System Design Roadmap
Learn to design large-scale distributed systems and ace system design interviews.
Prerequisites
- Strong programming fundamentals
- Understanding of data structures and algorithms
- Basic networking knowledge
- Database fundamentals
Phase 1: Fundamentals
Networking Basics
- HTTP/HTTPS protocols
- TCP/IP, DNS, CDN
- Load balancing
- Reverse proxy vs forward proxy
Database Concepts
- SQL vs NoSQL
- ACID properties
- CAP theorem
- Database indexing
- Normalization and denormalization
Caching
- Cache strategies (LRU, LFU)
- Cache invalidation
- CDN caching
- Redis and Memcached
Phase 2: Core Concepts
Scalability
- Vertical vs horizontal scaling
- Load balancing strategies
- Database replication
- Database sharding
- Consistent hashing
Reliability & Availability
- Single points of failure
- Redundancy
- Failover mechanisms
- Disaster recovery
- High availability patterns
Performance
- Latency vs throughput
- Performance metrics
- Bottleneck identification
- Performance optimization techniques
Phase 3: System Components
Storage Systems
- Object storage (S3)
- Block storage
- File systems
- Distributed file systems (HDFS)
Message Queues
- Pub/sub patterns
- Message brokers (Kafka, RabbitMQ)
- Event-driven architecture
- Stream processing
API Design
- REST vs GraphQL
- API versioning
- Rate limiting
- Authentication & authorization (OAuth, JWT)
Phase 4: Advanced Topics
Microservices
- Service decomposition
- Service discovery
- API gateway
- Circuit breakers
- Saga pattern
Data Processing
- Batch processing
- Stream processing
- MapReduce
- ETL pipelines
- Data warehousing
Monitoring & Observability
- Logging strategies
- Metrics and monitoring (Prometheus, Grafana)
- Distributed tracing
- Alerting systems
Phase 5: Design Patterns
Common System Designs
- URL shortener
- News feed system
- Chat application
- Video streaming platform
- E-commerce system
- Search engine
- Recommendation system
- Notification system
Design Principles
- Design for failure
- Incremental scalability
- Trade-offs and constraints
- Cost considerations
Resources
- Books: Designing Data-Intensive Applications by Martin Kleppmann
- Courses: Grokking the System Design Interview
- Practice: System Design Primer on GitHub
- Videos: YouTube channels (ByteByteGo, Gaurav Sen)
Interview Preparation
Framework
- Clarify requirements and constraints
- Estimate scale (users, data, QPS)
- Define system interface (APIs)
- High-level design
- Detailed component design
- Identify bottlenecks
- Scale and optimize
Tips
- Always ask clarifying questions
- Consider trade-offs
- Think about edge cases
- Discuss multiple approaches
- Consider cost implications
- Focus on scalability
Timeline
Estimated completion: 3-6 months with consistent study and practice