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.
- 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.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Target an Azure capacity reservation group for classic compute
Requires VNet injection, guarantees compute capacity for constrained VM types.
- 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) - MLflow trace storage in Unity Catalog is now generally available
Stores traces in OpenTelemetry format with unlimited storage and SQL query access.
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) - Get this table by email. One Monday mail covering the week, filtered to the clouds and products you run. Weekly digest
- Serve custom LLMs with Custom Model Serving (Beta)
Supports multimodal models and PEFT recipes, unlike Foundation Model APIs.
- Customer-managed keys now support MLflow managed evaluation features
Supports MLflow 3 scorers and requires non-CMK encrypted catalog.
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) - 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.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 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.
- Serverless compute is enabled by default
Eligible Google Cloud workspaces are affected, account admins no longer need to manually enable it.
- 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) - 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.
- 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.
- Store and query MLflow traces in Unity Catalog (Beta)
Stores MLflow traces in Delta tables for long-term retention and analysis using OpenTelemetry format.
- 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.
- Configure compute to use AWS Capacity Blocks
Replaces on-demand instances, requires AWS account setup.
- The Data Science Agent can now also use models served through Anthropic on Databricks
Uses models served through Anthropic when partner-powered AI features are enabled. Requires partner-powered AI features to be enabled.
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.