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| Section | Weight | Objectives |
|---|---|---|
| Cloud Native Observability | 8% | - Monitoring & Metrics
|
| Cloud Native Application Delivery | 8% | - Deployment Strategies
|
| Container Orchestration | 22% | - Orchestration Principles
|
| Kubernetes Fundamentals | 46% | - Containerization Basics
|
| Cloud Native Architecture | 16% | - Ecosystem & Landscape
|
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질문 # 283
Which are the two primary modes for Service discovery within a Kubernetes cluster?
정답：D
설명：
Kubernetes supports two primary built-in modes of Service discovery for workloads: environment variables and DNS, making A correct.
Environment variables: When a Pod is created, kubelet can inject environment variables for Services that exist in the same namespace at the time the Pod starts. These variables include the Service host and port (for example, MY_SERVICE_HOST and MY_SERVICE_PORT). This approach is simple but has limitations: values are captured at Pod creation time and don't automatically update if Services change, and it can become cluttered in namespaces with many Services.
DNS-based discovery: This is the most common and flexible method. Kubernetes cluster DNS (usually CoreDNS) provides names like service-name.namespace.svc.cluster.local. Clients resolve the name and connect to the Service, which then routes to backend Pods. DNS scales better, is dynamic with endpoint updates, supports headless Services for per-Pod discovery, and is the default pattern for microservice communication.
The other options are not Kubernetes service discovery modes. Labels and selectors are used internally to relate Services to Pods, but they are not what application code uses for discovery (apps typically don't query selectors; they call DNS names). LDAP and RADIUS are identity/authentication protocols, not service discovery. DHCP is for IP assignment on networks, not for Kubernetes Service discovery.
Operationally, DNS is central: many applications assume name-based connectivity. If CoreDNS is misconfigured or overloaded, service-to-service calls may fail even if Pods and Services are otherwise healthy. Environment-variable discovery can still work for some legacy apps, but modern cloud-native practice strongly prefers DNS (and sometimes service meshes on top of it). The key exam concept is: Kubernetes provides service discovery via env vars and DNS.
질문 # 284
In a cloud native environment, who is usually responsible for maintaining the workloads running across the different platforms?
정답：C
설명：
B (the Site Reliability Engineering team) is correct. In cloud-native organizations, SREs are commonly responsible for the reliability, availability, and operational health of workloads across platforms (multiple clusters, regions, clouds, and supporting services). While responsibilities vary by company, the classic SRE charter is to apply software engineering to operations: build automation, standardize runbooks, manage incident response, define SLOs/SLIs, and continuously improve system reliability.
Maintaining workloads "across different platforms" implies cross-cutting operational ownership: deployments need to behave consistently, rollouts must be safe, monitoring and alerting must be uniform, and incident practices must work across environments. SRE teams typically own or heavily influence the observability stack (metrics/logs/traces), operational readiness, capacity planning, and reliability guardrails (error budgets, progressive delivery, automated rollback triggers). They also collaborate closely with platform engineering and application teams, but SRE is often the group that ensures production workloads meet reliability targets.
Why other options are less correct:
The cloud provider (A) maintains the underlying cloud services, but not your application workloads' correctness, SLOs, or operational processes.
Developers (C) do maintain application code and may own on-call in some models, but the question asks "usually" in cloud-native environments; SRE is the widely recognized function for workload reliability across platforms.
Support Engineering (D) typically focuses on customer support and troubleshooting from a user perspective, not maintaining platform workload reliability at scale.
So, the best and verified answer is B: SRE teams commonly maintain and ensure reliability of workloads across cloud-native platforms.
질문 # 285
What edge and service proxy tool is designed to be integrated with cloud native applications?
정답：B
설명：
Envoy is a high-performance edge and service proxy designed for cloud native applications, often used in service mesh architectures.
질문 # 286
How is application data maintained in containers?
정답：B
질문 # 287
Which command lists the running containers in the current Kubernetes namespace?
정답：C
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.
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질문 # 288
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