Netflix System Design
Netflix is a streaming service that provides on-demand video content to millions of users worldwide. Let's analyze its system design.
System Requirements
Functional Requirements
- User authentication and profiles
- Video streaming
- Content recommendations
- Search functionality
- User preferences and watch history
Non-Functional Requirements
- High availability (99.99%)
- Low latency streaming
- Global content delivery
- Scalability for peak loads
- Data consistency
Architecture
High-Level Design
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Client │ │ API │ │ Services │
│ Apps │────▶│ Gateway │────▶│ Layer │
└─────────────┘ └─────────────┘ └─────────────┘
│ │
▼ ▼
┌─────────────┐ ┌─────────────┐
│ CDN │ │ Storage │
│ Network │ │ Layer │
└─────────────┘ └─────────────┘
Components
-
Client Applications
- Web browsers
- Mobile apps
- Smart TV apps
- Game consoles
-
API Gateway
- Request routing
- Authentication
- Rate limiting
- Load balancing
-
Microservices
- User Service
- Content Service
- Recommendation Service
- Search Service
- Playback Service
-
Content Delivery
- AWS CloudFront
- Netflix Open Connect
- Edge servers
- Caching strategy
-
Storage
- S3 for video storage
- Cassandra for user data
- Redis for caching
- Elasticsearch for search
Data Models
User Profile
{
"user_id": "123",
"email": "[email protected]",
"profiles": [
{
"profile_id": "p1",
"name": "John",
"preferences": {
"language": "en",
"maturity_level": "PG-13"
},
"watch_history": [
{
"content_id": "movie123",
"timestamp": "2023-01-01T00:00:00Z",
"progress": 3600
}
]
}
]
}
Content
{
"content_id": "movie123",
"title": "Example Movie",
"type": "movie",
"genres": ["Action", "Adventure"],
"languages": ["en", "es"],
"qualities": ["SD", "HD", "4K"],
"segments": [
{
"segment_id": "s1",
"quality": "HD",
"url": "https://cdn.netflix.com/movie123/HD/s1"
}
]
}
Key Features
Video Streaming
-
Adaptive Bitrate Streaming
- Multiple quality levels
- Dynamic switching
- Bandwidth detection
- Buffer management
-
Content Delivery
- Edge caching
- Pre-fetching
- Regional distribution
- Load balancing
Recommendation System
- Collaborative filtering
- Content-based filtering
- Machine learning models
- A/B testing
Scaling Strategies
Content Delivery
- Global CDN network
- Edge servers
- Caching at multiple levels
- Predictive pre-loading
Database Scaling
- Sharding by region
- Read replicas
- Caching layer
- Data partitioning
Challenges
-
Content Delivery
- Bandwidth management
- Quality of service
- Regional restrictions
- Cost optimization
-
Personalization
- Real-time recommendations
- User privacy
- Data consistency
- Performance
-
Global Scale
- Regional compliance
- Content licensing
- Network latency
- Infrastructure costs