Scaling Real-Time AI Agents with Session-Aware Load Balancing

Google’s developer blog argues that real-time AI agents do not fit conventional request-response load balancing because long-lived, stateful bidirectional streams hide each backend’s committed workload. It recommends tracking active sessions inside the application runtime and exposing those counts to the routing layer. A hybrid policy can then combine session concurrency with standard signals such as CPU utilization, distributing new conversations away from already committed backends and reducing localized bottlenecks. The supplied source summary does not specify benchmarks, implementation code, or measured production improvements.