Configuring Kubernetes Cluster on AWS and running/scaling a .Net Core application

Configuring Kubernetes

Development Environment Setup

Containerize the application

  • Clone this repo to a folder
  • Open a command prompt and navigate to your project folder.
  • Use the following commands to build and run your Docker image:
					 docker build . -t kubeservice:local
 docker run -d -p 8000:80 kubeservice:local
  • View the .Net Core application running from a container by navigating to localhost:8000

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Push the image to DockerHub

  • Log in on

  • Click on Create Repository.

  • Choose a name (e.g. kubeservice) and a description for your repository and click Create.

  • Log into the Docker Hub from the command line

					 docker login --username=yourhubusername

just with your own user name and email that you used for the account. Enter your password when prompted. If everything worked you will get a message similar to

					 WARNING: login credentials saved in /home/username/.docker/config.json
 Login Succeeded
  • Check the image ID using
					 docker images

and what you will see will be similar to

					 REPOSITORY                 TAG                  IMAGE ID            CREATED             SIZE
 kubeservice                local                a847aeef68b9        2 hours ago        257MB
 <none>                     <none>               92e722450fdb        2 hours ago        1.74GB
 microsoft/dotnet           sdk                  6baac5bd0ea2        3 weeks ago         1.73GB
 microsoft/dotnet           aspnetcore-runtime   1fe6774e5e9e        3 weeks ago         255MB
  • Tag image
					 docker tag a847aeef68b9 yourhubusername/kubeservice:latest
  • Push image to the repository created in previous steps
					 docker push yourhubusername/kubeservice

Configure Kubernetes Cluster on AWS

  • Login to your AWS console

  • Generate access keys for your user by navigating to Users/Security credentials page

  • Make sure your IAM user has following permissions:

  • Make sure to configure the AWS CLI to use your access key ID and secret access key
					 $ aws configure
 AWS Access Key ID [None]: <AccessKeyValue>
 AWS Secret Access Key [None]: <SecretAccessKeyValue>
 Default region name [None]: <us-east-1>
 Default output format [json]:
  • Create an S3 bucket for kops to use to store the state of the Kubernetes cluster and its configuration
					 $ bucket_name=vv-kops-state-store
 $ aws s3api create-bucket --bucket ${bucket_name} --region us-east-1
  • Enable versioning to revert or recover a previous state store.
					 $ aws s3api put-bucket-versioning --bucket ${bucket_name} --versioning-configuration Status=Enabled
  • Set the Kubernetes cluster name and S3 bucket URL environment variables
					 $ export KOPS_CLUSTER_NAME=vv.k8s.local
 $ export KOPS_STATE_STORE=s3://${bucket_name}
  • Generate Kubernetes cluster configuration using kops
					 $ kops create cluster --node-count=2 --node-size=t2.medium --zones=us-east-1a --name=${KOPS_CLUSTER_NAME}
  • Finally, build the Kubernetes cluster on AWS using following kops command. This might take a few minutes to boot the EC2 instances and download the Kubernetes components.
					 $ kops update cluster --name ${KOPS_CLUSTER_NAME} --yes

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  • Validate the cluster to ensure the master + 2 nodes have launched

					 $ kops validate cluster
 Validating cluster vv.k8s.local

 master-us-east-1a	Master	c4.large	1	1	us-east-1a
 nodes			Node	t2.medium	2	2	us-east-1a

 ip-172-20-37-8.ec2.internal	master	True
 ip-172-20-41-188.ec2.internal	node	True
 ip-172-20-43-113.ec2.internal	node	True

 Your cluster vv.k8s.local is ready
  • Finally, you can see your Kubernetes nodes with kubectl
					 $ kubectl get nodes
 NAME                            STATUS   ROLES    AGE   VERSION
 ip-172-20-37-8.ec2.internal     Ready    master   3m    v1.10.6
 ip-172-20-41-188.ec2.internal   Ready    node     2m    v1.10.6
 ip-172-20-43-113.ec2.internal   Ready    node     2m    v1.10.6

Deploy the Kubernetes Dashboard

  • Deploy the Kubernetes Dashboard by running following command
					 $ kubectl create -f

 secret/kubernetes-dashboard-certs created
 serviceaccount/kubernetes-dashboard created created created
 deployment.apps/kubernetes-dashboard created
 service/kubernetes-dashboard created
  • Access Dashboard using the kubectl command-line tool by running the following command
					 $ kubectl proxy

 Note: Kubectl will handle authentication with apiserver and make Dashboard available at http://localhost:8001/api/v1/namespaces/kube-system/services/https:kubernetes-dashboard:/proxy/
 The UI can only be accessed from the machine where the command is executed.
  • Execute the below command to find the admin service account token
					 $ kops get secrets admin --type secret -oplaintext
  • Provide the above service account token on the service token request page alt text

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Deploy the Application in Kubernetes using .yml file

  • Below is the content of kubeservice-deploy.yml file
					 apiVersion: apps/v1
 kind: Deployment
 	name: kubeservice-deployment
 	    app: kubeservice
 	replicas: 3
 			name: kubeservice
 				app: kubeservice
 		      - name: kubeservice
 		        image: venkataveera/kubeservice:latest
 		        imagePullPolicy: IfNotPresent
 		    restartPolicy: Always
 		      app: kubeservice
 apiVersion: v1
 kind: Service
 	 name: kubeservice-service
     app: kubeservice
     - port: 80
   type: LoadBalancer

  • Click on + CREATE on top right corner of the Kubernetes Dashboad
  • Navigate to ‘CREATE FROM FILE’ tab and select the kubeservice-deploy.yml file

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  • Finally, click on UPLOAD button. This will deploy the application and dashboard looks like below once the deployment is completed.

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  • Access the application using external endpoint listed in Kubernetes – Services Dashboard

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Scaling Kubernetes Cluster pods

  • Verify the current replicas # and deployment of application alt text

  • Navigate to Deployments and click on Scale as shown in below screen alt text

  • Change the Desired number of pods to 5 instead of 3 alt text

  • Click OK to scale the pods to 5 alt text

  • Finally, dashboard looks like this once the deployment is completed alt text

Delete the Kubernetes Cluster

  • Finally, when you are ready to tear down your Kubernetes cluster, you can delete the cluster using following command

					 kops delete cluster --name ${KOPS_CLUSTER_NAME} --yes
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