Day 28 — 🔭 Monitoring & Observability Part One
In Modern Time applications are no longer simple monolithic systems. Today organizations run: Microservices Kubernetes Containers Serverless Functions Multi-Cloud Platforms Distributed Systems As infrastructure becomes more distributed, troubleshooting becomes significantly harder. A single user request may travel through: Frontend ↓ API Gateway ↓ Microservice A ↓ Microservice B ↓ Database When something breaks, the biggest challenge becomes: "What exactly happened?" This is where Observability becomes critical. 🔗 Resources ** Support the Journey on GitHub: If you're following along, consider starring and forking the repo:** https://github.com/17J/30-Days-Cloud-DevSecOps-Journey What is Observability? Observability is the ability to understand the internal state of a system by analyzing the data it produces. In simple words: Can we understand what is happening inside our systems? Observability helps engineers answer: Why is the application slow? Which service is failing? Which request caused the issue? What changed recently? Where is latency occurring? Without observability: Problem Exists ↓ Guessing Begins With observability: Problem Exists ↓ Evidence Available ↓ Faster Resolution Why Observability Matters Modern cloud-native systems generate enormous amounts of data. Example: 100 Microservices ↓ Millions of Requests ↓ Thousands of Containers Traditional monitoring alone is no longer sufficient. Organizations need: Visibility Insights Correlation Root Cause Analysis Observability provides all of them. Monitoring vs Observability Many people confuse monitoring and observability. Monitoring asks: What is wrong? Observability asks: Why is it wrong? Example: Monitoring: CPU Usage = 95% Observability: Which service? Which request? Which dependency? Which deployment caused it? Observability provides context. The Three Pillars of Observability Modern observability is built on three primary pillars. Metrics Logs Traces Or: Monitoring Logging Tracing Together they provide a