Quarkus

In this tutorial, you learn how to create a simple RESTful Java AI application that asks a large language model (LLM) to write a short poem based on a topic provided by the user.

Learn how the Java ecosystem is adapting to the AI era and how IBM and Red Hat are investing to secure its future.

The future of enterprise Java and AI is secure with Quarkus and Jakarta EE. Quarkus provides a cloud-native Java stack with build-time optimization and instant startup. It supports AI-powered applications through LangChain4j. IBM invests in both, driving innovation and ensuring stability. Quarkus allows enterprises to innovate safely, designing AI-driven services that can be deployed in production and supported by Jakarta EE components. This ensures a stable and secure future for enterprise Java and AI.

Discover the challenges of running AI in production at enterprise scale. Java alone is not enough, as AI workloads require a platform designed for scale. Red Hat OpenShift AI provides the operational backbone, extending Kubernetes with capabilities for building, deploying, and managing AI workloads. It ensures governance, observability, and portability, aligning with open standards. This allows Java developers to treat AI workloads with the same discipline as other enterprise services, making AI viable at enterprise scale. IBM and Red Hat are investing in open standards and products to secure the future of enterprise Java and AI.

Learn about using Granite models and watsonx for enterprise AI with Java. Understand the importance of openness, interoperability, and long-term support in AI adoption. Granite models provide an open foundation for AI, while watsonx delivers enterprise governance and lifecycle management. The combination of Quarkus, LangChain4j, Jakarta EE, and Red Hat OpenShift AI provides a complete story for confident AI adoption. This approach aligns AI adoption with the principles that made Java successful, ensuring investments remain valuable over time.

Learn how Quarkus combined with LangChain4j provides a seamless way to build AI-powered applications that start in milliseconds and consume minimal resources.

In this tutorial, we’ll create applications that use the AMQP open messaging protocol which IBM MQ supports with QPid AMQP JMS APIs. We’ll run these applications as standard Java applications, as Quarkus applications, and finally as GraalVM applications.

This quick start guide gets you up and running with Quarkus on macOS, including necessary tools. You will build a basic database application using Quarkus, Java 17, PostgreSQL, and Hibernate ORM Panache.

In this tutorial, learn how to enable AMQP in an IBM MQ container, run a reactive Quarkus application with IBM MQ in developer mode, run a Quarkus demo in JVM mode, and build a native-image version of a Quarkus demo and deploy it in containers running highly optimized Java stacks.

The 12-factor app methodology provides guidelines to help developers design and build cloud-native apps. Explore how to take advantage of each of these factors to create apps, using open source technologies, that thrive in the cloud.