Chapter 3. Configuring core platform monitoring 3.1. Preparing to configure core platform 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 which monitoring components can be configured and how to prepare for configuring the 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. 3.1.1. 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 config map. Table 3.1. Configurable core platform monitoring components Component cluster-monitoring-config config map key Prometheus Operator prometheusOperator Prometheus prometheusK8s Alertmanager alertmanagerMain Thanos Querier thanosQuerier kube-state-metrics kubeStateMetrics monitoring-plugin monitoringPlugin openshift-state-metrics openshiftStateMetrics Telemeter Client telemeterClient Prometheus Adapter k8sPrometheusAdapter 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. 3.1.2. Creating a cluster monitoring config map You can configure the core OpenShift Container Platform monitoring components by creating and updating the cluster-monitoring-config config map 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 3.1.3. 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. 3.1.3.1. 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. 3.1.3.2. 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. 3.2. Configuring performance and scalability for core platform 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. About performance and scalability 3.2.1. 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 3.2.1.1. Moving monitoring components to different nodes To specify the nodes in your cluster on which monitoring stack components will run, configure the nodeSelector constraint for the components in the cluster-monitoring-config config map to match labels assigned to the nodes. Note You cannot add a node selector constraint directly to an existing scheduled pod. Prerequisites 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 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 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. 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 Preparing to configure core platform monitoring stack Understanding how to update labels on nodes Placing pods on specific nodes using node selectors nodeSelector (Kubernetes documentation) 3.2.1.2. Assigning tolerations to monitoring components You can assign tolerations to any of the monitoring stack components to enable moving them to tainted nodes. Prerequisites 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 installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map 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" Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources Preparing to configure core platform monitoring stack Controlling pod placement using node taints Taints and Tolerations (Kubernetes documentation) 3.2.2. 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 scrape_config configuration (Prometheus documentation) 3.2.3. 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 core platform monitoring components in the openshift-monitoring namespace. 3.2.3.1. Specifying limits and requests To configure CPU and memory resources, specify values for resource limits and requests in the cluster-monitoring-config ConfigMap object in the openshift-monitoring namespace. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have created the ConfigMap object named cluster-monitoring-config . You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-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: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheusK8s: resources: limits: cpu: 500m memory: 3Gi requests: cpu: 200m memory: 500Mi thanosQuerier: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheusOperator: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi k8sPrometheusAdapter: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi kubeStateMetrics: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi telemeterClient: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi openshiftStateMetrics: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi nodeExporter: resources: limits: cpu: 50m memory: 150Mi requests: cpu: 20m memory: 50Mi monitoringPlugin: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheusOperatorAdmissionWebhook: resources: limits: cpu: 50m memory: 100Mi requests: cpu: 20m memory: 50Mi Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources About specifying limits and requests Kubernetes requests and limits documentation (Kubernetes documentation) 3.2.4. Choosing a metrics collection profile Important Metrics collection profile is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . To choose a metrics collection profile for core OpenShift Container Platform monitoring components, edit the cluster-monitoring-config ConfigMap object. Prerequisites You have installed the OpenShift CLI ( oc ). You have enabled Technology Preview features by using the FeatureGate custom resource (CR). You have created the cluster-monitoring-config ConfigMap object. You have access to the cluster as a user with the cluster-admin cluster role. Procedure Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add the metrics collection profile setting under data/config.yaml/prometheusK8s : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: collectionProfile: <metrics_collection_profile_name> 1 1 The name of the metrics collection profile. The available values are full or minimal . If you do not specify a value or if the collectionProfile key name does not exist in the config map, the default setting of full is used. The following example sets the metrics collection profile to minimal for the core platform instance of Prometheus: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: