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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Kubernetes Fundamentals | 46% | - Kubernetes Architecture
|
| Topic 2: Cloud Native Application Delivery | 8% | - GitOps
|
| Topic 3: Cloud Native Observability | 8% | - Logging
|
| Topic 4: Cloud Native Architecture | 16% | - Infrastructure and Practices
|
| Topic 5: Container Orchestration | 22% | - Security
|
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NEW QUESTION # 206
What happens with a regular Pod running in Kubernetes when a node fails?
Answer: C
Explanation:
B is correct: when a node fails, Kubernetes does not "move" the same Pod instance; instead, a new Pod object (new UID) is created to replace it-assuming the Pod is managed by a controller (Deployment
/ReplicaSet, StatefulSet, etc.). A Pod is an API object with a unique identifier (UID) and is tightly associated with the node it's scheduled to via spec.nodeName. If the node becomes unreachable, that original Pod cannot be restarted elsewhere because it was bound to that node.
Kubernetes' high availability comes from controllers maintaining desired state. For example, a Deployment desires N replicas. If a node fails and the replicas on that node are lost, the controller will create replacement Pods, and the scheduler will place them onto healthy nodes. These replacement Pods will be "near-identical" in spec (same template), but they are still new instances with new UIDs and typically new IPs.
Why the other options are wrong:
* A is incorrect because the UID does not remain the same-Kubernetes creates a new Pod object rather than reusing the old identity.
* C is incorrect; pods are not restricted to the same node after failure. The whole point of orchestration is to reschedule elsewhere.
* D is incorrect; rescheduling does not require special explicit configuration for typical controller- managed workloads. The controller behavior is standard. (If it's a bare Pod without a controller, it will not be recreated automatically.) This also ties to the difference between "regular Pod" vs controller-managed workloads: a standalone Pod is not self-healing by itself, while a Deployment/ReplicaSet provides that resilience. In typical production design, you run workloads under controllers specifically so node failure triggers replacement and restores replica count.
Therefore, the correct outcome is B.
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NEW QUESTION # 207
You need to restrict access to your Kubernetes cluster from a specific IP address range. How would you implement this security measure?
Answer: D
Explanation:
The most appropriate way to restrict access to a Kubernetes cluster from a specific IP address range is to configure a NetworkPolicy. NetworkPolicies allow you to define ingress and egress rules based on source and destination IP addresses, ports, and other network attributes. This provides a flexible and granular way to control network traffic to and from pods within the cluster. Options B, C, and D are not suitable for this scenario as they focus on API server authorization, admission control, or node-level firewall rules, which are not specifically designed for IP address-based access control. Option E is incorrect because Service of type 'LoadBalancer' primarily deals with external access and doesn't provide direct IP address-based access control within the cluster-
NEW QUESTION # 208
What Kubernetes control plane component exposes the programmatic interface used to create, manage and interact with the Kubernetes objects?
Answer: C
Explanation:
The kube-apiserver is the front door of the Kubernetes control plane and exposes the programmatic interface used to create, read, update, delete, and watch Kubernetes objects-so C is correct. Every interaction with cluster state ultimately goes through the Kubernetes API. Tools like kubectl, client libraries, GitOps controllers, operators, and core control plane components (scheduler and controllers) all communicate with the API server to submit desired state and to observe current state.
The API server is responsible for handling authentication (who are you?), authorization (what are you allowed to do?), and admission control (should this request be allowed and possibly mutated/validated?). After a request passes these gates, the API server persists the object's desired state to etcd (the backing datastore) and returns a response. The API server also provides a watch mechanism so controllers can react to changes efficiently, enabling Kubernetes' reconciliation model.
It's important to distinguish this from the other options. etcd stores cluster data but does not expose the cluster's primary user-facing API; it's an internal datastore. kube-controller-manager runs control loops (controllers) that continuously reconcile resources (like Deployments, Nodes, Jobs) but it consumes the API rather than exposing it. kube-proxy is a node-level component implementing Service networking rules and is unrelated to the control-plane API endpoint.
Because Kubernetes is "API-driven," the kube-apiserver is central: if it is unavailable, you cannot create workloads, update configurations, or even reliably observe cluster state. This is why high availability architectures prioritize multiple API server instances behind a load balancer, and why securing the API server (RBAC, TLS, audit) is a primary operational concern.
NEW QUESTION # 209
What components are common in a service mesh?
Answer: C
Explanation:
A service mesh is an architectural pattern that manages service-to-service communication in a microservices environment by inserting a dedicated networking layer. The two most common building blocks you'll see across service mesh implementations are (1) a data plane of proxies and (2) a control plane that configures and manages those proxies-this aligns best with "service proxy and control plane," option D.
In practice, the data plane is usually implemented via sidecar proxies (or sometimes node/ambient proxies) that sit "next to" workloads and handle traffic functions such as mTLS encryption, retries, timeouts, load balancing policies, traffic splitting, and telemetry generation. These proxies can capture inbound and outbound traffic without requiring changes to application code, which is one of the defining benefits of a mesh.
The control plane provides the management layer: it distributes policy and configuration to the proxies (routing rules, security policies, identities/certificates), discovers services/endpoints, and often coordinates certificate rotation and workload identity. In Kubernetes environments, meshes typically integrate with the Kubernetes API for service discovery and configuration.
Option C is close in spirit but uses non-standard wording ("runtime plane" is not a typical service mesh term; "control plane" is). Options A and B describe capabilities that may exist in a mesh ecosystem (telemetry, circuit breaking), but they are not the universal "core components" across meshes. Tracing/log storage, for example, is usually handled by external observability backends (e.g., Jaeger, Tempo, Loki) rather than being intrinsic "mesh components." So, the most correct and broadly accepted answer is D: service proxy and control plane.
NEW QUESTION # 210
Which command retrieves container logs from a specific container in a multi-container Pod?
Answer: C
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 # 211
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