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AWS SAP-C02 · Question 40 · Domain 2.4: Reliability
An architect is designing a serverless data processing pipeline. Amazon S3 events trigger an AWS Lambda function, which processes the data and writes to Amazon DynamoDB. The Lambda function occasionally fails due to downstream throttling. How can the architect ensure no data is lost during these failures with the LEAST operational overhead?
An architect is designing a serverless data processing pipeline. Amazon S3 events trigger an AWS Lambda function, which processes the data and writes to Amazon DynamoDB. The Lambda function occasionally fails due to downstream throttling. How can the architect ensure no data is lost during these failures with the LEAST operational overhead?
Answer options:
A.
Write custom retry logic within the Lambda function code.
B.
Configure an Amazon SQS Dead-Letter Queue (DLQ) or an On-Failure destination for the Lambda function.
C.
Use AWS Step Functions to orchestrate the S3 to Lambda invocation.
D.
Increase the memory and timeout settings of the Lambda function.
How to approach this question
Identify the native AWS mechanism for handling failed asynchronous Lambda invocations.
Full Answer
B.Configure an Amazon SQS Dead-Letter Queue (DLQ) or an On-Failure destination for the Lambda function.✓ Correct
Configure an Amazon SQS Dead-Letter Queue (DLQ) or an On-Failure destination for the Lambda function.
For asynchronous invocations, Lambda retries failures automatically. If all retries fail, configuring a Dead-Letter Queue (DLQ) or an On-Failure destination ensures the event is saved for manual analysis or reprocessing.
Common mistakes
Writing custom retry logic, which is an anti-pattern for asynchronous Lambda invocations.
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