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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Environment, Configuration and Security | 25% | - Understand authentication, authorization and admission control - ServiceAccounts - Understanding and defining resource requirements, limits and quotas - SecurityContexts - Discover and use resources that extend Kubernetes (CRD, Operators) - ConfigMaps and Secrets |
| Topic 2: Services and Networking | 20% | - Demonstrate basic understanding of NetworkPolicies - Provide and troubleshoot access to applications via services - Use Ingress rules to expose applications |
| Topic 3: Application Deployment | 20% | - Understand Deployments and how to perform rolling updates - Kustomize - Use Kubernetes primitives to implement common deployment strategies (e.g., blue/green or canary) - Use the Helm package manager to deploy existing packages |
| Topic 4: Application Design and Build | 20% | - Define, build and modify container images - Choose and use the right workload resource (Deployment, DaemonSet, CronJob, etc.) - Utilize persistent and ephemeral volumes - Understand multi-container Pod design patterns (e.g., sidecar, init and others) |
| Topic 5: Application Observability and Maintenance | 15% | - Debugging in Kubernetes - Understand API deprecation policies - Utilize container logs - Implement probes and health checks - Use built-in CLI tools to monitor Kubernetes applications |
Viele IT-Fachleute traümt von dem Linux Foundation CKAD Zertifikat. Die Linux Foundation CKAD Zertifizierungsprüfung ist eine Prüfung, die IT-Fachkenntnisse und Erfahrungen eines Menschen testet. Um die Prüfung zu bestehen braucht man genügende Fachkenntnisse. Um diese Kenntnisse zu meistern muss man viel Zeit und Energie kosten. Fast2test ist eine Website, die Ihnen viel Zeit und Energie erspart und die relevanten Kenntnisse zur Linux Foundation CKAD Zertifizierungsprüfung ergänzt. Wenn Sie Interesse an Fast2test haben, können Sie im Internet teilweise die Fragen und Antworten zur Linux Foundation CKAD Zertifizierungsprüfung von Fast2test kostenlos als Probe herunterladen.
95. Frage
You are developing a microservices application and want to deploy it to Kubernetes using Helm. You have two services: 'user-service and 'order-service. The 'order-service depends on the "user-service'. How would you use Helm to manage these deployments, ensuring that the 'order- service' only starts after the 'user-service' is successfully deployed and running?
Antwort:
Begründung:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Helm Chart for Each Service:
- 'user-service' chart:
- Create a 'values.yamr file for the 'user-service' chart.
- Define the container image, resources, and any other necessary configurations for the 'user-service'.
- 'order-service' chart:
- Create a 'values-yamr file for the 'order-service' chart
- Define the container image, resources, and any other necessary configurations for the 'order-service'
- In tne 'values.yamr, add a dependency on the 'user-service' chart.
2. Configure Helm for Dependency Management: - Use the '-dependency-update' flag to ensure that Helm automatically updates the 'user-service chart before deploying the 'order-service' bash helm dependency update order-service 3. Deploy the Services Using Helm: - Deploy the 'user-service chart: bash helm install user-service Juser-service - Deploy the 'order-service' chart: bash helm install order-service ./order-service - Helm will automatically handle the dependency between the services, ensuring that the 'user-services is deployed before the 'order-service' 4. Verify Deployment and Dependency: - Use ' kubectl get pods -l app=user-service' and 'kubectl get pods -l app=order-service' to verify that the pods are running. - You Should observe that the 'user-service' pods are up and running before the 'order-services pods start. - You can also use 'kubectl describe pod' to see the pod events and confirm that the 'order-service' pod is waiting for the 'user-service' to be ready before starting.,
96. Frage 
Task:
Update the Deployment app-1 in the frontend namespace to use the existing ServiceAccount app.
Antwort:
Begründung:
See the solution below.
Explanation:
Solution:
97. Frage 
Context
It is always useful to look at the resources your applications are consuming in a cluster.
Task
* From the pods running in namespace cpu-stress , write the name only of the pod that is consuming the most CPU to file /opt/KDOBG030l/pod.txt, which has already been created.
Antwort:
Begründung:
See the solution below.
Explanation:
Solution:
98. Frage
You are running a web application with a backend service that needs to process daily batch jobs for generating reports. These jobs need to run at a specific time every day. Explain how you would implement these jobs using Kubernetes, ensuring they run reliably and handle potential failures.
Antwort:
Begründung:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a CronJob Resource: Define a CronJob resource in Kubernetes that specifies the schedule for your daily batch job. This resource will be responsible for triggering the job at the desired time.
2. Define a JOb Resource: Create a JOb resource tnat describes the container image and command to be executed for tne batcn job. This JOD Will be triggered by the CronJob.
