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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Observability and Maintenance | 15% | - Debug applications in Kubernetes - Work with container logs - Implement probes and health checks - Understand API deprecations - Monitor applications using CLI tools |
| Topic 2: Application Design and Build | 20% | - Define, build and modify container images - Choose and use appropriate workload resources - Utilize persistent and ephemeral volumes - Understand multi-container Pod design patterns |
| Topic 3: Application Environment, Configuration and Security | 25% | - Apply application security settings - Use custom resources and extensions - Understand authentication, authorization and admission control - Use ServiceAccounts - Work with ConfigMaps - Create and consume Secrets - Configure resource requirements, limits and quotas |
| Topic 4: Application Deployment | 20% | - Implement deployment strategies - Work with Kustomize - Use Helm package manager - Manage Deployments, rolling updates and rollbacks |
| Topic 5: Services and Networking | 20% | - Expose applications via Services - Understand and apply NetworkPolicies - Use Ingress rules - Troubleshoot network access |
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NEW QUESTION # 65
Context
Task:
1- Update the Propertunel scaling configuration of the Deployment web1 in the ckad00015 namespace setting maxSurge to 2 and maxUnavailable to 59
2- Update the web1 Deployment to use version tag 1.13.7 for the Ifconf/nginx container image.
3- Perform a rollback of the web1 Deployment to its previous version
Answer:
Explanation:
Solution:
NEW QUESTION # 66
You are running a Kubernetes cluster with a deployment for a critical application. The application uses sensitive data stored in a secret. To ensure security, you need to implement a policy that prevents the deployment of pods for this application if the secret containing the sensitive data is missing. How would you implement this using Custom Resource Definitions (CRDs) and Admission Webhooks?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1 . Create a CRD for Secret Validation:
- Define a Custom Resource Definition (CRD) named 'SecretValidator' to specify the required secret for the deployment.
- This CRD will have a 'spec' section containing the name of the secret.
2. Create a Validation Webhook Configuration: - Create a ValidatingWebhookConfiguration resource. - Define the 'rules' to match the 'SecretValidatoo CRD and ensure that the webhook is triggered for all operations on the CRD. - Specify the 'failurePolicy' as 'Fail' to prevent pod deployment if the validation fails. - Provide the 'admissionReviewVersions' to indicate the supported API versions. - Set the 'sideEffects' to 'None' as the webhook only performs validation and does not modify the object.
3. Create the Secret Validation Service: - Create a Deployment for a service that will handle the validation webhook requests. - The service should have a container with a code that checks if the required secret exists in the namespace.
4. Implement the Validation Logic in the Service: - In the code of the secret validation service container, you will need to: - Receive the request from the Kubernetes API server. - Retrieve the 'secretName' from the 'SecretValidator' CRD. - Check if a secret with that name exists in the namespace. - If the secret exists, allow the pod deployment. - If the secret does not exist, deny the pod deployment and return an error message. package main import ( "context" "encoding/json" "fmt" "io/ioutil" "net/http" metavl "k8s.io/apimachinery/pkg/apis/meta/v1" "k8s.io/apimachinery/pkg/runtime" "k8s.io/apimachinery/pkg/runtime/serializer" "k8s.io/apimachinery/pkg/types" "k8s.io/client-go/kubernetes" "k8s.io/client-go/rest" func main() { // Create a Kubernetes clientset config, err := rest. InClusterConfig() if err != nil { panic(err) clientset, err := kubernetes.NewForConfig(config) if err != nil { panic(err) // Create a scheme for decoding the CRD scheme := runtime.NewScheme() codecs := serializer.NewCodecFactory(scheme) deserializer := codecs.UniversalDeserializer() // Start the HTTP server http.HandleFunc("/validate", func(w http.ResponseWriter, r http.Request) { // Read the admission review request body body, err := ioutil.ReadAll(r.Body) if err != nil { http.Error(w, fmt.Sprintf("Error reading body: %v" err), http.StatuslnternalServerError) return } // Unmarshal the admission review request var admissionReview metavl .AdmissionReview , err = deserializer.Decode(body, nil, &admissionReview) if err != nil { http.Error(w, fmt.Sprintf("Error decoding admission review: %v", err), http.StatuslnternalServerError) return } // Unmarshal the admission review request var admissionReview metavl .AdmissionReview , err = deserializer.Decode(body, nil, &admissionReview) if err != nil { http.Error(w, fmt.Sprintf("Error decoding admission review: %v", err), http.StatuslnternalServerError) return } // Check if the secret exists , err = clientset.CoreV1 ().Secrets(admissionReview.Request.Namespace).Get(context.TODO(), secretValidator.Spec.SecretName, metavl .GetOptions{}) if err nil { // Secret does not exist, deny the request admissionReview.Response = &metavl .AdmissionResponse{ IJID: admissionReview.Request.UlD, Allowed: false, Result: &metavl .Status{ Status: metavl .StatusFailure, Message: fmt.Sprintf("Secret %s not found in namespace %s", secretValidator.Spec.SecretName, admissionReview.Request.Namespace), } } } else { // Secret exists, allow the request admissionReview.Response = &metavl .AdmissionResponse{ UID: admissionReview.Request.UlD, Allowed: true, Result: &metavl .Status{ Status: metavl .StatusSuccess, // Marshal the admission review response response, err := json.Marshal(admissionReview) if err nil { http.Error(w, fmt.Sprintf("Error marshaling admission review: %v", err), http.StatuslnternalServerError) return } // Write the response to the client w.WriteHeader(http.StatusOK) w.Write(response) }) // Start the HTTP server on port 8443 http.ListenAndServeTLS(":8443", "/path/to/cert.pem", "/path/to/key.pem", nil) } // Define the SecretValidator CRD type SecretValidator struct { metav1 .TypeMeta metav1 .ObjectMeta Spec SecretValidatorSpec } type SecretValidatorSpec struct {
} 5. Create a SecretValidator Resource: - Create a 'SecretValidator' resource in the same namespace as the deployment. - Set the 'spec.secretName' to the name of the required secret.
