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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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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.

Cache 246
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Data Reprocessing Pipeline in Asset Management Platform @Netflix

The Netflix TechBlog

This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case.

Media 237
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What are quality gates? How to use quality gates to deliver better software at speed and scale

Dynatrace

This approach supports innovation, ambitious SLOs, DevOps scalability, and competitiveness. Before a new version of the application is deployed, the software is subject to a series of load tests that evaluate capacity and performance under a series of simulated traffic and application demands. But how do they function in practice?

Speed 206
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Datadog Creates Scalable Data Ingestion Architecture

InfoQ

Datadog created a dedicated data ingestion architecture offering exactly-once semantics for their third-generation event store, Husky. The event-driven architecture (EDA) can accommodate bursts in traffic in the multi-tenant platform with reasonable ingestion latency and acceptable operational costs. By Rafal Gancarz

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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226
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Artificial Intelligence in Cloud Computing

Scalegrid

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Exploring artificial intelligence in cloud computing reveals a game-changing synergy.