Design Analysis of Netflix's Cloud‑Based Microservices Architecture

1 Introduction

Netflix serves over 167 million subscribers worldwide, consuming more than 15% of global internet bandwidth. To support this scale, the company migrated from its own data centers to AWS and rebuilt its platform using microservices, enabling high availability and global reach.

2 Architecture

The system consists of three major parts: the client (web browsers, iOS/Android apps, smart TVs), the backend (AWS services and Netflix‑specific microservices), and the Open Connect CDN.

Client – Uses SDKs to adapt streaming quality and select optimal Open Connect Appliances (OCAs) based on network conditions.

Backend – Runs entirely on AWS, leveraging EC2, S3, DynamoDB, Cassandra, EMR, Hadoop, Spark, Kafka, and custom Netflix tools. Key services include API Gateway (Zuul), Application APIs (signup, discovery, playback), and numerous stateless microservices that communicate via REST or gRPC.

Open Connect CDN – A network of OCAs deployed at ISPs and IXPs that store and stream video files, with a control plane that directs clients to the healthiest OCA.

2.1 Playback Flow

When a user clicks play, the client contacts the Playback service, which validates the request, queries the Steering service for a list of healthy OCAs, tests connectivity, and streams the video from the selected OCA.

2.2 Backend Architecture

Requests enter via AWS ELB, are routed to Zuul (API gateway) which performs routing, filtering, and service discovery (Eureka). The Application API orchestrates calls to microservices, using Hystrix for circuit breaking and EVCache for caching. Data is persisted in MySQL, Cassandra, Hadoop, Elasticsearch, and S3.

2.3 Stream Processing Pipeline

Netflix’s Keystone platform processes trillions of events daily, using Kafka for routing, and provides a SPaaS layer for engineers to build custom stream‑processing jobs.

3 Components

Detailed analysis of client, backend, microservices, data stores, and Open Connect is provided, highlighting how each component meets availability, latency, and scalability goals.

4 Design Goals

Global high availability

Resilience to network and system failures

Minimal latency across diverse network conditions

Scalable to high request volumes

5 Trade‑offs

Netflix chooses consistency over low latency and over high availability, using eventual‑consistent stores (Cassandra) and caching (EVCache) to meet performance targets.

6 Resilience

Chaos engineering practices inject failures into production to validate self‑healing mechanisms; Hystrix and Zuul provide retries, circuit breaking, and concurrency limits.

7 Scalability

AWS Auto Scaling and the Titus container platform enable horizontal scaling of EC2 instances; parallel execution in microservices and partitioned data stores (Cassandra, Elasticsearch) further support growth.

8 Conclusion

The study demonstrates that Netflix’s cloud‑native microservices architecture delivers high availability, low latency, strong scalability, and robust fault tolerance, serving millions of subscribers worldwide.