A distributed platform that creates a unified layer for data, APIs, automation, and AI on top of carefully selected open-source projects. We simplify IT and security operations through a single, cohesive platform.

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Quick Links

• Quick Start
• Documentation
• Community
• Security

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Highlights

• Unified Dashboard - Single interface for managing all services and workflows
• Smart Automation - Automated deployment and monitoring capabilities
• AI-Powered Insights - Real-time anomaly detection and intelligent assistants
• Enterprise Security - Integrated security controls across all services
• High Performance - Handles 100,000+ events/second with sub-500ms latency
• Scalable Architecture - Built on proven microservices principles

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Architecture

OpenFrame uses a modern microservices architecture with four key layers:

flowchart TB
    Client[Client Applications] --> LB[Load Balancer]
    LB --> Gateway[API Gateway]
    
    subgraph "Gateway Layer"
        Gateway --> GraphQL[GraphQL Engine]
        Gateway --> Auth[Auth Service]
    end
    
    subgraph "Processing Layer"
        Stream[Stream Processing] --> Kafka[Apache Kafka]
        Kafka --> |Analytics| Pinot[Apache Pinot]
        Kafka --> |Storage| Cassandra[Cassandra]
    end
    
    subgraph "Data Layer"
        GraphQL --> MongoDB[(MongoDB)]
        GraphQL --> Cassandra
        GraphQL --> Pinot
        GraphQL --> Redis[(Redis Cache)]
    end
    
    subgraph "Infrastructure Layer"
        Loki       --> Grafana
        Prometheus --> Grafana
    end
    
    style Gateway fill:#FFC109,stroke:#1A1A1A,color:#FAFAFA
    style Stream fill:#666666,stroke:#1A1A1A,color:#FAFAFA
    style MongoDB fill:#212121,stroke:#1A1A1A,color:#FAFAFA

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Quick Start

Get OpenFrame running locally:

CLI Usage

# Linux
./cli/openframe-linux-amd64 bootstrap
./cli/openframe-linux-amd64 bootstrap --non-interactive --verbose

# Windows
./cli/openframe-windows-amd64.exe bootstrap
./cli/openframe-windows-amd64.exe bootstrap --non-interactive --verbose

# macOS
./cli/openframe bootstrap
./cli/openframe bootstrap --non-interactive --verbose

For detailed CLI documentation, installation, and all available commands, see CLI Documentation.

Once started, OpenFrame will be available at:

• UI Dashboard: https://localhost

Screenshots

Dashboard Overview

Devices

Policies & Compliance

Technology Stack

Component	Technology	Purpose
Backend	Spring Boot 3.3 + Java 21	Core runtime & APIs
Frontend	Next.js 15 + React 19 + TypeScript 5.8	Modern web interface
Client	Rust + Tokio	Cross-platform system agent
API Layer	GraphQL + Netflix DGS	Unified data access
Message Queue	Apache Kafka 3.6	Event streaming
Databases	MongoDB + Cassandra + Pinot	Multi-model data storage
Cache	Redis	High-performance caching
Monitoring	Prometheus + Grafana + Loki	Observability stack

Roadmap

• Core microservices architecture
• GraphQL API with authentication
• Real-time stream processing
• Cross-platform Rust agent
• Multi-tenant support (Q2 2025)
• Advanced AI/ML integrations (Q3 2025)
• Edge computing capabilities (Q4 2025)
• Mobile companion app (2026)

Development Setup

Prerequisites

• Java: OpenJDK 21.0.1+
• Node.js: 18+ with npm
• Rust: 1.70+ with Cargo
• Docker: 24.0+ with Docker Compose
• Git: 2.42+

Local Development

Note: This project depends on openframe-oss-lib (version defined in pom.xml as <openframe.libs.version>). Maven authentication via GitHub Packages is required - set GITHUB_ACTOR and GITHUB_TOKEN environment variables before building.

# Clone the repository
git clone https://github.com/flamingo-stack/openframe-oss-tenant.git
cd openframe-oss-tenant

# Set up GitHub authentication
export GITHUB_ACTOR=your-github-username
export GITHUB_TOKEN=your-github-token

# Build backend services
mvn clean install

# Start frontend development server
cd openframe/services/openframe-frontend
npm install && npm run dev

# Build Rust agent
cd ../../client
cargo build --release

Running Tests

# Java tests
mvn test

# Frontend tests
cd openframe/services/openframe-frontend
npm run type-check

# Rust tests  
cd client
cargo test

Contributing

We love contributions! Please see our Contributing Guide for details.

Quick Contributing Steps:

1. Fork the project
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Documentation

Guide	Description
Getting Started	Quick start guide and basic concepts
Architecture	System design and components
Development Setup	Local development environment
API Reference	GraphQL schema and endpoints
Deployment	Production deployment guide
Operations	Monitoring and maintenance

FAQ

How does OpenFrame compare to other platforms?

OpenFrame uniquely combines data processing, API management, and AI capabilities in a single unified platform, while most alternatives focus on just one area.

What's the minimum hardware requirement?

For development: 8GB RAM, 4 CPU cores, 20GB storage. For production: 16GB RAM, 8 CPU cores, 100GB storage minimum.

Can I use OpenFrame with existing infrastructure?

Yes! OpenFrame is designed to integrate with existing systems through its flexible API layer and standard protocols.

Is there commercial support available?

Yes, enterprise support is available through Flamingo. Contact us for details.

Security

OpenFrame takes security seriously. We implement:

• OAuth 2.0 + JWT authentication
• AES-256 encryption for data at rest
• Comprehensive audit logging
• Multi-tenant isolation
• Rate limiting and circuit breakers
• Real-time security monitoring

Found a security issue? Please email security@flamingo.run instead of opening a public issue.

License

This project is licensed under the The Flamingo AI Unified License v1.0.

Acknowledgments

• Thanks to all our contributors
• Built with amazing open-source projects: Spring Boot, Apache Kafka, and many more
• Special thanks to the broader open-source community

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Built with 💛 by the Flamingo team

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