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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience.

Traffic 339
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

As the number of Titus users increased over the years, the load and pressure on the system increased substantially. We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe.

Cache 224
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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. For many of our applications, model explainability matters.

Systems 226
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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130
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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

The GraphQL shim enabled client engineers to move quickly onto GraphQL, figure out client-side concerns like cache normalization, experiment with different GraphQL clients, and investigate client performance without being blocked by server-side migrations. The Replay Tester tool samples raw traffic streams from Mantis.

Traffic 353
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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

A quick canary test was free of errors and showed lower latency, which is expected given that our standard canary setup routes an equal amount of traffic to both the baseline running on 4xl and the canary on 12xl. We also see much higher L1 cache activity combined with 4x higher count of MACHINE_CLEARS.

Hardware 363
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Cache and Prizes

Alex Russell

Browsers will cache tools popular among vocal, leading-edge developers. There's plenty of space for caching most popular frameworks. The best available proxy data also suggests that shared caches would have a minimal positive effect on performance. Browsers now understand the classic shared HTTP cache behaviour as a privacy bug.

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