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Linux Foundation Certified Kubernetes Application Developer Exam Sample Questions (Q163-Q168):

NEW QUESTION # 163
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 # 164
You nave a Deployment tnat runs an application that requires specific environment variables to be set. These variables snould be different for each Pod in the Deployment- How would you use a Daemonset to generate unique environment variables for each Pod based on its hostname?

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
I). Create a DaemonSet:
- Define a Daemonset named 'env-generator' that will run a container on every node in the cluster.
- The container in the Daemonset will be responsible tor generating unique environment variables for each Pod.
- Replace 'your-env-generator-image:latest with the actual image you want to use for the DaemonSet.

NEW QUESTION # 165
You're tasked with deploying a containerized application that handles sensitive customer datm The security policy mandates that only containers With specific security profiles can access the dat a. How would you implement Pod Security Standards (PSS) in your Kubernetes cluster to enforce this requirement?

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define Pod Security Policies:
- Create a Pod Security Policy (PSP) resource using a YAML file.
- Define the allowed security profiles based on your security requirements.
- You can restrict things like:
- Container privileges (root or non-root)
- Allowed capabilities (e.g., 'SYS_ADMINS)
- Security context constraints (e.g., read-only root filesystem)
- Access to host resources (e.g., devices, networking)

2. Apply the Pod Security Policy: - Use 'kubectl apply -f sensitive-data-psp.yamr to apply the PSP to your cluster. 3. Modify Your Deployment (or other workload) to IJse the PSP: - Update the Deployment (or other workload) YAML file to include a 'securitycontext' field that references the PSP you created. - Ensure that the container image and configuration adhere to the constraints defined in the PSP.

4. Verify Deployment: - Use ' kubectl get pods -l app=sensitive-data-app' to ensure your pods are running. - The poos should now adhere to the specified security constraints defined by the PSP 5. Enforcement: - Kubernetes will prevent pods from running if they violate the constraints defined in the PSP - This provides a layer of security enforcement for sensitive applications. Note: PSPs are deprecated in Kubernetes 1.25 and are replaced by Pod Security Admission. For newer Kubernetes versions, you would use Pod Security Admission to enforce these security constraints. ]

NEW QUESTION # 166
Exhibit:

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

A. Solution:
B. Solution:

Answer: A

NEW QUESTION # 167
You have a Deployment named 'my-app-deployment' running three replicas of an application container. You need to implement a rolling update strategy were only one pod is updated at a time. Additionally, you need to ensure tnat tne update process is triggered automatically whenever a new image is pushed to your private Docker registry.

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 2.
- Define 'maxunavailable: 1' and 'maxSurge: O' in the 'strategy-rollinglJpdate' section to control the rolling update process.
- Configure a 'strategy.types to 'Rollingupdates to trigger a rolling update wnen the deployment is updated.
- Add a 'spec-template.spec.imagePullP01icy: Always' to ensure tnat tne new image is pulled even if it exists in the pod's local cache.
- Add a 'spec-template-spec-imagePullSecrets' section to provide access to your private Docker registry. Replace 'registry-secret with the actual name of your secret.

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

NEW QUESTION # 168
......

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