It's a complete package with a wide selection of tools and APIs that are helpful during the developer's and DevOp's daily work. There's a Kinematic, for example, a desktop developer environment for using Docker on Windows and macOS X.
From a Java developer's perspective, there are tools available, which are especially useful in a programmer's daily job, such as the IntelliJ IDEA Docker integration plugin (we will be using this add-on heavily in the coming chapters). Eclipse fans can use the Docker tooling for Eclipse, which is available starting with Eclipse Mars. NetBeans also supports Docker commands. No matter which development environment you pick, these add-ons let you download and build Docker images, create and start containers, and carry out other related tasks straight from your favorite IDE.
Docker is so popular these days, no wonder hundreds of third-party tools have been developed to make Docker even more useful. The most prominent of them is Kubernetes, which we are going to focus on in this book. But apart from Kubernetes, there are many others. They will support you with Docker-related operations, such as continuous integration/continuous delivery, deployment and infrastructure, or optimizing images. Tens of hosting services now support running and managing Docker containers.
As Docker captures more attention, more and more Docker-related tools pop-up almost every month. You can find a very well-crafted list of Docker-related tools and services on the GitHub awesome Docker list, available at https://github.com/veggiemonk/awesome-docker.
But there are not only tools available. Additionally, Docker provides a set of APIs that can be very handy. One of them is the Remote API for the management of the images and containers. Using this API, you will be able to distribute your images to the runtime Docker engine. There's also the Stats API that will expose live resource usage information (such as CPU, memory, network I/O, and block I/O) for your containers. This API endpoint can be used create tools that show how your containers behave; for example, on a production system.
As we now know the idea behind Docker, the differences between virtualization and containerization, and the benefits of using Docker, let's get to the action. We are going to install Docker first.
