Introduction
This video lecture presents a comprehensive high-level system design for a ride-hailing platform similar to Uber or Ola (a distributed, real-time ride sharing service). It is structured to help learners understand how to architect a large-scale application that supports dynamic matching of riders and drivers, real-time location tracking, scalable dispatch systems, and fault-tolerant infrastructure — all of which are critical in high-throughput, low-latency systems.
The course begins by outlining the core functional and non-functional requirements such as ride request handling, matching logic, GPS tracking, pricing, and surge management. It then progresses through architectural components including API gateways, dispatch optimization, real-time communication channels (e.g., WebSockets), consistent data sharding, and backend persistence strategies.
Key learning objectives include:
- Understanding system requirements for a real-time, location-based service at global scale.
- Architectural decomposition into microservices and subsystems (dispatch, tracking, notifications).
- Designing for scale, resilience, and low latency — leveraging caching, message queues, and fault isolation.
- Applying principles of distributed systems such as sharding, consensus, and event-driven workflows.
This content is highly relevant for engineers and architects preparing for system design interviews or building real-time applications that must operate under massive concurrent load.
Course Instructor
