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)
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Designing for failure

Sooner or later, our stream processors will run into trouble. A target system may go down, poison events may start arriving, or someone may make an honest human error. It will happen, and we must be prepared. We will cover monitoring and alerting in Chapter 12, Optimizing Observability. In the meantime, we need to prepare for the worst and design our stream processors to be resilient and self-healing.

We will cover idempotence and order tolerance in Chapter 5, Turning the Cloud into the Database. In the next section, we will look at backpressure, rate limiting, and poison events. And when we do get into trouble, we will emit fault events.

Backpressure and rate limiting

Backpressure is an important characteristic of stream processing. A stream processor should not overload its target resource. In the best case, the target will throw throttling errors, and we will have low throughput, as the stream processor wastes time and resources. In the worst case...