Chapter 2. Configuring the monitoring stack The OpenShift Container Platform installation program provides only a low number of configuration options before installation. Configuring most OpenShift Container Platform framework components, including the cluster monitoring stack, happens after the installation. This section explains what configuration is supported, shows how to configure the monitoring stack, and demonstrates several common configuration scenarios. 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. 2.1. Prerequisites 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. 2.2. Maintenance and support for monitoring Not all configuration options for the monitoring stack are exposed. The only supported way of configuring OpenShift Container Platform monitoring is by configuring the Cluster Monitoring Operator (CMO) using the options described in the Config map reference for the Cluster Monitoring Operator . Do not use other configurations, as they are unsupported. Configuration paradigms might change across Prometheus releases, and such cases can only be handled gracefully if all configuration possibilities are controlled. If you use configurations other than those described in the Config map reference for the Cluster Monitoring Operator , your changes will disappear because the CMO automatically reconciles any differences and resets any unsupported changes back to the originally defined state by default and by design. Important Installing another Prometheus instance is not supported by the Red Hat Site Reliability Engineers (SRE). 2.2.1. Support considerations for monitoring Note Backward compatibility for metrics, recording rules, or alerting rules is not guaranteed. The following modifications are explicitly not supported: Creating additional ServiceMonitor , PodMonitor , and PrometheusRule objects in the openshift-* and kube-* projects. Modifying any resources or objects deployed in the openshift-monitoring or openshift-user-workload-monitoring projects. The resources created by the OpenShift Container Platform monitoring stack are not meant to be used by any other resources, as there are no guarantees about their backward compatibility. Note The Alertmanager configuration is deployed as the alertmanager-main secret resource in the openshift-monitoring namespace. If you have enabled a separate Alertmanager instance for user-defined alert routing, an Alertmanager configuration is also deployed as the alertmanager-user-workload secret resource in the openshift-user-workload-monitoring namespace. To configure additional routes for any instance of Alertmanager, you need to decode, modify, and then encode that secret. This procedure is a supported exception to the preceding statement. Modifying resources of the stack. The OpenShift Container Platform monitoring stack ensures its resources are always in the state it expects them to be. If they are modified, the stack will reset them. Deploying user-defined workloads to openshift-* , and kube-* projects. These projects are reserved for Red Hat provided components and they should not be used for user-defined workloads. Manually deploying monitoring resources into namespaces that have the openshift.io/cluster-monitoring: "true" label. Adding the openshift.io/cluster-monitoring: "true" label to namespaces. This label is reserved only for the namespaces with core OpenShift Container Platform components and Red Hat certified components. Installing custom Prometheus instances on OpenShift Container Platform. A custom instance is a Prometheus custom resource (CR) managed by the Prometheus Operator. Enabling symptom based monitoring by using the Probe custom resource definition (CRD) in Prometheus Operator. Installing custom Prometheus instances on OpenShift Container Platform. A custom instance is a Prometheus custom resource (CR) managed by the Prometheus Operator. Modifying the default platform monitoring components. You should not modify any of the components defined in the cluster-monitoring-config config map. Red Hat SRE uses these components to monitor the core cluster components and Kubernetes services. 2.2.2. Support policy for monitoring Operators Monitoring Operators ensure that OpenShift Container Platform monitoring resources function as designed and tested. If Cluster Version Operator (CVO) control of an Operator is overridden, the Operator does not respond to configuration changes, reconcile the intended state of cluster objects, or receive updates. While overriding CVO control for an Operator can be helpful during debugging, this is unsupported and the cluster administrator assumes full control of the individual component configurations and upgrades. Overriding the Cluster Version Operator The spec.overrides parameter can be added to the configuration for the CVO to allow administrators to provide a list of overrides to the behavior of the CVO for a component. Setting the spec.overrides[].unmanaged parameter to true for a component blocks cluster upgrades and alerts the administrator after a CVO override has been set: Disabling ownership via cluster version overrides prevents upgrades. Please remove overrides before continuing. Warning Setting a CVO override puts the entire cluster in an unsupported state and prevents the monitoring stack from being reconciled to its intended state. This impacts the reliability features built into Operators and prevents updates from being received. Reported issues must be reproduced after removing any overrides for support to proceed. 