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Documentation Index

Fetch the complete documentation index at: https://openmetadata-feat-feat-2mbfixdeploy.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

In this section, we provide guides and references to use the Grafana connector. Configure and schedule Grafana metadata and profiler workflows from the OpenMetadata UI:

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How to Run the Connector Externally

To run the Ingestion via the UI you’ll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment. If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.

External Schedulers

Get more information about running the Ingestion Framework Externally

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Requirements

You will need:
  • Grafana 9.0+ (Service Account Tokens)
  • Service Account Token with Admin role (for full metadata extraction)
  • Network access to Grafana API endpoints

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Python Requirements

We have support for Python versions 3.9-3.11
To run the Grafana ingestion, install: 
pip3 install "openmetadata-ingestion[grafana]"

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Metadata Ingestion

All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Grafana. In order to create and run a Metadata Ingestion workflow, we will follow the steps to create a YAML configuration able to connect to the source, process the Entities if needed, and reach the OpenMetadata server.

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1. Define the YAML Config

This is a sample config for Grafana:

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Securing Grafana Connection with SSL in OpenMetadata

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2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run: 
metadata ingest -c <path-to-yaml>
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration, you will be able to extract metadata from different sources.