SAA-C03 Q286 · Serverless

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?

Accepted Answer

**Option A** satisfies every requirement:

1. **No data loss**: A **Dead-Letter Queue (DLQ)** backed by Amazon SQS captures records that Lambda fails to process after its built-in retry attempts. Failed records are not discarded — they are preserved in the SQS queue for later processing.

2. **Recovery from failures**: Lambda natively retries asynchronous invocations **twice** before sending the event to the DLQ. By configuring a separate Lambda function (or the same function) to consume from the DLQ, failed records get reprocessed.

3. **Exponential backoff**: Implementing an exponential backoff algorithm prevents overwhelming downstream services (like DynamoDB) during transient failures. This is an AWS-recommended best practice for retries, reducing the chance of cascading failures due t

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