Workload isolation: 2 real scaling case studies
2 of the 73 engineering write-ups in our database are tagged with the technique "workload isolation". They come from 2 companies (GitHub and OpenAI) and were published in 2026. Often combined with caching (2) and read replicas (2). 2 of the 2 state concrete scale numbers, for example "473.3 billion Git events/month" (GitHub). Each card below links to our short summary and the original post.
Building Git infrastructure for agent-scale development
GitHub explains why agent workloads strain Spokes, which keeps five durable copies of each repo on fileserver disks, so every added read replica slows writes. The new design coordinates only the ref update, moves compaction and GC to separate workers, and separates storage from compute: Azure Blob Storage holds the authoritative data while lightweight caching workers serve reads.
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.