<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ceph on Chen Kai Blog</title><link>https://www.chenk.top/en/tags/ceph/</link><description>Recent content in Ceph on Chen Kai Blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 30 Mar 2023 09:00:00 +0000</lastBuildDate><atom:link href="https://www.chenk.top/en/tags/ceph/index.xml" rel="self" type="application/rss+xml"/><item><title>Cloud Computing (4): Cloud Storage Systems and Distributed Architecture</title><link>https://www.chenk.top/en/cloud-computing/storage-systems/</link><pubDate>Thu, 30 Mar 2023 09:00:00 +0000</pubDate><guid>https://www.chenk.top/en/cloud-computing/storage-systems/</guid><description>&lt;p>&lt;figure class="article-figure">
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&lt;p>When Netflix stores petabytes of video, when Instagram serves billions of photos, when a quant fund replays a year of market data in minutes — behind every one of these workloads is a &lt;em>distributed storage system&lt;/em>. Storage looks deceptively simple from a developer&amp;rsquo;s window (&lt;code>PUT key&lt;/code>, &lt;code>GET key&lt;/code>), but the moment you cross the boundary of a single machine, you inherit a stack of problems that has driven decades of research: how to survive disk failures, how to scale linearly, how to provide a consistency model that does not surprise the application, and how to do all of this while paying cents per gigabyte rather than dollars.&lt;/p></description></item></channel></rss>