptables , you must add rules that create a transparent proxy so that a real server will service packets sent to the VIP address, even though the VIP address does not exist on the system. The iptables method is simpler to configure than the arptables method. This method also circumvents the LVS ARP issue entirely, because the virtual IP address(es) only exist on the active LVS director. However, there are performance issues using the iptables method compared to arptables , as there is overhead in forwarding/masquerading every packet. You also cannot reuse ports using the iptables method. For example, it is not possible to run two separate Apache HTTP Server services bound to port 80, because both must bind to INADDR_ANY instead of the virtual IP addresses. To configure direct routing using the iptables method, perform the following steps: On each real server, enter the following command for every VIP, port, and protocol (TCP or UDP) combination intended to be serviced for the real server: iptables -t nat -A PREROUTING -p <tcp\|udp> -d <vip> --dport <port> -j REDIRECT This command will cause the real servers to process packets destined for the VIP and port that they are given. Save the configuration on each real server: The systemctl enable command will cause the system to reload the iptables configuration on bootup before the network is started. 3.2.4. Direct Routing Using sysctl Another way to deal with the ARP limitation when employing Direct Routing is using the sysctl interface. Administrators can configure two systcl settings such that the real server will not announce the VIP in ARP requests and will not reply to ARP requests for the VIP address. To enable this, enter the following commands: Alternatively, you may add the following lines to the /etc/sysctl.d/arp.conf file:	[ "arptables -A IN -d <virtual_ip> -j DROP arptables -A OUT -s <virtual_ip> -j mangle --mangle-ip-s <real_ip>", "ip addr add 192.168.76.24 dev eth0", "systemctl start firewalld", "systemctl enable firewalld", "firewall-cmd --permanent --direct --add-rule ipv4 nat PREROUTING 0 -d vip -p tcp\|udp -m tcp\|udp --dport port -j REDIRECT", "firewall-cmd --reload", "iptables-save > /etc/sysconfig/iptables systemctl enable iptables.service", "echo 1 > /proc/sys/net/ipv4/conf/eth0/arp_ignore echo 2 > /proc/sys/net/ipv4/conf/eth0/arp_announce", "net.ipv4.conf.eth0.arp_ignore = 1 net.ipv4.conf.eth0.arp_announce = 2" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/load_balancer_administration/s1-lvs-direct-VSA
22.3. One-Time Passwords	22.3. One-Time Passwords Important The IdM solution for OTP authentication is only supported for clients running Red Hat Enterprise Linux 7.1 or later. One-time password (OTP) is a password valid for only one authentication session and becomes invalid after use. Unlike a traditional static password, OTP generated by an authentication token keeps changing. OTPs are used as part of two-factor authentication: The user authenticates with a traditional password. The user provides an OTP code generated by a recognized OTP token. Two-factor authentication is considered safer than authentication using a traditional password alone. Even if a potential intruder intercepts the OTP during login, the intercepted OTP will already be invalid by that point because it can only be used for successful authentication once. Warning The following security and other limitations currently relate to the OTP support in IdM: The most important security limitation is the potential vulnerability to replay attacks across the system. Replication is asynchronous, and an OTP code can therefore be reused during the replication period. A user might be able to log on to two servers at the same time. However, this vulnerability is usually difficult to exploit due to comprehensive encryption. It is not possible to obtain a ticket-granting ticket (TGT) using a client that does not support OTP authentication. This might affect certain use cases, such as authentication using the mod_auth_kerb module or the Generic Security Services API (GSSAPI). It is not possible to use password + OTP in the IdM solution if the FIPS mode is enabled. 22.3.1. How OTP Authentication Works in IdM 22.3.1.1. OTP Tokens Supported in IdM Software and Hardware Tokens IdM supports both software and hardware tokens. User-managed and Administrator-managed Tokens Users can manage their own tokens, or the administrator can manage their tokens for them: User-managed tokens Users have full control over user-managed tokens in Identity Management: they are allowed to create, edit, or delete their tokens. Administrator-managed tokens The administrator adds administrator-managed tokens to the users' accounts. Users themselves have read-only access for such tokens: they do not have the permission to manage or modify the tokens and they are not required to configure them in any way. Note that users cannot delete or deactivate a token if it is their only active token at the moment. As an administrator, you cannot delete or deactivate your last active token, but you can delete or deactivate the last active token of another user. Supported OTP Algorithms Identity Management supports the following two standard OTP mechanisms: The HMAC-Based One-Time Password (HOTP) algorithm is based on a counter. HMAC stands for Hashed Message Authentication Code. The Time-Based One-Time Password (TOTP) algorithm is an extension of HOTP to support time-based moving factor. 22.3.1.2. Available OTP Authentication Methods When enabling OTP authentication, you can choose from the following authentication methods: Two-factor authentication (password + OTP) With this method, the user is always required to enter both a standard password and an OTP code. Password With this method, the user still has the option to authenticate using a standard password only. RADIUS proxy server authentication For information on configuring a RADIUS server for OTP validation, see Section 22.3.7, "Migrating from a Proprietary OTP Solution" . Global and User-specific Authentication Methods You can configure these authentication methods either globally or for individual users: By default, user-specific authentication method settings take precedence over global settings. If no authentication method is set for a user, the globally-defined methods apply. You can disable per-user authentication method settings for any user. This ensures IdM ignores the per-user settings and always applies the global settings for the user. Combining Multiple Authentication Methods If you set multiple methods at once, either one of them will be sufficient for successful authentication. For example: If you configure both two-factor and password authentication, the user must provide the password (first factor), but providing the OTP (second factor) is optional when using the command line: In the web UI, the user must still provide both factors. Note Individual hosts or services might be configured to require a certain authentication method, for example OTP. If you attempt to authenticate to such hosts or services using the first factor only, you will be denied access. See Section 22.4, "Restricting Access to Services and Hosts Based on How Users Authenticate" . However, a minor exception exists when RADIUS and another authentication method are configured: Kerberos will always use RADIUS, but LDAP will not. LDAP only recognizes the password and two-factor authentication methods. If you use an external two-factor authentication provider, use Kerberos from your applications. If you want to let users authenticate with a password only, use LDAP. It is recommended that the applications leverage Apache modules and SSSD, which allows to configure either Kerberos or LDAP. 22.3.1.3. GNOME Keyring Service Support IdM integrates OTP authentication with the GNOME Keyring service. Note that GNOME Keyring integration requires the user to enter the first and second factors separately: 22.3.1.4. Offline Authentication with OTP IdM supports offline OTP authentication. However, to be able to log in offline, the user must first authenticate when the system is online by entering the static password and OTP separately: If both passwords are entered separately like this when logging in online, the user will subsequently be able to authenticate even if the central authentication server is unavailable. Note that IdM only prompts for the first-factor traditional static password when the user authenticates offline. IdM also supports entering both the static password and OTP together in one string in the First factor prompt. However, note that this is not compatible with offline OTP authentication. If the user enters both factors in a single prompt, IdM will always have to contact the central authentication server when authenticating, which requires the system to be online. Important If you use OTP authentication on devices that also operate offline, such as laptops, Red Hat recommends to enter the static password and OTP separately to make sure offline authentication will be available. Otherwise, IdM will not allow you to log in after the system goes offline. If you want to benefit from OTP offline authentication, apart from entering the static and OTP passwords separately, also make sure to meet the following conditions: The cache_credentials option in the /etc/sssd/sssd.conf file is set to True , which enables caching the first factor password. The first-factor static password meets the password length requirement defined in the cache_credentials_minimal_first_factor_length option set in /etc/sssd/sssd.conf . The default minimal length is 8 characters. For more information about the option, see the sssd.conf (5) man page. Note that even if the krb5_store_password_if_offline option is set to true in /etc/sssd/sssd.conf , SSSD does not attempt to refresh the Kerberos ticket-granting ticket (TGT) when the system goes online again because the OTP might already be invalid at that point. To obtain a TGT in this situation, the user must authenticate again using both factors. 22.3.2. Required Settings for Configuring a RADIUS Proxy on an IdM Server Running in FIPS Mode In Federal Information Processing Standard (FIPS) mode, OpenSSL disables the use of the MD5 digest algorithm by default. Consequently, as the RADIUS protocol requires MD5 to encrypt a secret between the RADIUS client and the RADIUS server, the unavailability of MD5 in FIPS mode results in the IdM RADIUS proxy server to fail. If the RADIUS server is running on the same host as the IdM master, you can work around the problem and enable MD5 within the secure perimeter, by performing the following steps: Create the /etc/systemd/system/radiusd.service.d/ipa-otp.conf file with the following content: Reload the systemd configuration: Start the radiusd service: 22.3.3. Enabling Two Factor Authentication For details on the available authentication methods related to OTP, see Section 22.3.1.2, "Available OTP Authentication Methods" . To enable two factor authentication using: the web UI, see the section called "Web UI: Enabling Two Factor Authentication" . the command line, see the section called "Command Line: Enabling Two Factor Authentication" . Web UI: Enabling Two Factor Authentication To set authentication methods globally for all users: Select IPA Server Configuration . In the User Options area, select the required Default user authentication types . Figure 22.4. User Authentication Methods To ensure the global settings are not overridden with per-user settings, select Disable per-user override . If you do not select Disable per-user override , authentication methods configured per user take precedence over the global settings. To set authentication methods individually on a per-user basis: Select Identity Users , and click the name of the user to edit. In the Account Settings area, select the required User authentication types . Figure 22.5. User Authentication Methods Command Line: Enabling Two Factor Authentication To set authentication methods globally for all users: Run the ipa config-mod --user-auth-type command. For example, to set the global authentication method to two-factor authentication: For a list of values accepted by --user-auth-type , run the ipa config-mod --help command. To disable per-user overrides, thus ensuring the global settings are not overridden with per-user settings, add the --user-auth-type=disabled option as well. For example, to set the global authentication method to two-factor authentication and disable per-user overrides: If you do not set --user-auth-type=disabled , authentication methods configured per user take precedence over the global settings. To set authentication methods individually for a specified user: Run the ipa user-mod --user-auth-type command. For example, to set that user will be required to use two-factor authentication: To set multiple authentication methods, add --user-auth-type multiple times. For example, to configure both password and two-factor authentication globally for all users: 22.3.4. Adding a User-Managed Software Token Log in with your standard password. Make sure the FreeOTP Authenticator application is installed on your mobile device. To download FreeOTP Authenticator , see the FreeOTP source page . Create the software token in the IdM web UI or from the command line. To create the token in the web UI, click Add under the OTP tokens tab. If you are logged-in as the administrator, the OTP Tokens tab is accessible through the Authentication tab. Figure 22.6. Adding an OTP Token for a User To create the token from the command line, run the ipa otptoken-add command. For more information about ipa otptoken-add , run the command with the --help option added. A QR code is displayed in the web UI or on the command line. Scan the QR code with FreeOTP Authenticator to provision the token to the mobile device. 22.3.5. Adding a User-Managed YubiKey Hardware Token A programmable hardware token, such as a YubiKey token, can only be added from the command line. To add a YubiKey hardware token as the user owning the token: Log in with your standard password. Insert your YubiKey token. Run the ipa otptoken-add-yubikey command. If the YubiKey has an empty slot available, the command will select the empty slot automatically. If no empty slot is available, you must select a slot manually using the --slot option.For example: Note that this overwrites the selected slot. 22.3.6. Adding a Token for a User as the Administrator To add a software token as the administrator: Make sure you are logged-in as the administrator. Make sure the FreeOTP Authenticator application is installed on the mobile device. To download FreeOTP Authenticator , see the FreeOTP source page . Create the software token in the IdM web UI or from the command line. To create the token in the web UI, select Authentication OTP Tokens and click Add at the top of the list of OTP tokens. In the Add OTP Token form, select the owner of the token. Figure 22.7. Adding an Administrator-Managed Software Token To create the token from the command line, run the ipa otptoken-add command with the --owner option. For example: A QR code is displayed in the web UI or on the command line. Scan the QR code with FreeOTP Authenticator to provision the token to the mobile device. To add a programmable hardware token, such as a YubiKey token, as the administrator: Make sure you are logged-in as the administrator. Insert the YubiKey token. Run the ipa otptoken-add-yubikey command with the --owner option. For example: 22.3.7. Migrating from a Proprietary OTP Solution To enable the migration of a large deployment from a proprietary OTP solution to the IdM-native OTP solution, IdM offers a way to offload OTP validation to a third-party RADIUS server for a subset of users. The administrator creates a set of RADIUS proxies where each proxy can only reference a single RADIUS server. If more than one server needs to be addressed, it is recommended to create a virtual IP solution that points to multiple RADIUS servers. Such a solution needs to be built outside of RHEL IdM with the help of the keepalived daemon, for example. The administrator then assigns one of these proxy sets to a user. As long as the user has a RADIUS proxy set assigned, IdM bypasses all other authentication mechanisms. Note IdM does not provide any token management or synchronization support for tokens in the third-party system. To configure a RADIUS server for OTP validation and to add a user to the proxy server: Make sure that the radius user authentication method is enabled. See Section 22.3.3, "Enabling Two Factor Authentication" for details. Run the ipa radiusproxy-add proxy_name --secret secret command to add a RADIUS proxy. The command prompts you for inserting the required information. The configuration of the RADIUS proxy requires the use of a common secret between the client and the server to wrap credentials. Specify this secret in the --secret parameter. Run the ipa user-mod radiususer --radius= proxy_name command to assign a user to the added proxy. If required, configure the user name to be sent to RADIUS by running the ipa user-mod radiususer --radius-username= radius_user command. As a result, the user OTP authentication will start to be processed through the RADIUS proxy server. Note To run a RADIUS server on an IdM master with FIPS mode enabled, additionally, perform the steps described in Section 22.3.2, "Required Settings for Configuring a RADIUS Proxy on an IdM Server Running in FIPS Mode" . When the user is ready to be migrated to the IdM native OTP system, you can simply remove the RADIUS proxy assignment for the user. 22.3.7.1. Changing the Timeout Value of a KDC When Running a RADIUS Server in a Slow Network In certain situations, such as running a RADIUS proxy in a slow network, the IdM KDC closes the connection before the RADIUS server responds because the connection timed out while waiting for the user to enter the token. To change the timeout settings of the KDC: Change the value of the timeout parameter in the [otp] section in the /var/kerberos/krb5kdc/kdc.conf file. For example, to set the timeout to 120 seconds: Restart the krb5kdc service: 22.3.8. Promoting the Current Credentials to Two-Factor Authentication If both password and two-factor authentication are configured, but you only authenticated using the password, you might be denied access to certain services or hosts (see Section 22.4, "Restricting Access to Services and Hosts Based on How Users Authenticate" ). In this situation, promote your credentials from one-factor to two-factor authentication by authenticating again: Lock your screen. The default keyboard shortcut to lock the screen is Super key + L . Unlock your screen. When asked for credentials, use both password and OTP. 22.3.9. Resynchronizing an OTP Token See Section B.4.3, "OTP Token Out of Sync" . 22.3.10. Replacing a Lost OTP Token The following procedure describes how a user who lost its OTP token can replace the token: As an administrator, enable password and OTP authentication for the user: The user can now add a new token. For example, to add a new token that has New Token set in the description: For further details, enter the command the ipa otptoken-add --help parameter added. The user can now delete the old token: Optionally, list the tokens associated with the account: Delete the old token. For example, to delete the token with the e1e9e1ef-172c-4fa9-b637-6b017ce79315 ID: As an administrator, enable only OTP authentication for the user:	[ "First Factor: Second Factor (optional):", "First factor: static_password Second factor: one-time_password", "First factor: static_password Second factor: one-time_password", "[Service] Environment=OPENSSL_FIPS_NON_APPROVED_MD5_ALLOW=1", "systemctl daemon-reload", "systemctl start radiusd", "ipa config-mod --user-auth-type=otp", "ipa config-mod --user-auth-type=otp --user-auth-type=disabled", "ipa user-mod user --user-auth-type=otp", "ipa config-mod --user-auth-type=otp --user-auth-type=password", "ipa otptoken-add ------------------ Added OTP token \"\" ------------------ Unique ID: 7060091b-4e40-47fd-8354-cb32fecd548a Type: TOTP", "ipa otptoken-add-yubikey --slot=2", "ipa otptoken-add --owner=user ------------------ Added OTP token \"\" ------------------ Unique ID: 5303baa8-08f9-464e-a74d-3b38de1c041d Type: TOTP", "ipa otptoken-add-yubikey --owner=user", "[otp] DEFAULT = { timeout = 120 }", "systemctl restart krb5kdc", "ipa user-mod --user-auth-type=password --user-auth-type=otp user_name", "ipa otptoken-add --desc=\" New Token \"", "ipa otptoken-find -------------------- 2 OTP tokens matched -------------------- Unique ID: 4ce8ec29-0bf7-4100-ab6d-5d26697f0d8f Type: TOTP Description: New Token Owner: user Unique ID: e1e9e1ef-172c-4fa9-b637-6b017ce79315 Type: TOTP Description: Old Token Owner: user ---------------------------- Number of entries returned 2 ----------------------------", "# ipa otptoken-del e1e9e1ef-172c-4fa9-b637-6b017ce79315 -------------------------------------------------------- Deleted OTP token \" e1e9e1ef-172c-4fa9-b637-6b017ce79315 \" --------------------------------------------------------", "ipa user-mod --user-auth-type=otp user_name" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/linux_domain_identity_authentication_and_policy_guide/otp
Chapter 1. OpenShift Container Platform security and compliance	Chapter 1. OpenShift Container Platform security and compliance 1.1. Security overview It is important to understand how to properly secure various aspects of your OpenShift Container Platform cluster. Container security A good starting point to understanding OpenShift Container Platform security is to review the concepts in Understanding container security . This and subsequent sections provide a high-level walkthrough of the container security measures available in OpenShift Container Platform, including solutions for the host layer, the container and orchestration layer, and the build and application layer. These sections also include information on the following topics: Why container security is important and how it compares with existing security standards. Which container security measures are provided by the host (RHCOS and RHEL) layer and which are provided by OpenShift Container Platform. How to evaluate your container content and sources for vulnerabilities. How to design your build and deployment process to proactively check container content. How to control access to containers through authentication and authorization. How networking and attached storage are secured in OpenShift Container Platform. Containerized solutions for API management and SSO. Auditing OpenShift Container Platform auditing provides a security-relevant chronological set of records documenting the sequence of activities that have affected the system by individual users, administrators, or other components of the system. Administrators can configure the audit log policy and view audit logs . Certificates Certificates are used by various components to validate access to the cluster. Administrators can replace the default ingress certificate , add API server certificates , or add a service certificate . You can also review more details about the types of certificates used by the cluster: User-provided certificates for the API server Proxy certificates Service CA certificates Node certificates Bootstrap certificates etcd certificates OLM certificates Aggregated API client certificates Machine Config Operator certificates User-provided certificates for default ingress Ingress certificates Monitoring and cluster logging Operator component certificates Control plane certificates Encrypting data You can enable etcd encryption for your cluster to provide an additional layer of data security. For example, it can help protect the loss of sensitive data if an etcd backup is exposed to the incorrect parties. Vulnerability scanning Administrators can use the Red Hat Quay Container Security Operator to run vulnerability scans and review information about detected vulnerabilities. 1.2. Compliance overview For many OpenShift Container Platform customers, regulatory readiness, or compliance, on some level is required before any systems can be put into production. That regulatory readiness can be imposed by national standards, industry standards, or the organization's corporate governance framework. Compliance checking Administrators can use the Compliance Operator to run compliance scans and recommend remediations for any issues found. The oc-compliance plugin is an OpenShift CLI ( oc ) plugin that provides a set of utilities to easily interact with the Compliance Operator. File integrity checking Administrators can use the File Integrity Operator to continually run file integrity checks on cluster nodes and provide a log of files that have been modified. 1.3. Additional resources Understanding authentication Configuring the internal OAuth server Understanding identity provider configuration Using RBAC to define and apply permissions Managing security context constraints	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.14/html/security_and_compliance/security-compliance-overview
Building applications	Building applications OpenShift Dedicated 4 Configuring OpenShift Dedicated for your applications Red Hat OpenShift Documentation Team	null	https://docs.redhat.com/en/documentation/openshift_dedicated/4/html/building_applications/index
Chapter 4. MutatingWebhookConfiguration [admissionregistration.k8s.io/v1]	Chapter 4. MutatingWebhookConfiguration [admissionregistration.k8s.io/v1] Description MutatingWebhookConfiguration describes the configuration of and admission webhook that accept or reject and may change the object. Type object 4.1. Specification Property Type Description apiVersion string APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#resources kind string Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds metadata ObjectMeta Standard object metadata; More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata . webhooks array Webhooks is a list of webhooks and the affected resources and operations. webhooks[] object MutatingWebhook describes an admission webhook and the resources and operations it applies to. 4.1.1. .webhooks Description Webhooks is a list of webhooks and the affected resources and operations. Type array 4.1.2. .webhooks[] Description MutatingWebhook describes an admission webhook and the resources and operations it applies to. Type object Required name clientConfig sideEffects admissionReviewVersions Property Type Description admissionReviewVersions array (string) AdmissionReviewVersions is an ordered list of preferred AdmissionReview versions the Webhook expects. API server will try to use first version in the list which it supports. If none of the versions specified in this list supported by API server, validation will fail for this object. If a persisted webhook configuration specifies allowed versions and does not include any versions known to the API Server, calls to the webhook will fail and be subject to the failure policy. clientConfig object WebhookClientConfig contains the information to make a TLS connection with the webhook failurePolicy string FailurePolicy defines how unrecognized errors from the admission endpoint are handled - allowed values are Ignore or Fail. Defaults to Fail. Possible enum values: - "Fail" means that an error calling the webhook causes the admission to fail. - "Ignore" means that an error calling the webhook is ignored. matchConditions array MatchConditions is a list of conditions that must be met for a request to be sent to this webhook. Match conditions filter requests that have already been matched by the rules, namespaceSelector, and objectSelector. An empty list of matchConditions matches all requests. There are a maximum of 64 match conditions allowed. The exact matching logic is (in order): 1. If ANY matchCondition evaluates to FALSE, the webhook is skipped. 2. If ALL matchConditions evaluate to TRUE, the webhook is called. 3. If any matchCondition evaluates to an error (but none are FALSE): - If failurePolicy=Fail, reject the request - If failurePolicy=Ignore, the error is ignored and the webhook is skipped matchConditions[] object MatchCondition represents a condition which must by fulfilled for a request to be sent to a webhook. matchPolicy string matchPolicy defines how the "rules" list is used to match incoming requests. Allowed values are "Exact" or "Equivalent". - Exact: match a request only if it exactly matches a specified rule. For example, if deployments can be modified via apps/v1, apps/v1beta1, and extensions/v1beta1, but "rules" only included apiGroups:["apps"], apiVersions:["v1"], resources: ["deployments"] , a request to apps/v1beta1 or extensions/v1beta1 would not be sent to the webhook. - Equivalent: match a request if modifies a resource listed in rules, even via another API group or version. For example, if deployments can be modified via apps/v1, apps/v1beta1, and extensions/v1beta1, and "rules" only included apiGroups:["apps"], apiVersions:["v1"], resources: ["deployments"] , a request to apps/v1beta1 or extensions/v1beta1 would be converted to apps/v1 and sent to the webhook. Defaults to "Equivalent" Possible enum values: - "Equivalent" means requests should be sent to the webhook if they modify a resource listed in rules via another API group or version. - "Exact" means requests should only be sent to the webhook if they exactly match a given rule. name string The name of the admission webhook. Name should be fully qualified, e.g., imagepolicy.kubernetes.io, where "imagepolicy" is the name of the webhook, and kubernetes.io is the name of the organization. Required. namespaceSelector LabelSelector NamespaceSelector decides whether to run the webhook on an object based on whether the namespace for that object matches the selector. If the object itself is a namespace, the matching is performed on object.metadata.labels. If the object is another cluster scoped resource, it never skips the webhook. For example, to run the webhook on any objects whose namespace is not associated with "runlevel" of "0" or "1"; you will set the selector as follows: "namespaceSelector": { "matchExpressions": [ { "key": "runlevel", "operator": "NotIn", "values": [ "0", "1" ] } ] } If instead you want to only run the webhook on any objects whose namespace is associated with the "environment" of "prod" or "staging"; you will set the selector as follows: "namespaceSelector": { "matchExpressions": [ { "key": "environment", "operator": "In", "values": [ "prod", "staging" ] } ] } See https://kubernetes.io/docs/concepts/overview/working-with-objects/labels/ for more examples of label selectors. Default to the empty LabelSelector, which matches everything. objectSelector LabelSelector ObjectSelector decides whether to run the webhook based on if the object has matching labels. objectSelector is evaluated against both the oldObject and newObject that would be sent to the webhook, and is considered to match if either object matches the selector. A null object (oldObject in the case of create, or newObject in the case of delete) or an object that cannot have labels (like a DeploymentRollback or a PodProxyOptions object) is not considered to match. Use the object selector only if the webhook is opt-in, because end users may skip the admission webhook by setting the labels. Default to the empty LabelSelector, which matches everything. reinvocationPolicy string reinvocationPolicy indicates whether this webhook should be called multiple times as part of a single admission evaluation. Allowed values are "Never" and "IfNeeded". Never: the webhook will not be called more than once in a single admission evaluation. IfNeeded: the webhook will be called at least one additional time as part of the admission evaluation if the object being admitted is modified by other admission plugins after the initial webhook call. Webhooks that specify this option must be idempotent, able to process objects they previously admitted. Note: * the number of additional invocations is not guaranteed to be exactly one. * if additional invocations result in further modifications to the object, webhooks are not guaranteed to be invoked again. * webhooks that use this option may be reordered to minimize the number of additional invocations. * to validate an object after all mutations are guaranteed complete, use a validating admission webhook instead. Defaults to "Never". Possible enum values: - "IfNeeded" indicates that the webhook may be called at least one additional time as part of the admission evaluation if the object being admitted is modified by other admission plugins after the initial webhook call. - "Never" indicates that the webhook must not be called more than once in a single admission evaluation. rules array Rules describes what operations on what resources/subresources the webhook cares about. The webhook cares about an operation if it matches any Rule. However, in order to prevent ValidatingAdmissionWebhooks and MutatingAdmissionWebhooks from putting the cluster in a state which cannot be recovered from without completely disabling the plugin, ValidatingAdmissionWebhooks and MutatingAdmissionWebhooks are never called on admission requests for ValidatingWebhookConfiguration and MutatingWebhookConfiguration objects. rules[] object RuleWithOperations is a tuple of Operations and Resources. It is recommended to make sure that all the tuple expansions are valid. sideEffects string SideEffects states whether this webhook has side effects. Acceptable values are: None, NoneOnDryRun (webhooks created via v1beta1 may also specify Some or Unknown). Webhooks with side effects MUST implement a reconciliation system, since a request may be rejected by a future step in the admission chain and the side effects therefore need to be undone. Requests with the dryRun attribute will be auto-rejected if they match a webhook with sideEffects == Unknown or Some. Possible enum values: - "None" means that calling the webhook will have no side effects. - "NoneOnDryRun" means that calling the webhook will possibly have side effects, but if the request being reviewed has the dry-run attribute, the side effects will be suppressed. - "Some" means that calling the webhook will possibly have side effects. If a request with the dry-run attribute would trigger a call to this webhook, the request will instead fail. - "Unknown" means that no information is known about the side effects of calling the webhook. If a request with the dry-run attribute would trigger a call to this webhook, the request will instead fail. timeoutSeconds integer TimeoutSeconds specifies the timeout for this webhook. After the timeout passes, the webhook call will be ignored or the API call will fail based on the failure policy. The timeout value must be between 1 and 30 seconds. Default to 10 seconds. 4.1.3. .webhooks[].clientConfig Description WebhookClientConfig contains the information to make a TLS connection with the webhook Type object Property Type Description caBundle string caBundle is a PEM encoded CA bundle which will be used to validate the webhook's server certificate. If unspecified, system trust roots on the apiserver are used. service object ServiceReference holds a reference to Service.legacy.k8s.io url string url gives the location of the webhook, in standard URL form ( scheme://host:port/path ). Exactly one of url or service must be specified. The host should not refer to a service running in the cluster; use the service field instead. The host might be resolved via external DNS in some apiservers (e.g., kube-apiserver cannot resolve in-cluster DNS as that would be a layering violation). host may also be an IP address. Please note that using localhost or 127.0.0.1 as a host is risky unless you take great care to run this webhook on all hosts which run an apiserver which might need to make calls to this webhook. Such installs are likely to be non-portable, i.e., not easy to turn up in a new cluster. The scheme must be "https"; the URL must begin with "https://". A path is optional, and if present may be any string permissible in a URL. You may use the path to pass an arbitrary string to the webhook, for example, a cluster identifier. Attempting to use a user or basic auth e.g. "user:password@" is not allowed. Fragments ("#... ") and query parameters ("?... ") are not allowed, either. 4.1.4. .webhooks[].clientConfig.service Description ServiceReference holds a reference to Service.legacy.k8s.io Type object Required namespace name Property Type Description name string name is the name of the service. Required namespace string namespace is the namespace of the service. Required path string path is an optional URL path which will be sent in any request to this service. port integer If specified, the port on the service that hosting webhook. Default to 443 for backward compatibility. port should be a valid port number (1-65535, inclusive). 4.1.5. .webhooks[].matchConditions Description MatchConditions is a list of conditions that must be met for a request to be sent to this webhook. Match conditions filter requests that have already been matched by the rules, namespaceSelector, and objectSelector. An empty list of matchConditions matches all requests. There are a maximum of 64 match conditions allowed. The exact matching logic is (in order): 1. If ANY matchCondition evaluates to FALSE, the webhook is skipped. 2. If ALL matchConditions evaluate to TRUE, the webhook is called. 3. If any matchCondition evaluates to an error (but none are FALSE): - If failurePolicy=Fail, reject the request - If failurePolicy=Ignore, the error is ignored and the webhook is skipped Type array 4.1.6. .webhooks[].matchConditions[] Description MatchCondition represents a condition which must by fulfilled for a request to be sent to a webhook. Type object Required name expression Property Type Description expression string Expression represents the expression which will be evaluated by CEL. Must evaluate to bool. CEL expressions have access to the contents of the AdmissionRequest and Authorizer, organized into CEL variables: 'object' - The object from the incoming request. The value is null for DELETE requests. 'oldObject' - The existing object. The value is null for CREATE requests. 'request' - Attributes of the admission request(/pkg/apis/admission/types.go#AdmissionRequest). 'authorizer' - A CEL Authorizer. May be used to perform authorization checks for the principal (user or service account) of the request. See https://pkg.go.dev/k8s.io/apiserver/pkg/cel/library#Authz 'authorizer.requestResource' - A CEL ResourceCheck constructed from the 'authorizer' and configured with the request resource. Documentation on CEL: https://kubernetes.io/docs/reference/using-api/cel/ Required. name string Name is an identifier for this match condition, used for strategic merging of MatchConditions, as well as providing an identifier for logging purposes. A good name should be descriptive of the associated expression. Name must be a qualified name consisting of alphanumeric characters, '-', ' ' or '.', and must start and end with an alphanumeric character (e.g. 'MyName', or 'my.name', or '123-abc', regex used for validation is '([A-Za-z0-9][-A-Za-z0-9 .])?[A-Za-z0-9]') with an optional DNS subdomain prefix and '/' (e.g. 'example.com/MyName') Required. 4.1.7. .webhooks[].rules Description Rules describes what operations on what resources/subresources the webhook cares about. The webhook cares about an operation if it matches any Rule. However, in order to prevent ValidatingAdmissionWebhooks and MutatingAdmissionWebhooks from putting the cluster in a state which cannot be recovered from without completely disabling the plugin, ValidatingAdmissionWebhooks and MutatingAdmissionWebhooks are never called on admission requests for ValidatingWebhookConfiguration and MutatingWebhookConfiguration objects. Type array 4.1.8. .webhooks[].rules[] Description RuleWithOperations is a tuple of Operations and Resources. It is recommended to make sure that all the tuple expansions are valid. Type object Property Type Description apiGroups array (string) APIGroups is the API groups the resources belong to. ' ' is all groups. If ' ' is present, the length of the slice must be one. Required. apiVersions array (string) APIVersions is the API versions the resources belong to. ' ' is all versions. If ' ' is present, the length of the slice must be one. Required. operations array (string) Operations is the operations the admission hook cares about - CREATE, UPDATE, DELETE, CONNECT or for all of those operations and any future admission operations that are added. If '' is present, the length of the slice must be one. Required. resources array (string) Resources is a list of resources this rule applies to. For example: 'pods' means pods. 'pods/log' means the log subresource of pods. ' ' means all resources, but not subresources. 'pods/ ' means all subresources of pods. ' /scale' means all scale subresources. ' /' means all resources and their subresources. If wildcard is present, the validation rule will ensure resources do not overlap with each other. Depending on the enclosing object, subresources might not be allowed. Required. scope string scope specifies the scope of this rule. Valid values are "Cluster", "Namespaced", and " " "Cluster" means that only cluster-scoped resources will match this rule. Namespace API objects are cluster-scoped. "Namespaced" means that only namespaced resources will match this rule. " " means that there are no scope restrictions. Subresources match the scope of their parent resource. Default is "*". 4.2. API endpoints The following API endpoints are available: /apis/admissionregistration.k8s.io/v1/mutatingwebhookconfigurations DELETE : delete collection of MutatingWebhookConfiguration GET : list or watch objects of kind MutatingWebhookConfiguration POST : create a MutatingWebhookConfiguration /apis/admissionregistration.k8s.io/v1/watch/mutatingwebhookconfigurations GET : watch individual changes to a list of MutatingWebhookConfiguration. deprecated: use the 'watch' parameter with a list operation instead. /apis/admissionregistration.k8s.io/v1/mutatingwebhookconfigurations/{name} DELETE : delete a MutatingWebhookConfiguration GET : read the specified MutatingWebhookConfiguration PATCH : partially update the specified MutatingWebhookConfiguration PUT : replace the specified MutatingWebhookConfiguration /apis/admissionregistration.k8s.io/v1/watch/mutatingwebhookconfigurations/{name} GET : watch changes to an object of kind MutatingWebhookConfiguration. deprecated: use the 'watch' parameter with a list operation instead, filtered to a single item with the 'fieldSelector' parameter. 4.2.1. /apis/admissionregistration.k8s.io/v1/mutatingwebhookconfigurations HTTP method DELETE Description delete collection of MutatingWebhookConfiguration Table 4.1. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed Table 4.2. HTTP responses HTTP code Reponse body 200 - OK Status schema 401 - Unauthorized Empty HTTP method GET Description list or watch objects of kind MutatingWebhookConfiguration Table 4.3. HTTP responses HTTP code Reponse body 200 - OK MutatingWebhookConfigurationList schema 401 - Unauthorized Empty HTTP method POST Description create a MutatingWebhookConfiguration Table 4.4. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.5. Body parameters Parameter Type Description body MutatingWebhookConfiguration schema Table 4.6. HTTP responses HTTP code Reponse body 200 - OK MutatingWebhookConfiguration schema 201 - Created MutatingWebhookConfiguration schema 202 - Accepted MutatingWebhookConfiguration schema 401 - Unauthorized Empty 4.2.2. /apis/admissionregistration.k8s.io/v1/watch/mutatingwebhookconfigurations HTTP method GET Description watch individual changes to a list of MutatingWebhookConfiguration. deprecated: use the 'watch' parameter with a list operation instead. Table 4.7. HTTP responses HTTP code Reponse body 200 - OK WatchEvent schema 401 - Unauthorized Empty 4.2.3. /apis/admissionregistration.k8s.io/v1/mutatingwebhookconfigurations/{name} Table 4.8. Global path parameters Parameter Type Description name string name of the MutatingWebhookConfiguration HTTP method DELETE Description delete a MutatingWebhookConfiguration Table 4.9. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed Table 4.10. HTTP responses HTTP code Reponse body 200 - OK Status schema 202 - Accepted Status schema 401 - Unauthorized Empty HTTP method GET Description read the specified MutatingWebhookConfiguration Table 4.11. HTTP responses HTTP code Reponse body 200 - OK MutatingWebhookConfiguration schema 401 - Unauthorized Empty HTTP method PATCH Description partially update the specified MutatingWebhookConfiguration Table 4.12. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.13. HTTP responses HTTP code Reponse body 200 - OK MutatingWebhookConfiguration schema 201 - Created MutatingWebhookConfiguration schema 401 - Unauthorized Empty HTTP method PUT Description replace the specified MutatingWebhookConfiguration Table 4.14. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.15. Body parameters Parameter Type Description body MutatingWebhookConfiguration schema Table 4.16. HTTP responses HTTP code Reponse body 200 - OK MutatingWebhookConfiguration schema 201 - Created MutatingWebhookConfiguration schema 401 - Unauthorized Empty 4.2.4. /apis/admissionregistration.k8s.io/v1/watch/mutatingwebhookconfigurations/{name} Table 4.17. Global path parameters Parameter Type Description name string name of the MutatingWebhookConfiguration HTTP method GET Description watch changes to an object of kind MutatingWebhookConfiguration. deprecated: use the 'watch' parameter with a list operation instead, filtered to a single item with the 'fieldSelector' parameter. Table 4.18. HTTP responses HTTP code Reponse body 200 - OK WatchEvent schema 401 - Unauthorized Empty	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.18/html/extension_apis/mutatingwebhookconfiguration-admissionregistration-k8s-io-v1
