Monitoring tells you when something is wrong. Observability helps you understand why.
The Hospital Analogy
Think of monitoring like a hospital's vital signs monitor. It beeps when heart rate drops or blood pressure spikes. Useful? Absolutely. But it only tells you something is wrong.
Observability is like having a full medical record, lab results, and imaging at your fingertips. When something goes wrong, you can investigate. You can ask questions you didn't know to ask beforehand.
The Three Pillars
Observability is built on three data types, each answering a different question:
- Logs — What happened? (Detailed event records)
- Metrics — How is the system performing? (Numbers over time)
- Traces — Where did the request go? (End-to-end journey)
On their own, each pillar gives you partial visibility. Together, they give you understanding.
Why "Monitoring" Falls Short
Traditional monitoring is built around known failure modes. You set up dashboards for things you expect to break. CPU spikes? Set an alert. Memory usage high? Set an alert.
But modern distributed systems fail in ways you can't predict. A timeout in one service cascades across ten others. A rare edge case triggers once per million requests.
Monitoring only catches what you thought to look for. Observability lets you ask new questions after the fact.
The Practical Difference
The Bottom Line
Monitoring is necessary. Observability is what makes modern systems manageable. It's not about generating more data. It's about generating the right data, in a way that makes debugging possible.
As systems become more distributed, observability shifts from "nice to have" to "essential for survival."