Kubernetes Integrations Autodiscovery

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Consult the Autodiscovery Getting Started documentation to discover the concepts behind this feature.

This page covers how to configure integrations Autodiscovery with Kubernetes. If you are using Docker or Amazon ECS, see the Docker Integrations Autodiscovery documentation. The goal of Autodiscovery is to apply a Datadog integration configuration when running an Agent check against a given container. See how to configure Agent integrations when running the Agent on a host for more context on this logic.

If you have configuration values that you do not wish to store in plaintext, such as passwords, see Secrets Management.

To configure an integration with Autodiscovery, use the following parameters:

Parameter	Required	Description
`<INTEGRATION_NAME>`	Yes	Name of the Datadog integration
`<INIT_CONFIG>`	Yes	The configuration parameters listed under `init_config:` in your `conf.yaml` and required for any integrations you’re enabling.
`<INSTANCE_CONFIG>`	Yes	A part of the `<INIT_CONFIG>`, these are the configuration parameters listed under `instances:` in your `conf.yaml` and required for any integrations you’re enabling.
`<LOG_CONFIG>`	Yes	A part of the `<INIT_CONFIG>`, these are the configuration parameters listed under `logs:` in your `conf.yaml` and define the logs you’re sending to Datadog.

Each tab in sections below shows a different way to apply integration templates to a given container. The available methods are:

Note: Some supported integrations don’t work with standard Autodiscovery because they require either process tree data or filesystem access: Ceph, Varnish, Postfix, Cassandra Nodetools, and Gunicorn. To set up integrations that are not compatible with standard Autodiscovery, you can use an official Prometheus exporter in the pod, and then use the OpenMetrics check with Autodiscovery in the Agent to find the pod and query the endpoint. For example, the standard pattern in Kubernetes is: side car adapter with a node-level or cluster-level collector. This setup allows the exporter to access the data, which exposes it using an HTTP endpoint, and the OpenMetrics check with Datadog Autodiscovery can then access the data.

Configuration

Note: AD Annotations v2 was introduced in Datadog Agent 7.36 to simplify integration configuration. For previous versions of the Datadog Agent, use AD Annotations v1.

Integration templates can be stored in your Kubernetes pod annotations. With Autodiscovery, the Agent detects if it’s running on Kubernetes and automatically searches all pod annotations for integration templates.

To apply a specific configuration to a given container, Autodiscovery identifies containers by name, NOT image. It tries to match <CONTAINER_IDENTIFIER> to .spec.containers[0].name, not .spec.containers[0].image. To configure your Datadog integration Autodiscovery on a given <CONTAINER_IDENTIFIER> within your pod, add the following annotations to your pod:

apiVersion: v1
kind: Pod
# (...)
metadata:
  name: '<POD_NAME>'
  annotations:
    ad.datadoghq.com/<CONTAINER_IDENTIFIER>.checks: |
      {
        "<INTEGRATION_NAME>": {
          "init_config": <INIT_CONFIG>,
          "instances": [<INSTANCE_CONFIG>]
        }
      }      
    # (...)
spec:
  containers:
    - name: '<CONTAINER_IDENTIFIER>'
# (...)

init_config is usually an empty {}. In AD Annotations v2, it is optional.

To apply two different integration templates to two different containers: <CONTAINER_IDENTIFIER_1> and <CONTAINER_IDENTIFIER_2> within your pod, add the following annotations to your pod:

apiVersion: v1
kind: Pod
# (...)
metadata:
  name: '<POD_NAME>'
  annotations:
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_1>.checks: |
      {
        "<INTEGRATION_NAME_1>": {
          "init_config": <INIT_CONFIG_1>,
          "instances": [<INSTANCE_CONFIG_1>]
        }
      }      
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_2>.checks: |
      {
        "<INTEGRATION_NAME_2>": {
          "init_config": <INIT_CONFIG_2>,
          "instances": [<INSTANCE_CONFIG_2>]
        }
      }      
spec:
  containers:
    - name: '<CONTAINER_IDENTIFIER_1>'
    # (...)
    - name: '<CONTAINER_IDENTIFIER_2>'
# (...)

If you define your Kubernetes pods directly with kind: Pod, add each pod’s annotations directly under its metadata section. If you define pods indirectly with replication controllers, replica sets, or deployments, add pod annotations under .spec.template.metadata.

