Most teams find out when the job fails
The largest clouds pay whole teams to catch failing GPUs before customers notice. Smaller GPU clouds and AI teams running their own servers do the same job with a handful of people.
No migration
Signals that come too late
Most alerts fire only after a job has crashed, not when the hardware underneath starts to fail. A server can run half-broken for hours before anyone takes it out of service, and by then the work is lost.
Learns your fleet
Fixes don’t travel
Someone fixes a problem at 3 AM. A month later the same problem shows up in another data center, and the team starts from scratch.
stay in control
Manual every time
Every failure means the same manual checklist: collect logs, run tests, move work off the server, test again, send broken parts back to the vendor. Expensive engineering hours spent on work that never changes.
One loop that learns from every run
Harbor looks at all your GPU servers as one system. When something breaks, it finds the cause, fixes it, and remembers the fix for next time.
Whether you run the fleet or need the compute
Built to sit beside your stack
Harbor works with the tools your team already uses. Nothing has to be replaced, and nothing about how you run your servers has to change.
Detection
Deployment
Connects to the job scheduler and monitoring you already run. No migration project, no extra system to look after.
Knowledge
Privacy
Your telemetry stays yours. Harbor learns from your fleet and never shares it with anyone else’s.
Utilization
Explainability
Every action comes with an explanation. Your engineers approve it, change it, or let it run on its own.