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API Design Principles for Optimal Performance and Scalability

DZone

The goal is to help developers, technical managers, and business owners understand the importance of API performance optimization and how they can improve the speed, scalability, and reliability of their APIs. API performance optimization is the process of improving the speed, scalability, and reliability of APIs.

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Scalable Annotation Service?—?Marken

The Netflix TechBlog

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency.

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Designing Instagram

High Scalability

Currently, he is in the Alexa Shopping organization where he is developing machine-learning-based solutions to send personalized reorder hints to customers for improving their experience. Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design.

Design 334
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LinkedIn Migrates Espresso to HTTP2 and Reduces Connections by 88% and Latency by 75%

InfoQ

LinkedIn was able to dramatically improve the scalability and performance of its Espresso database by migrating it from HTTP1.1 to HTTP2, resulting in a reduction in the number of connections, latency, and garbage collection times. By Rafal Gancarz

Latency 99
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Such frameworks support software engineers in building highly scalable and efficient applications that process continuous data streams of massive volume. Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

This architecture shift greatly reduced the processing latency and increased system resiliency. We expanded pipeline support to serve our studio/content-development use cases, which had different latency and resiliency requirements as compared to the traditional streaming use case.

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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Since its inception , Metaflow has been designed to provide a human-friendly API for building data and ML (and today AI) applications and deploying them in our production infrastructure frictionlessly. Rapid development is enabled via Metaflow namespaces , so individual developers can develop without interfering with production deployments.

Systems 226