Carbon-Aware ML Ops for Kenyan Teams

The Green Software Foundation’s Green AI position paper distils two simple rules: (1) schedule heavy jobs when the grid is cleanest, and (2) publish the carbon math. For Kenya, that means leaning on mid-day solar windows and keeping a light audit trail of gCO2e per run. It is not theory—teams are doing it now. A fintech in Upper Hill shifted nightly model retrains to late morning when solar is abundant on the grid; they log gCO2e and KES per run and surface it in Slack. Result: same model quality, fewer genset hours, and an ESG line item the CFO can defend. Borrow their playbook: connect your scheduler to grid-intensity data (or your own solar forecast), create a “wait if clean window < 2 hours away” rule, and keep a monthly ledger of carbon and cash. After one quarter, you will have defensible numbers for leadership and a habit that costs almost nothing to maintain.