Day 37: Containerization with Docker
Building Production-Ready AI Quiz Platform Components
What We’re Building Today
Today we’re containerizing our AI Quiz Platform services - think of it as creating portable, self-contained packages for each component. We’ll Docker-ize our Python backend API, React frontend, Redis cache, and PostgreSQL database.
Learning Agenda:
Container fundamentals and why they matter in production
Creating Dockerfiles for multi-service applications
Building optimized images for AI/ML workloads
Container networking and volume management
Why Containerization Matters in AI Engineering
Remember when you tried running your friend’s code and spent hours fixing “works on my machine” issues? Containers solve this by packaging your application with its exact runtime environment.
In production AI systems handling millions of requests, containers provide:
Consistent deployments across development, staging, and production
Resource isolation preventing one service from crashing others
Horizontal scaling by spinning up identical container instances
Rollback capabilities when new versions break
