Why it matters

Kubeflow is comprehensive K8s ML. Understanding shapes platform choice.

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The architecture

Pipelines: DAG orchestration.

Notebooks: Jupyter on K8s.

Training Operators: PyTorch, TFJob.

KServe: serving.

Kubeflow ecosystemPipelinesDAG workflowsTraining OperatorsPyTorch, TFJobKServemodel servingComprehensive but heavy; some teams pick pieces vs whole
Kubeflow.
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How it works end to end

Pipelines: Argo-based DAGs.

Training Operators: distributed training.

KServe: model serving with scale-to-zero.

Notebooks: Jupyter.