2.2.3. Support version matrix for monitoring components The following matrix contains information about versions of monitoring components for OpenShift Container Platform 4.10 and later releases: Table 2.1. OpenShift Container Platform and component versions OpenShift Container Platform Prometheus Operator Prometheus Prometheus Adapter Alertmanager kube-state-metrics agent node-exporter agent Thanos 4.12 0.60.1 2.39.1 0.10.0 0.24.0 2.6.0 1.4.0 0.28.1 4.11 0.57.0 2.36.2 0.9.1 0.24.0 2.5.0 1.3.1 0.26.0 4.10 0.53.1 2.32.1 0.9.1 0.23.0 2.3.0 1.3.1 0.23.2 Note The openshift-state-metrics agent and Telemeter Client are OpenShift-specific components. Therefore, their versions correspond with the versions of OpenShift Container Platform. 2.3. Preparing to configure the monitoring stack You can configure the monitoring stack by creating and updating monitoring config maps. These config maps configure the Cluster Monitoring Operator (CMO), which in turn configures the components of the monitoring stack. 2.3.1. Creating a cluster monitoring config map You can configure the core OpenShift Container Platform monitoring components by creating the cluster-monitoring-config ConfigMap object in the openshift-monitoring project. The Cluster Monitoring Operator (CMO) then configures the core components of the monitoring stack. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have installed the OpenShift CLI ( oc ). Procedure Check whether the cluster-monitoring-config ConfigMap object exists: USD oc -n openshift-monitoring get configmap cluster-monitoring-config If the ConfigMap object does not exist: Create the following YAML manifest. In this example the file is called cluster-monitoring-config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | Apply the configuration to create the ConfigMap object: USD oc apply -f cluster-monitoring-config.yaml 2.3.2. Creating a user-defined workload monitoring config map You can configure the user workload monitoring components with the user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring project. The Cluster Monitoring Operator (CMO) then configures the components that monitor user-defined projects. Note If you enable monitoring for user-defined projects, the user-workload-monitoring-config ConfigMap object is created by default. When you save your changes to the user-workload-monitoring-config ConfigMap object, some or all of the pods in the openshift-user-workload-monitoring project might be redeployed. It can sometimes take a while for these components to redeploy. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have installed the OpenShift CLI ( oc ). Procedure Check whether the user-workload-monitoring-config ConfigMap object exists: USD oc -n openshift-user-workload-monitoring get configmap user-workload-monitoring-config If the user-workload-monitoring-config ConfigMap object does not exist: Create the following YAML manifest. In this example the file is called user-workload-monitoring-config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: | Apply the configuration to create the ConfigMap object: USD oc apply -f user-workload-monitoring-config.yaml Note Configurations applied to the user-workload-monitoring-config ConfigMap object are not activated unless a cluster administrator has enabled monitoring for user-defined projects. Additional resources Enabling monitoring for user-defined projects 2.4. Granting users permissions for core platform monitoring 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 for core platform monitoring. You can grant the permissions by assigning one of the following monitoring roles or cluster roles: Name Description Project cluster-monitoring-metrics-api Users with this role have the ability to access Thanos Querier API endpoints. Additionally, it grants access to the core platform Prometheus API and user-defined Thanos Ruler API endpoints. openshift-monitoring cluster-monitoring-operator-alert-customization Users with this role can manage AlertingRule and AlertRelabelConfig resources for core platform monitoring. These permissions are required for the alert customization feature. openshift-monitoring monitoring-alertmanager-edit Users with this role can manage the Alertmanager API for core platform monitoring. They can also manage alert silences in the Administrator perspective of the OpenShift Container Platform web console. openshift-monitoring monitoring-alertmanager-view Users with this role can monitor the Alertmanager API for core platform monitoring. They can also view alert silences in the Administrator perspective of the OpenShift Container Platform web console. openshift-monitoring cluster-monitoring-view Users with this cluster role have the same access rights as cluster-monitoring-metrics-api role, with additional permissions, providing access to the /federate endpoint for the user-defined Prometheus. Must be bound with ClusterRoleBinding to gain access to the /federate endpoint for the user-defined Prometheus. Additional resources Granting user permissions by using the web console Granting user permissions by using the CLI 2.5. Configuring the monitoring stack In OpenShift Container Platform 4.12, you can configure the monitoring stack using the cluster-monitoring-config or user-workload-monitoring-config ConfigMap objects. Config maps configure the Cluster Monitoring Operator (CMO), which in turn configures the components of the stack. Prerequisites If you are configuring core OpenShift Container Platform monitoring components : You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. If you are configuring components that monitor user-defined projects : 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 ConfigMap object. To configure core OpenShift Container Platform monitoring components : Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add your configuration under data/config.yaml as a key-value pair <component_name>: <component_configuration> : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | <component>: <configuration_for_the_component> Substitute <component> and <configuration_for_the_component> accordingly. The following example ConfigMap object configures a persistent volume claim (PVC) for Prometheus. This relates to the Prometheus instance that monitors core OpenShift Container Platform components only: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 1 volumeClaimTemplate: spec: storageClassName: fast volumeMode: Filesystem resources: requests: storage: 40Gi 1 Defines the Prometheus component and the subsequent lines define its configuration. To configure components that monitor user-defined projects : 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 your configuration under data/config.yaml as a key-value pair <component_name>: <component_configuration> : apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: | <component>: <configuration_for_the_component> Substitute <component> and <configuration_for_the_component> accordingly. The following example ConfigMap object configures a data retention period and minimum container resource requests for Prometheus. This relates to the Prometheus instance that monitors user-defined projects only: apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: | prometheus: 1 retention: 24h 2 resources: requests: cpu: 200m 3 memory: 2Gi 4 1 Defines the Prometheus component and the subsequent lines define its configuration. 2 Configures a twenty-four hour data retention period for the Prometheus instance that monitors user-defined projects. 3 Defines a minimum resource request of 200 millicores for the Prometheus container. 4 Defines a minimum pod resource request of 2 GiB of memory for the Prometheus container. Note The Prometheus config map component is called prometheusK8s in the cluster-monitoring-config ConfigMap object and prometheus in the user-workload-monitoring-config ConfigMap object. Save the file to apply the changes to the ConfigMap object. 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. Additional resources See Preparing to configure the monitoring stack for steps to create monitoring config maps Enabling monitoring for user-defined projects 2.6. Configurable monitoring components This table shows the monitoring components you can configure and the keys used to specify the components in the cluster-monitoring-config and user-workload-monitoring-config ConfigMap objects: Table 2.2. Configurable monitoring components Component cluster-monitoring-config config map key user-workload-monitoring-config config map key Prometheus Operator prometheusOperator prometheusOperator Prometheus prometheusK8s prometheus Alertmanager alertmanagerMain alertmanager kube-state-metrics kubeStateMetrics openshift-state-metrics openshiftStateMetrics Telemeter Client telemeterClient Prometheus Adapter k8sPrometheusAdapter Thanos Querier thanosQuerier Thanos Ruler thanosRuler Note The Prometheus key is called prometheusK8s in the cluster-monitoring-config ConfigMap object and prometheus in the user-workload-monitoring-config ConfigMap object. 2.7. Using node selectors to move monitoring components By using the nodeSelector constraint with labeled nodes, you can move any of the monitoring stack components to specific nodes. By doing so, you can 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 segregate workloads based on specific requirements or policies. 2.7.1. How node selectors work with other constraints If you move monitoring components by using node selector constraints, be aware that other constraints to control pod scheduling might exist for a cluster: Topology spread constraints might be in place to control pod placement. Hard anti-affinity rules are in place for Prometheus, Thanos Querier, Alertmanager, and other monitoring components to ensure that multiple pods for these components are always spread across different nodes and are therefore always highly available. When scheduling pods onto nodes, the pod scheduler tries to satisfy all existing constraints when determining pod placement. That is, all constraints compound when the pod scheduler determines which pods will be placed on which nodes. Therefore, if you configure a node selector constraint but existing constraints cannot all be satisfied, the pod scheduler cannot match all constraints and will not schedule a pod for placement onto a node. To maintain resilience and high availability for monitoring components, ensure that enough nodes are available and match all constraints when you configure a node selector constraint to move a component. Additional resources Understanding how to update labels on nodes Placing pods on specific nodes using node selectors Placing pods relative to other pods using affinity and anti-affinity rules Controlling pod placement by using pod topology spread constraints Configuring pod topology spread constraints for monitoring Kubernetes documentation about node selectors 2.7.2. Moving monitoring components to different nodes To specify the nodes in your cluster on which monitoring stack components will run, configure the nodeSelector constraint in the component's ConfigMap object to match labels assigned to the nodes. Note You cannot add a node selector constraint directly to an existing scheduled pod. Prerequisites If you are configuring core OpenShift Container Platform monitoring components : You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. If you are configuring components that monitor user-defined projects : 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> Edit the ConfigMap object: To move a component that monitors core OpenShift Container Platform projects : Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Specify