Observability

By default, observability is included with the product installation, but not enabled. Due to the requirement for persistent storage, the observability service is not enabled by default. Red Hat Advanced Cluster Management supports the following S3 compatible, stable object stores:

When the service is enabled, the observability-endpoint-operator is automatically deployed to each imported or created cluster. This controller collects the data from Red Hat OpenShift Container Platform Prometheus, then sends it to the Red Hat Advanced Cluster Management hub cluster.

If the hub cluster imports itself as the local-cluster, observability is also enabled on it and metrics are collected from the hub cluster.

The observability service deploys an instance of Prometheus AlertManager, which enables alerts to be forwarded with third-party applications. It also includes an instance of Grafana to enable data visualization with dashboards (static) or data exploration. Red Hat Advanced Cluster Management supports version 8.1.3 of Grafana. You can also design your Grafana dashboard. For more information, see Designing your Grafana dashboard.

You can customize the observability service by creating custom recording rules or alerting rules.

For more information about enabling observability, see Enable observability service.

By default, OpenShift Container Platform sends metrics to Red Hat using the Telemetry service. The acm_managed_cluster_info is available with Red Hat Advanced Cluster Management and is included with telemetry, but is not displayed on the Red Hat Advanced Cluster Management Observe environments overview dashboard.

View the following table of metric types that are supported by the framework:

Learn from the OpenShift Container Platform documentation what types of metrics are collected and sent using telemetry. See Information collected by Telemetry for information.

Observability components require 2701mCPU and 11972Mi memory to install the observability service. The following table is a list of the pod capacity requests for five managed clusters with observability-addons enabled:

When you install Red Hat Advanced Cluster Management the following persistent volumes (PV) must be created so that Persistent Volume Claims (PVC) can attach to it automatically. As a reminder, you must define a storage class in the MultiClusterObservability CR when there is no default storage class specified or you want to use a non-default storage class to host the PVs. It is recommended to use Block Storage, similare to what Prometheus uses. Also each replica of alertmanager, thanos-compactor, thanos-ruler, thanos-receive-default and thanos-store-shard must have its own PV. View the following table:

Note: The time series historical data is stored in object stores. Thanos uses object storage as the primary storage for metrics and meta data related to them. For more details about the object storage and downsampling, see Enable observability service

Red Hat Advanced Cluster Management is tested with and fully supported by Red Hat OpenShift Data Foundation (formerly Red Hat OpenShift Container Storage).

Red Hat Advanced Cluster Management supports the function of the multicluster observability operator on user-provided third-party object storage that is S3 API compatible.

Red Hat Advanced Cluster Management use commercial, reasonable efforts to assist in the identification of the root cause.

If a support ticket is raised and the root cause has been determined to be a result of the customer-provided S3 compatible object storage, then the issue must be resolved using the customer support channels.

Red Hat Advanced Cluster Management does not commit to fix support tickets raised by customers, where the root cause identified is the S3 compatible object storage provider.

See Customizing observability to learn how to configure the observability service, view metrics and other data.

Enable the observability service by creating a MultiClusterObservability custom resource (CR) instance. Before you enable observability, see Observability pod capacity requests for more information.

Note: When observability is enabled or disabled on OpenShift Container Platform managed clusters that are managed by Red Hat Advanced Cluster Management, the observability endpoint operator updates the cluster-monitoring-config ConfigMap by adding additional alertmanager configuration that restarts the local Prometheus automatically.

Complete the following steps to enable the observability service:

Complete the following steps to generate access keys using the AWS Security Service:

Optionally, you can enable observability from the Red Hat OpenShift Container Platform console, create a project named open-cluster-management-observability. Be sure to create an image pull-secret named, multiclusterhub-operator-pull-secret in the open-cluster-management-observability project.

Create your object storage secret named, thanos-object-storage in the open-cluster-management-observability project. Enter the object storage secret details, then click Create. See step four of the Enabling observability section to view an example of a secret.

