Description
Containerization, particularly with tools like Docker, has become a cornerstone in deploying applications efficiently. Building a Docker image for Python applications is generally uncomplicated, yet optimizing these images requires extra work. Notably, many of these optimizations are uniquely tailored to Python.
This talk focuses on techniques and best practices to build more efficient Docker images for Python in order to generate reproducible and quicker builds while reducing the image sizes at the same time.