Databricks-GenAI-Assoc Assembling and Deploying Apps Practice Question
A team wants to review what a Databricks Asset Bundle deployment would change in the production workspace before it actually creates or modifies any resources. Which command should the engineer run first?
⚠ Common exam trap
The trap here is assuming `databricks bundle deploy` supports a `--dry-run` flag, when the supported way to preview changes is the separate `databricks bundle plan` command.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
`databricks bundle plan -t prod`
The `databricks bundle plan` command produces a deployment plan that lists the resources the deployment would create, update, or delete in the target workspace, without applying any change. Running it with `-t prod` previews the production deployment. This lets the team review the impact before executing `databricks bundle deploy`, which is the recommended safe release workflow.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
`databricks bundle plan -t prod`
Why this is correct
`databricks bundle plan` computes and displays the changes the deployment would make to the target workspace, including resources to create, update, or delete, without actually applying them. Running it with `-t prod` shows the production plan. This is exactly the preview the team needs before committing the deployment, making it the correct first step in a safe release process.
- ✗
`databricks bundle deploy -t prod --dry-run`
Why it's wrong here
Databricks Asset Bundles do not support a `--dry-run` flag on `databricks bundle deploy`. Running this command would fail with an unknown flag error, so it cannot be used to preview changes. The correct way to preview the deployment plan is the dedicated `bundle plan` command, which shows the intended resource changes without applying them.
- ✗
`databricks bundle validate -t prod`
Why it's wrong here
`databricks bundle validate` checks that the bundle configuration is syntactically correct and that referenced variables and paths resolve. It does not show a diff of what resources would be created, updated, or deleted in the target workspace. The engineer could run it as a first sanity check, but it does not satisfy the requirement to preview the deployment changes.
- ✗
`databricks bundle summary -t prod`
Why it's wrong here
`databricks bundle summary` prints the resolved bundle configuration, including the target, workspace, and resources as they are defined. It shows what the bundle contains, not what would change in the workspace. Because it does not compare against the current workspace state, it cannot show creates, updates, or deletes, so it does not meet the preview requirement.
About these practice questions
This Databricks-GenAI-Assoc question is part of Courseiva's 330-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-GenAI-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-GenAI-Assoc exam.