Analytics SaaS
Project Atlas
A real-time analytics dashboard for B2B customers, processing 40 million events a day without slowing down.
- Built with
- React, Node.js, Redis, WebSockets
- Outcome
- Reports that took 8 seconds now load in under 100ms.
The problem
A B2B analytics platform shared by many client companies kept timing out during working hours. Its database ran at 100% CPU on unindexed time-based reports, and a 30-day dashboard took more than 8 seconds to load.
What I did
I built an ingestion pipeline with Node.js, Redis Streams, and PostgreSQL materialized views, so heavy reports are prepared ahead of time. Dashboards get live updates over WebSockets instead of asking the server again and again. Tuned connection pools, automatic query timeouts, and circuit breakers keep one slow query from taking the rest down.
The result
Queries went from 8,200ms to under 100ms across more than 40 million events a day. Server costs fell 54% because the database stopped triggering extra machines, and churn tied to slowness fell to zero.
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