Netflix developed a high-throughput graph abstraction designed to handle OLTP use cases requiring millions of operations per second on large graph datasets.

stateful-systems

distributed-systems

caching

scalability

graph-database

Netflix

01 min read

Architecture•2026-05-29

From Silos to Service Topology: Why Netflix Built a Real-Time Service Map

Netflix built a real-time service topology map to help engineers understand dependencies across thousands of microservices and troubleshoot incidents faster.

Machine Learning•2026-05-04

Democratizing Machine Learning at Netflix: Building the Model Lifecycle Graph

Netflix's machine learning infrastructure spans multiple business domains including personalization, studio workflows, payments, and advertising, but fragmented ML tools and silos prevent effective cross-domain collaboration and asset discovery.

mlops

event-driven-architecture

Machine Learning•2026-05-01

State of Routing in Model Serving

Netflix's Switchboard processes 1 million requests per second, providing centralized ML abstraction for clients.

Powering Multimodal Intelligence for Video Search

This article describes Netflix's multimodal video search system designed to help filmmakers quickly locate specific moments across massive media archives.

asset-management-software

111 min read

Architecture•2026-02-24

Piqama: Pinterest Quota Management Ecosystem

Pinterest's Piqama is a generic quota management ecosystem that handles the full lifecycle of resource quotas across Big Data Processing and Online Services.

Scaling Localization with AI at Lyft

Lyft rebuilt its translation pipeline by integrating LLMs to reduce translation latency from days to minutes while maintaining linguist oversight.

artificial-intelligence

Safeguarding Dynamic Configuration Changes at Scale

This post describes how Airbnb built "Sitar," their internal dynamic configuration platform for shipping runtime config changes safely at scale.

software-architecture

Lyft

31 min read

Machine Learning•2025-11-18

LyftLearn Evolution: Rethinking ML Platform Architecture

This post describes how Lyft evolved LyftLearn, their end-to-end ML platform, from a fully Kubernetes-based system to a hybrid architecture combining AWS SageMaker and Kubernetes.

distributed-systems

artificial-intelligence

machine-learning

aws

data-science