Your organization uploads relatively large compressed files ranging between 100MB – 200MB in size to AWS S3 bucket. Once uploaded, they are looking to calculate the total number objects in the compressed file and add the total count as a metadata to the compressed file in AWS S3. They approached you for a cost-effective solution. You have recommended using AWS Lambda through S3 event notifications to perform this operation. However, they were concerned about failures as S3 event notification is an asynchronous one-time trigger and Lambda can fail due to operation time outs, max memory limits, max execution time limits etc. What is the best retry approach you recommend?

Answer options:

A.All the failed events will be logged to CloudWatch. You can manually retrigger failed events.
B.Configure Dead-letter queue with SQS. Configure SQS to trigger Lambda function again.
C.All failures will be caught during exception inside Lambda function. Trigger lambda function inside lambda function code to process failed event.
D.Enable Active tracing using AWS X-Ray. It will automatically retrigger failed events.

Answer: B
Option A is not recommended approach. Although you can configure logging to CloudWatch, it is difficult to find the specific failure logs. Manual retries are not a best practice in an enterprise level solution designs.
Option B is correct. You can forward non-processed or failed payloads to Dead Letter Queue
(DLQ) using AWS SQS, AWS SNS.
https://aws.amazon.com/blogs/compute/robust-serverless-application-design-with-aws-lambda-dlq/
Option C is not correct. Max memory limit and max execution time limit gets terminated without being caught in the handler exception.
 Option D is not correct. Active tracing option can be used for detailed logging. It will not retry failed events.
https://docs.aws.amazon.com/lambda/latest/dg/lambda-x-ray.html