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Databricks releases, every cloud

22 releases of 1321

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  1. Base environments are now supported on classic compute (Beta)

    Manages Python dependencies using Databricks-provided or custom environments.

  2. Git Folder Serverless is in Beta

    Shares serverless compute and pyproject.toml environment across notebooks and files.

  3. Default Python package repositories are GA for Lakeflow pipelines and classic compute

    Supports private or authenticated registries as workspace defaults. Applies to UI and API created classic compute.

  4. Manage project environments with %uv commands

    Requires environment version 5 or above. Supports serverless notebooks.

  5. 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.

  6. Serverless compute access control is now generally available

    Governs access to notebooks, jobs, and pipelines through Default Interactive and Automated Compute objects. Existing workloads run unchanged.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. Web terminal on serverless GPU compute (AI Runtime) is in Public Preview

    Runs shell commands, monitors GPU usage, and manages files on serverless GPU compute. Requires environment version 5 or above.

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  9. Dedicated group clusters will soon be available by default for workspaces with the compliance security profile enabled Coming soon

    Enables shared compute for groups with compliance security profile, supporting Databricks Runtime for ML and RDD APIs.

  10. MLflow trace storage in Unity Catalog is now generally available

    Stores traces in OpenTelemetry format with unlimited storage and SQL query access.

  11. Schedule deferred policy enforcement for all-purpose compute

    Applies on next restart or immediately, and admins can cancel scheduled enforcements.

  12. Reorganized Spark Declarative Pipelines on Lakeflow documentation

    Conceptual topics are now under Concepts.

  13. Instance events and instance pools system tables are now available (Public Preview)

    Track instance state transitions and instance pool configurations via system.compute.instance_events and system.compute.instance_pools tables.

  14. Customer-managed keys now support MLflow managed evaluation features

    Supports MLflow 3 scorers and requires non-CMK encrypted catalog.

  15. Databricks Container Services for standard compute is now available (Beta)

    Requires Databricks Runtime 18.3 or later, allows custom Docker images in shared compute.

  16. 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.

  17. Compute log delivery to volumes is now GA

    Delivers Spark driver, worker, and event logs to Unity Catalog volumes, recommended for log storage.

  18. Upcoming breaking change: default behavior when deleting a Unity Catalog pipeline Coming soon

    Deletes now retain associated tables by default, set cascade=true to remove them.

  19. Databricks Documentation site table of contents tabs

    Replaces static sidebar with tabbed navigation, includes 6 context tabs.

    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(not on this cloud)
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  21. Change to use_case field in VPC endpoint API responses Coming soon

    Changes from WORKSPACE_ACCESS to GENERAL_ACCESS, see API docs for details.

    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(unknown)
  22. Store and query MLflow traces in Unity Catalog (Beta)

    Stores MLflow traces in Delta tables for long-term retention and analysis using OpenTelemetry format.

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  23. Flexible node types are now generally available

    Falls back to alternative instance types when specified type is unavailable, improving launch reliability.

  24. Configure compute to use AWS Capacity Blocks

    Replaces on-demand instances, requires AWS account setup.

    AWS, read it on their docsAzure(not on this cloud)GCP(not on this cloud)SAP(unknown)

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