What is Docker Containers?
Docker containers package your application and all its dependencies into a single portable unit that runs identically on any machine. They eliminate the classic 'works on my machine' problem.
In plain English
A Docker container is like a shipping container on a cargo ship. The container holds everything needed — no matter what ship or port it lands at, the contents arrive exactly as packed. The port doesn't need to know what's inside; it just needs to handle standard containers.
How it works
You write a Dockerfile that describes how to build your app image: base OS, dependencies, code, and start command. Docker builds this into an immutable image that you can run as a container anywhere Docker is installed. Container registries like Docker Hub or GHCR store and distribute these images.
Why it matters for AI-built apps
AI-generated apps often have implicit environment dependencies — a specific Node version, a system library, an environment variable — that aren't documented anywhere. Containers make those dependencies explicit and reproducible. Every deploy uses the exact same image, eliminating environment drift between development, staging, and production.
Best practices
Use small base images (Alpine or Distroless variants) to reduce attack surface and image size. Never store secrets in the image — pass them as environment variables at runtime. Use multi-stage builds to keep build tools out of the final production image.
Frequently asked questions
Do I need Docker to deploy my app?
Not necessarily — platforms like Vercel and Railway handle containerization for you. But understanding Docker helps when you need more control or are moving to Kubernetes.
What's the difference between a Docker image and a container?
An image is the static blueprint — like a class in code. A container is a running instance of that image — like an object instantiated from that class.
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