# Enhance Applications Non-Intrusively with Operators

Currently, only Java, Node.js, Python, .NET, and Golang support non-intrusive integration through the Operator approach.

## Prerequisites

Please ensure that the Insight Agent is ready. If not, please refer to
[Install insight-agent for data collection](../install/install-agent.md)
and make sure the following three items are ready:

- Enable trace functionality for Insight Agent
- Check if the address and port for trace data are correctly filled
- Ensure that the Pods corresponding to deployment/insight-agent-opentelemetry-operator and
  deployment/insight-agent-opentelemetry-collector are ready

## Install Instrumentation CR

!!! tip

    Starting from Insight v0.22.0, there is no longer a need to manually install the Instrumentation CR.

Install it in the insight-system namespace. There are some minor differences between different versions.

=== "Insight v0.21.x"

    ```bash
    K8S_CLUSTER_UID=$(kubectl get namespace kube-system -o jsonpath='{.metadata.uid}')
    kubectl apply -f - <<EOF
    apiVersion: opentelemetry.io/v1alpha1
    kind: Instrumentation
    metadata:
      name: insight-opentelemetry-autoinstrumentation
      namespace: insight-system
    spec:
      # https://github.com/open-telemetry/opentelemetry-operator/blob/main/docs/api.md#instrumentationspecresource
      resource:
        addK8sUIDAttributes: true
      env:
        - name: OTEL_EXPORTER_OTLP_ENDPOINT
          value: http://insight-agent-opentelemetry-collector.insight-system.svc.cluster.local:4317
      sampler:
        # Enum: always_on, always_off, traceidratio, parentbased_always_on, parentbased_always_off, parentbased_traceidratio, jaeger_remote, xray
        type: always_on
      java:
        image: ghcr.m.daocloud.io/openinsight-proj/autoinstrumentation-java:1.31.0
        env:
          - name: OTEL_JAVAAGENT_DEBUG
            value: "false"
          - name: OTEL_INSTRUMENTATION_JDBC_ENABLED
            value: "true"
          - name: SPLUNK_PROFILER_ENABLED
            value: "false"
          - name: OTEL_METRICS_EXPORTER
            value: "prometheus"
          - name: OTEL_METRICS_EXPORTER_PORT
            value: "9464"
          - name: OTEL_K8S_CLUSTER_UID
            value: $K8S_CLUSTER_UID
      nodejs:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-nodejs:0.41.1
      python:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.40b0
      dotnet:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-dotnet:1.0.0
      go:
        # Must set the default value manually for now.
        # See https://github.com/open-telemetry/opentelemetry-operator/issues/1756 for details.
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-go-instrumentation/autoinstrumentation-go:v0.2.2-alpha
    EOF
    ```

=== "Insight v0.20.x"

    ```bash
    kubectl apply -f - <<EOF
    apiVersion: opentelemetry.io/v1alpha1
    kind: Instrumentation
    metadata:
      name: insight-opentelemetry-autoinstrumentation
      namespace: insight-system
    spec:
      # https://github.com/open-telemetry/opentelemetry-operator/blob/main/docs/api.md#instrumentationspecresource
      resource:
        addK8sUIDAttributes: true
      env:
        - name: OTEL_EXPORTER_OTLP_ENDPOINT
          value: http://insight-agent-opentelemetry-collector.insight-system.svc.cluster.local:4317
      sampler:
        # Enum: always_on, always_off, traceidratio, parentbased_always_on, parentbased_always_off, parentbased_traceidratio, jaeger_remote, xray
        type: always_on
      java:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-java:1.29.0
        env:
          - name: OTEL_JAVAAGENT_DEBUG
            value: "false"
          - name: OTEL_INSTRUMENTATION_JDBC_ENABLED
            value: "true"
          - name: SPLUNK_PROFILER_ENABLED
            value: "false"
          - name: OTEL_METRICS_EXPORTER
            value: "prometheus"
          - name: OTEL_METRICS_EXPORTER_PORT
            value: "9464"
      nodejs:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-nodejs:0.41.1
      python:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.40b0
      dotnet:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-dotnet:1.0.0-rc.2
      go:
        # Must set the default value manually for now.
        # See https://github.com/open-telemetry/opentelemetry-operator/issues/1756 for details.
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-go-instrumentation/autoinstrumentation-go:v0.2.2-alpha
    EOF
    ```

