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Hands-On Software Engineering with Golang
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Hands-On Software Engineering with Golang
By:
Overview of this book
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.
Table of Contents (21 chapters)
Preface
Section 1: Software Engineering and the Software Development Life Cycle
Free Chapter
A Bird's-Eye View of Software Engineering
Section 2: Best Practices for Maintainable and Testable Go Code
Best Practices for Writing Clean and Maintainable Go Code
Dependency Management
The Art of Testing
Section 3: Designing and Building a Multi-Tier System from Scratch
The Links 'R'; Us Project
Building a Persistence Layer
Data-Processing Pipelines
Graph-Based Data Processing
Communicating with the Outside World
Building, Packaging, and Deploying Software
Section 4: Scaling Out to Handle a Growing Number of Users
Splitting Monoliths into Microservices
Building Distributed Graph-Processing Systems
Metrics Collection and Visualization
Epilogue
Assessments
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