Configure instrumentation for namespaces and pods

By default, Single Step Instrumentation instruments all services in all namespaces in your cluster. Alternatively, you can create targeting blocks with the targets label to specify which workloads to instrument and what configurations to apply.

Each target block has the following keys:

The file you need to configure depends on how you enabled Single Step Instrumentation:

• If you enabled SSI with Datadog Operator, edit datadog-agent.yaml.
• If you enabled SSI with Helm, edit datadog-values.yaml.

Example configurations

Review the following examples demonstrating how to select specific services:

   apm:
     instrumentation:
       enabled: true
       disabledNamespaces:
         - "jenkins"
       targets:
         - name: "all-remaining-services"
           ddTraceVersions:
             java: "default"
             python: "3.1.0"

  apm:
    instrumentation:
      enabled: true
      targets:
        - name: "login-service_namespace"
          namespaceSelector:
            matchNames:
              - "login-service"
          ddTraceVersions:
            java: "default"
          ddTraceConfigs:
            - name: "DD_PROFILING_ENABLED"  ## profiling is enabled for all services in this namespace
              value: "auto"
        - name: "billing-service_apps"
          namespaceSelector:
            matchLabels:
              app: "billing-service"
          ddTraceVersions:
            python: "3.1.0"

   apm:
     instrumentation:
       enabled: true
       targets:
         - name: "db-user"
           podSelector:
             matchLabels:
               app: "db-user"
           ddTraceVersions:
             java: "default"
           ddTraceConfigs:   ## trace configs set for services in matching pods
             - name: "DD_DSM_ENABLED"
               value: "true"
         - name: "user-request-router"
           podSelector:
             matchLabels:
               webserver: "user"
           ddTraceVersions:
             php: "default"

   apm:
     instrumentation:
       enabled: true
       targets:
         - name: "login-service-namespace"
           namespaceSelector:
             matchNames:
               - "login-service"
           podSelector:
             matchLabels:
               app: "password-resolver"
           ddTraceVersions:
             java: "default"
           ddTraceConfigs:
             - name: "DD_PROFILING_ENABLED"
               value: "auto"

   apm:
     instrumentation:
       enabled: true
       targets:
         - name: "default-target"
           matchExpressions:
             - key: app
               operator: NotIn
               values:
               - app1
               - app2

Enable or disable instrumentation for namespaces

You can choose to enable or disable instrumentation for applications in specific namespaces. You can only set enabledNamespaces or disabledNamespaces, not both.

The file you need to configure depends on if you enabled Single Step Instrumentation with Datadog Operator or Helm:

   features:
     apm:
       instrumentation:
         enabled: true
         enabledNamespaces: # Add namespaces to instrument
           - default
           - applications

   features:
     apm:
       instrumentation:
         enabled: true
         disabledNamespaces: # Add namespaces to not instrument
           - default
           - applications

   datadog:
      apm:
        instrumentation:
          enabled: true
          enabledNamespaces: # Add namespaces to instrument
             - namespace_1
             - namespace_2

   datadog:
      apm:
        instrumentation:
          enabled: true
          disabledNamespaces: # Add namespaces to not instrument
            - namespace_1
            - namespace_2

Specify tracing library versions

Specify Datadog tracing libraries and their versions to automatically instrument applications written in those languages. You can configure this in two ways, which are applied in the following order of precedence:

1. Specify at the service level, or
2. Specify at the cluster level.

Default: If you don’t specify any library versions, applications written in supported languages are automatically instrumented using the latest tracing library versions.

Specify at the service level

To automatically instrument applications in specific pods, add the appropriate language annotation and library version for your application in your pod spec:

Replace <CONTAINER IMAGE TAG> with the desired library version. Available versions are listed in the Datadog container registries and tracer source repositories for each language:

• Java
• Node.js
• Python
• .NET
• Ruby
• PHP

For example, to automatically instrument Java applications:

apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    # ...
spec:
  template:
    metadata:
      annotations:
        admission.datadoghq.com/java-lib.version: "<CONTAINER IMAGE TAG>"
    spec:
      containers:
        - # ...

Specify at the cluster level

If you don’t enable automatic instrumentation for specific pods using annotations, you can specify which languages to instrument across the entire cluster using the Single Step Instrumentation configuration. When apm.instrumentation.libVersions is set, only applications written in the specified languages will be instrumented, using the specified library versions.

The file you need to configure depends on if you enabled Single Step Instrumentation with Datadog Operator or Helm:

   features:
     apm:
       instrumentation:
         enabled: true
         libVersions: # Add any libraries and versions you want to set
            dotnet: "3.2.0"
            python: "1.20.6"
            js: "4.17.0"

   datadog:
     apm:
       instrumentation:
         enabled: true
         libVersions: # Add any libraries and versions you want to set
            dotnet: "3.2.0"
            python: "1.20.6"
            js: "4.17.0"

Container registries

Datadog publishes instrumentation libraries images on gcr.io, Docker Hub, and Amazon ECR:

The DD_ADMISSION_CONTROLLER_AUTO_INSTRUMENTATION_CONTAINER_REGISTRY environment variable in the Datadog Cluster Agent configuration specifies the registry used by the Admission Controller. The default value is gcr.io/datadoghq.

You can pull the tracing library from a different registry by changing it to docker.io/datadog, public.ecr.aws/datadog, or another URL if you are hosting the images in a local container registry.

For instructions on changing your container registry, see Changing Your Container Registry.

1. Set instrumentation.enabled=false in datadog-agent.yaml:

   features:
     apm:
       instrumentation:
         enabled: false
   

2. Deploy the Datadog Agent with the updated configuration file:

   kubectl apply -f /path/to/your/datadog-agent.yaml
   

1. Set instrumentation.enabled=false in datadog-values.yaml:

   datadog:
     apm:
       instrumentation:
         enabled: false
   

2. Run the following command:

   helm upgrade datadog-agent -f datadog-values.yaml datadog/datadog