This KCNA practice question tests your understanding of cloud native observability. 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.
Which component is responsible for aggregating metrics from Kubernetes nodes and exposing them to the metrics API?
Prometheus Server
Why wrong: Prometheus is a monitoring system that can scrape metrics but is not part of the default Kubernetes metrics API.
Grafana
Why wrong: Grafana is a visualization tool, not a metrics aggregator.
metrics-server
Correct. The metrics-server is a cluster-wide aggregator of resource usage data.
Fluentd
Why wrong: Fluentd is a log aggregator, not for metrics.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
metrics-server
The metrics-server is the correct component because it is specifically designed to collect resource metrics (CPU and memory) from the kubelet on each node via the Summary API and expose them through the Kubernetes Metrics API. This allows tools like `kubectl top` and the Horizontal Pod Autoscaler to access real-time resource usage without requiring a full monitoring stack.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Prometheus Server
Why it's wrong here
Prometheus is a monitoring system that can scrape metrics but is not part of the default Kubernetes metrics API.
Grafana
Why it's wrong here
Grafana is a visualization tool, not a metrics aggregator.
metrics-server
Why this is correct
Correct. The metrics-server is a cluster-wide aggregator of resource usage data.
Related concept
Read the scenario before looking for a memorised answer.
Fluentd
Why it's wrong here
Fluentd is a log aggregator, not for metrics.
Common exam traps
The trap here is that candidates often confuse Prometheus (a full monitoring system) with the metrics-server (a lightweight, Kubernetes-native component for the Metrics API), assuming Prometheus is required for `kubectl top` or HPA when in fact the metrics-server is the dedicated and simpler solution.
Detailed technical explanation
The metrics-server uses the kubelet's `/metrics/resource/v1alpha1` endpoint (or the Summary API) to gather resource usage data every 15 seconds by default, caching it in memory without storing it persistently. This design makes it lightweight and suitable for autoscaling, but it does not support historical queries—if the pod restarts, all data is lost. In real-world scenarios, relying solely on metrics-server for autoscaling can cause issues if the cluster has many nodes, as the default resource requests may need tuning to avoid performance bottlenecks.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the KCNA exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Cloud Native Observability — This question tests Cloud Native Observability — Read the scenario before looking for a memorised answer..
The correct answer is: metrics-server — The metrics-server is the correct component because it is specifically designed to collect resource metrics (CPU and memory) from the kubelet on each node via the Summary API and expose them through the Kubernetes Metrics API. This allows tools like `kubectl top` and the Horizontal Pod Autoscaler to access real-time resource usage without requiring a full monitoring stack.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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.
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