AWS Certified Solutions Architect – Professional — Question 866

A finance company is running its business-critical application on current-generation Linux EC2 instances. The application includes a self-managed MySQL database performing heavy I/O operations. The application is working fine to handle a moderate amount of traffic during the month. However, it slows down during the final three days of each month due to month-end reporting, even though the company is using Elastic Load Balancers and Auto Scaling within its infrastructure to meet the increased demand.
Which of the following actions would allow the database to handle the month-end load with the LEAST impact on performance?

Answer options

• A. Pre-warming Elastic Load Balancers, using a bigger instance type, changing all Amazon EBS volumes to GP2 volumes.
• B. Performing a one-time migration of the database cluster to Amazon RDS, and creating several additional read replicas to handle the load during end of month.
• C. Using Amazon CloudWatch with AWS Lambda to change the type, size, or IOPS of Amazon EBS volumes in the cluster based on a specific CloudWatch metric.
• D. Replacing all existing Amazon EBS volumes with new PIOPS volumes that have the maximum available storage size and I/O per second by taking snapshots before the end of the month and reverting back afterwards.

Correct answer: B

Explanation

Migrating the self-managed MySQL database to Amazon RDS allows the company to easily offload the heavy month-end reporting traffic by deploying read replicas, which directly addresses the read-heavy reporting bottleneck without impacting the primary write database. Other options like migrating to GP2 volumes (Option A) or manually swapping PIOPS volumes via snapshots (Option D) introduce high administrative overhead and potential downtime. Using Lambda to modify EBS volumes dynamically (Option C) does not solve the underlying read contention on a single database instance as effectively as database clustering and read replicas.