How to measure mean time to restore: The engineering leader's guide
Elite teams restore service in under an hour. Here's how to build resilience without burning out developers.
Taylor Bruneaux
Analyst
TL;DR: Mean time to restore (MTTR) measures average recovery time from production incidents. Elite teams restore service in under one hour. Formula: Total downtime ÷ Number of incidents.
When production systems fail, the question isn’t whether it happened. It’s how quickly you can recover.
At LinkedIn, the Developer Productivity and Insights Team discovered that teams with standardized processes and TPM involvement see dramatically higher engagement with reliability metrics. This matters because teams that actively track and discuss metrics like MTTR are better positioned to improve them systematically.
Mean time to restore (MTTR) measures organizational resilience under pressure.
Understanding MTTR: definition and importance
What is mean time to restore?
Mean time to restore (MTTR) captures the average time your engineering organization needs to return systems to normal after a failure.
Formula:
MTTR = Total downtime ÷ Number of incidents
Example: Four incidents totaling eight hours of downtime in one month equals two hours MTTR.
Why MTTR matters for engineering leaders
MTTR reveals more than uptime. It signals whether your teams have the right systems, processes, and culture to recover quickly without burning out.
- Revenue protection. Every minute restored reduces financial and reputational impact. Amazon famously loses $400,000 per minute during outages.
- Velocity enablement. Teams confident in recovery speed ship faster and experiment more, a capability central to modern software development best practices.
- Developer well-being. Long firefighting sessions kill focus and morale. Shorter, structured recoveries reinforce trust in both systems and leadership.
- Operational maturity. MTTR highlights whether your organization has mature incident response practices or relies on ad hoc heroics.
For executives, MTTR provides a bridge metric between engineering performance and business impact.
MTTR disambiguation: variants and related metrics
The acronym “MTTR” creates confusion because it refers to several different but related metrics. Understanding these distinctions is critical for accurate measurement:
MTTR variants:
Metric | Full name | What it measures | Key difference |
|---|---|---|---|
MTTR (restore) | Mean Time to Restore | Time to return service to normal operation | End-to-end customer impact |
MTTR (recover) | Mean Time to Recover | Time to restore system functionality | Internal system restoration |
MTTR (repair) | Mean Time to Repair | Time to fix the underlying issue | Focus on root cause resolution |
MTTR (resolve) | Mean Time to Resolve | Time to close the incident ticket | Administrative completion |
MTTR (respond) | Mean Time to Respond | Time to begin incident response | Initial acknowledgment only |
Related reliability metrics:
Metric | What it measures | Why it matters |
|---|---|---|
MTTA (acknowledge) | Time from detection to acknowledgment | Shows how quickly teams recognize incidents |
MTBF (between failures) | Average uptime between incidents | Captures how often failures occur |
MTTD (detect) | Time to identify a failure | Affects how quickly recovery can begin |
Best practice: Define which MTTR variant you’re measuring and stick to it consistently across teams. Most organizations tracking DORA metrics should focus on Mean Time to Restore, as it best captures the customer experience during incidents.
MTTR in measurement frameworks
MTTR in the Core 4 framework
In DX’s Core 4 framework, MTTR sits within the Quality dimension as failed deployment recovery time. This placement is intentional.
The Core 4 balances four perspectives—Speed, Effectiveness, Quality, and Impact—so leaders avoid over-optimizing in one area at the expense of another. Teams might achieve faster deployments or increase feature delivery, but if MTTR trends upward, that signals fragility.
This counterbalancing design makes the Core 4 effective at surfacing trade-offs. By incorporating MTTR directly, the framework helps leaders connect operational stability to developer experience and business outcomes.
MTTR in the DORA framework
MTTR is one of the four DORA metrics, alongside deployment frequency, lead time for changes, and change failure rate.
Together, these metrics balance speed and stability. The State of DevOps Report shows elite performers restore service in under one hour, while low performers may take days.
Importantly, MTTR should not be read in isolation. Paired with change failure rate, it shows whether failures are becoming both less frequent and less costly.
Performance benchmarks
Research consistently shows:
- Elite performers: Under 1 hour
- High performers: Under 1 day
- Low performers: Multiple days
What matters most is whether MTTR improves over time as your systems and processes mature. Many teams incorporate MTTR into operational maturity frameworks or production readiness checklists to set meaningful targets.
Improving MTTR: strategies and best practices
How to reduce MTTR
Improving MTTR is about reducing friction, not relying on heroics. Leading teams invest in:
Faster detection and alerting through comprehensive observability. Teams can’t fix what they can’t see.
Clear playbooks so response is automatic, not improvised. As LinkedIn’s experience shows, teams with established review processes and dedicated TPMs see significantly higher metric adoption and action.
Smaller, safer deployments with CI/CD and feature flags. When changes are smaller, rollbacks are faster and less risky.
Platform engineering to provide consistent tooling and reduce cognitive load. Platform teams create self-service recovery paths.
Blameless postmortems that turn incidents into lasting improvements. Culture matters as much as tooling.
These practices align closely with DevOps metrics and KPIs that drive meaningful improvement.
MTTR and developer experience
Incidents are not just operational events—they are human experiences.
Long, stressful recoveries erode trust and contribute to attrition risk. Short, well-handled incidents can build confidence in both systems and leadership.
Leading organizations combine MTTR with understanding developer experience. This ensures improvements in reliability don’t come at the expense of developer well-being, a connection increasingly critical for engineering productivity.
Common MTTR pitfalls
Gaming the metric. Teams declare incidents “resolved” prematurely to improve numbers. Define clear resolution criteria tied to customer impact, not internal dashboards.
Focusing only on technical solutions. Culture and process improvements often matter more than new monitoring tools. Balance technical investments with team training.
Comparing across different system types. A monolithic e-commerce platform and a distributed microservices architecture have different failure modes. Segment MTTR measurements by system criticality and complexity.
Where engineering leaders go from here
MTTR isn’t only about uptime. It’s also about trust: trust that your systems can recover, that your developers aren’t stuck firefighting, and that your organization can move fast without fear.
In the Core 4, MTTR serves as a counterbalance, reminding leaders that true productivity isn’t just about speed or output. It’s about resilience.
Get started with these steps:
- Establish baseline measurements using consistent incident definitions
- Implement basic monitoring and automated alerting across critical systems
- Create standardized playbooks for your most common failure scenarios
- Track trends over time rather than optimizing individual incidents
For engineering leaders, MTTR is one of the clearest signals of how healthy and sustainable your engineering culture really is. When teams can recover quickly from failures, they can take the calculated risks that drive innovation.