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Linux Foundation Kubernetes and Cloud Native Associate 認定 KCNA 試験問題 (Q170-Q175):

質問 # 170
What is a Kubernetes service with no cluster IP address called?

A. IPLess Service
B. Nodeless Service
C. Specless Service
D. Headless Service

正解：D

解説：
A Kubernetes Service normally provides a stable virtual IP (ClusterIP) and a DNS name that load-balances traffic across matching Pods. A headless Service is a special type of Service where Kubernetes does not allocate a ClusterIP. Instead, the Service's DNS returns individual Pod IPs (or other endpoint records), allowing clients to connect directly to specific backends rather than through a single virtual IP. That is why the correct answer is A (Headless Service).
Headless Services are created by setting spec.clusterIP: None. When you do this, kube-proxy does not program load-balancing rules for a virtual IP because there isn't one. Instead, service discovery is handled via DNS records that point to the actual endpoints. This behavior is especially important for stateful or identity-sensitive systems where clients must talk to a particular replica (for example, databases, leader/follower clusters, or StatefulSet members).
This is also why headless Services pair naturally with StatefulSets. StatefulSets provide stable network identities (pod-0, pod-1, etc.) and stable DNS names. The headless Service provides the DNS domain that resolves each Pod's stable hostname to its IP, enabling peer discovery and consistent addressing even as Pods move between nodes.
The other options are distractors: "Nodeless," "IPLess," and "Specless" are not Kubernetes Service types. In the core API, the Service "types" are things like ClusterIP, NodePort, LoadBalancer, and ExternalName; "headless" is a behavioral mode achieved through the ClusterIP field.
In short: a headless Service removes the virtual IP abstraction and exposes endpoint-level discovery. It's a deliberate design choice when load-balancing is not desired or when the application itself handles routing, membership, or sharding.

質問 # 171
Can a Kubernetes Service expose multiple ports?

A. No, you can only expose one port per each Service.
B. No, because the only port you can expose is port number 443.
C. Yes, but you must specify an unambiguous name for each port.
D. Yes, the only requirement is to use different port numbers.

正解：C

解説：
Yes, a Kubernetes Service can expose multiple ports, and when it does, each port should have a unique, unambiguous name, making B correct. In the Service spec, the ports field is an array, allowing you to define multiple port mappings (e.g., 80 for HTTP and 443 for HTTPS, or grpc and metrics). Each entry can include port (Service port), targetPort (backend Pod port), and protocol.
The naming requirement becomes important because Kubernetes needs to disambiguate ports, especially when other resources refer to them. For example, an Ingress backend or some proxies/controllers can reference Service ports by name. Also, when multiple ports exist, a name helps humans and automation reliably select the correct port. Kubernetes documentation and common practice recommend naming ports whenever there is more than one, and in several scenarios it's effectively required to avoid ambiguity.
Option A is incorrect because multi-port Services are common and fully supported. Option C is insufficient: while different port numbers are necessary, naming is the correct distinguishing rule emphasized by Kubernetes patterns and required by some integrations. Option D is incorrect and nonsensical-Services can expose many ports and are not restricted to 443.
Operationally, exposing multiple ports through one Service is useful when a single backend workload provides multiple interfaces (e.g., application traffic and a metrics endpoint). You can keep stable discovery under one DNS name while still differentiating ports. The backend Pods must still listen on the target ports, and selectors determine which Pods are endpoints. The key correctness point for this question is: multi-port Services are allowed, and each port should be uniquely named to avoid confusion and integration issues.

質問 # 172
You are using Prometheus to monitor your Kubernetes cluster. You notice that several pods are
experiencing high memory usage. You want to investigate further to determine which containers within these pods are consuming the most memory. How can you effectively use Prometheus to identify these memory-intensive containers?

A. Use the 'kube_pod_container_status_memory_usage_bytes' metric to analyze the actual memory usage of each container.
B. Utilize the • metric to identify containers that are frequently restarting due to memory pressure.
C. Use the metric to identify the requested memory limits for each containa
D. Filter Prometheus queries by container name and sort by memory usage to pinpoint the memory-intensive containers.
E. Utilize the metric to identify pods that are not ready due to memory constraints.

