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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Native Application Delivery | 8% | - Deployment Strategies
|
| Topic 2: Cloud Native Observability | 8% | - Monitoring & Metrics
|
| Topic 3: Cloud Native Architecture | 16% | - Ecosystem & Landscape
|
| Topic 4: Kubernetes Fundamentals | 46% | - Kubernetes Core Concepts
|
| Topic 5: Container Orchestration | 22% | - Security & Troubleshooting
|
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NEW QUESTION # 257
Which of the following Pod Security Standards enforces the most restrictive settings, designed for security-critical workloads?
Answer: C
Explanation:
The Restricted Pod Security Standard applies the strictest security controls, enforcing strong limitations on privileges, capabilities, and access to minimize the risk in security-critical workloads.
NEW QUESTION # 258
What is the practice of bringing financial accountability to the variable spend model of cloud resources?
Answer: B
Explanation:
The practice of bringing financial accountability to cloud spending-where costs are variable and usage- based-is called FinOps, so D is correct. FinOps (Financial Operations) is an operating model and culture that helps organizations manage cloud costs by connecting engineering, finance, and business teams. Because cloud resources can be provisioned quickly and billed dynamically, traditional budgeting approaches often fail to keep pace. FinOps addresses this by introducing shared visibility, governance, and optimization processes that enable teams to make cost-aware decisions while still moving fast.
In Kubernetes and cloud-native architectures, variable spend shows up in many ways: autoscaling node pools, over-provisioned resource requests, idle clusters, persistent volumes, load balancers, egress traffic, managed services, and observability tooling. FinOps practices encourage tagging/labeling for cost attribution, defining cost KPIs, enforcing budget guardrails, and continuously optimizing usage (right-sizing resources, scaling policies, turning off unused environments, and selecting cost-effective architectures).
Why the other options are incorrect: FaaS (Function as a Service) is a compute model (serverless), not a financial accountability practice. DevOps is a cultural and technical practice focused on collaboration and delivery speed, not specifically cloud cost accountability (though it can complement FinOps). CloudCost is not a widely recognized standard term in the way FinOps is.
In practice, FinOps for Kubernetes often involves improving resource efficiency: aligning requests/limits with real usage, using HPA/VPA appropriately, selecting instance types that match workload profiles, managing cluster autoscaler settings, and allocating shared platform costs to teams via labels/namespaces. It also includes forecasting and anomaly detection, because cloud-native spend can spike quickly due to misconfigurations (e.g., runaway autoscaling or excessive log ingestion).
So, the correct term for financial accountability in cloud variable spend is FinOps (D).
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NEW QUESTION # 259
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.
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NEW QUESTION # 260
Which of the following container runtime is planned to be deprecated in Kubernetes 1.20 and high-er?
Answer: E
Explanation:
https://kubernetes.io/blog/2020/12/02/dont-panic-kubernetes-and-docker/
NEW QUESTION # 261
In which framework do the developers no longer have to deal with capacity, deployments, scaling and fault tolerance, and OS?
Answer: D
Explanation:
Serverless is the model where developers most directly avoid managing server capacity, OS operations, and much of the deployment/scaling/fault-tolerance mechanics, which is why D is correct. In serverless computing (commonly Function-as-a-Service, FaaS, and managed serverless container platforms), the provider abstracts away the underlying servers. You typically deploy code (functions) or a container image, define triggers (HTTP events, queues, schedules), and the platform automatically provisions the required compute, scales it based on demand, and handles much of the availability and fault tolerance behind the scenes.
It's important to compare this to Kubernetes: Kubernetes does automate scheduling, self-healing, rolling updates, and scaling, but it still requires you (or your platform team) to design and operate cluster capacity, node pools, upgrades, runtime configuration, networking, and baseline reliability controls. Even in managed Kubernetes services, you still choose node sizes, scale policies, and operational configuration. Kubernetes reduces toil, but it does not eliminate infrastructure concerns in the same way serverless does.
Docker Swarm and Mesos are orchestration platforms that schedule workloads, but they also require managing the underlying capacity and OS-level aspects. They are not "no longer have to deal with capacity and OS" frameworks.
From a cloud native viewpoint, serverless is about consuming compute as an on-demand utility. Kubernetes can be a foundation for a serverless experience (for example, with event-driven autoscaling or serverless frameworks), but the pure framework that removes the most operational burden from developers is serverless.
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NEW QUESTION # 262
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