A Company Runs an Ordering System on AWS Using Amazon

A company runs an ordering system on AWS using Amazon SQS and AWS Lambda, with each order received as a JSON message. Recently the company had a marketing event that led to a tenfold increase in orders. With this increase, the following undesired behaviors started in the ordering system: Lambda failures while processing orders lead to queue backlogs. The same orders have been processed multiple times. A Solutions Architect has been asked to solve the existing issues with the ordering system and add the following resiliency features: Retain problematic orders for analysis. Send notification if errors go beyond a threshold value. How should the Solutions Architect meet these requirements?

A) Receive multiple messages with each Lambda invocation, add error handling to message processing code and delete messages after processing, increase the visibility timeout for the messages, create a dead letter queue for messages that could not be processed, create an Amazon CloudWatch alarm on Lambda errors for notification.
B) Receive single messages with each Lambda invocation, put additional Lambda workers to poll the queue, delete messages after processing, increase the message timer for the messages, use Amazon CloudWatch Logs for messages that could not be processed, create a CloudWatch alarm on Lambda errors for notification.
C) Receive multiple messages with each Lambda invocation, use long polling when receiving the messages, log the errors from the message processing code using Amazon CloudWatch Logs, create a dead letter queue with AWS Lambda to capture failed invocations, create CloudWatch events on Lambda errors for notification.
D) Receive multiple messages with each Lambda invocation, add error handling to message processing code and delete messages after processing, increase the visibility timeout for the messages, create a delay queue for messages that could not be processed, create an Amazon CloudWatch metric on Lambda errors for notification.