Create the MultiClusterObservability CR instance. When you receive the following message, the obseravbility service is enabled successfully from OpenShift Container Platform: Observability components are deployed and running.

collect_rules:
  - group: SNOResourceUsage
    annotations:
      description: >
        By default, a SNO cluster does not collect pod and container resource metrics. Once a SNO cluster
        reaches a level of resource consumption, these granular metrics are collected dynamically.
        When the cluster resource consumption is consistently less than the threshold for a period of time,
        collection of the granular metrics stops.
    selector:
      matchExpressions:
        - key: clusterType
          operator: In
          values: ["SNO"]
    rules:
    - collect: SNOHighCPUUsage
      annotations:
        description: >
          Collects the dynamic metrics specified if the cluster cpu usage is constantly more than 70% for 2 minutes
      expr: (1 - avg(rate(node_cpu_seconds_total{mode=\"idle\"}[5m]))) * 100 > 70
      for: 2m
      dynamic_metrics:
        names:
          - container_cpu_cfs_periods_total
          - container_cpu_cfs_throttled_periods_total
          - kube_pod_container_resource_limits
          - kube_pod_container_resource_requests
          - namespace_workload_pod:kube_pod_owner:relabel
          - node_namespace_pod_container:container_cpu_usage_seconds_total:sum_irate
          - node_namespace_pod_container:container_cpu_usage_seconds_total:sum_rate
    - collect: SNOHighMemoryUsage
      annotations:
        description: >
          Collects the dynamic metrics specified if the cluster memory usage is constantly more than 70% for 2 minutes
      expr: (1 - sum(:node_memory_MemAvailable_bytes:sum) / sum(kube_node_status_allocatable{resource=\"memory\"})) * 100 > 70
      for: 2m
      dynamic_metrics:
        names:
          - kube_pod_container_resource_limits
          - kube_pod_container_resource_requests
          - namespace_workload_pod:kube_pod_owner:relabel
        matches:
          - __name__="container_memory_cache",container!=""
          - __name__="container_memory_rss",container!=""
          - __name__="container_memory_swap",container!=""
          - __name__="container_memory_working_set_bytes",container!=""

collect_rules:
  - group: SNOResourceUsage
    annotations:
      description: >
        By default, a SNO cluster does not collect pod and container resource metrics. Once a SNO cluster
        reaches a level of resource consumption, these granular metrics are collected dynamically.
        When the cluster resource consumption is consistently less than the threshold for a period of time,
        collection of the granular metrics stops.
    selector:
      matchExpressions:
        - key: clusterType
          operator: In
          values: ["SNO"]
    rules:
    - collect: SNOHighCPUUsage
      annotations:
        description: >
          Collects the dynamic metrics specified if the cluster cpu usage is constantly more than 70% for 2 minutes
      expr: (1 - avg(rate(node_cpu_seconds_total{mode=\"idle\"}[5m]))) * 100 > 70
      for: 2m
      dynamic_metrics:
        names:
          - container_cpu_cfs_periods_total
          - container_cpu_cfs_throttled_periods_total
          - kube_pod_container_resource_limits
          - kube_pod_container_resource_requests
          - namespace_workload_pod:kube_pod_owner:relabel
          - node_namespace_pod_container:container_cpu_usage_seconds_total:sum_irate
          - node_namespace_pod_container:container_cpu_usage_seconds_total:sum_rate
    - collect: SNOHighMemoryUsage
      annotations:
        description: >
          Collects the dynamic metrics specified if the cluster memory usage is constantly more than 70% for 2 minutes
      expr: (1 - sum(:node_memory_MemAvailable_bytes:sum) / sum(kube_node_status_allocatable{resource=\"memory\"})) * 100 > 70
      for: 2m
      dynamic_metrics:
        names:
          - kube_pod_container_resource_limits
          - kube_pod_container_resource_requests
          - namespace_workload_pod:kube_pod_owner:relabel
        matches:
          - __name__="container_memory_cache",container!=""
          - __name__="container_memory_rss",container!=""
          - __name__="container_memory_swap",container!=""
          - __name__="container_memory_working_set_bytes",container!=""

collect_rules:
  - group: -SNOResourceUsage

collect_rules:
  - group: -SNOResourceUsage

To disable the observability service, uninstall the observability resource. From the OpenShift Container Platform console navigation, select Operators > Installed Operators > Advanced Cluster Manager for Kubernetes. Remove the MultiClusterObservability custom resource.

