8 essays
Another late night debugging a thrashing service? This is a debrief on why thread pools exist, when they actually save your ass in production, and the ugly truths you'll learn when you inevitably get them wrong.
After another night battling a production incident fueled by Java's 'enterprise-grade' complexity, it's time to admit: Java isn't dead, it's the undead zombie in our server rooms, a costly and exhausting relic.
Another 3 AM call, another 'why is this broken?' moment. Let's talk about RabbitMQ and Kafka not from some clean architecture diagram, but from the trenches where message queues and event streams either save your ass or become the reason you're looking for a new job.
Remember that Tuesday at 2 AM? The one where a minor tenant's custom webhook brought down notification delivery for everyone? Yeah. We ended up deep in the trenches, comparing Go and Node.js for a critical RabbitMQ-backed service.
Another 3 AM production incident survived. Time to talk about why we make our systems so damn complicated, and why sometimes, the most elegant solution is the one that just gets straight to the point.
AI coding assistants generate correct-looking code but often fail in production debugging. Learn why runtime profiling, system constraints, and execution paths matter more than generated solutions.
An API endpoint went from 500ms to 900ms after AI-suggested “optimizations,” until removing ORM abstraction and switching to raw SQL reduced it to 43ms, revealing how performance depends more on system understanding than generated fixes.
Localhost is a comfortable, consequence-free fantasy. Production is where software goes to find out what it actually is. A 3am field report from someone who has been profiling things nobody asked them to profile.