[{"data":1,"prerenderedAt":28},["ShallowReactive",2],{"nr-en-openai-habitat-storage-platform-10x-growth":3},{"slug":4,"title":5,"dek":6,"date":7,"time":8,"publishedAt":9,"updated":10,"updatedAt":10,"dateFmt":11,"updatedFmt":10,"kind":12,"tier":13,"author":14,"authorName":15,"topics":16,"tracker":10,"trackerLabel":10,"headlineStat":22,"image":23,"ogImage":24,"imageAlt":5,"csv":10,"minutes":25,"words":26,"html":27},"openai-habitat-storage-platform-10x-growth","OpenAI Unveils Habitat: Storage Platform Grows 10x Annually","OpenAI has publicly disclosed Habitat, its internal storage platform powering ChatGPT, Codex, and other services. The system processes millions of requests per second and has undergone a partial Rust rewrite.","2026-09-12","12:05","2026-09-12T12:05:00+02:00","","September 12, 2026","news","standard","ideal-syka","Ideal Syka",[17,18,19,20,21],"AI Infrastructure","OpenAI","Storage","Scaling","Rust","10x growth year-over-year","\u002Fnewsroom\u002Fimg\u002Fopenai-habitat-storage-platform-10x-growth.webp","\u002Fog-nr\u002Fopenai-habitat-storage-platform-10x-growth.en.png",1,151,"\u003Cp>OpenAI has shared details about \u003Cstrong>Habitat\u003C\u002Fstrong> on Bluesky – its central online storage platform that, according to the company, powers "everything from ChatGPT to Codex." The system has grown \u003Cstrong>10-fold year-over-year\u003C\u002Fstrong>, OpenAI reports.\u003C\u002Fp>\n\u003Ch2>Key Facts\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>\u003Cstrong>Habitat\u003C\u002Fstrong> is OpenAI's enterprise-wide storage infrastructure for AI services\u003C\u002Fli>\n\u003Cli>Before the Rust rewrite, the Python service handled over \u003Cstrong>20 million requests per second\u003C\u002Fstrong> at peak load\u003C\u002Fli>\n\u003Cli>Growth rate: \u003Cstrong>10x year-over-year\u003C\u002Fstrong>\u003C\u002Fli>\n\u003Cli>Parts of the platform have been reimplemented in \u003Cstrong>Rust\u003C\u002Fstrong>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2>What This Means\u003C\u002Fh2>\n\u003Cp>The disclosure of these infrastructure details underscores the massive scaling demands of large-scale AI systems. For German enterprises building their own AI infrastructure, it's clear that storage and data management at millions of concurrent requests requires specialized architectures – a challenge relevant to planning AI infrastructure in-house.\u003C\u002Fp>\n\u003Ch2>Sources\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fbsky.app\u002Fprofile\u002Fopenaibot.bsky.social\u002Fpost\u002F3mvbeguwhgt2b\">OpenAI {bot}\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cem>Editorially owned by \u003Ca href=\"\u002Fen\u002Fautor\u002Fideal-syka\">Ideal Syka\u003C\u002Fa>. Sources and method: \u003Ca href=\"\u002Fen\u002Fredaktion\">Newsroom & method\u003C\u002Fa>. Tips and corrections: \u003Ca href=\"mailto:ai@i6eal.de\">ai@i6eal.de\u003C\u002Fa>.\u003C\u002Fem>\u003C\u002Fp>\n",1789210682267]