NeverDown: Autonomous DevOps & Incident Remediation 🚀

The first AI-native system that detects, analyzes, and patches CI/CD failures before you even see the alert.

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💡 Why NeverDown?

Modern engineering teams spend 30-40% of their time debugging CI/CD failures, flaky tests, and environment mismatches. NeverDown turns this reactive toil into a proactive background process.

The Problem

• Alert Fatigue: Developers are bombarded with "Build Failed" notifications.
• Context Switching: Dropping a feature task to fix a typo in postcss.config.mjs kills velocity.
• Security Risks: Debugging often involves sharing raw logs that might contain leaked secrets.

The NeverDown Solution

1. Detect: Listen to GitHub Workflows and Monitoring hooks.
2. Sanitize: Automatically redact secrets and PII from logs before they touch an LLM.
3. Reason: Multi-agent LLM analysis to find the root cause and generate a surgical patch.
4. Verify: Run the fix in a secure, isolated Docker sandbox.
5. Remediate: Open a high-quality Pull Request with full context.

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🏗️ Technical Architecture

NeverDown uses a sophisticated 5-Agent Autonomous Pipeline designed for security and reliability.

graph TD
    A[Trigger: CI Failure / Log Alert] --> B[Agent 0: Sanitizer]
    B -->|Cleaned Context| C[Agent 1: Detective]
    C -->|Root Cause & Suspects| D[Agent 2: Reasoner]
    D -->|Unified Patch| E[Agent 3: Verifier]
    E -->|Verified Correctness| F[Agent 4: Publisher]
    F -->|GitHub PR| G[Human Approval]
    
    subgraph "Secure Sandbox"
    E
    end
    
    subgraph "Privacy Layer"
    B
    end

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The Agentic Pipeline

Agent	Role	Capabilities
0. Sanitizer	Privacy Guard	Redacts AWS, GitHub, Stripe keys, and high-entropy strings.
1. Detective	Forensics	Analyzes logs, git history (blame), and file relationships.
2. Reasoner	Engineer	Uses Claude-3.5-Sonnet/GPT-4o to generate surgical code fixes.
3. Verifier	QA	Runs fixes in isolated Docker containers with no network access.
4. Publisher	DevOps	Handles PR creation, branch management, and human-in-the-loop refinement.

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🔒 Security & Safety by Design

• Zero-Cloud-Leak Policy: Raw repository data and logs never leave your network without redaction.
• Isolated Execution: All verifications happen in chroot-like Docker sandboxes with strict resource limits.
• Human-in-the-Loop: NeverDown never auto-merges. It provides a "Request Changes" loop where the AI refines its fix based on your feedback.
• Read-Only Production: The system only interacts with your source control via PRs.

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🚀 Getting Started

Prerequisites

• Python 3.11+
• Docker (for sandbox verification)
• PostgreSQL (Neon, Supabase, or Local)

Installation

# Clone the repository
git clone https://github.com/manik3160/NeverDown.git
cd NeverDown

# Install core and dev dependencies
pip install -e ".[dev]"

# Configure environment
cp .env.example .env
# Open .env and add your GITHUB_TOKEN, LLM_API_KEY, and DATABASE_URL

Running Locally

# Start the backend API
python main.py

# Launch the Dashboard
cd web && npm run dev

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📺 Dashboard Preview

NeverDown provides a high-fidelity dashboard to monitor your autonomous fleet. View live execution logs, AI reasoning steps, and patch previews in real-time.

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📜 Development & Testing

We maintain a rigorous test suite for all agents.

# Run full suite
pytest

# Test specific agent
pytest tests/test_sanitizer.py

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🤝 Contributing

NeverDown is built for the community. See CONTRIBUTING.md for details on how to add new agent capabilities or integrations.

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📜 License

MIT © NeverDown Team