Lorena Mireles Rivero explores how concurrency works on the BEAM and why understanding its limits matters when building scalable systems.

Using real-world examples, she breaks down how schedulers, mailboxes, and latency behave under load, and explains approaches like workload distribution, back pressure, and graceful degradation.

Her main takeaway: the BEAM makes concurrency powerful, but resilient systems come from understanding capacity limits and designing around them.

PlanetErlang offers insights into Erlang programming language, OTP framework, and distributed systems, providing tutorials, articles, and case studies for building fault-tolerant and scalable applications. By exploring PlanetErlang's curated content, developers can learn about Erlang's lightweight processes, message passing semantics, and supervision trees for building highly available and resilient distributed systems. Whether you're developing telecom infrastructure, real-time messaging platforms, or IoT solutions, PlanetErlang offers resources to tackle the challenges of building concurrent and fault-tolerant systems.

Planet Erlang

A webinar talk exploring how concurrency works inside the BEAM virtual machine and Erlang runtime system, with a focus on understanding real capacity limits. Using an e-commerce pricing server as a running example, the talk explains how BEAM schedulers, run queues, process mailboxes, and memory interact to create system saturation. It covers three types of saturation signals (localized bottleneck, system-wide CPU saturation, and memory/queue compounding), how to observe them using tools like Observer and Recon, and strategies to address each — including worker pools, back pressure, caching, and dropping stale requests. The core message: BEAM makes concurrency cheap but not free, and sustainable systems require understanding and respecting capacity limits.

Concurrency, understanding the BEAM limits - Lorena Mireles Rivero | Erlang Solutions Webinar