We recently used Kind for a k8s workshop. We provisioned a beefy cloud server and ran 15 3-node Kind clusters on it, so everyone had it's own k8s instance without having to install anything locally. It worked absolutely great for this purpose.<p>I wrote some scripting around it so people can claim their own cluster via SSH. I'm planning to write a post about it soon and make the code available.
I’ve tried minikube, microk8s, the one bundled with Docker Desktop for Windows, k3s and Red Hat CodeReady. Of these I had the best experience with Kind (by far) and the worst experience with CodeReady (also by far).<p>The thing I like most with Kind: Being inside Docker makes Kind very ephemeral. Every time I start it up I get a fresh cluster. I know where everything is and it doesn’t contaminate my machine.<p>Since some of the authors are on the thread I would like say thank you. I really appreciated the recent improvements to kubectl-integration and the addition of local storage.<p>In the future I would like it to be easier to play with pod and network policies, reduced cluster startup time and reduced node image sizes.<p>Keep up the good work!
I'm a great fan of kind, it's made my life so much easier for a couple of use cases.<p>1) I run a training course on container security. We moved from using straight kubeadm on the student's VMs to using kind clusters. the advantage here being we can customize different clusters for different scenarios by providing a kind config file on start-up. We can also have multiple clusters running on a single VM easily with no interferance between them.<p>2) when evaluating software or trying out a feature, it's really nice to be able to spin up a test cluster in < 2 minutes and try it out, then it's just "kind delete cluster" to get rid of it again.<p>when I compare it to other options (e.g. minikube, microk8s etc) it subjectively feels less "magic" to me, in that it's just one or more Docker containers, running kubeadm, so as long as you understand those two things, you can get a picture of what's going on.
I've recently started prototyping our move to k8s - and my recommendation is stay away from minikube, k3s and kind. Kind looks the best on paper. But canonical has done great with <a href="https://microk8s.io/" rel="nofollow">https://microk8s.io/</a><p>I'd love to hear why anyone preferes any other solution for local development/experimentation.
So does this mean you can run containers in containers orchestrating other containers.
Containers must really be the holy grail of serverless and cloud "nativeness".
I like KinD, but find k3s much faster to bootstrap and lighter-weight too. Rancher have gone GA with it and provide commercial support, Darren Shepherd also tracks the latest k8s release very closely.<p>Linux -> k3s (build a cluster or single node via <a href="https://k3sup.dev" rel="nofollow">https://k3sup.dev</a>)
MacOS/Windows -> k3s (runs k3s in a Docker container, and is super fast)<p>That said, if you're hacking on K8s code, then KinD has nice features to support that workflow. KinD is only suitable for dev, k3s can run in prod also, try both, compare. They are both easy to use.
Used kind + skaffold for 6 months and it was pretty solid. However, eventually switched to k3d and tilt and feeling like this combo is amazing. Cluster takes 2 seconds to create now.
Kind has been a godsend for me. When you've got a 16Gb MBP with both Docker and K8S running, re-using the Docker virtual machine makes a big difference in memory and CPU usage. Thanks to the team!
I really wanted to use kind but the fact that it loses all the data after restart/sleep of computer keeps me from using it.<p>I’m developing Kubernetes controllers and the Custom Resources represent the bits of cloud infrastructure ( <a href="https://crossplane.io" rel="nofollow">https://crossplane.io</a> ). So when I lose the kind cluster, I have to go and delete each and every resource in AWS :( I am unhappily forced to use minikube until support comes to kind.
As a chromebook user with crostini, I'm wondering if this is going to work for me - as neither k3s, nor minikube, or minishift did (due to limitations in crostini).