Picture this: your application works perfectly on your laptop. Tests pass, features work, everything is smooth. Then you deploy to production, and it breaks. Different OS version, missing library, conflicting dependency. Hours of debugging later, you discover the server has Python 3.9 while you developed on Python 3.11.

This scenario, affectionately known as "it works on my machine," plagued software teams for decades. Docker solved it by letting you package your application along with its entire environment: runtime, libraries, system tools, and configuration.

In system design interviews, Docker comes up constantly. You will discuss it when designing microservices architectures, deployment pipelines, scaling strategies, and development workflows.

This chapter gives you the depth you need to discuss docker confidently in interviews. We will cover container architecture from the Linux kernel features that make it possible, through image optimization strategies, to production deployment patterns.

1. When to Choose Docker