AWS Certified Solutions Architect – Associate (SAA-C03) — Question 559

A solutions architect is designing a workload that will store hourly energy consumption by business tenants in a building. The sensors will feed a database through HTTP requests that will add up usage for each tenant. The solutions architect must use managed services when possible. The workload will receive more features in the future as the solutions architect adds independent components.

Which solution will meet these requirements with the LEAST operational overhead?

Answer options

• A. Use Amazon API Gateway with AWS Lambda functions to receive the data from the sensors, process the data, and store the data in an Amazon DynamoDB table.
• B. Use an Elastic Load Balancer that is supported by an Auto Scaling group of Amazon EC2 instances to receive and process the data from the sensors. Use an Amazon S3 bucket to store the processed data.
• C. Use Amazon API Gateway with AWS Lambda functions to receive the data from the sensors, process the data, and store the data in a Microsoft SQL Server Express database on an Amazon EC2 instance.
• D. Use an Elastic Load Balancer that is supported by an Auto Scaling group of Amazon EC2 instances to receive and process the data from the sensors. Use an Amazon Elastic File System (Amazon EFS) shared file system to store the processed data.

Correct answer: A

Explanation

Option A is correct because Amazon API Gateway, AWS Lambda, and Amazon DynamoDB are fully managed, serverless services that scale automatically and minimize operational overhead. Deploying Amazon EC2 instances (as in options B, C, and D) introduces significant administrative effort for patching, operating system maintenance, and scaling configuration. Furthermore, Amazon DynamoDB is an ideal, low-overhead database for fast key-value lookups like tenant energy metrics, unlike self-managed SQL databases on EC2 or file-based systems like Amazon S3 and Amazon EFS.