Categories: System DesignTechnology

Netflix Tech Stack: A Comprehensive Overview

Netflix, the world’s leading streaming service, relies on a robust and intricate technology stack to deliver high-quality video content to millions of users globally. Understanding the components and architecture of Netflix Tech Stack can provide valuable insights into how large-scale, high-performance systems are designed and managed. This guide will explore the various technologies and tools Netflix uses across different layers of its tech stack, including DevOps, Mobile, Frontend, Backend, Streaming, and Data Management.

Netflix's Tech Stack

This post is based on research from many Netflix engineering blogs and open-source projects. If you come across any inaccuracies, please feel free to inform us.

Mobile and Web

Mobile Development

Netflix has adopted Swift and Kotlin to build native mobile apps for iOS and Android, respectively. These languages offer robust features and performance benefits that enhance the user experience on mobile devices.

Swift: Swift is the language of choice for iOS app development. It is known for its performance, safety, and expressive syntax, making it easier for developers to write reliable and maintainable code. Swift’s powerful type system and error handling capabilities ensure fewer crashes and bugs in the app, contributing to a smooth user experience.
Kotlin: Kotlin is used for Android app development. It is fully interoperable with Java, which allows developers to use existing Java libraries and frameworks. Kotlin is designed to be concise, reducing the amount of boilerplate code, and it includes many modern features such as null safety, extension functions, and coroutines, which help in writing clean and efficient code.

Web Development

For its web application, Netflix uses React, a popular JavaScript library for building user interfaces. React allows developers to create large web applications that can update and render efficiently in response to data changes.

React: React’s component-based architecture promotes reusability and makes it easier to manage complex UIs. By using a virtual DOM, React ensures high performance by minimizing the number of direct manipulations to the real DOM. React also has a strong ecosystem, with tools like React Router for handling navigation and Redux for state management, further enhancing the development process

Key Technologies:

Swift: For iOS app development.
Kotlin: For Android app development.
React: For web application development.

Frontend/Server Communication

For efficient communication between the frontend and backend, Netflix utilizes GraphQL. This query language for APIs provides a flexible and efficient way to fetch only the necessary data, reducing the number of requests and improving performance.

GraphQL

GraphQL, developed by Facebook, allows clients to request exactly the data they need, nothing more and nothing less. This reduces the amount of data transferred over the network and minimizes the risk of over-fetching or under-fetching data.

Efficient Data Fetching: With REST APIs, fetching related data often requires multiple requests to different endpoints. GraphQL consolidates these into a single request, reducing the number of round trips and improving performance.
Strongly Typed Schema: GraphQL APIs are defined by a schema that specifies the types of data that can be queried. This schema serves as a contract between the client and server, providing clear documentation and enabling tools for validation and auto-completion.
Real-time Capabilities: GraphQL supports subscriptions, allowing clients to receive real-time updates whenever specific data changes. This is particularly useful for features like live notifications and activity feeds.

Key Technology:

GraphQL: For API queries and frontend/server communication.

Backend Services

Netflix’s backend infrastructure is powered by a combination of powerful tools and frameworks. Zuul and Eureka are essential components for API routing and service discovery, respectively. Additionally, the Spring Boot framework is widely used for building microservices.

Zuul

Zuul is Netflix’s edge service that provides dynamic routing, monitoring, resiliency, security, and more. It acts as a gateway between client requests and various backend services, ensuring that requests are routed efficiently.

Dynamic Routing: Zuul dynamically routes requests to different backend services based on the request’s metadata. This allows Netflix to manage traffic efficiently and ensures that users are directed to the appropriate service.
Security: Zuul provides security features such as authentication and authorization, protecting backend services from unauthorized access.
Resiliency: Zuul helps in handling failures gracefully by retrying requests, managing timeouts, and providing fallback mechanisms.

Eureka

Eureka is a service discovery tool used by Netflix to ensure that microservices can find and communicate with each other. It acts as a registry where services can register themselves and discover other services.

Service Registration: Microservices register themselves with Eureka, providing their network location and metadata. This allows other services to find and communicate with them without hardcoding their locations.
Health Checks: Eureka performs periodic health checks on registered services to ensure they are functioning correctly. Unhealthy services are removed from the registry, preventing them from receiving traffic.

Spring Boot

Spring Boot is a framework that simplifies the development of production-ready applications. It provides a set of conventions and defaults, reducing the amount of configuration required and enabling developers to focus on writing business logic.

Microservices: Spring Boot is well-suited for building microservices due to its lightweight nature and support for various cloud-native patterns. It integrates seamlessly with Netflix OSS components like Zuul and Eureka.
Rapid Development: Spring Boot’s opinionated approach provides sensible defaults, enabling rapid development and reducing boilerplate code.

Key Technologies:

Zuul: For API routing and filtering.
Eureka: For service discovery.

Spring Boot: For building robust microservices.

Databases

To handle the vast amount of data generated and consumed by Netflix users, the company employs a variety of databases. EVCache, Cassandra, and CockroachDB are among the primary databases used for different purposes, from caching frequently accessed data to storing large-scale distributed data.

