Databricks CLI
Recent items mentioning Databricks CLI across the Databricks ecosystem — releases, news, videos, and community Q&A. Updated hourly.
The Databricks CLI has recently reached general availability 4 and version 1.0 5, indicating a maturing tool for Databricks practitioners. It now supports managing Lakebase branches for AI-driven development 1 and has seen fixes for profile identification, particularly for OAuth cache keys 2, and --profile fallback issues 9.
Generated daily from the 9 most recent items mentioning Databricks CLI. Click any [N] to jump to the source.
Release: v2.11.0 (#1902)
This release introduces a Unity Catalog explorer and a workspace filesystem explorer, enhancing navigation and management within Databricks. It also adds support for SPOG host URLs.
TutorialsSafe AI-Driven Development with Lakebase Branches
Databricks Lakebase branches enable instant, cost-efficient database branching using copy-on-write, allowing developers to test features in isolated environments without affecting production data. The video demonstrates creating and managing these branches via the Lakebase console and Databricks CLI, and shows how to integrate them into an agentic development workflow for safe AI-driven development.
The config-file loader now correctly sets the profile name to "DEFAULT" when using the legacy fallback, ensuring consistent profile identification for consumers. This fixes issues where per-profile identifiers, like OAuth cache keys, might not match between login and read flows.
NewsTerraform AWS Databricks Deployment Guide!
The video demonstrates how to deploy an AWS Databricks workspace using a provided Terraform script. It covers prerequisites, AWS and Databricks authentication, variable configuration, and executing the Terraform commands to create the workspace.
OAuth tokens for interactive logins are now stored in OS-native secure stores by default, requiring re-authentication after upgrading. A new `databricks aitools` command group is introduced for installing Databricks skills into coding agents.
This release fixes an issue where the Databricks CLI `--profile` fallback was broken. It also introduces new API methods for `workspaceClient.supervisorAgents()` and `workspaceClient.vectorSearchEndpoints()`, along with several breaking changes related to `Example` and `Tool` fields, and `minQps` in Vector Search endpoints.
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.
Release: v2.10.7 (#1895)
This release adds initial remote development compatibility and renames "Databricks Asset Bundles" to "Declarative Automation Bundles." It also fixes issues with profile management and sign-in, and updates the Databricks CLI.
* 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.
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.
This release adds Azure MSI authentication support and improves `.databrickscfg` default profile resolution. It also fixes issues with non-JSON error responses and Databricks CLI token scope mismatches, alongside several API additions and two breaking changes.
Databricks CLI v0.297.2 fixes a critical "key expired" error that prevented `databricks bundle deploy` from downloading Terraform. This was resolved by using a hardcoded ArmoredPublicKey for Terraform binary installations.
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.
Release: v2.10.5 (#1834)
- Update Databricks CLI to v0.286.0
NewsDatabricks Breaking News: Week 2026 02: 5 January 2026 to 11 January 2026 #databricks news
Databricks now allows changing catalog and schema during dashboard deployments, addressing a previous issue with environment-specific configurations. The Databricks CLI has a breaking change with plan version 2, altering the structure of deployment plans.
Release: v2.10.4 (#1821)
- Update Databricks CLI to v0.280.0
Release: v2.10.3 (#1772)
This release updates the Databricks CLI to v0.266.0, which includes breaking changes. Databricks practitioners should review the CLI release notes for details on these changes.
Tutorials51 Setup Azure DevOps Pipeline with Databricks Asset Bundles (DABs) | Complete CICD Process
The video demonstrates how to set up an Azure DevOps pipeline to deploy Databricks Asset Bundles (DABs) to higher environments like QA. It covers configuring service principal permissions, setting up Azure pipeline variables for environment-specific details, and writing the YAML pipeline code to validate and deploy Databricks assets.
Tutorials50 Databricks Asset Bundles | Configure Production grade DABs | CICD using DABs (IAC)
The video demonstrates how to configure and deploy Databricks Asset Bundles (DABs) for managing Databricks assets like notebooks, jobs, and pipelines across different environments. It covers creating a structured DAB project, defining resources and targets in YAML, and deploying using both the Databricks UI and CLI, including setting up environment-specific configurations and variables.
Tutorials49 Databricks CLI | Install and Authenticate Databricks CLI | U2M and M2M Authentication
The video demonstrates how to install the Databricks CLI on Windows and authenticate it using both User-to-Machine (U2M) and Machine-to-Machine (M2M) methods. It then shows how to run various CLI commands to interact with Databricks workspaces and account consoles, such as listing catalogs, creating schemas, and managing groups.
Release: v2.10.2 (#1738)
- Update Databricks CLI to v0.259.0
Release: v2.10.1 (#1704)
This release updates the Databricks CLI to v0.253.0 and improves virtual environment management by using UV. It also adds support for complex variables in the UI and prevents `sys.exit` calls in Jupyter initialization scripts.
Release: v2.9.4 (#1670)
- Rollback Databricks CLI to v0.245.0 to fix auth problems
Release: v2.9.3 (#1665)
- Update Databricks CLI to v0.248.0