collectionProfile: minimal Save the file to apply the changes. The new configuration is applied automatically. Additional resources About metrics collection profiles Viewing a list of available metrics Enabling features using feature gates 3.2.5. Configuring pod topology spread constraints You can configure pod topology spread constraints for all the pods deployed by the Cluster Monitoring Operator 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 cluster-monitoring-config config map. Prerequisites 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 installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add the following settings under the data/config.yaml field to configure pod topology spread constraints: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-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 Prometheus apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: topologySpreadConstraints: - maxSkew: 1 topologyKey: monitoring whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: app.kubernetes.io/name: prometheus 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) 3.3. Storing and recording data for core platform 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. 3.3.1. 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. 3.3.1.1. 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. 3.3.1.2. 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. You have created the cluster-monitoring-config ConfigMap object. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map 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 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 Prometheus: Example PVC configuration 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 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) 3.3.1.3. Resizing a persistent volume You can resize a persistent volume (PV) for monitoring components, such as Prometheus 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 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. 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 cluster-monitoring-config config map 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: Example storage configuration for prometheusK8s apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: volumeClaimTemplate: spec: resources: requests: storage: 100Gi 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 3.3.2. Modifying retention time and size for Prometheus metrics data By default, Prometheus retains metrics data for 15 days for core platform monitoring. 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. You have created the cluster-monitoring-config ConfigMap object. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map 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: Example of setting retention time for Prometheus apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: retention: 24h retentionSize: 10GB 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 Preparing to configure core platform monitoring stack Prometheus database storage requirements Recommended configurable storage technology Understanding persistent storage Optimizing storage 3.3.3. 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. 3.3.3.1. 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. 3.3.4. Setting audit log levels for the Prometheus Adapter In default platform monitoring, you can configure the audit log level for the Prometheus Adapter. 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 You can set an audit log level for the Prometheus Adapter in the default openshift-monitoring project: Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add profile: in the k8sPrometheusAdapter/audit section under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | k8sPrometheusAdapter: audit: profile: <audit_log_level> 1 1 The audit log level to apply to the Prometheus Adapter. Set the audit log level by using one of the following values for the profile: parameter: None : Do not log events. Metadata : Log only the metadata for the request, such as user, timestamp, and so forth. Do not log the request text and the response text. Metadata is the default audit log level. Request : Log only the metadata and the request text but not the response text. This option does not apply for non-resource requests. RequestResponse : Log event metadata, request text, and response text. This option does not apply for non-resource requests. Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Verification In the config map, under k8sPrometheusAdapter/audit/profile , set the log level to Request and save the file. Confirm that the pods for the Prometheus Adapter are running. The following example lists the status of pods in the openshift-monitoring project: USD oc -n openshift-monitoring get pods Confirm that the audit log level and audit log file path are correctly configured: USD oc -n openshift-monitoring get deploy prometheus-adapter -o yaml Example output ... - --audit-policy-file=/etc/audit/request-profile.yaml - --audit-log-path=/var/log/adapter/audit.log Confirm that the correct log level has been applied in the prometheus-adapter deployment in the openshift-monitoring project: USD oc -n openshift-monitoring exec deploy/prometheus-adapter -c prometheus-adapter -- cat /etc/audit/request-profile.yaml Example output "apiVersion": "audit.k8s.io/v1" "kind": "Policy" "metadata": "name": "Request" "omitStages": - "RequestReceived" "rules": - "level": "Request" Note If you enter an unrecognized profile value for the Prometheus Adapter in the ConfigMap object, no changes are made to the Prometheus Adapter, and an error is logged by the Cluster Monitoring Operator. Review the audit log for the Prometheus Adapter: USD oc -n openshift-monitoring exec -c <prometheus_adapter_pod_name> -- cat /var/log/adapter/audit.log 3.3.5. Setting log levels for monitoring components You can configure the log level for Alertmanager, Prometheus Operator, Prometheus, and Thanos Querier. The following log levels can be applied to the relevant component in the cluster-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. You have created the cluster-monitoring-config ConfigMap object. