SAA-C03 · Question #279
A company is building a serverless application that processes large volumes of data from a mobile app. The application uses an AWS Lambda function to process the data and store the data in an Amazon…
The correct answer is A. Configure the Lambda function to use a dead-letter queue with an Amazon Simple Queue Service. Dead-letter queues (DLQs) with Amazon SQS allow Lambda functions to offload failed events for later inspection or retry. Using retry logic with exponential backoff ensures resilience and compliance with best practices for fault-tolerant serverless architectures. This guarantees…
Question
A company is building a serverless application that processes large volumes of data from a mobile app. The application uses an AWS Lambda function to process the data and store the data in an Amazon DynamoDB table. The company needs to ensure that the application can recover from failures and continue processing data without losing any records. Which solution will meet these requirements?
Options
- AConfigure the Lambda function to use a dead-letter queue with an Amazon Simple Queue Service
- BConfigure the Lambda function to read records from Amazon Data Firehose. Replay the Firehose
- CUse Amazon OpenSearch Service to store failed records. Configure AWS Lambda to retry failed
- DUse Amazon Simple Notification Service (Amazon SNS) to store the failed records. Configure
How the community answered
(43 responses)- A91% (39)
- B2% (1)
- C5% (2)
- D2% (1)
Explanation
Dead-letter queues (DLQs) with Amazon SQS allow Lambda functions to offload failed events for later inspection or retry. Using retry logic with exponential backoff ensures resilience and compliance with best practices for fault-tolerant serverless architectures. This guarantees no data is lost due to transient errors.
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