Docker · Lesson 8 of 8
Recap & Next Steps
Where to go from here.
You went from "it works on my machine" to running a complete multi-container stack with one command. Here is everything you learned, and where to go next.
What you can do now
Run containerspull images, map ports, read logs, exec inside
Build imageswrite Dockerfiles that build fast and stay small
Keep datavolumes for databases, bind mounts for development
Connect servicesnetworks with DNS by name
Run stacksdocker compose for the whole app
Docker cheat sheet
| Task | Command |
|---|---|
| Run a container | docker run -d --name NAME -p HOST:CONTAINER IMAGE |
| List containers | docker ps -a |
| Build an image | docker build -t NAME . |
| Shell inside | docker exec -it NAME sh |
| Logs | docker logs -f NAME |
| Volume | docker run -v VOLUME:/path IMAGE |
| Whole stack | docker compose up -d |
| Clean up | docker system prune |
Where to go next
- FastAPIbuild a real API and ship it in Docker
- Kubernetesrun containers at scale
- MLOpspackage and deploy machine learning models
All three are free full courses on AI Hints, each with a complete video on YouTube.
Summary
Key takeaways
- Containers package apps with their environment
- Dockerfiles, volumes, networks and Compose cover most needs
- Next: Kubernetes for running containers at scale