Amazon Exam DOP-C02 Topic 2 Question 32 Discussion

Actual exam question for Amazon's DOP-C02 exam

Question #: 32
Topic #: 2

A company releases a new application in a new AWS account. The application includes an AWS Lambda function that processes messages from an Amazon Simple Queue Service (Amazon SOS) standard queue. The Lambda function stores the results in an Amazon S3 bucket for further downstream processing. The Lambda function needs to process the messages within a specific period of time after the messages are published. The Lambda function has a batch size of 10 messages and takes a few seconds to process a batch of messages.

As load increases on the application's first day of service, messages in the queue accumulate at a greater rate than the Lambda function can process the messages. Some messages miss the required processing timelines. The logs show that many messages in the queue have data that is not valid. The company needs to meet the timeline requirements for messages that have valid data.

Which solution will meet these requirements?

AIncrease the Lambda function's batch size. Change the SOS standard queue to an SOS FIFO queue. Request a Lambda concurrency increase in the AWS Region.

BReduce the Lambda function's batch size. Increase the SOS message throughput quota. Request a Lambda concurrency increase in the AWS Region.

CIncrease the Lambda function's batch size. Configure S3 Transfer Acceleration on the S3 bucket. Configure an SOS dead-letter queue.

DKeep the Lambda function's batch size the same. Configure the Lambda function to report failed batch items. Configure an SOS dead-letter queue.
Step 1: Handling Invalid Data with Failed Batch Items
The Lambda function is processing batches of messages, and some messages contain invalid data, causing processing delays. Lambda provides the capability to report failed batch items, which allows valid messages to be processed while skipping invalid ones. This functionality ensures that the valid messages are processed within the required timeline.
Action: Keep the Lambda function's batch size the same and configure it to report failed batch items.
Why: By reporting failed batch items, the Lambda function can skip invalid messages and continue processing valid ones, ensuring that they meet the processing timeline.

Show Suggested Answer

Suggested Answer: D

Step 2: Using an SQS Dead-Letter Queue (DLQ) Configuring a dead-letter queue (DLQ) for SQS will ensure that messages with invalid data, or those that cannot be processed successfully, are moved to the DLQ. This prevents such messages from clogging the queue and allows the system to focus on processing valid messages.

Action: Configure an SQS dead-letter queue for the main queue.

Why: A DLQ helps isolate problematic messages, preventing them from continuously reappearing in the queue and causing processing delays for valid messages.

Step 3: Maintaining the Lambda Function's Batch Size Keeping the current batch size allows the Lambda function to continue processing multiple messages at once. By addressing the failed items separately, there's no need to increase or reduce the batch size.

Action: Maintain the Lambda function's current batch size.

Why: Changing the batch size is unnecessary if the invalid messages are properly handled by reporting failed items and using a DLQ.

This corresponds to Option D: Keep the Lambda function's batch size the same. Configure the Lambda function to report failed batch items. Configure an SQS dead-letter queue.

by Catarina at Aug 22, 2024, 02:18 PM

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Jaime

3 months ago

Yes, that sounds like a comprehensive solution to meet the requirements.

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Lucia

3 months ago

We should also request a Lambda concurrency increase in the AWS Region for better performance.

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Stanford

3 months ago

Yo, this is a no-brainer! Option D is the way to go. Shoutout to the Lambda team for that failed batch item feature. It's like having a cheat code for your code!

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Herminia

3 months ago

Hmm, I'm not sure about the other options. Increasing the batch size or changing the queue type might not solve the issue of invalid data. D looks like the most logical choice here.

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Margret

3 months ago

I agree. Reporting failed batch items will help ensure valid messages are processed on time.

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Janessa

3 months ago

I think D is the best option. It addresses the issue of invalid data.

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Deja

3 months ago

I agree with Lorrine. The dead-letter queue is a great way to handle the invalid messages and ensure the valid ones are processed in time.

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4 months ago

I think we should increase the Lambda function's batch size.

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