Production Notes
In production, disaster recovery planning requires monitoring for API rate limits, database connection pooling, log rotation, alert thresholds, and automated restart procedures. Document runbooks for incident response.
Testing Approach
Testing disaster recovery planning includes unit tests for signal logic, integration tests for exchange interaction, and backtests against historical data with realistic slippage modeling.
Code Structure
The code structure separates concerns: data ingestion, signal generation, risk checks, and order submission. This modularity enables testing and reuse across strategies.
# Example configuration for Disaster Recovery Planning
strategy:
name: disaster-recovery-planning
timeframe: 5m
indicators:
- rsi
- ema_fast
- ema_slow
entry_conditions:
- rsi_oversold
- ema_crossover_bullish
exit_conditions:
- rsi_overbought
- stop_loss_hit
risk:
max_position_size: 0.02
stop_loss_pct: 0.015
Overview
This guide covers disaster recovery planning implementation in automated trading systems. The approach combines established patterns with operational considerations drawn from production deployments.
Core Concepts
Understanding disaster recovery planning requires familiarity with market microstructure, order flow dynamics, and execution latency. The following sections detail each component.