- A
Increase the batch size to 1000
Why wrong: 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
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
Decrease the maximum record age
Why wrong: 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
Increase the function's memory and CPU allocation
Why wrong: 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.
DVA-C02 Troubleshooting and Optimization Practice Question
This DVA-C02 practice question tests your understanding of troubleshooting and optimization. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 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
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Increase the number of shards
The high IteratorAge indicates that the Lambda function is falling behind in processing records from the Kinesis stream. Throttling occurs because the function's reserved concurrency of 100 is insufficient to handle the total throughput of 10 shards × 5000 records/sec = 50,000 records/sec. Increasing the number of shards (option B) directly increases the parallelism of the stream, allowing more Lambda invocations to run concurrently (up to the reserved concurrency limit) and reducing the backlog, thereby decreasing IteratorAge and throttle rate.
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 to 1000
Why it's wrong here
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.
- ✓
Increase the number of shards
Why this is correct
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the maximum record age
Why it's wrong here
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.
- ✗
Increase the function's memory and CPU allocation
Why it's wrong here
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 traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume increasing batch size or memory will solve throughput issues, but the real bottleneck is concurrency limits and shard-level parallelism, not per-invocation processing capacity.
Detailed technical explanation
How to think about this question
Kinesis shard-level parallelism means each shard can trigger one Lambda invocation at a time, but with reserved concurrency set to 100, the function can process up to 100 shards concurrently. With only 10 shards, the concurrency bottleneck is not the shard count but the reserved concurrency; however, increasing shards (e.g., to 100) allows the function to fully utilize its reserved concurrency, distributing the load across more parallel invocations. Under the hood, the Kinesis event source mapping polls each shard independently, and the IteratorAge metric reflects the time lag between the latest record in the stream and the last record processed; reducing the backlog requires either more shards or higher concurrency.
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?
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 the number of shards — The high IteratorAge indicates that the Lambda function is falling behind in processing records from the Kinesis stream. Throttling occurs because the function's reserved concurrency of 100 is insufficient to handle the total throughput of 10 shards × 5000 records/sec = 50,000 records/sec. Increasing the number of shards (option B) directly increases the parallelism of the stream, allowing more Lambda invocations to run concurrently (up to the reserved concurrency limit) and reducing the backlog, thereby decreasing IteratorAge and throttle rate.
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: Jun 11, 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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