AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 68

An ML engineer is using Amazon SageMaker to train a deep learning model that requires distributed training. After some training attempts, the ML engineer observes that the instances are not performing as expected. The ML engineer identifies communication overhead between the training instances.
What should the ML engineer do to MINIMIZE the communication overhead between the instances?

Answer options

• A. Place the instances in the same VPC subnet. Store the data in a different AWS Region from where the instances are deployed.
• B. Place the instances in the same VPC subnet but in different Availability Zones. Store the data in a different AWS Region from where the instances are deployed.
• C. Place the instances in the same VPC subnet. Store the data in the same AWS Region and Availability Zone where the instances are deployed.
• D. Place the instances in the same VPC subnet. Store the data in the same AWS Region but in a different Availability Zone from where the instances are deployed.

Correct answer: C

Explanation

The correct answer is C because placing the instances in the same VPC subnet and storing the data in the same AWS Region and Availability Zone minimizes latency and communication overhead. Options A and B suggest storing data in a different AWS Region, which would increase communication delays. Option D, while in the same Region, still places the data in a different Availability Zone, leading to potential overhead issues.