DEA-C01 Data Ingestion and Transformation Practice Question
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?
⚠ Common exam trap
Watch out — candidates often confuse EC2 Auto Scaling concepts with Kinesis shard scaling, or assuming Lambda can programmatically add shards; the exam tests whether you know that only on-demand mode provides native automatic scaling for Kinesis Data Streams.
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
Kinesis Data Streams on-demand capacity mode automatically scales shard capacity up or down based on observed throughput, eliminating the need to manually provision or add shards. It handles the 50% growth without any CloudWatch alarms, Lambda functions, or Auto Scaling groups. This is the only option that provides fully managed, hands-off scaling.
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
Setting up a CloudWatch Alarm to trigger a Lambda function to add shards is a custom solution, not a native auto-scaling feature of Amazon Kinesis Data Streams. Kinesis Data Streams does not offer built-in auto-scaling based on resource utilisation, meaning this approach would require complex custom logic within the Lambda to monitor metrics and call `UpdateShardCount` effectively. This option is tempting because CloudWatch Alarms and Lambda are fundamental for implementing custom automation, and this pattern is used for auto-scaling other AWS services like EC2 or DynamoDB.
- ✗
Use an Auto Scaling group to add more shards
Why it's wrong here
Auto Scaling groups manage EC2 instances, not Kinesis shards, so they cannot resize a stream. It is tempting because Auto Scaling genuinely delivers hands-off capacity adjustment, but that applies to compute fleets; Kinesis scaling requires either the UpdateShardCount API or on-demand mode, which adjusts shard capacity automatically as throughput changes.
- ✓
Switch the Kinesis stream to on-demand capacity mode
Why this is correct
On-demand capacity mode automatically scales shard throughput in response to traffic, removing the need to manually reshard as volume grows by 50%. It satisfies the no-manual-intervention constraint directly, unlike provisioned mode, which requires monitoring and explicit shard splits or merges to match demand.
- ✗
Configure the stream to use a Lambda function that scales shards
Why it's wrong here
A Lambda function cannot itself scale Kinesis shards; it would need to call UpdateShardCount, and the stem requires scaling without manual intervention. It is tempting because Lambda-based automation genuinely handles scheduled or event-driven shard resizing, but that is custom tooling, whereas on-demand capacity mode adjusts shards automatically in response to traffic.
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 |
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.