KCNA덤프문제은행 & KCNA시험패스가능한인증공부자료
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참고: Itcertkr에서 Google Drive로 공유하는 무료 2026 Linux Foundation KCNA 시험 문제집이 있습니다: https://drive.google.com/open?id=1t4QTB5_3_YNiNhbgZuLbREkNEhz-e0xo
Itcertkr의 Linux Foundation인증 KCNA덤프의 무료샘플을 이미 체험해보셨죠? Itcertkr의 Linux Foundation인증 KCNA덤프에 단번에 신뢰가 생겨 남은 문제도 공부해보고 싶지 않나요? Itcertkr는 고객님들의 시험부담을 덜어드리기 위해 가벼운 가격으로 덤프를 제공해드립니다. Itcertkr의 Linux Foundation인증 KCNA로 시험패스하다 더욱 넓고 좋은곳으로 고고싱 하세요.
KCNA 시험은 공급 업체 중립 인증으로 특정 공급 업체 나 기술과 관련이 없음을 의미합니다. 이로 인해 클라우드 네이티브 컴퓨팅에서 지식과 기술을 넓히고 잠재적 인 고용주에게 자신의 전문 지식을 보여 주려고하는 전문가에게는 훌륭한 선택이됩니다.
Linux Foundation KCNA 인증 시험은 클라우드 네이티브 컴퓨팅 분야에서 다양한 수준의 경험을 가진 개인에게 적합합니다. 경력을 시작하든 수년간의 경험이 있든,이 시험은 포괄적이고 엄격한 방식으로 지식과 기술을 테스트합니다. 인증은 클라우드 네이티브 컴퓨팅에 대한 전문 지식을 보여 주고이 분야에서 경력을 발전시키려는 개인에게 귀중한 자산입니다.
리눅스 재단 KCNA 시험은 Kubernetes와 클라우드 네이티브 기술에 관심 있는 개인들을 대상으로 합니다. 이 시험은 Kubernetes 클러스터를 구현, 관리 및 문제 해결하는 능력을 비롯한 이러한 기술을 작업하는 데 필요한 지식과 기술을 검증하기 위해 설계되었습니다. 인증 프로그램은 또한 클라우드 네이티브 기술에 대해 더 많이 학습하고 지식을 향상시키고자 하는 IT 전문가들에게도 적합합니다.
KCNA시험패스 가능한 인증공부자료 - KCNA덤프샘플문제
Linux Foundation인증 KCNA시험은 등록하였는데 시험준비는 아직이라구요? Linux Foundation인증 KCNA시험일이 다가오고 있는데 공부를 하지 않아 두려워 하고 계시는 분들은 이 글을 보는 순간 시험패스에 자신을 가지게 될것입니다. 시험준비 시간이 적다고 하여 패스할수 없는건 아닙니다. Itcertkr의Linux Foundation인증 KCNA덤프와의 근사한 만남이Linux Foundation인증 KCNA패스에 화이팅을 불러드립니다. 덤프에 있는 문제만 공부하면 되기에 시험일이 며칠뒤라도 시험패스는 문제없습니다. 더는 공부하지 않은 자신을 원망하지 마시고 결단성있게Itcertkr의Linux Foundation인증 KCNA덤프로 시험패스에 고고싱하세요.
최신 Kubernetes Cloud Native Associate KCNA 무료샘플문제 (Q148-Q153):
질문 # 148
You are building a cloud-native application that uses a combination of Kubernetes, Istio, and Prometheus. You want to ensure that your application's logs, metrics, and traces are correlated for easy troubleshooting. What approach would you take to achieve this correlation?
- A. Integrate Jaeger with Istio and Prometheus using the Istio Mixer to enrich tracing data with metrics and log information.
- B. Use a custom logging agent to collect logs and forward them to Prometheus.
- C. Configure Istio to capture logs from pods and forward them to Prometheus.
- D. Use a centralized logging system like Fluentd to collect logs from Kubernetes and forward them to Prometheus.
- E. Use the •kubectl logs* command to retrieve logs from individual pods and manually correlate them with metrics and traces.
정답:A
설명:
The correct answer is B . Istio's Mixer allows you to integrate Jaeger with Istio and Prometheus. This integration enables you to enrich tracing data with relevant metrics and log information captured from Istio's traffic management capabilities. This approach provides a unified platform for correlating logs, metrics, and traces. The other options are not as effective for achieving correlation: A : This approach focuses only on logs and does not provide a way to link logs to metrics or traces. C : While Istio can capture logs, sending them to Prometheus is not an ideal solution for correlation. D : A centralized logging system like Fluentd can collect logs, but it does not inherently provide mechanisms to correlate them with metrics or traces. E : Manually correlating logs, metrics, and traces using 'kubectl logs is tedious and prone to errors, especially in a dynamic environment like Kubernetes.
질문 # 149
Explain the concept of "service discovery" in Prometheus and how it integrates with Kubernetes.
- A. Service discovery is primarily used to manage Prometheus data storage and retention policies within Kubernetes clusters.
