hardmultiple choiceObjective-mapped

A developer is monitoring an AWS Lambda function that processes events from an Amazon Kinesis stream. The function's CloudWatch metrics show high IteratorAge and the function is often throttled. The function's batch size is 100, maximum record age is 60s, and reserved concurrency is 100. The Kinesis stream has 10 shards, each with 5000 records/sec. Which action is most effective to reduce the IteratorAge and throttle rate?

Question 1hardmultiple choice
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A developer is monitoring an AWS Lambda function that processes events from an Amazon Kinesis stream. The function's CloudWatch metrics show high IteratorAge and the function is often throttled. The function's batch size is 100, maximum record age is 60s, and reserved concurrency is 100. The Kinesis stream has 10 shards, each with 5000 records/sec. Which action is most effective to reduce the IteratorAge and throttle rate?

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

Incorrect. Increasing batch size may reduce the number of invocations but each shard can only process one batch at a time; if the function is already CPU-bound, larger batches could increase latency. Also, Kinesis batch size max is 10,000, but the improvement is marginal if the function is throttled.

B

Best answer

Increase the number of shards

Correct. More shards increase the concurrency of Lambda invocations (each shard processed independently), directly reducing the IteratorAge and throttle rate by providing more parallel processing capacity.

C

Distractor review

Decrease the maximum record age

Incorrect. Decreasing the maximum record age does not affect the processing speed; it only tells Lambda to discard records older than the specified age. This would cause data loss but not reduce IteratorAge.

D

Distractor review

Increase the function's memory and CPU allocation

Incorrect. While increasing memory may improve processing speed per invocation, it doesn't increase concurrency. The function is already throttled due to concurrency limits, so per-invocation improvements are less effective.

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 number of shards — The high IteratorAge indicates the function is not keeping up with the data flowing through the Kinesis stream. Each shard can be processed by only one Lambda invocation at a time (per shard). Increasing the number of shards increases the parallelism, allowing more concurrent Lambda invocations to process records, which directly reduces backpressure. Increasing batch size or memory may help but are less effective when the function is already throttled and the parallelism is limited by shard count.

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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