Databricks AI Functions usage

Databricks contributes system-table usage rows for model-serving and foundation model workloads, plus cluster and Lakeflow context for attribution.

Release state

This guide documents the read-only databricks_ai_functions connector implemented in the platform connector surface.

Required access

Grant read access to these Databricks system tables:

Table	Purpose
system.billing.usage	Read AI billing usage rows.
system.compute.clusters	Correlate usage to cluster metadata.
system.lakeflow.pipeline_events	Correlate usage to pipeline owners.

Do not grant workspace mutation, job mutation, or cluster administration permissions.

Setup

1. Create or select a service principal for Venturi.
2. Grant read access to the system tables above.
3. Store the credential reference in Venturi.
4. Set ARGMIN_DATABRICKS_AI_LOOKBACK_HOURS and ARGMIN_DATABRICKS_AI_HIGH_VOLUME_THRESHOLD only when you need to override the default poll window or high-volume flag.
5. In Venturi, open Administration -> Connectors -> Databricks AI Functions and run Test connection.

Verification

• Only MODEL_SERVING and FOUNDATION_MODEL_SERVING usage rows survive the connector filter.
• Cluster and Lakeflow pipeline context appears when available.
• High-volume AI usage is flagged without blocking ingestion.
• The connector remains read-only and fail-open on upstream read errors.

Rotation and offboarding

Rotate the service-principal credential on your Databricks schedule. Removing the connector stops new Databricks AI usage correlation.