<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Architecture on EdgeProtocol Blog</title><link>https://blog.edgedevice.online/tags/architecture/</link><description>Recent content in Architecture on EdgeProtocol Blog</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>Copyright © 2026 EdgeProtocol. All rights reserved.</copyright><lastBuildDate>Tue, 11 Aug 2026 09:00:00 -0500</lastBuildDate><atom:link href="https://blog.edgedevice.online/tags/architecture/index.xml" rel="self" type="application/rss+xml"/><item><title>When to Use Ansible vs a Fleet Control Plane</title><link>https://blog.edgedevice.online/post/ansible-vs-fleet-control-plane/</link><pubDate>Tue, 11 Aug 2026 09:00:00 -0500</pubDate><guid>https://blog.edgedevice.online/post/ansible-vs-fleet-control-plane/</guid><description>
&lt;p&gt;If you operate Linux devices in production, &lt;strong&gt;configuration management and operations platforms solve different layers&lt;/strong&gt; eventually becomes a bottleneck. This article explains the problem, why it worsens at scale, and a practical path forward.&lt;/p&gt;
&lt;h2 id="the-problem"&gt;The Problem&lt;/h2&gt;
&lt;p&gt;Configuration management and operations platforms solve different layers. On a single host this is annoying; across a fleet it becomes operational debt that shows up during incidents, audits, and rollouts.&lt;/p&gt;
&lt;h2 id="why-it-gets-worse-at-scale"&gt;Why It Gets Worse at Scale&lt;/h2&gt;
&lt;p&gt;The pain grows quickly past a few dozen devices. The jump from 10 → 100 → 1,000 devices is not linear. Coordination cost dominates, and small inconsistencies compound into systemic risk.&lt;/p&gt;</description></item><item><title>Container vs Bare Metal Agents on Edge Linux</title><link>https://blog.edgedevice.online/post/container-vs-bare-metal-edge-agents/</link><pubDate>Thu, 16 Jul 2026 09:00:00 -0500</pubDate><guid>https://blog.edgedevice.online/post/container-vs-bare-metal-edge-agents/</guid><description>
&lt;p&gt;If you operate Linux devices in production, &lt;strong&gt;deployment model affects resource usage and updates&lt;/strong&gt; eventually becomes a bottleneck. This article explains the problem, why it worsens at scale, and a practical path forward.&lt;/p&gt;
&lt;h2 id="the-problem"&gt;The Problem&lt;/h2&gt;
&lt;p&gt;Deployment model affects resource usage and updates. On a single host this is annoying; across a fleet it becomes operational debt that shows up during incidents, audits, and rollouts.&lt;/p&gt;
&lt;h2 id="why-it-gets-worse-at-scale"&gt;Why It Gets Worse at Scale&lt;/h2&gt;
&lt;p&gt;The pain grows quickly past a few dozen devices. The jump from 10 → 100 → 1,000 devices is not linear. Coordination cost dominates, and small inconsistencies compound into systemic risk.&lt;/p&gt;</description></item><item><title>Network Partition Tolerance for Edge Agents</title><link>https://blog.edgedevice.online/post/network-partition-tolerance-edge-agents/</link><pubDate>Thu, 25 Jun 2026 09:00:00 -0500</pubDate><guid>https://blog.edgedevice.online/post/network-partition-tolerance-edge-agents/</guid><description>
&lt;p&gt;If you operate Linux devices in production, &lt;strong&gt;agents must survive offline periods without corrupting state&lt;/strong&gt; eventually becomes a bottleneck. This article explains the problem, why it worsens at scale, and a practical path forward.&lt;/p&gt;
&lt;h2 id="the-problem"&gt;The Problem&lt;/h2&gt;
&lt;p&gt;Agents must survive offline periods without corrupting state. On a single host this is annoying; across a fleet it becomes operational debt that shows up during incidents, audits, and rollouts.&lt;/p&gt;
&lt;h2 id="why-it-gets-worse-at-scale"&gt;Why It Gets Worse at Scale&lt;/h2&gt;
&lt;p&gt;The pain grows quickly past a few dozen devices. The jump from 10 → 100 → 1,000 devices is not linear. Coordination cost dominates, and small inconsistencies compound into systemic risk.&lt;/p&gt;</description></item><item><title>MCP and the Future of Infrastructure Automation</title><link>https://blog.edgedevice.online/post/mcp-future-infrastructure-automation/</link><pubDate>Tue, 26 May 2026 09:00:00 -0500</pubDate><guid>https://blog.edgedevice.online/post/mcp-future-infrastructure-automation/</guid><description>
