🎯 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 ...

🎯 Overview Even with a well-designed system, real-world operations introduce unexpected issues. This post covers: Common failure scenarios Root cause analysis Practical debugging strategi...

🎯 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 ...

🎯 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 ge...

🎯 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 notifica...

🎯 Overview After designing data storage, the next step is building the data pipeline that connects: Data collection Data storage Data aggregation Data delivery This post focuses on imp...

🎯 Overview In a monitoring system, how data is stored directly impacts: Query performance Storage efficiency Insight generation capability This post defines a dual-storage strategy using...

🎯 Overview In this post, we implement the data collection layer, which is the foundation of the entire monitoring system. We collect two types of data: System metrics (CPU, Memory, Disk) Ha...

🎯 Overview Before implementing the monitoring system, we need to establish a stable and reproducible environment. A monitoring system is only as reliable as its environment. This post defines a re...

🎯 Overview Before building the system, it is essential to define clear functional and non-functional requirements. 📊 Functional Requirements 1. System Metrics Collection CPU usage Memory ...