What is the primary purpose of a Databricks Asset Bundle (DAB)?

To automatically tune hyperparameters for machine learning models.

To provide a graphical interface for managing Databricks clusters.

To package and deploy Databricks resources as code for CI/CD.

To store large machine learning models in a compressed format.

A company is setting up a Databricks environment for ML projects. They have regulatory requirements to keep data in a specific geographic region and need to ensure that only authorized users can access sensitive data. What is the most important design consideration?

Use a single workspace with no region restrictions and rely on network security groups.

Use separate workspaces for each user to ensure data isolation.

Use a Databricks workspace in the required region and configure Unity Catalog for data access control.

Store data in an external cloud storage bucket in the required region and use shared clusters.

A team wants to deploy an MLflow registered model to a model serving endpoint using Databricks Asset Bundles. They need to ensure the endpoint is created and updated as part of their CI/CD pipeline. What is the primary benefit of defining the serving endpoint in a DABs configuration file?

It eliminates the need for a separate CI/CD pipeline because the bundle is self-deploying.

It automatically scales the endpoint based on traffic without any configuration.

It allows the endpoint to be created manually in the UI and then exported for backup.

It enables infrastructure-as-code management, allowing the endpoint to be versioned, reviewed, and deployed consistently across environments.

A company uses Databricks Asset Bundles to deploy a model serving endpoint. They have a CI/CD pipeline that deploys to staging and production. After a successful staging deployment, they want to promote the same configuration to production, but with a different model version. What is the best way to handle this?

Create a separate bundle for production and copy the staging configuration.

Use target overrides in the bundle to specify different model versions for staging and production.

Deploy the same bundle to production and then manually update the model version in the UI.

Use the same bundle for both environments and rely on environment variables to set the model version.

DatabricksCertified Machine Learning Professional

Domain 2Objective 3

Environment Architectures MACHINE-LEARNING-PROFESSIONAL Practice Questions (Page 2)

Part of the ML Ops domain, which accounts for 44% of the MACHINE-LEARNING-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~22–35 in this domain), expect 4–7 from this objective — we provide 28 practice questions to prepare you well beyond it. (estimate)

28questions here

6free pages

9concepts

44%of the exam

Questions 6–10

6foundation · easy
What is the primary purpose of a Databricks Asset Bundle (DAB)?
Select an answer first
7foundation · easy
In a Databricks Asset Bundle, which configuration field is used to specify the model version for a model serving endpoint?
Select an answer first
8application · medium
A company is setting up a Databricks environment for ML projects. They have regulatory requirements to keep data in a specific geographic region and need to ensure that only authorized users can access sensitive data. What is the most important design consideration?
Select an answer first
9application · medium
A team wants to deploy an MLflow registered model to a model serving endpoint using Databricks Asset Bundles. They need to ensure the endpoint is created and updated as part of their CI/CD pipeline. What is the primary benefit of defining the serving endpoint in a DABs configuration file?
Select an answer first
10expert · hard
A company uses Databricks Asset Bundles to deploy a model serving endpoint. They have a CI/CD pipeline that deploys to staging and production. After a successful staging deployment, they want to promote the same configuration to production, but with a different model version. What is the best way to handle this?
Select an answer first

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Environment Architectures MACHINE-LEARNING-PROFESSIONAL Practice Questions (Page 2)

Questions 6–10

What is the primary purpose of a Databricks Asset Bundle (DAB)?

In a Databricks Asset Bundle, which configuration field is used to specify the model version for a model serving endpoint?

A company is setting up a Databricks environment for ML projects. They have regulatory requirements to keep data in a specific geographic region and need to ensure that only authorized users can access sensitive data. What is the most important design consideration?

A team wants to deploy an MLflow registered model to a model serving endpoint using Databricks Asset Bundles. They need to ensure the endpoint is created and updated as part of their CI/CD pipeline. What is the primary benefit of defining the serving endpoint in a DABs configuration file?

Keep studying — ML Ops