DP-300 Configure and manage automation of tasks Practice Question
You are designing an automation strategy for deploying schema changes to 50 Azure SQL Databases in a elastic pool. You need to ensure that changes are applied in a consistent order and rolled back if any database fails. Which approach should you use?
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
✓
Create an Elastic Job that executes the schema change script within a transaction and uses target group error handling to roll back on failure.
Azure SQL Database Elastic Jobs can run T-SQL scripts across multiple databases with transactional control and error handling. Options A and C do not provide rollback capability. Option D is for infrastructure deployment, not schema changes.
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 Azure Data Studio with the Schema Compare extension and apply changes manually.
Why it's wrong here
No automation or rollback.
- ✓
Create an Elastic Job that executes the schema change script within a transaction and uses target group error handling to roll back on failure.
Why this is correct
Elastic Jobs support transactions and error handling.
- ✗
Deploy the schema changes using Azure Resource Manager templates with SQL extensions.
Why it's wrong here
ARM templates are for resource provisioning, not schema management.
- ✗
Use PowerShell to loop through each database and execute the script, catching exceptions.
Why it's wrong here
Requires custom rollback logic and is less reliable.
Go deeper
Related to this question
Learn chapter
Overview of Azure Data Platform Options
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
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