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Question 741 of 1,616

Troubleshooting and Optimization →mediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is to increase the Lambda function’s batch size. This is correct because raising the batch size allows each invocation to process more messages from the SQS queue, directly reducing the number of concurrent invocations needed to clear a backlog. Since the function already processes a batch in about 5 seconds and the visibility timeout is 30 seconds, there is ample room to handle larger batches without timing out, which lowers the throttle count without requiring additional reserved concurrency. On the AWS Certified Developer Associate DVA-C02 exam, this scenario tests your understanding of how Lambda concurrency and SQS batch size interact—a common trap is to request more reserved concurrency, but the most efficient fix is to optimize the batch size first. Remember the memory tip: “Bigger batches, fewer throttles”—when you see high throttles and a fast processing time, always consider increasing the batch size before scaling concurrency.

DVA-C02 Troubleshooting and Optimization Practice Question

This DVA-C02 practice question tests your understanding of troubleshooting and optimization. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A developer is monitoring an AWS Lambda function that processes messages from an SQS queue. CloudWatch metrics show that the function's throttles are high when the queue backlog grows. The function has a reserved concurrency of 50 and a batch size of 10. The SQS queue has a visibility timeout of 30 seconds. The function processes each batch in about 5 seconds. Which action will most effectively reduce throttles?

Question 1mediummultiple choice

Full question →

A
Increase the SQS queue visibility timeout
Why wrong: The visibility timeout controls how long a message is invisible after being received, but it does not affect the number of concurrent Lambda invocations or throttle rate.
B
Increase the Lambda function's reserved concurrency
Why wrong: Increasing reserved concurrency raises the limit on concurrent executions, which might reduce throttles if the limit is the bottleneck. However, it does not address the volume of messages; increasing batch size is more efficient.
C
Increase the Lambda function's batch size
Increasing the batch size reduces the number of invocations needed to process the same number of messages, thereby reducing the number of concurrent executions and decreasing throttles.
D
Decrease the SQS queue message retention period
Why wrong: Decreasing message retention period drops messages sooner, which may reduce backlog but is not a direct solution for throttles and could cause data loss.

Full breakdown with real-world context →

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Increase the Lambda function's batch size

Option C is correct because increasing the batch size allows each Lambda invocation to process more messages per batch (e.g., from 10 to a higher value up to 10,000 for standard queues). This reduces the number of concurrent invocations needed to clear the backlog, directly lowering the throttle count without requiring additional reserved concurrency. Since the function processes each batch in ~5 seconds and the visibility timeout is 30 seconds, there is ample time to handle larger batches, making this the most effective adjustment.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Increase the SQS queue visibility timeout
Why it's wrong here
The visibility timeout controls how long a message is invisible after being received, but it does not affect the number of concurrent Lambda invocations or throttle rate.
✗
Increase the Lambda function's reserved concurrency
Why it's wrong here
Increasing reserved concurrency raises the limit on concurrent executions, which might reduce throttles if the limit is the bottleneck. However, it does not address the volume of messages; increasing batch size is more efficient.
✓
Increase the Lambda function's batch size
Why this is correct
Increasing the batch size reduces the number of invocations needed to process the same number of messages, thereby reducing the number of concurrent executions and decreasing throttles.
Related concept
Read the scenario before looking for a memorised answer.
✗
Decrease the SQS queue message retention period
Why it's wrong here
Decreasing message retention period drops messages sooner, which may reduce backlog but is not a direct solution for throttles and could cause data loss.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often assume throttles are always solved by increasing concurrency (Option B), overlooking that batch size optimization can achieve the same throughput with fewer invocations, which is more efficient and directly addresses the backlog-driven throttle pattern.

Detailed technical explanation

How to think about this question

Lambda's batch size for SQS is controlled by the `BatchSize` parameter (default 10, max 10,000 for standard queues). When the batch size is increased, each invocation pulls more messages, reducing the number of concurrent executions needed to drain the queue. This is particularly effective when the function's processing time per message is low (here ~0.5 seconds per message), as the total execution time remains well within the visibility timeout, avoiding duplicate processing. In real-world scenarios, this optimization also reduces downstream API call overhead and can improve cost efficiency by lowering the number of invocations.

KKey Concepts to Remember

Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.

TExam Day Tips

Watch for words such as best, first, most likely and least administrative effort.
Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this DVA-C02 question test?

Troubleshooting and Optimization — This question tests Troubleshooting and Optimization — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Increase the Lambda function's batch size — Option C is correct because increasing the batch size allows each Lambda invocation to process more messages per batch (e.g., from 10 to a higher value up to 10,000 for standard queues). This reduces the number of concurrent invocations needed to clear the backlog, directly lowering the throttle count without requiring additional reserved concurrency. Since the function processes each batch in ~5 seconds and the visibility timeout is 30 seconds, there is ample time to handle larger batches, making this the most effective adjustment.

What should I do if I get this DVA-C02 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Same concept, more angles

1 more ways this is tested on DVA-C02

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A developer is troubleshooting an AWS Lambda function that is failing with a timeout error. The function has a 15-minute timeout and processes messages from an Amazon SQS queue. Which TWO actions should the developer take to resolve the issue?

easy

A.Reduce the SQS visibility timeout.
B.Increase the Lambda function timeout to 15 minutes.
✓ C.Increase the SQS batch size in the Lambda event source mapping.
D.Configure a dead-letter queue for the SQS queue.
✓ E.Use SQS batch operations in the Lambda function to process multiple messages at once.

Why C: Options A and D are correct. A: Increasing batch size reduces the number of invocations, but each invocation processes more messages quickly. D: Using SQS batch operations can improve throughput. Option B is wrong because dead-letter queue is for failed messages after retries. Option C is wrong because reducing visibility timeout would cause more retries. Option E is wrong because Lambda can have up to 15 minutes; the issue is processing speed.

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