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The CKA certification exam is designed to be challenging, and passing it requires a significant amount of preparation and practice. The Linux Foundation offers a variety of training courses and study materials to help candidates prepare for the exam. The CKA certification is highly valued by employers and IT professionals alike, as it demonstrates a high level of proficiency in managing Kubernetes clusters and ensures that the certified professional is up-to-date with the latest best practices in the industry.
The CKA program is an online, performance-based certification exam that tests candidates’ skills in managing and deploying Kubernetes clusters. CKA Exam is designed to evaluate the candidate’s ability to perform real-world tasks using Kubernetes, such as installing and configuring Kubernetes, deploying applications, managing storage, and troubleshooting common issues. CKA exam consists of 24 performance-based tasks that must be completed within three hours. Candidates must demonstrate their ability to complete these tasks efficiently and accurately to pass the exam.
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Linux Foundation Certified Kubernetes Administrator (CKA) Program Exam Sample Questions (Q11-Q16):
NEW QUESTION # 11
Perform the following tasks:
* Add an init container tohungry-bear(which has beendefined in spec file
/opt/KUCC00108/pod-spec-KUCC00108.yaml)
* The init container should createan empty file named/workdir/calm.txt
* If/workdir/calm.txtis notdetected, the pod should exit
* Once the spec file has beenupdatedwith the init containerdefinition, the pod should becreated
Answer:
Explanation:
See the solution below.
Explanation
solution
NEW QUESTION # 12
Score: 4%
Task
Scale the deployment presentation
Answer:
Explanation:
See the solution below.
Explanation
Solution:
kubectl get deployment
kubectl scale deployment.apps/presentation --replicas=6
NEW QUESTION # 13
Get list of all pods in all namespaces and write it to file "/opt/pods-list.yaml"
Answer:
Explanation:
See the solution below.
Explanation
kubectl get po -all-namespaces > /opt/pods-list.yaml
NEW QUESTION # 14
You are managing a Kubernetes cluster for a company with multiple teams working on different projects. You want to implement RBAC to ensure each team has access only to the resources they need.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Team A (developers) needs to create and manage deployments, pods, and services in the "dev" namespace.
Team B (ops) needs to manage the cluster's overall health and can access all resources in all namespaces.
Team C (security) needs to audit and monitor all cluster activity but cannot modify any resources.
Create a YAML file to define the roles and role bindings to implement this RBAC setup.
Solution (Step by Step) :
1 . Create the "dev" namespace:
kubectl create namespace dev
2. Define the "dev-team" role:
3. Create the "dev-team" role binding:
4. Define the "ops-team" role:
5. Create the "ops-team" role binding:
6. Define the "security-team" role:
7. Create the "security-team" role binding:
8. Apply the YAML file to the cluster: kubectl apply -f rbac-config.yaml
NEW QUESTION # 15
One of the nodes in your Kubernetes cluster is experiencing high CPU usage, which is affecting the performance of the entire cluster. The node is running multiple pods, and you need to identify which pod is responsible for the high CPU consumption and take steps to resolve the issue.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Identify the High-CPU Node:
- Use 'kubectl top nodes' to view the CPU usage of each node in the cluster.
- Identify the node that is experiencing the high CPU usage.
2. List Pods on the Node:
- Use 'kubectl get pods -R to list all pods in the cluster.
- Filter the pods to find those running on the high-CPU node.
- For example, 'kubectl get pods -A I grep
3. Monitor Pod CPU Usage:
- Use 'kubectl top pod -n to view the CPU usage of each pod running on the node.
- Pay attention to the CPU usage metrics for each container within the pod.
4. Examine Pod Logs:
- Use "kubectl logs -f to view the logs of the suspected high-CPU pod.
- Search for any error messages, stack traces, or other indications that the pod is experiencing excessive CPU utilization.
5. Analyze Pod Resource Requests and Limits:
- Check the pod's resource requests and limits using 'kubectl describe pod
- Ensure that the pod is not requesting or using significantly more CPU resources than it needs.
- If the CPU requests are too high, the pod might be consuming excessive CPU even when idle.
6. Troubleshooting Options:
- Based on the analysis of the logs and resource usage:
- Adjust resource limits: If the pod is requesting too much CPU, reduce its CPU requests and limits in the Deployment YAML.
- Optimize container images: Use a smaller container image to reduce the resource footprint.
- Improve application code: Identify and address any inefficient code that is causing high CPU usage.
- Scale down the pod replicas: If the pod's workload is high, reduce the number of replicas to distribute the load across fewer pods.
- Consider using a different pod scheduling strategy: For example, use a node selector or taint to run the pod on a dedicated node with more resources.
7. Monitor and Adjust:
- After making changes to the pod's resources or configuration, monitor the node's CPU usage:
- Use 'kubectl top nodes' and 'kubectl top pod' to observe the impact of the changes.
- Adjust the configuration further if needed: Continue to optimize the pod's resource usage to bring the node's CPU usage back to a healthy level.
NEW QUESTION # 16
......
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