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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

We could also swap out the implementation of a field from GraphQL Shim to Video API with federation directives. The next phase in the migration was to reimplement our existing Falcor API in a GraphQL-first server (Video API Service). To launch Phase 2 safely, we used Replay Testing and Sticky Canaries. How does it work?

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. To that end, the Video and Image Encoding team in Encoding Technologies (ET) has spent the last few years rebuilding the video processing pipeline on our next-generation microservice-based computing platform Cosmos.

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Best practices and key metrics for improving mobile app performance

Dynatrace

Observability data can be used to optimize mobile app performance by identifying areas of the app that are slow or resource intensive. By analyzing performance metrics, developers can improve app responsiveness and reduce resource consumption. Optimize images and videos. Capacity planning. Focused crash and error reporting.

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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

As an example, many retailers already leverage containerized workloads in-store to enhance customer experiences using video analytics or streamline inventory management using RFID tracking for improved security. These challenges stem from the distributed and often resource-constrained nature of edge computing.

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Bending pause times to your will with Generational ZGC

The Netflix TechBlog

More than half of our critical streaming video services are now running on JDK 21 with Generational ZGC, so it’s a good time to talk about our experience and the benefits we’ve seen. Half of all services required for streaming video use our Hollow library for on-heap metadata. That became a nearly 10% improvement with generational ZGC.

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Scaling Media Machine Learning at Netflix

The Netflix TechBlog

In addition, we provide a unified library that enables ML practitioners to seamlessly access video, audio, image, and various text-based assets. Background Match Cutting is a video editing technique. Each step was mapped to a Metaflow step , which allowed us to control the amount of resources used per step.

Media 290
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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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