Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A developer is troubleshooting an AWS Lambda function that processes records from an Amazon Kinesis Data Stream. The function is configured with a batch size of 100 and a parallelization factor of 1. The developer notices that the function is processing records slowly, and the iterator age is increasing. CloudWatch Logs show that the function is not experiencing errors or throttling, but the execution time per invocation is close to the 5-minute timeout. The stream has 10 shards. What is the most cost-effective way to increase processing throughput?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Increase the batch size to 1000
A larger batch size may increase execution time further, potentially causing the function to exceed the timeout. It does not address the per-record processing bottleneck.
B
Best answer
Increase the parallelization factor to 10
The parallelization factor determines the number of concurrent Lambda invocations per shard. Increasing it allows multiple invocations to process records from the same shard simultaneously, dramatically increasing throughput without additional shard costs.
C
Distractor review
Increase the memory of the Lambda function
Increasing memory may improve performance if the function is CPU-bound, but it is not guaranteed and increases cost. The function is already near its timeout, indicating a potential bottleneck in record processing logic.
D
Distractor review
Split the stream into more shards
Splitting the stream increases the number of shards, leading to more Lambda invocations but also higher Kinesis costs. This is less cost-effective than increasing the parallelization factor.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Related practice questions
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.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A developer is building a REST API using Amazon API Gateway that will serve static content from an Amazon S3 bucket. The API should cache responses for frequently accessed objects to reduce latency. Which API Gateway feature should the developer enable?
Question 2
A developer is running a web application on multiple Amazon EC2 instances behind an Application Load Balancer (ALB). The application needs to store user session state that must be available across all instances. The session data is small and temporary but must survive individual instance failures. Which AWS service should the developer use to store this session state?
Question 3
A developer has an AWS Lambda function that processes messages from an Amazon SQS standard queue. The function is idempotent and currently has a batch size of 10. The developer wants to increase throughput and increases the batch size to 100. After the change, CloudWatch metrics show a significant increase in throttles and the queue backlog is growing. The function's reserved concurrency is set to 10. What is the most effective action to resolve the throttling and improve throughput?
Question 4
A developer is managing an application running on Amazon EC2 instances behind an Application Load Balancer. Users report that the application becomes unresponsive after several hours, and restarting the instance temporarily fixes the issue. The developer suspects a memory leak but cannot add custom instrumentation. Which AWS service can collect memory utilization metrics and help identify the memory leak with minimal configuration?
Question 5
A developer is building a serverless web application using AWS Lambda and Amazon DynamoDB. The application needs to perform complex aggregations on data stored in DynamoDB. Which AWS service should the developer use to perform these aggregations efficiently without reading all the data into Lambda?
Question 6
A developer has an Amazon S3 bucket containing private user documents. The application must generate a time-limited URL for users to download their own documents without requiring the users to have AWS credentials. Which solution should the developer use?
FAQ
Questions learners often ask
What does this DVA-C02 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Increase the parallelization factor to 10 — When a Lambda function processes records from Kinesis, each shard can be processed by one or more concurrent Lambda invocations. The parallelization factor controls how many concurrent invocations can process a single shard. Increasing the parallelization factor from 1 to a higher value (up to 10 per shard) allows each shard to be processed by multiple concurrent invocations, greatly increasing throughput without adding more shards. Increasing batch size may not help if the per-record processing time is high, and might cause timeouts. Increasing memory could help if the function is compute-bound, but it is not guaranteed and increases cost. Splitting the stream into more shards increases shard count and Lambda invocations but also increases Kinesis costs, making it less cost-effective than increasing the parallelization factor.
What should I do if I get this DVA-C02 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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