Question
An ecommerce company is receiving reports that its order history page is experiencing delays in reflecting the processing status of orders. The order processing system consists of an AWS Lambda function that uses reserved concurrency. The Lambda function processes order messages from an Amazon Simple Queue Service (Amazon SQS) queue and inserts processed orders into an Amazon DynamoDB table. The DynamoDB table has auto scaling enabled for read and write capacity.
Which actions should a DevOps engineer take to resolve this delay? (Choose two.)
- A. Check the ApproximateAgeOfOldestMessage metric for the SQS queue. Increase the Lambda function concurrency limit. Correct
- B. Check the ApproximateAgeOfOldestMessage metric for the SQS queue. Configure a redrive policy on the SQS queue.
- C. Check the NumberOfMessagesSent metric for the SQS queue. Increase the SQS queue visibility timeout.
- D. Check the WriteThrottleEvents metric for the DynamoDB table. Increase the maximum write capacity units (WCUs) for the table's scaling policy. Correct
- E. Check the Throttles metric for the Lambda function. Increase the Lambda function timeout.
Explanation
Option A is correct because checking the ApproximateAgeOfOldestMessage metric helps identify if messages are not being processed promptly, and increasing the Lambda concurrency limit can help process more messages simultaneously. Option D is correct as it involves monitoring WriteThrottleEvents to ensure that DynamoDB writes do not throttle, and adjusting the auto-scaling policy's maximum write capacity units (WCUs) ensures sufficient write throughput.
