What is MTTR? Incident Metrics Explained (MTBF, MTTF, MTTA)

Curious about MTTR? We explain what the mean time to recovery is, why it matters to your development team, and how to reduce it.

What is MTTR?

MTTR (mean time to recovery or mean time to restore) is the average time it takes to recover from a system failure.  

The Many Meanings of MTTR

An acronym typically represents a single entity or concept. In the case of MTTR (which is technically an initialism, but that’s a conversation for another time), the R may represent four different measurements: repair, recovery, resolve, or respond. In a software-defined world, MTTR usually stands for mean time to resolution or mean time to resolve. However, each one of the four metrics has its own meanings and nuances and it’s important to clarify which MTTR your team is referring to and define it accordingly. 

Key Incident Metrics: MTBF, MTTR, MTTA, and MTTF

Incidents and outages are a mandatory part of any IT system. In today’s world, downtime can have real consequences on the business. That is why it’s important to quantify different metrics to check how quickly issues can be identified and resolved. The most common incident metrics are:

• MTBF - Mean Time Between Failures
• MTTR - Mean Time to Resolution, Repair, Respond, and Resolve
• MTTF - Mean Time to Failure
• MTTA - Mean Time to Acknowledge

MTTR: Mean Time to Repair

Mean Time to Repair is the average time spent on repairing a system. It is not the same as the system outage period. Rather, it includes time spent on both repair and testing, and only stops when the system is fully operational again. Sometimes, repairs start the minute an issue is detected and sometimes, it takes time to start working on the issue. 

MTTR is useful in tracking how fast the on-call team was able to contain and repair the issue. Teams often use the metric to identify how swiftly they repair the system. The goal is to keep the number as low as possible by increasing efficiency.  

How to Calculate Mean Time to Repair

Mean time to repair is calculated by adding the total time it spent on repair divided by the number of incidents that needed repairs. So, if there were six outages over the course of seven days and in total five hours were spent on repairs, then:

Mean Time to Repair = Total Repair and Testing Time / Number of Incidents

MTTR = 300 minutes/6 = 50 minutes

MTTR: Mean Time to Respond

Mean Time to Respond is the average time from the first alert to the time it takes to recover from a system failure. Any lag in the alerting system is not included in the MTTR. It’s used to measure a team’s success in case of a cybersecurity incident. 

How to Calculate Mean Time to Respond

To calculate Mean Time to Respond, add the total response time from the first alert to when the system became fully functional again, and divide the number by the total number of incidents. So, if three incidents occurred over a 40-hour work week, and you spent a total of one and half hours on repair, then:

Mean Time to Respond = Total Response Time / Number of Incidents

MTTR = 180 minutes/3 = 30 minutes

MTTR: Mean Time to Resolve

Mean Time to Resolve is the average time it takes to resolve a system failure from start to the end. That includes the time spent on detecting the problem, diagnosing, repairing the issue, and ensuring that the problem will not happen again. 

The difference between mean time to recover and mean time to resolve is that of putting out a fire and fireproofing a place. The importance of the metric lies in the fact that it has a direct correlation with customer happiness. Customers need to see that a solution is in place to help prevent further outages to remain happy with the service.

How to Calculate Mean Time to Resolve

To calculate the mean time to resolve, add the total time spent on a resolution during a certain time period you’re tracking, and divide it by the number of incidents. So, if a system was down for one hour in only one incident during a 24-hour window and the team spent an extra three hours making sure that the incident does not happen again, then:

Mean Time to Resolve = Total Incident Resolution Time / Number of Incidents

MTTR = 1 + 3 = 4 hours

MTTR: Mean Time to Recovery

Mean Time to Recovery is the average time it takes to recover from a partial or total system failure. It starts the minute that the outage begins and ends when the system is back to being fully operational again. According to the DORA (DevOps Research and Assessment), mean time to recovery is a DevOps metric that can also measure the stability of a DevOps team.

If there’s an issue within your recovery system, then mean time to recovery can be used to identify that along with the speed of your recovery process. It does not help you find out where the problem lies within the system but is an excellent starting point to diagnose whether there is a problem. 

How to Calculate Mean Time to Recovery

To calculate mean time to recovery, add up the total downtime within a specific period and divide it by the number of incidents. So, if your system was down for a total of 24 minutes in three separate incidents within a 24-hour period, then:

Mean Time to Recovery = Total Downtime / Number of Incidents

MTTR = 24/3 = 8 minutes

Other Key Incident Metrics

MTTR is an important metric, but one should never rely on a single metric. Using MTTR alongside other metrics such as MTBF and MTTA offers a more complete picture of the system’s infrastructure and performance. 

