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. Mutable image tags like :latest add another layer of complexity. Two nodes can end up running different code under identical tags, and a node that pulls next week may retrieve an image that was not covered by an earlier security review.
NVIDIA AI Cluster Runtime (AICR), an open source modular component of the NVIDIA DSX AI Factory Platform, now includes a qualified AI bill of materials (AIBOM) component to close that gap. An open source project created by Google, k8s-aibom tracks AI workloads running on Kubernetes. Two stock recipes select k8s-aibom by default: h100-gke-cos-inference and h100-gke-cos-inference-dynamo. Other GKE recipes can opt in during generation with –runtime-inventory enabled. Recipes selecting it can opt out with –runtime-inventory disabled.
AICR turns known-good GPU platform configurations into version-locked recipes and reproducible deployment bundles. Each recipe records the desired configuration for one hardware, cloud, OS, and intent combination: its components, version pins, values, constraints, deployment ordering, and validation expectations. AICR generates reproducible deployment artifacts from fixed recipe, catalog, and bundle inputs. Bundles include checksums; signing is optional through aicr bundle –attest.
Qualification with k8s-aibom is a specific claim, not a rubber stamp. AICR binds the exact upstream source, chart, CRDs, and digest-pinned controller image as one tested set, verifies provenance against Google’s expected build identity, reviews rendered RBAC and security defaults, and exercises installation, upgrade, health, and uninstall on the deployment paths it tested.
Source: NVIDIA Technical Blog — Read the full article on the original site ↗