the node labels for the nodeSelector constraint for the component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-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. To move a component that monitors user-defined projects : 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 See Preparing to configure the monitoring stack for steps to create monitoring config maps Enabling monitoring for user-defined projects 2.8. Assigning tolerations to monitoring components You can assign tolerations to any of the monitoring stack components to enable moving them to tainted nodes. Prerequisites If you are configuring core OpenShift Container Platform monitoring components : You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. If you are configuring components that monitor user-defined projects : 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 ConfigMap object: To assign tolerations to a component that monitors core OpenShift Container Platform projects : Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Specify tolerations for the component: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-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 alertmanagerMain component to tolerate the example taint: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: tolerations: - key: "key1" operator: "Equal" value: "value1" effect: "NoSchedule" To assign tolerations to a component that monitors user-defined projects : 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 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 See Preparing to configure the monitoring stack for steps to create monitoring config maps Enabling monitoring for user-defined projects See the OpenShift Container Platform documentation on taints and tolerations See the Kubernetes documentation on taints and tolerations 2.9. Setting the body size limit for metrics scraping By default, no limit exists for the uncompressed body size for data returned from scraped metrics targets. You can set a body size limit to help avoid situations in which Prometheus consumes excessive amounts of memory when scraped targets return a response that contains a large amount of data. In addition, by setting a body size limit, you can reduce the impact that a malicious target might have on Prometheus and on the cluster as a whole. After you set a value for enforcedBodySizeLimit , the alert PrometheusScrapeBodySizeLimitHit fires when at least one Prometheus scrape target replies with a response body larger than the configured value. Note If metrics data scraped from a target has an uncompressed body size exceeding the configured size limit, the scrape fails. Prometheus then considers this target to be down and sets its up metric value to 0 , which can trigger the TargetDown alert. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring namespace: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add a value for enforcedBodySizeLimit to data/config.yaml/prometheusK8s to limit the body size that can be accepted per target scrape: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: |- prometheusK8s: enforcedBodySizeLimit: 40MB 1 1 Specify the maximum body size for scraped metrics targets. This enforcedBodySizeLimit example limits the uncompressed size per target scrape to 40 megabytes. Valid numeric values use the Prometheus data size format: B (bytes), KB (kilobytes), MB (megabytes), GB (gigabytes), TB (terabytes), PB (petabytes), and EB (exabytes). The default value is 0 , which specifies no limit. You can also set the value to automatic to calculate the limit automatically based on cluster capacity. Save the file to apply the changes. The new configuration is applied automatically. Additional resources Prometheus scrape configuration documentation 2.10. Configuring a dedicated service monitor You can configure OpenShift Container Platform core platform monitoring to use dedicated service monitors to collect metrics for the resource metrics pipeline. When enabled, a dedicated service monitor exposes two additional metrics from the kubelet endpoint and sets the value of the honorTimestamps field to true. By enabling a dedicated service monitor, you can improve the consistency of Prometheus Adapter-based CPU usage measurements used by, for example, the oc adm top pod command or the Horizontal Pod Autoscaler. 2.10.1. Enabling a dedicated service monitor You can configure core platform monitoring to use a dedicated service monitor by configuring the dedicatedServiceMonitors key in the cluster-monitoring-config ConfigMap object in the openshift-monitoring namespace. Prerequisites You have installed the OpenShift CLI ( oc ). You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. Procedure Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring namespace: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add an enabled: true key-value pair as shown in the following sample: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | k8sPrometheusAdapter: dedicatedServiceMonitors: enabled: true 1 1 Set the value of the enabled field to true to deploy a dedicated service monitor that exposes the kubelet /metrics/resource endpoint. Save the file to apply the changes automatically. Warning When you save changes to a cluster-monitoring-config config map, the pods and other resources in the openshift-monitoring project might be redeployed. The running monitoring processes in that project might also restart. 2.11. 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. 2.11.1. 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. 