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Comment by MattGaiser

9 days ago

It’s also trivial to use now. With AI, there’s no meaningful additional work in using a VM.

Right, instead of using a managed serverless platform where you pay a premium for proprietary cloud provided services to take away the overhead of managing and patching servers for you and let you just deploy containers, you can… pay a premium for proprietary cloud-hosted AI engines to take away the overhead of managing and patching servers for you and let you just deploy containers.

  • That's what I'm doing for my personal stuff. It's all running on a pair of Raspberry Pi's. There's an automation in Codex to, once a week, run a ton of health checks, updates, make sure backups are running, etc., and let me know the outcome. Tailscale acting a little wonky? One quick prompt (from my phone! don't even need to sit down at the keyboard any more) and it's sorted out.

    It's lowered the threshold for homelab style projects dramatically. It's not doing anything I couldn't have, but the juice wasn't worth the squeeze before compared to, say, Pikapods. Now there basically is no squeeze, just juice.

    • Using AI to manage self-hosted servers is completely different from using AI to manage VPS servers.

      VPSes are usually compared to full-service cloud hosting and especially to serverless offerings, with proponents usually claiming that the costs of self-management of a VPS are vastly less than the premium AWS or Google charge for providing managed compute.

      I’m mostly pointing to the irony of eliminating the ‘advantage’ of a VPS (that you can self-manage it like a grown-up, you don’t need a cloud provider to babysit you) by outsourcing management to a stochastic sysadmin who charges by the keypress.