Chapter 15. Image-based upgrade for single-node OpenShift clusters	Chapter 15. Image-based upgrade for single-node OpenShift clusters 15.1. Understanding the image-based upgrade for single-node OpenShift clusters From OpenShift Container Platform 4.14.13, the Lifecycle Agent provides you with an alternative way to upgrade the platform version of a single-node OpenShift cluster. The image-based upgrade is faster than the standard upgrade method and allows you to directly upgrade from OpenShift Container Platform <4.y> to <4.y+2>, and <4.y.z> to <4.y.z+n>. This upgrade method utilizes a generated OCI image from a dedicated seed cluster that is installed on the target single-node OpenShift cluster as a new ostree stateroot. A seed cluster is a single-node OpenShift cluster deployed with the target OpenShift Container Platform version, Day 2 Operators, and configurations that are common to all target clusters. You can use the seed image, which is generated from the seed cluster, to upgrade the platform version on any single-node OpenShift cluster that has the same combination of hardware, Day 2 Operators, and cluster configuration as the seed cluster. Important The image-based upgrade uses custom images that are specific to the hardware platform that the clusters are running on. Each different hardware platform requires a separate seed image. The Lifecycle Agent uses two custom resources (CRs) on the participating clusters to orchestrate the upgrade: On the seed cluster, the SeedGenerator CR allows for the seed image generation. This CR specifies the repository to push the seed image to. On the target cluster, the ImageBasedUpgrade CR specifies the seed image for the upgrade of the target cluster and the backup configurations for your workloads. Example SeedGenerator CR apiVersion: lca.openshift.io/v1 kind: SeedGenerator metadata: name: seedimage spec: seedImage: <seed_image> Example ImageBasedUpgrade CR apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: name: upgrade spec: stage: Idle 1 seedImageRef: 2 version: <target_version> image: <seed_container_image> pullSecretRef: name: <seed_pull_secret> autoRollbackOnFailure: {} # initMonitorTimeoutSeconds: 1800 3 extraManifests: 4 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 5 - name: oadp-cm-example namespace: openshift-adp 1 Stage of the ImageBasedUpgrade CR. The value can be Idle , Prep , Upgrade , or Rollback . 2 Target platform version, seed image to be used, and the secret required to access the image. 3 Optional: Time frame in seconds to roll back when the upgrade does not complete within that time frame after the first reboot. If not defined or set to 0 , the default value of 1800 seconds (30 minutes) is used. 4 Optional: List of ConfigMap resources that contain your custom catalog sources to retain after the upgrade, and your extra manifests to apply to the target cluster that are not part of the seed image. 5 List of ConfigMap resources that contain the OADP Backup and Restore CRs. 15.1.1. Stages of the image-based upgrade After generating the seed image on the seed cluster, you can move through the stages on the target cluster by setting the spec.stage field to one of the following values in the ImageBasedUpgrade CR: Idle Prep Upgrade Rollback (Optional) Figure 15.1. Stages of the image-based upgrade 15.1.1.1. Idle stage The Lifecycle Agent creates an ImageBasedUpgrade CR set to stage: Idle when the Operator is first deployed. This is the default stage. There is no ongoing upgrade and the cluster is ready to move to the Prep stage. Figure 15.2. Transition from Idle stage You also move to the Idle stage to do one of the following steps: Finalize a successful upgrade Finalize a rollback Cancel an ongoing upgrade until the pre-pivot phase in the Upgrade stage Moving to the Idle stage ensures that the Lifecycle Agent cleans up resources, so that the cluster is ready for upgrades again. Figure 15.3. Transitions to Idle stage Important If using RHACM when you cancel an upgrade, you must remove the import.open-cluster-management.io/disable-auto-import annotation from the target managed cluster to re-enable the automatic import of the cluster. 15.1.1.2. Prep stage Note You can complete this stage before a scheduled maintenance window. For the Prep stage, you specify the following upgrade details in the ImageBasedUpgrade CR: seed image to use resources to back up extra manifests to apply and custom catalog sources to retain after the upgrade, if any Then, based on what you specify, the Lifecycle Agent prepares for the upgrade without impacting the current running version. During this stage, the Lifecycle Agent ensures that the target cluster is ready to proceed to the Upgrade stage by checking if it meets certain conditions. The Operator pulls the seed image to the target cluster with additional container images specified in the seed image. The Lifecycle Agent checks if there is enough space on the container storage disk and if necessary, the Operator deletes unpinned images until the disk usage is below the specified threshold. For more information about how to configure or disable the cleaning up of the container storage disk, see "Configuring the automatic image cleanup of the container storage disk". You also prepare backup resources with the OADP Operator's Backup and Restore CRs. These CRs are used in the Upgrade stage to reconfigure the cluster, register the cluster with RHACM, and restore application artifacts. In addition to the OADP Operator, the Lifecycle Agent uses the ostree versioning system to create a backup, which allows complete cluster reconfiguration after both upgrade and rollback. After the Prep stage finishes, you can cancel the upgrade process by moving to the Idle stage or you can start the upgrade by moving to the Upgrade stage in the ImageBasedUpgrade CR. If you cancel the upgrade, the Operator performs cleanup operations. Figure 15.4. Transition from Prep stage 15.1.1.3. Upgrade stage The Upgrade stage consists of two phases: pre-pivot Just before pivoting to the new stateroot, the Lifecycle Agent collects the required cluster specific artifacts and stores them in the new stateroot. The backup of your cluster resources specified in the Prep stage are created on a compatible Object storage solution. The Lifecycle Agent exports CRs specified in the extraManifests field in the ImageBasedUpgrade CR or the CRs described in the ZTP policies that are bound to the target cluster. After pre-pivot phase has completed, the Lifecycle Agent sets the new stateroot deployment as the default boot entry and reboots the node. post-pivot After booting from the new stateroot, the Lifecycle Agent also regenerates the seed image's cluster cryptography. This ensures that each single-node OpenShift cluster upgraded with the same seed image has unique and valid cryptographic objects. The Operator then reconfigures the cluster by applying cluster-specific artifacts that were collected in the pre-pivot phase. The Operator applies all saved CRs, and restores the backups. After the upgrade has completed and you are satisfied with the changes, you can finalize the upgrade by moving to the Idle stage. Important When you finalize the upgrade, you cannot roll back to the original release. Figure 15.5. Transitions from Upgrade stage If you want to cancel the upgrade, you can do so until the pre-pivot phase of the Upgrade stage. If you encounter issues after the upgrade, you can move to the Rollback stage for a manual rollback. 15.1.1.4. Rollback stage The Rollback stage can be initiated manually or automatically upon failure. During the Rollback stage, the Lifecycle Agent sets the original ostree stateroot deployment as default. Then, the node reboots with the release of OpenShift Container Platform and application configurations. Warning If you move to the Idle stage after a rollback, the Lifecycle Agent cleans up resources that can be used to troubleshoot a failed upgrade. The Lifecycle Agent initiates an automatic rollback if the upgrade does not complete within a specified time limit. For more information about the automatic rollback, see the "Moving to the Rollback stage with Lifecycle Agent" or "Moving to the Rollback stage with Lifecycle Agent and GitOps ZTP" sections. Figure 15.6. Transition from Rollback stage Additional resources Configuring the automatic image cleanup of the container storage disk Performing an image-based upgrade for single-node OpenShift clusters with Lifecycle Agent Performing an image-based upgrade for single-node OpenShift clusters using GitOps ZTP 15.1.2. Guidelines for the image-based upgrade For a successful image-based upgrade, your deployments must meet certain requirements. There are different deployment methods in which you can perform the image-based upgrade: GitOps ZTP You use the GitOps Zero Touch Provisioning (ZTP) to deploy and configure your clusters. Non-GitOps You manually deploy and configure your clusters. You can perform an image-based upgrade in disconnected environments. For more information about how to mirror images for a disconnected environment, see "Mirroring images for a disconnected installation". Additional resources Mirroring images for a disconnected installation 15.1.2.1. Minimum software version of components Depending on your deployment method, the image-based upgrade requires the following minimum software versions. Table 15.1. Minimum software version of components Component Software version Required Lifecycle Agent 4.16 Yes OADP Operator 1.4.1 Yes Managed cluster version 4.14.13 Yes Hub cluster version 4.16 No RHACM 2.10.2 No GitOps ZTP plugin 4.16 Only for GitOps ZTP deployment method Red Hat OpenShift GitOps 1.12 Only for GitOps ZTP deployment method Topology Aware Lifecycle Manager (TALM) 4.16 Only for GitOps ZTP deployment method Local Storage Operator [1] 4.14 Yes Logical Volume Manager (LVM) Storage [1] 4.14.2 Yes The persistent storage must be provided by either the LVM Storage or the Local Storage Operator, not both. 15.1.2.2. Hub cluster guidelines If you are using Red Hat Advanced Cluster Management (RHACM), your hub cluster needs to meet the following conditions: To avoid including any RHACM resources in your seed image, you need to disable all optional RHACM add-ons before generating the seed image. Your hub cluster must be upgraded to at least the target version before performing an image-based upgrade on a target single-node OpenShift cluster. 15.1.2.3. Seed image guidelines The seed image targets a set of single-node OpenShift clusters with the same hardware and similar configuration. This means that the seed cluster must match the configuration of the target clusters for the following items: CPU topology Number of CPU cores Tuned performance configuration, such as number of reserved CPUs MachineConfig resources for the target cluster IP version Note Dual-stack networking is not supported in this release. Set of Day 2 Operators, including the Lifecycle Agent and the OADP Operator Disconnected registry FIPS configuration The following configurations only have to partially match on the participating clusters: If the target cluster has a proxy configuration, the seed cluster must have a proxy configuration too but the configuration does not have to be the same. A dedicated partition on the primary disk for container storage is required on all participating clusters. However, the size and start of the partition does not have to be the same. Only the spec.config.storage.disks.partitions.label: varlibcontainers label in the MachineConfig CR must match on both the seed and target clusters. For more information about how to create the disk partition, see "Configuring a shared container partition between ostree stateroots" or "Configuring a shared container partition between ostree stateroots when using GitOps ZTP". For more information about what to include in the seed image, see "Seed image configuration" and "Seed image configuration using the RAN DU profile". Additional resources Configuring a shared container partition between ostree stateroots Configuring a shared container partition between ostree stateroots when using GitOps ZTP Seed image configuration 15.1.2.4. OADP backup and restore guidelines With the OADP Operator, you can back up and restore your applications on your target clusters by using Backup and Restore CRs wrapped in ConfigMap objects. The application must work on the current and the target OpenShift Container Platform versions so that they can be restored after the upgrade. The backups must include resources that were initially created. The following resources must be excluded from the backup: pods endpoints controllerrevision podmetrics packagemanifest replicaset localvolume , if using Local Storage Operator (LSO) There are two local storage implementations for single-node OpenShift: Local Storage Operator (LSO) The Lifecycle Agent automatically backs up and restores the required artifacts, including localvolume resources and their associated StorageClass resources. You must exclude the persistentvolumes resource in the application Backup CR. LVM Storage You must create the Backup and Restore CRs for LVM Storage artifacts. You must include the persistentVolumes resource in the application Backup CR. For the image-based upgrade, only one Operator is supported on a given target cluster. Important For both Operators, you must not apply the Operator CRs as extra manifests through the ImageBasedUpgrade CR. The persistent volume contents are preserved and used after the pivot. When you are configuring the DataProtectionApplication CR, you must ensure that the .spec.configuration.restic.enable is set to false for an image-based upgrade. This disables Container Storage Interface integration. 15.1.2.4.1. lca.openshift.io/apply-wave guidelines The lca.openshift.io/apply-wave annotation determines the apply order of Backup or Restore CRs. The value of the annotation must be a string number. If you define the lca.openshift.io/apply-wave annotation in the Backup or Restore CRs, they are applied in increasing order based on the annotation value. If you do not define the annotation, they are applied together. The lca.openshift.io/apply-wave annotation must be numerically lower in your platform Restore CRs, for example RHACM and LVM Storage artifacts, than that of the application. This way, the platform artifacts are restored before your applications. If your application includes cluster-scoped resources, you must create separate Backup and Restore CRs to scope the backup to the specific cluster-scoped resources created by the application. The Restore CR for the cluster-scoped resources must be restored before the remaining application Restore CR(s). 15.1.2.4.2. lca.openshift.io/apply-label guidelines You can back up specific resources exclusively with the lca.openshift.io/apply-label annotation. Based on which resources you define in the annotation, the Lifecycle Agent applies the lca.openshift.io/backup: <backup_name> label and adds the labelSelector.matchLabels.lca.openshift.io/backup: <backup_name> label selector to the specified resources when creating the Backup CRs. To use the lca.openshift.io/apply-label annotation for backing up specific resources, the resources listed in the annotation must also be included in the spec section. If the lca.openshift.io/apply-label annotation is used in the Backup CR, only the resources listed in the annotation are backed up, even if other resource types are specified in the spec section or not. Example CR apiVersion: velero.io/v1 kind: Backup metadata: name: acm-klusterlet namespace: openshift-adp annotations: lca.openshift.io/apply-label: rbac.authorization.k8s.io/v1/clusterroles/klusterlet,apps/v1/deployments/open-cluster-management-agent/klusterlet 1 labels: velero.io/storage-location: default spec: includedNamespaces: - open-cluster-management-agent includedClusterScopedResources: - clusterroles includedNamespaceScopedResources: - deployments 1 The value must be a list of comma-separated objects in group/version/resource/name format for cluster-scoped resources or group/version/resource/namespace/name format for namespace-scoped resources, and it must be attached to the related Backup CR. 15.1.2.5. Extra manifest guidelines The Lifecycle Agent uses extra manifests to restore your target clusters after rebooting with the new stateroot deployment and before restoring application artifacts. Different deployment methods require a different way to apply the extra manifests: GitOps ZTP You use the lca.openshift.io/target-ocp-version: <target_ocp_version> label to mark the extra manifests that the Lifecycle Agent must extract and apply after the pivot. You can specify the number of manifests labeled with lca.openshift.io/target-ocp-version by using the lca.openshift.io/target-ocp-version-manifest-count annotation in the ImageBasedUpgrade CR. If specified, the Lifecycle Agent verifies that the number of manifests extracted from policies matches the number provided in the annotation during the prep and upgrade stages. Example for the lca.openshift.io/target-ocp-version-manifest-count annotation apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: annotations: lca.openshift.io/target-ocp-version-manifest-count: "5" name: upgrade Non-Gitops You mark your extra manifests with the lca.openshift.io/apply-wave annotation to determine the apply order. The labeled extra manifests are wrapped in ConfigMap objects and referenced in the ImageBasedUpgrade CR that the Lifecycle Agent uses after the pivot. If the target cluster uses custom catalog sources, you must include them as extra manifests that point to the correct release version. Important You cannot apply the following items as extra manifests: MachineConfig objects OLM Operator subscriptions Additional resources Performing an image-based upgrade for single-node OpenShift clusters with Lifecycle Agent Preparing the hub cluster for ZTP Creating ConfigMap objects for the image-based upgrade with Lifecycle Agent Creating ConfigMap objects for the image-based upgrade with GitOps ZTP About installing OADP 15.2. Preparing for an image-based upgrade for single-node OpenShift clusters 15.2.1. Configuring a shared container partition for the image-based upgrade Your single-node OpenShift clusters need to have a shared /var/lib/containers partition for the image-based upgrade. You can do this at install time. 15.2.1.1. Configuring a shared container partition between ostree stateroots Apply a MachineConfig to both the seed and the target clusters during installation time to create a separate partition and share the /var/lib/containers partition between the two ostree stateroots that will be used during the upgrade process. Important You must complete this procedure at installation time. Procedure Apply a MachineConfig to create a separate partition: apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: master name: 98-var-lib-containers-partitioned spec: config: ignition: version: 3.2.0 storage: disks: - device: /dev/disk/by-path/pci-<root_disk> 1 partitions: - label: var-lib-containers startMiB: <start_of_partition> 2 sizeMiB: <partition_size> 3 filesystems: - device: /dev/disk/by-partlabel/var-lib-containers format: xfs mountOptions: - defaults - prjquota path: /var/lib/containers wipeFilesystem: true systemd: units: - contents: \|- # Generated by Butane [Unit] Before=local-fs.target Requires=systemd-fsck@dev-disk-by\x2dpartlabel-var\x2dlib\x2dcontainers.service After=systemd-fsck@dev-disk-by\x2dpartlabel-var\x2dlib\x2dcontainers.service [Mount] Where=/var/lib/containers What=/dev/disk/by-partlabel/var-lib-containers Type=xfs Options=defaults,prjquota [Install] RequiredBy=local-fs.target enabled: true name: var-lib-containers.mount 1 Specify the root disk. 2 Specify the start of the partition in MiB. If the value is too small, the installation will fail. 3 Specify a minimum size for the partition of 500 GB to ensure adequate disk space for precached images. If the value is too small, the deployments after installation will fail. 15.2.1.2. Configuring a shared container directory between ostree stateroots when using GitOps ZTP When you are using the GitOps Zero Touch Provisioning (ZTP) workflow, you do the following procedure to create a separate disk partition on both the seed and target cluster and to share the /var/lib/containers partition. Important You must complete this procedure at installation time. Prerequisites You have installed Butane. For more information, see "Installing Butane". Procedure Create the storage.bu file: variant: fcos version: 1.3.0 storage: disks: - device: /dev/disk/by-path/pci-<root_disk> 1 wipe_table: false partitions: - label: var-lib-containers start_mib: <start_of_partition> 2 size_mib: <partition_size> 3 filesystems: - path: /var/lib/containers device: /dev/disk/by-partlabel/var-lib-containers format: xfs wipe_filesystem: true with_mount_unit: true mount_options: - defaults - prjquota 1 Specify the root disk. 2 Specify the start of the partition in MiB. If the value is too small, the installation will fail. 3 Specify a minimum size for the partition of 500 GB to ensure adequate disk space for precached images. If the value is too small, the deployments after installation will fail. Convert the storage.bu to an Ignition file by running the following command: USD butane storage.bu Example output {"ignition":{"version":"3.2.0"},"storage":{"disks":[{"device":"/dev/disk/by-path/pci-0000:00:17.0-ata-1.0","partitions":[{"label":"var-lib-containers","sizeMiB":0,"startMiB":250000}],"wipeTable":false}],"filesystems":[{"device":"/dev/disk/by-partlabel/var-lib-containers","format":"xfs","mountOptions":["defaults","prjquota"],"path":"/var/lib/containers","wipeFilesystem":true}]},"systemd":{"units":[{"contents":"# Generated by Butane\n[Unit]\nRequires=systemd-fsck@dev-disk-by\\x2dpartlabel-var\\x2dlib\\x2dcontainers.service\nAfter=systemd-fsck@dev-disk-by\\x2dpartlabel-var\\x2dlib\\x2dcontainers.service\n\n[Mount]\nWhere=/var/lib/containers\nWhat=/dev/disk/by-partlabel/var-lib-containers\nType=xfs\nOptions=defaults,prjquota\n\n[Install]\nRequiredBy=local-fs.target","enabled":true,"name":"var-lib-containers.mount"}]}} Copy the output into the .spec.clusters.nodes.ignitionConfigOverride field in the SiteConfig CR: [...] spec: clusters: - nodes: - hostName: <name> ignitionConfigOverride: '{"ignition":{"version":"3.2.0"},"storage":{"disks":[{"device":"/dev/disk/by-path/pci-0000:00:17.0-ata-1.0","partitions":[{"label":"var-lib-containers","sizeMiB":0,"startMiB":250000}],"wipeTable":false}],"filesystems":[{"device":"/dev/disk/by-partlabel/var-lib-containers","format":"xfs","mountOptions":["defaults","prjquota"],"path":"/var/lib/containers","wipeFilesystem":true}]},"systemd":{"units":[{"contents":"# Generated by Butane\n[Unit]\nRequires=systemd-fsck@dev-disk-by\\x2dpartlabel-var\\x2dlib\\x2dcontainers.service\nAfter=systemd-fsck@dev-disk-by\\x2dpartlabel-var\\x2dlib\\x2dcontainers.service\n\n[Mount]\nWhere=/var/lib/containers\nWhat=/dev/disk/by-partlabel/var-lib-containers\nType=xfs\nOptions=defaults,prjquota\n\n[Install]\nRequiredBy=local-fs.target","enabled":true,"name":"var-lib-containers.mount"}]}}' [...] Verification During or after installation, verify on the hub cluster that the BareMetalHost object shows the annotation by running the following command: USD oc get bmh -n my-sno-ns my-sno -ojson \| jq '.metadata.annotations["bmac.agent-install.openshift.io/ignition-config-overrides"]' Example output "{\"ignition\":{\"version\":\"3.2.0\"},\"storage\":{\"disks\":[{\"device\":\"/dev/disk/by-path/pci-0000:00:17.0-ata-1.0\",\"partitions\":[{\"label\":\"var-lib-containers\",\"sizeMiB\":0,\"startMiB\":250000}],\"wipeTable\":false}],\"filesystems\":[{\"device\":\"/dev/disk/by-partlabel/var-lib-containers\",\"format\":\"xfs\",\"mountOptions\":[\"defaults\",\"prjquota\"],\"path\":\"/var/lib/containers\",\"wipeFilesystem\":true}]},\"systemd\":{\"units\":[{\"contents\":\"# Generated by Butane\\n[Unit]\\nRequires=systemd-fsck@dev-disk-by\\\\x2dpartlabel-var\\\\x2dlib\\\\x2dcontainers.service\\nAfter=systemd-fsck@dev-disk-by\\\\x2dpartlabel-var\\\\x2dlib\\\\x2dcontainers.service\\n\\n[Mount]\\nWhere=/var/lib/containers\\nWhat=/dev/disk/by-partlabel/var-lib-containers\\nType=xfs\\nOptions=defaults,prjquota\\n\\n[Install]\\nRequiredBy=local-fs.target\",\"enabled\":true,\"name\":\"var-lib-containers.mount\"}]}}" After installation, check the single-node OpenShift disk status by running the following commands: # lsblk Example output NAME MAJ:MIN RM SIZE RO TYPE MOUNTPOINTS sda 8:0 0 446.6G 0 disk ├─sda1 8:1 0 1M 0 part ├─sda2 8:2 0 127M 0 part ├─sda3 8:3 0 384M 0 part /boot ├─sda4 8:4 0 243.6G 0 part /var │ /sysroot/ostree/deploy/rhcos/var │ /usr │ /etc │ / │ /sysroot └─sda5 8:5 0 202.5G 0 part /var/lib/containers # df -h Example output Filesystem Size Used Avail Use% Mounted on devtmpfs 4.0M 0 4.0M 0% /dev tmpfs 126G 84K 126G 1% /dev/shm tmpfs 51G 93M 51G 1% /run /dev/sda4 244G 5.2G 239G 3% /sysroot tmpfs 126G 4.0K 126G 1% /tmp /dev/sda5 203G 119G 85G 59% /var/lib/containers /dev/sda3 350M 110M 218M 34% /boot tmpfs 26G 0 26G 0% /run/user/1000 Additional resources Installing Butane 15.2.2. Installing Operators for the image-based upgrade Prepare your clusters for the upgrade by installing the Lifecycle Agent and the OADP Operator. To install the OADP Operator with the non-GitOps method, see "Installing the OADP Operator". Additional resources Installing the OADP Operator About backup and snapshot locations and their secrets Creating a Backup CR Creating a Restore CR 15.2.2.1. Installing the Lifecycle Agent by using the CLI You can use the OpenShift CLI ( oc ) to install the Lifecycle Agent. Prerequisites You have installed the OpenShift CLI ( oc ). You have logged in as a user with cluster-admin privileges. Procedure Create a Namespace object YAML file for the Lifecycle Agent: apiVersion: v1 kind: Namespace metadata: name: openshift-lifecycle-agent annotations: workload.openshift.io/allowed: management Create the Namespace CR by running the following command: USD oc create -f <namespace_filename>.yaml Create an OperatorGroup object YAML file for the Lifecycle Agent: apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: openshift-lifecycle-agent namespace: openshift-lifecycle-agent spec: targetNamespaces: - openshift-lifecycle-agent Create the OperatorGroup CR by running the following command: USD oc create -f <operatorgroup_filename>.yaml Create a Subscription CR for the Lifecycle Agent: apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-lifecycle-agent-subscription namespace: openshift-lifecycle-agent spec: channel: "stable" name: lifecycle-agent source: redhat-operators sourceNamespace: openshift-marketplace Create the Subscription CR by running the following command: USD oc create -f <subscription_filename>.yaml Verification To verify that the installation succeeded, inspect the CSV resource by running the following command: USD oc get csv -n openshift-lifecycle-agent Example output NAME DISPLAY VERSION REPLACES PHASE lifecycle-agent.v4.17.0 Openshift Lifecycle Agent 4.17.0 Succeeded Verify that the Lifecycle Agent is up and running by running the following command: USD oc get deploy -n openshift-lifecycle-agent Example output NAME READY UP-TO-DATE AVAILABLE AGE lifecycle-agent-controller-manager 1/1 1 1 14s 15.2.2.2. Installing the Lifecycle Agent by using the web console You can use the OpenShift Container Platform web console to install the Lifecycle Agent. Prerequisites You have logged in as a user with cluster-admin privileges. Procedure In the OpenShift Container Platform web console, navigate to Operators OperatorHub . Search for the Lifecycle Agent from the list of available Operators, and then click Install . On the Install Operator page, under A specific namespace on the cluster select openshift-lifecycle-agent . Click Install . Verification To confirm that the installation is successful: Click Operators Installed Operators . Ensure that the Lifecycle Agent is listed in the openshift-lifecycle-agent project with a Status of InstallSucceeded . Note During installation an Operator might display a Failed status. If the installation later succeeds with an InstallSucceeded message, you can ignore the Failed message. If the Operator is not installed successfully: Click Operators Installed Operators , and inspect the Operator Subscriptions and Install Plans tabs for any failure or errors under Status . Click Workloads Pods , and check the logs for pods in the openshift-lifecycle-agent project. 15.2.2.3. Installing the Lifecycle Agent with GitOps ZTP Install the Lifecycle Agent with GitOps Zero Touch Provisioning (ZTP) to do an image-based upgrade. Procedure Extract the following CRs from the ztp-site-generate container image and push them to the source-cr directory: Example LcaSubscriptionNS.yaml file apiVersion: v1 kind: Namespace metadata: name: openshift-lifecycle-agent annotations: workload.openshift.io/allowed: management ran.openshift.io/ztp-deploy-wave: "2" labels: kubernetes.io/metadata.name: openshift-lifecycle-agent Example LcaSubscriptionOperGroup.yaml file apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: lifecycle-agent-operatorgroup namespace: openshift-lifecycle-agent annotations: ran.openshift.io/ztp-deploy-wave: "2" spec: targetNamespaces: - openshift-lifecycle-agent Example LcaSubscription.yaml file apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: lifecycle-agent namespace: openshift-lifecycle-agent annotations: ran.openshift.io/ztp-deploy-wave: "2" spec: channel: "stable" name: lifecycle-agent source: redhat-operators sourceNamespace: openshift-marketplace installPlanApproval: Manual status: state: AtLatestKnown Example directory structure ├── kustomization.yaml ├── sno │ ├── example-cnf.yaml │ ├── common-ranGen.yaml │ ├── group-du-sno-ranGen.yaml │ ├── group-du-sno-validator-ranGen.yaml │ └── ns.yaml ├── source-crs │ ├── LcaSubscriptionNS.yaml │ ├── LcaSubscriptionOperGroup.yaml │ ├── LcaSubscription.yaml Add the CRs to your common PolicyGenTemplate : apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: "example-common-latest" namespace: "ztp-common" spec: bindingRules: common: "true" du-profile: "latest" sourceFiles: - fileName: LcaSubscriptionNS.yaml policyName: "subscriptions-policy" - fileName: LcaSubscriptionOperGroup.yaml policyName: "subscriptions-policy" - fileName: LcaSubscription.yaml policyName: "subscriptions-policy" [...] 15.2.2.4. Installing and configuring the OADP Operator with GitOps ZTP Install and configure the OADP Operator with GitOps ZTP before starting the upgrade. Procedure Extract the following CRs from the ztp-site-generate container image and push them to the source-cr directory: Example OadpSubscriptionNS.yaml file apiVersion: v1 kind: Namespace metadata: name: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: "2" labels: kubernetes.io/metadata.name: openshift-adp Example OadpSubscriptionOperGroup.yaml file apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: redhat-oadp-operator namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: "2" spec: targetNamespaces: - openshift-adp Example OadpSubscription.yaml file apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: redhat-oadp-operator namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: "2" spec: channel: stable-1.4 name: redhat-oadp-operator source: redhat-operators sourceNamespace: openshift-marketplace installPlanApproval: Manual status: state: AtLatestKnown Example OadpOperatorStatus.yaml file apiVersion: operators.coreos.com/v1 kind: Operator metadata: name: redhat-oadp-operator.openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: "2" status: components: refs: - kind: Subscription namespace: openshift-adp conditions: - type: CatalogSourcesUnhealthy status: "False" - kind: InstallPlan namespace: openshift-adp conditions: - type: Installed status: "True" - kind: ClusterServiceVersion namespace: openshift-adp conditions: - type: Succeeded status: "True" reason: InstallSucceeded Example directory structure ├── kustomization.yaml ├── sno │ ├── example-cnf.yaml │ ├── common-ranGen.yaml │ ├── group-du-sno-ranGen.yaml │ ├── group-du-sno-validator-ranGen.yaml │ └── ns.yaml ├── source-crs │ ├── OadpSubscriptionNS.yaml │ ├── OadpSubscriptionOperGroup.yaml │ ├── OadpSubscription.yaml │ ├── OadpOperatorStatus.yaml Add the CRs to your common PolicyGenTemplate : apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: "example-common-latest" namespace: "ztp-common" spec: bindingRules: common: "true" du-profile: "latest" sourceFiles: - fileName: OadpSubscriptionNS.yaml policyName: "subscriptions-policy" - fileName: OadpSubscriptionOperGroup.yaml policyName: "subscriptions-policy" - fileName: OadpSubscription.yaml policyName: "subscriptions-policy" - fileName: OadpOperatorStatus.yaml policyName: "subscriptions-policy" [...] Create the DataProtectionApplication CR and the S3 secret only for the target cluster: Extract the following CRs from the ztp-site-generate container image and push them to the source-cr directory: Example DataProtectionApplication.yaml file apiVersion: oadp.openshift.io/v1alpha1 kind: DataProtectionApplication metadata: name: dataprotectionapplication namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: "100" spec: configuration: restic: enable: false 1 velero: defaultPlugins: - aws - openshift resourceTimeout: 10m backupLocations: - velero: config: profile: "default" region: minio s3Url: USDurl insecureSkipTLSVerify: "true" s3ForcePathStyle: "true" provider: aws default: true credential: key: cloud name: cloud-credentials objectStorage: bucket: USDbucketName 2 prefix: USDprefixName 3 status: conditions: - reason: Complete status: "True" type: Reconciled 1 The spec.configuration.restic.enable field must be set to false for an image-based upgrade because persistent volume contents are retained and reused after the upgrade. 2 3 The bucket defines the bucket name that is created in S3 backend. The prefix defines the name of the subdirectory that will be automatically created in the bucket. The combination of bucket and prefix must be unique for each target cluster to avoid interference between them. To ensure a unique storage directory for each target cluster, you can use the RHACM hub template function, for example, prefix: {{hub .ManagedClusterName hub}} . Example OadpSecret.yaml file apiVersion: v1 kind: Secret metadata: name: cloud-credentials namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: "100" type: Opaque Example OadpBackupStorageLocationStatus.yaml file apiVersion: velero.io/v1 kind: BackupStorageLocation metadata: namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: "100" status: phase: Available The OadpBackupStorageLocationStatus.yaml CR verifies the availability of backup storage locations created by OADP. Add the CRs to your site PolicyGenTemplate with overrides: apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: "example-cnf" namespace: "ztp-site" spec: bindingRules: sites: "example-cnf" du-profile: "latest" mcp: "master" sourceFiles: ... - fileName: OadpSecret.yaml policyName: "config-policy" data: cloud: <your_credentials> 1 - fileName: DataProtectionApplication.yaml policyName: "config-policy" spec: backupLocations: - velero: config: region: minio s3Url: <your_S3_URL> 2 profile: "default" insecureSkipTLSVerify: "true" s3ForcePathStyle: "true" provider: aws default: true credential: key: cloud name: cloud-credentials objectStorage: bucket: <your_bucket_name> 3 prefix: <cluster_name> 4 - fileName: OadpBackupStorageLocationStatus.yaml policyName: "config-policy" 1 Specify your credentials for your S3 storage backend. 2 Specify the URL for your S3-compatible bucket. 3 4 The bucket defines the bucket name that is created in S3 backend. The prefix defines the name of the subdirectory that will be automatically created in the bucket . The combination of bucket and prefix must be unique for each target cluster to avoid interference between them. To ensure a unique storage directory for each target cluster, you can use the RHACM hub template function, for example, prefix: {{hub .ManagedClusterName hub}} . 15.2.3. Generating a seed image for the image-based upgrade with the Lifecycle Agent Use the Lifecycle Agent to generate the seed image with the SeedGenerator custom resource (CR). 15.2.3.1. Seed image configuration The seed image targets a set of single-node OpenShift clusters with the same hardware and similar configuration. This means that the seed image must have all of the components and configuration that the seed cluster shares with the target clusters. Therefore, the seed image generated from the seed cluster cannot contain any cluster-specific configuration. The following table lists the components, resources, and configurations that you must and must not include in your seed image: Table 15.2. Seed image configuration Cluster configuration Include in seed image Performance profile Yes MachineConfig resources for the target cluster Yes IP version [1] Yes Set of Day 2 Operators, including the Lifecycle Agent and the OADP Operator Yes Disconnected registry configuration [2] Yes Valid proxy configuration [3] Yes FIPS configuration Yes Dedicated partition on the primary disk for container storage that matches the size of the target clusters Yes Local volumes StorageClass used in LocalVolume for LSO LocalVolume for LSO LVMCluster CR for LVMS No OADP DataProtectionApplication CR No Dual-stack networking is not supported in this release. If the seed cluster is installed in a disconnected environment, the target clusters must also be installed in a disconnected environment. The proxy configuration on the seed and target clusters does not have to match. 15.2.3.1.1. Seed image configuration using the RAN DU profile The following table lists the components, resources, and configurations that you must and must not include in the seed image when using the RAN DU profile: Table 15.3. Seed image configuration with RAN DU profile Resource Include in seed image All extra manifests that are applied as part of Day 0 installation Yes All Day 2 Operator subscriptions Yes DisableOLMPprof.yaml Yes TunedPerformancePatch.yaml Yes PerformanceProfile.yaml Yes SriovOperatorConfig.yaml Yes DisableSnoNetworkDiag.yaml Yes StorageClass.yaml No, if it is used in StorageLV.yaml StorageLV.yaml No StorageLVMCluster.yaml No Table 15.4. Seed image configuration with RAN DU profile for extra manifests Resource Apply as extra manifest ClusterLogForwarder.yaml Yes ReduceMonitoringFootprint.yaml Yes SriovFecClusterConfig.yaml Yes PtpOperatorConfigForEvent.yaml Yes DefaultCatsrc.yaml Yes PtpConfig.yaml If the interfaces of the target cluster are common with the seed cluster, you can include them in the seed image. Otherwise, apply it as extra manifests. SriovNetwork.yaml SriovNetworkNodePolicy.yaml If the configuration, including namespaces, is exactly the same on both the seed and target cluster, you can include them in the seed image. Otherwise, apply them as extra manifests. 15.2.3.2. Generating a seed image with the Lifecycle Agent Use the Lifecycle Agent to generate a seed image from a managed cluster. The Operator checks for required system configurations, performs any necessary system cleanup before generating the seed image, and launches the image generation. The seed image generation includes the following tasks: Stopping cluster Operators Preparing the seed image configuration Generating and pushing the seed image to the image repository specified in the SeedGenerator CR Restoring cluster Operators Expiring seed cluster certificates Generating new certificates for the seed cluster Restoring and updating the SeedGenerator CR on the seed cluster Prerequisites RHACM and multicluster engine for Kubernetes Operator are not installed on the seed cluster. You have configured a shared container directory on the seed cluster. You have installed the minimum version of the OADP Operator and the Lifecycle Agent on the seed cluster. Ensure that persistent volumes are not configured on the seed cluster. Ensure that the LocalVolume CR does not exist on the seed cluster if the Local Storage Operator is used. Ensure that the LVMCluster CR does not exist on the seed cluster if LVM Storage is used. Ensure that the DataProtectionApplication CR does not exist on the seed cluster if OADP is used. Procedure Detach the managed cluster from the hub to delete any RHACM-specific resources from the seed cluster that must not be in the seed image: Manually detach the seed cluster by running the following command: USD oc delete managedcluster sno-worker-example Wait until the managed cluster is removed. After the cluster is removed, create the proper SeedGenerator CR. The Lifecycle Agent cleans up the RHACM artifacts. If you are using GitOps ZTP, detach your cluster by removing the seed cluster's SiteConfig CR from the kustomization.yaml . If you have a kustomization.yaml file that references multiple SiteConfig CRs, remove your seed cluster's SiteConfig CR from the kustomization.yaml : apiVersion: kustomize.config.k8s.io/v1beta1 kind: Kustomization generators: #- example-seed-sno1.yaml - example-target-sno2.yaml - example-target-sno3.yaml If you have a kustomization.yaml that references one SiteConfig CR, remove your seed cluster's SiteConfig CR from the kustomization.yaml and add the generators: {} line: apiVersion: kustomize.config.k8s.io/v1beta1 kind: Kustomization generators: {} Commit the kustomization.yaml changes in your Git repository and push the changes to your repository. The ArgoCD pipeline detects the changes and removes the managed cluster. Create the Secret object so that you can push the seed image to your registry. Create the authentication file by running the following commands: USD MY_USER=myuserid USD AUTHFILE=/tmp/my-auth.json USD podman login --authfile USD{AUTHFILE} -u USD{MY_USER} quay.io/USD{MY_USER} USD base64 -w 0 USD{AUTHFILE} ; echo Copy the output into the seedAuth field in the Secret YAML file named seedgen in the openshift-lifecycle-agent namespace: apiVersion: v1 kind: Secret metadata: name: seedgen 1 namespace: openshift-lifecycle-agent type: Opaque data: seedAuth: <encoded_AUTHFILE> 2 1 The Secret resource must have the name: seedgen and namespace: openshift-lifecycle-agent fields. 2 Specifies a base64-encoded authfile for write-access to the registry for pushing the generated seed images. Apply the Secret by running the following command: USD oc apply -f secretseedgenerator.yaml Create the SeedGenerator CR: apiVersion: lca.openshift.io/v1 kind: SeedGenerator metadata: name: seedimage 1 spec: seedImage: <seed_container_image> 2 1 The SeedGenerator CR must be named seedimage . 2 Specify the container image URL, for example, quay.io/example/seed-container-image:<tag> . It is recommended to use the <seed_cluster_name>:<ocp_version> format. Generate the seed image by running the following command: USD oc apply -f seedgenerator.yaml Important The cluster reboots and loses API capabilities while the Lifecycle Agent generates the seed image. Applying the SeedGenerator CR stops the kubelet and the CRI-O operations, then it starts the image generation. If you want to generate more seed images, you must provision a new seed cluster with the version that you want to generate a seed image from. Verification After the cluster recovers and it is available, you can check the status of the SeedGenerator CR by running the following command: USD oc get seedgenerator -o yaml Example output status: conditions: - lastTransitionTime: "2024-02-13T21:24:26Z" message: Seed Generation completed observedGeneration: 1 reason: Completed status: "False" type: SeedGenInProgress - lastTransitionTime: "2024-02-13T21:24:26Z" message: Seed Generation completed observedGeneration: 1 reason: Completed status: "True" type: SeedGenCompleted 1 observedGeneration: 1 1 The seed image generation is complete. Additional resources Configuring a shared container partition between ostree stateroots Configuring a shared container partition between ostree stateroots when using GitOps ZTP 15.2.4. Creating ConfigMap objects for the image-based upgrade with the Lifecycle Agent The Lifecycle Agent needs all your OADP resources, extra manifests, and custom catalog sources wrapped in a ConfigMap object to process them for the image-based upgrade. 