← DVA-C02·Amazon Web Services

Question 154 of 1,616

Development with AWS Services →hardMultiple ChoiceObjective-mapped

Handling Large Payloads in AWS Lambda Without Increasing Timeout

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 developer is debugging a Lambda function that is triggered by an S3 event. The function is supposed to process images and store metadata in DynamoDB. However, the function times out after 3 seconds for large images. The function's timeout is currently set to 5 seconds. What should the developer do to resolve the issue without increasing the timeout?

A
Increase the Lambda function's memory allocation to improve performance.
Increasing memory allocation boosts CPU and network resources, reducing processing time for compute-intensive tasks, allowing the function to complete within the existing timeout.
B
Increase the Lambda function's timeout to 15 minutes.
Why wrong: Increasing the timeout is explicitly prohibited by the question, and even if allowed, it would not address the root cause of slow processing.
C
Use multipart upload or stream processing to handle the image in chunks.
Why wrong: Multipart upload or stream processing are for uploading large files to S3, not for processing images inside a Lambda function. They would not reduce processing time for the image transformation itself.
D
Offload the processing to an Amazon SQS queue and process asynchronously.
Why wrong: Offloading to SQS processes asynchronously, but the Lambda function itself would still complete quickly; it does not solve the timeout issue within the function.

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 memory allocation to improve performance.

Option A is correct because increasing the Lambda function's memory allocation also increases CPU and network performance, which can reduce execution time for CPU-bound or memory-bound tasks like image processing. This allows the function to complete within the current timeout without increasing the timeout value. Option C, multipart upload or stream processing, is not directly applicable to processing images within a Lambda function; it applies to uploading large objects to S3, not to processing within Lambda. Option B increases timeout, which is explicitly prohibited. Option D introduces asynchronous processing via SQS, but that does not address the timeout issue within the function itself.

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 Lambda function's memory allocation to improve performance.
Why this is correct
Increasing memory allocation boosts CPU and network resources, reducing processing time for compute-intensive tasks, allowing the function to complete within the existing timeout.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the Lambda function's timeout to 15 minutes.
Why it's wrong here
Increasing the timeout is explicitly prohibited by the question, and even if allowed, it would not address the root cause of slow processing.
✗
Use multipart upload or stream processing to handle the image in chunks.
Why it's wrong here
Multipart upload or stream processing are for uploading large files to S3, not for processing images inside a Lambda function. They would not reduce processing time for the image transformation itself.
✗
Offload the processing to an Amazon SQS queue and process asynchronously.
Why it's wrong here
Offloading to SQS processes asynchronously, but the Lambda function itself would still complete quickly; it does not solve the timeout issue within the function.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap is that candidates often think increasing memory only helps with memory errors, but AWS Lambda also allocates CPU proportionally to memory, so increasing memory can reduce execution time for CPU-bound tasks. Additionally, options like multipart upload may seem relevant but are actually for different scenarios.

Detailed technical explanation

How to think about this question

Under the hood, Lambda functions have a maximum invocation payload size of 6 MB for synchronous and 256 KB for asynchronous invocations, but large images (e.g., >50 MB) can cause timeouts due to memory and CPU constraints. Multipart upload splits the image into parts (e.g., 5 MB each) and processes each part independently, leveraging S3's multipart upload API (ETag and part numbers) to reassemble metadata later. In real-world scenarios, this pattern is common for video transcoding or large file processing where streaming or chunking avoids Lambda's 15-minute timeout limit.

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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

Visual reference

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

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?

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 Lambda function's memory allocation to improve performance. — Option A is correct because increasing the Lambda function's memory allocation also increases CPU and network performance, which can reduce execution time for CPU-bound or memory-bound tasks like image processing. This allows the function to complete within the current timeout without increasing the timeout value. Option C, multipart upload or stream processing, is not directly applicable to processing images within a Lambda function; it applies to uploading large objects to S3, not to processing within Lambda. Option B increases timeout, which is explicitly prohibited. Option D introduces asynchronous processing via SQS, but that does not address the timeout issue within the function itself.

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. A developer is writing an AWS Lambda function in Python that needs to download a file from Amazon S3, process it, and upload the result to a different S3 bucket. The function currently runs within the default 3-second timeout, but the developer expects the file size to increase. What is the MOST cost-effective way to handle the increase in processing time?

easy

✓ A.Increase the Lambda function's timeout to a value higher than the expected processing time.
B.Increase the Lambda function's timeout to 15 minutes.
C.Use Lambda provisioned concurrency to keep the function warm.
D.Refactor the code to use AWS Step Functions to orchestrate the processing.

Why A: Increasing the Lambda function's timeout is the most cost-effective solution because it directly addresses the expected increase in processing time without incurring additional costs. Lambda pricing is based on the number of invocations and duration (in GB-seconds), so extending the timeout only charges for the actual time the function runs, not for idle time or additional services. This approach avoids the complexity and cost of Step Functions or provisioned concurrency, which would add unnecessary overhead for a simple sequential task.

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.