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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Observability and Maintenance | 15% | - Utilize container logs - Use built-in CLI tools to monitor Kubernetes applications - Implement probes and health checks - Debugging in Kubernetes - Understand API deprecation policies |
| Topic 2: Application Design and Build | 20% | - Understand multi-container Pod design patterns (e.g., sidecar, init and others) - Choose and use the right workload resource (Deployment, DaemonSet, CronJob, etc.) - Define, build and modify container images - Utilize persistent and ephemeral volumes |
| Topic 3: Services and Networking | 20% | - Provide and troubleshoot access to applications via services - Demonstrate basic understanding of NetworkPolicies - Use Ingress rules to expose applications |
| Topic 4: Application Environment, Configuration and Security | 25% | - Discover and use resources that extend Kubernetes (CRD, Operators) - ConfigMaps and Secrets - SecurityContexts - Understand authentication, authorization and admission control - Understanding and defining resource requirements, limits and quotas - ServiceAccounts |
| Topic 5: Application Deployment | 20% | - Use Kubernetes primitives to implement common deployment strategies (e.g., blue/green or canary) - Kustomize - Understand Deployments and how to perform rolling updates - Use the Helm package manager to deploy existing packages |
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NEW QUESTION # 55
You are developing a service that uses a custom configuration file called 'service.properties'. You want to use ConfigMaps to store and manage this file in a secure and efficient manner. The 'service-properties' file contains sensitive information such as database credentials and API keys.
How would you create a ConfigMap that securely stores the 'service-properties' file, ensuring that the file is accessible only to the service's container?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Secret for Sensitive Data:
- Create a Secret
- Encode the 'service-properties' file: bash echo "your-database-username=your-database-username" > service-properties echo "your-database-password=your-database-password" >> service-properties echo 'Your-api-key=your-api-key" >> service.properties base64 -w 0 service.properties - Replace with the output from the base64 command. 2. Create the ConfigMap for the File:
3. Apply the Secret and ConfigMap: bash kubectl apply -f service-secrets-yaml kubectl apply -f service-config.yaml 4. Update the Deployment to use the ConfigMap and Secret
5. Apply the updated Deployment: bash kubectl apply -f my-service-deployment-yaml 6. Access the File in the Container. - Mount the ConfigMap and Secret: - The ConfigMap mounts the 'service.properties' file as a placeholder. - The Secret mounts the actual 'service.properties' file securely. - Access the File: - The container should access the 'service.properties' file from '/var/secrets/service/service.properties' This approach uses a Secret to store sensitive data and a ConfigMap to mount the file securely within the container. The container will have access to the 'service-properties' file, but the actual data is stored in the Secret, ensuring its confidentiality'.
NEW QUESTION # 56
You are building a Kubernetes application that involves a microservice architecture with multiple pods for each service. One of your services requires a sidecar container to handle logging and monitoring. How would you design the pod structure and define the relationships between the application container and the sidecar container?
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Define Pod Specification:
- Create a pod definition file (e.g., 'pod.yaml').
- Include the 'apiVersion', 'kind', 'metadata' (name, labels), and 'spec' sections.
2. Define Application Container:
- Within the 'spec.containerS section, define the primary application container:
- 'name': Provide a descriptive name for the application container (e.g., 'app').
- Simage: Specify the Docker image for the application.
- 'ports': Define any ports that the application exposes.
- 'resources': (Optional) Specify resource requests and limits for the application container.
3. Define Sidecar Container.
- Add another container definition within the 'spec-containers' section for the sidecar:
- 'name': Provide a name for the sidecar container (e.g., Slogger').
- 'image': Specify the Docker image for the sidecar container (e.g., "busybox'
- 'command': Define the command to run within the sidecar. This might involve using a logging agent, monitoring tool, or any other custom script.
- 'volumeMountss: (Optional) If the sidecar needs access to shared data, mount volumes here.
4. Define Shared Volumes (Optional):
- If necessary, create a 'spec-volumes' section to define any shared volumes that both containers can access. This might include:
- 'emptyDir': For temporary data that only exists within the pod.
- 'persistentVolumeClaim': To use a persistent volume claim for shared data that persists beyond pod restarts.
5. Configure Container Relationships:
- Ensure that the 'name' of the application container and sidecar container is the same as the 'name' used in the 'volumeMounts' section.
Example YAML:
- The pod named 'my-app-pod' includes two containers: 'app' (the primary application) and 'logger' (the sidecar). - The 'loggers container uses a 'command' to simulate logging activity. - Both containers can access the 'logs' volume, which is an empty directory. Important Note: - The sidecar container should ideally be configured to interact with the application container. This might involve using shared volumes, environment variables, or inter-process communication mecnanisms to facilitate data exchange or Signal passing. - Remember to adapt the example to your specific application requirements, choosing the appropriate container images, commands, and volumes.]
NEW QUESTION # 57
Context
Context
A pod is running on the cluster but it is not responding.
