Autonomous AI Resilience System for Enterprise Agent Infrastructure
Ouroboros is an autonomous AI resilience platform that detects and remediates catastrophic failure modes in enterprise AI agent systems. It acts as an immune system for AI infrastructure, automatically detecting infinite loops, semantic drift, and runaway costs—then healing them without human intervention.
The Problem: Multi-agent AI systems fail in unpredictable ways. A single trapped agent can burn $3,000+ per hour in API costs while grinding operations to a halt.
The Solution: Ouroboros combines deep observability (Datadog), generative AI (Google Vertex AI), and event-driven architecture (Confluent Kafka) to detect pathological behavior within 30 seconds and execute autonomous remediation.
- 🔍 Autonomous Loop Detection: Detects infinite reasoning loops using semantic similarity analysis (95% threshold, 5 consecutive turns)
- 💉 The Antidote: Automatically injects system instruction overrides to break loops
- ⚡ Circuit Breaker: Suspends agents exceeding cost thresholds ($100 limit)
- 📊 Real-Time Observability: Full trace capture of agent reasoning with Datadog LLM Observability
- 🎨 Neon Dashboard: Cyberpunk-themed Next.js dashboard with live remediation feed
- 🔄 Event Streaming: Kafka-based audit trail for forensic analysis and replay
- 💰 Cost Prevention: Prevents runaway API costs with token velocity monitoring
┌─────────────────────────────────────────────────────────────┐
│ OUROBOROS ARCHITECTURE │
├─────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────┐ ┌──────────────┐ ┌────────────┐ │
│ │ Vertex AI │ │ Datadog │ │ Confluent │ │
│ │ Agent Engine│─────▶│ Observability│─────▶│ Kafka │ │
│ │ (Brain) │ │ (Nervous │ │ (Memory) │ │
│ └─────────────┘ │ System) │ └────────────┘ │
│ │ └──────────────┘ │ │
│ │ │ │ │
│ │ ▼ │ │
│ │ ┌──────────────┐ │ │
│ │ │ Webhook │ │ │
│ │ │ Triggers │ │ │
│ │ └──────────────┘ │ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ Google Cloud Functions (Effector Arms) │ │
│ │ ┌──────────────┐ ┌─────────────────┐ │ │
│ │ │inject-antidote│ │circuit-breaker │ │ │
│ │ └──────────────┘ └─────────────────┘ │ │
│ └──────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────┘
Design Philosophy: Tripartite organism pattern
- Brain (Vertex AI): Agent reasoning and execution
- Nervous System (Datadog): Observability and alerting
- Memory (Kafka): Durable event log and audit trail
- Google Cloud Platform account with billing
- Datadog account (14-day trial acceptable)
- Confluent Cloud account (free tier)
- Python 3.11+, Node.js 18+, gcloud CLI
# Clone the repository
cd /home/ugrads/majors/arnavpant27/oroboros
# Step 1: Create GCP project and enable billing
cd infrastructure/gcp
chmod +x create-project.sh
./create-project.sh
# Step 2: Load environment variables
source ../../config/gcp-project.env
# Step 3: Verify setup
gcloud projects describe $GCP_PROJECT_IDNext Steps: See SETUP.md for complete installation guide.