15.2.4.1. Creating OADP ConfigMap objects for the image-based upgrade with Lifecycle Agent Create your OADP resources that are used to back up and restore your resources during the upgrade. Prerequisites You have generated a seed image from a compatible seed cluster. You have created OADP backup and restore resources. You have created a separate partition on the target cluster for the container images that is shared between stateroots. For more information, see "Configuring a shared container partition for the image-based upgrade". You have deployed a version of Lifecycle Agent that is compatible with the version used with the seed image. You have installed the OADP Operator, the DataProtectionApplication CR, and its secret on the target cluster. You have created an S3-compatible storage solution and a ready-to-use bucket with proper credentials configured. For more information, see "About installing OADP". Procedure Create the OADP Backup and Restore CRs for platform artifacts in the same namespace where the OADP Operator is installed, which is openshift-adp . If the target cluster is managed by RHACM, add the following YAML file for backing up and restoring RHACM artifacts: PlatformBackupRestore.yaml for RHACM apiVersion: velero.io/v1 kind: Backup metadata: name: acm-klusterlet annotations: lca.openshift.io/apply-label: "apps/v1/deployments/open-cluster-management-agent/klusterlet,v1/secrets/open-cluster-management-agent/bootstrap-hub-kubeconfig,rbac.authorization.k8s.io/v1/clusterroles/klusterlet,v1/serviceaccounts/open-cluster-management-agent/klusterlet,scheduling.k8s.io/v1/priorityclasses/klusterlet-critical,rbac.authorization.k8s.io/v1/clusterroles/open-cluster-management:klusterlet-admin-aggregate-clusterrole,rbac.authorization.k8s.io/v1/clusterrolebindings/klusterlet,operator.open-cluster-management.io/v1/klusterlets/klusterlet,apiextensions.k8s.io/v1/customresourcedefinitions/klusterlets.operator.open-cluster-management.io,v1/secrets/open-cluster-management-agent/open-cluster-management-image-pull-credentials" 1 labels: velero.io/storage-location: default namespace: openshift-adp spec: includedNamespaces: - open-cluster-management-agent includedClusterScopedResources: - klusterlets.operator.open-cluster-management.io - clusterroles.rbac.authorization.k8s.io - clusterrolebindings.rbac.authorization.k8s.io - priorityclasses.scheduling.k8s.io includedNamespaceScopedResources: - deployments - serviceaccounts - secrets excludedNamespaceScopedResources: [] --- apiVersion: velero.io/v1 kind: Restore metadata: name: acm-klusterlet namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "1" spec: backupName: acm-klusterlet 1 If your multiclusterHub CR does not have .spec.imagePullSecret defined and the secret does not exist on the open-cluster-management-agent namespace in your hub cluster, remove v1/secrets/open-cluster-management-agent/open-cluster-management-image-pull-credentials . If you created persistent volumes on your cluster through LVM Storage, add the following YAML file for LVM Storage artifacts: PlatformBackupRestoreLvms.yaml for LVM Storage apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: lvmcluster namespace: openshift-adp spec: includedNamespaces: - openshift-storage includedNamespaceScopedResources: - lvmclusters - lvmvolumegroups - lvmvolumegroupnodestatuses --- apiVersion: velero.io/v1 kind: Restore metadata: name: lvmcluster namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "2" 1 spec: backupName: lvmcluster 1 The lca.openshift.io/apply-wave value must be lower than the values specified in the application Restore CRs. If you need to restore applications after the upgrade, create the OADP Backup and Restore CRs for your application in the openshift-adp namespace. Create the OADP CRs for cluster-scoped application artifacts in the openshift-adp namespace. Example OADP CRs for cluster-scoped application artifacts for LSO and LVM Storage apiVersion: velero.io/v1 kind: Backup metadata: annotations: lca.openshift.io/apply-label: "apiextensions.k8s.io/v1/customresourcedefinitions/test.example.com,security.openshift.io/v1/securitycontextconstraints/test,rbac.authorization.k8s.io/v1/clusterroles/test-role,rbac.authorization.k8s.io/v1/clusterrolebindings/system:openshift:scc:test" 1 name: backup-app-cluster-resources labels: velero.io/storage-location: default namespace: openshift-adp spec: includedClusterScopedResources: - customresourcedefinitions - securitycontextconstraints - clusterrolebindings - clusterroles excludedClusterScopedResources: - Namespace --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app-cluster-resources namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "3" 2 spec: backupName: backup-app-cluster-resources 1 Replace the example resource name with your actual resources. 2 The lca.openshift.io/apply-wave value must be higher than the value in the platform Restore CRs and lower than the value in the application namespace-scoped Restore CR. Create the OADP CRs for your namespace-scoped application artifacts. Example OADP CRs namespace-scoped application artifacts when LSO is used apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 excludedClusterScopedResources: - persistentVolumes --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "4" spec: backupName: backup-app 1 Define custom resources for your application. Example OADP CRs namespace-scoped application artifacts when LVM Storage is used apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 includedClusterScopedResources: - persistentVolumes 2 - logicalvolumes.topolvm.io 3 - volumesnapshotcontents 4 --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "4" spec: backupName: backup-app restorePVs: true restoreStatus: includedResources: - logicalvolumes 5 1 Define custom resources for your application. 2 Required field. 3 Required field 4 Optional if you use LVM Storage volume snapshots. 5 Required field. Important The same version of the applications must function on both the current and the target release of OpenShift Container Platform. Create the ConfigMap object for your OADP CRs by running the following command: USD oc create configmap oadp-cm-example --from-file=example-oadp-resources.yaml=<path_to_oadp_crs> -n openshift-adp Patch the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade \ -p='{"spec": {"oadpContent": [{"name": "oadp-cm-example", "namespace": "openshift-adp"}]}}' \ --type=merge -n openshift-lifecycle-agent Additional resources Configuring a shared container partition between ostree stateroots About installing OADP 15.2.4.2. Creating ConfigMap objects of extra manifests for the image-based upgrade with Lifecycle Agent Create additional manifests that you want to apply to the target cluster. Note If you add more than one extra manifest, and the manifests must be applied in a specific order, you must prefix the filenames of the manifests with numbers that represent the required order. For example, 00-namespace.yaml , 01-sriov-extra-manifest.yaml , and so on. Procedure Create a YAML file that contains your extra manifests, such as SR-IOV. Example SR-IOV resources apiVersion: sriovnetwork.openshift.io/v1 kind: SriovNetworkNodePolicy metadata: name: "example-sriov-node-policy" namespace: openshift-sriov-network-operator spec: deviceType: vfio-pci isRdma: false nicSelector: pfNames: [ens1f0] nodeSelector: node-role.kubernetes.io/master: "" mtu: 1500 numVfs: 8 priority: 99 resourceName: example-sriov-node-policy --- apiVersion: sriovnetwork.openshift.io/v1 kind: SriovNetwork metadata: name: "example-sriov-network" namespace: openshift-sriov-network-operator spec: ipam: \|- { } linkState: auto networkNamespace: sriov-namespace resourceName: example-sriov-node-policy spoofChk: "on" trust: "off" Create the ConfigMap object by running the following command: USD oc create configmap example-extra-manifests-cm --from-file=example-extra-manifests.yaml=<path_to_extramanifest> -n openshift-lifecycle-agent Patch the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade \ -p='{"spec": {"extraManifests": [{"name": "example-extra-manifests-cm", "namespace": "openshift-lifecycle-agent"}]}}' \ --type=merge -n openshift-lifecycle-agent 15.2.4.3. Creating ConfigMap objects of custom catalog sources for the image-based upgrade with Lifecycle Agent You can keep your custom catalog sources after the upgrade by generating a ConfigMap object for your catalog sources and adding them to the spec.extraManifest field in the ImageBasedUpgrade CR. For more information about catalog sources, see "Catalog source". Procedure Create a YAML file that contains the CatalogSource CR: apiVersion: operators.coreos.com/v1 kind: CatalogSource metadata: name: example-catalogsources namespace: openshift-marketplace spec: sourceType: grpc displayName: disconnected-redhat-operators image: quay.io/example-org/example-catalog:v1 Create the ConfigMap object by running the following command: USD oc create configmap example-catalogsources-cm --from-file=example-catalogsources.yaml=<path_to_catalogsource_cr> -n openshift-lifecycle-agent Patch the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade \ -p='{"spec": {"extraManifests": [{"name": "example-catalogsources-cm", "namespace": "openshift-lifecycle-agent"}]}}' \ --type=merge -n openshift-lifecycle-agent Additional resources Catalog source Performing an image-based upgrade for single-node OpenShift with Lifecycle Agent 15.2.5. Creating ConfigMap objects for the image-based upgrade with the Lifecycle Agent using GitOps ZTP Create your OADP resources, extra manifests, and custom catalog sources wrapped in a ConfigMap object to prepare for the image-based upgrade. 15.2.5.1. Creating OADP resources for the image-based upgrade with GitOps ZTP Prepare your OADP resources to restore your application after an upgrade. Prerequisites You have provisioned one or more managed clusters with GitOps ZTP. You have logged in as a user with cluster-admin privileges. You have generated a seed image from a compatible seed cluster. You have created a separate partition on the target cluster for the container images that is shared between stateroots. For more information, see "Configuring a shared container partition between ostree stateroots when using GitOps ZTP". You have deployed a version of Lifecycle Agent that is compatible with the version used with the seed image. You have installed the OADP Operator, the DataProtectionApplication CR, and its secret on the target cluster. You have created an S3-compatible storage solution and a ready-to-use bucket with proper credentials configured. For more information, see "Installing and configuring the OADP Operator with GitOps ZTP". The openshift-adp namespace for the OADP ConfigMap object must exist on all managed clusters and the hub for the OADP ConfigMap to be generated and copied to the clusters. Procedure Ensure that your Git repository that you use with the ArgoCD policies application contains the following directory structure: ├── source-crs/ │ ├── ibu/ │ │ ├── ImageBasedUpgrade.yaml │ │ ├── PlatformBackupRestore.yaml │ │ ├── PlatformBackupRestoreLvms.yaml │ │ ├── PlatformBackupRestoreWithIBGU.yaml ├── ... ├── kustomization.yaml The source-crs/ibu/PlatformBackupRestoreWithIBGU.yaml file is provided in the ZTP container image. PlatformBackupRestoreWithIBGU.yaml apiVersion: velero.io/v1 kind: Backup metadata: name: acm-klusterlet annotations: lca.openshift.io/apply-label: "apps/v1/deployments/open-cluster-management-agent/klusterlet,v1/secrets/open-cluster-management-agent/bootstrap-hub-kubeconfig,rbac.authorization.k8s.io/v1/clusterroles/klusterlet,v1/serviceaccounts/open-cluster-management-agent/klusterlet,scheduling.k8s.io/v1/priorityclasses/klusterlet-critical,rbac.authorization.k8s.io/v1/clusterroles/open-cluster-management:klusterlet-work:ibu-role,rbac.authorization.k8s.io/v1/clusterroles/open-cluster-management:klusterlet-admin-aggregate-clusterrole,rbac.authorization.k8s.io/v1/clusterrolebindings/klusterlet,operator.open-cluster-management.io/v1/klusterlets/klusterlet,apiextensions.k8s.io/v1/customresourcedefinitions/klusterlets.operator.open-cluster-management.io,v1/secrets/open-cluster-management-agent/open-cluster-management-image-pull-credentials" 1 labels: velero.io/storage-location: default namespace: openshift-adp spec: includedNamespaces: - open-cluster-management-agent includedClusterScopedResources: - klusterlets.operator.open-cluster-management.io - clusterroles.rbac.authorization.k8s.io - clusterrolebindings.rbac.authorization.k8s.io - priorityclasses.scheduling.k8s.io includedNamespaceScopedResources: - deployments - serviceaccounts - secrets excludedNamespaceScopedResources: [] --- apiVersion: velero.io/v1 kind: Restore metadata: name: acm-klusterlet namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "1" spec: backupName: acm-klusterlet 1 If your multiclusterHub CR does not have .spec.imagePullSecret defined and the secret does not exist on the open-cluster-management-agent namespace in your hub cluster, remove v1/secrets/open-cluster-management-agent/open-cluster-management-image-pull-credentials . Note If you perform the image-based upgrade directly on managed clusters, use the PlatformBackupRestore.yaml file. If you use LVM Storage to create persistent volumes, you can use the source-crs/ibu/PlatformBackupRestoreLvms.yaml provided in the ZTP container image to back up your LVM Storage resources. PlatformBackupRestoreLvms.yaml apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: lvmcluster namespace: openshift-adp spec: includedNamespaces: - openshift-storage includedNamespaceScopedResources: - lvmclusters - lvmvolumegroups - lvmvolumegroupnodestatuses --- apiVersion: velero.io/v1 kind: Restore metadata: name: lvmcluster namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "2" 1 spec: backupName: lvmcluster 1 The lca.openshift.io/apply-wave value must be lower than the values specified in the application Restore CRs. If you need to restore applications after the upgrade, create the OADP Backup and Restore CRs for your application in the openshift-adp namespace: Create the OADP CRs for cluster-scoped application artifacts in the openshift-adp namespace: Example OADP CRs for cluster-scoped application artifacts for LSO and LVM Storage apiVersion: velero.io/v1 kind: Backup metadata: annotations: lca.openshift.io/apply-label: "apiextensions.k8s.io/v1/customresourcedefinitions/test.example.com,security.openshift.io/v1/securitycontextconstraints/test,rbac.authorization.k8s.io/v1/clusterroles/test-role,rbac.authorization.k8s.io/v1/clusterrolebindings/system:openshift:scc:test" 1 name: backup-app-cluster-resources labels: velero.io/storage-location: default namespace: openshift-adp spec: includedClusterScopedResources: - customresourcedefinitions - securitycontextconstraints - clusterrolebindings - clusterroles excludedClusterScopedResources: - Namespace --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app-cluster-resources namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "3" 2 spec: backupName: backup-app-cluster-resources 1 Replace the example resource name with your actual resources. 2 The lca.openshift.io/apply-wave value must be higher than the value in the platform Restore CRs and lower than the value in the application namespace-scoped Restore CR. Create the OADP CRs for your namespace-scoped application artifacts in the source-crs/custom-crs directory: Example OADP CRs namespace-scoped application artifacts when LSO is used apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 excludedClusterScopedResources: - persistentVolumes --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "4" spec: backupName: backup-app 1 Define custom resources for your application. Example OADP CRs namespace-scoped application artifacts when LVM Storage is used apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 includedClusterScopedResources: - persistentVolumes 2 - logicalvolumes.topolvm.io 3 - volumesnapshotcontents 4 --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "4" spec: backupName: backup-app restorePVs: true restoreStatus: includedResources: - logicalvolumes 5 1 Define custom resources for your application. 2 Required field. 3 Required field 4 Optional if you use LVM Storage volume snapshots. 5 Required field. Important The same version of the applications must function on both the current and the target release of OpenShift Container Platform. Create a kustomization.yaml with the following content: apiVersion: kustomize.config.k8s.io/v1beta1 kind: Kustomization configMapGenerator: 1 - files: - source-crs/ibu/PlatformBackupRestoreWithIBGU.yaml #- source-crs/custom-crs/ApplicationClusterScopedBackupRestore.yaml #- source-crs/custom-crs/ApplicationApplicationBackupRestoreLso.yaml name: oadp-cm namespace: openshift-adp 2 generatorOptions: disableNameSuffixHash: true 1 Creates the oadp-cm ConfigMap object on the hub cluster with Backup and Restore CRs. 2 The namespace must exist on all managed clusters and the hub for the OADP ConfigMap to be generated and copied to the clusters. Push the changes to your Git repository. Additional resources Configuring a shared container partition between ostree stateroots when using GitOps ZTP Installing and configuring the OADP Operator with GitOps ZTP 15.2.5.2. Labeling extra manifests for the image-based upgrade with GitOps ZTP Label your extra manifests so that the Lifecycle Agent can extract resources that are labeled with the lca.openshift.io/target-ocp-version: <target_version> label. Prerequisites You have provisioned one or more managed clusters with GitOps ZTP. You have logged in as a user with cluster-admin privileges. You have generated a seed image from a compatible seed cluster. You have created a separate partition on the target cluster for the container images that is shared between stateroots. For more information, see "Configuring a shared container directory between ostree stateroots when using GitOps ZTP". You have deployed a version of Lifecycle Agent that is compatible with the version used with the seed image. Procedure Label your required extra manifests with the lca.openshift.io/target-ocp-version: <target_version> label in your existing site PolicyGenTemplate CR: apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: example-sno spec: bindingRules: sites: "example-sno" du-profile: "4.15" mcp: "master" sourceFiles: - fileName: SriovNetwork.yaml policyName: "config-policy" metadata: name: "sriov-nw-du-fh" labels: lca.openshift.io/target-ocp-version: "4.15" 1 spec: resourceName: du_fh vlan: 140 - fileName: SriovNetworkNodePolicy.yaml policyName: "config-policy" metadata: name: "sriov-nnp-du-fh" labels: lca.openshift.io/target-ocp-version: "4.15" spec: deviceType: netdevice isRdma: false nicSelector: pfNames: ["ens5f0"] numVfs: 8 priority: 10 resourceName: du_fh - fileName: SriovNetwork.yaml policyName: "config-policy" metadata: name: "sriov-nw-du-mh" labels: lca.openshift.io/target-ocp-version: "4.15" spec: resourceName: du_mh vlan: 150 - fileName: SriovNetworkNodePolicy.yaml policyName: "config-policy" metadata: name: "sriov-nnp-du-mh" labels: lca.openshift.io/target-ocp-version: "4.15" spec: deviceType: vfio-pci isRdma: false nicSelector: pfNames: ["ens7f0"] numVfs: 8 priority: 10 resourceName: du_mh - fileName: DefaultCatsrc.yaml 2 policyName: "config-policy" metadata: name: default-cat-source namespace: openshift-marketplace labels: lca.openshift.io/target-ocp-version: "4.15" spec: displayName: default-cat-source image: quay.io/example-org/example-catalog:v1 1 Ensure that the lca.openshift.io/target-ocp-version label matches either the y-stream or the z-stream of the target OpenShift Container Platform version that is specified in the spec.seedImageRef.version field of the ImageBasedUpgrade CR. The Lifecycle Agent only applies the CRs that match the specified version. 2 If you do not want to use custom catalog sources, remove this entry. Push the changes to your Git repository. Additional resources Configuring a shared container partition between ostree stateroots when using GitOps ZTP Performing an image-based upgrade for single-node OpenShift clusters using GitOps ZTP 15.2.6. Configuring the automatic image cleanup of the container storage disk Configure when the Lifecycle Agent cleans up unpinned images in the Prep stage by setting a minimum threshold for available storage space through annotations. The default container storage disk usage threshold is 50%. The Lifecycle Agent does not delete images that are pinned in CRI-O or are currently used. The Operator selects the images for deletion by starting with dangling images and then sorting the images from oldest to newest that is determined by the image Created timestamp. 15.2.6.1. Configuring the automatic image cleanup of the container storage disk Configure the minimum threshold for available storage space through annotations. Prerequisites You have created an ImageBasedUpgrade CR. Procedure Increase the threshold to 65% by running the following command: USD oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/disk-usage-threshold-percent='65' (Optional) Remove the threshold override by running the following command: USD oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/disk-usage-threshold-percent- 15.2.6.2. Disable the automatic image cleanup of the container storage disk Disable the automatic image cleanup threshold. Procedure Disable the automatic image cleanup by running the following command: USD oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/on-prep='Disabled' (Optional) Enable automatic image cleanup again by running the following command: USD oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/on-prep- 15.3. Performing an image-based upgrade for single-node OpenShift clusters with the Lifecycle Agent You can use the Lifecycle Agent to do a manual image-based upgrade of a single-node OpenShift cluster. When you deploy the Lifecycle Agent on a cluster, an ImageBasedUpgrade CR is automatically created. You update this CR to specify the image repository of the seed image and to move through the different stages. 15.3.1. Moving to the Prep stage of the image-based upgrade with Lifecycle Agent When you deploy the Lifecycle Agent on a cluster, an ImageBasedUpgrade custom resource (CR) is automatically created. After you created all the resources that you need during the upgrade, you can move on to the Prep stage. For more information, see the "Creating ConfigMap objects for the image-based upgrade with Lifecycle Agent" section. Note In a disconnected environment, if the seed cluster's release image registry is different from the target cluster's release image registry, you must create an ImageDigestMirrorSet (IDMS) resource to configure alternative mirrored repository locations. For more information, see "Configuring image registry repository mirroring". You can retrieve the release registry used in the seed image by running the following command: USD skopeo inspect docker://<imagename> \| jq -r '.Labels."com.openshift.lifecycle-agent.seed_cluster_info" \| fromjson \| .release_registry' Prerequisites You have created resources to back up and restore your clusters. Procedure Check that you have patched your ImageBasedUpgrade CR: apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: name: upgrade spec: stage: Idle seedImageRef: version: 4.15.2 1 image: <seed_container_image> 2 pullSecretRef: <seed_pull_secret> 3 autoRollbackOnFailure: {} # initMonitorTimeoutSeconds: 1800 4 extraManifests: 5 - name: example-extra-manifests-cm namespace: openshift-lifecycle-agent - name: example-catalogsources-cm namespace: openshift-lifecycle-agent oadpContent: 6 - name: oadp-cm-example namespace: openshift-adp 1 Target platform version. The value must match the version of the seed image. 2 Repository where the target cluster can pull the seed image from. 3 Reference to a secret with credentials to pull container images if the images are in a private registry. 4 Optional: Time frame in seconds to roll back if the upgrade does not complete within that time frame after the first reboot. If not defined or set to 0 , the default value of 1800 seconds (30 minutes) is used. 5 Optional: List of ConfigMap resources that contain your custom catalog sources to retain after the upgrade and your extra manifests to apply to the target cluster that are not part of the seed image. 6 List of ConfigMap resources that contain the OADP Backup and Restore CRs. To start the Prep stage, change the value of the stage field to Prep in the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{"spec": {"stage": "Prep"}}' --type=merge -n openshift-lifecycle-agent If you provide ConfigMap objects for OADP resources and extra manifests, Lifecycle Agent validates the specified ConfigMap objects during the Prep stage. You might encounter the following issues: Validation warnings or errors if the Lifecycle Agent detects any issues with the extraManifests parameters. Validation errors if the Lifecycle Agent detects any issues with the oadpContent parameters. Validation warnings do not block the Upgrade stage but you must decide if it is safe to proceed with the upgrade. These warnings, for example missing CRDs, namespaces, or dry run failures, update the status.conditions for the Prep stage and annotation fields in the ImageBasedUpgrade CR with details about the warning. Example validation warning # ... metadata: annotations: extra-manifest.lca.openshift.io/validation-warning: '...' # ... However, validation errors, such as adding MachineConfig or Operator manifests to extra manifests, cause the Prep stage to fail and block the Upgrade stage. When the validations pass, the cluster creates a new ostree stateroot, which involves pulling and unpacking the seed image, and running host-level commands. Finally, all the required images are precached on the target cluster. Verification Check the status of the ImageBasedUpgrade CR by running the following command: USD oc get ibu -o yaml Example output conditions: - lastTransitionTime: "2024-01-01T09:00:00Z" message: In progress observedGeneration: 13 reason: InProgress status: "False" type: Idle - lastTransitionTime: "2024-01-01T09:00:00Z" message: Prep completed observedGeneration: 13 reason: Completed status: "False" type: PrepInProgress - lastTransitionTime: "2024-01-01T09:00:00Z" message: Prep stage completed successfully observedGeneration: 13 reason: Completed status: "True" type: PrepCompleted observedGeneration: 13 validNextStages: - Idle - Upgrade Additional resources Creating ConfigMap objects for the image-based upgrade with Lifecycle Agent Configuring image registry repository mirroring 15.3.2. Moving to the Upgrade stage of the image-based upgrade with Lifecycle Agent After you generate the seed image and complete the Prep stage, you can upgrade the target cluster. During the upgrade process, the OADP Operator creates a backup of the artifacts specified in the OADP custom resources (CRs), then the Lifecycle Agent upgrades the cluster. If the upgrade fails or stops, an automatic rollback is initiated. If you have an issue after the upgrade, you can initiate a manual rollback. For more information about manual rollback, see "Moving to the Rollback stage of the image-based upgrade with Lifecycle Agent". Prerequisites You have completed the Prep stage. Procedure To move to the Upgrade stage, change the value of the stage field to Upgrade in the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{"spec": {"stage": "Upgrade"}}' --type=merge Check the status of the ImageBasedUpgrade CR by running the following command: USD oc get ibu -o yaml Example output status: conditions: - lastTransitionTime: "2024-01-01T09:00:00Z" message: In progress observedGeneration: 5 reason: InProgress status: "False" type: Idle - lastTransitionTime: "2024-01-01T09:00:00Z" message: Prep completed observedGeneration: 5 reason: Completed status: "False" type: PrepInProgress - lastTransitionTime: "2024-01-01T09:00:00Z" message: Prep completed successfully observedGeneration: 5 reason: Completed status: "True" type: PrepCompleted - lastTransitionTime: "2024-01-01T09:00:00Z" message: \|- Waiting for system to stabilize: one or more health checks failed - one or more ClusterOperators not yet ready: authentication - one or more MachineConfigPools not yet ready: master - one or more ClusterServiceVersions not yet ready: sriov-fec.v2.8.0 observedGeneration: 1 reason: InProgress status: "True" type: UpgradeInProgress observedGeneration: 1 rollbackAvailabilityExpiration: "2024-05-19T14:01:52Z" validNextStages: - Rollback The OADP Operator creates a backup of the data specified in the OADP Backup and Restore CRs and the target cluster reboots. Monitor the status of the CR by running the following command: USD oc get ibu -o yaml If you are satisfied with the upgrade, finalize the changes by patching the value of the stage field to Idle in the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{"spec": {"stage": "Idle"}}' --type=merge Important You cannot roll back the changes once you move to the Idle stage after an upgrade. The Lifecycle Agent deletes all resources created during the upgrade process. You can remove the OADP Operator and its configuration files after a successful upgrade. For more information, see "Deleting Operators from a cluster". Verification Check the status of the ImageBasedUpgrade CR by running the following command: USD oc get ibu -o yaml Example output status: conditions: - lastTransitionTime: "2024-01-01T09:00:00Z" message: In progress observedGeneration: 5 reason: InProgress status: "False" type: Idle - lastTransitionTime: "2024-01-01T09:00:00Z" message: Prep completed observedGeneration: 5 reason: Completed status: "False" type: PrepInProgress - lastTransitionTime: "2024-01-01T09:00:00Z" message: Prep completed successfully observedGeneration: 5 reason: Completed status: "True" type: PrepCompleted - lastTransitionTime: "2024-01-01T09:00:00Z" message: Upgrade completed observedGeneration: 1 reason: Completed status: "False" type: UpgradeInProgress - lastTransitionTime: "2024-01-01T09:00:00Z" message: Upgrade completed observedGeneration: 1 reason: Completed status: "True" type: UpgradeCompleted observedGeneration: 1 rollbackAvailabilityExpiration: "2024-01-01T09:00:00Z" validNextStages: - Idle - Rollback Check the status of the cluster restoration by running the following command: USD oc get restores -n openshift-adp -o custom-columns=NAME:.metadata.name,Status:.status.phase,Reason:.status.failureReason Example output NAME Status Reason acm-klusterlet Completed <none> 1 apache-app Completed <none> localvolume Completed <none> 1 The acm-klusterlet is specific to RHACM environments only. Additional resources Moving to the Rollback stage of the image-based upgrade with Lifecycle Agent Deleting Operators from a cluster 15.3.3. Moving to the Rollback stage of the image-based upgrade with Lifecycle Agent An automatic rollback is initiated if the upgrade does not complete within the time frame specified in the initMonitorTimeoutSeconds field after rebooting. Example ImageBasedUpgrade CR apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: name: upgrade spec: stage: Idle seedImageRef: version: 4.15.2 image: <seed_container_image> autoRollbackOnFailure: {} # initMonitorTimeoutSeconds: 1800 1 # ... 1 Optional: The time frame in seconds to roll back if the upgrade does not complete within that time frame after the first reboot. If not defined or set to 0 , the default value of 1800 seconds (30 minutes) is used. You can manually roll back the changes if you encounter unresolvable issues after an upgrade. Prerequisites You have logged into the hub cluster as a user with cluster-admin privileges. You ensured that the control plane certificates on the original stateroot are valid. If the certificates expired, see "Recovering from expired control plane certificates". Procedure To move to the rollback stage, patch the value of the stage field to Rollback in the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{"spec": {"stage": "Rollback"}}' --type=merge The Lifecycle Agent reboots the cluster with the previously installed version of OpenShift Container Platform and restores the applications. If you are satisfied with the changes, finalize the rollback by patching the value of the stage field to Idle in the ImageBasedUpgrade CR by running the following command: USD oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{"spec": {"stage": "Idle"}}' --type=merge -n openshift-lifecycle-agent Warning If you move to the Idle stage after a rollback, the Lifecycle Agent cleans up resources that can be used to troubleshoot a failed upgrade. Additional resources Recovering from expired control plane certificates 15.3.4. Troubleshooting image-based upgrades with Lifecycle Agent Perform troubleshooting steps on the managed clusters that are affected by an issue. Important If you are using the ImageBasedGroupUpgrade CR to upgrade your clusters, ensure that the lcm.openshift.io/ibgu-<stage>-completed or lcm.openshift.io/ibgu-<stage>-failed cluster labels are updated properly after performing troubleshooting or recovery steps on the managed clusters. This ensures that the TALM continues to manage the image-based upgrade for the cluster. 15.3.4.1. Collecting logs You can use the oc adm must-gather CLI to collect information for debugging and troubleshooting. Procedure Collect data about the Operators by running the following command: USD oc adm must-gather \ --dest-dir=must-gather/tmp \ --image=USD(oc -n openshift-lifecycle-agent get deployment.apps/lifecycle-agent-controller-manager -o jsonpath='{.spec.template.spec.containers[?(@.name == "manager")].image}') \ --image=quay.io/konveyor/oadp-must-gather:latest \// 1 --image=quay.io/openshift/origin-must-gather:latest 2 1 Optional: Add this option if you need to gather more information from the OADP Operator. 2 Optional: Add this option if you need to gather more information from the SR-IOV Operator. 15.3.4.2. AbortFailed or FinalizeFailed error Issue During the finalize stage or when you stop the process at the Prep stage, Lifecycle Agent cleans up the following resources: Stateroot that is no longer required Precaching resources OADP CRs ImageBasedUpgrade CR If the Lifecycle Agent fails to perform the above steps, it transitions to the AbortFailed or FinalizeFailed states. The condition message and log show which steps failed. Example error message message: failed to delete all the backup CRs. Perform cleanup manually then add 'lca.openshift.io/manual-cleanup-done' annotation to ibu CR to transition back to Idle observedGeneration: 5 reason: AbortFailed status: "False" type: Idle Resolution Inspect the logs to determine why the failure occurred. To prompt Lifecycle Agent to retry the cleanup, add the lca.openshift.io/manual-cleanup-done annotation to the ImageBasedUpgrade CR. After observing this annotation, Lifecycle Agent retries the cleanup and, if it is successful, the ImageBasedUpgrade stage transitions to Idle . If the cleanup fails again, you can manually clean up the resources. 15.3.4.2.1. Cleaning up stateroot manually Issue Stopping at the Prep stage, Lifecycle Agent cleans up the new stateroot. When finalizing after a successful upgrade or a rollback, Lifecycle Agent cleans up the old stateroot. If this step fails, it is recommended that you inspect the logs to determine why the failure occurred. Resolution Check if there are any existing deployments in the stateroot by running the following command: USD ostree admin status If there are any, clean up the existing deployment by running the following command: USD ostree admin undeploy <index_of_deployment> After cleaning up all the deployments of the stateroot, wipe the stateroot directory by running the following commands: Warning Ensure that the booted deployment is not in this stateroot. USD stateroot="<stateroot_to_delete>" USD unshare -m /bin/sh -c "mount -o remount,rw /sysroot && rm -rf /sysroot/ostree/deploy/USD{stateroot}" 15.3.4.2.2. Cleaning up OADP resources manually Issue Automatic cleanup of OADP resources can fail due to connection issues between Lifecycle Agent and the S3 backend. By restoring the connection and adding the lca.openshift.io/manual-cleanup-done annotation, the Lifecycle Agent can successfully cleanup backup resources. Resolution Check the backend connectivity by running the following command: USD oc get backupstoragelocations.velero.io -n openshift-adp Example output NAME PHASE LAST VALIDATED AGE DEFAULT dataprotectionapplication-1 Available 33s 8d true Remove all backup resources and then add the lca.openshift.io/manual-cleanup-done annotation to the ImageBasedUpgrade CR. 15.3.4.3. LVM Storage volume contents not restored When LVM Storage is used to provide dynamic persistent volume storage, LVM Storage might not restore the persistent volume contents if it is configured incorrectly. 15.3.4.3.1. Missing LVM Storage-related fields in Backup CR Issue Your Backup CRs might be missing fields that are needed to restore your persistent volumes. You can check for events in your application pod to determine if you have this issue by running the following: USD oc describe pod <your_app_name> Example output showing missing LVM Storage-related fields in Backup CR Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 58s (x2 over 66s) default-scheduler 0/1 nodes are available: pod has unbound immediate PersistentVolumeClaims. preemption: 0/1 nodes are available: 1 Preemption is not helpful for scheduling.. Normal Scheduled 56s default-scheduler Successfully assigned default/db-1234 to sno1.example.lab Warning FailedMount 24s (x7 over 55s) kubelet MountVolume.SetUp failed for volume "pvc-1234" : rpc error: code = Unknown desc = VolumeID is not found Resolution You must include logicalvolumes.topolvm.io in the application Backup CR. Without this resource, the application restores its persistent volume claims and persistent volume manifests correctly, however, the logicalvolume associated with this persistent volume is not restored properly after pivot. Example Backup CR apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: small-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets includedClusterScopedResources: 1 - persistentVolumes - volumesnapshotcontents - logicalvolumes.topolvm.io 1 To restore the persistent volumes for your application, you must configure this section as shown. 15.3.4.3.2. Missing LVM Storage-related fields in Restore CR Issue The expected resources for the applications are restored but the persistent volume contents are not preserved after upgrading. List the persistent volumes for you applications by running the following command before pivot: USD oc get pv,pvc,logicalvolumes.topolvm.io -A Example output before pivot NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Retain Bound default/pvc-db lvms-vg1 4h45m NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 4h45m NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 4h45m List the persistent volumes for you applications by running the following command after pivot: USD oc get pv,pvc,logicalvolumes.topolvm.io -A Example output after pivot NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Delete Bound default/pvc-db lvms-vg1 19s NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 19s NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 18s Resolution The reason for this issue is that the logicalvolume status is not preserved in the Restore CR. This status is important because it is required for Velero to reference the volumes that must be preserved after pivoting. You must include the following fields in the application Restore CR: Example Restore CR apiVersion: velero.io/v1 kind: Restore metadata: name: sample-vote-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "3" spec: backupName: sample-vote-app restorePVs: true 1 restoreStatus: 2 includedResources: - logicalvolumes 1 To preserve the persistent volumes for your application, you must set restorePVs to true . 2 To preserve the persistent volumes for your application, you must configure this section as shown. 15.3.4.4. Debugging failed Backup and Restore CRs Issue The backup or restoration of artifacts failed. Resolution You can debug Backup and Restore CRs and retrieve logs with the Velero CLI tool. The Velero CLI tool provides more detailed information than the OpenShift CLI tool. Describe the Backup CR that contains errors by running the following command: USD oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe backup -n openshift-adp backup-acm-klusterlet --details Describe the Restore CR that contains errors by running the following command: USD oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe restore -n openshift-adp restore-acm-klusterlet --details Download the backed up resources to a local directory by running the following command: USD oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero backup download -n openshift-adp backup-acm-klusterlet -o ~/backup-acm-klusterlet.tar.gz 15.4. Performing an image-based upgrade for single-node OpenShift clusters using GitOps ZTP You can use a single resource on the hub cluster, the ImageBasedGroupUpgrade custom resource (CR), to manage an imaged-based upgrade on a selected group of managed clusters through all stages. Topology Aware Lifecycle Manager (TALM) reconciles the ImageBasedGroupUpgrade CR and creates the underlying resources to complete the defined stage transitions, either in a manually controlled or a fully automated upgrade flow. For more information about the image-based upgrade, see "Understanding the image-based upgrade for single-node OpenShift clusters". Additional resources Understanding the image-based upgrade for single-node OpenShift clusters 15.4.1. Managing the image-based upgrade at scale using the ImageBasedGroupUpgrade CR on the hub The ImageBasedGroupUpgrade CR combines the ImageBasedUpgrade and ClusterGroupUpgrade APIs. For example, you can define the cluster selection and rollout strategy with the ImageBasedGroupUpgrade API in the same way as the ClusterGroupUpgrade API. The stage transitions are different from the ImageBasedUpgrade API. The ImageBasedGroupUpgrade API allows you to combine several stage transitions, also called actions, into one step that share one rollout strategy. Example ImageBasedGroupUpgrade.yaml apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: 1 - matchExpressions: - key: name operator: In values: - spoke1 - spoke4 - spoke6 ibuSpec: seedImageRef: 2 image: quay.io/seed/image:4.17.0-rc.1 version: 4.17.0-rc.1 pullSecretRef: name: "<seed_pull_secret>" extraManifests: 3 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 4 - name: oadp-cm namespace: openshift-adp plan: 5 - actions: ["Prep", "Upgrade", "FinalizeUpgrade"] rolloutStrategy: maxConcurrency: 200 6 timeout: 2400 7 1 Clusters to upgrade. 2 Target platform version, the seed image to be used, and the secret required to access the image. Note If you add the seed image pull secret in the hub cluster, in the same namespace as the ImageBasedGroupUpgrade resource, the secret is added to the manifest list for the Prep stage. The secret is recreated in each spoke cluster in the openshift-lifecycle-agent namespace. 3 Optional: Applies additional manifests, which are not in the seed image, to the target cluster. Also applies ConfigMap objects for custom catalog sources. 4 ConfigMap resources that contain the OADP Backup and Restore CRs. 5 Upgrade plan details. 6 Number of clusters to update in a batch. 7 Timeout limit to complete the action in minutes. 15.4.1.1. Supported action combinations Actions are the list of stage transitions that TALM completes in the steps of an upgrade plan for the selected group of clusters. Each action entry in the ImageBasedGroupUpgrade CR is a separate step and a step contains one or several actions that share the same rollout strategy. You can achieve more control over the rollout strategy for each action by separating actions into steps. These actions can be combined differently in your upgrade plan and you can add subsequent steps later. Wait until the steps either complete or fail before adding a step to your plan. The first action of an added step for clusters that failed a steps must be either Abort or Rollback . Important You cannot remove actions or steps from an ongoing plan. The following table shows example plans for different levels of control over the rollout strategy: Table 15.5. Example upgrade plans Example plan Description plan: - actions: ["Prep", "Upgrade", "FinalizeUpgrade"] rolloutStrategy: maxConcurrency: 200 timeout: 60 All actions share the same strategy plan: - actions: ["Prep", "Upgrade"] rolloutStrategy: maxConcurrency: 200 timeout: 60 - actions: ["FinalizeUpgrade"] rolloutStrategy: maxConcurrency: 500 timeout: 10 Some actions share the same strategy plan: - actions: ["Prep"] rolloutStrategy: maxConcurrency: 200 timeout: 60 - actions: ["Upgrade"] rolloutStrategy: maxConcurrency: 200 timeout: 20 - actions: ["FinalizeUpgrade"] rolloutStrategy: maxConcurrency: 500 timeout: 10 All actions have different strategies Important Clusters that fail one of the actions will skip the remaining actions in the same step. The ImageBasedGroupUpgrade API accepts the following actions: Prep Start preparing the upgrade resources by moving to the Prep stage. Upgrade Start the upgrade by moving to the Upgrade stage. FinalizeUpgrade Finalize the upgrade on selected clusters that completed the Upgrade action by moving to the Idle stage. Rollback Start a rollback only on successfully upgraded clusters by moving to the Rollback stage. FinalizeRollback Finalize the rollback by moving to the Idle stage. AbortOnFailure Cancel the upgrade on selected clusters that failed the Prep or Upgrade actions by moving to the Idle stage. Abort Cancel an ongoing upgrade only on clusters that are not yet upgraded by moving to the Idle stage. The following action combinations are supported. A pair of brackets signifies one step in the plan section: ["Prep"] , ["Abort"] ["Prep", "Upgrade", "FinalizeUpgrade"] ["Prep"] , ["AbortOnFailure"] , ["Upgrade"] , ["AbortOnFailure"] , ["FinalizeUpgrade"] ["Rollback", "FinalizeRollback"] Use one of the following combinations when you need to resume or cancel an ongoing upgrade from a completely new ImageBasedGroupUpgrade CR: ["Upgrade","FinalizeUpgrade"] ["FinalizeUpgrade"] ["FinalizeRollback"] ["Abort"] ["AbortOnFailure"] 15.4.1.2. Labeling for cluster selection Use the spec.clusterLabelSelectors field for initial cluster selection. In addition, TALM labels the managed clusters according to the results of their last stage transition. When a stage completes or fails, TALM marks the relevant clusters with the following labels: lcm.openshift.io/ibgu-<stage>-completed lcm.openshift.io/ibgu-<stage>-failed Use these cluster labels to cancel or roll back an upgrade on a group of clusters after troubleshooting issues that you might encounter. Important If you are using the ImageBasedGroupUpgrade CR to upgrade your clusters, ensure that the lcm.openshift.io/ibgu-<stage>-completed or lcm.openshift.io/ibgu-<stage>-failed cluster labels are updated properly after performing troubleshooting or recovery steps on the managed clusters. This ensures that the TALM continues to manage the image-based upgrade for the cluster. For example, if you want to cancel the upgrade for all managed clusters except for clusters that successfully completed the upgrade, you can add an Abort action to your plan. The Abort action moves back the ImageBasedUpgrade CR to the Idle stage, which cancels the upgrade on clusters that are not yet upgraded. Adding a separate Abort action ensures that the TALM does not perform the Abort action on clusters that have the lcm.openshift.io/ibgu-upgrade-completed label. The cluster labels are removed after successfully canceling or finalizing the upgrade. 15.4.1.3. Status monitoring The ImageBasedGroupUpgrade CR ensures a better monitoring experience with a comprehensive status reporting for all clusters that is aggregated in one place. You can monitor the following actions: status.clusters.completedActions Shows all completed actions defined in the plan section. status.clusters.currentAction Shows all actions that are currently in progress. status.clusters.failedActions Shows all failed actions along with a detailed error message. 