=== "Insight v0.18.x"

    ```bash
    kubectl apply -f - <<EOF
    apiVersion: opentelemetry.io/v1alpha1
    kind: Instrumentation
    metadata:
      name: insight-opentelemetry-autoinstrumentation
      namespace: insight-system
    spec:
      # https://github.com/open-telemetry/opentelemetry-operator/blob/main/docs/api.md#instrumentationspecresource
      resource:
        addK8sUIDAttributes: true
      env:
        - name: OTEL_EXPORTER_OTLP_ENDPOINT
          value: http://insight-agent-opentelemetry-collector.insight-system.svc.cluster.local:4317
      sampler:
        # Enum: always_on, always_off, traceidratio, parentbased_always_on, parentbased_always_off, parentbased_traceidratio, jaeger_remote, xray
        type: always_on
      java:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-java:1.25.0
        env:
          - name: OTEL_JAVAAGENT_DEBUG
            value: "false"
          - name: OTEL_INSTRUMENTATION_JDBC_ENABLED
            value: "true"
          - name: SPLUNK_PROFILER_ENABLED
            value: "false"
          - name: OTEL_METRICS_EXPORTER
            value: "prometheus"
          - name: OTEL_METRICS_EXPORTER_PORT
            value: "9464"
      nodejs:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-nodejs:0.37.0
      python:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.38b0
      go:
        # Must set the default value manually for now.
        # See https://github.com/open-telemetry/opentelemetry-operator/issues/1756 for details.
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-go-instrumentation/autoinstrumentation-go:v0.2.1-alpha
    EOF
    ```

=== "Insight v0.17.x"

    ```bash
    kubectl apply -f - <<EOF
    apiVersion: opentelemetry.io/v1alpha1
    kind: Instrumentation
    metadata:
      name: insight-opentelemetry-autoinstrumentation
      namespace: insight-system
    spec:
      # https://github.com/open-telemetry/opentelemetry-operator/blob/main/docs/api.md#instrumentationspecresource
      resource:
        addK8sUIDAttributes: true
      env:
        - name: OTEL_EXPORTER_OTLP_ENDPOINT
          value: http://insight-agent-opentelemetry-collector.insight-system.svc.cluster.local:4317
      sampler:
        # Enum: always_on, always_off, traceidratio, parentbased_always_on, parentbased_always_off, parentbased_traceidratio, jaeger_remote, xray
        type: always_on
      java:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-java:1.23.0
        env:
          - name: OTEL_JAVAAGENT_DEBUG
            value: "false"
          - name: OTEL_INSTRUMENTATION_JDBC_ENABLED
            value: "true"
          - name: SPLUNK_PROFILER_ENABLED
            value: "false"
          - name: OTEL_METRICS_EXPORTER
            value: "prometheus"
          - name: OTEL_METRICS_EXPORTER_PORT
            value: "9464"
      nodejs:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-nodejs:0.34.0
      python:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.33b0
    EOF
    ```

=== "Insight v0.16.x"