- B. Service discovery allows Prometheus to automatically find and scrape metrics from target endpoints, making it easier to monitor dynamic Kubernetes environments.
- C. Service discovery is responsible for distributing Prometheus workloads across Kubernetes nodes for high availability.
- D. Service discovery is not related to Kubernetes and is only used for external monitoring solutions.
- E. Service discovery is a feature that enables Prometheus to create alerts based on changes in Kubernetes service configurations.
정답:B
설명:
Service discovery in Prometheus enables it to locate and collect metrics from dynamic Kubernetes environments. It automatically discovers and configures scraping targets based on Kubernetes service definitions. This simplifies the monitoring process and ensures that Prometheus stays up-to-date with changes in the Kubernetes cluster.
질문 # 150
In the Kubernetes platform, which component is responsible for running containers?
- A. CRI-O
- B. cloud-controller-manager
- C. kube-controller-manager
- D. etcd
정답:A
설명:
In Kubernetes, the actual act of running containers on a node is performed by the container runtime. The kubelet instructs the runtime via CRI, and the runtime pulls images, creates containers, and manages their lifecycle. Among the options provided, CRI-O is the only container runtime, so B is correct.
It's important to be precise: the component that "runs containers" is not the control plane and not etcd. etcd (option A) stores cluster state (API objects) as the backing datastore. It never runs containers. cloud-controller-manager (option C) integrates with cloud APIs for infrastructure like load balancers and nodes. kube-controller-manager (option D) runs controllers that reconcile Kubernetes objects (Deployments, Jobs, Nodes, etc.) but does not execute containers on worker nodes.
CRI-O is a CRI implementation that is optimized for Kubernetes and typically uses an OCI runtime (like runc) under the hood to start containers. Another widely used runtime is containerd. The runtime is installed on nodes and is a prerequisite for kubelet to start Pods. When a Pod is scheduled to a node, kubelet reads the PodSpec and asks the runtime to create a "pod sandbox" and then start the container processes. Runtime behavior also includes pulling images, setting up namespaces/cgroups, and exposing logs/stdout streams back to Kubernetes tooling.
So while "the container runtime" is the most general answer, the question's option list makes CRI-O the correct selection because it is a container runtime responsible for running containers in Kubernetes.
질문 # 151
Which command lists the running containers in the current Kubernetes namespace?
- A. kubectl get pods
- B. kubectl ls
- C. kubectl show pods
- D. kubectl ps
정답:A
설명:
The correct answer is A: kubectl get pods. Kubernetes does not manage "containers" as standalone top-level objects; the primary schedulable unit is the Pod, and containers run inside Pods. Therefore, the practical way to list what's running in a namespace is to list the Pods in that namespace. kubectl get pods shows Pods and their readiness, status, restarts, and age-giving you the canonical view of running workloads.
If you need the container-level details (images, container names), you typically use additional commands and output formatting:
kubectl describe pod <pod> to view container specs, images, states, and events kubectl get pods -o jsonpath=... or -o wide to surface more fields kubectl get pods -o=json to inspect .spec.containers and .status.containerStatuses But among the provided options, kubectl get pods is the only real kubectl command that lists the running workload objects in the current namespace.
The other options are not valid kubectl subcommands: kubectl ls, kubectl ps, and kubectl show pods are not standard Kubernetes CLI operations. Kubernetes intentionally centers around the API resource model, so listing resources uses kubectl get <resource>. This also aligns with Kubernetes' declarative nature: you observe and manage the state via API objects, not by directly enumerating OS-level processes.
So while the question says "running containers," the Kubernetes-correct interpretation is "containers in running Pods," and the appropriate listing command in the namespace is kubectl get pods, option A.
질문 # 152
You have a Kubernetes cluster with multiple namespaces. You are running different applications in separate namespaces and want to ensure that HPAs in each namespace are not interfering with each other. Which of the following measures should you take?
- A. Ensure that the •minReplicas• and •maxReplicaS values for HPAs across namespaces are aligned.
- B. Create a custom controller to manage HPAs across multiple namespaces and coordinate scaling decisions.
- C. Configure resource quotas for each namespace to prevent resource over-allocation by HPAs.
- D. Use a single HPA for all applications in all namespaces.
- E. There is no need for any specific measures as HPAs are isolated by default within their respective namespaces.
정답:B,C
설명:
You need to ensure that HPAs are not competing for resources across namespaces- Resource quotas (C) limit resource consumption within each namespace, preventing HPAs from consuming resources intended for other applications. A custom controller (D) can be used to manage HPAs across multiple namespaces, coordinating scaling decisions to avoid resource contention and optimize utilization across the cluster. While options A and B might seem relevant, they are not effective solutions for preventing interference between HPAs in different namespaces. Option E is incorrect; HPAs operate within their namespaces, but resource contention can occur if not managed properly.
질문 # 153
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그 외, Itcertkr KCNA 시험 문제집 일부가 지금은 무료입니다: https://drive.google.com/open?id=1t4QTB5_3_YNiNhbgZuLbREkNEhz-e0xo
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