<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Performance-Optimization on Netdata</title><link>https://www.netdata.cloud/tags/performance-optimization/</link><description>Recent content in Performance-Optimization on Netdata</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 04 Aug 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://www.netdata.cloud/tags/performance-optimization/index.xml" rel="self" type="application/rss+xml"/><item><title>Save Hours on Troubleshooting with Automated Investigations</title><link>https://www.netdata.cloud/blog/automated-investigations/</link><pubDate>Mon, 04 Aug 2025 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/blog/automated-investigations/</guid><description>&lt;p>How many times has your team stared at a dashboard, pointed to a spike, and asked a question that charts alone can&amp;rsquo;t answer? &amp;ldquo;What was the real impact of that deployment?&amp;rdquo; &amp;ldquo;Why are our Kubernetes pods in the us-east-1 cluster suddenly crashing?&amp;rdquo; &amp;ldquo;Are we wasting money on overprovisioned servers?&amp;rdquo;&lt;/p>
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&lt;p>Answering these questions is the real work of operations and SRE. It often kicks off a time-consuming scramble, sending engineers down rabbit holes for hours, days, or even weeks. You dig through logs, correlate metrics across services, and piece together clues from Slack conversations and Jira tickets.&lt;/p></description></item><item><title>Netdata Implements MCP Protocol</title><link>https://www.netdata.cloud/blog/netdata-mcp-server/</link><pubDate>Wed, 18 Jun 2025 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/blog/netdata-mcp-server/</guid><description>&lt;p>&lt;strong>Update (February 2026):&lt;/strong> Netdata now also provides MCP via Netdata Cloud at &lt;code>app.netdata.cloud/api/v1/mcp&lt;/code> for infrastructure-wide access (Business/Homelab plan). See &lt;a href="https://learn.netdata.cloud/docs/netdata-ai/mcp">MCP documentation&lt;/a> for details.&lt;/p>
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&lt;p>We are excited to announce that Netdata has officially implemented the Model Context Protocol (MCP), joining the forefront of AI-powered infrastructure monitoring.&lt;/p>
&lt;p>By enabling direct connections between AI assistants and your data sources and tools, the Model Context Protocol is a new open standard that builds a crucial link between artificial intelligence and practical systems. Instead of the AI providing generic suggestions that don’t understand your environment, MCP enables it to communicate and then interact with your infrastructure data in real time.
Being among the first monitoring platforms to adopt this groundbreaking protocol, Netdata is at the forefront of intelligent observability. With the help of this integration, traditional monitoring becomes a dialogue that your entire technical team is able to participate in.
We encourage you to dive deeper into the technical foundations of MCP, explore &lt;a href="https://www.anthropic.com/news/model-context-protocol">Anthropic&amp;rsquo;s comprehensive&lt;/a> explanation, and discover how this protocol is reshaping the future of AI-data interaction.&lt;/p></description></item><item><title>Introducing Netdata Insights</title><link>https://www.netdata.cloud/blog/netdata-insights/</link><pubDate>Tue, 27 May 2025 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/blog/netdata-insights/</guid><description>&lt;p>We&amp;rsquo;ve been thinking a lot about synthesis lately.&lt;/p>
&lt;p>Netdata already samples every metric every second at the edge. Engineers told us the remaining pain point was synthesis, the ability to pull hours or days or months of high‑resolution time‑series into a concise explanation they could hand to a teammate (or use themselves to debug faster).&lt;/p>
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&lt;p>You know the pattern. An incident happens, and suddenly you&amp;rsquo;re context-switching between dozens of dashboards, trying to reconstruct a timeline. Or you need to write a capacity planning report, and you&amp;rsquo;re copy-pasting screenshots into slides, manually correlating trends across different retention windows. The raw data is there, but the synthesis step (the part where you turn metrics into narrative) doesn&amp;rsquo;t scale.&lt;/p></description></item><item><title>Linux CPU Consumption, Load &amp; Pressure Explained</title><link>https://www.netdata.cloud/blog/understanding-linux-cpu-consumption-load-and-pressure-for-performance-optimisation/</link><pubDate>Tue, 02 May 2023 00:00:00 +0000</pubDate><guid>https://www.netdata.cloud/blog/understanding-linux-cpu-consumption-load-and-pressure-for-performance-optimisation/</guid><description>&lt;p>&lt;img src="../2023-05-02-understanding-linux-cpu-consumption-load-and-pressure-for-performance-optimisation/img/stacked-netdata.png" alt="stacked-netdata">&lt;/p>
&lt;p>As a system administrator, understanding how your Linux system&amp;rsquo;s CPU is being utilized is crucial for identifying bottlenecks and &lt;a href="https://www.netdata.cloud/academy/what-is-cardinality-in-databases-a-comprehensive-guide/">optimizing performance&lt;/a>. In this blog post, we&amp;rsquo;ll dive deep into the world of Linux CPU consumption, load, and pressure, and discuss how to use these metrics effectively to identify issues and improve your system&amp;rsquo;s performance.&lt;/p>
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&lt;h2 id="cpu-consumption-and-utilization">CPU Consumption and Utilization&lt;/h2>
&lt;p>CPU consumption refers to the amount of processing power being used by applications running on your system. The &lt;code>system.cpu&lt;/code> chart in Netdata represents the Total CPU utilization of your Linux system, broken down into different dimensions. Each dimension provides insight into how the CPU is being used by various tasks and processes. Here&amp;rsquo;s a brief explanation of each dimension:&lt;/p></description></item></channel></rss>