Most IoT tutorials assume a flat, predictable stream of sensor data: 1,000 devices sending 1 payload per minute . In the real world, weather telemetry behaves nothing like that.

During calm weather, thousands of remote monitoring stations report once every 60 seconds . The moment a storm front or rapid barometric pressure drop hits (

Δ P > 3 hPa / 3 h \Delta P > 3\text{ hPa} / 3\text{h} ), scientists and automated control loops command those stations to switch to 1-second high-resolution sampling . Overnight, your ingestion pipeline faces an immediate 60x traffic explosion —right when losing data is least acceptable.

In this post, I’ll walk through how we designed and built the Cloud-Native Weather Telemetry Monitoring System —a 100% open-source microservices platform built with Node.js, TypeScript, NestJS, gRPC, RabbitMQ, TimescaleDB, and Redis —and the engineering trade-offs we made to guarantee scalability, availability, and chaos resilience.

1. The Core Requirements vs.…