KCNA Cloud Native Architecture Practice Question
In serverless computing, what is the primary characteristic of Function-as-a-Service (FaaS)?
⚠ Common exam trap
KCNA often tests whether candidates confuse FaaS with containers or PaaS, so the trap is picking 'always running instances' because it sounds like a managed service rather than recognizing that scale-to-zero is the defining FaaS trait.
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
✓
Auto-scaling to zero
The defining characteristic of FaaS is that functions are event-driven and the platform automatically scales the number of running instances from zero up to meet demand, then back down to zero when idle. This means you pay only for actual execution time, not for idle capacity. Auto-scaling to zero is what fundamentally separates FaaS from container-as-a-service or VM-based models.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Stateful execution
Why it's wrong here
FaaS functions execute statelessly, with any state externalised to services such as DynamoDB or S3, so stateful execution contradicts the model. It is tempting because long-running containers and virtual machines do retain in-process state, which is why those platforms suit session-bound workloads rather than event-triggered functions.
- ✗
Always running instances
Why it's wrong here
FaaS instances are provisioned on invocation and torn down after execution, so nothing runs continuously. It is tempting because always-on servers and containers avoid cold-start latency, making them the right choice for latency-sensitive, steady-traffic services, but they contradict the pay-per-invocation, scale-to-zero FaaS model.
- ✓
Auto-scaling to zero
Why this is correct
Auto-scaling to zero means no function instances run while there is no traffic, so the platform provisions capacity only on invocation and releases it afterwards. That scale-to-zero behaviour, with no idle server cost, is the defining characteristic of FaaS.
- ✗
Manual scaling
Why it's wrong here
FaaS platforms scale automatically in response to invocation concurrency, so manual scaling is not a characteristic. It is tempting because manually provisioned capacity is the norm for virtual machines and container clusters, where engineers choose instance counts; that approach suits steady, predictable workloads rather than bursty event-driven functions.
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 |
Go deeper
Related to this question
Learn chapter
Container Orchestration Essentials
Key term
Serverless computing
Serverless computing is a cloud execution model where the cloud provider dynamically manages the allocation and provisioning of servers, allowing developers to write and deploy code without thinking about the underlying infrastructure.
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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 CNCF exam blueprint
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