2.11.2. Configuring a persistent volume claim To use a persistent volume (PV) for monitoring components, you must configure a persistent volume claim (PVC). Prerequisites If you are configuring core OpenShift Container Platform monitoring components : You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. If you are configuring components that monitor user-defined projects : 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 ConfigMap object: To configure a PVC for a component that monitors core OpenShift Container Platform projects : Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add your PVC configuration for the component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | <component>: 1 volumeClaimTemplate: spec: storageClassName: <storage_class> 2 resources: requests: storage: <amount_of_storage> 3 1 Specify the core 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. See the Kubernetes documentation on PersistentVolumeClaims for information on how to specify volumeClaimTemplate . The following example configures a PVC that claims persistent storage for the Prometheus instance that monitors core OpenShift Container Platform components: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s : volumeClaimTemplate: spec: storageClassName: my-storage-class resources: requests: storage: 40Gi To configure a PVC for a component that monitors user-defined projects : 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 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 component for user-defined monitoring 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. See the Kubernetes documentation on PersistentVolumeClaims for information on how to specify volumeClaimTemplate . The following example configures a PVC that claims persistent storage for Thanos Ruler: 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. 2.11.3. Resizing a persistent volume You can resize a persistent volume (PV) for monitoring components, such as Prometheus, Thanos Ruler, or 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 installed the OpenShift CLI ( oc ). If you are configuring core OpenShift Container Platform monitoring components : You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. You have configured at least one PVC for core OpenShift Container Platform monitoring components. If you are configuring components that monitor user-defined projects : 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. 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 ConfigMap object: If you are configuring core OpenShift Container Platform monitoring components : Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add a new storage size for the PVC configuration for the component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-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 100 gigabytes for the Prometheus instance that monitors core OpenShift Container Platform components: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: volumeClaimTemplate: spec: resources: requests: storage: 100Gi If you are configuring components that monitor user-defined projects : Note You can resize the volumes for the Thanos Ruler and for instances of Alertmanager and Prometheus that monitor user-defined projects. 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 Update the PVC configuration for the monitoring 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: 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 2.11.4. Modifying the retention time and size for Prometheus metrics data By default, Prometheus retains metrics data for the following durations: Core platform monitoring : 15 days Monitoring for user-defined projects : 24 hours You can modify the retention time to change how soon data is deleted by specifying a time value in the retention field. You can also configure the maximum amount of disk space the retained metrics data uses by specifying a size value in the retentionSize field. If the data reaches this size limit, Prometheus deletes the oldest data first until the disk space used is again below the limit. Note the following behaviors of these data retention settings: The size-based retention policy applies to all data block directories in the /prometheus directory, including persistent blocks, write-ahead log (WAL) data, and m-mapped chunks. Data in the /wal and /head_chunks directories counts toward the retention size limit, but Prometheus never purges data from these directories based on size- or time-based retention policies. Thus, if you set a retention size limit lower than the maximum size set for the /wal and /head_chunks directories, you have configured the system not to retain any data blocks in the /prometheus data directories. The size-based retention policy is applied only when Prometheus cuts a new data block, which occurs every two hours after the WAL contains at least three hours of data. If you do not explicitly define values for either retention or retentionSize , retention time defaults to 15 days for core platform monitoring and 24 hours for user-defined project monitoring. Retention size is not set. If you define values for both retention and retentionSize , both values apply. If any data blocks exceed the defined retention time or the defined size limit, Prometheus purges these data blocks. If you define a value for retentionSize and do not define retention , only the retentionSize value applies. If you do not define a value for retentionSize and only define a value for retention , only the retention value applies. If you set the retentionSize or retention value to 0 , the default settings apply. The default settings set retention time to 15 days for core platform monitoring and 24 hours for user-defined project monitoring. By default, retention size is not set. 