Understand Environment-Specific Configuration Using Automation Bundle (formerly Databricks Asset Bundles) Variables and Overrides While Promoting the Same Codebase Across Dev, Test, and Prod Targets. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 5)

Questions 21–23

1. 21expert · hard

   A team has a Databricks Asset Bundle with a variable `retention_days` defined as follows: the default is 30; the `dev` target overrides it to 7; the `test` target overrides it to 14; the `prod` target has no override. A CI/CD pipeline runs `databricks bundle deploy --target prod --var retention_days=90`. What is the final value of `retention_days` for the prod deployment?

   • A14
   • B7
   • C90
   • D30
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2. 22foundation · easy

   When promoting a Databricks Asset Bundle from dev to prod, what is the recommended approach?

   • ADeploy the dev bundle to prod without any changes
   • BCopy the bundle code to a new repository and modify it for prod
   • CUse the same bundle codebase and apply different target overrides for prod
   • DRewrite the bundle configuration from scratch for prod
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3. 23application · medium

   A team is setting up a Databricks Asset Bundle for a new project. They want to define a variable `schema_name` that has a default value of `default_schema`, but the `dev` target should use `dev_schema` and the `prod` target should use `prod_schema`. Where should the default value and the target overrides be placed in the bundle configuration?

   • ADefault in a separate `variables.yml` file; overrides in `databricks.yml`
   • BDefault in each target's `variables` block; no top-level default
   • CDefault in the `resources` section; overrides in the `environments` section
   • DDefault in the `variables` section of `databricks.yml`; overrides in each target's `variables` block
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