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)
Other Books You May Enjoy

Implementing idempotence and order tolerance

In Chapter 4, Trusting Facts and Eventual Consistency, we learned that exactly-once delivery of messages is unrealistic. For example, a client request may time out due to network unreliability and have no choice but to resubmit the request because it cannot be certain that the service successfully processed the request; a stream processor may fail in the middle of a batch and retry the entire batch even though part of the batch was successfully processed; or we may replay events from the event lake to repair a service that may have dropped a subset of those events. To account for the reality of at-least-once delivery, we must design our systems to be idempotent. In other words, no matter how many times we receive and process an event or request, it must only update the system once.

We also learned that delivering messages in order can be problematic. A stream will certainly deliver events in the order that it received them, but it may...