Wondering about software reliability metrics? We explain the important metrics you need to track.
What are software reliability metrics?
Software reliability metrics are used to measure an aspect of a software’s reliability. Some common metrics are:
- Mean Time to Failure (MTTF)
- Mean Time to Repair (MTTR)
- Rate of occurrence of failure (ROCOF)
- Mean Time Between Failure (MTBR)
- Probability Of Failure On Demand (POFOD)
- Availability (AVAIL)
Why do software reliability metrics matter?
As products scale and teams grow, software reliability becomes all the more critical. Software reliability metrics give teams insight into how the product performs and what customers are experiencing. No one wants a buggy, failing product, but without metrics in place, how can you identify what problems need to be solved? Applying a software reliability methodology enables teams to measure product performance across different functions and maintain customer trust. The metric provides a birds-eye view into every part of the product and gives teams the data needed to prioritize fixes and issues.
SLAs, SLOs, and software reliability metrics
Software reliability metrics are also integral in meeting reliability targets. Teams may have Service Level Agreements (SLAs) that guarantee to users reliability metrics above some threshold. These can have legal consequences if not met. By creating Service Level Objects (SLOs) that are stricter than SLAs, teams can ensure that SLAs aren’t breached.
Teams can use SLOs to set up target values and expectations around service performance, but without metrics in place, there is no way to measure whether these objectives are actually being met and where improvement is needed. The metrics are an accurate and comprehensive way to measure various performance aspects and understand how those affect SLOs set by the teams.
What are the different types of software reliability metrics?
Multiple types of software reliability metrics monitor different parts of the software. They are used as a comprehensive way to measure every function of the software as well as how frequently they’re used.
Software reliability methodology measures two different segments. One looks at validating the software’s functional behavior against requirements, and the other segment looks at functions and performance. We’ll look at some of the essential software reliability metrics in more detail to understand their role during the development process.
Mean Time To Failure (MTTF)
MTTF looks at how much time has elapsed between two failure occurrences, and it’s averaged over the total number of failures. The metric only looks at the time interval between the failures – not the time it took to fix the error and get the software back up and running. It’s an important metric to understand how long software can perform before failing and gives developers the ability to predict failures better and get ahead of issues moving forward.
Mean Time To Repair (MTTR)
Building off MTTF, MTTR is used to measure the average time taken to track the cause of the error and repair it. It’s a metric used to understand how long it takes to fix an error after a failure occurs and is helpful to help teams understand their working process for reliability and come up with ways to improve.
Mean Time Between Failure (MTBF)
To calculate MTBF, you’ll need to put together MTTF and MTTR like this.
MTTF + MTTR = MTBF
This metric enables teams to better predict when the next failure can be expected and helps teams understand the length of uptime and predict software reliability.
Rate of Occurrence of Failure (ROCOF)
As the name might suggest, ROCOF is a metric to understand the frequency of failures. While the other metrics measure the length of time between failures and how long it takes to repair, this metric is used to understand how often failures occur.
The metric is calculated by looking at how the software performs over a specific time period. The ROCOF value is a ratio of the total number of failures and the length of the observation.
Probability Of Failure On Demand (POFOD)
POFOD is used to measure the likelihood of the system failing when services are requested. It measures the possibility of the system failing when receiving a service request.It can be used in systems where services are requested at an infrequent pace. It’s calculated as failures/requests
over a specific time interval.
Availability measures how likely the system is available for the user in a specific time interval. It encompasses the number of failures, downtime, and repair needed to fix the failure to represent the total amount of time a system is unavailable.
It measures how likely the system would be available for use over a given period of time. Availability helps teams understand software reliability on a broader level and how it affects the customer experience.
What do with metrics
Employing a software reliability methodology isn’t just about tracking metrics, but it’s also about how teams improve. Before instituting a set of metrics to follow, it’s crucial to come together as a team to set up SLAs, SLOs, and service level indicators (SLIs) that make the most sense for the product.
Having an error budget established also helps teams balance innovation and reliability.
Once there’s a site reliability structure in place, it’s time to employ metrics. Creating a comprehensive system that measures each aspect of reliability gives teams a better understanding of improving the product and customer experience moving forward. Plus, it gives them insight into what needs to be prioritized to build a better product and which metrics are the most pressing.
Another thing to bear in mind is that SRE implementation comes with growing pains, and incidents might increase before they get better. Communicating that to teams is vital, so they don’t get discouraged as they discover latent incidents. As the team exposes and fixes issues, the product will get better in the long run. You can read more on how to structure site reliability teams here.
How can Blameless help?
Blameless SLO and incident retrospective tools help teams achieve SRE goals by collecting the data and analysis needed for faster incident resolution and ongoing team learning. In addition, the Reliability Insights platform by Blameless helps teams explore, analyze and share reliability data quickly and efficiently to make team learning a collaborative process. To learn more, check out a demo or sign up for our newsletter below.