coreweave-migration-deep-dive
'Migrate ML workloads from AWS/GCP/Azure to CoreWeave GPU cloud.
Allowed Tools
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Provided by Plugin
coreweave-pack
Claude Code skill pack for CoreWeave (24 skills)
Installation
This skill is included in the coreweave-pack plugin:
/plugin install coreweave-pack@claude-code-plugins-plusClick to copy
Instructions
CoreWeave Migration Deep Dive
Cost Comparison
| Instance | AWS | CoreWeave | Savings |
|---|---|---|---|
| 1x A100 80GB | ~$3.60/hr (p4d) | ~$2.21/hr | ~39% |
| 8x A100 80GB | ~$32/hr (p4d.24xl) | ~$17.70/hr | ~45% |
| 1x H100 80GB | ~$6.50/hr (p5) | ~$4.76/hr | ~27% |
Migration Steps
Phase 1: Containerize
# If running on bare EC2/GCE, containerize first
docker build -t inference-server:v1 .
docker push ghcr.io/myorg/inference-server:v1
Phase 2: Adapt YAML for CoreWeave
Key changes from AWS EKS / GKE:
- Node affinity: Use
gpu.nvidia.com/classinstead ofnvidia.com/gpu.product - Storage: Use CoreWeave storage classes (
shared-ssd-ord1) - Networking: CoreWeave provides flat networking within VPC
Phase 3: Parallel Deploy
Run both old and new infrastructure simultaneously, gradually shift traffic.
Phase 4: Cut Over
Decommission old GPU instances after validation period.
Common Gotchas
| Issue | Solution |
|---|---|
| Different CUDA drivers | Match container CUDA to CoreWeave node drivers |
| Storage migration | Use rclone or rsync to move data to CoreWeave PVC |
| DNS changes | Update ingress/load balancer DNS |
| IAM differences | CoreWeave uses kubeconfig, not IAM roles |
Resources
Next Steps
This completes the CoreWeave skill pack. Start with coreweave-install-auth for new deployments.