EVCache

EVCache is a distributed in-memory caching system built on top of Memcached. It is designed to provide fast and reliable caching for high-traffic applications.

High Performance: EVCache stores data in memory, enabling rapid access and reducing latency for read-heavy workloads.
Scalability: EVCache is designed to scale horizontally, allowing Netflix to handle large volumes of traffic and data.

Cassandra

Cassandra is a highly scalable NoSQL database designed for handling large amounts of structured data across many commodity servers.

High Availability: Cassandra’s peer-to-peer architecture ensures high availability and fault tolerance. Data is replicated across multiple nodes, allowing the database to remain operational even if some nodes fail.
Scalability: Cassandra scales linearly, meaning that adding more nodes to a cluster increases its capacity without degrading performance.

CockroachDB

CockroachDB is a distributed SQL database that combines the consistency and familiarity of traditional relational databases with the scalability and resilience of NoSQL databases.

Global Distribution: CockroachDB is designed to run across multiple datacenters and geographies, providing low-latency access to data for users worldwide.

Transactional Consistency: CockroachDB supports ACID transactions, ensuring data integrity and consistency across distributed environments.

Key Technologies:

EVCache: For caching and fast data retrieval.
Cassandra: A NoSQL database for handling large volumes of data.
CockroachDB: A distributed SQL database for high availability.

Messaging/Streaming

For messaging and real-time data streaming, Netflix employs Apache Kafka and Apache Flink. These technologies ensure that data is efficiently processed and streamed in real-time, supporting Netflix’s recommendation systems and other data-driven features.

Apache Kafka

Apache Kafka is a distributed streaming platform used for building real-time data pipelines and streaming applications.

Scalability: Kafka is designed to handle high throughput and can scale horizontally by adding more brokers to the cluster.
Durability: Kafka persists messages to disk and replicates them across multiple brokers, ensuring data durability and fault tolerance.
Flexibility: Kafka’s publish-subscribe model allows multiple consumers to process the same stream of messages independently, enabling various real-time analytics and monitoring applications.

Apache Flink

Apache Flink is a stream processing framework that enables real-time data analytics and event-driven applications.

Low Latency: Flink processes data in real-time with millisecond latency, making it suitable for time-sensitive applications such as fraud detection and recommendation engines.
Complex Event Processing: Flink supports complex event processing, allowing users to define sophisticated event patterns and correlations.

Key Technologies:

Apache Kafka: For distributed messaging and streaming.
Apache Flink: For real-time data processing and analytics.

Video Storage

Storing and delivering video content efficiently is critical for Netflix. The company uses AWS S3 and its own Open Connect content delivery network (CDN) to store and deliver video content with minimal latency.

AWS S3

Amazon S3 (Simple Storage Service) is an object storage service that provides scalable, durable, and secure storage for data.

Scalability: S3 can scale to store virtually unlimited amounts of data, making it ideal for storing Netflix’s vast video library.
Durability: S3 stores data across multiple devices and facilities, ensuring 99.999999999% (11 9’s) durability.

Open Connect

Netflix Open Connect is the company’s proprietary content delivery network (CDN) designed to deliver streaming video to customers with minimal latency and high reliability.

Edge Caching: Open Connect caches video content closer to users, reducing the distance data must travel and improving streaming performance.
Peering: Open Connect establishes direct peering relationships with ISPs, optimizing the delivery of video content and reducing congestion.

Key Technologies:

AWS S3: For scalable object storage.
Open Connect: Netflix’s proprietary CDN for efficient video delivery.

Data Processing

Netflix leverages powerful data processing technologies to analyze and process large datasets. Apache Flink and Apache Spark are used for data processing tasks, while Tableau is used for data visualization. AWS Redshift handles structured data warehouse information, enabling complex queries and analytics.

Apache Flink

Apache Flink is a stream processing framework that enables real-time data analytics and event-driven applications.

Real-time Processing: Flink processes data in real-time with millisecond latency, making it suitable for time-sensitive applications such as fraud detection and recommendation engines.
Stateful Computations: Flink supports stateful computations, allowing users to maintain and query state information across streaming data.

Apache Spark

Apache Spark is a unified analytics engine for large-scale data processing. It provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

In-memory Processing: Spark processes data in memory, significantly speeding up data processing tasks compared to traditional disk-based processing frameworks.
Rich Ecosystem: Spark includes libraries for SQL, machine learning, graph processing, and stream processing, making it a versatile tool for various data processing needs.

Tableau

Tableau is a data visualization tool that helps Netflix create interactive and shareable dashboards. It allows users to explore and analyze data visually.

Interactive Dashboards: Tableau’s drag-and-drop interface makes it easy to create interactive dashboards that can be shared across the organization.
Data Integration: Tableau integrates with various data sources, including databases, spreadsheets, and cloud services, allowing users to combine data from multiple sources for comprehensive analysis.

AWS Redshift

AWS Redshift is a fully managed data warehouse service that makes it easy to analyze large amounts of structured data using SQL.

