The answer is to enable DynamoDB Auto Scaling for the table, as this is the most efficient way to handle ProvisionedThroughputExceededException errors and reduce retries. DynamoDB Auto Scaling works by continuously monitoring the actual consumed throughput against the provisioned capacity, and it automatically adjusts the read and write capacity units in response to real-time traffic patterns, which directly prevents throttling before it becomes a problem. On the AWS Certified Database Specialty DBS-C01 exam, this question tests your understanding of operational efficiency versus manual intervention; a common trap is choosing to switch to eventually consistent reads, which reduces throttling but changes the data consistency model—a trade-off that may violate application requirements. Another trap is manually increasing read capacity, which is reactive and inefficient compared to the proactive, automated scaling that Auto Scaling provides. Memory tip: think “Auto Scale, Auto Heal”—if you let DynamoDB manage its own capacity, you eliminate the need for manual retries and throttling fixes.
DBS-C01 Monitoring and Troubleshooting Practice Question
This DBS-C01 practice question tests your understanding of monitoring and troubleshooting. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 for a high-traffic application. Users report occasional 'ProvisionedThroughputExceededException' errors. The application uses consistent reads and retries with exponential backoff. What is the MOST efficient way to handle these errors and reduce the number of retries?
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
Option B is correct because DynamoDB Auto Scaling adjusts the provisioned throughput automatically in response to traffic patterns, reducing throttling. Option A is wrong because switching to eventually consistent reads may reduce throttling but changes the consistency model, which may not be acceptable. Option C is wrong because increasing read capacity is a manual action and not efficient. Option D is wrong because increasing write capacity does not address read throttling.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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 provisioned read capacity units manually
Why it's wrong here
Manual scaling is not efficient and may lead to over-provisioning.
✗
Switch to eventually consistent reads
Why it's wrong here
Eventually consistent reads reduce throttling but change consistency guarantees.
✓
Enable DynamoDB Auto Scaling for the table
Why this is correct
Auto Scaling adjusts capacity automatically to handle traffic spikes.
Related concept
Static NAT maps one inside address to one outside address.
✗
Increase the provisioned write capacity units manually
Why it's wrong here
Write capacity does not affect read throttling.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. 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.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
Monitoring and Troubleshooting — This question tests Monitoring and Troubleshooting — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Enable DynamoDB Auto Scaling for the table — Option B is correct because DynamoDB Auto Scaling adjusts the provisioned throughput automatically in response to traffic patterns, reducing throttling. Option A is wrong because switching to eventually consistent reads may reduce throttling but changes the consistency model, which may not be acceptable. Option C is wrong because increasing read capacity is a manual action and not efficient. Option D is wrong because increasing write capacity does not address read throttling.
What should I do if I get this DBS-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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 developer reports that an application using Amazon DynamoDB is experiencing high latency during peak hours. The table has a provisioned capacity of 500 read capacity units (RCUs) and 500 write capacity units (WCUs). The application uses eventually consistent reads and the table is about 50 GB. The developer notices throttled write requests in CloudWatch. Which action would most effectively reduce write throttling?
medium
A.Enable DynamoDB Accelerator (DAX) for the table.
B.Create a global secondary index on the table.
✓ C.Increase the provisioned write capacity for the table.
D.Switch from eventually consistent reads to strongly consistent reads.
Why C: The developer reports throttled write requests, which directly indicates that the provisioned write capacity (500 WCUs) is insufficient to handle the peak write traffic. Increasing the provisioned write capacity for the table is the most direct and effective action to eliminate write throttling, as it raises the limit on write operations per second. Option C is correct because it addresses the root cause—write capacity exhaustion—without introducing unnecessary components or changing read behavior.
Variation 2. A developer is troubleshooting an issue where an application using Amazon DynamoDB is receiving occasional 'ThrottlingException' errors. The application uses eventually consistent reads. What is the MOST likely cause of this error?
easy
A.The application is using an incorrect table name
✓ B.The read capacity units are set too low for the current traffic pattern
C.The application is using eventually consistent reads instead of strongly consistent reads
D.There is a network connectivity issue between the application and DynamoDB
Why B: Option B is correct because ThrottlingException occurs when the request rate exceeds the provisioned throughput capacity. Option A is wrong because eventually consistent reads consume half the read capacity units, so they are less likely to cause throttling. Option C is wrong because network issues would cause timeout errors, not throttling. Option D is wrong because incorrect table name would cause ResourceNotFoundException.
Variation 3. A company is using Amazon DynamoDB for a gaming leaderboard application. Recently, users have experienced increased latency when updating scores. The DynamoDB table has on-demand capacity mode. The application performs UpdateItem calls with a condition expression. Which action is most likely to reduce the latency?
easy
A.Add a global secondary index (GSI) with the score as the sort key to improve update performance.
B.Switch the table to provisioned capacity and increase the read capacity units to handle peak load.
C.Disable conditional writes to reduce the overhead of condition expression evaluation.
✓ D.Ensure that there are no throttled requests in the CloudWatch metrics and verify that the table is not experiencing hot partitions.
Why D: Option A is correct because with on-demand capacity, DynamoDB can handle sudden traffic spikes without throttling. Increasing read capacity is not applicable because on-demand mode automatically adjusts. Optimistic locking is already used implicitly with condition expressions. Adding a global secondary index does not directly reduce UpdateItem latency.
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Question Discussion
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