The answer is to enable DynamoDB auto scaling for the table to handle traffic spikes. This is correct because DynamoDB auto scaling dynamically adjusts the provisioned read and write capacity units based on actual traffic patterns, preventing throttling at the database layer that would otherwise cause Lambda function retries and increased error rates. In a serverless architecture, the database tier is often the bottleneck; by automatically scaling throughput, you eliminate the root cause of Lambda throttling when traffic spikes exceed fixed capacity. On the AWS Certified DevOps Engineer Professional DOP-C02 exam, this scenario tests your understanding of how to decouple compute and storage scaling—a common trap is to over-provision Lambda concurrency or add more API Gateway throttling, which only masks the database issue. Remember the memory tip: “Scale the table, not the function” to focus on DynamoDB auto scaling as the primary resilience mechanism for serverless workloads.
DOP-C02 Resilient Cloud Solutions Practice Question
This DOP-C02 practice question tests your understanding of resilient cloud solutions. 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 DevOps engineer is designing a resilient architecture for a serverless application using AWS Lambda, Amazon API Gateway, and Amazon DynamoDB. The application experiences occasional spikes in traffic that cause Lambda function throttling and increased error rates. What is the MOST effective way to improve resilience and reduce throttling?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable DynamoDB auto scaling for the table to handle traffic spikes.
DynamoDB auto scaling adjusts the provisioned throughput (read/write capacity units) in response to traffic spikes, preventing throttling at the database layer that would cause Lambda retries and errors. This directly addresses the root cause of increased error rates when the table's capacity is exceeded, which is a common bottleneck in serverless architectures.
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 memory to the maximum allowed.
Why it's wrong here
Memory increase does not affect concurrency limits.
✓
Enable DynamoDB auto scaling for the table to handle traffic spikes.
Why this is correct
Auto scaling adjusts capacity to prevent throttling.
Related concept
Read the scenario before looking for a memorised answer.
✗
Set API Gateway throttling limits to match the expected peak traffic.
Why it's wrong here
API Gateway throttling does not prevent DynamoDB throttling.
✗
Reserve concurrency for the Lambda function to ensure it always has available capacity.
Why it's wrong here
Reserving concurrency can limit scaling and cause throttling if traffic exceeds reserved amount.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often focus on Lambda concurrency or API Gateway throttling as the first line of defense, but the scenario's 'increased error rates' and 'spikes' point to a downstream dependency (DynamoDB) being overwhelmed, not the upstream request path.
Detailed technical explanation
How to think about this question
DynamoDB auto scaling uses the AWS Application Auto Scaling service to adjust provisioned capacity based on target utilization (e.g., 70% of consumed capacity), with cooldown periods to prevent rapid oscillations. In practice, a spike that exceeds the table's write capacity units (WCU) causes ProvisionedThroughputExceededException, which Lambda retries with exponential backoff, leading to increased latency and error rates; auto scaling preemptively raises capacity to absorb the spike.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
Resilient Cloud Solutions — This question tests Resilient Cloud Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable DynamoDB auto scaling for the table to handle traffic spikes. — DynamoDB auto scaling adjusts the provisioned throughput (read/write capacity units) in response to traffic spikes, preventing throttling at the database layer that would cause Lambda retries and errors. This directly addresses the root cause of increased error rates when the table's capacity is exceeded, which is a common bottleneck in serverless architectures.
What should I do if I get this DOP-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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Question Discussion
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