Databricks releases, every cloud
- Custom trace views in the MLflow trace explorer are in Beta
Genie generates views based on plain language descriptions, surfacing relevant trace fields and metrics.
- MLflow trace storage in Unity Catalog is now generally available
Stores traces in OpenTelemetry format with unlimited storage and SQL query access.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Reorganized Spark Declarative Pipelines on Lakeflow documentation
Conceptual topics are now under Concepts.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Customer-managed keys now support MLflow managed evaluation features
Supports MLflow 3 scorers and requires non-CMK encrypted catalog.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - MLflow trace storage in Unity Catalog is now in Public Preview
Stores OpenTelemetry traces, governed by Unity Catalog permissions, queryable from Databricks SQL or MLflow Python SDK.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Store and query MLflow traces in Unity Catalog (Beta)
Stores MLflow traces in Delta tables for long-term retention and analysis using OpenTelemetry format.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.