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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Observability and Maintenance | 15% | - Use built-in CLI tools to monitor Kubernetes applications - Debugging in Kubernetes - Understand API deprecation policies - Implement probes and health checks - Utilize container logs |
| Topic 2: Application Design and Build | 20% | - Define, build and modify container images - Understand multi-container Pod design patterns (e.g., sidecar, init and others) - Utilize persistent and ephemeral volumes - Choose and use the right workload resource (Deployment, DaemonSet, CronJob, etc.) |
| Topic 3: Application Environment, Configuration and Security | 25% | - Discover and use resources that extend Kubernetes (CRD, Operators) - ServiceAccounts - Understanding and defining resource requirements, limits and quotas - SecurityContexts - ConfigMaps and Secrets - Understand authentication, authorization and admission control |
| Topic 4: Application Deployment | 20% | - Use Kubernetes primitives to implement common deployment strategies (e.g., blue/green or canary) - Kustomize - Use the Helm package manager to deploy existing packages - Understand Deployments and how to perform rolling updates |
| Topic 5: Services and Networking | 20% | - Demonstrate basic understanding of NetworkPolicies - Provide and troubleshoot access to applications via services - Use Ingress rules to expose applications |
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질문 # 94
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?
정답：
설명：
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.
질문 # 95
You need to implement a mechanism for automatically rolling out new versions of your application pods. This process should be triggered by a change in tne application's container image tag in a Docker Hub repository.
정답：
설명：
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Configure the Deployment for Rolling Updates:
- IJpdate your application deployment to specify a 'rollinglJpdate' strategy
- Set 'maxunavailable' and 'maxSurge' to control the rolling update process-
- Include a 'strategy.type' to 'Rollingupdates
- Set ' imagePullPolicy' to 'Always' to ensure that new images are always pulled from the Docker Hub repository.
2. Apply the Deployment: - Apply the updated deployment using 'kubectl apply -f your-application-deployment-yamr 3. Push a New Image to Docker Hub: - UPdate your application's container image in the Docker Hub repository and push the new image With a different tag. For example, update the tag from "latest to 'v2'. 4. Monitor the Deployment: - Observe the rolling update process using 'kubectl get pods -l app=your-application'. You should see new pods with the updated image being created and old pods being terminated. 5. Verify the Update: - Once the rolling update is complete, use 'kubectl describe deployment your-application-deployment to verify that the 'updatedReplicas' field matches the 'replicas' field. This confirms that the update was successful. ,
질문 # 96
You are building a container image for a Python application that requires several external libraries. You want to ensure that the image is as small as possible while still containing all necessary dependencies. What strategy should you use to optimize the image size? Explain your approach and provide a code example.
정답：
설명：
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
I). Use a multi-stage Dockerfile: This allows you to have separate build and runtime stages. The build stage can include all necessary tools and dependencies for building the application, while the runtime stage only includes the essential components needed to run the application.
2. Minimize the base image: Choose a base image With only the necessary operating system components, tools, and libraries. I-Ising a slim image variant like 'python:3.9-slim' reduces the image Size significantly. 3. Use a lightweight package manager: Employ a lightweight package manager like 'pip' for installing Python dependencies. This helps keep the image lean 4. Optimize dependencies: Analyze your 'requirements.txt' file and remove any unnecessary dependencies or packages. This is crucial for reducing the overall size of the image. 5. Use caching wisely: In the 'Dockerfile', leverage caching by placing 'COPY commands for your application code before 'RUN' commands. This prevents unnecessary rebuilds of the image when only the application code changes. 6. Consider dependency bundling: If your application relies on specific library versions, consider using a tool like 'pip-tools' to lock down dependencies. This avoids issues where updates to external libraries introduce compatibility problems. 7. Remove unnecessary files: After building your image, inspect the image layers and identify any unneeded files. Remove these files using 'docker image prune' to further reduce image size.
질문 # 97
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.
정답：
설명：
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.,
질문 # 98
You are deploying a new microservice called 'payment-service' that requires access to a confidential data volume mounted at /sensitive- data'. This volume is mounted as a Secret in Kubernetes. The 'payment-service' container should only be allowed to access this volume. You need to configure the PodSecurityPolicy to enforce this access restriction.
정답：
설명：
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
I). Create a PodSecurityPoIicy:
- Create a YAML file for your P0dSecurityP01icy.
- Define the 'apiVersion' and 'kind'
- Add a 'metadata' section with a unique name for the policy (e.g., 'payment-service-psp').
- In the 'spec' section:
- Set 'runAsUser' to ' RunAsAny' to allow any user ID.
- Set readOnlyRootFilesystem' to 'talse' to allow modifications within the container.
- Set 'hostNetworR to 'false' to avoid using the host's network.
- Set 'allowPrivilegeEscalatiorU to 'false' to prevent privilege escalation.
- In the 'volumes' sectiom
- Define 'hostPath' as the allowed volume type with the specified path "Isensitive-data'
2. Apply the PodSecurityPolicy: - Use ' kubectl apply -f payment-service-psp.yamr to create the PodSecurityPoIicy in your cluster. 3. Create a ServiceAccount: - Create a new ServiceAccount tor the 'payment-service deployment. - Apply the ServiceAccount YAML file using 'kubectl apply -f payment-service-sa_yamr 4. Bind the PodSecurityPolicy to the ServiceAccount: - Create a RoleBinding to bind the 'payment-service-psp' to the 'payment-service' ServiceAccount - Apply the RoleBinding YAML file using "kubectl apply -f payment-service-rb.yaml'
5. Deploy the Payment Service: - Create the 'payment-service' Deployment configuration. - Specify the 'payment-service' ServiceAccount in the field. - Define the 'volumeMount tor the 'sensitive-data' volume and specify the corresponding 'volume' in the 'volumes' section. - Ensure the volume is mounted as a Secret from the 'default' namespace.
- The PodSecurityPolicy restricts the benavior of pods and their containers. - 'runAslJser' , 'readOnlyRootFilesystem', 'hostNetwork' , and sallowPrivilegeEscalation' define various security constraints for the container. - The 'volumes' section specifies allowed volume types (e.g., 'hostPath') and paths. - The ServiceAccount binds the PodSecurityPolicy to the deployment. - The ROIeBinding assigns the PodSecurityPolicy to the ServiceAccount, effectively enforcing the specified constraints. This configuration ensures that only the payment-service' deployment can access the confidential data volume mounted as a Secret in Kubernetes.
질문 # 99
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