Remove Cache Remove Efficiency Remove Tuning Remove Video
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Improving our video encodes for legacy devices

The Netflix TechBlog

by Mariana Afonso , Anush Moorthy , Liwei Guo , Lishan Zhu , Anne Aaron Netflix has been one of the pioneers of streaming video-on-demand content?—?we we announced our intention to stream video over 13 years ago, in January 2007?—?and and thus fall back to less efficient encode families. 264/AVC Main profile family.

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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.

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Dynatrace Kubernetes Observability for Persistent Volume Claims

Dynatrace

Interestingly, our partner RedHat reported in 2021 that around 80% of deployed workloads are databases or data caches, storing data in persistent volume claims (PVCs). You also decide to run your database for storing user uploads – such as images or videos – directly in Kubernetes. Stay tuned. Coming Soon.

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Turbocharge Your Content Delivery With CDN Multiple Origins Load Balancer!

IO River

With the ever-growing demands of the internet, websites and web applications face the challenge of delivering content swiftly and efficiently to users worldwide. For instance, you might set up rules to send video streaming requests to data center A and image loading requests to data center B. That’s where rules come in.

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Turbocharge Your Content Delivery With CDN Multiple Origins Load Balancer!

IO River

With the ever-growing demands of the internet, websites and web applications face the challenge of delivering content swiftly and efficiently to users worldwide. Just like how a traffic cop ensures cars flow smoothly at an intersection, a Load Balancer makes sure data moves efficiently across the network. That’s where rules come in.

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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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MongoDB Best Practices: Security, Data Modeling, & Schema Design

Percona

The main objective of this post is to share my experience over the past years tuning MongoDB and centralize the diverse sources that I crossed in this journey in a unique place. systemctl stop tuned $ systemctl disable tuned Dirty ratio The dirty_ratio is the percentage of total system memory that can hold dirty pages.