<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Infinite-Scale on Netdata</title><link>https://www.netdata.cloud/tags/infinite-scale/</link><description>Recent content in Infinite-Scale on Netdata</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 04 May 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://www.netdata.cloud/tags/infinite-scale/index.xml" rel="self" type="application/rss+xml"/><item><title>Infinite Scalability: Monitoring Without Limits</title><link>https://www.netdata.cloud/blog/netdata-inifinite-scalability/</link><pubDate>Thu, 04 May 2023 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/blog/netdata-inifinite-scalability/</guid><description>&lt;p>Scalability is crucial for monitoring systems as it ensures that they can accommodate growth, maintain performance, provide flexibility, optimize costs, enhance fault tolerance, and support informed decision-making, all of which are critical for effective infrastructure management.&lt;/p>
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&lt;p>Most monitoring solutions struggle with scalability, mainly because of:&lt;/p>
&lt;ol>
&lt;li>&lt;strong>High data volume and velocity&lt;/strong>: Monitoring systems generate vast amounts of data and as the infrastructure grows, so does the volume and velocity of these data.&lt;/li>
&lt;li>&lt;strong>Resource constraints&lt;/strong>: Scalability requires efficient resource utilization, leading to bottlenecks and performance issues as the monitored environment grows.&lt;/li>
&lt;li>&lt;strong>Architectural limitations&lt;/strong>: Monitoring systems are usually designed with certain architectural constraints that limit their scalability. Most open source solutions rely on monolithic or centralized architectures that can become overwhelmed at scale.&lt;/li>
&lt;/ol>
&lt;p>For open source solutions scalability has always been a challenge, increasing their complexity significantly (check for example the scalability issues of Prometheus), while for commercial solutions it usually results in increased data collection to visualization latency and cost.&lt;/p></description></item></channel></rss>