Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

by Martin Kleppmann

In this chapter, we have explored some fundamental ways of thinking about data-intensive applications. These principles will guide us through the rest of the book, where we dive into deep technical detail. An application has to meet various requirements in order to be useful. There are functional requirements (what it should do, such as allowing data to be stored, retrieved, searched, and processed in various ways), and some nonfunctional requirements (general properties like security, reliability, compliance, scalability, compatibility, and maintainability). In this chapter we discussed reliability, scalability, and maintainability in detail. Reliability means making systems work correctly, even when faults occur. Faults can be in hardware (typically random and uncorrelated), software (bugs are typically systematic and hard to deal with), and humans (who inevitably make mistakes from time to time). Fault-tolerance techniques can hide certain types of faults from the end user. Scalability means having strategies for keeping performance good, even when load increases. In order to discuss scalability, we first need ways of describing load and performance quantitatively. We briefly looked at Twitter’s home timelines as an example of describing load, and response time percentiles as a way of measuring performance. In a scalable system, you can add processing capacity in order to remain reliable under high load. Maintainability has many facets, but in essence it’s about making ...