awesome-scalability

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An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users.

#### If your system goes slow
> Understand your problems: scalability problem (fast for a single user but slow under heavy load) or performance problem (slow for a single user) by reviewing some [design principles](#principle) and checking how [scalability](#scalability) and [performance](#performance) problems are solved at tech companies. The section of [intelligence](#intelligence) are created for those who work with data and machine learning at big (data) and deep (learning) scale.

#### If your system goes down
> "Even if you lose all one day, you can build all over again if you retain your calm!" - Thuan Pham, former CTO of Uber. So, keep calm and mind the [availability](#availability) and [stability](#stability) matters! 

#### If you are having a system design interview
> Look at some [interview notes](#interview) and [real-world architectures with completed diagrams](#architecture) to get a comprehensive view before designing your system on whiteboard. You can check some [talks](#talk) of engineers from tech giants to know how they build, scale, and optimize their systems. Good luck!

#### If you are building your dream team
> The goal of scaling team is not growing team size but increasing team output and value. You can find out how tech companies reach that goal in various aspects: hiring, management, organization, culture, and communication in the [organization](#organization) section.

#### Community power

> Contributions are greatly welcome! You may want to take a look at the [contribution guidelines](CONTRIBUTING.md). If you see a link here that is no longer maintained or is not a good fit, please submit a pull request!

> Many long hours of hard work have gone into this project. If you find it helpful, please share on Facebook, [on Twitter](https://ctt.ec/V8B2p), [on Weibo](http://t.cn/RnjFLCB), or on your chat groups! Knowledge is power, knowledge shared is power multiplied. Thank you!

## Content
- [Principle](#principle)
- [Scalability](#scalability)
- [Availability](#availability)
- [Stability](#stability)
- [Performance](#performance)
- [Intelligence](#intelligence)
- [Architecture](#architecture)
- [Interview](#interview)
- [Organization](#organization)
- [Talk](#talk)
- [Book](#book)

## Principle
* [Lessons from Giant-Scale Services - Eric Brewer, UC Berkeley & Google](https://people.eecs.berkeley.edu/~brewer/papers/GiantScale-IEEE.pdf)
* [Designs, Lessons and Advice from Building Large Distributed Systems - Jeff Dean, Google](https://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf)
* [How to Design a Good API & Why it Matters - Joshua Bloch, C