Try Linux Foundation CKA Dumps To Conquer Success in One Go [2026]

Try Linux Foundation CKA Dumps To Conquer Success in One Go [2026]


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Linux Foundation CKA Exam Syllabus Topics:

Section Weight Objectives Storage 10% - PersistentVolumes and PersistentVolumeClaims

- Storage classes

Troubleshooting 30% - Application and networking debugging

- Cluster component troubleshooting

Workloads & Scheduling 15% - Deployments and rolling updates

- ConfigMaps and Secrets

- Scheduling constraints

Services & Networking 20% - Ingress configuration

- Services (ClusterIP, NodePort, LoadBalancer)

- Network policies

Cluster Architecture, Installation & Configuration 25% - High availability setup

- Cluster installation and configuration

- Kubernetes architecture components

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Linux Foundation Certified Kubernetes Administrator (CKA) Program Exam Sample Questions (Q78-Q83):

NEW QUESTION # 78

You have a Kubernetes cluster with a Deployment named 'web-app' that runs a web application. You need to set up a mechanism to automatically scale the deployment based on the CPU utilization of the pods. The scaling should be triggered when the average CPU utilization across all pods reaches 70%. You should set the minimum and maximum replicas to 2 and 5 respectively.

Answer:

Explanation:

See the solution below with Step by Step Explanation.

Explanation:

Solution (Step by Step) :

1. Create a Horizontal Pod Autoscaler (HPA):

- Use "kubectl create hpa' command to create an HPA resource.

- Specify the name of the HPA, the Deployment to scale, the target CPU utilization (70%), and the minimum and maximum replicas.

kubectl create hpa web-app-hpa --min=2 --max=5 --cpu-utilization-percentage=70 --target- ref=Deployment/web-app

2. Verify the HPA Creation:

- Use 'kubectl get hpa' command to check if the HPA was created successfully. You should see an HPA named 'web-app-hpa' with the configured settings.

3. Monitor the Scaling Behavior:

- You can use the 'kubectl get pods -l command to monitor the number of pods running as the CPU utilization changes.

- When the average CPU utilization across the pods reaches 70%, the HPA will automatically scale up the Deployment to add more pods.

- Conversely, when the CPU utilization falls below the threshold, the HPA will scale down the Deployment to reduce the number of pods.

Ensure that the 'metrics-server' is installed in your cluster to enable CPU utilization monitoring.,


NEW QUESTION # 79

You have a Deployment named 'worker-deployment' that runs a set of worker Pods. You need to configure a PodDisruptionBudget (PDB) for this deployment, ensuring that at least 60% of the worker Pods are always available, even during planned or unplanned disruptions. How can you achieve this?

Answer:

Explanation:

See the solution below with Step by Step Explanation.

Explanation:

Solution (Step by Step) :

1. PDB YAML Definition:


2. Explanation: - 'apiVersion: policy/vl ' : Specifies the API version for PodDisruptionBudget resources. - 'kind: PodDisruptionBudget': Specifies that this is a PodDisruptionBudget resource. - 'metadata.name: worker-pdb": Sets the name of the PDB. - 'spec.selector.matchLabels: app: worker': This selector targets the Pods labeled with 'app: worker' , ensuring the PDB applies to the 'worker-deployment' Pods. - 'spec.minAvailable: 60%': Specifies that at least 60% of the total worker Pods must remain available during disruptions. This means that if your deployment has 5 replicas, at least 3 Pods must remain running. 3. How it works: - The 'minAvailable' field in the PDB can be specified as a percentage of the total number of Pods in the deployment or as an absolute number of Pods. In this case, we are using a percentage ('600/0') to ensure a flexible approach to maintaining availability, even if the number of replicas changes. 4. Implementation: - Apply the YAML using 'kubectl apply -f worker-pdb.yaml' 5. Verification: You can verify the PDB's effectiveness by trying to delete Pods or simulating a node failure. The scheduler will prevent actions that would violate the 'minAvailable' constraint, ensuring that at least 60% of the worker Pods remain available.


NEW QUESTION # 80

Fix a node that shows as non-ready

  • A. Kubectl get nodes
  • // Check which node shows a not ready
  • kubectl describe nodes "node-name"
  • // Login to the node which shows as not ready and check the
  • systemctl start kubelet / docker
  • // Verify
  • ps -auxxww | grep -i "process-name"
  • kubectl get nodes
  • B. Kubectl get nodes
  • // Check which node shows a not ready
  • kubectl describe nodes "node-name"
  • // Login to the node which shows as not ready and check the
  • process for kubelet, docker , kube-proxy.
  • // systemctl status kubelet (or) ps -aux | grep -i "processname"
  • // If the process is not started, then start using
  • systemctl start kubelet / docker
  • // Verify
  • ps -auxxww | grep -i "process-name"
  • kubectl get nodes

Answer: B


NEW QUESTION # 81

You need to set up a load balancer for your Nginx service with the following requirements:

- Session affinity: Preserve client sessions across multiple pods, even if the pod is restarted or rescheduled.

- Health checks: Regularly check the health of Nginx pods and automatically remove unhealthy pods from the load balancer pool.

- Custom header: Add a custom header with the name "X-App-Version" and value "vl .0" to all requests to your Nginx service. How would you configure your Kubernetes resources to meet these requirements?

Answer:

Explanation:

See the solution below with Step by Step Explanation.

Explanation:

Solution (Step by Step) :

1. Define the Service:

- Create a Service of type "LoadBalancer" for your Nginx service.

- Include the sessionAffinity' field with a value of 'ClientlP' to enable client IP-based session affinity.

- Example:


2. Configure the Deployment: - In your Nginx Deployment, define a liveness probe and readiness probe to check the health of your Nginx containers. - Example:


3. Implement the Custom Header: - Configure an Ingress resource with the nginx.ingress.kubernetes.io/add-request-headeo annotation. - Example:


4. Apply the Configurations: - Apply the updated Service, Deployment, and Ingress resources using 'kubectl apply -f service.yaml -f deployment.yaml -f ingress.yamr. 5. Verify the Load Balancer: - Access the Nginx service using the external IP address provided by the LoadBalancer. - Verify session affinity by making multiple requests and observing that they are consistently routed to the same pod. - Check the "X-App-Version" header in the responses to confirm that it is set to "vl .0".


NEW QUESTION # 82

Ensure a single instance of pod nginx is running on each node of the Kubernetes cluster where nginx also represents the Image name which has to be used. Do not override any taints currently in place.

Use DaemonSet to complete this task and use ds-kusc00201 as DaemonSet name.

Answer:

Explanation:

solution






NEW QUESTION # 83

......

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