---
title: 'OpenObserve'
description: 'LLM Observability with OpenObserve and OpenLIT'
---

<Frame>
  <img src="/images/openobserve-dashboard-1.png" />
  <img src="/images/openobserve-dashboard-2.png" />
</Frame>

To directly send OpenTelemetry metrics and traces generated by OpenLIT from your AI Application to OpenObserve, Follow the below steps.
<Steps>
  <Step title="Get your OpenObserve Credentials">
    <Steps>
      1. Log into your OpenObserve instance.
      1. Click **Ingestion** in the side navigation and select Traces (OpenTelemetry) option.
      1. Under the **OTLP HTTP** section, Copy the Ingestion HTTP Endpoint and the Ingestion Authorization key (After `Basic`)
    </Steps>
  </Step>
  <Step title="Add the following two lines to your application code:">
    <Tabs>
      <Tab title="Setup using function arguments">
      ```python
      import openlit

      openlit.init(
        otlp_endpoint="YOUR_OPENOBSERVE_HTTP_ENDPOINT", 
        otlp_headers="YOUR_OPENOBSERVE_AUTH_HEADER"
      )
      ```

      Replace:
      1. `YOUR_OPENOBSERVE_HTTP_ENDPOINT` with the Ingestion HTTP Endpoint value you copied in Step 1. 
        * Example - `http://127.0.0.1:5080/api/default`
      1. `YOUR_OPENOBSERVE_AUTH_HEADER` with the Ingestion Authorization key value you copied in Step 1. 
        * Example - `Authorization=Basic%20<Ingestion Authorization key>`
      </Tab>
      <Tab title="Setup using Environment Variables">
      ```python
      import openlit

      openlit.init()
      ```

      Run the following command to configure the OTEL endpoint and headers to send metrics and traces to OpenObserve:
      ```shell
      export OTEL_EXPORTER_OTLP_ENDPOINT = "YOUR_OPENOBSERVE_HTTP_ENDPOINT"
      export OTEL_EXPORTER_OTLP_HEADERS = "YOUR_OPENOBSERVE_AUTH_HEADER"
      ```

      Replace:
      1. `YOUR_OPENOBSERVE_HTTP_ENDPOINT` with the Ingestion HTTP Endpoint value you copied in Step 1. 
        * Example - `http://127.0.0.1:5080/api/default`
      1. `YOUR_OPENOBSERVE_AUTH_HEADER` with the Ingestion Authorization key value you copied in Step 1. 
        * Example - `Authorization=Basic%20<Ingestion Authorization key>`
      </Tab>
    </Tabs>
  Refer to the OpenLIT [Python SDK repository](https://github.com/openlit/openlit/tree/main/sdk/python) for more advanced configurations and use cases.
  </Step>
  <Step title="Import the pre-built Dashboard">
  1. Log into your OpenObserve Instance.
  1. Click **Dashboards** in the side navgivation menu.
  1. Click **Import** on the top right corner.
  1. Copy the dashboard JSON provided in the accordion named [`Dashboard`](#dashboard) below.
  1. Paste the dashboard JSON text directly under the **Import Dashboard from JSON** section
  1. Click **Import**.
  1. Save the dashboard.
  <Accordion title="Dashboard">
      ```json
      {
        "version": 4,
        "dashboardId": "7232616793020301352",
        "title": "GenAI Observability",
        "description": "This dashboard tracks the performance of LLM and VectorDB, recording metrics like latency, tokens used, and cost. It also logs input and output data, including request IDs, timestamps, user IDs, and model versions. This helps identify how well the systems are working and where improvements can be made.",
        "role": "",
        "owner": "",
        "created": "2024-08-23T05:46:38.299Z",
        "tabs": [
            {
            "tabId": "default",
            "name": "GenAI",
            "panels": [
                {
                "id": "Panel_ID4678610",
                "type": "metric",
                "title": "Total Successful GenAI Requests",
                "description": "",
                "config": {
                    "show_legends": true,
                    "legends_position": null,
                    "decimals": 2,
                    "axis_border_show": false,
                    "legend_width": {
                    "unit": "px"
                    },
                    "base_map": {
                    "type": "osm"
                    },
                    "map_view": {
                    "zoom": 1,
                    "lat": 0,
                    "lng": 0
                    },
                    "map_symbol_style": {
                    "size": "by Value",
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                    "size_fixed": 2
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                    "drilldown": [],
                    "mark_line": [],
                    "connect_nulls": false,
                    "no_value_replacement": "",
                    "wrap_table_cells": false
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                "queryType": "sql",
                "queries": [
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                    "vrlFunctionQuery": "",
                    "customQuery": false,
                    "fields": {
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                        "stream_type": "metrics",
                        "x": [],
                        "y": [
                        {
                            "label": "Value",
                            "alias": "y_axis_1",
                            "column": "value",
                            "color": "#121969",
                            "aggregationFunction": "count",
                            "isDerived": false
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                        ],
                        "z": [],
                        "breakdown": [],
                        "filter": [
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                            "operator": null,
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                "layout": {
                    "x": 24,
                    "y": 0,
                    "w": 12,
                    "h": 4,
                    "i": 1
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                "htmlContent": "",
                "markdownContent": ""
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                {
                "id": "Panel_ID6880210",
                "type": "markdown",
                "title": "-",
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                "queryType": "",
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                    "query": "",
                    "vrlFunctionQuery": "",
                    "customQuery": false,
                    "fields": {
                        "stream": "",
                        "stream_type": "logs",
                        "x": [],
                        "y": [],
                        "z": [],
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                "layout": {
                    "x": 0,
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                "htmlContent": "",
                "markdownContent": "---\n#### GenAI Observability\n\nThis dashboard displays the usage stats of LLMs, Vector Databases and GPUs, tracking OpenTelemetry Traces and Metrics sent using [OpenLIT](https://github.com/openlit/openlit).\n\n---"
                },
                {
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                "description": "",
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                "id": "Panel_ID3428310",
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                },
                {
                "id": "Panel_ID3329710",
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      ```
  </Accordion>

  </Step>
</Steps>


---

<CardGroup cols={2}>
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