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I just won an auction for 25 computers. What should I setup on them? (reddthat.com)

submitted 2 years ago* (last edited 2 years ago) by Trainguyrom@reddthat.com to c/selfhosted@lemmy.world

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I placed a low bid on an auction for 25 Elitedesk 800 G1s on a government auction and unexpectedly won (ultimately paying less than $20 per computer)

In the long run I plan on selling 15 or so of them to friends and family for cheap, and I'll probably have 4 with Proxmox, 3 for a lab cluster and 1 for the always-on home server and keep a few for spares and random desktops around the house where I could use one.

But while I have all 25 of them what crazy clustering software/configurations should I run? Any fun benchmarks I should know about that I could run for the lolz?

Edit to add:

Specs based on the auction listing and looking computer models:

4th gen i5s (probably i5-4560s or similar)
8GB of DDR3 RAM
256GB SSDs
Windows 10 Pro (no mention of licenses, so that remains to be seen)
Looks like 3 PCIe Slots (2 1x and 2 16x physically, presumably half-height)

Possible projects I plan on doing:

Proxmox cluster
Baremetal Kubernetes cluster
Harvester HCI cluster (which has the benefit of also being a Rancher cluster)
Automated Windows Image creation, deployment and testing
Pentesting lab
Multi-site enterprise network setup and maintenance
Linpack benchmark then compare to previous TOP500 lists

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[–] Trainguyrom@reddthat.com 3 points 2 years ago (1 children)

From the listing photos these actually have half-height expansion slots! So GPU options are practically nonexistant, but networking and storage is blown wide open for options compared to the miniPCs that are more prevalent now.

[–] seaQueue@lemmy.world 2 points 2 years ago

Yeah, you'll be fairly limited as far as GPU solutions go. I have a handful of hh AMD cards kicking around that were originally shipped in t740s and similar but they're really only good for hardware transcoding or hanging extra monitors off the machine - it's difficult to find a hh board with a useful amount of vram for ml/ai tasks.