Energy-awareAIcompute
AI workloads are becoming a material electrical load at exactly the moment European grids are most constrained. That makes energy an input to the scheduling decision rather than a line item after it.
Theschedulingdecision
Grid and site signals inform a placement decision, bounded by workload criticality. Work a person is waiting on is never traded against price.
Orchestration
Workload criticality decides what may be deferred. Governed work that a person is waiting on is never traded against price.
Thepremise
Not all compute is equally urgent. An operator waiting for a decision needs an answer now. A nightly re-embedding job, a batch evaluation run, a model fine-tune or a large back-population does not care whether it happens at two in the afternoon or three in the morning — but the grid does, and so does the electricity bill.
Once a scheduler knows which workloads are deferrable and by how long, energy price and grid conditions become legitimate inputs to placement. At sufficient scale, deferrable compute starts to look like a grid asset: a load that can be shifted, reduced or moved between locations in response to conditions.
The reason this is on the infrastructure section rather than in a sustainability statement is that it is an engineering problem with a governance dimension, and it only works if workload criticality is modelled honestly.
Whatisreal,andwhatisnotyet
This is a differentiated direction and it is early. The distinction below is the point of the page.
Workload classification
AvailableDeclaring which workloads are interactive, deferrable or discretionary, with a maximum acceptable delay per class.
Priority and preemption
AvailableScheduling policy that protects interactive work and preempts discretionary work under capacity pressure.
Spend and budget control
AvailableEnforced cost ceilings per workload and per period, which is the crude form of the same idea.
Price-aware scheduling
In developmentShifting deferrable work towards cheaper or cleaner windows using forward price and carbon-intensity signals.
Thermal-aware placement
ResearchUsing site temperature and cooling headroom as a placement input rather than only as an alarm.
Battery and on-site generation
ResearchIncorporating storage state and local generation into the decision.
Grid constraint response
ResearchResponding to distribution-level constraint signals by curtailing or migrating discretionary compute.
Demand-response participation
Strategic directionTreating deferrable compute as a dispatchable resource in a flexibility market.
Energy-aware scheduling is easy to describe and hard to do without degrading service. Anything on this page marked research or direction has not been demonstrated in a customer environment, and we will not describe it as though it has.
Questions
- Will this delay work our operators depend on?
- No. Interactive and governed work with a person waiting is never deferred. Only workloads explicitly classified as deferrable or discretionary are eligible, and the maximum delay is declared per class.
- Is this a sustainability feature or a cost feature?
- Both, and they mostly point the same way, because cheap windows and low-carbon windows correlate on European grids. Where they diverge, which one to optimise is a policy choice you make rather than one we make for you.
- Does this require your own datacenter?
- No. Classification, priority and budget control apply in any posture today. The signal-driven parts benefit from more control over the facility, which is one of the reasons the infrastructure direction and this research are connected.
- Available
- In production use today.
- In development
- Being built now. Not yet generally deployable.
- Planned
- On the roadmap. Not yet in development.
- Research
- Under investigation in Labs. May not become a product.
- Strategic direction
- Intent, not a delivery commitment.
Continue
- AI datacenterThe infrastructure direction this research informs.
- Energy & utilitiesThe sector that understands this problem best.
- LabsHow research becomes platform capability.
- RuntimeWorkload policies and placement today.
- Infrastructure overviewWhere this sits in the stack.
- StrategyWhy infrastructure control is a growth engine.
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