To learn more about customizing the observability service, see Customizing observability.

The search architecture is composed of the following components:

Search is enabled by default. Search is also enabled when you provision or manually import a managed cluster. If you want to disable search on your managed cluster, see Modifying the klusterlet add-ons settings of your cluster for more information.

When you install Red Hat Advanced Cluster Management, the product is configured to persist the data in-memory to a file system. The StatefulSet search-redisgraph deploys the Redisgraph pod, which mounts the persistent volume named persist. If your cluster has a defined default storage class, the search component creates a Persistent Volume Claim (PVC) of 10Gi on the default storage class. If a default storage class does not exist in your cluster, search saves the index in an empty directory (emptyDir).

You can customize the storage settings for search by creating the searchcustomization custom resource. Search customization is namespace-scoped and located where search is installed in the hub cluster. View the following example of the search customization custom resource:

apiVersion: search.open-cluster-management.io/v1alpha1
kind: SearchCustomization
metadata:
  name: searchcustomization
  namespace: open-cluster-management
  labels:
    cluster.open-cluster-management.io/backup: ""
spec:
  persistence: true
  storageClass: gp2
  storageSize: 12Gi

apiVersion: search.open-cluster-management.io/v1alpha1
kind: SearchCustomization
metadata:
  name: searchcustomization
  namespace: open-cluster-management
  labels:
    cluster.open-cluster-management.io/backup: ""
spec:
  persistence: true
  storageClass: gp2
  storageSize: 12Gi

Run the following command to view search customization custom resource definition:

oc get crd searchcustomizations.search.open-cluster-management.io -o yaml

oc get crd searchcustomizations.search.open-cluster-management.io -o yaml

You can disable persistence by updating the persistence flag to false in the customization custom resource, which turns off saving search index to the file system. A status for persistence can be retrieved from the search operator (searchoperator) custom resource. Run the following command to view search operator custom resource: oc get searchoperator searchoperator -o yaml.

oc patch searchoperator searchoperator --type='merge' -p '{"spec":{"redisgraph_resource":{"limit_memory":"8Gi"}}}'

oc patch searchoperator searchoperator --type='merge' -p '{"spec":{"redisgraph_resource":{"limit_memory":"8Gi"}}}'

You can type any text value in the Search box and results include anything with that value from any property, such as a name or namespace. Users are unable to search for values that contain an empty space.

For more specific search results, include the property selector in your search. You can combine related values for the property, for a more precise scope of your search. For example, search for cluster:dev red to receive results that match the string "red" in the dev cluster.

View the following steps to make queries with search:

To collect the Kubernetes objects from the managed clusters, the klusterlet-addon-search pod is run on all the managed clusters where search is enabled. This deployment is run in the open-cluster-management-agent-addon namespace. A managed cluster with a high number of resources might require more memory for the klusterlet-addon-search deployment to function.

