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Software Architecture Patterns for Serverless Systems

Software Architecture Patterns for Serverless Systems - Second Edition

By : Gilbert
5 (15)
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Software Architecture Patterns for Serverless Systems

Software Architecture Patterns for Serverless Systems

5 (15)
By: Gilbert

Overview of this book

Organizations undergoing digital transformation rely on IT professionals to design systems to keep up with the rate of change while maintaining stability. With this edition, enriched with more real-world examples, you’ll be perfectly equipped to architect the future for unparalleled innovation. This book guides through the architectural patterns that power enterprise-grade software systems while exploring key architectural elements (such as events-driven microservices, and micro frontends) and learning how to implement anti-fragile systems. First, you'll divide up a system and define boundaries so that your teams can work autonomously and accelerate innovation. You'll cover the low-level event and data patterns that support the entire architecture while getting up and running with the different autonomous service design patterns. This edition is tailored with several new topics on security, observability, and multi-regional deployment. It focuses on best practices for security, reliability, testability, observability, and performance. You'll be exploring the methodologies of continuous experimentation, deployment, and delivery before delving into some final thoughts on how to start making progress. By the end of this book, you'll be able to architect your own event-driven, serverless systems that are ready to adapt and change.
Table of Contents (16 chapters)
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Other Books You May Enjoy
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Index

Optimizing testing for continuous deployment

In Chapter 1, Architecting for Innovation, we stated that the purpose of software architecture is to enable change. We want to continuously deliver innovations to our end users and produce business value. To meet this goal, we strive to reduce lead times so that we can increase the rate of feedback from end users and create knowledge about what works and what does not. To this end, we have focused throughout this book on optimizing our architecture for short lead times.

Now, we need to turn our attention toward optimizing our testing processes. Traditional testing assumes that we know what is going to work, and we can gather all the requirements and acceptance criteria upfront. Then, we assert that the software is correct before we deploy and release it to the end user.

However, our traditional testing practices work against our stated goal. They are optimized for large batch sizes, which increases deployment risk. They encourage...

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