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nvidia-gpu-operator-kubernetes-hardening

Esta skill revisa implantações do NVIDIA GPU Operator no Kubernetes, incluindo plugin de dispositivo, gerenciador MIG, rótulos NFD, configuração de GPU fatiada no tempo, toolkit de contêiner, securityContext, tenancy de namespace e política de admissão. Ela é acionada quando usuários perguntam sobre o compartilhamento seguro de GPUs, perfis MIG aplicados ou implantação adequada do GPU Operator.

19estrelas
Atualizado há 4 meses

Ver no GitHub ↗ Licença: Apache-2.0

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NVIDIA GPU Operator on Kubernetes Hardening

Purpose

Review NVIDIA GPU Operator deployments on Kubernetes against NVIDIA documentation and Kubernetes pod-security hardening: device plugin posture, MIG manager configuration, time-sliced GPU configuration, NFD label usage, container toolkit isolation, securityContext posture for GPU workloads, and admission policy enforcement of GPU resource requests.

Lean operating rules

  • Prefer live evidence (kubectl -n gpu-operator get pods, kubectl get clusterpolicy, kubectl get nodes -L nvidia.com/gpu.product, MIG profile annotations) when the active client exposes it; otherwise fall back to NVIDIA GPU Operator documentation and sanitized manifests.
  • Separate confirmed facts from inference. If MIG strategy, time-slicing config, or admission posture was not directly queried, say so.
  • Treat GPU workload pods running with privileged: true outside of the GPU Operator's own DaemonSets as a critical finding — privilege creep across tenant workloads.
  • Treat MIG-capable nodes running in single strategy on multi-tenant clusters when mixed is required as a high finding — partition diversity is impossible.
  • Treat time-sliced GPU configuration shared across tenants without namespace-scoped admission as a high finding — noisy-neighbor and side-channel risk.
  • Treat absence of an admission policy (Kyverno / OPA / ValidatingAdmissionPolicy) gating nvidia.com/gpu requests by namespace as a high finding for multi-tenant clusters.
  • Treat default GPU Operator deployment with public, unsigned image pulls as a medium finding — add image-verification policy.
  • Treat node-feature-discovery labels absent on GPU nodes as a low finding — scheduling reliability is reduced.

Response minimum

Return, at minimum:

  • the scoped target (cluster, GPU Operator version, MIG strategy) and evidence level,
  • device plugin and toolkit posture,
  • MIG / time-slicing posture,
  • admission policy posture for GPU resources,
  • namespace tenancy posture,
  • image verification posture,
  • safe next actions and assumptions or blockers.
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