LINUX FOUNDATION IN-DEPTH EXPLANATIONS OF CKAD EXAM SUCCESS

Linux Foundation In-Depth Explanations of CKAD exam success

Linux Foundation In-Depth Explanations of CKAD exam success

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Linux Foundation Certified Kubernetes Application Developer Exam Sample Questions (Q70-Q75):

NEW QUESTION # 70
Exhibit:

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.

  • A. 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"
    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
  • B. 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

Answer: B


NEW QUESTION # 71
You have a Spring Boot application that requires access to a PostgreSQL database. Implement a sidecar container pattern using a PostgreSQL container within the same pod to provide database access for the application. Ensure tnat tne application can connect to the database through the PostgreSQL container's service name.

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define the PostgreSQL Container:
- Create a YAML file (e.g., 'postgresql-sidecar.yaml') to define the PostgreSQL container as a sidecar-
- Specify the image, resource requests, and ports for the PostgreSQL container.
- Define the container's environment variables, including the database name, username, and password.
- Add a volume mount to share a persistent volume claim (PVC) for database data.

2. Create a Persistent Volume Claim (PVC): - Create a PVC (e.g., 'postgresql-pvc.yaml') to store the PostgreSQL data. - Specify the storage class, access modes, and storage capacity for the PVC.

3. Configure the Spring Boot Applicatiom - Update your Spring Boot application to connect to the database using the environment variables you defined. - Ue the service name 'postgresql-sidecar' to access the PostgreSQL database from within the application. 4. Deploy the Pod: - Apply the YAML file to create the pod using 'kubectl apply -f spring-boot-app-with-sidecar_yaml' 5. Verify the Deployment: - Check the status of the pod using 'kubectl get pods' - Verity that both the Spring Boot application container and the PostgreSQL sidecar container are running. - Access your application's endpoint to ensure it can successfully connect to the database and perform operations. Important Notes: - Replace 'your-spring-boot-application-image:latest , 'your-password' , 'your-database-name', 'your-pvc-name' , and 'your-storage-class-name' with your actual values. - You may need to adjust the resource requests and limits for the containers based on your application's requirements. - The PostgreSQL container will initialize the database and stan the service automatically.]


NEW QUESTION # 72
You are building a microservices architecture for a web application. One of your services handles user authentication. To ensure the service remains available even if one of the pods fails, you need to implement a high-availability solution. Design a deployment strategy for the authentication service that utilizes Kubernetes features to achieve high availability and fault tolerance.

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Deploy as a StatefuISet:
- Use a StatefuISet to deploy your authentication service. StatefuISets maintain persistent storage and unique identities for each pod, ensuring that data is preserved and the service can recover from failures without losing state.

2. I-Ise Persistent Volumes: - Provision persistent volumes for each pod in the StatefulSet to store sensitive data like user credentials or session information. This ensures that the data persists even if a pod iS restarted or replaced. 3. Configure a Service with Load Balancing: - Create a Service that uses a load balancer (like a Kubernetes Ingress or external load balancer) to distribute traffic across the replicas of your authentication service. This ensures that requests are evenly distributed, even if some pods are down.

4. Implement Health Checks: - Set up liveness and readiness probes for the authentication service. Liveness probes ensure that unhealthy pods are restarted, while readiness probes ensure that only nealtny pods receive traffic. 5. Enable TLS/SSL: - Secure your authentication service with TLS/SSL to protect sensitive user data during communication. You can use certificates issued by a certificate authority (CA) or self-signed certificates for development environments. 6. Consider a Distributed Cache: - For improved performance and scalability, consider using a distributed cache like Redis or Memcached to store frequently accessed data, such as user authentication tokens. This can reduce the load on the authentication service and improve user response times.


NEW QUESTION # 73
You are building a microservice that relies on a third-party API for its functionality_ To ensure the reliability and performance of your microservice, you need to implement a robust strategy tor handling API calls. Design a deployment strategy that addresses potential issues with the third-pany API and ensures the stability of your microservice.

Answer:

Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
I). Use a Deployment:
- Deploy your microservice using a Deployment. Deployments provide a robust mechanism for managing and scaling your microservices, making it easy to update and manage your application.

2. Secure API Credentials: - Store API credentials (like API keys or tokens) securely using a Kubernetes Secret. This prevents credentials from being exposed in plain text within your deployments.

3. Implement Retry Mechanisms: - Add retry logic to your code to handle transient errors (like network hiccups or temporary service outages) during API calls. This helps ensure that your microservice can recover from temporary issues and continue functioning. 4. Utilize Rate Limiting: - Implement rate limiting to prevent your microservice from ovenvhelming the third-party API. This helps protect both your microservice and the API from performance degradation- 5. Use a Circuit Breaker Pattern: - Integrate a circuit breaker pattern into your API call handling. This pattern helps prevent cascading failures by automatically stopping requests to the third-party API it it is experiencing prolonged outages or errors- 6. Consider a Proxy or Gateway: - Implement a proxy or gateway layer between your microservice and the third-party API. This layer can help with request routing, load balancing, security, and performance optimization. 7. Monitor API Calls: - Implement monitoring and logging to track API call performance and identify potential issues. This allows you to proactively identify and address problems before they impact your microservice's reliability 8. Utilize Caching: - Consider caching API responses to reduce the load on the third-party API and improve the response time of your microservice. 9. Implement Fallbacks: - Have fallback mechanisms in place if the third-party API is unavailable. This could involve returning default data or using alternative data sources to provide a degraded but functional experience. 10. Consider Using a Service Mesh: - For complex microservice architectures, consider implementing a service mesh like Istio. Service meshes provide features like traffic management, security, observability, and resilience, which can be very beneficial for managing interactions with third-party APIs.,


NEW QUESTION # 74
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 # 75
......

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