Speaking Topic: Observability & MTTI (Mean Time to Insight)
Why Mean Time to Recovery is the metric everyone tracks, and Mean Time to Insight is the one that actually prevents the next outage.
Every engineering organization measures MTTR, Mean Time to Recovery. Almost none measure MTTI, Mean Time to Insight. Recovery restores uptime. Insight restores structural understanding and eliminates an entire class of defect permanently, instead of patching the same failure mode under a new name six months later.
When an organization optimizes for MTTI, investing in high-fidelity distributed tracing, reproducible staging environments, and genuinely deep post-incident forensic audits, it does not merely fix bugs faster. It stops reintroducing them.
I pair this with a talk on green dashboards that lie: the observability stack, which was supposed to be a lighthouse, becomes a blinding blizzard of disconnected data points the moment a true operational failure strikes, because nobody built the system to answer "why," only to answer "is it up."
Key Takeaways
- 01MTTR tells you how fast you recovered; MTTI tells you whether you will fail the same way again.
- 02Deep post-incident forensic audits eliminate failure classes, not individual incidents.
- 03A dashboard that only answers "is it up" is not an observability strategy.
Frequently Asked
What is MTTI and why does it matter more than MTTR?
MTTI, Mean Time to Insight, measures how fast an organization understands why a failure happened, which prevents recurrence. MTTR only measures how fast service was restored.
From the Q&A
“Can a team have good uptime numbers and still have a reliability problem?”
Yes. Strong MTTR can coexist with the same failure class recurring every few releases, if nobody is measuring whether the structural cause was ever found.
“What's the simplest way to start measuring MTTI?”
Require every post-incident review to reach a structural root cause before it can be closed, not just a proximate trigger.