01 - Why Your API Crashes Under Load (and how to fix it)- Scaling with RabbitMQ

Описание: Most developers build APIs that work perfectly for 10 users, but completely fail when production traffic hits. If you’ve ever faced Gunicorn worker timeouts, 504 Gateway errors, or OOM (Out of Memory) crashes during heavy data processing, this video is for you.

In this first episode of the Advanced Backend Engineering series, we perform a "System Autopsy" on a common failure point: processing 10-Lakh (1 Million) records synchronously. We explore why your server RAM spikes and how "Occupied Workers" paralyze your platform.

What we cover in this architectural deep-dive:
The Invisible Wall: Why traditional Request-Response patterns fail at scale.

Resource Exhaustion: How heavy tasks (PDF generation, Data Syncs) trigger the Linux OOM Killer.

The RabbitMQ Solution: A minimal look at using Message Brokers as an architectural "Pressure Valve."

Decoupling: How to keep your API responsive (10ms) while background workers handle the heavy lifting.

About the Series:
I’m Krishnadas, a Senior Backend Developer with 12 years of experience and a Node.js Core Contributor. This series isn't about "Hello World" tutorials—it's about building resilient, production-grade systems that scale to millions of users.

#rabbitmq #systemdesign #casestudy , #Howtoscale #backend, #Message #queues #pubsub , #fastapi #scaling, #Node.js #backgroundworkers, #Gunicorn #learnprogramming