&lt;p&gt;If you operate Linux devices in production, &lt;strong&gt;MCP infrastructure&lt;/strong&gt; eventually becomes a bottleneck. This article explains the problem, why it worsens at scale, and a practical path forward.&lt;/p&gt;
&lt;h2 id="the-problem"&gt;The Problem&lt;/h2&gt;
&lt;p&gt;Every ai assistant needs bespoke integrations. On a single host this is annoying; across a fleet it becomes operational debt that shows up during incidents, audits, and rollouts.&lt;/p&gt;
&lt;h2 id="why-it-gets-worse-at-scale"&gt;Why It Gets Worse at Scale&lt;/h2&gt;
&lt;p&gt;Standard tool interfaces reduce integration sprawl. The jump from 10 → 100 → 1,000 devices is not linear. Coordination cost dominates, and small inconsistencies compound into systemic risk.&lt;/p&gt;</description></item><item><title>Polling vs Events: How Should a Device Fleet Detect Problems?</title><link>https://blog.edgedevice.online/post/polling-vs-events-device-fleet/</link><pubDate>Tue, 12 May 2026 09:00:00 -0500</pubDate><guid>https://blog.edgedevice.online/post/polling-vs-events-device-fleet/</guid><description>
&lt;p&gt;If you operate Linux devices in production, &lt;strong&gt;polling vs events&lt;/strong&gt; eventually becomes a bottleneck. This article explains the problem, why it worsens at scale, and a practical path forward.&lt;/p&gt;
&lt;h2 id="the-problem"&gt;The Problem&lt;/h2&gt;
&lt;p&gt;Wrong detection model wastes bandwidth or misses failures. On a single host this is annoying; across a fleet it becomes operational debt that shows up during incidents, audits, and rollouts.&lt;/p&gt;
&lt;h2 id="why-it-gets-worse-at-scale"&gt;Why It Gets Worse at Scale&lt;/h2&gt;
&lt;p&gt;Hybrid designs usually win at the edge. The jump from 10 → 100 → 1,000 devices is not linear. Coordination cost dominates, and small inconsistencies compound into systemic risk.&lt;/p&gt;</description></item><item><title>How a Linux Device Agent Actually Works</title><link>https://blog.edgedevice.online/post/how-linux-device-agent-works/</link><pubDate>Thu, 07 May 2026 09:00:00 -0500</pubDate><guid>https://blog.edgedevice.online/post/how-linux-device-agent-works/</guid><description>
&lt;p&gt;If you operate Linux devices in production, &lt;strong&gt;agent architecture&lt;/strong&gt; eventually becomes a bottleneck. This article explains the problem, why it worsens at scale, and a practical path forward.&lt;/p&gt;
&lt;h2 id="the-problem"&gt;The Problem&lt;/h2&gt;
&lt;p&gt;Operators need a mental model for device-side software. On a single host this is annoying; across a fleet it becomes operational debt that shows up during incidents, audits, and rollouts.&lt;/p&gt;
&lt;h2 id="why-it-gets-worse-at-scale"&gt;Why It Gets Worse at Scale&lt;/h2&gt;
&lt;p&gt;Agents must be lightweight, secure, and resilient. The jump from 10 → 100 → 1,000 devices is not linear. Coordination cost dominates, and small inconsistencies compound into systemic risk.&lt;/p&gt;</description></item><item><title>From Server Management to Fleet Management</title><link>https://blog.edgedevice.online/post/from-server-management-to-fleet-management/</link><pubDate>Tue, 07 Apr 2026 09:00:00 -0500</pubDate><guid>https://blog.edgedevice.online/post/from-server-management-to-fleet-management/</guid><description>
&lt;p&gt;If you operate Linux devices in production, &lt;strong&gt;fleet mindset&lt;/strong&gt; eventually becomes a bottleneck. This article explains the problem, why it worsens at scale, and a practical path forward.&lt;/p&gt;
&lt;h2 id="the-problem"&gt;The Problem&lt;/h2&gt;
&lt;p&gt;Teams apply single-host habits to multi-host environments. On a single host this is annoying; across a fleet it becomes operational debt that shows up during incidents, audits, and rollouts.&lt;/p&gt;
&lt;h2 id="why-it-gets-worse-at-scale"&gt;Why It Gets Worse at Scale&lt;/h2&gt;
&lt;p&gt;Blast radius and coordination dominate. The jump from 10 → 100 → 1,000 devices is not linear. Coordination cost dominates, and small inconsistencies compound into systemic risk.&lt;/p&gt;</description></item></channel></rss>