Linux Foundation Certified Kubernetes Administrator (CKA) Program CKA Exam Dumps: Updated Questions & Answers (October 2025)

Task Summary

You are managing a WordPress Deployment in namespace relative-fawn.

Deployment has 3 replicas.

Pods are not starting due to high resource requests.

Your job:✅ Adjust CPU and memory requests so that all 3 pods evenly split the node’s capacity.

Step-by-Step Solution

1️⃣ SSH into the correct host

bash

CopyEdit

ssh cka000058

???? Skipping this will result in a zero score.

2️⃣ Check node resource capacity

You need to know the node’s CPU and memory resources.

bash

CopyEdit

kubectl describe node | grep -A5 "Capacity"

Example output:

yaml

CopyEdit

Capacity:

cpu: 3

memory: 3Gi

Let’s assume the node has:

3 CPUs

3Gi memory

So for 3 pods, divide evenly:

CPU request per pod: 1

Memory request per pod: 1Gi

⚠️ In the actual exam, check real values and divide accordingly. If the node has 4 CPUs and 8Gi, you'd allocate ~1.33 CPUs and ~2.66Gi RAM per pod (rounded reasonably).

3️⃣ Edit the Deployment

Edit the WordPress deployment in the relative-fawn namespace:

kubectl edit deployment wordpress -n relative-fawn

Look for the resources section under spec.template.spec.containers like this:

resources:

requests:

cpu: "1"

memory: "1Gi"

If the section doesn’t exist, add it manually.

Save and exit the editor (:wq if using vi).

4️⃣ Confirm changes

Wait a few seconds, then check:

kubectl get pods -n relative-fawn

Ensure all 3 pods are in Running state.

You can also describe a pod to confirm resource requests are set:

kubectl describe pod -n relative-fawn | grep -A5 "Containers"

ssh cka000058

kubectl describe node | grep -A5 "Capacity"

kubectl edit deployment wordpress -n relative-fawn

# Set CPU: 1, Memory: 1Gi (or according to node capacity)

kubectl get pods -n relative-fawn

solution

F:\Work\Data Entry Work\Data Entry\20200827\CKA\4 B.JPG

F:\Work\Data Entry Work\Data Entry\20200827\CKA\4 C.JPG

F:\Work\Data Entry Work\Data Entry\20200827\CKA\4 D.JPG

kubectl get po -o=custom-columns="POD_NAME:.metadata.name,

POD_STATUS:.status.containerStatuses[].state"

Task Summary

SSH into cka000048b

Update the nginx-config ConfigMap in the nginx-static namespace to allow TLSv1.2

Ensure the nginx-static Deployment picks up the new config

Verify the change using the provided curl command

Step-by-Step Instructions

Step 1: SSH into the correct host

ssh cka000048b

Step 2: Get the ConfigMap

kubectl get configmap nginx-config -n nginx-static -o yaml > nginx-config.yaml

Open the file for editing:

nano nginx-config.yaml

Look for the TLS configuration in the data field. You are likely to find something like:

ssl_protocols TLSv1.3;

Modify it to include TLSv1.2 as well:

ssl_protocols TLSv1.2 TLSv1.3;

Save and exit the file.

Now update the ConfigMap:

kubectl apply -f nginx-config.yaml

Step 3: Restart the NGINX pods to pick up the new ConfigMap

Pods will not reload a ConfigMap automatically unless it’s mounted in a way that supports dynamic reload and the app is watching for it (NGINX typically doesn't by default).

The safest way is to restart the pods:

Option 1: Roll the deployment

kubectl rollout restart deployment nginx-static -n nginx-static

Option 2: Delete pods to force recreation

kubectl delete pod -n nginx-static -l app=nginx-static

Step 4: Verify using curl

Use the provided curl command to confirm that TLS 1.2 is accepted:

curl --tls-max 1.2 https://web.k8s.local

A successful response means the TLS configuration is correct.

Final Command Summary

ssh cka000048b

kubectl get configmap nginx-config -n nginx-static -o yaml > nginx-config.yaml

nano nginx-config.yaml # Modify to include "ssl_protocols TLSv1.2 TLSv1.3;"

kubectl apply -f nginx-config.yaml

kubectl rollout restart deployment nginx-static -n nginx-static

# or

kubectl delete pod -n nginx-static -l app=nginx-static

curl --tls-max 1.2 https://web.k8s.local

Solution:

Task should be complete on node k8s -1 master, 2 worker for this connect use command

[student@node-1] > ssh k8s

kubectl create clusterrole deployment-clusterrole --verb=create --resource=deployments,statefulsets,daemonsets

kubectl create serviceaccount cicd-token --namespace=app-team1

kubectl create rolebinding deployment-clusterrole --clusterrole=deployment-clusterrole --serviceaccount=default:cicd-token --namespace=app-team1

solution

Persistent Volume

A persistent volume is a piece of storage in a Kubernetes cluster. PersistentVolumes are a cluster-level resource like nodes, which don’t belong to any namespace. It is provisioned by the administrator and has a particular file size. This way, a developer deploying their app on Kubernetes need not know the underlying infrastructure. When the developer needs a certain amount of persistent storage for their application, the system administrator configures the cluster so that they consume the PersistentVolume provisioned in an easy way.

