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Optimizing data warehouse storage

The Netflix TechBlog

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 208
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Pushy to the Limit: Evolving Netflix’s WebSocket proxy for the future

The Netflix TechBlog

To support this growth, we’ve revisited Pushy’s past assumptions and design decisions with an eye towards both Pushy’s future role and future stability. KeyValue is an abstraction over the storage engine itself, which allows us to choose the best storage engine that meets our SLO needs.

Latency 230
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These 7 Edge Data Challenges Will Test Companies the Most in 2025

VoltDB

Edge computing has transformed how businesses and industries process and manage data. By bringing computation closer to the data source, edge-based deployments reduce latency, enhance real-time capabilities, and optimize network bandwidth. As data streams grow in complexity, processing efficiency can decline.

IoT 52
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. We explore all the systems necessary to make and stream content from Netflix.

AWS 38
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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

Whether in analyzing A/B tests, optimizing studio production, training algorithms, investing in content acquisition, detecting security breaches, or optimizing payments, well structured and accurate data is foundational. Users configure the workflow to read the data in a window (e.g. data arrives too late to be useful).

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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems.

Systems 231
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. We explore all the systems necessary to make and stream content from Netflix.

AWS 100