Stop guessing. Cloud Carbon Dating traces the actual energy source powering your AWS, GCP, and Azure instances in real time — then shifts your workloads to minimize emissions automatically.
The same workload produces 90× more carbon depending on where you run it. Norway vs. South Africa.
Add your AWS, GCP, and Azure services below to calculate your aggregated real-time carbon cost.
Your aggregated infrastructure footprint in terms that actually mean something.
Based on your designed monthly cloud architecture usage.
Aggregated footprint of all your architecture items.
Automatically identify the greenest time windows and regions for your workloads — before they run.
Average carbon intensity across all regions, today.
Grid carbon intensity is fetched in real time from ElectricityMap / WattTime APIs for the exact electrical zone powering your cloud region. Intensity fluctuates every 5–15 minutes.
Each cloud service (EC2, Lambda, RDS, S3, Kubernetes, GPU) has a power consumption model in Watts. We multiply by your actual usage × PUE (Power Usage Effectiveness) to get kWh.
Carbon (gCO₂) = Energy (kWh) × Grid Intensity (gCO₂/kWh) × PUE. Converted to relatable equivalents — flights, tree-years, km driven — so the numbers mean something.
Non-urgent batch jobs are held back and scheduled for the cleanest grid window in the next 24 hours (typically during solar peak hours, 11am–3pm local time).
If latency requirements allow, workloads are migrated to a greener region. A job in
ap-south-1 (Mumbai, 713 gCO₂/kWh) vs eu-north-1 (Stockholm, 10 gCO₂/kWh) = 98%
savings.
The Guilt Dashboard refreshes every few seconds with live intensity data, keeping your guilt score and relatable metrics accurate. Set thresholds and get alerts when your footprint spikes.