1aef51f99b
Web-gateway routing: - Point TRADING_SERVICE_URL at api-gateway (proto mismatch fix) Web-gateway uses foxhunt.tli.TradingService proto but was connecting directly to trading-service which implements trading.TradingService. api-gateway already proxies Subscribe* → Stream* correctly. GitLab KAS: - Disable gitlab_kas in appConfig to stop sidekiq NotifyGitPushWorker errors (KAS pod was already disabled but Rails still tried to connect) Trading service monitoring (3 stubs → real): - AcknowledgeAlert: real alert lookup + state mutation in shared store - GetActiveAlerts: returns actual active alerts from in-memory store - StreamAlerts: now persists generated alerts (capped at 1000 entries) Trading service ML streams (2 stubs → real): - StreamModelMetrics: emits real inference_count, error_count, latency per model every N seconds from the RuntimeModelInfo registry - StreamSignalStrength: emits per-symbol signal aggregation from model ensemble weights and latency confidence Backtesting service: - stop_backtest: real CancellationToken cancellation (was no-op) Tokens stored per-backtest, execute_backtest wraps strategy call in tokio::select! for immediate cancellation Deleted 7 empty placeholder files: - 4 Wave D regime stubs (dynamic_stops, ensemble, performance_tracker, position_sizer) — comment-only files, never wired - 2 Wave 3 feature stubs (microstructure, statistical) - 1 PPO stub (unified_ppo.rs — empty struct definitions) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backtesting Service
Overview
The backtesting_service offers an independent and isolated environment for rigorously testing and validating trading strategies against historical market data. It provides a robust platform for simulating trading performance, analyzing strategy efficacy, and generating comprehensive performance reports before live deployment.
Features
- Independent Backtesting Service: Operates autonomously, allowing for parallel and isolated strategy evaluations.
- gRPC API for Backtest Execution: Exposes a clear API for submitting and managing backtesting jobs.
- Strategy Testing and Validation: Enables comprehensive testing of various trading strategies under different market conditions.
- Performance Reporting: Generates detailed reports including metrics like P&L, Sharpe ratio, drawdown, and win rate.
- Data Replay Engine: Accurately replays historical market data, simulating real-world order book dynamics and trade execution.
- Results Persistence: Stores backtesting results and reports for historical analysis and comparison.
gRPC API
The backtesting_service exposes a gRPC API for initiating and retrieving backtest results. Key endpoints include:
RunBacktest- Submit backtest configuration and strategyGetBacktestResults- Retrieve results for completed backtestsListAvailableStrategies- List registered strategiesGetBacktestReport- Get detailed performance report
Running the service
To run the backtesting_service binary:
cargo run --bin backtesting_service
Data Requirements
The service requires historical market data in Parquet format:
- Data should be stored in the configured data directory
- Supports tick data, order book snapshots, and OHLCV candles
- Data must include instrument, timestamp, and price/quantity fields
Testing
To run the tests for the backtesting_service crate:
cargo test --package backtesting_service
Documentation
Comprehensive API documentation is available at docs.rs/backtesting_service.