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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
#### 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
#### 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
#### 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. There are some selected [books](#book) for you (most of them are free)! Good luck!
#### If you are building your dream team
#### 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
#### 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 If you see a link here that is no longer maintained or is not a good fit, please submit a pull request!