Resource requirements for the klusterlet-addon-search pod in a managed cluster can be specified in the ManagedClusterAddon custom resource in your Red Hat Advanced Cluster Management hub cluster. There is a namespace for each managed cluster with the managed cluster name. Edit the ManagedClusterAddon custom resource from the namespace matching the managed cluster name. Run the following command to update the resource requirement in xyz managed cluster:

oc edit managedclusteraddon search-collector -n xyz

oc edit managedclusteraddon search-collector -n xyz

Append the resource requirements as annotations. View the following example:

apiVersion: addon.open-cluster-management.io/v1alpha1
kind: ManagedClusterAddOn
metadata:
  annotations: addon.open-cluster-management.io/search_memory_limit: 2048Mi
  addon.open-cluster-management.io/search_memory_request: 512Mi

apiVersion: addon.open-cluster-management.io/v1alpha1
kind: ManagedClusterAddOn
metadata:
  annotations: addon.open-cluster-management.io/search_memory_limit: 2048Mi
  addon.open-cluster-management.io/search_memory_request: 512Mi

The annotation overrides the resource requirements on the managed clusters and automatically restarts the pod with new resource requirements.

Learn more about the Red Hat Advanced Cluster Management for Kubernetes console, see Web console.

Create custom rules for the observability installation by adding Prometheus recording rules and alerting rules to the observability resource. For more information, see Prometheus configuration.

Define custom rules with Prometheus to create alert conditions, and send notifications to an external messaging service. Note: When you update your custom rules, observability-thanos-rule pods are restarted automatically.

Create a ConfigMap named thanos-ruler-custom-rules in the open-cluster-management-observability namespace. The key must be named, custom_rules.yaml, as shown in the following example. You can create multiple rules in the configuration.

To verify that the alert rules are functioning appropriately, launch the Grafana dashboard, navigate to the Explore page, and query ALERTS. The alert is only available in Grafana if the alert is initiated.

Integrate external messaging tools such as email, Slack, and PagerDuty to receive notifications from AlertManager. You must override the alertmanager-config secret in the open-cluster-management-observability namespace to add integrations, and configure routes for AlertManager. Complete the following steps to update the custom receiver rules:

Your changes are applied immediately after it is modified. For an example of AlertManager, see prometheus/alertmanager.

Add metrics to the metrics_list.yaml file, to be collected from managed clusters.

Before you add a custom metric, verify that mco observability is enabled with the following command: oc get mco observability -o yaml. Check for the following message in the status.conditions.message reads: Observability components are deployed and running.

Create a file named observability-metrics-custom-allowlist.yaml and add the name of the custom metric to the metrics_list.yaml parameter. Your YAML for the ConfigMap might resemble the following content:

kind: ConfigMap
apiVersion: v1
metadata:
  name: observability-metrics-custom-allowlist
data:
  metrics_list.yaml: |
    names:
      - node_memory_MemTotal_bytes
    rules:
    - record: apiserver_request_duration_seconds:histogram_quantile_90
      expr: histogram_quantile(0.90,sum(rate(apiserver_request_duration_seconds_bucket{job=\"apiserver\",
        verb!=\"WATCH\"}[5m])) by (verb,le))

kind: ConfigMap
apiVersion: v1
metadata:
  name: observability-metrics-custom-allowlist
data:
  metrics_list.yaml: |
    names:
      - node_memory_MemTotal_bytes
    rules:
    - record: apiserver_request_duration_seconds:histogram_quantile_90
      expr: histogram_quantile(0.90,sum(rate(apiserver_request_duration_seconds_bucket{job=\"apiserver\",
        verb!=\"WATCH\"}[5m])) by (verb,le))

Create the observability-metrics-custom-allowlist ConfigMap in the open-cluster-management-observability namespace with the following command: oc apply -n open-cluster-management-observability -f observability-metrics-custom-allowlist.yaml.

Verify that data from your custom metric is being collected by querying the metric from the Explore page, from the Grafana dashboard. You can also use the custom metrics in your own dashboard. For more information about viewing the dashboard, see Designing your Grafana dashboard.

If you want data to not be collected in your managed cluster for a specific metric, remove the metric from the observability-metrics-custom-allowlist.yaml file. When you remove a metric, the metric data is not collected in your managed clusters. As mentioned previously, first verify that mco observability is enabled.

Add the name of the default metric to the metrics_list.yaml parameter with a hyphen - at the start of the metric name. For example, -cluster_infrastructure_provider.

