Live data from Hacker News

Turing Pi: Kubernetes Cluster on Your Desk

turingpi.com

11–20 of 65 posts

Re: Turing Pi: Kubernetes Cluster on Your Desk

#11
post #2

Looking at the specs, it seems almost dishonest to promote this for kubernetes. > The nodes interconnected with the onboard 1 Gbps switch. However, each node is limited with 100 Mbps USB speed. Not only that but Compute Module 3+ are limited to 1GB RAM, is it really expected someone could run a realistic workload? How stable is the control plane node with such limited resources? It seems like picking up 3 raspi4s (4G…

I built a cluster of 6 pi 3b+ duct taped to a USB hub for power and a switch and router a few years ago for the explicit purpose of experimenting with clustering technologies, including kubernetes. I wasn't running it for long periods of time but it was surprisingly stable. But to your point, 1GB RAM doesn't get you very far with many of the popular distributed systems these days.

Re: Turing Pi: Kubernetes Cluster on Your Desk

#12

There's something amusingly cyclical about a blade server architecture for Kubernetes. The tech comes out of a whole movement towards combining commodity machines using clever software instead of buying specialist hardware, but then adds the specialist hardware back in. Some deeper integration between Kubernetes and the hardware (acceleration/offload ASICs maybe), branding of k8s + this hardware as a unified product,…

Think of it as a way of using mixed hardware: mainframe hardware in conjunction with commodity hardware. It's extremely useful in that context.

Re: Turing Pi: Kubernetes Cluster on Your Desk

#14
While Raspberry Pi's are awesome, and the power consumption is nothing to scoff at (when considering a cluster), you can accomplish this same thing for a lot less, and have quite a lot more compute power, by purchasing a used server or even something like an AMD 3600X...

A single 3600X will grossly outperform this cluster (and cost less) with less headaches (you don't have N physical machines) by using KVM to deploy a few virtual machines and using Kubernetes to orchestrate and allocate within those VMs. You'll also have a lot less latency between nodes running in VMs on the same physical host.

Another thing that unfortunately sucks about Raspberry Pis (less with Pi 4, but still mostly applies) is really shitty I/O performance...

I spent a large amount of time over the past summer and fall trying out various ideas to have a "cluster" at home that was both practical and useful. While, the PIs were nice, they never really amounted to much more than a demo. Latency and I/O become real problems for a lot of useful interconnected services and applications.

Honestly, if Ryzen 3000 hadn't come out, for cheaper cluster builds (~300-400) I still think Pis would be a solid choice but... Ryzen 3000 is just so fucking fast with a lot of cores, it's truly hard to beat.

Addendum: to touch on used servers, yes your power bill will go way up, no joke, but for some applications like large storage arrays-- it's hands down the cheapest/easiest route. Search by case, not by processor, it sounds weird but the case is likely the most valuable part of the old server (like ones with 20+ SAS2 slots for $500) or PCI-E slots that GPUs can fit into.

Re: Turing Pi: Kubernetes Cluster on Your Desk

#15
This is neat, but I'm really more interested to hear about potential use cases. I'm guessing this is mostly useful for ARM workloads? Maybe some situations with low power requirements?

Personally, for my multi-node test clusters, I just run VMs on cheap x86 hardware.

Re: Turing Pi: Kubernetes Cluster on Your Desk

#16

This is neat, but I'm really more interested to hear about potential use cases. I'm guessing this is mostly useful for ARM workloads? Maybe some situations with low power requirements? Personally, for my multi-node test clusters, I just run VMs on cheap x86 hardware.

some ideas https://blog.alexellis.io/

Re: Turing Pi: Kubernetes Cluster on Your Desk

#17

While Raspberry Pi's are awesome, and the power consumption is nothing to scoff at (when considering a cluster), you can accomplish this same thing for a lot less, and have quite a lot more compute power, by purchasing a used server or even something like an AMD 3600X... A single 3600X will grossly outperform this cluster (and cost less) with less headaches (you don't have N physical machines) by using KVM to deploy…

you mean using a ryzen with VMs (cluster on one ryzen) I assume? bc cost of ryzan as a node would be pretty pricey compared to Pi 4s.

Re: Turing Pi: Kubernetes Cluster on Your Desk

#18
post #17

While Raspberry Pi's are awesome, and the power consumption is nothing to scoff at (when considering a cluster), you can accomplish this same thing for a lot less, and have quite a lot more compute power, by purchasing a used server or even something like an AMD 3600X... A single 3600X will grossly outperform this cluster (and cost less) with less headaches (you don't have N physical machines) by using KVM to deploy…

you mean using a ryzen with VMs (cluster on one ryzen) I assume? bc cost of ryzan as a node would be pretty pricey compared to Pi 4s.

Yes, a single ryzen node running multiple VMs.

Re: Turing Pi: Kubernetes Cluster on Your Desk

#19

While Raspberry Pi's are awesome, and the power consumption is nothing to scoff at (when considering a cluster), you can accomplish this same thing for a lot less, and have quite a lot more compute power, by purchasing a used server or even something like an AMD 3600X... A single 3600X will grossly outperform this cluster (and cost less) with less headaches (you don't have N physical machines) by using KVM to deploy…

The other part of 'on your desk' is hearing damage.

Server hardware vendors have traditionally not given two shits about their servers being north of 90 decibels, and I'm pretty sure I've witnessed a few that were pushing 100.

That Raspberry Pi is probably going to absorb more noise than it makes.

Re: Turing Pi: Kubernetes Cluster on Your Desk

#20
post #2

Looking at the specs, it seems almost dishonest to promote this for kubernetes. > The nodes interconnected with the onboard 1 Gbps switch. However, each node is limited with 100 Mbps USB speed. Not only that but Compute Module 3+ are limited to 1GB RAM, is it really expected someone could run a realistic workload? How stable is the control plane node with such limited resources? It seems like picking up 3 raspi4s (4G…

I'd hope people wouldn't be using a setup like this for any other reason than learning k8s or tinkering/fun.

edit-before-actually-posting (sorry I'm a bad person for typing a reply before clicking the link): Wait, they're selling these things? Ok, then I'm stumped. What would you do with 8 rpi's that you couldn't do with one?

Post reply on HN