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Databricks releases, every cloud

8 releases of 1321

Last updated

  1. Session restore for serverless jobs is in Public Preview

    Restores Python variables and Spark session into a new notebook for debugging or exploration, requires eligible serverless compute job runs.

  2. Session restore for serverless jobs is now in Beta

    Restores Python variables and Spark session into a new notebook. Captures state snapshots on failure or long runs.

  3. 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.

  4. Git CLI commands in Git folders are now in Public Preview

    Enables standard Git commands like git stash and rebase in Databricks terminals. Requires workspace eligibility.

  5. 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.

  6. Notebook tagging (Public Preview)

    Organizes notebooks for easier management, supports governed tags for trust levels or lifecycle status.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Databricks Assistant Agent mode: Data Science Agent is in Beta

    Orchestrates multi-step workflows from a single prompt, building entire notebooks for tasks like EDA and machine learning.

  9. Admins can now manage a workspace's serverless base environments (Public Preview)

    Defines custom environment specs for serverless notebooks, allows setting a default for new notebooks.

Headlines, dates and product areas are Databricks' own, from the release notes published for each cloud, and every item links to the note it came from. The one-line summaries are ours. Not a Databricks product and not affiliated with Databricks, Inc.