prose-contracts/gpu-monitor.prose.md

---
kind: responsibility
name: gpu-monitor
description: >
  Comprehensive GPU fleet monitor — polls every subsystem (sidecars, router,
  LiteLLM, Strix Halo, dashboard) every 15s, renders a live HTML dashboard,
  checks alert thresholds, and exposes a JSON API for downstream consumers.
agent: abiba
---

## Maintains

- gpu-fleet-data: { gpus: array, strix: object, router: object, litellm: object, summary: object, alerts: array } — Full fleet snapshot refreshed every 15s
- dashboard: live HTML at `/root/dashboard/gpu-fleet.html`, served on port 9100
- gpu-data-api: JSON at `GET /gpu-data` on port 9100
- health-endpoint: `GET /health` on port 9100 → 200 if cache populated, 503 if warming up

## GPU Fleet Topology

```
┌─────────────────────────────────────────────────────────┐
│  GPU Monitor Server (:9100) — 192.168.68.24              │
│  Polls every 15s, serves dashboard + JSON API            │
└──┬──────────┬──────────┬────────────────────────────────┘
   │          │          │
   ▼          ▼          ▼
┌──────┐ ┌──────┐ ┌────────┐
│.8:8080│ │.110  │ │.116:80 │
│RTX3090│ │:8080 │ │nginx   │
│gemma  │ │RTX5070│ │router  │
└──────┘ │qwen27B│ │LiteLLM │
         └──────┘ │dashboard│
                  └────────┘

Note: JSON sidecar exporters at :8090 were never deployed on any
GPU host. Router falls back to GPU /health direct probe. Monitor
should use router /health/unified as source of truth for GPU status.
Strix Halo :8080 is firewalled to .116 only — monitor on .24 cannot
poll .15:8080 directly; must go through router on .116.
```

### Subsystems Polled

| Subsystem | Endpoint | Frequency | Metrics |
|-----------|----------|-----------|---------|
| GPU Status (all, via router) | `http://192.168.68.116/health/unified` | 15s | models, CB, scores, GPU status (router probes each GPU /health directly) |
| Router (unified) | `http://192.168.68.116/health/unified` | 15s | models, CB, scores, GPU status |
| Router (basic) | `http://192.168.68.116/health` | 15s | basic aliveness |
| LiteLLM | `http://192.168.68.116/litellm/health` | 15s | proxy health, model count |
| Strix Halo | `http://192.168.68.116/health/unified` (router) | 15s | Strix Halo status via router — cannot poll .15:8080 directly (firewalled to .116 only) |
| Dashboard | `http://192.168.68.116/dashboard/` | 15s | harness-dashboard aliveness |

### Alert Delivery

All alerts are sent to `#agent-hub` stream topics:
- `alerts-gpu` — GPU fleet alerts (temp, VRAM, utilization)
- `alerts-pm2` — PM2 process health (restarts, crashes)
- `alerts-infra` — Infrastructure health (LiteLLM, Zulip, containers)

This replaces the previous DM-only delivery. All agents on the mesh can see and respond to alerts.

## Alert Thresholds

| Metric | Warning | Critical |
|--------|---------|----------|
| GPU Temp | >80°C | >90°C |
| VRAM Usage | >90% | >95% |
| GPU Util | >95% | >98% |
| Sidecar Unreachable | — | info (sidecars not deployed — use router /health/unified) |
| Model Down | — | critical (circuit breaker open) |

### JSON API Response Schema (/gpu-data)

```json
{
  "gpus": [{ "name", "gpu_name", "temp_c", "vram_used_mb", "vram_total_mb",
             "gpu_util_pct", "power_w", "power_limit_w", "fan_pct",
             "models", "hostname", "active_requests", "health_score",
             "circuit_open" }],
  "strix": { "status", "cpu_load", "llama_health" },
  "router": { "available_models", "circuit_breaker", "gpus", "scores",
              "status", "redis", "_basic" },
  "litellm": { ... },
  "dashboard": { "reachable": bool },
  "summary": { "fleet_status", "models_available", "models_total",
               "circuit_breakers_open", "gpu_count", "gpu_errors",
               "strix_running", "router_reachable", "litellm_reachable" },
  "alerts": [{ "gpu", "metric", "level", "value", "threshold" }],
  "updated": "ISO8601",
  "monitor_version": "2.0.0"
}
```

## Operations

### list
`curl http://localhost:9100/gpu-data | jq` — Full fleet status

### check-health
`curl http://localhost:9100/health` — Monitor self-check

### view-dashboard
Open `http://localhost:9100/` in browser — Live HTML dashboard

### restart
```bash
pkill -f gpu-monitor-server.py
python3 /root/scripts/gpu-monitor-server.py &
```
Or via PM2: `pm2 restart gpu-monitor`

### check-router
The router health is accessed through nginx on port 80 (NOT port 9000 directly).
`curl http://192.168.68.116/health/unified` — Router unified health via nginx proxy
`curl http://192.168.68.116:9000/health/unified` — ❌ WILL FAIL (port bound to 127.0.0.1 only)

## Configuration Files

| File | Host | Purpose |
|------|------|---------|
| `/root/scripts/gpu-monitor-server.py` | pi (.24) | Monitor server v2.0.0 |
| `/root/dashboard/gpu-fleet.html` | pi (.24) | Live HTML dashboard |
| `/etc/nginx/nginx.conf` | CT 116 | Routes /health/* → router |

## Execution

1. **Poll router** (every 15s): GET .116/health/unified — single source of truth for all GPU status (router probes each GPU /health directly via sidecar fallback)
2. **Poll router** (every 15s): GET .116/health via nginx:80
3. **Poll LiteLLM** (every 15s): GET .116/litellm/health via nginx:80
4. **Poll Strix** (every 15s): via router /health/unified (cannot poll .15:8080 directly — firewalled to .116 only)
5. **Poll dashboard** (every 15s): GET .116/dashboard/
6. **Check alerts**: Compare metrics against thresholds
7. **Compute summary**: Fleet-wide health aggregation
8. **Render dashboard**: Generate HTML at /root/dashboard/gpu-fleet.html
9. **Serve API**: HTTP server on port 9100
10. **Repeat** every 15 seconds