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
- Databricks Blog blogawsdatabricksengineer ·
Databricks Simplifies S3 Data Connection with Delegated IAM Permissions
Databricks has introduced a streamlined, automated flow for connecting Amazon S3 buckets to Unity Catalog, reducing manual configuration from days to minutes. This new method uses AWS IAM temporary delegation, eliminating the need for complex IAM policies and CloudFormation templates, and directly benefiting users by simplifying a foundational step for data ingestion, pipelines, and analytics. The process is now a few clicks within the Databricks workspace, automatically provisioning necessary storage credentials and external locations with least-privilege permissions. Users lacking sufficient AWS access can request it from their administrator directly within the flow, and the authorization automatically expires after provisioning, enhancing security.
feature - Databricks Java SDK Releases sdkinfraawsazuregcpdatabricksengineer ·
Databricks SDK Java v0.105.0: AI agent detection, breaking changes, new APIs
Databricks SDK Java v0.105.0 introduces automatic detection of AI coding agents in HTTP request headers, enhancing environment identification. It also includes breaking changes by removing the experimental unified host flag and several API method path updates. Several new APIs and fields have been added across services like secrets, supervisor agents, and postgres, with bug fixes for SPOG host compatibility.
breaking patch - Terraform Databricks Provider Releases terraforminfraawsazuregcpdatabricksengineer ·
Databricks Terraform Provider v1.113.0: New PostgreSQL resources, explicit cloud config
Version 1.113.0 of the Databricks Terraform provider introduces new resources for managing PostgreSQL catalogs and synced tables, alongside Databricks environments. It enhances configuration by allowing explicit cloud provider specification and control over account-level versus workspace-level API usage for dual resources. These updates benefit engineers and architects managing Databricks infrastructure via Terraform by improving flexibility and resolving import inconsistencies.
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.