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 If you are configuring core OpenShift Container Platform monitoring components : You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. If you are configuring components that monitor user-defined projects : 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 ConfigMap object: To modify the retention time and size for the Prometheus instance that monitors core OpenShift Container Platform projects : Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add the retention time and size configuration under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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 that monitors core OpenShift Container Platform components: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: retention: 24h retentionSize: 10GB To modify the retention time and size for the Prometheus instance that monitors user-defined projects : 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 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), or EB (exabytes). The following example sets the retention time to 24 hours and the retention size to 10 gigabytes for the Prometheus instance that monitors user-defined projects: 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. 2.11.5. 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 installed the OpenShift CLI ( oc ). A cluster administrator has enabled monitoring for user-defined projects. 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. 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 Creating a cluster monitoring config map Prometheus database storage requirements Recommended configurable storage technology Understanding persistent storage Optimizing storage Enabling monitoring for user-defined projects 2.12. 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 If you are configuring core OpenShift Container Platform monitoring components: You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. If you are configuring components that monitor user-defined projects: 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 same namespace as the Prometheus object for which you configure remote write: the openshift-monitoring namespace for default platform monitoring or the openshift-user-workload-monitoring namespace for user workload monitoring. Warning To reduce security risks, use HTTPS and authentication to send metrics to an endpoint. Procedure Follow these steps to configure remote write for default platform monitoring in the cluster-monitoring-config config map in the openshift-monitoring namespace. Note If you configure remote write for the Prometheus instance that monitors user-defined projects, make similar edits to the user-workload-monitoring-config config map in the openshift-user-workload-monitoring namespace. Note that the Prometheus config map component is called prometheus in the user-workload-monitoring-config ConfigMap object and not prometheusK8s , as it is in the cluster-monitoring-config ConfigMap object. Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add a remoteWrite: section under data/config.yaml/prometheusK8s . Add an endpoint URL and authentication credentials in this section: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" <endpoint_authentication_credentials> <your_write_relabel_configs> 1 1 The write relabel configuration settings. For <your_write_relabel_configs> substitute a list of write relabel configurations for metrics that you want to send to the remote endpoint. The following sample shows how to forward a single metric called my_metric : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" writeRelabelConfigs: - sourceLabels: [__name__] regex: 'my_metric' action: keep See the Prometheus relabel_config documentation for information about write relabel configuration options. Save the file to apply the changes. The new configuration is applied automatically. 2.12.1. 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, authentication using HTTP in an Authorization request header, 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. 2.12.1.1. Config map location for authentication settings The following shows the location of the authentication configuration in the ConfigMap object for default platform monitoring. apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" 1 <endpoint_authentication_details> 2 1 The URL of the remote write endpoint. 2 The required configuration details for the authentication method for the endpoint. Currently supported authentication methods are Amazon Web Services (AWS) Signature Version 4, authentication using HTTP in an Authorization request header, Basic authentication, OAuth 2.0, and TLS client. Note If you configure remote write for the Prometheus instance that monitors user-defined projects, edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring namespace. Note that the Prometheus config map component is called prometheus in the user-workload-monitoring-config ConfigMap object and not prometheusK8s , as it is in the cluster-monitoring-config ConfigMap object. 2.12.1.2. 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 default platform monitoring in the openshift-monitoring namespace. Sample YAML for AWS Signature Version 4 authentication The following shows the settings for a sigv4 secret named sigv4-credentials in the openshift-monitoring namespace. apiVersion: v1 kind: Secret metadata: name: sigv4-credentials namespace: openshift-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-monitoring namespace: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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. Sample YAML for Basic authentication The following shows sample Basic authentication settings for a Secret object named rw-basic-auth in the openshift-monitoring namespace: apiVersion: v1 kind: Secret metadata: name: rw-basic-auth namespace: openshift-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-monitoring namespace. It assumes that you have already set up authentication credentials for the endpoint. apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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. 