How Netflix Uses Cassandra

This article discusses how Netflix built a resilient data platform using a Write-Ahead Log (WAL) to address data consistency, reliability, and operational efficiency challenges at scale.

The article discusses the evolution of Netflix's Tudum architecture, transitioning from a CQRS model utilizing Kafka to a more efficient system based on RAW Hollow.

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

Netflix's TimeSeries Data Abstraction Layer is designed to efficiently store and query vast amounts of temporal event data with low latency.

Netflix's Key-Value Data Abstraction Layer (KV DAL) enhances data access across its distributed databases, addressing challenges in consistency, durability, and performance.

The article discusses Netflix's development of a Media Understanding Platform that integrates machine learning capabilities into studio applications.

The article discusses Netflix's data ingestion pipeline, specifically focusing on the Annotation Operations concept that allows teams to create data pipelines for media annotations without concerni...

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.

The article discusses Data Mesh, a data movement and processing platform developed by Netflix, aimed at enhancing real-time data processing capabilities.

The article discusses the Rapid Event Notification System (RENO) developed by Netflix to ensure real-time communication between backend systems and devices, enhancing the user experience for over 2...

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 Netflix Data Explorer, an open-source tool designed to provide engineers with fast and safe access to data stored in Cassandra and Dynomite/Redis.

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 Bulldozer, a self-serve data platform developed by Netflix for efficiently moving batch data from data warehouse tables to online key-value stores.

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 Netflix's approach to optimizing its data infrastructure costs through transparency and a custom dashboard.

The article announces the open sourcing of Mantis, a platform developed by Netflix for building cost-effective, real-time, operations-focused applications.

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

Delta is a data synchronization and enrichment platform developed by Netflix to address the challenges of keeping multiple datastores in sync while allowing for data enrichment.

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

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

The article discusses the implementation of the Netflix Media Database (NMDB), focusing on its architecture, system requirements, and key components that enable scalability, reliability, and effici...

This article discusses Netflix's approach to scaling its time series data storage architecture in response to increased demand from global expansion and new features.

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

The article discusses the lessons learned from building observability tools at Netflix, emphasizing the importance of log management, distributed request tracing, metrics analysis, and user interfa...

This article discusses Netflix's evolution of its time series data storage architecture to manage the massive growth of viewing history data.

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

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.

The article introduces Bolt, a diagnostic and remediation platform designed for AWS EC2 instances, which automates common tasks and integrates with Netflix's existing orchestration service, Winston.

Netflix Conductor is a microservices orchestration engine designed to manage complex workflows in the content platform engineering team.

The article discusses Netflix's development of NDBench, a pluggable benchmarking tool for cloud data stores, aimed at validating updates, performing capacity planning, and testing various workloads.

The article discusses Netflix's implementation of distributed delay queues using Dynomite, a generic Dynamo implementation.

This article details Netflix's technical journey in migrating its Billing applications and datastores from a Data Center to AWS Cloud, emphasizing the challenges and strategies employed throughout ...

The article discusses Netflix's migration of its billing infrastructure to AWS, highlighting the challenges faced and the strategies employed to ensure a seamless transition without impacting user ...

Dynomite-manager is a tool developed by Netflix to manage Dynomite clusters efficiently, ensuring high availability and performance.

The article discusses Meson, a workflow orchestration and scheduling framework developed by Netflix to manage machine learning (ML) pipelines for video recommendations.

The article discusses Netflix's Experimentation Platform, emphasizing the importance of A/B testing in enhancing user experience through data-driven decisions.

The article discusses Netflix's evolution towards a global cloud architecture, emphasizing the transition from a single point of failure to a multi-regional deployment.

The article discusses Netflix's innovative approach to feature generation using a system called DeLorean, which allows for distributed time travel to generate features from historical data.

The article discusses the retirement of Astyanax, a Java client library for Apache Cassandra, which was created in 2011.

The article discusses Netflix's innovative localization technologies, focusing on the Global String Repository and Hydra.

Vector is an open-source host-level performance monitoring framework developed by Netflix, designed to provide high-resolution system and application metrics directly in engineers' browsers.

The article discusses Netflix's development of tools for performance and reliability analysis in a microservice architecture, emphasizing the need for tailored monitoring solutions at scale.

The article discusses the backend infrastructure that powers the 'Trending Now' row on Netflix, highlighting the importance of real-time data processing and personalized recommendations.

The article introduces Nicobar, an open-source dynamic scripting library for Java developed by Netflix, designed to allow UI teams to inject code dynamically into the JVM without API team involveme...

The article discusses Netflix's architecture for processing viewing data, detailing its evolution from a monolithic system to a more scalable architecture that handles billions of viewing-related e...

The article introduces Raigad, an Elasticsearch sidecar developed by Netflix to automate the management of Elasticsearch clusters.