Databricks Asset Bundles Demo

What you’ll learn

Databricks asset bundles make it possible to express complete data, analytics, and ML projects as a collection of source files called a bundle. A bundle’s source files serve as an end-to-end definition of a project. These source files include information about how they are to be tested and deployed. This end-to-end definition makes it simple to apply data engineering best practices such as source control, code review, testing, and CI/CD.

A bundle includes the following parts:

  • Source files, such as notebooks and Python files, include the business logic.

  • Declarations and settings for Databricks resources, such as Databricks jobs, Delta Live Tables pipelines, Model Serving endpoints, MLflow Experiments, and MLflow registered models.

  • Unit tests and integration tests.

  • Configurations that define to which workspace or workspaces the bundle is to be deployed.

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