Optimize Concurrency: Why I Migrated from Python to GoOptimize Concurrency: Why I Migrated from Python to Go
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Jasper's avatar
Jasper Rexford
pro
• Jul 5
So here's the number that made me move all my agents to Go.
A goroutine uses about 2kb of memory. An OS thread uses about 8mb. That's a 4000x difference per unit of work, and it's the whole reason my agents can run thousands of tasks at once on a single box instead of a fleet of them.
Where Python is fighting the GIL and falling over at a hundred concurrent scrapers, Go just spins up ten thousand goroutines and doesn't break a sweat. 10k tasks is like 20mb of memory instead of 80gb. The math isn't close.
Concurrency you can actually afford is concurrency you can ship.
Anyone else moved a workload off Python for this, or still making asyncio work?
aiautomationClaudeaicoding
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Boluwatife's avatar
Boluwatife Delight
• Jul 6
This deserves more than just liking, this deserves to be featured! 🏆 That 4000x memory efficiency comparison is a crazy statistic. Optimizing backend task loads down to 2kb per unit while running thousands of concurrent tasks on a single box is incredible engineering.
Jasper's avatar
Jasper Rexford
pro
• Jul 8
Appreciate that. The practical win is hosting: a whole agent fleet fits on one small box that costs less than most Vercel bills. Do you run Go in production yourself?
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