AWS Certified Solutions Architect – Associate (SAA-C03) — Question 985

A company recently migrated to the AWS Cloud. The company wants a serverless solution for large-scale parallel on-demand processing of a semistructured dataset. The data consists of logs, media files, sales transactions, and IoT sensor data that is stored in Amazon S3. The company wants the solution to process thousands of items in the dataset in parallel.

Which solution will meet these requirements with the MOST operational efficiency?

Answer options

• A. Use the AWS Step Functions Map state in Inline mode to process the data in parallel.
• B. Use the AWS Step Functions Map state in Distributed mode to process the data in parallel.
• C. Use AWS Glue to process the data in parallel.
• D. Use several AWS Lambda functions to process the data in parallel.

Correct answer: B

Explanation

AWS Step Functions Map state in Distributed mode is optimized for high-concurrency, serverless processing of massive datasets in Amazon S3, allowing up to 10,000 parallel executions. In contrast, Inline mode is limited to only 40 concurrent iterations, which is inadequate for processing thousands of items in parallel. While AWS Glue and custom AWS Lambda orchestrations could process the data, they require significantly more operational and management overhead compared to the native Distributed Map state.