A company has designed an application where users provide small sets of textual data by calling a public API. The application runs on AWS and includes a public Amazon API Gateway API that forwards requests to an AWS Lambda function for processing. The Lambda function then writes the data to an Amazon Aurora Serverless database for consumption.
The company is concerned that it could lose some user data if a Lambda function fails to process the request properly or reaches a concurrency limit.
What should a solutions architect recommend to resolve this concern?
A. Split the existing Lambda function into two Lambda functions. Configure one function to receive API Gateway requests and put relevant items into Amazon Simple Queue Service (Amazon SQS).
Configure the other function to read items from Amazon SQS and save the data into Aurora.
B. Configure the Lambda function to receive API Gateway requests and write relevant items to Amazon ElastiCache. Configure ElastiCache to save the data into Aurora.
C. Increase the memory for the Lambda function. Configure Aurora to use the Multi-AZ feature.
D. Split the existing Lambda function into two Lambda functions. Configure one function to receive API Gateway requests and put relevant items into Amazon Simple Notification Service (Amazon SNS). Configure the other function to read items from Amazon SNS and save the data into Aurora.
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