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Monitoring and Troubleshooting →mediumMultiple SelectObjective-mapped

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 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 THREE actions should the specialist take to identify and resolve the issue?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "primary"
Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

A
Examine the partition key value distribution to identify hot partitions
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.
B
Implement DynamoDB Accelerator (DAX) to offload read traffic
Why wrong: 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.
C
Change the table to provisioned capacity mode
Why wrong: 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.
D
Increase the read capacity units on the table
Why wrong: 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.
E
Review Amazon CloudWatch metrics for 'WriteThrottleEvents' and 'ConsumedWriteCapacityUnits'
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.

Full breakdown with real-world context →

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

Option A is correct because high throttling on write requests often results from uneven partition key distribution, creating 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. Although the stem asks for three actions, only two of the listed options (A and E) are valid. The third action (not listed) would involve improving the partition key design to distribute writes more evenly.

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.

✓
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.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
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.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates may 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.

Detailed technical explanation

How to think about this question

DynamoDB on-demand capacity mode automatically scales to handle traffic spikes, but it still enforces per-partition throughput limits (up to 3,000 read capacity units or 1,000 write capacity units per partition). When a single partition key receives excessive writes, it can throttle even if overall table usage is within limits. CloudWatch metrics like 'WriteThrottleEvents' and 'ConsumedWriteCapacityUnits' (Option E) help pinpoint the exact partitions and timeframes where throttling occurs, enabling targeted remediation such as adaptive capacity or partition key redesign.

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.

Visual reference

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.

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FAQ

Questions learners often ask

What does this DBS-C01 question test?

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: Examine the partition key value distribution to identify hot partitions — Option A is correct because high throttling on write requests often results from uneven partition key distribution, creating 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. Although the stem asks for three actions, only two of the listed options (A and E) are valid. The third action (not listed) would involve improving the partition key design to distribute writes more evenly.

What should I do if I get this DBS-C01 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Are there clue words in this question I should notice?

Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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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.