Observed Signal · Sep 11, 2026 · Technical Release · Source: OpenAI Blog · Impact: 3/5 · Sentiment: Positive
OpenAI Scales Habitat Storage to 1 Billion Users
OpenAI has shared details on scaling its internal storage platform, Habitat, to support over 1 billion weekly users. Habitat now handles more than 70 million requests per second and serves over 500 petabytes of data across nearly 40 regions. The platform evolved from a simple Python client-side library into a standalone service to handle the operational complexity of coordinating deployments across multiple products. Key decisions included adopting Python for flexibility despite performance trade-offs, then rewriting the service in Rust for efficiency. The engineering team addressed issues like asyncio scheduling delays, metastable failures due to LIFO connection pooling, and thundering herd problems by using Envoy for connection management. Habitat uses Azure Cosmos DB for storage and offers an offline analytical view via Rockset. The post is part one of a series on scaling online storage infrastructure.
OpenAI details scaling its storage infrastructure to handle massive user growth, highlighting architectural decisions and performance optimizations that are relevant for AI-powered advertising and marketing platforms.
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Key Takeaways & Evidence Grounding
- Habitat now serves over 70 million requests per second.
- Habitat supports products used by over 1 billion people weekly.
- Habitat serves more than 500 petabytes of data.
- Habitat was rewritten in Rust in Q2 2026, improving CPU efficiency by 6x and memory efficiency by 15x.
- The new Rust service handles 95% of production requests.
Connected Companies & Entities
2 Entities mapped“Every OpenAI product depends on fast, reliable access to data... Habitat is the online storage platform we built so OpenAI products can quic...”
“we scaled our partnership with Azure Cosmos DB to reliably handle unprecedented demand....”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Powering 800 Million ChatGPT Users with PostgreSQL
OpenAI published an engineering post describing how it scaled PostgreSQL to support millions of queries per second and serve 800 million ChatGPT users. The team retained a single-primary Azure PostgreSQL flexible server for writes and operated nearly 50 geo-distributed read replicas, while migrating shardable, write-heavy workloads to sharded systems such as Azure Cosmos DB. Key techniques included aggressive query optimization, workload isolation, PgBouncer connection pooling (reducing average connection time from 50ms to 5ms), cache locking to prevent cache-miss storms, rate limiting, strict schema-change controls, and testing cascading replication with Azure to scale replicas. OpenAI reports low p99 read latency, five-nines availability, and only one SEV-0 Postgres incident in the past 12 months.
OpenAI and AWS Forge $38 Billion AI Partnership
Amazon Web Services (AWS) and OpenAI announced a multi-year strategic partnership under which OpenAI will run and scale its core AI workloads on AWS infrastructure. The agreement represents a $38 billion commitment over the next seven years with growth potential, giving OpenAI immediate access to hundreds of thousands of NVIDIA GPUs (GB200s and GB300s) via Amazon EC2 UltraServers and the ability to scale to tens of millions of CPUs. AWS aims to deploy the targeted capacity before the end of 2026 with the option to expand into 2027 and beyond. The infrastructure is designed for low-latency clustered GPU performance to support both inference (e.g., ChatGPT) and training of next-generation models. The announcement references prior collaboration through availability of OpenAI models on Amazon Bedrock.
Anthropic and OpenAI pursue smaller data center capacity deals
Anthropic and OpenAI are reportedly exploring smaller data center capacity agreements, ranging from 20 to 30 MW, to accelerate deployment of AI workloads across the U.S., U.K., and Nordics. Sources told CNBC that both companies are seeking faster 'speed to usable capacity' from existing powered sites, as large-scale gigawatt projects face community and infrastructural pushback. The shift reflects a growing focus on inference workloads, which can be served by smaller clusters. OpenAI surpassed its Stargate commitment of 10 GW and is adding capacity in Georgia and Ohio, while Anthropic recently signed a $45 billion cloud deal with Nscale. Smaller deployments are seen as practical alternatives to large projects, allowing quicker deployment and flexibility.
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