9dc4d2585f
Rewrite all 5 Grafana dashboards using only confirmed-existing Prometheus
metric names (1023 metrics inventoried). Dashboards now use hardcoded
datasource UIDs instead of unresolvable ${DS_*} template variables.
- Cockpit: 38 panels (service health, gRPC, Argo CI/CD, trading, metrics)
- Training: 33 panels (epochs, loss, Sharpe, Q-values, GPU, hyperopt)
- Trading: 5 rows (overview, latency, gRPC pipeline, data acq, backtesting)
- Infrastructure: 25 panels (cluster, nodes, workloads, storage, GPU, Prometheus)
- Observability: 22 panels (API gateway auth/security/routing, Loki, Tempo)
Fix kube-state-metrics: add part-of label for netpol, fix nodeSelector
(infra→platform), increase memory limit (128→256Mi for OOM), add K8s API
egress rules covering both 10.32.0.0/16 and 172.16.0.0/16 CIDR ranges.
Add training-pods pod-based scrape job for ephemeral Argo workflow pods
exposing metrics on port 9094.
Migrate all image references from localhost:30500 to internal DNS
(gitlab-registry.foxhunt.svc.cluster.local:5000) across 14 YAML files.
Fix import.sh ConfigMap name (grafana-dashboards-infra → infrastructure).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.