SPRUCE helps estimate the environmental impact of your cloud usage. By leveraging open source models and data, it enriches usage reports generated by cloud providers and allows you to build reports and visualisations. Having the GreenOps and FinOps data in the same place makes it easier to expose your costs and impacts side by side.
Why SPRUCE?
Cloud providers do report environmental impact — but at a level of aggregation that makes it impossible to act on. Figures are rolled up at account or service level, cover carbon at best, and sit entirely separate from your cost data. They tell you how you’re doing; they don’t help you do better.
SPRUCE is built around the idea that actionable GreenOps requires the same granularity as FinOps:
- Resource-level detail — identify which workloads, teams, or environments are driving your footprint, not just your bill.
- Multiple impact dimensions — beyond carbon, SPRUCE models water consumption, giving a fuller picture of your cloud’s environmental cost.
- GreenOps and FinOps together — cost and impact share the same pipeline, so trade-off decisions are grounded in real data.
- Open and auditable — built on open source models and public data, so your methodology is transparent, not black-boxed.
- Your data stays yours — running on EMR means your CUR data never leaves your AWS environment.
- Actively maintained — unlike Cloud Carbon Footprint, which has been abandoned, SPRUCE is under active development.
SPRUCE handles CUR reports from AWS and partially supports Azure. However, most of the cost from a typical usage already gets estimates.
How it works
SPRUCE uses Apache Spark® to read and write the usage reports (typically in Parquet format) in a scalable way and, thanks to its modular approach, splits the enrichment of the data into configurable stages.
A typical sequence of stages would be:
- estimation of embodied emissions from the hardware
- estimation of energy used
- estimation of water consumption
- application of PUE / WUE and other overheads
- application of carbon intensity factors
Have a look at the methodology section for more details.
One of the benefits of using Apache Spark is that you can use EMR on AWS to enrich the CURs at scale without having to export or expose any of your data.
The code of the project is in our GitHub repo.
SPRUCE is licensed under the Apache License, Version 2.0.
Support
Do you need help with SPRUCE? Want some bespoke work, training or a workshop? We at DigitalPebble, provide consulting services for SPRUCE. Send us an email at spruce@digitalpebble.com!