<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:media="http://search.yahoo.com/mrss/"><channel><title>KEDA on Shaowen Chen's Website</title><link>https://www.chenshaowen.com/en/tags/keda/</link><description>Recent content in KEDA on Shaowen Chen's Website</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>&amp;copy;2016 - {year}, All Rights Reserved.</copyright><lastBuildDate>Thu, 18 May 2023 00:00:00 +0000</lastBuildDate><sy:updatePeriod>weekly</sy:updatePeriod><atom:link href="https://www.chenshaowen.com/en/tags/keda/atom.xml" rel="self" type="application/rss+xml"/><item><title>Autoscaling Kubernetes Applications with KEDA</title><link>https://www.chenshaowen.com/en/blog/autoscale-kubernetes-applications-with-keda.html</link><pubDate>Thu, 18 May 2023 00:00:00 +0000</pubDate><atom:modified>Thu, 18 May 2023 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/autoscale-kubernetes-applications-with-keda.html</guid><description>1. HPA VS KEDA HPA also provides:
Elasticity based on custom metrics Scale to Zero Compared with KEDA, these are no longer disadvantages.
The real difference is that HPA can only scale using monitoring data, whereas KEDA can scale using many more data sources — queue messages, databases, Redis, and so on, including monitoring data as well.</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>KEDA</category><category>Autoscaling</category><category>Elastic Scaling</category><category>Operations</category><category>Learning</category><category>HPA</category><category>Event-Driven</category></item></channel></rss>