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The KCNA certification exam is a valuable credential for professionals who work with Kubernetes and cloud-native technologies. It is recognized by industry leaders and can help individuals advance their careers in the rapidly growing field of cloud-native computing. Passing KCNA Exam not only demonstrates one's proficiency in Kubernetes and cloud-native technologies, but also proves one's commitment to continuous learning and professional development.
NEW QUESTION # 81
What is the primary interface for Kubernetes cluster?
Answer: C
Explanation:
https://kubernetes.io/docs/concepts/overview/components/#kube-apiserver
NEW QUESTION # 82
Which kubernetes resource type allows defining which pods are isolated when it comes to network-ing?
Answer: D
Explanation:
https://kubernetes.io/docs/concepts/services-networking/network-policies/#the-two-sorts-of-pod-isolation
NEW QUESTION # 83
Which control plane component is responsible for scheduling pods?
Answer: D
Explanation:
https://kubernetes.io/docs/concepts/overview/components/
NEW QUESTION # 84
Which of the following is a valid PromQL query?
Answer: D
Explanation:
Prometheus Query Language (PromQL) uses a function-and-selector syntax, not SQL. A valid query typically starts with a metric name and optionally includes label matchers in curly braces. In the simplified quiz syntax given, the valid PromQL-style selector is best represented by D: http_requests_total(job="apiserver"), so D is correct.
Conceptually, what this query means is "select time series for the metric http_requests_total where the job label equals apiserver." In standard PromQL formatting you most often see this as: http_requests_total{job="apiserver"}. Many training questions abbreviate braces and focus on the idea of filtering by labels; the key is that PromQL uses label matchers rather than SQL WHERE clauses.
Options A and C are invalid because they use SQL (SELECT * FROM ...) which is not PromQL. Option B is also invalid because PromQL does not use the keyword WHERE. PromQL filtering is done by applying label matchers directly to the metric selector.
In Kubernetes observability, PromQL is central to building dashboards and alerts from cluster metrics. For example, you might compute rates from counters: rate(http_requests_total{job="apiserver"}[5m]), aggregate by labels: sum by (code) (...), or alert on error ratios. Understanding the selector and label-matcher model is foundational because Prometheus metrics are multi-dimensional-labels define the slices you can filter and aggregate on.
So, within the provided options, D is the only one that follows PromQL's metric+label-filter style and therefore is the verified correct answer.
NEW QUESTION # 85
What do control groups provide when it come to containers
Answer: C
Explanation:
NEW QUESTION # 86
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