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-monitoring namespace: apiVersion: v1 kind: Secret metadata: name: rw-bearer-auth namespace: openshift-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-monitoring namespace: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | enableUserWorkload: true prometheusK8s: 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. 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-monitoring namespace: apiVersion: v1 kind: Secret metadata: name: oauth2-credentials namespace: openshift-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-monitoring namespace: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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. Sample YAML for TLS client authentication The following shows sample TLS client settings for a tls Secret object named mtls-bundle in the openshift-monitoring namespace. apiVersion: v1 kind: Secret metadata: name: mtls-bundle namespace: openshift-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: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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. 2.12.2. 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 default platform monitoring in the openshift-monitoring namespace. Example configuration of remote write parameters with default values apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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 2.13. Adding cluster ID labels to metrics If you manage multiple OpenShift Container Platform clusters and use the remote write feature to send metrics data from these clusters to an external storage location, you can add cluster ID labels to identify the metrics data coming from different clusters. You can then query these labels to identify the source cluster for a metric and distinguish that data from similar metrics data sent by other clusters. This way, if you manage many clusters for multiple customers and send metrics data to a single centralized storage system, you can use cluster ID labels to query metrics for a particular cluster or customer. Creating and using cluster ID labels involves three general steps: Configuring the write relabel settings for remote write storage. Adding cluster ID labels to the metrics. Querying these labels to identify the source cluster or customer for a metric. 2.13.1. Creating cluster ID labels for metrics You can create cluster ID labels for metrics for default platform monitoring and for user workload monitoring. For default platform monitoring, you add cluster ID labels for metrics in the write_relabel settings for remote write storage in the cluster-monitoring-config config map in the openshift-monitoring namespace. For user workload monitoring, you edit the settings 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 installed the OpenShift CLI ( oc ). You have configured remote write storage. If you are configuring default platform monitoring components: You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config ConfigMap object. If you are configuring components that monitor user-defined projects: 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. Procedure Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Note If you configure cluster ID labels for metrics for the Prometheus instance that monitors user-defined projects, edit the user-workload-monitoring-config config map in the openshift-user-workload-monitoring namespace. Note that the Prometheus component is called prometheus in this config map and not prometheusK8s , which is the name used in the cluster-monitoring-config config map. In the writeRelabelConfigs: section under data/config.yaml/prometheusK8s/remoteWrite , add cluster ID relabel configuration values: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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 in default platform monitoring: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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 Configuring remote write storage Obtaining your cluster ID 2.14. Controlling the impact of unbound metrics attributes in user-defined projects Developers can create labels to define attributes for metrics in the form of key-value pairs. The number of potential key-value pairs corresponds to the number of possible values for an attribute. An attribute that has an unlimited number of potential values is called an unbound attribute. For example, a customer_id attribute is unbound because it has an infinite number of possible values. Every assigned key-value pair has a unique time series. Using many unbound attributes in labels can create exponentially more time series, which can impact Prometheus performance and available disk space. 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 To prevent issues caused by adding many unbound attributes, limit the number of scrape samples, label names, and unbound attributes you define for metrics. Also reduce the number of potential key-value pair combinations by using attributes that are bound to a limited set of possible values. 2.14.1. 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. 2.14.2. 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 Additional resources Creating a user-defined workload monitoring config map Enabling monitoring for user-defined projects See Determining why Prometheus is consuming a lot of disk space for steps to query which metrics have the highest number of scrape samples.

