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For local development I much prefer kind [1], which runs everything inside Docker containers and doesn'ttiuch your system.
I do like k3sfor self hosted deployments.
[1] https://kind.sigs.k8s.io/
Anyone else experiencing DNS lookup failures on Minikube-managed clusters running under VirtualBox? The host O/S or host DNS server doesn't seem to matter. I've noticed this when trying to build Alpine Linux-based images, an issue I reported here:
https://github.com/kubernetes/minikube/issues/13968
I'm really at a loss as to how to troubleshoot this as I'm still learning how to use Kubernetes.
as someone late to the party, what's the local development auto-reload, auto-deployment, etc. story in k8s? i can set up a k8s instance with that or k3s or microk8s or whatever relatively easily, but how do i get my code into there without having to build and push images after the smallest change? short googling points to skaffold[0], but is that state of the art?
[0] https://skaffold.dev/
I'm currently working on creating a local dev with https://tilt.dev/ and having a good time
I usually opt for k3d, because it gives you a cluster (or multiple) that runs inside a docker container. If you already have docker running, it's a quick and easy solution for setting up different development clusters.
https://k3d.io/
I'll strongly second this.
Consul + Nomad makes for an excellent home lab setup, using docker, podman, raw binaries, etc, as you observe. It strongly recommends 3-node cluster, but works fine on a single host if you don't need the distributed / HA aspect. We've been running it in production at work for a couple of years and it's been rock solid.
The big problem with Nomad is that it's not as popular as k8s -- so while you can leverage docker hub, there's fewer oven-ready packs for more complex systems, eg cortex metrics or mimir, as current challenges for us.
Hashicorp is building up a public repository [1] which is great to see, but it's a long way from having the same scope as the collected repositories of helm charts.
[1] https://github.com/hashicorp/nomad-pack-community-registry
Have you tried https://mpr.makedeb.org/ ?
It seems like it’s made for Debian based systems, much like the AUR for Arch.
2. https://microk8s.io/
The problem with minikube if you have low resource system. It would definitely headache if you run any heavy Workloads.
KinD requires some docker engine to run it on. That's all I'm using from Rancher. It allows me to switch between containerd and docker-engine.
My options on this physical machine as I see it are: lima, rancher desktop, or Docker Desktop itself. I don't actually use Rancher Desktop for its Kubernetes integration, and in earlier versions it wasn't even possible to do this without weird vague workarounds, but now it has an "Off" switch, and I use it for the rare occasion that I need to run container images locally, or a kind cluster.
I ruled out Docker Desktop because I can't use it alongside of other VMs (not because it doesn't work, which I understood to be true for Windows users, but because it is composed of a virtual machine, with a memory footprint, and one shouldn't have too many of those unless you have a beast of a laptop...) and because it requires paid volume licensing. Don't get me wrong, I like to pay for things, but I also like to evaluate alternatives!
I used this for a while: https://github.com/lima-vm/lima/blob/master/examples/k8s.yam...
It wasn't quite perfectly stable, also not maintained by the Kubernetes core team but externally, so it has to play catch-up a bit when releases are done, rather than in the case of KinD it can enjoy a release on the schedule with Kubernetes.
I am a kubeadm baseline user and I find that Kind is actually the best way to do experiments (I don't use MiniKube at all so can't compare) Some experiments require a bit more control of the VM that runs your CRI and for those there are raw nodes (physical machines) or a Lima VM for a convincing approximation of one.
When there's a need to go to production, I'm generally not using any of these choices, but I am using KinD quite extensively (even on remote nodes!) through tailscale. This is actually really nice.