Coreweave prod checklist
Production readiness checklist for CoreWeave GPU workloads. Use when launching inference services, preparing GPU training for production, or validating deployment configurations. Trigger with phrases like "coreweave production", "coreweave go-live", "coreweave checklist", "coreweave launch".From its SKILL.md
npx -y skills add ComeOnOliver/skillshub --skill coreweave-prod-checklistAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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CoreWeave Production Checklist
Inference Services
- GPU type and count validated for model size
- Autoscaling configured (KServe or HPA)
- Health and readiness probes set
- Resource requests AND limits specified
- Node affinity targeting correct GPU class
-
minReplicas >= 1for production (no cold starts)
Storage
- Model weights in PVC (not downloaded at startup)
- Checkpoints saved to persistent storage
- Storage class appropriate (SSD for inference, HDD for archival)
Security
- Secrets for model tokens and registry access
- Network policies applied
- Container images from trusted registries
Monitoring
- GPU utilization metrics collected
- Inference latency and throughput tracked
- Alert on pod restarts and OOM events
- Log aggregation configured
Rollback
kubectl rollout undo deployment/my-inference
kubectl rollout status deployment/my-inference
Resources
Next Steps
For upgrades, see coreweave-upgrade-migration.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.