Docker Basics: Build, Run, and Manage Containers

Containers changed how I deploy applications. Same environment locally as in production. No "works on my machine" problems. Here's the essential workflow.

Verify Installation

docker --version
Docker version 24.0.5, build ced0996

Write a Dockerfile

A Dockerfile defines how to build your image:

FROM python:3.11-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .

EXPOSE 8000

CMD ["python", "app.py"]

This creates a Python environment, installs dependencies, copies your code, and defines the startup command.

Build the Image

docker build -t my-app .

The -t tags the image with a name. The . is the build context (current directory).

Run a Container

docker run -p 8000:8000 my-app

Maps port 8000 on your host to port 8000 in the container.

Run in background:

docker run -d -p 8000:8000 my-app

The -d flag runs detached.

Managing Containers

List running containers:

docker ps

List all containers (including stopped):

docker ps -a

Stop a container:

docker stop <container_id>

Remove a container:

docker rm <container_id>

View logs:

docker logs <container_id>
docker logs -f <container_id>  # Follow logs

Execute command in running container:

docker exec -it <container_id> bash

Managing Images

List images:

docker images

Remove image:

docker rmi <image_id>

Clean up unused resources:

docker system prune

Environment Variables

Pass environment variables at runtime:

docker run -e DATABASE_URL=postgres://... my-app

Or use an env file:

docker run --env-file .env my-app

Volumes for Persistent Data

Mount a local directory:

docker run -v $(pwd)/data:/app/data my-app

Changes in /app/data persist on your host.

Key Takeaways

Dockerfile defines reproducible build instructions
docker build -t name . creates an image
docker run -p host:container image runs a container with port mapping
Use -d for background execution
docker exec -it container bash gets you a shell
Volumes persist data outside the container lifecycle
docker system prune cleans up unused resources