Creating Persistent Volume

kind: PersistentVolume

apiVersion: v1

metadata:

name:app-data

spec:

capacity: # defines the capacity of PV we are creating

storage: 2Gi #the amount of storage we are tying to claim

accessModes: # defines the rights of the volume we are creating

- ReadWriteMany

hostPath:

path: "/srv/app-data" # path to which we are creating the volume

Challenge

Create a Persistent Volume named app-data, with access mode ReadWriteMany, storage classname shared, 2Gi of storage capacity and the host path /srv/app-data.

2. Save the file and create the persistent volume.

Image for post

3. View the persistent volume.

Our persistent volume status is available meaning it is available and it has not been mounted yet. This status will change when we mount the persistentVolume to a persistentVolumeClaim.

PersistentVolumeClaim

In a real ecosystem, a system admin will create the PersistentVolume then a developer will create a PersistentVolumeClaim which will be referenced in a pod. A PersistentVolumeClaim is created by specifying the minimum size and the access mode they require from the persistentVolume.

Challenge

Create a Persistent Volume Claim that requests the Persistent Volume we had created above. The claim should request 2Gi. Ensure that the Persistent Volume Claim has the same storageClassName as the persistentVolume you had previously created.

kind: PersistentVolume

apiVersion: v1

metadata:

name:app-data

spec:

accessModes:

- ReadWriteMany

resources:

requests:

storage: 2Gi

storageClassName: shared

2. Save and create the pvc

njerry191@cloudshell:~ (extreme-clone-2654111)$ kubect1 create -f app-data.yaml

persistentvolumeclaim/app-data created

3. View the pvc

Image for post

4. Let’s see what has changed in the pv we had initially created.

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Our status has now changed from available to bound.

5. Create a new pod named myapp with image nginx that will be used to Mount the Persistent Volume Claim with the path /var/app/config.

Mounting a Claim

apiVersion: v1

kind: Pod

metadata:

creationTimestamp: null

name: app-data

spec:

volumes:

- name:congigpvc

persistenVolumeClaim:

claimName: app-data

containers:

- image: nginx

name: app

volumeMounts:

- mountPath: "/srv/app-data "

name: configpvc

SOLUTION:

[student@node-1] > ssh ek8s

kubectl cordon k8s-master

kubectl drain k8s-master --delete-local-data --ignore-daemonsets --force

apt-get install kubeadm=1.20.1-00 kubelet=1.20.1-00 kubectl=1.20.1-00 --disableexcludes=kubernetes

kubeadm upgrade apply 1.20.1 --etcd-upgrade=false

systemctl daemon-reload

systemctl restart kubelet

kubectl uncordon k8s-master

kubectl run nginx --image=nginx --restart=Never --port=80

Kubectl logs frontend | grep -i “started” > /opt/error-logs

Task Summary

SSH into cka000022 ✅

Modify an existing Deployment:

Namespace: spline-reticulator

Deployment: front-end

Container: nginx

Expose: port 80/tcp

Create a Service:

Name: front-end-svc

Type: NodePort

Port: 80 → container port 80

✅ Step-by-Step Solution

1️⃣ SSH into the correct node

ssh cka000022

⚠️ Skipping this = zero score

2️⃣ Edit the Deployment to expose port 80

kubectl edit deployment front-end -n spline-reticulator

Under containers: → nginx, add this if not present:

ports:

- containerPort: 80

protocol: TCP

✅ This enables the container to accept traffic on port 80.

3️⃣ Create a NodePort Service

Create a file named front-end-svc.yaml:

cat < front-end-svc.yaml

apiVersion: v1

kind: Service

metadata:

name: front-end-svc

namespace: spline-reticulator

spec:

type: NodePort

selector:

app: front-end

ports:

- port: 80

targetPort: 80

protocol: TCP

EOF

⚠️ Make sure the Deployment has a matching label selector like app: front-end. You can verify with:

kubectl get deployment front-end -n spline-reticulator -o yaml | grep labels -A 2

4️⃣ Apply the service

kubectl apply -f front-end-svc.yaml

5️⃣ Verify

Check if the service is created and has a NodePort assigned:

kubectl get svc front-end-svc -n spline-reticulator

✅ You should see something like:

NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE

front-end-svc NodePort 10.96.0.123 80:3XXXX/TCP 10s

Where 3XXXX is your automatically assigned NodePort (between 30000–32767).

Final Command Summary

ssh cka000022

kubectl edit deployment front-end -n spline-reticulator

# Add:

# ports:

# - containerPort: 80

cat < front-end-svc.yaml

apiVersion: v1

kind: Service

metadata:

name: front-end-svc

namespace: spline-reticulator

spec:

type: NodePort

selector:

app: front-end

ports:

- port: 80

targetPort: 80

protocol: TCP

EOF

kubectl apply -f front-end-svc.yaml

kubectl get svc front-end-svc -n spline-reticulator