What WebLogic Costs Your AI Roadmap

When teams integrate LLM APIs, embedding services, vector databases, or RAG pipelines, the runtime underneath the application becomes the constraint. Virtual threads, fast container startup, modern observability, and Jakarta EE 10+ form the foundation for productive AI work in Java. WebLogic does not clear that floor.

This session is a structured look at where WebLogic breaks under AI workloads, and what the migration path off it looks like for organizations that already moved their JDK to Azul. You’ll learn:

• The five WebLogic bottlenecks that block AI adoption: Java version lock, no Jakarta EE 9 or beyond, the packaging mismatch with Kubernetes, the observability gap, and the I/O-bound concurrency story.
• Why virtual threads (Java 21) change the unit economics of AI service calls, and why WebLogic 14c does not get them in production.
• The MicroProfile patterns AI architectures rely on: Config, Health, Fault Tolerance, JWT, and OpenAPI, none of which ship in WebLogic.
• The financial frame: how WebLogic renewal cost compounds against AI infrastructure budget, and the case an architect or IT director can take to procurement.The migration path from WebLogic to Azul Payara Server, including the javax.* to jakarta.* namespace work and how it maps to Jakarta EE 10 and 11.
• Customer stories from organizations that moved off legacy application servers, including timelines, performance outcomes, and what the migration cost.