Advisory · GPU operations

Stand up and scale GPU capacity without stranding it.

Operating guidance for teams bringing GPU capacity online or scaling it, framed against the facility, power, and cooling limits that bind first.

Readiness and scale triggers

When this engagement is relevant.

  • A GPU deployment has to stand up on a fixed timeline.
  • Capacity is scaling faster than the operating model can keep up.
  • Utilization is uneven and the reason is not clear.
  • Power or cooling headroom is close to binding.
  • A capacity plan has to hold as demand grows.

Capacity and facility constraint map

Where capacity binds first.

Power

Available supply, redundancy, and the headroom left before it binds.

Cooling

What the design can reject as density and utilization rise.

Space

Floor, rack, and layout limits against the deployment plan.

Network

Fabric and connectivity limits that shape usable capacity.

Supply

Lead times on the hardware and parts the plan depends on.

Operating model topics

What the operating model has to answer.

Utilization

How busy the fleet actually is, and where it idles.

Scheduling

How work is placed against the capacity available.

Reliability

How failures are absorbed without stranding capacity.

Capacity planning

How the next block of capacity is sized and timed.

Decision artifacts

What gets documented.

  • A documented constraint map across power, cooling, space, network, and supply.
  • A view of where capacity binds first as the fleet scales.
  • A set of operating topics with the trade-offs made explicit.
  • A clear statement of what was assumed and what was withheld.

Boundaries and handoff

Advisory, not managed operations.

  • Advisory guidance, not managed operations.
  • No on-call, monitoring, or run duties are taken on.
  • No staff augmentation or seconded headcount.
  • The work ends with the brief and its handoff.

Questions

Common questions.

Do you run the operation for us?
No. This is advisory, not managed operations. The work documents the decisions and the constraints, then hands off. It does not take on run duties.
Can you work from our own metrics?
Yes. The guidance is built on your utilization, capacity, and facility data. Karaya does not invent capacity or utilization figures.
Where does the engagement end?
It ends with the brief: a documented constraint map and the decision artifacts agreed at the start. No retainer is assumed.

Related

Industry News.

Signals on GPU systems, facilities, power, and capital, with context for the decision.

Follow Industry News

Related

Insights.

Original written analysis on operating and scaling compute capacity.

Read Insights

Start with the brief

Bring the operating decision in front of you.

Two or three sentences on what you are standing up or scaling is enough to start.