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[General] 100% Pass Linux Foundation - KCNA - Valid Test Kubernetes and Cloud Native Assoc

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【General】 100% Pass Linux Foundation - KCNA - Valid Test Kubernetes and Cloud Native Assoc

Posted at yesterday 18:08      View：3 | Replies：0        Print      Only Author   [Copy Link] 1#
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Linux Foundation KCNA (Kubernetes and Cloud Native Associate) Certification Exam is a highly sought-after certification for professionals working in the field of cloud computing. Kubernetes and Cloud Native Associate certification exam is designed to test the candidate’s knowledge and skills in Kubernetes and cloud-native technologies. KCNA exam is conducted by the Linux Foundation, which is a non-profit organization that supports the development of open-source software.
Linux Foundation Kubernetes and Cloud Native Associate (KCNA) Certification Exam is a highly regarded certification that demonstrates an individual's understanding of Kubernetes and cloud-native technologies. The KCNA Certification Exam is designed to test a candidate's knowledge of Kubernetes architecture, deployment, and maintenance, as well as the fundamental concepts of cloud-native computing. Kubernetes and Cloud Native Associate certification is valuable for individuals who want to validate their skills in Kubernetes and cloud-native technologies, such as cloud engineers, DevOps engineers, software developers, and system administrators.
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Linux Foundation KCNA Certification Exam is a valuable credential for IT professionals who want to enhance their career in the rapidly growing field of cloud computing. KCNA exam is designed to test the candidate's practical knowledge and skills, rather than just theoretical knowledge. Kubernetes and Cloud Native Associate certification is recognized globally and is highly respected in the IT industry. KCNA Exam is conducted online, which makes it accessible to candidates from around the world.
Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q28-Q33):NEW QUESTION # 28
Your application requires a specific storage class for its persistent dat
a. How do you configure this storage class within your deployment YAML?
  • A. None of the above
  • B. Specify the storage class name directly within the 'spec.template.spec.containers[0].volumeMounts[0].name' field of the deployment.
  • C. Create a separate PersistentVolumeClaim (PVC) with the desired storage class and reference the PVC in the deployment's name' field.
  • D. Specify the storage class name within the field of the deployment.
  • E. Specify the storage class name within the 'spec.template.spec.containers[01.volumeMounts[0].storageClassName' field of the deployment.
Answer: C
Explanation:
The correct approach is to create a separate PersistentVolumeClaim (PVC) that specifies the desired storage class and reference the PVC in the deployments 'spec_template.spec_containers[0]_volumeMounts[0]_name' field. This ensures the PVC is automatically bound to a PV with the correct storage class. Specifying the storage class name directly within the deployment or the volumeMounts section is not the standard practice for defining storage requirements.

NEW QUESTION # 29
Which item is a Kubernetes node component?
  • A. kube-proxy
  • B. kube-scheduler
  • C. kubectl
  • D. etcd
Answer: A
Explanation:
A Kubernetes node component is a component that runs on worker nodes to support Pods and node-level networking/operations. Among the options, kube-proxy is a node component, so C is correct.
kube-proxy runs on each node and implements parts of the Kubernetes Service networking model. It watches the API server for Service and endpoint updates and then programs node networking rules (iptables/IPVS, or equivalent) so traffic sent to a Service IP/port is forwarded to one of the backend Pod endpoints. This is essential for stable virtual IPs and load distribution across Pods.
Why the other options are not node components:
kube-scheduler is a control plane component; it assigns Pods to nodes but does not run on every node as part of node functionality.
kubectl is a client CLI tool used by humans/automation; it is not a cluster component.
etcd is the control plane datastore; it stores cluster state and is not a per-node workload component.
Operationally, kube-proxy can be replaced by some modern CNI/eBPF dataplanes, but in classic Kubernetes architecture it remains the canonical node-level component for Service rule programming. Understanding which components are node vs control plane is key for troubleshooting: node issues involve kubelet/runtime/kube-proxy/CNI; control plane issues involve API server/scheduler/controller-manager/etcd.
So, the verified node component in this list is kube-proxy (C).

