What is the significance of DORA Metrics?
DORA metrics aid engineers take data-driven decisions to continually improve their practices to deliver software faster and ensure that it stays solid. Four metrics are:
- Change Lead Time
- Deployment Frequency
- Change Failure Rate
- Mean Time To Recovery (MTTR)
“You cannot improve what you don’t quantify.” It’s a rule to follow in the context of DevOps. Making DevOps measureable is crucial to knowing and invest in processes and tools work and to correct or eliminate those that aren’t. DORA metrics are now the standard for teams seeking to maximize their efficiency and attain the DevOps goals in terms of stability and speed.
Do you know what DORA is?
The DevOps Research and Assessment (DORA) team is a research-based program which was purchased by Google in the year 2018. Their aim is to discover the processes, practices, and capabilities that allow teams to deliver high-performance in the field of software and deliver value. From 2014 to 2019the group released their most well-known research, which included a series of annual reports that benchmark DevOps practices, provide answers to questions that are common to all DevOps team members, and then give guidance on the ways DevOps teams can continue to enhance their capabilities and processes.
In their book of the year, Accelerate The DORA group identified a number of measures that they claim shows the effectiveness of software teams in relation to development as well as delivery capability. Length of Lead, Time to Deployment Mean Time from Resolution along with Change Failure rate. These are the metrics that have become known by the name of DORA metrics.
The DORA group discovered that top software teams – the ones which provide the greatest value, are the fastest and consistently – improve for four specific factors particularly:
Change Lead Time
Change lead time is the duration of time between the point at which work on a change request initiated until the change has been put into production, and therefore handed over to the customer. Leap time allows you to understand the efficiency of the development process we use is. The long lead time could be due to an slow process or bottlenecks along the pipeline for development or deployment.
The most commonly used method to determine lead time is to compare the time of the initial commit of code to an issue with the date of deployment. A more complete (though it is also harder to define) approach is to evaluate the time an issue is chosen for development to the date of deployment.
The Deployment Frequency
Deployment Frequency tells you how often an organization pushes changes into production. This is how fast you team has been delivering the software at your speed. DORA informs us that the best performance teams strive to make smaller and more frequently scheduled deployments. This can result in improving the efficiency for customers as well as reducing risk (smaller modifications mean less trouble in the event that changes cause production problems) for the team working on development.
Change Failure Rate
The Change Failure Rate a measure of the speed of production changes that can cause rollbacks, incidents or even failures. This is a measure of how well your code is performing when you’re pushing into production. The lower the percentage here, the more efficient (higher performers have a failure rate for changes of between 0 and 15 percent) however the main objective of the team in this case is to reduce the rate of failure to change in the course of time as their capabilities and processes get better.
The biggest challenge for most teams is defining what constitutes a failure for the team. It is too broad or limiting of a definition are likely to encourage the wrong behavior. The definition of failure must be specific for each service, company or even a the team.
Mean Time To Recovery (MTTR)
MTTR is all about resolving issues and production failures when they occur. It’s the measure of the period of time between the moment an incident is initiated to the point at which it was resolved by changes to production. The aim of optimizing MTTR is to reduce the amount of downtime and then, as time passes develop the systems to identify, diagnose, and rectify issues when they occur.
Utilizing DORA metrics to help you improve your DevOps methods
As an engineer as an engineer, you’re in a position to provide your team with direction and tools needed to be successful. By analyzing and monitoring DORA metrics and developments over time, teams, developers and engineers are able to make better informed decisions on what needs to be improved and the best way to improve developing processes. If your DORA metrics increase you’ll be able to feel confident that you’ve taken the right decisions to empower your team and also that you’re providing greater value to your customers.