15.4.2. Performing an image-based upgrade on managed clusters at scale in several steps For use cases when you need better control of when the upgrade interrupts your service, you can upgrade a set of your managed clusters by using the ImageBasedGroupUpgrade CR with adding actions after the step is complete. After evaluating the results of the steps, you can move to the upgrade stage or troubleshoot any failed steps throughout the procedure. Important Only certain action combinations are supported and listed in Supported action combinations . Prerequisites You have logged in to the hub cluster as a user with cluster-admin privileges. You have created policies and ConfigMap objects for resources used in the image-based upgrade. You have installed the Lifecycle Agent and OADP Operators on all managed clusters through the hub cluster. Procedure Create a YAML file on the hub cluster that contains the ImageBasedGroupUpgrade CR: apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: 1 - matchExpressions: - key: name operator: In values: - spoke1 - spoke4 - spoke6 ibuSpec: seedImageRef: 2 image: quay.io/seed/image:4.16.0-rc.1 version: 4.16.0-rc.1 pullSecretRef: name: "<seed_pull_secret>" extraManifests: 3 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 4 - name: oadp-cm namespace: openshift-adp plan: 5 - actions: ["Prep"] rolloutStrategy: maxConcurrency: 2 timeout: 2400 1 Clusters to upgrade. 2 Target platform version, the seed image to be used, and the secret required to access the image. Note If you add the seed image pull secret in the hub cluster, in the same namespace as the ImageBasedGroupUpgrade resource, the secret is added to the manifest list for the Prep stage. The secret is recreated in each spoke cluster in the openshift-lifecycle-agent namespace. 3 Optional: Applies additional manifests, which are not in the seed image, to the target cluster. Also applies ConfigMap objects for custom catalog sources. 4 List of ConfigMap resources that contain the OADP Backup and Restore CRs. 5 Upgrade plan details. Apply the created file by running the following command on the hub cluster: USD oc apply -f <filename>.yaml Monitor the status updates by running the following command on the hub cluster: USD oc get ibgu -o yaml Example output # ... status: clusters: - completedActions: - action: Prep name: spoke1 - completedActions: - action: Prep name: spoke4 - failedActions: - action: Prep name: spoke6 # ... The output of an example plan starts with the Prep stage only and you add actions to the plan based on the results of the step. TALM adds a label to the clusters to mark if the upgrade succeeded or failed. For example, the lcm.openshift.io/ibgu-prep-failed is applied to clusters that failed the Prep stage. After investigating the failure, you can add the AbortOnFailure step to your upgrade plan. It moves the clusters labeled with lcm.openshift.io/ibgu-<action>-failed back to the Idle stage. Any resources that are related to the upgrade on the selected clusters are deleted. Optional: Add the AbortOnFailure action to your existing ImageBasedGroupUpgrade CR by running the following command: USD oc patch ibgu <filename> --type=json -p \ '[{"op": "add", "path": "/spec/plan/-", "value": {"actions": ["AbortOnFailure"], "rolloutStrategy": {"maxConcurrency": 5, "timeout": 10}}}]' Continue monitoring the status updates by running the following command: USD oc get ibgu -o yaml Add the action to your existing ImageBasedGroupUpgrade CR by running the following command: USD oc patch ibgu <filename> --type=json -p \ '[{"op": "add", "path": "/spec/plan/-", "value": {"actions": ["Upgrade"], "rolloutStrategy": {"maxConcurrency": 2, "timeout": 30}}}]' Optional: Add the AbortOnFailure action to your existing ImageBasedGroupUpgrade CR by running the following command: USD oc patch ibgu <filename> --type=json -p \ '[{"op": "add", "path": "/spec/plan/-", "value": {"actions": ["AbortOnFailure"], "rolloutStrategy": {"maxConcurrency": 5, "timeout": 10}}}]' Continue monitoring the status updates by running the following command: USD oc get ibgu -o yaml Add the action to your existing ImageBasedGroupUpgrade CR by running the following command: USD oc patch ibgu <filename> --type=json -p \ '[{"op": "add", "path": "/spec/plan/-", "value": {"actions": ["FinalizeUpgrade"], "rolloutStrategy": {"maxConcurrency": 10, "timeout": 3}}}]' Verification Monitor the status updates by running the following command: USD oc get ibgu -o yaml Example output # ... status: clusters: - completedActions: - action: Prep - action: AbortOnFailure failedActions: - action: Upgrade name: spoke1 - completedActions: - action: Prep - action: Upgrade - action: FinalizeUpgrade name: spoke4 - completedActions: - action: AbortOnFailure failedActions: - action: Prep name: spoke6 # ... Additional resources Configuring a shared container partition between ostree stateroots when using GitOps ZTP Creating ConfigMap objects for the image-based upgrade with Lifecycle Agent using GitOps ZTP About backup and snapshot locations and their secrets Creating a Backup CR Creating a Restore CR Supported action combinations 15.4.3. Performing an image-based upgrade on managed clusters at scale in one step For use cases when service interruption is not a concern, you can upgrade a set of your managed clusters by using the ImageBasedGroupUpgrade CR with several actions combined in one step with one rollout strategy. With one rollout strategy, the upgrade time can be reduced but you can only troubleshoot failed clusters after the upgrade plan is complete. Prerequisites You have logged in to the hub cluster as a user with cluster-admin privileges. You have created policies and ConfigMap objects for resources used in the image-based upgrade. You have installed the Lifecycle Agent and OADP Operators on all managed clusters through the hub cluster. Procedure Create a YAML file on the hub cluster that contains the ImageBasedGroupUpgrade CR: apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: 1 - matchExpressions: - key: name operator: In values: - spoke1 - spoke4 - spoke6 ibuSpec: seedImageRef: 2 image: quay.io/seed/image:4.17.0-rc.1 version: 4.17.0-rc.1 pullSecretRef: name: "<seed_pull_secret>" extraManifests: 3 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 4 - name: oadp-cm namespace: openshift-adp plan: 5 - actions: ["Prep", "Upgrade", "FinalizeUpgrade"] rolloutStrategy: maxConcurrency: 200 6 timeout: 2400 7 1 Clusters to upgrade. 2 Target platform version, the seed image to be used, and the secret required to access the image. Note If you add the seed image pull secret in the hub cluster, in the same namespace as the ImageBasedGroupUpgrade resource, the secret is added to the manifest list for the Prep stage. The secret is recreated in each spoke cluster in the openshift-lifecycle-agent namespace. 3 Optional: Applies additional manifests, which are not in the seed image, to the target cluster. Also applies ConfigMap objects for custom catalog sources. 4 ConfigMap resources that contain the OADP Backup and Restore CRs. 5 Upgrade plan details. 6 Number of clusters to update in a batch. 7 Timeout limit to complete the action in minutes. Apply the created file by running the following command on the hub cluster: USD oc apply -f <filename>.yaml Verification Monitor the status updates by running the following command: USD oc get ibgu -o yaml Example output # ... status: clusters: - completedActions: - action: Prep failedActions: - action: Upgrade name: spoke1 - completedActions: - action: Prep - action: Upgrade - action: FinalizeUpgrade name: spoke4 - failedActions: - action: Prep name: spoke6 # ... 15.4.4. Canceling an image-based upgrade on managed clusters at scale You can cancel the upgrade on a set of managed clusters that completed the Prep stage. Important Only certain action combinations are supported and listed in Supported action combinations . Prerequisites You have logged in to the hub cluster as a user with cluster-admin privileges. Procedure Create a separate YAML file on the hub cluster that contains the ImageBasedGroupUpgrade CR: apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: - matchExpressions: - key: name operator: In values: - spoke4 ibuSpec: seedImageRef: image: quay.io/seed/image:4.16.0-rc.1 version: 4.16.0-rc.1 pullSecretRef: name: "<seed_pull_secret>" extraManifests: - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: - name: oadp-cm namespace: openshift-adp plan: - actions: ["Abort"] rolloutStrategy: maxConcurrency: 5 timeout: 10 All managed clusters that completed the Prep stage are moved back to the Idle stage. Apply the created file by running the following command on the hub cluster: USD oc apply -f <filename>.yaml Verification Monitor the status updates by running the following command: USD oc get ibgu -o yaml Example output # ... status: clusters: - completedActions: - action: Prep currentActions: - action: Abort name: spoke4 # ... Additional resources Supported action combinations 15.4.5. Rolling back an image-based upgrade on managed clusters at scale Roll back the changes on a set of managed clusters if you encounter unresolvable issues after a successful upgrade. You need to create a separate ImageBasedGroupUpgrade CR and define the set of managed clusters that you want to roll back. Important Only certain action combinations are supported and listed in Supported action combinations . Prerequisites You have logged in to the hub cluster as a user with cluster-admin privileges. Procedure Create a separate YAML file on the hub cluster that contains the ImageBasedGroupUpgrade CR: apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: - matchExpressions: - key: name operator: In values: - spoke4 ibuSpec: seedImageRef: image: quay.io/seed/image:4.17.0-rc.1 version: 4.17.0-rc.1 pullSecretRef: name: "<seed_pull_secret>" extraManifests: - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: - name: oadp-cm namespace: openshift-adp plan: - actions: ["Rollback", "FinalizeRollback"] rolloutStrategy: maxConcurrency: 200 timeout: 2400 Apply the created file by running the following command on the hub cluster: USD oc apply -f <filename>.yaml All managed clusters that match the defined labels are moved back to the Rollback and then the Idle stages to finalize the rollback. Verification Monitor the status updates by running the following command: USD oc get ibgu -o yaml Example output # ... status: clusters: - completedActions: - action: Rollback - action: FinalizeRollback name: spoke4 # ... Additional resources Supported action combinations Recovering from expired control plane certificates 15.4.6. Troubleshooting image-based upgrades with Lifecycle Agent Perform troubleshooting steps on the managed clusters that are affected by an issue. Important If you are using the ImageBasedGroupUpgrade CR to upgrade your clusters, ensure that the lcm.openshift.io/ibgu-<stage>-completed or lcm.openshift.io/ibgu-<stage>-failed cluster labels are updated properly after performing troubleshooting or recovery steps on the managed clusters. This ensures that the TALM continues to manage the image-based upgrade for the cluster. 15.4.6.1. Collecting logs You can use the oc adm must-gather CLI to collect information for debugging and troubleshooting. Procedure Collect data about the Operators by running the following command: USD oc adm must-gather \ --dest-dir=must-gather/tmp \ --image=USD(oc -n openshift-lifecycle-agent get deployment.apps/lifecycle-agent-controller-manager -o jsonpath='{.spec.template.spec.containers[?(@.name == "manager")].image}') \ --image=quay.io/konveyor/oadp-must-gather:latest \// 1 --image=quay.io/openshift/origin-must-gather:latest 2 1 Optional: Add this option if you need to gather more information from the OADP Operator. 2 Optional: Add this option if you need to gather more information from the SR-IOV Operator. 15.4.6.2. AbortFailed or FinalizeFailed error Issue During the finalize stage or when you stop the process at the Prep stage, Lifecycle Agent cleans up the following resources: Stateroot that is no longer required Precaching resources OADP CRs ImageBasedUpgrade CR If the Lifecycle Agent fails to perform the above steps, it transitions to the AbortFailed or FinalizeFailed states. The condition message and log show which steps failed. Example error message message: failed to delete all the backup CRs. Perform cleanup manually then add 'lca.openshift.io/manual-cleanup-done' annotation to ibu CR to transition back to Idle observedGeneration: 5 reason: AbortFailed status: "False" type: Idle Resolution Inspect the logs to determine why the failure occurred. To prompt Lifecycle Agent to retry the cleanup, add the lca.openshift.io/manual-cleanup-done annotation to the ImageBasedUpgrade CR. After observing this annotation, Lifecycle Agent retries the cleanup and, if it is successful, the ImageBasedUpgrade stage transitions to Idle . If the cleanup fails again, you can manually clean up the resources. 15.4.6.2.1. Cleaning up stateroot manually Issue Stopping at the Prep stage, Lifecycle Agent cleans up the new stateroot. When finalizing after a successful upgrade or a rollback, Lifecycle Agent cleans up the old stateroot. If this step fails, it is recommended that you inspect the logs to determine why the failure occurred. Resolution Check if there are any existing deployments in the stateroot by running the following command: USD ostree admin status If there are any, clean up the existing deployment by running the following command: USD ostree admin undeploy <index_of_deployment> After cleaning up all the deployments of the stateroot, wipe the stateroot directory by running the following commands: Warning Ensure that the booted deployment is not in this stateroot. USD stateroot="<stateroot_to_delete>" USD unshare -m /bin/sh -c "mount -o remount,rw /sysroot && rm -rf /sysroot/ostree/deploy/USD{stateroot}" 15.4.6.2.2. Cleaning up OADP resources manually Issue Automatic cleanup of OADP resources can fail due to connection issues between Lifecycle Agent and the S3 backend. By restoring the connection and adding the lca.openshift.io/manual-cleanup-done annotation, the Lifecycle Agent can successfully cleanup backup resources. Resolution Check the backend connectivity by running the following command: USD oc get backupstoragelocations.velero.io -n openshift-adp Example output NAME PHASE LAST VALIDATED AGE DEFAULT dataprotectionapplication-1 Available 33s 8d true Remove all backup resources and then add the lca.openshift.io/manual-cleanup-done annotation to the ImageBasedUpgrade CR. 15.4.6.3. LVM Storage volume contents not restored When LVM Storage is used to provide dynamic persistent volume storage, LVM Storage might not restore the persistent volume contents if it is configured incorrectly. 15.4.6.3.1. Missing LVM Storage-related fields in Backup CR Issue Your Backup CRs might be missing fields that are needed to restore your persistent volumes. You can check for events in your application pod to determine if you have this issue by running the following: USD oc describe pod <your_app_name> Example output showing missing LVM Storage-related fields in Backup CR Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 58s (x2 over 66s) default-scheduler 0/1 nodes are available: pod has unbound immediate PersistentVolumeClaims. preemption: 0/1 nodes are available: 1 Preemption is not helpful for scheduling.. Normal Scheduled 56s default-scheduler Successfully assigned default/db-1234 to sno1.example.lab Warning FailedMount 24s (x7 over 55s) kubelet MountVolume.SetUp failed for volume "pvc-1234" : rpc error: code = Unknown desc = VolumeID is not found Resolution You must include logicalvolumes.topolvm.io in the application Backup CR. Without this resource, the application restores its persistent volume claims and persistent volume manifests correctly, however, the logicalvolume associated with this persistent volume is not restored properly after pivot. Example Backup CR apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: small-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets includedClusterScopedResources: 1 - persistentVolumes - volumesnapshotcontents - logicalvolumes.topolvm.io 1 To restore the persistent volumes for your application, you must configure this section as shown. 15.4.6.3.2. Missing LVM Storage-related fields in Restore CR Issue The expected resources for the applications are restored but the persistent volume contents are not preserved after upgrading. List the persistent volumes for you applications by running the following command before pivot: USD oc get pv,pvc,logicalvolumes.topolvm.io -A Example output before pivot NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Retain Bound default/pvc-db lvms-vg1 4h45m NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 4h45m NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 4h45m List the persistent volumes for you applications by running the following command after pivot: USD oc get pv,pvc,logicalvolumes.topolvm.io -A Example output after pivot NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Delete Bound default/pvc-db lvms-vg1 19s NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 19s NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 18s Resolution The reason for this issue is that the logicalvolume status is not preserved in the Restore CR. This status is important because it is required for Velero to reference the volumes that must be preserved after pivoting. You must include the following fields in the application Restore CR: Example Restore CR apiVersion: velero.io/v1 kind: Restore metadata: name: sample-vote-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: "3" spec: backupName: sample-vote-app restorePVs: true 1 restoreStatus: 2 includedResources: - logicalvolumes 1 To preserve the persistent volumes for your application, you must set restorePVs to true . 2 To preserve the persistent volumes for your application, you must configure this section as shown. 15.4.6.4. Debugging failed Backup and Restore CRs Issue The backup or restoration of artifacts failed. Resolution You can debug Backup and Restore CRs and retrieve logs with the Velero CLI tool. The Velero CLI tool provides more detailed information than the OpenShift CLI tool. Describe the Backup CR that contains errors by running the following command: USD oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe backup -n openshift-adp backup-acm-klusterlet --details Describe the Restore CR that contains errors by running the following command: USD oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe restore -n openshift-adp restore-acm-klusterlet --details Download the backed up resources to a local directory by running the following command: USD oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero backup download -n openshift-adp backup-acm-klusterlet -o ~/backup-acm-klusterlet.tar.gz	[ "apiVersion: lca.openshift.io/v1 kind: SeedGenerator metadata: name: seedimage spec: seedImage: <seed_image>", "apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: name: upgrade spec: stage: Idle 1 seedImageRef: 2 version: <target_version> image: <seed_container_image> pullSecretRef: name: <seed_pull_secret> autoRollbackOnFailure: {} initMonitorTimeoutSeconds: 1800 3 extraManifests: 4 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 5 - name: oadp-cm-example namespace: openshift-adp", "apiVersion: velero.io/v1 kind: Backup metadata: name: acm-klusterlet namespace: openshift-adp annotations: lca.openshift.io/apply-label: rbac.authorization.k8s.io/v1/clusterroles/klusterlet,apps/v1/deployments/open-cluster-management-agent/klusterlet 1 labels: velero.io/storage-location: default spec: includedNamespaces: - open-cluster-management-agent includedClusterScopedResources: - clusterroles includedNamespaceScopedResources: - deployments", "apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: annotations: lca.openshift.io/target-ocp-version-manifest-count: \"5\" name: upgrade", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: master name: 98-var-lib-containers-partitioned spec: config: ignition: version: 3.2.0 storage: disks: - device: /dev/disk/by-path/pci-<root_disk> 1 partitions: - label: var-lib-containers startMiB: <start_of_partition> 2 sizeMiB: <partition_size> 3 filesystems: - device: /dev/disk/by-partlabel/var-lib-containers format: xfs mountOptions: - defaults - prjquota path: /var/lib/containers wipeFilesystem: true systemd: units: - contents: \|- # Generated by Butane [Unit] Before=local-fs.target Requires=systemd-fsck@dev-disk-by\\x2dpartlabel-var\\x2dlib\\x2dcontainers.service After=systemd-fsck@dev-disk-by\\x2dpartlabel-var\\x2dlib\\x2dcontainers.service [Mount] Where=/var/lib/containers What=/dev/disk/by-partlabel/var-lib-containers Type=xfs Options=defaults,prjquota [Install] RequiredBy=local-fs.target enabled: true name: var-lib-containers.mount", "variant: fcos version: 1.3.0 storage: disks: - device: /dev/disk/by-path/pci-<root_disk> 1 wipe_table: false partitions: - label: var-lib-containers start_mib: <start_of_partition> 2 size_mib: <partition_size> 3 filesystems: - path: /var/lib/containers device: /dev/disk/by-partlabel/var-lib-containers format: xfs wipe_filesystem: true with_mount_unit: true mount_options: - defaults - prjquota", "butane storage.bu", "{\"ignition\":{\"version\":\"3.2.0\"},\"storage\":{\"disks\":[{\"device\":\"/dev/disk/by-path/pci-0000:00:17.0-ata-1.0\",\"partitions\":[{\"label\":\"var-lib-containers\",\"sizeMiB\":0,\"startMiB\":250000}],\"wipeTable\":false}],\"filesystems\":[{\"device\":\"/dev/disk/by-partlabel/var-lib-containers\",\"format\":\"xfs\",\"mountOptions\":[\"defaults\",\"prjquota\"],\"path\":\"/var/lib/containers\",\"wipeFilesystem\":true}]},\"systemd\":{\"units\":[{\"contents\":\"# Generated by Butane\\n[Unit]\\nRequires=systemd-fsck@dev-disk-by\\\\x2dpartlabel-var\\\\x2dlib\\\\x2dcontainers.service\\nAfter=systemd-fsck@dev-disk-by\\\\x2dpartlabel-var\\\\x2dlib\\\\x2dcontainers.service\\n\\n[Mount]\\nWhere=/var/lib/containers\\nWhat=/dev/disk/by-partlabel/var-lib-containers\\nType=xfs\\nOptions=defaults,prjquota\\n\\n[Install]\\nRequiredBy=local-fs.target\",\"enabled\":true,\"name\":\"var-lib-containers.mount\"}]}}", "[...] spec: clusters: - nodes: - hostName: <name> ignitionConfigOverride: '{\"ignition\":{\"version\":\"3.2.0\"},\"storage\":{\"disks\":[{\"device\":\"/dev/disk/by-path/pci-0000:00:17.0-ata-1.0\",\"partitions\":[{\"label\":\"var-lib-containers\",\"sizeMiB\":0,\"startMiB\":250000}],\"wipeTable\":false}],\"filesystems\":[{\"device\":\"/dev/disk/by-partlabel/var-lib-containers\",\"format\":\"xfs\",\"mountOptions\":[\"defaults\",\"prjquota\"],\"path\":\"/var/lib/containers\",\"wipeFilesystem\":true}]},\"systemd\":{\"units\":[{\"contents\":\"# Generated by Butane\\n[Unit]\\nRequires=systemd-fsck@dev-disk-by\\\\x2dpartlabel-var\\\\x2dlib\\\\x2dcontainers.service\\nAfter=systemd-fsck@dev-disk-by\\\\x2dpartlabel-var\\\\x2dlib\\\\x2dcontainers.service\\n\\n[Mount]\\nWhere=/var/lib/containers\\nWhat=/dev/disk/by-partlabel/var-lib-containers\\nType=xfs\\nOptions=defaults,prjquota\\n\\n[Install]\\nRequiredBy=local-fs.target\",\"enabled\":true,\"name\":\"var-lib-containers.mount\"}]}}' [...]", "oc get bmh -n my-sno-ns my-sno -ojson \| jq '.metadata.annotations[\"bmac.agent-install.openshift.io/ignition-config-overrides\"]'", "\"{\\\"ignition\\\":{\\\"version\\\":\\\"3.2.0\\\"},\\\"storage\\\":{\\\"disks\\\":[{\\\"device\\\":\\\"/dev/disk/by-path/pci-0000:00:17.0-ata-1.0\\\",\\\"partitions\\\":[{\\\"label\\\":\\\"var-lib-containers\\\",\\\"sizeMiB\\\":0,\\\"startMiB\\\":250000}],\\\"wipeTable\\\":false}],\\\"filesystems\\\":[{\\\"device\\\":\\\"/dev/disk/by-partlabel/var-lib-containers\\\",\\\"format\\\":\\\"xfs\\\",\\\"mountOptions\\\":[\\\"defaults\\\",\\\"prjquota\\\"],\\\"path\\\":\\\"/var/lib/containers\\\",\\\"wipeFilesystem\\\":true}]},\\\"systemd\\\":{\\\"units\\\":[{\\\"contents\\\":\\\"# Generated by Butane\\\\n[Unit]\\\\nRequires=systemd-fsck@dev-disk-by\\\\\\\\x2dpartlabel-var\\\\\\\\x2dlib\\\\\\\\x2dcontainers.service\\\\nAfter=systemd-fsck@dev-disk-by\\\\\\\\x2dpartlabel-var\\\\\\\\x2dlib\\\\\\\\x2dcontainers.service\\\\n\\\\n[Mount]\\\\nWhere=/var/lib/containers\\\\nWhat=/dev/disk/by-partlabel/var-lib-containers\\\\nType=xfs\\\\nOptions=defaults,prjquota\\\\n\\\\n[Install]\\\\nRequiredBy=local-fs.target\\\",\\\"enabled\\\":true,\\\"name\\\":\\\"var-lib-containers.mount\\\"}]}}\"", "lsblk", "NAME MAJ:MIN RM SIZE RO TYPE MOUNTPOINTS sda 8:0 0 446.6G 0 disk ├─sda1 8:1 0 1M 0 part ├─sda2 8:2 0 127M 0 part ├─sda3 8:3 0 384M 0 part /boot ├─sda4 8:4 0 243.6G 0 part /var │ /sysroot/ostree/deploy/rhcos/var │ /usr │ /etc │ / │ /sysroot └─sda5 8:5 0 202.5G 0 part /var/lib/containers", "df -h", "Filesystem Size Used Avail Use% Mounted on devtmpfs 4.0M 0 4.0M 0% /dev tmpfs 126G 84K 126G 1% /dev/shm tmpfs 51G 93M 51G 1% /run /dev/sda4 244G 5.2G 239G 3% /sysroot tmpfs 126G 4.0K 126G 1% /tmp /dev/sda5 203G 119G 85G 59% /var/lib/containers /dev/sda3 350M 110M 218M 34% /boot tmpfs 26G 0 26G 0% /run/user/1000", "apiVersion: v1 kind: Namespace metadata: name: openshift-lifecycle-agent annotations: workload.openshift.io/allowed: management", "oc create -f <namespace_filename>.yaml", "apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: openshift-lifecycle-agent namespace: openshift-lifecycle-agent spec: targetNamespaces: - openshift-lifecycle-agent", "oc create -f <operatorgroup_filename>.yaml", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: openshift-lifecycle-agent-subscription namespace: openshift-lifecycle-agent spec: channel: \"stable\" name: lifecycle-agent source: redhat-operators sourceNamespace: openshift-marketplace", "oc create -f <subscription_filename>.yaml", "oc get csv -n openshift-lifecycle-agent", "NAME DISPLAY VERSION REPLACES PHASE lifecycle-agent.v4.17.0 Openshift Lifecycle Agent 4.17.0 Succeeded", "oc get deploy -n openshift-lifecycle-agent", "NAME READY UP-TO-DATE AVAILABLE AGE lifecycle-agent-controller-manager 1/1 1 1 14s", "apiVersion: v1 kind: Namespace metadata: name: openshift-lifecycle-agent annotations: workload.openshift.io/allowed: management ran.openshift.io/ztp-deploy-wave: \"2\" labels: kubernetes.io/metadata.name: openshift-lifecycle-agent", "apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: lifecycle-agent-operatorgroup namespace: openshift-lifecycle-agent annotations: ran.openshift.io/ztp-deploy-wave: \"2\" spec: targetNamespaces: - openshift-lifecycle-agent", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: lifecycle-agent namespace: openshift-lifecycle-agent annotations: ran.openshift.io/ztp-deploy-wave: \"2\" spec: channel: \"stable\" name: lifecycle-agent source: redhat-operators sourceNamespace: openshift-marketplace installPlanApproval: Manual status: state: AtLatestKnown", "├── kustomization.yaml ├── sno │ ├── example-cnf.yaml │ ├── common-ranGen.yaml │ ├── group-du-sno-ranGen.yaml │ ├── group-du-sno-validator-ranGen.yaml │ └── ns.yaml ├── source-crs │ ├── LcaSubscriptionNS.yaml │ ├── LcaSubscriptionOperGroup.yaml │ ├── LcaSubscription.yaml", "apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: \"example-common-latest\" namespace: \"ztp-common\" spec: bindingRules: common: \"true\" du-profile: \"latest\" sourceFiles: - fileName: LcaSubscriptionNS.yaml policyName: \"subscriptions-policy\" - fileName: LcaSubscriptionOperGroup.yaml policyName: \"subscriptions-policy\" - fileName: LcaSubscription.yaml policyName: \"subscriptions-policy\" [...]", "apiVersion: v1 kind: Namespace metadata: name: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: \"2\" labels: kubernetes.io/metadata.name: openshift-adp", "apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: redhat-oadp-operator namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: \"2\" spec: targetNamespaces: - openshift-adp", "apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: redhat-oadp-operator namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: \"2\" spec: channel: stable-1.4 name: redhat-oadp-operator source: redhat-operators sourceNamespace: openshift-marketplace installPlanApproval: Manual status: state: AtLatestKnown", "apiVersion: operators.coreos.com/v1 kind: Operator metadata: name: redhat-oadp-operator.openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: \"2\" status: components: refs: - kind: Subscription namespace: openshift-adp conditions: - type: CatalogSourcesUnhealthy status: \"False\" - kind: InstallPlan namespace: openshift-adp conditions: - type: Installed status: \"True\" - kind: ClusterServiceVersion namespace: openshift-adp conditions: - type: Succeeded status: \"True\" reason: InstallSucceeded", "├── kustomization.yaml ├── sno │ ├── example-cnf.yaml │ ├── common-ranGen.yaml │ ├── group-du-sno-ranGen.yaml │ ├── group-du-sno-validator-ranGen.yaml │ └── ns.yaml ├── source-crs │ ├── OadpSubscriptionNS.yaml │ ├── OadpSubscriptionOperGroup.yaml │ ├── OadpSubscription.yaml │ ├── OadpOperatorStatus.yaml", "apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: \"example-common-latest\" namespace: \"ztp-common\" spec: bindingRules: common: \"true\" du-profile: \"latest\" sourceFiles: - fileName: OadpSubscriptionNS.yaml policyName: \"subscriptions-policy\" - fileName: OadpSubscriptionOperGroup.yaml policyName: \"subscriptions-policy\" - fileName: OadpSubscription.yaml policyName: \"subscriptions-policy\" - fileName: OadpOperatorStatus.yaml policyName: \"subscriptions-policy\" [...]", "apiVersion: oadp.openshift.io/v1alpha1 kind: DataProtectionApplication metadata: name: dataprotectionapplication namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: \"100\" spec: configuration: restic: enable: false 1 velero: defaultPlugins: - aws - openshift resourceTimeout: 10m backupLocations: - velero: config: profile: \"default\" region: minio s3Url: USDurl insecureSkipTLSVerify: \"true\" s3ForcePathStyle: \"true\" provider: aws default: true credential: key: cloud name: cloud-credentials objectStorage: bucket: USDbucketName 2 prefix: USDprefixName 3 status: conditions: - reason: Complete status: \"True\" type: Reconciled", "apiVersion: v1 kind: Secret metadata: name: cloud-credentials namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: \"100\" type: Opaque", "apiVersion: velero.io/v1 kind: BackupStorageLocation metadata: namespace: openshift-adp annotations: ran.openshift.io/ztp-deploy-wave: \"100\" status: phase: Available", "apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: \"example-cnf\" namespace: \"ztp-site\" spec: bindingRules: sites: \"example-cnf\" du-profile: \"latest\" mcp: \"master\" sourceFiles: - fileName: OadpSecret.yaml policyName: \"config-policy\" data: cloud: <your_credentials> 1 - fileName: DataProtectionApplication.yaml policyName: \"config-policy\" spec: backupLocations: - velero: config: region: minio s3Url: <your_S3_URL> 2 profile: \"default\" insecureSkipTLSVerify: \"true\" s3ForcePathStyle: \"true\" provider: aws default: true credential: key: cloud name: cloud-credentials objectStorage: bucket: <your_bucket_name> 3 prefix: <cluster_name> 4 - fileName: OadpBackupStorageLocationStatus.yaml policyName: \"config-policy\"", "oc delete managedcluster sno-worker-example", "apiVersion: kustomize.config.k8s.io/v1beta1 kind: Kustomization generators: #- example-seed-sno1.yaml - example-target-sno2.yaml - example-target-sno3.yaml", "apiVersion: kustomize.config.k8s.io/v1beta1 kind: Kustomization generators: {}", "MY_USER=myuserid AUTHFILE=/tmp/my-auth.json podman login --authfile USD{AUTHFILE} -u USD{MY_USER} quay.io/USD{MY_USER}", "base64 -w 0 USD{AUTHFILE} ; echo", "apiVersion: v1 kind: Secret metadata: name: seedgen 1 namespace: openshift-lifecycle-agent type: Opaque data: seedAuth: <encoded_AUTHFILE> 2", "oc apply -f secretseedgenerator.yaml", "apiVersion: lca.openshift.io/v1 kind: SeedGenerator metadata: name: seedimage 1 spec: seedImage: <seed_container_image> 2", "oc apply -f seedgenerator.yaml", "oc get seedgenerator -o yaml", "status: conditions: - lastTransitionTime: \"2024-02-13T21:24:26Z\" message: Seed Generation completed observedGeneration: 1 reason: Completed status: \"False\" type: SeedGenInProgress - lastTransitionTime: \"2024-02-13T21:24:26Z\" message: Seed Generation completed observedGeneration: 1 reason: Completed status: \"True\" type: SeedGenCompleted 1 observedGeneration: 1", "apiVersion: velero.io/v1 kind: Backup metadata: name: acm-klusterlet annotations: lca.openshift.io/apply-label: \"apps/v1/deployments/open-cluster-management-agent/klusterlet,v1/secrets/open-cluster-management-agent/bootstrap-hub-kubeconfig,rbac.authorization.k8s.io/v1/clusterroles/klusterlet,v1/serviceaccounts/open-cluster-management-agent/klusterlet,scheduling.k8s.io/v1/priorityclasses/klusterlet-critical,rbac.authorization.k8s.io/v1/clusterroles/open-cluster-management:klusterlet-admin-aggregate-clusterrole,rbac.authorization.k8s.io/v1/clusterrolebindings/klusterlet,operator.open-cluster-management.io/v1/klusterlets/klusterlet,apiextensions.k8s.io/v1/customresourcedefinitions/klusterlets.operator.open-cluster-management.io,v1/secrets/open-cluster-management-agent/open-cluster-management-image-pull-credentials\" 1 labels: velero.io/storage-location: default namespace: openshift-adp spec: includedNamespaces: - open-cluster-management-agent includedClusterScopedResources: - klusterlets.operator.open-cluster-management.io - clusterroles.rbac.authorization.k8s.io - clusterrolebindings.rbac.authorization.k8s.io - priorityclasses.scheduling.k8s.io includedNamespaceScopedResources: - deployments - serviceaccounts - secrets excludedNamespaceScopedResources: [] --- apiVersion: velero.io/v1 kind: Restore metadata: name: acm-klusterlet namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"1\" spec: backupName: acm-klusterlet", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: lvmcluster namespace: openshift-adp spec: includedNamespaces: - openshift-storage includedNamespaceScopedResources: - lvmclusters - lvmvolumegroups - lvmvolumegroupnodestatuses --- apiVersion: velero.io/v1 kind: Restore metadata: name: lvmcluster namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"2\" 1 spec: backupName: lvmcluster", "apiVersion: velero.io/v1 kind: Backup metadata: annotations: lca.openshift.io/apply-label: \"apiextensions.k8s.io/v1/customresourcedefinitions/test.example.com,security.openshift.io/v1/securitycontextconstraints/test,rbac.authorization.k8s.io/v1/clusterroles/test-role,rbac.authorization.k8s.io/v1/clusterrolebindings/system:openshift:scc:test\" 1 name: backup-app-cluster-resources labels: velero.io/storage-location: default namespace: openshift-adp spec: includedClusterScopedResources: - customresourcedefinitions - securitycontextconstraints - clusterrolebindings - clusterroles excludedClusterScopedResources: - Namespace --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app-cluster-resources namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"3\" 2 spec: backupName: backup-app-cluster-resources", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 excludedClusterScopedResources: - persistentVolumes --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"4\" spec: backupName: backup-app", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 includedClusterScopedResources: - persistentVolumes 2 - logicalvolumes.topolvm.io 3 - volumesnapshotcontents 4 --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"4\" spec: backupName: backup-app restorePVs: true restoreStatus: includedResources: - logicalvolumes 5", "oc create configmap oadp-cm-example --from-file=example-oadp-resources.yaml=<path_to_oadp_crs> -n openshift-adp", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"oadpContent\": [{\"name\": \"oadp-cm-example\", \"namespace\": \"openshift-adp\"}]}}' --type=merge -n openshift-lifecycle-agent", "apiVersion: sriovnetwork.openshift.io/v1 kind: SriovNetworkNodePolicy metadata: name: \"example-sriov-node-policy\" namespace: openshift-sriov-network-operator spec: deviceType: vfio-pci isRdma: false nicSelector: pfNames: [ens1f0] nodeSelector: node-role.kubernetes.io/master: \"\" mtu: 1500 numVfs: 8 priority: 99 resourceName: example-sriov-node-policy --- apiVersion: sriovnetwork.openshift.io/v1 kind: SriovNetwork metadata: name: \"example-sriov-network\" namespace: openshift-sriov-network-operator spec: ipam: \|- { } linkState: auto networkNamespace: sriov-namespace resourceName: example-sriov-node-policy spoofChk: \"on\" trust: \"off\"", "oc create configmap example-extra-manifests-cm --from-file=example-extra-manifests.yaml=<path_to_extramanifest> -n openshift-lifecycle-agent", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"extraManifests\": [{\"name\": \"example-extra-manifests-cm\", \"namespace\": \"openshift-lifecycle-agent\"}]}}' --type=merge -n openshift-lifecycle-agent", "apiVersion: operators.coreos.com/v1 kind: CatalogSource metadata: name: example-catalogsources namespace: openshift-marketplace spec: sourceType: grpc displayName: disconnected-redhat-operators image: quay.io/example-org/example-catalog:v1", "oc create configmap example-catalogsources-cm --from-file=example-catalogsources.yaml=<path_to_catalogsource_cr> -n openshift-lifecycle-agent", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"extraManifests\": [{\"name\": \"example-catalogsources-cm\", \"namespace\": \"openshift-lifecycle-agent\"}]}}' --type=merge -n openshift-lifecycle-agent", "├── source-crs/ │ ├── ibu/ │ │ ├── ImageBasedUpgrade.yaml │ │ ├── PlatformBackupRestore.yaml │ │ ├── PlatformBackupRestoreLvms.yaml │ │ ├── PlatformBackupRestoreWithIBGU.yaml ├── ├── kustomization.yaml", "apiVersion: velero.io/v1 kind: Backup metadata: name: acm-klusterlet annotations: lca.openshift.io/apply-label: \"apps/v1/deployments/open-cluster-management-agent/klusterlet,v1/secrets/open-cluster-management-agent/bootstrap-hub-kubeconfig,rbac.authorization.k8s.io/v1/clusterroles/klusterlet,v1/serviceaccounts/open-cluster-management-agent/klusterlet,scheduling.k8s.io/v1/priorityclasses/klusterlet-critical,rbac.authorization.k8s.io/v1/clusterroles/open-cluster-management:klusterlet-work:ibu-role,rbac.authorization.k8s.io/v1/clusterroles/open-cluster-management:klusterlet-admin-aggregate-clusterrole,rbac.authorization.k8s.io/v1/clusterrolebindings/klusterlet,operator.open-cluster-management.io/v1/klusterlets/klusterlet,apiextensions.k8s.io/v1/customresourcedefinitions/klusterlets.operator.open-cluster-management.io,v1/secrets/open-cluster-management-agent/open-cluster-management-image-pull-credentials\" 1 labels: velero.io/storage-location: default namespace: openshift-adp spec: includedNamespaces: - open-cluster-management-agent includedClusterScopedResources: - klusterlets.operator.open-cluster-management.io - clusterroles.rbac.authorization.k8s.io - clusterrolebindings.rbac.authorization.k8s.io - priorityclasses.scheduling.k8s.io includedNamespaceScopedResources: - deployments - serviceaccounts - secrets excludedNamespaceScopedResources: [] --- apiVersion: velero.io/v1 kind: Restore metadata: name: acm-klusterlet namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"1\" spec: backupName: acm-klusterlet", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: lvmcluster namespace: openshift-adp spec: includedNamespaces: - openshift-storage includedNamespaceScopedResources: - lvmclusters - lvmvolumegroups - lvmvolumegroupnodestatuses --- apiVersion: velero.io/v1 kind: Restore metadata: name: lvmcluster namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"2\" 1 spec: backupName: lvmcluster", "apiVersion: velero.io/v1 kind: Backup metadata: annotations: lca.openshift.io/apply-label: \"apiextensions.k8s.io/v1/customresourcedefinitions/test.example.com,security.openshift.io/v1/securitycontextconstraints/test,rbac.authorization.k8s.io/v1/clusterroles/test-role,rbac.authorization.k8s.io/v1/clusterrolebindings/system:openshift:scc:test\" 1 name: backup-app-cluster-resources labels: velero.io/storage-location: default namespace: openshift-adp spec: includedClusterScopedResources: - customresourcedefinitions - securitycontextconstraints - clusterrolebindings - clusterroles excludedClusterScopedResources: - Namespace --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app-cluster-resources namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"3\" 2 spec: backupName: backup-app-cluster-resources", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 excludedClusterScopedResources: - persistentVolumes --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"4\" spec: backupName: backup-app", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: backup-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets - configmaps - cronjobs - services - job - poddisruptionbudgets - <application_custom_resources> 1 includedClusterScopedResources: - persistentVolumes 2 - logicalvolumes.topolvm.io 3 - volumesnapshotcontents 4 --- apiVersion: velero.io/v1 kind: Restore metadata: name: test-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"4\" spec: backupName: backup-app restorePVs: true restoreStatus: includedResources: - logicalvolumes 5", "apiVersion: kustomize.config.k8s.io/v1beta1 kind: Kustomization configMapGenerator: 1 - files: - source-crs/ibu/PlatformBackupRestoreWithIBGU.yaml #- source-crs/custom-crs/ApplicationClusterScopedBackupRestore.yaml #- source-crs/custom-crs/ApplicationApplicationBackupRestoreLso.yaml name: oadp-cm namespace: openshift-adp 2 generatorOptions: disableNameSuffixHash: true", "apiVersion: ran.openshift.io/v1 kind: PolicyGenTemplate metadata: name: example-sno spec: bindingRules: sites: \"example-sno\" du-profile: \"4.15\" mcp: \"master\" sourceFiles: - fileName: SriovNetwork.yaml policyName: \"config-policy\" metadata: name: \"sriov-nw-du-fh\" labels: lca.openshift.io/target-ocp-version: \"4.15\" 1 spec: resourceName: du_fh vlan: 140 - fileName: SriovNetworkNodePolicy.yaml policyName: \"config-policy\" metadata: name: \"sriov-nnp-du-fh\" labels: lca.openshift.io/target-ocp-version: \"4.15\" spec: deviceType: netdevice isRdma: false nicSelector: pfNames: [\"ens5f0\"] numVfs: 8 priority: 10 resourceName: du_fh - fileName: SriovNetwork.yaml policyName: \"config-policy\" metadata: name: \"sriov-nw-du-mh\" labels: lca.openshift.io/target-ocp-version: \"4.15\" spec: resourceName: du_mh vlan: 150 - fileName: SriovNetworkNodePolicy.yaml policyName: \"config-policy\" metadata: name: \"sriov-nnp-du-mh\" labels: lca.openshift.io/target-ocp-version: \"4.15\" spec: deviceType: vfio-pci isRdma: false nicSelector: pfNames: [\"ens7f0\"] numVfs: 8 priority: 10 resourceName: du_mh - fileName: DefaultCatsrc.yaml 2 policyName: \"config-policy\" metadata: name: default-cat-source namespace: openshift-marketplace labels: lca.openshift.io/target-ocp-version: \"4.15\" spec: displayName: default-cat-source image: quay.io/example-org/example-catalog:v1", "oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/disk-usage-threshold-percent='65'", "oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/disk-usage-threshold-percent-", "oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/on-prep='Disabled'", "oc -n openshift-lifecycle-agent annotate ibu upgrade image-cleanup.lca.openshift.io/on-prep-", "skopeo inspect docker://<imagename> \| jq -r '.Labels.\"com.openshift.lifecycle-agent.seed_cluster_info\" \| fromjson \| .release_registry'", "apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: name: upgrade spec: stage: Idle seedImageRef: version: 4.15.2 1 image: <seed_container_image> 2 pullSecretRef: <seed_pull_secret> 3 autoRollbackOnFailure: {} initMonitorTimeoutSeconds: 1800 4 extraManifests: 5 - name: example-extra-manifests-cm namespace: openshift-lifecycle-agent - name: example-catalogsources-cm namespace: openshift-lifecycle-agent oadpContent: 6 - name: oadp-cm-example namespace: openshift-adp", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"stage\": \"Prep\"}}' --type=merge -n openshift-lifecycle-agent", "metadata: annotations: extra-manifest.lca.openshift.io/validation-warning: '...'", "oc get ibu -o yaml", "conditions: - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: In progress observedGeneration: 13 reason: InProgress status: \"False\" type: Idle - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Prep completed observedGeneration: 13 reason: Completed status: \"False\" type: PrepInProgress - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Prep stage completed successfully observedGeneration: 13 reason: Completed status: \"True\" type: PrepCompleted observedGeneration: 13 validNextStages: - Idle - Upgrade", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"stage\": \"Upgrade\"}}' --type=merge", "oc get ibu -o yaml", "status: conditions: - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: In progress observedGeneration: 5 reason: InProgress status: \"False\" type: Idle - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Prep completed observedGeneration: 5 reason: Completed status: \"False\" type: PrepInProgress - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Prep completed successfully observedGeneration: 5 reason: Completed status: \"True\" type: PrepCompleted - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: \|- Waiting for system to stabilize: one or more health checks failed - one or more ClusterOperators not yet ready: authentication - one or more MachineConfigPools not yet ready: master - one or more ClusterServiceVersions not yet ready: sriov-fec.v2.8.0 observedGeneration: 1 reason: InProgress status: \"True\" type: UpgradeInProgress observedGeneration: 1 rollbackAvailabilityExpiration: \"2024-05-19T14:01:52Z\" validNextStages: - Rollback", "oc get ibu -o yaml", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"stage\": \"Idle\"}}' --type=merge", "oc get ibu -o yaml", "status: conditions: - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: In progress observedGeneration: 5 reason: InProgress status: \"False\" type: Idle - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Prep completed observedGeneration: 5 reason: Completed status: \"False\" type: PrepInProgress - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Prep completed successfully observedGeneration: 5 reason: Completed status: \"True\" type: PrepCompleted - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Upgrade completed observedGeneration: 1 reason: Completed status: \"False\" type: UpgradeInProgress - lastTransitionTime: \"2024-01-01T09:00:00Z\" message: Upgrade completed observedGeneration: 1 reason: Completed status: \"True\" type: UpgradeCompleted observedGeneration: 1 rollbackAvailabilityExpiration: \"2024-01-01T09:00:00Z\" validNextStages: - Idle - Rollback", "oc get restores -n openshift-adp -o custom-columns=NAME:.metadata.name,Status:.status.phase,Reason:.status.failureReason", "NAME Status Reason acm-klusterlet Completed <none> 1 apache-app Completed <none> localvolume Completed <none>", "apiVersion: lca.openshift.io/v1 kind: ImageBasedUpgrade metadata: name: upgrade spec: stage: Idle seedImageRef: version: 4.15.2 image: <seed_container_image> autoRollbackOnFailure: {} initMonitorTimeoutSeconds: 1800 1", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"stage\": \"Rollback\"}}' --type=merge", "oc patch imagebasedupgrades.lca.openshift.io upgrade -p='{\"spec\": {\"stage\": \"Idle\"}}' --type=merge -n openshift-lifecycle-agent", "oc adm must-gather --dest-dir=must-gather/tmp --image=USD(oc -n openshift-lifecycle-agent get deployment.apps/lifecycle-agent-controller-manager -o jsonpath='{.spec.template.spec.containers[?