A Quant Strategy Needs More Than Just Code: Building Your Complete Monitoring & Alerting Stack Running a quant strategy requires far more than the strategy itself—you need a full suite of tools to execute it reliably, monitor its state, and get alerted when things go wrong. This post shares my complete tooling setup, from strategy execution through alerts.
Overall Architecture Strategy Layer (Python) ↓ Trading Orders Binance API ↓ Execution Results State Files / CF KV ↓ Metrics Prometheus + node_exporter ↓ Storage Grafana Visualization ↓ Alert Rules Alertmanager → Telegram Strategy Execution Layer Tech Stack Language: Python 3.11 Binance SDK: python-binance Scheduled Tasks: APScheduler or system cron Dependency Management: requirements.txt + venv Directory Structure quant/ ├── strategy/ │ ├── main.py # Core strategy logic (signal generation + order placement) │ ├── signals.py # Indicator calculations (technical indicator library) │ └── risk.py # Position sizing, stop-loss logic ├── exchange/ │ └── binance_client.py # Binance API wrapper ├── monitor/ │ └── exporter.py # Expose state metrics in Prometheus format ├── config/ │ └── settings.py # Configuration (read from environment variables) └── run.py # Entry point Key Code: Exposing State Metrics While your strategy runs, write key metrics in Prometheus text file format for node_exporter to scrape:
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