~/talk

Kubeflow Ecosystem: What’s Next for Cloud Native AI/ML and LLMOps

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Kubeflow announces the 1.0 release and stitches concrete LLMOps pieces: a donated Spark Operator now in the ecosystem with a benchmark of 60,000 Spark apps across 36,000 pods, a new Kubeflow Trainer B2 (supports PyTorch, DeepSpeed, MLX, TensorFlow; Hugging Face coming), model registry UI and model caching via PV/PVC, KServe + Envoy AI gateway for multi‑RM routing, and a demo fine‑tuning Gemma‑3‑1B with GRPO (Unsloth) via KFP that completes training and shows improving rewards.

AI-written summary · about

  1. 0:00Introduction and panel
  2. 1:44Kubeflow ecosystem overview
  3. 3:40Kubeflow notebooks update
  4. 4:13Spark operator improvements
  5. 5:40Hyperparameter tuning with Katib
  6. 6:51Distributed training with Trainer
  7. 10:51Distributed data caching
  8. 11:52SDK and developer experience
  9. 14:29Model registry and management
  10. 15:53Model serving with KServe
  11. 17:46End-to-end LLMOps demo
  12. 27:20Roadmap and community call
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