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Kubernetes - Getting Started with the Cloud Controller Manager

Reviewed on 10 May 2021Published on 19 March 2020
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Cloud Contoller Manager Overview

A Cloud Controller Manager is a daemon that embeds cloud-specific control loops. It can be used to deploy resources in the Scaleway Elements ecosystem.

Currently the scaleway-cloud-controller-manager implements:

  • Instances interface: updates nodes with cloud provider specific labels and addresses, also deletes kubernetes nodes when deleted from the cloud-provider.
  • LoadBalancer interface: responsible for creating load balancers when a service of type: LoadBalancer is created in Kubernetes.
  • Zone interface: makes Kubernetes aware of the failure domain of each node.

The Scaleway Cloud Controller Manager is currently under active development and released as open-source project on GitHub.

Requirements:

Creating a Kubernetes Cluster using kubeadm on Scaleway Elements

The goal of this step is to create a Kubernetes cluster using kubeadm on Scaleway Elements Virtual Instances.

For the purpose on this example, it is required to create three Ubuntu Bionic instances:

  • master1
  • node1
  • node2
  1. Prepare the instances by runnisng the following commands on each of them:

    apt-get update && apt-get install -y \    iptables \    arptables \    ebtables \    apt-transport-https \    ca-certificates \    curl \    gnupg-agent \    software-properties-commoncurl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -add-apt-repository \  "deb [arch=amd64] https://apt.kubernetes.io kubernetes-xenial main"curl -fsSL https://download.docker.com/linux/ubuntu/gpg | apt-key add -add-apt-repository \  "deb [arch=amd64] https://download.docker.com/linux/ubuntu \  $(lsb_release -cs) \  stable"apt-get update && apt-get install -y \    docker-ce docker-ce-cli containerd.io kubelet kubeadm kubectlapt-mark hold \    docker-ce docker-ce-cli containerd.io kubelet kubeadm kubectlecho KUBELET_EXTRA_ARGS=\"--cloud-provider=external\" > /etc/default/kubelet
  2. Initalize the Kubernetes master on the instance master1:

    root@master1:~# kubeadm init --control-plane-endpoint=$(scw-metadata PUBLIC_IP_ADDRESS) --apiserver-cert-extra-sans=$(scw-metadata PUBLIC_IP_ADDRESS)root@master1:~# mkdir -p ~/.kuberoot@master1:~# cp -i /etc/kubernetes/admin.conf $HOME/.kube/configroot@master1:~# chown $(id -u):$(id -g) $HOME/.kube/configroot@master1:~# kubectl apply -f https://docs.projectcalico.org/v3.11/manifests/calico.yaml
  3. During the installation the kubeadm join command displays. Note it down as it is required for the worker nodes to join the cluster. You can also copy the kubeconfig file and save it on your local computer.

  4. Execute the kubeadm join command on your on each of the worker nodes to join the cluster:

    root@node1:~# kubeadm join 10.68.34.145:6443 --token itvo0b.kwoao79ptlj22gno \    --discovery-token-ca-cert-hash sha256:07bc3f9601f1659771a7a6fd696c2969cbc757b088ec752ba95d5a42c06ed91f
  5. Verify the status of the cluster on the master by running the kubectl get nodes command.

    root@master1:~#  kubectl get nodesNAME       STATUS   ROLES    AGE     VERSIONmaster1    Ready    master   18m     v1.17.4node1      Ready    <none>   8m38s   v1.17.4node2      Ready    <none>   2m31s   v1.17.4

    The cluster is ready and working. Continue by deploying the cloud-controller-manager.

Deploying the cloud-controller-manager on the Cluster

To deploy the cloud-controller-manager the following information are required:

  • Your access key.
  • Your secret key.
  • Your organization id.
  • The Scaleway region.
Note:

You can find this information in the Scaleway Console.

  1. Create a k8s-scaleway-secret.yml containing the follwing information:

    root@master1:~#  nano k8s-scaleway-secret.yml
    apiVersion: v1kind: Secretmetadata:  name: scaleway-secret  namespace: kube-systemstringData:  SCW_ACCESS_KEY: 'xxxxxxxxxxxxxxxx'  SCW_SECRET_KEY: 'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx'  SCW_DEFAULT_REGION: 'fr-par'  SCW_DEFAULT_ORGANIZATION_ID: 'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxx'
  2. Create the secret and deploy the controller

    root@master1:~# kubectl create -f k8s-scaleway-secret.ymlroot@master1:~# kubectl apply -f https://raw.githubusercontent.com/scaleway/scaleway-cloud-controller-manager/master/examples/k8s-scaleway-ccm-latest.yml

Checking that the cloud-controller-manager is working

  1. Verify the cloud-controller-manager is running from the master1 instance:

    root@master1:~# kubectl get pods -n kube-system -l app=scaleway-cloud-controller-managerNAME                                                 READY   STATUS    RESTARTS   AGEscaleway-cloud-controller-manager-584558b994-rln4j   1/1     Running   0          12sroot@master1:~# kubectl get nodesNAME       STATUS   ROLES    AGE     VERSIONmaster1    Ready    master   18m     v1.17.4node1      Ready    <none>   8m38s   v1.17.4node2      Ready    <none>   2m31s   v1.17.4
  2. Deploy a LoadBalancer service and verify a public ip is assigned to this service. The service will automatically create a managed Load Balancer on the Scaleway Elements platform.

    Create a lb.yml file that contains the following information:

    root@master1:~# nano lb.yml
    apiVersion: v1kind: Servicemetadata:  name: example-servicespec:  selector:    app: example  ports:    - port: 8765      targetPort: 9376  type: LoadBalancer
  3. Create the service from the configuration file:

    root@master1:~# kubectl create -f lb.yml
  4. Verify if the service has been created:

    root@master1:~# kubectl get servicesNAME              TYPE           CLUSTER-IP       EXTERNAL-IP     PORT(S)          AGEexample-service   LoadBalancer   10.106.144.144   51.159.26.121   8765:30175/TCP   7skubernetes        ClusterIP      10.96.0.1        <none>          443/TCP          21m

The LoadBalancer service with the internal IP 10.106.144.144 and external IP 51.159.26.121 has been created. You have sucessfully deployed a cluster with kubeadm and the scaleway-cloud-controlle-manager. For more information about the Scaleway Cloud Controller Manager, follow the project on GitHub.