Which solution meets these requirements?

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A company has developed a mobile game.The backend for the game runs on several virtual machines located in an on-premises data center.The business logic is exposed using a REST API with multiple functions.Player session data is stored in central file storage.Backend services use different API keys for throttling and to distinguish between live and test traffic.The load on the game backend varies throughout the day.During peak hours, the server capacity is not sufficient.There are also latency issues when fetching player session data.Management has asked a solutions architect to present a cloud architecture that can handle the game’s varying load and provide low-latency data access.The API model should not be changed.

Which solution meets these requirements?

Implement the REST API using a Network Load Balancer (NLB). Run the business logic on an Amazon EC2 instance behind the NLB. Store player session data in Amazon Aurora Serverless.

Implement the REST API using an Application Load Balancer (ALB). Run the business logic in AWS Lambda. Store player session data in Amazon DynamoDB with on-demand capacity.

Implement the REST API using Amazon API Gateway. Run the business logic in AWS Lambda. Store player session data in Amazon DynamoDB with on- demand capacity.

Implement the REST API using AWS AppSync. Run the business logic in AWS Lambda. Store player session data in Amazon Aurora Serverless.

Explanations:

Using a Network Load Balancer (NLB) and Amazon EC2 does not efficiently handle varying loads since EC2 instances need to be manually scaled. Aurora Serverless could improve data access but is not the best fit with the current setup.

An Application Load Balancer (ALB) with AWS Lambda can handle varying loads, but it does not support REST API functions natively without modifications. DynamoDB on-demand capacity is suitable for varying load but may not address latency issues efficiently.

Amazon API Gateway provides a fully managed REST API solution that integrates seamlessly with AWS Lambda, allowing for auto-scaling and low-latency access to DynamoDB. This configuration meets the requirement of handling varying loads while maintaining the existing API model.

AWS AppSync is more suited for GraphQL APIs, and while it can run on AWS Lambda and use Aurora Serverless, it does not fit the requirement of maintaining a REST API without modifications. Aurora Serverless can provide better data access but does not align with the required API model.

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