Data Engineering on Microsoft Azure — Question 59

You have an Azure Data Factory pipeline named pipeline1 that includes a Copy activity named Copy1. Copy1 has the following configurations:

• The source of Copy1 is a table in an on-premises Microsoft SQL Server instance that is accessed by using a linked service connected via a self-hosted integration runtime.
• The sink of Copy1 uses a table in an Azure SQL database that is accessed by using a linked service connected via an Azure integration runtime.

You need to maximize the amount of compute resources available to Copy1. The solution must minimize administrative effort.

What should you do?

Answer options

• A. Scale out the self-hosted integration runtime.
• B. Scale up the data flow runtime of the Azure integration runtime and scale out the self-hosted integration runtime.
• C. Scale up the data flow runtime of the Azure integration runtime.

Correct answer: A

Explanation

The correct answer is A, as scaling out the self-hosted integration runtime directly increases the compute resources available for the on-premises data processing without adding extra complexity. Options B and C are incorrect because they do not address the need to scale the self-hosted integration runtime, which is necessary to optimize the performance of Copy1 that relies on an on-premises source.