6 posts found
Many developers believe FastAPI is faster simply because it uses async, but that is only partially true. This guide explains how async actually works inside FastAPI, why it improves concurrency for I/O-bound workloads, when it does not improve performance, and the common mistakes developers make when using async in production APIs.
Database queries are the primary performance bottleneck in many Django applications. In this guide, we build a practical multi-layer caching strategy using Redis. Starting with a baseline Django API, we measure response times, introduce caching step-by-step, and analyze how each caching layer improves performance while addressing cache invalidation, data consistency, and production pitfalls.
Deploying a FastAPI application to a production server is an essential skill for backend engineers. In this guide, we will go step-by-step through the entire process of deploying a FastAPI application on an Ubuntu server, starting from server setup to running the application with a production server and configuring a reverse proxy.
Building a FastAPI application that survives the jump to production is about far more than writing fast endpoints. Folder layout, async database setup, environment configuration, middleware, testing, and Docker all need to work together from day one. This guide walks you through every layer of a production-grade FastAPI project with working code you can copy directly into your own setup.
AI can generate UI in seconds, but real product quality depends on engineers who understand state architecture, data synchronization, performance trade-offs, and reliability under real-world constraints. This post explores why frontend is evolving from component building to systems design and what skills now matter most.
How to connect user-facing failures, performance regressions, and release metadata so frontend issues become diagnosable in minutes.
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