BharatMLStack is a comprehensive, production-ready machine learning infrastructure platform designed to democratize ML capabilities across India and beyond. Our mission is to provide a robust, scalable, and accessible ML stack that empowers organizations to build, deploy, and manage machine learning solutions at massive scale.
🎯 Democratize Machine Learning: Make advanced ML infrastructure accessible to organizations of all sizes 🚀 Scale Without Limits: Built to handle millions of requests per second with enterprise-grade reliability 🇮🇳 India-First Approach: Optimized for Indian market needs while maintaining global standards ⚡ Real-Time Intelligence: Enable instant decision-making with sub-millisecond feature serving 🔧 Developer-Friendly: Intuitive APIs and interfaces that accelerate ML development cycles
BharatMLStack is battle-tested in production environments, powering:
- 1M+ feature vector retrievals per second across distributed deployments
- Sub-10ms latency for real-time feature retrieval
- 99.99% uptime with auto-scaling and fault tolerance
- Petabyte-scale feature storage and processing
- Multi-region deployments with global load balancing
| Component | Version | Description |
|---|---|---|
| 🚀 Horizon | v1.0.0 |
Control Plane & Backend |
| 🎨 Trufflebox UI | v1.0.0 |
ML Management Console |
| 🗄️ Online Feature Store | v1.0.0 |
Real-Time Features |
| 🐹 Go SDK | v1.0.0 |
Go Client Library |
| 🐍 Python SDK | v1.0.1 |
Python Client Library |
The central control plane for BharatMLStack components, serving as the backend for Trufflebox UI.
- Component orchestration: Manages and coordinates all BharatMLStack services
- API gateway: Unified interface for all MLOps and workflows
Modern web interface for managing ML models, features, and experiments. Currently it supports:
- Feature Registry: Centralized repository for feature definitions and metadata
- Feature Cataloging: Discovery and search capabilities for available features
- Online Feature Store Control System: Management interface for feature store operations
- Approval Flows: Workflow management for feature deployment and changes
High-performance feature store for real-time ML inference and training.
- Real-time serving: Sub-10ms feature retrieval at scale
- Streaming ingestion: Process millions of feature updates per second
- Feature Backward Compatible Versioning: Track and manage feature evolution
- Multi-source integration: Push from stream, batch and real-time sources
- ✨ Production-Ready: Battle-tested components used in high-traffic production systems
- 🌐 Cloud Agnostic: Kubernetes-native, so deploy on the cloud you love
- 📊 Observability: Built-in monitoring, logging
🚀 Get started with BharatMLStack in minutes!
For comprehensive setup instructions, examples, and deployment guides, see our detailed Quick Start documentation:
- 🐳 Docker Setup: Complete stack deployment with Docker Compose
- 📊 Sample Data: Pre-configured examples to get you started
- 🔍 Health Checks: Verify your deployment is working
- 📝 Step-by-Step Tutorials: From installation to first feature operations
# Clone and start the complete stack
git clone https://github.com/Meesho/BharatMLStack.git
cd BharatMLStack/quick-start
ONFS_VERSION=<version> HORIZON_VERSION=<version> TRUFFLEBOX_VERSION=<version> ./start.shThen follow the Quick Start Guide for detailed setup and usage instructions.
BharatMLStack follows a microservices architecture designed for scalability and maintainability. Several components are to be open-sourced
| Component | Documentation | Quick Start |
|---|---|---|
| Online Feature Store | Docs | Setup |
| Go SDK | Docs | Examples |
| Python SDK | Docs | Quickstart |
| User Guide | Docs | Setup |
We welcome contributions from the community! Please see our Contributing Guide for details on how to get started.
- 💬 Discord: Join our community chat
- 🐛 Issues: Report bugs and request features on GitHub Issues
- 📧 Email: Contact us at ml-oss@meesho.com
BharatMLStack is open-source software licensed under the BharatMLStack Business Source License 1.1.