Production-ready containerized stack for backtesting and live trading quantitative strategies.
Remote (You) --> [VPN:10.8.0.1] --> Internet --> Firewall:Port 1194
|
Docker Host:192.168.1.1
|
.---------------'--------------.
| Docker Bridge |
| 172.18.0.0/16 |
'------------------------------'
|
.------------------------------------------------------.
| [Jupyter:8888] <--> [Prometheus:9090] --> [Grafana:3000] |
| | | ^ |
| v v | |
| [MLflow:5000] <--> [Redis:6379] [Loki:3100] |
| | | |
| v v |
| [MinIO:9000] <--> [TimescaleDB:5432] |
'------------------------------------------------------'
- **JupyterLab**: Strategy development (port 8888)
- **TimescaleDB**: Market data storage (port 5432)
- **MLflow**: Model tracking (port 5000)
- **MinIO**: Artifact storage (port 9000)
- **Redis**: Signal cache (port 6379)
- **Prometheus + Grafana + Loki**: Observability (ports 9090, 3000, 3100)
## Quick Start
```bash
# 1. Clone
git clone https://github.com/raynayam/quant-devops-stack
cd algorithmic-trading-platform
# 2. Configure
cp .env.example .env
# Edit .env with your credentials
# 3. Start
docker-compose up -d