OpenMetadata/openmetadata-docs/content/v1.1.x/connectors/ml-model/mlflow/index.md

title	slug
MLflow	/connectors/ml-model/mlflow

MLflow

In this section, we provide guides and references to use the MLflow connector.

Configure and schedule MLflow metadata and profiler workflows from the OpenMetadata UI:

• Requirements
• Metadata Ingestion

{% partial file="/v1.1/connectors/ingestion-modes-tiles.md" variables={yamlPath: "/connectors/ml-model/mlflow/yaml"} /%}

Requirements

To extract metadata, OpenMetadata needs two elements:

• Tracking URI: Address of local or remote tracking server. More information on the MLFlow documentation here
• Registry URI: Address of local or remote model registry server.

Metadata Ingestion

{% partial file="/v1.1/connectors/metadata-ingestion-ui.md" variables={ connector: "Mlflow", selectServicePath: "/images/v1.1/connectors/mlflow/select-service.png", addNewServicePath: "/images/v1.1/connectors/mlflow/add-new-service.png", serviceConnectionPath: "/images/v1.1/connectors/mlflow/service-connection.png", } /%}

{% stepsContainer %} {% extraContent parentTagName="stepsContainer" %}

Connection Details

• trackingUri: MLflow Experiment tracking URI. E.g., http://localhost:5000
• registryUri: MLflow Model registry backend. E.g., mysql+pymysql://mlflow:password@localhost:3307/experiments

{% /extraContent %}

{% partial file="/v1.1/connectors/test-connection.md" /%}

{% partial file="/v1.1/connectors/ml-model/configure-ingestion.md" /%}

{% partial file="/v1.1/connectors/ingestion-schedule-and-deploy.md" /%}

{% /stepsContainer %}

{% partial file="/v1.1/connectors/troubleshooting.md" /%}