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A Bird's-Eye View of Software Engineering

"Hiring people to write code to sell is not the same as hiring people to design and build durable, usable, dependable software."

- Larry Constantine ^[6]

Through the various stages of my career, I have met several people that knew how to code; people whose skill level ranged from beginner to, what some would refer to as, guru. All those people had different backgrounds and worked for both start-ups and large organizations. For some, coding was seen as a natural progression from their CS studies, while others turned to coding as part of a career change decision.

Regardless of all these differences, all of them had one thing in common: when asked to describe their current role, all of them used the term software engineer. It is quite a common practice for job candidates to use this term in their CVs as the means to set themselves...

Key benefits

Apply best practices to produce lean, testable, and maintainable Go code to avoid accumulating technical debt

Explore Go’s built-in support for concurrency and message passing to build high-performance applications

Scale your Go programs across machines and manage their life cycle using Kubernetes

Description

Over the last few years, Go has become one of the favorite languages for building scalable and distributed systems. Its opinionated design and built-in concurrency features make it easy for engineers to author code that efficiently utilizes all available CPU cores. This Golang book distills industry best practices for writing lean Go code that is easy to test and maintain, and helps you to explore its practical implementation by creating a multi-tier application called Links ‘R’ Us from scratch. You’ll be guided through all the steps involved in designing, implementing, testing, deploying, and scaling an application. Starting with a monolithic architecture, you’ll iteratively transform the project into a service-oriented architecture (SOA) that supports the efficient out-of-core processing of large link graphs. You’ll learn about various cutting-edge and advanced software engineering techniques such as building extensible data processing pipelines, designing APIs using gRPC, and running distributed graph processing algorithms at scale. Finally, you’ll learn how to compile and package your Go services using Docker and automate their deployment to a Kubernetes cluster. By the end of this book, you’ll know how to think like a professional software developer or engineer and write lean and efficient Go code.

What you will learn

Understand different stages of the software development life cycle and the role of a software engineer Create APIs using gRPC and leverage the middleware offered by the gRPC ecosystem Discover various approaches to managing package dependencies for your projects Build an end-to-end project from scratch and explore different strategies for scaling it Develop a graph processing system and extend it to run in a distributed manner Deploy Go services on Kubernetes and monitor their health using Prometheus

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