AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 70

A company is using Amazon SageMaker and millions of files to train an ML model. Each file is several megabytes in size. The files are stored in an Amazon S3 bucket. The company needs to improve training performance.
Which solution will meet these requirements in the LEAST amount of time?

Answer options

• A. Transfer the data to a new S3 bucket that provides S3 Express One Zone storage. Adjust the training job to use the new S3 bucket.
• B. Create an Amazon FSx for Lustre file system. Link the file system to the existing S3 bucket. Adjust the training job to read from the file system.
• C. Create an Amazon Elastic File System (Amazon EFS) file system. Transfer the existing data to the file system. Adjust the training job to read from the file system.
• D. Create an Amazon ElastiCache (Redis OSS) cluster. Link the Redis OSS cluster to the existing S3 bucket. Stream the data from the Redis OSS cluster directly to the training job.

Correct answer: B

Explanation

The correct answer is B because Amazon FSx for Lustre is optimized for high-performance workloads and can efficiently read data directly from S3, improving training times. Options A, C, and D involve additional steps that would not provide the same level of performance enhancement or would take more time to implement, such as transferring data or setting up different storage solutions.