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add logLevel: <log_level> for a component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-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 prometheusK8s , alertmanagerMain , prometheusOperator , and thanosQuerier . 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-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-monitoring get pods Note If an unrecognized logLevel value is included in the ConfigMap object, the pods for the component might not restart successfully. 3.3.6. 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. You have created the cluster-monitoring-config ConfigMap object. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add the queryLogFile parameter for Prometheus under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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-monitoring get pods Example output ... prometheus-operator-567c9bc75c-96wkj 2/2 Running 0 62m prometheus-k8s-0 6/6 Running 1 57m prometheus-k8s-1 6/6 Running 1 57m thanos-querier-56c76d7df4-2xkpc 6/6 Running 0 57m thanos-querier-56c76d7df4-j5p29 6/6 Running 0 57m ... Read the query log: USD oc -n openshift-monitoring exec prometheus-k8s-0 -- cat <path> Important Revert the setting in the config map after you have examined the logged query information. Additional resources Preparing to configure core platform monitoring stack 3.3.7. Enabling query logging for Thanos Querier For default platform monitoring in the openshift-monitoring project, you can enable the Cluster Monitoring Operator (CMO) to log all queries run by Thanos Querier. 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 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 You can enable query logging for Thanos Querier in the openshift-monitoring project: Edit the cluster-monitoring-config ConfigMap object in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add a thanosQuerier section under data/config.yaml and add values as shown in the following example: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | thanosQuerier: enableRequestLogging: <value> 1 logLevel: <value> 2 1 Set the value to true to enable logging and false to disable logging. The default value is false . 2 Set the value to debug , info , warn , or error . If no value exists for logLevel , the log level defaults to error . Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Verification Verify that the Thanos Querier pods are running. The following sample command lists the status of pods in the openshift-monitoring project: USD oc -n openshift-monitoring get pods Run a test query using the following sample commands as a model: USD token=`oc create token prometheus-k8s -n openshift-monitoring` USD oc -n openshift-monitoring exec -c prometheus prometheus-k8s-0 -- curl -k -H "Authorization: Bearer USDtoken" 'https://thanos-querier.openshift-monitoring.svc:9091/api/v1/query?query=cluster_version' Run the following command to read the query log: USD oc -n openshift-monitoring logs <thanos_querier_pod_name> -c thanos-query Note Because the thanos-querier pods are highly available (HA) pods, you might be able to see logs in only one pod. After you examine the logged query information, disable query logging by changing the enableRequestLogging value to false in the config map. 3.4. Configuring metrics for core platform 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 3.4.1. 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. You have created the cluster-monitoring-config ConfigMap object. 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-monitoring namespace. Warning To reduce security risks, use HTTPS and authentication to send metrics to an endpoint. Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add a remoteWrite: section under data/config.yaml/prometheusK8s , as shown in the following example: 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> 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: 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 Example of forwarding metrics called my_metric_1 and my_metric_2 in my_namespace namespace 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__,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. 3.4.1.1. 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. 3.4.1.2. 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 default platform monitoring in the openshift-monitoring namespace. 3.4.1.2.1. Sample YAML for AWS Signature Version 4 authentication The following shows the settings for a sigv4 secret named sigv4-credentials in the openshift-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. 3.4.1.2.2. Sample YAML for Basic authentication The following shows sample Basic authentication settings for a Secret object named rw-basic-auth in the openshift-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. 3.4.1.2.3. 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-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. 3.4.1.2.4. 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-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. 3.4.1.2.5. Sample YAML for TLS client authentication The following shows sample TLS client settings for a tls Secret object named mtls-bundle in the openshift-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. 