An open call to every cloud provider: let tenants see exactly how much energy their VMs consume in real time. Once that data exists, tools like Kepler can break it down to every container and process.
Every major cloud provider has a sustainability pledge. Every one publishes a carbon dashboard — monthly, aggregated, weeks delayed. Yet not a single one gives tenants the one thing that would make software carbon intensity actionable: real-time energy measurements for the workloads they run.
The best the ecosystem can offer today is estimation. Projects like Kepler use ML models to infer energy from CPU counters. Tools like Cloud Carbon Footprint reverse-engineer consumption from billing line items. These are impressive engineering efforts — and they are fundamentally limited by the absence of ground truth.
The hardware already knows. On x86 servers, RAPL (Running Average Power Limit) reads energy at the socket level with hardware-grade accuracy. The hypervisor has this data. It is being withheld from the tenants who need it most.
Energy data exposed to tenants must originate from hardware counters, not from billing-derived estimates. Any hardware measurement — even imperfect — is closer to reality than reverse-engineering energy from cloud bills.
Aggregate carbon dashboards cannot drive workload-level optimization. Energy telemetry must be attributable to individual VM instances and consumable by existing observability stacks like Prometheus and OpenTelemetry.
Rate limiting, noise injection, and domain aggregation are non-negotiable. Energy telemetry must never become a side-channel vector.
Energy telemetry should be a configuration flag on VM creation — available to those who need it, invisible to those who don't.
The telemetry format should be standardized across providers — OpenMetrics-compatible, documented publicly, and governed by a neutral body. No vendor lock-in on sustainability data.
Begin with CPU package energy on x86 where hardware measurement exists and the proportional attribution model is validated. Network, storage, and accelerator attribution should follow as separate, honest specifications.
We built kubmin — a Kubernetes observability tool that tracks per-workload cost, energy consumption, and Software Carbon Intensity scores. It works. But in cloud environments, every energy number it shows is an estimate. The ML models behind tools like Kepler are the best available — and they're still models. We have no way to validate them against ground truth because ground truth is locked inside the hypervisor. Real energy measurements would transform estimates into auditable metrics — not just for kubmin, but for every tool in the ecosystem.
Organizations and projects that support open VM energy telemetry.
We're applying the principle of the Open Cloud Manifesto to the one resource cloud providers measure but don't share — energy. Join the discussion.