Inside WhatsApp with Roberto Aloi & Michał Muskała

Everyone quotes WhatsApp when the topic of Erlang and scale comes up. Fewer people know what it actually looks like from the inside - what was hard, what was never hard, and what the team spent their time on once the concurrency stopped being the problem.

Roberto Aloi and Michał Muskała work on the team keeping it running. This is the first of two episodes with them.

Topics include:

• what Roberto's first Erlang moment was - implementing a GenServer for a robot at university and learning binary pattern matching felt like cheating

• why Michał came to Erlang backwards, from Elixir, and what the tooling gap actually felt like

• the column numbers OTP bug that caused cascading failures and taught Roberto what no documentation could

• the optimization that made the JSON Unicode parser slower - binary pattern matching was the wrong tool, and a custom state machine was faster

• what "let it crash" actually means at WhatsApp scale: letting it crash is the easy part, recovery is where the engineering lives

• why the 30th employee was the first person at WhatsApp with Erlang experience - and what that means for hiring

• the most misunderstood thing about Erlang at WhatsApp: scaling isn't the exotic part, keeping the codebase healthy is

• how WhatsApp does deployments: 1% of servers first, one region next, monitoring throughout, ready to roll back

• what types of failures become normal at this scale - and why disaster recovery drills are a regular practice

• overly dynamic code as the anti-pattern that creates the most sustained pain

Part two covers ELP, Equalizer, and the tooling that keeps a codebase this large navigable. You want both.

Recorded June 25, 2026.