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35 releases of 1321

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  1. Standard performance mode is now available for one-time runs in the Jobs API

    Sets performance_target to STANDARD. Supports Apache Airflow's DatabricksSubmitRunOperator.

    #Lakeflow#Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  2. Environment version 6 is now available

    Supports serverless and standard classic compute.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  3. 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)
  4. 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)
  5. JAR tasks on serverless compute are now generally available

    Requires matching Scala, Java Development Kit, and Databricks Connect versions.

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

    #Compute#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
  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. July 6, 2026

    Updates from Databricks Runtime 18, adds Spark Declarative Pipelines and IP address functions.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  12. 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)
  13. 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)
  14. Reorganized Spark Declarative Pipelines on Lakeflow documentation

    Conceptual topics are now under Concepts.

    #Documentation#Lakeflow
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  15. Workspace admin setting for serverless notebook execution timeout

    Replaces manual override process, defaults to 2.5 hours.

    #Admin#Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP, read it on their docs
  16. 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)
  17. 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)
  18. Version 18.2

    Adds CREATE OR REPLACE TEMP TABLE syntax and upgrades Snowflake JDBC driver to 3.28.0.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  19. Faster package installs with %uv pip in serverless notebooks

    Requires environment version 5 or above. Replaces %pip for faster installs.

    #Notebooks#Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP, read it on their docs
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  21. 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)
  22. Workspace base environments are now generally available

    Lets workspace admins create pre-built environments for serverless notebooks, enabled by default in compliance security profile workspaces.

    #Admin#Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  23. 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)
  24. Version 18.1

    Supports DATETIMEOFFSET for Azure Synapse and adds schema evolution with INSERT statements.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud)
  25. Databricks Documentation site table of contents tabs

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

    #Documentation
    AWS, read it on their docsAzure(not on this cloud)GCP, read it on their docsSAP(not on this cloud)
  26. 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)
  27. 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)
  28. 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)
  29. Version 18.0

    Upgrades Redshift JDBC driver to 2.1.0.28, adds SQL window functions to metric views.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  30. Serverless environment version 5 is now available

    Includes CPU and GPU versions.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  31. Serverless workspaces are now generally available

    Come pre-configured with serverless compute and default storage.

    #Serverless#Workspace
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  32. 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)
  33. You can now use custom base environments for Python, Python Wheels, and notebook tasks in serverless jobs

    Defined with YAML files, they support Python, Python wheel, and notebook tasks.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  34. Serverless notebook tasks can now use jobs environment

    Replaces inherited serverless environment with configurable job environment.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  35. Serverless compute has been updated to version 17.3

    Updated from version 17.2, requires no configuration changes.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  36. The billable usage table now records the performance mode of serverless jobs and pipelines

    Records performance mode in product_features.performance_target column with values PERFORMANCE_OPTIMIZED, STANDARD, or null.

    #Serverless
    AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(unknown)
  37. 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)

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