Book Image

Microservices Development Cookbook

By : Paul Osman
Book Image

Microservices Development Cookbook

By: Paul Osman

Overview of this book

Microservices have become a popular choice for building distributed systems that power modern web and mobile apps. They enable you to deploy apps as a suite of independently deployable, modular, and scalable services. With over 70 practical, self-contained tutorials, the book examines common pain points during development and best practices for creating distributed microservices. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so you can copy the code and configuration files and modify them for your own needs. You’ll start by understanding microservice architecture. Next, you'll learn to transition from a traditional monolithic app to a suite of small services that interact to ensure your client apps are running seamlessly. The book will then guide you through the patterns you can use to organize services, so you can optimize request handling and processing. In addition this, you’ll understand how to handle service-to-service interactions. As you progress, you’ll get up to speed with securing microservices and adding monitoring to debug problems. Finally, you’ll cover fault-tolerance and reliability patterns that help you use microservices to isolate failures in your apps. By the end of this book, you’ll have the skills you need to work with a team to break a large, monolithic codebase into independently deployable and scalable microservices.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
Packt Upsell

Rate limiting

In addition to techniques such as circuit breaking, rate limiting can be an effective way to prevent cascading failures in a distributed system. Rate limiting can be effective at preventing spam, protecting against Denial of Service (DoS) attacks, and protecting parts of a system from becoming overloaded by too many simultaneous requests. Typically implemented as either a global or per-client limit, rate limiting is usually part of a proxy or load balancer. In this recipe, we'll use NGINX, a popular open source load balancer, web server, and reverse proxy.

Most rate-limiting implementations use the leaky-bucket algorithm—an algorithm that originated in computer network switches and telecommunications networks. As the name suggests, the leaky-bucket algorithm is based on the metaphor of a bucket with a small leak in it that controls a constant rate. Water is poured into the bucket in bursts, but the leak guarantees that water exists in the bucket at a steady, fixed rate. If the...