Designing a scalable real-time conversational platform
Case Study · Real-time · WebSocket · Scaling
I led engineering on a real-time messaging product that required low-latency updates, multi-tenant isolation, and predictable scaling. The project combined event-driven architecture with pragmatic operational controls to deliver a reliable product under load.
Problem
The existing system used polling and suffered from high database load and inconsistent message delivery at scale. Customers experienced delays and out-of-order events during busy periods.
Solution
We introduced WebSockets backed by a lightweight broker and a message queue for durability. Each tenant received scoped channels and rate limits. We separated read-heavy workflows into eventual-consistency reads with cache priming and used worker queues for heavy processing tasks.
Work done
The work included schema changes to support sharding, adding Redis channels for pub/sub, deploying horizontally-scaled websocket nodes, and creating graceful reconnect logic to handle transient failures. Monitoring and synthetic tests were added to detect message lag and backpressure.
Impact
- Message delivery success rate improved to 99.9%.
- Operational costs were predictable and scaled linearly with clients.
- Customer satisfaction improved due to reliable real-time updates.