kops VS k3d

The general problem of patching resource definitions that are not fully under your control has also been recognized for some time. This is true of default resources created and updated by cluster maintenance tools (e.g. kOps), or by public helm charts that you use to install common services and operators (e.g. nginx-ingress, cert-manager, and so on). High quality charts will allow you to override the configuration of important components such as service account references, but some simpler charts offer much less configuration.

The kops documentation is not very clear about this.

Very fast progress and great article with lots of useful information. I found myself nodding a lot having recently seen GitLab Dedicated https://docs.gitlab.com/ee/subscriptions/gitlab_dedicated/ being developed that had my similar challenges. I wonder what other people think of Kops https://kops.sigs.k8s.io/

note: I work with kube on a daily basis. All current clusters under my care use a managed backplane service though there are a number of small (3+ years-old) clusters that I still keep an eye on that were initialized using kops.

kOps with your own instances.

Companies run their own clusters (sometimes for cost reasons), using tools like kops, and kubeadm to set up their own clusters.

curl -Lo kops https://github.com/kubernetes/kops/releases/download/$(curl -s https://api.github.com/repos/kubernetes/kops/releases/latest | grep tag_name | cut -d '"' -f 4)/kops-linux-amd64 chmod +x kops sudo mv kops /usr/local/bin/

Kops is a cluster setup and management command line tool that deploys a Kubernetes cluster to AWS. It provides configuration abstractions such as manifest YAML files that facilitate node and components configuration. And like Ansible, it will provide dry-run capabilities and ensures idempotency of changing the nodes.

K3D: is a lightweight distribution of Kubernetes designed for resource-constrained environments. It is an excellent option for running Kubernetes on virtual machines or cloud servers.

k3d is a lightweight wrapper that makes running Kubernetes (specifically, the lightweight k3s distribution) in Docker straightforward and efficient. It's designed to provide developers with a quick and easy way to test Kubernetes without the overhead of setting up a full cluster.

If you customer prefers to run the standard docker engine you could use k3d

You don’t need to run Rancher from a Kubernetes cluster, the rancher/rancher image works fine with Docker (it uses k3d, aka « k3s in docker » : https://k3d.io/).

K3d and Skaffold for local development

If you are a developer and want to learn how to deploy applications to a cluster, getting a cluster up an running can be a daunting task in it's own rights. There are many ways to do it: spinning up local virtual machines and configuring from scratch or using tools like minikube, etc. You may not care for the pain of setting up and configuring a cluster, and if that is you, then the quickest way that I have found is using k3d.