Summary
Databricks Asset Bundles introduces PyDABs catalog support, updates default templates to Databricks Runtime 16.4, and adds validation checks before completing migrations to the direct engine. The release also fixes several direct deployment engine update bugs and improves Python fallback handling during local environment setup.
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More from databricks/cli
Databricks CLI v1.23.0 makes databricks ssh connect provide claude and codex on dedicated clusters and in serverless IDE sessions and non-interactive commands, and adds GPU_1xRTX6000 workload support plus workspace.sync_mode (overwrite, in-place, immutable), which replaces the deprecated presets.source_linked_deployment and experimental.immutable_folder settings. The release also reverts bundle file uploads to the legacy /workspace-files/import-file endpoint to fix notebooks being uploaded as plain files, adds lifecycle.depends_on and bundle deploy --select for deletions, and fixes bundle validate errors when a schedule, trigger, or continuous block is referenced as a whole.
Fix GitHub API rate limit errors in aitools list and plugin installs by pinning skills to 0.2.32. (#7159)
Release v1.22.0 adds support for the features resource type, lets bundle deployment bind and unbind accept type.key references, and removes the 50-workspace limit in auth login. It also adds DATABRICKS_BUNDLE_STRICT_PROFILE_MATCH for exact profile matching, and release binaries now require macOS 13 Ventura or later.
Databricks Asset Bundles now utilize a multipart upload endpoint for improved deployment throughput and automatically retry operations encountering transient server errors. This release also adds uv workspace support for local environment setup alongside fixes for bundle deployment binding, immutable folders, and relative path resolution.
The Terraform deployment engine for Databricks Asset Bundles has been removed, requiring users to migrate to the direct engine or remain on CLI v1.19.x. Additional updates include a fix for large integer corruption in API commands, group-level run-as support in bundles, and expanded authentication options for Databricks Apps.
The CLI introduces a preview image push command for the Databricks Artifact Registry, preconfigures coding assistants in serverless SSH sessions, and adds expiration flags for Postgres branch creation. In Asset Bundles, clusters now support library configurations, Terraform deployments migrate to the direct engine prior to execution, and Postgres snapshot schedules are restricted to YAML.