custom_check.md

Custom Check

To configure one of Datadog's 400+ integrations, leverage the Agent Autodiscovery feature. But if you want to run a custom check, the DatadogAgent resource can be configured to provide custom checks (checks.d) and their configuration files (conf.d) at initialization time. A ConfigMap resource needs to be configured for each of these settings before the DatadogAgent resource using them is created.

Below is an example of configuring these ConfigMaps for a single check hello that submits the hello.world metrics to Datadog. See the Introduction to Integrations to learn what is a check in the Datadog ecosystem.

Create the check files

A check needs a configuration file hello.yaml and a script file hello.py:

1. Create the hello.yaml with the following content:

   init_config:
   
   instances: [{}]

2. Create the hello.py with the following content:

   from datadog_checks.base import AgentCheck
   
   __version__ = "1.0.0"
   class HelloCheck(AgentCheck):
       def check(self, instance):
           self.gauge('hello.world', 1, tags=['env:dev'])

Create the check ConfigMaps

Once the hello check files are created, create the associated ConfigMaps:

1. Create the ConfigMap for the custom check YAML configuration file hello.yaml:

   $ kubectl create configmap -n $DD_NAMESPACE confd-config --from-file=hello.yaml
   configmap/confd-config created

2. Verify that the ConfigMap has been correctly created:

   $ kubectl get configmap -n $DD_NAMESPACE confd-config -o yaml
   apiVersion: v1
   data:
     hello.yaml: |
       init_config:
   
       instances: [{}]
   kind: ConfigMap
   metadata:
     name: confd-config
     namespace: datadog

3. Create the ConfigMap for the custom check Python file hello.py:

   $ kubectl create configmap -n $DD_NAMESPACE checksd-config --from-file=hello.py
   configmap/checksd-config created

4. Verify that the ConfigMap has been correctly created:

   $ kubectl get configmap -n $DD_NAMESPACE checksd-config -o yaml
   apiVersion: v1
   data:
     hello.py: |
      from datadog_checks.base import AgentCheck
   
      __version__ = "1.0.0"
      class HelloCheck(AgentCheck):
        def check(self, instance):
          self.gauge('hello.world', 1, tags=['env:dev'])
    kind: ConfigMap
    metadata:
      name: checksd-config
      namespace: datadog

Configure the Agent

Once the ConfigMaps are configured, a DatadogAgent resource can be created to use them with the following chart:

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    credentials:
      apiKey: "<DATADOG_API_KEY>"
      appKey: "<DATADOG_APP_KEY>"
  override:
    nodeAgent:
      extraConfd:
        configMap:
          name: confd-config
      extraChecksd:
        configMap:
          name: checksd-config

Note: Any ConfigMaps you create need to be in the same DD_NAMESPACE as the DatadogAgent resource.

This deploys the Datadog Agent with your custom check.

Multiple checks

In order to populate ConfigMaps with the content of multiple checks or their respective configurations files, the following approach can be used:

• Populating all check configuration files:

  $ kubectl create cm -n $DD_NAMESPACE confd-config $(find ./conf.d -name "*.yaml" | xargs -I'{}' echo -n '--from-file={} ')
  configmap/confd-config created

• Populating all check script files:

  $ kubectl create cm -n $DD_NAMESPACE checksd-config $(find ./checks.d -name "*.py" | xargs -I'{}' echo -n '--from-file={} ')
  configmap/checksd-config created

Providing additional volumes

Additional user-configured volumes can be mounted in either the node or Cluster Agent containers by setting the volumes and volumeMounts properties. Find below an example of using a volume to mount a secret:

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    credentials:
      apiKey: "<DATADOG_API_KEY>"
      appKey: "<DATADOG_APP_KEY>"
  override:
    nodeAgent:
      image:
        name: "gcr.io/datadoghq/agent:latest"
      volumes:
        - name: secrets
          secret:
            secretName: secrets
      containers:
        agent:
          volumeMounts:
            - name: secrets
              mountPath: /etc/secrets
              readOnly: true