How teams scaled Go: 7 real case studies
7 of the 73 engineering write-ups in our database mention Go in their stack. They come from 5 companies (Cloudflare, Datadog, Discord, Dropbox and Slack) and were published between 2017 and 2023 (1 undated). Techniques that show up most often alongside Go: columnar storage (2) and multi-tenancy (2). It's often paired with Kafka (2) and Rust (2). 3 of the 7 state concrete scale numbers, for example "14 million HTTP requests/sec (network peak)" (Cloudflare). Each card below links to our short summary and the original post.
Husky: Exactly-once ingestion and multi-tenancy at scale
A deep dive on how Husky routes, shards and ingests events exactly once across tenants.
Introducing Husky, Datadog's third-generation event store
Datadog's Husky is a distributed, schemaless column store that keeps event data on object storage.
Introducing Quicksilver: Configuration Distribution at Internet Scale
Quicksilver replicates Cloudflare's config key-value store to every edge server in seconds, built on LMDB.
Why Discord is switching from Go to Rust
Discord rewrote its Read States service from Go to Rust to get rid of garbage-collection latency spikes in a large in-memory cache.
HTTP Analytics for 6M requests per second using ClickHouse
Cloudflare rebuilt its HTTP analytics pipeline on ClickHouse, replacing a Postgres/Citus setup.
Flannel: An Application-Level Edge Cache to Make Slack Scale
Slack added Flannel, an edge cache that serves user and channel data lazily so huge teams no longer need giant boot payloads.
Scaling to exabytes and beyond
Dropbox built Magic Pocket, its own exabyte-class block store, and moved user data off third-party cloud storage.