Remove Cache Remove Latency Remove Video
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Re-Architecting the Video Gatekeeper

The Netflix TechBlog

Gatekeeper is the system at Netflix responsible for evaluating the “liveness” of videos and assets on the site. Gatekeeper accomplishes its prescribed task by aggregating data from multiple upstream systems, applying some business logic, then producing an output detailing the status of each video in each country.

Cache 184
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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

The GraphQL shim enabled client engineers to move quickly onto GraphQL, figure out client-side concerns like cache normalization, experiment with different GraphQL clients, and investigate client performance without being blocked by server-side migrations. To launch Phase 1 safely, we used AB Testing.

Traffic 358
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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. Uploading and downloading data always come with a penalty, namely latency.

Cloud 242
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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

Cache 260
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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

This allows the app to query a list of “paths” in each HTTP request, and get specially formatted JSON (jsonGraph) that we use to cache the data and hydrate the UI. In the snippet above, we’re accessing the detail key for the video object with id 80154610. Instead, it is part of a different path : [videos, <id>, similars].

Latency 243
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Designing Instagram

High Scalability

Generating machine learning based personalized recommendations to discover new people, photos, videos, and stories relevant one’s interest. When a user requests for feed then there will be two parallel threads involved in fetching the user feeds to optimize for latency. Users should be able to like and comment the posts.

Design 334
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Data ingestion pipeline with Operation Management

The Netflix TechBlog

in a video file. As described in the above picture During the first run of the algorithm it identified 500 objects in a particular Video file. Now when we re-ran the algorithm on the same video file it created 600 annotations of schema type Objects and stored them in our service. The Algorithm team improved their algorithm.

Media 275