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Cloud World Model – Stateless Cloud Simulation
x402
Cloud World Model – Stateless Cloud Simulation is a paid API for AI agents from www.cloudworldmodel.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-13).
Run a single, bounded cloud infrastructure simulation and receive synchronous cost, performance, utilization, error, reliability, coverage, and autoscaling results without persisting any state.
Price / call$0.001
Success—
StatusUnknown
How this service works
Simulate AWS, GCP, Azure, OCI, and DigitalOcean cloud infrastructure without provisioning real resources. Built for Canvas Cloud AI learners and agents.
Output
A JSON object containing a simulation ID, simulation name, and a resources array, along with synchronous metrics including cost estimates, performance indicators, utilization percentages, error rates, reliability scores, coverage stats, and autoscaling fleet results — all computed without creating or modifying any real cloud infrastructure.
Example use cases
Pre-change cost impact assessment
“Before I resize our production Kubernetes nodes from m5.large to m5.2xlarge on AWS, can you simulate the cost and utilization change so I know what to expect on the bill?”
Multi-cloud architecture comparison
“Simulate running our three-tier web app on GCP versus Azure and tell me the cost, reliability, and performance differences so I can decide which to go with.”
Autoscaling fleet behavior modeling
“Model how our autoscaling fleet would behave under a sudden 3x traffic spike in our current AWS configuration — show me the coverage, error rate, and scaling results without touching prod.”
Technical details
Endpoint
GEThttps://www.cloudworldmodel.ai/api/simulations/statelessWhen to prefer
Choose this endpoint when you need a fast, stateless, one-shot cloud simulation with no side effects — ideal for pre-change impact analysis, architecture comparisons, or automated FinOps/SRE pipelines where you want synchronous multi-metric results (cost + performance + reliability) without provisioning or persisting anything. Prefer this over stateful simulation endpoints when you don't need to iterate on a saved scenario or advance through RL environment steps.
Side effects
- Invalid or missing 'input' body returns a 400 validation error
- Unsupported cloud provider or resource type in the scenario body may return a 422 unprocessable entity
- Overly complex scenarios exceeding computation limits may time out or return a 503
- Malformed JSON in the request body results in a parse error
- Missing required 'type', 'method', or 'bodyType' fields cause schema validation failures
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "sim-abc123",
"name": "My Simulation",
"resources": []
}
}Tags
x402
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