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

# Metrics

> Visualize and monitor AI application metrics in OpenLIT platform with custom dashboards and advanced analytics

<MetricsQuickstart />

***

## SDK Configuration Options

OpenLIT offers automatic instrumentation with OpenTelemetry for various LLM providers, frameworks, and VectorDBs, enabling you to gain valuable insights into the behavior and performance of your AI applications through metrics.

<CardGroup cols={2}>
  <Card title="Quickstart: LLM Observablity" href="/latest/sdk/quickstart-ai-observability" icon="bolt">
    Production-ready AI monitoring setup in 2 simple steps with zero code changes
  </Card>

  <Card title="Integrations" href="/latest/sdk/integrations/overview" icon="circle-nodes">
    60+ AI integrations with automatic instrumentation and performance tracking
  </Card>
</CardGroup>

## Disable Metrics

You have the option to disable the collection of metrics if needed. By default, metrics collection is enabled.

Example:

```python theme={null}
# Disable metrics collection
openlit.init(disable_metrics=True)
```

## Using an existing OTel Metrics instance

You have the flexibility to integrate your existing OpenTelemetry (OTel) Metrics instance configuration with OpenLIT.
If you already have an OTel Metrics instance instantiated in your application, you can pass it directly to `openlit.init(meter=meter)`.
This integration ensures that OpenLIT utilizes your custom OTel metrics instance settings, allowing for a unified metrics setup across your application.

Example:

```python theme={null}
# Instantiate an OpenTelemetry Metrics meter
meter = ...

# Pass the meter to OpenLIT
openlit.init(meter=meter)
```

## Add custom resource attributes

The [`OTEL_RESOURCE_ATTRIBUTES`](https://opentelemetry.io/docs/languages/sdk-configuration/general/#otel_resource_attributes) environment variable allows you to provide additional OpenTelemetry resource attributes when starting your application with OpenLIT. OpenLIT already includes some default resource attributes:

* `telemetry.sdk.name: openlit`
* `service.name: YOUR_SERVICE_NAME`
* `deployment.environment: YOUR_ENVIRONMENT_NAME`

You can enhance these default resource attributes by adding your own using the `OTEL_RESOURCE_ATTRIBUTES` variable. Your custom attributes will be added on top of the existing OpenLIT attributes, providing additional context to your telemetry data. Simply format your attributes as `key1=value1,key2=value2`.

For example:

```shell theme={null}
export OTEL_RESOURCE_ATTRIBUTES="service.instance.id=YOUR_SERVICE_ID,k8s.pod.name=K8S_POD_NAME,k8s.namespace.name=K8S_NAMESPACE,k8s.node.name=K8S_NODE_NAME"
```

***

<CardGroup cols={3}>
  <Card title="Deploy OpenLIT" href="/latest/openlit/installation" icon="circle-down">
    Deployment options for scalable LLM monitoring infrastructure
  </Card>

  <Card title="Integrations" href="/latest/sdk/integrations/overview" icon="circle-nodes">
    60+ AI integrations with automatic instrumentation and performance tracking
  </Card>

  <Card title="Destinations" href="/latest/sdk/destinations/overview" icon="link">
    Send elemetry to Datadog, Grafana, New Relic, and other observability stacks
  </Card>
</CardGroup>

<Card title="Zero-code observability with the OpenLIT Controller" icon="tower-broadcast" href="/latest/controller/overview">
  Discover and instrument LLM traffic across Kubernetes, Docker, and Linux using eBPF — no code changes required.
</Card>