An application ingests a large number of small messages and stores them in a database. The application uses AWS Lambda. A Development team is making change to the application's processing logic. In testing, it is taking more than 15 minutes to process each message. The team is concerned the current backend may time out. Which changes should be made to the backend system to ensure each message is processed in the MOST scalable way?
A) Add the messages to an Amazon SQS queue. Set up and Amazon EC2 instance to poll the queue and process messages as they arrive.
B) Add the messages to an Amazon SQS queue. Set up Amazon EC2 instances in an Auto Scaling group to poll the queue and process the messages as they arrive.
C) Create a support ticket to increase the Lambda timeout to 60 minutes to allow for increased processing time.
D) Change the application to directly insert the body of the message into an Amazon RDS database.

Question

Quizplus · Accepted Answer

Using Amazon SQS with EC2 instances in an Auto Scaling group allows for scalable processing of messages, as the number of instances can automatically adjust based on the queue length, preventing timeouts and handling large volumes efficiently.

An Application Ingests a Large Number of Small Messages and Stores