What is MTTR?

Mean time to repair (MTTR) is a metric used to measure the average time required to diagnose and fix a malfunctioning system or component, ensuring it returns to full operational status.

In software development, downtime halts user access and disrupts operations, leading to customer dissatisfaction and financial losses. In manufacturing, it slows production, affecting supply chains and profitability. In healthcare, downtime can compromise patient care and safety.

Regardless of industry, one of the best ways to evaluate and enhance operational efficiency is assessing your MTTR. Understanding it helps you identify weaknesses, optimize maintenance processes, and implement proactive measures to reduce downtime, improving operational performance and customer satisfaction.

How MTTR is calculated

MTTR is the average time required to return a malfunctioning system or component to a fully functional state. This duration includes any diagnosis and additional testing to confirm functionality. A lower MTTR indicates quicker recovery times, higher operational efficiency, and system resilience

To calculate MTTR, you divide your system’s total downtime over a given period by the number of repairs performed on it.

MTTR = Total downtime / Number of repairs

For example, if your website experienced a total of 15 hours of downtime in a month and required 5 repair incidents to restore functionality, the MTTR would be 3.

MTTR = Total downtime / Number of repairs = 15 hours / 5 repairs = 3 hours

This means that, on average, it took 3 hours to restore the site to full functionality after each incident.

The concept is relatively simple, but why do you need to know MTTR in the first place?

Why do teams track MTTR?

The significance of tracking MTTR extends beyond mere measurement. It plays a crucial role in maintaining high service availability and reliability, guiding preemptive maintenance efforts to reduce the risk of future downtime.

MTTR insights are instrumental in disaster recovery planning, directly impacting customer satisfaction by ensuring service continuity. Moreover, improving MTTR can help reduce downtime, which lowers operational costs and curbs potential revenue loss.

The benefits of monitoring and minimizing MTTR are numerous. They include:

  • Less downtime: Tracking and reducing MTTR helps lessen the time services remain unavailable to users.
  • Improved incident response: Analyzing MTTR data aids in identifying areas for improvement, streamlining workflows, and implementing best practices to expedite incident resolution.
  • Enhanced customer experience: Reduced MTTR means quicker issue resolution and improved customer satisfaction. Users expect complete service availability and efficient incident resolution facilitates reliability.
  • Increased reliability and resilience: Tracking and analyzing MTTR data encourages a proactive approach to incident management, focusing on prevention, detection, and rapid response. This stance enhances reliability and resilience, making services more robust in the face of future incidents.
  • Greater ability to meet service level agreements (SLAs): Many organizations have SLAs that define acceptable levels of service availability and response times. Tracking MTTR helps meet or exceed these SLAs, fostering trust among customers and stakeholders.

The importance of MTTR across industries

The relevance of MTTR spans industries. Minimizing downtime enhances productivity, revenue generation, customer satisfaction, and brand reputation.

MTTR in manufacturing

In the manufacturing industry, downtime can bring production lines to a standstill, leading to missed deadlines, increased operational costs, and potential supply chain disruptions. MTTR is crucial for ensuring faster recovery and enhancing system resilience, thereby maintaining consistent production and reliable supply chains.

In this scenario, MTTR measures the average time required to restore manufacturing software or machinery to full operation after a breakdown. If a critical software component managing an assembly line malfunctions, technicians can quickly assess the issue, diagnose it, and begin repairs. A lower MTTR — such as two hours — translates to minimal production downtime, which ensures efficient operations and timely delivery of goods to customers.

MTTR in healthcare

Within the healthcare system, system downtime can compromise patient care and put lives at risk. The rapid restoration of service-dependent medical equipment or systems can be life-saving.

Consider sophisticated ventilators using advanced software to control airflow and monitor patient breathing. A software error can start a race against the clock to release a patch and ensure affected machines resume operation. For this type of malfunction, assessing MTTR is vital for minimizing the negative impact on ventilator-dependent patients.

MTTR in the digital sphere

Our world runs on software, and our reliance on digital platforms means we also expect them to be available 24/7. But as any software developer can tell you, software is never completely free of bugs and failure, making MTTR crucial to understanding service availability.

For instance, if a bug in a server’s operating system causes website downtime, MTTR calculates the time taken to identify and resolve the error. Teams can use this information to improve their response strategies, accelerate their troubleshooting processes, and ultimately reduce future downtime.

A lower MTTR indicates efficient troubleshooting and quicker recovery, ensuring minimal disruption to users and enhancing overall platform reliability. Ensuring a low MTTR is paramount for maximizing revenue, maintaining user engagement, and securing brand trust.


While MTTR is a significant metric, understanding it in the broader context of system reliability metrics is crucial. Mean time between failures (MTBF) and mean time to failure (MTTF) complement MTTR, offering a comprehensive view of system durability and maintenance efficiency.

While MTTR focuses on repair times, MTBF measures the average time between failures, and MTTF denotes the expected lifespan of a non-repairable system.

Together, these metrics provide a holistic view of system reliability and maintenance effectiveness.

