Databricks Asset Bundles Demo
Type
On-Demand Video
Duration
2.5 minutes
Related Content
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.