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Linux Foundation Certified Kubernetes Application Developer Exam Sample Questions (Q50-Q55):

NEW QUESTION # 50
Refer to Exhibit.

Task:
The pod for the Deployment named nosql in the craytisn namespace fails to start because its container runs out of resources.
Update the nosol Deployment so that the Pod:
1) Request 160M of memory for its Container
2) Limits the memory to half the maximum memory constraint set for the crayfah name space.

Answer:

Explanation:
Solution:




NEW QUESTION # 51

Context
A project that you are working on has a requirement for persistent data to be available.
Task
To facilitate this, perform the following tasks:
* Create a file on node sk8s-node-0 at /opt/KDSP00101/data/index.html with the content Acct=Finance
* Create a PersistentVolume named task-pv-volume using hostPath and allocate 1Gi to it, specifying that the volume is at /opt/KDSP00101/data on the cluster's node. The configuration should specify the access mode of ReadWriteOnce . It should define the StorageClass name exam for the PersistentVolume , which will be used to bind PersistentVolumeClaim requests to this PersistenetVolume.
* Create a PefsissentVolumeClaim named task-pv-claim that requests a volume of at least 100Mi and specifies an access mode of ReadWriteOnce
* Create a pod that uses the PersistentVolmeClaim as a volume with a label app: my-storage-app mounting the resulting volume to a mountPath /usr/share/nginx/html inside the pod

Answer:

Explanation:
See the solution below.
Explanation
Solution:










NEW QUESTION # 52
You have a Kubernetes Job that runs a Python script for data processing. The script takes 30 minutes to complete, and you need to ensure that the Job is retried up to 3 times if it fails. Additionally, you want the Job to complete within a maximum of 45 minutes. Create a Job YAML file with appropriate configuration.

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Job YAML file:

2. Apply the Job YAML file: bash kubectl apply -f data-processing-job.yaml 3. Monitor the Job: bash kubectl get jobs -w This will show the status of the Job, including its completion status and retries, if any. 4. Examine the Job's Pods: bash kubectl get pods -l job-name-data-processing-job You can use the 'kubectl logs command to cneck tne logs of tne POdS created by tne Job to investigate any potential failures. - 'backoffLimit: 3': This specifies that the Job can be retried up to 3 times in case of failures. - 'activeDeadlineSeconds: 2700': This sets the maximum duration for the Job to run (2700 seconds, which is equal to 45 minutes). If the Job exceeds this time limit, it will be automatically terminated. - 'restartPolicy: Never: This ensures that Pods created by the Job will not be restarted automatically. - 'command: ["python", "data_processing_script.py'T: This defines the command to execute inside the container. - 'resources-requests': This defines the minimum resource requirements for the container, including CPU and memory. - 'resources-limits: This can be used to define maximum resource limits for the container. This setup will attempt to run the data processing script If it fails, it will be retried up to 3 times, with an increasing delay between each retry. The Job will be terminated after 45 minutes if it does not complete successfully.,


NEW QUESTION # 53
Context

Context
A user has reported an aopticauon is unteachable due to a failing livenessProbe .
Task
Perform the following tasks:
* Find the broken pod and store its name and namespace to /opt/KDOB00401/broken.txt in the format:

The output file has already been created
* Store the associated error events to a file /opt/KDOB00401/error.txt, The output file has already been created. You will need to use the -o wide output specifier with your command
* Fix the issue.

Answer:

Explanation:
Solution:
Create the Pod:
kubectl create -f http://k8s.io/docs/tasks/configure-pod-container/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 "gcr.io/google_containers/busybox"
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "gcr.io/google_containers/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 "gcr.io/google_containers/busybox"
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "gcr.io/google_containers/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 m


NEW QUESTION # 54

Context
A container within the poller pod is hard-coded to connect the nginxsvc service on port 90 . As this port changes to 5050 an additional container needs to be added to the poller pod which adapts the container to connect to this new port. This should be realized as an ambassador container within the pod.
Task
* Update the nginxsvc service to serve on port 5050.
* Add an HAproxy container named haproxy bound to port 90 to the poller pod and deploy the enhanced pod.
Use the image haproxy and inject the configuration located at /opt/KDMC00101/haproxy.cfg, with a ConfigMap named haproxy-config, mounted into the container so that haproxy.cfg is available at
/usr/local/etc/haproxy/haproxy.cfg. Ensure that you update the args of the poller container to connect to localhost instead of nginxsvc so that the connection is correctly proxied to the new service endpoint. You must not modify the port of the endpoint in poller's args . The spec file used to create the initial poller pod is available in /opt/KDMC00101/poller.yaml See the solution below.

Answer:

Explanation:
Explanation
Solution:
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-nginx
spec:
selector:
matchLabels:
run: my-nginx
replicas: 2
template:
metadata:
labels:
run: my-nginx
spec:
containers:
- name: my-nginx
image: nginx
ports:
- containerPort: 90
This makes it accessible from any node in your cluster. Check the nodes the Pod is running on:
kubectl apply -f ./run-my-nginx.yaml
kubectl get pods -l run=my-nginx -o wide
NAME READY STATUS RESTARTS AGE IP NODE
my-nginx-3800858182-jr4a2 1/1 Running 0 13s 10.244.3.4 kubernetes-minion-905m my-nginx-3800858182-kna2y 1/1 Running 0 13s 10.244.2.5 kubernetes-minion-ljyd Check your pods' IPs:
kubectl get pods -l run=my-nginx -o yaml | grep podIP
podIP: 10.244.3.4
podIP: 10.244.2.5


NEW QUESTION # 55
......

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