> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/openlit/openlit/llms.txt
> Use this file to discover all available pages before exploring further.

# Operator configuration

> Configure the OpenLIT Operator deployment with Helm values, and define AutoInstrumentation custom resources to control how workloads are instrumented.

Operator configuration is split into two areas:

1. **Helm values** — control the operator deployment itself (replicas, resources, log level, images)
2. **AutoInstrumentation CRD** — control which pods are instrumented and how

## Operator Helm values

Pass values at install or upgrade time with `--set` flags or a `values.yaml` file.

### Deployment

<ParamField path="deployment.replicas" type="integer" default="1">
  Number of operator replicas. For high availability, set to `3` and configure `podAntiAffinity`.
</ParamField>

<ParamField path="deployment.strategy.type" type="string" default="RollingUpdate">
  Kubernetes deployment strategy. Use `Recreate` if you need to avoid running two operator versions simultaneously.
</ParamField>

<ParamField path="deployment.priorityClassName" type="string" default="">
  Priority class for the operator pod. Set to `system-cluster-critical` for production environments.
</ParamField>

### Resource limits

<ParamField path="resources.requests.cpu" type="string" default="100m">
  CPU request for the operator pod.
</ParamField>

<ParamField path="resources.requests.memory" type="string" default="128Mi">
  Memory request for the operator pod.
</ParamField>

<ParamField path="resources.limits.cpu" type="string" default="500m">
  CPU limit for the operator pod.
</ParamField>

<ParamField path="resources.limits.memory" type="string" default="512Mi">
  Memory limit for the operator pod.
</ParamField>

**Example — high availability deployment:**

```yaml theme={null}
deployment:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxUnavailable: 1
      maxSurge: 1
  priorityClassName: system-cluster-critical
  affinity:
    podAntiAffinity:
      preferredDuringSchedulingIgnoredDuringExecution:
      - weight: 100
        podAffinityTerm:
          labelSelector:
            matchLabels:
              app.kubernetes.io/name: openlit-operator
          topologyKey: kubernetes.io/hostname

resources:
  requests:
    cpu: 200m
    memory: 256Mi
  limits:
    cpu: 500m
    memory: 512Mi
```

### Observability

<ParamField path="observability.logLevel" type="string" default="info">
  Operator log level. Accepts `debug`, `info`, `warn`, or `error`.
</ParamField>

<ParamField path="observability.selfMonitoringEnabled" type="boolean" default="false">
  Emit the operator's own telemetry via OpenTelemetry. Requires `observability.otel.endpoint`.
</ParamField>

<ParamField path="observability.otel.endpoint" type="string" default="">
  OTLP endpoint to send operator telemetry to, for example `http://openlit:4318`.
</ParamField>

**Example:**

```yaml theme={null}
observability:
  logLevel: info
  selfMonitoringEnabled: true
  otel:
    endpoint: "http://openlit:4318"
    headers: "Authorization=Bearer my-secret-token"
```

### Provider images

The operator uses pre-built init container images for each instrumentation provider. By default these inherit the operator's own image tag.

<ParamField path="providerImages.openlit.repository" type="string" default="ghcr.io/openlit/openlit-ai-instrumentation">
  Image repository for the OpenLIT instrumentation provider.
</ParamField>

<ParamField path="providerImages.openllmetry.repository" type="string" default="ghcr.io/openlit/openllmetry-ai-instrumentation">
  Image repository for the OpenLLMetry instrumentation provider.
</ParamField>

<ParamField path="providerImages.openinference.repository" type="string" default="ghcr.io/openlit/openinference-ai-instrumentation">
  Image repository for the OpenInference instrumentation provider.
</ParamField>

**Example — using a private registry:**

```yaml theme={null}
providerImages:
  openlit:
    repository: my-registry.example.com/openlit-ai-instrumentation
    tag: "v1.0.0"
  openllmetry:
    repository: my-registry.example.com/openllmetry-ai-instrumentation
  openinference:
    repository: my-registry.example.com/openinference-ai-instrumentation
```

### Instrumentation defaults

<ParamField path="instrumentation.defaultProvider" type="string" default="openlit">
  Default instrumentation provider used when none is specified in the `AutoInstrumentation` CR. Accepts `openlit`, `openinference`, `openllmetry`, or `custom`.
</ParamField>

<ParamField path="instrumentation.defaultVersion" type="string" default="latest">
  Default provider image tag.
</ParamField>

<ParamField path="instrumentation.defaultImagePullPolicy" type="string" default="IfNotPresent">
  Image pull policy for init containers.
</ParamField>

***

## AutoInstrumentation CRD

The `AutoInstrumentation` custom resource defines which pods to instrument, how to instrument them, and where to send telemetry.

