From coreweave-pack
Configures Kubernetes RBAC, role bindings, and GPU quotas for namespace isolation in multi-team CoreWeave setups.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin coreweave-packThis skill is limited to using the following tools:
```yaml
Secures CoreWeave Kubernetes deployments using RBAC, network policies, secrets for GPU workloads, model access, and namespace isolation.
Implements team RBAC and spending controls for Vast.ai GPU cloud using Python policy enforcer, per-team API keys, GPU whitelists, and budget limits.
Configures Kubernetes RBAC to enforce least privilege access on cluster resources. Covers Role/ClusterRole design, RoleBinding setup, service account security, namespace isolation, and audit logging for multi-tenant clusters.
Share bugs, ideas, or general feedback.
# Team namespace with GPU quota
apiVersion: v1
kind: ResourceQuota
metadata:
name: ml-team-gpu-quota
namespace: ml-team
spec:
hard:
requests.nvidia.com/gpu: "8"
limits.nvidia.com/gpu: "8"
persistentvolumeclaims: "10"
requests.storage: 2Ti
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: ml-team-access
namespace: ml-team
subjects:
- kind: Group
name: ml-engineers
apiGroup: rbac.authorization.k8s.io
roleRef:
kind: ClusterRole
name: edit
apiGroup: rbac.authorization.k8s.io
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: ml-team-readonly
namespace: ml-team
subjects:
- kind: Group
name: ml-managers
roleRef:
kind: ClusterRole
name: view
apiGroup: rbac.authorization.k8s.io
For migration strategies, see coreweave-migration-deep-dive.