DynamoDB Auto Scaling for Predictable Spikes
A company uses Amazon DynamoDB with provisioned capacity for a gaming application. During a new game launch, write traffic spikes to 2x the provisioned write capacity for 30 minutes. Some writes are throttled. The company wants to handle these predictable spikes without manual intervention. What is the MOST cost-effective solution?
Quick Answer
The correct answer is to enable DynamoDB auto scaling with a target utilization of 70%. This works because auto scaling uses a built-in application auto scaling policy that adjusts provisioned capacity based on actual consumption, allowing the table to scale up ahead of the predictable spike and then scale back down, keeping costs aligned with usage. On the AWS Certified Database Specialty DBS-C01 exam, this question tests your ability to distinguish between provisioned capacity with auto scaling and on-demand mode—a common trap is assuming on-demand is always cheaper, but for predictable workloads like a game launch, auto scaling with a target utilization of 70% is more cost-effective because it avoids the premium per-request pricing of on-demand. Remember the memory tip: “70% target keeps cost on target” — the 70% utilization buffer gives auto scaling room to absorb spikes without throttling while minimizing over-provisioning.
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 with a target utilization of 70%.
DynamoDB auto scaling automatically adjusts provisioned capacity based on actual usage, handling predictable spikes without manual intervention while minimizing cost by scaling down when demand drops. Option A is wrong because permanently doubling capacity leads to wasted resources and higher costs. Option B is wrong because on-demand mode can be more expensive for predictable workloads with consistent baseline traffic. Option D is wrong because SQS buffers writes but does not directly address DynamoDB write throttling; it adds latency and complexity without solving the capacity issue.
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 write capacity to 2x the baseline permanently.
Why it's wrong here
Permanent increase leads to higher costs during off-peak times.
- ✗
Change the table to on-demand capacity mode.
Why it's wrong here
On-demand capacity mode eliminates throttling by scaling instantly, but it incurs a higher per-write cost than provisioned capacity, making it cost-ineffective for predictable, short-duration spikes that could instead be handled with DynamoDB auto scaling. This option is tempting because on-demand is designed for unpredictable or intermittent traffic patterns where provisioning is impractical; it would be the correct choice if the spikes were irregular or unknown in timing.
- ✓
Enable DynamoDB auto scaling with a target utilization of 70%.
Why this is correct
Auto scaling dynamically adjusts capacity to match traffic, cost-effective for predictable spikes.
- ✗
Use Amazon SQS to buffer writes and process them later.
Why it's wrong here
SQS can decouple but adds latency and complexity; real-time writes may be needed.
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Same concept, more angles
1 more way this is tested on DBS-C01
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 company has an Amazon DynamoDB table with provisioned capacity. The table experiences occasional spikes in write traffic that exceed the provisioned write capacity units (WCU). Which feature should the database specialist enable to handle these spikes without throttling?
easy- A.Enable DynamoDB burst capacity.
- ✓ B.Configure DynamoDB Auto Scaling for write capacity.
- C.Use DynamoDB Accelerator (DAX) to cache writes.
- D.Switch to on-demand capacity mode.
Why B: DynamoDB Auto Scaling automatically adjusts the provisioned read and write capacity based on actual traffic patterns, enabling the table to handle spikes without throttling while maintaining cost efficiency. Option A is incorrect because burst capacity provides a limited buffer for short-term spikes but can be exhausted, leading to throttling. Option C is incorrect because DAX is an in-memory cache for read operations, not writes. Option D is incorrect because switching to on-demand capacity mode can handle spikes but may result in higher costs compared to Auto Scaling with provisioned capacity.
JA
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.