The answer is to enable DAX to cache read requests, increase the maximum read capacity, and implement exponential backoff. This combination directly addresses the root cause of DynamoDB auto scaling throttling: auto scaling reacts to sustained load, not sudden spikes, so a burst of 12,000 RCU against a 10,000 RCU ceiling will always cause throttling until scaling completes. DAX offloads read traffic from the table, reducing the effective RCU demand, while raising the maximum capacity ensures the table can handle peak loads without waiting for auto scaling to catch up. Exponential backoff, meanwhile, is a best practice for client-side retry logic that prevents overwhelming the table during transient throttling events. On the AWS Certified Database Specialty DBS-C01 exam, this scenario tests your understanding that auto scaling is reactive, not proactive—a common trap is assuming lowering target utilization (e.g., to 50%) would help, but that only triggers scaling earlier on sustained traffic, not during instantaneous bursts. Memory tip: think “DAX for reads, raise the max, and back off” to remember the three pillars of throttling resolution.
DBS-C01 Monitoring and Troubleshooting Practice Question
This DBS-C01 practice question tests your understanding of monitoring and troubleshooting. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 using Amazon DynamoDB with auto scaling enabled. The table has a provisioned read capacity of 10,000 RCU and write capacity of 5,000 WCU. Auto scaling target utilization is 70%. The table experiences a sudden spike in read traffic, reaching 12,000 RCU. The table throttles some requests. Which THREE actions should the company take to prevent future throttling?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement exponential backoff in the application to retry throttled requests.
Option A is correct because increasing the maximum read capacity prevents throttling. Option B is correct because enabling DynamoDB Accelerator (DAX) reduces read load. Option E is correct because implementing exponential backoff helps handle throttling gracefully. Option C is wrong because decreasing target utilization would cause auto scaling to scale out earlier, but it would not prevent throttling during spikes because auto scaling reacts after the spike. Option D is wrong because write capacity is not the issue.
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.
✓
Implement exponential backoff in the application to retry throttled requests.
Why this is correct
Exponential backoff helps handle throttled requests without data loss.
Related concept
Read the scenario before looking for a memorised answer.
✓
Increase the maximum read capacity in the auto scaling configuration.
Why this is correct
Allowing the table to scale higher prevents throttling during spikes.
Related concept
Read the scenario before looking for a memorised answer.
✗
Decrease the auto scaling target utilization to 50% to scale out earlier.
Why it's wrong here
This would cause scaling at lower utilization, but during sudden spikes, auto scaling may not react fast enough.
✗
Increase the write capacity to 10,000 WCU.
Why it's wrong here
Write capacity is not related to read throttling.
✓
Enable DAX to cache read requests and reduce the load on the table.
Why this is correct
DAX reduces read traffic to the table.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
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.
Detailed technical explanation
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.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
Identify which DBS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Monitoring and Troubleshooting — This question tests Monitoring and Troubleshooting — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement exponential backoff in the application to retry throttled requests. — Option A is correct because increasing the maximum read capacity prevents throttling. Option B is correct because enabling DynamoDB Accelerator (DAX) reduces read load. Option E is correct because implementing exponential backoff helps handle throttling gracefully. Option C is wrong because decreasing target utilization would cause auto scaling to scale out earlier, but it would not prevent throttling during spikes because auto scaling reacts after the spike. Option D is wrong because write capacity is not the issue.
What should I do if I get this DBS-C01 question wrong?
Identify which DBS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses Amazon DynamoDB with auto scaling enabled. They notice that a table's write capacity is frequently throttled during a specific hour each day. The access pattern is uniform across partitions. Which action would resolve the throttling without manual intervention?
hard
A.Enable DynamoDB Accelerator (DAX) to cache writes.
B.Disable auto scaling and set a fixed higher capacity.
C.Create a larger number of partitions by splitting the table.
✓ D.Increase the minimum provisioned capacity in auto scaling.
Why D: Option C is correct because auto scaling should increase capacity to meet demand, but if it is not scaling fast enough, adjusting the scaling policy can help. Option A is wrong because disabling auto scaling is not a solution. Option B is wrong because the pattern is uniform, so partitioning is not the issue. Option D is wrong because DAX is for reads, not writes.
Variation 2. A company is using Amazon DynamoDB with auto scaling enabled. The application is experiencing higher than expected write throttling. Which action should be taken to resolve this issue?
medium
✓ A.Increase the minimum provisioned capacity for the table.
B.Disable auto scaling and set a fixed provisioned capacity.
C.Decrease the maximum provisioned capacity to limit writes.
D.Switch the table to on-demand capacity mode.
Why A: Auto scaling can lag behind sudden traffic spikes. Increasing the minimum provisioned capacity can help reduce throttling during bursts. Option B is correct. Option A is incorrect because on-demand mode may be costly but could solve throttling, but the question asks for a resolution with auto scaling. Option C is incorrect because auto scaling already adjusts capacity. Option D is incorrect because decreasing capacity would worsen throttling.
Variation 3. A company is using Amazon DynamoDB with auto scaling enabled. Despite auto scaling, the application is still experiencing throttling during traffic spikes. Which THREE actions should the company take to resolve this issue? (Choose THREE.)
hard
✓ A.Implement exponential backoff in the application code
✓ B.Enable DynamoDB Accelerator (DAX) to cache read-heavy workloads
✓ C.Use DynamoDB global tables to distribute write traffic across regions
D.Switch to on-demand capacity mode
E.Disable auto scaling and set fixed capacity
Why A: Options A, D, and E are correct. Enabling DynamoDB Accelerator (DAX) reduces read load. Implementing exponential backoff helps retry gracefully. Using DynamoDB global tables can distribute write load. Option B is wrong because disabling auto scaling would not help. Option C is wrong because switching to on-demand capacity might help but is not always cost-effective and does not address hot keys.
Variation 4. A team is using Amazon DynamoDB with auto scaling enabled. They notice that some requests are returning ProvisionedThroughputExceededException errors during a sudden traffic spike. The application uses strong consistent reads. Which two actions would help mitigate the throttling without over-provisioning capacity? (Choose two.)
hard
✓ A.Implement DynamoDB Accelerator (DAX) to cache read results.
✓ B.Enable DynamoDB adaptive capacity.
C.Switch to eventually consistent reads for all queries.
D.Disable auto scaling and manually set higher capacity.
E.Use DynamoDB burst capacity for the spike.
Why A: Option A and D are correct. Using DynamoDB Accelerator (DAX) reduces read load, and enabling adaptive capacity helps handle uneven access patterns. Option B is wrong because disabling auto scaling would worsen the issue. Option C is wrong because eventual reads may not be acceptable. Option E is wrong because bursting is limited and not guaranteed.
Last reviewed: Jun 20, 2026
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This DBS-C01 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 DBS-C01 exam.
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