- A
Increase the number of shards in the Kinesis data stream
More shards increase throughput capacity.
- B
Replace Lambda with Amazon Kinesis Data Firehose for the transformation
Why wrong: Firehose does not support custom transformations natively; would require Lambda pre-processing.
- C
Increase the Lambda function timeout to 15 minutes
Why wrong: Timeout alone doesn't solve processing bottleneck.
- D
Set a reserved concurrency on the Lambda function
Why wrong: Limits concurrency, could worsen the problem.
- E
Increase the memory allocated to the Lambda function
More memory provides more CPU, reducing processing time.
Quick Answer
The answer is to increase the memory allocated to the Lambda function and increase the number of shards in the Kinesis data stream. Increasing Lambda memory proportionally boosts CPU and network throughput, directly addressing timeouts caused by tripled data volume, while adding shards raises the stream’s capacity to handle higher ingestion rates and allows more Lambda consumers to process records in parallel. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of scaling Lambda consumers for Kinesis Data Streams under load—a common trap is choosing to increase Lambda concurrency, which can cause throttling if the account limit or reserved concurrency is exceeded, or simply adjusting the timeout without giving the function more resources. Remember the memory tip: “More shards, more speed; more memory, less bleed.”
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 company ingests streaming data from social media feeds into Amazon Kinesis Data Streams. The data is consumed by an AWS Lambda function that transforms and writes to Amazon S3. Recently, the Lambda function started timing out and dropping records. The data volume has tripled. Which actions should the data engineer take to resolve this? (Choose TWO.)
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
Increase the number of shards in the Kinesis data stream
Options A and D are correct because increasing the number of shards increases throughput, and increasing Lambda memory can improve processing speed and reduce timeouts. Option B (Lambda concurrency) may cause throttling. Option C (Lambda timeout) may not be sufficient without more resources. Option E (Data Firehose) is a different service; replacing Lambda with Firehose could be an alternative but not a direct fix for current architecture.
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.
- ✓
Increase the number of shards in the Kinesis data stream
Why this is correct
More shards increase throughput capacity.
Related concept
Static NAT maps one inside address to one outside address.
- ✗
Replace Lambda with Amazon Kinesis Data Firehose for the transformation
Why it's wrong here
Firehose does not support custom transformations natively; would require Lambda pre-processing.
- ✗
Increase the Lambda function timeout to 15 minutes
Why it's wrong here
Timeout alone doesn't solve processing bottleneck.
- ✗
Set a reserved concurrency on the Lambda function
Why it's wrong here
Limits concurrency, could worsen the problem.
- ✓
Increase the memory allocated to the Lambda function
Why this is correct
More memory provides more CPU, reducing processing time.
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.
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Data Ingestion and Transformation — study guide chapter
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — 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 in the Kinesis data stream — Options A and D are correct because increasing the number of shards increases throughput, and increasing Lambda memory can improve processing speed and reduce timeouts. Option B (Lambda concurrency) may cause throttling. Option C (Lambda timeout) may not be sufficient without more resources. Option E (Data Firehose) is a different service; replacing Lambda with Firehose could be an alternative but not a direct fix for current architecture.
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.
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Last reviewed: Jun 20, 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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