AWS Certified Developer Associate DVA-C02 Practice Question
Given an application that processes a high volume of messages and requires a resilient architecture to manage potential processing bottlenecks, which approach would most effectively guarantee no loss of messages and facilitate recovery for messages that could not be processed after multiple attempts?
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Deploy an Amazon Kinesis stream and attach a Lambda function to process the streamed records, ensuring the function has robust exception handling.
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Create an SQS Delay Queue to postpone the delivery of new messages and give the system time to recover from any current processing delay.
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Set up an Amazon SQS queue and configure a dead-letter queue (DLQ) to catch messages that fail to be processed after a certain number of attempts.
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Apply a backoff retry strategy on a Lambda function triggered by message arrival, ensuring that temporary processing issues are mitigated.
Implementing an Amazon Kinesis stream with a corresponding Lambda function as a processor is a good starting point; however, it doesn't provide a built-in solution for handling messages that fail processing after several attempts. Using an Amazon SQS queue with a properly configured dead-letter queue (DLQ) offers the best approach, as it explicitly handles failed message processing by moving them to the DLQ after a predefined number of attempts, thereby preventing message loss and allowing for future inspection or reprocessing. Enabling backoff retry strategies on a Lambda function without a DLQ does offer some temporary resilience but eventually may lead to message loss if the issue persists. Similarly, implementing an SQS Delay Queue does not inherently handle failed processing attempts, but only delays message visibility to consumers.
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AWS Certified Developer Associate DVA-C02
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