The problem

Teams pick optimisation targets by what annoys them, not by where the energy is. A small saving in software running on millions of machines beats a big saving in a tool run once a month.

The fix you can use today

• List systems by instances deployed and hours run.
• Prioritise high-deployment, always-on code.
• Contribute fixes upstream to open-source you depend on, so every install gains.

GreenCode's climate case shows that a saving counts again on every machine that runs the code.

Tools that help

• cloc: counts lines of code by language, a quick way to size a codebase
• Software Carbon Intensity (SCI) (Green Software Foundation): the Green Software Foundation's method, SCI = ((E x I) + M) per R, adopted as ISO/IEC 21031:2024

How GreenCode helps

GreenCode helps tackle this by weighing each system by its install base, not just its size, so a saving is counted on every copy. Its reports show where capacity can be retired, so the saving is banked rather than spent. More on this.

Tags

#governance#cost

Sources

• Decarbonising computing at scale: why deployment count is the multiplier
• The climate case: what one optimisation is worth

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