Understand the Databricks CLI to Validate, Deploy, and Manage Declarative Automation Bundles (formerly Databricks Asset Bundles) and Other Workspace Assets in Automated CI/CD Workflows. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Which file format is used to define the configuration of a Declarative Automation Bundle?

   • AYAML
   • BJSON
   • CTOML
   • DXML
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2. 2foundation · easy

   Why is the Databricks CLI commonly used in CI/CD pipelines for managing Databricks resources?

   • AIt allows for automated, scriptable management of Databricks resources
   • BIt provides a graphical interface for managing resources
   • CIt automatically syncs resources with GitHub
   • DIt is the only way to deploy Databricks resources
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4. 3application · medium

   A team is building a CI/CD pipeline to manage their Databricks workspace assets. They have a notebook that needs to be uploaded to a specific path in the workspace, and they also need to update the configuration of an existing cluster. They want to use the Databricks CLI for these tasks. Which two CLI commands should they use?

   • Adatabricks workspace import and databricks clusters update
   • Bdatabricks workspace export and databricks clusters list
   • Cdatabricks fs cp and databricks clusters edit
   • Ddatabricks workspace mkdirs and databricks clusters create
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5. 4foundation · easy

   A data engineer wants to install the Databricks CLI on their local machine to interact with a Databricks workspace. Which package manager command installs the Databricks CLI?

   • Anpm install databricks-cli
   • Bapt-get install databricks-cli
   • Cpip install databricks-cli
   • Dbrew install databricks-cli
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6. 5expert · hard

   A team has a Databricks bundle that deploys a job. They have deployed it to the 'staging' target. Now they want to deploy the same bundle to the 'prod' target, but they want to ensure that the job in 'prod' has a different schedule than the one in 'staging'. How should they configure this?

   • ACreate two separate jobs in the bundle, one for 'staging' and one for 'prod', with different schedules.
   • BUse the same job definition for both targets and change the schedule in the workspace after deployment.
   • CDefine the job in the 'resources' section with the 'staging' schedule, and override the schedule in the 'prod' target.
   • DUse environment variables to set the schedule, and set different values in the CI/CD pipeline for each target.
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