Create the observability-metrics-custom-allowlist ConfigMap in the open-cluster-management-observability namespace with the following command: oc apply -n open-cluster-management-observability -f observability-metrics-custom-allowlist.yaml.

Verify that the specific metric is not being collected from your managed clusters. When you query the metric from the Grafana dashboard, the metric is not displayed.

You can customize observability to export the metrics to external endpoints, which support Prometheus Remote Write protocol in real time. For more information, see Prometheus Remote Write protocol.

apiVersion: v1
kind: Secret
metadata:
  name: victoriametrics
  namespace: open-cluster-management-observability
type: Opaque
stringData:
  ep.yaml: |
    url: http://victoriametrics:8428/api/v1/write
    http_client_config:
      basic_auth:
        username: test
        password: test

apiVersion: v1
kind: Secret
metadata:
  name: victoriametrics
  namespace: open-cluster-management-observability
type: Opaque
stringData:
  ep.yaml: |
    url: http://victoriametrics:8428/api/v1/write
    http_client_config:
      basic_auth:
        username: test
        password: test

spec:
  storageConfig:
    writeStorage:
    - key: ep.yaml
      name: victoriametrics

spec:
  storageConfig:
    writeStorage:
    - key: ep.yaml
      name: victoriametrics

Add the advanced configuration section to update the retention for each observability component, according to your needs.

Edit the MultiClusterObservability CR and add the advanced section with the following command: oc edit mco observability -o yaml. Your YAML file might resemble the following contents:

spec:
  advanced:
    retentionConfig:
      blockDuration: 2h
      deleteDelay: 48h
      retentionInLocal: 24h
      retentionResolutionRaw: 30d
      retentionResolution5m: 180d
      retentionResolution1h: 0d
    receive:
      resources:
        limits:
          memory: 4096Gi
      replicas: 3

spec:
  advanced:
    retentionConfig:
      blockDuration: 2h
      deleteDelay: 48h
      retentionInLocal: 24h
      retentionResolutionRaw: 30d
      retentionResolution5m: 180d
      retentionResolution1h: 0d
    receive:
      resources:
        limits:
          memory: 4096Gi
      replicas: 3

For descriptions of all the parameters that can added into the advanced configuration, see the Observability API.

If your workload increases, increase the number of replicas of your observability pods. Navigate to the Red Hat OpenShift Container Platform console from your hub cluster. Locate the multiclusterobservability custom resource (CR), and update the replicas parameter value for the component where you want to change the replicas. Your updated YAML might resemble the following content:

spec:
   advanced:
      receive:
         replicas: 6

spec:
   advanced:
      receive:
         replicas: 6

For more information about the parameters within the mco observability CR, see the Observability API.

After you enable observability, alerts from your OpenShift Container Platform managed clusters are automatically sent to the hub cluster. You can use the alertmanager-config YAML file to configure alerts with an external notification system.

View the following example of the alertmanager-config YAML file:

global:
  slack_api_url: '<slack_webhook_url>'

route:
  receiver: 'slack-notifications'
  group_by: [alertname, datacenter, app]

receivers:
- name: 'slack-notifications'
  slack_configs:
  - channel: '#alerts'
    text: 'https://internal.myorg.net/wiki/alerts/{{ .GroupLabels.app }}/{{ .GroupLabels.alertname }}'

global:
  slack_api_url: '<slack_webhook_url>'

route:
  receiver: 'slack-notifications'
  group_by: [alertname, datacenter, app]

receivers:
- name: 'slack-notifications'
  slack_configs:
  - channel: '#alerts'
    text: 'https://internal.myorg.net/wiki/alerts/{{ .GroupLabels.app }}/{{ .GroupLabels.alertname }}'

If you want to configure a proxy for alert forwarding, add the following global entry to the alertmanager-config YAML file:

global:
  slack_api_url: '<slack_webhook_url>'
  http_config:
    proxy_url: http://****

global:
  slack_api_url: '<slack_webhook_url>'
  http_config:
    proxy_url: http://****

To learn more, see the Prometheus Alertmanager documentation.

metadata:
      annotations:
        mco-disable-alerting: "true"

metadata:
      annotations:
        mco-disable-alerting: "true"

Add alerts that you do not want to receive. You can silence alerts by the alert name, match label, or time duration. After you add the alert that you want to silence, an ID is created. Your ID for your silenced alert might resemble the following string, d839aca9-ed46-40be-84c4-dca8773671da.

