How teams scaled Azure: 2 real case studies
2 of the 73 engineering write-ups in our database mention Azure in their stack. They come from 2 companies (GitHub and OpenAI) and were published in 2026. Techniques that show up most often alongside Azure: read replicas (2). 2 of the 2 state concrete scale numbers, for example "99.99999% of repositories copied to Azure" (GitHub). Each card below links to our short summary and the original post.
The bridge to agent-scale Git infrastructure
GitHub has copied 99.99999% of its Git repositories to Azure, where most now keep two of their five replicas and Azure serves about half of Git traffic. The busiest remaining repositories were blocked by a ~25ms cross-region round trip, because Spokes held a repository-wide lock for each write while waiting on the slowest healthy replica. Scoping the quorum to individual Git references lets writes to different branches proceed in parallel (3-4x higher throughput in internal testing), and a virtual write replica that streams writes into Azure Blob Storage lets stateless read replicas scale out on demand.
Scaling PostgreSQL to power 800 million ChatGPT users
OpenAI runs ChatGPT on a single-primary Postgres with nearly 50 global read replicas. Reads are offloaded, write-heavy shardable workloads move to Cosmos DB, and PgBouncer, cache leasing and multi-layer rate limits keep the primary safe.