In Q3 2024, our production Celery 5.3 worker fleet running Python 3.13 hit a wall: GIL contention spiked CPU utilization to 92% across 48 cores, with p99 task latency ballooning to 4.7 seconds. After a 6-week deep dive into CPython 3.13’s improved GIL implementation and Celery’s worker pool internals, we cut CPU usage by 40%, reduced p99 latency to 1.1 seconds, and saved $22,000/month in EC2 costs. Here’s exactly how we did it, with reproducible benchmarks and production-grade code. 🔴 Live Ecosystem Stats ⭐ python/cpython — 72,593 stars, 34,557 forks Data pulled live from GitHub and npm.…