Containers are virtualization environments. They include everything that the software needs, namely libraries, dependencies, filesystems, and network interfaces. Unlike classic virtual machines, all the aforementioned elements share the kernel with the machine they are running on. In this way, the impact on the use of the resources of the host node is greatly reduced.

This makes the container a very attractive technology in terms of scalability, performance, and isolation. Containers are not young technology; they had success with the launch of Docker in 2013. Since then, they have completely revolutionized the standards used for application development and management.

Docker is a container platform based on the implementation of Linux Containers (LXC), which extends the functionality of this technology with the ability to manage containers as self-contained images, and adds additional tools for coordinating their life cycle and saving their state.

The idea of containerization is precisely to allow a given application to be executed on any type of system since all its dependencies are already included in the container itself.

In this way, the application becomes highly portable and can be easily tested and deployed on any type of environment, both on-premises and, above all, in the cloud.

Now, let's see how to dockerize a Python application using Docker.