oroboros/
├── infrastructure/ # GCP and Terraform setup
│ ├── gcp/
│ │ ├── create-project.sh # Task 1.1 ✅
│ │ ├── enable-apis.sh # Task 1.2 (next)
│ │ └── service-accounts.sh # Task 1.3 (next)
│ └── terraform/ # IaC configuration
├── agents/ # FinBot test agent
│ └── finbot/
│ ├── agent_config.py # Vertex AI config
│ ├── tools.py # Custom tools
│ └── poison_prompts.py # Test prompts
├── observability/ # Datadog integration
│ ├── datadog_tracer.py # LLM tracing
│ ├── semantic_analyzer.py # Loop detection
│ └── monitors/ # Alert configs
├── functions/ # Cloud Functions (remediation)
│ ├── inject-antidote/ # The Antidote
│ └── circuit-breaker/ # Agent suspension
├── kafka/ # Event streaming
│ ├── schemas/ # Avro schemas
│ ├── producers/ # Event publishers
│ └── consumers/ # Audit processors
├── dashboard/ # Next.js frontend (neon theme)
│ ├── app/ # App Router pages
│ ├── src/components/ # React components
│ └── tailwind.config.ts # Neon theme config
├── api/ # FastAPI backend
│ ├── routers/ # API endpoints
│ └── services/ # Business logic
├── tests/ # Test suite
│ ├── unit/ # Unit tests
│ ├── integration/ # E2E tests
│ └── load/ # Load testing
├── config/ # Configuration files
│ ├── gcp-project.env # GCP settings ✅
│ └── .env.example # Template
├── docs/ # Documentation
│ └── SETUP.md # Setup guide ✅
└── tasks/ # Project management
├── prd-ouroboros-ai-resilience.md
└── tasks-prd-ouroboros-ai-resilience.md
- ✅ Detection Speed: <30 seconds from loop onset to detection
- ✅ Remediation Success: 3/3 auto-heals during live demo
- ✅ Cost Savings: Dashboard shows "$127 saved by auto-remediation"
- ✅ Zero Human Intervention: Fully autonomous healing
| Component | Technology | Purpose |
|---|---|---|
| AI Runtime | Google Vertex AI Agent Engine | Multi-agent orchestration |
| Observability | Datadog LLM Observability | Trace capture & alerting |
| Event Streaming | Confluent Kafka | Durable audit log |
| Remediation | Google Cloud Functions | Serverless auto-healing |
| Frontend | Next.js 14 + React 18 | Neon cyberpunk dashboard |
| Backend API | FastAPI | Metrics & agent data |
| Secrets | Google Secret Manager | Secure credential storage |
Phase: 1 - Infrastructure Foundation (Hours 0-48)
Progress: Task 1.1 Complete ✅
| Phase | Status | Tasks Complete |
|---|---|---|
| Phase 1: Infrastructure | 🟡 In Progress | 1/12 |
| Phase 2: Agent Development | ⚪ Not Started | 0/14 |
| Phase 3: Remediation | ⚪ Not Started | 0/14 |
| Phase 4: Kafka Streaming | ⚪ Not Started | 0/11 |
| Phase 5: Dashboard & Demo | ⚪ Not Started | 0/29 |
- Setup Guide - Step-by-step installation
- PRD - Product requirements
- Task List - Implementation roadmap
- Architecture Guide (coming in Phase 2)
- API Documentation (coming in Phase 3)
- Frontend Guide (coming in Phase 5)
This is a hackathon project for the AI Partner Catalyst event.
Development Workflow:
- Follow the task list in
tasks/tasks-prd-ouroboros-ai-resilience.md - One sub-task at a time (per process guidelines)
- Commit after each completed parent task
- Run tests before committing
- All secrets stored in Google Secret Manager
- Service accounts use least-privilege IAM roles
- No API keys committed to Git
- Audit logs enabled for all API calls
7-Day Hackathon Budget: $25-60
| Service | Cost |
|---|---|
| Vertex AI (Gemini 1.5 Pro) | $20-50 |
| Cloud Functions | $5-10 |
| Datadog Trial | $0 |
| Confluent Kafka Free Tier | $0 |
Cost Control: $100 circuit breaker prevents runaway costs
Total: 168 hours (7 days)
- Phase 1 (Hours 0-48): Infrastructure setup
- Phase 2 (Hours 49-96): Agent development & observability
- Phase 3 (Hours 97-120): Autonomous remediation
- Phase 4 (Hours 121-144): Kafka event streaming
- Phase 5 (Hours 145-168): Dashboard & demo prep
Project: Ouroboros AI Resilience Platform
Event: AI Partner Catalyst Hackathon
Date: December 22, 2025
This is a hackathon POC project. Not licensed for production use.
Built with ❤️ for the AI Partner Catalyst Hackathon
"The snake that eats its own tail—regenerating infinitely."