Continue reading for ways to silence alerts:

Suppress Red Hat Advanced Cluster Management alerts across your clusters globally that are less severe. Suppress alerts by defining an inhibition rule in the alertmanager-config in the open-cluster-management-observability namespace.

An inhibition rule mutes an alert when there is a set of parameter matches that match another set of existing matchers. In order for the rule to take effect, both the target and source alerts must have the same label values for the label names in the equal list. Your inhibit_rules might resemble the following:

global:
  resolve_timeout: 1h
inhibit_rules:
  - equal:
      - namespace
    source_match:
      severity: critical
    target_match_re:
      severity: warning|info

global:
  resolve_timeout: 1h
inhibit_rules:

  - equal:
      - namespace
    source_match:

      severity: critical
    target_match_re:
      severity: warning|info

If you want to customize the OpenShift Container Platform route certification, you must add the routes in the alt_names section. To ensure your OpenShift Container Platform routes are accessible, add the following information: alertmanager.apps.<domainname>, observatorium-api.apps.<domainname>, rbac-query-proxy.apps.<domainname>.

Note: Users are responsible for certificate rotations and updates.

 thanos.yaml: |
    type: s3
    config:
      bucket: "thanos"
      endpoint: "minio:9000"
      insecure: false
      access_key: "minio"
      secret_key: "minio123"
      http_config:
        tls_config:
          ca_file: /etc/minio/certs/ca.crt
          insecure_skip_verify: false

 thanos.yaml: |
    type: s3
    config:
      bucket: "thanos"
      endpoint: "minio:9000"
      insecure: false
      access_key: "minio"
      secret_key: "minio123"
      http_config:
        tls_config:
          ca_file: /etc/minio/certs/ca.crt
          insecure_skip_verify: false

 thanos.yaml: |
    type: s3
    config:
      ...
      http_config:
        tls_config:
          ca_file: /etc/minio/certs/ca.crt
          cert_file: /etc/minio/certs/public.crt
          key_file: /etc/minio/certs/private.key
          insecure_skip_verify: false

 thanos.yaml: |
    type: s3
    config:
      ...
      http_config:
        tls_config:
          ca_file: /etc/minio/certs/ca.crt
          cert_file: /etc/minio/certs/public.crt
          key_file: /etc/minio/certs/private.key
          insecure_skip_verify: false

metricObjectStorage:
      key: thanos.yaml
      name: thanos-object-storage
      tlsSecretName: tls-certs-secret

metricObjectStorage:
      key: thanos.yaml
      name: thanos-object-storage
      tlsSecretName: tls-certs-secret

View the data from your managed clusters by accessing Grafana from the hub cluster. You can query specific alerts and add filters for the query.

For example, to cluster_infrastructure_provider from a single node cluster, use the following query expression: cluster_infrastructure_provider{clusterType="SNO"}

Note: Do not set the ObservabilitySpec.resources.CPU.limits parameter if observability is enabled on single node managed clusters. When you set the CPU limits, it causes the observability pod to be counted against the capacity for your managed cluster. See Management Workload Partitioning for more information.

