Book Image

Mastering RabbitMQ

By : Yusuf Aytas, Emrah Ayanoglu, Dotan Nahum
Book Image

Mastering RabbitMQ

By: Yusuf Aytas, Emrah Ayanoglu, Dotan Nahum

Overview of this book

RabbitMQ is one of the most powerful Open Source message broker software, which is widely used in tech companies such as Mozilla, VMware, Google, AT&T, and so on. RabbitMQ gives you lots of fantastic and easy-to-manage functionalities to control and manage the messaging facility with lots of community support. As scalability is one of our major modern problems, messaging with RabbitMQ is the main part of the solution to this problem This book explains and demonstrates the RabbitMQ server in a detailed way. It provides you with lots of real-world examples and advanced solutions to tackle the scalability issues. You’ll begin your journey with the installation and configuration of the RabbitMQ server, while also being given specific details pertaining to the subject. Next, you’ll study the major problems that our server faces, including scalability and high availability, and try to get the solutions for both of these issues by using the RabbitMQ mechanisms. Following on from this, you’ll get to design and develop your own plugins using the Erlang language and RabbitMQ’s internal API. This knowledge will help you to start with the management and monitoring of the messages, tools, and applications. You’ll also gain an understanding of the security and integrity of the messaging facilities that RabbitMQ provides. In the last few chapters, you will build and keep track of your clients (senders and receivers) using Java, Python, and C#.
Table of Contents (18 chapters)
Mastering RabbitMQ
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Case study


For this study, we'll choose the world of Real Time Analytics. You will learn about the challenges in real-time data, and how they can be solved with scalability in mind. But first, let's talk about analytics, Small data, Medium data, and Big data.

Small data

Small data is when you have enough data to process, but fits into a single machine. Any processing and analysis you want to run can finish in a reasonable amount of time. Of course term "reasonable" may refer to different amount of time depending on your business needs.

For example, if we want to generate a daily report, it is reasonable to assume that we're still okay with it taking around 30 minutes to complete. This is because we will still have 47 other tries to make it happen (we have 48 half hours within a 24 hour day).

However, it is unreasonable to agree to a job or series of interdependent jobs that take more than, or very close to, 24 hours. In this case, you will seek to scale out of your single machine or workstation...