How to improve your MTTR

You can reduce your MTTR through various strategies, including the following:

  • Implement predictive maintenance practices to anticipate and prevent potential failures.
  • Use advanced technology like Internet of Things (IoT) sensors and artificial intelligence (AI)-driven analytics for faster issue detection.
  • Integrate remote monitoring solutions to enable real-time assessment and diagnosis of equipment.
  • Provide adequate time and resources for proactive maintenance of critical systems.
  • Establish clear communication channels for swift coordination among maintenance teams and stakeholders.
  • Regularly review and update maintenance processes for optimal efficiency.

Challenges with measuring MTTR

Accurately measuring MTTR can be difficult. Variability in data recording methods across teams or systems can skew MTTR calculations, leading to inaccurate insights.

Additionally, defining downtime can be complicated. It involves identifying when a system is truly non-operational versus partially functioning. Factors like scheduled maintenance, partial outages, or intermittent issues further complicate this assessment. Moreover, MTTR may differ depending on the type of incident or the context in which it occurs.

Overcoming these obstacles requires a systematic approach to data collection and analysis, ensuring reliability and accuracy in MTTR measurement.

Mean time to recovery: MTTR in a CI/CD context

Closely related to mean time to repair is another MTTR acronym: mean time to recovery. This metric is used in the context of continuous integration and continuous delivery (CI/CD) to measure the average time between a failed CI/CD pipeline execution and the next successful run.

For example, let’s consider a scenario where a software development team encounters multiple failures in their CI/CD pipeline over the course of a week:

  • Incident 1: On Monday, the pipeline fails at 9 AM due to a syntax error in the code. The error is fixed, and the pipeline is back up and running by 11 AM.
  • Incident 2: On Wednesday, an integration test fails at 1 PM, causing the pipeline to stop. The issue is resolved, and a successful run is completed at 4 PM.
  • Incident 3: On Friday, a deployment script issue causes a failure at 2 PM, which is corrected, and the pipeline successfully executes again at 5 PM.

In this case, the total amount of downtime is 8 hours across three incidents.

MTTR = Total downtime/Number of incidents = 8 hours/3 incidents = 2.67 hours.

This example shows an MTTR of approximately 2.67 hours, indicating that, on average, it took about 2.67 hours to recover from each failure. This metric helps the team gauge their efficiency in resolving pipeline issues and maintaining a smooth workflow, which is critical for the continuous development and deployment process.

What mean time to recovery means in software delivery

Mean time to recovery is an important measurement of the efficiency of software development pipelines. It directly measures the amount of time your development team spends repairing defects in code rather than innovating. These disruptions affect the speed at which you can deploy new features, fixes, and updates, directly impacting product quality and customer satisfaction.

Consider the following implications of mean time to recovery on CI/CD processes:

  • Development pace: A shorter mean time to recovery allows you to respond quickly to failures or issues detected during the CI/CD process. It allows you to address problems promptly, iterate on code changes, and continue the development cycle without significant delays. As a result, development velocity remains high, since you spend less time troubleshooting and more time delivering new features or improvements to the software.
  • Deployment frequency: A shorter mean time to recovery helps you maintain a high deployment frequency by minimizing downtime in the CI/CD pipeline. This ensures that deployments can proceed smoothly without prolonged interruptions, allowing you to release updates or changes to production environments more frequently.
  • Time-to-market: By minimizing your mean time to recovery, you can accelerate the delivery of new functionalities, updates, or bug fixes to end-users. This also allows you and your organization to seize opportunities in the market more quickly, respond to customer feedback promptly, and adapt to changing business requirements quickly.
  • System reliability: The continuous monitoring and optimization of mean time to recovery in your CI/CD pipeline helps improve the overall reliability and resilience of the system. By identifying and addressing the root causes of failures, you can strengthen the infrastructure, enhance fault tolerance, and minimize the likelihood of recurring incidents.

How CI/CD enables faster MTTR in production

Efficient recovery mechanisms in CI/CD environments are critical in minimizing MTTR in production, helping to improve reliability and resilience. These mechanisms ensure minimal disruption to operations by swiftly identifying and rectifying issues.

Automated testing, rollback strategies, and proactive monitoring enable rapid detection of faults during deployment, triggering immediate corrective actions. This agility reduces downtime and prevents cascading failures, bolstering system resilience. Additionally, CI/CD pipelines facilitate iterative improvements, allowing you to quickly iterate on fixes and enhancements, further reducing MTTR over time.

Efficient recovery mechanisms improve system stability by accelerating the repair process and promoting rapid feedback loops. In turn, this efficiency instills greater confidence among stakeholders, leading to increased organizational agility.


MTTR is an important indicator of operational performance across various industries. Low MTTR is essential for businesses aiming to maintain high service levels, ensure customer satisfaction, and control operational costs by minimizing downtime and repairs.

Implementing CI/CD can significantly reduce MTTR by automating build, test, and deployment processes, enabling quicker identification and resolution of issues. CI/CD feedback loops ensure that problems are caught early and addressed promptly.

In the 2024 State of Software Delivery, CircleCI customers recovered from failed pipelines in under 60 minutes on average. To help your organization achieve similar levels of performance and resilience, sign up for a free CircleCI account and get started with CI/CD today.

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