You can disable observability, which stops data collection on the Red Hat Advanced Cluster Management hub cluster.

spec:
  imagePullPolicy: Always
  imagePullSecret: multiclusterhub-operator-pull-secret
  observabilityAddonSpec: # The ObservabilityAddonSpec defines the global settings for all managed clusters which have observability add-on enabled
    enableMetrics: false #indicates the observability addon push metrics to hub server

spec:
  imagePullPolicy: Always
  imagePullSecret: multiclusterhub-operator-pull-secret
  observabilityAddonSpec: # The ObservabilityAddonSpec defines the global settings for all managed clusters which have observability add-on enabled
    enableMetrics: false #indicates the observability addon push metrics to hub server

First, clone the stolostron/multicluster-observability-operator/ repository, so that you are able to run the scripts that are in the tools folder. Be sure to use the most current grafana-dev instance.

Complete the following steps to set up the Grafana developer instance:

The Grafana developer instance is set up.

After you set up the Grafana instance, you can design the dashboard. Complete the following steps to refresh the Grafana console and design your dashboard:

./generate-dashboard-configmap-yaml.sh "Your Dashboard Name"
Save dashboard <your-dashboard-name> to ./your-dashboard-name.yaml

./generate-dashboard-configmap-yaml.sh "Your Dashboard Name"
Save dashboard <your-dashboard-name> to ./your-dashboard-name.yaml

oc apply -f demo-dashboard.yaml

oc apply -f demo-dashboard.yaml

When you uninstall the instance, the related resources are also deleted. Run the following command:

./setup-grafana-dev.sh --clean
secret "grafana-dev-config" deleted
deployment.apps "grafana-dev" deleted
serviceaccount "grafana-dev" deleted
route.route.openshift.io "grafana-dev" deleted
persistentvolumeclaim "grafana-dev" deleted
oauthclient.oauth.openshift.io "grafana-proxy-client-dev" deleted
clusterrolebinding.rbac.authorization.k8s.io "open-cluster-management:grafana-crb-dev" deleted

./setup-grafana-dev.sh --clean
secret "grafana-dev-config" deleted
deployment.apps "grafana-dev" deleted
serviceaccount "grafana-dev" deleted
route.route.openshift.io "grafana-dev" deleted
persistentvolumeclaim "grafana-dev" deleted
oauthclient.oauth.openshift.io "grafana-proxy-client-dev" deleted
clusterrolebinding.rbac.authorization.k8s.io "open-cluster-management:grafana-crb-dev" deleted

Continue reading to view functionality descriptions of the integration:

See Managing insight PolicyReports for more information.

You can search for a specific insight PolicyReport that has a violation, across your managed clusters.

After you log into your Red Hat Advanced Cluster Management hub cluster, click the Search icon in the console header to navigate to the Search page. Enter the following query: kind:policyreport.

Note: The PolicyReport name matches the name of the cluster.

You can also further specify your query by the insight policy violation and categories. When you select a PolicyReport name, you are redirected to the Details page of the associated cluster. The Insights sidebar is automatically displayed.

If the search service is disabled and you want to search for an insight, run the following command from your hub cluster:

oc get policyreport --all-namespaces

oc get policyreport --all-namespaces

You can view the identified issues on a specific cluster.

After you log into your Red Hat Advanced Cluster Management cluster, select Overview from the navigation menu. Select a severity to view the PolicyReports that are associated with that severity. Details of the cluster issues and the severities are displayed from the Cluster issues summary card.

Alternatively, you can select Clusters from the navigation menu. Select a managed cluster from the table to view more details. From the Status card, view the number of identified issues.

Select the number of potential issues to view the severity chart and recommended remediations for the issues. Click the link to the vulnerability to view steps on How to remediate and the Reason for the vulnerability.

Note: After the issue is resolved, the Red Hat Insights are received by Red Hat Advanced Cluster Management every 30 minutes and Red Hat Insights is updated every two hours.

Be sure to verify which component sent the alert message from the PolicyReport. Navigate to the Governance page and select a specific policyreport. Select the Status tab and click the View details link to view the PolicyReport YAML file.

Locate the source parameter, which informs you of the component that sent the violation. The value options are grc and insights.

Learn how to create custom alert rules for the PolicyReports, see Configuring AlertManager for more information.