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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Native Architecture | 16% | - Cloud Native Principles
|
| Topic 2: Container Orchestration | 22% | - Orchestration Principles
|
| Topic 3: Kubernetes Fundamentals | 46% | - Scheduling and Administration
|
| Topic 4: Cloud Native Application Delivery | 8% | - Delivery Models
|
| Topic 5: Cloud Native Observability | 8% | - Logging & Tracing
|
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NEW QUESTION # 126
Manual reclamation policy of a PV resource is known as:
Answer: C
Explanation:
The correct answer is C: Retain. In Kubernetes persistent storage, a PersistentVolume (PV) has a persistentVolumeReclaimPolicy that determines what happens to the underlying storage asset after its PersistentVolumeClaim (PVC) is deleted. The reclaim policy options historically include Delete and Retain (and Recycle, which is deprecated/removed in many modern contexts). "Manual reclamation" refers to the administrator having to manually clean up and/or rebind the storage after the claim is released-this behavior corresponds to Retain.
With Retain, when the PVC is deleted, the PV moves to a "Released" state, but the actual storage resource (cloud disk, NFS path, etc.) is not deleted automatically. Kubernetes will not automatically make that PV available for a new claim until an administrator takes action-typically cleaning the data, removing the old claim reference, and/or creating a new PV/PVC binding flow. This is important for data safety: you don't want to automatically delete sensitive or valuable data just because a claim was removed.
By contrast, Delete means Kubernetes (via the storage provisioner/CSI driver) will delete the underlying storage asset when the claim is deleted-useful for dynamic provisioning and disposable environments.
Recycle used to scrub the volume contents and make it available again, but it's not the recommended modern approach and has been phased out in favor of dynamic provisioning and explicit workflows.
So, the policy that implies manual intervention and manual cleanup/reuse is Retain, which is option C.
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NEW QUESTION # 127
The cloud native architecture centered around microservices provides a strong system that ensures ______________.
Answer: D
NEW QUESTION # 128
What is the telemetry component that represents a series of related distributed events that encode the end-to-end request flow through a distributed system?
Answer: A
Explanation:
In observability, traces represent an end-to-end view of a request as it flows through multiple services, so D is correct. Tracing is particularly important in cloud-native microservices architectures because a single user action (like "checkout" or "search") may traverse many services via HTTP/gRPC calls, message queues, and databases. Traces link those related events together so you can see where time is spent, where errors occur, and how dependencies behave.
A trace is typically composed of multiple spans (option C). A span is a single timed operation (e.g., "HTTP GET /orders", "DB query", "call payment service"). Spans include timing, attributes (tags), status/error information, and parent/child relationships. While spans are essential building blocks, the "series of related distributed events encoding end-to-end request flow" is the trace as a whole, not an individual span.
Metrics (option A) are numeric time series used for aggregation and alerting (rates, latency percentiles when derived, resource usage). Logs (option B) are discrete event records (text or structured) useful for forensic detail and debugging. Both are valuable, but neither inherently provides a stitched, causal, end-to-end request path across services. Traces do exactly that by propagating trace context (trace IDs/span IDs) across service boundaries (often via headers).
In Kubernetes environments, traces are commonly exported via OpenTelemetry instrumentation/collectors and visualized in tracing backends. Tracing enables faster incident resolution by pinpointing the slow hop, the failing downstream dependency, or unexpected fan-out. Therefore, the correct telemetry component for end-to-end distributed request flow is Traces (D).
NEW QUESTION # 129
Which of the following systems is NOT compatible with the CRI runtime interface standard?
(Typo corrected: "CRI-0" # "CRI-O")
Answer: D
Explanation:
Kubernetes uses the Container Runtime Interface (CRI) to support pluggable container runtimes. The kubelet talks to a CRI-compatible runtime via gRPC, and that runtime is responsible for pulling images and running containers. In this context, containerd and CRI-O are CRI-compatible container runtimes (or runtime stacks) used widely with Kubernetes, and dockershim historically served as a compatibility layer that allowed kubelet to talk to Docker Engine as if it were CRI (before dockershim was removed from kubelet in newer Kubernetes versions). That leaves systemd as the correct "NOT compatible with CRI" answer, so C is correct.
systemd is an init system and service manager for Linux. While it can be involved in how services (like kubelet) are started and managed on the host, it is not a container runtime implementing CRI. It does not provide CRI gRPC endpoints for kubelet, nor does it manage containers in the CRI sense.
The deeper Kubernetes concept here is separation of responsibilities: kubelet is responsible for Pod lifecycle at the node level, but it delegates "run containers" to a runtime via CRI. Runtimes like containerd and CRI-O implement that contract; Kubernetes can swap them without changing kubelet logic. Historically, dockershim translated kubelet's CRI calls into Docker Engine calls. Even though dockershim is no longer part of kubelet, it was still "CRI-adjacent" in purpose and often treated as compatible in older curricula.
Therefore, among the provided options, systemd is the only one that is clearly not a CRI-compatible runtime system, making C correct.
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NEW QUESTION # 130
What is the API that exposes resource metrics from the metrics-server?
Answer: D
Explanation:
he metrics-server exposes resource metrics through the metrics.k8s.io API for use by components like the Horizontal Pod Autoscaler.
NEW QUESTION # 131
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