name: coreweave-common-errors description: '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".

' allowed-tools: Read, Bash(kubectl:*), Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

• saas
• gpu-cloud
• kubernetes
• inference
• coreweave compatibility: Designed for Claude Code

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

• CoreWeave Documentation
• GPU Instance Types

Next Steps

For diagnostics, see coreweave-debug-bundle.