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CloudWorldModel Autoscaling Threshold Optimizer
x402
CloudWorldModel Autoscaling Threshold Optimizer is a paid API for AI agents from www.cloudworldmodel.ai, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).
Analyzes traffic forecast and simulation results to recommend optimal autoscaling thresholds for cloud infrastructure.
Price / call$0.005
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
Returns recommended autoscaling threshold values derived from the simulation run — including scale-up and scale-down trigger points calibrated to the provided traffic forecast and RPS patterns.
Example use cases
Example prompt
“Based on my simulation ID 'sim-20240601' and a traffic forecast peaking at 8500 RPS with an average of 2200 RPS across these hourly data points, run 150 simulation steps and tell me what autoscaling thresholds I should configure.”
Technical details
Endpoint
POSThttps://www.cloudworldmodel.ai/api/predictions/optimize-thresholdsWhen to prefer
Use this endpoint when you have an active cloud simulation and traffic forecast data and need data-driven autoscaling threshold recommendations. It is distinct from static rule-based autoscaling configs because it incorporates simulation dynamics and RL-style optimization from CloudWorldModel's hybrid engine, making it especially useful after running traffic spike or node-kill simulations to stress-test threshold candidates.
Side effects
- Invalid simulationId returns 404 or error indicating simulation not found
- Missing required trafficForecast fields (name, dataPoints) returns 400 bad request
- Malformed dataPoints array (missing timestamp or rps) causes validation error
- Payment not included or insufficient USDC triggers 402 Payment Required
- testSteps value out of accepted range may return an error or be clamped to default
- Simulation not yet advanced enough to produce meaningful threshold recommendations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| testSteps | number | Simulation steps to run (default 100) |
| simulationId | string | |
| trafficForecast | object |
Output
Schema · Response
{
"type": "json",
"example": {
"job": {
"id": "job-id",
"type": "optimize_thresholds",
"status": "pending",
"createdAt": "2024-01-01T00:00:00.000Z"
},
"message": "Validation job created and processing started"
}
}Tags
x402
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