Measuring energy consumption is an important step for teams to reduce the carbon footprint of their software. Cloud Carbon Footprint (CCF) estimates energy based on billing and usage data retrieved from cloud APIs. Kepler — short for Kubernetes-based Efficient Power Level Exporter — goes one step further: it uses software counters via RAPL, ACPI and nvml to measure power consumption by hardware resources and employs an eBPF-based approach to attribute power consumption to processes, containers and Kubernetes pods. Power usage is then converted to energy estimates using a custom ML model and data from the SPEC Power benchmark. Finally, pod-level energy consumption reporting is made available as Prometheus metrics. In cases where Kubernetes is running on virtual machines, for example when not using bare metal instances, Kepler uses cgroups to estimate energy consumption. We've had significant experience with CCF and can attest to its usefulness, but we're intrigued by the Kepler project’s approach.
