Book Image

Architecting Data-Intensive Applications

By : Anuj Kumar
Book Image

Architecting Data-Intensive Applications

By: Anuj Kumar

Overview of this book

<p>Are you an architect or a developer who looks at your own applications gingerly while browsing through Facebook and applauding it silently for its data-intensive, yet ?uent and efficient, behaviour? This book is your gateway to build smart data-intensive systems by incorporating the core data-intensive architectural principles, patterns, and techniques directly into your application architecture.</p> <p>This book starts by taking you through the primary design challenges involved with architecting data-intensive applications. You will learn how to implement data curation and data dissemination, depending on the volume of your data. You will then implement your application architecture one step at a time. You will get to grips with implementing the correct message delivery protocols and creating a data layer that doesn’t fail when running high traffic. This book will show you how you can divide your application into layers, each of which adheres to the single responsibility principle. By the end of this book, you will learn to streamline your thoughts and make the right choice in terms of technologies and architectural principles based on the problem at hand.</p>
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Samza architecture


Samza[1] is an open source stream/event processing system that was developed at LinkedIn.

You may know LinkedIn as a social network for professionals, but just like with every successful social network, the core and hidden part of such successful organizations is their engineering department, which churns out some next-gen technologies to solve their present-day issues. Samza was born out of one of those needs.

As per LinkedIn Engineering[3] , at the start of 2016, a staggering 1.3 trillion events (pertaining to application and system monitoring, member-behavior tracking, and inter-application communication) were being published every day into Kafka (their primary messaging system in the event processing framework) with peaks of 4.5 million messages/sec per cluster. And this is just part of the overall events that get generated at LinkedIn. LinkedIn uses Samza to process this deluge of events in real time. And LinkedIn is not the only one that uses Apache Samza. Companies...