The Production Incident That Taught Me Monitoring Was Lying to Us

 


For a long time, I trusted our dashboards.

They were clean. Metrics looked healthy. Alerts were configured. On paper, everything was “production-ready.”

Then came the incident.

When Users Felt Pain Before Metrics Did

Users started reporting delayed confirmations.
Support tickets arrived before any alert fired.

At first, I assumed this was edge-case noise. The dashboards showed normal throughput and acceptable latency. Nothing looked broken.

That assumption cost us time.

The False Comfort of Green Metrics

What I didn’t realize then was simple:
our monitoring reflected infrastructure health, not user reality.

Blocks were still being produced. Nodes were still online. But the system was no longer behaving the way users expected.

By the time alerts triggered, we were already in damage control.

The Moment My Mental Model Broke

Sitting there during the incident, I stopped trusting the graphs.

We were debugging from logs, tracing requests manually, trying to understand where time was actually being lost. The dashboards were decorative at best.

That’s when it hit me:
monitoring wasn’t failing accidentally—it was failing by design.

What I Changed After That Night

After the incident, my approach changed:

  • I stopped treating dashboards as truth

  • I started asking what guarantees actually mattered

  • I designed alerts around broken expectations, not resource limits

That shift didn’t make incidents disappear - but it made them understandable.

Why I’m Writing This

I’m sharing this because many teams don’t realize monitoring is failing until production forces the lesson.

If your system only looks healthy on dashboards, it probably isn’t ready.

This was one of those experiences that permanently changed how I build.

— Peesh Chopra

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