Deploy framework from local machine

Deploy the Lakeflow Framework (Framework Bundle) to your Databricks workspace from your local machine using the Declarative Automation Bundle (DAB) CLI workflow.

For deployment modes (flat DAB deploy, wheel, wheel + overlay), see Framework Deployment Options. For deploy order and ownership models, see Before you deploy. For automated pipelines, see Setting up CI/CD.

Prerequisites

Before you begin, verify:

  • Databricks workspace access with permission to deploy bundles

  • Databricks CLI installed — required for local Asset Bundle deployment (CLI documentation)

  • CLI authentication — run databricks auth login for your workspace, or use a configured CLI profile

  • Unity Catalog enabled in your workspace

Step 1 — Authenticate the Databricks CLI

Authenticate against the workspace you will deploy to:

databricks auth login --host https://<your-workspace-url>

Or use an existing named profile. Pass the profile on later commands with -p <profile>:

databricks bundle deploy -t dev -p <profile>

Step 2 — Configure the workspace host (optional)

Ensure the correct Databricks workspace is selected. Either:

  • Leave workspace.host unset in databricks.yml so the CLI uses the host from the selected profile, or

  • Set the host explicitly under the target you will deploy to.

The Databricks CLI must be authenticated with credentials that can access this workspace.

Step 3 — Validate the bundle

From the framework repository root (clone lakeflow_framework):

databricks bundle validate

This runs checks to ensure the bundle is correctly set up and ready for deployment.

Step 4 — Deploy the bundle

databricks bundle deploy -t dev

Note

By default the CLI deploys to the dev target in databricks.yml. Use -t <target> to deploy elsewhere and -p <profile> to select a different CLI profile.

To deploy a specific framework version:

databricks bundle deploy -t dev --var="version=1.2.3"

See Setting up CI/CD and Versioning - Framework for version pinning in higher environments.

Step 5 — Verify the deployment

When deployment succeeds, framework source is present in your Databricks workspace under the .bundle directory for the deploying user (see workspace.root_path in databricks.yml), typically under .bundle/<project>/<target>/<version>/files/src.

Open the workspace UI and confirm bundle files are present, or inspect the path reported by the CLI deploy output.

Example — clone and deploy

git clone https://github.com/databricks-solutions/lakeflow_framework.git
cd lakeflow_framework
databricks bundle validate
databricks bundle deploy -t dev

See also