Docker is one of the most popular open-source platforms that every data engineer should know. It is a modern and lightweight alternative to virtual machines. With Docker, you can deploy your code, run tools in the cloud, and package applications into isolated images, which provides complete control over the environment. In this course, you will master all the basic skills necessary for confidently working with Docker in the data engineering profession.
Introduction to Docker Concepts
To start, we will explore the difference between virtual machines and Docker. You will learn why Docker has become the preferred solution in the modern world of Data Engineering. We will discuss key concepts:
- Images
- Containers
- Registries
- Tags and others
You will install Docker Desktop as the main development environment.
Working with DockerHub
In the second part, you will get acquainted with DockerHub—learn how to find and use ready-made images from developers and companies for production deployment, testing, and local development.
Practical Applications of Docker
Hands-On Experience
In the practical module you will:
- Download and run ready-made images from DockerHub via the command line and Docker Compose
- Develop and run your own image
- Add modules and expand the functionality of the container
- Create your own repository on DockerHub and publish your image there
This way you will fully master how Docker works and how to share your solutions.
Deploying Docker in Production
To help you understand how Docker is applied in real projects, we will look at deploying containers in a cloud environment. You will learn how to run containers using various cloud services and get acquainted with best security practices to protect your containers from external threats.
The course is ideal for beginners and those who want to confidently include Docker in their engineering stack.