3.4.1.3. 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 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 3.4.2. 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 cluster-monitoring-config config map in the openshift-monitoring namespace. Prerequisites 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 installed the OpenShift CLI ( oc ). You have configured remote write storage. Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config 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 : 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 Adding cluster ID labels to metrics Obtaining your cluster ID 3.5. Configuring alerts and notifications for core platform 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. 3.5.1. 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 core OpenShift Container Platform 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. You have created the cluster-monitoring-config ConfigMap object. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add an additionalAlertmanagerConfigs section with configuration details under data/config.yaml/prometheusK8s : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: additionalAlertmanagerConfigs: - <alertmanager_specification> 1 1 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 ). The following sample config map configures an additional Alertmanager for Prometheus by using a bearer token with client TLS authentication: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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. 3.5.1.1. Disabling the local Alertmanager A local Alertmanager that routes alerts from Prometheus instances is enabled by default in the openshift-monitoring project of the OpenShift Container Platform monitoring stack. If you do not need the local Alertmanager, you can disable it by configuring the cluster-monitoring-config config map in the openshift-monitoring project. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. You have created the cluster-monitoring-config config map. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add enabled: false for the alertmanagerMain component under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: enabled: false Save the file to apply the changes. The Alertmanager instance is disabled automatically when you apply the change. Additional resources Alertmanager (Prometheus documentation) Managing alerts as an Administrator 3.5.2. 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. 3.5.2.1. Adding a secret to the Alertmanager configuration You can add secrets to the Alertmanager configuration by editing the cluster-monitoring-config config map in the openshift-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. You have created the cluster-monitoring-config config map. You have created the secret to be configured in Alertmanager in the openshift-monitoring project. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Add a secrets: section under data/config.yaml/alertmanagerMain with the following configuration: apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: 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: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: secrets: - test-secret-basic-auth - test-secret-api-token Save the file to apply the changes. The new configuration is applied automatically. 3.5.3. 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. You have created the cluster-monitoring-config ConfigMap object. You have installed the OpenShift CLI ( oc ). Procedure Edit the cluster-monitoring-config config map in the openshift-monitoring project: USD oc -n openshift-monitoring edit configmap cluster-monitoring-config Define labels you want to add for every metric under data/config.yaml : apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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. 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: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: externalLabels: region: eu environment: prod Save the file to apply the changes. The pods affected by the new configuration are automatically redeployed. Additional resources Preparing to configure core platform monitoring stack 3.5.4. Configuring alert notifications In OpenShift Container Platform 4.14, you can view firing alerts in the Alerting UI. You can configure Alertmanager to send notifications about default platform alerts by configuring alert receivers. Important Alertmanager does not send notifications by default. It is strongly recommended to configure Alertmanager to receive notifications by configuring alert receivers through the web console or through the alertmanager-main secret. Additional resources 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 3.5.4.1. Configuring alert routing for default platform alerts You can configure Alertmanager to send notifications. Customize where and how Alertmanager sends notifications about default platform alerts by editing the default configuration in the alertmanager-main secret in the openshift-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. Procedure Open the Alertmanager YAML configuration file: To open the Alertmanager configuration from the CLI: Print the currently active Alertmanager configuration from the alertmanager-main secret into alertmanager.yaml file: USD oc -n openshift-monitoring get secret alertmanager-main --template='{{ index .data "alertmanager.yaml" }}' | base64 --decode > alertmanager.yaml Open the alertmanager.yaml file. To open the Alertmanager configuration from the OpenShift Container Platform web console: Go to the Administration Cluster Settings Configuration Alertmanager YAML page of the web console. Edit the Alertmanager configuration by updating parameters in the YAML: global: resolve_timeout: 5m route: group_wait: 30s 1 group_interval: 5m 2 repeat_interval: 12h 3 receiver: default routes: - matchers: - "alertname=Watchdog" repeat_interval: 2m receiver: watchdog - matchers: - "service=<your_service>" 4 routes: - matchers: - <your_matching_rules> 5 receiver: <receiver> 6 receivers: - name: default - name: watchdog - name: <receiver> <receiver_configuration> 7 1 Specify how long Alertmanager waits while collecting initial alerts for a group of alerts before sending a notification. 