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 4)

Questions 16–20

1. 16application · medium

   A data team uses a Databricks Asset Bundle to deploy a job to multiple environments. The job's schedule is defined in the bundle. In dev, the job should run every hour; in prod, it should run daily at 2 AM. The team wants to keep the job definition in one place. What is the best approach?

   • AUse a single schedule and disable the job in dev via a target override
   • BDefine the schedule as a bundle variable and override it in each target's configuration
   • CCreate two separate job definitions in the bundle, one for dev and one for prod
   • DSet the schedule in the notebook code using a Python `if` statement
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2. 17application · medium

   A company uses a single Databricks Asset Bundle repository to deploy a data pipeline to dev, test, and prod. The pipeline reads from a catalog named `bronze` in dev, but in prod it must read from `prod_bronze`. The team wants to avoid hardcoding the catalog name in the notebook code. What is the recommended way to handle this?

   • AHardcode `prod_bronze` in the notebook and use a `if` statement to check the environment
   • BUse a different notebook for each environment with the catalog name hardcoded
   • CSet the catalog name in the cluster's Spark configuration and reference it as a global variable
   • DDefine a bundle variable `catalog_name` and reference it in the notebook via `{{var.catalog_name}}`, then override it per target
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4. 18foundation · easy

   What is the purpose of target-specific overrides in a Databricks Asset Bundle?

   • ATo restrict which users can deploy to each environment
   • BTo define the order in which environments are deployed
   • CTo create separate copies of the bundle code for each environment
   • DTo allow the same bundle code to use different configuration values for different environments
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5. 19foundation · easy

   In a Databricks Asset Bundle, what is the purpose of defining a variable in the bundle configuration?

   • ATo encrypt secrets used by the bundle
   • BTo define the order in which resources are deployed
   • CTo parameterize configuration values so they can be reused and overridden per environment
   • DTo store a fixed value that cannot be changed between deployments
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6. 20application · medium

   A data team promotes a Databricks Asset Bundle from dev to test to prod. The bundle contains a job that writes to a path in DBFS. In dev, the path is `/mnt/dev/data`; in test, it is `/mnt/test/data`; in prod, it is `/mnt/prod/data`. The team wants to keep the job definition identical across environments. What should they do?

   • AUse a different job definition for each environment
   • BHardcode the prod path in the job and use a `if` statement in the notebook
   • CSet the path in the cluster's Spark configuration
   • DDefine a variable `output_path` and reference it in the job, then override it per target
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