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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.
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.
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>.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>'
# (...)
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.
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:
conf.d/<INTEGRATION_NAME>.d/conf.yaml
file on your host and add your custom auto-configuration.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.
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"
...
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
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 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]
.
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.
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 redis.yaml
file with the above configuration in the /confd
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.
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 page: Datadog-Apache integration, 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
conf.d/
and conf.d/apache.d
on your host.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.
conf.d/http_check.d
on your host.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
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.
Additional helpful documentation, links, and articles: