Databricks
Databricks blog and Terraform provider releases.
- Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.115.0: New fields for deployment and collaboration settings
Databricks SDK Java v0.115.0 introduces new fields for deployment mode and collaboration platform connectivity. These additions allow for finer control over deployment configurations and integration settings within Databricks environments, impacting developers and architects working with the Java SDK.
feature patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.140.0: Account discovery, workspace ID header change, API updates
Databricks SDK Go v0.140.0 introduces an option for account-level discovery, streamlining the user login flow. It also switches workspace API calls to use `X-Databricks-Workspace-Id` for improved addressing. Several new fields and methods have been added across job, pipeline, and token management services, affecting developers building integrations and managing Databricks resources programmatically.
feature patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.114.0: Workspace ID header change, new API fields
Databricks SDK Java v0.114.0 updates the workspace addressing header for workspace-scoped API calls and introduces new fields related to token management and job/pipeline deployments. These changes provide enhanced control and visibility for developers managing Databricks resources.
breaking feature patch - Databricks Python SDK Releases sdkdatabricksengineer ·
Databricks SDK for Python v0.113.0 Released
Databricks SDK for Python version 0.113.0 has been released. This update includes several enhancements and bug fixes, improving the developer experience for interacting with Databricks services programmatically. Engineers and data scientists using the SDK will benefit from a more stable and feature-rich toolset.
feature patch - Terraform Databricks Provider Releases terraforminfragcpdatabrickspreviewengineer ·
Databricks Terraform Provider v1.116.0: Git credential, Agent Bricks, and Metastore updates
Databricks Terraform Provider v1.116.0 adds the `principal_id` argument to manage Git credentials for service principals and supports permissions for Agent Bricks resources. It also includes bug fixes for metastore updates, UC object destruction, and library handling, alongside improvements to vector search index timeouts and child group collection.
feature patch - Databricks Go SDK Releases sdkmldatabricksengineer ·
Databricks SDK Go v0.139.0: Feature Engineering API & Pipeline Parameter Updates
This release of the Databricks SDK for Go introduces new methods for managing feature engineering streams and adds parameter fields to pipeline tasks. These updates enhance the SDK's capabilities for managing ML workflows and pipeline configurations, affecting engineers working with Databricks' machine learning and data pipeline services.
feature breaking - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Java v0.113.0 Adds Stream Management, Several Breaking Changes
Databricks SDK Java v0.113.0 introduces new methods for managing streaming jobs within the feature engineering service. It also adds parameter fields to pipeline and job-related objects. Two breaking changes are noted: the removal of `catalogId` from `CatalogCatalogStatus` and `syncedTableId` from `SyncedTableSyncedTableStatus`.
feature breaking - Databricks Go SDK Releases sdkdatabricksengineer ·
Databricks SDK Go v0.138.0 fixes config profile loading
The Databricks SDK Go v0.138.0 release updates the configuration file loader to correctly set the profile name to 'DEFAULT' when falling back to legacy configurations. This change ensures consistency for consumers who derive profile identifiers, preventing issues where a write operation under 'DEFAULT' might not be recognized by subsequent read operations.
patch - Databricks Python SDK Releases sdkdatabricksengineer ·
Databricks SDK for Python v0.112.0
Version 0.112.0 of the Databricks SDK for Python is now available. This release includes updates to improve stability and address reported issues, benefiting developers who interact with Databricks programmatically.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.137.0: AI agent header, SCIM optimization, new API fields
Databricks SDK Go v0.137.0 enhances AI agent detection in User-Agent headers and optimizes SCIM requests by excluding entitlements, preventing performance issues on large workspaces. The release also introduces new fields and methods across various services including Lakeview dashboards, apps, materialized features, and PostgreSQL sync.
feature patch - Databricks Java SDK Releases sdkdatabricksengineer ·
Databricks SDK Java v0.112.0 Release
Databricks SDK Java version 0.112.0 introduces several new methods and fields across various services, including Lakeview, Postgres, Dashboards, IAM, Jobs, and ML features. It also includes breaking changes to fields in the bundle and marketplace services, and a change to pagination for cluster events. These updates provide enhanced functionality and control for developers interacting with Databricks services.
feature breaking patch - Databricks Python SDK Releases sdkdatabricksengineer ·
Databricks SDK for Python v0.111.0
Databricks SDK for Python has released version 0.111.0. This update likely includes various improvements and bug fixes to enhance the developer experience when interacting with Databricks services. Engineers and architects using the SDK will benefit from a more stable and efficient integration.
patch - Databricks Go SDK Releases sdkinfradatabricksengineer ·
Databricks SDK Go v0.136.0: New features and breaking changes
Databricks SDK Go v0.136.0 introduces new methods for branch management and updates to IAM and job requests. Several breaking changes affect bundle operations, versioning, marketplace listings, and cluster event pagination. These updates require developers using the SDK to review and potentially adjust their code to maintain compatibility.
feature breaking - Databricks Java SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Java v0.111.0 adds bundle API, ML AuthConfig updates
Databricks SDK Java v0.111.0 introduces a new `com.databricks.sdk.service.bundle` package and a `workspaceClient.bundle()` service for managing Databricks bundles. Additionally, the `mtlsConfig` field is now available in `com.databricks.sdk.service.ml.AuthConfig`. These changes enhance bundle management capabilities and provide more configuration options for ML authentication.
feature patch - Databricks Go SDK Releases sdkdatadatabricksengineer ·
Databricks SDK Go v0.134.0: New Pipeline and Settings Fields
Databricks SDK Go v0.134.0 introduces new fields for pipeline refresh strategies and email customization in job settings. These additions provide developers with more granular control over pipeline operations and notification configurations, impacting engineers working with Databricks job orchestration.
feature patch - Databricks Python SDK Releases sdkdatabricksengineer ·
Databricks SDK for Python v0.110.0
Databricks SDK for Python version 0.110.0 introduces several new features and improvements, enhancing the developer experience for interacting with Databricks services. This update is relevant for Python developers and engineers who leverage the Databricks platform for data engineering and AI workloads, enabling more robust and efficient programmatic control.
feature patch - Databricks Go SDK Releases sdkmldatabricksengineer ·
Databricks SDK for Go v0.133.0 includes new IAM and Feature Engineering APIs
Databricks SDK for Go v0.133.0 introduces new methods for account and workspace-level IAM v2, expanding capabilities for managing workspace assignments. It also enhances Feature Engineering APIs with new fields for ML features and includes several other API additions and modifications. These changes provide developers with more granular control over IAM and feature management, though some updates may be breaking.
breaking feature patch - Databricks Python SDK Releases sdkdatabrickspreviewengineer ·
Databricks SDK for Python v0.109.0 Released
Databricks SDK for Python v0.109.0 introduces new features and improvements, enhancing programmatic interaction with Databricks platform services. This release aims to streamline workflows for developers and data engineers by offering more robust and efficient tools for managing Databricks resources and automating tasks. Developers and architects leveraging the Databricks platform for their data and AI initiatives will find these updates beneficial.
feature patch - Databricks Java SDK Releases sdkmldatabricksengineer ·
Databricks SDK Java v0.108.0: API updates and breaking changes
This release of the Databricks SDK for Java introduces several API changes, including new fields for Feature objects and requests, and new enum values for serving workloads. It also includes breaking changes such as modified method signatures and removed fields, requiring users to update their integrations. These updates are relevant for developers interacting with Databricks features like Feature Engineering and Model Serving.
breaking feature patch - Databricks Python SDK Releases sdkdatabricksengineer ·
Databricks SDK for Python v0.108.0
Version 0.108.0 of the Databricks SDK for Python has been released. This update includes a variety of enhancements and bug fixes across the SDK, improving usability and stability for developers interacting with Databricks services. Engineers and architects using the SDK will benefit from these refinements.
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