Note: As a best practice in containerized environments, Datadog recommends using unified service tagging when assigning tags. Unified service tagging ties Datadog telemetry together through the use of three standard tags: env, service, and version. To learn how to configure your environment with unified tagging, refer to the dedicated unified service tagging documentation.

apiVersion: v1
kind: Pod
# (...)
metadata:
  name: '<POD_NAME>'
  annotations:
    ad.datadoghq.com/<CONTAINER_IDENTIFIER>.check_names: '[<INTEGRATION_NAME>]'
    ad.datadoghq.com/<CONTAINER_IDENTIFIER>.init_configs: '[<INIT_CONFIG>]'
    ad.datadoghq.com/<CONTAINER_IDENTIFIER>.instances: '[<INSTANCE_CONFIG>]'
    # (...)
spec:
  containers:
    - name: '<CONTAINER_IDENTIFIER>'
# (...)

To apply two different integration templates to two different containers: <CONTAINER_IDENTIFIER_1> and <CONTAINER_IDENTIFIER_2> within your pod, add the following annotations to your pod:

apiVersion: v1
kind: Pod
# (...)
metadata:
  name: '<POD_NAME>'
  annotations:
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_1>.check_names: '[<INTEGRATION_NAME_1>]'
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_1>.init_configs: '[<INIT_CONFIG_1>]'
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_1>.instances: '[<INSTANCE_CONFIG_1>]'
    # (...)
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_2>.check_names: '[<INTEGRATION_NAME_2>]'
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_2>.init_configs: '[<INIT_CONFIG_2>]'
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_2>.instances: '[<INSTANCE_CONFIG_2>]'
spec:
  containers:
    - name: '<CONTAINER_IDENTIFIER_1>'
    # (...)
    - name: '<CONTAINER_IDENTIFIER_2>'
# (...)

Storing templates as local files and mounting them inside the containerized Agent doesn’t require an external service or a specific orchestration platform. The downside is that you need to restart your Agent containers each time you change, add, or remove templates. The Agent looks for Autodiscovery templates in the mounted /conf.d directory.

Since Agent v6.2.0 (and v5.24.0), the default templates use the default port for the monitored software, instead of auto-detecting it. If you need to use a different port, provide a custom Autodiscovery template in the Kubernetes pod annotations.

These integration templates are meant for basic cases. If you need a custom Datadog integration configuration to enable extra options, use different container identifiers—or use template variables indexing and write your own auto-configuration file:

Create a conf.d/<INTEGRATION_NAME>.d/conf.yaml file on your host and add your custom auto-configuration.
Mount your host conf.d/ folder to the containerized Agent’s conf.d folder.

Example auto-configuration file:

ad_identifiers:
  <INTEGRATION_AUTODISCOVERY_IDENTIFIER>

init_config:
  <INIT_CONFIG>

instances:
  <INSTANCES_CONFIG>

See the Autodiscovery Container Identifiers documentation for information on the <INTEGRATION_AUTODISCOVERY_IDENTIFIER>.

Note: You don’t need to set up the <INTEGRATIONS_NAME> since the Agent infers it from the file name directly.

On Kubernetes, you can use ConfigMaps to externally define configurations and subsequently mount them using the manifest. Reference the template below and the Kubernetes Custom Integrations documentation.

kind: ConfigMap
apiVersion: v1
metadata:
  name: "<NAME>-config-map"
  namespace: default
data:
  <INTEGRATION_NAME>-config: |-
    ad_identifiers:
      <INTEGRATION_AUTODISCOVERY_IDENTIFIER>
    init_config:
      <INIT_CONFIG>
    instances:
      <INSTANCES_CONFIG>

See the Autodiscovery Container Identifiers documentation for information on the <INTEGRATION_AUTODISCOVERY_IDENTIFIER>.

Autodiscovery can use Consul, Etcd, and Zookeeper as integration template sources. To use a key-value store, configure it in the Agent datadog.yaml configuration file and mount this file inside the containerized Agent. Alternatively, pass your key-value store as environment variables to the containerized Agent.

