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Databricks releases, every cloud

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6 releases of 1321

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  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.

    #Lakeflow#Notebooks
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  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.

    #Notebooks
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  3. 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.

    #Notebooks
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  4. Notebook tagging (Public Preview)

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

    #Notebooks
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  5. 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.

    #Assistant#Notebooks
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  6. 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.

    #Notebooks#Serverless
    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

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.