Kubeadm control plane

Using the Kubeadm control plane type to manage a control plane provides several ways to upgrade control plane machines.

Upgrading workload clusters

The high level steps to fully upgrading a workload cluster are to first upgrade the control plane and then upgrade the worker machines.

Upgrading the control plane machines

How to upgrade the underlying machine image

To upgrade the control plane machines underlying machine images, the MachineTemplate resource referenced by the KubeadmControlPlane must be changed. Since MachineTemplate resources are immutable, the recommended approach is to

  1. Copy the existing MachineTemplate.
  2. Modify the values that need changing, such as instance type or image ID.
  3. Create the new MachineTemplate on the management cluster.
  4. Modify the existing KubeadmControlPlane resource to reference the new MachineTemplate resource.

The final step will trigger a rolling update of the control plane using the new values found in the MachineTemplate.

How to upgrade the Kubernetes control plane version

To upgrade the Kubernetes control plane version, which will likely, depending on the provider, also upgrade the underlying machine image, make a modification to the KubeadmControlPlane resource’s Spec.Version field. This will trigger a rolling upgrade of the control plane.

Some infrastructure providers, such as CAPA, require that if a specific machine image is specified, it has to match the Kubernetes version specified in the KubeadmControlPlane spec. In order to only trigger a single upgrade, the new MachineTemplate should be created first and then both the Version and InfrastructureTemplate should be modified in a single transaction.

Upgrading workload machines managed by a MachineDeployment

Upgrades are not limited to just the control plane. This section is not related to Kubeadm control plane specifically, but is the final step in fully upgrading a Cluster API managed cluster.

It is recommended to manage workload machines with one or more MachineDeployments. MachineDeployments will transparently manage MachineSets and Machines to allow for a seamless scaling experience. A modification to the MachineDeployments spec will begin a rolling update of the workload machines.

For a more in-depth look at how MachineDeployments manage scaling events, take a look at the MachineDeployment controller documentation and the MachineSet controller documentation.