3. Configure Resource Requirements: Set appropriate resource limits (CPU, memory) for the Job container to ensure it doesn't consume excessive resources. 4. Implement Error Handling: In the Python script implement proper error handling. Log any errors to a file or a logging service like Elasticsearch. 5. Enable Job Monitoring: Use tools like 'kubectl get jobs' or kubectl get pods -l job-name=daily-report-generator-job' to monitor the status of your jobs- Monitor the logs for any errors. 6. Consider a Backup/Retry Mechanism: If the job fails, you might want to implement a backup or retry mechanism. You could add a 'backoffLimit' field to the 'spec' of your Job to retry the job a certain number of times. 7. Store the Output: Ensure that the generated report is stored in a persistent location (e.g., a shared volume, cloud storage) so that it is available for furtner analysis. Important Notes: 7. Store the Output: Ensure that the generated report is stored in a persistent location (e.g., a shared volume, cloud storage) so that it is available for furtner analysis. Important Notes: Replace 'your-image-repository:latest' with the actual image repository and tag for your report generation script. Adjust the 'schedule' in the CronJob definition to match your desired execution time. You can add more sophisticated error handling and retry logic as needed based on your application's requirements. Example Script (report_generator.py): python import datetime import logging level logging
99. Frage
You are asked to prepare a canary deployment for testing a new application release.
You must connect to the correct host . Failure to do so may result in a zero score.
[candidate@base] $ ssh ckad00023
Modify the Deployments so that:
a maximum number of 10 Pods run in the moose namespace.
20% of the chipmunk-service 's traffic goes to the canary-chipmunk-deployment Pod (s).
The Service is exposed on NodePort 30000. To test its load- balancing, run
[candidate@ckad00023]
$ curl http://localhost:30000/
or open this URL in the remote desktop's browser.
Antwort:
Begründung:
See the Explanation below for complete solution.
Explanation:
ssh ckad00023
You need two outcomes in moose:
* At most 10 Pods total (across both Deployments).
* About 20% of chipmunk-service traffic goes to canary-chipmunk-deployment.
In Kubernetes Services, traffic distribution is (roughly) proportional to the number of ready endpoints behind the Service. So the standard canary trick is:
* total endpoints = 10
* canary endpoints = 2
* current endpoints = 8That gives ~20% to canary.
1) Inspect what exists
kubectl -n moose get deploy
kubectl -n moose get svc chipmunk-service -o wide
kubectl -n moose describe svc chipmunk-service
Get the Service selector (important):
kubectl -n moose get svc chipmunk-service -o jsonpath='{.spec.selector}{"\n"}' Check current replicas:
kubectl -n moose get deploy current-chipmunk-deployment -o jsonpath='{.spec.replicas}{"\n"}' kubectl -n moose get deploy canary-chipmunk-deployment -o jsonpath='{.spec.replicas}{"\n"}' List pods + labels (to confirm both Deployments' pods match the Service selector):
kubectl -n moose get pods --show-labels
2) Ensure both Deployments are behind the Service
This is the key: the pods from BOTH deployments must match the Service selector.
* If the Service selector is something like app=chipmunk, then both Deployments' pod templates must include app: chipmunk.
* If one Deployment doesn't match, patch its pod template labels to match the selector.
2A) Example: selector is app=chipmunk
(Only do this if you see the Service selector contains app=chipmunk and one of the deployments is missing it.) kubectl -n moose patch deploy current-chipmunk-deployment \
-p '{"spec":{"template":{"metadata":{"labels":{"app":"chipmunk"}}}}}'
kubectl -n moose patch deploy canary-chipmunk-deployment \
-p '{"spec":{"template":{"metadata":{"labels":{"app":"chipmunk"}}}}}'
Wait for rollouts if patches triggered new ReplicaSets:
kubectl -n moose rollout status deploy current-chipmunk-deployment
kubectl -n moose rollout status deploy canary-chipmunk-deployment
Verify endpoints now include pods from both deployments:
kubectl -n moose get endpoints chipmunk-service -o wide
3) Set replicas to enforce "max 10 pods" and "20% canary"
Set:
* current = 8
* canary = 2Total = 10.
kubectl -n moose scale deploy current-chipmunk-deployment --replicas=8
kubectl -n moose scale deploy canary-chipmunk-deployment --replicas=2
Wait until ready:
kubectl -n moose rollout status deploy current-chipmunk-deployment
kubectl -n moose rollout status deploy canary-chipmunk-deployment
Confirm total pods is 10 (or less) and all are Running/Ready:
kubectl -n moose get pods
kubectl -n moose get pods | tail -n +2 | wc -l
Confirm endpoints count matches 10:
kubectl -n moose get endpoints chipmunk-service -o jsonpath='{.subsets[*].addresses[*].ip}' | wc -w
4) Test load balancing via NodePort 30000
Run several times:
for
i in $(seq 1 30); do curl -s http://localhost:30000/; echo; done
You should see canary responses appear roughly ~20% of the time (not exact every run).
If you want a clearer signal, check which pods are endpoints and ensure 2 belong to canary and 8 to current:
kubectl -n moose get pods -l app=chipmunk -o wide
kubectl -n moose get endpoints chipmunk-service -o wide
100. Frage
......
Manchmal muss man mit große Menge von Prüfungsaufgaben üben, um eine wichtige Prüfung zu bestehen. Die Linux Foundation CKAD von uns hat diese Forderung gut erfüllt. Und mit den fachlichen Erklärungen können Sie besser die Antworten verstehen. Die Demo der Linux Foundation CKAD von unterschiedlichen Versionen werden von uns gratis angeboten. Probieren Sie mal und wählen Sie die geeignete Version für Sie! Mit unserer gemeinsamen Arbeit werden Sie bestimmt die Linux Foundation CKAD Prüfung erfolgreich bestehen!
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