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Finished Reading: Building Evolutionary Architectures
Mar 01, 2018

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Building Evolutionary Architectures is a book written by Neal Ford, Rebecca Parsons and Patrick Kua, it was published by O’Reilly in October 2017, it is a short and concise read. It somehow feels similar to Building Microservices, maybe because both books were written by ThoughtWorks employees.

Building Evolutionary Architectures introduces (not surprisingly because that’s the book’s title!) the concept of building evolvable architectures, which in short describes how to build architectures that have the flexibility to be updated without too much hassle and, more importantly, in an easy way.

It does not enforce any type of architecture nor it tries to preach why some of them are better than others; it is not a step-by-step guide either; instead it focuses on detailing how to measure your architecture to correctly record metrics associated to the -ilities, like adaptibility, flexibility or testability, just to name few (and actually the full list of ilities is way longer than that).

In Building Evolutionary Architectures the authors use a concept I never heard before, which we all have been using professionally for years already, called Fitness Functions which indicates how certain architectural characteristics are measured, think of writing Unitary Tests, measuring Latency or Deployment Process, for example.

Those Fitness Functions are what in the end drive the evolvability of your Architecture, for example, measuring the speed of your existing Deployment Process can indicate how fast or slow you can deliver new code to production.

Building Evolutionary Architectures includes a lot of gems like tips to avoid falling into traps for example: following the “Share Nothing” idea when building microservices, avoiding vendor locking, inappropriate data coupling and the abuse of code reuse; as well as building proper interfaces internally between dependencies and more.

Building Evolutionary Architectures is a recommended book, it is a quick read that should help Software Architects measure [brown/green]field projects and prepare them for the constant and imminent change in the future.

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