Configure in datadog.yaml:

In the datadog.yaml file, set the <KEY_VALUE_STORE_IP> address and <KEY_VALUE_STORE_PORT> of your key-value store:

config_providers:
  - name: etcd
    polling: true
    template_dir: /datadog/check_configs
    template_url: '<KV_STORE_IP>:<KV_STORE_PORT>'
    username:
    password:

  - name: consul
    polling: true
    template_dir: datadog/check_configs
    template_url: '<KV_STORE_IP>:<KV_STORE_PORT>'
    ca_file:
    ca_path:
    cert_file:
    key_file:
    username:
    password:
    token:

  - name: zookeeper
    polling: true
    template_dir: /datadog/check_configs
    template_url: '<KV_STORE_IP>:<KV_STORE_PORT>'
    username:
    password:

Then restart the Agent to apply the configuration change.

Configure in environment variables:

Note: As a best practice in containerized environments, Datadog recommends using unified service tagging when configuring tags and environment variables. Unified service tagging ties Datadog telemetry together through the use of three standard tags: env, service, and version. To learn how to configure your environment with unified tagging, refer to the dedicated [unified service tagging][9] documentation.

With the key-value store enabled as a template source, the Agent looks for templates under the key /datadog/check_configs. Autodiscovery expects a key-value hierarchy like this:

/datadog/
  check_configs/
    <CONTAINER_IDENTIFIER>/
      - check_names: ["<INTEGRATION_NAME>"]
      - init_configs: ["<INIT_CONFIG>"]
      - instances: ["<INSTANCE_CONFIG>"]
    ...

Note: To apply a specific configuration to a given container, Autodiscovery identifies containers by image when using the key-value stores by trying to match <CONTAINER_IDENTIFIER> to .spec.containers[0].image.

The values.yaml file contains a confd section to define both static and Autodiscovery integration checks. You can find inline examples in the sample values.yaml. Each key becomes a file in the Agent’s conf.d directory.

  confd:
    <INTEGRATION_NAME>.yaml: |-
      ad_identifiers:
        - <INTEGRATION_AUTODISCOVERY_IDENTIFIER>
      init_config:
        - <INIT_CONFIG>
      instances:
        - <INSTANCES_CONFIG>

See Autodiscovery Container Identifiers for information on the <INTEGRATION_AUTODISCOVERY_IDENTIFIER>.

Note: The Helm chart has two confd sections: one for Agent checks, and a second for cluster checks. If you are using the Cluster Agent and looking to configure Autodiscovery for a cluster check, follow the cluster check configuration example and make sure to include cluster_check: true. See Cluster Check for more context.

You can add an override extraConfd.configDataMap to the nodeAgent component of your DatadogAgent configuration to define both static and Autodiscovery integration checks. Each key becomes a file in the Agent’s conf.d directory.

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    [...]
  features:
    [...]
  override:
    nodeAgent:
      extraConfd:
        configDataMap:
          <INTEGRATION_NAME>.yaml: |-
            ad_identifiers:
              - <INTEGRATION_AUTODISCOVERY_IDENTIFIER>
            init_config:
              - <INIT_CONFIG>
            instances:
              - <INSTANCES_CONFIG>

See Autodiscovery Container Identifiers for information on the <INTEGRATION_AUTODISCOVERY_IDENTIFIER>.

Note: If you are using the Cluster Agent and looking to configure Autodiscovery for a cluster check, add an override extraConfd.configDataMap to the clusterAgent component and make sure to include cluster_check: true. See Cluster Checks for more context.

Tolerate unready pods

By default, unready pods are ignored when the Datadog Agent schedules checks. Therefore, metrics, service checks, and logs are not collected from these pods. To override this behavior, set the annotation ad.datadoghq.com/tolerate-unready to "true". For example:

apiVersion: v1
kind: Pod
# (...)
metadata:
  name: '<POD_NAME>'
  annotations:
    ad.datadoghq.com/tolerate-unready: "true"
  ...

Examples

Datadog Redis integration

Note: AD Annotations v2 was introduced in Datadog Agent 7.36 to simplify integration configuration. For previous versions of the Datadog Agent, use AD Annotations v1.

