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

Collecting resource metrics

So far, we have seen that serverless and our autonomous service patterns provide us with a lot of fine-grained metrics without the need for explicit instrumentation. Now we need to turn all this data into actionable information so that we can fail forward fast.Back in 2015, when I first found myself in the role of operation manager, I went looking for guidance so that I could put together a mental model for reasoning about all this data. One of the best sources I found was a series of posts by Alexis Lê-Quôc, Datadog's CTO and co-founder, called Monitoring 101 (https://www.datadoghq.com/blog/monitoring-101-collecting-data).In this series he recommends grouping observability data into three main categories: work metrics, resource metrics, and system events. In this section we will dig in resource metrics and cover the USE method and how it applies to serverless and our autonomous service patterns. Specifically, we will look at capacity and concurrency...