<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Distributed Systems on Anurag Chaudhary</title><link>https://anuragsinghchaudhary.github.io/tags/distributed-systems/</link><description>Recent content in Distributed Systems on Anurag Chaudhary</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Fri, 11 Nov 2016 00:00:00 +0000</lastBuildDate><atom:link href="https://anuragsinghchaudhary.github.io/tags/distributed-systems/index.xml" rel="self" type="application/rss+xml"/><item><title>CAP Theorem Explained</title><link>https://anuragsinghchaudhary.github.io/blog/cap-theorem-explained/</link><pubDate>Fri, 11 Nov 2016 00:00:00 +0000</pubDate><guid>https://anuragsinghchaudhary.github.io/blog/cap-theorem-explained/</guid><description>A refreshed legacy explainer on consistency, availability, and partition tolerance in distributed systems.</description></item><item><title>Spark Standalone Mode Explained</title><link>https://anuragsinghchaudhary.github.io/blog/spark-standalone-mode-explained/</link><pubDate>Tue, 20 Sep 2016 00:00:00 +0000</pubDate><guid>https://anuragsinghchaudhary.github.io/blog/spark-standalone-mode-explained/</guid><description>A refreshed legacy introduction to Spark standalone mode and why it remains useful for testing, learning, and simple cluster setups.</description></item></channel></rss>