🏗️ System Design at Scale
Overview
In this phase, we'll tackle the challenge of designing systems that can scale from hundreds to millions of users. Students will work in teams to develop comprehensive system architectures that demonstrate an understanding of distributed systems principles in real-world scenarios.
📋 Learning Objectives
- Apply distributed systems concepts to practical, industry-relevant problems
- Design scalable architectures that evolve with increasing user demands
- Identify and resolve bottlenecks in system performance
- Make informed trade-offs between consistency, availability, and partition tolerance
- Document and present technical designs effectively
🔄 Methodology
Each team will:
- Select a Project: Choose from the example projects listed below
- Design in Stages: Create a three-stage scaling plan:
- Stage 1: Initial design for minimal viable product (~1,000 users)
- Stage 2: Enhanced design for moderate growth (~100,000 users)
- Stage 3: Full-scale architecture for massive adoption (~1,000,000+ users)
- Document Components: For each stage, specify:
- Infrastructure requirements (servers, load balancers, CDNs)
- Database choices and data modeling approaches
- Caching strategies and implementation
- API design and service boundaries
- Monitoring and observability solutions
- Present Solutions: Deliver a comprehensive presentation with diagrams, justifications for design choices, and analysis of potential failure points
🚀 Example Projects
Each project presents unique scaling challenges that will test your understanding of distributed systems:
| Project | Key Challenges |
|---|---|
| 1. Twitter Timeline & Search | Real-time updates, high read throughput, efficient search indexing |
| 2. URL Shortener (like Bit.ly) | High availability, redirect performance, analytics tracking |
| 3. Personal Finance App (like Mint.com) | Data security, third-party integrations, background processing |
| 4. Social Network Data Structure | Complex relationships, feed generation, privacy controls |
| 5. Search Engine Key-Value Store | Distributed indexing, query optimization, fault tolerance |
| 6. E-commerce Category Rankings | Real-time analytics, caching strategies, consistency requirements |
| 7. Web Crawler | Distributed work coordination, politeness policies, data processing pipeline |
📚 Resources
- System Design Primer - Comprehensive resource for system design concepts
- AWS Scaling Example - Reference implementation for scaling on AWS
- System Design - Recommended reading for System Design
- Advanced System Design - Recommended reading for Advance System Design