Day 34 Task: Working with Services in Kubernetes

Congratulations 🎊 on your learning on Deployments in K8s on Day 33

What are Services in K8s

• In Kubernetes, Services are objects that provide stable network identities to Pods and abstract away the details of Pod IP addresses. Services allow Pods to receive traffic from other Pods, Services, and external clients.

Task-1:

• Create a Service for your todo-app Deployment from Day-32

• Create a Service definition for your todo-app Deployment in a YAML file.

• Apply the Service definition to your K8s (minikube) cluster using the kubectl apply -f service.yml -n <namespace-name> command.

• Verify that the Service is working by accessing the todo-app using the Service's IP and Port in your Namespace.

• Create a Service.yaml file for your django-todo-app Deployment from Day 32

apiVersion: v1
kind: Service
metadata:
  name: todo-service
  namespace: django-app
spec:
  type: NodePort
  selector:
    app: todo-app
  ports:
      # By default and for convenience, the `targetPort` is set to the same value as the `port` field.
    - port: 80
      targetPort: 8000
      # Optional field
      # By default and for convenience, the Kubernetes control plane will allocate a port from a range (default: 30000-32767)
      nodePort: 30007

• Apply the updated deployment using the command

kubectl apply -f service.yaml -n <namespace>

• To get services , we use kubectl get svc -n <namespace> and for wide overview we can use kubectl get svc -o wide -n <namespace>

• After that use this command

minikube ssh

curl -L http://<cluster-IP>

Task-2:

• Create a ClusterIP Service for accessing the todo-app from within the cluster

• Create a ClusterIP Service definition for your todo-app Deployment in a YAML file.

• Apply the ClusterIP Service definition to your K8s (minikube) cluster using the kubectl apply -f cluster-ip-service.yml -n <namespace-name> command.

• Verify that the ClusterIP Service is working by accessing the todo-app from another Pod in the cluster in your Namespace.

• Create a YAML file called cluster-ip-service.yml with the following contents:

apiVersion: v1
kind: Service
metadata:
  name: todo-app-cluster-ip-service
  namespace: django-app
spec:
  type: ClusterIP
  selector:
    app: todo-app
  ports:
  - port: 80
    targetPort: 8000

• Apply the ClusterIP Service definition to your Kubernetes cluster using the following command:

kubectl apply -f cluster-ip-service.yml -n django-app

• Verify that the ClusterIP Service is working by accessing the todo-app from another Pod in the cluster in your Namespace. You can find the ClusterIP Service's IP by running the following command

kubectl get svc -n <namespace> && kubectl get svc -o wide -n <namespace>

• After that use this command

minikube ssh

curl -L http://<cluster-IP>

Task-3:

• Create a LoadBalancer Service for accessing the todo-app from outside the cluster

• Create a LoadBalancer Service definition for your todo-app Deployment in a YAML file.

• Apply the LoadBalancer Service definition to your K8s (minikube) cluster using the kubectl apply -f load-balancer-service.yml -n <namespace-name> command.

• Verify that the LoadBalancer Service is working by accessing the todo-app from outside the cluster in your Namespace.

• Create a YAML file called load-balancer-service.yml with the following contents:

apiVersion: v1
kind: Service
metadata:
  name: todo-app-load-balancer-service
  namespace: django-app
spec:
  type: LoadBalancer
  selector:
    app: todo-app
  ports:
  - port: 80
    targetPort: 8000

• Apply the LoadBalancer Service definition to your Kubernetes cluster using the following command:

kubectl apply -f load-balancer-service.yml -n django-app

• Verify that the LoadBalancer Service is working by accessing the todo-app from outside the cluster in your Namespace. You can find the LoadBalancer Service's IP by running the following command:

kubectl get svc -n <namespace> && kubectl get svc -o wide -n <namespace>

• After that use this command

minikube ssh

curl -L http://<clister-IP>

• Your day 34 successfully completed 💥💥💥

Happy Learning

Thanks For Reading! :)

sriparthu 💥