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

Locale proof performance


One of the worst situations that can occur when we are working with microservices architecture is to put a code in production and see that the performance is poor. The work to bring the code back to the development environment, knowing that production in the project is compromised and the users are going through a bad experience, when it is something that could have been analyzed on the technical side, is extremely frustrating.

The problem now in production could have been predicted, and even solved in the development environment. To register this type of metric, there are many tools that can prove performance in the local environment.

Obviously, the local behavior will not perfectly reflect the production environment. There are many factors to be considered such as network latency, the machine where it was held for deployment and production, and communication with external tools. However, we can take local metrics to highlight a new algorithm or functionality that...