<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Taxonomy on Revelara</title><link>https://revelara.ai/tags/taxonomy/</link><description>Recent content in Taxonomy on Revelara</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 05 Oct 2026 08:00:00 -0700</lastBuildDate><atom:link href="https://revelara.ai/tags/taxonomy/index.xml" rel="self" type="application/rss+xml"/><item><title>The Reliability Top 10, First Edition</title><link>https://revelara.ai/blog/reliability-top-10-first-edition/</link><pubDate>Mon, 05 Oct 2026 08:00:00 -0700</pubDate><guid>https://revelara.ai/blog/reliability-top-10-first-edition/</guid><description>&lt;p&gt;When teams think about reliability, they usually think about how a lack of it wakes them up in the middle of the night. Many teams stay in that mode, examining their own incident history but unable to move toward a more proactive reliability posture. They have a list of how things have gone wrong for them in the past, but not an evidence-based set of factors to watch for. This list is a second reference: the ten conditions that show up most often across 1,287 public incidents from 139 organizations. Use it to look for the gaps your own history can&amp;rsquo;t show you. If you only have a few minutes, read the table and then skip to &lt;a href="#what-to-do-with-it"&gt;What to do with it&lt;/a&gt;.&lt;/p&gt;</description></item><item><title>Causal Factor Enumeration v1: The Full Catalog</title><link>https://revelara.ai/blog/causal-factor-enumeration/</link><pubDate>Tue, 29 Sep 2026 09:00:00 -0700</pubDate><guid>https://revelara.ai/blog/causal-factor-enumeration/</guid><description>&lt;p&gt;This page lists every entry in the first edition of the catalog from &lt;a href="https://revelara.ai/blog/building-a-reliability-cwe/"&gt;Building a Causal Factor Enumeration for Reliability&lt;/a&gt;. That post covers the prior work, the method and the known limitations. This page is the reference. &lt;a href="https://revelara.ai/blog/reliability-top-10-first-edition/"&gt;The Reliability Top 10&lt;/a&gt; ranks ten of these entries by the number of public incidents each appears in.&lt;/p&gt;
&lt;p class="cf-edition"&gt;Edition v1 &amp;middot; curated 2026-09-22 &amp;middot; 38 entries &amp;middot; 7 categories&lt;/p&gt;
&lt;h2 id="how-to-read-an-entry"&gt;How to read an entry&lt;/h2&gt;
&lt;p&gt;Each entry has an identifier, a name and a definition.&lt;/p&gt;</description></item><item><title>Building a Causal Factor Enumeration for Reliability</title><link>https://revelara.ai/blog/building-a-reliability-cwe/</link><pubDate>Tue, 29 Sep 2026 08:00:00 -0700</pubDate><guid>https://revelara.ai/blog/building-a-reliability-cwe/</guid><description>&lt;p&gt;When someone asked what the &amp;ldquo;OWASP Top 10 for Reliability&amp;rdquo; was a couple of weeks ago in a forum I frequent, I was instantly intrigued by the question. It raised more questions than answers. What would the list consist of, but also why hasn&amp;rsquo;t one been created before? Is it because the act of ranking itself is bad (rankings do have a number of inherent problems), or is it something else? I could imagine all sorts of things, from bad data, to limited analysis. But I have a fair chunk of incident data, so I set off to learn something and figure out if the results might be interesting.&lt;/p&gt;</description></item></channel></rss>