Deploy Declarative Automation Bundles (formerly Databricks Asset Bundles) to Package, Configure, and Promote Lakeflow Jobs, Lakeflow Spark Declarative Pipelines, and Other Workspace Assets Across Dev, Test, and Prod Environments. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   A company is promoting a Databricks Asset Bundle from test to prod. They have already deployed to test and validated the bundle. Now they want to deploy to prod. What is the recommended practice before deploying to prod?

   • ARun `databricks bundle deploy --target prod` directly, as validation is not required.
   • BRun `databricks bundle run --target prod` to test the bundle before deploying.
   • CRun `databricks bundle validate --target prod` to ensure the bundle is valid for prod.
   • DRun `databricks bundle destroy --target test` before deploying to prod.
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2. 12foundation · easy

   In a Databricks Asset Bundle, what is the purpose of the 'artifacts' section in the bundle configuration?

   • ATo define the files (e.g., notebooks, JARs) that are uploaded and referenced by the bundle resources
   • BTo define the environment variables for the bundle
   • CTo list the users and groups who can access the bundle
   • DTo specify the target workspace URL for deployment
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4. 13foundation · easy

   What is the primary purpose of the 'databricks bundle deploy' command in the context of promoting a bundle from dev to test?

   • ATo delete resources from the target environment
   • BTo deploy the bundle to the target environment specified by the --target flag
   • CTo validate the bundle configuration without deploying
   • DTo generate a deployment plan for review
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5. 14application · medium

   A data team is using Databricks Asset Bundles to manage their Lakeflow Jobs. They have a CI/CD pipeline that deploys the bundle to dev, test, and prod. They want to ensure that the deployment to prod is only triggered after a successful deployment to test. What is the recommended way to achieve this?

   • ARun `databricks bundle deploy --target prod` only after manually verifying the test deployment.
   • BUse the `targets` section to define a `promote` field that automatically deploys to prod after test.
   • CConfigure the CI/CD pipeline to have separate stages for test and prod, with the prod stage requiring the test stage to pass.
   • DUse the `depends_on` field in the bundle configuration to define the dependency between test and prod.
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6. 15application · medium

   A data engineer is packaging a Databricks Asset Bundle that includes a Lakeflow Job. The job references a Python wheel file that is built from source code in the same repository. How should the wheel file be included in the bundle?

   • APlace the wheel file in the `resources` section of the bundle.
   • BUpload the wheel file to the workspace manually and reference the path in the job definition.
   • CInclude the wheel file in the `variables` section as a path variable.
   • DDefine the wheel file as an artifact in the `artifacts` section and reference it in the job definition.
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