As teams deploy and scale AI workloads using NVIDIA Dynamo, Kubeflow, or Slurm, tracking what actually runs requires visibility beyond the platform... As teams deploy and scale AI workloads using NVIDIA Dynamo, Kubeflow, or Slurm, tracking what actually runs requires visibility beyond the platform configuration captured in a recipe. Application teams define and update these workloads independently of the platform recipe, so a reproducible deployment bundle alone cannot establish which workload artifacts are running on each node.
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