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All of Netflix’s HDR video streaming is now dynamically optimized

The Netflix TechBlog

by Aditya Mavlankar , Zhi Li , Lukáš Krasula and Christos Bampis High dynamic range ( HDR ) video brings a wider range of luminance and a wider gamut of colors, paving the way for a stunning viewing experience. 1) depicts the migration of traffic from fixed bitrates to DO encodes. By June 2023 the entire HDR catalog was optimized.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Investigating a video streaming failure consists of inspecting all aspects of a member account. Troubleshooting a session in Edgar When we started building Edgar four years ago, there were very few open-source distributed tracing systems that satisfied our needs. which is difficult when troubleshooting distributed systems.

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Dynatrace Cloud Automation Module provides observability-driven automation across the full lifecycle

Dynatrace

Think curbside delivery for groceries, video conferencing for work and school, and telemedicine for doctor visits. Broad-scale observability focused on using AI safely drives shorter release cycles, faster delivery, efficiency at scale, tighter collaboration, and higher service levels, resulting in seamless customer experiences.

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From AVIF to WebP: A New Smashing Book By Addy Osmani

Smashing Magazine

To be effective, all these images need to be carefully orchestrated to appear on the screen fast — but as it turns out, loading images efficiently at scale isn’t a project for a quiet afternoon. Next to videos, images are the heaviest, most requested assets on the web. Keeping this efficient helps ensure a good user experience.

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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

These applications range from critical low-latency services powering our customer-facing video streaming service, to batch jobs for encoding or machine learning. We’re using cvxpy as a nice generic symbolic front-end to represent the problem which can then be fed into various open-source or proprietary MIP solver backends.

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ML Platform Meetup: Infra for Contextual Bandits and Reinforcement Learning

The Netflix TechBlog

In this talk, Kinjal used the example of the LinkedIn Feed, to demonstrate how they use bandit algorithms to solve for the optimal parameter selection problem efficiently. He concluded by stressing the efficiency their teams had achieved by doing online parameter exploration instead of the much slower human-in-the-loop manual explorations.

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Meet Image Optimization, A New Smashing Book By Addy Osmani

Smashing Magazine

To be effective, all these images need to be carefully orchestrated to appear on the screen fast — but as it turns out, loading images efficiently at scale isn’t a project for a quiet afternoon. Next to videos, images are the heaviest, most requested assets on the web. Keeping this efficient helps ensure a good user experience.

Media 92