MTBF: Mean Time Between Failures

MTBF measures the average time between one incident to another during the normal operation of a system. It’s used to track the availability and reliability of a system. In a more reliable system, the time between failures is higher. Most organizations try to keep a high MTBF by preventing the most common and frequent incidents. If something is causing failures often, fixing it should be prioritized highly.

When MTBF is Used

MTBF is used by engineering and technology-based professionals in correlation with MTTR to determine the reliability of a product. MTBF shows the mean time to resolution by revealing:

• Longevity of specific components and their wholes
• Potential issues that may arise
• Future availability of products

When using MTBF for these purposes, the higher the number, the longer the lifespan of the product.

MTBF is a valuable metric in the aviation industry where the consequences are major in terms of human life and costs. For buyers, this metric allows them to choose the most reliable and safest product and for internal teams, it helps identify any issues and track success and failures.

MTTA: Mean Time to Acknowledge 

MTTA is the average time between when an alert is triggered and the team starts working on the issue. It’s useful to track the efficiency of your alert system and the responsiveness of your team. It helps you identify whether you have alert fatigue and flag the issues related to responsiveness.

When to Use MTTA

MTTA is useful when working with specific products or on unique projects to make sure the infrastructure around them is working. MTTA is used in situations when you need to determine:

• The efficiency of monitoring tools
• How reliably a team will be alerted when failure occurs
• How long you can expect to wait for the resolution process to start

MTTA shows your team's responsiveness in various situations. As you determine the mean time to repair a project, the MTTA offers insight into your team’s abilities and performance.

MTTF: Mean Time to Failure

MTTF is the average time between non-fixable issues within a system. The metric is used to find out how long a system’s life expectancy is and whether a new version is outperforming the old system. 

The issue with MTTF arises when you’re measuring it for a product that has a long lifetime. That’s because the product is not used until it fails, but tested for a defined period of time, which is used to measure how many will fail. MTTF is a valuable metric for products that have a shorter lifespan such as a light bulb. 

When to Use MTTF

MTTF is useful when calculating mean time to repair because it offers insight into potentially unrepairable products. MTTF is only used to assess the longevity of systems or products that experience full failure. In this way, MTTF improves productivity and response times by avoiding unrepairable projects and products.

MTTF is a valuable metric for services that will be wholly replaced rather than repaired, such as a hard drive failing in your servers. It provides an average lifespan for that system, which can be recorded for future projects.

How Does MTTR Relate to SLAs?

MTTR provides information about the system’s reliability and performance. The metric is often used to support contracts such as an SLA (System Level Agreement). An SLA is a contract between the service provider and the client that outlines the repercussions of failure. Organizations usually have an error budget (amount of acceptable unreliability of a service) that provides the acceptable time to recover from incidents. In that case, MTTR is often used and negotiated in the SLA alongside other metrics. 

Causes of Poor MTTR

In the event a company is unable to repair an issue in the time frame outlined by an SLA, poor mean time to restore or mean time to resolution could be at fault. MTTR is impacted by a variety of factors. Determining the foundation of the poor MTTR ensures these failures don’t repeat in the future.

Some of the causes of poor mean time to resolution include:

Lack of Visibility

Lack of visibility refers to the monitoring of system failures, usage, and overall performance. Limited monitoring of system performance and incidents by IT professionals result in delays to detect and diagnose issues.

Increased monitoring enhances visibility and the mean time to restore the system. For physical components, asset tracking allows an organization to create solution protocols.

Inefficient Incident Response Process

Incident response is the timeframe and process organizations put in place for data breaches and similar issues. Responding to an incident quickly and efficiently minimizes data loss and the risk of future problems.

A manual incident response process that lacks standardization leads to inconsistent resolution times. This increases MTTR and causes bigger issues. An audit of the incident response process reduces room for error. Take note of potential flaws in the system to limit the same problems later.

Communication Gaps

Communication is integral to any project. In software and IT-related projects, communication directly impacts the development and delivery of a project. Miscommunication leads to shortcomings, including the potential to miss the goal of a project completely.

A lack of collaboration and priority between the teams involved in incident response negatively impacts MTTR. It’s impossible to determine the mean time to resolve an issue if the issue and responses are ineffectively communicated.

Some of the individuals that communication gaps affect include:

• Developers
• Operations
• Support

When collaboration is not seamless, it causes delays in the resolution time, extending the mean time to repair. Training and communication framework implementation are two strategies to bridge gaps in the system.

