Book Image

Microservice Patterns and Best Practices

By : Vinicius Feitosa Pacheco
Book Image

Microservice Patterns and Best Practices

By: Vinicius Feitosa Pacheco

Overview of this book

Microservices are a hot trend in the development world right now. Many enterprises have adopted this approach to achieve agility and the continuous delivery of applications to gain a competitive advantage. This book will take you through different design patterns at different stages of the microservice application development along with their best practices. Microservice Patterns and Best Practices starts with the learning of microservices key concepts and showing how to make the right choices while designing microservices. You will then move onto internal microservices application patterns, such as caching strategy, asynchronism, CQRS and event sourcing, circuit breaker, and bulkheads. As you progress, you'll learn the design patterns of microservices. The book will guide you on where to use the perfect design pattern at the application development stage and how to break monolithic application into microservices. You will also be taken through the best practices and patterns involved while testing, securing, and deploying your microservice application. At the end of the book, you will easily be able to create interoperable microservices, which are testable and prepared for optimum performance.
Table of Contents (20 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Separating containers


It is very important to understand how failures happen in order to know how to prevent them. Let's start thinking about common practices in monolithic applications that are routinely taken for microservices architecture. This example will help us understand how to react before the failure.

A common approach is to place the entire structure of an application in a single repository. What I mean is that software code, database, cache, and all the other features of the application, will be on the same machine. I've lost count of the number of times I have come across this scenario.

The following image shows that the cache, database, API, and Business Logic layer are in the same place. At first glance, there's nothing wrong with that. With everything in the same machine, problems such as latency, packet loss, and complexity to deploy are minified:

Now, imagine the scenario where the container begins to fail. It is very difficult to clearly identify which component is responsible...