Understanding Distributed Systems
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Understanding Distributed Systems

What every developer should know about large distributed applications

About the Book

Learning to build distributed systems is hard, especially if they are large scale. It's not that there is a lack of information out there. You can find academic papers, engineering blogs, and even books on the subject. The problem is that the available information is spread out all over the place, and if you were to put it on a spectrum from theory to practice, you would find a lot of material at the two ends, but not much in the middle.

That is why I decided to write a book to teach the fundamentals of distributed systems so that you don’t have to spend countless hours scratching your head to understand how everything fits together. This is the guide I wished existed when I first started out, and it's based on my experience building large distributed systems that scale to millions of requests per second and billions of devices.

If you develop the back-end of web or mobile applications (or would like to!), this book is for you. When building distributed systems, you need to be familiar with the network stack, data consistency models, scalability and reliability patterns, and much more. Although you can build applications without knowing any of that, you will end up spending hours debugging and re-designing their architecture, learning lessons that you could have acquired in a much faster and less painful way.

More information available at https://understandingdistributed.systems/

About the Author

Roberto Vitillo
Roberto Vitillo

I have over 10 years of experience in the tech industry as a software engineer, tech lead, and manager.

In 2017 I joined Microsoft to work on an internal SaaS data platform. Since then, I have helped launch two public SaaS products, Product Insights and Playfab. The data pipeline I am responsible for is one of the largest in the world. It processes millions of events per second from billions of devices worldwide.

Before that, I worked for Mozilla, where I wore different hats, from performance engineer to data platform engineer. What I am most proud of is having set the direction of the data platform from its very early days and built a large part of it, including the team.

After getting my master's degree in computer science, I worked on scientific computing applications at the Berkeley Lab. The software I have contributed to is used to this day by the ATLAS experiment at the Large Hadron Collider.

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