KubeCon + CloudNativeCon Europe 2025

Over the years, Kubeflow has become one of the most widely adopted ML platforms on Kubernetes, managing the entire AI/ML lifecycle, from pipeline orchestration and data processing to distributed training, tuning, and inference. The challenges in the MLOps domain evolved over time with newer ML models and advancements in infrastructure capabilities. With the recent GenAI wave, users want to train and deploy custom LLMs on public clouds or on-premises infrastructure. Unlike traditional ML models, LLMs are massive, requiring significant data processing and computing resources for training and inference. The Kubeflow community has been working hard to provide first-class citizen support to generative models and their core abstractions, focusing more on LLMOps. In this talk, the speakers will discuss the requirements for the next-generation ML platform, its current shortcomings, the roadmap to solving these challenges and how you or your organization can contribute to Kubeflow’s success.