Which option provides a scalable application architecture to handle peak seasons 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.
Explanations:
Migrating to AWS Lambda would handle scaling but does not optimize DynamoDB beyond increasing capacity, which may not be cost-effective or optimal for unpredictable peaks.
Using Lambda with DynamoDB global tables provides high availability, but global tables add complexity for read/write performance. They are not needed if traffic is regional.
Auto Scaling groups with DynamoDB auto scaling is a scalable, low-development solution that dynamically handles variable traffic without major changes to the architecture.
SQS with Lambda introduces extra latency for processing writes to DynamoDB and adds complexity without directly addressing the core issue of scaling during peak times.
I reckon the answer is:
Use Auto Scaling groups for the backend services. Use DynamoDB auto scaling.
I would say the answer is:
Use Auto Scaling groups for the backend services. Use DynamoDB auto scaling.