11–20 of 52 posts
As has become my habit lately, I'll chime in and say if you're interested in accessing your self-hosted services from the internet, IMO tunneling is the way to go: https://github.com/anderspitman/awesome-tunneling
I've been looking into doing an SBC K8s cluster, but had my eyes on the ODroid N2+. Its big.LITTLE design with 4 high-performance cores and 2 low-performance ones would not only boost the compute capacity vs the RPi4, but also perhaps cgroups on the nodes could be configured such that pods only run on the 4 high-performance cores, leaving the 2 low-performance ones available for system daemons, kubelet, etc. The bigg…
In my experience memory is a much bigger bottleneck than CPU, net IO or disk iops.
At the moment my favorite home lab cluster is a bunch of old laptops. They're quad cores too but I've dropped 16 GB of memory in each. It's doing a lot better. Right now the cluster is using 21GB of memory.
I'm able to run everything I've wanted as well as the occasional experiment to try something out.
If I could leave you with something - get more memory than you think you will need. That's been my experience anyway.
I have what I feel is an irrational desire to build an RPi k8s cluster. I feel like I would be better served by a small x86 box, but something about having a real cluster really appeals to me.
I just had to switch to a SFF desktop PC with Ubuntu on it and never looked back. For toying around rPis can be fun but in real life applications, they were getting extremely hot. Had to add extra fans etc.
I still use my rPi4s, one of them connected to my 3D printer with Octoprint installed on it, but that's it.
I have what I feel is an irrational desire to build an RPi k8s cluster. I feel like I would be better served by a small x86 box, but something about having a real cluster really appeals to me.
Pulled the trigger on that three times now.
My first cluster was Raspis and ODroids. The two issues I had - not everything runs on Arm (yet) and memory constraints were tough to work with.
My second cluster - 4 Atomic Pis. The (Intel Atom) quad cores were fine but the 2GB of memory was a real problem when I started playing with more interesting workloads.
The current "production" home cluster is 4 old laptops. They're earlier gen i7s and I've dropped 16GB of memory and 1TB spinning disks in each one. I've never been happier with a cluster. I've been free to spin whatever I want up and it just works. Using RKE to setup Kubernetes takes about 5 minutes to build a cluster and I'm using Longhorn for replicated container native storage. I've run experiments for work and my own experience. Whether its Redis / Cassandra cluster or a Kubernetes Operator I wrote, it can always handle it.
I've found k3s ( https://k3s.io/ ) to be extremely easy to use for setting up and running kubernetes on a group of Raspberry Pis. Specifically, I followed this guide to get my clusters up and running quickly and it's worked out pretty well: https://blog.alexellis.io/test-drive-k3s-on-raspberry-pi/
I would agree here - k3s is much better suited for RPi than kubeadm, this looks like a rehash of my original tutorial from several years ago -> https://github.com/teamserverless/k8s-on-raspbian/
Today, I point folks here to get everything up and running with minimal overheads -> https://alexellisuk.medium.com/walk-through-install-kubernet...
[1] https://k3s.io/
As has become my habit lately, I'll chime in and say if you're interested in accessing your self-hosted services from the internet, IMO tunneling is the way to go: https://github.com/anderspitman/awesome-tunneling
I use chisel for dancing across firewalls and across Big Corp's (TM) network policies. Chisel is fantastic. It wraps an SSH tunnel for proxying TCP (or reverse proxying) in HTTP, which I expose over TLS. https://github.com/jpillora/chisel
So you can get a LoadBalancer etc.
https://blog.alexellis.io/ingress-for-your-local-kubernetes-...
Earlier quoted context omitted.
I use chisel for dancing across firewalls and across Big Corp's (TM) network policies. Chisel is fantastic. It wraps an SSH tunnel for proxying TCP (or reverse proxying) in HTTP, which I expose over TLS. https://github.com/jpillora/chisel
I'm the author of inlets and would suggest you take a look at that. It's great for the use-case in question and built as a cloud native application with Docker images, Kubernetes YAML files and an operator available. So you can get a LoadBalancer etc. https://blog.alexellis.io/ingress-for-your-local-kubernetes-...
As has become my habit lately, I'll chime in and say if you're interested in accessing your self-hosted services from the internet, IMO tunneling is the way to go: https://github.com/anderspitman/awesome-tunneling
i've been using tailscale for this and am very happy with it