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Soumyajit Mukherjee
Soumyajit Mukherjee

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Why Observability Is Different From Logging

#observability #devops #monitoring #backend

Many developers think observability means "add more logs."

Logging is important.

But observability is broader.

The Three Common Pillars

Observability is commonly discussed through:

Logs
Metrics
Traces
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Each answers different questions.

Logs

Logs tell you about events.

Example:

2026-08-14 14:20:03
Order 12345 payment failed
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Useful, but often isolated.

Metrics

Metrics measure numerical behavior.

For example:

HTTP requests/sec
CPU usage
Memory usage
Error rate
Request latency
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You might discover:

95th percentile latency = 2.4 seconds
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That tells you something is happening at scale.

Traces

Distributed tracing follows a request across multiple components.

For example:

API Gateway
   ↓
User Service
   ↓
Order Service
   ↓
Payment Service
   ↓
Database
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If the request takes five seconds, tracing can help identify where that time went.

Why Logs Alone Aren't Enough

Imagine:

Payment failed
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A log tells you the payment failed.

A metric tells you that payment failures increased from:

0.5% → 12%
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A trace can help show that requests are timing out inside a specific dependency.

Together, these signals provide much better visibility.

Final Thoughts

Logging answers:

What happened?

Metrics help answer:

How often is it happening?

Tracing helps answer:

Where did the request spend its time?

Understanding all three is an important step toward production-grade engineering.

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