KCNA Cloud Native Observability Practice Question
A team wants to implement cost monitoring for their Kubernetes clusters. Which approach is most effective?
⚠ Common exam trap
Test-takers frequently confuse resource monitoring (CPU/memory) with cost monitoring, assuming that tracking utilization alone (e.g., with Prometheus or kubectl top) is sufficient to understand spending, when in fact cost data requires explicit billing integration.
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
✓
Use cloud provider billing APIs combined with resource utilization data
Cloud provider billing APIs provide actual cost data per resource (e.g., per node, per persistent volume, per network egress), and combining this with resource utilization data (e.g., CPU/memory requests and actual usage from metrics) enables accurate cost allocation per namespace, pod, or workload. This approach directly maps infrastructure spend to Kubernetes abstractions, which is essential for chargeback or showback in multi-tenant clusters.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use cloud provider billing APIs combined with resource utilization data
Why this is correct
Provider billing APIs expose actual spend per cluster and namespace, while utilisation data attributes that cost to workloads, revealing idle or over-provisioned resources. Correlating the two axes is what enables meaningful cost monitoring rather than raw invoice totals alone.
- ✗
Use kubectl top to get resource usage
Why it's wrong here
kubectl top reports instantaneous CPU and memory consumption from metrics-server, giving no historical data, no aggregation and no cost attribution per namespace or workload. It fits quick spot-checks of pod resource usage during troubleshooting, not ongoing cost monitoring.
- ✗
Estimate costs based on node count
Why it's wrong here
Node count ignores actual pod requests, idle capacity and workload distribution, so it cannot attribute spend to teams or namespaces. It suits rough capacity planning for homogeneous clusters where every node runs at similar utilisation.
- ✗
Monitor CPU and memory usage with Prometheus
Why it's wrong here
Prometheus captures CPU and memory metrics but has no pricing data, so it cannot convert consumption into monetary cost or show per-namespace spend. It fits performance monitoring and capacity trending, where resource usage rather than billing is the goal.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.