Rapidly scaling online storage to serve over 1 billion ChatGPT users
Which summary reads better? Pick one — models revealed after.Both summaries are AI-generated.
OpenAI scaled their storage system to handle 1 billion users and 22 million requests per second by evolving a Python library into a globally distributed platform. This shows you can start small with flexible tools and scale massively without losing agility, proving rapid, cost-effective scaling is achievable for any high-growth AI service. If you're building agents or LLM products, expect to manage similar demand spikes; this approach lets you scale infrastructure incrementally rather than over-provisioning upfront.
OpenAI scaled storage to handle 22 million requests per second, a capability that directly impacts the infrastructure requirements for running large language models in production, and shipping similar LLM-based services will now need to consider supporting comparable request volumes.