Correct Answer:

See the Explanation below for complete solution.
Explanation:
ssh ckad00028
You're seeing RBAC errors like:
User "system:serviceaccount:gorilla:default" cannot list resource "pods" ... in namespace "gorilla" That means the Pod is running as the default ServiceAccount and needs permission to list pods (and possibly also get/watch).
You must fix it by updating the Deployment (via its manifest file) and giving it the proper RBAC.
1) Confirm the error in logs
kubectl -n gorilla get deploy honeybee-deployment
kubectl -n gorilla logs deploy/honeybee-deployment --tail=200
If it's CrashLooping and you need previous logs:
POD=$(kubectl -n gorilla get pods -l app=honeybee -o jsonpath='{.items[0].metadata.name}' 2>/dev/null || kubectl -n gorilla get pods -o jsonpath='{.items[0].metadata.name}') kubectl -n gorilla logs "$POD" --previous --tail=200 You should see the "cannot list resource pods" line.
2) Create a dedicated ServiceAccount for the app
(Using a dedicated SA is standard practice; the task wants you to "resolve the errors".) kubectl -n gorilla create serviceaccount honeybee-sa kubectl -n gorilla get sa honeybee-sa
3) Create RBAC: Role + RoleBinding (namespaced)
This will allow listing pods in namespace gorilla.
cat <<'EOF' > honeybee-rbac.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: honeybee-pod-reader
namespace: gorilla
rules:
- apiGroups: [""]
resources: ["pods"]
verbs: ["get", "list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: honeybee-pod-reader-binding
namespace: gorilla
subjects:
- kind: ServiceAccount
name: honeybee-sa
namespace: gorilla
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: honeybee-pod-reader
EOF
Apply it:
kubectl apply -f honeybee-rbac.yaml
Quick verification (optional but very useful):
kubectl auth can-i list pods -n gorilla --as=system:serviceaccount:gorilla:honeybee-sa Should return yes.
4) Update the Deployment manifest to use the new ServiceAccount
The manifest is at:
/home/candidate/prompt-escargot/honey bee-deployment.yaml
Because there's a space in the filename, quote it.
4.1 Edit the file
cd /home/candidate/prompt-escargot
ls -l
vi "honey bee-deployment.yaml"
In the Deployment YAML, add (or set) this under:
spec.template.spec:
serviceAccountName: honeybee-sa
Example location:
spec:
template:
spec:
serviceAccountName: honeybee-sa
containers:
- name: ...
Save and exit.
4.2 Apply the updated manifest
kubectl apply -f "/home/candidate/prompt-escargot/honey bee-deployment.yaml"
5) Ensure rollout succeeds and errors are gone
kubectl -n gorilla rollout status deploy honeybee-deployment
kubectl -n gorilla logs deploy/honeybee-deployment --tail=200
Also confirm the pods now run with the right ServiceAccount:
kubectl -n gorilla get pods -o jsonpath='{range .items[*]}{.metadata.name}{" sa="}{.spec.
serviceAccountName}{"\n"}{end}'
You should no longer see the RBAC "cannot list pods" errors.

Correct Answer:

See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Use initContainers:
- Define one or more 'initContainers' within the Pod'S 'spec.template.spec' section.
- The 'initContainerS will run before any other container in the Pod.
- In this case, you would create an 'initcontainer' for the MySQL database.
2. Configure the initContainer:
- The 'initcontainer' should have the following attributes:
- Name: A unique name for the container.
- Image: The Docker image containing the necessary tools to initialize the database.
- Command: The command to execute for database initialization.
- LivenessProbe: Optional, but recommended to check if the database initialization process is successful.
3. Sequence the containers:
- Ensure the 'initContainers' are listed before the main containers in the Pod's 'spec-template-spec-containers' section.
4. Exam le YAML:

- The 'mysql-init' 'initcontainer' will run before the 'nginx' and 'mysql' containers- - The 'command' in the 'injtContainer' Will create a database named within tne MySQL container. - The livenessprobe' will ensure that the database iS reachable on pon 3306 atter the initialization process completes. Note: This solution assumes that the 'mysqr image already includes the necessary database initialization tools. You might need to use a custom image with these tools if the default image doesn't provide them.,

Correct Answer:

See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Helm Chart for Each Service:
- 'user-service' chart:
- Create a 'values.yamr file for the 'user-service' chart.
- Define the container image, resources, and any other necessary configurations for the 'user-service'.
- 'order-service' chart:
- Create a 'values-yamr file for the 'order-service' chart
- Define the container image, resources, and any other necessary configurations for the 'order-service'
- In tne 'values.yamr, add a dependency on the 'user-service' chart.

2. Configure Helm for Dependency Management: - Use the '-dependency-update' flag to ensure that Helm automatically updates the 'user-service chart before deploying the 'order-service' bash helm dependency update order-service 3. Deploy the Services Using Helm: - Deploy the 'user-service chart: bash helm install user-service Juser-service - Deploy the 'order-service' chart: bash helm install order-service ./order-service - Helm will automatically handle the dependency between the services, ensuring that the 'user-services is deployed before the 'order-service' 4. Verify Deployment and Dependency: - Use ' kubectl get pods -l app=user-service' and 'kubectl get pods -l app=order-service' to verify that the pods are running. - You Should observe that the 'user-service' pods are up and running before the 'order-services pods start. - You can also use 'kubectl describe pod' to see the pod events and confirm that the 'order-service' pod is waiting for the 'user-service' to be ready before starting.,

Correct Answer:

See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Job YAML file:

2. Apply the Job YAML file: bash kubectl apply -f data-processing-job.yaml 3. Monitor the Job: bash kubectl get jobs -w This will show the status of the Job, including its completion status and retries, if any. 4. Examine the Job's Pods: bash kubectl get pods -l job-name-data-processing-job You can use the 'kubectl logs command to cneck tne logs of tne POdS created by tne Job to investigate any potential failures. - 'backoffLimit: 3': This specifies that the Job can be retried up to 3 times in case of failures. - 'activeDeadlineSeconds: 2700': This sets the maximum duration for the Job to run (2700 seconds, which is equal to 45 minutes). If the Job exceeds this time limit, it will be automatically terminated. - 'restartPolicy: Never: This ensures that Pods created by the Job will not be restarted automatically. - 'command: ["python", "data_processing_script.py'T: This defines the command to execute inside the container. - 'resources-requests': This defines the minimum resource requirements for the container, including CPU and memory. - 'resources-limits: This can be used to define maximum resource limits for the container. This setup will attempt to run the data processing script If it fails, it will be retried up to 3 times, with an increasing delay between each retry. The Job will be terminated after 45 minutes if it does not complete successfully.,

Correct Answer:

See the solution below with Step by Step Explanation.
Explanation:
Solution (Step by Step) :
1. Create a Service:
- Create a Service resource that defines how the pods of your application will be accessed externallv
- Specify a unique name for the Service and define the port mapping-
- Example:

2. Set Selector: - Use the 'selector field to specify the label that the Service should use to identify the pods it should target - Ensure that the pods of your Deployment are labeled with the specified 'app: myapp' label. 3. Configure Load Balancing: - The default load balancing strategy for Kubernetes Services is round-robin, which distributes traffic evenly across the available pods. - No additional configuration is needed for this strategyc 4. Deploy and Test: - Apply the Service YAML file. - Test the Service by accessing it from outside the cluster. - Ensure that the traffic is distributed evenly across the pods using the round-robin strategy. 5. Optional: External Access: - If you want to expose the Service to the internet, you can set the Service 'type' to 'Load8alancer'. This will create a LoadBalancer resource (often an external IP address) that routes traffic to the Service.