Databricks SDK

This release adds new fields and methods across various Databricks services, including support for visualization downloads, enhanced job scheduling with SQL conditions, and new PostgreSQL service configurations. A breaking change removes the 'name' field from the IAMv2 User object.

The `ssh connect` command now supports a `--base-environment` flag for custom serverless session environments. Bundles received fixes for persistent drift in model serving endpoints and spurious updates with `apply_policy_default_values` on job tasks.

Query parameters specified in `ForceSendFields` with zero values are now sent, which is a breaking change if you relied on them being omitted. New API fields and methods were added across disaster recovery, dashboards, Postgres, and serving endpoints.

* Add `Spec` field for [environments.WorkspaceBaseEnvironment](https://pkg.go.dev/github.com/databricks/databricks-sdk-go/service/environments#WorkspaceBaseEnvironment).

This release adds a new method to cancel pending cluster policy enforcement and introduces several new fields related to AI runtime tasks in jobs. A breaking change makes the `replicate_workspace_assets` field optional for disaster recovery workspace sets.

The `workspace export-dir` command now sanitizes invalid filenames instead of aborting, and `ssh connect` defaults to a bash login shell in the user's workspace home. Bundle deployments now correctly resolve registered model IDs and fix issues with `postgres_role` recreation and spurious cluster recreates.

This release fixes an issue where repeated user agent injections could cause the User-Agent header to grow indefinitely. It also introduces new API methods and fields for managing cluster policy compliance and makes a breaking change by making the `ReplicateWorkspaceAssets` field optional in `disasterrecovery.WorkspaceSet`.

This release adds a `BundleRootPath` field to `bundledeployments.WorkspaceInfo`. It also introduces an `AiRuntimeTask` field across several `jobs` service objects, including `ResolvedValues`, `RunOutput`, `RunTask`, `SubmitTask`, and `Task`.

The Databricks SDK for Go now includes an Xlarge compute size option for apps. It also adds a `meta-harness` user-agent dimension for better tracking of omnigent meta-harness usage.

This release adds new methods for managing PostgreSQL data APIs at the workspace level. It also introduces `serverless_compute_id` fields for various Delta Live Tables pipeline operations and `endpoint_id` for Vector Search indexes.

Databricks SDK for Java now supports specifying a serverless compute ID when cloning, creating, or editing Delta Live Tables pipelines. This enables users to manage DLT pipelines with serverless compute directly through the SDK.

The Databricks SDK for Go now includes a `ServerlessComputeId` field across several pipeline-related operations. This allows specifying serverless compute for cloning, creating, and editing Databricks pipelines.

The Databricks SDK for Java now supports CRUD operations for Postgres data APIs and includes new fields for Azure compute attributes, synced table specifications, and vector search indexes. A breaking change makes the `resourceId` field optional for bundle deployment operations.

This release adds new methods for managing Postgres data APIs at the workspace level. Compute clusters can now specify an Azure Capacity Reservation Group in their attributes.

This release fixes an issue where tag policy and assignment operations failed with 404 errors when tag keys contained forward slashes. It also introduces a breaking change by making the `ResourceId` field optional in `bundledeployments.Operation`.

The Databricks SDK for Go now includes a TypeOverrides field for database.SyncedTableSpec and postgres.SyncedTableSyncedTableSpec. This allows practitioners to specify type overrides when defining synced tables.

1.12.1

This release exposes Databricks Jobs IDs in dbt's adapter response for better run correlation and adds support for Databricks SPOG vanity URLs. It also fixes issues with streaming tables, materialized views, column-level constraints, and managed Iceberg incremental models.

This release adds an AcceleratedSync field to SyncedTableSpec for both generic database and PostgreSQL services. This new field enables configuring accelerated synchronization for synced tables.

This release introduces new services for AI Search and Bundle Deployments, along with numerous new fields across existing services like Catalog, ML, and Vector Search. The `bundle` package and its associated workspace service have been removed.

This release introduces new services for AI Search and Bundle Deployments, along with several new fields across existing services like Catalog, ML, and Pipelines. A breaking change removes the old Bundle package and its associated workspace-level service.

The SDK now explicitly supports token and offset pagination with new factory methods, deprecating the old Paginator constructor. A bug was fixed where token-paginated list methods would prematurely stop if an empty page with a next token was encountered.

