Carbon-Aware Scheduling

A Nairobi logistics firm now runs route optimisation at 11 am instead of 7 pm because the grid is cleaner mid-day when solar floods in. Same result quality, lower gCO2e per job, and servers run cooler in the morning. They publish a monthly AI carbon ledger that shows what was shifted to low-carbon windows and how much diesel the genset avoided. Hook your job scheduler to Kenya’s grid-intensity signals or your own solar/battery forecast. Tag each task with gCO2e and cost, and create a simple rule: if a clean window is within two hours, wait. For SLAs that cannot move, reserve battery power to keep them green during brownouts. Once you show a monthly chart of “jobs shifted, carbon saved, KES saved,” engineering teams get competitive and product managers stop insisting every job run instantly.