cluster-api VS argo-rollouts

In this blog post, we will demonstrate how easy and fast it is to deploy Sveltos on an RKE2 cluster with the help of ArgoCD, register two RKE2 Cluster API (CAPI) clusters and create a ClusterProfile to deploy Prometheus and Grafana Helm charts down the managed CAPI clusters.

4. Having moved to a container orchestrator, all of my nodes are immutable. Hardware and VM instances _can_ be born magically into existence. Nearly all infra providers support [cluster-api](https://cluster-api.sigs.k8s.io/). Network infrastructure can now be managed with TF, so I go that route.

## Linux curl -L https://github.com/kubernetes-sigs/cluster-api/releases/download/v1.4.4/clusterctl-linux-amd64 -o clusterctl sudo install -o root -g root -m 0755 clusterctl /usr/local/bin/clusterctl ## Mac brew install clusterctl

Did you ever try CAPI? https://github.com/kubernetes-sigs/cluster-api

You might find interesting the capi-rancher-import k8s operator we use in Sylva, it would adopt in Rancher server the Cluster API created k8s clusters (with bootstrap provider kubeadm or even rke2 - you can lookup CAPBR for the latter). I understand your clusters are not created by Cluster API, so if you could move the workloads/resources to new clusters created by Cluster API, this can come handy. (Adoption of non-CAPI clusters into CAPI is not yet a standard practice, more in https://github.com/kubernetes-sigs/cluster-api/issues/7776)

Most of the comments have mentioned older tools like kubespray, Ansible, Rancher etc. I would suggest the cloud native way using ClusterAPI or use a tool that relies on ClusterAPI in the backend called Talos

Cluster API

Sveltos is a powerful open source project that makes managing Kubernetes add-ons a breeze. It automatically discovers ClusterAPI powered clusters and allows you to easily register any other cluster (like GKE). Then, it seamlessly manages Kubernetes add-ons across all your clusters.

And support is on it's way for Argo Rollouts 🎉 https://github.com/argoproj/argo-rollouts/pull/2004

curl -LO https://github.com/argoproj/argo-rollouts/releases/latest/download/kubectl-argo-rollouts-linux-amd64 chmod +x ./kubectl-argo-rollouts-linux-amd64 sudo mv ./kubectl-argo-rollouts-linux-amd64 /usr/local/bin/kubectl-argo-rollouts kubectl argo rollouts version

kubectl create namespace argo-rollouts kubectl apply -n argo-rollouts -f https://github.com/argoproj/argo-rollouts/releases/latest/download/install.yaml

You can see in why argo section here what are the limitations of rolling updates and how rollouts solves it: https://github.com/argoproj/argo-rollouts

Argo Rollouts

Check the public users list https://github.com/argoproj/argo-rollouts/blob/master/USERS.md

Supplementary GitOps operators can also be used for deployment strategies, such as canary releases, A/B tests, and blue/green deployments, which have now been grouped under the term “progressive delivery”. The resources of most GitOps operators are not sufficient for this. One solution is Flagger. The tool that was launched by Weaveworks is now being developed as part of the Flux project. The Argo project also has an operator for this use case: Argo Rollouts. Both offer CRs for implementing progressive delivery strategies in interaction with various ingress controllers and service meshes.