The answer is to decrease the Lambda batch size to 10. This directly reduces DynamoDB write throttling in a Kinesis to Lambda pipeline because on-demand DynamoDB, while scaling automatically, still enforces a per-partition throughput limit; by processing fewer records per invocation, you lower the burst of concurrent writes hitting a single partition, which prevents the ProvisionedThroughputExceededException during peak traffic. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of how Lambda batch size interacts with DynamoDB’s internal partition limits—a common trap is assuming more shards or lower concurrency will help, but the real lever is batch size. Remember the memory tip: “Smaller batches, fewer throttles—think per-partition, not per-table.”
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 data engineer is responsible for a real-time data pipeline that ingests clickstream data from a website into Amazon Kinesis Data Streams, then processed by an AWS Lambda function that writes to an Amazon DynamoDB table for user session tracking. The Lambda function is idempotent and uses the DynamoDB PutItem API with a condition expression to avoid overwriting existing records. Over the past week, the engineer has observed an increase in DynamoDB write throttling (ProvisionedThroughputExceededException) during peak traffic hours. The DynamoDB table has on-demand capacity. The engineer checks the Lambda function's reserved concurrency and finds it set to 1000. The Kinesis stream has 10 shards. The Lambda function's batch size is set to 100. The engineer suspects that the retry behavior is causing duplicate writes and throttling. Which change should the engineer make to reduce throttling?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Decrease the Lambda batch size to 10 to reduce the number of records processed per invocation.
Option B is correct. On-demand DynamoDB can scale, but it has a per-partition throughput limit. Reducing the Lambda batch size reduces the number of concurrent writes per shard, decreasing the chance of hitting partition limits. Option A is wrong because increasing shards would increase concurrency, worsening throttling. Option C is wrong because decreasing reserved concurrency could cause Lambda throttling but not DynamoDB throttling. Option D is wrong because using a DynamoDB stream adds complexity and does not directly reduce write throttling.
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.
✗
Increase the number of Kinesis shards to 20 to distribute the load.
Why it's wrong here
More shards increase the number of concurrent Lambda invocations, increasing write pressure.
✓
Decrease the Lambda batch size to 10 to reduce the number of records processed per invocation.
Why this is correct
Smaller batches reduce the number of concurrent writes to DynamoDB, lowering throttling.
Related concept
Read the scenario before looking for a memorised answer.
✗
Decrease the Lambda reserved concurrency to 500 to limit the number of concurrent invocations.
Why it's wrong here
This would cause Lambda throttling, but DynamoDB throttling is caused by high write volume.
✗
Use a DynamoDB Stream to trigger a second Lambda function that writes to the table.
Why it's wrong here
Adding a stream does not reduce write throttling; it adds complexity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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: Decrease the Lambda batch size to 10 to reduce the number of records processed per invocation. — Option B is correct. On-demand DynamoDB can scale, but it has a per-partition throughput limit. Reducing the Lambda batch size reduces the number of concurrent writes per shard, decreasing the chance of hitting partition limits. Option A is wrong because increasing shards would increase concurrency, worsening throttling. Option C is wrong because decreasing reserved concurrency could cause Lambda throttling but not DynamoDB throttling. Option D is wrong because using a DynamoDB stream adds complexity and does not directly reduce write throttling.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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