Distributed Systems Course
This is an introductory course in Distributed Systems. Distributed systems is the study of how to build a computer system where the state of the program is divided over more than one machine (or "node"). This course is in active development. At the moment, it consists of a series of short videos. The intention is to create a complete set of video lectures and then add additional content (such as m
Distributed Systems Reading List
Introduction I often argue that the toughest thing about distributed systems is changing the way you think. The below is a collection of material I've found useful for motivating these changes. Thought Provokers Ramblings that make you think about the way you design. Not everything can be solved with big servers, databases and transactions. Harvest, Yield and Scalable Tolerant Systems - Real world
6.5840 Home Page: Spring 2025
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Design Patterns for Container-based Distributed Systems | USENIX
In the late 1980s and early 1990s, object-oriented programming revolutionized software development, popularizing the approach of building of applications as collections of modular components. Today we are seeing a similar revolution in distributed system development, with the increasing popularity of microservice architectures built from containerized software components. Containers [15] [22] [1]
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Back-to-Basics Weekend Reading - Survey of Local Algorithms
Back-to-Basics Weekend Reading - Survey of Local AlgorithmsMay 29, 2015 • 132 words As we know the run time of most algorithms increases when the input set increases in size. There is one noticeable exception: there is a class of distributed algorithms, dubbed local algorithms, that run in constant time, independently of the size of the network. Being highly scalable and fault tolerant, such algor
Simple Testing Can Prevent Most Critical Failures: An Analysis of Production Failures in Distributed Data-Intensive Systems | USENIX
Ding Yuan, Yu Luo, Xin Zhuang, Guilherme Renna Rodrigues, Xu Zhao, Yongle Zhang, Pranay U. Jain, and Michael Stumm, University of Toronto Large, production quality distributed systems still fail periodically, and do so sometimes catastrophically, where most or all users experience an outage or data loss. We present the result of a comprehensive study investigating 198 randomly selected, user-repor
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Massively Parallel Graph Computation: From Theory to Practice
Systems@NYU
Distributed Systems (Fall 2019)
My Distributed Systems Seminar's reading list for Fall 2020
Google's Luiz André Barroso to Receive 2020 Eckert-Mauchly Award
Reza Zadeh
Modern Parallel and Distributed Python: A Quick Tutorial on Ray
Cloud Trends | Microsoft Azure
The Eight Fallacies of Distributed Computing
http://cseweb.ucsd.edu/~gmporter/classes/fa17/cse124/post/schedule/p74-dean.pdf
Distributed TensorFlow
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