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Databricks releases, every cloud

11 releases of 1321

Last updated

  1. Genie Code for AI Runtime (Public Preview)

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

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(unknown)
  2. 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)
  3. Protobuf tensor input for custom model serving endpoints (Public Preview)

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

  4. Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are in Beta

    Powered by Apache Spark 4.2.0.

  5. Databricks Runtime 18 and Databricks Runtime 18 for Machine Learning are in Beta

    Powered by Apache Spark 4.1.0, replacing separate release notes for feature versions.

  6. Databricks Runtime 18.2 and Databricks Runtime 18.2 ML are in Beta

    Powered by Apache Spark 4.1.0.

  7. Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
  8. AI Runtime is now in Public Preview

    Adds GPU support to serverless compute for deep learning workloads.

    AWS, read it on their docsAzure, read it on their docsGCP(not on this cloud)SAP(not on this cloud)
  9. Databricks Runtime 18.1 and Databricks Runtime 18.1 ML are in Beta

    Powered by Apache Spark 4.1.0.

  10. Databricks Runtime 18.0 and Databricks Runtime 18.0 ML are in Beta

    Powered by Apache Spark 4.1.0, includes JDK 21 as default.

  11. Databricks Runtime 17.3 LTS and Databricks Runtime 17.3 LTS ML are in Beta

    Powered by Apache Spark 4.0.0, includes new configuration options.

  12. 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.