Netflix architecture overview in Microservices - Scalability & System Analysis

Scalability Analysis - Netflix architecture overview

Growth Table: Netflix Architecture Scaling

Scale	Users	Requests per Second	Data Volume	Infrastructure Changes
Small	100 users	~200 RPS	Few GBs of metadata	Single region, few microservices, basic caching
Medium	10,000 users	~20,000 RPS	TBs of metadata and video indexing	Multiple microservices, regional caching, CDN usage
Large	1,000,000 users	~2,000,000 RPS	Petabytes of video and metadata	Global CDN, multi-region deployment, microservice scaling, database sharding
Very Large	100,000,000 users	~200,000,000 RPS	Exabytes of data	Massive global distribution, advanced caching, multi-cloud, AI-driven load balancing

First Bottleneck

At small to medium scale, the database becomes the first bottleneck. Netflix stores user data, viewing history, and metadata which require fast reads and writes. As user count grows, the database faces high query loads and storage demands.

At large scale, network bandwidth and content delivery become bottlenecks due to massive video streaming traffic. The application servers and microservices also face CPU and memory pressure handling requests.

Scaling Solutions

• Database: Use sharding to split data across multiple databases. Employ read replicas to handle read-heavy workloads.
• Caching: Implement multi-layer caching (in-memory caches like Redis, CDN edge caches) to reduce database load and latency.
• Microservices: Scale horizontally by adding more instances behind load balancers. Use container orchestration (e.g., Kubernetes) for management.
• Content Delivery: Use a global CDN to serve video content close to users, reducing bandwidth and latency.
• Network: Optimize streaming protocols and compress data to reduce bandwidth usage.
• Multi-region Deployment: Deploy services in multiple geographic regions for fault tolerance and lower latency.

Back-of-Envelope Cost Analysis

For 1 million users streaming simultaneously:

• Requests per second: ~2 million (assuming 2 requests per second per user)
• Storage: Petabytes of video and metadata (Netflix stores thousands of movies and shows)
• Bandwidth: Video streaming at 3 Mbps per user -> 3 Mbps * 1M = 3 Tbps (~375 GB/s)
• Servers: Thousands of microservice instances and CDN edge servers globally

Interview Tip

Structure your scalability discussion by:

1. Identifying key components (database, microservices, CDN, network)
2. Estimating load and data growth at different scales
3. Pinpointing the first bottleneck and why it occurs
4. Proposing targeted scaling solutions for each bottleneck
5. Considering cost and complexity trade-offs
6. Discussing monitoring and fallback strategies

Self Check

Your database handles 1000 QPS. Traffic grows 10x to 10,000 QPS. What do you do first?

Answer: Add read replicas to distribute read queries and reduce load on the primary database. Also consider caching frequently accessed data to reduce database hits.

Key Result

Netflix architecture scales by evolving from a single-region microservice setup with a single database to a globally distributed system using sharded databases, multi-layer caching, and a global CDN to handle massive video streaming traffic efficiently.