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| Section | Weight | Objectives |
|---|---|---|
| Services and Networking | 20% | - Provide and troubleshoot access to applications via services - Demonstrate basic understanding of NetworkPolicies - Use Ingress rules to expose applications |
| Application Observability and Maintenance | 15% | - Implement probes and health checks - Debugging in Kubernetes - Utilize container logs - Understand API deprecation policies - Use built-in CLI tools to monitor Kubernetes applications |
| Application Deployment | 20% | - Kustomize - Understand Deployments and how to perform rolling updates - Use the Helm package manager to deploy existing packages - Use Kubernetes primitives to implement common deployment strategies (e.g., blue/green or canary) |
| Application Design and Build | 20% | - Understand multi-container Pod design patterns (e.g., sidecar, init and others) - Utilize persistent and ephemeral volumes - Define, build and modify container images - Choose and use the right workload resource (Deployment, DaemonSet, CronJob, etc.) |
| Application Environment, Configuration and Security | 25% | - Understand authentication, authorization and admission control - Understanding and defining resource requirements, limits and quotas - Discover and use resources that extend Kubernetes (CRD, Operators) - ConfigMaps and Secrets - ServiceAccounts - SecurityContexts |
>> Linux Foundation CKADトレーリングサンプル <<
なにごとによらず初手は难しいです、どのようにLinux Foundation CKAD試験への復習を始めて悩んでいますか。我々のLinux Foundation CKAD問題集を購買するのはあなたの試験に準備する第一歩です。我々の提供するLinux Foundation CKAD問題集はあなたの需要に満足できるだけでなく、試験に合格する必要があることです。あなたはまだ躊躇しているなら、JapancertのCKAD問題集デモを参考しましょ。
質問 # 65 
Context
You are tasked to create a ConfigMap and consume the ConfigMap in a pod using a volume mount.
Task
Please complete the following:
* Create a ConfigMap named another-config containing the key/value pair: key4/value3
* start a pod named nginx-configmap containing a single container using the nginx image, and mount the key you just created into the pod under directory /also/a/path See the solution below.
正解：
解説：
Explanation
Solution:
質問 # 66
You are running a critical application that requires high availability and minimal downtime during updates. Your current deployment strategy uses a single Deployment with 3 replicas. You need to ensure that during updates, only one pod is unavailable at any given time, minimizing service disruption. Design a deployment strategy that meets this requirement and allows for seamless updates.
正解：
解説：
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define Rolling Update Strategy:
- In your Deployment configuration, specify the rolling update strategy with 'maxunavailable: 1 s and 'maxSurge: O'. This ensures that during updates, only one pod is taken down at a time, while the remaining two continue serving traffic.
2. Use Liveness and Readiness Probes: - Configure liveness and readiness probes for your application containers. Liveness probes Check tne nealth of running containers and restan them if unhealthy. Readiness probes check if a container is ready to receive traffic. - This ensures that only healthy pods are marked as ready, and traffic is routed only to ready pods.
3. Implement Horizontal Pod Autoscaling (HPA): - Set up HPA to automatically scale the number of pods based on CPU or memory utilization- This ensures that the application can handle increased trattiC during updates without compromising performance. - You can configure the desired minimum and maximum replicas for the HPA based on your application's requirements. 4. Use Service with Session Affinity: - Configure your Service to use 'ClientlP' or 'Cookie' session affinity. This ensures that client connections are consistently routed to the same pod during the rolling update, minimizing disruption for users.
5. Use Daemonsets for System Components: - If you have any system components (like monitoring agents or log collectors) that need to run on every node in the cluster, use DaemonSets instead of Deployments. - DaemonSets ensure that these components are always running on all nodes, even during node restarts or updates, ensuring continuous monitoring and logging.
質問 # 67
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 # 68
You are building a new web application that utilizes a microservice architecture- One of the microservices, 'recommendation-service', is responsible for providing personalized product recommendations to users.
This service uses a machine learning model for generating recommendations based on user purchase history and browsing behavior. The model is trained offline and its weights are stored in a 'model-store' service.
Design a mufti-container Pod for the 'recommendation-service' that incorporates the following considerations:
- The Pod should include a primary container for the 'recommendation-service' application.
- The Pod should include a secondary container that runs the 'model-store' service to provide access to the trained model weights.
- Both containers should share a common volume to ensure that the model weights are available to the 'recommendation-service' container-
- The recommendation-service' snould be able to access the model weignts from the 'model-store' container witnout relying on a network call to another service-
- The recommendation-service' container should be configured to periodically update the model weights from the 'model-store' container when a new version of the model is available.
正解：
解説：
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create the Deployment YAML:
- Define a Deployment with the name 'recommendation-service'
- Set the replicas to for redundancy and scalability.
- Specify the labels Sapp: recommendation-service' for selecting the Pods in the Deployment.
- Create a 'template' section to define the Pod specificatiom
2. Deploy the Resources: - Apply the Deployment using 'kubectl apply -f deployment-yamp 3. Verify the Deployment: - Check the status of the Deployment using 'kubectl get deployments recommendation-service and ensure that three Pods are running. 4. Contigure the 'recommendation-service' - Modify the 'recommendation-service application to load the model weights from the specified path ClmodeVIatest-modeI_weightS). - Implement a mechanism within the 'recommendation-service to periodically check tor updated model weights in the shared volume. 5. Configure the 'model-store service: - Ensure that the model-store service is properly configured to store and retrieve the model weights. - Implement a mechanism in the 'model-store' service to notify the 'recommendation-service when a new model version is available. This notification can be achieved using a shared volume or a separate messaging system. 6. Test the Application: - Send requests to the 'recommendation-service' to generate recommendations. - Monitor the 'model-store' service and the shared volume to verify that the model weights are being updated correctly and the recommendation- service' is using the latest model version. Important Considerations: - Ensure that the 'recommendation-service' application is properly configured to access and load the model weights from the shared volume. - Implement a robust model management strategy, including versioning and rollback mechanisms, to ensure that the recommendation-service always uses the appropriate model. - Consider using a dedicated model store service that provides a dedicated API for retrieving and updating model weights. This can simplify the communication between the 'recommendation-service' and the model store. - Monitor the performance and resource usage of both services to ensure optimal performance.,
質問 # 69
You have a container image that uses a specific version of a library. You want to update this library to a newer version while still keeping the previous version available for compatibility purposes. Describe the steps involved in modifying the container image to include both versions of the library without rebuilding the entire application.
正解：
解説：
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Dockerfile:
- Create a new 'Dockerfile' with the following content:
- Replace 'your-library' Witn the actual library name. - Replace 'new-version' and 'old-version' witn tne desired versions. 2. Build the Image: - Build the image using tne DockerTlle: docker build -t updated-image:latest 3. Modify your application code: - Modify your application code to explicitly import the specific version of the library that you want to use. For example: python # Import the new version for new functionality from your_library impon new_functionality # Import the Old version for backward compatibility from your_library import old_functionality # Use the appropriate version of the library based on your requirements 4. IJpdate the Deployment - Modify your Deployment YAML file to use the newly built image:
5. Apply the Changes: - Apply the updated Deployment using kubectl apply -f deployment.yamr 6. Test the Application: - Access your application and ensure it functions correctly with both versions of the library.
質問 # 70
......
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