Foundations
Core concepts of distributed systems and software architecture.
System Design MasteryMaster the art of building scalable systems
Comprehensive guides, case studies, and real-world architectures.
Skip to content
🚀 Getting Started
How to Start
Follow this proven path from beginner to system design expert in structured phases.
Grasp the Foundations
Before designing any system, solidify your understanding of distributed systems concepts, CAP theorem, and core architecture principles.
Explore →Learn to Scale
Understand horizontal vs. vertical scaling, load balancing strategies, and how to design systems that handle millions of requests.
Explore →Master Databases
Choose the right database for the job. Learn SQL, NoSQL, NewSQL, indexing strategies, and database partitioning patterns.
Explore →Caching & Messaging
Speed up systems with caching layers (Redis, Memcached) and decouple services with message queues (Kafka, RabbitMQ).
Explore →Real-World Systems
Reverse-engineer production systems like Netflix, Uber, and WhatsApp. Understand their architectural decisions and trade-offs.
Explore →Interview Preparation
Practice structured system design interviews using the 8-step framework. Tackle mock problems with expert-level solutions.
Explore →🧠 Interview Framework
The 8-Step System Design Framework
A battle-tested, structured approach to tackle any system design problem — in interviews or at work.
01
Requirements Clarification
Define functional and non-functional requirements. Never assume — always ask.
- Functional requirements
- Non-functional requirements
- Scale constraints
- SLAs & SLOs
02
Capacity Estimation
Back-of-the-envelope calculations for storage, bandwidth, and compute needs.
- DAU/MAU estimates
- Read/write ratios
- Storage requirements
- Bandwidth needs
03
API Design
Define clean REST or gRPC API contracts before diving into implementation.
- REST endpoints
- Request/response schemas
- Versioning strategy
- Rate limiting
04
Database Design
Choose SQL vs. NoSQL and design schemas optimized for your access patterns.
- Schema design
- SQL vs NoSQL choice
- Indexing strategy
- Normalization
05
High-Level Architecture
Draw the big picture — services, data flows, clients, and external dependencies.
- Component diagram
- Data flow arrows
- Client interaction
- External APIs
06
Deep Dive Design
Go deep on the 2–3 most critical or complex components of your system.
- Core algorithm
- Critical path
- Data pipelines
- Service internals
07
Trade-offs & Bottlenecks
Identify failure points, discuss trade-offs, and propose mitigation strategies.
- Single points of failure
- CAP trade-offs
- Consistency models
- Fallback strategies
08
Monitoring & Observability
Define how you will observe, alert, and debug your system in production.
- Metrics (RED/USE)
- Distributed tracing
- Log aggregation
- Alerting strategy
🎯 Career Tracks
Choose Your Learning Path
Role-based learning tracks designed to match your career stage and goals.
Junior Engineer
4–6 weeks
Build a rock-solid foundation in distributed systems and core design principles.
- ✓ Foundations & CAP Theorem
- ✓ Databases (SQL + NoSQL)
- ✓ Basic Scalability
- ✓ Caching Fundamentals
Mid-Level Engineer
6–8 weeks
Level up with real-world system analysis and messaging architecture patterns.
- ✓ Microservices Architecture
- ✓ Message Queues & Kafka
- ✓ Real-World Systems
- ✓ Design Patterns
Senior / Staff Engineer
8–12 weeks
Master advanced architectures, case studies, and interview-ready system design.
- ✓ Case Studies (Netflix, Uber)
- ✓ Academic Research
- ✓ Interview Framework
- ✓ Trade-off Analysis