Enterprise-Grade Infrastructure Intelligence Platform Automated Discovery • Security Scanning • AI Analysis • Beautiful Dashboards
Quick Start • Features • Documentation • Installation • Contributing
🚀 Enterprise-Grade Infrastructure Intelligence Platform that combines automated discovery, security scanning, AI analysis, and beautiful dashboards.
# Run the complete NOIP demo pipeline
make demo# Clone and setup
git clone https://github.com/your-org/noip.git
cd noip
make setup
# Configure credentials
export ANTHROPIC_API_KEY="your-anthropic-key-here"
export KUBECONFIG="$HOME/.kube/config"
# Run pipeline
make scan && make analyze && make dashboardThe NetOps Intelligence Platform transforms infrastructure management through:
- Kubernetes Cluster Analysis - Real-time cluster state and resource monitoring
- Network Topology Mapping - Automatic network discovery and visualization
- Cloud Resource Inventory - Multi-cloud asset tracking and management
- Configuration Drift Detection - Identify unauthorized infrastructure changes
- Secret Detection - Scan for exposed credentials and sensitive data
- Vulnerability Assessment - Comprehensive security scanning and reporting
- Compliance Validation - Automated compliance checks against industry standards
- File Integrity Monitoring - Tamper detection and audit trail maintenance
- Claude AI Integration - Advanced analysis using Anthropic's Claude API
- Anomaly Detection - Machine learning powered pattern recognition
- Predictive Insights - Proactive issue identification and resolution
- Executive Summaries - Automated report generation with actionable insights
- Real-time Visualization - Interactive dashboards with live data
- Executive Reporting - Professional summaries and trend analysis
- Custom Metrics - Flexible monitoring and alerting
- Export Capabilities - Multiple formats (JSON, CSV, PDF)
netops-intelligence-platform/
├── .github/workflows/ # CI/CD Pipeline
│ ├── infrastructure-scan.yml # Automated discovery
│ ├── security-audit.yml # Security scanning
│ └── ai-analysis.yml # AI analysis
├── scripts/ # Core Platform Scripts
│ ├── ai_analysis.py # Claude AI analysis
│ ├── generate_dashboard.py # Dashboard generation
│ ├── update_rag.py # RAG database management
│ ├── file-hasher.py # File integrity
│ ├── cargocrypt-integration.py # Cryptographic operations
│ └── security-testing-framework.py # Security testing
├── inventory/ # Infrastructure Data
│ ├── kubernetes/ # K8s cluster state
│ ├── network/ # Network topology
│ └── cloud/ # Cloud resources
├── rag/ # Knowledge Base
│ ├── embeddings/ # Vector embeddings
│ └── vectors/ # RAG data
├── reports/ # Analysis Reports
│ ├── daily/ # Daily summaries
│ ├── incidents/ # Security incidents
│ └── dashboard.html # Live dashboard
└── docs/ # Documentation
- Kubernetes Diagnostics - Cluster health, resource utilization, pod analysis
- Network Mapping - Automatic topology discovery and dependency tracking
- Cloud Asset Management - Multi-cloud inventory and cost optimization
- Configuration Drift - Detect and alert on unauthorized changes
- Secret Scanning - Detect hardcoded credentials, API keys, tokens
- Vulnerability Assessment - CVE scanning, security posture analysis
- Compliance Checking - SOC2, ISO27001, GDPR compliance validation
- Threat Detection - Anomaly-based security monitoring
- Claude Integration - Natural language analysis of infrastructure data
- Predictive Analytics - Trend analysis and capacity planning
- Automated Reporting - Executive summaries and technical reports
- Root Cause Analysis - AI-powered incident investigation
- Interactive Dashboards - Real-time metrics and KPIs
- Custom Reports - Flexible reporting and data export
- Trend Analysis - Historical data visualization
- Alert Integration - Slack, Teams, email notifications
- Python 3.11+
- Node.js 18+
- Docker (optional)
- kubectl (for Kubernetes features)
- Anthropic API Key
# Clone repository
git clone https://github.com/your-org/noip.git
cd noip
# Automatic setup
make setup
# Verify installation
make test# Python dependencies
pip install -r requirements.txt
# Node.js dependencies
npm install
# Create directories
mkdir -p inventory/{kubernetes,network,cloud}
mkdir -p rag/{embeddings,vectors}
mkdir -p reports/{daily,incidents}# Required
export ANTHROPIC_API_KEY="your-anthropic-api-key"
export KUBECONFIG="$HOME/.kube/config"
# Optional
export SLACK_WEBHOOK="your-slack-webhook-url"
export GITHUB_TOKEN="your-github-token"
export LOG_LEVEL="INFO"
export RAG_PERSIST_DIR="./rag"# config/noip.yaml
platform:
scan_interval: "6h" # Infrastructure scan frequency
retention_days: 30 # Data retention period
parallel_scans: 5 # Concurrent scan limit
security:
secret_scanning: true # Enable secret detection
vulnerability_scan: true # Enable vulnerability checks
compliance_checks: true # Enable compliance validation
ai:
model: "claude-3-sonnet-20240229" # Claude model
max_tokens: 4000 # Response token limit
temperature: 0.1 # Analysis creativity
dashboard:
refresh_interval: 300 # Dashboard refresh (seconds)
export_formats: ["json", "csv", "pdf"]
theme: "dark" # UI theme# Full pipeline execution
make demo
# Individual components
make scan # Infrastructure discovery
make analyze # AI analysis
make report # Generate reports
make dashboard # Create dashboard
# Manual script execution
python scripts/ai_analysis.py --analysis-type comprehensive
python scripts/generate_dashboard.py reports/ --export json
python scripts/update_rag.py inventory/ rag/The platform includes automated workflows:
- Infrastructure Scan - Runs every 6 hours or on demand
- Security Audit - Comprehensive security scanning
- AI Analysis - Intelligent analysis using Claude API
