BharatMLStack
What is BharatMLStack?
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.
Our Vision
🎯 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
Running at Million Scale
BharatMLStack is battle-tested in production environments, powering:
1M+ feature vector retrievals per second across distributed deployments
across distributed deployments Sub-10ms latency for real-time feature retrieval
for real-time feature retrieval 99.99% uptime with auto-scaling and fault tolerance
with auto-scaling and fault tolerance Petabyte-scale feature storage and processing
feature storage and processing Multi-region deployments with global load balancing
Document
Core Components
📋 Current Releases
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
🚀 Horizon - Control Plane & Backend
The central control plane for BharatMLStack components, serving as the backend for Trufflebox UI.
Component orchestration : Manages and coordinates all BharatMLStack services
: Manages and coordinates all BharatMLStack services API gateway: Unified interface for all MLOps and workflows
🎨 Trufflebox UI - ML Management Console
Modern web interface for managing ML models, features, and experiments. Currently it supports:
Feature Registry : Centralized repository for feature definitions and metadata
: Centralized repository for feature definitions and metadata Feature Cataloging : Discovery and search capabilities for available features
: Discovery and search capabilities for available features Online Feature Store Control System : Management interface for feature store operations
: Management interface for feature store operations Approval Flows: Workflow management for feature deployment and changes
🗄️ Online Feature Store - Real-Time Features
High-performance feature store for real-time ML inference and training.
Real-time serving : Sub-10ms feature retrieval at scale
: Sub-10ms feature retrieval at scale Streaming ingestion : Process millions of feature updates per second
: Process millions of feature updates per second Feature Backward Compatible Versioning : Track and manage feature evolution
: Track and manage feature evolution Multi-source integration: Push from stream, batch and real-time sources
Key Differentiators
✨ Production-Ready : Battle-tested components used in high-traffic production systems
: Battle-tested components used in high-traffic production systems 🌐 Cloud Agnostic : Kubernetes-native, so deploy on the cloud you love
: Kubernetes-native, so deploy on the cloud you love 📊 Observability: Built-in monitoring, logging
Quick Start
🚀 Get started with BharatMLStack in minutes!
For comprehensive setup instructions, examples, and deployment guides, see our detailed Quick Start documentation:
📖 Quick Start Guide →
What You'll Find:
🐳 Docker Setup : Complete stack deployment with Docker Compose
: Complete stack deployment with Docker Compose 📊 Sample Data : Pre-configured examples to get you started
: Pre-configured examples to get you started 🔍 Health Checks : Verify your deployment is working
: Verify your deployment is working 📝 Step-by-Step Tutorials: From installation to first feature operations
TL;DR - One Command Setup:
# 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.sh
Then follow the Quick Start Guide for detailed setup and usage instructions.
Architecture
BharatMLStack follows a microservices architecture designed for scalability and maintainability. Several components are to be open-sourced
🚀 Quick Navigation
Component Documentation Quick Start Online Feature Store Docs Setup Go SDK Docs Examples Python SDK Docs Quickstart User Guide Docs Setup
Contributing
We welcome contributions from the community! Please see our Contributing Guide for details on how to get started.
Community & Support
💬 Discord : Join our community chat
: Join our community chat 🐛 Issues : Report bugs and request features on GitHub Issues
: Report bugs and request features on GitHub Issues 📧 Email: Contact us at [email protected]
License
BharatMLStack is open-source software licensed under the BharatMLStack Business Source License 1.1.
Built with ❤️ for the ML community from Meesho
If you find this useful, ⭐️ the repo — your support means the world to us!