AWS Certified Solutions Architect – Associate (SAA-C02) — Question 399

A solutions architect needs to host a high performance computing (HPC) workload in the AWS Cloud. The workload will run on hundreds of Amazon EC2 instances and will require parallel access to a shared file system to enable distributed processing of large datasets. Datasets will be accessed across multiple instances simultaneously. The workload requires access latency within 1 ms. After processing has completed, engineers will need access to the dataset for manual postprocessing.
Which solution will meet these requirements?

Answer options

• A. Use Amazon Elastic File System (Amazon EFS) as a shared file system. Access the dataset from Amazon EFS.
• B. Mount an Amazon S3 bucket to serve as the shared file system. Perform postprocessing directly from the S3 bucket.
• C. Use Amazon FSx for Lustre as a shared file system. Link the file system to an Amazon S3 bucket for postprocessing.
• D. Configure AWS Resource Access Manager to share an Amazon S3 bucket so that it can be mounted to all instances for processing and postprocessing.

Correct answer: C

Explanation

Amazon FSx for Lustre is designed specifically for high-performance computing (HPC) workloads, providing sub-millisecond latencies and parallel access to hundreds of Amazon EC2 instances. It natively integrates with Amazon S3, allowing processed data to be easily written back to S3 for manual postprocessing. Amazon EFS does not provide the same level of parallel performance for HPC workloads as FSx for Lustre, and Amazon S3 is an object store that does not natively support POSIX-compliant parallel file system access with sub-millisecond latency.