MTTR: The Emergency Room Metric for SRE

When a critical incident strikes, speed is everything. That’s why Mean Time to Recovery (MTTR) is a crucial metric in incident response. MTTR is the emergency-room metric. It tells you how quickly your team can stop the bleeding when systems go down.

And it matters. The 2023 DORA State of DevOps Report found that elite teams restore service in under an hour. Yet even those high performers still face multiple incidents per month. Meanwhile, the Uptime Institute’s 2025 Outage Analysis shows that two-thirds of outages now cost more than $100,000, and nearly a quarter exceed $1 million. A study by the Ponemon Institute estimates that the mean cost of downtime per minute exceeds $7,900.

But here’s the problem: MTTR only tells you how fast you stabilized the patient. It doesn't reveal whether your ER was equipped with the right diagnostics, staffed appropriately, and prepared to handle the crisis.

That’s where readiness comes in.

MTTR and Readiness: Acute Speed Meets Systemic Preparedness

Think of an emergency room:

• MTTR is stopping the bleeding.
• Readiness is having the crash cart stocked, the monitors live, and the team trained to use them.

Both matter. A fast MTTR without readiness is luck. Readiness without speed means the patient loses too much blood. Reliability comes from combining them.

A Five-Part Readiness Model: Where AI Helps

1. Detection — Catch issues before customers do

Analogy: Monitors detect arrhythmias before chest pain.
Practice: Proactive monitoring is central to reliability. The Google SRE workbook on incident response emphasizes structured detection and escalation to ensure teams act before users are impacted.
AI: Filters repetitive alerts, correlates related signals, and highlights anomalies for faster detection.

2. Triage — Auto-assemble the chart

Analogy: Nurses gather labs and scans before the doctor acts.
Practice: Effective triage requires pulling logs, metrics, deploy diffs, and past incidents quickly. The SRE workbook describes the value of clearly defined roles and information gathering during incidents.
AI: Assembles relevant data, giving engineers a head start on investigation and triage.

3. Blast radius — See what’s affected fast

Analogy: Local fracture vs. multi-system trauma.
Practice: Mapping service dependencies and customer impact is essential to prioritization. The Uptime Institute’s 2025 report shows that the largest incidents often cascade across multiple systems, amplifying both cost and response complexity.
AI: Generates real-time impact snapshots that tie telemetry to customers, services, or regions.

4. Root cause — Diagnose with evidence, not guesses

Analogy: Use labs and imaging, not hunches.
Practice: The Google SRE book stresses evidence-based response: command logs, timelines, and metrics should be captured so others can verify the diagnosis.
AI: Produces reasoning traces tied to supporting data, reducing time wasted on false leads.

5. Knowledge capture — Update protocols for next time

Analogy: Every unusual case logged for the next shift.
Practice: Blameless postmortems ensure incidents improve the system over time. Atlassian’s postmortem guide outlines how to document, share, and act on lessons learned.
AI: Automates post-incident summaries and updates runbooks so teams don’t repeat the same failures.

How AI Helps Shorten MTTR

AI reduces the manual work that slows down incident response:

• Acute response: AI cuts through noisy alerts and assembles the evidence so the engineer on call can start investigating immediately.
• Prepared response: AI turns post-incident insights into updated runbooks and knowledge bases so teams improve future time-to-resolution.

The Takeaway for Leaders

MTTR shows how fast you stopped the bleeding. Readiness is whether your team was equipped and trained when the emergency began. Celebrate fast MTTR, but invest in the preparation and practices that make every response faster and more effective. That’s how elite teams move from firefighting to resilience, with AI supporting both speed and preparation.