Scalability: Redshift can scale from a few hundred gigabytes to a petabyte or more, enabling Netflix to handle large-scale data warehousing needs.
Performance: Redshift uses columnar storage and parallel query execution to provide high performance for complex queries and analytics.

Key Technologies:

Apache Flink: For real-time stream processing.
Apache Spark: For large-scale data processing.
Tableau: For data visualization and business intelligence.
AWS Redshift: For data warehousing and analytics.

CI/CD

Continuous Integration and Continuous Delivery (CI/CD) are crucial for Netflix’s development and deployment processes. The company employs various tools to automate and streamline these processes, ensuring rapid and reliable software delivery. Key tools include JIRA, Confluence, PagerDuty, Jenkins, Gradle, Chaos Monkey, Spinnaker, and Atlas.

JIRA

JIRA is a project management and issue tracking tool used by Netflix to plan, track, and manage software development projects.

Agile Project Management: JIRA supports agile methodologies, enabling teams to plan sprints, track progress, and manage backlogs.
Customization: JIRA’s flexible workflows and custom fields allow teams to tailor the tool to their specific needs and processes.

Confluence

Confluence is a collaboration tool used for documentation and knowledge sharing. It integrates with JIRA, providing a seamless experience for managing project documentation.

Collaboration: Confluence enables teams to collaborate on documents, share knowledge, and track changes in real-time.
Integration: Confluence integrates with various tools, including JIRA and Slack, streamlining communication and collaboration.

PagerDuty

PagerDuty is an incident management tool that helps Netflix monitor and respond to incidents in real-time.

Alerting: PagerDuty provides real-time alerting and notification, ensuring that the right people are informed of incidents promptly.
Incident Management: PagerDuty’s incident management workflows help teams respond to incidents efficiently and reduce downtime.

Jenkins

Jenkins is an open-source automation server used by Netflix for continuous integration and continuous delivery.

Automated Builds: Jenkins automates the build process, allowing developers to compile code, run tests, and create deployable artifacts automatically.

Plugin Ecosystem: Jenkins has a rich ecosystem of plugins that extend its functionality, integrating with various tools and services

Gradle

Gradle is a build automation tool used for building, testing, and deploying applications.

Flexibility: Gradle’s flexible build scripts allow teams to define custom build logic and workflows.
Performance: Gradle’s incremental build feature improves build performance by only rebuilding parts of the project that have changed.

Chaos Monkey

Chaos Monkey is a tool developed by Netflix to test the resilience of their systems by intentionally causing failures.

Resilience Testing: Chaos Monkey randomly terminates instances in Netflix’s production environment, ensuring that the system can handle failures gracefully.
Automated Testing: Chaos Monkey runs continuously, providing ongoing validation of the system’s resilience.

Spinnaker

Spinnaker is a multi-cloud continuous delivery platform that automates the deployment process.

Deployment Pipelines: Spinnaker enables teams to define complex deployment pipelines, automating the release process from code commit to production.
Multi-cloud Support: Spinnaker supports deploying applications to multiple cloud providers, including AWS, Google Cloud, and Kubernetes.

Atlas

Atlas is an application monitoring and performance tracking tool developed by Netflix.

Real-time Monitoring: Atlas provides real-time monitoring of Netflix’s applications, collecting and visualizing metrics to help teams identify and resolve performance issues.
Custom Dashboards: Atlas’s customizable dashboards enable teams to create tailored views of their application metrics.

Key Technologies:

JIRA: For issue tracking and project management.
Confluence: For documentation and collaboration.
PagerDuty: For incident management.
Jenkins: For automated build and deployment.
Gradle: For build automation.
Chaos Monkey: For testing system resilience.
Spinnaker: For multi-cloud continuous delivery.
Atlas: For application monitoring and performance tracking.

Conclusion

Netflix’s technology stack is a testament to the company’s commitment to delivering high-quality, reliable, and scalable services to its users. By leveraging a wide range of cutting-edge technologies across various domains, Netflix ensures that it remains at the forefront of the streaming industry. Understanding this tech stack not only highlights the complexity and efficiency of Netflix’s operations but also provides valuable insights for developers and engineers looking to build robust systems.

From mobile development with Swift and Kotlin to frontend applications built with React, Netflix’s tech stack is designed for performance and scalability. Backend services like Zuul, Eureka, and Spring Boot enable efficient routing and service discovery, while databases such as EVCache, Cassandra, and CockroachDB handle vast amounts of data with high availability.

Real-time messaging and streaming are powered by Apache Kafka and Apache Flink, ensuring that data is processed and delivered efficiently. Video storage solutions like AWS S3 and Open Connect enable seamless video delivery, while data processing tools such as Apache Spark and Tableau provide valuable insights and visualizations.

The CI/CD pipeline, supported by tools like JIRA, Confluence, Jenkins, and Spinnaker, ensures rapid and reliable software delivery. Netflix’s commitment to resilience is demonstrated by tools like Chaos Monkey, which continuously tests the system’s ability to handle failures.

By understanding and adopting similar technologies and practices, other organizations can enhance their own development processes and build scalable, resilient systems capable of meeting the demands of modern users.

Abhishek Sharma