How Netflix Uses Java

Netflix redesigned Maestro's internal workflow engine, replacing the legacy Conductor 2. x-based stateless worker model with a custom stateful actor model built on Java 21 virtual threads.

The article discusses how Netflix scales its Muse application to provide data-driven creative insights at a massive scale, focusing on the architectural evolution and optimizations made to handle t...

The article discusses Netflix's Unified Data Architecture (UDA), which aims to streamline data modeling across its various platforms by allowing teams to define business concepts once and use them ...

This article discusses Netflix's Distributed Counter Abstraction, a service designed to enable distributed counting at scale while maintaining low latency performance.

The article discusses how Netflix's Compute and Performance Engineering teams utilized eBPF for continuous, low-overhead monitoring of the Linux scheduler to detect noisy neighbor issues in their m...

The article discusses the challenges and insights gained from deploying virtual threads in Java 21 at Netflix, particularly focusing on performance issues encountered with SpringBoot and Tomcat.

The article discusses Maestro, a horizontally scalable workflow orchestrator developed by Netflix for managing large-scale Data/ML workflows.

The article discusses Netflix's implementation of service-level prioritized load shedding to enhance system reliability and user experience during high traffic conditions.

The article discusses the benefits of the Generational Z Garbage Collector (ZGC) introduced in JDK 21, highlighting its impact on reducing latency and improving operational efficiency for Netflix's...

This article discusses Netflix's implementation of a zero-configuration service mesh with on-demand cluster discovery, detailing the motivations behind adopting service mesh technology and the coll...

In 2022, Netflix successfully migrated its mobile applications from a monolithic Falcor API to a Federated GraphQL API with zero downtime.

The article discusses Netflix's efforts to scale its media machine learning infrastructure, focusing on the challenges faced by media ML practitioners and the solutions developed to optimize and st...

The article discusses Marken, a scalable annotation service developed by Netflix to allow various microservices to annotate their entities with metadata.

The article discusses the development of a data reprocessing pipeline within Netflix's Asset Management Platform (AMP), designed to efficiently manage and update digital media assets' metadata.

This article discusses the challenges faced by Netflix when migrating a Java microservice to a larger AWS instance, which unexpectedly resulted in suboptimal performance.

The article discusses the implementation of a consistent caching mechanism in the Titus Gateway, which is part of Netflix's cloud container runtime.

The article discusses Netflix Maestro, a next-generation workflow orchestrator designed to manage data and machine learning workflows at scale.

The article discusses the challenges and improvements in certificate path building within TLS implementations, particularly in light of recent certificate expirations that caused widespread issues.

The article discusses Netflix's approach to enhancing security at scale through the development of Wall-E, a custom implementation of Zuul that integrates Single Sign-On (SSO) to streamline securit...

This article discusses the use of Protocol Buffers (protobuf) FieldMask at Netflix to optimize API design for gRPC communications.

The article discusses the evolution of data movement at Netflix Studio through the implementation of a Data Mesh architecture.

The article discusses the Elasticsearch indexing strategy implemented in Netflix's Asset Management Platform (AMP), focusing on how to efficiently manage and query large volumes of digital media as...

The article discusses the challenges and solutions related to achieving observability in asynchronous workflows, particularly within Netflix's Prodicle Distribution service.

The article discusses how the Revenue & Growth Tools (RGT) team at Netflix develops full-stack tools to support various engineering teams involved in managing financial operations.

The article discusses the development of Netflix Workstations, which are remote workstations designed to provide artists with the necessary tools and resources to create visual effects and animatio...

The article discusses Netflix's approach to simplifying edge authentication and identity propagation using a token-agnostic identity model.

Netflix has open-sourced its Domain Graph Service (DGS) framework, which simplifies the implementation of GraphQL for Spring Boot applications.

This article discusses the optimization of data warehouse storage at Netflix, focusing on the AutoOptimize system designed to enhance performance and reduce costs.

This article discusses Netflix's implementation of GraphQL Federation, detailing the core infrastructure, developer experience, schema governance, observability, security, and resilience strategies...

The article discusses the development of Netflix's distributed tracing infrastructure, specifically focusing on the design and implementation of Edgar, a troubleshooting tool for streaming sessions.

The article discusses the migration of the Netflix Android app's API backend from a monolithic service to a microservice architecture, detailing the strategies, tools, and challenges encountered du...

The article discusses the implementation of Hexagonal Architecture at Netflix to enhance application flexibility and efficiency in managing data sources.

DBLog is a generic Change-Data-Capture (CDC) framework developed to capture committed changes from databases in real-time and propagate them to downstream consumers.

The article discusses how Netflix utilizes a microservices architecture to manage dataset propagation through an in-house pub/sub system called Gutenberg.

The article discusses Netflix's evolution of its regional evacuation strategy to enhance service availability and resilience.

The article discusses the challenges faced by Netflix in customizing Windows images and how they improved their methodology using DevOps patterns.

The article discusses the evolution of Netflix Conductor, a workflow orchestration engine that has gained significant adoption within Netflix for managing core workflows.

The article discusses Netflix's Hack Day in May 2019, highlighting innovative projects developed by employees to explore new ideas and technologies.

The article discusses the design principles for mathematical engineering in the Experimentation Platform at Netflix, highlighting the challenges and strategies for enhancing data science productivi...

The article discusses the development of a cross-platform in-app messaging orchestration service at Netflix, focusing on the evolution of messaging from the website to a dedicated service that enha...

This article discusses Netflix's marketing technology systems designed to scale paid media campaigns effectively.

The article discusses Netflix's transition from internal cloud infrastructure solutions to adopting Spring Boot as their core Java framework, leveraging the community-driven Spring Cloud Netflix.

The article discusses Netflix's engineering efforts to enhance marketing effectiveness through scalable ad creation and management.

The article discusses Netflix's innovative approach to Jupyter notebooks, emphasizing their evolution from niche tools to integral components of the Netflix Data Platform.

The article discusses Netflix's Growth Engineering team and their approach to optimizing the signup experience for millions of users across various devices and countries.

Netflix FlameScope is a new open-source performance visualization tool designed for analyzing CPU performance and time-based issues.

The article discusses Netflix's participation in AWS re:Invent 2017, highlighting various talks and sessions led by Netflix engineers.

The article discusses the developer experience lessons learned from operating a serverless-like platform at Netflix.

The article discusses Netflix's ongoing journey in platform engineering, highlighting the evolution of their cloud ecosystem, engineering challenges, and the adoption of new technologies.

The article discusses Simone, a distributed simulation service developed by Netflix that automates the testing and certification of its app on various devices.