<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Anomaly-Advisor on Netdata</title><link>https://www.netdata.cloud/tags/anomaly-advisor/</link><description>Recent content in Anomaly-Advisor on Netdata</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 18 Dec 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://www.netdata.cloud/tags/anomaly-advisor/index.xml" rel="self" type="application/rss+xml"/><item><title>Anomaly Advisor: Root Cause In Seconds, Not Hours</title><link>https://www.netdata.cloud/features/aiml/anomaly-advisor/</link><pubDate>Thu, 18 Dec 2025 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/features/aiml/anomaly-advisor/</guid><description>Netdata Anomaly Advisor uses edge-native machine learning with 18-model consensus to eliminate 99% of false positives while surfacing root causes in the top 30-50 metrics from thousands collected. Get sub-2-second correlation analysis at any scale without configuration, training delays, or specialist expertise.</description></item><item><title>How Netdata’s Machine Learning works</title><link>https://www.netdata.cloud/blog/how-netdatas-machine-learning-works/</link><pubDate>Thu, 01 Sep 2022 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/blog/how-netdatas-machine-learning-works/</guid><description>&lt;p>Following on from the &lt;a href="https://www.netdata.cloud/blog/introducing-anomaly-advisor-unsupervised-anomaly-detection-in-netdata" target="_blank" rel="noopener">recent launch&lt;/a> of our &lt;a href="https://learn.netdata.cloud/docs/cloud/insights/anomaly-advisor" target="_blank" rel="noopener">Anomaly Advisor&lt;/a> feature, and in keeping with &lt;a href="https://www.netdata.cloud/blog/our-approach-to-machine-learning/" target="_blank" rel="noopener">our approach to machine learning&lt;/a>, &lt;a href="https://github.com/netdata/netdata/blob/master/ml/notebooks/netdata_anomaly_detection_deepdive.ipynb" target="_blank" rel="noopener">here&lt;/a> is a detailed Python notebook outlining exactly how the machine learning powering the Anomaly Advisor actually works under the hood.&lt;/p>
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&lt;p>Or if you&amp;rsquo;d rather watch a video walkthrough of the notebook then check out below.&lt;/p>
&lt;iframe width="560" height="315" src="https://www.youtube.com/embed/L1xleckyuDQ?si=rptYzWE-eLlhSL9x" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen>&lt;/iframe>
&lt;p>Try it for yourself, &lt;a href="https://learn.netdata.cloud/docs/cloud/get-started" target="_blank" rel="noopener">get started&lt;/a> by &lt;a href="https://app.netdata.cloud/?utm_source=blog&amp;amp;utm_content=how_netdata_ml_works" target="_blank" rel="noopener">signing in to Netdata&lt;/a> and connecting a node. Once initial models have been trained (usually after the agent has about one hour of data, zero configuration needed), you&amp;rsquo;ll be able to start exploring in the &lt;a href="https://learn.netdata.cloud/docs/cloud/insights/anomaly-advisor" target="_blank" rel="noopener">Anomaly Advisor&lt;/a> tab of Netdata.&lt;/p></description></item><item><title>Anomaly rate in every chart</title><link>https://www.netdata.cloud/blog/anomaly-rate-in-every-chart/</link><pubDate>Thu, 23 Jun 2022 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/blog/anomaly-rate-in-every-chart/</guid><description>&lt;p>A month ago, we introduced unsupervised ML &amp;amp; Anomaly Detection in Netdata, the &lt;a href="https://www.netdata.cloud/blog/introducing-anomaly-advisor-unsupervised-anomaly-detection-in-netdata/">Anomaly Advisor&lt;/a>. Today, we’re happy to announce that we’re bringing anomaly rates to every chart in Netdata Cloud. Anomaly information is no longer limited to the Anomalies tab and will be accessible to you from the Overview and Single Node View tabs as well. This will make your troubleshooting journey easier, as you will have the anomaly rates for any metric available with a single click. Whichever metric or chart you&amp;rsquo;re exploring will be instant.&lt;/p></description></item></channel></rss>