Databricks releases, every cloud
- Base environments are now supported on classic compute (Beta)
Manages Python dependencies using Databricks-provided or custom environments.
- Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.
- Genie Code for AI Runtime (Public Preview)
Generates distributed training code and resolves environment issues. Requires AI Runtime.
- 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.
- Manage project environments with %uv commands
Requires environment version 5 or above. Supports serverless notebooks.
- Target an Azure capacity reservation group for classic compute
Requires VNet injection, guarantees compute capacity for constrained VM types.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- 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) - Serverless compute is now available in the Azure UK West region
Supports notebooks, jobs, pipelines, and SQL warehouses, with private connectivity.
- Protobuf tensor input for custom model serving endpoints (Public Preview)
Replaces JSON with serialized KServe v2 ModelInferRequest. Requires endpoints deployed after July 9, 2026.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Custom Docker images for AI Runtime CLI workloads (Beta)
Allows custom system library versions and complex dependencies, requires setup via Use custom Docker images.
- AI Runtime CLI (Beta)
Submits and manages distributed training workloads on serverless GPU compute from a local machine.
- 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) - Genie Code now supports auto-approve for tool actions
Approves tool actions without prompts, using an AI classifier to block risky ones.
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) - Serve custom LLMs with Custom Model Serving (Beta)
Supports multimodal models and PEFT recipes, unlike Foundation Model APIs.
- 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) - Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- AI Runtime 1xH100 accelerator (Beta)
Supports 1xH100 accelerator, see Hardware options for details.
- 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) - Sample Data Explorer is generally available
Lets you ask questions about Unity Catalog tables using natural language, returning SQL queries.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Workspace skills for Genie Code are now available
Workspace admins can create shared skills for machine learning pipelines and domain-specific processes.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - AI Runtime is now in Public Preview
Adds GPU support to serverless compute for deep learning workloads.
- Databricks Assistant is now Genie Code
Adds autonomous multi-step data tasks, replaces Databricks Assistant.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Endpoint telemetry for custom model serving endpoints (Beta)
Stores logs, traces, and metrics in Unity Catalog Delta tables using OpenTelemetry.
- Connect Databricks Assistant to MCP servers
Connects to external tools and data sources through MCP servers, requiring permission to use added servers.
- Partner-powered AI features are now supported in the Canada, Brazil, and United Kingdom Azure Geographies
Uses models hosted in the same Azure Geography as the workspace, requires cross-geo processing for some features.
- Create skills for Databricks Assistant
Extends Databricks Assistant with domain-specific tasks, following the open Agent Skills standard.
- Databricks Assistant Agent mode is now in Public Preview
Automates multiple steps from a single prompt, using Azure OpenAI or Anthropic.
- Flexible node types are now generally available
Falls back to alternative instance types when specified type is unavailable, improving launch reliability.
- Databricks Assistant Agent mode can now use models served through Anthropic on Databricks
Requires partner-powered AI features to be enabled. Uses endpoints hosted by Databricks.
- Notebook improvements
Cell execution minimap appears in right margin, supports up to 100MB notebooks.
- 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.
- Databricks Assistant integrated with compute
Creates compute resources, pools, and policies, and answers questions about them. Available on some compute pages.
- Databricks-hosted models for Assistant are now GA
Available on all cloud platforms at no extra cost.
- Databricks Assistant: User and workspace instructions now available
Custom instructions can be added by users or admins, applying to all Assistant experiences.
- Edit mode in Assistant does multi-cell code refactoring and more
Performs reasoning and editing across multiple cells without manual intervention.
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.