Tower of Babel to Babel Fish Demo

A demonstration project showcasing the evolution from chaotic polyglot Kafka architecture to Schema Registry-managed data contracts.

🚀 Project Overview

This demo illustrates how Schema Registry solves cross-language serialization challenges in a distributed system. It demonstrates:

1. Tower of Babel - Serialization chaos across languages
2. Babel Fish - Schema Registry solution with code generation
3. Safe Evolution - Schema compatibility management
4. Prevented Disasters - Blocking incompatible changes

🏗️ System Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Order Service │    │ Inventory Svc   │    │ Analytics API   │
│   (Java/Spring) │    │ (Python/FastAPI)│    │ (Node.js/Express│
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         └───────────────────────┼───────────────────────┘
                                 │
                    ┌─────────────────┐
                    │ Kafka + Schema  │
                    │    Registry     │
                    └─────────────────┘

🛠️ Technology Stack

• Kafka: Confluent Platform 7.9.0 (KRaft mode, no Zookeeper)
• Schema Registry: Confluent Platform 7.9.0
• Order Service: Java 17 + Spring Boot 3.x + Gradle/Kotlin DSL
• Inventory Service: Python 3.9+ + FastAPI + uv
• Analytics API: Node.js 18+ + Express + TypeScript

🚀 Getting Started

Prerequisites

• Docker and Docker Compose
• Java 17+
• Python 3.9+
• Node.js 18+
• Make

Quick Start

# Set up local environment
make setup

# Check service status
make status

# Clean up everything
make clean

📊 Demo Scenarios

1. Tower of Babel (Serialization Chaos)

Demonstrates cross-language serialization failures:

• Java Object Serialization → Python can't deserialize
• JSON field naming inconsistencies
• Type mismatches between languages

2. Babel Fish (Schema Registry Solution)

Shows how Schema Registry enables:

• Centralized schema management
• Automatic code generation
• Type safety across languages

3. Safe Evolution (Schema Compatibility)

Demonstrates how Schema Registry enables:

• Adding optional fields safely
• Backward/forward compatibility
• Automatic code regeneration

4. Prevented Disasters (Breaking Changes)

Shows how Schema Registry prevents:

• Removing required fields
• Incompatible type changes
• Other breaking schema modifications

📁 Project Structure

tower-of-babel/
├── docker-compose.yml          # Local Kafka + Schema Registry
├── docker-compose.cloud.yml    # Confluent Cloud configuration
├── Makefile                    # Automation with emoji/colors
├── schemas/                    # Central Avro schema repository
├── services/
│   ├── order-service/          # Java/Spring Boot
│   ├── inventory-service/      # Python/FastAPI
│   └── analytics-api/          # Node.js/Express
├── scripts/                    # Utility scripts
└── docs/                       # Documentation

📝 Documentation

• Requirements
• Implementation Plan
• Task List

🧪 Development Status

• ✅ Phase 1: Infrastructure Foundation
• ✅ Phase 2: Schema-First Development
• ✅ Phase 3: Broken Services Implementation
• ✅ Phase 4: Schema Registry Integration
• 🔜 Phase 5: Evolution and Automation
• 🔜 Phase 6: Polish and Testing