Phoenix Channels PubSub: Memory Overhead vs Broadcast Latency in High-Concurrency Clusters

Scaling State Distribution

Phoenix Channels rely on a pub-sub mechanism to synchronize state across a cluster. While the BEAM handles concurrent TCP connections efficiently via Cowboy, the memory overhead associated with maintaining active process states increases as the number of concurrent subscribers grows.

When scaling to thousands of concurrent users, there is a documented trade-off between the frequency of broadcast updates and the memory pressure exerted on the Erlang VM. If the producer rate exceeds the consumer's ability to process messages, process mailbox overflow can occur, potentially introducing latency spikes that are only visible under heavy concurrent load.

Given these constraints, what is the recommended strategy for balancing broadcast frequency against memory consumption to prevent mailbox saturation? How does the framework behave when the pub-sub distribution exceeds the available heap space for individual channel processes?