<feed xmlns="http://www.w3.org/2005/Atom"> <id>https://ramfaster.github.io/pc-iot-monitoring/</id><title>IoT PC Monitoring</title><subtitle>IoT-based PC monitoring system using InfluxDB, Python, and Slack.</subtitle> <updated>2026-04-23T13:46:52+09:00</updated> <author> <name>KyleHyben</name> <uri>https://ramfaster.github.io/pc-iot-monitoring/</uri> </author><link rel="self" type="application/atom+xml" href="https://ramfaster.github.io/pc-iot-monitoring/feed.xml"/><link rel="alternate" type="text/html" hreflang="en" href="https://ramfaster.github.io/pc-iot-monitoring/"/> <generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator> <rights> © 2026 KyleHyben </rights> <icon>/pc-iot-monitoring/assets/img/favicons/favicon.ico</icon> <logo>/pc-iot-monitoring/assets/img/favicons/favicon-96x96.png</logo> <entry><title>Conclusion — Lessons Learned and Future Directions</title><link href="https://ramfaster.github.io/pc-iot-monitoring/posts/conclusion/" rel="alternate" type="text/html" title="Conclusion — Lessons Learned and Future Directions" /><published>2026-04-17T10:00:00+09:00</published> <updated>2026-04-17T10:00:00+09:00</updated> <id>https://ramfaster.github.io/pc-iot-monitoring/posts/conclusion/</id> <content type="text/html" src="https://ramfaster.github.io/pc-iot-monitoring/posts/conclusion/" /> <author> <name>KyleHyben</name> </author> <category term="Conclusion" /> <summary>🎯 Overview This project started as a simple idea: Monitor PC hardware metrics. However, it evolved into a full data pipeline system that includes: Data collection Processing Storage Alerting Analytics 🏗️ What We Built [Collection] Telegraf + HWiNFO [Processing] Python Layer [Storage] InfluxDB + MySQL [Alert] Slack [Analytics] Metabase 🧠 Key Learnings 1. Monito...</summary> </entry> <entry><title>Troubleshooting — Real-world Issues and Debugging Strategies</title><link href="https://ramfaster.github.io/pc-iot-monitoring/posts/troubleshooting/" rel="alternate" type="text/html" title="Troubleshooting — Real-world Issues and Debugging Strategies" /><published>2026-04-16T10:00:00+09:00</published> <updated>2026-04-16T10:00:00+09:00</updated> <id>https://ramfaster.github.io/pc-iot-monitoring/posts/troubleshooting/</id> <content type="text/html" src="https://ramfaster.github.io/pc-iot-monitoring/posts/troubleshooting/" /> <author> <name>KyleHyben</name> </author> <category term="Troubleshooting" /> <summary>🎯 Overview Even with a well-designed system, real-world operations introduce unexpected issues. This post covers: Common failure scenarios Root cause analysis Practical debugging strategies 🧠 Troubleshooting Approach We follow a structured approach: 1. Detect issue 2. Identify affected layer 3. Trace data flow 4. Validate assumptions 5. Fix and monitor 🏗️ System Layers Un...</summary> </entry> <entry><title>Optimization &amp; Performance — Scaling a Reliable Monitoring System</title><link href="https://ramfaster.github.io/pc-iot-monitoring/posts/optimization-performance/" rel="alternate" type="text/html" title="Optimization &amp;amp; Performance — Scaling a Reliable Monitoring System" /><published>2026-04-15T10:00:00+09:00</published> <updated>2026-04-15T10:00:00+09:00</updated> <id>https://ramfaster.github.io/pc-iot-monitoring/posts/optimization-performance/</id> <content type="text/html" src="https://ramfaster.github.io/pc-iot-monitoring/posts/optimization-performance/" /> <author> <name>KyleHyben</name> </author> <category term="Optimization" /> <summary>🎯 Overview As the system grows, performance becomes critical. Without optimization, the system may face: High resource usage Slow query performance Storage overload Alert delays This post focuses on optimizing: Data ingestion Storage efficiency Query performance Processing layer 🏗️ Performance Architecture [Data Collection] ↓ [InfluxDB (Write-heavy)] ...</summary> </entry> <entry><title>Analytics &amp; Dashboard — Turning Data into Actionable Insights</title><link href="https://ramfaster.github.io/pc-iot-monitoring/posts/analytics-dashboard/" rel="alternate" type="text/html" title="Analytics &amp;amp; Dashboard — Turning Data into Actionable Insights" /><published>2026-04-14T10:00:00+09:00</published> <updated>2026-04-14T10:00:00+09:00</updated> <id>https://ramfaster.github.io/pc-iot-monitoring/posts/analytics-dashboard/</id> <content type="text/html" src="https://ramfaster.github.io/pc-iot-monitoring/posts/analytics-dashboard/" /> <author> <name>KyleHyben</name> </author> <category term="Analytics" /> <summary>🎯 Overview After building the data pipeline and alert system, the final step is to transform data into actionable insights. This post focuses on: KPI design Dashboard structure Insight generation Visualization using Metabase 🏗️ Analytics Architecture [InfluxDB (Raw Data)] ↓ [Python Aggregation Layer] ↓ [MySQL (Summary Data)] ↓ [Metabase Dashboard] ...</summary> </entry> <entry><title>Alert System — Real-time Monitoring with Slack and Anomaly Detection</title><link href="https://ramfaster.github.io/pc-iot-monitoring/posts/alert-system/" rel="alternate" type="text/html" title="Alert System — Real-time Monitoring with Slack and Anomaly Detection" /><published>2026-04-13T10:00:00+09:00</published> <updated>2026-04-13T10:00:00+09:00</updated> <id>https://ramfaster.github.io/pc-iot-monitoring/posts/alert-system/</id> <content type="text/html" src="https://ramfaster.github.io/pc-iot-monitoring/posts/alert-system/" /> <author> <name>KyleHyben</name> </author> <category term="Analytics" /> <summary>🎯 Overview Collecting and storing data is not enough. The real value of a monitoring system comes from real-time alerts and anomaly detection. This post implements: Slack-based alert notifications Threshold-based alert rules Basic anomaly detection strategy 🏗️ Alert System Architecture [InfluxDB (Raw Data)] ↓ [Python Alert Engine] ↓ [Slack Webhook] ↓ [Use...</summary> </entry> </feed>
