- A
Increase the batch size in the event source mapping.
Increasing batch size allows more messages per invocation, directly improving throughput.
- B
Increase the visibility timeout of the SQS queue.
Why wrong: Increasing visibility timeout helps prevent duplicate processing but does not increase throughput.
- C
Decrease the batch size in the event source mapping.
Why wrong: Decreasing batch size reduces the number of messages per invocation, decreasing throughput.
- D
Increase the reserved concurrency of the Lambda function.
Why wrong: Increasing reserved concurrency does not increase the number of messages processed per invocation.
Question 786 of 1,616
Lambda SQS Batch Size for Throughput
This DVA-C02 practice question tests your understanding of development with aws services. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 company uses AWS Lambda to process incoming messages from an Amazon SQS queue. The Lambda function sometimes fails with a timeout error when the queue has a large backlog. What is the MOST efficient way to increase throughput without causing duplicate processing?
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 batch size in the event source mapping.
Increasing the batch size in the event source mapping allows the Lambda function to retrieve and process more messages per invocation from the SQS queue. This directly increases throughput by reducing the number of Lambda invocations needed to clear the backlog, and it does not cause duplicate processing because SQS messages are deleted only after the function successfully processes the batch.
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 batch size in the event source mapping.
Why this is correct
Increasing batch size allows more messages per invocation, directly improving throughput.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the visibility timeout of the SQS queue.
Why it's wrong here
Increasing visibility timeout helps prevent duplicate processing but does not increase throughput.
- ✗
Decrease the batch size in the event source mapping.
Why it's wrong here
Decreasing batch size reduces the number of messages per invocation, decreasing throughput.
- ✗
Increase the reserved concurrency of the Lambda function.
Why it's wrong here
Increasing reserved concurrency does not increase the number of messages processed per invocation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume increasing concurrency (Option D) is the best way to handle a backlog, but they overlook that concurrency increases can lead to duplicate processing when functions timeout, whereas adjusting the batch size directly improves efficiency without that risk.
Detailed technical explanation
How to think about this question
Lambda polls the SQS queue in batches of up to 10 messages by default (maximum batch size is 10). When a large backlog exists, increasing the batch size to the maximum (10) ensures each invocation processes more messages, reducing the total number of invocations and the overhead of polling. The function's timeout error is likely caused by the cumulative processing time of many small batches; larger batches can reduce the number of invocations and thus the total time spent on overhead, but the function's timeout setting may also need adjustment if individual message processing is slow.
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.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DVA-C02 question test?
Development with AWS Services — This question tests Development with AWS Services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the batch size in the event source mapping. — Increasing the batch size in the event source mapping allows the Lambda function to retrieve and process more messages per invocation from the SQS queue. This directly increases throughput by reducing the number of Lambda invocations needed to clear the backlog, and it does not cause duplicate processing because SQS messages are deleted only after the function successfully processes the batch.
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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Last reviewed: Jul 4, 2026
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.
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