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| Section | Objectives |
|---|---|
| Services and Networking | - Ingress basics - Services (ClusterIP, NodePort) - Pod networking concepts |
| Application Design and Build | - Define, build and modify container images - Understand Jobs and CronJobs - Understand multi-container Pod design patterns |
| State Persistence | - Storage classes and volume mounting - PersistentVolumes and PersistentVolumeClaims |
| Application Environment, Configuration and Security | - Security contexts and service accounts - ConfigMaps and Secrets usage |
| Application Deployment | - Understand rolling updates and rollbacks - Use Kubernetes primitives to implement deployments |
| Application Observability and Maintenance | - Monitor and troubleshoot applications - Understand probes and health checks |
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質問 # 203
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.
正解：
解説：
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.]
質問 # 204
Refer to 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
正解：
解説：
Solution:
質問 # 205 
Context
You are asked to prepare a Canary deployment for testing a new application release.
Task:
A Service named krill-Service in the goshark namespace points to 5 pod created by the Deployment named current-krill-deployment
1) Create an identical Deployment named canary-kill-deployment, in the same namespace.
2) Modify the Deployment so that:
-A maximum number of 10 pods run in the goshawk namespace.
-40% of the krill-service 's traffic goes to the canary-krill-deployment pod(s)
正解：
解説：
See the solution below.
Explanation:
Solution:
質問 # 206
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.
正解：
解説：
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.,
質問 # 207
You have a Deployment named 'redis-deployment that runs 3 replicas of a Redis container. You need to implement a rolling update strategy that allows tor a maximum ot one pod to be unavailable at any given time during tne update process, With the new pod becoming available before the old pod is terminated. Additionally, you want to ensure that the update process is triggered automatically whenever a new image is pushed to the Docker Hub repository 'redislabs/redis:latest.
正解：
解説：
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: 1 ' in the 'strategy.rollingupdate' section to control the rolling update process.
- Configure a 'strategy-type' to 'Rollingupdate' to trigger a rolling update when the deployment is updated.
- Add a 'spec-template.spec.imagePullPolicy: Always' to ensure that the new image is pulled even if it exists in the pod's local cache.
2. Create the Deployment: - Apply the updated YAML file using 'kubectl apply -f redis-deployment.yaml' 3. Verify the Deployment - Check the status of the deployment using 'kubectl get deployments redis-deployment' to confirm the rollout and updated replica count. 4. Trigger the Automatic Update. - Push a new image to the Docker Hub repository 5. Monitor the Deployment: - Use 'kubectl get pods -l app=rediS to monitor the pod updates during the rolling update process. You will observe that one new pod with the updated image is created, and then one old pod is terminated- This ensures that there is no downtime during the update process. 6. Check for Successful Update: - Once the deployment is complete, use 'kubectl describe deployment redis-deployment' to see that the 'updatedReplicaS field matches the 'replicas' field, indicating a successful update.
質問 # 208
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CKAD最新日本語版参考書: https://www.goshiken.com/Linux-Foundation/CKAD-mondaishu.html
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