System Design Learning Hub

What is System Design?

How it works

System Design Overview
How it works
  1. Gather requirements
  2. Sketch components and flows
  3. Evaluate trade-offs
  4. Iterate and stress test

🎯 Core Definition

System design is the process of defining the architecture, modules, interfaces, and data for a system to satisfy specified requirements. It's like being an architect for software systems - you need to plan, design, and build structures that can withstand various loads and conditions.
🏛️

Architecture Planning

Designing the overall structure and high-level components that work together harmoniously

  • Identify major components
  • Define component relationships
  • Plan for scalability and growth
🧩

Component Design

Breaking down into manageable, reusable parts with clear responsibilities

  • Single responsibility principle
  • Loose coupling between components
  • High cohesion within components
🔗

Interface Design

How components communicate and interact through well-defined contracts

  • API design and protocols
  • Data formats and schemas
  • Error handling strategies
💾

Data Design

How data flows, is stored, processed, and maintained throughout the system

  • Data models and schemas
  • Storage strategies
  • Data flow optimization

🚀 Why Learn System Design?

Transform Your Engineering Career

System design skills are the difference between building toys and building systems that serve millions

⚡

Build Scalable Applications

Essential for creating systems that grow with your business from 100 to 100 million users

Performance Scalability Growth
💼

Ace Technical Interviews

Critical skill for senior engineering positions at top tech companies

FAANG Senior Roles Leadership
🧠

Understand Trade-offs

Make informed decisions in software engineering with deep understanding of implications

Decision Making Architecture Strategy
🛡️

Build Robust Systems

Create maintainable, fault-tolerant applications that stand the test of time

Reliability Maintainability Quality

🏗️ Key Design Principles

The Four Pillars of System Design

These fundamental principles guide every architectural decision

📈

Scalability

Handle increased load gracefully as your system grows

Horizontal Scaling

  • Add more servers to handle load
  • Distribute processing across machines
  • No single point of bottleneck

Vertical Scaling

  • Upgrade existing server hardware
  • Increase CPU, RAM, storage
  • Simple but has limits

Auto-scaling

  • Automatically adjust capacity
  • Based on demand metrics
  • Cost-effective resource usage
🔄

Reliability

System continues to work correctly even when failures occur

Fault Tolerance

  • Graceful handling of component failures
  • Redundant systems and backups
  • Circuit breakers and timeouts

Recovery Mechanisms

  • Automatic failover systems
  • Data backup and restoration
  • Health monitoring and alerts

Graceful Degradation

  • Reduce functionality vs complete failure
  • Prioritize critical features
  • Maintain core user experience
🟢

Availability

System remains operational and accessible when needed

High Availability Targets

  • 99.9% (8.76 hours downtime/year)
  • 99.99% (52.56 minutes downtime/year)
  • 99.999% (5.26 minutes downtime/year)

Load Balancing

  • Distribute traffic across servers
  • Health checks and routing
  • Geographic distribution

Redundancy

  • Multiple instances of services
  • Database replication
  • Multi-region deployments
🔐

Consistency

All nodes see the same data at the same time

Strong Consistency

  • Immediate consistency across nodes
  • ACID transaction properties
  • Higher latency but guaranteed accuracy

Eventual Consistency

  • System becomes consistent over time
  • Lower latency, higher availability
  • Acceptable for many use cases

Distributed Consensus

  • Paxos and Raft algorithms
  • Leader election mechanisms
  • Conflict resolution strategies

📊 System Design Process

Structured Approach to System Design

Follow this proven methodology to tackle any system design challenge

1

📋 Requirements Gathering

15-20 minutes

Understand what you're building and the constraints

Functional Requirements
  • What features does the system need?
  • What are the core user workflows?
  • What operations should be supported?
Non-Functional Requirements
  • How many users will use the system?
  • What is the expected read/write ratio?
  • What are the latency requirements?
  • What is the availability requirement?
2

📏 Capacity Estimation

10-15 minutes

Calculate storage, bandwidth, and compute needs

Traffic Estimation
  • Daily/Monthly active users
  • Requests per second (read/write)
  • Peak traffic patterns
Storage Estimation
  • Data size per user/record
  • Total storage over time
  • Backup and replication overhead
Bandwidth Estimation
  • Data transfer per request
  • Network bandwidth requirements
  • CDN and caching impact
3

🎨 High-Level Design

15-20 minutes

Create overall architecture and main components

Core Components
  • Web servers and load balancers
  • Application servers
  • Databases and data stores
  • Caching layers
Data Flow
  • User request flow
  • Data read/write paths
  • Inter-service communication
4

🔍 Detailed Design

15-20 minutes

Dive deep into each component and interface

Database Schema
  • Table design and relationships
  • Indexing strategy
  • Partitioning and sharding
API Design
  • RESTful endpoints
  • Request/response formats
  • Authentication and authorization
Algorithm Design
  • Core algorithms and data structures
  • Optimization techniques
  • Caching strategies
5

⚖️ Scale & Optimize

10-15 minutes

Identify bottlenecks and optimization opportunities

Bottleneck Analysis
  • Database performance issues
  • Network latency concerns
  • CPU and memory constraints
Scaling Solutions
  • Read replicas and write sharding
  • Microservices decomposition
  • CDN and edge computing
Monitoring & Observability
  • Metrics and alerting
  • Logging and tracing
  • Performance monitoring

🎯 Common System Design Questions

🟢 Beginner Level

  • Design a URL shortener (like bit.ly)
  • Design a simple cache system
  • Design a basic chat application
  • Design a parking lot system

🟡 Intermediate Level

  • Design Instagram or Twitter
  • Design a ride-sharing service
  • Design a search engine
  • Design a notification system

🔴 Advanced Level

  • Design a distributed file system
  • Design a payment processing system
  • Design a video streaming platform
  • Design a global chat system

🎯 Ready to Start Your Journey?

Begin with understanding scalability concepts and core principles. Each topic builds upon the previous ones to give you a comprehensive understanding of system design.

Start with Scalability → View Full Roadmap
Learning Journey

🧭 High‑Level Design (HLD) at a glance

High‑Level Design is the macro view of your system: what the major building blocks are, how they talk, and where they run. It aligns stakeholders and turns requirements into an architectural blueprint.

🏗️

Core Components

  • System Architecture: Services, data stores, and how requests flow
  • Modules & Boundaries: Clear responsibilities and interfaces
  • Data Flows: What data moves where (DFDs, sequence diagrams)
  • Interfaces: External APIs and user entry points
  • Tech Stack: Languages, frameworks, databases, messaging
  • Deployment: Regions, networks, cloud resources, topology
⚖️

HLD vs LLD

  • HLD: Architectural choices and trade‑offs (C/A/C, latency, cost)
  • LLD: Classes, APIs, data structures, and algorithms
  • Think what and where (HLD) before how (LLD)
📝

HLD Deliverables

  • Context + component diagrams with data paths
  • Interface contracts and SLAs
  • Capacity and scaling assumptions
  • Deployment/infra view and run‑time concerns
1

📋 Capture Requirements

Functional goals plus SLOs for latency, availability, and throughput.

2

📏 Capacity Estimation

Traffic, storage, read/write mix, growth, and peak patterns.

3

🔌 Interfaces & Protocols

HTTP/HTTPS methods, streaming (WebSockets/SSE), or polling where needed.

4

⚖️ Resiliency & Limits

Rate limiting, retries/timeouts, circuit breakers, redundancy, and failover.

5

⚡ Performance Levers

Caching (browser, CDN, app, DB), pagination, async queues, and load balancing.

6

🔭 Observability

Structured logging, metrics, tracing, and health checks with alerts.