- A
Increase the DynamoDB table's provisioned read and write capacity.
Higher provisioned capacity reduces throttling and write latency, directly improving performance.
- B
Increase the Lambda reserved concurrency.
Why wrong: Reserved concurrency limits the number of concurrent executions, which can throttle requests but does not directly reduce latency per invocation.
- C
Move the Lambda function into a VPC with a DynamoDB VPC endpoint.
Why wrong: A VPC endpoint reduces network hops but does not address DynamoDB throttling; adding VPC can introduce cold start latency.
- D
Enable DynamoDB Accelerator (DAX) for the table.
Why wrong: DAX is a caching layer for reads, not writes; the function writes metadata, so DAX would not help.
Question 934 of 1,616
Improve Lambda-DynamoDB Performance by Increasing Capacity
This DVA-C02 practice question tests your understanding of development with aws services. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 is building a serverless application using AWS Lambda and Amazon DynamoDB. The Lambda function processes user uploads from Amazon S3 and stores metadata in DynamoDB. The function is experiencing high latency during peak hours. Which action would MOST improve the performance without increasing the function timeout?
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 DynamoDB table's provisioned read and write capacity.
Increasing the DynamoDB table's provisioned read and write capacity directly addresses the root cause of high latency during peak hours: throttling due to insufficient throughput. When the Lambda function's write requests exceed the table's capacity, DynamoDB throttles them, causing retries and increased latency. Raising the capacity allows DynamoDB to handle the burst of metadata writes without throttling, reducing response times without requiring a longer function timeout.
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 DynamoDB table's provisioned read and write capacity.
Why this is correct
Higher provisioned capacity reduces throttling and write latency, directly improving performance.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the Lambda reserved concurrency.
Why it's wrong here
Reserved concurrency limits the number of concurrent executions, which can throttle requests but does not directly reduce latency per invocation.
- ✗
Move the Lambda function into a VPC with a DynamoDB VPC endpoint.
Why it's wrong here
A VPC endpoint reduces network hops but does not address DynamoDB throttling; adding VPC can introduce cold start latency.
- ✗
Enable DynamoDB Accelerator (DAX) for the table.
Why it's wrong here
DAX is a caching layer for reads, not writes; the function writes metadata, so DAX would not help.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse read optimization (DAX) with write optimization, or assume that increasing concurrency or improving network connectivity will fix a throughput bottleneck, when the actual issue is insufficient DynamoDB write capacity.
Detailed technical explanation
How to think about this question
DynamoDB throttles requests when they exceed the provisioned capacity (or consumed burst capacity) by returning a ProvisionedThroughputExceededException, which the AWS SDK automatically retries with exponential backoff, adding significant latency. Increasing provisioned write capacity units (WCUs) directly raises the number of write operations per second the table can handle, eliminating throttling. Under the hood, DynamoDB distributes partitions based on throughput; increasing capacity may trigger partition splits, but this is handled automatically and is far more effective than other options for write-heavy workloads.
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
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.
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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 DynamoDB table's provisioned read and write capacity. — Increasing the DynamoDB table's provisioned read and write capacity directly addresses the root cause of high latency during peak hours: throttling due to insufficient throughput. When the Lambda function's write requests exceed the table's capacity, DynamoDB throttles them, causing retries and increased latency. Raising the capacity allows DynamoDB to handle the burst of metadata writes without throttling, reducing response times without requiring a longer function timeout.
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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