Getting Started

Cluster API Provider RKE2 is compliant with the clusterctl contract, which means that clusterctl simplifies its deployment to the CAPI Management Cluster. In this Getting Started guide, we will be using the RKE2 Provider with the docker provider (also called CAPD).

Prerequisites

clusterctl to handle the lifecycle of a Cluster API management cluster
kubectl to apply the workload cluster manifests that clusterctl generates
kind and docker to create a local Cluster API management cluster

Management Cluster

In order to use this provider, you need to have a management cluster available to you and have your current KUBECONFIG context set to talk to that cluster. If you do not have a cluster available to you, you can create a kind cluster. These are the steps needed to achieve that:

Ensure kind is installed.

Create a special kind configuration file if you intend to use the Docker infrastructure provider:

cat > kind-cluster-with-extramounts.yaml <<EOF
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
name: capi-test
nodes:
- role: control-plane
  extraMounts:
    - hostPath: /var/run/docker.sock
      containerPath: /var/run/docker.sock
EOF

Run the following command to create a local kind cluster:

kind create cluster --config kind-cluster-with-extramounts.yaml

Check your newly created kind cluster :

kubectl cluster-info

and get a similar result to this:

Kubernetes control plane is running at https://127.0.0.1:40819
CoreDNS is running at https://127.0.0.1:40819/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy

To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.

Setting up clusterctl

CAPI >= v1.6.0

No additional steps are required and you can install the RKE2 provider with clusterctl directly:

clusterctl init --core cluster-api:v1.9.5 --bootstrap rke2:v0.13.0 --control-plane rke2:v0.13.0 --infrastructure docker:v1.9.5

Next, you can proceed to creating a workload cluster.

CAPI < v1.6.0

With CAPI & clusterctl versions less than v1.6.0 you need a specific configuration. To do this create a file called clusterctl.yaml in the $HOME/.cluster-api folder with the following content (substitute ${VERSION} with a valid semver specification - e.g. v0.5.0 - from releases):

providers:
  - name: "rke2"
    url: "https://github.com/rancher/cluster-api-provider-rke2/releases/${VERSION}/bootstrap-components.yaml"
    type: "BootstrapProvider"
  - name: "rke2"
    url: "https://github.com/rancher/cluster-api-provider-rke2/releases/${VERSION}/control-plane-components.yaml"
    type: "ControlPlaneProvider"

This configuration tells clusterctl where to look for provider manifests in order to deploy provider components in the management cluster.

The next step is to run the clusterctl init command:

clusterctl init --bootstrap rke2 --control-plane rke2

This should output something similar to the following:

Fetching providers
Installing cert-manager Version="v1.10.1"
Waiting for cert-manager to be available...
Installing Provider="cluster-api" Version="v1.3.3" TargetNamespace="capi-system"
Installing Provider="bootstrap-rke2" Version="v0.1.0-alpha.1" TargetNamespace="rke2-bootstrap-system"
Installing Provider="control-plane-rke2" Version="v0.1.0-alpha.1" TargetNamespace="rke2-control-plane-system"

Your management cluster has been initialized successfully!

You can now create your first workload cluster by running the following:

  clusterctl generate cluster [name] --kubernetes-version [version] | kubectl apply -f -

Create a workload cluster

There are some sample cluster templates available under the examples/templates folder. This section assumes you are using CAPI v1.6.0 or higher.

For this Getting Started section, we will be using the docker samples available under examples/templates/docker/ folder. This folder contains a YAML template file called cluster-template.yaml which contains environment variable placeholders which can be substituted using the envsubst tool. We will use clusterctl to generate the manifests from these template files. Set the following environment variables:

NAMESPACE
CLUSTER_NAME
CONTROL_PLANE_MACHINE_COUNT
WORKER_MACHINE_COUNT
KIND_IMAGE_VERSION
RKE2_VERSION

for example:

export NAMESPACE=example
export CLUSTER_NAME=capd-rke2-test
export CONTROL_PLANE_MACHINE_COUNT=3
export WORKER_MACHINE_COUNT=2
export KIND_IMAGE_VERSION=v1.31.4
export RKE2_VERSION=v1.31.4+rke2r1

The next step is to substitue the values in the YAML using the following commands:

cd examples/docker/
cat cluster-template.yaml | clusterctl generate yaml > rke2-docker-example.yaml

At this moment, you can take some time to study the resulting YAML, then you can apply it to the management cluster:

kubectl apply -f rke2-docker-example.yaml

and see the following output:

namespace/example created
cluster.cluster.x-k8s.io/capd-rke2-test created
dockercluster.infrastructure.cluster.x-k8s.io/capd-rke2-test created
rke2controlplane.controlplane.cluster.x-k8s.io/capd-rke2-test-control-plane created
dockermachinetemplate.infrastructure.cluster.x-k8s.io/controlplane created
machinedeployment.cluster.x-k8s.io/worker-md-0 created
dockermachinetemplate.infrastructure.cluster.x-k8s.io/worker created
rke2configtemplate.bootstrap.cluster.x-k8s.io/capd-rke2-test-agent created
configmap/capd-rke2-test-lb-config created

