Files

jgrusewski 82197efb59 🚀 Wave 127 Wave 2: Execution Validation (6 agents)

**Mission**: Validate frameworks created in Wave 126

**Agent 120b: Prometheus Exporters Fix** ⚠️ Code Complete
- Fixed all 4 services (wrong Prometheus registries)
- API Gateway: Now uses GatewayMetrics registry
- Trading Service: Uses TradingMetricsServer
- Backtesting/ML: Created simple_metrics modules
- Built successfully (1m 51s)
- BLOCKER: Docker rebuild needed for deployment

**Agent 122: E2E Test Execution** ❌ BLOCKED
- Fixed Tonic 0.12 → 0.14 migration (all proto enums)
- 54 E2E tests compile successfully
- BLOCKER: JWT auth not implemented in test framework
- Impact: 0/54 tests can execute

**Agent 123: Load Test Execution** ❌ BLOCKED
- Framework validated (7,960-9,354 req/sec client-side)
- HDR histogram metrics working
- BLOCKER: SQL schema mismatch (price vs limit_price)
- Impact: 100% failure rate (477K attempted, 0 successful)

**Agent 124: Benchmark Execution** ✅ PARTIAL
- Authentication: 4.4μs ✅ (<10μs target)
- Order matching: 1-6μs P99 ✅ (<50μs target)
- Component latencies validated
- Gap: E2E, risk, ML benchmarks not executed

**Agent 125: PPO Test Fix** ✅ COMPLETE
- Test already passing (575/575 ML tests)
- 100% pass rate in ML crate
- No fix needed (transient failure)

**Agent 126: Security Hardening** ✅ COMPLETE
- RSA 4096-bit certificates generated and deployed
- All services restarted successfully
- H1 security gap closed

**Wave 2 Results**:
- Achievements: Component latency validated, security hardened, GPU working
- Critical Blockers: 3 identified (E2E auth, load test SQL, Prometheus deployment)
- Production Readiness: 91-92% (unchanged - blockers prevent further validation)

**Files Modified** (21):
- services/integration_tests/* (6 files - E2E test compilation fixes)
- services/*/src/main.rs (3 files - Prometheus exporters)
- services/backtesting_service/src/simple_metrics.rs (new)
- services/ml_training_service/src/simple_metrics.rs (new)
- certs/production/* (RSA 4096-bit certificates)
- services/load_tests/tests/* (relocated)

**Critical Blockers Identified**:
1. E2E: JWT Interceptor missing (2-4h fix)
2. Load: SQL schema mismatch (1-2h fix)
3. Prometheus: Docker rebuild needed (30m)

**Validation Report**: /tmp/wave2_gate_validation.md

**Next**: Deploy 3 blocker-fix agents, then Wave 3

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

2025-10-08 09:41:43 +02:00

migrations

🚀 PRODUCTION READY: Foxhunt HFT Trading System v1.0

2025-09-24 23:47:21 +02:00

src

🚀 Wave 127 Wave 2: Execution Validation (6 agents)

2025-10-08 09:41:43 +02:00

tests

🚀 Wave 122 Complete: Deployment Readiness Validated

2025-10-07 14:25:46 +02:00

build.rs

🚀 Wave 119 Complete: 11 Agents - 202 Tests Added, 58-60% Coverage

2025-10-07 00:42:57 +02:00

Cargo.toml

🚀 Wave 127 Wave 2: Execution Validation (6 agents)

2025-10-08 09:41:43 +02:00

Dockerfile

🚀 Wave 125 Phase 3C: Deploy Agents 101-105 - TLS + Optional Services + Health Endpoints

2025-10-07 23:28:04 +02:00

Dockerfile.dev

🐛 Fix Docker builds: Update Rust 1.75→1.83 for edition2024 support

2025-10-07 22:01:06 +02:00

Dockerfile.production

🐛 Fix Docker builds: Update Rust 1.75→1.83 for edition2024 support

2025-10-07 22:01:06 +02:00

README.md

🔧 Tonic 0.14 Upgrade: Auto-generated and build system changes

2025-10-03 07:34:26 +02:00

README.md

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 strategy
GetBacktestResults - Retrieve results for completed backtests
ListAvailableStrategies - List registered strategies
GetBacktestReport - 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.