- A
Switch to DynamoDB on-demand mode.
Why wrong: On-demand can handle spikes but may cost more; auto scaling is more cost-effective for predictable patterns.
- B
Add a global secondary index with different partition key.
Why wrong: Indexes don't increase base table capacity.
- C
Enable DynamoDB auto scaling for reads.
Dynamically adjusts capacity to handle spikes.
- D
Add a DAX cluster to cache read requests.
Why wrong: DAX does not increase write capacity.
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 uses Amazon DynamoDB for a session management workload. The access pattern is random and requires single-digit millisecond latency. The table has a read capacity of 5000 RCU. During peak hours, read requests occasionally exceed this capacity, causing throttling. Which design change is most appropriate to handle traffic spikes?
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
Enable DynamoDB auto scaling for reads.
Option C is correct because DynamoDB auto scaling allows the table to dynamically adjust its provisioned read capacity (RCU) in response to traffic spikes, preventing throttling while maintaining single-digit millisecond latency. This is the most appropriate design change for a session management workload with random access patterns, as it handles occasional bursts without requiring manual intervention or architectural changes.
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.
- ✗
Switch to DynamoDB on-demand mode.
Why it's wrong here
On-demand can handle spikes but may cost more; auto scaling is more cost-effective for predictable patterns.
- ✗
Add a global secondary index with different partition key.
Why it's wrong here
Indexes don't increase base table capacity.
- ✓
Enable DynamoDB auto scaling for reads.
Why this is correct
Dynamically adjusts capacity to handle spikes.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Add a DAX cluster to cache read requests.
Why it's wrong here
DAX does not increase write capacity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose DAX (Option D) thinking it solves throttling by caching, but DAX only reduces read load if the same items are frequently requested—random access patterns with low cache hit rates make DAX ineffective for preventing throttling, and it does not increase the table's RCU limit.
Detailed technical explanation
How to think about this question
DynamoDB auto scaling uses the AWS Application Auto Scaling service to adjust provisioned capacity based on a target utilization percentage (default 70%) and CloudWatch metrics like ConsumedReadCapacityUnits. It can scale up quickly (within minutes) to handle spikes, but it cannot react instantly to sudden bursts; for workloads requiring sub-second scaling, on-demand mode or a combination of auto scaling with a buffer (e.g., reserved capacity) may be needed. In session management, where read patterns are random and latency-sensitive, auto scaling provides a balance of cost and performance without requiring application-level caching or schema 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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
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?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable DynamoDB auto scaling for reads. — Option C is correct because DynamoDB auto scaling allows the table to dynamically adjust its provisioned read capacity (RCU) in response to traffic spikes, preventing throttling while maintaining single-digit millisecond latency. This is the most appropriate design change for a session management workload with random access patterns, as it handles occasional bursts without requiring manual intervention or architectural changes.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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