Datadog CPU Check

Last updated on Jul 16, 2026

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Datadog CPU check validates the CPU utilisation of a service using Datadog container metrics. The target service name and Kubernetes namespace are supplied at runtime via probe variables, allowing this probe to be reused across services.

Infrastructure type

• Kubernetes

Use cases

Datadog CPU Check probe helps you:

• Verify CPU stays within limits during pod CPU hog faults
• Monitor container CPU after resource stress experiments
• Validate autoscaling behavior under load chaos
• Detect CPU saturation before it affects latency

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Overview

This probe queries Datadog for sum:container.cpu.usage filtered by kube_deployment and kube_namespace, converts nanoseconds to CPU cores using the formula cpu/1000000000, and compares the mean aggregated value against your threshold.

Probe type

APM Probe (Datadog)

Prerequisites

• Kubernetes chaos infrastructure with Harness Delegate
• A configured Datadog connector
• Datadog agent reporting container.cpu.usage for the target deployment
• Probe variables SERVICE_NAME and NAMESPACE set at experiment runtime

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Probe properties

Comparator

Type	Criteria	Default value
float	<=	0.50

The probe passes when the mean CPU usage (in cores) is less than or equal to the comparator value.

Datadog APM probe inputs

Field	Description	Default
connectorID	Identifier of the Datadog connector	Required at runtime
durationInMin	Look-back window in minutes	5
queryType	Datadog query API version	v2
queries[0].name	Query alias used in the formula	cpu
queries[0].dataSource	Metric source type	metrics
queries[0].params.query	Datadog metric query	sum:container.cpu.usage{kube_deployment:<+probe.variables.SERVICE_NAME>,kube_namespace:<+probe.variables.NAMESPACE>}
formula	Converts query result to CPU cores	cpu/1000000000
aggregation	Aggregation over the time window	mean

Probe variables

Variable	Description	Required
SERVICE_NAME	Kubernetes deployment name of the target service	Yes
NAMESPACE	Kubernetes namespace of the target service	Yes

Configurable inputs

Input	Description	Required	Default
CONNECTOR_ID	Datadog connector identifier	Yes	-
DURATION_IN_MIN	Look-back window in minutes	No	5
COMPARATOR_VALUE	CPU threshold in cores	Yes	0.50

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Run properties

Property	Description	Type	Default
timeout	Maximum time to wait for the probe to complete	String	30s
interval	Time between probe executions	String	5s
attempt	Number of retry attempts before marking as failed	Integer	1
pollingInterval	Time between retry attempts	String	30s
initialDelay	Initial delay before starting the probe	String	1s
stopOnFailure	Stop the experiment if the probe fails	Boolean	false
verbosity	Log verbosity level	String	debug

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Probe definition

You can define this probe in your chaos experiment as follows:

probe:
  - name: datadog-cpu-check
    type: apmProbe
    mode: Continuous
    apmProbe/inputs:
      type: Datadog
      comparator:
        type: float
        value: "0.50"
        criteria: <=
      datadogApmProbeInputs:
        connectorID: <+connector.identifier>
        durationInMin: 5
        queryType: v2
        queries:
          - name: cpu
            dataSource: metrics
            params:
              query: sum:container.cpu.usage{kube_deployment:<+probe.variables.SERVICE_NAME>,kube_namespace:<+probe.variables.NAMESPACE>}
        formula: cpu/1000000000
        aggregation: mean
    runProperties:
      timeout: 30s
      interval: 5s
      attempt: 1
      pollingInterval: 30s
      initialDelay: 1s
      stopOnFailure: false
      verbosity: debug

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Next steps

• Go to Datadog Memory Check to validate memory utilisation.
• Go to Datadog APM Probe Templates to browse all Datadog probe templates.