Rapidly scaling online storage to serve over 1 billion ChatGPT users (Part II)
2026-10-25 · OpenAI
Rapidly scaling online storage to serve over 1 billion ChatGPT users (Part II)
With the explosive global growth of ChatGPT, its user base has now surpassed the 1 billion mark. Supporting an AI application of this magnitude places unprecedented pressure on the underlying online storage infrastructure. This article details how OpenAI successfully addressed this challenge by scaling its core storage system, Habitat.
The Core Storage System: Habitat
Habitat is the online storage system built by OpenAI to support ChatGPT. Serving over 1 billion users requires the system to handle massive volumes of data read and write requests. To accommodate this rapid business growth, OpenAI performed deep architectural scaling and optimization on Habitat, ensuring its stable operation under ultra-large-scale workloads.
Key Technological Upgrades
To achieve this rapid scaling of the storage system, OpenAI introduced and enhanced three core technologies within Habitat:
1. Reliable Multi-tenancy
When serving over 1 billion users, the system must ensure strict data isolation and security between different users. Habitat achieves this through a reliable multi-tenancy architecture, allowing the same underlying storage infrastructure to securely serve a massive user base. This architecture not only improves resource utilization but also guarantees that data access for different tenants does not interfere with one another during traffic spikes, thereby enhancing the overall stability and reliability of the system.
2. Global Caching
Because ChatGPT users are distributed worldwide, data read latency becomes a critical factor affecting user experience. OpenAI deployed a global caching mechanism within Habitat. By caching frequently accessed data at nodes across the globe, the system significantly reduces the latency of cross-regional data retrieval. This mechanism ensures that users can quickly retrieve the data they need regardless of their location, providing a low-latency access experience for a massive global user base.
3. Integration with Azure Cosmos DB
At the underlying infrastructure level, OpenAI integrated Azure Cosmos DB to scale Habitat's storage capacity. As a highly scalable distributed database service, Azure Cosmos DB provides robust foundational support for Habitat. Through this integration, Habitat is better equipped to handle the storage demands of massive data volumes, leveraging the global distribution capabilities of Cosmos DB to further enhance system elasticity and throughput.
Results: 12× Faster Reads
Through these technological upgrades and architectural optimizations, OpenAI achieved a significant performance breakthrough on Habitat. The most notable result is the delivery of 12× faster reads for ChatGPT.
This performance leap translates to several key benefits:
- Faster response times: When processing user requests, ChatGPT can read context and historical data from the storage layer much more quickly.
- Enhanced concurrency handling: The 12× improvement in read speed allows the system to process a higher volume of user requests within the same timeframe, supporting reliable concurrent access at very large scale.
- Superior user experience: Breaking the storage read bottleneck directly translates to a smoother and faster interactive experience for ChatGPT users.
Conclusion
Serving over 1 billion ChatGPT users is not only a test of AI model computing power but also an extreme challenge for the underlying online storage infrastructure. By building reliable multi-tenancy, deploying global caching, and deeply integrating Azure Cosmos DB within Habitat, OpenAI successfully achieved rapid scaling of its storage system. This not only resulted in 12× faster reads but also provided a highly valuable practical example for the future evolution of storage architectures in ultra-large-scale AI applications.