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Linux Foundation Certified Kubernetes Application Developer Exam Sample Questions (Q159-Q164):

NEW QUESTION # 159
Context

Task:
1) First update the Deployment cka00017-deployment in the ckad00017 namespace:
To run 2 replicas of the pod
Add the following label on the pod:
Role userUI
2) Next, Create a NodePort Service named cherry in the ckad00017 nmespace exposing the ckad00017-deployment Deployment on TCP port 8888

Answer:

Explanation:
Solution:

NEW QUESTION # 160
Context

Context
A pod is running on the cluster but it is not responding.
Task
The desired behavior is to have Kubemetes restart the pod when an endpoint returns an HTTP 500 on the /healthz endpoint. The service, probe-pod, should never send traffic to the pod while it is failing. Please complete the following:
* The application has an endpoint, /started, that will indicate if it can accept traffic by returning an HTTP 200. If the endpoint returns an HTTP 500, the application has not yet finished initialization.
* The application has another endpoint /healthz that will indicate if the application is still working as expected by returning an HTTP 200. If the endpoint returns an HTTP 500 the application is no longer responsive.
* Configure the probe-pod pod provided to use these endpoints
* The probes should use port 8080

Answer:

Explanation:
Solution:
apiVersion: v1
kind: Pod
metadata:
labels:
test: liveness
name: liveness-exec
spec:
containers:
- name: liveness
image: k8s.gcr.io/busybox
args:
- /bin/sh
- -c
- touch /tmp/healthy; sleep 30; rm -rf /tmp/healthy; sleep 600
livenessProbe:
exec:
command:
- cat
- /tmp/healthy
initialDelaySeconds: 5
periodSeconds: 5
In the configuration file, you can see that the Pod has a single Container. The periodSeconds field specifies that the kubelet should perform a liveness probe every 5 seconds. The initialDelaySeconds field tells the kubelet that it should wait 5 seconds before performing the first probe. To perform a probe, the kubelet executes the command cat /tmp/healthy in the target container. If the command succeeds, it returns 0, and the kubelet considers the container to be alive and healthy. If the command returns a non-zero value, the kubelet kills the container and restarts it.
When the container starts, it executes this command:
/bin/sh -c "touch /tmp/healthy; sleep 30; rm -rf /tmp/healthy; sleep 600" For the first 30 seconds of the container's life, there is a /tmp/healthy file. So during the first 30 seconds, the command cat /tmp/healthy returns a success code. After 30 seconds, cat /tmp/healthy returns a failure code.
Create the Pod:
kubectl apply -f https://k8s.io/examples/pods/probe/exec-liveness.yaml
Within 30 seconds, view the Pod events:
kubectl describe pod liveness-exec
The output indicates that no liveness probes have failed yet:
FirstSeen LastSeen Count From SubobjectPath Type Reason Message
--------- -------- ----- ---- ------------- -------- ------ -------
24s 24s 1 {default-scheduler } Normal Scheduled Successfully assigned liveness-exec to worker0
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Pulling pulling image "k8s.gcr.io/busybox"
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "k8s.gcr.io/busybox"
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Created Created container with docker id 86849c15382e; Security:[seccomp=unconfined]
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Started Started container with docker id 86849c15382e After 35 seconds, view the Pod events again:
kubectl describe pod liveness-exec
At the bottom of the output, there are messages indicating that the liveness probes have failed, and the containers have been killed and recreated.
FirstSeen LastSeen Count From SubobjectPath Type Reason Message
--------- -------- ----- ---- ------------- -------- ------ -------
37s 37s 1 {default-scheduler } Normal Scheduled Successfully assigned liveness-exec to worker0
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Pulling pulling image "k8s.gcr.io/busybox"
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "k8s.gcr.io/busybox"
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Created Created container with docker id 86849c15382e; Security:[seccomp=unconfined]
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Started Started container with docker id 86849c15382e
2s 2s 1 {kubelet worker0} spec.containers{liveness} Warning Unhealthy Liveness probe failed: cat: can't open '/tmp/healthy': No such file or directory Wait another 30 seconds, and verify that the container has been restarted:
kubectl get pod liveness-exec
The output shows that RESTARTS has been incremented:
NAME READY STATUS RESTARTS AGE
liveness-exec 1/1 Running 1 1m

NEW QUESTION # 161

Task:
A Dockerfile has been prepared at -/human-stork/build/Dockerfile
1) Using the prepared Dockerfile, build a container image with the name macque and lag 3.0. You may install and use the tool of your choice.

2) Using the tool of your choice export the built container image in OC-format and store it at -/human stork/macque 3.0 tar See the solution below.

Answer:

Explanation:
Explanation
Solution:

NEW QUESTION # 162
You have a Deployment that runs a critical service with 5 replicas. You need to update the service with a new image, but you want to ensure that only one replica is unavailable at a time during the update process. You also want to control how long the update process can take. How would you implement this using the 'rollinglJpdate' strategy?

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Update the Deployment YAMLI
- Set 'strategy.type' to 'RollingLJpdate'
- Configure 'strategy.rollingupdate.maxunavailable' to 'I' to limit the number of unavailable replicas during the update.
- Set 'strategy-rollinglJpdate.maxSurge' to to allow for a maximum of six replicas during the update process.

2. Control Update Duration (Optional): - Optionally, you can use 'strategy-rollingUpdate.partition' to control the number of pods updated at a time. This allows you to slow down the update process by updating fewer pods at once- For example, setting 'partition' to ' 2' would update only two pods at a time.

3. Create or IJpdate the Deployment: - Apply the updated YAML file using 'kubectl apply -f my-critical-service-deployment.yaml' 4. Trigger the Update: - Update the image of your application to a newer version. - You can trigger the update by pushing a new image to your container registry. 5. Monitor the Update: - Use 'kubectl get pods -I app=my-critical-service to monitor the pod updates during the rolling update process. - Observe the pods being updated one at a time, ensuring that there's always at least four replicas available. 6. Check for Successful Update: - Once the update is complete, use 'kubectl describe deployment my-critical-service' to verify that the 'updatedReplicaS field matches the 'replicas' field.,

NEW QUESTION # 163
Context

Context
As a Kubernetes application developer you will often find yourself needing to update a running application.
Task
Please complete the following:
* Update the app deployment in the kdpd00202 namespace with a maxSurge of 5% and a maxUnavailable of 2%
* Perform a rolling update of the web1 deployment, changing the Ifccncf/ngmx image version to 1.13
* Roll back the app deployment to the previous version

Answer:

Explanation:
Solution:

NEW QUESTION # 164
......

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