A company has built a serverless application for its ecommerce website. The application includes a REST API in Amazon API Gateway that invokes an AWS Lambda function. The

Lambda function processes data and stores the data in a Amazon DynamoDB table. The Lambda function calls a third$-$party stock application API to process the order. After the ordered

is processed, the Lambda function returns an HTTP $200$ status code with no body to the client.

During peak usage when the API calls exceeds a certain threshold, the third$-$party stock application sometimes fails to process the data and responds with error messages. The

company needs a solution that will not overwhelm the third$-$party stock application.

Which solution will meet these requirements?

A$.$ Configure the REST API in API Gateway to write the requests directly into DynamoDB. Configure a DynamoDB intrinsic function to perform the transformation. Set up a

DynamoDB stream to call the third$-$party stock application API with each new row. Delete the Lambda function.

B$.$ Configure the RESTAPI in API Gateway to write the requests directly into an Amazon Simple Queue Service $($Amazon SQS$)$ queue. Configure the Lambda function with a

reserved concurrency equal to the third$-$party stock application's threshold. Set Lambda function to process the messages from the SQS queue.

C$.$ Configure the REST API in API Gateway to write the requests directly into an Amazon Simple Notification Service $($Amazon SNS$)$ topic. Configure the Lambda function with

a provisioned concurrency equal to the third$-$party stock application's threshold. Set the Lambda function to process the messages from the SNS topic.

D$.$ Configure the REST API in API Gateway to write the requests directly into Amazon Athena. Configure the transformation of the data by using SQL with multiple query result

locations set up to point to the DynamoDB table and the third$-$party stock fulfilment application API. Delete the Lambda function.