Attribute cloud emissions from provider billing and usage data across multiple providers
#00167
Convert itemised cloud billing and usage records into energy and emissions figures using published hardware power coefficients and region-specific grid carbon intensity, producing a per-service, per-region footprint across multiple providers.
Parent issue
#00164 The carbon footprint of software and AI compute is rarely measured, so it cannot be managed
Sustainable Development Goals
Location
Description
The proposal
Pull compute, storage, networking and memory line items from cloud billing and usage APIs, map them to energy using published hardware power coefficients and utilisation heuristics, then apply region-specific carbon intensity to produce a per-service, per-region emissions estimate. Cover scope 2 (electricity) and, where possible, scope 3 (embodied hardware).
Why it works
Billing data is a ready proxy for how much hardware ran and of what type. A provider-agnostic method produces one consistent figure across clouds — something vendor-native tools cannot, since their methodologies differ and are not directly comparable.
Where it fits
Multi-cloud organisations needing a scope 3 cloud-emissions baseline for reporting and reduction opportunities, embedded in existing cloud governance and FinOps processes.
Trade-offs and limitations
Billing-derived usage is coarser than direct metering and typically assumes average rather than measured utilisation, so absolute figures will diverge between tools. The value is a consistent baseline and trend, not an exact number. Provider-native tools can be more accurate for their own cloud (hourly grid mix, machine-level power) at the cost of portability and methodological transparency.
Sub-issues
0Case studies
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