Measure the emissions of compute you run yourself by sampling hardware power and applying local grid carbon intensity
#00165
For code you operate, sample the energy drawn by CPU, GPU and RAM during execution, multiply by the carbon intensity of the local electricity grid, and log the resulting CO2 estimate next to other run metrics so it can be tracked and reduced.
Red Hat Emerging Technologies and IBM Research, with contributors including Intel and Weaveworks; a CNCF project · since 2023 · Global
Kepler (Kubernetes-based Efficient Power Level Exporter) attributes energy to individual processes, containers, pods, and nodes in orchestrated environments, exporting results as Prometheus metrics. It draws power readi…
Open-source, developed by member companies under the Cloud Native Computing Foundation · 3 sources
Montreal, Quebec, Canada
OngoingMila, BCG GAMMA, Haverford College, Comet.ml, with Data For Good France volunteers (now stewarded by the CodeCarbon non-profit) · since 2020 · Global
CodeCarbon is an open-source Python package that estimates CO2 from code execution. An EmissionsTracker (used as a context manager or decorator) samples CPU energy via Intel RAPL, GPU energy via NVIDIA NVML, and RAM e…
3 sources