ClusterClass and managed topologies blog
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layout: blog
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title: "Introducing ClusterClass and Managed Topologies in Cluster API"
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date: 2021-10-04
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slug: capi-clusterclass-and-managed-topologies
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---
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**Author:** Fabrizio Pandini (VMware)
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The [Cluster API community](https://cluster-api.sigs.k8s.io/) is happy to announce the implementation of *ClusterClass and Managed Topologies*, a new feature that will greatly simplify how you can provision, upgrade, and operate multiple Kubernetes clusters in a declarative way.
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## A little bit of context…
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Before getting into the details, let's take a step back and look at the history of Cluster API.
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The [Cluster API project](https://github.com/kubernetes-sigs/cluster-api/) started three years ago, and the first releases focused on extensibility and implementing a declarative API that allows a seamless experience across infrastructure providers. This was a success with many cloud providers: AWS, Azure, Digital Ocean, GCP, Metal3, vSphere and still counting.
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With extensibility addressed, the focus shifted to features, like automatic control plane and etcd management, health-based machine remediation, machine rollout strategies and more.
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Fast forwarding to 2021, with lots of companies using Cluster API to manage fleets of Kubernetes clusters running workloads in production, the community focused its effort on stabilization of both code, APIs and documentation, and on extensive test signals which inform Kubernetes releases.
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With solid foundations in place, and a vibrant and welcoming community that still continues to grow, it was time to plan another iteration on our UX for both new and advanced users.
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Enter ClusterClass and manage topologies, tada!
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## ClusterClass
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As the name suggests, ClusterClass and managed topologies are built in two parts.
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The idea behind ClusterClass is simple: let’s define the shape of your cluster once, and then reuse it many times, abstracting the complexities and the internals of a Kubernetes cluster away.
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ClusterClass, at its heart, is a collection of Cluster and Machine templates. You can use it as a “stamp” that can be leveraged to create many clusters of a similar shape.
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```yaml
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---
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apiVersion: cluster.x-k8s.io/v1beta1
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kind: ClusterClass
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metadata:
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name: my-amazing-cluster-class
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namespace: bar
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spec:
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controlPlane:
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ref:
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apiVersion: controlplane.cluster.x-k8s.io/v1beta1
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kind: KubeadmControlPlaneTemplate
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name: high-availability-kcp
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machineInfrastructure:
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ref:
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apiVersion: infrastructure.cluster.x-k8s.io/v1alpha4
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kind: VSphereMachineTemplate
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name: controlplane-vsphere-machinetemplate
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workers:
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deployments:
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- class: linux-worker
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template:
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bootstrap:
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ref:
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apiVersion: bootstrap.cluster.x-k8s.io/v1beta1
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kind: KubeadmConfigTemplate
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name: linux-bootstrap
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infrastructure:
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ref:
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apiVersion: infrastructure.cluster.x-k8s.io/v1alpha4
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kind: VSphereMachineTemplate
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name: linux-vsphere-template
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- class: windows-worker
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template:
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bootstrap:
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ref:
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apiVersion: bootstrap.cluster.x-k8s.io/v1beta1
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kind: KubeadmConfigTemplate
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name: windows-bootstrap
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infrastructure:
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ref:
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apiVersion: infrastructure.cluster.x-k8s.io/v1alpha4
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kind: VSphereMachineTemplate
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name: windows-vsphere-template
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infrastructure:
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ref:
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apiVersion: infrastructure.cluster.x-k8s.io/v1alpha4
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kind: VSphereClusterTemplate
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name: vsphere-cluster
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```
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The possibilities are endless; you can get a default ClusterClass from the community, “off-the shelf” classes from your vendor of choice, “certified” classes from the platform admin in your company, or even create custom ones for advanced scenarios.
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## Managed Topologies
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Managed topologies let you put the power that ClusterClass provides into action.
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Given a ClusterClass, you can create many Clusters of a similar shape by providing a single resource, the Cluster.
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Here is an example:
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```yaml
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---
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apiVersion: cluster.x-k8s.io/v1beta1
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kind: Cluster
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metadata:
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name: my-amazing-cluster
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namespace: bar
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spec:
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topology: # define a managed topology
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class: my-amazing-cluster-class # use the ClusterClass mentioned earlier
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version: v1.21.2
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controlPlane:
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replicas: 3
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workers:
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machineDeployments:
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- class: linux-worker
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name: big-pool-of-linux-machines-1
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replicas: 5
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- class: linux-worker
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name: small-pool-of-linux-machines-1
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replicas: 1
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- class: windows-worker
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name: pool-of-windows-machines
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replicas: 3
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```
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But there is more than simplified cluster creation. Now the Cluster acts as a single control point for your entire topology.
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All the power of Cluster API, extensibility, lifecycle automation, stability, all the features required for managing an enterprise grade Kubernetes cluster on the infrastructure provider of your choice are now at your fingertips: you can create your Cluster, add new machines, upgrade to the next Kubernetes version, and all from a single place.
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It is just as simple as it looks!
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## What’s next
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While the amazing Cluster API community is working hard to deliver the first version of ClusterClass and managed topologies later this year, we are already looking forward to what comes next for the project and its ecosystem.
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There are a lot of great ideas and opportunities ahead!
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We want to make managed topologies even more powerful and flexible, allowing users to dynamically change bits of a ClusterClass according to the specific needs of a Cluster; this will ensure the same simple and intuitive UX for solving complex problems like e.g. selecting machine image for a specific Kubernetes version and for a specific region of your infrastructure provider, or injecting proxy configurations in the entire Cluster, and so on.
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Stay tuned for what comes next, and if you have any question, comment or suggestion:
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* Chat with us on the Kubernetes [Slack](http://slack.k8s.io/):[#cluster-api](https://kubernetes.slack.com/archives/C8TSNPY4T)
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* Join the SIG Cluster Lifecycle [Google Group](https://groups.google.com/g/kubernetes-sig-cluster-lifecycle) to receive calendar invites and gain access to documents
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* Join our [Zoom meeting](https://zoom.us/j/861487554), every Wednesday at 10:00 Pacific Time
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