The answer is to increase the number of shards and use a Kinesis Data Analytics application for windowed aggregation before Lambda. This is the most scalable solution because adding shards directly increases the stream’s throughput capacity, allowing more data to be ingested per second, while Kinesis Data Analytics performs windowed aggregation—such as tumbling or sliding windows—to reduce the volume of records sent to Lambda, preventing the function from timing out during spikes. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of how to decouple bursty ingestion from downstream processing; a common trap is to simply increase the Lambda timeout or reserved concurrency, but those approaches fail to address the root cause of throughput overload. Remember the memory tip: “Shards for speed, Analytics to feed”—shards boost raw input, and Analytics pre-aggregates so Lambda doesn’t bleed.
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. 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 data engineer is designing a data pipeline that ingests streaming data from an IoT fleet using Kinesis Data Streams and processes it with a Lambda function. The Lambda function often times out when the data volume spikes. What is the most scalable solution?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the number of shards and use a Kinesis Data Analytics application for windowed aggregation before Lambda.
Option D is correct because increasing shard count increases throughput, and using a fan-out pattern with Kinesis Data Analytics involves windowed processing that can handle spikes without Lambda timeouts. Option A is wrong because increasing Lambda timeout may not be enough for large spikes. Option B is wrong because Lambda reserved concurrency limits scaling. Option C is wrong because reducing batch size decreases throughput.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Reduce the batch size in the event source mapping.
Why it's wrong here
Smaller batches mean more invocations, which can increase overhead.
✗
Increase the Lambda function timeout to 15 minutes.
Why it's wrong here
Timeout alone does not help with high data volume; processing still takes time.
✗
Increase the Lambda function memory and set reserved concurrency.
Why it's wrong here
Memory helps CPU, but reserved concurrency limits parallelism.
✓
Increase the number of shards and use a Kinesis Data Analytics application for windowed aggregation before Lambda.
Why this is correct
More shards increase parallelism, and pre-aggregation reduces Lambda load.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
Data Operations and Support — This question tests Data Operations and Support — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Increase the number of shards and use a Kinesis Data Analytics application for windowed aggregation before Lambda. — Option D is correct because increasing shard count increases throughput, and using a fan-out pattern with Kinesis Data Analytics involves windowed processing that can handle spikes without Lambda timeouts. Option A is wrong because increasing Lambda timeout may not be enough for large spikes. Option B is wrong because Lambda reserved concurrency limits scaling. Option C is wrong because reducing batch size decreases throughput.
What should I do if I get this DEA-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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 →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.