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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Services & Networking | 20% | - Ingress resources and controllers - CNI configuration and troubleshooting - CoreDNS and service discovery - Service types: ClusterIP, NodePort, LoadBalancer, ExternalName - Network policies |
| Topic 2: Storage | 10% | - Volume types and access modes - StatefulSet storage configuration - Persistent Volumes (PV) and Persistent Volume Claims (PVC) - StorageClasses and dynamic provisioning |
| Topic 3: Workloads & Scheduling | 15% | - Pod lifecycle, init containers, probes - Deployments, rolling updates and rollbacks - Configure applications with ConfigMaps and Secrets - Pod scheduling: node selector, affinity, taints/tolerations - Resource requests, limits and autoscaling |
| Topic 4: Troubleshooting | 30% | - Worker node issues and recovery - Log collection and analysis - Cluster component health checks - Pod and application failures - Network connectivity and DNS resolution problems - Control plane component failures |
| Topic 5: Cluster Architecture, Installation & Configuration | 25% | - Manage RBAC - Implement high availability control plane - Install components via Helm / Kustomize - Work with CRDs and Operators - Create and manage clusters with kubeadm - Manage cluster lifecycle and upgrades - Understand CNI, CSI, CRI interfaces - Prepare infrastructure for cluster installation |
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NEW QUESTION # 65
Create the nginx pod with version 1.17.4 and expose it on port 80
Answer:
Explanation:
kubectl run nginx --image=nginx:1.17.4 --restart=Never -- port=80
NEW QUESTION # 66
Scale the deployment webserver to
Answer:
Explanation:
See the solution below.
Explanation
solution
NEW QUESTION # 67
Your organization uses a private DNS server for internal services and requires all Kubernetes pods to resolve names against this DNS server. You need to configure CoreDNS to forward all DNS requests to this private server.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1 . Configure CoreDNS with Forwarding:
- In the CoreDNS ConfigMap, configure the 'forward' plugin to forward all DNS requests to your private DNS server.
2. Test DNS Resolution: - Use the 'nslookup' command from a pod in your cluster to test DNS resolution for internal services. - The requests should be forwarded to the private DNS server, and the corresponding records should be returned.
NEW QUESTION # 68
You must connect to the correct host.
Failure to do so may result in a zero score.
[candidate@base] $ ssh Cka000049
Task
Perform the following tasks:
Create a new PriorityClass named high-priority for user-workloads with a value that is one less than the highest existing user-defined priority class value.
Patch the existing Deployment busybox-logger running in the priority namespace to use the high-priority priority class.
Answer:
Explanation:
Task Summary
* SSH into the correct node: cka000049
* Find the highest existing user-defined PriorityClass
* Create a new PriorityClass high-priority with a value one less
* Patch Deployment busybox-logger (in namespace priority) to use this new PriorityClass Step-by-Step Solution
1## SSH into the correct node
bash
CopyEdit
ssh cka000049
## Skipping this = zero score
2## Find the highest existing user-defined PriorityClass
Run:
bash
CopyEdit
kubectl get priorityclasses.scheduling.k8s.io
Example output:
vbnet
CopyEdit
NAME VALUE GLOBALDEFAULT AGE
default-low 1000 false 10d
mid-tier 2000 false 7d
critical-pods 1000000 true 30d
Exclude system-defined classes like system-* and the default global one (e.g., critical-pods).
Let's assume the highest user-defined value is 2000.
So your new class should be:
* Value = 1999
3## Create the high-priority PriorityClass
Create a file called high-priority.yaml:
cat <<EOF > high-priority.yaml
apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
name: high-priority
value: 1999
globalDefault: false
description: "High priority class for user workloads"
EOF
Apply it:
kubectl apply -f high-priority.yaml
4## Patch the busybox-logger deployment
Now patch the existing Deployment in the priority namespace:
kubectl patch deployment busybox-logger -n priority \
--type='merge' \
-p '{"spec": {"template": {"spec": {"priorityClassName": "high-priority"}}}}'
5## Verify your work
Confirm the patch was applied:
kubectl get deployment busybox-logger -n priority -o jsonpath='{.spec.template.spec.priorityClassName}'
# You should see:
high-priority
Also, confirm the class exists:
kubectl get priorityclass high-priority
Final Command Summary
ssh cka000049
kubectl get priorityclass
# Create the new PriorityClass
cat <<EOF > high-priority.yaml
apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
name: high-priority
value: 1999
globalDefault: false
description: "High priority class for user workloads"
EOF
kubectl apply -f high-priority.yaml
# Patch the deployment
kubectl patch deployment busybox-logger -n priority \
--type='merge' \
-p '{"spec": {"template": {"spec": {"priorityClassName": "high-priority"}}}}'
# Verify
kubectl get deployment busybox-logger -n priority -o jsonpath='{.spec.template.spec.priorityClassName}' kubectl get priorityclass high-priority
NEW QUESTION # 69
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 # 70
......
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P.S. Free 2026 Linux Foundation CKA dumps are available on Google Drive shared by BraindumpQuiz: https://drive.google.com/open?id=1EqntU7kcCWwFzF40ieO30juH9bO8jiiX