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hjnormey 01c19662cb initial: import DOLPHIN baseline 2026-04-21 from dolphinng5_predict working tree

Includes core prod + GREEN/BLUE subsystems:
- prod/ (BLUE harness, configs, scripts, docs)
- nautilus_dolphin/ (GREEN Nautilus-native impl + dvae/ preserved)
- adaptive_exit/ (AEM engine + models/bucket_assignments.pkl)
- Observability/ (EsoF advisor, TUI, dashboards)
- external_factors/ (EsoF producer)
- mc_forewarning_qlabs_fork/ (MC regime/envelope)

Excludes runtime caches, logs, backups, and reproducible artifacts per .gitignore.

2026-04-21 16:58:38 +02:00

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ExF Latency Options

Current: 500ms Standard

HZ Push Interval: 0.5 seconds
Latency: Data in HZ within 500ms of change
CPU: Minimal (~1%)
Use Case: Standard 5-second Alpha Engine scans

Option 1: 100ms Fast (5x faster)

HZ Push Interval: 0.1 seconds
Latency: Data in HZ within 100ms of change
CPU: Low (~2-3%)
Use Case: High-frequency Alpha Engine
Run: python exf_fetcher_flow_fast.py

Option 2: Event-Driven (Near-zero)

HZ Push: Immediately on indicator change
Latency: <10ms for critical indicators
CPU: Minimal (only push on change)
Use Case: Ultra-low-latency requirements
Run: python realtime_exf_service_hz_events.py

Recommendation

For your setup with 5-second Alpha Engine scans:

Standard (500ms): ✅ Sufficient - 10x oversampling
Fast (100ms): ⚡ Better - 50x oversampling, minimal overhead
Event-driven: 🚀 Best - Near-zero latency, efficient

Quick Start

cd /mnt/dolphinng5_predict/prod

# Option 1: Standard (current)
./start_exf.sh restart

# Option 2: Fast (100ms)
nohup python exf_fetcher_flow_fast.py --warmup 10 > /var/log/exf_fast.log 2>&1 &

# Option 3: Event-driven
nohup python realtime_exf_service_hz_events.py --warmup 10 > /var/log/exf_event.log 2>&1 &

Data Freshness by Option

Option	Max Latency	Use Case
Standard	500ms	Normal operation
Fast	100ms	HFT-style trading
Event-Driven	<10ms	Ultra-HFT, market making

Note: The in-memory cache is updated every 0.5s for critical indicators regardless of HZ push rate. The push rate only affects how quickly data appears in Hazelcast.

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