A real-time ride booking simulation system built using FastAPI, Azure Event Hub, and Python.
This project demonstrates how ride booking events can be generated, streamed, and processed in a modern data engineering workflow.
This application simulates an Uber-style ride booking platform where:
- Users can book rides through a web interface
- Ride data is dynamically generated using Faker
- Booking events are streamed into Azure Event Hub
- FastAPI powers the backend APIs
- HTML/CSS frontend provides an interactive user experience
The project showcases a simple but realistic real-time event streaming architecture commonly used in modern data engineering systems.
- Python
- FastAPI
- Azure Event Hub
- Faker
- HTML/CSS
- Jinja2 Templates
- Uvicorn
- 🚗 Ride booking simulation
- ⚡ Real-time event streaming
- 📡 Azure Event Hub integration
- 🎨 Modern responsive frontend
- 🔄 Dynamic ride generation using Faker
- 🧩 FastAPI backend architecture
The architecture demonstrates a real-time event-driven pipeline where ride booking events are generated from the web application, streamed through Azure Event Hub, processed using Spark/Databricks, and transformed into analytical star-schema structures for downstream analytics and reporting.
The project uses Azure Data Factory (ADF) to orchestrate and automate the real-time data ingestion workflow. The pipeline dynamically processes incoming ride booking files/events and triggers downstream streaming activities for scalable data processing.
The homepage provides a modern ride booking interface where users can initiate ride requests that trigger real-time event streaming workflows.
After booking a ride, the application confirms successful event ingestion and demonstrates the end-to-end integration between the frontend, FastAPI backend, and Azure Event Hub.
git clone https://github.com/Anushka285/Uber_Data_Engineer_Project.git