Pretty anecdotal use case, but when trying to do some type of neural architecture search for ML models that are ultimately going to be run on the edge, running some performance evaluation on a raspberry pi is a decent proxy. I have seen teams build their own type a raspberry clusters for this to be able to evaluate many models in parallel. It's basically a testing proxy for ARM architecture.

But this thing only has 4 RPI per box so I don't quite understand which problem they are targeting either.

This is a great case study of how the Turing Pi helps with CI/CD for ARM infrastructure https://synyx.de/blog/turing-pi-gitlab-ci-ansible/

Besides that the main direction here is edge computing.

I use mine to host some non-revenue-generating websites (they are super cheap for that purpose), and also for some ARM image builds that I integrate into my Docker/Kubernetes pipeline.

I haven't yet moved to ARM CPUs on AWS for some of my projects, but may be able to more quickly if I can have a local cluster like this for testing that isn't as slow as the CM3+-based one the Turing Pi V1 supported.

i often see people claim raspberry pi cheap but in reality it's not. a cluster like this is probably not cheap and performance wise, it's slower than, say an AMD x86 system.

>>Besides academic uses to perhaps teach distributed systems on these are there any real world use cases for these clusters?

A considerable amount of people is already assembling and running clusters of raspberry pis, including hosting companies. A cursory search through eBay or Amazon can provide you with an idea of how many people are already operating these small clusters and spending money on this sort of setup. I'm sure there's a significant demand for a COTS cluster solution that allows people to avoid having to MacGyver their own cluster just to get Docker Swarm or Kubernetes running on a small cluster of raspberry pis.

I know people are building these the questions is for what, CI/CD for ARM like others mentioned is plausible but only if you are targeting the Pi or something very similar just due to how “fragmented” the ARM ecosystem is with its multiple uArchs.

If you are building for mobile then it doesn’t makes sense to run CI/CD on the Pi and if you are targeting your own bespoke edge then likely having dev boards which can represent your edge hardware more accurately is probably going to be a better way.

Running CI/CD for ARMLinux apps is pretty much the only use case I can think of and even that might be limited if you are using extensions.

> I know people are building these the questions is for what, CI/CD for ARM like others mentioned is plausible but only if you are targeting the Pi or something very similar just due to how “fragmented” the ARM ecosystem is with its multiple uArchs.

I don't understand what point you tried to make. These hosting services, and also clients, are quite intentionally targetting the raspberry pi. More specifically, they do target Debian running on Raspberry Pi. I don't understand the confusion. I mean, is it also hard to understand why AWS users pay for ARM instances running Amazon's custom linux distro? In both the Pi and Graviton you can run nginx, nodejs, Python, ssh... So, what's the problem again?

Main use case might be doing whatever you would do on 10 year old laptop reused to be your home server. Similar performance, similar power usage.

You'd be hard pressed to find an old laptop with 32GB of RAM, and a laptop doesn't provide the same operational conditions experienced by a cluster of 4 computers communicating over a network connection.

Scaling horizontally presents entirely new classes of challenges that aren't experienced while scaling vertically.

ThinkPad W530 fits the bill quite well. Broken screen puts it at around $100-150, $300 gets you fully working one. Less tyhan 4 CM4 modules, and what about Turing Pi 2 case? power supply?

>Scaling horizontally presents entirely new classes of challenges that aren't experienced while scaling vertically.

Pay more for challenges? If you really want to fight with bad scaling just run a VM.

Couldn't you buy four 10 year old laptops?

Anyone can buy a brand new raspberry pi 4 with 4GB of RAM for around 50€, which fits on the palm of your hand. You can even get them delivered to your doorstep with a few mouse clicks.

The same can't really be said for 10 year old laptops.

Yes, for the former you have to walk across the room and dig in the closet, optionally ask friends.

- cloud software developers .. (testing/developing with/without internet connections)