The following pod annotation defines the integration template for redis containers with a custom password parameter:

apiVersion: v1
kind: Pod
metadata:
  name: redis
  annotations:
    ad.datadoghq.com/redis.checks: |
      {
        "redisdb": {
          "instances": [
            {
              "host": "%%host%%",
              "port":"6379",
              "password":"%%env_REDIS_PASSWORD%%"
            }
          ]
        }
      }      
  labels:
    name: redis
spec:
  containers:
    - name: redis
      image: redis:latest
      ports:
        - containerPort: 6379

Note: The "%%env_<ENV_VAR>%%" template variable logic is used to avoid storing the password in plain text, hence the REDIS_PASSWORD environment variable must be passed to the Agent. See the Autodiscovery template variable documentation.

The following pod annotation defines the integration template for redis containers with a custom password parameter:

apiVersion: v1
kind: Pod
metadata:
  name: redis
  annotations:
    ad.datadoghq.com/redis.check_names: '["redisdb"]'
    ad.datadoghq.com/redis.init_configs: '[{}]'
    ad.datadoghq.com/redis.instances: |
      [
        {
          "host": "%%host%%",
          "port":"6379",
          "password":"%%env_REDIS_PASSWORD%%"
        }
      ]      
  labels:
    name: redis
spec:
  containers:
    - name: redis
      image: redis:latest
      ports:
        - containerPort: 6379

The following ConfigMap defines the integration template for redis containers:

kind: ConfigMap
apiVersion: v1
metadata:
  name: redis-config-map
  namespace: default
data:
  redisdb-config: |-
    ad_identifiers:
      - redis
      - redis-test
    init_config:
    instances:
      - host: "%%host%%"
        port: "6379"

In the manifest, define the volumeMounts and volumes:

# [...]
        volumeMounts:
        # [...]
          - name: redisdb-config-map
            mountPath: /conf.d/redisdb.d
        # [...]
      volumes:
      # [...]
        - name: redisdb-config-map
          configMap:
            name: redisdb-config-map
            items:
              - key: redisdb-config
                path: conf.yaml
# [...]

The following etcd commands create a Redis integration template with a custom password parameter:

etcdctl mkdir /datadog/check_configs/redis
etcdctl set /datadog/check_configs/redis/check_names '["redisdb"]'
etcdctl set /datadog/check_configs/redis/init_configs '[{}]'
etcdctl set /datadog/check_configs/redis/instances '[{"host": "%%host%%","port":"6379","password":"%%env_REDIS_PASSWORD%%"}]'

Notice that each of the three values is a list. Autodiscovery assembles list items into the integration configurations based on shared list indexes. In this case, it composes the first (and only) check configuration from check_names[0], init_configs[0] and instances[0].

Unlike auto-conf files, key-value stores may use the short OR long image name as container identifiers, for example, redis OR redis:latest.

The following configuration defines the integration template for Redis containers with a custom password parameter:

  confd:
    redisdb.yaml: |-
      ad_identifiers:
        - redis
      init_config:
      instances:
        - host: "%%host%%"
          port: 6379
          password: "%%env_REDIS_PASSWORD%%"

As a result, the Agent contains a redisdb.yaml file with the above configuration in the conf.d directory. Note: The "%%env_<ENV_VAR>%%" template variable logic is used to avoid storing the password in plain text. Hence, you must pass the REDIS_PASSWORD environment variable to the Agent. See the Autodiscovery Template Variable documentation.

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    [...]
  features:
    [...]
  override:
    nodeAgent:
      extraConfd:
        configDataMap:
          redisdb.yaml: |-
            ad_identifiers:
              - redis
            init_config:
            instances:
              - host: "%%host%%"
                port: 6379
                password: "%%env_REDIS_PASSWORD%%"

Datadog Apache and HTTP check integrations

Configurations below apply to an Apache container image with the <CONTAINER_IDENTIFIER>: apache. The Autodiscovery templates are configured to collect metrics from the Apache container and set up a Datadog-HTTP check with instances for testing two endpoints.

Check names are apache, http_check, their <INIT_CONFIG>, and <INSTANCE_CONFIG>. Full configurations can be found in their respective documentation: Datadog-Apache integration and Datadog-HTTP check integration.

