# Aequitas-Parallel-Triage v0.3.0 🛡️🚀

**"Because processing 10 million tasks shouldn't feel like a boss fight."**

Aequitas is a production-grade, concurrent audit engine that treats system resources with clinical efficiency. I have Aequitas hitting **23k+ TPS on a Windows laptop** without breaking a sweat, ensuring zero tolerance for logic errors and maximum resource dexterity.

## 📊 Performance Benchmarks (Validated March 14, 2026)
- **Throughput:** 23,696.6 TPS.
- **RSS Footprint:** 45.6 MB at 10,000 tasks.
- **Engine Latency:** < 0.5s for 10k task bursts. 
- **Stability:** 77/77 Unit Tests Passed.

---

## 🏗️ Architecture Overview

```text
 Ingestion (generator)
       │
       ▼
 Dispatcher (token-bucket backpressure, bounded queue)
       │
   ┌───┴────────────────────────────────┐
   │  Executor pool (threaded / process / async-hybrid)
   │        │
   │   Worker N  ──► SubprocessWrapper (Popen, timeouts, cgroups)
   │        │              │
   │        └──► ContainerPool (checkout / overlay-reset / checkin)
   │
   ├──► LogWriter  (QueueHandler → bounded queue → QueueListener → NDJSON RotatingFile)
   │
   ├──► EscalationModule (Redis INCR+TTL  ──fallback──► in-process aggregator)
   │
   └──► Metrics / Telemetry (Prometheus-compatible counters, histograms)

Key Design Decisions

Concern	Decision	Why
Backpressure	Token-bucket dispatcher	Prevents unbounded queue growth at 10M+ scale.
Logging	Single-writer QueueListener	Eliminates cross-process lock contention on log files.
Memory	GC only on high-water mark	Per-batch GC destroys throughput; RSS sampling is cheap.
Escalation	Redis INCR+TTL primary	Atomic, TTL-native, survives worker restarts.
Containers	Pooled + overlay reset	Warm-start latency < 10 ms; avoids Docker create overhead.
Security	shell=False everywhere	Eliminates command injection surface.

---

🧠 Core Engineering (The "Secret Sauce")

• True Cross-Platform Mastery: Most engines cry on Windows. I built a custom platform_compat layer to orchestrate spawn (Windows) and forkserver (POSIX) contexts with pinpoint accuracy and dexterity.
• Single-Writer Logging: I decoupled I/O using a bounded QueueListener. Workers don't wait for the disk; they get back to work.
• Resource Governance: My platform-aware signal handling and safe fsync wrappers ensure that even when Windows VFS gets moody, the audit trail remains immortal.

⚔️ The War Stories (Difficulties Overcome)

During the refactor from v2 to v3, I leveraged AI-collaborative engineering to overcome three major "Wall-Clock" bottlenecks:

1. The Windows Signal Trap: Windows doesn't handle SIGKILL like POSIX. I architected a layer to translate these into Windows-native termination to prevent zombie processes.
2. The Moody VFS: High-speed logging on Windows triggered OSError during os.fsync(). I implemented a "Safe Fsync" wrapper that absorbs non-critical OS sync errors.
3. Context Drift: Moving to Windows spawn meant every object had to be picklable. I had to clean up task ingestion to ensure zero state-leakage.

🎯 Mission Profile

• Massive Fleet Audits: Running security checks across 100,000+ nodes.
• High-Volume Command Orchestration: Executing millions of system-level transactions.
• Parallel Log Triage: Ingesting and processing massive NDJSON streams in real-time.

⚠️ Where this will break (The Honest Limits)

• Container Churn: Creating 10 million ephemeral containers will kill the Docker Daemon. Use the ContainerPool.
• Windows Process Overhead: Even at 23k TPS, Windows spawn is heavier than Linux. For absolute peak performance, use a Linux host.
• Redis Latency: Remote Redis will plummet throughput. Use local or co-located instances.

---

🛠️ Quick Start & Validation

1. Initialize Environment:

python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows
pip install -r requirements.txt

2. Logic Check (77 Tests):

python run_tests.py -v

3. Performance Smoke Run:

python ci_runner.py --use-run-tests --no-slow

---

📂 Module Index

Module	Path	Purpose
Config	aequitas/config.py	YAML loader + safe defaults.
Dispatcher	aequitas/dispatcher.py	Token-bucket ingestion.
Worker	aequitas/worker.py	Pluggable executor interface.
LogWriter	aequitas/log_writer.py	QueueListener NDJSON writer.
Escalation	aequitas/escalation.py	Redis + in-process sliding window.
ContainerPool	aequitas/container_pool.py	Async pool with overlay reset.
Subprocess	aequitas/subprocess_wrapper.py	Secure Popen + timeouts.

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Architected by DDRG15 via Human-AI Collaborative Engineering.