Your pods reserve four times the CPU they use.
Resource requests are set once, generously, and never revisited. The scheduler reserves the capacity, so nodes fill up on paper while sitting mostly idle.
GreenCode helps tackle this by mapping a running estate and rebuilding it as infrastructure as code. It attributes energy and CO2e to the services that cause it, including services that barely run. More on this.
Your pods may reserve four times the processor power they actually use. Resource requests are often set once, generously, and never checked again. The scheduler holds that space, even when nothing uses it. So your nodes look full on paper, while they sit mostly idle. You run more nodes than the work needs, and every node draws power. Here is the fix you can use today. Compare each request with real usage over a few weeks. Set requests near the ninety-fifth percentile of real use. Review them after each release, because usage changes with the code. GreenCode researchers list over-sized pods among the energy wastes to fix. GreenCode's Constitution skill can help an AI coding agent fix over-sized requests. Then check each pod's energy, using tools like Kepler. GreenCode helps tackle this by mapping your running systems and rebuilding them as code. It shows which services use the energy, including ones that barely run. That was GreenCode Tech Tip number thirty-three. Follow for the next tip, and find more on greencode.ai/tech-tips.
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