How to Reduce MTTR

Incidents impact customers and their happiness. If the service is unavailable for too long, the customer will become unhappy. The ultimate goal of every business is to make their customers happy. MTTR or the time it takes to resolve an incident can be reduced by devising the best incident response process. We will discuss a few ways you can help you reduce MTTR by stepping up your incident response game. 

Create an Action Plan for Incident Management 

An incident management plan provides a detailed account of how an incident will be managed from the first alert to when the system becomes fully functional and resumes operation. It also outlines how the incident management team should be structured, what should be documented, the required resources, and critical processes.

Define a Clear Chain of Command and Roles

In incident response, specifying a clear chain of command and roles is critical. At the very beginning, an incident commander (IC) takes charge who leads and overlooks everything from start to the end. The other important roles are communication lead (CL) and operations lead (OL). The CL manages communication between teams and stakeholders, and the OL runs the operations tasks. Both CL and OL report to the IC, and roles are added or deducted as needed. 

Continuous Monitoring

To fix something, you need to know that it’s broken in time. Proper visibility into your system allows you to diagnose the problem early, and reduce MTTR. A real-time flow of monitoring data regarding the server, application, and infrastructure gives the team information such as server load, memory, response time, and other metrics. This way teams can find out what caused the problem, and fix it faster.

Leverage Tools to Detect, Diagnose, and Reduce MTTR

Leveraging tools to automate the incident response can help the teams focus on the problem on hand without getting distracted. Blameless offers an Automated Incident Response tool that manages everything from checklists to runbooks, and configurations for you. You can also manage the events timeline and auto-sync it by issuing commands from your communication tools. The Automated Incident Response tool also captures performance analytics and highlights important information from your observability and monitoring tools. 

Design Runbooks

Runbooks, also known as playbooks, are documents that outline the step-by-step process of performing certain tasks. They’re designed to ease the cognitive load of day-to-day tasks by offering clear information and instructions. Creating runbooks for troubleshooting simple tasks and triggering them during incident response can immensely reduce MTTR. Although, you can’t always automate runbooks, as there will be new and unexpected incidents. 

Create an Incident Retrospective

Resolving an incident successfully is not the end of the line. An efficient team ends with a follow-up also known as an incident retrospective or postmortem. During the retrospective, the team comes together to investigate and document what happened, how it happened, possible causes, and how it can be avoided in the future.

Get Proactive with Chaos Engineering

The last step towards managing a great IT system is to be proactive instead of reactive. Chaos engineering is a practice utilized by many IT organizations, where they randomly inject problems into their system to test its resiliency. It happens in a controlled environment and helps teams look at the problem, the recovery process, and monitoring data. 

What are Reliability, Availability, and Maintainability?

Reliability, availability, and maintainability (RAM) are three attributes that influence a system’s potential to meet its mission goals and influence the lifecycle costs. To put it simply, we can say that RAM is an organization's confidence in its hardware, software, and networks. Each attribute highlights the system’s strengths and weaknesses and its impact on customer satisfaction and productivity. 

Reliability is referred to as the probability that a system will continuously perform its intended operation over a given period of time without failure. However, every hardware and software component is subject to failure at some point, so failure metrics such as MTTR, and MTTF are used to measure and predict the reliability of a system and its components. Reliability is often a subjective measurement, depending on how users perceive the importance of different components.

Availability is a system’s ability to operate as intended whenever the need arises. It’s calculated by dividing MTBF by the sum of MTTR and MTBF. 

Maintainability is the rate at which a system and its components can be repaired to replace after failure to restore operation. The maintainability of a system depends on several factors including the quality of equipment, its installation, skills of the IT personnel, and the procedure’s efficiency.

Importance of MTTR in SRE and DevOps

MTTR is an important metric for SRE and DevOps teams. It refers to the team's efficiency and quality of service rather than the system itself. In DevOps and SRE practices, MTTR generally measures the reliability and availability of an IT system based on how well your processes function. It's directly proportional to customer happiness which is why reducing MTTR is critical. Higher MTTR and longer downtim can harm a company's reputation among its customers when they have to wait hours for you to fix the issue. In the worst case, bad MMTR metrics can violate the SLA leading to huge expenses. 

How Can Blameless Help with MTTR?

Implementing sound monitoring practices and leveraging automation tools can help reduce MTTR and eventually the downtime. Blameless offers tools to help you automate incident resolution, create incident retrospectives, and various integrations for your communication, alerting, APM, and other tools. Want to learn more? Sign up for the newsletter below or request a demo.