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Answer: Implement Auto Scaling groups for the backend services and enable DynamoDB auto scaling.
Option C is correct because it involves using Auto Scaling groups for the backend services and enabling DynamoDB auto scaling. This approach leverages existing AWS services to automatically adjust capacity based on demand, thus handling peak season traffic with minimal development effort. Option B, although a robust solution, would require significant redevelopment to migrate the backend services to AWS Lambda. Therefore, the least development effort is achieved by configuring Auto Scaling groups and DynamoDB auto scaling.
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A company that provides job boards for seasonal workers is experiencing increased traffic and usage, leading to slow application performance during peak seasons. The backend services are currently hosted on two Amazon EC2 instances behind an Application Load Balancer, with Amazon DynamoDB serving as the datastore. To address this issue with minimal development effort, which scalable architecture option should be implemented to effectively manage peak season traffic?
A
Migrate the backend services to AWS Lambda and enhance DynamoDB's read and write capacity.
B
Migrate the backend services to AWS Lambda and configure DynamoDB to utilize global tables.
C
Implement Auto Scaling groups for the backend services and enable DynamoDB auto scaling.
D
Implement Auto Scaling groups for the backend services and integrate Amazon Simple Queue Service (Amazon SQS) with an AWS Lambda function for writing to DynamoDB.
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