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Title: Docker

👀 Overview

The module is designed to teach Machine Learning Engineers how to use Docker and Docker-compose, powerful tools that allow for the creation and deployment of containerized applications in a consistent and reproducible way. Learn how to use Docker to build reproducible environment, optimize Docker image size and build time, and ML models deployment.

🎯 Goals

Learn how to:

  • Build a Docker image
  • Run Docker containers
  • Mount data and code into Docker container
  • Build and run Docker containers with docker-compose
  • Share Docker images with Docker Hub and GitLab Registry
  • Optimize Docker images

⚒️ Tutorial: Docker

Docker is a powerful tool that helps developers package their software and all its dependencies into self-contained units known as Docker containers.


Source: What is Docker

Good reasons to use Docker

  1. Consistent and Reproducible Environments: Docker ensures that your ML models run consistently across different machines and environments.
  2. Easy Dependency Management: Docker simplifies managing the specific versions of software components needed for your ML project.
  3. Scalability and Portability: Docker containers are lightweight and portable, allowing you to easily scale and move your ML applications across different environments.
  4. Simplified Collaboration: Docker enables team members to work with the same environment, facilitating collaboration and accurate reproduction of ML experiments.
  5. Streamlined Deployment with CI/CD: Docker integrates smoothly with CI/CD pipelines, automating testing, building, and deployment of ML applications, and enhancing production deployments.

Key Concepts


Docker is an open platform for developing, shipping, and running applications.

  • Container image (or Docker image) is a standardized unit of software that packages an application with all its dependencies - application code, runtime environment, system tools, libraries, and configurations.
  • A container image becomes a container when we run it (e.g., execute docker run).

Example of a Typical Folder Structure

├── Dockerfile    <- how to create a Docker image
├── Pipfile       <- pipenv
├── Pipfile.lock  <- pipenv
└──        <- the application itself


A text file which contains a sequential set of all the commands or instructions that you want to include in your Docker Image of an application. Helps to:

  • set the host OS (base image)
  • write a list of packages you want to install
  • add dependencies for your application
  • set environmental variables
  • provide the default command which the application will execute when the container will start executing


FROM ubuntu:18.04
COPY . /app
RUN make /app
CMD python /app/

Main Dockerfile statements:

Command Purpose
FROM To specify the parent image.
WORKDIR To set the working directory for any commands that follow.
RUN To install applications and packages required for the container.
COPY To copy files or directories from a specific location.
ADD Similar to COPY, but can handle remote URLs and unpack files.
ENTRYPOINT Command that always executes when the container starts.
CMD Arguments passed to the entrypoint command.
EXPOSE To define the port through which to access the container.

Docker Hub

Docker Hub is a registry of Docker images that contains images uploaded by third-party developers as well as images released by Docker developers. Find configured Docker images for different purposes, or store your own.


Source: Docker Hub

Get Started: workflow

Take 10 minutes to follow the official tutorial: Get Started with Containerize an application


Source: Docker workflow

Here is an explanation of the example "Docker Hello World":

$ docker run hello-world

This command pulls the "hello-world" image from the Docker Hub registry and runs a container based on that image. The container displays a simple message to indicate that the Docker installation is working correctly.

$ docker ps -a

This command lists all containers, including both running and stopped containers. Running this command after executing the previous command will show the "hello-world" container in the list.

$ docker stop hello-world

This command stops the running "hello-world" container by sending a termination signal. The container will transition from a running state to a stopped state.

$ docker start hello-world

This command starts the stopped "hello-world" container. The container will transition from a stopped state to a running state.

The Docker Hello World example is a simple way to verify that your Docker installation is functioning properly. By running the container, you can confirm that Docker is able to pull images, create and manage containers, and execute applications within them.

Key Image Commands

These commands are helpful for managing Docker images and containers during the development and deployment of applications.

Key Container Commands

Container Volumes

Container Volumes provide the ability to connect a folder inside the container to a folder on the host machine.

There are two types of Container Volumes

Container Volumes

Creating a new Named Volume

 docker volume create new-volume

Passing it as an argument in the docker run command

 docker run -v new-volume:/etc/data image-name

🎼 Docker Compose

Docker Compose is a tool that allows you to define and manage multi-container applications using a YAML file. With Docker Compose, you can easily specify the services, networks, and volumes required for your application and launch them with a single command.


Source: Docker Compose

Check out an official tutorial.

🏁 Conclusion

Docker provides a powerful and efficient way to package and deploy applications, enabling consistent environments and facilitating the management of dependencies. It is widely used in the software development and deployment process, particularly in the context of microservices and containerization.

By understanding the principles and techniques covered in this overview, you can leverage Docker to streamline your development workflow, improve scalability, and enhance the portability of your applications.

🎓 Additional Resources

Best practices for Docker

Docker Compose best practices

*Demo projects & tools*

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