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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Storage | 10% | - Understand volume mode, access modes and reclaim policies - Understand persistent volume claims primitive - Understand how to configure applications with persistent storage - Understand Storage Classes and Persistent Volumes |
| Topic 2: Services & Networking | 20% | - Understand and use CoreDNS - Use the Gateway API to manage Ingress traffic - Know how to use Ingress controllers and Ingress resources - Use ClusterIP, NodePort, LoadBalancer service types and endpoints - Understand connectivity between Pods - Define and enforce Network Policies |
| Topic 3: Troubleshooting | 30% | - Troubleshoot application failure - Understand how to monitor applications - Manage container stdout & stderr logs - Troubleshoot networking - Troubleshoot cluster component failure - Evaluate cluster and node logging |
| Topic 4: Cluster Architecture, Installation & Configuration | 25% | - Implement and configure a highly-available control plane - Manage role based access control (RBAC) - Understand extension interfaces (CNI, CSI, CRI, etc.) - Create and manage Kubernetes clusters using kubeadm - Use Helm and Kustomize to install cluster components - Manage the lifecycle of Kubernetes clusters - Prepare underlying infrastructure for installing a Kubernetes cluster - Understand CRDs, install and configure operators |
| Topic 5: Workloads & Scheduling | 15% | - Understand resource limits and requests - Use ConfigMaps and Secrets to configure applications - Understand how to run multiple schedulers and configure scheduler policies - Understand Deployments and rolling update/rollback - Understand Static Pods - Understand how scheduler works - Understand DaemonSets - Use label selectors to schedule Pods |
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NEW QUESTION # 16
Score: 5%
Task
Monitor the logs of pod bar and:
* Extract log lines corresponding to error file-not-found
* Write them to /opt/KUTR00101/bar
Answer:
Explanation:
Solution:
kubectl logs bar | grep 'unable-to-access-website' > /opt/KUTR00101/bar cat /opt/KUTR00101/bar
NEW QUESTION # 17
Create a pod as follows:
* Name: mongo
* Using Image: mongo
* In a new Kubernetes namespace named
Answer:
Explanation:
See the solution below.
Explanation
solution
NEW QUESTION # 18
You have a Deployment named 'my-app-deployment' running a complex microservice application with several pods. You suspect that some pods are experiencing high CPU utilization, causing performance issues. How would you monitor and troubleshoot the CPU usage of individual pods within this deployment?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Identify the Deployment Pods:
- Use 'kubectl get pods -l app=my-app to list the pods associated with the 'my-app-deployment' deployment.
Note the pod names.
2. Check CPU Utilization:
- Use 'kubectl top pods to check the real-time CPU usage of the pods you identified in step 1 .
- Alternatively, use 'kubectl describe pod ' to see the average CPU usage over time.
3. Analyze CPU Metrics:
- Look for pods with consistently high CPU usage (e.g., 80% or more).
- Identify the specific containers within the pod consuming the most CPU resources. You can use 'kubectl top pod -c for this.
4. Investigate the Cause:
- Review the pod logs: Use 'kubectl logs to examine the logs of the affected pods. Look for error messages, unusual patterns, or indications of resource-intensive operations.
- Examine the application code: If possible, access the source code of the application running within the affected pods. Analyze the code for potential CPU-intensive operations or bottlenecks.
- Check resource limits: Ensure that the resource requests and limits defined for the containers in the pod are appropriate. If the limits are too low, the containers might be throttled, leading to high CPU usage. Use 'kubectl describe pod to check resource limits.
5. Possible Solutions:
- Increase resource limits: If the containers are being throttled, increase their CPU limits in the Deployment YAML.
- Optimize application code: If the application code is inefficient, you might need to optimize it to reduce CPU consumption.
- Scale down pods: If the high CPU usage is due to a temporary spike in demand, consider scaling down the number of pods in the deployment.
- Use a horizontal pod autoscaler (HPA): An HPA can automatically adjust the number of pods based on CPU utilization metrics.
6. Monitor and Iterate:
- After implementing any changes, monitor the CPU usage of the pods to ensure that the issue is resolved.
- Repeat this process of monitoring, troubleshooting, and optimization until the CPU usage is within acceptable levels.
NEW QUESTION # 19
Fix a node that shows as non-ready
Answer: B
NEW QUESTION # 20
Create a deployment as follows:
* Name: nginx-random
* Exposed via a service nginx-random
* Ensure that the service & pod are accessible via their respective DNS records
* The container(s) within any pod(s) running as a part of this deployment should use the nginx Image Next, use the utility nslookup to look up the DNS records of the service & pod and write the output to
/opt/KUNW00601/service.dns and /opt/KUNW00601/pod.dns respectively.
Answer:
Explanation:
See the solution below.
Explanation
Solution:
NEW QUESTION # 21
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