2 Specify how much time must elapse before Alertmanager sends a notification about new alerts added to a group of alerts for which an initial notification was already sent. 3 Specify the minimum amount of time that must pass before an alert notification is repeated. If you want a notification to repeat at each group interval, set the repeat_interval value to less than the group_interval value. The repeated notification can still be delayed, for example, when certain Alertmanager pods are restarted or rescheduled. 4 Specify the name of the service that fires the alerts. 5 Specify labels to match your alerts. 6 Specify the name of the receiver to use for the alerts. 7 Specify the receiver configuration. Important Use the matchers key name to indicate the matchers that an alert has to fulfill to match the node. Do not use the match or match_re key names, which are both deprecated and planned for removal in a future release. If you define inhibition rules, use the following key names: target_matchers : to indicate the target matchers source_matchers : to indicate the source matchers Do not use the target_match , target_match_re , source_match , or source_match_re key names, which are deprecated and planned for removal in a future release. The following Alertmanager configuration example configures PagerDuty as an alert receiver: global: resolve_timeout: 5m route: group_wait: 30s group_interval: 5m repeat_interval: 12h receiver: default routes: - matchers: - "alertname=Watchdog" repeat_interval: 2m receiver: watchdog - matchers: - "service=example-app" routes: - matchers: - "severity=critical" receiver: team-frontend-page receivers: - name: default - name: watchdog - name: team-frontend-page pagerduty_configs: - service_key: "<your_key>" With this configuration, alerts of critical severity that are fired by the example-app service are sent through the team-frontend-page receiver. Typically, these types of alerts would be paged to an individual or a critical response team. Apply the new configuration in the file: To apply the changes from the CLI, run the following command: USD oc -n openshift-monitoring create secret generic alertmanager-main --from-file=alertmanager.yaml --dry-run=client -o=yaml | oc -n openshift-monitoring replace secret --filename=- To apply the changes from the OpenShift Container Platform web console, click Save . 3.5.4.2. Configuring alert routing with the OpenShift Container Platform web console You can configure alert routing through the OpenShift Container Platform web console to ensure that you learn about important issues with your cluster. Note The OpenShift Container Platform web console provides fewer settings to configure alert routing than the alertmanager-main secret. To configure alert routing with the access to more configuration settings, see "Configuring alert routing for default platform alerts". Prerequisites You have access to the cluster as a user with the cluster-admin cluster role. Procedure In the Administrator perspective, go to Administration Cluster Settings Configuration Alertmanager . Note Alternatively, you can go to the same page through the notification drawer. Select the bell icon at the top right of the OpenShift Container Platform web console and choose Configure in the AlertmanagerReceiverNotConfigured alert. Click Create Receiver in the Receivers section of the page. In the Create Receiver form, add a Receiver name and choose a Receiver type from the list. Edit the receiver configuration: For PagerDuty receivers: Choose an integration type and add a PagerDuty integration key. Add the URL of your PagerDuty installation. Click Show advanced configuration if you want to edit the client and incident details or the severity specification. For webhook receivers: Add the endpoint to send HTTP POST requests to. Click Show advanced configuration if you want to edit the default option to send resolved alerts to the receiver. For email receivers: Add the email address to send notifications to. Add SMTP configuration details, including the address to send notifications from, the smarthost and port number used for sending emails, the hostname of the SMTP server, and authentication details. Select whether TLS is required. Click Show advanced configuration if you want to edit the default option not to send resolved alerts to the receiver or edit the body of email notifications configuration. For Slack receivers: Add the URL of the Slack webhook. Add the Slack channel or user name to send notifications to. Select Show advanced configuration if you want to edit the default option not to send resolved alerts to the receiver or edit the icon and username configuration. You can also choose whether to find and link channel names and usernames. By default, firing alerts with labels that match all of the selectors are sent to the receiver. If you want label values for firing alerts to be matched exactly before they are sent to the receiver, perform the following steps: Add routing label names and values in the Routing labels section of the form. Click Add label to add further routing labels. Click Create to create the receiver. 3.5.4.3. 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.

