The answer is DynamoDB auto scaling with a target utilization of 70%. This solution is correct because auto scaling dynamically adjusts the provisioned read and write capacity based on actual traffic patterns, scaling up during sudden spikes to prevent throttling errors and scaling down during low traffic to avoid over-provisioning, making it a cost-effective approach to DynamoDB throttling handling. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of balancing performance and cost under unpredictable workloads; a common trap is choosing DAX (which caches reads but does not handle write throttling) or exponential backoff (which retries requests but does not prevent throttling). Remember the 70% target utilization sweet spot: it leaves headroom for spikes while minimizing waste, and think of it as the “Goldilocks” setting—not too high, not too low.
DEA-C01 Data Store Management Practice Question
This DEA-C01 practice question tests your understanding of data store management. 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 for an e-commerce application. The application experiences sudden spikes in traffic, causing throttling errors. The data engineer needs to handle the spikes cost-effectively. Which solution should be used?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use DynamoDB auto scaling with a target utilization of 70%.
Option C is correct because DynamoDB auto scaling with a target utilization of 70% allows the table to dynamically adjust provisioned read/write capacity based on actual traffic patterns, handling sudden spikes without manual intervention while avoiding over-provisioning. This balances performance and cost by scaling up during spikes and scaling down during low traffic, preventing throttling errors cost-effectively.
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.
✗
Implement DynamoDB Accelerator (DAX) to cache reads.
Why it's wrong here
DAX reduces read latency but does not handle write spikes.
✗
Switch to DynamoDB on-demand capacity mode.
Why it's wrong here
On-demand can handle spikes but is more expensive for steady traffic.
✓
Use DynamoDB auto scaling with a target utilization of 70%.
Why this is correct
Auto scaling adjusts capacity dynamically based on traffic.
Related concept
Read the scenario before looking for a memorised answer.
✗
Provision high read and write capacity units to handle peak traffic.
Why it's wrong here
Overprovisioning wastes cost; spikes may still exceed provisioned capacity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse caching (DAX) with scaling, or assume on-demand mode is always the best for spikes without considering cost, when the question explicitly requires a cost-effective solution for sudden but intermittent traffic.
Detailed technical explanation
How to think about this question
DynamoDB auto scaling uses the AWS Application Auto Scaling service to adjust provisioned throughput based on CloudWatch metrics like ConsumedWriteCapacityUnits, with a target utilization (e.g., 70%) that triggers scaling policies. Under the hood, it applies a cooldown period (default 5 minutes) to prevent rapid fluctuations, and the scaling is governed by a target tracking scaling policy that maintains the utilization ratio. In real-world scenarios, sudden spikes from flash sales or viral events can be absorbed by auto scaling if the table has sufficient burst capacity (up to 5 minutes of unused capacity), but sustained spikes require scaling to avoid throttling.
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.
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use DynamoDB auto scaling with a target utilization of 70%. — Option C is correct because DynamoDB auto scaling with a target utilization of 70% allows the table to dynamically adjust provisioned read/write capacity based on actual traffic patterns, handling sudden spikes without manual intervention while avoiding over-provisioning. This balances performance and cost by scaling up during spikes and scaling down during low traffic, preventing throttling errors cost-effectively.
What should I do if I get this DEA-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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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 uses Amazon DynamoDB for a gaming application. The application experiences throttling during peak hours. The table's read and write capacity is provisioned. Which TWO actions can reduce throttling?
medium
A.Enable TTL (time to live) on the table to automatically delete old items
✓ B.Enable DynamoDB auto scaling for the table
C.Increase the provisioned read capacity units (RCUs)
✓ D.Implement DynamoDB Accelerator (DAX) to cache read requests
E.Add a DynamoDB Global Table for the table
Why B: DynamoDB auto scaling (Option B) automatically adjusts the provisioned read and write capacity based on actual traffic patterns, preventing throttling during peak hours without manual intervention. This is the correct action because it dynamically increases capacity when demand spikes and reduces it during low traffic, directly addressing the throttling issue.
Variation 2. A company uses Amazon DynamoDB as the primary data store for a web application. The application experiences occasional throttling on write requests. The data engineer needs to implement a solution that handles throttling gracefully without losing data. Which approach should the engineer use?
easy
A.Increase the provisioned write capacity to a higher value
B.Use an Amazon SQS queue to buffer write requests before sending to DynamoDB
✓ C.Implement exponential backoff in the application's write retry logic
D.Enable DynamoDB Accelerator (DAX) to cache writes
Why C: Option C is correct because implementing exponential backoff in the application's write retry logic is the standard AWS-recommended approach for handling DynamoDB throttling (ProvisionedThroughputExceededException). Exponential backoff gradually increases the wait time between retries, reducing the retry rate and allowing the throttling condition to subside, while ensuring no write data is lost as long as the retries eventually succeed. This approach is lightweight, requires no additional AWS services, and aligns with best practices for building resilient applications against DynamoDB throttling.
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Question Discussion
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