6. Deploy the Application with the Validation: - Ensure that the deployment for the application is in the same namespace as the 'SecretValidator' resource. - The deployment should reference the 'SecretValidator' resource in its annotations to trigger the validation webhook.
Note: This setup will only work for deployment creation. For other operations (e.g., updates), you need to update the 'rules' in the 'ValidatingWebhookConfiguration'. You can also extend this solution to validate other resources or create more specific validation policies.]
NEW QUESTION # 67
You are building a web application with two microservices: a frontend service ('frontend') and a backend service ( ' backend'). The frontend service requires access to the backend service, which iS exposed on port 8080 within the Kubernetes cluster. How would you configure an Ingress resource to direct traffic to the correct service based on the hostname, ensuring that the frontend service can access the backend service internally without exposing the backend service to the public internet?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Service tor the Backend Service:
- Define a Service for the 'backend' service, exposing it internally within the Kubernetes cluster on port 8080.
2. Configure the Ingress Resource: - Create an Ingress resource that directs traffic to the frontend service based on the hostname, allowing the frontend service to access the backend service internally without exposing it to the public internet - Define the Ingress rule to map the hostname 'frontend-example.com' to the 'frontend' service on port 80. - Configure an Ingress rule to enable access to the 'backend' service on port 8080 using the hostname 'internal-backend-example-com' within the Kubernetes cluster.
3. Create a Secret for the Frontend TLS Certificate: - Create a Secret in Kubernetes to store the TLS certificate and key for the frontend service.
4. Apply the Resources: - Apply the Service, Ingress, and Secret YAML files to your Kubernetes cluster using 'kubectl apply -f 5. Access the Frontend Service: - Access the frontend service using the hostname 'frontend-example.com'. The frontend service can now access the backend service internally using the hostname 'internal-backend-example-com' without exposing the backend service to the public internet.]
NEW QUESTION # 68
Exhibit:
Context
A container within the poller pod is hard-coded to connect the nginxsvc service on port 90 . As this port changes to 5050 an additional container needs to be added to the poller pod which adapts the container to connect to this new port. This should be realized as an ambassador container within the pod.
Task
* Update the nginxsvc service to serve on port 5050.
* Add an HAproxy container named haproxy bound to port 90 to the poller pod and deploy the enhanced pod. Use the image haproxy and inject the configuration located at /opt/KDMC00101/haproxy.cfg, with a ConfigMap named haproxy-config, mounted into the container so that haproxy.cfg is available at /usr/local/etc/haproxy/haproxy.cfg. Ensure that you update the args of the poller container to connect to localhost instead of nginxsvc so that the connection is correctly proxied to the new service endpoint. You must not modify the port of the endpoint in poller's args . The spec file used to create the initial poller pod is available in /opt/KDMC00101/poller.yaml
Answer: A
NEW QUESTION # 69
You have a custom resource definition (CRD) named that represents a database resource in your Kubernetes cluster. You want to create a custom operator that automates the creation and management of these database instances. The operator should handle the following:
- Creation: When a new 'database.example.com' resource is created, the operator should provision a new PostgreSQL database instance on the cluster-
- Deletion: When a 'database.example_com' resource is deleted, the operator should clean up the corresponding PostgreSQL database instance.
- Scaling: If the 'spec-replicas' field of the 'database-example.com' resource is updated, the operator should scale the number of database instances accordingly.
Provide the necessary Kubernetes resources, custom operator code, and steps to implement this operator. You should use the 'Operator Framework' to build and deploy this operator
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create the CRD:
- Apply this YAML file to your cluster using ' kubectl apply -f database-crd.yamr. 2. Create the Operator Project: - IJse the Operator Framework' to initialize a new operator project bash operator-sdk init -domain example.com -repo example.com/database-operator --version VO.O. I -license apache2 - Replace 'example_com' with your desired domain name. 3. Define the Custom Resource: - Create a 'database_types.go' file in the 'api/vl' directory of your project. - Define the 'Database' resource as a custom resource struct Go package v1 import ( metavl "k8s.iofapimachinery/pkg/apis/meta/v1" // DatabaseSpec defines the desired state of Database type DatabaseSpec struct { If Replicas specifies the number of database instances to run.
// Password is the password for the database users.
} // DatabaseStatus defines the observed state of Database type DatabaseStatus struct { // Replicas is the actual number of database instances running.
// Ready indicates if the database is ready to accept connections.
}
4. Implement the Controller Logic: - Create a 'database_controller.go' file in the 'controllers' directory- - Implement the logic for creating, deleting, and scaling database instances.
5. Build and Deploy the Operator: - Build the operator using the 'operator-sdk build' command: bash operator-sdk build example.com/database-operator:vO.O.I --local - Deploy the operator to your Kubernetes cluster: bash kubectl apply -f deploy/operator.yaml 6. Test the Operator: - Create a new 'database-example-com' resource:
- Apply the YAML file to your cluster: bash kubectl apply -f my-database.yaml - Verify that the operator creates a PostgreSQL database instance. - Test scaling the database by updating the 'spec.replicas' field of the 'database.example.com' resource. - Delete the 'database.example.com' resource and verify that the operator cleans up the database instance. This step-by-step guide demonstrates a basic example of a custom operator using the Operator Framework. You can Kustomize this operator further to handle more complex operations and integrate with other Kubernetes resources. ,
NEW QUESTION # 70
......
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