In this chapter, you were introduced to Docker and containers, and learned about the history of containers and how Docker has risen to become one of most popular solutions for testing, building, deploying, and running your container workloads.  You learned about the basic architecture of Docker, which includes the Docker client, Docker Engine, and Docker registry, and we introduced the various types of objects and resources that you will work with when using Docker, which include Docker images, volumes, networks, services, and, of course, Docker containers. 

We also discussed the wide array of options you have to run your Docker applications in AWS, which include the Elastic Container Service, Fargate, Elastic Kubernetes Service, Elastic Beanstalk, and running your own Docker platforms, such as Docker Swarm. 

You then installed Docker in your local environment, which is supported natively on Linux and requires a virtual machine on macOS and Windows platforms.  Docker for Mac and Docker for Windows automatically installs and configures a virtual machine for you, making it easier than ever to get up and running with Docker on these platforms.  You also learned how to integrate the Windows subsystem for Linux with Docker for Windows, which will allow you to support the *nix-based tooling that we will use throughout this book.

Finally, you set up a GitHub account, forked the sample application repository to your account, and cloned the repository to your local environment.  You then learned how to install the sample application dependencies, how to run a local development server,  how to run database migrations to ensure that the application database schema and tables are in place, and how to run unit tests to ensure that the application is functioning as expected.  All of these tasks are important to understand before you can expect to be able to test, build, and publish your applications as Docker images, which will be the focus of the next chapter, where you will create a complete local Docker workflow to automate the process of creating production-ready Docker images for your application.