opentelemetry

Instrumenting Java applications with EDOT SDKs on Kubernetes

This document focuses on instrumenting Java applications on Kubernetes, using the OpenTelemetry Operator, Elastic Distribution of OpenTelemetry (EDOT) Collectors, and the EDOT Java SDK.

For general knowledge about the EDOT Java SDK, refer to the getting started guide.
For Java auto-instrumentation specifics, refer to OpenTelemetry Operator Java auto-instrumentation.
For general information about instrumenting applications on kubernetes, refer to instrumenting applications.

Java agent extensions consideration

The operator supports a configuration that installs Java agent extensions in Instrumentation objects. The extension needs to be available in an image. Refer to using extensions with the OpenTelemetry Java agent for an example of adding an extension to an agent.

Instrument a Java app with EDOT Java SDK on Kubernetes

In this example, you’ll learn how to:

Enable auto-instrumentation of a Java application using one of the following supported methods:
- Adding an annotation to the deployment Pods.
- Adding an annotation to the namespace.
Verify that auto-instrumentation libraries are injected and configured correctly.
Confirm data is flowing to Kibana Observability.

For this example, we assume the application you’re instrumenting is a deployment named java-app running in the java-ns namespace.

Ensure you have successfully installed the OpenTelemetry Operator, and confirm that the following Instrumentation object exists in the system:

$ kubectl get instrumentation -n opentelemetry-operator-system
NAME                      AGE    ENDPOINT
elastic-instrumentation   107s   http://opentelemetry-kube-stack-daemon-collector.opentelemetry-operator-system.svc.cluster.local:4318

[!NOTE] If your Instrumentation object has a different name or is created in a different namespace, you will have to adapt the annotation value in the next step.

Enable auto-instrumentation of your Java application using one of the following methods:

Edit your application workload definition and include the annotation under spec.template.metadata.annotations:

kind: Deployment
metadata:
  name: java-app
  namespace: java-ns
spec:
...
  template:
    metadata:
...
      annotations:
        instrumentation.opentelemetry.io/inject-java: opentelemetry-operator-system/elastic-instrumentation
...

Alternatively, add the annotation at namespace level to apply auto-instrumentation in all Pods of the namespace:

kubectl annotate namespace java-ns instrumentation.opentelemetry.io/inject-java=opentelemetry-operator-system/elastic-instrumentation

Restart application

Once the annotation has been set, restart the application to create new Pods and inject the instrumentation libraries:

```bash
kubectl rollout restart deployment java-app -n java-ns
```

Verify the auto-instrumentation resources are injected in the Pod:

Run a kubectl describe of one of your application Pods and check:

There should be an init container named opentelemetry-auto-instrumentation-java in the Pod:

$ kubectl describe pod java-app-8d84c47b8-8h5z2 -n java-ns
Name:             java-app-8d84c47b8-8h5z2
Namespace:        java-ns
...
...
Init Containers:
  opentelemetry-auto-instrumentation-java:
    Container ID:  containerd://cbf67d7ca1bd62c25614b905a11e81405bed6fd215f2df21f84b90fd0279230b
    Image:         docker.elastic.co/observability/elastic-otel-javaagent:1.0.0
    Image ID:      docker.elastic.co/observability/elastic-otel-javaagent@sha256:28d65d04a329c8d5545ed579d6c17f0d74800b7b1c5875e75e0efd29e210566a
    Port:          <none>
    Host Port:     <none>
    Command:
      cp
      /javaagent.jar
      /otel-auto-instrumentation-java/javaagent.jar
    State:          Terminated
      Reason:       Completed
      Exit Code:    0
      Started:      Wed, 13 Nov 2024 15:47:02 +0100
      Finished:     Wed, 13 Nov 2024 15:47:03 +0100
    Ready:          True
    Restart Count:  0
    Environment:    <none>
    Mounts:
      /otel-auto-instrumentation-java from opentelemetry-auto-instrumentation-java (rw)
      /var/run/secrets/kubernetes.io/serviceaccount from kube-api-access-swhn5 (ro)

The main container of the deployment is using the SDK as javaagent:

...
Containers:
  java-app:
    Environment:
...
      JAVA_TOOL_OPTIONS:                      -javaagent:/otel-auto-instrumentation-java/javaagent.jar
      OTEL_SERVICE_NAME:                     java-app
      OTEL_EXPORTER_OTLP_ENDPOINT:           http://opentelemetry-kube-stack-daemon-collector.opentelemetry-operator-system.svc.cluster.local:4318
...

The Pod has an EmptyDir volume named opentelemetry-auto-instrumentation-java mounted in both the main and the init containers in path /otel-auto-instrumentation-java.

Init Containers:
  opentelemetry-auto-instrumentation-java:
...
    Mounts:
      /otel-auto-instrumentation-java from opentelemetry-auto-instrumentation-java (rw)
Containers:
  java-app:
...
    Mounts:
      /otel-auto-instrumentation-java from opentelemetry-auto-instrumentation-java (rw)
...
Volumes:
...
  opentelemetry-auto-instrumentation-java:
    Type:        EmptyDir (a temporary directory that shares a pod's lifetime)

Ensure the environment variable OTEL_EXPORTER_OTLP_ENDPOINT points to a valid endpoint and there’s network communication between the Pod and the endpoint.

Confirm data is flowing to Kibana:

Open Observability -> Applications -> Service inventory, and determine if:
- The application appears in the list of services.
- The application shows transactions and metrics.
For application container logs, open Kibana Discover and filter for your Pods’ logs. In the provided example, we could filter for them with either of the following:
- k8s.deployment.name: "java-app" (adapt the query filter to your use case)
- k8s.pod.name: java-app* (adapt the query filter to your use case)

Note that the container logs are not provided by the instrumentation library, but by the DaemonSet collector deployed as part of the operator installation.

Troubleshooting

Refer to troubleshoot auto-instrumentation for further analysis.