Modernizing legacy applications for the cloud native world is full of challenges, from technical to strategic. This panel doesn't just list the problems such as technical debt, migration risk, skill gaps, cost constraints, and infrastructure misalignment; we jump straight to the solutions. Panelists will share practical strategies for phased migration, emphasizing how these efforts pave the way for Kubernetes adoption. Our discussion will focus on critical questions like:
* How do you assess whether AI-enabled tools are right for preparing workloads for K8s vs manual refactoring?
* When leveraging AI for refactoring, what validation or human oversight processes are needed?
*How do we design a Cloud Native AI reference architecture that runs modernized apps and AI workloads on Kubernetes, and accelerates innovation and time-to-market for new AI capabilities?
Attendees will leave with a practical roadmap to adopt AI modernization tools that balance innovation with safety and oversight.