    ```bash
    kubectl apply -f - <<EOF
    apiVersion: opentelemetry.io/v1alpha1
    kind: Instrumentation
    metadata:
      name: insight-opentelemetry-autoinstrumentation
      namespace: insight-system
    spec:
      # https://github.com/open-telemetry/opentelemetry-operator/blob/main/docs/api.md#instrumentationspecresource
      resource:
        addK8sUIDAttributes: true
      env:
        - name: OTEL_EXPORTER_OTLP_ENDPOINT
          value: http://insight-agent-opentelemetry-collector.insight-system.svc.cluster.local:4317
      sampler:
        # Enum: always_on, always_off, traceidratio, parentbased_always_on, parentbased_always_off, parentbased_traceidratio, jaeger_remote, xray
        type: always_on
      java:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-java:1.23.0
        env:
          - name: OTEL_JAVAAGENT_DEBUG
            value: "false"
          - name: OTEL_INSTRUMENTATION_JDBC_ENABLED
            value: "true"
          - name: SPLUNK_PROFILER_ENABLED
            value: "false"
          - name: OTEL_METRICS_EXPORTER
            value: "prometheus"
          - name: OTEL_METRICS_EXPORTER_PORT
            value: "9464"
      nodejs:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-nodejs:0.34.0
      python:
        image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.33b0
    EOF
    ```

## Works with the Service Mesh Product (Mspider)

If you enable the tracing capability of the Mspider(Service Mesh), you need to add an additional environment variable injection configuration when you install Instrumentation CR:

```yaml
    - name: OTEL_SERVICE_NAME
      valueFrom:
        fieldRef:
          fieldPath: metadata.labels['app'] 
```

The complete example is as follows:

```bash title="For Insight v0.18.x"
kubectl apply -f - <<EOF
apiVersion: opentelemetry.io/v1alpha1
kind: Instrumentation
metadata:
  name: insight-opentelemetry-autoinstrumentation
  namespace: insight-system
spec:
  # https://github.com/open-telemetry/opentelemetry-operator/blob/main/docs/api.md#instrumentationspecresource
  resource:
    addK8sUIDAttributes: true
  env:
    - name: OTEL_EXPORTER_OTLP_ENDPOINT
      value: http://insight-agent-opentelemetry-collector.insight-system.svc.cluster.local:4317
    - name: OTEL_SERVICE_NAME
      valueFrom:
        fieldRef:
          fieldPath: metadata.labels['app'] 
  sampler:
    # Enum: always_on, always_off, traceidratio, parentbased_always_on, parentbased_always_off, parentbased_traceidratio, jaeger_remote, xray
    type: always_on
  java:
    image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-java:1.25.0
    env:
      - name: OTEL_JAVAAGENT_DEBUG
        value: "false"
      - name: OTEL_INSTRUMENTATION_JDBC_ENABLED
        value: "true"
      - name: SPLUNK_PROFILER_ENABLED
        value: "false"
      - name: OTEL_METRICS_EXPORTER
        value: "prometheus"
      - name: OTEL_METRICS_EXPORTER_PORT
        value: "9464"
  nodejs:
    image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-nodejs:0.37.0
  python:
    image: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-python:0.38b0
  dotnet:
    repository: ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-dotnet:0.6.0
  go:
    # Must set the default value manually for now.
    # See https://github.com/open-telemetry/opentelemetry-operator/issues/1756 for details.
    repository: ghcr.m.daocloud.io/open-telemetry/opentelemetry-go-instrumentation/autoinstrumentation-go:v0.2.1-alpha
EOF
```

## Add annotations to automatically access traces

After the above is ready, you can access traces for the application through annotations (Annotation). Otel currently supports accessing traces through annotations. Depending on the service language, different pod annotations need to be added.
Each service can add one of two types of annotations:

- Only inject environment variable annotations

    There is only one such annotation, which is used to add otel-related environment variables, such as link reporting address, cluster id where the container is located, namespace, etc. (this annotation is very useful when the application does not support automatic probe language)

    ```console
    instrumentation.opentelemetry.io/inject-sdk: "insight-system/insight-opentelemetry-autoinstrumentation"
    ```

    The value is divided into two parts by /, the first value (insight-system) is the namespace of the CR installed in the previous step, and the second value (insight-opentelemetry-autoinstrumentation) is the name of the CR.