# Generate and open dashboard
make dashboard open
# View dashboard
open reports/dashboard.html- Security Posture - Critical issues, risk score, compliance status
- Infrastructure Health - Node health, resource utilization, drift status
- Performance Metrics - Response times, throughput, error rates
- Cost Analysis - Resource costs, optimization opportunities
- Filterable Data - Time range, severity, component filtering
- Export Options - JSON, CSV, PDF export capabilities
- Drill-down Analysis - Click to investigate specific issues
- Alert Integration - Real-time notifications for critical events
# Custom dashboard generation
python scripts/generate_dashboard.py \
--reports-dir reports/ \
--output-dir web/ \
--export pdf \
--open-browser- Multi-Scanner Engine - Combines multiple secret detection tools
- Pattern Recognition - Advanced regex and ML-based detection
- False Positive Reduction - Intelligent validation and context analysis
- Automated Remediation - Automatic secret rotation and alerts
- Framework Support - SOC2, ISO27001, GDPR, HIPAA, PCI-DSS
- Automated Checks - Continuous compliance monitoring
- Audit Trail - Complete change tracking and reporting
- Evidence Collection - Automatic evidence gathering for audits
- Cryptographic Verification - SHA-256, SHA-512, MD5 hashing
- Real-time Monitoring - Immediate detection of unauthorized changes
- Baseline Management - Automatic baseline creation and updates
- Comprehensive Reporting - Detailed integrity reports and alerts
# Run AI analysis
python scripts/ai_analysis.py \
--analysis-type comprehensive \
--data-dir reports/ \
--output-format markdown- Comprehensive - Complete infrastructure analysis
- Security-Focused - Security posture and vulnerabilities
- Performance-Optimization - Performance bottlenecks and improvements
- Cost-Optimization - Cost reduction opportunities and ROI
The platform maintains a knowledge base using ChromaDB for:
- Historical Analysis - Track trends and patterns over time
- Context-Aware Insights - Leverage historical data for better analysis
- Continuous Learning - Improve analysis accuracy over time
- Knowledge Search - Query historical infrastructure data
# Development setup
make dev-setup
# Run tests
make test
# Lint code
make lint
# Type check
make typecheck- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
# Unit tests
pytest tests/unit/
# Integration tests
pytest tests/integration/
# E2E tests
pytest tests/e2e/
# Coverage report
pytest --cov=scripts --cov-report=htmlAPI Key Issues
# Verify Anthropic API key
echo $ANTHROPIC_API_KEY
# Test API connectivity
python -c "import anthropic; print('API accessible')"Kubernetes Connection
# Check kubectl configuration
kubectl cluster-info
# Test cluster access
kubectl get nodesDashboard Generation
# Verify report data exists
ls -la reports/
# Test dashboard generation
python scripts/generate_dashboard.py reports/ --preview-only# Enable debug logging
export LOG_LEVEL=DEBUG
# Run with verbose output
python scripts/ai_analysis.py --verbose
# Check system requirements
python scripts/requirements_check.py- Small Deployments - Single server, <100 resources
- Medium Deployments - Multi-server, <1,000 resources
- Large Deployments - Cluster-based, <10,000 resources
- Enterprise Deployments - Distributed, 100,000+ resources
- CPU: 2-8 cores depending on infrastructure size
- Memory: 4-32GB RAM
- Storage: 50GB-1TB (for data retention)
- Network: 1-10 Gbps connectivity
- Scan Time: <5 minutes for 1,000 resources
- AI Analysis: <30 seconds for comprehensive analysis
- Dashboard Generation: <10 seconds for complex dashboards
- Data Ingestion: <1 second per resource
- GitHub Issues - Report bugs and request features
- Discussions - Community discussions and Q&A
- Wiki - Community-contributed documentation
- Examples - Sample configurations and use cases
- Email Support - Priority email support
- Slack Community - Real-time chat support
- Onboarding - Enterprise setup and training
- Custom Development - Feature development and integration
- Documentation - Comprehensive guides and API reference
- Video Tutorials - Step-by-step video guides
- Webinars - Live training and demonstrations
- Blog - Best practices and case studies
This project is licensed under the MIT License - see the LICENSE file for details.
- Free for personal and academic use
- Commercial license required for enterprise deployments
- Contact sales@noip-platform.com for enterprise pricing
- Anthropic Claude - Separate API terms and pricing
- ChromaDB - Apache 2.0 License
- Plotly - MIT License
- Anthropic Claude - AI-powered analysis and insights
- ChromaDB - Vector database for RAG implementation
- Plotly - Interactive dashboards and visualization
- Python & Node.js - Core development platforms
- DevOps Best Practices - Modern infrastructure management
- Security-First Design - Comprehensive security posture
- AI-Driven Operations - Intelligent automation and analysis
- Community Feedback - User-driven feature development
- Multi-cloud provider support (AWS, Azure, GCP)
- Advanced anomaly detection using ML
- Mobile app for infrastructure monitoring
- API-first architecture for third-party integrations
- Predictive maintenance capabilities
- Automated remediation workflows
- Enterprise SSO integration
- Advanced compliance reporting
- IoT device monitoring integration
- Blockchain-based audit trails
- Advanced threat hunting capabilities
- Global infrastructure mapping
Get Started Today:
git clone https://github.com/your-org/noip.git
cd noip
make demoExperience the future of infrastructure intelligence with NOIP!
NetOps Intelligence Platform Enterprise-Grade Infrastructure Intelligence & Security