Databricks Releases
Databricks blog and Terraform provider releases. New features, breaking changes, security advisories and deprecations - each summarised in plain English and updated continuously.
Tracking 180 Databricks releases · Updated
- Terraform Databricks Provider Releases terraforminfradatabricksgadeprecationengineer ·
Databricks Terraform Provider v1.121.0: Breaking Changes and New AI Features
Databricks Terraform provider version 1.121.0 introduces breaking changes to the `databricks_mws_ncc_private_endpoint_rule` resource, tightening read-only attributes and improving provisioning state visibility. It also adds new resources for AI Search and enhancements to cluster configurations. These changes primarily affect users managing Databricks infrastructure with Terraform, particularly those using the `mws_ncc_private_endpoint_rule` resource or looking to integrate with Databricks AI Search capabilities.
breaking patch - Terraform Databricks Provider Releases terraforminfradatabricksdeprecationengineer ·
Databricks Terraform Provider v1.120.0: New Postgres API resource, SDKv2 deprecation
Databricks Terraform Provider v1.120.0 introduces a new resource for the PostgreSQL Data API and deprecates older SDKv2 fallback implementations for several resources and data sources. This change affects users managing Databricks resources with Terraform, particularly those relying on the older SDKv2 fallbacks, who should transition to the default Plugin Framework implementations to avoid issues in future releases. The release also includes bug fixes for permissions drift and application authorization.
patch - Databricks Java SDK Releases sdkaidatabricksdeprecationengineer ·
Databricks SDK Java v0.117.0: Enhanced AI agent detection and pagination
Databricks SDK Java version 0.117.0 enhances AI agent detection by recognizing the AI_AGENT environment variable, improving user agent reporting for recognized AI tools. It also introduces explicit factory methods for pagination strategies, deprecating the direct constructor. Bug fixes address issues with paginators silently dropping results on empty pages. These updates benefit developers using the SDK for interacting with Databricks AI features and data listing operations.
patch - Terraform Databricks Provider Releases terraforminfradatabricksdeprecationengineer ·
Databricks Terraform Provider v1.115.0: Bug Fixes and Deprecations
This release of the Databricks Terraform provider addresses several critical bugs affecting various resources when used with account-level configurations. Specifically, issues with decoding state, resolving workspace IDs, and handling OAuth configurations are resolved, ensuring greater stability for users managing Databricks resources via Terraform. Additionally, the provider deprecates the `provider_config` field for account-level settings, signaling a move towards more streamlined configuration management. These fixes benefit users managing complex Databricks environments, particularly those leveraging account-level configurations or migrating to newer provider versions.
patch - Databricks Go SDK Releases sdkgovernancedatabricksdeprecation ·
Databricks SDK Go v0.129.0: New Services, API Additions, and Breaking Changes
Databricks SDK Go version 0.129.0 introduces new workspace-level services for supervisor agents and secrets, alongside numerous API additions across various modules. This release also includes several breaking changes, primarily affecting method paths for updating configurations related to data classification, environments, knowledge assistants, Postgres resources, and SQL warehouses. These updates impact developers using the Go SDK to interact with Databricks platform features.
breaking patch - Databricks Java SDK Releases sdkinfraazuredatabricksdeprecationengineer ·
Databricks SDK Java v0.104.0: New Auth, AI Agent Support, API Updates
Databricks SDK Java v0.104.0 introduces Azure Managed Service Identity (MSI) authentication and automatic detection of AI coding agents in user-agent strings. It enhances error handling for non-JSON responses and fixes token scope mismatches for Databricks CLI authentication. The release also includes numerous API additions and two breaking changes affecting the `com.databricks.sdk.service.postgres.SyncedTableSyncedTableSpec` and `com.databricks.sdk.service.settings.CustomerFacingIngressNetworkPolicyRequestDestination` configurations.
breaking patch - Databricks Go SDK Releases sdkazuregcpdatabricksgadeprecationengineer ·
Databricks SDK for Go v0.127.0 Release
Databricks SDK for Go v0.127.0 introduces several new features, including host metadata customization and lazy iteration with limits. It also contains numerous bug fixes, particularly around token acquisition and caching for various credential providers. Breaking changes include raising the minimum Go version and removing a field from the Postgres SyncedTableSpec. These updates affect developers using the Go SDK for interacting with Databricks services.
breaking patch
About Databricks release tracking on ReleaseBytes
Databricks platform releases, runtime versions and Terraform provider updates each have their own changelog. ReleaseBytes merges them into one feed with plain-English summaries, and its EOL tracker follows Databricks runtime support windows — including the Python and Spark versions each runtime pins.
Frequently asked questions
How often are Databricks release notes updated on ReleaseBytes? ›
Continuously. ReleaseBytes monitors the official Databricks release channels around the clock and publishes a plain-English summary of each announcement shortly after it lands.
What kinds of Databricks changes does ReleaseBytes track? ›
New features, enhancements, bug fixes, security advisories, breaking changes, deprecations and end-of-life announcements. Every item is tagged by type so you can filter to just the changes that need action.
How can I get alerts for new Databricks releases? ›
Set up a free email or Slack alert filtered to Databricks, subscribe to the weekly digest, or follow the RSS feed. Teams can also install the ReleaseBytes GitHub App or connect via MCP.
Where does the Databricks release data come from? ›
From the official sources: Databricks blog and Terraform provider releases. Every item links back to the original vendor announcement.