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It's still additional operational overhead for marginal RoI. If you're an organization that already has a SRE or Infra Eng hired, there's no point supporting a
by alephnerd 2y ago
It's still additional operational overhead for marginal RoI.
If you're an organization that already has a SRE or Infra Eng hired, there's no point supporting a niche setup when every other team is using a prebuilt and troubleshooted environment.
Edit: Can't reply to OP atm, but he makes a good point. For a higher margins and less commodified segment like ML Compute, on-prem computing still makes financial sense.
That said, that's still managed by actual SWEs not a generic Sysadmin, due to intricacies of GPU Architecture and Model Development, and OP is extremely underskilled for this role.
- shortrounddev2 2y agoI think if all you're running is web microservices, then it's probably not worth it. But my company builds machine learning models offline and I feel that if we bought a dedicated GPU machine (literally just build one and put it in the office, not a rack mounted thing), we would save money in the long run after building a custom training pipeline