Configure and deploy bundles ============================ Use this with a project that already passes ``lhp validate``. You need a Databricks CLI installation and authentication to deploy; local generation does not require workspace access. Configure resource inclusion ---------------------------- An LHP project created with bundle support already contains ``databricks.yml``. For a project created with ``--no-bundle``, add it at the project root: .. code-block:: yaml bundle: name: my_project include: - resources/*.yml - resources/lhp/*.yml targets: dev: mode: development default: true workspace: host: https://your-workspace-host Replace the workspace host and use the same target name as the LHP environment. The top-level ``resources`` glob includes generated jobs; ``resources/lhp`` includes generated pipeline resources. LHP leaves this bundle file under your control. See :doc:`/reference/config/bundle` for the integration boundary. Set pipeline defaults --------------------- Create ``config/pipeline_config.yaml``: .. code-block:: yaml project_defaults: catalog: "${catalog}" schema: "${bronze_schema}" serverless: true Define those tokens in ``substitutions/dev.yaml``. Add per-pipeline documents when individual pipelines need different settings; see the complete :doc:`pipeline configuration reference `. Generate, validate and deploy ----------------------------- From the project root: .. code-block:: bash lhp validate --env dev -pc config/pipeline_config.yaml lhp generate --env dev -pc config/pipeline_config.yaml databricks bundle validate -t dev databricks bundle deploy -t dev Inspect ``resources/lhp/*.pipeline.yml`` before deployment. Confirm the catalog, schema, libraries and compute settings. Deployment creates or updates workspace resources; run a pipeline or the generated job to process data. Continue with :doc:`jobs` to schedule dependent pipelines, or use the :doc:`sample deployment walkthrough `.