Commands:
Disabling ownership via cluster version overrides prevents upgrades. Please remove overrides before continuing.
oc -n openshift-monitoring get configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: |
oc apply -f cluster-monitoring-config.yaml
oc -n openshift-user-workload-monitoring get configmap user-workload-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: |
oc apply -f user-workload-monitoring-config.yaml
oc -n openshift-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | <component>: <configuration_for_the_component>
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 1 volumeClaimTemplate: spec: storageClassName: fast volumeMode: Filesystem resources: requests: storage: 40Gi
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>: <configuration_for_the_component>
apiVersion: v1 kind: ConfigMap metadata: name: user-workload-monitoring-config namespace: openshift-user-workload-monitoring data: config.yaml: | prometheus: 1 retention: 24h 2 resources: requests: cpu: 200m 3 memory: 2Gi 4
oc label nodes <node-name> <node-label>
oc -n openshift-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-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>: 1 nodeSelector: <node-label-1> 2 <node-label-2> 3 <...>
oc -n openshift-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | <component>: tolerations: <toleration_specification>
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: 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: | <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-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: |- prometheusK8s: enforcedBodySizeLimit: 40MB 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: | k8sPrometheusAdapter: dedicatedServiceMonitors: enabled: true 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: | <component>: 1 volumeClaimTemplate: spec: storageClassName: <storage_class> 2 resources: requests: storage: <amount_of_storage> 3
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s : volumeClaimTemplate: spec: storageClassName: my-storage-class resources: requests: storage: 40Gi
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-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | <component>: 1 volumeClaimTemplate: spec: resources: requests: storage: <amount_of_storage> 2
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: volumeClaimTemplate: spec: resources: requests: storage: 100Gi
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-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: retention: <time_specification> 1 retentionSize: <size_specification> 2
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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: | 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-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" 1 <endpoint_authentication_credentials> 2
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" <endpoint_authentication_credentials> <your_write_relabel_configs> 1
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" writeRelabelConfigs: - sourceLabels: [__name__] regex: 'my_metric' action: keep
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" 1 <endpoint_authentication_details> 2
apiVersion: v1 kind: Secret metadata: name: sigv4-credentials namespace: openshift-monitoring stringData: accessKey: <AWS_access_key> 1 secretKey: <AWS_secret_key> 2 type: Opaque
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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-monitoring stringData: user: <basic_username> 1 password: <basic_password> 2 type: Opaque
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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-monitoring stringData: token: <authentication_token> 1 type: Opaque
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | enableUserWorkload: true prometheusK8s: 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-monitoring stringData: id: <oauth2_id> 1 secret: <oauth2_secret> 2 type: Opaque
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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-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: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" <endpoint_authentication_credentials> writeRelabelConfigs: 1 - <relabel_config> 2
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: remoteWrite: - url: "https://remote-write-endpoint.example.com" writeRelabelConfigs: - sourceLabels: - __tmp_openshift_cluster_id__ 1 targetLabel: cluster_id 2 action: replace 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: | 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