coreweave-upgrade-migration
Upgrade CoreWeave deployments and migrate between GPU types. Use when migrating from A100 to H100, upgrading CUDA versions, or updating inference server versions. Trigger with phrases like "upgrade coreweave", "coreweave gpu migration", "coreweave cuda upgrade", "migrate coreweave".
Best use case
coreweave-upgrade-migration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Upgrade CoreWeave deployments and migrate between GPU types. Use when migrating from A100 to H100, upgrading CUDA versions, or updating inference server versions. Trigger with phrases like "upgrade coreweave", "coreweave gpu migration", "coreweave cuda upgrade", "migrate coreweave".
Teams using coreweave-upgrade-migration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/coreweave-upgrade-migration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How coreweave-upgrade-migration Compares
| Feature / Agent | coreweave-upgrade-migration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Upgrade CoreWeave deployments and migrate between GPU types. Use when migrating from A100 to H100, upgrading CUDA versions, or updating inference server versions. Trigger with phrases like "upgrade coreweave", "coreweave gpu migration", "coreweave cuda upgrade", "migrate coreweave".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# CoreWeave Upgrade & Migration
## GPU Type Migration
```yaml
# Before: A100
affinity:
nodeAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
nodeSelectorTerms:
- matchExpressions:
- key: gpu.nvidia.com/class
operator: In
values: ["A100_PCIE_80GB"]
# After: H100 (update affinity label)
values: ["H100_SXM5"]
```
### Migration Steps
1. Build new container with updated CUDA version if needed
2. Deploy with new GPU affinity alongside old deployment
3. Shift traffic gradually (canary)
4. Validate latency and throughput match or improve
5. Scale down old deployment
### CUDA Version Matrix
| GPU Type | Recommended CUDA | Driver |
|----------|-----------------|--------|
| A100 | CUDA 12.2+ | 535+ |
| H100 | CUDA 12.4+ | 550+ |
| L40 | CUDA 12.2+ | 535+ |
### Rollback
```bash
kubectl rollout undo deployment/my-inference
```
## Resources
- [CoreWeave GPU Instances](https://docs.coreweave.com/docs/platform/instances/gpu-instances)
## Next Steps
For CI/CD, see `coreweave-ci-integration`.Related Skills
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