#scaling

Fanout-on-write vs fanout-on-read for engineers: why every social feed ends up hybrid, and how the naive design fails at the moment of success.

Enterprises deploying AI at scale face challenges in performance, security, and cost. This...

How to Scale a Python App to Handle 1 Million Requests Scaling Your Python App to...

From a product management or user interface perspective, copy-trading looks deceptively simple. A...

3 services, 1 PostgreSQL, shared Redis, one docker-compose — and the illusion of independence. How to spot a distributed monolith in your own architecture, when it's actually useful, and when it's time for real separation.

Busy Laravel apps often hit Postgres connection limits before they hit real query limits. This post covers when transaction pooling helps, what breaks with session state, and how to migrate without guessing.

How 9 Autonomous Agents Operate a Gym on 2 CPU Cores Without an Orchestrator Tags:...

The Architecture That Won't Break — Why Our System Doesn't Need VC Money to Scale Tags:...

Introduction: The Serendipity of Homelab Evolution My foray into homelabbing began with...

How we replaced BIGSERIAL primary keys with PostgreSQL UUID v7 across eight regional video-metadata

Traditional auto-scaling is a liability when you're dealing with AI agent fleets during global...

Introduction to AI Scaling Secrets As we navigate the ever-evolving landscape of...