Rapidly scaling online storage to serve over 1 billion ChatGPT users (Part II)
Which summary reads better? Pick one — models revealed after.Both summaries are AI-generated.
OpenAI scaled ChatGPT storage to deliver 12x faster reads, enabling sub-100ms latency for over 1B users globally. This matters because reliable low-latency storage at scale is critical for maintaining real-time conversational quality in production LLM agents—slow reads directly degrade user experience and increase inference costs due to idle compute.
OpenAI achieved 12× faster read speeds for ChatGPT's storage backend by pairing Azure Cosmos DB with global caching and strict multi-tenancy controls to serve over one billion users. For teams running stateful agents or high-traffic LLM applications, this establishes a production-proven architecture for session state and memory retrieval, proving that geographically distributed caching layers are non-negotiable for keeping user-context retrieval latencies from bottlenecking your LLM generation times.