<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Scale on Ryan Orban</title><link>https://ryanorban.com/categories/scale/</link><description>Recent content in Scale on Ryan Orban</description><generator>Hugo</generator><language>en-us</language><managingEditor>me@ryanorban.com (Ryan Orban)</managingEditor><webMaster>me@ryanorban.com (Ryan Orban)</webMaster><copyright>Ryan Orban</copyright><lastBuildDate>Mon, 17 Aug 2015 00:00:00 +0000</lastBuildDate><atom:link href="https://ryanorban.com/categories/scale/index.xml" rel="self" type="application/rss+xml"/><item><title>What Does It Take to Make Google Work at Scale?</title><link>https://ryanorban.com/notes/google-at-scale/</link><pubDate>Mon, 17 Aug 2015 00:00:00 +0000</pubDate><author>me@ryanorban.com (Ryan Orban)</author><guid>https://ryanorban.com/notes/google-at-scale/</guid><description>&lt;h3 id="summary" class="scroll-mt-8 group"&gt;
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&lt;p&gt;This Google Slides presentation covers the distributed systems challenges behind running Google&amp;rsquo;s infrastructure at scale — the problems that arise when you move from a few servers to millions of them, and the architectural decisions that address them. The content covers the core distributed systems primitives: consistency vs. availability tradeoffs (CAP theorem), MapReduce for parallel computation, Bigtable and Spanner for distributed storage, and the general challenge of building reliable systems from unreliable components.&lt;/p&gt;</description></item><item><title>Twitter Powers of Ten</title><link>https://ryanorban.com/notes/twitter-powers-of-ten/</link><pubDate>Thu, 23 May 2013 00:00:00 +0000</pubDate><author>me@ryanorban.com (Ryan Orban)</author><guid>https://ryanorban.com/notes/twitter-powers-of-ten/</guid><description>&lt;p&gt;&lt;img
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&lt;p&gt;Rob Weir used a powers of ten framing to characterize Twitter&amp;rsquo;s scale properties — from a single tweet (140 characters, ~0.1KB) up through the full Twitter firehose (400 million tweets/day in 2011, ~40 GB/day of raw text). Each order of magnitude reveals different engineering and analytical concerns.&lt;/p&gt;</description></item><item><title>HERE IS TODAY</title><link>https://ryanorban.com/notes/here-is-today-temporal-visualization/</link><pubDate>Sun, 28 Apr 2013 00:00:00 +0000</pubDate><author>me@ryanorban.com (Ryan Orban)</author><guid>https://ryanorban.com/notes/here-is-today-temporal-visualization/</guid><description>&lt;h3 id="summary" class="scroll-mt-8 group"&gt;
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&lt;p&gt;Here Is Today is a simple interactive data visualization that uses a single design technique — progressive zooming out through timescales — to make geological and cosmic time comprehensible. You start with today highlighted on a bar. The bar zooms out to show the current month. Then the year. Then your lifetime. Then human history. Then civilizations. Then the age of humans. Then mammals. Then life on Earth. Then the age of the Earth. Then the age of the universe. Each step dwarfs the previous.&lt;/p&gt;</description></item></channel></rss>