Note: AD Annotations v2 was introduced in Datadog Agent 7.36 to simplify integration configuration. For previous versions of the Datadog Agent, use AD Annotations v1.

apiVersion: v1
kind: Pod
metadata:
  name: apache
  annotations:
    ad.datadoghq.com/apache.checks: |
      {
        "apache": {
          "instances": [
            {
              "apache_status_url": "http://%%host%%/server-status?auto"
            }
          ]
        },
        "http_check": {
          "instances": [
            {
              "name": "<WEBSITE_1>",
              "url": "http://%%host%%/website_1",
              "timeout": 1
            },
            {
              "name": "<WEBSITE_2>",
              "url": "http://%%host%%/website_2",
              "timeout": 1
            }
          ]
        }
      }      
  labels:
    name: apache
spec:
  containers:
    - name: apache
      image: httpd
      ports:
        - containerPort: 80

apiVersion: v1
kind: Pod
metadata:
  name: apache
  annotations:
    ad.datadoghq.com/apache.check_names: '["apache","http_check"]'
    ad.datadoghq.com/apache.init_configs: '[{},{}]'
    ad.datadoghq.com/apache.instances: |
      [
        [
          {
            "apache_status_url": "http://%%host%%/server-status?auto"
          }
        ],
        [
          {
            "name": "<WEBSITE_1>",
            "url": "http://%%host%%/website_1",
            "timeout": 1
          },
          {
            "name": "<WEBSITE_2>",
            "url": "http://%%host%%/website_2",
            "timeout": 1
          }
        ]
      ]      
  labels:
    name: apache
spec:
  containers:
    - name: apache
      image: httpd
      ports:
        - containerPort: 80

Create the folders conf.d/ and conf.d/apache.d on your host.
Add the custom auto-configuration below to conf.d/apache.d/conf.yaml on your host.

ad_identifiers:
  - httpd

init_config:

instances:
  - apache_status_url: http://%%host%%/server-status?auto

Note: It looks like a minimal Apache check configuration, but notice the ad_identifiers option. This required option lets you provide container identifiers. Autodiscovery applies this template to any containers on the same host that run an httpd image. See the dedicated Autodiscovery Identifier documentation to learn more.

Next, create the folder conf.d/http_check.d on your host.
Add the custom auto-configuration below to conf.d/http_check.d/conf.yaml on your host.

ad_identifiers:
  - httpd

init_config:

instances:
  - name: "<WEBSITE_1>"
    url: "http://%%host%%/website_1"
    timeout: 1

  - name: "<WEBSITE_2>"
    url: "http://%%host%%/website_2"
    timeout: 1

Finally, mount the host conf.d/ folder to the containerized Agent conf.d/ folder.

The following ConfigMap defines the integration template for the apache and http_check containers:

kind: ConfigMap
apiVersion: v1
metadata:
  name: httpd-config-map
  namespace: default
data:
  apache-config: |-
    ad_identifiers:
      - httpd
    init_config:
    instances:
      - apache_status_url: http://%%host%%/server-status?auto    
  http-check-config: |-
    ad_identifiers:
      - httpd
    init_config:
    instances:
      - name: "<WEBSITE_1>"
        url: "http://%%host%%/website_1"
        timeout: 1
      - name: "<WEBSITE_2>"
        url: "http://%%host%%/website_2"
        timeout: 1

In the manifest, define the volumeMounts and volumes:

# [...]
        volumeMounts:
        # [...]
          - name: apache-auto-config
            mountPath: /conf.d/apache.d/
          - name: http-auto-config
            mountPath: /conf.d/http_check.d/
        # [...]
      volumes:
      # [...]
        - name: apache-auto-config
          configMap:
            name: httpd-config-map
            items:
              - key: apache-config
                path: auto_conf.yaml
        - name: http-auto-config
          configMap:
            name: httpd-config-map
            items:
              - key: http-check-config
                path: auto_conf.yaml
# [...]

etcdctl set /datadog/check_configs/httpd/check_names '["apache", "http_check"]'
etcdctl set /datadog/check_configs/httpd/init_configs '[{}, {}]'
etcdctl set /datadog/check_configs/httpd/instances '[[{"apache_status_url": "http://%%host%%/server-status?auto"}],[{"name": "<WEBSITE_1>", "url": "http://%%host%%/website_1", timeout: 1},{"name": "<WEBSITE_2>", "url": "http://%%host%%/website_2", timeout: 1}]]'

Note: The order of each list matters. The Agent can only generate the HTTP check configuration correctly if all parts of its configuration have the same index across the three lists.

Kubernetes Integrations Autodiscovery

Configuration

Tolerate unready pods

Examples

Datadog Redis integration

Datadog Apache and HTTP check integrations

Further Reading