Book Image

Architecting Cloud Native Applications

By : Kamal Arora, Erik Farr, John Gilbert, Piyum Zonooz
Book Image

Architecting Cloud Native Applications

By: Kamal Arora, Erik Farr, John Gilbert, Piyum Zonooz

Overview of this book

Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems. This Learning Path teaches you everything you need to know for designing industry-grade cloud applications and efficiently migrating your business to the cloud. It begins by exploring the basic patterns that turn your database inside out to achieve massive scalability. You’ll learn how to develop cloud native architectures using microservices and serverless computing as your design principles. Then, you’ll explore ways to continuously deliver production code by implementing continuous observability in production. In the concluding chapters, you’ll learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform, and understand the future trends and expectations of cloud providers. By the end of this Learning Path, you’ll have learned the techniques to adopt cloud native architectures that meet your business requirements. This Learning Path includes content from the following Packt products: • Cloud Native Development Patterns and Best Practices by John Gilbert • Cloud Native Architectures by Erik Farr et al.
Table of Contents (24 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Task branch workflow


When discussing the topic of continuous deployment, it is understandable that you might conjure up the image of every single commit by every developer being automatically deployed to production. It is natural to find this concerning because there are too many human factors involved that can send this awry. There is also the notion that there are no manual gates, but this isn't really true either. What is true is that we want to make small and controlled changes that are automatically deployed to production. This is because it is much easier to reason about the correctness of small changes and it is much easier to diagnose a problem in production when it could only be the result of a small change.

To facilitate these small deployment units, we must decouple deployment from release and treat the two as separate, continuous threads working in tandem. We define a release roadmap that consists of a series of experiments that implement thin slices of functionality in an effort...