- Automatic probe injection and environment variable injection annotations

    There are currently 4 such annotations, corresponding to 4 different programming languages: java, nodejs, python, dotnet. After using it, automatic probes and otel default environment variables will be injected into the first container under spec.pod:

    1. Java application

        ```bash
          instrumentation.opentelemetry.io/inject-java: "insight-system/insight-opentelemetry-autoinstrumentation"
        ```

    2. NodeJs application

        ```bash
        instrumentation.opentelemetry.io/inject-nodejs: "insight-system/insight-opentelemetry-autoinstrumentation"
        ```

    3. Python application

        ```bash
        instrumentation.opentelemetry.io/inject-python: "insight-system/insight-opentelemetry-autoinstrumentation"
        ```

    4. Dotnet application

        ```bash
        instrumentation.opentelemetry.io/inject-dotnet: "insight-system/insight-opentelemetry-autoinstrumentation"
        ```

!!! tip

The OpenTelemetry Operator automatically adds some OTEL-related environment variables when injecting probes and also supports overriding these variables. The priority order for overriding these environment variables is as follows:

1. Original container environment variables
2. Language-specific environment variables
3. Common environment variables
4. Instrument specification configuration variables

However, it is important to avoid manually overriding __OTEL_RESOURCE_ATTRIBUTES_NODE_NAME__ .
This variable serves as an identifier within the operator to determine if a pod has already
been injected with a probe. Manually adding this variable may prevent the probe from being
injected successfully.

## Automatic injection Demo

Note that annotations are added under spec.annotations.

```yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
  labels:
    app: my-app
spec:
  selector:
    matchLabels:
      app: my-app
  replicas: 1
  template:
    metadata:
      labels:
        app: my-app
      annotations:
        instrumentation.opentelemetry.io/inject-java: "insight-system/insight-opentelemetry-autoinstrumentation"
    spec:
      containers:
      - name: myapp
        image: jaegertracing/vertx-create-span:operator-e2e-tests
        ports:
          - containerPort: 8080
            protocol: TCP
```

