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
This maps resource consumption to cost.
- ✗
Use kubectl top to get resource usage
Why it's wrong here
kubectl top gives current usage but not cost.
- ✗
Estimate costs based on node count
Why it's wrong here
Node count is too coarse.
- ✗
Monitor CPU and memory usage with Prometheus
Why it's wrong here
Usage metrics alone don't give cost data.
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JA
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.