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 blogdataaigovernancearchitecthealthcare ·
Building an AI-Forward Healthcare Organization on Data and Governance
This article outlines the key blockers and enablers for healthcare organizations aiming to become AI-forward. It argues that building a solid foundation of unified data, robust governance, and a clear operating model is crucial for successfully building, trusting, and scaling AI initiatives. The piece highlights that modern platforms can now enable governed use cases to go live in weeks, not months, allowing healthcare providers to overcome common challenges and adopt AI more effectively.
announcement - Databricks Blog bloggovernancedatabricksengineerfinancegovernment ·
Databricks enables real-time fraud prevention for government benefits
Databricks is enhancing fraud prevention for government benefit programs by leveraging its data and AI platform. This approach aims to shift from a reactive 'pay and chase' model to real-time detection, significantly reducing billions lost annually to fraud. The platform facilitates cross-agency data sharing and sophisticated AI-driven risk scoring for entities like federal departments that already utilize Databricks.
feature announcement - Databricks Blog bloggovernancecompliancedatabricksengineer ·
EU Digital Product Passport: Databricks Solution for Traceability Deadline
Manufacturers selling into the EU must comply with the Digital Product Passport regulation by February 2027, a deadline that mandates product traceability and sustainability data. This regulation poses significant data challenges, particularly concerning data availability, quality, and integration across complex supply chains. Databricks offers a Solution Accelerator on its platform to address these issues, providing a unified data foundation for compliance, resilience, and sustainability reporting.
announcement - Databricks Blog blogaigovernancedatabricksengineer ·
Databricks Unity AI Gateway adds spend controls and budget alerts
Databricks' Unity AI Gateway now offers AI spend controls, allowing users to set budgets and hard caps at various granularities including user, workspace, and organization levels. This feature addresses the challenge of managing unpredictable AI workload costs by providing proactive budget alerts and automated spending limits. The controls are integrated with Unity Catalog and Databricks budgets, offering unified governance for AI usage, cost visibility, and operational accountability across all models and providers, and are available starting today.
feature - Databricks Blog bloggovernancedatabricksengineerhealthcare ·
FDA Builds Widely Adopted Generative AI Platform on Databricks
The US Food and Drug Administration (FDA) successfully launched a generative AI platform, ELSA, built on Databricks Halo, achieving 85% staff adoption within two months. This initiative consolidated data silos across eight agency centers, enabling faster regulatory research and custom AI agent development for 16,000 staff. The platform utilizes Databricks Unity Catalog for governance and is now expediting critical tasks like drug application reviews, reducing them from days to minutes.
feature announcement - Databricks Go SDK Releases sdkgovernancedatabricksengineer ·
Databricks SDK for Go v0.162.0 Adds IAM and Jobs Fields
The Databricks SDK for Go version 0.162.0 introduces new fields to enhance IAM and job cluster configurations. It adds `EffectiveEntitlements` for `WorkspaceAssignmentDetail` and `ServerlessComputeId` for `JobCluster`, providing more granular control and visibility into workspace assignments and serverless compute options. These updates are relevant for Go developers integrating with Databricks APIs, offering expanded capabilities for managing entitlements and configuring serverless job clusters.
patch - Databricks Blog blogdatagovernancedatabricksengineer ·
Dow Builds Carbon Footprint Ledger on Databricks for Sustainability
Dow has implemented a Carbon Footprint Ledger (CFL) on the Databricks Data Intelligence Platform to calculate cradle-to-gate Product Carbon Footprints (PCFs) for its entire product portfolio. This initiative significantly reduces processing time from weeks to a fraction of that by leveraging Apache Spark, Delta Lake, Unity Catalog, and MLflow, enabling faster optimization and verifiable certification of low-carbon products. The system is designed for third-party assurance against ISO 14067 and the GHG Protocol Product Standard, benefiting both Dow's sustainability goals and its customers' Scope 3 emission reduction efforts.
announcement feature - Databricks Blog blogaigovernancedatabricksengineer ·
Databricks Blog Post: Navigating AI Compliance
This Databricks blog post explains the necessity of AI compliance, covering frameworks like the EU AI Act and NIST AI RMF, and outlines how organizations can manage risks and implement controls across the AI lifecycle. It emphasizes the importance of continuous monitoring, bias testing, and data governance to ensure AI systems operate within legal and ethical boundaries, especially as regulations like the EU AI Act impose significant penalties for non-compliance. The guide is intended for compliance teams, data science leads, and business owners involved in deploying AI systems at scale.
announcement - Databricks Blog blogaigovernancedatabricksengineer ·
Responsible AI Guide: Governance, Principles, and Practical Application
Databricks has released a comprehensive guide on Responsible AI, covering its definition, core principles, and practical implementation across the AI lifecycle. This guide emphasizes the shift of Responsible AI from a compliance footnote to a core governance discipline, driven by increasing regulatory pressure and generative AI adoption. It is essential for data scientists, AI governance teams, and business leaders to manage risks, build trust, and ensure ethical AI development. The guide details technical best practices, governance structures, and regulatory considerations, including the EU AI Act.
announcement - Databricks Blog blogaigovernancedatabricksengineer ·
AI Transparency: Governance, Explainability, and Data Practices in AI Systems
This article outlines the importance of AI transparency in building trustworthy and compliant AI systems, emphasizing governance, explainability, and robust data practices. It highlights how transparency, distinct from explainability and interpretability, is crucial for decision-making, trust, and meeting regulatory demands like the EU AI Act. The piece details necessary documentation artifacts, architectural considerations for explainability, and the practical integration of these concepts for effective AI deployment.
announcement - Databricks Blog blogaigovernancedatabricksengineer ·
Databricks Unity AI Gateway adds Model Provider Services
Databricks introduced Model Provider Services (MPS) in Unity AI Gateway, allowing organizations to securely access and govern external AI models like Meta's Muse Spark 1.1. This feature centralizes API key management, enforces access controls via Unity Catalog, and provides end-to-end observability for usage and spend. MPS aims to simplify the adoption of new AI models by consolidating governance and security across different providers.
feature announcement - Databricks Blog blogaigovernancedatabricksengineer ·
Databricks: Data-Native AI Agents Offer Integrated Governance and Security
Databricks advocates for running AI agents within their Data Intelligence Platform instead of separate stacks to avoid issues like fragmented governance, high egress costs, and latency. Data-native agents embed governance directly into computation, enforced at query planning time, unlike post-hoc controls that fail when agents compute over data. This integrated approach on Databricks, using features like Unity Catalog and AI Gateway, enables faster, more secure deployment of enterprise AI applications by keeping data, governance, and policies together.
feature announcement - Databricks Blog blogaigovernancedatabricksengineer ·
Omnigent Adds Contextual Policies for Enhanced AI Agent Governance
Omnigent, an open-source meta-harness for AI agents, now features contextual policies that leverage session state to enhance governance. These policies allow for more nuanced control over agent actions, improving security and cost management by considering the agent's history within a session. This capability is available for various coding and custom agents wrapped by Omnigent, providing richer policy options than traditional static controls.
feature - 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
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.
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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.