MLflow Connector | OpenMetadata ML Model Integration

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
• Troubleshooting

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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.

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Metadata Ingestion

To ingest metadata from MLflow, you need to create a service connection. The service connects MLflow with OpenMetadata. Once you create a service, OpenMetadata automatically starts ingesting metadata.

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Step 1: Add New Service

1. Navigate to Settings > Services.
2. Click Add New Service.

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Step 2: Select a Service and Connector

From the service type dropdown, select ML Model Services, then click the MLflow connector tile.

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Step 3: Add Service Name and Description

• Enter a unique, descriptive Service Name. OpenMetadata identifies services by their service name. Enter a name that distinguishes this deployment from other MLflow services you are ingesting metadata from.
• Optional: Enter a Description for the service.

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Step 4: Configure Connection Options

Specify your source credentials and verify the connection.

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Enter Connection Details

Enter the connection details for MLflow. The right-hand panel in the UI displays inline help for each field.

• Tracking URI: MLflow experiment tracking URI, for example http://localhost:5000.
• Registry URI: MLflow model registry backend, for example mysql+pymysql://mlflow:password@localhost:3307/experiments.

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Test Connection

Once the credentials have been added, click on Test Connection and Save the changes.

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Step 5: Configure Ingestion Options

In the What to Ingest step, use filter patterns to control which assets OpenMetadata ingests from your ML model service. Filter patterns use regular expressions applied to model names.

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How Filter Patterns Work

• Include: Add one or more comma-separated regular expressions. OpenMetadata ingests only assets whose names match at least one expression. Leave blank to include all assets.
• Exclude: Add one or more comma-separated regular expressions. OpenMetadata skips any asset whose name matches an expression. Leave blank to exclude nothing.

Rules match asset names using one of five expressions:

• contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
• starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
• ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
• is exactly: matches the exact name only. For example, analytics matches only analytics.
• matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.

When both Include and Exclude are set, Exclude takes priority. Filter Options The ML Model section includes the following filter options:

• ML Model: Controls which ML models OpenMetadata ingests from the source.

Each section provides the following controls:

• Scan Mode: You can choose between the following scan modes:
  • Scan all: Ingests every asset of that type the connector can access. This is the default.
  • Only specific: Enables include rules so only assets matching at least one rule are ingested.
• Exclude system toggle: Use this toggle to automatically filter out system-reserved names defined by the connector, for example, Exclude system databases for the Databases section.
• Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
• Preview: Shows a real-time summary of what will be in scope based on your current rules.
• Include rules (available only in Only specific mode): Click + Add to define a rule. Added rules appear as chips; an asset is included if it matches any rule.

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Step 6: Create & Deploy

Click Create & Deploy to deploy the agent and start the first metadata ingestion run. OpenMetadata saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to Settings > Services and select your service.

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Configure Metadata Agent and Schedule Ingestion

The Metadata Agent extracts ML models, features, and other structural metadata from your source and keeps your OpenMetadata catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click Create & Deploy, OpenMetadata automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the Agents tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps:

1. Navigate to Settings > Services and select the service type.
2. Click the service you have added.
3. Select the Agents tab and click Add Agent > Metadata. For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
4. On the Configure Ingestion page, do the following and click Next.
   • Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline.
   • Agent Setup: Configure the core parameters for this agent. The following fields are available:

     Field	Default	Description
     Db Service Prefixes	—	List of database service name prefixes used to resolve lineage between ML models and database assets. Accepted formats: DBService, DBService.Database, DBService.Database.Schema, DBService.Database.Schema.Table.
     Mark Deleted ML Models	On	Soft-delete ML models in OpenMetadata when they are removed from the source. Associated entities like lineage are also deleted.

     
   • Filter Patterns: Apply include or exclude rules to scope which ML models this agent ingests. These follow the same filter options described in Step 5: Configure Ingestion Options.
   • Scope & Behaviour: Control what metadata to include and how to handle deletions. Toggle each option on or off based on your needs:

     Toggle	Default	Description
     Enable Debug Log	Off	Sets the ingestion log level to DEBUG. Useful for troubleshooting.
     Override Metadata	Off	When on, source values overwrite existing descriptions, tags, owners, and display names in OpenMetadata. When off, OpenMetadata only updates fields that have no existing value.
     Override Lineage	Off	When on, existing lineage is replaced with newly extracted lineage on each run.

     
5. On the Schedule Interval page, set when the agent runs:
   • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
   • On-Demand: No automatic schedule; trigger the agent manually when needed.
   
6. Click Add to deploy the agent.

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