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Designing Instagram

High Scalability

Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. Generating machine learning based personalized recommendations to discover new people, photos, videos, and stories relevant one’s interest. High Level Design. Component Design. API Design.

Design 334
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How To Design For High-Traffic Events And Prevent Your Website From Crashing

Smashing Magazine

How To Design For High-Traffic Events And Prevent Your Website From Crashing How To Design For High-Traffic Events And Prevent Your Website From Crashing Saad Khan 2025-01-07T14:00:00+00:00 2025-01-07T22:04:48+00:00 This article is sponsored by Cloudways Product launches and sales typically attract large volumes of traffic.

Traffic 86
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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.

Cloud 242
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Introducing Configurable Metaflow

The Netflix TechBlog

This has been a guiding design principle with Metaflow since its inception. this could take a few minutes) All packages already cached in s3. All environments already cached in s3. Take a look at two interesting examples of this pattern in the documentation. training.mP4eIStG.yaml run --prediction_date20241006 Metaflow 2.12.39+nflxfastdata(2.13.5);nflx(2.13.5);metaboost(0.0.27)

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Foundation Model for Personalized Recommendation

The Netflix TechBlog

These insights have shaped the design of our foundation model, enabling a transition from maintaining numerous small, specialized models to building a scalable, efficient system. At inference time, when multi-step decoding is needed, we can deploy KV caching to efficiently reuse past computations and maintain lowlatency.

Tuning 163
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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 241
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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 258