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Docker for AI services

Docker lets you start repeatable services without installing half the internet on your computer.

When to use Docker

Use it for persistent services: vector databases, n8n, Open WebUI, Postgres, Redis, or tools you want to restart the same way tomorrow. For small Python scripts, uv is usually enough.

Minimum Compose

Terminal
services:
  qdrant:
    image: qdrant/qdrant:latest
    ports:
      - "6333:6333"
    volumes:
      - qdrant_data:/qdrant/storage

volumes:
  qdrant_data:
Terminal
docker compose up -d
docker compose ps
docker compose logs -f qdrant

Common errors

  • Port already used: change the left port, for example 6334:6333.
  • Data disappears: you are missing a persistent volume.
  • Ollama does not connect from Docker: try host.docker.internal on macOS/Windows.
  • Strange Linux permissions: check user, docker group, and mounted paths.

Maintenance rule

Every service you will use more than once should have a docker-compose.yml, a short README, and a verification command.

Complete Aulafy mapSee how this lesson fits without leaving your path.

Complete Aulafy map

How all courses connect

This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.

  1. 1Understand
  2. 2Apply or build
  3. 3Operate with confidence
01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

Build with code

Prepare your environment, work with coding agents, and run models while keeping control of your projects.

This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

You do not need every course: choose the component your system needs and return as it grows.

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