Declarative Automation Bundles (DABs, previously known as Databricks Asset Bundles) bring an "infrastructure-as-code" approach to packaging and deploying notebooks, jobs, pipelines, and workflows across environments. Instead of clicking through the workspace UI or stitching together ad-hoc scripts, teams can define their entire Databricks project - code, configuration, and infrastructure - in YAML, version it alongside their source code, and deploy it consistently through a CI/CD pipeline.

In this session, we'll explore how DevOps practices translate into the Databricks world. We'll cover what Bundles are and how they compare to notebook-based deployments, how to structure a bundle for dev/test/prod environments, and how to wire them into a CI/CD pipeline (GitHub Actions/Azure DevOps) for automated validation and deployment. Along the way, we'll look at common pitfalls, testing strategies, and how Bundles fit into a broader data platform governance and release process.

You'll leave with a practical blueprint for automating Databricks deployments - reducing manual work, improving repeatability, and bringing real DevOps discipline to your data engineering workflows.