Coreweave common errors
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Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. Use when pods are stuck Pending, GPUs are not allocated, or experiencing CUDA and NCCL errors. Trigger with phrases like "coreweave error", "coreweave pod pending", "coreweave gpu not found", "coreweave debug", "fix coreweave".
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SKILL.md
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CoreWeave Common Errors
Error Reference
1. Pod Stuck Pending -- No GPU Available
kubectl describe pod <pod-name> | grep -A5 Events
# "0/N nodes are available: insufficient nvidia.com/gpu"
Fix: Check GPU availability: kubectl get nodes -l gpu.nvidia.com/class=A100_PCIE_80GB. Try a different GPU type or region.
2. CUDA Out of Memory
torch.cuda.OutOfMemoryError: CUDA out of memory
Fix: Reduce batch size, enable gradient checkpointing, or use a larger GPU (A100-80GB instead of 40GB).
3. Image Pull BackOff
Fix: Create an imagePullSecret:
kubectl create secret docker-registry regcred \
--docker-server=ghcr.io \
--docker-username=$GH_USER \
--docker-password=$GH_TOKEN
4. NCCL Timeout (Multi-GPU)
NCCL error: unhandled system error
Fix: Ensure all GPUs are on the same node (NVLink). For multi-node, use InfiniBand-connected nodes.
5. PVC Not Mounting
Fix: Check storage class availability: kubectl get sc. Use CoreWeave storage classes like shared-hdd-ord1 or shared-ssd-ord1.
6. Node Affinity Mismatch
Fix: List valid GPU class labels:
kubectl get nodes -o json | jq -r '.items[].metadata.labels["gpu.nvidia.com/class"]' | sort -u
7. Service Not Reachable
Fix: Check Service and Endpoints:
kubectl get svc,endpoints <service-name>
Resources
Next Steps
For diagnostics, see coreweave-debug-bundle.