A team is migrating from a legacy deployment process that uses a mix of Terraform scripts and manual notebook uploads. They want to adopt Databricks Asset Bundles for all new resources. However, they have a requirement to keep the existing Terraform-managed resources untouched. What is the best way to introduce bundles without affecting the Terraform-managed resources?

Import all Terraform-managed resources into the bundle and deploy the bundle to take over management

Use bundles only for notebooks and continue using Terraform for jobs and pipelines

Delete the Terraform scripts and recreate all resources in the bundle

Create a new bundle that defines only the new resources and deploy it alongside the existing Terraform-managed resources

In a CI/CD pipeline, what is the typical role of a step that runs 'databricks bundle deploy'?

To create a pull request in the Git repository

To run unit tests on the bundle code

To deploy the bundle resources to a Databricks workspace

To build a Docker image for the Databricks runtime

What is the main benefit of automating Databricks resource deployment in a CI/CD pipeline?

It provides a graphical interface for managing resources

It ensures consistent and repeatable deployments across environments

It automatically scales clusters based on load

It eliminates the need for version control

A team has a bundle with a job that uses a notebook. The notebook path is different in dev and production. How should they handle this in the bundle configuration?

Hardcode the production notebook path in the job definition

Use a relative path that works in both environments

Define the job twice, once for each environment, with the correct notebook path

Use a variable for the notebook path and override it per target

A developer has just updated a job definition in their bundle and wants to deploy it to the staging workspace. They have already run 'databricks bundle validate' successfully. What is the next command they should run to make the job available in staging?

databricks bundle run --target staging

databricks bundle deploy --target staging

databricks bundle destroy --target staging

databricks bundle sync --target staging

DatabricksCertified Data Engineer Professional

Domain 9Objective 2

Deploying CI/CD DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 3)

Part of the Debugging and Deploying domain, which accounts for 10% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~5–8 in this domain), expect 3–4 from this objective — we provide 25 practice questions to prepare you well beyond it. (estimate)

25questions here

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Questions 11–15

11expert · hard
A team is migrating from a legacy deployment process that uses a mix of Terraform scripts and manual notebook uploads. They want to adopt Databricks Asset Bundles for all new resources. However, they have a requirement to keep the existing Terraform-managed resources untouched. What is the best way to introduce bundles without affecting the Terraform-managed resources?
Select an answer first
12foundation · easy
In a CI/CD pipeline, what is the typical role of a step that runs 'databricks bundle deploy'?
Select an answer first
13foundation · easy
What is the main benefit of automating Databricks resource deployment in a CI/CD pipeline?
Select an answer first
14application · medium
A team has a bundle with a job that uses a notebook. The notebook path is different in dev and production. How should they handle this in the bundle configuration?
Select an answer first
15application · easy
A developer has just updated a job definition in their bundle and wants to deploy it to the staging workspace. They have already run 'databricks bundle validate' successfully. What is the next command they should run to make the job available in staging?
Select an answer first

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