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KCNA考試適用於具有基本Linux，容器化和雲計算理解的個人。它是一種供應商中立的認證，涵蓋廣泛的主題，包括Kubernetes架構，部署，網絡，存儲和安全性。考試還涵蓋其他雲原生技術，如Docker，Helm和Prometheus。
Linux Foundation KCNA考試是供應商中立的認證，獲得了科技行業領先組織的認可。它非常適合那些希望增強雲計算和Kubernetes技能或者對這些技術尚不熟悉但希望獲得堅實基礎的專業人士。該認證還對於希望使用Kubernetes和其他雲原生技術在雲中構建和部署現代應用程序的組織非常有益。
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Linux Foundation KCNA考試涵蓋廣泛的主題，包括Kubernetes架構、部署、網絡、安全和故障排除。它還涵蓋了容器化、微服務和無服務計算等雲原生技術。該考試旨在測試候選人在Kubernetes上部署和管理應用程序的能力以及設計和實施雲原生解決方案的能力。
問題 #67
Which Kubernetes feature is the simplest way to force a Pod or Deployment to run only on nodes with a specific label?
答案：C
解題說明：
A nodeSelector directly matches Pod scheduling to nodes with specific labels, providing the simplest and most straightforward way to constrain where Pods run.
問題 #68
Which of the following characteristics is associated with container orchestration?
答案：A
解題說明：
A core capability of container orchestration is dynamic scheduling, so B is correct. Orchestration platforms (like Kubernetes) are responsible for deciding where containers (packaged as Pods in Kubernetes) should run, based on real-time cluster conditions and declared requirements. "Dynamic" means the system makes placement decisions continuously as workloads are created, updated, or fail, and as cluster capacity changes.
In Kubernetes, the scheduler evaluates Pods that have no assigned node, filters nodes that don't meet requirements (resources, taints/tolerations, affinity/anti-affinity, topology constraints), and then scores remaining nodes to pick the best target. This scheduling happens at runtime and adapts to the current state of the cluster. If nodes go down or Pods crash, controllers create replacements and the scheduler places them again-another aspect of dynamic orchestration.
The other options don't define container orchestration: "application message distribution" is more about messaging systems or service communication patterns, not orchestration. "Deploying application JAR files" is a packaging/deployment detail relevant to Java apps but not a defining orchestration capability. "Virtual machine distribution" refers to VM management rather than container orchestration; Kubernetes focuses on containers and Pods (even if those containers sometimes run in lightweight VMs via sandbox runtimes).
So, the defining trait here is that an orchestrator automatically and continuously schedules and reschedules workloads, rather than relying on static placement decisions.
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問題 #69
What are the initial namespaces that Kubernetes starts with?
答案：A
問題 #70
Which file in a Helm chart is responsible for defining the default configuration values that can be overridden during deployment?
答案：A
解題說明：
The values.yaml file defines the default configuration values for a Helm chart, which can be overridden by users at deployment time to customize the behavior of the chart.
問題 #71
Which of the following options is true about considerations for large Kubernetes clusters?
答案：D
解題說明：
The correct answer is C: Kubernetes scalability guidance commonly cites support up to 5000 nodes and recommends no more than 110 Pods per node. The "110 Pods per node" recommendation is a practical limit based on kubelet, networking, and IP addressing constraints, as well as performance characteristics for scheduling, service routing, and node-level resource management. It is also historically aligned with common CNI/IPAM defaults where node Pod CIDRs are sized for ~110 usable Pod IPs.
Why the other options are incorrect: A and D reference "containers per node," which is not the standard sizing guidance (Kubernetes typically discusses Pods per node). B's "500 Pods per node" is far above typical recommended limits for many environments and would stress IPAM, kubelet, and node resources significantly.
In large clusters, several considerations matter beyond the headline limits: API server and etcd performance, watch/list traffic, controller reconciliation load, CoreDNS scaling, and metrics/observability overhead. You must also plan for IP addressing (cluster CIDR sizing), node sizes (CPU/memory), and autoscaling behavior. On each node, kubelet and the container runtime must handle churn (starts/stops), logging, and volume operations. Networking implementations (kube-proxy, eBPF dataplanes) also have scaling characteristics.
Kubernetes provides patterns to keep systems stable at scale: request/limit discipline, Pod disruption budgets, topology spread constraints, namespaces and quotas, and careful observability sampling. But the exam-style fact this question targets is the published scalability figure and per-node Pod recommendation.
Therefore, the verified true statement among the options is C.
問題 #72
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