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Scaling real-time AI agents with session-aware load balancing

Traditional load balancing strategies based on QPS and CPU utilization break down for real-time AI agents that maintain long-lived, stateful streaming sessions. The post explains why active session counts are a critical missing signal, how to implement application-level session tracking (with concurrency-safe counters), and how to combine session counts with CPU/memory utilization into a hybrid load balancing model. It also covers benchmarking pitfalls specific to streaming workloads and performance considerations for high-concurrency session trackers, including sharded counters and LongAdder-style aggregation on the JVM.

    #webdev#authentication#distributed-systems
Aug 03•8m read time•From developers.googleblog.com
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Why QPS is not enoughStreams create application-level loadTracking active sessions inside the runtimeUsing session count as a balancing signalBenchmarking session-aware balancingValidating tracker overheadLoad balancing sessions, not just requests
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