# ByteLyst Single-VM Deployment

> Deploy the **entire ByteLyst ecosystem** on a single Azure VM from scratch.
> Two files: this README and `setup.sh`. Copy both to the VM and run the script.

---

## Prerequisites

- **Azure VM:** Ubuntu 24.04 LTS (or 22.04), Standard_D8s_v5 (8 vCPU, 32 GB RAM) recommended
- **Disk:** 100 GB+ (Docker images, Cosmos emulator, build artifacts)
- **Network:** NSG allowing inbound on ports 80, 3000-3100, 4003-4019, 8025, 8080, 8081
- **GitHub access:** Repos must be accessible (public or deploy key configured)

## Quick Start

```bash
# 1. SSH into your Azure VM
ssh azureuser@<vm-ip>

# 2. Copy setup.sh and make executable
chmod +x setup.sh

# 3. Run — provide your GitHub username (repos are cloned via HTTPS)
#    If repos are private, also export GITHUB_TOKEN first.
sudo ./setup.sh

# 4. Wait ~15-25 minutes for full build + deploy

# 5. Verify
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml ps
```

## What the Script Does

| Phase | Duration | Description |
|-------|----------|-------------|
| 1. System | ~2 min | Install Docker, Node.js 22, pnpm 10.6.5, git |
| 2. Gitea | ~1 min | Start Gitea Docker container (npm registry on :3300) |
| 3. Clone | ~3 min | Clone all 11 repos to `/opt/bytelyst/` |
| 4. Build | ~5 min | Build all `@bytelyst/*` packages in common-plat |
| 5. Publish | ~3 min | Publish all packages to local Gitea npm registry |
| 6. Env | instant | Generate `.env.ecosystem` with all required values |
| 7. Deploy | ~10 min | `docker compose up --build` for 27 services |
| 8. Verify | ~1 min | Health-check all services |

## Port Map (after deployment)

### Infrastructure
| Service | Port | URL |
|---------|------|-----|
| Gitea (npm registry) | 3300 | `http://<vm-ip>:3300` |
| Cosmos Data Explorer | 1234 | `http://<vm-ip>:1234` |
| Azurite (Blob) | 10000 | — |
| Mailpit UI | 8025 | `http://<vm-ip>:8025` |
| Grafana | 3000 | `http://<vm-ip>:3000` |
| Traefik Dashboard | 8080 | `http://<vm-ip>:8080` |

### Platform Services
| Service | Port | URL |
|---------|------|-----|
| platform-service | 4003 | `http://<vm-ip>:4003/health` |
| extraction-service | 4005 | `http://<vm-ip>:4005/health` |
| mcp-server | 4007 | `http://<vm-ip>:4007/health` |

### Platform Dashboards
| Dashboard | Port | URL |
|-----------|------|-----|
| Admin Console | 3001 | `http://<vm-ip>:3001` |
| Issue Tracker | 3003 | `http://<vm-ip>:3003` |

### Product Backends
| Product | Port | Health |
|---------|------|--------|
| PeakPulse | 4010 | `http://<vm-ip>:4010/health` |
| ChronoMind | 4011 | `http://<vm-ip>:4011/health` |
| JarvisJr | 4012 | `http://<vm-ip>:4012/health` |
| NomGap | 4013 | `http://<vm-ip>:4013/health` |
| MindLyst | 4014 | `http://<vm-ip>:4014/health` |
| LysnrAI | 4015 | `http://<vm-ip>:4015/health` |
| NoteLett | 4016 | `http://<vm-ip>:4016/health` |
| FlowMonk | 4017 | `http://<vm-ip>:4017/health` |
| ActionTrail | 4018 | `http://<vm-ip>:4018/health` |
| LocalMemGPT | 4019 | `http://<vm-ip>:4019/health` |

### Product Web Apps
| Product | Port | URL |
|---------|------|-----|
| LysnrAI Dashboard | 3002 | `http://<vm-ip>:3002` |
| ChronoMind | 3030 | `http://<vm-ip>:3030` |
| JarvisJr | 3035 | `http://<vm-ip>:3035` |
| FlowMonk | 3040 | `http://<vm-ip>:3040` |
| NoteLett | 3045 | `http://<vm-ip>:3045` |
| MindLyst | 3050 | `http://<vm-ip>:3050` |
| NomGap | 3055 | `http://<vm-ip>:3055` |
| ActionTrail | 3060 | `http://<vm-ip>:3060` |
| LocalMemGPT | 3070 | `http://<vm-ip>:3070` |

## Post-Deployment Commands

```bash
# Check all service health
/opt/bytelyst/check-health.sh

# View logs for a specific service
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml \
  logs -f platform-service

# Restart a specific service
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml \
  restart flowmonk-backend

# Stop everything
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml down

# Stop and wipe all data
docker compose -f /opt/bytelyst/learning_ai_common_plat/docker-compose.ecosystem.yml down -v
```

## Troubleshooting

- **Cosmos emulator slow:** It needs 20-30s on first boot. Services wait via health checks.
- **Out of memory:** Use at least 32 GB RAM. The Cosmos emulator alone needs ~4 GB.
- **Build failures:** Check that Gitea is running (`docker ps | grep gitea`) and packages published (`curl http://localhost:3300/api/packages/bytelyst/npm/`).
- **Port conflicts:** Ensure nothing else runs on the listed ports before deploying.