SAA-C03 Question #571: Real Exam Question with Answer & Explanation

Question

The customers of a finance company request appointments with financial advisors by sending text messages. A web application that runs on Amazon EC2 instances accepts the appointment requests. The text messages are published to an Amazon Simple Queue Service (Amazon SQS) queue through the web application. Another application that runs on EC2 instances then sends meeting invitations and meeting confirmation email messages to the customers. After successful scheduling, this application stores the meeting information in an Amazon DynamoDB database. As the company expands, customers report that their meeting invitations are taking longer to arrive. What should a solutions architect recommend to resolve this issue?

Options

• AAdd a DynamoDB Accelerator (DAX) cluster in front of the DynamoDB database.
• BAdd an Amazon API Gateway API in front of the web application that accepts the appointment
• CAdd an Amazon CloudFront distribution. Set the origin as the web application that accepts the
• DAdd an Auto Scaling group for the application that sends meeting invitations. Configure the Auto

Explanation

For SQS-backed worker architectures, AWS recommends scaling consumers based on queue metrics (e.g., ApproximateNumberOfMessagesVisible, AgeOfOldestMessage). EC2 Auto Scaling can "scale out based on Amazon CloudWatch alarms" tied to SQS backlog, increasing worker capacity to reduce latency as demand grows. DAX (A) accelerates DynamoDB reads, not message processing. API Gateway (B) and CloudFront (C) optimize request ingress and content delivery, not the asynchronous email-sending application. The bottleneck is consumer throughput; scaling workers with an SQS- driven policy restores timely processing without downtime and follows Well-Architected patterns for decoupled, elastic systems.

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