- A
Increase the write capacity units manually.
Why wrong: Manual adjustment is not dynamic and may not minimize costs.
- B
Use DynamoDB Accelerator (DAX) to cache writes.
Why wrong: DAX caches reads, not writes.
- C
Switch to provisioned capacity with auto scaling.
Provisioned with auto scaling can handle predictable patterns and reduce cost vs. on-demand.
- D
Use batch writes to combine small writes.
Why wrong: Batch writes may help but not directly address throttling for individual small writes.
Question 1 of 1,730
DBS-C01 Management and Operations Practice Question
This DBS-C01 practice question tests your understanding of management and operations. 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 with on-demand capacity. The application performs many small writes that are throttled frequently. The company wants to minimize costs while reducing throttling. What should the company do?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
✓
Switch to provisioned capacity with auto scaling.
DynamoDB on-demand capacity can throttle small writes if the traffic pattern exceeds the table's previous peak traffic, as on-demand capacity scales based on traffic volume but has a per-second burst limit. Switching to provisioned capacity with auto scaling allows you to set a baseline capacity that matches the application's average write throughput, while auto scaling adjusts capacity based on actual usage, reducing throttling without the premium cost of on-demand capacity for predictable workloads.
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 write capacity units manually.
Why it's wrong here
Manual adjustment is not dynamic and may not minimize costs.
- ✗
Use DynamoDB Accelerator (DAX) to cache writes.
Why it's wrong here
DAX caches reads, not writes.
- ✓
Switch to provisioned capacity with auto scaling.
Why this is correct
Provisioned with auto scaling can handle predictable patterns and reduce cost vs. on-demand.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use batch writes to combine small writes.
Why it's wrong here
Batch writes may help but not directly address throttling for individual small writes.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume on-demand capacity automatically handles all traffic patterns without throttling, but on-demand throttles when traffic exceeds the table's previous peak, and they may overlook that switching to provisioned capacity with auto scaling provides a cost-effective solution for predictable workloads with frequent small writes.
Detailed technical explanation
How to think about this question
DynamoDB on-demand capacity uses a token bucket algorithm for burst capacity, allowing up to 5 minutes of burst at up to 30,000 RCU/WCU per second, but sustained traffic beyond the table's previous peak can cause throttling. Provisioned capacity with auto scaling uses the Application Auto Scaling service to adjust read and write capacity units based on CloudWatch metrics like ConsumedWriteCapacityUnits, with a target utilization (default 70%), ensuring cost efficiency by scaling down during low traffic and scaling up to prevent throttling during spikes.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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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Management and Operations — study guide chapter
Learn the concepts, then practise the questions
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Management and Operations — This question tests Management and Operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Switch to provisioned capacity with auto scaling. — DynamoDB on-demand capacity can throttle small writes if the traffic pattern exceeds the table's previous peak traffic, as on-demand capacity scales based on traffic volume but has a per-second burst limit. Switching to provisioned capacity with auto scaling allows you to set a baseline capacity that matches the application's average write throughput, while auto scaling adjusts capacity based on actual usage, reducing throttling without the premium cost of on-demand capacity for predictable workloads.
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: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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