Stateful Conversations at Database Scale: The Session Store Architecture Every Production Chat Feature Needs
Most engineers shipping chat features discover their session architecture is wrong in production, not in design review. The demo ran fine: you tested with five messages, the conversation history fit in memory, and the LLM responded coherently. Then you launched, and somewhere between the first thousand concurrent sessions and the first deployment rollout, users started experiencing forgotten context, partial responses, or conversations that reset without warning. The in-memory pattern that makes chat features trivial to prototype is precisely what makes them fragile to operate.
This is not a subtle architectural mistake. Conversation state is fundamentally different from request state. Request state lives for milliseconds; conversation state must survive pod restarts, horizontal scaling, deployment cycles, and mobile network interruptions — for minutes, hours, or days. Building on the wrong abstraction creates reliability debt that compounds as conversation length grows and user load increases.