(@.name == \"manager\")].image}') --image=quay.io/konveyor/oadp-must-gather:latest \\// 1 --image=quay.io/openshift/origin-must-gather:latest 2", "message: failed to delete all the backup CRs. Perform cleanup manually then add 'lca.openshift.io/manual-cleanup-done' annotation to ibu CR to transition back to Idle observedGeneration: 5 reason: AbortFailed status: \"False\" type: Idle", "ostree admin status", "ostree admin undeploy <index_of_deployment>", "stateroot=\"<stateroot_to_delete>\"", "unshare -m /bin/sh -c \"mount -o remount,rw /sysroot && rm -rf /sysroot/ostree/deploy/USD{stateroot}\"", "oc get backupstoragelocations.velero.io -n openshift-adp", "NAME PHASE LAST VALIDATED AGE DEFAULT dataprotectionapplication-1 Available 33s 8d true", "oc describe pod <your_app_name>", "Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 58s (x2 over 66s) default-scheduler 0/1 nodes are available: pod has unbound immediate PersistentVolumeClaims. preemption: 0/1 nodes are available: 1 Preemption is not helpful for scheduling.. Normal Scheduled 56s default-scheduler Successfully assigned default/db-1234 to sno1.example.lab Warning FailedMount 24s (x7 over 55s) kubelet MountVolume.SetUp failed for volume \"pvc-1234\" : rpc error: code = Unknown desc = VolumeID is not found", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: small-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets includedClusterScopedResources: 1 - persistentVolumes - volumesnapshotcontents - logicalvolumes.topolvm.io", "oc get pv,pvc,logicalvolumes.topolvm.io -A", "NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Retain Bound default/pvc-db lvms-vg1 4h45m NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 4h45m NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 4h45m", "oc get pv,pvc,logicalvolumes.topolvm.io -A", "NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Delete Bound default/pvc-db lvms-vg1 19s NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 19s NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 18s", "apiVersion: velero.io/v1 kind: Restore metadata: name: sample-vote-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"3\" spec: backupName: sample-vote-app restorePVs: true 1 restoreStatus: 2 includedResources: - logicalvolumes", "oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe backup -n openshift-adp backup-acm-klusterlet --details", "oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe restore -n openshift-adp restore-acm-klusterlet --details", "oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero backup download -n openshift-adp backup-acm-klusterlet -o ~/backup-acm-klusterlet.tar.gz", "apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: 1 - matchExpressions: - key: name operator: In values: - spoke1 - spoke4 - spoke6 ibuSpec: seedImageRef: 2 image: quay.io/seed/image:4.17.0-rc.1 version: 4.17.0-rc.1 pullSecretRef: name: \"<seed_pull_secret>\" extraManifests: 3 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 4 - name: oadp-cm namespace: openshift-adp plan: 5 - actions: [\"Prep\", \"Upgrade\", \"FinalizeUpgrade\"] rolloutStrategy: maxConcurrency: 200 6 timeout: 2400 7", "plan: - actions: [\"Prep\", \"Upgrade\", \"FinalizeUpgrade\"] rolloutStrategy: maxConcurrency: 200 timeout: 60", "plan: - actions: [\"Prep\", \"Upgrade\"] rolloutStrategy: maxConcurrency: 200 timeout: 60 - actions: [\"FinalizeUpgrade\"] rolloutStrategy: maxConcurrency: 500 timeout: 10", "plan: - actions: [\"Prep\"] rolloutStrategy: maxConcurrency: 200 timeout: 60 - actions: [\"Upgrade\"] rolloutStrategy: maxConcurrency: 200 timeout: 20 - actions: [\"FinalizeUpgrade\"] rolloutStrategy: maxConcurrency: 500 timeout: 10", "apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: 1 - matchExpressions: - key: name operator: In values: - spoke1 - spoke4 - spoke6 ibuSpec: seedImageRef: 2 image: quay.io/seed/image:4.16.0-rc.1 version: 4.16.0-rc.1 pullSecretRef: name: \"<seed_pull_secret>\" extraManifests: 3 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 4 - name: oadp-cm namespace: openshift-adp plan: 5 - actions: [\"Prep\"] rolloutStrategy: maxConcurrency: 2 timeout: 2400", "oc apply -f <filename>.yaml", "oc get ibgu -o yaml", "status: clusters: - completedActions: - action: Prep name: spoke1 - completedActions: - action: Prep name: spoke4 - failedActions: - action: Prep name: spoke6", "oc patch ibgu <filename> --type=json -p '[{\"op\": \"add\", \"path\": \"/spec/plan/-\", \"value\": {\"actions\": [\"AbortOnFailure\"], \"rolloutStrategy\": {\"maxConcurrency\": 5, \"timeout\": 10}}}]'", "oc get ibgu -o yaml", "oc patch ibgu <filename> --type=json -p '[{\"op\": \"add\", \"path\": \"/spec/plan/-\", \"value\": {\"actions\": [\"Upgrade\"], \"rolloutStrategy\": {\"maxConcurrency\": 2, \"timeout\": 30}}}]'", "oc patch ibgu <filename> --type=json -p '[{\"op\": \"add\", \"path\": \"/spec/plan/-\", \"value\": {\"actions\": [\"AbortOnFailure\"], \"rolloutStrategy\": {\"maxConcurrency\": 5, \"timeout\": 10}}}]'", "oc get ibgu -o yaml", "oc patch ibgu <filename> --type=json -p '[{\"op\": \"add\", \"path\": \"/spec/plan/-\", \"value\": {\"actions\": [\"FinalizeUpgrade\"], \"rolloutStrategy\": {\"maxConcurrency\": 10, \"timeout\": 3}}}]'", "oc get ibgu -o yaml", "status: clusters: - completedActions: - action: Prep - action: AbortOnFailure failedActions: - action: Upgrade name: spoke1 - completedActions: - action: Prep - action: Upgrade - action: FinalizeUpgrade name: spoke4 - completedActions: - action: AbortOnFailure failedActions: - action: Prep name: spoke6", "apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: 1 - matchExpressions: - key: name operator: In values: - spoke1 - spoke4 - spoke6 ibuSpec: seedImageRef: 2 image: quay.io/seed/image:4.17.0-rc.1 version: 4.17.0-rc.1 pullSecretRef: name: \"<seed_pull_secret>\" extraManifests: 3 - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: 4 - name: oadp-cm namespace: openshift-adp plan: 5 - actions: [\"Prep\", \"Upgrade\", \"FinalizeUpgrade\"] rolloutStrategy: maxConcurrency: 200 6 timeout: 2400 7", "oc apply -f <filename>.yaml", "oc get ibgu -o yaml", "status: clusters: - completedActions: - action: Prep failedActions: - action: Upgrade name: spoke1 - completedActions: - action: Prep - action: Upgrade - action: FinalizeUpgrade name: spoke4 - failedActions: - action: Prep name: spoke6", "apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: - matchExpressions: - key: name operator: In values: - spoke4 ibuSpec: seedImageRef: image: quay.io/seed/image:4.16.0-rc.1 version: 4.16.0-rc.1 pullSecretRef: name: \"<seed_pull_secret>\" extraManifests: - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: - name: oadp-cm namespace: openshift-adp plan: - actions: [\"Abort\"] rolloutStrategy: maxConcurrency: 5 timeout: 10", "oc apply -f <filename>.yaml", "oc get ibgu -o yaml", "status: clusters: - completedActions: - action: Prep currentActions: - action: Abort name: spoke4", "apiVersion: lcm.openshift.io/v1alpha1 kind: ImageBasedGroupUpgrade metadata: name: <filename> namespace: default spec: clusterLabelSelectors: - matchExpressions: - key: name operator: In values: - spoke4 ibuSpec: seedImageRef: image: quay.io/seed/image:4.17.0-rc.1 version: 4.17.0-rc.1 pullSecretRef: name: \"<seed_pull_secret>\" extraManifests: - name: example-extra-manifests namespace: openshift-lifecycle-agent oadpContent: - name: oadp-cm namespace: openshift-adp plan: - actions: [\"Rollback\", \"FinalizeRollback\"] rolloutStrategy: maxConcurrency: 200 timeout: 2400", "oc apply -f <filename>.yaml", "oc get ibgu -o yaml", "status: clusters: - completedActions: - action: Rollback - action: FinalizeRollback name: spoke4", "oc adm must-gather --dest-dir=must-gather/tmp --image=USD(oc -n openshift-lifecycle-agent get deployment.apps/lifecycle-agent-controller-manager -o jsonpath='{.spec.template.spec.containers[?(@.name == \"manager\")].image}') --image=quay.io/konveyor/oadp-must-gather:latest \\// 1 --image=quay.io/openshift/origin-must-gather:latest 2", "message: failed to delete all the backup CRs. Perform cleanup manually then add 'lca.openshift.io/manual-cleanup-done' annotation to ibu CR to transition back to Idle observedGeneration: 5 reason: AbortFailed status: \"False\" type: Idle", "ostree admin status", "ostree admin undeploy <index_of_deployment>", "stateroot=\"<stateroot_to_delete>\"", "unshare -m /bin/sh -c \"mount -o remount,rw /sysroot && rm -rf /sysroot/ostree/deploy/USD{stateroot}\"", "oc get backupstoragelocations.velero.io -n openshift-adp", "NAME PHASE LAST VALIDATED AGE DEFAULT dataprotectionapplication-1 Available 33s 8d true", "oc describe pod <your_app_name>", "Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 58s (x2 over 66s) default-scheduler 0/1 nodes are available: pod has unbound immediate PersistentVolumeClaims. preemption: 0/1 nodes are available: 1 Preemption is not helpful for scheduling.. Normal Scheduled 56s default-scheduler Successfully assigned default/db-1234 to sno1.example.lab Warning FailedMount 24s (x7 over 55s) kubelet MountVolume.SetUp failed for volume \"pvc-1234\" : rpc error: code = Unknown desc = VolumeID is not found", "apiVersion: velero.io/v1 kind: Backup metadata: labels: velero.io/storage-location: default name: small-app namespace: openshift-adp spec: includedNamespaces: - test includedNamespaceScopedResources: - secrets - persistentvolumeclaims - deployments - statefulsets includedClusterScopedResources: 1 - persistentVolumes - volumesnapshotcontents - logicalvolumes.topolvm.io", "oc get pv,pvc,logicalvolumes.topolvm.io -A", "NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Retain Bound default/pvc-db lvms-vg1 4h45m NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 4h45m NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 4h45m", "oc get pv,pvc,logicalvolumes.topolvm.io -A", "NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE persistentvolume/pvc-1234 1Gi RWO Delete Bound default/pvc-db lvms-vg1 19s NAMESPACE NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE default persistentvolumeclaim/pvc-db Bound pvc-1234 1Gi RWO lvms-vg1 19s NAMESPACE NAME AGE logicalvolume.topolvm.io/pvc-1234 18s", "apiVersion: velero.io/v1 kind: Restore metadata: name: sample-vote-app namespace: openshift-adp labels: velero.io/storage-location: default annotations: lca.openshift.io/apply-wave: \"3\" spec: backupName: sample-vote-app restorePVs: true 1 restoreStatus: 2 includedResources: - logicalvolumes", "oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe backup -n openshift-adp backup-acm-klusterlet --details", "oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero describe restore -n openshift-adp restore-acm-klusterlet --details", "oc exec -n openshift-adp velero-7c87d58c7b-sw6fc -c velero -- ./velero backup download -n openshift-adp backup-acm-klusterlet -o ~/backup-acm-klusterlet.tar.gz" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.17/html/edge_computing/image-based-upgrade-for-single-node-openshift-clusters
1.9.2. Cluster Administration GUI	1.9.2. Cluster Administration GUI This section provides an overview of the system-config-cluster cluster administration graphical user interface (GUI) available with Red Hat Cluster Suite. The GUI is for use with the cluster infrastructure and the high-availability service management components (refer to Section 1.3, "Cluster Infrastructure" and Section 1.4, "High-availability Service Management" ). The GUI consists of two major functions: the Cluster Configuration Tool and the Cluster Status Tool . The Cluster Configuration Tool provides the capability to create, edit, and propagate the cluster configuration file ( /etc/cluster/cluster.conf ). The Cluster Status Tool provides the capability to manage high-availability services. The following sections summarize those functions. Section 1.9.2.1, " Cluster Configuration Tool " Section 1.9.2.2, " Cluster Status Tool " 1.9.2.1. Cluster Configuration Tool You can access the Cluster Configuration Tool ( Figure 1.28, " Cluster Configuration Tool " ) through the Cluster Configuration tab in the Cluster Administration GUI. Figure 1.28. Cluster Configuration Tool The Cluster Configuration Tool represents cluster configuration components in the configuration file ( /etc/cluster/cluster.conf ) with a hierarchical graphical display in the left panel. A triangle icon to the left of a component name indicates that the component has one or more subordinate components assigned to it. Clicking the triangle icon expands and collapses the portion of the tree below a component. The components displayed in the GUI are summarized as follows: Cluster Nodes - Displays cluster nodes. Nodes are represented by name as subordinate elements under Cluster Nodes . Using configuration buttons at the bottom of the right frame (below Properties ), you can add nodes, delete nodes, edit node properties, and configure fencing methods for each node. Fence Devices - Displays fence devices. Fence devices are represented as subordinate elements under Fence Devices . Using configuration buttons at the bottom of the right frame (below Properties ), you can add fence devices, delete fence devices, and edit fence-device properties. Fence devices must be defined before you can configure fencing (with the Manage Fencing For This Node button) for each node. Managed Resources - Displays failover domains, resources, and services. Failover Domains - For configuring one or more subsets of cluster nodes used to run a high-availability service in the event of a node failure. Failover domains are represented as subordinate elements under Failover Domains . Using configuration buttons at the bottom of the right frame (below Properties ), you can create failover domains (when Failover Domains is selected) or edit failover domain properties (when a failover domain is selected). Resources - For configuring shared resources to be used by high-availability services. Shared resources consist of file systems, IP addresses, NFS mounts and exports, and user-created scripts that are available to any high-availability service in the cluster. Resources are represented as subordinate elements under Resources . Using configuration buttons at the bottom of the right frame (below Properties ), you can create resources (when Resources is selected) or edit resource properties (when a resource is selected). Note The Cluster Configuration Tool provides the capability to configure private resources, also. A private resource is a resource that is configured for use with only one service. You can configure a private resource within a Service component in the GUI. Services - For creating and configuring high-availability services. A service is configured by assigning resources (shared or private), assigning a failover domain, and defining a recovery policy for the service. Services are represented as subordinate elements under Services . Using configuration buttons at the bottom of the right frame (below Properties ), you can create services (when Services is selected) or edit service properties (when a service is selected).	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/4/html/cluster_suite_overview/s2-clumgmttools-overview-cso
9.4. Changing Passwords	9.4. Changing Passwords Password policies ( Chapter 19, Policy: Defining Password Policies ) and minimal access restrictions can be applied to a password change operation: Regular, non-administrative users can change only their personal passwords, and all passwords are constrained by the IdM password policies. This allows administrators to create intro passwords or to reset passwords easily, while still keeping the final password confidential. Since any password sent by an administrator to the user is temporary, there is little security risk. Changing a password as the IdM admin user overrides any IdM password policies, but the password expires immediately. This requires the user to change the password at the login. Similarly, any user who has password change rights can change a password and no password policies are applied, but the other user must reset the password at the login. Changing a password as the LDAP Directory Manager user, using LDAP tools , overrides any IdM password policies. 9.4.1. From the Web UI Open the Identity tab, and select the Users subtab. Click the name of the user for whom to reset the password. All users can change their own password; only administrators or users with delegated permissions can change other user's passwords. Scroll to the Account Settings area. Click the Reset Password link. In the pop-up box, enter and confirm the new password. 9.4.2. From the Command Line Changing a password - your own or another user's - is done using the user-mod command, as with other user account changes.	[ "[bjensen@ipaserver ~]USD kinit admin [bjensen@ipaserver ~]USD ipa user-mod jsmith --password" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/identity_management_guide/changing-pwds
Chapter 9. Creating VMDK images for RHEL for Edge	Chapter 9. Creating VMDK images for RHEL for Edge You can create a .vmdk image for RHEL for Edge by using the RHEL image builder. You can create an edge-vsphere image type with Ignition support, to inject the user configuration into the image at an early stage of the boot process. Then, you can load the image on vSphere and boot the image in a vSphere VM. The image is compatible with ESXi 7.0 U2, ESXi 8.0 and later. The vSphere VM is compatible with version 19 and 20. 9.1. Creating a blueprint with the Ignition configuration Create a blueprint for the .vmdk image and customize it with the customizations.ignition section. With that, you can create your image and, at boot time, the operating system will inject the user configuration to the image. Prerequisites You have created an Ignition configuration file. For example: Procedure Create a blueprint in the Tom's Obvious, Minimal Language (TOML) format, with the following content: Where: The name is the name and description is the description for your blueprint. The version is the version number according to the Semantic Versioning scheme. The modules and packages describe the package name and matching version glob to be installed into the image. For example, the package name = "open-vm-tools" . Notice that currently there are no differences between packages and modules. The groups are packages groups to be installed into the image. For example groups = "anaconda-tools" group package. If you do not know the modules and groups, leave them empty. The customizations.user creates a username and password to log in to the VM. The customizations.ignition.firstboot contains the URL where the Ignition configuration file is being served. Note By default, the open-vm-tools package is not included in the edge-vsphere image. If you need this package, you must include it in the blueprint customization. Import the blueprint to the image builder server: List the existing blueprints to check whether the created blueprint is successfully pushed and exists: Check whether the components and versions listed in the blueprint and their dependencies are valid: steps Use the blueprint you created to build your .vmdk image. 9.2. Creating a VMDK image for RHEL for Edge To create a RHEL for Edge .vmdk image, use the 'edge-vsphere' image type in the RHEL image builder command-line interface. Prerequisites You created a blueprint for the .vmdk image. You served an OSTree repository of the commit to embed it in the image. For example, http://10.0.2.2:8080/repo . For more details, see Setting up a web server to install RHEL for Edge image . Procedure Start the compose of a .vmdk image: The -- <url> is the URL of your repo, for example: http://10.88.0.1:8080/repo . A confirmation that the composer process has been added to the queue appears. It also shows a Universally Unique Identifier (UUID) number for the image created. Use the UUID number to track your build. Also, keep the UUID number handy for further tasks. Check the image compose status: The output displays the status in the following format: After the compose process finishes, download the resulting image file: steps Upload the .vmdk image to vSphere. 9.3. Uploading VMDK images and creating a RHEL virtual machine in vSphere Upload the .vmdk image to VMware vSphere by using the govc import.vmdk CLI tool and boot the image in a VM. Prerequisites You created an .vmdk image by using RHEL image builder and downloaded it to your host system. You installed the govc import.vmdk CLI tool. You configured the govc import.vmdk CLI tool client. You must set the following values in the environment: Procedure Navigate to the directory where you downloaded your .vmdk image. Launch the image on vSphere by executing the following steps: Import the .vmdk image in to vSphere: Create the VM in vSphere without powering it on: Power-on the VM: Retrieve the VM IP address: Use SSH to log in to the VM, using the username and password you specified in your blueprint:	[ "{ \"ignition\":{ \"version\":\"3.3.0\" }, \"passwd\":{ \"users\":[ { \"groups\":[ \"wheel\" ], \"name\":\"core\", \"passwordHash\":\"USD6USDjfuNnO9t1Bv7N\" } ] } }", "name = \"vmdk-image\" description = \"Blueprint with Ignition for the vmdk image\" version = \"0.0.1\" packages = [\"open-vm-tools\"] modules = [] groups = [] distro = \"\" [[customizations.user]] name = \"admin\" password = \"admin\" groups = [\"wheel\"] [customizations.ignition.firstboot] url = http:// <IP_address> :8080/ config.ig", "composer-cli blueprints push <blueprint-name> .toml", "composer-cli blueprints show <blueprint-name>", "composer-cli blueprints depsolve <blueprint-name>", "composer-cli compose start start-ostree <blueprint-name> edge-vsphere -- <url>", "composer-cli compose status", "<UUID> RUNNING date <blueprint-name> <blueprint-version> edge-vsphere", "composer-cli compose image <UUID>", "GOVC_URL GOVC_DATACENTER GOVC_FOLDER GOVC_DATASTORE GOVC_RESOURCE_POOL GOVC_NETWORK", "govc import.vmdk ./composer-api.vmdk foldername", "govc vm.create -net=\"VM Network\" -net.adapter=vmxnet3 -disk.controller=pvscsi -on=false -m=4096 -c=2 -g=rhel9_64Guest -firmware=efi vm_name govc vm.disk.attach -disk=\" foldername /composer-api.vmdk\" govc vm.power -on -vm vm_name -link=false vm_name", "govc vm.power -on vmname", "HOST=USD(govc vm.ip vmname )", "ssh admin@HOST" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/9/html/composing_installing_and_managing_rhel_for_edge_images/creating-vmdk-images-for-rhel-for-edge_composing-installing-managing-rhel-for-edge-images
Chapter 4. Converting virtual machines to run on Red Hat Enterprise Virtualization	Chapter 4. Converting virtual machines to run on Red Hat Enterprise Virtualization Warning The Red Hat Enterprise Linux 6 version of the virt-v2v utility has been deprecated. Users of Red Hat Enterprise Linux 6 are advised to create a Red Hat Enterprise 7 virtual machine, and install virt-v2v in that virtual machine. The Red Hat Enterprise Linux 7 version is fully supported and documented in virt-v2v Knowledgebase articles . virt-v2v can convert virtual machines to run on Red Hat Enterprise Virtualization. Virtual machines can be converted from Xen, KVM and VMware ESX / ESX(i) environments. Before converting virtual machines to run on Red Hat Enterprise Virtualization, you must attach an export storage domain to the Red Hat Enterprise Virtualization data center being used. Section 4.2, "Attaching an export storage domain" explains the process of attaching an export storage domain. For more information on export storage domains, see the Red Hat Enterprise Virtualization Administration Guide . 4.1. Acceptable converted storage output formats It is important to note that when converting a guest virtual machine to run on Red Hat Enterprise Virtualization, not all combinations of storage format and allocation policy are supported. The supported combinations differ according to whether the Red Hat Enterprise Virtualization data center the guest will be imported into uses block (FC or iSCSI) or file (NFS) for its data storage domain. Note that virt-v2v writes to an export storage domain, and this is always required to be NFS. Note The important element for a successful virtual machine import into Red Hat Enterprise Virtualization is the type of the data domain. virt-v2v is unable to detect the data center type, so this check must be applied manually by the user. Table 4.1. Allocation Policy: Preallocated Data Domain Type Storage Format Supported NFS raw Yes qcow2 No FC/iSCSI raw Yes qcow2 No Table 4.2. Allocation Policy: Sparse Data Domain Type Storage Format Supported NFS raw Yes qcow2 Yes FC/iSCSI raw No qcow2 Yes Data format and allocation policy of the virtual machine being converted by virt-v2v will be preserved unless the output data format and allocation policy are specified using the -of and -oa parameters respectively. To import virtual machines using sparse allocation into an FC or iSCSI data center, the storage format must be converted to qcow2. This is achieved by passing the parameters -of qcow2 -oa sparse to virt-v2v . Note that converting between raw and qcow2 formats is a resource intensive operation, and roughly doubles the length of time taken for the conversion process. Important Preallocated qcow2 storage is never supported in Red Hat Enterprise Virtualization, although virt-v2v is able to write it. Import to Red Hat Enterprise Virtualization will fail.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/v2v_guide/chap-v2v-vms_to_run_on_rhev
Chapter 349. Tika Component	Chapter 349. Tika Component Available as of Camel version 2.19 The Tika : components provides the ability to detect and parse documents with Apache Tika. This component uses Apache Tika as underlying library to work with documents. In order to use the Tika component, Maven users will need to add the following dependency to their pom.xml : pom.xml <dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-tika</artifactId> <version>x.x.x</version> <!-- use the same version as your Camel core version --> </dependency> The TIKA component only supports producer endpoints. 349.1. Options The Tika component has no options. The Tika endpoint is configured using URI syntax: with the following path and query parameters: 349.1.1. Path Parameters (1 parameters): Name Description Default Type operation Required Tika Operation. parse or detect TikaOperation 349.1.2. Query Parameters (5 parameters): Name Description Default Type tikaConfig (producer) Tika Config TikaConfig tikaConfigUri (producer) Tika Config Uri: The URI of tika-config.xml String tikaParseOutputEncoding (producer) Tika Parse Output Encoding - Used to specify the character encoding of the parsed output. Defaults to Charset.defaultCharset() . String tikaParseOutputFormat (producer) Tika Output Format. Supported output formats. xml: Returns Parsed Content as XML. html: Returns Parsed Content as HTML. text: Returns Parsed Content as Text. textMain: Uses the boilerpipe library to automatically extract the main content from a web page. xml TikaParseOutputFormat synchronous (advanced) Sets whether synchronous processing should be strictly used, or Camel is allowed to use asynchronous processing (if supported). false boolean 349.2. Spring Boot Auto-Configuration The component supports 2 options, which are listed below. Name Description Default Type camel.component.tika.enabled Enable tika component true Boolean camel.component.tika.resolve-property-placeholders Whether the component should resolve property placeholders on itself when starting. Only properties which are of String type can use property placeholders. true Boolean 349.3. To Detect a file's MIME Type The file should be placed in the Body. from("direct:start") .to("tika:detect"); 349.4. To Parse a File The file should be placed in the Body. from("direct:start") .to("tika:parse");	[ "<dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-tika</artifactId> <version>x.x.x</version> <!-- use the same version as your Camel core version --> </dependency>", "tika:operation", "from(\"direct:start\") .to(\"tika:detect\");", "from(\"direct:start\") .to(\"tika:parse\");" ]	https://docs.redhat.com/en/documentation/red_hat_fuse/7.13/html/apache_camel_component_reference/tika-component
Chapter 2. Introduction to content creator workflows and automation execution environments	Chapter 2. Introduction to content creator workflows and automation execution environments 2.1. About content workflows Before Red Hat Ansible Automation Platform 2.0, an automation content developer may have needed so many Python virtual environments that they required their own automation in order to manage them. To reduce this level of complexity, Ansible Automation Platform 2.0 is moving away from virtual environments and using containers, referred to as automation execution environments, instead, as they are straightforward to build and manage and are more shareable across teams and orgs. As automation controller shifts to using automation execution environments, tools like automation content navigator and Ansible Builder ensure that you can take advantage of those automation execution environments locally within your own development system. Additional resources See the Automation Content Navigator Creator Guide for more on using automation content navigator. For more information on Ansible Builder, see Creating and Consuming Execution Environments . 2.2. Architecture overview The following list shows the arrangements and uses of tools available on Ansible Automation Platform 2.0, along with how they can be utilized: automation content navigator only - can be used today in Ansible Automation Platform 1.2 automation content navigator + downloaded automation execution environments - used directly on laptop/workstation automation content navigator + downloaded automation execution environments + automation controller - for pushing/executing locally remotely automation content navigator + automation controller + Ansible Builder + Layered custom EE - provides even more control over utilized content for how to execute automation jobs	null	https://docs.redhat.com/en/documentation/red_hat_ansible_automation_platform/2.4/html/red_hat_ansible_automation_platform_creator_guide/assembly-introduction
4.9. Mounting File Systems	4.9. Mounting File Systems By default, when a file system that supports extended attributes is mounted, the security context for each file is obtained from the security.selinux extended attribute of the file. Files in file systems that do not support extended attributes are assigned a single, default security context from the policy configuration, based on file system type. Use the mount -o context command to override existing extended attributes, or to specify a different, default context for file systems that do not support extended attributes. This is useful if you do not trust a file system to supply the correct attributes, for example, removable media used in multiple systems. The mount -o context command can also be used to support labeling for file systems that do not support extended attributes, such as File Allocation Table (FAT) or NFS volumes. The context specified with the context option is not written to disk: the original contexts are preserved, and are seen when mounting without context if the file system had extended attributes in the first place. For further information about file system labeling, see James Morris's "Filesystem Labeling in SELinux" article: http://www.linuxjournal.com/article/7426 . 4.9.1. Context Mounts To mount a file system with the specified context, overriding existing contexts if they exist, or to specify a different, default context for a file system that does not support extended attributes, as the root user, use the mount -o context= SELinux_user:role:type:level command when mounting the required file system. Context changes are not written to disk. By default, NFS mounts on the client side are labeled with a default context defined by policy for NFS volumes. In common policies, this default context uses the nfs_t type. Without additional mount options, this may prevent sharing NFS volumes using other services, such as the Apache HTTP Server. The following example mounts an NFS volume so that it can be shared using the Apache HTTP Server: Newly-created files and directories on this file system appear to have the SELinux context specified with -o context . However, since these changes are not written to disk, the context specified with this option does not persist between mounts. Therefore, this option must be used with the same context specified during every mount to retain the required context. For information about making context mount persistent, see Section 4.9.5, "Making Context Mounts Persistent" . Type Enforcement is the main permission control used in SELinux targeted policy. For the most part, SELinux users and roles can be ignored, so, when overriding the SELinux context with -o context , use the SELinux system_u user and object_r role, and concentrate on the type. If you are not using the MLS policy or multi-category security, use the s0 level. Note When a file system is mounted with a context option, context changes by users and processes are prohibited. For example, running the chcon command on a file system mounted with a context option results in a Operation not supported error. 4.9.2. Changing the Default Context As mentioned in Section 4.8, "The file_t and default_t Types" , on file systems that support extended attributes, when a file that lacks an SELinux context on disk is accessed, it is treated as if it had a default context as defined by SELinux policy. In common policies, this default context uses the file_t type. If it is desirable to use a different default context, mount the file system with the defcontext option. The following example mounts a newly-created file system on /dev/sda2 to the newly-created test/ directory. It assumes that there are no rules in /etc/selinux/targeted/contexts/files/ that define a context for the test/ directory: In this example: the defcontext option defines that system_u:object_r:samba_share_t:s0 is "the default security context for unlabeled files" [5] . when mounted, the root directory ( test/ ) of the file system is treated as if it is labeled with the context specified by defcontext (this label is not stored on disk). This affects the labeling for files created under test/ : new files inherit the samba_share_t type, and these labels are stored on disk. files created under test/ while the file system was mounted with a defcontext option retain their labels. 4.9.3. Mounting an NFS Volume By default, NFS mounts on the client side are labeled with a default context defined by policy for NFS volumes. In common policies, this default context uses the nfs_t type. Depending on policy configuration, services, such as Apache HTTP Server and MariaDB, may not be able to read files labeled with the nfs_t type. This may prevent file systems labeled with this type from being mounted and then read or exported by other services. If you would like to mount an NFS volume and read or export that file system with another service, use the context option when mounting to override the nfs_t type. Use the following context option to mount NFS volumes so that they can be shared using the Apache HTTP Server: Since these changes are not written to disk, the context specified with this option does not persist between mounts. Therefore, this option must be used with the same context specified during every mount to retain the required context. For information about making context mount persistent, see Section 4.9.5, "Making Context Mounts Persistent" . As an alternative to mounting file systems with context options, Booleans can be enabled to allow services access to file systems labeled with the nfs_t type. See Part II, "Managing Confined Services" for instructions on configuring Booleans to allow services access to the nfs_t type. 4.9.4. Multiple NFS Mounts When mounting multiple mounts from the same NFS export, attempting to override the SELinux context of each mount with a different context, results in subsequent mount commands failing. In the following example, the NFS server has a single export, export/ , which has two subdirectories, web/ and database/ . The following commands attempt two mounts from a single NFS export, and try to override the context for each one: The second mount command fails, and the following is logged to /var/log/messages : To mount multiple mounts from a single NFS export, with each mount having a different context, use the -o nosharecache,context options. The following example mounts multiple mounts from a single NFS export, with a different context for each mount (allowing a single service access to each one): In this example, server:/export/web is mounted locally to the /local/web/ directory, with all files being labeled with the httpd_sys_content_t type, allowing Apache HTTP Server access. server:/export/database is mounted locally to /local/database/ , with all files being labeled with the mysqld_db_t type, allowing MariaDB access. These type changes are not written to disk. Important The nosharecache options allows you to mount the same subdirectory of an export multiple times with different contexts, for example, mounting /export/web/ multiple times. Do not mount the same subdirectory from an export multiple times with different contexts, as this creates an overlapping mount, where files are accessible under two different contexts. 4.9.5. Making Context Mounts Persistent To make context mounts persistent across remounting and reboots, add entries for the file systems in the /etc/fstab file or an automounter map, and use the required context as a mount option. The following example adds an entry to /etc/fstab for an NFS context mount: [5] Morris, James. "Filesystem Labeling in SELinux". Published 1 October 2004. Accessed 14 October 2008: http://www.linuxjournal.com/article/7426 .	[ "~]# mount server:/export /local/mount/point -o \\ context=\"system_u:object_r:httpd_sys_content_t:s0\"", "~]# mount /dev/sda2 /test/ -o defcontext=\"system_u:object_r:samba_share_t:s0\"", "~]# mount server:/export /local/mount/point -o context=\"system_u:object_r:httpd_sys_content_t:s0\"", "~]# mount server:/export/web /local/web -o context=\"system_u:object_r:httpd_sys_content_t:s0\"", "~]# mount server:/export/database /local/database -o context=\"system_u:object_r:mysqld_db_t:s0\"", "kernel: SELinux: mount invalid. Same superblock, different security settings for (dev 0:15, type nfs)", "~]# mount server:/export/web /local/web -o nosharecache,context=\"system_u:object_r:httpd_sys_content_t:s0\"", "~]# mount server:/export/database /local/database -o \\ nosharecache,context=\"system_u:object_r:mysqld_db_t:s0\"", "server:/export /local/mount/ nfs context=\"system_u:object_r:httpd_sys_content_t:s0\" 0 0" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/selinux_users_and_administrators_guide/sect-Security-Enhanced_Linux-Working_with_SELinux-Mounting_File_Systems
Chapter 4. action	Chapter 4. action This chapter describes the commands under the action command. 4.1. action definition create Create new action. Usage: Table 4.1. Positional Arguments Value Summary definition Action definition file Table 4.2. Optional 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. --public With this flag action will be marked as "public". Table 4.3. Output Formatters 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 --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 Table 4.4. CSV Formatter Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 4.5. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.6. Table Formatter 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. 4.2. action definition definition show Show action definition. Usage: Table 4.7. Positional Arguments Value Summary name Action name Table 4.8. Optional Arguments Value Summary -h, --help Show this help message and exit 4.3. action definition delete Delete action. Usage: Table 4.9. Positional Arguments Value Summary action Name or id of action(s). Table 4.10. Optional Arguments Value Summary -h, --help Show this help message and exit 4.4. action definition list List all actions. Usage: Table 4.11. Optional 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 4.12. Output Formatters 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 --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 Table 4.13. CSV Formatter Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 4.14. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.15. Table Formatter 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. 4.5. action definition show Show specific action. Usage: Table 4.16. Positional Arguments Value Summary action Action (name or id) Table 4.17. Optional Arguments Value Summary -h, --help Show this help message and exit Table 4.18. Output Formatters 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 Table 4.19. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.20. Shell Formatter Value Summary --prefix PREFIX Add a prefix to all variable names Table 4.21. Table Formatter 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. 4.6. action definition update Update action. Usage: Table 4.22. Positional Arguments Value Summary definition Action definition file Table 4.23. Optional 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 Action id. --public With this flag action will be marked as "public". Table 4.24. Output Formatters 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 --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 Table 4.25. CSV Formatter Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 4.26. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.27. Table Formatter 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. 4.7. action execution delete Delete action execution. Usage: Table 4.28. Positional Arguments Value Summary action_execution Id of action execution identifier(s). Table 4.29. Optional Arguments Value Summary -h, --help Show this help message and exit 4.8. action execution input show Show Action execution input data. Usage: Table 4.30. Positional Arguments Value Summary id Action execution id. Table 4.31. Optional Arguments Value Summary -h, --help Show this help message and exit 4.9. action execution list List all Action executions. Usage: Table 4.32. Positional Arguments Value Summary task_execution_id Task execution id. Table 4.33. Optional 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 Table 4.34. Output Formatters 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 --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 Table 4.35. CSV Formatter Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 4.36. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.37. Table Formatter 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. 4.10. action execution output show Show Action execution output data. Usage: Table 4.38. Positional Arguments Value Summary id Action execution id. Table 4.39. Optional Arguments Value Summary -h, --help Show this help message and exit 4.11. action execution run Create new Action execution or just run specific action. Usage: Table 4.40. Positional Arguments Value Summary name Action name to execute. input Action input. Table 4.41. Optional Arguments Value Summary -h, --help Show this help message and exit -s, --save-result Save the result into db. --run-sync Run the action synchronously. -t TARGET, --target TARGET Action will be executed on <target> executor. Table 4.42. Output Formatters 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 Table 4.43. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.44. Shell Formatter Value Summary --prefix PREFIX Add a prefix to all variable names Table 4.45. Table Formatter 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. 4.12. action execution show Show specific Action execution. Usage: Table 4.46. Positional Arguments Value Summary action_execution Action execution id. Table 4.47. Optional Arguments Value Summary -h, --help Show this help message and exit Table 4.48. Output Formatters 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 Table 4.49. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.50. Shell Formatter Value Summary --prefix PREFIX Add a prefix to all variable names Table 4.51. Table Formatter 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. 4.13. action execution update Update specific Action execution. Usage: Table 4.52. Positional Arguments Value Summary id Action execution id. Table 4.53. Optional Arguments Value Summary -h, --help Show this help message and exit --state {PAUSED,RUNNING,SUCCESS,ERROR,CANCELLED} Action execution state --output OUTPUT Action execution output Table 4.54. Output Formatters 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 Table 4.55. JSON Formatter Value Summary --noindent Whether to disable indenting the json Table 4.56. Shell Formatter Value Summary --prefix PREFIX Add a prefix to all variable names Table 4.57. Table Formatter 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 action definition 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] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS] [--public] definition", "openstack action definition definition show [-h] name", "openstack action definition delete [-h] action [action ...]", "openstack action definition 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] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS]", "openstack action definition show [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] action", "openstack action definition 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] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS] [--id ID] [--public] definition", "openstack action execution delete [-h] action_execution [action_execution ...]", "openstack action execution input show [-h] id", "openstack action 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] [--marker [MARKER]] [--limit [LIMIT]] [--sort_keys [SORT_KEYS]] [--sort_dirs [SORT_DIRS]] [--filter FILTERS] [--oldest] [task_execution_id]", "openstack action execution output show [-h] id", "openstack action execution run [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] [-s] [--run-sync] [-t TARGET] name [input]", "openstack action execution show [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] action_execution", "openstack action execution update [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] [--state {PAUSED,RUNNING,SUCCESS,ERROR,CANCELLED}] [--output OUTPUT] id" ]	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/16.0/html/command_line_interface_reference/action