The final generated Yaml content is as follows:

```yaml
apiVersion: v1
kind: Pod
metadata:
  name: my-deployment-with-sidecar-565bd877dd-nqkk6
  generateName: my-deployment-with-sidecar-565bd877dd-
  namespace: default
  uid: aa89ca0d-620c-4d20-8bc1-37d67bad4ea4
  resourceVersion: '2668986'
  creationTimestamp: '2022-04-08T05:58:48Z'
  labels:
    app: my-pod-with-sidecar
    pod-template-hash: 565bd877dd
  annotations:
    cni.projectcalico.org/containerID: 234eae5e55ea53db2a4bc2c0384b9a1021ed3908f82a675e4a92a49a7e80dd61
    cni.projectcalico.org/podIP: 192.168.134.133/32
    cni.projectcalico.org/podIPs: 192.168.134.133/32
    instrumentation.opentelemetry.io/inject-java: "insight-system/insight-opentelemetry-autoinstrumentation"
spec:
  volumes:
    - name: kube-api-access-sp2mz
      projected:
        sources:
          - serviceAccountToken:
              expirationSeconds: 3607
              path: token
          - configMap:
              name: kube-root-ca.crt
              items:
                - key: ca.crt
                  path: ca.crt
          - downwardAPI:
              items:
                - path: namespace
                  fieldRef:
                    apiVersion: v1
                    fieldPath: metadata.namespace
        defaultMode: 420
    - name: opentelemetry-auto-instrumentation
      emptyDir: {}
  initContainers:
    - name: opentelemetry-auto-instrumentation
      image: >-
        ghcr.m.daocloud.io/open-telemetry/opentelemetry-operator/autoinstrumentation-java
      command:
        - cp
        - /javaagent.jar
        - /otel-auto-instrumentation/javaagent.jar
      resources: {}
      volumeMounts:
        - name: opentelemetry-auto-instrumentation
          mountPath: /otel-auto-instrumentation
        - name: kube-api-access-sp2mz
          readOnly: true
          mountPath: /var/run/secrets/kubernetes.io/serviceaccount
      terminationMessagePath: /dev/termination-log
      terminationMessagePolicy: File
      imagePullPolicy: Always
  containers:
    - name: myapp
      image: ghcr.io/pavolloffay/spring-petclinic:latest
      env:
        - name: OTEL_JAVAAGENT_DEBUG
          value: 'true'
        - name: OTEL_INSTRUMENTATION_JDBC_ENABLED
          value: 'true'
        - name: SPLUNK_PROFILER_ENABLED
          value: 'false'
        - name: JAVA_TOOL_OPTIONS
          value: ' -javaagent:/otel-auto-instrumentation/javaagent.jar'
        - name: OTEL_TRACES_EXPORTER
          value: otlp
        - name: OTEL_EXPORTER_OTLP_ENDPOINT
          value: http://insight-agent-opentelemetry-collector.svc.cluster.local:4317
        - name: OTEL_EXPORTER_OTLP_TIMEOUT
          value: '20'
        - name: OTEL_TRACES_SAMPLER
          value: parentbased_traceidratio
        - name: OTEL_TRACES_SAMPLER_ARG
          value: '0.85'
        - name: SPLUNK_TRACE_RESPONSE_HEADER_ENABLED
          value: 'true'
        - name: OTEL_SERVICE_NAME
          value: my-deployment-with-sidecar
        - name: OTEL_RESOURCE_ATTRIBUTES_POD_NAME
          valueFrom:
            fieldRef:
              apiVersion: v1
              fieldPath: metadata.name
        - name: OTEL_RESOURCE_ATTRIBUTES_POD_UID
          valueFrom:
            fieldRef:
              apiVersion: v1
              fieldPath: metadata.uid
        - name: OTEL_RESOURCE_ATTRIBUTES_NODE_NAME
          valueFrom:
            fieldRef:
              apiVersion: v1
              fieldPath: spec.nodeName
        - name: OTEL_RESOURCE_ATTRIBUTES
          value: >-
            k8s.container.name=myapp,k8s.deployment.name=my-deployment-with-sidecar,k8s.deployment.uid=8de6929d-dda0-436c-bca1-604e9ca7ea4e,k8s.namespace.name=default,k8s.node.name=$(OTEL_RESOURCE_ATTRIBUTES_NODE_NAME),k8s.pod.name=$(OTEL_RESOURCE_ATTRIBUTES_POD_NAME),k8s.pod.uid=$(OTEL_RESOURCE_ATTRIBUTES_POD_UID),k8s.replicaset.name=my-deployment-with-sidecar-565bd877dd,k8s.replicaset.uid=190d5f6e-ba7f-4794-b2e6-390b5879a6c4
        - name: OTEL_PROPAGATORS
          value: jaeger,b3
      resources: {}
      volumeMounts:
        - name: kube-api-access-sp2mz
          readOnly: true
          mountPath: /var/run/secrets/kubernetes.io/serviceaccount
        - name: opentelemetry-auto-instrumentation
          mountPath: /otel-auto-instrumentation
      terminationMessagePath: /dev/termination-log
      terminationMessagePolicy: File
      imagePullPolicy: Always
  restartPolicy: Always
  terminationGracePeriodSeconds: 30
  dnsPolicy: ClusterFirst
  serviceAccountName: default
  serviceAccount: default
  nodeName: k8s-master3
  securityContext:
    runAsUser: 1000
    runAsGroup: 3000
    fsGroup: 2000
  schedulerName: default-scheduler
  tolerations:
    - key: node.kubernetes.io/not-ready
      operator: Exists
      effect: NoExecute
      tolerationSeconds: 300
    - key: node.kubernetes.io/unreachable
      operator: Exists
      effect: NoExecute
      tolerationSeconds: 300
  priority: 0
  enableServiceLinks: true
  preemptionPolicy: PreemptLowerPriority
```

## Trace query

How to query the connected services, refer to [Trace Query](../../user-guide/trace/trace.md).