Cluster Check Runners

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While the regular Datadog Agent executes endpoint checks for your node and application Pods, a cluster check runner is specifically dedicated to running cluster checks, which monitor internal Kubernetes services, as well as external services like managed databases and network devices.

Note: When using a cluster check runner, it is not necessary to enable cluster checks for the regular Datadog Agent.

Set up

First, deploy the Cluster Agent.

Then, deploy the cluster check runner using either Datadog Operator or Helm:

    Using the Operator, you can launch and manage all of these resources with a single manifest. For example:

    apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    credentials:
      apiKey: <DATADOG_API_KEY>
      appKey: <DATADOG_APP_KEY>
    clusterAgentToken: <DATADOG_CLUSTER_AGENT_TOKEN>
  features:
    clusterChecks:
      enabled: true
      useClusterChecksRunners: true
  override:
    clusterAgent:
      replicas: 2

    Deploy these resources into your cluster:

    kubectl apply -f datadog-agent-with-dca-clusterchecksrunner.yaml

    If you see the following output, it confirms the configuration was applied successfully:

    datadogagent.datadoghq.com/datadog created

    See the Datadog Operator repo for more information about the Datadog Operator.

    You can update the relevant sections of the chart to enable cluster checks, the Cluster Agent, and the cluster check runner at the same time. For example:

    datadog:
  clusterChecks:
    enabled: true
  #(...)

clusterAgent:
  enabled: true
  #(...)

clusterChecksRunner:
  enabled: true
  replicas: 2

    Note: Both the Datadog Operator and the Helm chart use podAntiAffinity to avoid having multiple cluster check runners on the same node. This is important because the Cluster Agent identifies the cluster check runners by their node names. Using podAntiAffinity avoids having name collisions.