4.4. Packaging the Image for Google Compute Engine	4.4. Packaging the Image for Google Compute Engine Create a gzip sparse tar archive to package the image for Google Compute Engine, using the following command:	[ "tar -czSf disk.raw.tar.gz disk.raw" ]	https://docs.redhat.com/en/documentation/red_hat_gluster_storage/3.5/html/deployment_guide_for_public_cloud/sect-documentation-deployment_guide_for_public_cloud-google_cloud_platform-package_image
17.14. Applying Network Filtering	17.14. Applying Network Filtering This section provides an introduction to libvirt's network filters, their goals, concepts and XML format. 17.14.1. Introduction The goal of the network filtering, is to enable administrators of a virtualized system to configure and enforce network traffic filtering rules on virtual machines and manage the parameters of network traffic that virtual machines are allowed to send or receive. The network traffic filtering rules are applied on the host physical machine when a virtual machine is started. Since the filtering rules cannot be circumvented from within the virtual machine, it makes them mandatory from the point of view of a virtual machine user. From the point of view of the guest virtual machine, the network filtering system allows each virtual machine's network traffic filtering rules to be configured individually on a per interface basis. These rules are applied on the host physical machine when the virtual machine is started and can be modified while the virtual machine is running. The latter can be achieved by modifying the XML description of a network filter. Multiple virtual machines can make use of the same generic network filter. When such a filter is modified, the network traffic filtering rules of all running virtual machines that reference this filter are updated. The machines that are not running will update on start. As previously mentioned, applying network traffic filtering rules can be done on individual network interfaces that are configured for certain types of network configurations. Supported network types include: network ethernet -- must be used in bridging mode bridge Example 17.1. An example of network filtering The interface XML is used to reference a top-level filter. In the following example, the interface description references the filter clean-traffic. Network filters are written in XML and may either contain: references to other filters, rules for traffic filtering, or hold a combination of both. The above referenced filter clean-traffic is a filter that only contains references to other filters and no actual filtering rules. Since references to other filters can be used, a tree of filters can be built. The clean-traffic filter can be viewed using the command: # virsh nwfilter-dumpxml clean-traffic . As previously mentioned, a single network filter can be referenced by multiple virtual machines. Since interfaces will typically have individual parameters associated with their respective traffic filtering rules, the rules described in a filter's XML can be generalized using variables. In this case, the variable name is used in the filter XML and the name and value are provided at the place where the filter is referenced. Example 17.2. Description extended In the following example, the interface description has been extended with the parameter IP and a dotted IP address as a value. In this particular example, the clean-traffic network traffic filter will be represented with the IP address parameter 10.0.0.1 and as per the rule dictates that all traffic from this interface will always be using 10.0.0.1 as the source IP address, which is one of the purpose of this particular filter. 17.14.2. Filtering Chains Filtering rules are organized in filter chains. These chains can be thought of as having a tree structure with packet filtering rules as entries in individual chains (branches). Packets start their filter evaluation in the root chain and can then continue their evaluation in other chains, return from those chains back into the root chain or be dropped or accepted by a filtering rule in one of the traversed chains. Libvirt's network filtering system automatically creates individual root chains for every virtual machine's network interface on which the user chooses to activate traffic filtering. The user may write filtering rules that are either directly instantiated in the root chain or may create protocol-specific filtering chains for efficient evaluation of protocol-specific rules. The following chains exist: root mac stp (spanning tree protocol) vlan arp and rarp ipv4 ipv6 Multiple chains evaluating the mac, stp, vlan, arp, rarp, ipv4, or ipv6 protocol can be created using the protocol name only as a prefix in the chain's name. Example 17.3. ARP traffic filtering This example allows chains with names arp-xyz or arp-test to be specified and have their ARP protocol packets evaluated in those chains. The following filter XML shows an example of filtering ARP traffic in the arp chain. The consequence of putting ARP-specific rules in the arp chain, rather than for example in the root chain, is that packets protocols other than ARP do not need to be evaluated by ARP protocol-specific rules. This improves the efficiency of the traffic filtering. However, one must then pay attention to only putting filtering rules for the given protocol into the chain since other rules will not be evaluated. For example, an IPv4 rule will not be evaluated in the ARP chain since IPv4 protocol packets will not traverse the ARP chain. 17.14.3. Filtering Chain Priorities As previously mentioned, when creating a filtering rule, all chains are connected to the root chain. The order in which those chains are accessed is influenced by the priority of the chain. The following table shows the chains that can be assigned a priority and their default priorities. Table 17.1. Filtering chain default priorities values Chain (prefix) Default priority stp -810 mac -800 vlan -750 ipv4 -700 ipv6 -600 arp -500 rarp -400 Note A chain with a lower priority value is accessed before one with a higher value. The chains listed in Table 17.1, "Filtering chain default priorities values" can be also be assigned custom priorities by writing a value in the range [-1000 to 1000] into the priority (XML) attribute in the filter node. Section 17.14.2, "Filtering Chains" filter shows the default priority of -500 for arp chains, for example. 17.14.4. Usage of Variables in Filters There are two variables that have been reserved for usage by the network traffic filtering subsystem: MAC and IP. MAC is designated for the MAC address of the network interface. A filtering rule that references this variable will automatically be replaced with the MAC address of the interface. This works without the user having to explicitly provide the MAC parameter. Even though it is possible to specify the MAC parameter similar to the IP parameter above, it is discouraged since libvirt knows what MAC address an interface will be using. The parameter IP represents the IP address that the operating system inside the virtual machine is expected to use on the given interface. The IP parameter is special in so far as the libvirt daemon will try to determine the IP address (and thus the IP parameter's value) that is being used on an interface if the parameter is not explicitly provided but referenced. For current limitations on IP address detection, consult the section on limitations Section 17.14.12, "Limitations" on how to use this feature and what to expect when using it. The XML file shown in Section 17.14.2, "Filtering Chains" contains the filter no-arp-spoofing , which is an example of using a network filter XML to reference the MAC and IP variables. Note that referenced variables are always prefixed with the character USD . The format of the value of a variable must be of the type expected by the filter attribute identified in the XML. In the above example, the IP parameter must hold a legal IP address in standard format. Failure to provide the correct structure will result in the filter variable not being replaced with a value and will prevent a virtual machine from starting or will prevent an interface from attaching when hot plugging is being used. Some of the types that are expected for each XML attribute are shown in the example Example 17.4, "Sample variable types" . Example 17.4. Sample variable types As variables can contain lists of elements, (the variable IP can contain multiple IP addresses that are valid on a particular interface, for example), the notation for providing multiple elements for the IP variable is: This XML file creates filters to enable multiple IP addresses per interface. Each of the IP addresses will result in a separate filtering rule. Therefore, using the XML above and the following rule, three individual filtering rules (one for each IP address) will be created: As it is possible to access individual elements of a variable holding a list of elements, a filtering rule like the following accesses the 2nd element of the variable DSTPORTS . Example 17.5. Using a variety of variables As it is possible to create filtering rules that represent all of the permissible rules from different lists using the notation USDVARIABLE[@<iterator id="x">] . The following rule allows a virtual machine to receive traffic on a set of ports, which are specified in DSTPORTS , from the set of source IP address specified in SRCIPADDRESSES . The rule generates all combinations of elements of the variable DSTPORTS with those of SRCIPADDRESSES by using two independent iterators to access their elements. Assign concrete values to SRCIPADDRESSES and DSTPORTS as shown: Assigning values to the variables using USDSRCIPADDRESSES[@1] and USDDSTPORTS[@2] would then result in all variants of addresses and ports being created as shown: 10.0.0.1, 80 10.0.0.1, 8080 11.1.2.3, 80 11.1.2.3, 8080 Accessing the same variables using a single iterator, for example by using the notation USDSRCIPADDRESSES[@1] and USDDSTPORTS[@1] , would result in parallel access to both lists and result in the following combination: 10.0.0.1, 80 11.1.2.3, 8080 Note USDVARIABLE is short-hand for USDVARIABLE[@0] . The former notation always assumes the role of iterator with iterator id="0" added as shown in the opening paragraph at the top of this section. 17.14.5. Automatic IP Address Detection and DHCP Snooping This section provides information about automatic IP address detection and DHCP snooping. 17.14.5.1. Introduction The detection of IP addresses used on a virtual machine's interface is automatically activated if the variable IP is referenced but no value has been assigned to it. The variable CTRL_IP_LEARNING can be used to specify the IP address learning method to use. Valid values include: any , dhcp , or none . The value any instructs libvirt to use any packet to determine the address in use by a virtual machine, which is the default setting if the variable CTRL_IP_LEARNING is not set. This method will only detect a single IP address per interface. Once a guest virtual machine's IP address has been detected, its IP network traffic will be locked to that address, if for example, IP address spoofing is prevented by one of its filters. In that case, the user of the VM will not be able to change the IP address on the interface inside the guest virtual machine, which would be considered IP address spoofing. When a guest virtual machine is migrated to another host physical machine or resumed after a suspend operation, the first packet sent by the guest virtual machine will again determine the IP address that the guest virtual machine can use on a particular interface. The value of dhcp instructs libvirt to only honor DHCP server-assigned addresses with valid leases. This method supports the detection and usage of multiple IP address per interface. When a guest virtual machine resumes after a suspend operation, any valid IP address leases are applied to its filters. Otherwise the guest virtual machine is expected to use DHCP to obtain a new IP addresses. When a guest virtual machine migrates to another physical host physical machine, the guest virtual machine is required to re-run the DHCP protocol. If CTRL_IP_LEARNING is set to none , libvirt does not do IP address learning and referencing IP without assigning it an explicit value is an error. 17.14.5.2. DHCP Snooping CTRL_IP_LEARNING= dhcp (DHCP snooping) provides additional anti-spoofing security, especially when combined with a filter allowing only trusted DHCP servers to assign IP addresses. To enable this, set the variable DHCPSERVER to the IP address of a valid DHCP server and provide filters that use this variable to filter incoming DHCP responses. When DHCP snooping is enabled and the DHCP lease expires, the guest virtual machine will no longer be able to use the IP address until it acquires a new, valid lease from a DHCP server. If the guest virtual machine is migrated, it must get a new valid DHCP lease to use an IP address (for example by bringing the VM interface down and up again). Note Automatic DHCP detection listens to the DHCP traffic the guest virtual machine exchanges with the DHCP server of the infrastructure. To avoid denial-of-service attacks on libvirt, the evaluation of those packets is rate-limited, meaning that a guest virtual machine sending an excessive number of DHCP packets per second on an interface will not have all of those packets evaluated and thus filters may not get adapted. Normal DHCP client behavior is assumed to send a low number of DHCP packets per second. Further, it is important to setup appropriate filters on all guest virtual machines in the infrastructure to avoid them being able to send DHCP packets. Therefore, guest virtual machines must either be prevented from sending UDP and TCP traffic from port 67 to port 68 or the DHCPSERVER variable should be used on all guest virtual machines to restrict DHCP server messages to only be allowed to originate from trusted DHCP servers. At the same time anti-spoofing prevention must be enabled on all guest virtual machines in the subnet. Example 17.6. Activating IPs for DHCP snooping The following XML provides an example for the activation of IP address learning using the DHCP snooping method: 17.14.6. Reserved Variables Table 17.2, "Reserved variables" shows the variables that are considered reserved and are used by libvirt: Table 17.2. Reserved variables Variable Name Definition MAC The MAC address of the interface IP The list of IP addresses in use by an interface IPV6 Not currently implemented: the list of IPV6 addresses in use by an interface DHCPSERVER The list of IP addresses of trusted DHCP servers DHCPSERVERV6 Not currently implemented: The list of IPv6 addresses of trusted DHCP servers CTRL_IP_LEARNING The choice of the IP address detection mode 17.14.7. Element and Attribute Overview The root element required for all network filters is named <filter> with two possible attributes. The name attribute provides a unique name of the given filter. The chain attribute is optional but allows certain filters to be better organized for more efficient processing by the firewall subsystem of the underlying host physical machine. Currently, the system only supports the following chains: root , ipv4 , ipv6 , arp and rarp . 17.14.8. References to Other Filters Any filter may hold references to other filters. Individual filters may be referenced multiple times in a filter tree but references between filters must not introduce loops. Example 17.7. An Example of a clean traffic filter The following shows the XML of the clean-traffic network filter referencing several other filters. To reference another filter, the XML node <filterref> needs to be provided inside a filter node. This node must have the attribute filter whose value contains the name of the filter to be referenced. New network filters can be defined at any time and may contain references to network filters that are not known to libvirt, yet. However, once a virtual machine is started or a network interface referencing a filter is to be hot-plugged, all network filters in the filter tree must be available. Otherwise the virtual machine will not start or the network interface cannot be attached. 17.14.9. Filter Rules The following XML shows a simple example of a network traffic filter implementing a rule to drop traffic if the IP address (provided through the value of the variable IP) in an outgoing IP packet is not the expected one, thus preventing IP address spoofing by the VM. Example 17.8. Example of network traffic filtering The traffic filtering rule starts with the rule node. This node may contain up to three of the following attributes: action is mandatory can have the following values: drop (matching the rule silently discards the packet with no further analysis) reject (matching the rule generates an ICMP reject message with no further analysis) accept (matching the rule accepts the packet with no further analysis) return (matching the rule passes this filter, but returns control to the calling filter for further analysis) continue (matching the rule goes on to the rule for further analysis) direction is mandatory can have the following values: in for incoming traffic out for outgoing traffic inout for incoming and outgoing traffic priority is optional. The priority of the rule controls the order in which the rule will be instantiated relative to other rules. Rules with lower values will be instantiated before rules with higher values. Valid values are in the range of -1000 to 1000. If this attribute is not provided, priority 500 will be assigned by default. Note that filtering rules in the root chain are sorted with filters connected to the root chain following their priorities. This allows to interleave filtering rules with access to filter chains. See Section 17.14.3, "Filtering Chain Priorities" for more information. statematch is optional. Possible values are '0' or 'false' to turn the underlying connection state matching off. The default setting is 'true' or 1 For more information, see Section 17.14.11, "Advanced Filter Configuration Topics" . The above example Example 17.7, "An Example of a clean traffic filter" indicates that the traffic of type ip will be associated with the chain ipv4 and the rule will have priority= 500 . If for example another filter is referenced whose traffic of type ip is also associated with the chain ipv4 then that filter's rules will be ordered relative to the priority= 500 of the shown rule. A rule may contain a single rule for filtering of traffic. The above example shows that traffic of type ip is to be filtered. 17.14.10. Supported Protocols The following sections list and give some details about the protocols that are supported by the network filtering subsystem. This type of traffic rule is provided in the rule node as a nested node. Depending on the traffic type a rule is filtering, the attributes are different. The above example showed the single attribute srcipaddr that is valid inside the ip traffic filtering node. The following sections show what attributes are valid and what type of data they are expecting. The following datatypes are available: UINT8 : 8 bit integer; range 0-255 UINT16: 16 bit integer; range 0-65535 MAC_ADDR: MAC address in dotted decimal format, for example 00:11:22:33:44:55 MAC_MASK: MAC address mask in MAC address format, for instance, FF:FF:FF:FC:00:00 IP_ADDR: IP address in dotted decimal format, for example 10.1.2.3 IP_MASK: IP address mask in either dotted decimal format (255.255.248.0) or CIDR mask (0-32) IPV6_ADDR: IPv6 address in numbers format, for example FFFF::1 IPV6_MASK: IPv6 mask in numbers format (FFFF:FFFF:FC00::) or CIDR mask (0-128) STRING: A string BOOLEAN: 'true', 'yes', '1' or 'false', 'no', '0' IPSETFLAGS: The source and destination flags of the ipset described by up to 6 'src' or 'dst' elements selecting features from either the source or destination part of the packet header; example: src,src,dst. The number of 'selectors' to provide here depends on the type of ipset that is referenced Every attribute except for those of type IP_MASK or IPV6_MASK can be negated using the match attribute with value no . Multiple negated attributes may be grouped together. The following XML fragment shows such an example using abstract attributes. Rules behave evaluate the rule as well as look at it logically within the boundaries of the given protocol attributes. Thus, if a single attribute's value does not match the one given in the rule, the whole rule will be skipped during the evaluation process. Therefore, in the above example incoming traffic will only be dropped if: the protocol property attribute1 does not match both value1 and the protocol property attribute2 does not match value2 and the protocol property attribute3 matches value3 . 17.14.10.1. MAC (Ethernet) Protocol ID: mac Rules of this type should go into the root chain. Table 17.3. MAC protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to MAC address of sender dstmacaddr MAC_ADDR MAC address of destination dstmacmask MAC_MASK Mask applied to MAC address of destination protocolid UINT16 (0x600-0xffff), STRING Layer 3 protocol ID. Valid strings include [arp, rarp, ipv4, ipv6] comment STRING text string up to 256 characters The filter can be written as such: 17.14.10.2. VLAN (802.1Q) Protocol ID: vlan Rules of this type should go either into the root or vlan chain. Table 17.4. VLAN protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to MAC address of sender dstmacaddr MAC_ADDR MAC address of destination dstmacmask MAC_MASK Mask applied to MAC address of destination vlan-id UINT16 (0x0-0xfff, 0 - 4095) VLAN ID encap-protocol UINT16 (0x03c-0xfff), String Encapsulated layer 3 protocol ID, valid strings are arp, ipv4, ipv6 comment STRING text string up to 256 characters 17.14.10.3. STP (Spanning Tree Protocol) Protocol ID: stp Rules of this type should go either into the root or stp chain. Table 17.5. STP protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to MAC address of sender type UINT8 Bridge Protocol Data Unit (BPDU) type flags UINT8 BPDU flagdstmacmask root-priority UINT16 Root priority range start root-priority-hi UINT16 (0x0-0xfff, 0 - 4095) Root priority range end root-address MAC _ADDRESS root MAC Address root-address-mask MAC _MASK root MAC Address mask roor-cost UINT32 Root path cost (range start) root-cost-hi UINT32 Root path cost range end sender-priority-hi UINT16 Sender priority range end sender-address MAC_ADDRESS BPDU sender MAC address sender-address-mask MAC_MASK BPDU sender MAC address mask port UINT16 Port identifier (range start) port_hi UINT16 Port identifier range end msg-age UINT16 Message age timer (range start) msg-age-hi UINT16 Message age timer range end max-age-hi UINT16 Maximum age time range end hello-time UINT16 Hello time timer (range start) hello-time-hi UINT16 Hello time timer range end forward-delay UINT16 Forward delay (range start) forward-delay-hi UINT16 Forward delay range end comment STRING text string up to 256 characters 17.14.10.4. ARP/RARP Protocol ID: arp or rarp Rules of this type should either go into the root or arp/rarp chain. Table 17.6. ARP and RARP protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to MAC address of sender dstmacaddr MAC_ADDR MAC address of destination dstmacmask MAC_MASK Mask applied to MAC address of destination hwtype UINT16 Hardware type protocoltype UINT16 Protocol type opcode UINT16, STRING Opcode valid strings are: Request, Reply, Request_Reverse, Reply_Reverse, DRARP_Request, DRARP_Reply, DRARP_Error, InARP_Request, ARP_NAK arpsrcmacaddr MAC_ADDR Source MAC address in ARP/RARP packet arpdstmacaddr MAC _ADDR Destination MAC address in ARP/RARP packet arpsrcipaddr IP_ADDR Source IP address in ARP/RARP packet arpdstipaddr IP_ADDR Destination IP address in ARP/RARP packet gratuitous BOOLEAN Boolean indicating whether to check for a gratuitous ARP packet comment STRING text string up to 256 characters 17.14.10.5. IPv4 Protocol ID: ip Rules of this type should either go into the root or ipv4 chain. Table 17.7. IPv4 protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to MAC address of sender dstmacaddr MAC_ADDR MAC address of destination dstmacmask MAC_MASK Mask applied to MAC address of destination srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address protocol UINT8, STRING Layer 4 protocol identifier. Valid strings for protocol are: tcp, udp, udplite, esp, ah, icmp, igmp, sctp srcportstart UINT16 Start of range of valid source ports; requires protocol srcportend UINT16 End of range of valid source ports; requires protocol dstportstart UNIT16 Start of range of valid destination ports; requires protocol dstportend UNIT16 End of range of valid destination ports; requires protocol comment STRING text string up to 256 characters 17.14.10.6. IPv6 Protocol ID: ipv6 Rules of this type should either go into the root or ipv6 chain. Table 17.8. IPv6 protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to MAC address of sender dstmacaddr MAC_ADDR MAC address of destination dstmacmask MAC_MASK Mask applied to MAC address of destination srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address protocol UINT8, STRING Layer 4 protocol identifier. Valid strings for protocol are: tcp, udp, udplite, esp, ah, icmpv6, sctp scrportstart UNIT16 Start of range of valid source ports; requires protocol srcportend UINT16 End of range of valid source ports; requires protocol dstportstart UNIT16 Start of range of valid destination ports; requires protocol dstportend UNIT16 End of range of valid destination ports; requires protocol comment STRING text string up to 256 characters 17.14.10.7. TCP/UDP/SCTP Protocol ID: tcp, udp, sctp The chain parameter is ignored for this type of traffic and should either be omitted or set to root. Table 17.9. TCP/UDP/SCTP protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address scripto IP_ADDR Start of range of source IP address srcipfrom IP_ADDR End of range of source IP address dstipfrom IP_ADDR Start of range of destination IP address dstipto IP_ADDR End of range of destination IP address scrportstart UNIT16 Start of range of valid source ports; requires protocol srcportend UINT16 End of range of valid source ports; requires protocol dstportstart UNIT16 Start of range of valid destination ports; requires protocol dstportend UNIT16 End of range of valid destination ports; requires protocol comment STRING text string up to 256 characters state STRING comma separated list of NEW,ESTABLISHED,RELATED,INVALID or NONE flags STRING TCP-only: format of mask/flags with mask and flags each being a comma separated list of SYN,ACK,URG,PSH,FIN,RST or NONE or ALL ipset STRING The name of an IPSet managed outside of libvirt ipsetflags IPSETFLAGS flags for the IPSet; requires ipset attribute 17.14.10.8. ICMP Protocol ID: icmp Note: The chain parameter is ignored for this type of traffic and should either be omitted or set to root. Table 17.10. ICMP protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to the MAC address of the sender dstmacaddr MAD_ADDR MAC address of the destination dstmacmask MAC_MASK Mask applied to the MAC address of the destination srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address srcipfrom IP_ADDR start of range of source IP address scripto IP_ADDR end of range of source IP address dstipfrom IP_ADDR Start of range of destination IP address dstipto IP_ADDR End of range of destination IP address type UNIT16 ICMP type code UNIT16 ICMP code comment STRING text string up to 256 characters state STRING comma separated list of NEW,ESTABLISHED,RELATED,INVALID or NONE ipset STRING The name of an IPSet managed outside of libvirt ipsetflags IPSETFLAGS flags for the IPSet; requires ipset attribute 17.14.10.9. IGMP, ESP, AH, UDPLITE, 'ALL' Protocol ID: igmp, esp, ah, udplite, all The chain parameter is ignored for this type of traffic and should either be omitted or set to root. Table 17.11. IGMP, ESP, AH, UDPLITE, 'ALL' Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcmacmask MAC_MASK Mask applied to the MAC address of the sender dstmacaddr MAD_ADDR MAC address of the destination dstmacmask MAC_MASK Mask applied to the MAC address of the destination srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address srcipfrom IP_ADDR start of range of source IP address scripto IP_ADDR end of range of source IP address dstipfrom IP_ADDR Start of range of destination IP address dstipto IP_ADDR End of range of destination IP address comment STRING text string up to 256 characters state STRING comma separated list of NEW,ESTABLISHED,RELATED,INVALID or NONE ipset STRING The name of an IPSet managed outside of libvirt ipsetflags IPSETFLAGS flags for the IPSet; requires ipset attribute 17.14.10.10. TCP/UDP/SCTP over IPV6 Protocol ID: tcp-ipv6, udp-ipv6, sctp-ipv6 The chain parameter is ignored for this type of traffic and should either be omitted or set to root. Table 17.12. TCP, UDP, SCTP over IPv6 protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address srcipfrom IP_ADDR start of range of source IP address scripto IP_ADDR end of range of source IP address dstipfrom IP_ADDR Start of range of destination IP address dstipto IP_ADDR End of range of destination IP address srcportstart UINT16 Start of range of valid source ports srcportend UINT16 End of range of valid source ports dstportstart UINT16 Start of range of valid destination ports dstportend UINT16 End of range of valid destination ports comment STRING text string up to 256 characters state STRING comma separated list of NEW,ESTABLISHED,RELATED,INVALID or NONE ipset STRING The name of an IPSet managed outside of libvirt ipsetflags IPSETFLAGS flags for the IPSet; requires ipset attribute 17.14.10.11. ICMPv6 Protocol ID: icmpv6 The chain parameter is ignored for this type of traffic and should either be omitted or set to root. Table 17.13. ICMPv6 protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address srcipfrom IP_ADDR start of range of source IP address scripto IP_ADDR end of range of source IP address dstipfrom IP_ADDR Start of range of destination IP address dstipto IP_ADDR End of range of destination IP address type UINT16 ICMPv6 type code UINT16 ICMPv6 code comment STRING text string up to 256 characters state STRING comma separated list of NEW,ESTABLISHED,RELATED,INVALID or NONE ipset STRING The name of an IPSet managed outside of libvirt ipsetflags IPSETFLAGS flags for the IPSet; requires ipset attribute 17.14.10.12. IGMP, ESP, AH, UDPLITE, 'ALL' over IPv6 Protocol ID: igmp-ipv6, esp-ipv6, ah-ipv6, udplite-ipv6, all-ipv6 The chain parameter is ignored for this type of traffic and should either be omitted or set to root. Table 17.14. IGMP, ESP, AH, UDPLITE, 'ALL' over IPv6 protocol types Attribute Name Datatype Definition srcmacaddr MAC_ADDR MAC address of sender srcipaddr IP_ADDR Source IP address srcipmask IP_MASK Mask applied to source IP address dstipaddr IP_ADDR Destination IP address dstipmask IP_MASK Mask applied to destination IP address srcipfrom IP_ADDR start of range of source IP address scripto IP_ADDR end of range of source IP address dstipfrom IP_ADDR Start of range of destination IP address dstipto IP_ADDR End of range of destination IP address comment STRING text string up to 256 characters state STRING comma separated list of NEW,ESTABLISHED,RELATED,INVALID or NONE ipset STRING The name of an IPSet managed outside of libvirt ipsetflags IPSETFLAGS flags for the IPSet; requires ipset attribute 17.14.11. Advanced Filter Configuration Topics The following sections discuss advanced filter configuration topics. 17.14.11.1. Connection tracking The network filtering subsystem (on Linux) makes use of the connection tracking support of IP tables. This helps in enforcing the direction of the network traffic (state match) as well as counting and limiting the number of simultaneous connections towards a guest virtual machine. As an example, if a guest virtual machine has TCP port 8080 open as a server, clients may connect to the guest virtual machine on port 8080. Connection tracking and enforcement of the direction and then prevents the guest virtual machine from initiating a connection from (TCP client) port 8080 to the host physical machine back to a remote host physical machine. More importantly, tracking helps to prevent remote attackers from establishing a connection back to a guest virtual machine. For example, if the user inside the guest virtual machine established a connection to port 80 on an attacker site, the attacker will not be able to initiate a connection from TCP port 80 back towards the guest virtual machine. By default the connection state match that enables connection tracking and then enforcement of the direction of traffic is turned on. Example 17.9. XML example for turning off connections to the TCP port The following shows an example XML fragment where this feature has been turned off for incoming connections to TCP port 12345. This now allows incoming traffic to TCP port 12345, but would also enable the initiation from (client) TCP port 12345 within the VM, which may or may not be desirable. 17.14.11.2. Limiting number of connections To limit the number of connections a guest virtual machine may establish, a rule must be provided that sets a limit of connections for a given type of traffic. If for example a VM is supposed to be allowed to only ping one other IP address at a time and is supposed to have only one active incoming ssh connection at a time. Example 17.10. XML sample file that sets limits to connections The following XML fragment can be used to limit connections Note Limitation rules must be listed in the XML prior to the rules for accepting traffic. According to the XML file in Example 17.10, "XML sample file that sets limits to connections" , an additional rule for allowing DNS traffic sent to port 22 go out the guest virtual machine, has been added to avoid ssh sessions not getting established for reasons related to DNS lookup failures by the ssh daemon. Leaving this rule out may result in the ssh client hanging unexpectedly as it tries to connect. Additional caution should be used in regards to handling timeouts related to tracking of traffic. An ICMP ping that the user may have terminated inside the guest virtual machine may have a long timeout in the host physical machine's connection tracking system and will therefore not allow another ICMP ping to go through. The best solution is to tune the timeout in the host physical machine's sysfs with the following command:# echo 3 > /proc/sys/net/netfilter/nf_conntrack_icmp_timeout . This command sets the ICMP connection tracking timeout to 3 seconds. The effect of this is that once one ping is terminated, another one can start after 3 seconds. If for any reason the guest virtual machine has not properly closed its TCP connection, the connection to be held open for a longer period of time, especially if the TCP timeout value was set for a large amount of time on the host physical machine. In addition, any idle connection may result in a timeout in the connection tracking system which can be re-activated once packets are exchanged. However, if the limit is set too low, newly initiated connections may force an idle connection into TCP backoff. Therefore, the limit of connections should be set rather high so that fluctuations in new TCP connections do not cause odd traffic behavior in relation to idle connections. 17.14.11.3. Command-line tools virsh has been extended with life-cycle support for network filters. All commands related to the network filtering subsystem start with the prefix nwfilter . The following commands are available: nwfilter-list : lists UUIDs and names of all network filters nwfilter-define : defines a new network filter or updates an existing one (must supply a name) nwfilter-undefine : deletes a specified network filter (must supply a name). Do not delete a network filter currently in use. nwfilter-dumpxml : displays a specified network filter (must supply a name) nwfilter-edit : edits a specified network filter (must supply a name) 17.14.11.4. Pre-existing network filters The following is a list of example network filters that are automatically installed with libvirt: Table 17.15. ICMPv6 protocol types Protocol Name Description allow-arp Accepts all incoming and outgoing Address Resolution Protocol (ARP) traffic to a guest virtual machine. no-arp-spoofing , no-arp-mac-spoofing , and no-arp-ip-spoofing These filters prevent a guest virtual machine from spoofing ARP traffic. In addition, they only allows ARP request and reply messages, and enforce that those packets contain: no-arp-spoofing - the MAC and IP addresses of the guest no-arp-mac-spoofing - the MAC address of the guest no-arp-ip-spoofing - the IP address of the guest low-dhcp Allows a guest virtual machine to request an IP address via DHCP (from any DHCP server). low-dhcp-server Allows a guest virtual machine to request an IP address from a specified DHCP server. The dotted decimal IP address of the DHCP server must be provided in a reference to this filter. The name of the variable must be DHCPSERVER . low-ipv4 Accepts all incoming and outgoing IPv4 traffic to a virtual machine. low-incoming-ipv4 Accepts only incoming IPv4 traffic to a virtual machine. This filter is a part of the clean-traffic filter. no-ip-spoofing Prevents a guest virtual machine from sending IP packets with a source IP address different from the one inside the packet. This filter is a part of the clean-traffic filter. no-ip-multicast Prevents a guest virtual machine from sending IP multicast packets. no-mac-broadcast Prevents outgoing IPv4 traffic to a specified MAC address. This filter is a part of the clean-traffic filter. no-other-l2-traffic Prevents all layer 2 networking traffic except traffic specified by other filters used by the network. This filter is a part of the clean-traffic filter. no-other-rarp-traffic , qemu-announce-self , qemu-announce-self-rarp These filters allow QEMU's self-announce Reverse Address Resolution Protocol (RARP) packets, but prevent all other RARP traffic. All of them are also included in the clean-traffic filter. clean-traffic Prevents MAC, IP and ARP spoofing. This filter references several other filters as building blocks. These filters are only building blocks and require a combination with other filters to provide useful network traffic filtering. The most used one in the above list is the clean-traffic filter. This filter itself can for example be combined with the no-ip-multicast filter to prevent virtual machines from sending IP multicast traffic on top of the prevention of packet spoofing. 17.14.11.5. Writing your own filters Since libvirt only provides a couple of example networking filters, you may consider writing your own. When planning on doing so there are a couple of things you may need to know regarding the network filtering subsystem and how it works internally. Certainly you also have to know and understand the protocols very well that you want to be filtering on so that no further traffic than what you want can pass and that in fact the traffic you want to allow does pass. The network filtering subsystem is currently only available on Linux host physical machines and only works for QEMU and KVM type of virtual machines. On Linux, it builds upon the support for ebtables, iptables and ip6tables and makes use of their features. Considering the list found in Section 17.14.10, "Supported Protocols" the following protocols can be implemented using ebtables: mac stp (spanning tree protocol) vlan (802.1Q) arp, rarp ipv4 ipv6 Any protocol that runs over IPv4 is supported using iptables, those over IPv6 are implemented using ip6tables. Using a Linux host physical machine, all traffic filtering rules created by libvirt's network filtering subsystem first passes through the filtering support implemented by ebtables and only afterwards through iptables or ip6tables filters. If a filter tree has rules with the protocols including: mac, stp, vlan arp, rarp, ipv4, or ipv6; the ebtable rules and values listed will automatically be used first. Multiple chains for the same protocol can be created. The name of the chain must have a prefix of one of the previously enumerated protocols. To create an additional chain for handling of ARP traffic, a chain with name arp-test, can for example be specified. As an example, it is possible to filter on UDP traffic by source and destination ports using the ip protocol filter and specifying attributes for the protocol, source and destination IP addresses and ports of UDP packets that are to be accepted. This allows early filtering of UDP traffic with ebtables. However, once an IP or IPv6 packet, such as a UDP packet, has passed the ebtables layer and there is at least one rule in a filter tree that instantiates iptables or ip6tables rules, a rule to let the UDP packet pass will also be necessary to be provided for those filtering layers. This can be achieved with a rule containing an appropriate udp or udp-ipv6 traffic filtering node. Example 17.11. Creating a custom filter Suppose a filter is needed to fulfill the following list of requirements: prevents a VM's interface from MAC, IP and ARP spoofing opens only TCP ports 22 and 80 of a VM's interface allows the VM to send ping traffic from an interface but not let the VM be pinged on the interface allows the VM to do DNS lookups (UDP towards port 53) The requirement to prevent spoofing is fulfilled by the existing clean-traffic network filter, thus the way to do this is to reference it from a custom filter. To enable traffic for TCP ports 22 and 80, two rules are added to enable this type of traffic. To allow the guest virtual machine to send ping traffic a rule is added for ICMP traffic. For simplicity reasons, general ICMP traffic will be allowed to be initiated from the guest virtual machine, and will not be specified to ICMP echo request and response messages. All other traffic will be prevented to reach or be initiated by the guest virtual machine. To do this a rule will be added that drops all other traffic. Assuming the guest virtual machine is called test and the interface to associate our filter with is called eth0 , a filter is created named test-eth0 . The result of these considerations is the following network filter XML: 17.14.11.6. Sample custom filter Although one of the rules in the above XML contains the IP address of the guest virtual machine as either a source or a destination address, the filtering of the traffic works correctly. The reason is that whereas the rule's evaluation occurs internally on a per-interface basis, the rules are additionally evaluated based on which (tap) interface has sent or will receive the packet, rather than what their source or destination IP address may be. Example 17.12. Sample XML for network interface descriptions An XML fragment for a possible network interface description inside the domain XML of the test guest virtual machine could then look like this: To more strictly control the ICMP traffic and enforce that only ICMP echo requests can be sent from the guest virtual machine and only ICMP echo responses be received by the guest virtual machine, the above ICMP rule can be replaced with the following two rules: Example 17.13. Second example custom filter This example demonstrates how to build a similar filter as in the example above, but extends the list of requirements with an ftp server located inside the guest virtual machine. The requirements for this filter are: prevents a guest virtual machine's interface from MAC, IP, and ARP spoofing opens only TCP ports 22 and 80 in a guest virtual machine's interface allows the guest virtual machine to send ping traffic from an interface but does not allow the guest virtual machine to be pinged on the interface allows the guest virtual machine to do DNS lookups (UDP towards port 53) enables the ftp server (in active mode) so it can run inside the guest virtual machine The additional requirement of allowing an FTP server to be run inside the guest virtual machine maps into the requirement of allowing port 21 to be reachable for FTP control traffic as well as enabling the guest virtual machine to establish an outgoing TCP connection originating from the guest virtual machine's TCP port 20 back to the FTP client (FTP active mode). There are several ways of how this filter can be written and two possible solutions are included in this example. The first solution makes use of the state attribute of the TCP protocol that provides a hook into the connection tracking framework of the Linux host physical machine. For the guest virtual machine-initiated FTP data connection (FTP active mode) the RELATED state is used to enable detection that the guest virtual machine-initiated FTP data connection is a consequence of ( or 'has a relationship with' ) an existing FTP control connection, thereby allowing it to pass packets through the firewall. The RELATED state, however, is only valid for the very first packet of the outgoing TCP connection for the FTP data path. Afterwards, the state is ESTABLISHED, which then applies equally to the incoming and outgoing direction. All this is related to the FTP data traffic originating from TCP port 20 of the guest virtual machine. This then leads to the following solution: Before trying out a filter using the RELATED state, you have to make sure that the appropriate connection tracking module has been loaded into the host physical machine's kernel. Depending on the version of the kernel, you must run either one of the following two commands before the FTP connection with the guest virtual machine is established: modprobe nf_conntrack_ftp - where available OR modprobe ip_conntrack_ftp if above is not available If protocols other than FTP are used in conjunction with the RELATED state, their corresponding module must be loaded. Modules are available for the protocols: ftp, tftp, irc, sip, sctp, and amanda. The second solution makes use of the state flags of connections more than the solution did. This solution takes advantage of the fact that the NEW state of a connection is valid when the very first packet of a traffic flow is detected. Subsequently, if the very first packet of a flow is accepted, the flow becomes a connection and thus enters into the ESTABLISHED state. Therefore, a general rule can be written for allowing packets of ESTABLISHED connections to reach the guest virtual machine or be sent by the guest virtual machine. This is done writing specific rules for the very first packets identified by the NEW state and dictates the ports that the data is acceptable. All packets meant for ports that are not explicitly accepted are dropped, thus not reaching an ESTABLISHED state. Any subsequent packets sent from that port are dropped as well. 17.14.12. Limitations The following is a list of the currently known limitations of the network filtering subsystem. VM migration is only supported if the whole filter tree that is referenced by a guest virtual machine's top level filter is also available on the target host physical machine. The network filter clean-traffic for example should be available on all libvirt installations and thus enable migration of guest virtual machines that reference this filter. To assure version compatibility is not a problem make sure you are using the most current version of libvirt by updating the package regularly. Migration must occur between libvirt insallations of version 0.8.1 or later in order not to lose the network traffic filters associated with an interface. VLAN (802.1Q) packets, if sent by a guest virtual machine, cannot be filtered with rules for protocol IDs arp, rarp, ipv4 and ipv6. They can only be filtered with protocol IDs, MAC and VLAN. Therefore, the example filter clean-traffic Example 17.1, "An example of network filtering" will not work as expected.	