coreweave-reference-architecture
Reference architecture for CoreWeave GPU cloud deployments. Use when designing ML infrastructure, planning multi-model serving, or establishing CoreWeave deployment standards. Trigger with phrases like "coreweave architecture", "coreweave design", "coreweave infrastructure", "coreweave best practices".
Best use case
coreweave-reference-architecture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Reference architecture for CoreWeave GPU cloud deployments. Use when designing ML infrastructure, planning multi-model serving, or establishing CoreWeave deployment standards. Trigger with phrases like "coreweave architecture", "coreweave design", "coreweave infrastructure", "coreweave best practices".
Teams using coreweave-reference-architecture 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-reference-architecture/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How coreweave-reference-architecture Compares
| Feature / Agent | coreweave-reference-architecture | 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?
Reference architecture for CoreWeave GPU cloud deployments. Use when designing ML infrastructure, planning multi-model serving, or establishing CoreWeave deployment standards. Trigger with phrases like "coreweave architecture", "coreweave design", "coreweave infrastructure", "coreweave best practices".
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 Reference Architecture
## Architecture Diagram
```
┌─────────────────────┐
│ Load Balancer │
│ (Ingress/LB) │
└──────────┬──────────┘
│
┌────────────────┼────────────────┐
│ │ │
┌────────▼──────┐ ┌──────▼────────┐ ┌─────▼───────┐
│ Model A │ │ Model B │ │ Model C │
│ (vLLM, A100) │ │ (TGI, H100) │ │ (SD, L40) │
│ 2 replicas │ │ 1 replica │ │ 3 replicas │
└───────────────┘ └───────────────┘ └─────────────┘
│ │ │
┌────────▼────────────────▼────────────────▼───────┐
│ Shared Storage (PVC) │
│ Models / Checkpoints / Data │
└──────────────────────────────────────────────────┘
```
## Project Structure
```
ml-platform/
├── k8s/
│ ├── base/ # Shared templates
│ ├── models/
│ │ ├── llama-8b/ # Per-model manifests
│ │ ├── llama-70b/
│ │ └── stable-diffusion/
│ └── infra/
│ ├── storage.yaml # PVCs
│ ├── secrets.yaml # Model tokens
│ └── monitoring.yaml # Prometheus rules
├── containers/
│ ├── vllm/Dockerfile
│ └── custom-server/Dockerfile
├── scripts/
│ ├── deploy.sh
│ └── benchmark.sh
└── monitoring/
├── grafana-dashboards/
└── alert-rules.yaml
```
## Key Design Decisions
| Decision | Choice | Rationale |
|----------|--------|-----------|
| Serving framework | vLLM | Continuous batching, PagedAttention |
| GPU type (production) | A100 80GB | Best price/performance for inference |
| Storage | Shared PVC (SSD) | Fast model loading across replicas |
| Autoscaling | KServe + Knative | Native scale-to-zero support |
| Container registry | GHCR | GitHub integration, free for public |
## Resources
- [CoreWeave Documentation](https://docs.coreweave.com)
- [CoreWeave Examples](https://github.com/coreweave/kubernetes-cloud)
## Next Steps
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