Book Image

Mastering Elixir

By : André Albuquerque, Daniel Caixinha
Book Image

Mastering Elixir

By: André Albuquerque, Daniel Caixinha

Overview of this book

Running concurrent, fault-tolerant applications that scale is a very demanding responsibility. After learning the abstractions that Elixir gives us, developers are able to build such applications with inconceivable low effort. There is a big gap between playing around with Elixir and running it in production, serving live requests. This book will help you fll this gap by going into detail on several aspects of how Elixir works and showing concrete examples of how to apply the concepts learned to a fully ?edged application. In this book, you will learn how to build a rock-solid application, beginning by using Mix to create a new project. Then you will learn how the use of Erlang's OTP, along with the Elixir abstractions that run on top of it (such as GenServer and GenStage), that allow you to build applications that are easy to parallelize and distribute. You will also master supervisors (and supervision trees), and comprehend how they are the basis for building fault-tolerant applications. Then you will use Phoenix to create a web interface for your application. Upon fnishing implementation, you will learn how to take your application to the cloud, using Kubernetes to automatically deploy, scale, and manage it. Last, but not least, you will keep your peace of mind by learning how to thoroughly test and then monitor your application.
Table of Contents (18 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
5
Demand-Driven Processing
Index

Summary


In this chapter we learned how Elixir elegantly tackles the problem of processing events in stages by analyzing the GenStage and Flow abstractions:

  • We implemented our media upload and download pipelines with GenStage, putting to good use its elegant back-pressure mechanism. To achieve this, we had to implement the needed callbacks on the different modules behind the pipeline stages and start each pipeline supervisor on the application initialization.
  • We then examined Flow, an abstraction based on GenStage that lets you process collections in a lazy and concurrent fashion, while keeping much of the semantics one associates with the Enum and Stream modules.

The advantage of using GenStage is that no step in the media pipeline will ever be overwhelmed with requests coming from upstream. If you want to process large datasets or when the bulk of the processing is CPU- or I/O-bound, that's when Flow shines. In this day and age, where multi-core processors are the norm, having a tool like...