This DEA-C01 practice question tests your understanding of data store management. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 runs a real-time analytics platform on AWS. Data is ingested from thousands of IoT devices into Amazon Kinesis Data Streams. A Lambda function consumes the stream, processes the data, and writes the results to an Amazon DynamoDB table. The DynamoDB table has a provisioned write capacity of 1000 WCU, and the read capacity is set to 200 RCU. Recently, the company noticed that the Lambda function is failing with ProvisionedThroughputExceededException on DynamoDB writes. The Lambda function is configured with a batch size of 100 and a concurrency limit of 10. The Kinesis shard count is 4. The number of devices has increased, but the data volume per device has remained the same. The company needs to resolve the write throttling without increasing the DynamoDB write capacity. Which action should the data engineer take?
Increase the number of Kinesis shards to 8.
Why wrong: More shards increase parallelism, worsening throttling.
Increase the Lambda concurrency limit to 20.
Why wrong: More concurrency increases write pressure.
Increase the batch size to 200.
Why wrong: Larger batches increase write volume per invocation.
Reduce the batch size of the Lambda function to 10.
Smaller batches reduce write volume per invocation.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Reduce the batch size of the Lambda function to 10.
Reducing the batch size from 100 to 10 decreases the number of records processed per Lambda invocation, which reduces the burst of write requests to DynamoDB per invocation. This helps stay within the 1000 WCU limit without increasing capacity, as the same total throughput is spread across more invocations with smaller batches.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Increase the number of Kinesis shards to 8.
Why it's wrong here
More shards increase parallelism, worsening throttling.
Increase the Lambda concurrency limit to 20.
Why it's wrong here
More concurrency increases write pressure.
Increase the batch size to 200.
Why it's wrong here
Larger batches increase write volume per invocation.
Reduce the batch size of the Lambda function to 10.
Why this is correct
Smaller batches reduce write volume per invocation.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates assume increasing concurrency or shards will distribute the load better, but in reality, those actions increase the total write throughput, exacerbating throttling when DynamoDB capacity is fixed.
Detailed technical explanation
DynamoDB's WriteShard mechanism distributes writes across partitions based on the partition key; throttling occurs when the per-partition throughput limit is exceeded. Reducing batch size smooths the write traffic, allowing DynamoDB's adaptive capacity to better distribute the load across partitions without hitting the provisioned limit. In real-world scenarios, this approach is often combined with exponential backoff and retries in the Lambda function to handle transient throttling gracefully.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
The correct answer is: Reduce the batch size of the Lambda function to 10. — Reducing the batch size from 100 to 10 decreases the number of records processed per Lambda invocation, which reduces the burst of write requests to DynamoDB per invocation. This helps stay within the 1000 WCU limit without increasing capacity, as the same total throughput is spread across more invocations with smaller batches.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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