Question #911
A popular e-commerce platform runs its backend services on Amazon EC2 instances behind an Application Load Balancer, using Amazon DynamoDB for product inventory and user sessions. During holiday sales, the platform experiences significant latency in both read and write operations.
Which option provides a scalable application architecture to handle peak traffic with the LEAST development effort?
Migrate the backend services to AWS Lambda. Increase the read and write capacity of DynamoDB.
Migrate the backend services to AWS Lambda. Configure DynamoDB to use global tables.
Use Auto Scaling groups for the backend services. Use DynamoDB auto scaling.
Use Auto Scaling groups for the backend services. Use Amazon Simple Queue Service (Amazon SQS) and an AWS Lambda function to write to DynamoDB.
Explanation
The correct answer is C because it builds on the existing architecture with minimal changes. Auto Scaling groups automatically adjust EC2 instances to handle backend traffic spikes, while DynamoDB auto scaling adjusts read/write capacity dynamically. This avoids the need to migrate services to Lambda (Options A/B) or redesign the write workflow with SQS (Option D), which would require significant development effort. DynamoDB auto scaling is a native feature requiring only configuration, and EC2 Auto Scaling uses existing infrastructure, aligning with the 'least effort' requirement.
Key points:
- Auto Scaling groups scale EC2 horizontally without code changes.
- DynamoDB auto scaling avoids manual capacity adjustments.
- Migrating to Lambda (A/B) or SQS (D) adds complexity and development work.
- Global tables (B) address multi-region latency, not peak traffic scaling.
AWS services involved: EC2 Auto Scaling, DynamoDB, ALB.
Answer
The correct answer is: C