- A
Set up a CloudWatch Alarm to trigger a Lambda function to add shards
Why wrong: This is possible but requires custom logic; on-demand is simpler and recommended.
- B
Use an Auto Scaling group to add more shards
Why wrong: Auto Scaling groups are not applicable to Kinesis shards.
- C
Switch the Kinesis stream to on-demand capacity mode
On-demand mode automatically scales shards based on ingestion throughput.
- D
Configure the stream to use a Lambda function that scales shards
Why wrong: Lambda does not directly scale shards; it can be used with API but not natively.
Question 1,465 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 streaming ingestion pipeline using Amazon Kinesis Data Streams. The stream has 10 shards, and the data volume is expected to grow by 50% over the next month. The engineer needs to ensure that the pipeline can scale without manual intervention. Which approach should be used?
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
✓
Switch the Kinesis stream to on-demand capacity mode
Option C is correct because Kinesis Data Streams on-demand capacity mode automatically scales the number of shards based on the incoming traffic pattern, eliminating the need for manual intervention. Option A is incorrect because CloudWatch Alarms can trigger a Lambda function to add shards via the UpdateShardCount API, but this approach requires custom code and does not provide automatic scaling without manual setup. Option B is incorrect because Auto Scaling groups are used for EC2 instances, not for Kinesis stream shards. Option D is incorrect because Lambda functions can be used to scale shards programmatically, but this still requires custom implementation and is not a native automatic scaling feature.
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.
- ✗
Set up a CloudWatch Alarm to trigger a Lambda function to add shards
Why it's wrong here
This is possible but requires custom logic; on-demand is simpler and recommended.
- ✗
Use an Auto Scaling group to add more shards
Why it's wrong here
Auto Scaling groups are not applicable to Kinesis shards.
- ✓
Switch the Kinesis stream to on-demand capacity mode
Why this is correct
On-demand mode automatically scales shards based on ingestion throughput.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Configure the stream to use a Lambda function that scales shards
Why it's wrong here
Lambda does not directly scale shards; it can be used with API but not natively.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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.
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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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Switch the Kinesis stream to on-demand capacity mode — Option C is correct because Kinesis Data Streams on-demand capacity mode automatically scales the number of shards based on the incoming traffic pattern, eliminating the need for manual intervention. Option A is incorrect because CloudWatch Alarms can trigger a Lambda function to add shards via the UpdateShardCount API, but this approach requires custom code and does not provide automatic scaling without manual setup. Option B is incorrect because Auto Scaling groups are used for EC2 instances, not for Kinesis stream shards. Option D is incorrect because Lambda functions can be used to scale shards programmatically, but this still requires custom implementation and is not a native automatic scaling feature.
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.
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 →
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Last reviewed: Jun 20, 2026
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