正解：A、D

解説：
Both options B and D provide effective solutions for identifying memory-intensive containers. Option B allows you to directly analyze the 'kube_pod_container_status_memory_usage_bytes• metric, which provides the actual memory usage of each container within the pod. Option D suggests filtering Prometheus queries by container name and sorting by memory usage, enabling you to easily pinpoint containers with the highest memory consumption. While option A provides information about requested memory limits, it doesn't directly reflect the actual memory usage. Options C and E are not directly relevant to identifying memory-intensive containers.

質問 # 173
In the DevOps framework and culture, who builds, automates, and offers continuous delivery tools for developer teams?

A. Application Users
B. Cluster Operators
C. Platform Engineers
D. Application Developers

正解：C

解説：
The correct answer is C (Platform Engineers). In modern DevOps and platform operating models, platform engineering teams build and maintain the shared delivery capabilities that product/application teams use to ship software safely and quickly. This includes CI/CD pipeline templates, standardized build and test automation, artifact management (registries), deployment tooling (Helm/Kustomize/GitOps), secrets management patterns, policy guardrails, and paved-road workflows that reduce cognitive load for developers.
While application developers (B) write the application code and often contribute pipeline steps for their service, the "build, automate, and offer tooling for developer teams" responsibility maps directly to platform engineering: they provide the internal platform that turns Kubernetes and cloud services into a consumable product. This is especially common in Kubernetes-based organizations where you want consistent deployment standards, repeatable security checks, and uniform observability.
Cluster operators (D) typically focus on the health and lifecycle of the Kubernetes clusters themselves: upgrades, node pools, networking, storage, cluster security posture, and control plane reliability. They may work closely with platform engineers, but "continuous delivery tools for developer teams" is broader than cluster operations. Application users (A) are consumers of the software, not builders of delivery tooling.
In cloud-native application delivery, this division of labor is important: platform engineers enable higher velocity with safety by automating the software supply chain-builds, tests, scans, deploys, progressive delivery, and rollback. Kubernetes provides the runtime substrate, but the platform team makes it easy and safe for developers to use it repeatedly and consistently across many services.
Therefore, Platform Engineers (C) is the verified correct choice.

質問 # 174
What's the difference between a security profile and a security context?

A. Security Profiles configure Pods and Containers at runtime. Security Contexts are control plane mechanisms to enforce specific settings in the Security Profile.
B. Security Contexts configure Pods and Containers at runtime. Security profiles are control plane mechanisms to enforce specific settings in the Security Context.
C. Security Contexts configure Clusters and Namespaces at runtime. Security profiles are control plane mechanisms to enforce specific settings in the Security Context.
D. Security Profiles configure Clusters and Namespaces at runtime. Security Contexts are control plane mechanisms to enforce specific settings in the Security Profile.

正解：B

解説：
The correct answer is B. In Kubernetes, a securityContext is part of the Pod and container specification that configures runtime security settings for that workload-things like runAsUser, runAsNonRoot, Linux capabilities, readOnlyRootFilesystem, allowPrivilegeEscalation, SELinux options, seccomp profile selection, and filesystem group (fsGroup). These settings directly affect how the Pod's containers run on the node.
A security profile, in contrast, is a higher-level policy/standard enforced by the cluster control plane (typically via admission control) to ensure workloads meet required security constraints. In modern Kubernetes, this concept aligns with mechanisms like Pod Security Standards (Privileged, Baseline, Restricted) enforced through Pod Security Admission. The "profile" defines what is allowed or forbidden (for example, disallow privileged containers, disallow hostPath mounts, require non-root, restrict capabilities). The control plane enforces these constraints by validating or rejecting Pod specs that do not comply-ensuring consistent security posture across namespaces and teams.
Option A and D are incorrect because security contexts do not "configure clusters and namespaces at runtime"; security contexts apply to Pods/containers. Option C reverses the relationship: security profiles don't configure Pods at runtime; they constrain what security context settings (and other fields) are acceptable.
Practically, you can think of it as:
SecurityContext = workload-level configuration knobs (declared in manifests, applied at runtime).
SecurityProfile/Standards = cluster-level guardrails that determine which knobs/settings are permitted.
This separation supports least privilege: developers declare needed runtime settings, and cluster governance ensures those settings stay within approved boundaries. Therefore, B is the verified answer.

質問 # 175
......

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