[ "<devices> <interface type='bridge'> <mac address='00:16:3e:5d:c7:9e'/> <filterref filter='clean-traffic'/> </interface> </devices>", "<devices> <interface type='bridge'> <mac address='00:16:3e:5d:c7:9e'/> <filterref filter='clean-traffic'> <parameter name='IP' value='10.0.0.1'/> </filterref> </interface> </devices>", "<filter name='no-arp-spoofing' chain='arp' priority='-500'> <uuid>f88f1932-debf-4aa1-9fbe-f10d3aa4bc95</uuid> <rule action='drop' direction='out' priority='300'> <mac match='no' srcmacaddr='USDMAC'/> </rule> <rule action='drop' direction='out' priority='350'> <arp match='no' arpsrcmacaddr='USDMAC'/> </rule> <rule action='drop' direction='out' priority='400'> <arp match='no' arpsrcipaddr='USDIP'/> </rule> <rule action='drop' direction='in' priority='450'> <arp opcode='Reply'/> <arp match='no' arpdstmacaddr='USDMAC'/> </rule> <rule action='drop' direction='in' priority='500'> <arp match='no' arpdstipaddr='USDIP'/> </rule> <rule action='accept' direction='inout' priority='600'> <arp opcode='Request'/> </rule> <rule action='accept' direction='inout' priority='650'> <arp opcode='Reply'/> </rule> <rule action='drop' direction='inout' priority='1000'/> </filter>", "<devices> <interface type='bridge'> <mac address='00:16:3e:5d:c7:9e'/> <filterref filter='clean-traffic'> <parameter name='IP' value='10.0.0.1'/> <parameter name='IP' value='10.0.0.2'/> <parameter name='IP' value='10.0.0.3'/> </filterref> </interface> </devices>", "<rule action='accept' direction='in' priority='500'> <tcp srpipaddr='USDIP'/> </rule>", "<rule action='accept' direction='in' priority='500'> <udp dstportstart='USDDSTPORTS[1]'/> </rule>", "<rule action='accept' direction='in' priority='500'> <ip srcipaddr='USDSRCIPADDRESSES[@1]' dstportstart='USDDSTPORTS[@2]'/> </rule>", "SRCIPADDRESSES = [ 10.0.0.1, 11.1.2.3 ] DSTPORTS = [ 80, 8080 ]", "<interface type='bridge'> <source bridge='virbr0'/> <filterref filter='clean-traffic'> <parameter name='CTRL_IP_LEARNING' value='dhcp'/> </filterref> </interface>", "<filter name='clean-traffic'> <uuid>6ef53069-ba34-94a0-d33d-17751b9b8cb1</uuid> <filterref filter='no-mac-spoofing'/> <filterref filter='no-ip-spoofing'/> <filterref filter='allow-incoming-ipv4'/> <filterref filter='no-arp-spoofing'/> <filterref filter='no-other-l2-traffic'/> <filterref filter='qemu-announce-self'/> </filter>", "<filter name='no-ip-spoofing' chain='ipv4'> <uuid>fce8ae33-e69e-83bf-262e-30786c1f8072</uuid> <rule action='drop' direction='out' priority='500'> <ip match='no' srcipaddr='USDIP'/> </rule> </filter>", "[...] <rule action='drop' direction='in'> <protocol match='no' attribute1='value1' attribute2='value2'/> <protocol attribute3='value3'/> </rule> [...]", "[...] <mac match='no' srcmacaddr='USDMAC'/> [...]", "[...] <rule direction='in' action='accept' statematch='false'> <cp dstportstart='12345'/> </rule> [...]", "[...] <rule action='drop' direction='in' priority='400'> <tcp connlimit-above='1'/> </rule> <rule action='accept' direction='in' priority='500'> <tcp dstportstart='22'/> </rule> <rule action='drop' direction='out' priority='400'> <icmp connlimit-above='1'/> </rule> <rule action='accept' direction='out' priority='500'> <icmp/> </rule> <rule action='accept' direction='out' priority='500'> <udp dstportstart='53'/> </rule> <rule action='drop' direction='inout' priority='1000'> <all/> </rule> [...]", "<filter name='test-eth0'> <!- - This rule references the clean traffic filter to prevent MAC, IP and ARP spoofing. By not providing an IP address parameter, libvirt will detect the IP address the guest virtual machine is using. - -> <filterref filter='clean-traffic'/> <!- - This rule enables TCP ports 22 (ssh) and 80 (http) to be reachable - -> <rule action='accept' direction='in'> <tcp dstportstart='22'/> </rule> <rule action='accept' direction='in'> <tcp dstportstart='80'/> </rule> <!- - This rule enables general ICMP traffic to be initiated by the guest virtual machine including ping traffic - -> <rule action='accept' direction='out'> <icmp/> </rule>> <!- - This rule enables outgoing DNS lookups using UDP - -> <rule action='accept' direction='out'> <udp dstportstart='53'/> </rule> <!- - This rule drops all other traffic - -> <rule action='drop' direction='inout'> <all/> </rule> </filter>", "[...] <interface type='bridge'> <source bridge='mybridge'/> <filterref filter='test-eth0'/> </interface> [...]", "<!- - enable outgoing ICMP echo requests- -> <rule action='accept' direction='out'> <icmp type='8'/> </rule>", "<!- - enable incoming ICMP echo replies- -> <rule action='accept' direction='in'> <icmp type='0'/> </rule>", "<filter name='test-eth0'> <!- - This filter (eth0) references the clean traffic filter to prevent MAC, IP, and ARP spoofing. By not providing an IP address parameter, libvirt will detect the IP address the guest virtual machine is using. - -> <filterref filter='clean-traffic'/> <!- - This rule enables TCP port 21 (FTP-control) to be reachable - -> <rule action='accept' direction='in'> <tcp dstportstart='21'/> </rule> <!- - This rule enables TCP port 20 for guest virtual machine-initiated FTP data connection related to an existing FTP control connection - -> <rule action='accept' direction='out'> <tcp srcportstart='20' state='RELATED,ESTABLISHED'/> </rule> <!- - This rule accepts all packets from a client on the FTP data connection - -> <rule action='accept' direction='in'> <tcp dstportstart='20' state='ESTABLISHED'/> </rule> <!- - This rule enables TCP port 22 (SSH) to be reachable - -> <rule action='accept' direction='in'> <tcp dstportstart='22'/> </rule> <!- -This rule enables TCP port 80 (HTTP) to be reachable - -> <rule action='accept' direction='in'> <tcp dstportstart='80'/> </rule> <!- - This rule enables general ICMP traffic to be initiated by the guest virtual machine, including ping traffic - -> <rule action='accept' direction='out'> <icmp/> </rule> <!- - This rule enables outgoing DNS lookups using UDP - -> <rule action='accept' direction='out'> <udp dstportstart='53'/> </rule> <!- - This rule drops all other traffic - -> <rule action='drop' direction='inout'> <all/> </rule> </filter>", "<filter name='test-eth0'> <!- - This filter references the clean traffic filter to prevent MAC, IP and ARP spoofing. By not providing and IP address parameter, libvirt will detect the IP address the VM is using. - -> <filterref filter='clean-traffic'/> <!- - This rule allows the packets of all previously accepted connections to reach the guest virtual machine - -> <rule action='accept' direction='in'> <all state='ESTABLISHED'/> </rule> <!- - This rule allows the packets of all previously accepted and related connections be sent from the guest virtual machine - -> <rule action='accept' direction='out'> <all state='ESTABLISHED,RELATED'/> </rule> <!- - This rule enables traffic towards port 21 (FTP) and port 22 (SSH)- -> <rule action='accept' direction='in'> <tcp dstportstart='21' dstportend='22' state='NEW'/> </rule> <!- - This rule enables traffic towards port 80 (HTTP) - -> <rule action='accept' direction='in'> <tcp dstportstart='80' state='NEW'/> </rule> <!- - This rule enables general ICMP traffic to be initiated by the guest virtual machine, including ping traffic - -> <rule action='accept' direction='out'> <icmp state='NEW'/> </rule> <!- - This rule enables outgoing DNS lookups using UDP - -> <rule action='accept' direction='out'> <udp dstportstart='53' state='NEW'/> </rule> <!- - This rule drops all other traffic - -> <rule action='drop' direction='inout'> <all/> </rule> </filter>" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/virtualization_deployment_and_administration_guide/sect-Virtual_Networking-Applying_network_filtering
Chapter 14. ImageTagMirrorSet [config.openshift.io/v1]	Chapter 14. ImageTagMirrorSet [config.openshift.io/v1] Description ImageTagMirrorSet holds cluster-wide information about how to handle registry mirror rules on using tag pull specification. When multiple policies are defined, the outcome of the behavior is defined on each field. Compatibility level 1: Stable within a major release for a minimum of 12 months or 3 minor releases (whichever is longer). Type object Required spec 14.1. Specification Property Type Description apiVersion string APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#resources kind string Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds metadata ObjectMeta Standard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata spec object spec holds user settable values for configuration status object status contains the observed state of the resource. 14.1.1. .spec Description spec holds user settable values for configuration Type object Property Type Description imageTagMirrors array imageTagMirrors allows images referenced by image tags in pods to be pulled from alternative mirrored repository locations. The image pull specification provided to the pod will be compared to the source locations described in imageTagMirrors and the image may be pulled down from any of the mirrors in the list instead of the specified repository allowing administrators to choose a potentially faster mirror. To use mirrors to pull images using digest specification only, users should configure a list of mirrors using "ImageDigestMirrorSet" CRD. If the image pull specification matches the repository of "source" in multiple imagetagmirrorset objects, only the objects which define the most specific namespace match will be used. For example, if there are objects using quay.io/libpod and quay.io/libpod/busybox as the "source", only the objects using quay.io/libpod/busybox are going to apply for pull specification quay.io/libpod/busybox. Each "source" repository is treated independently; configurations for different "source" repositories don't interact. If the "mirrors" is not specified, the image will continue to be pulled from the specified repository in the pull spec. When multiple policies are defined for the same "source" repository, the sets of defined mirrors will be merged together, preserving the relative order of the mirrors, if possible. For example, if policy A has mirrors a, b, c and policy B has mirrors c, d, e , the mirrors will be used in the order a, b, c, d, e . If the orders of mirror entries conflict (e.g. a, b vs. b, a ) the configuration is not rejected but the resulting order is unspecified. Users who want to use a deterministic order of mirrors, should configure them into one list of mirrors using the expected order. imageTagMirrors[] object ImageTagMirrors holds cluster-wide information about how to handle mirrors in the registries config. 14.1.2. .spec.imageTagMirrors Description imageTagMirrors allows images referenced by image tags in pods to be pulled from alternative mirrored repository locations. The image pull specification provided to the pod will be compared to the source locations described in imageTagMirrors and the image may be pulled down from any of the mirrors in the list instead of the specified repository allowing administrators to choose a potentially faster mirror. To use mirrors to pull images using digest specification only, users should configure a list of mirrors using "ImageDigestMirrorSet" CRD. If the image pull specification matches the repository of "source" in multiple imagetagmirrorset objects, only the objects which define the most specific namespace match will be used. For example, if there are objects using quay.io/libpod and quay.io/libpod/busybox as the "source", only the objects using quay.io/libpod/busybox are going to apply for pull specification quay.io/libpod/busybox. Each "source" repository is treated independently; configurations for different "source" repositories don't interact. If the "mirrors" is not specified, the image will continue to be pulled from the specified repository in the pull spec. When multiple policies are defined for the same "source" repository, the sets of defined mirrors will be merged together, preserving the relative order of the mirrors, if possible. For example, if policy A has mirrors a, b, c and policy B has mirrors c, d, e , the mirrors will be used in the order a, b, c, d, e . If the orders of mirror entries conflict (e.g. a, b vs. b, a ) the configuration is not rejected but the resulting order is unspecified. Users who want to use a deterministic order of mirrors, should configure them into one list of mirrors using the expected order. Type array 14.1.3. .spec.imageTagMirrors[] Description ImageTagMirrors holds cluster-wide information about how to handle mirrors in the registries config. Type object Required source Property Type Description mirrorSourcePolicy string mirrorSourcePolicy defines the fallback policy if fails to pull image from the mirrors. If unset, the image will continue to be pulled from the repository in the pull spec. sourcePolicy is valid configuration only when one or more mirrors are in the mirror list. mirrors array (string) mirrors is zero or more locations that may also contain the same images. No mirror will be configured if not specified. Images can be pulled from these mirrors only if they are referenced by their tags. The mirrored location is obtained by replacing the part of the input reference that matches source by the mirrors entry, e.g. for registry.redhat.io/product/repo reference, a (source, mirror) pair .redhat.io, mirror.local/redhat causes a mirror.local/redhat/product/repo repository to be used. Pulling images by tag can potentially yield different images, depending on which endpoint we pull from. Configuring a list of mirrors using "ImageDigestMirrorSet" CRD and forcing digest-pulls for mirrors avoids that issue. The order of mirrors in this list is treated as the user's desired priority, while source is by default considered lower priority than all mirrors. If no mirror is specified or all image pulls from the mirror list fail, the image will continue to be pulled from the repository in the pull spec unless explicitly prohibited by "mirrorSourcePolicy". Other cluster configuration, including (but not limited to) other imageTagMirrors objects, may impact the exact order mirrors are contacted in, or some mirrors may be contacted in parallel, so this should be considered a preference rather than a guarantee of ordering. "mirrors" uses one of the following formats: host[:port] host[:port]/namespace[/namespace...] host[:port]/namespace[/namespace...]/repo for more information about the format, see the document about the location field: https://github.com/containers/image/blob/main/docs/containers-registries.conf.5.md#choosing-a-registry-toml-table source string source matches the repository that users refer to, e.g. in image pull specifications. Setting source to a registry hostname e.g. docker.io. quay.io, or registry.redhat.io, will match the image pull specification of corressponding registry. "source" uses one of the following formats: host[:port] host[:port]/namespace[/namespace...] host[:port]/namespace[/namespace...]/repo [.]host for more information about the format, see the document about the location field: https://github.com/containers/image/blob/main/docs/containers-registries.conf.5.md#choosing-a-registry-toml-table 14.1.4. .status Description status contains the observed state of the resource. Type object 14.2. API endpoints The following API endpoints are available: /apis/config.openshift.io/v1/imagetagmirrorsets DELETE : delete collection of ImageTagMirrorSet GET : list objects of kind ImageTagMirrorSet POST : create an ImageTagMirrorSet /apis/config.openshift.io/v1/imagetagmirrorsets/{name} DELETE : delete an ImageTagMirrorSet GET : read the specified ImageTagMirrorSet PATCH : partially update the specified ImageTagMirrorSet PUT : replace the specified ImageTagMirrorSet /apis/config.openshift.io/v1/imagetagmirrorsets/{name}/status GET : read status of the specified ImageTagMirrorSet PATCH : partially update status of the specified ImageTagMirrorSet PUT : replace status of the specified ImageTagMirrorSet 14.2.1. /apis/config.openshift.io/v1/imagetagmirrorsets HTTP method DELETE Description delete collection of ImageTagMirrorSet Table 14.1. HTTP responses HTTP code Reponse body 200 - OK Status schema 401 - Unauthorized Empty HTTP method GET Description list objects of kind ImageTagMirrorSet Table 14.2. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSetList schema 401 - Unauthorized Empty HTTP method POST Description create an ImageTagMirrorSet Table 14.3. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 14.4. Body parameters Parameter Type Description body ImageTagMirrorSet schema Table 14.5. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSet schema 201 - Created ImageTagMirrorSet schema 202 - Accepted ImageTagMirrorSet schema 401 - Unauthorized Empty 14.2.2. /apis/config.openshift.io/v1/imagetagmirrorsets/{name} Table 14.6. Global path parameters Parameter Type Description name string name of the ImageTagMirrorSet HTTP method DELETE Description delete an ImageTagMirrorSet Table 14.7. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed Table 14.8. HTTP responses HTTP code Reponse body 200 - OK Status schema 202 - Accepted Status schema 401 - Unauthorized Empty HTTP method GET Description read the specified ImageTagMirrorSet Table 14.9. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSet schema 401 - Unauthorized Empty HTTP method PATCH Description partially update the specified ImageTagMirrorSet Table 14.10. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 14.11. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSet schema 401 - Unauthorized Empty HTTP method PUT Description replace the specified ImageTagMirrorSet Table 14.12. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 14.13. Body parameters Parameter Type Description body ImageTagMirrorSet schema Table 14.14. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSet schema 201 - Created ImageTagMirrorSet schema 401 - Unauthorized Empty 14.2.3. /apis/config.openshift.io/v1/imagetagmirrorsets/{name}/status Table 14.15. Global path parameters Parameter Type Description name string name of the ImageTagMirrorSet HTTP method GET Description read status of the specified ImageTagMirrorSet Table 14.16. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSet schema 401 - Unauthorized Empty HTTP method PATCH Description partially update status of the specified ImageTagMirrorSet Table 14.17. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 14.18. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSet schema 401 - Unauthorized Empty HTTP method PUT Description replace status of the specified ImageTagMirrorSet Table 14.19. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 14.20. Body parameters Parameter Type Description body ImageTagMirrorSet schema Table 14.21. HTTP responses HTTP code Reponse body 200 - OK ImageTagMirrorSet schema 201 - Created ImageTagMirrorSet schema 401 - Unauthorized Empty	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.15/html/config_apis/imagetagmirrorset-config-openshift-io-v1
10. Kernel	10. Kernel Kdump Auto Enablement Kdump is now enabled by default on systems with large amounts of memory. Specifically, kdump is enabled by default on: systems with more than 4GB of memory on architectures with a 4KB page size (i.e. x86 or x86_64), or systems with more than 8GB of memory on architectures with larger than a 4KB page size (i.e PPC64). On systems with less than the above memory configurations, kdump is not auto enabled. Refer to /usr/share/doc/kexec-tools-2.0.0/kexec-kdump-howto.txt for instructions on enabling kdump on these systems. crashkernel parameter syntax Please note that in future versions of Red Hat Enterprise Linux 6 (i.e. Red Hat Enterprise Linux 6.1 and later) the auto value setting of the crashkernel= parameter (i.e. crashkernel=auto ) will be deprecated. Barrier Implementation in the Kernel The barrier implementation in the Red Hat Enterprise Linux 6 kernel works by completely draining the I/O scheduler's queue, then issuing a preflush, a barrier, and finally a postflush request. However, since the supported file systems in Red Hat Enterprise Linux 6 all implement their own ordering guarantees, the block layer need only provide a mechanism to ensure that a barrier request is ordered with respect to other I/O already in the disk cache. This mechanism avoids I/O stalls experienced by queue draining. The block layer will be updated in future kernels to provide this more efficient mechanism of ensuring ordering. Workloads that include heavy fsync or metadata activity will see an overall improvement in disk performance. Users taking advantage of the proportional weight I/O controller will also see a boost in performance. In preparation for the block layer updates, third party file system developers need to ensure that data ordering surrounding journal commits are handled within the file system itself, since the block layer will no longer provide this functionality. These future block layer improvements will change some kernel interfaces such that symbols which are not on the kABI whitelist shall be modified. This may result in the need to recompile third party file system or storage drivers. Systemtap Tracepoints The following 3 virtual memory tracepoints are deprecated in Red Hat Enterprise Linux 6 trace_mm_background_writeout(unsigned long written) trace_mm_olddata_writeout(unsigned long written) trace_mm_balancedirty_writeout(unsigned long written) 10.1. Technology Previews Remote Audit Logging The audit package contains the user space utilities for storing and searching the audit records generated by the audit subsystem in the Linux 2.6 kernel. Within the audispd-plugins subpackage is a utility that allows for the transmission of audit events to a remote aggregating machine. This remote audit logging application, audisp-remote, is considered a Technology Preview in Red Hat Enterprise Linux 6. Linux (NameSpace) Container [LXC] Linux (NameSpace) Containers [LXC] is a Technology Preview feature in Red Hat Enterprise Linux 6 Beta that provides isolation of resources assigned to one or more processes. A process is assigned a separate user permission, networking, filesystem name space from its parent.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.0_technical_notes/kernel
Chapter 2. Installing the Self-hosted Engine Deployment Host	Chapter 2. Installing the Self-hosted Engine Deployment Host A self-hosted engine can be deployed from a Red Hat Virtualization Host or a Red Hat Enterprise Linux host . Important If you plan to use bonded interfaces for high availability or VLANs to separate different types of traffic (for example, for storage or management connections), you should configure them on the host before beginning the self-hosted engine deployment. See Networking Recommendations in the Planning and Prerequisites Guide . 2.1. Installing Red Hat Virtualization Hosts Red Hat Virtualization Host (RHVH) is a minimal operating system based on Red Hat Enterprise Linux that is designed to provide a simple method for setting up a physical machine to act as a hypervisor in a Red Hat Virtualization environment. The minimal operating system contains only the packages required for the machine to act as a hypervisor, and features a Cockpit web interface for monitoring the host and performing administrative tasks. See Running Cockpit for the minimum browser requirements. RHVH supports NIST 800-53 partitioning requirements to improve security. RHVH uses a NIST 800-53 partition layout by default. The host must meet the minimum host requirements . Warning When installing or reinstalling the host's operating system, Red Hat strongly recommends that you first detach any existing non-OS storage that is attached to the host to avoid accidental initialization of these disks, and with that, potential data loss. Procedure Go to the Get Started with Red Hat Virtualization on the Red Hat Customer Portal and log in. Click Download Latest to access the product download page. Choose the appropriate Hypervisor Image for RHV from the list and click Download Now . Start the machine on which you are installing RHVH, booting from the prepared installation media. From the boot menu, select Install RHVH 4.4 and press Enter . Note You can also press the Tab key to edit the kernel parameters. Kernel parameters must be separated by a space, and you can boot the system using the specified kernel parameters by pressing the Enter key. Press the Esc key to clear any changes to the kernel parameters and return to the boot menu. Select a language, and click Continue . Select a keyboard layout from the Keyboard Layout screen and click Done . Select the device on which to install RHVH from the Installation Destination screen. Optionally, enable encryption. Click Done . Important Use the Automatically configure partitioning option. Select a time zone from the Time & Date screen and click Done . Select a network from the Network & Host Name screen and click Configure... to configure the connection details. Note To use the connection every time the system boots, select the Connect automatically with priority check box. For more information, see Configuring network and host name options in the Red Hat Enterprise Linux 8 Installation Guide . Enter a host name in the Host Name field, and click Done . Optional: Configure Security Policy and Kdump . See Customizing your RHEL installation using the GUI in Performing a standard RHEL installation for Red Hat Enterprise Linux 8 for more information on each of the sections in the Installation Summary screen. Click Begin Installation . Set a root password and, optionally, create an additional user while RHVH installs. Warning Do not create untrusted users on RHVH, as this can lead to exploitation of local security vulnerabilities. Click Reboot to complete the installation. Note When RHVH restarts, nodectl check performs a health check on the host and displays the result when you log in on the command line. The message node status: OK or node status: DEGRADED indicates the health status. Run nodectl check to get more information. Note If necessary, you can prevent kernel modules from loading automatically . 2.1.1. Enabling the Red Hat Virtualization Host Repository Register the system to receive updates. Red Hat Virtualization Host only requires one repository. This section provides instructions for registering RHVH with the Content Delivery Network , or with Red Hat Satellite 6 . Registering RHVH with the Content Delivery Network Enable the Red Hat Virtualization Host 8 repository to allow later updates to the Red Hat Virtualization Host: # subscription-manager repos --enable=rhvh-4-for-rhel-8-x86_64-rpms Registering RHVH with Red Hat Satellite 6 Log in to the Cockpit web interface at https:// HostFQDNorIP :9090 . Click Terminal . Register RHVH with Red Hat Satellite 6: Note You can also configure virtual machine subscriptions in Red Hat Satellite using virt-who. See Using virt-who to manage host-based subscriptions . 2.2. Installing Red Hat Enterprise Linux hosts A Red Hat Enterprise Linux host is based on a standard basic installation of Red Hat Enterprise Linux 8 on a physical server, with the Red Hat Enterprise Linux Server and Red Hat Virtualization subscriptions attached. For detailed installation instructions, see the Performing a standard RHEL installation . The host must meet the minimum host requirements . Warning When installing or reinstalling the host's operating system, Red Hat strongly recommends that you first detach any existing non-OS storage that is attached to the host to avoid accidental initialization of these disks, and with that, potential data loss. Important Virtualization must be enabled in your host's BIOS settings. For information on changing your host's BIOS settings, refer to your host's hardware documentation. Important Do not install third-party watchdogs on Red Hat Enterprise Linux hosts. They can interfere with the watchdog daemon provided by VDSM. 2.2.1. Enabling the Red Hat Enterprise Linux host Repositories To use a Red Hat Enterprise Linux machine as a host, you must register the system with the Content Delivery Network, attach the Red Hat Enterprise Linux Server and Red Hat Virtualization subscriptions, and enable the host repositories. Procedure Register your system with the Content Delivery Network, entering your Customer Portal user name and password when prompted: # subscription-manager register Find the Red Hat Enterprise Linux Server and Red Hat Virtualization subscription pools and record the pool IDs: # subscription-manager list --available Use the pool IDs to attach the subscriptions to the system: # subscription-manager attach --pool= poolid Note To view currently attached subscriptions: # subscription-manager list --consumed To list all enabled repositories: # dnf repolist Configure the repositories: # subscription-manager repos \ --disable='*' \ --enable=rhel-8-for-x86_64-baseos-eus-rpms \ --enable=rhel-8-for-x86_64-appstream-eus-rpms \ --enable=rhv-4-mgmt-agent-for-rhel-8-x86_64-rpms \ --enable=fast-datapath-for-rhel-8-x86_64-rpms \ --enable=advanced-virt-for-rhel-8-x86_64-rpms \ --enable=openstack-16.2-cinderlib-for-rhel-8-x86_64-rpms \ --enable=rhceph-4-tools-for-rhel-8-x86_64-rpms \ --enable=rhel-8-for-x86_64-appstream-tus-rpms \ --enable=rhel-8-for-x86_64-baseos-tus-rpms Set the RHEL version to 8.6: # subscription-manager release --set=8.6 Reset the virt module: # dnf module reset virt Note If this module is already enabled in the Advanced Virtualization stream, this step is not necessary, but it has no negative impact. You can see the value of the stream by entering: Enable the virt module in the Advanced Virtualization stream with the following command: For RHV 4.4.2: # dnf module enable virt:8.2 For RHV 4.4.3 to 4.4.5: # dnf module enable virt:8.3 For RHV 4.4.6 to 4.4.10: # dnf module enable virt:av For RHV 4.4 and later: Note Starting with RHEL 8.6 the Advanced virtualization packages will use the standard virt:rhel module. For RHEL 8.4 and 8.5, only one Advanced Virtualization stream is used, rhel:av . Ensure that all packages currently installed are up to date: # dnf upgrade --nobest Reboot the machine. Note If necessary, you can prevent kernel modules from loading automatically . Although the existing storage domains will be migrated from the standalone Manager, you must prepare additional storage for a self-hosted engine storage domain that is dedicated to the Manager virtual machine.	[ "subscription-manager repos --enable=rhvh-4-for-rhel-8-x86_64-rpms", "rpm -Uvh http://satellite.example.com/pub/katello-ca-consumer-latest.noarch.rpm # subscription-manager register --org=\" org_id \" # subscription-manager list --available # subscription-manager attach --pool= pool_id # subscription-manager repos --disable='' --enable=rhvh-4-for-rhel-8-x86_64-rpms", "subscription-manager register", "subscription-manager list --available", "subscription-manager attach --pool= poolid", "subscription-manager list --consumed", "dnf repolist", "subscription-manager repos --disable='' --enable=rhel-8-for-x86_64-baseos-eus-rpms --enable=rhel-8-for-x86_64-appstream-eus-rpms --enable=rhv-4-mgmt-agent-for-rhel-8-x86_64-rpms --enable=fast-datapath-for-rhel-8-x86_64-rpms --enable=advanced-virt-for-rhel-8-x86_64-rpms --enable=openstack-16.2-cinderlib-for-rhel-8-x86_64-rpms --enable=rhceph-4-tools-for-rhel-8-x86_64-rpms --enable=rhel-8-for-x86_64-appstream-tus-rpms --enable=rhel-8-for-x86_64-baseos-tus-rpms", "subscription-manager release --set=8.6", "dnf module reset virt", "dnf module list virt", "dnf module enable virt:8.2", "dnf module enable virt:8.3", "dnf module enable virt:av", "dnf module enable virt:rhel", "dnf upgrade --nobest" ]	https://docs.redhat.com/en/documentation/red_hat_virtualization/4.4/html/migrating_from_a_standalone_manager_to_a_self-hosted_engine/Installing_the_self-hosted_engine_deployment_host_migrating_to_SHE
Part IV. Technology Previews	Part IV. Technology Previews This part provides a list of all Technology Previews available in Red Hat Enterprise Linux 7.6. For information on Red Hat scope of support for Technology Preview features, see https://access.redhat.com/support/offerings/techpreview/ .	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/7.6_release_notes/technology-previews
function::task_execname	function::task_execname Name function::task_execname - The name of the task Synopsis Arguments task task_struct pointer Description Return the name of the given task.	[ "task_execname:string(task:long)" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/systemtap_tapset_reference/api-task-execname
C.2. Selection Criteria Operators	C.2. Selection Criteria Operators Table C.2, "Selection Criteria Grouping Operators" describes the selection criteria grouping operators. Table C.2. Selection Criteria Grouping Operators Grouping Operator Description ( ) Used for grouping statements [ ] Used to group strings into a string list (exact match) { } Used to group strings into a string list (subset match) Table C.3, "Selection Criteria Comparison Operators" describes the selection criteria comparison operators and the field types with which they can be used. Table C.3. Selection Criteria Comparison Operators Comparison Operator Description Field Type =~ Matching regular expression regex !~ Not matching regular expression. regex = Equal to number, size, percent, string, string list, time != Not equal to number, size, percent, string, string list, time >= Greater than or equal to number, size, percent, time > Greater than number, size, percent, time <= Less than or equal to number, size, percent, time < Less than number, size, percent, time since Since specified time (same as >=) time after After specified time (same as >) time until Until specified time (same as <=) time before Before specified time (same as <) time Table C.4, "Selection Criteria Logical and Grouping Operators" describes the selection criteria logical and grouping operators. Table C.4. Selection Criteria Logical and Grouping Operators Logical and Grouping Operator Description && All fields must match , All fields must match (same as &&) \|\| At least one field must match # At least one field must match (same as \|\|) ! Logical negation ( Left parenthesis (grouping operator) ) Right parenthesis (grouping operator) [ List start (grouping operator) ] List end (grouping operator) { List subset start (grouping operator) } List subset end (grouping operator)	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/logical_volume_manager_administration/selection_operators
16.10. virt-win-reg: Reading and Editing the Windows Registry	16.10. virt-win-reg: Reading and Editing the Windows Registry 16.10.1. Introduction virt-win-reg is a tool that manipulates the Registry in Windows guest virtual machines. It can be used to read out registry keys. You can also use it to make changes to the Registry, but you must never try to do this for live/running guest virtual machines, as it will result in disk corruption.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/virtualization_administration_guide/sect-virt-win-reg
Chapter 85. Disruptor Component	Chapter 85. Disruptor Component Available as of Camel version 2.12 The disruptor: component provides asynchronous SEDA behavior much as the standard SEDA Component, but utilizes a Disruptor instead of a BlockingQueue utilized by the standard SEDA . Alternatively, a disruptor-vm: endpoint is supported by this component, providing an alternative to the standard VM . As with the SEDA component, buffers of the disruptor: endpoints are only visible within a single CamelContext and no support is provided for persistence or recovery. The buffers of the disruptor-vm: endpoints also provides support for communication across CamelContexts instances so you can use this mechanism to communicate across web applications (provided that camel-disruptor.jar is on the system/boot classpath). The main advantage of choosing to use the Disruptor Component over the SEDA or the VM Component is performance in use cases where there is high contention between producer(s) and/or multicasted or concurrent Consumers. In those cases, significant increases of throughput and reduction of latency has been observed. Performance in scenarios without contention is comparable to the SEDA and VM Components. The Disruptor is implemented with the intention of mimicing the behaviour and options of the SEDA and VM Components as much as possible. The main differences with the them are the following: The buffer used is always bounded in size (default 1024 exchanges). As a the buffer is always bouded, the default behaviour for the Disruptor is to block while the buffer is full instead of throwing an exception. This default behaviour may be configured on the component (see options). The Disruptor enpoints don't implement the BrowsableEndpoint interface. As such, the exchanges currently in the Disruptor can't be retrieved, only the amount of exchanges. The Disruptor requires its consumers (multicasted or otherwise) to be statically configured. Adding or removing consumers on the fly requires complete flushing of all pending exchanges in the Disruptor. As a result of the reconfiguration: Data sent over a Disruptor is directly processed and 'gone' if there is at least one consumer, late joiners only get new exchanges published after they've joined. The pollTimeout option is not supported by the Disruptor Component. When a producer blocks on a full Disruptor, it does not respond to thread interrupts. Maven users will need to add the following dependency to their pom.xml for this component: <dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-disruptor</artifactId> <version>x.x.x</version> <!-- use the same version as your Camel core version --> </dependency> 85.1. URI format disruptor:someName[?options] or disruptor-vm:someName[?options] Where someName can be any string that uniquely identifies the endpoint within the current CamelContext (or across contexts in case of disruptor-vm: ). You can append query options to the URI in the following format: ?option=value&option=value&... 85.2. Options All the following options are valid for both the disruptor: and disruptor-vm: components. The Disruptor component supports 8 options, which are listed below. Name Description Default Type defaultConcurrent Consumers (consumer) To configure the default number of concurrent consumers 1 int defaultMultiple Consumers (consumer) To configure the default value for multiple consumers false boolean defaultProducerType (producer) To configure the default value for DisruptorProducerType The default value is Multi. Multi DisruptorProducerType defaultWaitStrategy (consumer) To configure the default value for DisruptorWaitStrategy The default value is Blocking. Blocking DisruptorWaitStrategy defaultBlockWhenFull (producer) To configure the default value for block when full The default value is true. true boolean queueSize (common) Deprecated To configure the ring buffer size int bufferSize (common) To configure the ring buffer size 1024 int resolveProperty Placeholders (advanced) Whether the component should resolve property placeholders on itself when starting. Only properties which are of String type can use property placeholders. true boolean The Disruptor endpoint is configured using URI syntax: with the following path and query parameters: 85.2.1. Path Parameters (1 parameters): Name Description Default Type name Required Name of queue String 85.2.2. Query Parameters (12 parameters): Name Description Default Type size (common) The maximum capacity of the Disruptors ringbuffer Will be effectively increased to the nearest power of two. Notice: Mind if you use this option, then its the first endpoint being created with the queue name, that determines the size. To make sure all endpoints use same size, then configure the size option on all of them, or the first endpoint being created. 1024 int 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 concurrentConsumers (consumer) Number of concurrent threads processing exchanges. 1 int multipleConsumers (consumer) Specifies whether multiple consumers are allowed. If enabled, you can use Disruptor for Publish-Subscribe messaging. That is, you can send a message to the queue and have each consumer receive a copy of the message. When enabled, this option should be specified on every consumer endpoint. false boolean waitStrategy (consumer) Defines the strategy used by consumer threads to wait on new exchanges to be published. The options allowed are:Blocking, Sleeping, BusySpin and Yielding. Blocking DisruptorWaitStrategy exceptionHandler (consumer) 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) Sets the exchange pattern when the consumer creates an exchange. ExchangePattern blockWhenFull (producer) Whether a thread that sends messages to a full Disruptor will block until the ringbuffer's capacity is no longer exhausted. By default, the calling thread will block and wait until the message can be accepted. By disabling this option, an exception will be thrown stating that the queue is full. false boolean producerType (producer) Defines the producers allowed on the Disruptor. The options allowed are: Multi to allow multiple producers and Single to enable certain optimizations only allowed when one concurrent producer (on one thread or otherwise synchronized) is active. Multi DisruptorProducerType timeout (producer) Timeout (in milliseconds) before a producer will stop waiting for an asynchronous task to complete. You can disable timeout by using 0 or a negative value. 30000 long waitForTaskToComplete (producer) Option to specify whether the caller should wait for the async task to complete or not before continuing. The following three options are supported: Always, Never or IfReplyExpected. The first two values are self-explanatory. The last value, IfReplyExpected, will only wait if the message is Request Reply based. IfReplyExpected WaitForTaskToComplete synchronous (advanced) Sets whether synchronous processing should be strictly used, or Camel is allowed to use asynchronous processing (if supported). false boolean 85.3. Spring Boot Auto-Configuration The component supports 18 options, which are listed below. Name Description Default Type camel.component.disruptor-vm.buffer-size To configure the ring buffer size 1024 Integer camel.component.disruptor-vm.default-block-when-full To configure the default value for block when full The default value is true. true Boolean camel.component.disruptor-vm.default-concurrent-consumers To configure the default number of concurrent consumers 1 Integer camel.component.disruptor-vm.default-multiple-consumers To configure the default value for multiple consumers false Boolean camel.component.disruptor-vm.default-producer-type To configure the default value for DisruptorProducerType The default value is Multi. DisruptorProducerType camel.component.disruptor-vm.default-wait-strategy To configure the default value for DisruptorWaitStrategy The default value is Blocking. DisruptorWaitStrategy camel.component.disruptor-vm.enabled Enable disruptor-vm component true Boolean camel.component.disruptor-vm.resolve-property-placeholders Whether the component should resolve property placeholders on itself when starting. Only properties which are of String type can use property placeholders. true Boolean camel.component.disruptor.buffer-size To configure the ring buffer size 1024 Integer camel.component.disruptor.default-block-when-full To configure the default value for block when full The default value is true. true Boolean camel.component.disruptor.default-concurrent-consumers To configure the default number of concurrent consumers 1 Integer camel.component.disruptor.default-multiple-consumers To configure the default value for multiple consumers false Boolean camel.component.disruptor.default-producer-type To configure the default value for DisruptorProducerType The default value is Multi. DisruptorProducerType camel.component.disruptor.default-wait-strategy To configure the default value for DisruptorWaitStrategy The default value is Blocking. DisruptorWaitStrategy camel.component.disruptor.enabled Enable disruptor component true Boolean camel.component.disruptor.resolve-property-placeholders Whether the component should resolve property placeholders on itself when starting. Only properties which are of String type can use property placeholders. true Boolean camel.component.disruptor-vm.queue-size To configure the ring buffer size Integer camel.component.disruptor.queue-size To configure the ring buffer size Integer 85.4. Wait strategies The wait strategy effects the type of waiting performed by the consumer threads that are currently waiting for the exchange to be published. The following strategies can be chosen: Name Description Advice Blocking Blocking strategy that uses a lock and condition variable for Consumers waiting on a barrier. This strategy can be used when throughput and low-latency are not as important as CPU resource. Sleeping Sleeping strategy that initially spins, then uses a Thread.yield(), and eventually for the minimum number of nanos the OS and JVM will allow while the Consumers are waiting on a barrier. This strategy is a good compromise between performance and CPU resource. Latency spikes can occur after quiet periods. BusySpin Busy Spin strategy that uses a busy spin loop for Consumers waiting on a barrier. This strategy will use CPU resource to avoid syscalls which can introduce latency jitter. It is best used when threads can be bound to specific CPU cores. Yielding Yielding strategy that uses a Thread.yield() for Consumers waiting on a barrier after an initially spinning. This strategy is a good compromise between performance and CPU resource without incurring significant latency spikes. 