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

Bottleneck anti-pattern


The aggregator design pattern is very efficient for scalability, as we have seen throughout the chapter. However, this pattern can provide us with an anti-pattern if we aren't very careful with what we're doing. The anti-pattern that we can create is called a bottleneck. Let's understand how this anti-pattern can be created.

Our application that was a part of the News microservice was divided into Public Facing Services and Internal Services. With this design, to access the Internal Services, it is necessary to go through Public Facing Services, and it is here that the problem can occur.

The bottleneck happens whenever engineers misunderstand where the stress point of the application is and where it needs to be scaled. Consider the following scenario—it's the World Series and people want news on this end. Obviously, sports_news_service will receive a larger load access. The natural procedure is to create more instances of sports_news_service. However, even with a greater...