CKAD EXAM DUMPS PDF & CKAD TEST VCE FREE

CKAD Exam Dumps Pdf & CKAD Test Vce Free

CKAD Exam Dumps Pdf & CKAD Test Vce Free

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Quiz Linux Foundation CKAD - First-grade Linux Foundation Certified Kubernetes Application Developer Exam Exam Dumps Pdf

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Linux Foundation Certified Kubernetes Application Developer Exam Sample Questions (Q43-Q48):

NEW QUESTION # 43
You're managing a Kubernetes cluster with various applications. You want to implement a mechanism that automatically scales deployments based on CPU utilization. The scaling should be triggered when CPU utilization exceeds 70% and should scale down to 50% utilization.

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define the Horizontal Pod Autoscaler (HPA) YAMLI
- Create an HPA YAML file named 'auto-scaler.yaml' with the following contents:

2. Apply the HPA: - Apply the HPA YAML file using 'kubectl apply -f auto-scaler.yamr. 3. Test the Auto-scaler - Monitor the CPU utilization of your deployment. When it exceeds 70%, the HPA will automatically scale up the deployment. - Observe the deployment scaling down when CPIJ utilization drops below 50%.


NEW QUESTION # 44
Context

Task:
Update the Deployment app-1 in the frontend namespace to use the existing ServiceAccount app.

Answer:

Explanation:
Solution:


NEW QUESTION # 45
You are building a data processing pipeline that involves multiple steps. Each step is implemented as a separate container image. The pipeline snould run only once, and it should nandle errors gracefully by retrying failed steps. How can you design this pipeline using Kubernetes Jobs, and how would you handle error handling and retries?

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define a Pipeline with Multiple Jobs:
- Create a Job for each stage in your data processing pipeline.
- Each Job should have a dedicated container image specific to its processing step.
2. Implement Error Handling:
- Retry Mechanism Use the 'backoffLimit' and 'retries' settings within each Job's 'spec-template-spec-containers' to specify the number of retries and the delay between retries for each step.
- Error Logging: Ensure each Job logs errors to a centralized location (e.g., a persistent volume) for debugging and analysis. You can use a sidecar container to collect and process logs.
3. Chain Jobs:
- Use a Kubernetes 'Job' to chain the individual steps, ensuring that each step runs successfully before moving to the next.
- For example, use a script within the first Job's container to trigger the next Job once it completes.
4. Example Code (Simplified):

5. Execute the Pipeline: - Run the first Job ('data-extraction'). - If it fails, it will retry up to 'backoffLimit' times. - Once successful, it can trigger the second Job ('data-transformation') using a script in its container or by creating a dependent Job. 6. Monitoring and Logging: - Use Kubernetes dashboards to monitor the progress of each Job. - Check logs for error messages and debug failures. - Implement a centralized logging solution to collect logs from all Jobs. Note: For more complex pipelines, you can consider using tools like Argo Workflows or Tekton Pipelines for more advanced orchestration and error handling capabilities.,


NEW QUESTION # 46
You are deploying a new application named 'cnat-app' that requires 5 replicas. You want to implement a rolling update strategy that ensures only one pod is unavailable at any given time, while also allowing for the creation of two new pods simultaneously. This will help to ensure that the application remains available during the update process.

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Update the Deployment YAML.
- Update the 'replicas' to 5.
- Define 'maxunavailable: and 'maxSurge: 2' in the 'strategy.roIIingUpdate' section.
- Configure a 'strategy-type' to 'Rollingupdate' to trigger a rolling update when the deployment is updated.
- Add a 'spec-template-spec-imagePullPolicy: Always' to ensure that the new image is pulled even if it exists in the pod's local cache.

2. Create the Deployment: - Apply the updated YAML file using 'kubectl apply -f chat-app-deployment.yamr 3. Verify the Deployment: - Check the status of the deployment using 'kubectl get deployments chat-app-deployment to confirm the rollout and updated replica count. 4. Trigger the Automatic Update: - Push a new image to the 'example/chat-app:latest' Docker Hub repository. 5. Monitor the Deployment - Use ' kubectl get pods -l app=chat-app' to monitor the pod updates during the rolling update process. You will observe that one pod is terminated at a time, while two new pods with the updated image are created- 6. Check for Successful Update: - Once the deployment is complete, use 'kubectl describe deployment chat-app-deployment to see that the 'updatedReplicas' field matches the 'replicas' field, indicating a successful update.


NEW QUESTION # 47
You are building a container image for a Spring Boot application that connects to a MySQL database. The application requires specific environment variables, such as the database nostname, username, password, and port. How would you define these environment variables Within the Docker-file to ensure the application runs correctly in a Kubernetes cluster?

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
1. Define Environment Variables in Docker-file:
- Utilize the 'ENV' instruction within your Dockerfile to set the necessary environment variables.
- These variables will be accessible to your Spring Boot application during runtime.
- Example:
dockerfile

2. Build the Docker Image: - Construct your Docker image using the Docker-file. - Run the following command: 'docker build -t your-image-name 3. Deploy to Kubernetes: - Create a Deployment or Pod in Kubernetes that utilizes your built image. - Ensure the pod's environment variables align with the ones defined in your Dockerfile. - Example (Deployment YAML):

4. Verify Application Functionality: - Access your deployed application in the Kubernetes cluster. - Verify that it connects successfully to the database and operates as expected.


NEW QUESTION # 48
......

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