### Full spec reference

```yaml theme={null}
apiVersion: openlit.io/v1alpha1
kind: AutoInstrumentation
metadata:
  name: my-instrumentation
  namespace: default
spec:
  # Pod selection — required
  selector:
    matchLabels:
      openlit.io/instrument: "true"
    matchExpressions:
    - key: "environment"
      operator: In
      values: ["production", "staging"]

  # Pods to skip even when they match the selector
  ignore:
    matchLabels:
      openlit.io/skip: "true"

  # Python instrumentation settings
  python:
    instrumentation:
      enabled: true
      provider: "openlit"        # openlit | openinference | openllmetry | custom
      version: "latest"
      imagePullPolicy: "IfNotPresent"
      customPackages: "langchain>=0.1.0,chromadb>=0.4.0"
      env:
      - name: OPENLIT_ENVIRONMENT
        value: "production"
      - name: OPENLIT_API_KEY
        valueFrom:
          secretKeyRef:
            name: openlit-secret
            key: api-key

  # OTLP endpoint — required
  otlp:
    endpoint: "http://openlit.openlit.svc.cluster.local:4318"
    headers: "authorization=Bearer token123"
    timeout: 30

  # Resource attributes added to all telemetry
  resource:
    environment: "production"
    serviceName: "ai-chat-service"
    serviceNamespace: "ai-platform"
    serviceVersion: "v2.1.0"
```

### Pod selection

<ParamField path="spec.selector" type="LabelSelector" required>
  Pods matching this selector in the same namespace will be instrumented. Supports `matchLabels` (exact match) and `matchExpressions` (operators: `In`, `NotIn`, `Exists`, `DoesNotExist`).
</ParamField>

<ParamField path="spec.ignore" type="LabelSelector">
  Pods matching this selector are skipped, even if they match `spec.selector`. Use to exclude system components or debug pods.
</ParamField>

<Note>
  `AutoInstrumentation` resources only affect pods **in the same namespace**. To instrument pods across namespaces, create a separate `AutoInstrumentation` resource in each namespace.
</Note>

### Python instrumentation

<ParamField path="spec.python.instrumentation.enabled" type="boolean" default="true">
  Enable or disable Python instrumentation.
</ParamField>

<ParamField path="spec.python.instrumentation.provider" type="string" default="openlit">
  Instrumentation provider. Accepted values:

  | Value           | Description                              | Init image                                         |
  | --------------- | ---------------------------------------- | -------------------------------------------------- |
  | `openlit`       | Full AI observability with cost tracking | `ghcr.io/openlit/openlit-ai-instrumentation`       |
  | `openinference` | OpenInference conventions, OTel-standard | `ghcr.io/openlit/openinference-ai-instrumentation` |
  | `openllmetry`   | LLM-focused OpenTelemetry extensions     | `ghcr.io/openlit/openllmetry-ai-instrumentation`   |
  | `custom`        | Your own init container image            | Set `customInitImage`                              |
</ParamField>

<ParamField path="spec.python.instrumentation.version" type="string" default="latest">
  Provider image tag to use.
</ParamField>

<ParamField path="spec.python.instrumentation.customPackages" type="string" default="">
  Comma-separated list of additional pip packages to install in the init container, e.g. `langchain>=0.1.0,chromadb>=0.4.0`.
</ParamField>

<ParamField path="spec.python.instrumentation.customInitImage" type="string" default="">
  Full image reference for a custom init container. Required when `provider` is `custom`.
</ParamField>

### OTLP configuration

<ParamField path="spec.otlp.endpoint" type="string" required>
  OTLP HTTP endpoint. Must be a valid HTTP or HTTPS URL.

  | Format              | Example                                         | Use case         |
  | ------------------- | ----------------------------------------------- | ---------------- |
  | In-cluster service  | `http://openlit:4318`                           | Same namespace   |
  | Fully qualified DNS | `http://openlit.openlit.svc.cluster.local:4318` | Cross-namespace  |
  | External HTTPS      | `https://traces.example.com:4318`               | Cloud / external |
</ParamField>

<ParamField path="spec.otlp.headers" type="string" default="">
  HTTP headers as comma-separated `key=value` pairs, e.g. `authorization=Bearer token123,x-api-key=secret`. Used for authentication with external backends.
</ParamField>

<ParamField path="spec.otlp.timeout" type="integer" default="30">
  Request timeout in seconds. Accepted range: 1–300.
</ParamField>

### Resource attributes

Resource attributes are attached to every span and metric as OpenTelemetry resource attributes. The operator also automatically adds `k8s.pod.name`, `k8s.namespace.name`, `k8s.deployment.name`, `k8s.node.name`, and related Kubernetes attributes.

<ParamField path="spec.resource.environment" type="string" default="">
  Maps to `deployment.environment`. Example: `production`.
</ParamField>

<ParamField path="spec.resource.serviceName" type="string" default="">
  Maps to `service.name`. Overrides the auto-detected service name.
</ParamField>

<ParamField path="spec.resource.serviceNamespace" type="string" default="">
  Maps to `service.namespace`.
</ParamField>

<ParamField path="spec.resource.serviceVersion" type="string" default="">
  Maps to `service.version`. Example: `v2.1.0`.
</ParamField>