article thumbnail

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.

Latency 212
article thumbnail

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. The streaming data store makes the system extensible to support other use-cases (e.g. System Components. Component Design. API Design. Problem Statement.

Design 334
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems. ETL workflows), as well as downstream (e.g.

Systems 226
article thumbnail

Architectural Insights: Designing Efficient Multi-Layered Caching With Instagram Example

DZone

Leveraging this hierarchical structure can significantly reduce latency and improve overall performance.

Cache 161
article thumbnail

API Design Principles for Optimal Performance and Scalability

DZone

It involves a combination of techniques and best practices aimed at reducing latency, improving user experience, and increasing the overall efficiency of the system. API performance optimization is the process of improving the speed, scalability, and reliability of APIs.

article thumbnail

What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130
article thumbnail

Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. We designed experimental scenarios inspired by chaos engineering.