QuestionQ21

Continuous Improvement for Existing Solutions

A company must optimize the cost of its AWS application. The application uses AWS Lambda functions and Amazon Elastic Container Service (Amazon ECS) containers running on AWS Fargate. It is write-heavy and stores data in an Amazon Aurora MySQL database.

The application's load is inconsistent. It has lengthy periods of no use, followed by sudden, significant rises and falls in traffic. The database runs on a memory-optimized DB instance that cannot handle the load.

A solutions architect must design a solution that can scale to accommodate the traffic changes.

Which solution meets these requirements MOST cost-effectively?

Explanation

Aurora Serverless v1 automatically scales database capacity up and down in response to unpredictable load and can pause an idle cluster entirely, eliminating compute charges during extended inactivity. This is ideal for write-heavy workloads with inconsistent traffic patterns. Compute Savings Plans apply to both Lambda and Fargate usage, providing cost coverage for this application's compute services. Read replicas address read scaling, not the write-heavy bottleneck. Multiple writer instances and global databases are designed for different access patterns and don't provide pause capability for cost optimization.

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