KCNA Cloud Native Observability Practice Question
What is the purpose of the metrics-server in Kubernetes?
⚠ Common exam trap
KCNA often tests the distinction between metrics-server (real-time resource metrics for HPA) and full monitoring solutions like Prometheus (historical metrics and long-term storage), so candidates may incorrectly assume metrics-server stores historical data.
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
✓
To provide resource usage metrics for pods and nodes
The metrics-server is a cluster-wide aggregator of resource usage data. It collects CPU and memory metrics from each node's kubelet (via the Summary API) and exposes them through the Kubernetes API server using the Metrics API (metrics.k8s.io). This enables core Kubernetes components like the Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) to make scaling decisions, and allows users to view resource usage with `kubectl top`.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
To provide resource usage metrics for pods and nodes
Why this is correct
The metrics-server aggregates kubelet-reported resource consumption and exposes it through the Metrics API, letting Horizontal Pod Autoscalers and kubectl top read live CPU and memory figures for pods and nodes. It satisfies the requirement for cluster-wide resource usage visibility, unlike full monitoring stacks that persist historical data.
- ✗
To manage service meshes
Why it's wrong here
The metrics-server only supplies resource metrics for the Horizontal Pod Autoscaler and kubectl top; service mesh control planes such as Istio manage traffic, mTLS and routing. It is tempting because both are cluster add-ons, and a mesh would be correct when the requirement is traffic shaping or mutual TLS between services.
- ✗
To collect application logs
Why it's wrong here
The metrics-server exposes CPU and memory resource metrics through the Metrics API; log aggregation is handled by node-level agents forwarding to a logging backend. It is tempting because both are observability components deployed cluster-wide, and a log collector would be correct when the requirement is searching application output.
- ✗
To store historical metrics
Why it's wrong here
The metrics-server serves current resource usage from the kubelet's Summary API for autoscaling decisions; it keeps only the latest samples in memory and exposes no historical store. It is tempting because monitoring dashboards display trends, but long-term retention belongs to a time-series database such as Prometheus.
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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
This KCNA practice question is part of Courseiva's free CNCF 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 KCNA exam.