turing pi

tl;dr: This website is currently being hosted off-grid, on a cluster of Raspberry Pis, via 4G LTE—or at some points through the same tunnel via WiFi if signal strength gets too low. Here's the GitHub repo for the project.

Note: The website was down for a few hours this morning, as shortly after this post I started getting a 40-50 Mbps flood of POST requests (over 6 million in a 30 minute time frame)... and yeah, no way the little Pi cluster could handle that. Thanks, Internet. It's back up through Cloudflare now, and I'll post more on this 'fun' experience later.

A couple weeks ago, after months of preparation, I took my 4-node Turing Pi 2 cluster (see my earlier review) to my cousin's farm, and ran this website (JeffGeerling.com) on it, live on the Internet—completely disconnected from grid power or hard-wired Internet.

Last year I spent a bit of time building a Kubernetes cluster with the original Turing Pi. It was fun, and interesting, but ultimately the performance of the Compute Module 3+ it was designed around led me to running my homelab off some newer Pi 4 model B computers, which are at least twice as fast for almost everything I run on them.

So this year, I was excited when the folks at Turing Pi sent me a Turing Pi 2 to test drive. And the board arrived just in time for Patrick Kennedy from ServeTheHome to challenge me to a cluster build-off at Supercomputing '21! Check out his ARM cluster build here.

A few months ago, in the 'before times', I noticed this post on Hacker News mentioning the Turing Pi, a 'Plug & Play Raspberry Pi Cluster' that sits on your desk.

It caught my attention because I've been running my own old-fashioned 'Raspberry Pi Dramble' cluster since 2015.

So today, I'm wrapping up my Raspberry Pi Cluster series with my thoughts about the Turing Pi that I used to build a 7-node Kubernetes cluster.

Video version of this post

This blog post has a companion video embedded below:

At this point, I've showed you how you can use the Turing Pi as a Kubernetes cluster to run different things. I barely scratched the surface of what's possible with Kubernetes, but I'm planning on doing another series exploring Kubernetes itself later this year. Subscribe to my YouTube channel if you want to see it!

In this post, I'm going to talk about the Turing Pi's performance. I'll compare it to a more traditional Raspberry Pi cluster, my Pi Dramble, and talk about important considerations for your cluster, like what kind of storage you should use, or whether you should run a 32-bit or 64-bit Pi operating system.

As with all the other work I've done on this cluster, I've been documenting it all in my open source Turing Pi Cluster project on GitHub.

Video version of this post

This blog post has a companion video embedded below:

This is the fourth video in a series discussing cluster computing with the Raspberry Pi, and I'm posting the video + transcript to my blog so you can follow along even if you don't enjoy sitting through a video :)

In the last episode, I showed you how to install Kubernetes on the Turing Pi cluster, running on seven Raspberry Pi Compute Modules.

In this episode, I'm going to show you some of the things you can do with the cluster.

This is the third video in a series discussing cluster computing with the Raspberry Pi, and I'm posting the video + transcript to my blog so you can follow along even if you don't enjoy sitting through a video :)

This post is based on one of the videos in my series on Raspberry Pi Clustering, and I'm posting the video + transcript to my blog so you can follow along even if you don't enjoy sitting through a video :)

In the first episode, I talked about how and why I build Raspberry Pi clusters.

I mentioned my Raspberry Pi Dramble cluster, and how it's evolved over the past five years.

I will be posting a few videos discussing cluster computing with the Raspberry Pi in the next few weeks, and I'm going to post the video + transcript to my blog so you can follow along even if you don't enjoy sitting through a video :)

This is a Raspberry Pi Compute Module.

And this is a stack of 7 Raspberry Pi Compute Modules.

I recently got to play around with a Turing Pi, which uses Raspberry Pi Compute Modules to build a cluster of up to 7 Raspberry Pi nodes.

Interested in learning more about building a Turing Pi cluster? Subscribe to my YouTube channel—I'm going to be posting a series on the Turing Pi and Rasbperry Pi clustering in the next few weeks!

You can buy Compute Modules with or without onboard eMMC memory. If you don't have memory, you can attach a microSD card and boot from it, just like you would on any Raspberry Pi model B or model A. But if you have the eMMC memory, it's nice to be able to 'flash' that memory with an OS, so the compute module uses the onboard storage and doesn't require a separate boot device (either microSD card or USB disk).