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API Design Principles for Optimal Performance and Scalability

DZone

The post will provide a comprehensive guide to understanding the key principles and best practices for optimizing the performance of APIs. What Is API Performance Optimization? 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

Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design. from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. Component Design.

Design 334
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Allegro Reduces Kafka Producer Latency Outliers by 82% After Switching to XFS

InfoQ

Allegro experimented with different performance optimization options to improve Apache Kafka producer tail latency and eventually switched all its clusters to the XFS filesystem. The company used Kafka protocol sniffing, JVM profiling, and eBPF, which proved instrumental in identifying and eliminating performance bottlenecks.

Latency 112
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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 101
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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. Occasionally, these use cases involve terabytes of data, so we have to pay attention to performance.

Systems 226
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Artificial Intelligence in Cloud Computing

Scalegrid

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Exploring artificial intelligence in cloud computing reveals a game-changing synergy.