DEA-C01 Data Store Management Practice Question
A company uses Amazon DynamoDB with provisioned capacity. During a sales event, write traffic spikes and some requests receive ProvisionedThroughputExceeded exceptions. The reads are within limits. The data engineer needs to minimize latency for the spike without manual intervention. Which solution is MOST cost-effective?
⚠ Common exam trap
A common mix-up: candidates confuse DAX as a solution for write performance, but DAX only accelerates reads (via caching) and does not mitigate write throttling, leading to an incorrect choice of Option D.
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 write capacity with a target utilization of 70%.
DynamoDB auto scaling for write capacity automatically adjusts the provisioned write capacity units (WCUs) based on the actual traffic pattern, using a target utilization of 70% to balance cost and performance. This eliminates manual intervention and handles spikes efficiently by scaling up before throttling occurs, while remaining cost-effective since capacity scales down when traffic subsides.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Amazon SQS to buffer write requests and process them in batches.
Why it's wrong here
Buffering adds latency and does not prevent ProvisionedThroughputExceeded exceptions; it only queues the requests.
- ✗
Disable auto scaling and set write capacity to the peak observed value.
Why it's wrong here
This over-provisions capacity, increasing cost unnecessarily when traffic is low.
- ✓
Enable DynamoDB auto scaling for write capacity with a target utilization of 70%.
Why this is correct
Auto scaling adjusts capacity dynamically based on traffic, handling spikes cost-effectively.
- ✗
Enable DynamoDB Accelerator (DAX) to cache write operations.
Why it's wrong here
DAX is a read cache and does not help with write throughput exceptions.
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Variation 1. A company has an Amazon DynamoDB table with a provisioned write capacity of 1000 WCU. During a flash sale, the write traffic spikes to 5000 WCU for 10 minutes. The table is not auto-scaled. Which action should the data engineer take to handle the spike without throttling?
hard- ✓ A.Convert the table to on-demand capacity mode before the sale.
- B.Set a CloudWatch alarm to increase provisioned capacity when write throttling occurs.
- C.Use DynamoDB Accelerator (DAX) to cache writes.
- D.Enable auto-scaling with a target utilization of 70% and a maximum capacity of 5000 WCU.
Why A: The table is currently provisioned with 1000 WCU and cannot handle a spike to 5000 WCU. Converting to on-demand mode before the sale allows DynamoDB to automatically handle varying traffic without throttling, as on-demand capacity scales instantly to meet demand. Option D (auto-scaling) might not react quickly enough for a short 10-minute spike, and the table is not currently auto-scaled. Option C is incorrect because DAX is a read cache and does not buffer or improve write capacity. Option B is reactive and would not prevent initial throttling.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-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 DEA-C01 exam.