Modernizing Enterprise Java Applications: Jakarta EE, Spring Boot, and AI Integration (Rerun)

Due to high popularity and limited seats available on the previous live broadcast, we are re-running this webinar!

We will explore practical strategies for enhancing enterprise Java applications with generative AI capabilities across Jakarta EE (Java EE) and Spring Boot platforms. Through hands-on demonstrations and real-world case studies, we’ll examine framework-specific approaches for AI integration, including Spring AI for Boot applications and REST client patterns for Jakarta EE systems.

Attendees will learn:

• Building AI-powered features using Spring Boot’s native AI tooling
• Implementing LLM integration patterns in Jakarta EE applications
• Managing asynchronous AI processing and response caching
• Handling security considerations when connecting to AI services
• Designing maintainable architectures that combine AI with enterprise patterns

Whether you’re maintaining legacy Jakarta EE systems or developing new Spring Boot applications, you’ll gain actionable insights for incorporating AI capabilities while preserving enterprise-grade reliability. Join us for live coding, architecture deep-dives, and interactive discussions with experienced enterprise architects who have successfully deployed AI features in production Java systems.

Key Takeaways

1. Framework-Specific AI Integration Techniques:

Learn how to build AI-powered features using Spring Boot’s native AI tooling and implement LLM integration patterns for Jakarta EE systems, leveraging REST client patterns for seamless AI service communication.

2. Advanced Architectural and Operational Insights:

Understand strategies for managing asynchronous AI processing, response caching, and handling security considerations when integrating AI into enterprise Java applications, ensuring maintainable and scalable systems.

3. Practical Implementation and Real-World Applications:

Benefit from live coding demonstrations, architecture deep-dives, and real-world case studies showcasing successful AI feature deployments in production environments for both legacy Jakarta EE systems and new Spring Boot applications.