← DVA-C02·Amazon Web Services

Question 945 of 1,616

Troubleshooting and Optimization →hardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to increase both the batch size to 100 and the reserved concurrency to a higher value. This is the most effective way to optimize Lambda SQS throughput because it directly addresses the two primary bottlenecks: the batch size limits how many messages are processed per invocation, and reserved concurrency caps the number of parallel invocations. With a batch size of 10 and concurrency of 5, the maximum throughput is only 50 messages per second (10 × 5), but raising the batch size to 100 allows each invocation to handle more messages, while increasing concurrency enables more parallel processing—together eliminating throttling without exceeding account-level limits. On the AWS Certified Developer Associate DVA-C02 exam, this scenario tests your understanding of Lambda’s integration with SQS, specifically how batch size and concurrency interact to drive throughput; a common trap is assuming that increasing only one parameter is sufficient. Remember the memory tip: “Batch for bulk, concurrency for crowd”—both must scale together to clear a backlog.

DVA-C02 Troubleshooting and Optimization Practice Question

This DVA-C02 practice question tests your understanding of troubleshooting and optimization. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 using AWS Lambda with a function that processes messages from an SQS queue. The function is configured with a batch size of 10 and reserved concurrency of 5. The queue has a large backlog, and messages are being throttled, leading to retries and eventual DLQ. The function is idempotent and can handle up to 100 messages per invocation. What is the most effective way to increase throughput without increasing throttling?

Question 1hardmultiple choice

Full question →

A
Increase reserved concurrency to 100
Why wrong: This increases the number of concurrent invocations, which can lead to more throttling if the function cannot handle the rate. Without increasing batch size, each invocation processes only 10 messages, so throughput increase is limited.
B
Increase batch size to 100
Why wrong: This reduces the number of invocations, but with only 5 reserved concurrency, the total throughput may still be limited. The function can process 100 messages per invocation, but the concurrency cap restricts how many invocations can run simultaneously.
C
Increase both batch size to 100 and reserved concurrency to a higher value
Increasing batch size reduces the number of invocations, lowering throttling risk. Increasing reserved concurrency allows more invocations to run concurrently, fully utilizing the function's capacity. This combination maximizes throughput without causing excessive throttling.
D
Decrease batch size to 1 and increase reserved concurrency to 50
Why wrong: Decreasing batch size increases the number of invocations, which would increase throttling risk under the same concurrency limits. This approach is counterproductive.

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 both batch size to 100 and reserved concurrency to a higher value

Option C is correct because increasing both the batch size to 100 and the reserved concurrency to a higher value directly addresses the two bottlenecks: the batch size limits how many messages are processed per invocation, and reserved concurrency limits how many concurrent invocations can run. With a batch size of 10 and reserved concurrency of 5, the maximum messages processed per second is 50 (10 × 5), assuming each invocation takes 1 second. Increasing batch size to 100 allows each invocation to process more messages, reducing the number of invocations needed, while increasing reserved concurrency allows more parallel processing, together eliminating throttling without exceeding Lambda's account-level concurrency limits.

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 reserved concurrency to 100
Why it's wrong here
This increases the number of concurrent invocations, which can lead to more throttling if the function cannot handle the rate. Without increasing batch size, each invocation processes only 10 messages, so throughput increase is limited.
✗
Increase batch size to 100
Why it's wrong here
This reduces the number of invocations, but with only 5 reserved concurrency, the total throughput may still be limited. The function can process 100 messages per invocation, but the concurrency cap restricts how many invocations can run simultaneously.
✓
Increase both batch size to 100 and reserved concurrency to a higher value
Why this is correct
Increasing batch size reduces the number of invocations, lowering throttling risk. Increasing reserved concurrency allows more invocations to run concurrently, fully utilizing the function's capacity. This combination maximizes throughput without causing excessive throttling.
Related concept
Read the scenario before looking for a memorised answer.
✗
Decrease batch size to 1 and increase reserved concurrency to 50
Why it's wrong here
Decreasing batch size increases the number of invocations, which would increase throttling risk under the same concurrency limits. This approach is counterproductive.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often think increasing reserved concurrency alone is sufficient to handle a large backlog, but they overlook that the batch size limits how many messages are processed per invocation, and without increasing both, the function may still be throttled due to excessive invocations or hitting account-level concurrency limits.

Detailed technical explanation

How to think about this question

AWS Lambda integrates with SQS via event source mapping, which uses a long poll to retrieve messages from the queue. The batch size determines the maximum number of messages in a single event payload, and the reserved concurrency sets a per-function limit on concurrent executions. Under the hood, Lambda's SQS event source mapping uses a polling loop that respects the batch window and batch size; increasing both allows the function to consume messages faster without hitting the concurrency cap. In real-world scenarios, a common mistake is to only increase concurrency, which can lead to throttling at the account level (default 1000 concurrent executions) and increased costs due to more invocations, whereas increasing batch size reduces the number of invocations and improves cost efficiency.

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.

Related DVA-C02 practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

Development with AWS Services practice questions

Practise DVA-C02 questions linked to Development with AWS Services.

Security practice questions

Practise DVA-C02 questions linked to Security.

Deployment practice questions

Practise DVA-C02 questions linked to Deployment.

Troubleshooting and Optimization practice questions

Practise DVA-C02 questions linked to Troubleshooting and Optimization.

DVA-C02 fundamentals practice questions

Practise DVA-C02 questions linked to DVA-C02 fundamentals.

DVA-C02 scenario practice questions

Practise DVA-C02 questions linked to DVA-C02 scenario.

DVA-C02 troubleshooting practice questions

Practise DVA-C02 questions linked to DVA-C02 troubleshooting.

Practice this exam

Start a free DVA-C02 practice session

Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.

10 questions 20 questions 30 questions 50 questions Timed 30

DVA-C02 practice-test guide →Study guide →Browse all practice tests

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 both batch size to 100 and reserved concurrency to a higher value — Option C is correct because increasing both the batch size to 100 and the reserved concurrency to a higher value directly addresses the two bottlenecks: the batch size limits how many messages are processed per invocation, and reserved concurrency limits how many concurrent invocations can run. With a batch size of 10 and reserved concurrency of 5, the maximum messages processed per second is 50 (10 × 5), assuming each invocation takes 1 second. Increasing batch size to 100 allows each invocation to process more messages, reducing the number of invocations needed, while increasing reserved concurrency allows more parallel processing, together eliminating throttling without exceeding Lambda's account-level concurrency limits.

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.

About these practice questions

Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

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. An AWS Lambda function that processes messages from an SQS queue is experiencing throttling (TooManyRequestsException). The function has reserved concurrency set to 100. The SQS queue has a redrive policy configured with maxReceiveCount of 5. CloudWatch metrics show that the function's concurrent executions occasionally spike to 100, and throttling occurs. The function execution time averages 2 seconds. What is the most effective way to reduce throttling?

hard

✓ A.Increase the batch size of the SQS event source mapping
B.Increase the reserved concurrency of the Lambda function
C.Decrease the batch window of the event source mapping
D.Add a dead-letter queue (DLQ) for the Lambda function

Why A: Increasing the batch size allows the Lambda function to process more messages per invocation, reducing the number of concurrent executions needed to handle the same message volume. Since the function already spikes to its reserved concurrency of 100, processing more messages per batch lowers the invocation rate and thus reduces throttling without requiring additional concurrency.

Keep practising

Question Discussion

Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.

Loading comments…

This DVA-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DVA-C02 exam.