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 63 Databricks releases · Updated
- Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.140.0: Enhanced Workspace Addressing and API Features
Databricks SDK for Go version 0.140.0 introduces an improved workspace addressing mechanism using `X-Databricks-Workspace-Id` for API calls, enhancing the unification initiative. It also adds several new API fields and methods, including `UpdateTokenManagement` and fields for job and pipeline deployments, benefiting developers working with Databricks workspaces and configurations.
patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.113.0
Databricks SDK for Python v0.113.0 introduces internal workspace addressing changes and adds new API methods for feature engineering and token management. It also introduces several new fields related to job deployments, pipeline tasks, and token settings, while removing two fields from the postgres service. These changes affect developers interacting with Databricks services programmatically, with some breaking changes requiring attention.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Go v0.139.0: Feature Engineering API and breaking changes
Databricks SDK for Go version 0.139.0 introduces new methods for managing Feature Engineering streams and adds parameters to job and pipeline configurations. This release also includes breaking changes with the removal of `CatalogId` and `SyncedTableId` fields from PostgreSQL catalog status types, which may require users to update their integrations. The update is relevant for Go developers working with the Databricks platform.
patch - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Java v0.113.0 adds feature engineering APIs, includes breaking changes
Databricks SDK for Java version 0.113.0 introduces new methods for managing streaming objects within the feature engineering service. It also adds several new fields to existing Job and Pipeline task configurations. However, this release includes breaking changes, removing the `catalogId` and `syncedTableId` fields from specific Postgres-related status objects, which may require consumers to update their code.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.138.0 addresses config profile loading
Databricks SDK Go v0.138.0 fixes an issue where the configuration file loader would not set the profile name when using the legacy fallback. This change ensures consumers can correctly derive a per-profile identifier, preventing issues where writes under the 'DEFAULT' profile could not be found by subsequent reads. This fix is relevant for users of the Databricks CLI and any applications deriving profile identifiers from the SDK's configuration.
patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python: Ruff Integration and Formatting Updates
The Databricks SDK for Python has integrated Ruff for formatting and linting, replacing Black, isort, and autoflake. This change aligns the SDK's formatting with Databricks' internal guidelines and prepares for a unified internal repository. While the underlying code formatting logic is updated, there are no behavioral changes for users of the published SDK.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.137.0: Agent detection, SCIM optimization, API additions
Databricks SDK Go v0.137.0 improves AI agent detection in User-Agent headers and optimizes SCIM requests by excluding entitlements for faster workspace ID retrieval. This update also introduces new API fields for dashboards, apps, materialized features, and synced tables, benefiting developers working with Databricks services. These changes are now available in the latest SDK release.
patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Java v0.112.0: API additions and breaking changes
Databricks SDK for Java version 0.112.0 introduces several new methods and fields across various services, including workspace, IAM, jobs, and ML. Notably, it includes breaking changes related to required fields in bundle operations, tag types for marketplace listings, and pagination for cluster events. These updates primarily affect developers building applications and integrations with Databricks using the Java SDK.
patch - Databricks Python SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Python v0.111.0: Bundle package, Lakeview revert, Postgres undelete
Databricks SDK for Python version 0.111.0 introduces a new bundle package and workspace-level services for Lakeview and Postgres, alongside several field additions across various modules. These changes primarily affect developers using the Python SDK for interacting with Databricks services. Notably, two breaking changes are included regarding tag handling for marketplace listings and pagination for cluster events.
breaking patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.136.0: New features and breaking changes
Databricks SDK Go v0.136.0 introduces several new API methods and fields, enhancing functionality for Postgres workspace services and job management. It also includes breaking changes to the bundle operations and marketplace listing requests, requiring users to update their code for compatibility. This release primarily impacts developers using the Go SDK to interact with Databricks services.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.135.0 Adds Bundle Package and TLS Config
The Databricks SDK for Go version 0.135.0 introduces a new bundle package and a workspace-level bundle API, enhancing deployment capabilities. It also adds an MtlsConfig field to the ML AuthConfig, improving secure authentication for machine learning workloads. These updates are primarily relevant to Go developers utilizing the Databricks SDK for infrastructure and ML operations.
patch - Databricks Java SDK Releases sdkinfradatabricksengineer ·
Databricks SDK for Java v0.111.0
Databricks SDK for Java has released version 0.111.0, introducing a new package for bundle operations and a corresponding client service. Additionally, it includes an update to the ML AuthConfig with a new mtlsConfig field. These changes are primarily relevant for developers working with Databricks bundles and ML authentication within their Java applications.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.134.0 adds new job and settings fields
The Databricks SDK for Go has been updated to version 0.134.0, introducing new fields for managing pipeline refresh and operational email settings. These additions provide more granular control over job refresh behaviors and custom email recipient configurations within Databricks. The update is primarily relevant for Go developers interacting with Databricks jobs and settings via the SDK.
patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.110.0 adds pipeline and settings fields
Databricks SDK Java version 0.110.0 introduces new fields for pipeline parameters and tasks, enabling more granular control over full refreshes, flow refreshes, and checkpoint selections. It also adds custom recipient options for operational emails within settings. These changes primarily affect developers integrating with Databricks Jobs and Settings APIs using the Java SDK.
patch - Databricks Python SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Python adds job pipeline refresh fields
Databricks SDK for Python version 0.110.0 introduces new fields for managing pipeline refresh behavior within job configurations. This enhancement provides more granular control over how data pipelines are refreshed, affecting users who develop and manage automated data workflows on Databricks. The update is available now as part of the SDK release.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.133.0 Introduces New IAM and Feature APIs
Databricks SDK Go version 0.133.0 adds significant new functionality for managing IAM assignments at both account and workspace levels, alongside enhancements for feature engineering and job task configurations. These updates benefit developers and architects working with Databricks for ML and data engineering, introducing new APIs and fields to support more complex use cases. Notably, several breaking changes are included, requiring developers to update their code when integrating these new features.
patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.109.0 adds new methods and fields
Databricks SDK Java v0.109.0 introduces new methods for managing workspace assignments and adds several new fields across various services. These updates enhance programmatic control over account and workspace configurations, including disaster recovery, job submissions, and network policies. The release affects developers using the Java SDK to interact with Databricks services.
patch - Databricks Python SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Python v0.109.0: New IAM, ML, and Serving features
Databricks SDK for Python version 0.109.0 introduces new methods for managing workspace assignments and several new fields across IAM, ML, and serving functionalities. Notably, it includes breaking changes to the `ListFeaturesRequest` and `list_features` method, impacting how features are requested and listed. This release is primarily for Python developers working with the Databricks platform, particularly those involved in account and workspace management, feature engineering, and model serving.
breaking patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK for Java v0.108.0 includes breaking API changes
Databricks SDK for Java version 0.108.0 introduces several breaking changes, including modifications to Feature API fields and method signatures, and the removal of a resource name field. These changes primarily impact Java developers using the Databricks SDK for feature engineering and serving, requiring code updates for compatibility. New enum values for GPU workload types have also been added, alongside other feature enhancements.
patch - Databricks Python SDK Releases sdkdatadatabricksengineer ·
Databricks SDK for Python v0.108.0 Updates
Databricks SDK for Python v0.108.0 introduces new fields for job task configuration and adds new connection types for catalog integrations. It also includes a breaking change by removing an unspecified resource name field. This release impacts developers building and managing Databricks workloads using the Python SDK.
breaking patch