This is the companion repo to: Complete Docker Course - From BEGINNER to PRO! (Learn Containers)
Thank you to Shipyard for sponsoring this course! It is because of their support that I am able to provide it to the community free of charge!
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Examines the evolution of virtualization technologies from bare metal, virtual machines, and containers and the tradeoffs between them.
Explores the three core Linux features that enable containers to function (cgroups, namespaces, and union filesystems), as well as the architecture of the Docker components.
Covers the steps to install and configure Docker Desktop on your system.
Before we build our own container images, we can familiarize ourselves with the technology by using publicly available container images. This section covers the nuances of data persistence with containers and then highlights some key use cases for using public container images.
Learning about containerization is interesting, but without a practical example it isn't very useful. In this section we create a 3 tier web application with a React front end client, two apis (node.js + golang), and a database. The application is as simple as possible while still providing a realistic microservice system to containerize.
Demonstrates how to write Dockerfiles and build container images for the components of the example web app. Starting with a naive implementation, we then iterate towards a production ready container image.
Explains what container registries are and how to use them to share and distribute container images.
Using the containerized web application from sections 05 and 06, we craft the necessary commands to run our application with Docker and Docker Compose. We also cover the variety of runtime configuration options and when to use them.
Highlights best practices for container image and container runtime security.
Describes how to use Docker to interact with containers, container images, volumes, and networks.
Establishes tooling and configuration to enable improved developer experience when working with containers.
Demonstrates deploying container applications to production using three different approaches: railway.app, a single node Docker Swarm, and a Kubernetes cluster.
