Monitoring & Observability

Any system will eventually fail. The difference between a minor glitch and a major outage is how fast you spot it. Learn the 3 Pillars: Logs, Metrics, and Traces.

What you will learn

  • Understand the difference: Monitoring (Dashboard) vs Observability (Detective)
  • Master the 3 Pillars: Logs, Metrics, Distributed Tracing
  • Implement Google's 4 Golden Signals (Latency, Traffic, Errors, Saturation)
  • Avoid the High Cardinality Trap that crashes your metrics server

You launch your code. It works. Three days later, a user tweets: "Your app is slow."

Do you know why? Do you verify if it is slow? Do you know which service is slow?

If you cannot answer these questions within 2 minutes, you are flying blind.

These terms are often confused.

Analogy:

  • Monitoring: The "Check Engine" light on your car dashboard. (Something is broken).
  • Observability: Pop the hood and connect the diagnostic computer. (Cylinder 4 is misfiring).

To build an observable system, you need three discrete types of data.

You can measure 1,000 things. Don't. Start with these 4.

  1. Latency: "How long does it take?"
    • Watch out: Don't use Average. Use P99.
  2. Traffic: "How much load is there?"
    • Measured in RPS (HTTP) or Concurrent Sessions.
  3. Errors: "How often do we fail?"
    • Explicit Failures (500s).
    • Implicit Failures (200 OK, but empty content).
  4. Saturation: "How full is the resource?"
    • CPU usage, Memory usage, Thread Pool capacity.
    • Insight: When Saturation hits 100%, performance doesn't just plateau; it often degrades to zero (the cliff).

Create a free account to read the full chapter — advanced chapters, progress tracking, and quizzes are free with sign-up.