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| Section | Weight | Objectives |
|---|---|---|
| Application Design and Build | 20% | - Utilize persistent and ephemeral volumes - Understand multi-container Pod design patterns - Define, build and modify container images - Choose and use appropriate workload resources |
| Application Deployment | 20% | - Work with Kustomize - Implement deployment strategies - Use Helm package manager - Manage Deployments, rolling updates and rollbacks |
| Services and Networking | 20% | - Expose applications via Services - Use Ingress rules - Troubleshoot network access - Understand and apply NetworkPolicies |
| Application Observability and Maintenance | 15% | - Understand API deprecations - Debug applications in Kubernetes - Implement probes and health checks - Work with container logs - Monitor applications using CLI tools |
| Application Environment, Configuration and Security | 25% | - Apply application security settings - Work with ConfigMaps - Configure resource requirements, limits and quotas - Use custom resources and extensions - Create and consume Secrets - Use ServiceAccounts - Understand authentication, authorization and admission control |
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NEW QUESTION # 216
You have a Deployment running a container image for a web application. The application's configuration files are currently stored within the image itself. you want to move the configuration files to a ConfigMap so that they can be updated independently or the application image. Describe the steps involved in modifying the Deployment and creating a ConfigMap to achieve this separation.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a ConfigMap:
- Create a ConfigMap using 'kubectl create configmap' with the configuration files. For example:
kubectl create configmap webapp-config -from-literal=config.json='{"port": 8080, "database_url": "mongodb://localhost27017"}'
- Replace 'config_json' with the name of your configuration file and the JSON content with your actual configuration values.
2. Modify the Deployment:
- Modify your Deployment YAML file to mount the ConfigMap as a volume. Here's an example:
- Modify your application code to read configuration files from '/etctwebapp/config' 3. Apply the Changes: - Apply the updated Deployment using 'kubectl apply -f deployment_yamr 4. Verify the Update: - Check the logs of the pods using 'kubectl logs -f You should see the application loading configuration values from the ConfigMap. 5. Update the Configuration: - You can now update the configuration files within the ConfigMap without rebuilding the image. For example.
- This will update the ConfigMap and trigger a rolling update of the Deployment, effectively updating the application configuration without rebuilding the image.
NEW QUESTION # 217 
Set Configuration Context:
[student@node-1] $ | kubectl
Config use-context k8s
Context
You sometimes need to observe a pod's logs, and write those logs to a file for further analysis.
Task
Please complete the following;
* Deploy the counter pod to the cluster using the provided YAMLspec file at /opt/KDOB00201/counter.yaml
* Retrieve all currently available application logs from the running pod and store them in the file /opt
/KDOB0020l/log_Output.txt, which has already been created
Answer:
Explanation:
See the solution below.
Explanation:
Solution:
To deploy the counter pod to the cluster using the provided YAML spec file, you can use the kubectl apply command. The apply command creates and updates resources in a cluster.
kubectl apply -f /opt/KDOB00201/counter.yaml
This command will create the pod in the cluster. You can use the kubectl get pods command to check the status of the pod and ensure that it is running.
kubectl get pods
To retrieve all currently available application logs from the running pod and store them in the file /opt
/KDOB0020l/log_Output.txt, you can use the kubectl logs command. The logs command retrieves logs from a container in a pod.
kubectl logs -f <pod-name> > /opt/KDOB0020l/log_Output.txt
Replace <pod-name> with the name of the pod.
You can also use -f option to stream the logs.
kubectl logs -f <pod-name> > /opt/KDOB0020l/log_Output.txt &
This command will retrieve the logs from the pod and write them to the /opt/KDOB0020l/log_Output.txt file.
Please note that the above command will retrieve all logs from the pod, including previous logs. If you want to retrieve only the new logs that are generated after running the command, you can add the --since flag to the kubectl logs command and specify a duration, for example --since=24h for logs generated in the last 24 hours.
Also, please note that, if the pod has multiple containers, you need to specify the container name using -c option.
kubectl logs -f <pod-name> -c <container-name> > /opt/KDOB0020l/log_Output.txt The above command will redirect the logs of the specified container to the file.
NEW QUESTION # 218
You have a Kubernetes Job that runs a Python script for data processing. The script takes 30 minutes to complete, and you need to ensure that the Job is retried up to 3 times if it fails. Additionally, you want the Job to complete within a maximum of 45 minutes. Create a Job YAML file with appropriate configuration.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Job YAML file:
2. Apply the Job YAML file: bash kubectl apply -f data-processing-job.yaml 3. Monitor the Job: bash kubectl get jobs -w This will show the status of the Job, including its completion status and retries, if any. 4. Examine the Job's Pods: bash kubectl get pods -l job-name-data-processing-job You can use the 'kubectl logs command to cneck tne logs of tne POdS created by tne Job to investigate any potential failures. - 'backoffLimit: 3': This specifies that the Job can be retried up to 3 times in case of failures. - 'activeDeadlineSeconds: 2700': This sets the maximum duration for the Job to run (2700 seconds, which is equal to 45 minutes). If the Job exceeds this time limit, it will be automatically terminated. - 'restartPolicy: Never: This ensures that Pods created by the Job will not be restarted automatically. - 'command: ["python", "data_processing_script.py'T: This defines the command to execute inside the container. - 'resources-requests': This defines the minimum resource requirements for the container, including CPU and memory. - 'resources-limits: This can be used to define maximum resource limits for the container. This setup will attempt to run the data processing script If it fails, it will be retried up to 3 times, with an increasing delay between each retry. The Job will be terminated after 45 minutes if it does not complete successfully.,
NEW QUESTION # 219
You are building a microservice application that consists of multiple Pods. Each Pod needs to access a shared database hosted in a separate Pod. How would you create a ConfigMap to store the database connection details and make it available to all Pods in the application?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
I). Create a ConfigMap:
- Create a ConfigMap named "database-config' to store the database connection details.
- Replace 'your-database-hostname' , 'your-database-port, 'your-database-user, and 'your-database-password' with the actual connection information.
2. Mount the ConfigMap to Pods: - In tne Deployment configurations for each microservice Pod, mount the 'database-config' ConfigMap as a volume. - Use 'envFror-n' to include the ConfigMap's data as environment variables for the application container - This way, the application can access the database connection details directly through environment variables.
3. Verify the Connection: - Once the Pods are deployed, you can check the application logs to ensure that they are successfully connecting to the database using the provided connection details.
NEW QUESTION # 220
You're building a Kubernetes application that manages user profiles and requires a custom resource for storing profile information. Design a custom resource definition (CRD) and its corresponding controller, ensuring that every time a profile is created or updated, a unique user ID is assigned to the profile.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create the Custom Resource Definition (CRD)I
- Define the CRD Spec:
- Apply the CRD: bash kubectl apply -f profile-crd_yaml 2. Create a Controller for the Custom Resource: - Define the Controller Logic:
- Check the 'userld' field in the output You should see the automatically generated unique user ID. This comprehensive solution demonstrates how to implement a custom resource definition and a controller for managing user profiles in Kubernetes. You can adjust the code and logic according to your specific requirements. ,
NEW QUESTION # 221
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