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[Hardware] Certification Linux Foundation CKA Dump, Trustworthy CKA Exam Torrent

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【Hardware】 Certification Linux Foundation CKA Dump, Trustworthy CKA Exam Torrent

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The CKA certification is highly valued by organizations that use Kubernetes as their container orchestration platform. It is a testament to the skills and knowledge of an individual in Kubernetes administration, and it demonstrates their ability to work with Kubernetes in a production environment. The CKA Certification is also a prerequisite for other Kubernetes certifications, such as the Certified Kubernetes Application Developer (CKAD) and the Kubernetes Security Specialist (CKS) certifications.
Linux Foundation Certified Kubernetes Administrator (CKA) Program Exam Sample Questions (Q69-Q74):NEW QUESTION # 69
You have a Deployment named 'frontend-deployment' with 5 replicas of a frontend container. You need to implement a rolling update strategy that allows for a maximum of 2 pods to be unavailable at any given time. You also want to ensure that the update process is completed within a specified timeout of 8 minutes. If the update fails to complete within the timeout, the deployment should revert to the previous version. Additionally, you want to configure a 'post-start' hook for the frontend container that executes a health check script to verify the application's readiness before it starts accepting traffic.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Update the Deployment YAML:
- Update the 'replicas' to 5.
- Define 'maxUnavailable: 2' and 'maxSurge: 0' in the 'strategy.rollingUpdate' section to control the rolling update process.
- Configure a 'strategy.type' to 'RollingUpdate' to trigger a rolling update when the deployment is updated.
- Set Always' to ensure that the new image is pulled even if
it exists in the pod's local cache.
- Add a 'spec.progressDeadlineSeconds: 480' to set a timeout of 8 minutes for the update process.
- Add a 'spec.template.spec.containers[0].lifecycle.postStart' hook to define a script that executes a health check script before the container starts accepting traffic.

2. Create the Deployment: - Apply the updated YAML file using 'kubectl apply -f frontend-deployment.yaml' 3. Verify the Deployment: - Check the status of the deployment using 'kubectl get deployments frontend-deployment' to confirm the rollout and updated replica count. 4. Trigger the Automatic Update: - Push a new image to the 'my.org/frontend:latest' Docker Hub repository. 5. Monitor the Deployment: - Use 'kubectl get pods -l app=frontend' to monitor the pod updates during the rolling update process. 6. Observe Rollback if Timeout Exceeds: - If the update process takes longer than 8 minutes to complete, the deployment will be rolled back to the previous version. This can be observed using 'kubectl describe deployment frontend-deployment' and checking the 'updatedReplicas' and 'availableReplicas' fields.,

NEW QUESTION # 70
You have a Deployment running a complex application that requires significant resource allocation. How can you optimize the Deployment to use resources efficiently and avoid resource contention with other deployments?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define Resource Requests and Limits:
- Set 'requests' and 'limits' for CPU and memory for the containers in the Deployment.
- This helps in specifying the minimum resources required by the pods and the maximum resources that they can consume.

2. Optimize Container Images: - Use smaller and more efficient container images to reduce the resource footprint of the pods. 3. Use Resource Quotas: - Apply resource quotas at the namespace level to control the resource consumption of the pods within a namespace. 4. Consider Pod Disruption Budgets (PDB): - Implement PDBs to control the maximum number of pods that can be unavailable during a rolling update or pod deletion. - This ensures that the application remains available during resource-intensive events. 5. Utilize Node Affinity and Tolerations: - Configure node affinity and tolerations to schedule pods on specific nodes that have the required resources. 6. Monitor Resource Utilization: - Regularly monitor the resource utilization of the cluster and the pods. - Use tools like 'kubectl top pods', 'kubectl top nodes', and 'kubectl describe nodes' to gather resource - Adjust resource requests and limits accordingly based on the monitoring data. 7. Consider Vertical Pod Autoscaler (VPA): - Utilize VPA to automatically adjust the resource requests and limits of pods based on their actual resource consumption. 8. Optimize Application Code: - Identify and optimize resource-intensive parts of the application code to reduce resource consumption. - Use profiling tools to identify areas for improvement. 9. Implement Resource Optimization Techniques: - Utilize techniques such as caching, lazy loading, and efficient data structures to reduce resource usage within the application. 10. Explore Resource Sharing Techniques: - If possible, explore resource sharing techniques such as using shared volumes or databases to reduce overall resource consumption.,

NEW QUESTION # 71
You have a Deployment named 'api-server' with 4 replicas of an API server container. You need to implement a rolling update strategy that allows for a maximum of 2 pods to be unavailable at any given time. You also want to ensure that the update process is triggered automatically whenever a new image is pushed to the Docker Hub repository "my.org/api-server:latest'. Furthermore, you want to ensure that the update process is completed within a specified timeout of 5 minutes. If the update fails to complete within the timeout, the deployment should revert to the previous version.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Update the Deployment YAML:
- Update the 'replicas' to 4.
- Define 'maxUnavailable: 2' and maxSurge: in the 'strategy.rollingUpdate' section to control the rolling update process.
- Configure a 'strategy.type' to to trigger a rolling update when the deployment is updated.
- Set 'spec.template.spec.containers[0].imagePullPolicy: Always' to ensure that the new image is pulled even if it exists in the pod's local cache.
- Add a 'spec.progressDeadlineSeconds: 300' to set a timeout of 5 minutes for the update process.

2. Create the Deployment: - Apply the updated YAML file using 'kubectl apply -f api-server.yaml' 3. Verify the Deployment: - Check the status of the deployment using "kubectl get deployments api-server' to confirm the rollout and updated replica count. 4. Trigger the Automatic Update: - Push a new image to the 'my.org/api-server:latest' Docker Hub repository. 5. Monitor the Deployment: - Use Vxubectl get pods -l app=api-server' to monitor the pod updates during the rolling update process. 6. Observe Rollback if Timeout Exceeds: - If the update process takes longer than 5 minutes to complete, the deployment will be rolled back to the previous version. This can be observed using 'kubectl describe deployment api-server' and checking the 'updatedReplicas' and 'availableReplicas' fields.

NEW QUESTION # 72
Create 5 nginx pods in which two of them is labeled env=prod and
three of them is labeled env=dev
  • A. kubectl run nginx-dev1 --image=nginx --restart=Never --
    labels=env=dev
    kubectl run nginx-dev2 --image=nginx --restart=Never --
    labels=env=dev
    kubectl run nginx-prod1 --image=nginx --restart=Never --
    labels=env=prod
    kubectl run nginx-prod2 --image=nginx --restart=Never --
    labels=env=prod
  • B. kubectl run nginx-dev1 --image=nginx --restart=Never --
    labels=env=dev
    kubectl run nginx-dev2 --image=nginx --restart=Never --
    labels=env=dev
    kubectl run nginx-dev3 --image=nginx --restart=Never --
    labels=env=dev
    kubectl run nginx-prod1 --image=nginx --restart=Never --
    labels=env=prod
    kubectl run nginx-prod2 --image=nginx --restart=Never --
    labels=env=prod
Answer: B

NEW QUESTION # 73
You are deploying a microservices application on Kubernetes where each service has its own dedicated namespace. You want to implement a robust network security policy that allows communication between specific services only. How can you achieve this using NetworkPolicies?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define Network Policies for Each Service:
- For each service, create a NetworkPolicy that defines the allowed ingress and egress traffic.
- Example for service "service-A":

2. Apply Network Policies: - Apply the NetworkPolicies to the respective namespaces using 'kubectl apply -f networkpolicy.yaml'

NEW QUESTION # 74
......
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