Jakarta EE Overview

This collection examines Jakarta EE, highlighting its evolution from Java EE, focusing on open governance and cloud-native architecture. It covers key specifications, performance enhancements, and migration strategies, along with deployment practices specifically for cloud environments like Azure. The importance of integrating AI and leveraging microservices within Jakarta EE applications is discussed. Additionally, insights into standards and tools for building efficient enterprise applications underscore the ongoing development within the Jakarta EE ecosystem.

EspressDashboard: ダッシュボードのテクノロジー概要、デプロイメント、インテグレーション、各種機能のホワイトペーパー
Introducing Langchain4J-CDI, a simplified approach to building AI agents the Jakarta EE way!
Bring AI and build AI agents into your Jakarta EE Apps with LangChain4J-CDI
langchain4j-cdi: Infuse your Jakarta and MicroProfile applications with all the AI
Jakarta Tech Talk - Building and hosting an MCP server with Jakarta EE
Jakarta EE 11: What's New and Why You Should Care
AI in Java - MCP in Action, Langchain4J-CDI, SmallRye-LLM, Spring AI
Java and AI with LangChain4j: Jakarta EE gets AI
Java and AI with LangChain4j: Jakarta EE and AI
20250403-trusted-ai-favorite-ide-javaland.pdf
A survey of cloud readiness for Jakarta EE 11
How to get trusted AI in your favorite IDE
How to get trusted AI in your favorite IDE
How to get trusted AI in your favorite IDE
How to get trusted AI in your favorite IDE
Jakarta meets AI (JakartaEE One Livestream presentation)
2024-09-10 Jacksonville JUG Java on Azure with AI
Deliver AI infused app innovation with Open Liberty on AKS
Embracing the Cloud A Java Developer’s Guide to Jakarta EE on The Cloud - A Real-World Example
DevTalks Romania: Prepare for Jakarta EE 11