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Designing Instagram

High Scalability

Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design. Architecture. Component Design. API Design.

Design 334
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Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support…

The Netflix TechBlog

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloads by Kostas Christidis Introduction Timestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of Cosmos , our media encoding platform. Over the past 2.5

Latency 212
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Scalable Annotation Service?—?Marken

The Netflix TechBlog

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. Our service will be used by a lot of internal UI applications hence the latency for CRUD and search operations must be low. Teams should be able to define their data model for annotation.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Retrieval-augmented generation emerges as the standard architecture for LLM-based applications Given that LLMs can generate factually incorrect or nonsensical responses, retrieval-augmented generation (RAG) has emerged as an industry standard for building GenAI applications.

Cache 201
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For your eyes only: improving Netflix video quality with neural networks

The Netflix TechBlog

Our approach to NN-based video downscaling The deep downscaler is a neural network architecture designed to improve the end-to-end video quality by learning a higher-quality video downscaler. We employed an adaptive network design that is applicable to the wide variety of resolutions we use for encoding.

Network 292
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Towards a Unified Theory of Web Performance

Alex Russell

Here are two renderings of the same Gmail inbox in different architectural styles: one based on Ajax, and the other on "basic" HTML : The Ajax version of Gmail loads 4.8MiB of resources, including 3.8MiB of JavaScript to load an inbox containing two messages. Today's web architecture debates (e.g.

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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

This allowed Android engineers to have much more control and observability over how we get our data. We tried a few iterations of what this new service should look like, and eventually settled on a modern architecture that aimed to give more control of the API experience to the client teams. It was a Node.js

Latency 233