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Building In-Video Search

The Netflix TechBlog

We have built an internal system that allows someone to perform in-video search across the entire Netflix video catalog, and we’d like to share our experience in building this system. Building in-video search To build such a visual search engine, we needed a machine learning system that can understand visual elements.

Media 225
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How To Implement Video Information and Editing APIs in Java

DZone

In the past 15+ years, online video traffic has experienced a dramatic boom utterly unmatched by any other form of content. It must be said that this video traffic phenomenon primarily owes itself to modernizations in the scalability of streaming infrastructure, which simply weren’t present fifteen years ago.

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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. HDR was launched at Netflix in 2016 and the number of titles available in HDR has been growing ever since.

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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

After content ingestion, inspection and encoding, the packaging step encapsulates encoded video and audio in codec agnostic container formats and provides features such as audio video synchronization, random access and DRM protection. Packaging has always been an important step in media processing. is 220 Mbps.

Cloud 237
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MezzFS?—?Mounting object storage in Netflix’s media processing platform

The Netflix TechBlog

Mounting object storage in Netflix’s media processing platform By Barak Alon (on behalf of Netflix’s Media Cloud Engineering team) MezzFS (short for “Mezzanine File System”) is a tool we’ve developed at Netflix that mounts cloud objects as local files via FUSE. What problem are we solving? Encoding is not a one-time process?—?large

Media 214
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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

Cloud-native workloads on edge devices are gaining momentum among organizations as they extend the hybrid cloud closer to the data source and end users at the edge. Successful deployments of cloud-native workloads at the edge help to reduce costs, boost performance, and improve customer experience.

Retail 264
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Dynatrace Kubernetes Observability for Persistent Volume Claims

Dynatrace

For example, let’s say you have an idea for a new social network and decide to use Kubernetes as your container management platform. You also decide to run your database for storing user uploads – such as images or videos – directly in Kubernetes. Two days later, your database runs out of storage in the middle of the night.

Storage 193