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CKAD dumps materials - exam dumps for CKAD: Linux Foundation Certified Kubernetes Application Developer Exam
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Linux Foundation Certified Kubernetes Application Developer Exam Sample Questions (Q181-Q186):
NEW QUESTION # 181
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 # 182
You have a Kubernetes cluster running a critical application With multiple pods. Recently, the application has started experiencing intermittent performance issues, with some pods exhibiting high CPU utilization and others remaining idle. You suspect a network issue might be the culprit. Describe the steps you would take to investigate this issue and determine the source of the network problem.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Gather Logs and Metrics:
- Kubernetes Events: use 'kubectl get events' to see if any events related to pods, services, or network issues are being logged.
- Container Logs: Inspect the logs of the affected pods to see if any network-related errors are reported.
- Metrics: Utilize tools like Prometheus or Grafana to monitor metrics like:
- CPU Utilization: Identify pods With high CPIJ usage.
- Network 1/0: Monitor network traffic patterns and look for anomalies.
- Latency: Check for network delays pods and services-
- Network Monitoring Tools: TOOIS like Wireshark or tcpdump can be used to capture and analyze network traffic for deeper insignts.
2. Examine Network Connectivity:
- Ping Test Run 'pings commands to check the connectivity between pods, nodes, and external services.
- Connectivity Tests: Use 'kubectl exec' to access a pod and #fform 'curl' commands to verify connectivity to services and other pods.
3. Inspect Network Configuration:
- Network Policies: Review any network policies applied to the pods, namespaces, or the cluster.
- Service Definitions: Check tne 'service' definitions to ensure tney are correctly configured and routing traffic as intended.
- Network Plugins: If using a network Plugin like Calico or Flannel, review its configuration and logs for any issues.
- Network Namespaces: Verity if the pods are using the correct network namespaces.
4. Analyze Network Traffic:
- Traffic Flow IJse tools like 'kubectl describe service' to analyze how traffic flows through the services and pods.
- Network Tracing: Utilize tracing tools to map tne flow of requests through the network and identify potential bottlenecks.
- Network Bandwidth: Check if the network bandwidth is sufficient to handle the traffic load-
5. Isolate and Resolve the Issue:
- Restart Pods: Try restarting the affected pods to see if it resolves the issue.
- Update Network Configurations: Adjust network policies, service definitions, or plugin settings if required.
- Network Troubleshooting: Utilize the collected information and network analysis tools to pinpoint the root cause.
6. Implement a Solution:
- Network Optimization: Adjust network settings or configurations to improve performance.
- Scaling: Increase the number of pods or modify deployment strategies if necessary.
- Network Monitoring: Implement continuous monitoring and alerting for potential network issues.,
NEW QUESTION # 183
You have a Deployment that runs a critical service with 5 replicas. You need to update the service with a new image, but you want to ensure that only one replica is unavailable at a time during the update process. You also want to control how long the update process can take. How would you implement this using the 'rollinglJpdate' strategy?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Update the Deployment YAMLI
- Set 'strategy.type' to 'RollingLJpdate'
- Configure 'strategy.rollingupdate.maxunavailable' to 'I' to limit the number of unavailable replicas during the update.
- Set 'strategy-rollinglJpdate.maxSurge' to to allow for a maximum of six replicas during the update process.
2. Control Update Duration (Optional): - Optionally, you can use 'strategy-rollingUpdate.partition' to control the number of pods updated at a time. This allows you to slow down the update process by updating fewer pods at once- For example, setting 'partition' to ' 2' would update only two pods at a time.
3. Create or IJpdate the Deployment: - Apply the updated YAML file using 'kubectl apply -f my-critical-service-deployment.yaml' 4. Trigger the Update: - Update the image of your application to a newer version. - You can trigger the update by pushing a new image to your container registry. 5. Monitor the Update: - Use 'kubectl get pods -I app=my-critical-service to monitor the pod updates during the rolling update process. - Observe the pods being updated one at a time, ensuring that there's always at least four replicas available. 6. Check for Successful Update: - Once the update is complete, use 'kubectl describe deployment my-critical-service' to verify that the 'updatedReplicaS field matches the 'replicas' field.,
NEW QUESTION # 184
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.
Answer:
Explanation:
See the solution below.
Explanation
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
NEW QUESTION # 185
You are deploying a microservice application that requires secure access to an external database. The database credentials are stored as environment variables Within the application container. You want to create a Kubernetes secret that securely stores these credentials and can be mounted as a file in the container.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Kubernetes Secret:
- Create a YAML file, for example, 'database-secret.yamr , with the following content:
- Replace ". ". ". and with the actual values, Base64 encoded. You can use the 'base64' command to encode the values: bash echo "your _ username" | base64 echo 'Your_password" | base64 echo "your _ host" | base64 echo "your _ port" | base64 2. Apply the Secret: - Apply the secret to your Kubernetes cluster: bash kubectl apply -f database-secret.yaml 3. Modify the Deployment: - Modify your Deployment YAML file to mount the secret as a file:
4. Apply the Updated Deployment: - Apply the updated Deployment YAML file using: bash kubectl apply -f my-microservice-deployment.yaml 5. Accessing Credentials: - The application container can now access the environment variables from the secret using 'process-env-DATABASE USER , 'process.env.DATABASE_PASSWORD', etc. Additionally, the secret data is mounted as a file at '/var/secrets/database'.
NEW QUESTION # 186
......
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