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

Tuning continuously

Continuous performance tuning is a natural benefit of the implicit scalability and high observability of serverless solutions because we can safely deploy with reasonable defaults and tune as we learn from the metrics. The resource and work metrics show us how our services actually perform, so we can make informed decisions about optimizing performance and throughput. For example, in Chapter 4, Trusting Facts and Eventual Consistency, we covered various techniques and parameters for optimizing the throughput of our stream processors. We will set these parameters upfront based on educated guesses and reasonable defaults. We can perform load testing to double-check these hypotheses. But it is ultimately the real observability metrics that dictate proper tuning.

Of all the autonomous service patterns, performance is of the utmost importance for BFF services, because they are user-facing, and users have high expectations. The work metrics are the place to start...