Kubernetes log collection

This page discusses collecting logs from Kubernetes log files.

The Datadog Agent has two ways to collect logs: from Kubernetes log files, or from the Docker socket. Datadog recommends using Kubernetes log files when:

• Docker is not the runtime, or
• More than 10 containers are used on each node

The Docker API is optimized to get logs from one container at a time. When there are many containers in the same node, collecting logs through the Docker socket may consume more resources than collecting logs through Kubernetes log files. To see how to collect logs using the Docker socket, see Log collection with Docker socket.

Log collection

Before you start collecting application logs, ensure that you are running the Datadog Agent in your Kubernetes cluster.

To configure log collection using a DaemonSet, see DaemonSet Log Collection. Otherwise, follow the instructions below:

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    credentials:
      apiKey: <DATADOG_API_KEY>

  features:
    logCollection:
      enabled: true
      containerCollectAll: true

kubectl apply -n $DD_NAMESPACE -f datadog-agent.yaml

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    credentials:
      apiKey: <DATADOG_API_KEY>

  features:
    logCollection:
      enabled: true
      containerCollectAll: true

  override:
    nodeAgent:
      securityContext:
        runAsUser: <USER_ID>
        supplementalGroups:
          - <DOCKER_GROUP_ID>

datadog:
  logs:
    enabled: true
    containerCollectAll: true

datadog:
  securityContext:
      runAsUser: <USER_ID>
      supplementalGroups:
        - <DOCKER_GROUP_ID>

Integration logs

Autodiscovery enables you to use templates to configure log collection (and other capabilities) on containers.

To configure log collection for an integration with Autodiscovery, use the following parameter:

The schema for <LOG_CONFIG> depends on the integration. You can find this schema in each integration’s conf.yaml.example file.

Configuration

apiVersion: v1
kind: Pod
# (...)
metadata:
  name: '<POD_NAME>'
  annotations:
    ad.datadoghq.com/<CONTAINER_IDENTIFIER>.logs: '[<LOG_CONFIG>]'
    # (...)
spec:
  containers:
    - name: '<CONTAINER_IDENTIFIER>'
# (...)

apiVersion: v1
kind: Pod
# (...)
metadata:
  name: '<POD_NAME>'
  annotations:
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_1>.logs: '[<LOG_CONFIG_1>]'
    # (...)
    ad.datadoghq.com/<CONTAINER_IDENTIFIER_2>.logs: '[<LOG_CONFIG_2>]'
spec:
  containers:
    - name: '<CONTAINER_IDENTIFIER_1>'
    # (...)
    - name: '<CONTAINER_IDENTIFIER_2>'
# (...)

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:

/datadog/
  check_configs/
    <CONTAINER_IDENTIFIER>/
      - logs: ["<LOGS_CONFIG>"]
    ...

Examples

Datadog-Redis integration

apiVersion: v1
kind: Pod
metadata:
  name: redis
  annotations:
    ad.datadoghq.com/redis.checks: |
      {
        "redisdb": {
          "init_config": {},
          "instances": [
            {
              "host": "%%host%%",
              "port":"6379",
              "password":"%%env_REDIS_PASSWORD%%"
            }
          ]
        }
      }        
    ad.datadoghq.com/redis.logs: '[{"source": "redis","service": "<YOUR_APP_NAME>","tags": ["env:prod"]}]'
  labels:
    name: redis
spec:
  containers:
    - name: redis
      image: redis:latest
      ports:
        - containerPort: 6379

etcdctl mkdir /datadog/check_configs/redis
etcdctl set /datadog/check_configs/redis/logs '[{"source": "redis", "service": "redis", "tags": ["env:prod"]}]'

For more information about source and service attributes, see Reserved Attributes.

From a file configured in an annotation

Datadog recommends that you use the stdout and stderr output streams for containerized applications, so that you can more automatically set up log collection. However, the Agent can also directly collect logs from a file based on an annotation. To collect these logs, use ad.datadoghq.com/<CONTAINER_IDENTIFIER>.logs with a type: file and path configuration. Logs collected from files with such an annotation are automatically tagged with the same set of tags as logs coming from the container itself.

These file paths are relative to the Agent. Therefore, the directory containing the log file needs to be mounted into both the application and Agent container so the Agent can have proper visibility.

For example, you can do this with a shared hostPath volume. The Pod below is emitting logs into the file /var/log/example/app.log. This is done in the /var/log/example directory, where a volume and volumeMount have set this as a hostPath.

apiVersion: v1
kind: Pod
metadata:
  name: logger
  annotations:
    ad.datadoghq.com/busybox.logs: |
      [{
          "type": "file",
          "path": "/var/log/example/app.log",
          "source": "example-source",
          "service": "example-service"
      }]      
spec:
  containers:
   - name: busybox
     image: busybox
     command: [ "/bin/sh", "-c", "--" ]
     args: [ "while true; do sleep 1; echo `date` example file log >> /var/log/example/app.log; done;" ]
     volumeMounts:
     - name: applogs
       mountPath: /var/log/example
  volumes:
     - name: applogs
       hostPath:
         path: /var/log/example

The equivalent volume and volumeMount path need to be set in the Agent container so it can read that same log file.

  containers:
  - name: agent
    # (...)
    volumeMounts:
    - mountPath: /var/log/example
      name: applogs
    # (...)
  volumes:
  - name: applogs
    hostPath:
      path: /var/log/example
    # (...)

Note: When using this kind of annotation with a container, stdout and stderr logs are not collected automatically from the container. If collection from both the container and a file are needed it should be explicitly enabled in the annotation. For example:

ad.datadoghq.com/<CONTAINER_IDENTIFIER>.logs: |
  [
    {"type":"file","path":"/var/log/example/app.log","source":"file","service":"example-service"},
    {"source":"container","service":"example-service"}
  ]  

When using this kind of combination, source and service have no default value for logs collected from a file and should be explicitly set in the annotation.

Advanced log collection

Use Autodiscovery log labels to apply advanced log collection processing logic, for example:

• Filter logs before sending them to Datadog.
• Scrub sensitive data from your logs.
• Proceed to multi-line aggregation.

Filter containers

It is possible to manage from which containers you want to collect logs. This can be useful to prevent the collection of the Datadog Agent logs. See the Container Discovery Management to learn more.

Short lived containers

By default the Agent looks every 5 seconds for new containers.

For Agent v6.12+, short lived container logs (stopped or crashed) are automatically collected when using the K8s file log collection method (through /var/log/pods). This also includes the collection init container logs.

Troubleshooting

If you are missing tags on Kubernetes logs, this may be because the Agent’s internal tagger does not yet have the related container or pod tags when logs are sent. To make the Log Agent wait a few seconds for the tagger to be ready, you can use the environment variable DD_LOGS_CONFIG_TAGGER_WARMUP_DURATION to set how many seconds to wait. The default value is 0.

# The number of seconds the Log Agent waits for the internal tagger to add the related container or pod tags to the logs before the logs are sent.
# For example, in order to set the Log Agent to wait five seconds, use an integer in the value:
tagger_warmup_duration: 5

Further Reading

Documentation, liens et articles supplémentaires utiles:

Collect your application tracesDOCUMENTATION Collect your Prometheus metricsDOCUMENTATION Collect automatically your applications metrics and logsDOCUMENTATION Limit data collection to a subset of containers onlyDOCUMENTATION Assign tags to all data emitted by a containerDOCUMENTATION