DBS-C01 Monitoring and Troubleshooting Practice Question
A database specialist is troubleshooting an Amazon DynamoDB table that is experiencing high throttling on write requests. The table has on-demand capacity and uses a composite primary key (partition key and sort key). Which TWO actions should the specialist take to identify and resolve the issue?
⚠ Common exam trap
Watch out — candidates often confuse read and write capacity units or assume that on-demand capacity eliminates all throttling, when in fact hot partitions can still cause throttling regardless of the capacity mode.
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
✓
Examine the partition key value distribution to identify hot partitions
High throttling on write requests often results from uneven partition key distribution, creating hot partitions. Option A is correct: examining the partition key value distribution helps identify hot partitions. Option E is correct: reviewing CloudWatch metrics for WriteThrottleEvents and ConsumedWriteCapacityUnits helps identify throttled write requests and analyze capacity usage. Options B, C, and D are incorrect: DAX is a read cache and does not affect write throughput; changing to provisioned capacity or increasing read capacity units does not resolve write throttling caused by hot partitions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Examine the partition key value distribution to identify hot partitions
Why this is correct
Correct. Uneven partition key value distribution leads to hot partitions that exceed per-partition throughput limits. Examining the distribution helps identify the bottleneck, and strategies like write sharding or adjusting the partition key design can resolve the issue.
- ✗
Implement DynamoDB Accelerator (DAX) to offload read traffic
Why it's wrong here
Incorrect. DAX is an in-memory cache for read-intensive workloads. It does not handle write requests, so it cannot offload write traffic or reduce write throttling. The issue is write throttling, not read traffic.
- ✗
Change the table to provisioned capacity mode
Why it's wrong here
Incorrect. Changing to provisioned capacity does not inherently resolve hot partition issues; in fact, on-demand capacity already auto-scales to handle large traffic bursts, but hot partitions can still cause throttling. Swapping capacity modes does not fix the root cause.
- ✗
Increase the read capacity units on the table
Why it's wrong here
Incorrect. The table has on-demand capacity, so increasing read capacity units is not applicable. Moreover, the issue is write throttling; read capacity adjustments do not address write limitations.
- ✓
Review Amazon CloudWatch metrics for 'WriteThrottleEvents' and 'ConsumedWriteCapacityUnits'
Why this is correct
Correct. CloudWatch metrics such as WriteThrottleEvents directly show throttled write requests, and ConsumedWriteCapacityUnits provides insight into write usage. Analyzing these metrics helps pinpoint the extent and pattern of throttling.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.