Kubeflow Virtual Planning Symposium 2025
2025-07-09
-- online --
who it's for
Kubeflow contributors, mlops engineers, machine learning engineers, platform engineers, data scientists, site reliability engineers, bioinformatics engineers
topics
local_exec SDK-driven training; Kubeflow Trainer local mode; cross-namespace PVC sharing; VS Code notebook images proxy; self-hosted GitHub runners autoscaling; Spark Operator on Kubeflow Pipelines; MinIO/S3 driver log archival; Helm templatized executable ConfigMap; PyTorchJob and MP frameworks; Karpenter accelerator autoscaling; KServe with VLM inference; Kubeflow LLM Trainer fine-tuning API
| title | author | length |
|---|---|---|
| Bringing Kubeflow Training Local: SDK-Driven “Local-exec”... | Saad Zaher, Anna Kramar, Eoin Fennessy | 16m |
Kubeflow Trainer adds a local_exec mode that runs training jobs on a laptop (containerized via Docker/Podman or as local subprocesses) while keeping the same… | ||
| Kubeflow for enabling AI Powered Drug Discovery and development... | Shrinidhi Venkataraman, Nithin R | 27m |
Azimuth runs Kubeflow for end-to-end ML with concrete practices: cross-namespace PVC sharing implemented via Trident annotations and a volume reference, custom… | ||
| Spark Operator - Feature Engineering with Spark on Kubeflow | Vikas Saxena | 33m |
Shows a reproducible setup that runs Apache Spark via the Spark Operator on Kubeflow Pipelines, submits spark-application YAMLs with kubectl, and returns… | ||
| Simplifying Generative AI Model Training on Kubernetes using Helm Charts | Ajay Vohra, Omri Shiv | 28m |
Claims a Helm-based stack that standardizes training by putting code and configs into an executable ConfigMap templatized via Helm and driving PyTorchJob/MP… | ||
| Opening Remarks | Chase Christensen | 04m |
Virtual kickoff records over 400+ registrations and is being recorded for the CNCF YouTube channel, with participants from Ireland, Sri Lanka, United States… | ||
| Inferencing LLMs in production with Kubernetes and KubeFlow | Chamod Shehanka Perera, Suresh Peiris | 20m |
A production pipeline uses Kubernetes on GKE with Kubeflow pipelines, KServe as the serverless model layer, KEDA for event-driven scaling and a VLM layer to… | ||
| Streamline LLM Fine-Tuning on Kubernetes with Kubeflow LLM Trainer | Shao Wang | 21m |
Kubeflow LLM Trainer v2 claims to let data scientists fine-tune LLMs on Kubernetes with a simple Python API (about ten lines of code or even one-line… | ||
| Closing Remarks | Valentina Rodriguez Sosa | 05m |
Closing remarks summarize actionable resources: Kubeflow maintains a web page (QR code linked) with concrete generative AI use cases and an hour-long YouTube… | ||
| nothing matches | ||