Databricks releases, every cloud
- Databricks Apps is now on by default for workspaces with the compliance security profile enabled
Requires compliance security profile.
- Databricks Apps telemetry is now generally available
Collects traces, logs, and metrics to Unity Catalog tables using OpenTelemetry.
- Base environments are now supported on classic compute (Beta)
Manages Python dependencies using Databricks-provided or custom environments.
- 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.
- 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.
- Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Default Python package repositories are GA for Lakeflow pipelines and classic compute
Supports private or authenticated registries as workspace defaults. Applies to UI and API created classic compute.
- 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.
- Manage project environments with %uv commands
Requires environment version 5 or above. Supports serverless notebooks.
- 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.
- Target an Azure capacity reservation group for classic compute
Requires VNet injection, guarantees compute capacity for constrained VM types.
- Search and replace text across files
Works in Databricks Git folders or Declarative Automation Bundles projects from the Search pane.
- Organize your work with spaces
Preserves open tabs for specific folders or projects.
- 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.
- 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.
- Dedicated group clusters will soon be available by default for workspaces with the compliance security profile enabled Coming soon
Enables shared compute for groups with compliance security profile, supporting Databricks Runtime for ML and RDD APIs.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 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.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Mention Genie Code in notebook comments
Triggers AI help inline by typing @ and selecting Genie Code.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- Serverless compute is now available in the Azure UK West region
Supports notebooks, jobs, pipelines, and SQL warehouses, with private connectivity.
- Schedule deferred policy enforcement for all-purpose compute
Applies on next restart or immediately, and admins can cancel scheduled enforcements.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Apps horizontal scaling (Beta)
Runs across multiple instances behind a single URL, supports zero-downtime deployments.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Instance events and instance pools system tables are now available (Public Preview)
Track instance state transitions and instance pool configurations via system.compute.instance_events and system.compute.instance_pools tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Container Services for standard compute is now available (Beta)
Requires Databricks Runtime 18.3 or later, allows custom Docker images in shared compute.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - App telemetry for Databricks Apps is now in Public Preview
Collects traces, logs, and metrics via OpenTelemetry protocol to Unity Catalog tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Faster package installs with %uv pip in serverless notebooks
Requires environment version 5 or above. Replaces %pip for faster installs.
- Native data profiling for notebook results tables
View column statistics by selecting headers and clicking Open selection details. Available in notebooks and new SQL editor.
- Compute log delivery to volumes is now GA
Delivers Spark driver, worker, and event logs to Unity Catalog volumes, recommended for log storage.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Updated UI navigation for Databricks Apps
Streamlines app editing and deployment workflows, accessible from the app switcher.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Git-backed app deployments are now generally available
Deploys apps from Git repositories, allowing Git-only deployments across a workspace.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Apps supports uv for Python dependency management
Uses pyproject.toml and uv.lock files. Replaces prior dependency management methods.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Lakebase databases as Databricks Apps resources
Replaces manual database configuration, requires Lakebase setup.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Serverless compute is enabled by default
Eligible Google Cloud workspaces are affected, account admins no longer need to manually enable it.
- 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.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - New resources for Databricks Apps
Adds app-to-app communication and governed table access. Requires Unity Catalog tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Apps telemetry (Beta)
Collects traces, logs, and metrics via OpenTelemetry protocol to Unity Catalog tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Notebook tagging (Public Preview)
Organizes notebooks for easier management, supports governed tags for trust levels or lifecycle status.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Deploy Databricks apps from Git repositories (Beta)
Deploys from any branch, tag, or commit, without uploading files to the workspace.
- Tag Databricks Apps (Public Preview)
Organize and categorize apps, but search is not supported.
- Paste images into notebooks
Copies images from local file system using ⌘ + V or Ctrl + V.
- View and restore your recent workspace tab sessions
Restores up to 10 recent sessions.
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.