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| Section | Weight | Objectives |
|---|---|---|
| Kubernetes Fundamentals | 46% | - Scheduling
|
| Container Orchestration | 22% | - Service Mesh
|
| Cloud Native Architecture | 16% | - Infrastructure and Practices
|
| Cloud Native Observability | 8% | - Logging
|
| Cloud Native Application Delivery | 8% | - CI/CD
|
>> New KCNA Test Objectives <<
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NEW QUESTION # 318
Which command retrieves container logs from a specific container in a multi-container Pod?
Answer: D
Explanation:
The kubectl logs command with the -c flag specifies the exact container within a multi-container Pod, allowing retrieval of logs from that specific container.
NEW QUESTION # 319
At which layer would distributed tracing be implemented in a cloud native deployment?
Answer: A
Explanation:
Distributed tracing is implemented primarily at the application layer, so B is correct. The reason is simple: tracing is about capturing the end-to-end path of a request as it traverses services, libraries, queues, and databases. That "request context" (trace ID, span ID, baggage) must be created, propagated, and enriched as code executes. While infrastructure components (proxies, gateways, service meshes) can generate or augment trace spans, the fundamental unit of tracing is still tied to application operations (an HTTP handler, a gRPC call, a database query, a cache lookup).
In Kubernetes-based microservices, distributed tracing typically uses standards like OpenTelemetry for instrumentation and context propagation. Application frameworks emit spans for key operations, attach attributes (route, status code, tenant, retry count), and propagate context via headers (e.g., W3C Trace Context). This is what lets you reconstruct "Service A → Service B → Service C" for one user request and identify the slow or failing hop.
Why other layers are not the best answer:
Network focuses on packets/flows, but tracing is not a packet-capture problem; it's a causal request-path problem across services.
Database spans are part of traces, but tracing is not "implemented in the database layer" overall; DB spans are one component.
Infrastructure provides the platform and can observe traffic, but without application context it can't fully represent business operations (and many useful attributes live in app code).
So the correct layer for "where tracing is implemented" is the application layer-even when a mesh or proxy helps, it's still describing application request execution across components.
NEW QUESTION # 320
Which type of Service requires manual creation of Endpoints?
Answer: D
Explanation:
A Kubernetes Service without selectors requires you to manage its backend endpoints manually, so B is correct. Normally, a Service uses a selector to match a set of Pods (by labels). Kubernetes then automatically maintains the backend list (historically Endpoints, now commonly EndpointSlice) by tracking which Pods match the selector and are Ready. This automation is one of the key reasons Services provide stable connectivity to dynamic Pods.
When you create a Service without a selector, Kubernetes has no way to know which Pods (or external IPs) should receive traffic. In that pattern, you explicitly create an Endpoints object (or EndpointSlices, depending on your approach and controller support) that maps the Service name to one or more IP:port tuples. This is commonly used to represent external services (e.g., a database running outside the cluster) while still providing a stable Kubernetes Service DNS name for in-cluster clients. Another use case is advanced migration scenarios where endpoints are controlled by custom controllers rather than label selection.
Why the other options are wrong: Service types like ClusterIP, NodePort, and LoadBalancer describe how a Service is exposed, but they do not inherently require manual endpoint management. A ClusterIP Service with selectors (D) is the standard case where endpoints are automatically created and updated. NodePort and LoadBalancer Services also typically use selectors and therefore inherit automatic endpoint management; the difference is in how traffic enters the cluster, not how backends are discovered.
Operationally, when using Services without selectors, you must ensure endpoint IPs remain correct, health is accounted for (often via external tooling), and you update endpoints when backends change. The key concept is: no selector # Kubernetes can't auto-populate endpoints # you must provide them.
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NEW QUESTION # 321
What is the name of the Kubernetes resource used to expose an application?
Answer: D
Explanation:
To expose an application running on Pods so that other components can reliably reach it, Kubernetes uses a Service, making B the correct answer. Pods are ephemeral: they can be recreated, rescheduled, and scaled, which means Pod IPs change. A Service provides a stable endpoint (virtual IP and DNS name) and load-balances traffic across the set of Pods selected by its label selector.
Services come in multiple forms. The default is ClusterIP, which exposes the application inside the cluster. NodePort exposes the Service on a static port on each node, and LoadBalancer (in supported clouds) provisions an external load balancer that routes traffic to the Service. ExternalName maps a Service name to an external DNS name. But across these variants, the abstraction is consistent: a Service defines how to access a logical group of Pods.
Option A (Port) is not a Kubernetes resource type; ports are fields within resources. Option C (DNS) is a supporting mechanism (CoreDNS creates DNS entries for Services), but DNS is not the resource you create to expose the app. Option D (Deployment) manages Pod replicas and rollouts, but it does not directly provide stable networking access; you typically pair a Deployment with a Service to expose it.
This is a core cloud-native pattern: controllers manage compute, Services manage stable connectivity, and higher-level gateways like Ingress provide L7 routing for HTTP/HTTPS. So, the Kubernetes resource used to expose an application is Service (B).
NEW QUESTION # 322
Which of the following options include only mandatory fields to create a Kubernetes object using a YAML file?
Answer: A
Explanation:
D is correct: the mandatory top-level fields for creating a Kubernetes object manifest are apiVersion, kind, metadata, and (for most objects you create) spec. These fields establish what the object is and what you want Kubernetes to do with it.
* apiVersion tells Kubernetes which API group/version schema to use (e.g., apps/v1, v1). This determines valid fields and behavior.
* kind identifies the resource type (e.g., Pod, Deployment, Service).
* metadata contains identifying information like name, namespace, and labels/annotations used for organization, selection, and automation.
* spec describes the desired state. Controllers and the kubelet reconcile actual state to match spec.
Why other choices are wrong:
* status is not a mandatory input field. It's generally written by Kubernetes controllers and reflects observed state (conditions, readiness, assigned node, etc.). Users typically do not set status when creating objects.
* template is not a universal top-level field. It exists inside some resources (notably Deployment.spec.
template), but it's not a required top-level field across Kubernetes objects.
It's true that some resources can be created without a spec (or with minimal fields), but in the exam-style framing-"mandatory fields... using a YAML file"-the canonical expected set is exactly the four in D. This aligns with how Kubernetes documentation and examples present manifests: identify the API schema and kind, give object metadata, and declare desired state.
Therefore, apiVersion + metadata + kind + spec is the only option that includes only the mandatory fields, making D the verified correct answer.
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NEW QUESTION # 323
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