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Every team faces incidents - it's not a matter of if, but when.
The key differentiator between teams that thrive and those that struggle isn't whether they have incidents – it's how quickly they recover. Elite engineering teams consistently bounce back from incidents in less than an hour, while others might take days.
That's where Mean Time to Recovery (MTTR) comes in — to measure how effectively engineering teams can address incidents. But here's the thing: MTTR is an acronym that can be used for different metrics (confusing, right?).
This guide breaks down MTTR in all its forms (mean time to recovery, respond, repair, resolve), along with other essential incident metrics that high-performing engineering teams monitor.
Sections:
Mean Time to Recovery (MTTR), also known as Mean Time to Restore, is the average time it takes to recover from a system or product failure.
This metric indicates the stability of your teams’ software. A higher MTTR increases the risk of app downtime. Further, it can result in a higher Change Lead Time due to more time being taken up fixing outages, and ultimately impact your organization's ability to deliver value to customers.
In this study by Nicole Forsgren (author of DORA and SPACE), high performing teams had the lowest times for Mean Time to Recovery. The study also highlights the importance of organizational culture in maintaining a low Mean Time to Recovery.
According to research conducted on The Verica Open Incident Database (VOID), a database of all publicly available software-related incident reports, MTTR metrics can indicate recovery speed but not without limitations.
The metric often falls into the category of “gray data” – high in variability and low in fidelity.
Traditional MTTR fails to capture the complexity of socio-technical systems, where both technical and human factors contribute to incidents.
This focus on a single averaged metric can create a false sense of system reliability, as central tendency measures like mean and median often don’t accurately represent real-world incident distributions. This is because incident response time distributions are usually skewed left rather than being normally distributed.
Due to these issues, the DORA team introduced a new metric called Failed Deployment Recovery Time (FDRT) in 2023, as they deemed it a more accurate metric relative to MTTR. However, at Multitudes we still include MTTR — as we find the majority of leaders and boards are more accustomed to working with MTTR.
FDRT measures the time it takes to restore service when a deployment results in an outage or service failure in production.
Unlike Mean Time to Recovery, which covers recovery from all types of service interruptions, FDRT specifically isolates issues caused by deployment failures (and excludes uncontrollable events like natural disasters). This specificity allows teams to focus on improving deployment processes and mitigating deployment-related risks.
FDRT = total time to recover from deployment failures / number of deployment failure incidents
Both MTTR and FDRT show how effectively teams deliver software. Together with Change Lead Time, Deployment Frequency, and Change Failure Rate, these DORA metrics have proven to be reliable indicators of high-performing technology teams.
DORA's 10+ years of research and the book Accelerate show something powerful: organizations that perform well against DORA consistently outperform their peers in terms of productivity, profitability, market share, and customer satisfaction.
From the incidents perspective — when teams can recover quickly from incidents, they minimize disruptions and keep systems reliable. This directly impacts customer trust and operational efficiency, which contribute to business success.
While MTTR has been replaced by FDRT by DORA, many executive and leadership teams are now accustomed to seeing reports with MTTR included. So we recommend including it along with other metrics showing more about incident response.
Research Courtney Nash suggests that the answer isn’t to search for the perfect single metric. Instead, to "putting some spinach in your fruit smoothie" by keeping what people expect but also weaving in additional data points like Service Level Objectives (SLOs), customer feedback, and post-incident reviews.
Ultimately, you are aiming to kick-start a conversation about the overall system resilience — rather than optimizing for a single metric (which will inevitably always be flawed).
MTTR commonly refers to Mean Time to Recovery, but it can also mean different metrics in the incident management process. Most of the time when people use it, they refer to Mean Time to Recovery, since that used to be one of the four key DORA metrics.
To avoid confusion, if you intend it to mean one of the phrases besides Mean Time to Recovery, using the full term is recommended.
Here are other incident metrics like MTTR and how they fit together:
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MTTA measures the average time it takes for an incident to be acknowledged after it’s detected.
While Mean Time to Recovery measures the time from detection to full restoration, MTTA only covers the initial response, assessing the team’s responsiveness to alerts. This metric ensures the team is aware of issues as they arise, critical for rapid incident resolution.
MTTA = total time to acknowledge incidents / number of incidentsThe average time required to repair a system, starting from the beginning of the repair process.
Unlike Mean Time to Recovery, which measures the full recovery time, Mean Time to Repair focuses only on the actual hands-on time spent fixing the issue.
MTTR = total time to repair / number of incidentsThe average time to fully resolve an issue, including identifying the root cause and implementing a fix to prevent recurrence.
In contrast to Mean Time to Recovery, which focuses on restoring functionality, Mean Time to Resolve emphasizes the resolution of the underlying issue to prevent future incidents.
MTTR = total time to resolve / number of incidentsThe average time between system failures, serving as a metric for system reliability.
Unlike Mean Time to Recovery, which addresses recovery from incidents, MTBF focuses on the system’s stability and durability over time. A higher MTBF indicates fewer breakdowns, highlighting preventative maintenance and design stability.
MTBF = total operating time / number of failuresHere is a good diagram from Atlassian showing how it comes together.
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These distinctions help incident management teams to ensure clarity and accuracy in assessing incident response and recovery effectiveness. Depending on what is the key question you are answering, you may refer to different metrics:
Generally, we recommend focusing on MTTR/FDRT as they come from DORA — meaning they have strong research backing and rigorous industry benchmarks for comparison. However, different organizations face different issues.
For example, you may have a very fast time to repair but a long time to acknowledge incidents. In this case, you may switch your focus to MTTA for a quarter to identify what is causing that.
When incidents happen (and they will!), the difference between a minor hiccup and a major disruption often comes down to preparation. Fast recovery times don't happen by accident – they're the result of thoughtful planning and regular practice.
You can use Multitudes to track and analyze MTTR, FDRT, and other incident metrics — which is an engineering insights platform for sustainable delivery. Multitudes integrates with your existing development tools, such as GitHub and Jira, to provide insights into your team's productivity and collaboration patterns.
With Multitudes, you can:
Our clients ship 25% faster without sacrificing code quality.
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