- A
Switch the table to provisioned capacity and enable auto-scaling.
Why wrong: On-demand tables already handle spikes; auto-scaling is for provisioned mode.
- B
Increase the write capacity units to handle the peak load.
Why wrong: On-demand tables do not use write capacity units.
- C
Enable S3 bucket versioning to reduce the number of writes.
Why wrong: S3 versioning does not affect DynamoDB operations.
- D
Implement DynamoDB Accelerator (DAX) to cache frequent reads.
DAX reduces read load on the table, lowering throttling.
Quick Answer
The correct answer is to implement DynamoDB Accelerator (DAX) to cache frequent reads. DAX acts as an in-memory cache that sits between your application and the DynamoDB table, serving read requests from its cache instead of hitting the table directly, which directly reduces read throttling during peak hours. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding that throttling errors on an on-demand table are typically caused by read or write spikes, and that DAX offloads read traffic without requiring any table capacity changes or application rewrites. A common trap is to assume the Lambda trigger is causing the throttling, but the trigger writes to S3, not reads; the real issue is excessive read requests from the application. Memory tip: think of DAX as a “read shield” that absorbs the burst so your table doesn’t feel the heat.
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 team manages an Amazon DynamoDB table with on-demand capacity. Recently, they noticed increased throttling errors during peak hours. The table has a Lambda trigger that processes changes and writes to an S3 bucket. Which design change would BEST reduce throttling?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
Implement DynamoDB Accelerator (DAX) to cache frequent reads.
Option D is correct because DynamoDB Accelerator (DAX) provides an in-memory cache that reduces the number of read requests hitting the table, which can alleviate throttling during peak hours. The question describes throttling errors, which are typically caused by exceeding the table's read or write capacity; DAX offloads read traffic, reducing the load on the table and thus decreasing throttling events.
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 the table to provisioned capacity and enable auto-scaling.
Why it's wrong here
On-demand tables already handle spikes; auto-scaling is for provisioned mode.
- ✗
Increase the write capacity units to handle the peak load.
Why it's wrong here
On-demand tables do not use write capacity units.
- ✗
Enable S3 bucket versioning to reduce the number of writes.
Why it's wrong here
S3 versioning does not affect DynamoDB operations.
- ✓
Implement DynamoDB Accelerator (DAX) to cache frequent reads.
Why this is correct
DAX reduces read load on the table, lowering throttling.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may assume throttling is always due to insufficient write capacity, but the question's context of a Lambda trigger writing to S3 can increase read traffic (e.g., via stream processing or re-reading items), making DAX a read-side solution that addresses the actual cause.
Detailed technical explanation
How to think about this question
DynamoDB on-demand capacity uses a per-partition throughput limit of 3,000 read request units (RRU) or 1,000 write request units (WRU) per partition, and throttling occurs when a single partition's traffic exceeds these limits. DAX acts as a write-through cache that absorbs repeated read requests, reducing the read load on individual partitions and preventing throttling without requiring capacity changes. In real-world scenarios, a Lambda trigger that processes DynamoDB Streams and writes to S3 can generate high read traffic if the Lambda function re-reads the same items, making DAX an effective mitigation.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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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Data Operations and Support — study guide chapter
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Operations and Support — This question tests Data Operations and Support — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement DynamoDB Accelerator (DAX) to cache frequent reads. — Option D is correct because DynamoDB Accelerator (DAX) provides an in-memory cache that reduces the number of read requests hitting the table, which can alleviate throttling during peak hours. The question describes throttling errors, which are typically caused by exceeding the table's read or write capacity; DAX offloads read traffic, reducing the load on the table and thus decreasing throttling events.
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.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
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.
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