NEW QUESTION # 30
Your application requires specific network configurations for its pods, including custom DNS settings and network namespaces. How can you achieve this in Kubernetes?
  • A. Use a NetworkPolicy to define custom network rules for the pods.
  • B. Use a DaemonSet to deploy a network configuration agent on each node.
  • C. Modify the Kubernetes API server's network configuration settings.
  • D. Configure a Pod's security context with specific network settings.
  • E. Create a custom network plugin and integrate it with Kubernetes-
Answer: E
Explanation:
The correct answer is 'Create a custom network plugin and integrate it with Kubernetes'. Kubernetes allows you to extend its networking functionality by developing and integrating custom network plugins. These plugins can provide advanced network configurations, including custom DNS settings, network namespaces, and other specific network requirements. Options A, B, C, and E are not suitable for this scenario. 'NetworkPolicy' is used for network access control, 'Pod security context' defines security settings for a pod, 'DaemonSet' is used for deploying agents on nodes, and modifying the API server's network settings can affect the entire cluster's network configuration.

NEW QUESTION # 31
What is a Kubernetes Service Endpoint?
  • A. It is the API endpoint of our Kubernetes cluster.
  • B. It is an object that gets IP addresses of individual Pods assigned to it.
  • C. It is a name of special Pod in kube-system namespace.
  • D. It is an IP address that we can access from the Internet.
Answer: B
Explanation:
A Kubernetes Service routes traffic to a dynamic set of backends (usually Pods). The set of backend IPs and ports is represented by endpoint-tracking resources. Historically this was the Endpoints object; today Kubernetes commonly uses EndpointSlice for scalability, but the concept remains the same: endpoints represent the concrete network destinations behind a Service. That's why D is correct: a Service endpoint is an object that contains the IP addresses (and ports) of the individual Pods (or other backends) associated with that Service.
When a Service has a selector, Kubernetes automatically maintains endpoints by watching which Pods match the selector and are Ready, then publishing those Pod IPs into Endpoints/EndpointSlices. Consumers don't usually use endpoints directly; instead they call the Service DNS name, and kube-proxy (or an alternate dataplane) forwards traffic to one of the endpoints. Still, endpoints are critical because they are what make Service routing accurate and up to date during scaling events, rolling updates, and failures.
Option A confuses this with the Kubernetes API server endpoint (the cluster API URL). Option B is incorrect; there's no special "Service Endpoint Pod." Option C describes an external/public IP concept, which may exist for LoadBalancer Services, but "Service endpoint" in Kubernetes vocabulary is about the backend destinations, not the public entrypoint.
Operationally, endpoints are useful for debugging: if a Service isn't routing traffic, checking Endpoints/EndpointSlices shows whether the Service actually has backends and whether readiness is excluding Pods. This ties directly into Kubernetes service discovery and load balancing: the Service is the stable front door; endpoints are the actual backends.

NEW QUESTION # 32
You are implementing a continuous integration and continuous deployment (CI/CD) pipeline for a cloud native application running in Kubernetes. Which of the following tools can be used for building, testing, and deploying the application to the cluster?
  • A. Jenkins
  • B. CircleCl
  • C. Travis Cl
  • D. GitHub Actions
  • E. GitLab CI/CD
Answer: A,B,C,D,E
Explanation:
All of the listed tools are widely used for CI/CD pipelines and can be integrated with Kubernetes. Each tool has its own strengths and weaknesses depending on your specific needs. Here's a brief overview: Jenkins: Open-source, highly customizable, and supports a wide range of plugins. CircleCl: Cloud-based, user-friendly, and well-suited for smaller teams and projects. Travis Cl: Also cloud-based, popular for open-source projects and known for its simple setup. GitHub Actions: Native to GitHub, allows you to build, test, and deploy directly within your repository. GitLab CI/CD: Integrated with GitLab, provides a complete CI/CD solution with features for building, testing, and deploying applications.

NEW QUESTION # 33
......
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