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CKAD Mock Exam | CKAD VCE Dumps
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The Linux Foundation Certified Kubernetes Application Developer Exam certification exam is administered online and can be taken from anywhere in the world. Candidates must have a strong understanding of Kubernetes fundamentals, including how to deploy and manage applications in a Kubernetes cluster. They must also have a solid understanding of Linux command-line tools and basic networking concepts. Upon successful completion of the CKAD certification exam, candidates will receive a certification that demonstrates their proficiency in Kubernetes application development.
The CKAD certification exam is a rigorous test that evaluates the candidate’s ability to work with Kubernetes to deploy and manage containerized applications. Candidates are expected to have a good understanding of Kubernetes concepts and be able to use Kubernetes to solve real-world problems. CKAD Exam consists of a series of performance-based tasks that require the candidate to complete various Kubernetes-related challenges, such as deploying a multi-container application, configuring a Kubernetes cluster, creating and deploying a service, and troubleshooting a Kubernetes cluster. CKAD exam is proctored, and candidates are required to demonstrate their skills in a real-world environment. Upon completion of the exam, candidates receive a CKAD certification, which is recognized by organizations worldwide as a symbol of expertise in Kubernetes application development.
Quiz 2025 CKAD: Latest Linux Foundation Certified Kubernetes Application Developer Exam Mock Exam
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The CKAD Certification Exam is a hands-on, performance-based exam that assesses a candidate's skills in solving real-world problems related to Kubernetes. CKAD exam is conducted on a live Kubernetes cluster, and candidates are required to complete a set of practical tasks within a given time limit. These tasks cover a wide range of topics, including Kubernetes architecture, Kubernetes API objects, pod scheduling, application deployment, and troubleshooting.
Linux Foundation Certified Kubernetes Application Developer Exam Sample Questions (Q101-Q106):
NEW QUESTION # 101
Context
Given a container that writes a log file in format A and a container that converts log files from format A to format B, create a deployment that runs both containers such that the log files from the first container are converted by the second container, emitting logs in format B.
Task:
* Create a deployment named deployment-xyz in the default namespace, that:
* Includes a primary
lfccncf/busybox:1 container, named logger-dev
* includes a sidecar Ifccncf/fluentd:v0.12 container, named adapter-zen
* Mounts a shared volume /tmp/log on both containers, which does not persist when the pod is deleted
* Instructs the logger-dev
container to run the command
which should output logs to /tmp/log/input.log in plain text format, with example values:
* The adapter-zen sidecar container should read /tmp/log/input.log and output the data to /tmp/log/output.* in Fluentd JSON format. Note that no knowledge of Fluentd is required to complete this task: all you will need to achieve this is to create the ConfigMap from the spec file provided at /opt/KDMC00102/fluentd-configma p.yaml , and mount that ConfigMap to /fluentd/etc in the adapter-zen sidecar container
Answer:
Explanation:
Solution:
NEW QUESTION # 102
Refer to Exhibit.
Context
You are tasked to create a ConfigMap and consume the ConfigMap in a pod using a volume mount.
Task
Please complete the following:
* Create a ConfigMap named another-config containing the key/value pair: key4/value3
* start a pod named nginx-configmap containing a single container using the nginx image, and mount the key you just created into the pod under directory /also/a/path
Answer:
Explanation:
Solution:
NEW QUESTION # 103
You have a Deployment running a microservice that is responsible for processing user data To ensure the security of this data, you need to implement a NetworkPolicy that restricts network traffic to and from the microservice's pods.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a NetworkP01icy:
- Create a NetworkPolicy YAML file to define the traffic rules:
2. Apply the NetworkPolicy: - Apply tne NetworkPoliCY configuration to your Kubernetes cluster: basn kubectl apply -f restrict-microservice-traffic_yaml 3. Test the NetworkPoIicy: - Create a pod in a different namespace or on a different node. - Attempt to connect to the microservice pod from the new pod. - Verity that the connection is blocked as per the defined NetworkPolicy rules.
NEW QUESTION # 104
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 # 105
You have a Deployment named 'my-app-deployment running a Flask application. You want to add a liveness probe that checks if the Flask application is responding on port '5000' and a readiness probe that checks if the application is ready to receive requests. Implement these probes using Kustomize.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a base Deployment configuration:
2. Create a 'kustomization.yamr file:
3. Create 'patcnes/liveness-probe.yaml':
4. Create 'patches/readiness-probe-yaml':
5. Apply the Kustomize configuration: bash kustomize . I kubectl apply -t- - Liveness probe: This probe checks if the application is still alive and running. It uses a TCP socket to connect to port ' 5000' and waits for 15 seconds before making the first cneck. It checks every 20 seconds, and if it fails 3 times in a row, the pod is restarted. - Readiness probe: This probe checks if the application is ready to receive requests. It also uses a TCP socket to connect to port '5000'. It checks every 10 seconds and waits for 5 seconds before the first check. If it fails 2 times in a row, the pod is marked as unhealthy and excluded trom receiving traffic. Note: Make sure your Flask application is actually listening on port '5000' and responding to requests. ,
NEW QUESTION # 106
......
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