Scaling Real-Time AI: From Infrastructure Breakdown to Production Architecture

Most teams underestimate infrastructure overhead as the primary bottleneck when scaling real-time AI systems, focusing instead on compute optimization. This post reveals how one team's monolithic architecture collapsed under 10M daily WebSocket events and how separating concerns—dedicated WebSocket termination, durable event-streaming with consumer groups, and lightweight orchestration—enabled reliable scaling. The architectural patterns presented here are essential blueprints for any organization building production-grade real-time AI systems.