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12 releases of 1321

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  1. 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)
  2. Query text is now masked by default in system tables and APIs

    Masking applies to system.query.history, Query History API, and List Queries API. Account admins can grant access to unmasked text via databricks_pii_access group.

    #Audit logs#Security
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  3. 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)
  4. 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)
  5. 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)
  6. 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)
  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. 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)
  9. 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)
  10. 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)
  11. 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)
  12. 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)
  13. The sourceIpAddress field in audit logs will no longer include a port number Coming soon

    Removes port number, which was always 0, for consistency with other logs.

    #Audit logs
    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.