Top Spring Boot courses in 2026 help Java developers learn backend skills, microservices, cloud basics, and real project building, with simple lessons, strong concepts, and career-ready knowledge for ...

Frameworks like Spring Boot remain dominant in backend and microservices development thanks to mature ecosystems and extensive support. Cloud-native Java frameworks such as Quarkus and Micronaut focus ...

REpresentational State Transfer (REST) [1] is widely used to expose Application Programming Interfaces (APls) of web services and facilitates the development of loosely coupled systems. Each web ...

Abstract: The service consists of hosting an AWS-based web page application utilizing EC2 instance services. The backend development is done in Java and set up on port 3001 as proprietary REST API ...

The rise of artificial intelligence in recent years has been a non-stop gala for programmers, and one programming language—Python—has been the undeniable belle of the ball. Java and other languages ...

In today's data-driven world, real-time data processing is crucial for building responsive and scalable applications. Apache Kafka, a distributed streaming platform, has become the go-to solution for ...

Building web services and documenting RESTful endpoints is no easy task, but testing RESTful APIs has always been a particularly sore point with Spring Boot and Java. Sure, you can test a GET ...

This crash course on how to build a RESTful API with Spring Boot teaches everything you need to know to immediately develop enterprise-grade microservices in Java. In just 90 minutes you'll learn how ...

NB! Please note that the Web eID Spring Boot example code was moved to web-eid-authtoken-validation-java repository. We won't be accepting pull requests or responding to issues in this repository ...

In this article we're going to compare some essential metrics of the web applications using two different Java stacks: Spring Boot and Eclipse Microprofile. And since there are several implementations ...

Java users can integrate ML into their Spring applications with Spring Boot Starter for Deep Java Library. Apply these frameworks to integrate ML capabilities into microservices for deep learning.