DP-300 Configure and manage automation of tasks Practice Question
A company uses Azure SQL Database for a critical application. They need to automate the process of exporting a database to a storage account every night, ensuring the export is consistent. The solution must minimize administrative overhead. What should they use?
⚠ Common exam trap
The trap here is that candidates often overcomplicate the solution by choosing Azure Data Factory or Logic Apps, thinking they need a full ETL tool, when a simple scheduled PowerShell runbook is the most direct and low-overhead method for a consistent database export to storage.
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 Azure Automation runbook that uses the Export-AzureRmSqlDatabase cmdlet and schedule it to run nightly.
Azure Automation runbooks can execute PowerShell cmdlets like Export-AzureRmSqlDatabase (or the newer Export-AzSqlDatabase) to perform a consistent export of an Azure SQL Database to a storage account. By scheduling the runbook to run nightly, you automate the export with minimal administrative overhead, as the export operation uses database snapshots to ensure consistency without requiring complex orchestration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create an Azure Automation runbook that uses the Export-AzureRmSqlDatabase cmdlet and schedule it to run nightly.
Why this is correct
This is correct because Azure Automation provides a native scheduler for PowerShell runbooks, and Export-AzureRmSqlDatabase creates a BACPAC file (a transactionally consistent backup) in Azure Storage. The cmdlet orchestrates the export through the Azure SQL Database management plane, ensuring a consistent snapshot of the live database. Running nightly via schedule meets the backup requirement without manual intervention, making it the simplest and most reliable option for automated database export.
- ✗
Create an Elastic Database Job that runs a T-SQL script to export the database.
Why it's wrong here
Elastic Database Jobs execute T-SQL scripts across multiple databases in an elastic pool or across servers. They are designed for administrative tasks like index maintenance or data consistency checks, but they do not have direct capability to export a database to a BACPAC file. A T-SQL script cannot invoke the Azure SQL export operation; the export requires a PowerShell cmdlet, REST API, or portal action. Therefore, this approach cannot fulfill the requirement.
- ✗
Deploy an Azure Data Factory pipeline with a Copy activity to export the database.
Why it's wrong here
An Azure Data Factory Copy activity directly moves data, but it does not create a transactionally consistent snapshot of an entire live Azure SQL Database. This means the exported data could be inconsistent if writes occur during the copy, failing the consistency requirement for the critical application. However, Data Factory pipelines are ideal for general data movement, ETL processes, and replicating specific datasets between various Azure data stores, making it a powerful tool for data integration where snapshot consistency isn't paramount.
- ✗
Use an Azure Logic App with the SQL Server connector to export the database.
Why it's wrong here
The SQL Server connector in Logic Apps is intended for executing queries, stored procedures, and modifying data. It does not have a native action to produce a BACPAC export. While you could potentially call an Azure REST API or trigger an Automation runbook from a Logic App, the connector itself does not provide the export operation. This adds unnecessary complexity and requires custom API calls to achieve what Automation does natively, so it's not a straightforward solution.
Go deeper
Related to this question
Learn chapter
Configuring Automation Tasks for Database Administration
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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