The experimental open command now supports opening a wider range of Databricks resource types directly in the workspace. Databricks Bundles gain a new --select flag for partial deployments, improved retry logic for transient HTTP errors, and support for Terraform references.

The Databricks SDK for Java now correctly handles OAuth token exchanges for browser-authenticated users by making the client ID optional in `DatabricksOAuthTokenSource`. This fixes a `NullPointerException` when no client ID is present, allowing account-wide token federation.

Databricks Asset Bundles now support a DeploymentMode field for both Deployment and Version objects. Workspace settings include new fields for CollaborationPlatformConnectivity and EffectiveCollaborationPlatformConnectivity.

The SDK now allows specifying an account target for the discovery flow, directing users to the account selector. New fields were added for job and pipeline deployments, token management, and bundle operations, alongside a new `UpdateTokenManagement` method.

Workspace-scoped API calls now use `X-Databricks-Workspace-Id` instead of `X-Databricks-Org-Id`, accepting classic numeric or other workspace ID formats. New fields and methods were added across various services, including token management, job and pipeline deployments, and token information.

This release adds comprehensive CRUD operations for feature engineering streams and a method to update token management settings. It also introduces breaking changes by removing `catalog_id` and `synced_table_id` fields from specific Postgres service objects.

This release adds new methods for managing feature engineering streams and introduces a `Parameters` field for various jobs and pipelines API calls. It also includes breaking changes by removing `CatalogId` and `SyncedTableId` fields from specific PostgreSQL service statuses.

Bundle users now receive a suggestion to set `bundle.engine: direct` in `databricks.yml` when using direct-only resources with the Terraform engine. Vector search indexes are now supported as a bundle resource (direct engine only), including UC grants and destructive operation confirmations.

The SDK now supports more granular AI agent detection in User-Agent headers and passes unrecognized values as-is. Several API changes introduce new fields for dashboards, apps, ML materialized features, and synced table statuses, along with a `Revert` method for Lakeview dashboards.

This release introduces a new Databricks Asset Bundles service and adds `revert()` to Lakeview dashboards and `undelete_branch()` to Postgres. It also includes breaking changes to the `tags` field in Marketplace listings and pagination for Cluster events.

This release introduces new fields for IAM user information, job trigger state, and enhanced branch management capabilities including undelete and purge options. It also includes several breaking changes, making fields like `ActionType`, `ResourceId`, and `CliVersion` required, and altering pagination for cluster events.

This release introduces a new bundle package and workspace-level service for managing Databricks Asset Bundles. It also adds an MtlsConfig field to ml.AuthConfig for mTLS authentication configurations.

Databricks SDK for Go now supports new fields for configuring pipeline refresh selections within jobs. Additionally, new fields for operational email custom recipients are available in settings.

* Add `CreateWorkspaceAssignmentDetail`, `DeleteWorkspaceAssignmentDetail`, `GetWorkspaceAssignmentDetail`, `ListWorkspaceAssignmentDetails` and `UpdateWorkspaceAssignmentDetail` methods for [a.AccountIamV2](https://pkg.go.dev/github.com/databricks/databricks-sdk-go/service/iamv2#AccountIamV2API) account-level service.

This release introduces new methods for managing IAMv2 workspace assignments at both account and workspace levels, along with new fields for ML features, disaster recovery stable URLs, and customer-facing ingress network policies. It also includes breaking changes to the `list_features()` method and `ListFeaturesRequest` by adding new required catalog and schema name fields.

The `vector_search_endpoints` configuration and commands now use `target_qps` instead of `min_qps`, requiring updates to `databricks.yml` and CLI invocations. Authentication commands received several usability improvements, including better keyring handling, clearer profile selection, and improved reporting of token storage locations.

This release introduces new methods for managing supervisor agents and vector search endpoints, along with several new fields for connector options, ingestion sources, and customer-managed keys. Breaking changes include the removal of `min_qps` fields from vector search endpoint configurations and making `guidelines` and `description` fields optional in certain services.

* Add `ConfluenceOptions` field for [pipelines.ConnectorOptions](https://pkg.go.dev/github.com/databricks/databricks-sdk-go/service/pipelines#ConnectorOptions).