Task
The desired behavior is to have Kubemetes restart the pod when an endpoint returns an HTTP 500 on the /healthz endpoint. The service, probe-pod, should never send traffic to the pod while it is failing. Please complete the following:
* The application has an endpoint, /started, that will indicate if it can accept traffic by returning an HTTP 200. If the endpoint returns an HTTP 500, the application has not yet finished initialization.
* The application has another endpoint /healthz that will indicate if the application is still working as expected by returning an HTTP 200. If the endpoint returns an HTTP 500 the application is no longer responsive.
* Configure the probe-pod pod provided to use these endpoints
* The probes should use port 8080
Answer:
Explanation:
Solution:
apiVersion: v1
kind: Pod
metadata:
labels:
test: liveness
name: liveness-exec
spec:
containers:
- name: liveness
image: k8s.gcr.io/busybox
args:
- /bin/sh
- -c
- touch /tmp/healthy; sleep 30; rm -rf /tmp/healthy; sleep 600
livenessProbe:
exec:
command:
- cat
- /tmp/healthy
initialDelaySeconds: 5
periodSeconds: 5
In the configuration file, you can see that the Pod has a single Container. The periodSeconds field specifies that the kubelet should perform a liveness probe every 5 seconds. The initialDelaySeconds field tells the kubelet that it should wait 5 seconds before performing the first probe. To perform a probe, the kubelet executes the command cat /tmp/healthy in the target container. If the command succeeds, it returns 0, and the kubelet considers the container to be alive and healthy. If the command returns a non-zero value, the kubelet kills the container and restarts it.
When the container starts, it executes this command:
/bin/sh -c "touch /tmp/healthy; sleep 30; rm -rf /tmp/healthy; sleep 600" For the first 30 seconds of the container's life, there is a /tmp/healthy file. So during the first 30 seconds, the command cat /tmp/healthy returns a success code. After 30 seconds, cat /tmp/healthy returns a failure code.
Create the Pod:
kubectl apply -f https://k8s.io/examples/pods/probe/exec-liveness.yaml
Within 30 seconds, view the Pod events:
kubectl describe pod liveness-exec
The output indicates that no liveness probes have failed yet:
FirstSeen LastSeen Count From SubobjectPath Type Reason Message
--------- -------- ----- ---- ------------- -------- ------ -------
24s 24s 1 {default-scheduler } Normal Scheduled Successfully assigned liveness-exec to worker0
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Pulling pulling image "k8s.gcr.io/busybox"
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "k8s.gcr.io/busybox"
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Created Created container with docker id 86849c15382e; Security:[seccomp=unconfined]
23s 23s 1 {kubelet worker0} spec.containers{liveness} Normal Started Started container with docker id 86849c15382e After 35 seconds, view the Pod events again:
kubectl describe pod liveness-exec
At the bottom of the output, there are messages indicating that the liveness probes have failed, and the containers have been killed and recreated.
FirstSeen LastSeen Count From SubobjectPath Type Reason Message
--------- -------- ----- ---- ------------- -------- ------ -------
37s 37s 1 {default-scheduler } Normal Scheduled Successfully assigned liveness-exec to worker0
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Pulling pulling image "k8s.gcr.io/busybox"
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Pulled Successfully pulled image "k8s.gcr.io/busybox"
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Created Created container with docker id 86849c15382e; Security:[seccomp=unconfined]
36s 36s 1 {kubelet worker0} spec.containers{liveness} Normal Started Started container with docker id 86849c15382e
2s 2s 1 {kubelet worker0} spec.containers{liveness} Warning Unhealthy Liveness probe failed: cat: can't open '/tmp/healthy': No such file or directory Wait another 30 seconds, and verify that the container has been restarted:
kubectl get pod liveness-exec
The output shows that RESTARTS has been incremented:
NAME READY STATUS RESTARTS AGE
liveness-exec 1/1 Running 1 1m
NEW QUESTION # 58
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 # 59
You have a Deployment named 'nginx-deployment' running 3 replicas of an Nginx container. You need to ensure that all 3 pods are using the same ConfigMap for configuration. Additionally, you need to configure the ConfigMap so that changes made to it are automatically reflected in the running pods without requiring a new Deployment update.
Answer:
Explanation:
See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create the ConfigMap:
2. Apply the ConfigMap: bash kubectl apply -f nginx-config_yaml 3. Update the Deployment to use the ConfigMap:
4. Apply the updated Deployment bash kubectl apply -f nginx-deployment.yaml 5. Verify the Deployment: bash kubectl get deployments nginx-deployment You should see that the Deployment is using the 'nginx-config' ConfigMap for its configuration. 6. Test the automatic update: - Modify the 'nginx-config' ConfigMap: bash kubectl edit configmap nginx-config Change the 'nginx_conf' value in the ConfigMap. - Verify the change in the pods: bash kubectl exec -it -- bash -c 'cat /etc/nginxfconf-d/nginx_conf' Replace with the name of one of the pods- This command will display the contents of the nginx configuration file within the pod. You will observe that the nginx configuration file in the running pods is automatically updated without needing a Deployment update.
NEW QUESTION # 60
......
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