> coreweave-migration-deep-dive

Migrate ML workloads from AWS/GCP/Azure to CoreWeave GPU cloud. Use when moving inference services from hyperscaler GPU instances, migrating training pipelines, or evaluating CoreWeave vs cloud GPU costs. Trigger with phrases like "migrate to coreweave", "coreweave migration", "move from aws to coreweave", "coreweave vs aws gpu".

fetch
$curl "https://skillshub.wtf/jeremylongshore/claude-code-plugins-plus-skills/coreweave-migration-deep-dive?format=md"
SKILL.mdcoreweave-migration-deep-dive

CoreWeave Migration Deep Dive

Cost Comparison

InstanceAWSCoreWeaveSavings
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:

  1. Node affinity: Use gpu.nvidia.com/class instead of nvidia.com/gpu.product
  2. Storage: Use CoreWeave storage classes (shared-ssd-ord1)
  3. 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

IssueSolution
Different CUDA driversMatch container CUDA to CoreWeave node drivers
Storage migrationUse rclone or rsync to move data to CoreWeave PVC
DNS changesUpdate ingress/load balancer DNS
IAM differencesCoreWeave uses kubeconfig, not IAM roles

Resources

Next Steps

This completes the CoreWeave skill pack. Start with coreweave-install-auth for new deployments.

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first seenMar 23, 2026
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┌ repo

jeremylongshore/claude-code-plugins-plus-skills
by jeremylongshore
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