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Pass Guaranteed 2025 Valid Linux Foundation New KCNA Exam Price

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Linux Foundation KCNA (Kubernetes and Cloud Native Associate) Exam is a certification program that is designed to provide individuals with the skills and knowledge required to work with Kubernetes and cloud-native technologies. Kubernetes and Cloud Native Associate certification is ideal for individuals who are interested in pursuing a career in the field of cloud computing or for those who want to enhance their skills in this area. The program covers various areas such as containerization, orchestration, networking, security, and storage.

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 Online Practice Test (Linux Foundation-KCNA-Practice-Test)

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Linux Foundation KCNA Exam is an excellent opportunity for IT professionals to validate their skills and knowledge in cloud-native technologies. Whether you are a developer, system administrator, or IT manager, the certification can help you advance your career and stay competitive in the rapidly evolving world of cloud computing.

Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q177-Q182):

NEW QUESTION # 177
What do you call the pattern where you add a second container to the pod to collect logs infor-mation?

A. Sidecar container logging
B. Application level logging
C. Node level logging
D. Cluster level logging

Answer: A

Explanation:
https://kubernetes.io/docs/concepts/cluster-administration/logging/

NEW QUESTION # 178
What feature is used for selecting the container runtime configuration?

A. RuntimeContainer
B. Runtime
C. RuntimeClass
D. RuntimeConfig

Answer: C

Explanation:
https://kubernetes.io/docs/concepts/containers/runtime-class/

NEW QUESTION # 179
You are building a distributed system with microservices deployed in a Kubernetes cluster. Each microservice has its own database. How would you manage the consistency and reliability of data across these microservices?

A. Use a combination of event sourcing and CQRS (Command Query Responsibility Segregation)
B. Implement a distributed database system
C. Use a shared database for all microservices
D. Implement a distributed transaction manager
E. Use a message broker to ensure data synchronization

Answer: A,B,D,E

Explanation:
Managing data consistency and reliability in a distributed system with microservices is a complex challenge- There are various approaches to achieve this, including: Distributed Database System: Using a distributed database system like Cassandra or MongoDB allows for data replication and fault tolerance across different nodes. This ensures data availability and consistency. Message Broker A message broker can facilitate data synchronization between microservices- Messages are used to communicate data changes and ensure that all services are aware of the latest state. Distributed Transaction Manager: A distributed transaction manager ensures that multiple transactions across different microservices are completed as a single atomic operation. This helps maintain data consistency and integrity. Event Sourcing and CQRS: Event sourcing involves storing a sequence of events that represent changes to the system. CQRS (Command Query Responsibility Segregation) separates commands (which modify data) from queries (which retrieve data). This approach can help manage data consistency and provide a more robust architecture. The best approach depends on the specific requirements of your application, such as data consistency levels, performance needs, and scalability requirements.

NEW QUESTION # 180
You have a Kubernetes cluster with a HorizontalPodAutoscaler (HPA) configured to scale a Deployment. You want to limit the maximum number of Pods the HPA can create to avoid resource exhaustion. How can you achieve this?

A. Set a resource quota for the namespace where the Deployment is running.
B. Use the •replicas' field in the Deployment to specify the maximum number of Pods.
C. Use the *maxReplicas• parameter in the HPA configuration.
D. Configure a limit range for the Deployment to restrict the number of Pods.
E. There is no direct way to limit the maximum number of Pods in an HPA.

Answer: C

Explanation:
The •maxReplicas* parameter in the HPA configuration directly controls the maximum number of Pods that the HPAcan create. Resource quotas (B) limit resource usage for the entire namespace, not specifically the HPA. Limit ranges (C) define resource limits for Pods, not their total number. The •replicas' field in the Deployment (D) sets the initial number of Pods, not the maximum.

NEW QUESTION # 181
What is the purpose of the kube-proxy component in Kubernetes?

A. Provides a secure and reliable connection between the Kubernetes control plane and nodes-
B. Manages the Kubernetes API server and handles authentication and authorization requests.
C. Stores the configuration and state of the Kubernetes cluster
D. Monitors and manages the health and status of Pods and other Kubernetes objects
E. Enables communication between Pods and services within a Kubernetes cluster.

Answer: E

Explanation:
kube-proxy acts as a network proxy that enables communication between Pods and services within a Kubernetes cluster. It handles service discovery, load balancing, and network rules for Pods.

NEW QUESTION # 182
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