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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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Black Friday traffic exposes gaps in observability strategies

Dynatrace

What’s the problem with Black Friday traffic? But that’s difficult when Black Friday traffic brings overwhelming and unpredictable peak loads to retailer websites and exposes the weakest points in a company’s infrastructure, threatening application performance and user experience. Why Black Friday traffic threatens customer experience.

Traffic 191
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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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Ensuring the Successful Launch of Ads on Netflix

The Netflix TechBlog

To do this, we devised a novel way to simulate the projected traffic weeks ahead of launch by building upon the traffic migration framework described here. New content or national events may drive brief spikes, but, by and large, traffic is usually smoothly increasing or decreasing.

Traffic 342
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Five-nines availability: Always-on infrastructure delivers system availability during the holidays’ peak loads

Dynatrace

For retail organizations, peak traffic can be a mixed blessing. While high-volume traffic often boosts sales, it can also compromise uptimes. The nirvana state of system uptime at peak loads is known as “five-nines availability.” How can IT teams deliver system availability under peak loads that will satisfy customers?

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POTS: protective optimization technologies

The Morning Paper

POTS: Protective optimization technologies , Kulynych, Overdorf et al., Last time out we looked at fairness in the context of machine learning systems, coming to the realisation that you can’t define ‘fair’ solely from the perspective of an algorithm and the data it is trained on. arXiv 2019.

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Monitoring Distributed Systems

Dotcom-Montior

Web developers or administrators did not have to worry or even consider the complexity of distributed systems of today. Great, your system was ready to be deployed. Once the system was deployed, to ensure everything was running smoothly, it only took a couple of simple checks to verify. What is a Distributed System?

Systems 74