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Design and implement build and release pipelineshardMultiple ChoiceObjective-mapped

AZ-400 Practice Question: Design and implement build and release pipelines

You are designing a release pipeline for a mission-critical application that must achieve zero-downtime deployments to Azure App Service (Web App for Containers). The application uses Azure SQL Database with schema migrations. The current deployment slot strategy uses staging and production slots. You need to ensure that during a swap, the staging slot is warmed up and the database schema is rolled back if the swap fails. Which combination of deployment slots and pre/post-swap actions should you implement?

⚠ Common exam trap

Test-takers frequently assume auto-swap handles database rollback automatically, but Azure App Service does not manage database schema changes—only application code and configuration are swapped, so a manual rollback strategy is required.

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

Use three slots: production, staging, and a new slot for the new version. Apply schema changes in the new slot, then swap new to staging, warm up staging, then swap staging to production. On failure, swap staging back to production.

It uses three slots to isolate schema changes in a new slot, then swaps to staging for warm-up, and finally swaps to production. If the swap fails, rolling back staging to production reverses the schema changes, ensuring zero-downtime. This approach aligns with Azure App Service slot-swap best practices for mission-critical applications requiring database rollback capability.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use three slots: production, staging, and a new slot for the new version. Apply schema changes in the new slot, then swap new to staging, warm up staging, then swap staging to production. On failure, swap staging back to production.

    Why this is correct

    This allows you to test schema changes in the new slot, warm up in staging, and swap staging to production. If the final swap fails, you swap staging back to production, which still has the old code and old schema.

  • Use two slots (staging and production) with auto-swap enabled. The auto-swap handles warm-up automatically. If the swap fails, Azure automatically rolls back.

    Why it's wrong here

    Auto-swap does not handle database schema rollback automatically; it only swaps code and configuration. A failed swap would leave the new schema in place even though the old code returns.

  • Use three slots: production, staging, and a new slot for the new version. Apply schema changes in the new slot, then swap new slot to staging, then staging to production. On failure, swap staging back to production.

    Why it's wrong here

    Schema changes are applied in the new slot, but swapping new to staging then staging to production doesn't guarantee zero-downtime rollback because the production slot's schema changes on the first swap.

  • Use two slots (staging and production). Apply schema changes in staging before swap. If swap fails, manually redeploy the old version to production.

    Why it's wrong here

    Schema changes are applied to staging, then swapped to production. If swap fails, the production slot still has old code but staging has new schema, causing inconsistency.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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