Commissioning & Go-Live

Commissioning converts design intent into evidence; an AI factory needs two interlocked acceptance tracks — facility and cluster — whose gates you sequence deliberately or the schedule sequences for you.

Every commissioning test needs a pre-agreed quantitative gate and a witnessed signature; the test that proves an AI building works is the one a facility load bank cannot run.

Electrical acceptance forces the paper power chain to prove, with instrumented evidence, that it holds a GPU cluster's synchronized megawatt-scale swings — a load no static load bank reproduces.

Behind the meter you are the grid, and commissioning is where you prove your generation, controls, and storage can keep a gigawatt-class AI load alive when the utility lets go.

A load bank rejects heat to air, never into a cold plate, so the liquid loop first meets realistic transient heat-flux when real GPUs arrive — mechanical Cx and burn-in form one overlapping gate.

IST is the one chance to fail the building on purpose, but load banks miss the millisecond electrical swings and cold-plate heat flux of real GPUs — acceptance must bridge to the first workload.

Fabric defects surface quietly, one marginal optic and one mis-cabled rail at a time; every defect you fail to screen at layer 1 returns as a straggler or a stalled all-reduce in production.

Burn-in forces a GPU fleet's infant-mortality failures into a bounded acceptance window, on synthetic load, before any node joins a synchronous training job whose whole run restarts when one GPU dies.

A cluster is accepted on one number — measured goodput from a sustained reference training run through the production scheduler and storage — because component-level green checkmarks cannot price in system interactions.

Go-live ramps megawatts and synchronized GPU load in stages through an operational-readiness gate; the failure modes are outpacing what grid and cooling can absorb, and handing over before operations is ready.