Book Image

Practical Cloud-Native Java Development with MicroProfile

By : Emily Jiang, Andrew McCright, John Alcorn, David Chan, Alasdair Nottingham
Book Image

Practical Cloud-Native Java Development with MicroProfile

By: Emily Jiang, Andrew McCright, John Alcorn, David Chan, Alasdair Nottingham

Overview of this book

In this cloud-native era, most applications are deployed in a cloud environment that is public, private, or a combination of both. To ensure that your application performs well in the cloud, you need to build an application that is cloud native. MicroProfile is one of the most popular frameworks for building cloud-native applications, and fits well with Kubernetes. As an open standard technology, MicroProfile helps improve application portability across all of MicroProfile's implementations. Practical Cloud-Native Java Development with MicroProfile is a comprehensive guide that helps you explore the advanced features and use cases of a variety of Jakarta and MicroProfile specifications. You'll start by learning how to develop a real-world stock trader application, and then move on to enhancing the application and adding day-2 operation considerations. You'll gradually advance to packaging and deploying the application. The book demonstrates the complete process of development through to deployment and concludes by showing you how to monitor the application's performance in the cloud. By the end of this book, you will master MicroProfile's latest features and be able to build fast and efficient cloud-native applications.
Table of Contents (18 chapters)
1
Section 1: Cloud-Native Applications
5
Section 2: MicroProfile 4.1 Deep Dive
10
Section 3: End-to-End Project Using MicroProfile
13
Section 4: MicroProfile Standalone Specifications and the Future

Summary

In this chapter, we've learned about GraphQL and how it addresses some of the gaps in REST. We've also learned how to create and consume GraphQL services using MP GraphQL, without the overhead of maintaining a schema in addition to Java code. We've learned that we can build queries and mutations by applying annotations to our API classes and that we can enrich them by adding descriptions, parameters, formatting, and more. By outsourcing, we've learned that we can avoid executing expensive operations when they are not necessary. We've also learned how to send partial results when exceptions occur. We've learned that there are some useful tools such as GraphiQL that can simplify testing. And while the client APIs aren't fully supported from the specification, we've been able to view two different clients, and we've seen how we could use them for integration testing or to consume GraphQL services.

With what we've learned in...