Inside Netflix’s Tech Stack: How They Power Billions of Streams

Netflix, as one of the world’s largest streaming platforms, supports billions of users with a robust technical architecture. This article explains Netflix’s technology stack and the secrets behind it.

Cross‑platform experience on mobile and web

To provide seamless cross‑platform experience, Netflix uses different solutions for mobile and web.

Mobile:

Swift (iOS): Swift is the primary language for Netflix’s iOS app, valued for its simplicity, efficiency and safety.

Kotlin (Android): Kotlin, the officially supported Android language, is widely used in Netflix’s Android app.

Web:

React: Netflix builds its web application with React, leveraging componentization and virtual DOM for high‑performance, reusable UI.

The bridge between front‑end and back‑end: GraphQL

For data exchange, Netflix adopts GraphQL, which lets clients request exactly the data they need, avoiding over‑fetching and the “request waterfall” problem of REST APIs.

Backend foundation: Microservices architecture

Netflix’s backend relies on a microservices architecture supported by several open‑source components.

Zuul: Netflix’s open‑source API gateway handling routing, filtering and monitoring.

Eureka: Service registry and discovery component for dynamic inter‑service calls.

Spring Boot: Rapid development framework based on Spring, simplifying configuration and deployment of microservices.

Diverse data storage options

To meet massive data storage and processing needs, Netflix uses multiple database technologies.

EVCache: Open‑source in‑memory cache system for frequently accessed data.

Cassandra: Distributed NoSQL database offering high availability, scalability and fault tolerance.

CockroachDB: Open‑source distributed SQL database with strong consistency and scalability.

Messaging and streaming transport

Real‑time data processing and streaming are core to Netflix; the following technologies are employed:

Apache Kafka: High‑throughput distributed message queue for user behavior and monitoring streams.

Flink: Netflix’s open‑source stream processing platform built on Kafka for real‑time analytics.

Video storage and delivery optimization

To handle massive video libraries, Netflix uses:

Amazon S3: Object storage service for reliable, scalable, low‑cost video files.

Open Connect: Netflix’s own global CDN that caches video close to users to reduce latency.

Data processing and visualization tools

For extracting value from large datasets, Netflix employs:

Apache Flink: Distributed stream processing engine for real‑time analysis.

Apache Spark: Distributed computing framework for large‑scale data processing and machine learning.

Tableau: Visualization tool for interactive dashboards and reports.

Amazon Redshift: Cloud data warehouse for storing and analyzing structured data.

CI/CD automation arsenal

To improve development efficiency and delivery quality, Netflix uses a CI/CD pipeline with various tools:

JIRA: Project management and bug tracking.

Confluence: Team collaboration and documentation.

PagerDuty: Incident response platform for monitoring and alerts.

Jenkins: Continuous integration for automated builds, tests and deployments.

Gradle: Build tool for dependency and build management.

Chaos Monkey: Open‑source chaos engineering tool to simulate failures and test resilience.

Spinnaker: Open‑source continuous delivery platform for automated deployments across clouds.

Atlas: Monitoring system for collecting and visualizing metrics.

Conclusion

Netflix’s tech stack continuously evolves with business growth and technological advances. Its engineers constantly explore new technologies to meet rising user demand and technical challenges.

Analyzing Netflix’s architecture shows that a successful streaming platform depends on strong technical foundations, offering valuable lessons for other internet companies.