OpenShift cluster-api-provider-aws

This repository hosts an implementation of a provider for AWS for the OpenShift machine-api.

This provider runs as a machine-controller deployed by the machine-api-operator

How to build the images in the RH infrastructure

The Dockerfiles use as builder in the FROM instruction which is not currently supported by the RH's docker fork (see https://github.com/kubernetes-sigs/kubebuilder/issues/268). One needs to run the imagebuilder command instead of the docker build.

Note: this info is RH only, it needs to be backported every time the README.md is synced with the upstream one.

Deploy machine API plane with minikube

1. Install kvm

   Depending on your virtualization manager you can choose a different driver. In order to install kvm, you can run (as described in the drivers documentation):

   $ sudo yum install libvirt-daemon-kvm qemu-kvm libvirt-daemon-config-network
   $ systemctl start libvirtd
   $ sudo usermod -a -G libvirt $(whoami)
   $ newgrp libvirt

   To install to kvm2 driver:

   curl -Lo docker-machine-driver-kvm2 https://storage.googleapis.com/minikube/releases/latest/docker-machine-driver-kvm2 \
   && chmod +x docker-machine-driver-kvm2 \
   && sudo cp docker-machine-driver-kvm2 /usr/local/bin/ \
   && rm docker-machine-driver-kvm2

2. Deploying the cluster

   To install minikube v1.1.0, you can run:

   $ curl -Lo minikube https://storage.googleapis.com/minikube/releases/v1.1.0/minikube-linux-amd64 && chmod +x minikube && sudo mv minikube /usr/local/bin/
   

   To deploy the cluster:

   $ minikube start --vm-driver kvm2 --kubernetes-version v1.13.1 --v 5
   $ eval $(minikube docker-env)
   

3. Deploying machine API controllers

   For development purposes the aws machine controller itself will run out of the machine API stack. Otherwise, docker images needs to be built, pushed into a docker registry and deployed within the stack.

   To deploy the stack:

   kustomize build config | kubectl apply -f -
   

4. Deploy secret with AWS credentials

   AWS actuator assumes existence of a secret file (references in machine object) with base64 encoded credentials:

   apiVersion: v1
   kind: Secret
   metadata:
     name: aws-credentials-secret
     namespace: default
   type: Opaque
   data:
     aws_access_key_id: FILLIN
     aws_secret_access_key: FILLIN

   You can use examples/render-aws-secrets.sh script to generate the secret:

   ./examples/render-aws-secrets.sh examples/addons.yaml | kubectl apply -f -

5. Provision AWS resource

   The actuator expects existence of certain resource in AWS such as:

   • vpc
   • subnets
   • security groups
   • etc.

   To create them, you can run:

   $ ENVIRONMENT_ID=aws-actuator-k8s ./hack/aws-provision.sh install

   To delete the resources, you can run:

   $ ENVIRONMENT_ID=aws-actuator-k8s ./hack/aws-provision.sh destroy

   All machine manifests expect ENVIRONMENT_ID to be set to aws-actuator-k8s.

Test locally built aws actuator

1. Tear down machine-controller

   Deployed machine API plane (machine-api-controllers deployment) is (among other controllers) running machine-controller. In order to run locally built one, simply edit machine-api-controllers deployment and remove machine-controller container from it.

2. Build and run aws actuator outside of the cluster

   $ go build -o bin/manager sigs.k8s.io/cluster-api-provider-aws/cmd/manager

   $ ./bin/manager --kubeconfig ~/.kube/config --logtostderr -v 5 -alsologtostderr

3. Deploy k8s apiserver through machine manifest:

   To deploy user data secret with kubernetes apiserver initialization (under config/master-user-data-secret.yaml):

   $ kubectl apply -f config/master-user-data-secret.yaml

   To deploy kubernetes master machine (under config/master-machine.yaml):

   $ kubectl apply -f config/master-machine.yaml

4. Pull kubeconfig from created master machine

   The master public IP can be accessed from AWS Portal. Once done, you can collect the kube config by running:

   $ ssh -i SSHPMKEY ec2-user@PUBLICIP 'sudo cat /root/.kube/config' > kubeconfig
   $ kubectl --kubeconfig=kubeconfig config set-cluster kubernetes --server=https://PUBLICIP:8443
   

   Once done, you can access the cluster via kubectl. E.g.

   $ kubectl --kubeconfig=kubeconfig get nodes

Deploy k8s cluster in AWS with machine API plane deployed

1. Generate bootstrap user data

   To generate bootstrap script for machine api plane, simply run:

   $ ./config/generate-bootstrap.sh

   The script requires AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables to be set. It generates config/bootstrap.yaml secret for master machine under config/master-machine.yaml.

   The generated bootstrap secret contains user data responsible for:

   • deployment of kube-apiserver
   • deployment of machine API plane with aws machine controllers
   • generating worker machine user data script secret deploying a node
   • deployment of worker machineset

2. Deploy machine API plane through machine manifest:

   First, deploy generated bootstrap secret:

   $ kubectl apply -f config/bootstrap.yaml

   Then, deploy master machine (under config/master-machine.yaml):

   $ kubectl apply -f config/master-machine.yaml

3. Pull kubeconfig from created master machine

   The master public IP can be accessed from AWS Portal. Once done, you can collect the kube config by running:

   $ ssh -i SSHPMKEY ec2-user@PUBLICIP 'sudo cat /root/.kube/config' > kubeconfig
   $ kubectl --kubeconfig=kubeconfig config set-cluster kubernetes --server=https://PUBLICIP:8443
   

   Once done, you can access the cluster via kubectl. E.g.

   $ kubectl --kubeconfig=kubeconfig get nodes

Upstream Implementation

Other branches of this repository may choose to track the upstream Kubernetes Cluster-API AWS provider

In the future, we may align the master branch with the upstream project as it stabilizes within the community.