Personally I would not use pi's for this. Massive waste of money, the experience is worth it but other than that..
What would you use then?
https://www.servethehome.com/introducing-project-tinyminimic...
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Personally I would not use pi's for this. Massive waste of money, the experience is worth it but other than that..
What would you use then?
https://www.servethehome.com/introducing-project-tinyminimic...
It's actually usable for live services on RPi 2 and on RPi 4 it beats Intel on float ops./joules at 100% utilization.
And if you use multicast UDP you can make these behave cooperatively to scale horizontally beyond what's possible with a vertical solution at a fraction of the purchase/maintenance cost.
I think we are peaking at 2 Gflops/watt for CPU, so if you need silence (passive cooling) and small size this is as good as it will get, probably ever: http://talk.binarytask.com/task?id=8015986770003767235
I'm building a RPi 4 cluster with these heatsinks.
People wanting to torture themselves with k8s at home ... I still dont understand why.
Imagine that the jobs you are interested in want to see some k8s experience. Either you teach it to yourself at home or you justify implementing it at your current job (resume driven development basically).
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Thanks for the tip. I did consider Ebay, but at that point, I figured it was more trouble than it's worth if I bought them used. Ebay doesn't exactly have the best reputation.
Ahhh. I guess it depends on what you're looking for. Mellanox cards and related cabling is generally still pretty good (in UK and Australia anyway). A few years ago I obtained a few 24 port HP Procurve switches (3400cl-24G), with 10GbE (CX4 connectors) on the back. Those worked pretty well, though turned out to be slightly too noisy for use as desktop switches. ;) Taking a quick look on US Ebay now, something like th…
Just be aware that sometimes they change the pins around from the standard pinout, I blew out one of the fans before discovering this. Fan still works, just lost the rpm monitoring :(
What's the actual use case for rpi clusters like this? If the goal is to learn docker or k8s using a realistic setup involving multiple machines, can't it be achieved by using multiple VMs on one physical desktop instead of using the cluster? The 7-node cluster has only 7GB RAM in total, which is not too much to ask on a desktop. I don't know what people do with rpi clusters and I'm honestly puzzled why people bother…
Hello, original author here. I saw a bunch of traffic from Hacker News and decided to drop by. Thanks for sharing it here! I'd be happy to answer any questions.
Hey there. Thanks for the article! I wanted to ask you if it is worth it implementing something similar in the cloud to learn kubernetes. The hardware is prohibitively expensive on Brazil, so maybe a cluster of t2.micro on AWS running for the total amount of 750 hours could serve the learning purpose for free
Servethehome has a series of articles about the machines, though they're focusing on the slightly higher end ones.
And this one special for k8s: https://www.instagram.com/p/CAqtrRBpNRH/
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Very cool work! I wonder the same, for a 'cluster' I'm expecting performance and large memory for example for scientific computing. Other than that I couldn't think of any other use cases. If anyone could enlighten me? Cheers
They built a multi-thousand pi cluster to test the SMP and configuration stuff before running it on a super computer. Virtualising thousands of CPUs on a single machine is still not trivial. Never mind simulating real world network issues. https://www.bitscope.com/blog/FM/?p=GF19A
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Hey mate. The rig looks awesome. How is the performance output compared to a regular desktop with Ryzen-5/7 or Core-i7 processor in it? Can it run Spark? Apologies if my questions are irrelevant. I'm not sure if Spark/Java works well on the ARM platform yet. Although it'd be foolish on my part to expect too much performance from something like this that costs around $600! It'd be an interesting setup to test parallel…
Imagine clustering 7 desktops from 2006, same performance.