Load balancing: 4 real scaling case studies

4 of the 73 engineering write-ups in our database are tagged with the technique "load balancing". They come from 4 companies (Dropbox, Meta, OpenAI and Zalando) and were published in 2026 (1 undated). Stack that shows up most often in these stories: Envoy (2). Often combined with load shedding (2). 3 of the 4 state concrete scale numbers, for example "30 million+ WhatsApp messages/sec" (Meta). Each card below links to our short summary and the original post.

Meta · 2026

2026 World Cup: Breaking Records, Spiky Charts and Reliability at Scale

How Meta absorbed the 2026 World Cup, when WhatsApp set a record of more than 30 million messages per second during the final. Pre-provisioned capacity buffers were the most effective lever, alongside country-level shedding of non-critical load, load-testing and resizing 100+ services, forecasting each region's peak separately, and no deploy freeze.

30 million+ WhatsApp messages/sec8.4 billion messages in 5 minutescapacity planningload testingload sheddingTaijiKatranProxygen
OpenAI · 2026

Rapidly scaling online storage to serve over 1 billion ChatGPT users

OpenAI's Habitat storage platform grew from a Python client library over Cosmos DB into a central service handling 70M+ requests per second. The team ran many low-concurrency Python processes to keep asyncio delay down, switched aiohttp connection reuse from LIFO to FIFO to stop a metastable failure, used Envoy for connection fan-in, kept a deliberately simple NoSQL API, then rewrote the service in Rust.

70 million+ requests/sec1 billion+ weekly usersconnection poolingload balancingrate limitingPythonRustCosmos DB
Zalando · 2026

Client-Side Load Balancing at a Million Requests Per Second

Zalando moved the internal fan-out of its Product Read API off the shared Skipper ingress into an in-process JVM load balancer that rebuilds the same xxHash64 consistent-hash ring. They added N-ring fade-in so new pods warm only the products they will keep, bounded load based on occupancy (Little's Law) weighted by latency, and a capped ring walk. Pods ran more evenly, the autoscaler target rose from 50% to 65% CPU, and the fleet shrank by over 25%.

1 million+ requests/sec moved off shared ingressup to 100 downstream calls per batchload balancingconsistent hashingcachingJavaKubernetesSkipper
Dropbox · n.d.

How we migrated Dropbox from Nginx to Envoy

Dropbox moved its edge traffic proxy from Nginx to Envoy for better observability and extensibility.

proxy migrationload balancingEnvoyNginx

Get new load balancing scaling stories weekly

One email a week. No spam.

Subscribe

Companies in these stories

Browse all 87 topics →