* Fixed Databricks CLI `--profile` fallback by detecting the CLI version at init time. The previous error-based detection was broken because `--profile` is a global Cobra flag silently accepted by old CLIs.

This release introduces a new disaster recovery package and adds methods for managing knowledge assistant examples. It also includes breaking changes related to the `supervisoragents.Connection` and `supervisoragents.Tool` fields.

Unified host detection is now automatic, removing the `Experimental_IsUnifiedHost` field and enabling a single configuration profile for both account and workspace operations. The file-based OAuth token cache has been removed, defaulting to an in-memory cache unless a persistent cache is explicitly provided.

The SDK now automatically detects AI coding agents and appends agent information to HTTP request headers, while also removing the unused `experimentalIsUnifiedHost` field from `DatabricksConfig`. A bug fix addresses `X-Databricks-Org-Id` header issues for `SharesExtImpl.list()` on SPOG hosts, and several API method paths have changed, which are breaking changes.

This release introduces new workspace-level services for secrets_uc and supervisor_agents, along with an update method for tokens. Several breaking changes occurred, primarily due to method path changes for data classification, environments, knowledge assistants, postgres, and warehouses services.

The CLI now supports a --limit flag for paginated list commands and caches host metadata lookups for faster repeated invocations. Bundles gain support for Vector Search Endpoints and prompt before destroying Lakebase resources.

This release introduces new workspace-level services for supervisor agents and Unity Catalog secrets, along with an update method for tokens. Several existing API methods for data classification, environments, knowledge assistants, Postgres, and warehouses have breaking changes due to path modifications.

This release automatically detects unified hosts for account and workspace operations, and accepts DATABRICKS_OIDC_TOKEN_FILEPATH for OIDC token files. Python 3.8 and 3.9 are no longer supported, requiring Python 3.10 or newer.

This release raises the minimum Go version to 1.24 and introduces new features like a host metadata resolver hook and a lazy iteration utility with item limits. It also includes numerous bug fixes for token acquisition and caching, along with extensive API additions for various Databricks services.

The SDK now automatically detects AI coding agents and appends `agent/<name>` to HTTP request headers. Two new `DisableGovTagCreation` fields were added to `RestrictWorkspaceAdminsMessage` in both `settings` and `settingsv2`.

OAuth token refreshing is now proactive for tokens expiring within five minutes, improving token validity for callers. The `dashboards.GenieSpace` struct gains a new `ParentPath` field.

This release introduces a new `environments` service for managing Databricks environments and adds a `parent_path` field to `GenieSpace` dashboards. It also includes a new `can_create_app` permission level for IAM.

The Databricks SDK for Go now supports specifying a `default_profile` within the `[__settings__]` section of your `.databrickscfg` file. This allows for easier configuration management when working with multiple profiles.

Release: v2.10.6 (#1858)

This release fixes an issue where the VS Code extension would not correctly handle 404 errors from the Databricks SDK. This improves stability when interacting with Databricks resources that might not exist.

This release adds new fields for job alert configurations across various job-related structs, including `RunOutput`, `RunTask`, `SubmitTask`, and `Task`. It also introduces a new `environments` package and service for managing workspace environments, alongside a `CanCreateApp` permission level for IAM.

This release adds new fields and methods across several services, including updates for ML features, pipelines, and Postgres roles. It also introduces breaking changes by making previously required fields optional in ML-related DeltaTableSource, Feature, Function, and KafkaSource configurations.

Databricks SDK for Python now supports new fields for defining ingestion pipelines, including connector type, data staging options, and detailed ingestion source information. External function requests in model serving can now specify a sub-domain.

This release introduces new methods for the Genie workspace service and an update_role method for the Postgres service. Several fields across ML and other services are now optional, including breaking changes for `entity_columns`, `inputs`, `function_type`, `entity_column_identifiers`, and `timeseries_column_identifier` in various ML-related services.

Databricks SDK for Java now allows fine-grained control over HTTP request timeouts through a new `withRequestConfig` method on `CommonsHttpClient.Builder`. This enables practitioners to configure specific timeout settings for their API calls.

Databricks CLI authentication now correctly errors on token scope mismatches, prompting re-authentication instead of silently using incorrect permissions. New `dataclassification` and `knowledgeassistants` services and corresponding workspace-level APIs have been added.