How teams scaled Workers: 2 real case studies
2 of the 94 engineering write-ups in our database mention Workers in their stack. They come from 1 company (Cloudflare) and were published in 2026. 2 of the 2 state concrete scale numbers, for example "99.99% production availability target" (Cloudflare). Each card below links to our short summary and the original post.
Inside Hyperdrive: How we solved a rare Hyperdrive MySQL caching bug
Hyperdrive, Cloudflare's distributed connection pooler for Workers, keeps warm database connections on its network and can cache common query results in the CDN cache. Taking its MySQL support from beta to GA meant finding bugs like utf8 being a 3-byte alias (fixed with utf8mb4) and COM_RESET_CONNECTION silently resetting the charset to the server default. The hardest was an empty-result bug seen by the highest-volume MySQL customer in about 0.001% of queries, only with caching on. Each Hyperdrive instance has a Client node next to the Worker and an Endpoint node near the database, and they share a cache when they run in the same data center. Because drivers like Node's mysql2 don't support CLIENT_DEPRECATE_EOF, the Client rewrites results into the Worker's capabilities, so the two nodes were caching different bytes for the same query and could read each other's entries. Caching one canonical encoding no matter which node stores it fixed the bug, and Client connection success reached 99.99%.
Under the hood, off the hot path: how D1 scales to millions of databases
How Cloudflare's D1 keeps query execution at the edge while a separate control plane manages millions of SQLite databases.