Checking the workload cluster

After waiting several minutes, you can check the state of CAPI machines, by running the following command:

kubectl get machine -n example

and you should see output similar to the following:

NAME                                 CLUSTER          NODENAME                                 PROVIDERID                                          PHASE     AGE    VERSION
capd-rke2-test-control-plane-9kw26   capd-rke2-test   capd-rke2-test-control-plane-9kw26       docker:////capd-rke2-test-control-plane-9kw26       Running   21m    v1.31.4+rke2r1
capd-rke2-test-control-plane-pznp8   capd-rke2-test   capd-rke2-test-control-plane-pznp8       docker:////capd-rke2-test-control-plane-pznp8       Running   8m5s   v1.31.4+rke2r1
capd-rke2-test-control-plane-rwzgk   capd-rke2-test   capd-rke2-test-control-plane-rwzgk       docker:////capd-rke2-test-control-plane-rwzgk       Running   17m    v1.31.4+rke2r1
worker-md-0-hm765-hlzgr              capd-rke2-test   capd-rke2-test-worker-md-0-hm765-hlzgr   docker:////capd-rke2-test-worker-md-0-hm765-hlzgr   Running   18m    v1.31.4+rke2r1
worker-md-0-hm765-w6h5j              capd-rke2-test   capd-rke2-test-worker-md-0-hm765-w6h5j   docker:////capd-rke2-test-worker-md-0-hm765-w6h5j   Running   18m    v1.31.4+rke2r1

Accessing the workload cluster

Once cluster is fully provisioned, you can check its status with:

kubectl get cluster -n example

and see an output similar to this:

NAMESPACE   NAME             CLUSTERCLASS   PHASE         AGE   VERSION
example     capd-rke2-test                  Provisioned   22m

You can also get an “at glance” view of the cluster and its resources by running:

clusterctl describe cluster capd-rke2-test -n example

This should output similar to this:

NAME                                                            READY  SEVERITY  REASON  SINCE  MESSAGE
Cluster/capd-rke2-test                                          True                     5m8s
├─ClusterInfrastructure - DockerCluster/capd-rke2-test          True                     22m
├─ControlPlane - RKE2ControlPlane/capd-rke2-test-control-plane  True                     5m8s
│ └─3 Machines...                                               True                     20m    See capd-rke2-test-control-plane-9kw26, capd-rke2-test-control-plane-pznp8, ...
└─Workers
  └─MachineDeployment/worker-md-0                               True                     11m
    └─2 Machines...                                             True                     15m    See worker-md-0-hm765-hlzgr, worker-md-0-hm765-w6h5j

🎉 CONGRATULATIONS! 🎉 You created your first RKE2 cluster with CAPD as an infrastructure provider.

Using ClusterClass for cluster creation

This provider supports using ClusterClass, a Cluster API feature that implements an extra level of abstraction on top of the existing Cluster API functionality. The ClusterClass object is used to define a collection of template resources (control plane and machine deployment) which are used to generate one or more clusters of the same flavor.

If you are interested in leveraging this functionality, you can refer to the examples here:

clusterclass-template.yaml: creates a sample ClusterClass and necessary resources.
cluster-template-topology.yaml: creates a workload cluster using the ClusterClass.

As with other sample templates, you will need to set a number environment variables:

CLUSTER_NAME
CONTROL_PLANE_MACHINE_COUNT
WORKER_MACHINE_COUNT
KUBERNETES_VERSION
KIND_IP

for example:

export CLUSTER_NAME=capd-rke2-clusterclass
export CONTROL_PLANE_MACHINE_COUNT=3
export WORKER_MACHINE_COUNT=2
export KUBERNETES_VERSION=v1.30.3
export KIND_IP=192.168.20.20

Remember that, since we are using Kind, the value of KIND_IP must be an IP address in the range of the kind network. You can check the range Docker assigns to this network by inspecting it:

docker network inspect kind

The next step is to substitue the values in the YAML using the following commands:

cat clusterclass-quick-start.yaml | clusterctl generate yaml > clusterclass-example.yaml

At this moment, you can take some time to study the resulting YAML, then you can apply it to the management cluster:

kubectl apply -f clusterclass-example.yaml

This will create a new ClusterClass template that can be used to provision one or multiple workload clusters of the same flavor. To do so, you can follow the same procedure and substitute the values in the YAML for the cluster definition:

cat rke2-sample.yaml | clusterctl generate yaml > rke2-clusterclass-example.yaml

And then apply the resulting YAML file to create a cluster from the existing ClusterClass.

kubectl apply -f rke2-clusterclass-example.yaml

Known Issues

When using CAPD < v1.6.0 unmodified, Cluster creation is stuck after first node and API is not reachable

If you use docker as your infrastructure provider without any modification, Cluster creation will stall after provisioning the first node, and the API will not be available using the LB address. This is caused by Load Balancer configuration used in CAPD which is not compatible with RKE2. Therefore, it is necessary to use our own fork of v1.3.3 by using a specific clusterctl configuration.

Kubernetes Cluster API Provider RKE2