85.5. Use of Request Reply The Disruptor component supports using Request Reply , where the caller will wait for the Async route to complete. For instance: from("mina:tcp://0.0.0.0:9876?textline=true&sync=true").to("disruptor:input"); from("disruptor:input").to("bean:processInput").to("bean:createResponse"); In the route above, we have a TCP listener on port 9876 that accepts incoming requests. The request is routed to the disruptor:input buffer. As it is a Request Reply message, we wait for the response. When the consumer on the disruptor:input buffer is complete, it copies the response to the original message response. 85.6. Concurrent consumers By default, the Disruptor endpoint uses a single consumer thread, but you can configure it to use concurrent consumer threads. So instead of thread pools you can use: from("disruptor:stageName?concurrentConsumers=5").process(...) As for the difference between the two, note a thread pool can increase/shrink dynamically at runtime depending on load, whereas the number of concurrent consumers is always fixed and supported by the Disruptor internally so performance will be higher. 85.7. Thread pools Be aware that adding a thread pool to a Disruptor endpoint by doing something like: from("disruptor:stageName").thread(5).process(...) Can wind up with adding a normal BlockingQueue to be used in conjunction with the Disruptor, effectively negating part of the performance gains achieved by using the Disruptor. Instead, it is advices to directly configure number of threads that process messages on a Disruptor endpoint using the concurrentConsumers option. 85.8. Sample In the route below we use the Disruptor to send the request to this async queue to be able to send a fire-and-forget message for further processing in another thread, and return a constant reply in this thread to the original caller. public void configure() throws Exception { from("direct:start") // send it to the disruptor that is async .to("disruptor:") // return a constant response .transform(constant("OK")); from("disruptor:").to("mock:result"); } Here we send a Hello World message and expects the reply to be OK. Object out = template.requestBody("direct:start", "Hello World"); assertEquals("OK", out); The "Hello World" message will be consumed from the Disruptor from another thread for further processing. Since this is from a unit test, it will be sent to a mock endpoint where we can do assertions in the unit test. 85.9. Using multipleConsumers In this example we have defined two consumers and registered them as spring beans. <!-- define the consumers as spring beans --> <bean id="consumer1" class="org.apache.camel.spring.example.FooEventConsumer"/> <bean id="consumer2" class="org.apache.camel.spring.example.AnotherFooEventConsumer"/> <camelContext xmlns="http://camel.apache.org/schema/spring"> <!-- define a shared endpoint which the consumers can refer to instead of using url --> <endpoint id="foo" uri="disruptor:foo?multipleConsumers=true"/> </camelContext> Since we have specified multipleConsumers=true on the Disruptor foo endpoint we can have those two or more consumers receive their own copy of the message as a kind of pub-sub style messaging. As the beans are part of an unit test they simply send the message to a mock endpoint, but notice how we can use @Consume to consume from the Disruptor. public class FooEventConsumer { @EndpointInject(uri = "mock:result") private ProducerTemplate destination; @Consume(ref = "foo") public void doSomething(String body) { destination.sendBody("foo" + body); } } 85.10. Extracting disruptor information If needed, information such as buffer size, etc. can be obtained without using JMX in this fashion: DisruptorEndpoint disruptor = context.getEndpoint("disruptor:xxxx"); int size = disruptor.getBufferSize();	[ "<dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-disruptor</artifactId> <version>x.x.x</version> <!-- use the same version as your Camel core version --> </dependency>", "disruptor:someName[?options]", "disruptor-vm:someName[?options]", "?option=value&option=value&...", "disruptor:name", "from(\"mina:tcp://0.0.0.0:9876?textline=true&sync=true\").to(\"disruptor:input\"); from(\"disruptor:input\").to(\"bean:processInput\").to(\"bean:createResponse\");", "from(\"disruptor:stageName?concurrentConsumers=5\").process(...)", "from(\"disruptor:stageName\").thread(5).process(...)", "public void configure() throws Exception { from(\"direct:start\") // send it to the disruptor that is async .to(\"disruptor:next\") // return a constant response .transform(constant(\"OK\")); from(\"disruptor:next\").to(\"mock:result\"); }", "Object out = template.requestBody(\"direct:start\", \"Hello World\"); assertEquals(\"OK\", out);", "<!-- define the consumers as spring beans --> <bean id=\"consumer1\" class=\"org.apache.camel.spring.example.FooEventConsumer\"/> <bean id=\"consumer2\" class=\"org.apache.camel.spring.example.AnotherFooEventConsumer\"/> <camelContext xmlns=\"http://camel.apache.org/schema/spring\"> <!-- define a shared endpoint which the consumers can refer to instead of using url --> <endpoint id=\"foo\" uri=\"disruptor:foo?multipleConsumers=true\"/> </camelContext>", "public class FooEventConsumer { @EndpointInject(uri = \"mock:result\") private ProducerTemplate destination; @Consume(ref = \"foo\") public void doSomething(String body) { destination.sendBody(\"foo\" + body); } }", "DisruptorEndpoint disruptor = context.getEndpoint(\"disruptor:xxxx\"); int size = disruptor.getBufferSize();" ]	https://docs.redhat.com/en/documentation/red_hat_fuse/7.13/html/apache_camel_component_reference/disruptor-component
Installing on IBM Cloud Bare Metal (Classic)	Installing on IBM Cloud Bare Metal (Classic) OpenShift Container Platform 4.12 Installing OpenShift Container Platform on IBM Cloud Bare Metal (Classic) Red Hat OpenShift Documentation Team	[ "<cluster_name>.<domain>", "test-cluster.example.com", "ipmi://<IP>:<port>?privilegelevel=OPERATOR", "ibmcloud sl hardware create --hostname <SERVERNAME> --domain <DOMAIN> --size <SIZE> --os <OS-TYPE> --datacenter <DC-NAME> --port-speed <SPEED> --billing <BILLING>", "useradd kni", "passwd kni", "echo \"kni ALL=(root) NOPASSWD:ALL\" \| tee -a /etc/sudoers.d/kni", "chmod 0440 /etc/sudoers.d/kni", "su - kni -c \"ssh-keygen -f /home/kni/.ssh/id_rsa -N ''\"", "su - kni", "sudo subscription-manager register --username=<user> --password=<pass> --auto-attach", "sudo subscription-manager repos --enable=rhel-8-for-x86_64-appstream-rpms --enable=rhel-8-for-x86_64-baseos-rpms", "sudo dnf install -y libvirt qemu-kvm mkisofs python3-devel jq ipmitool", "sudo usermod --append --groups libvirt kni", "sudo systemctl start firewalld", "sudo systemctl enable firewalld", "sudo firewall-cmd --zone=public --add-service=http --permanent", "sudo firewall-cmd --reload", "sudo systemctl enable libvirtd --now", "PRVN_HOST_ID=<ID>", "ibmcloud sl hardware list", "PUBLICSUBNETID=<ID>", "ibmcloud sl subnet list", "PRIVSUBNETID=<ID>", "ibmcloud sl subnet list", "PRVN_PUB_IP=USD(ibmcloud sl hardware detail USDPRVN_HOST_ID --output JSON \| jq .primaryIpAddress -r)", "PUBLICCIDR=USD(ibmcloud sl subnet detail USDPUBLICSUBNETID --output JSON \| jq .cidr)", "PUB_IP_CIDR=USDPRVN_PUB_IP/USDPUBLICCIDR", "PUB_GATEWAY=USD(ibmcloud sl subnet detail USDPUBLICSUBNETID --output JSON \| jq .gateway -r)", "PRVN_PRIV_IP=USD(ibmcloud sl hardware detail USDPRVN_HOST_ID --output JSON \| jq .primaryBackendIpAddress -r)", "PRIVCIDR=USD(ibmcloud sl subnet detail USDPRIVSUBNETID --output JSON \| jq .cidr)", "PRIV_IP_CIDR=USDPRVN_PRIV_IP/USDPRIVCIDR", "PRIV_GATEWAY=USD(ibmcloud sl subnet detail USDPRIVSUBNETID --output JSON \| jq .gateway -r)", "sudo nohup bash -c \" nmcli --get-values UUID con show \| xargs -n 1 nmcli con delete nmcli connection add ifname provisioning type bridge con-name provisioning nmcli con add type bridge-slave ifname eth1 master provisioning nmcli connection add ifname baremetal type bridge con-name baremetal nmcli con add type bridge-slave ifname eth2 master baremetal nmcli connection modify baremetal ipv4.addresses USDPUB_IP_CIDR ipv4.method manual ipv4.gateway USDPUB_GATEWAY nmcli connection modify provisioning ipv4.addresses 172.22.0.1/24,USDPRIV_IP_CIDR ipv4.method manual nmcli connection modify provisioning +ipv4.routes \\\"10.0.0.0/8 USDPRIV_GATEWAY\\\" nmcli con down baremetal nmcli con up baremetal nmcli con down provisioning nmcli con up provisioning init 6 \"", "ssh kni@provisioner.<cluster-name>.<domain>", "sudo nmcli con show", "NAME UUID TYPE DEVICE baremetal 4d5133a5-8351-4bb9-bfd4-3af264801530 bridge baremetal provisioning 43942805-017f-4d7d-a2c2-7cb3324482ed bridge provisioning virbr0 d9bca40f-eee1-410b-8879-a2d4bb0465e7 bridge virbr0 bridge-slave-eth1 76a8ed50-c7e5-4999-b4f6-6d9014dd0812 ethernet eth1 bridge-slave-eth2 f31c3353-54b7-48de-893a-02d2b34c4736 ethernet eth2", "vim pull-secret.txt", "sudo dnf install dnsmasq", "sudo vi /etc/dnsmasq.conf", "interface=baremetal except-interface=lo bind-dynamic log-dhcp dhcp-range=<ip_addr>,<ip_addr>,<pub_cidr> 1 dhcp-option=baremetal,121,0.0.0.0/0,<pub_gateway>,<prvn_priv_ip>,<prvn_pub_ip> 2 dhcp-hostsfile=/var/lib/dnsmasq/dnsmasq.hostsfile", "ibmcloud sl subnet detail <publicsubnetid> --output JSON \| jq .cidr", "ibmcloud sl subnet detail <publicsubnetid> --output JSON \| jq .gateway -r", "ibmcloud sl hardware detail <id> --output JSON \| jq .primaryBackendIpAddress -r", "ibmcloud sl hardware detail <id> --output JSON \| jq .primaryIpAddress -r", "ibmcloud sl hardware list", "ibmcloud sl hardware detail <id> --output JSON \| jq '.networkComponents[] \| \"\\(.primaryIpAddress) \\(.macAddress)\"' \| grep -v null", "\"10.196.130.144 00:e0:ed:6a:ca:b4\" \"141.125.65.215 00:e0:ed:6a:ca:b5\"", "sudo vim /var/lib/dnsmasq/dnsmasq.hostsfile", "00:e0:ed:6a:ca:b5,141.125.65.215,master-0 <mac>,<ip>,master-1 <mac>,<ip>,master-2 <mac>,<ip>,worker-0 <mac>,<ip>,worker-1", "sudo systemctl start dnsmasq", "sudo systemctl enable dnsmasq", "sudo systemctl status dnsmasq", "● dnsmasq.service - DNS caching server. Loaded: loaded (/usr/lib/systemd/system/dnsmasq.service; enabled; vendor preset: disabled) Active: active (running) since Tue 2021-10-05 05:04:14 CDT; 49s ago Main PID: 3101 (dnsmasq) Tasks: 1 (limit: 204038) Memory: 732.0K CGroup: /system.slice/dnsmasq.service └─3101 /usr/sbin/dnsmasq -k", "sudo firewall-cmd --add-port 53/udp --permanent", "sudo firewall-cmd --add-port 67/udp --permanent", "sudo firewall-cmd --change-zone=provisioning --zone=external --permanent", "sudo firewall-cmd --reload", "export VERSION=stable-4.12", "export RELEASE_ARCH=<architecture>", "export RELEASE_IMAGE=USD(curl -s https://mirror.openshift.com/pub/openshift-v4/USDRELEASE_ARCH/clients/ocp/USDVERSION/release.txt \| grep 'Pull From: quay.io' \| awk -F ' ' '{print USD3}')", "export cmd=openshift-baremetal-install", "export pullsecret_file=~/pull-secret.txt", "export extract_dir=USD(pwd)", "curl -s https://mirror.openshift.com/pub/openshift-v4/clients/ocp/USDVERSION/openshift-client-linux.tar.gz \| tar zxvf - oc", "sudo cp oc /usr/local/bin", "oc adm release extract --registry-config \"USD{pullsecret_file}\" --command=USDcmd --to \"USD{extract_dir}\" USD{RELEASE_IMAGE}", "sudo cp openshift-baremetal-install /usr/local/bin", "apiVersion: v1 baseDomain: <domain> metadata: name: <cluster_name> networking: machineNetwork: - cidr: <public-cidr> networkType: OVNKubernetes compute: - name: worker replicas: 2 controlPlane: name: master replicas: 3 platform: baremetal: {} platform: baremetal: apiVIP: <api_ip> ingressVIP: <wildcard_ip> provisioningNetworkInterface: <NIC1> provisioningNetworkCIDR: <CIDR> hosts: - name: openshift-master-0 role: master bmc: address: ipmi://10.196.130.145?privilegelevel=OPERATOR 1 username: root password: <password> bootMACAddress: 00:e0:ed:6a:ca:b4 2 rootDeviceHints: deviceName: \"/dev/sda\" - name: openshift-worker-0 role: worker bmc: address: ipmi://<out-of-band-ip>?privilegelevel=OPERATOR 3 username: <user> password: <password> bootMACAddress: <NIC1_mac_address> 4 rootDeviceHints: deviceName: \"/dev/sda\" pullSecret: '<pull_secret>' sshKey: '<ssh_pub_key>'", "ibmcloud sl hardware detail <id> --output JSON \| jq '\"(.networkManagementIpAddress) (.remoteManagementAccounts[0].password)\"'", "mkdir ~/clusterconfigs", "cp install-config.yaml ~/clusterconfigs", "ipmitool -I lanplus -U <user> -P <password> -H <management_server_ip> power off", "for i in USD(sudo virsh list \| tail -n +3 \| grep bootstrap \| awk {'print USD2'}); do sudo virsh destroy USDi; sudo virsh undefine USDi; sudo virsh vol-delete USDi --pool USDi; sudo virsh vol-delete USDi.ign --pool USDi; sudo virsh pool-destroy USDi; sudo virsh pool-undefine USDi; done", "metadata: name:", "networking: machineNetwork: - cidr:", "compute: - name: worker", "compute: replicas: 2", "controlPlane: name: master", "controlPlane: replicas: 3", "- name: master-0 role: master bmc: address: ipmi://10.10.0.3:6203 username: admin password: redhat bootMACAddress: de:ad:be:ef:00:40 rootDeviceHints: deviceName: \"/dev/sda\"", "./openshift-baremetal-install --dir ~/clusterconfigs create manifests", "INFO Consuming Install Config from target directory WARNING Making control-plane schedulable by setting MastersSchedulable to true for Scheduler cluster settings WARNING Discarding the OpenShift Manifest that was provided in the target directory because its dependencies are dirty and it needs to be regenerated", "./openshift-baremetal-install --dir ~/clusterconfigs --log-level debug create cluster", "tail -f /path/to/install-dir/.openshift_install.log" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.12/html-single/installing_on_ibm_cloud_bare_metal_classic/index
Preface	Preface Making open source more inclusive Red Hat is committed to replacing problematic language in our code, documentation, and web properties. We are beginning with these four terms: master, slave, blacklist, and whitelist. Because of the enormity of this endeavor, these changes will be implemented gradually over several upcoming releases. For more details, see our CTO Chris Wright's message .	null	https://docs.redhat.com/en/documentation/red_hat_build_of_apache_camel/4.0/html/getting_started_with_red_hat_build_of_apache_camel_for_quarkus/pr01
Part V. Deprecated Functionality	Part V. Deprecated Functionality This part provides an overview of functionality that has been deprecated in all minor releases up to Red Hat Enterprise Linux 7.4. Deprecated functionality continues to be supported until the end of life of Red Hat Enterprise Linux 7. Deprecated functionality will likely not be supported in future major releases of this product and is not recommended for new deployments. For the most recent list of deprecated functionality within a particular major release, refer to the latest version of release documentation. Deprecated hardware components are not recommended for new deployments on the current or future major releases. Hardware driver updates are limited to security and critical fixes only. Red Hat recommends replacing this hardware as soon as reasonably feasible. A package can be deprecated and not recommended for further use. Under certain circumstances, a package can be removed from a product. Product documentation then identifies more recent packages that offer functionality similar, identical, or more advanced to the one deprecated, and provides further recommendations.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/7.4_release_notes/part-Red_Hat_Enterprise_Linux-7.4_Release_Notes-Deprecated_Functionality
Chapter 9. Error handling	Chapter 9. Error handling Errors in Red Hat build of Rhea can be handled by intercepting named events corresponding to AMQP protocol or connection errors. 9.1. Handling connection and protocol errors You can handle protocol-level errors by intercepting the following events: connection_error session_error sender_error receiver_error protocol_error error These events are fired whenever there is an error condition with the specific object that is in the event. After calling the error handler, the corresponding <object> _close handler is also called. The event argument has an error attribute for accessing the error object. Example: Handling errors container.on("error", function (event) { console.log("An error!", event.error); }); Note Because the close handlers are called in the event of any error, only the error itself needs to be handled within the error handler. Resource cleanup can be managed by close handlers. If there is no error handling that is specific to a particular object, it is typical to handle the general error event and not have a more specific handler. Note When reconnect is enabled and the remote server closes a connection with the amqp:connection:forced condition, the client does not treat it as an error and thus does not fire the connection_error event. The client instead begins the reconnection process.	[ "container.on(\"error\", function (event) { console.log(\"An error!\", event.error); });" ]	https://docs.redhat.com/en/documentation/red_hat_build_of_rhea/3.0/html/using_rhea/error_handling
Chapter 23. Cron	Chapter 23. Cron Only consumer is supported The Cron component is a generic interface component that allows triggering events at specific time interval specified using the Unix cron syntax (e.g. 0/2 * * * * ? to trigger an event every two seconds). Being an interface component, the Cron component does not contain a default implementation, instead it requires that the users plug the implementation of their choice. The following standard Camel components support the Cron endpoints: Camel-quartz Camel-spring The Cron component is also supported in Camel K , which can use the Kubernetes scheduler to trigger the routes when required by the cron expression. Camel K does not require additional libraries to be plugged when using cron expressions compatible with Kubernetes cron syntax. 23.1. Dependencies When using cron with Red Hat build of Camel 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-cron-starter</artifactId> </dependency> Additional libraries may be needed in order to plug a specific implementation. 23.2. Configuring Options Camel components are configured on two levels: Component level Endpoint level 23.2.1. Component Level Options The component level is the highest level. The configurations you define at this level are inherited by all the endpoints. For example, a component can have security settings, credentials for authentication, urls for network connection, and so on. Since components typically have pre-configured defaults for the most common cases, you may need to only configure a few component options, or maybe none at all. You can configure components with Component DSL in a configuration file (application.properties\|yaml), or directly with Java code. 23.2.2. Endpoint Level Options At the Endpoint level you have many options, which you can use to configure what you want the endpoint to do. The options are categorized according to whether the endpoint is used as a consumer (from) or as a producer (to) or used for both. You can configure endpoints directly in the endpoint URI as path and query parameters. You can also use Endpoint DSL and DataFormat DSL as type safe ways of configuring endpoints and data formats in Java. When configuring options, use Property Placeholders for urls, port numbers, sensitive information, and other settings. Placeholders allows you to externalize the configuration from your code, giving you more flexible and reusable code. 23.3. Component Options The Cron component supports 3 options, which are listed below. Name Description Default Type 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 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 cronService (advanced) The id of the CamelCronService to use when multiple implementations are provided. String 23.4. Endpoint Options The Cron endpoint is configured using URI syntax: with the following path and query parameters: 23.4.1. Path Parameters (1 parameters) Name Description Default Type name (consumer) Required The name of the cron trigger. String 23.4.2. Query Parameters (4 parameters) Name Description Default Type 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 schedule (consumer) Required A cron expression that will be used to generate events. String 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 23.5. Usage The component can be used to trigger events at specified times, as in the following example: from("cron:tab?schedule=0/1+++++?") .setBody().constant("event") .log("USD{body}"); The schedule expression 0/3+10+ * +? can be also written as 0/3 10 * * * ? and triggers an event every three seconds only in the tenth minute of each hour. Parts in the schedule expression means (in order): Seconds (optional) Minutes Hours Day of month Month Day of week Year (optional) Schedule expressions can be made of 5 to 7 parts. When expressions are composed of 6 parts, the first items is the "seconds" part (and year is considered missing). Other valid examples of schedule expressions are: 0/2 * * * ? (5 parts, an event every two minutes) 0 0/2 * * * MON-FRI 2030 (7 parts, an event every two minutes only in year 2030) Routes can also be written using the XML DSL. <route> <from uri="cron:tab?schedule=0/1+++++?"/> <setBody> <constant>event</constant> </setBody> <to uri="log:info"/> </route> 23.6. Spring Boot Auto-Configuration The component supports 4 options, which are listed below. Name Description Default Type camel.component.cron.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.cron.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.cron.cron-service The id of the CamelCronService to use when multiple implementations are provided. String camel.component.cron.enabled Whether to enable auto configuration of the cron component. This is enabled by default. Boolean	[ "<dependency> <groupId>org.apache.camel.springboot</groupId> <artifactId>camel-cron-starter</artifactId> </dependency>", "cron:name", "from(\"cron:tab?schedule=0/1+++++?\") .setBody().constant(\"event\") .log(\"USD{body}\");", "<route> <from uri=\"cron:tab?schedule=0/1+++++?\"/> <setBody> <constant>event</constant> </setBody> <to uri=\"log:info\"/> </route>" ]	https://docs.redhat.com/en/documentation/red_hat_build_of_apache_camel/4.4/html/red_hat_build_of_apache_camel_for_spring_boot_reference/csb-camel-cron-component-starter
Chapter 1. OpenShift Container Platform storage overview	Chapter 1. OpenShift Container Platform storage overview OpenShift Container Platform supports multiple types of storage, both for on-premise and cloud providers. You can manage container storage for persistent and non-persistent data in an OpenShift Container Platform cluster. 1.1. Glossary of common terms for OpenShift Container Platform storage This glossary defines common terms that are used in the storage content. Access modes Volume access modes describe volume capabilities. You can use access modes to match persistent volume claim (PVC) and persistent volume (PV). The following are the examples of access modes: ReadWriteOnce (RWO) ReadOnlyMany (ROX) ReadWriteMany (RWX) ReadWriteOncePod (RWOP) Cinder The Block Storage service for Red Hat OpenStack Platform (RHOSP) which manages the administration, security, and scheduling of all volumes. Config map A config map provides a way to inject configuration data into pods. You can reference the data stored in a config map in a volume of type ConfigMap . Applications running in a pod can use this data. Container Storage Interface (CSI) An API specification for the management of container storage across different container orchestration (CO) systems. Dynamic Provisioning The framework allows you to create storage volumes on-demand, eliminating the need for cluster administrators to pre-provision persistent storage. Ephemeral storage Pods and containers can require temporary or transient local storage for their operation. The lifetime of this ephemeral storage does not extend beyond the life of the individual pod, and this ephemeral storage cannot be shared across pods. Fiber channel A networking technology that is used to transfer data among data centers, computer servers, switches and storage. FlexVolume FlexVolume is an out-of-tree plugin interface that uses an exec-based model to interface with storage drivers. You must install the FlexVolume driver binaries in a pre-defined volume plugin path on each node and in some cases the control plane nodes. fsGroup The fsGroup defines a file system group ID of a pod. iSCSI Internet Small Computer Systems Interface (iSCSI) is an Internet Protocol-based storage networking standard for linking data storage facilities. An iSCSI volume allows an existing iSCSI (SCSI over IP) volume to be mounted into your Pod. hostPath A hostPath volume in an OpenShift Container Platform cluster mounts a file or directory from the host node's filesystem into your pod. KMS key The Key Management Service (KMS) helps you achieve the required level of encryption of your data across different services. you can use the KMS key to encrypt, decrypt, and re-encrypt data. Local volumes A local volume represents a mounted local storage device such as a disk, partition or directory. NFS A Network File System (NFS) that allows remote hosts to mount file systems over a network and interact with those file systems as though they are mounted locally. This enables system administrators to consolidate resources onto centralized servers on the network. OpenShift Data Foundation A provider of agnostic persistent storage for OpenShift Container Platform supporting file, block, and object storage, either in-house or in hybrid clouds Persistent storage Pods and containers can require permanent storage for their operation. OpenShift Container Platform uses the Kubernetes persistent volume (PV) framework to allow cluster administrators to provision persistent storage for a cluster. Developers can use PVC to request PV resources without having specific knowledge of the underlying storage infrastructure. Persistent volumes (PV) OpenShift Container Platform uses the Kubernetes persistent volume (PV) framework to allow cluster administrators to provision persistent storage for a cluster. Developers can use PVC to request PV resources without having specific knowledge of the underlying storage infrastructure. Persistent volume claims (PVCs) You can use a PVC to mount a PersistentVolume into a Pod. You can access the storage without knowing the details of the cloud environment. Pod One or more containers with shared resources, such as volume and IP addresses, running in your OpenShift Container Platform cluster. A pod is the smallest compute unit defined, deployed, and managed. Reclaim policy A policy that tells the cluster what to do with the volume after it is released. A volume's reclaim policy can be Retain , Recycle , or Delete . Role-based access control (RBAC) Role-based access control (RBAC) is a method of regulating access to computer or network resources based on the roles of individual users within your organization. Stateless applications A stateless application is an application program that does not save client data generated in one session for use in the session with that client. Stateful applications A stateful application is an application program that saves data to persistent disk storage. A server, client, and applications can use a persistent disk storage. You can use the Statefulset object in OpenShift Container Platform to manage the deployment and scaling of a set of Pods, and provides guarantee about the ordering and uniqueness of these Pods. Static provisioning A cluster administrator creates a number of PVs. PVs contain the details of storage. PVs exist in the Kubernetes API and are available for consumption. Storage OpenShift Container Platform supports many types of storage, both for on-premise and cloud providers. You can manage container storage for persistent and non-persistent data in an OpenShift Container Platform cluster. Storage class A storage class provides a way for administrators to describe the classes of storage they offer. Different classes might map to quality of service levels, backup policies, arbitrary policies determined by the cluster administrators. VMware vSphere's Virtual Machine Disk (VMDK) volumes Virtual Machine Disk (VMDK) is a file format that describes containers for virtual hard disk drives that is used in virtual machines. 1.2. Storage types OpenShift Container Platform storage is broadly classified into two categories, namely ephemeral storage and persistent storage. 1.2.1. Ephemeral storage Pods and containers are ephemeral or transient in nature and designed for stateless applications. Ephemeral storage allows administrators and developers to better manage the local storage for some of their operations. For more information about ephemeral storage overview, types, and management, see Understanding ephemeral storage . 1.2.2. Persistent storage Stateful applications deployed in containers require persistent storage. OpenShift Container Platform uses a pre-provisioned storage framework called persistent volumes (PV) to allow cluster administrators to provision persistent storage. The data inside these volumes can exist beyond the lifecycle of an individual pod. Developers can use persistent volume claims (PVCs) to request storage requirements. For more information about persistent storage overview, configuration, and lifecycle, see Understanding persistent storage . 1.3. Container Storage Interface (CSI) CSI is an API specification for the management of container storage across different container orchestration (CO) systems. You can manage the storage volumes within the container native environments, without having specific knowledge of the underlying storage infrastructure. With the CSI, storage works uniformly across different container orchestration systems, regardless of the storage vendors you are using. For more information about CSI, see Using Container Storage Interface (CSI) . 1.4. Dynamic Provisioning Dynamic Provisioning allows you to create storage volumes on-demand, eliminating the need for cluster administrators to pre-provision storage. For more information about dynamic provisioning, see Dynamic provisioning .	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.16/html/storage/storage-overview
Chapter 42. Kernel	Chapter 42. Kernel Heterogeneous memory management included as a Technology Preview Red Hat Enterprise Linux 7.3 offers the heterogeneous memory management (HMM) feature as a Technology Preview. This feature has been added to the kernel as a helper layer for devices that want to mirror a process address space into their own memory management unit (MMU). Thus a non-CPU device processor is able to read system memory using the unified system address space. To enable this feature, add experimental_hmm=enable to the kernel command line. (BZ#1230959) User namespace This feature provides additional security to servers running Linux containers by providing better isolation between the host and the containers. Administrators of a container are no longer able to perform administrative operations on the host, which increases security. (BZ#1138782) libocrdma RoCE support on Oce141xx cards As a Technology Preview, the ocrdma module and the libocrdma package support the Remote Direct Memory Access over Converged Ethernet (RoCE) functionality on all network adapters in the Oce141xx family. (BZ#1334675) No-IOMMU mode for VFIO drivers As a Technology Preview, this update adds No-IOMMU mode for virtual function I/O (VFIO) drivers. The No-IOMMU mode provides the user with full user-space I/O (UIO) access to a direct memory access (DMA)-capable device without a I/O memory management unit (IOMMU). Note that in addition to not being supported, using this mode is not secure due to the lack of I/O management provided by IOMMU. (BZ# 1299662 ) criu rebased to version 2.3 Red Hat Enterprise Linux 7.2 introduced the criu tool as a Technology Preview. This tool implements Checkpoint/Restore in User-space (CRIU) , which can be used to freeze a running application and store it as a collection of files. Later, the application can be restored from its frozen state. Note that the criu tool depends on Protocol Buffers , a language-neutral, platform-neutral extensible mechanism for serializing structured data. The protobuf and protobuf-c packages, which provide this dependency, were also introduced in Red Hat Enterprise Linux 7.2 as a Technology Preview. With Red Hat Enterprise Linux 7.3, the criu packages have been upgraded to upstream version 2.3, which provides a number of bug fixes and enhancements over the version. Notably, criu is now available also on Red Hat Enterprise Linux for POWER, little endian. Additionally, criu can now be used for following applications running in a Red Hat Enterprise Linux 7 runc container: vsftpd apache httpd sendmail postgresql mongodb mariadb mysql tomcat dnsmasq (BZ# 1296578 ) The ibmvnic Device Driver has been added The ibmvnic Device Driver has been introduced as a Technology Preview in Red Hat Enterprise Linux 7.3 for IBM POWER architectures. vNIC (Virtual Network Interface Controller) is a new PowerVM virtual networking technology that delivers enterprise capabilities and simplifies network management. It is a high-performance, efficient technology that when combined with SR-IOV NIC provides bandwidth control Quality of Service (QoS) capabilities at the virtual NIC level. vNIC significantly reduces virtualization overhead, resulting in lower latencies and fewer server resources, including CPU and memory, required for network virtualization. (BZ#947163) Kexec as a Technology Preview The kexec system call has been provided as a Technology Preview. This system call enables loading and booting into another kernel from the currently running kernel, thus performing the function of the boot loader from within the kernel. Hardware initialization, which is normally done during a standard system boot, is not performed during a kexec boot, which significantly reduces the time required for a reboot. (BZ#1460849)	null	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/7.3_release_notes/technology_previews_kernel
Chapter 12. Multiple branches in Business Central	Chapter 12. Multiple branches in Business Central Multiple branches support in Business Central provides the ability to create a new branch based on an existing one, including all of its assets. All new, imported, and sample projects open in the default master branch. You can create as many branches as you need and can work on multiple branches interchangeably without impacting the original project on the master branch. Red Hat Decision Manager 7.13 includes support for persisting branches, which means that Business Central remembers the last branch used and will open in that branch when you log back in. 12.1. Creating branches You can create new branches in Business Central and name them whatever you like. Initially, you will only have the default master branch. When you create a new branch for a project, you are making a copy of the selected branch. You can make changes to the project on the new branch without impacting the original master branch version. Procedure In Business Central, go to Menu Design Projects . Click the project to create the new branch, for example the Mortgages sample project. Click master Add Branch . Figure 12.1. Create the new branch menu Type testBranch1 in the Name field and select master from the Add Branch window. Where testBranch1 is any name that you want to name the new branch. Select the branch that will be the base for the new branch from the Add Branch window. This can be any existing branch. Click Add . Figure 12.2. Add the new branch window After adding the new branch, you will be redirected to it, and it will contain all of the assets that you had in your project in the master branch. 12.2. Selecting branches You can switch between branches to make modifications to project assets and test the revised functionality. Procedure Click the current branch name and select the desired project branch from the drop-down list. Figure 12.3. Select a branch menu After selecting the branch, you are redirected to that branch containing the project and all of the assets that you had defined. 12.3. Deleting branches You can delete any branch except for the master branch. Business Central does not allow you to delete the master branch to avoid corrupting your environment. You must be in any branch other than master for the following procedure to work. Procedure Click in the upper-right corner of the screen and select Delete Branch . Figure 12.4. Delete a branch In the Delete Branch window, enter the name of the branch you want to delete. Click Delete Branch . The branch is deleted and the project branch switches to the master branch. 12.4. Building and deploying projects After your project is developed, you can build the project from the specified branch in Business Central and deploy it to the configured KIE Server. Procedure In Business Central, go to Menu Design Projects and click the project name. In the upper-right corner, click Deploy to build the project and deploy it to KIE Server. Note You can also select the Build & Install option to build the project and publish the KJAR file to the configured Maven repository without deploying to a KIE Server. In a development environment, you can click Deploy to deploy the built KJAR file to a KIE Server without stopping any running instances (if applicable), or click Redeploy to deploy the built KJAR file and replace all instances. The time you deploy or redeploy the built KJAR, the deployment unit (KIE container) is automatically updated in the same target KIE Server. In a production environment, the Redeploy option is disabled and you can click Deploy only to deploy the built KJAR file to a new deployment unit (KIE container) on a KIE Server. To configure the KIE Server environment mode, set the org.kie.server.mode system property to org.kie.server.mode=development or org.kie.server.mode=production . To configure the deployment behavior for a corresponding project in Business Central, go to project Settings General Settings Version and toggle the Development Mode option. By default, KIE Server and all new projects in Business Central are in development mode. You cannot deploy a project with Development Mode turned on or with a manually added SNAPSHOT version suffix to a KIE Server that is in production mode. If the build fails, address any problems described in the Alerts panel at the bottom of the screen. To review project deployment details, click View deployment details in the deployment banner at the top of the screen or in the Deploy drop-down menu. This option directs you to the Menu Deploy Execution Servers page. For more information about project deployment options, see Packaging and deploying an Red Hat Decision Manager project .	null	https://docs.redhat.com/en/documentation/red_hat_decision_manager/7.13/html/deploying_and_managing_red_hat_decision_manager_services/multiple-branches-con
Chapter 9. Consoles and logging during installation	Chapter 9. Consoles and logging during installation The Red Hat Enterprise Linux installer uses the tmux terminal multiplexer to display and control several windows in addition to the main interface. Each of these windows serve a different purpose; they display several different logs, which can be used to troubleshoot issues during the installation process. One of the windows provides an interactive shell prompt with root privileges, unless this prompt was specifically disabled using a boot option or a Kickstart command. The terminal multiplexer is running in virtual console 1. To switch from the actual installation environment to tmux , press Ctrl + Alt + F1 . To go back to the main installation interface which runs in virtual console 6, press Ctrl + Alt + F6 . During the text mode installation, start in virtual console 1 ( tmux ), and switching to console 6 will open a shell prompt instead of a graphical interface. The console running tmux has five available windows; their contents are described in the following table, along with keyboard shortcuts. Note that the keyboard shortcuts are two-part: first press Ctrl + b , then release both keys, and press the number key for the window you want to use. You can also use Ctrl + b n , Alt+ Tab , and Ctrl + b p to switch to the or tmux window, respectively. Table 9.1. Available tmux windows Shortcut Contents Ctrl + b 1 Main installation program window. Contains text-based prompts (during text mode installation or if you use VNC direct mode), and also some debugging information. Ctrl + b 2 Interactive shell prompt with root privileges. Ctrl + b 3 Installation log; displays messages stored in /tmp/anaconda.log . Ctrl + b 4 Storage log; displays messages related to storage devices and configuration, stored in /tmp/storage.log . Ctrl + b 5 Program log; displays messages from utilities executed during the installation process, stored in /tmp/program.log .	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/9/html/interactively_installing_rhel_from_installation_media/consoles-logging-during-install_rhel-installer
4.5. Migrating with virt-manager	4.5. Migrating with virt-manager This section covers migrating a KVM guest virtual machine with virt-manager from one host physical machine to another. Open virt-manager Open virt-manager . Choose Applications System Tools Virtual Machine Manager from the main menu bar to launch virt-manager . Figure 4.1. Virt-Manager main menu Connect to the target host physical machine Connect to the target host physical machine by clicking on the File menu, then click Add Connection . Figure 4.2. Open Add Connection window Add connection The Add Connection window appears. Figure 4.3. Adding a connection to the target host physical machine Enter the following details: Hypervisor : Select QEMU/KVM . Method : Select the connection method. Username : Enter the user name for the remote host physical machine. Hostname : Enter the host name for the remote host physical machine. Click the Connect button. An SSH connection is used in this example, so the specified user's password must be entered in the step. Figure 4.4. Enter password Migrate guest virtual machines Open the list of guests inside the source host physical machine (click the small triangle on the left of the host name) and right click on the guest that is to be migrated ( guest1-rhel6-64 in this example) and click Migrate . Figure 4.5. Choosing the guest to be migrated In the New Host field, use the drop-down list to select the host physical machine you wish to migrate the guest virtual machine to and click Migrate . Figure 4.6. Choosing the destination host physical machine and starting the migration process A progress window will appear. Figure 4.7. Progress window virt-manager now displays the newly migrated guest virtual machine running in the destination host. The guest virtual machine that was running in the source host physical machine is now listed inthe Shutoff state. Figure 4.8. Migrated guest virtual machine running in the destination host physical machine Optional - View the storage details for the host physical machine In the Edit menu, click Connection Details , the Connection Details window appears. Click the Storage tab. The iSCSI target details for the destination host physical machine is shown. Note that the migrated guest virtual machine is listed as using the storage Figure 4.9. Storage details This host was defined by the following XML configuration: <pool type='iscsi'> <name>iscsirhel6guest</name> <source> <host name='virtlab22.example.com.'/> <device path='iqn.2001-05.com.iscsivendor:0-8a0906-fbab74a06-a700000017a4cc89-rhevh'/> </source> <target> <path>/dev/disk/by-path</path> </target> </pool> ... Figure 4.10. XML configuration for the destination host physical machine	[ "<pool type='iscsi'> <name>iscsirhel6guest</name> <source> <host name='virtlab22.example.com.'/> <device path='iqn.2001-05.com.iscsivendor:0-8a0906-fbab74a06-a700000017a4cc89-rhevh'/> </source> <target> <path>/dev/disk/by-path</path> </target> </pool>" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/virtualization_administration_guide/sect-virtualization-kvm_live_migration-migrating_with_virt_manager