Still Burning GPUs On Debugging? Scale AI In One Line
summary
Kubeflow SDK offers one unified Python API installable with pip that runs identically as a local subprocess, a containerized backend (Docker/Podman), or on Kubernetes with no YAML changes; code runs locally for debugging and scales to 800 GPUs by changing a single line to the Kubernetes backend. It provides optimizer, model registry and Spark clients, plans pipelines and OpenTelemetry/MLflow integrations, and reports ~140,000 recent downloads as evidence of adoption.
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