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Databricks releases, every cloud

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33 releases of 1321

Last updated

  1. Databricks Apps is now on by default for workspaces with the compliance security profile enabled

    Requires compliance security profile.

    #Databricks Apps#Security
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  2. Databricks Apps telemetry is now generally available

    Collects traces, logs, and metrics to Unity Catalog tables using OpenTelemetry.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  3. Horizontal scaling for Databricks Apps will soon be available for workspaces with the compliance security profile enabled Coming soon

    Automatically enabled in October 2026 for compliance workspaces, allowing multiple instances behind a single URL.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  4. Genie Code for AI Runtime (Public Preview)

    Generates distributed training code and resolves environment issues. Requires AI Runtime.

    #Genie Code#Machine Learning
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  5. User authorization for Databricks Apps will soon be available for workspaces with the compliance security profile enabled Coming soon

    Enables apps to act with user identity, enforcing existing permissions. Automatically enabled in late September 2026.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  6. 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.

    #Gen AI#MLflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  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.

    #Compute#Machine Learning
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  9. MLflow trace storage in Unity Catalog is now generally available

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

    #MLflow#Unity Catalog
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  10. Protobuf tensor input for custom model serving endpoints (Public Preview)

    Replaces JSON with serialized KServe v2 ModelInferRequest. Requires endpoints deployed after July 9, 2026.

    #Machine Learning#Model Serving
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  11. Custom Docker images for AI Runtime CLI workloads (Beta)

    Allows custom system library versions and complex dependencies, requires setup via Use custom Docker images.

    #Machine Learning
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  12. AI Runtime CLI (Beta)

    Submits and manages distributed training workloads on serverless GPU compute from a local machine.

    #Machine Learning
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  13. Databricks Apps horizontal scaling (Beta)

    Runs across multiple instances behind a single URL, supports zero-downtime deployments.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  14. Serve custom LLMs with Custom Model Serving (Beta)

    Supports multimodal models and PEFT recipes, unlike Foundation Model APIs.

    #Machine Learning#Model Serving
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  15. Customer-managed keys now support MLflow managed evaluation features

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

    #MLflow#Security
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  16. App telemetry for Databricks Apps is now in Public Preview

    Collects traces, logs, and metrics via OpenTelemetry protocol to Unity Catalog tables.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  17. 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.

    #MLflow#Unity Catalog
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  18. AI Runtime 1xH100 accelerator (Beta)

    Supports 1xH100 accelerator, see Hardware options for details.

    #Machine Learning
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  19. Updated UI navigation for Databricks Apps

    Streamlines app editing and deployment workflows, accessible from the app switcher.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  20. Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
  21. Git-backed app deployments are now generally available

    Deploys apps from Git repositories, allowing Git-only deployments across a workspace.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  22. AI Runtime is now in Public Preview

    Adds GPU support to serverless compute for deep learning workloads.

    #Machine Learning
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  23. Databricks Apps supports uv for Python dependency management

    Uses pyproject.toml and uv.lock files. Replaces prior dependency management methods.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  24. Lakebase databases as Databricks Apps resources

    Replaces manual database configuration, requires Lakebase setup.

    #Databricks Apps#Lakebase
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  25. Databricks Apps compute sizing support for compliance security profile standards

    Available by default for workspaces with compliance security profile enabled, supporting all Databricks compliance standards.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  26. Declarative Feature Engineering APIs (Beta)

    Define time-windowed aggregation features from data sources, materialize to Delta tables or Lakebase. Available in us-east-1 and us-west-2 regions.

    #Machine Learning
    AWS, read it on their docsAzure(not on this cloud)GCP(not on this cloud)SAP(not on this cloud)
  27. New resources for Databricks Apps

    Adds app-to-app communication and governed table access. Requires Unity Catalog tables.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  28. Databricks Apps telemetry (Beta)

    Collects traces, logs, and metrics via OpenTelemetry protocol to Unity Catalog tables.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  29. Endpoint telemetry for custom model serving endpoints (Beta)

    Stores logs, traces, and metrics in Unity Catalog Delta tables using OpenTelemetry.

    #Machine Learning#Model Serving
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  30. Deploy Databricks apps from Git repositories (Beta)

    Deploys from any branch, tag, or commit, without uploading files to the workspace.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  31. Tag Databricks Apps (Public Preview)

    Organize and categorize apps, but search is not supported.

    #Databricks Apps#Unity Catalog
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  32. Compute sizing for Databricks Apps is now generally available

    Offers Medium (2 vCPUs, 6 GB) and Large (4 vCPUs, 12 GB) sizes.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  33. Store and query MLflow traces in Unity Catalog (Beta)

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

    #Gen AI#MLflow
    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  34. New resource types for Databricks Apps

    Adds MLflow experiments, vector search indexes, UDFs, and Unity Catalog connections as resources.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  35. Configure compute size for Databricks Apps (Public Preview)

    Controls CPU, memory, and cost based on workload requirements.

    #Databricks Apps
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)

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.