KubeCon Europe 2025 and Co-located Events at London
Kubeflow Ecosystem: What’s Next for Cloud Native AI/ML and LLMOps
Abstract:
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.
Advancements in AI/ML Inference Workloads on Kubernetes From WG Serving and Ecosystem Projects
Abstract:
The emergence of Generative AI (GenAI) has introduced new challenges and demands in AI/ML inference, necessitating advanced solutions for efficient serving infrastructures. The Kubernetes Working Group Serving (WG Serving) is dedicated to enhancing serving workload on K8s, especially for hardware-accelerated AI/ML inference. This group prioritizes compute-intensive inference scenarios using specialized accelerators, benefiting various serving workloads such as web services and stateful databases.
This session will dive into recent progress and updates on WG Serving’s initiatives and workstreams. We will spotlight discussions and advancements in each workstream. We are also actively looking for feedback and partnership with model server authors and other practitioners who want to utilize powers of K8s for their serving workloads. Join us to gain insight into our work and learn how to contribute to advancing AI/ML inference on K8s.
Panel: Engaging the Kubeflow Community: Building an Enterprise-Ready AI/ML Platform
Abstract:
Organizations often ask themselves when building a new solution whether to develop everything from scratch or integrate existing tools into an end-to-end solution. Kubeflow’s journey was exactly at this crossroads when it started. Part of CNCF as an incubating project, Kubeflow integrates a series of leading open source tools such as Knative, Istio, KServe amongst other AI/ML tools for both predictive and GenAI/LLM applications.
In this panel we will discuss the trade-offs between building a product based on existing tools vs. a DIY approach. We will delve into the key considerations of adding new enhancements and components, based on the developments in the industry and user adoption. The panel will highlight the challenges of being an official distribution of such a product and customer use cases and the influence they had over the project’s roadmap. We will talk through the trials and tribulations that paid off in a win-win outcome for the Kubeflow community and our users.