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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Kubernetes Fundamentals | 46% | - Kubernetes API
|
| Topic 2: Cloud Native Observability | 8% | - Tracing
|
| Topic 3: Cloud Native Application Delivery | 8% | - CI/CD
|
| Topic 4: Container Orchestration | 22% | - Networking
|
| Topic 5: Cloud Native Architecture | 16% | - Infrastructure and Practices
|
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NEW QUESTION # 302
How is application data maintained in containers?
Answer: D
Explanation:
Container filesystems are ephemeral: the writable layer is tied to the container lifecycle and can be lost when containers are recreated. Therefore, maintaining application data correctly means storing it in volumes, making D the correct answer. In Kubernetes, volumes provide durable or shareable storage that is mounted into containers at specific paths. Depending on the volume type, the data can persist across container restarts and even Pod rescheduling.
Kubernetes supports many volume patterns. For transient scratch data you might use emptyDir (ephemeral for the Pod's lifetime). For durable state, you typically use PersistentVolumes consumed by PersistentVolumeClaims (PVCs), backed by storage systems via CSI drivers (cloud disks, SAN/NAS, distributed storage). This decouples the application container image from its state and enables rolling updates, rescheduling, and scaling without losing data.
Options A and B ("folders") are incomplete because folders inside the container filesystem do not guarantee persistence. A folder is only as durable as the underlying storage; without a mounted volume, it lives in the container's writable layer and will disappear when the container is replaced. Option C is incorrect because "sidecar containers" are not a data durability mechanism; sidecars can help ship logs or sync data, but persistent data should still be stored on volumes (or external services like managed databases).
From an application delivery standpoint, the principle is: containers should be immutable and disposable, and state should be externalized. Volumes (and external managed services) make this possible. In Kubernetes, this is a foundational pattern enabling safe rollouts, self-healing, and portability: the platform can kill and recreate Pods freely because data is maintained independently via volumes.
Therefore, the verified correct choice is D: Store data into volumes.
NEW QUESTION # 303
Which type of Service requires manual creation of Endpoints?
Answer: C
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.
NEW QUESTION # 304
What is the difference between a Deployment and a ReplicaSet?
Answer: D
Explanation:
A Deployment is a higher-level controller that manages ReplicaSets and provides rollout/rollback behavior, so D is correct. A ReplicaSet's primary job is to ensure that a specified number of Pod replicas are running at any time, based on a label selector and Pod template. It's a fundamental "keep N Pods alive" controller.
Deployments build on that by managing the lifecycle of ReplicaSets over time. When you update a Deployment (for example, changing the container image tag or environment variables), Kubernetes creates a new ReplicaSet for the new Pod template and gradually shifts replicas from the old ReplicaSet to the new one according to the rollout strategy (RollingUpdate by default). Deployments also retain revision history, making it possible to roll back to a previous ReplicaSet if a rollout fails.
Why the other options are incorrect:
A is false: Deployments absolutely control the number of replicas via spec.replicas and can also be controlled by HPA.
B is false: ReplicaSets do guarantee that a stable number of replicas is running (that is their core purpose).
C is false: a Deployment is not "a ReplicaSet with annotations." It is a distinct API resource with additional controller logic for declarative updates, rollouts, and revision tracking.
Operationally, most teams create Deployments rather than ReplicaSets directly because Deployments are safer and more feature-complete for application delivery. ReplicaSets still appear in real clusters because Deployments create them automatically; you'll commonly see multiple ReplicaSets during rollout transitions. Understanding the hierarchy is crucial for troubleshooting: if Pods aren't behaving as expected, you often trace from Deployment → ReplicaSet → Pod, checking selectors, events, and rollout status.
So the key difference is: ReplicaSet maintains replica count; Deployment manages ReplicaSets and orchestrates updates. Therefore, D is the verified answer.
NEW QUESTION # 305
What is a sidecar container?
Answer: D
NEW QUESTION # 306
What is etcd used for in Kubernetes?
Answer: B
Explanation:
etcd serves as a distributed object store that backs the Kubernetes API.
NEW QUESTION # 307
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