Book Image

Software Architecture Patterns for Serverless Systems - Second Edition

By : John Gilbert
Book Image

Software Architecture Patterns for Serverless Systems - Second Edition

By: John 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)
14
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15
Index

Employing the Saga pattern

In Chapter 4, Trusting Facts and Eventual Consistency, we addressed the reality that modern distributed systems no longer rely on distributed transactions because they do not scale well and because of the heterogeneity of the many technologies involved. Instead, we create resilient, eventually consistent systems by breaking long-lived transactions down into a sequence of atomic actions. The outcome of each action is emitted as an event that is recorded as a fact. Downstream services react and the cycle repeats until the system reaches a consistent state in near-real time.However, we do need to account for scenarios when something goes wrong downstream and the long-lived transaction is not able to move forward to a consistent state. In these cases, we need to undo the sequence of actions performed up to the point of failure so that the system is returned to a consistent state. This pattern is referred to as a Saga and was first discussed by Hector Garcia-Molina...