Deep dives into backend engineering, system design, AI, and developer tooling — written for practitioners, optimized for search.
A deep dive into token bucket algorithms, sliding window counters, and production-ready rate limiting in Spring Boot.
Why traditional databases fall short for semantic search and how vector embeddings change the game.
A practical, no-fluff migration checklist with code examples for upgrading from Spring Boot 2.x.
Frameworks and patterns for writing technical documentation that developers actually want to read.
Patterns for reliable async communication between services using message queues.
SEO strategies specifically for developer content — from keyword research to technical on-page optimization.
No Redis. No django-ratelimit. Just a sliding window, a dictionary, and 40 lines of code.
A corrupted log file, thousands of lines of noise, and one bug that breaks everything — a missing newline you'd never think to check.
A backend engineer's mental model of Django — how it actually works, why it's still relevant in 2026, and what makes it different from a library.
What REST actually is, how it works step-by-step, and the design principles that make APIs maintainable at scale.
What actually happens when you run a Java program — from compilation through class loading, linking, and garbage collection.