Commands:
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 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 nodes <node_name> <node_label> 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 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-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: | alertmanagerMain: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheusK8s: resources: limits: cpu: 500m memory: 3Gi requests: cpu: 200m memory: 500Mi thanosQuerier: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheusOperator: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi k8sPrometheusAdapter: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi kubeStateMetrics: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi telemeterClient: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi openshiftStateMetrics: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi nodeExporter: resources: limits: cpu: 50m memory: 150Mi requests: cpu: 20m memory: 50Mi monitoringPlugin: resources: limits: cpu: 500m memory: 1Gi requests: cpu: 200m memory: 500Mi prometheusOperatorAdmissionWebhook: resources: limits: cpu: 50m memory: 100Mi requests: cpu: 20m memory: 50Mi
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: collectionProfile: <metrics_collection_profile_name> 1
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: collectionProfile: minimal
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 topologySpreadConstraints: - maxSkew: <n> 2 topologyKey: <key> 3 whenUnsatisfiable: <value> 4 labelSelector: 5 <match_option>
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: topologySpreadConstraints: - maxSkew: 1 topologyKey: monitoring whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: app.kubernetes.io/name: prometheus
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-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-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-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: | k8sPrometheusAdapter: audit: profile: <audit_log_level> 1
oc -n openshift-monitoring get pods
oc -n openshift-monitoring get deploy prometheus-adapter -o yaml
- --audit-policy-file=/etc/audit/request-profile.yaml - --audit-log-path=/var/log/adapter/audit.log
oc -n openshift-monitoring exec deploy/prometheus-adapter -c prometheus-adapter -- cat /etc/audit/request-profile.yaml
"apiVersion": "audit.k8s.io/v1" "kind": "Policy" "metadata": "name": "Request" "omitStages": - "RequestReceived" "rules": - "level": "Request"
oc -n openshift-monitoring exec -c <prometheus_adapter_pod_name> -- cat /var/log/adapter/audit.log
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 logLevel: <log_level> 2
oc -n openshift-monitoring get deploy prometheus-operator -o yaml | grep "log-level"
- --log-level=debug
oc -n openshift-monitoring get pods
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: queryLogFile: <path> 1
oc -n openshift-monitoring get pods
prometheus-operator-567c9bc75c-96wkj 2/2 Running 0 62m prometheus-k8s-0 6/6 Running 1 57m prometheus-k8s-1 6/6 Running 1 57m thanos-querier-56c76d7df4-2xkpc 6/6 Running 0 57m thanos-querier-56c76d7df4-j5p29 6/6 Running 0 57m
oc -n openshift-monitoring exec prometheus-k8s-0 -- cat <path>
oc -n openshift-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | thanosQuerier: enableRequestLogging: <value> 1 logLevel: <value> 2
oc -n openshift-monitoring get pods
token=`oc create token prometheus-k8s -n openshift-monitoring` oc -n openshift-monitoring exec -c prometheus prometheus-k8s-0 -- curl -k -H "Authorization: Bearer USDtoken" 'https://thanos-querier.openshift-monitoring.svc:9091/api/v1/query?query=cluster_version'
oc -n openshift-monitoring logs <thanos_querier_pod_name> -c thanos-query
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> writeRelabelConfigs: - <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" 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-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-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: additionalAlertmanagerConfigs: - <alertmanager_specification> 1
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: 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-monitoring edit configmap cluster-monitoring-config
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: enabled: false
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: secrets: 1 - <secret_name_1> 2 - <secret_name_2>
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | alertmanagerMain: secrets: - test-secret-basic-auth - test-secret-api-token
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: externalLabels: <key>: <value> 1
apiVersion: v1 kind: ConfigMap metadata: name: cluster-monitoring-config namespace: openshift-monitoring data: config.yaml: | prometheusK8s: externalLabels: region: eu environment: prod
oc -n openshift-monitoring get secret alertmanager-main --template='{{ index .data "alertmanager.yaml" }}' | base64 --decode > alertmanager.yaml
global: resolve_timeout: 5m route: group_wait: 30s 1 group_interval: 5m 2 repeat_interval: 12h 3 receiver: default routes: - matchers: - "alertname=Watchdog" repeat_interval: 2m receiver: watchdog - matchers: - "service=<your_service>" 4 routes: - matchers: - <your_matching_rules> 5 receiver: <receiver> 6 receivers: - name: default - name: watchdog - name: <receiver> <receiver_configuration> 7
global: resolve_timeout: 5m route: group_wait: 30s group_interval: 5m repeat_interval: 12h receiver: default routes: - matchers: - "alertname=Watchdog" repeat_interval: 2m receiver: watchdog - matchers: - "service=example-app" routes: - matchers: - "severity=critical" receiver: team-frontend-page receivers: - name: default - name: watchdog - name: team-frontend-page pagerduty_configs: - service_key: "<your_key>"
oc -n openshift-monitoring create secret generic alertmanager-main --from-file=alertmanager.yaml --dry-run=client -o=yaml | oc -n openshift-monitoring replace secret --filename=-