# Cloud World Model – Analyze Bottlenecks

> Cloud World Model – Analyze Bottlenecks is a paid API for AI agents from www.cloudworldmodel.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-14).

Analyzes a running cloud infrastructure simulation to identify performance bottlenecks and provides actionable recommendations without provisioning real resources.

## Facts

- Endpoint: POST https://www.cloudworldmodel.ai/api/simulations/%7BsimulationId%7D/analyze-bottlenecks
- Price: $0.001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/cloud-world-model-analyze-bottlenecks-695bf583
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8j_fOnj-Nyndcful19hJT

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability cloud-world-model-analyze-bottlenecks-695bf583 -d '<json body>'
```

Example prompt: My Cloud World Model simulation (ID: sim_abc123) seems to be struggling — can you analyze it for bottlenecks and tell me what's slowing things down? Use beginner mode so I can understand the results.

## When to prefer this

Choose this endpoint when you have an existing Cloud World Model simulation and need to programmatically identify which infrastructure tier is the performance bottleneck and get a concrete, provider-specific recommendation for improvement — all without incurring real cloud provisioning costs. Prefer this over general cloud cost tools when the goal is latency and throughput diagnosis within a sandboxed simulation, especially useful for learners, pre-production architecture reviews, or AI agents iterating on cloud designs.

## Known failure modes

- simulationId not found or expired — returns 404 with error message
- simulation still initializing — returns 409 conflict or 503
- malformed request body — returns 400 with validation error
- payment not received or insufficient — returns 402 Payment Required
- internal simulation engine error — returns 500

## 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 a JSON object with a natural-language 'analysis' field describing the primary bottleneck (e.g. database connection pool pressure, p95 latency stats, CPU utilization levels) and a provider-specific 'doRecommendation' suggesting a concrete upgrade or configuration change (e.g. switching to a managed database with read replicas on DigitalOcean) along with estimated performance improvements.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "beginnerMode": {
   "type": "boolean",
   "description": "Return simplified bottleneck analysis"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "analysis": "The primary bottleneck is the database tier: connection pool pressure is at 94% and p95 latency has climbed to 340 ms. The compute nodes are healthy at 55% CPU. Migrating to a managed database with read replicas would reduce latency by an estimated 40%.",
  "doRecommendation": "Upgrade to a DigitalOcean Managed Database (db-s-2vcpu-4gb) with one read replica to offload analytics queries and reduce connection pool pressure."
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/cloud-world-model-analyze-bottlenecks-695bf583/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from www.cloudworldmodel.ai](https://www.zero.xyz/host/www.cloudworldmodel.ai/llms.txt)