DORA is an acronym for “DevOps Research and Assessment.” Dr. Nicole Forsgren, Jez Humble, and Gene Kim developed these metrics for their book “Accelerate: The Science of Lean Software and DevOps: Building and Scaling High-Performing Technology Organizations.”1
Are you tired of feeling like your software development process is a bit of a black box? Do you wish you had a better way to measure your team’s progress and identify areas for improvement? Well, have no fear because DORA metrics are here!
You are probably familiar with what are DORA metrics if you are involved in DevOps. A potent set of performance indicators, called DORA metrics, can assist you in gaining visibility into your software development process and helping you in making data-driven decisions.
In this blog post, we will explore what are DORA metrics, what are the 4 key DORA metrics, how they are calculated, and how you can use them to improve your DevOps performance.
What are DORA Metrics?
The DevOps Research and Assessment (DORA) team, made up of Nicole Forsgren, Jez Humble, and Gene Kim, undertook a multi-year research project to pinpoint the critical variables that influence the efficiency of software delivery.2 They discovered that successful teams shared particular cultural norms and practices. This study served as the foundation for the DORA team’s development of a set of metrics that could be used to assess the effectiveness of software delivery and identify areas for improvement.3
Measuring specific elements of the software development process, such as the number of lines of code or bugs, is typically the focus of traditional software metrics. However, they do not always offer a complete picture of software delivery performance, even though these metrics can help provide information.
On the other hand, DORA metrics are made to assess the general effectiveness of the software delivery procedure. They concentrate on four main areas: change failure rate, change lead time, time to restore service, and deployment frequency. Teams can better understand their software delivery performance and pinpoint areas for development by tracking these metrics.
The use of DORA metrics has changed how we assess software delivery efficiency. They give teams a more thorough picture of performance than traditional metrics and are made to help them pinpoint problem areas and streamline the software delivery process.
What are the Four Key DORA Metrics?
- Deployment Frequency: The frequency with which code is deployed into production is gauged by this metric. High deployment frequency means teams can roll out software updates frequently, enabling quicker feedback cycles. The number of deployments over a specified period is counted to determine this metric. The ability to deploy code more frequently enables high-performing teams to provide users with new features and fixes more quickly.
- Lead Time for Changes: This is a metric used to determine how long it takes for a code change to be implemented ( for changes to be deployed to production from the time they are first committed to the repository.) A shorter lead time suggests that teams can deliver software changes more quickly, which is critical for providing customers with value more quickly. The time between a code commit and a production deployment is used to measure this metric. High-performing teams can deploy code changes with little to no lead time.
- Mean Time to Recover (MTTR): The average time it takes to recover from a production incident, such as a service outage or security breach, is measured by the mean time to recover (MTTR) metric. It shows that teams can recover from incidents more quickly, lessening customer impact when service restoration times are shorter. The time between the discovery of an incident and the service restoration is used to calculate this metric. Faster recovery times enable high-performing teams to lessen the effect of incidents on users.
- Change Failure Rate: This metric tracks the proportion of code changes that cause a production incident or necessitate correction. Low change failure rates enable teams to deliver production changes with high quality and dependability. Significant change failure rates are a sign of low-performing teams’ insufficient testing of their code or insufficiently secure deployment of changes. The total number of deployments divided by the number of failed deployments or incidents yields this metric.
To calculate these metrics, teams can use practices such as continuous integration and continuous delivery pipelines, and monitoring and incident management systems. By routinely tracking and analyzing these metrics, teams can improve their DevOps practices to deliver software changes with greater speed, quality, and reliability.
How are the DORA metrics calculated?
The data gathered from your DevOps systems and tools calculate the DORA metrics. For instance, your continuous integration/continuous deployment (CI/CD) tool can be used to measure the frequency of deployments, while your version control system can be used to measure the lead time for changes.
To calculate these metrics, you must gather data over an extended period, such as a month or a quarter. The four DORA metrics can be determined using the data once gathered.
How can you enhance your DevOps performance using the DORA metrics?
- Identify areas for improvement: The DORA metrics can help you decide where your team needs to improve. For instance, if your change failure rate is high, you might need to implement more reliable deployment processes or improve your testing procedures.
- Set goals: Set objectives for your team to work towards after identifying areas that need improvement. For instance, you might aim to cut your change failure rate in half over the upcoming quarter.
- Track progress: The DORA metrics allow you to track how well you’re achieving your goals. Monitoring and assessing your performance on a regular basis will allow you to identify the areas where you are making progress and those where your strategy may need to be changed.
Teams can make data-driven decisions and increase their efficiency by using DORA metrics’ valuable insights into their software development processes. Organizations can improve their business outcomes, such as greater customer satisfaction and higher revenue, by optimizing their development pipeline. Numerous prosperous businesses have adopted DORA metrics and seen notable improvements in their development procedures.
Limitations of DORA metrics
While these metrics can be helpful, there are several challenges and limitations that you should be aware of.
- The possibility of DORA metrics being overly focused is one potential pitfall. They might only track a small number of variables, like lead time or deployment frequency. These metrics might not fully reflect a team’s performance, even though they can offer valuable insights into particular areas.
- The fact that DORA metrics might be tricky to interpret presents another difficulty. For instance, a high deployment frequency might appear to be good, but it could also mean that a team is releasing incomplete or bug-ridden code. It’s essential to consider DORA metrics and use additional data sources, such as customer feedback or code review data, to get a complete picture of a team’s performance.
- The use of DORA metrics to evaluate software development performance also has limitations. For some development projects, for instance, DORA metrics might not be appropriate. Performance metrics for teams working on highly regulated software, like those for medical devices, may differ from those working on consumer-facing apps.
- Additionally, the complexity of software development may not be considered by DORA metrics. For instance, a team working on a straightforward web application might be able to deploy code more frequently than a team on a complex, interconnected system. The latter team might need to conduct more testing and validation, which might reduce how frequently they deploy.
So, while DORA metrics can be a helpful tool for measuring software development performance, it’s essential to be aware of their limitations and potential pitfalls. You can better understand a team’s performance by using DORA metrics in conjunction with other information sources and taking them into context.
Despite these drawbacks, DORA has established DevOps standards that allow organizations to determine the metrics for Elite, High, Medium, and Low performing teams. This indicates that Elite teams have a twofold increased likelihood of exceeding their organizational performance targets.
The table below for instance also helps enterprises assess their DevOps maturity and where they stand based on their KPIs:
| Aspect of Software Delivery Performance | Elite IT Performers | High IT Performers | Medium IT Performers | Low IT Performers |
| Deployment FrequencyHow frequently does your company release code to users or deploy it to production? | On-demand (multiple deployments per day) | Between once per day and once per week | Between once per week and once per month | Between once per month and once every six months |
| Lead Time for ChangesHow long does it take for code to successfully run in production after it has been committed? | Less than one day | Between one day and one week | Between one week and one month | Between one month and six months |
| Mean Time to RecoverHow long does it take to restore service following a service incident or a bug that negatively affects users? | Less than an hour | Less than one day | Less than one day | Between one week and one month |
| Change Failure RateHow often does service degradation occur as a result of production or end-user changes? | 0-15% | 0-15% | 0-15% | 46-60% |
DORA Metrics on Ozone
Ozone offers the most simplest and meaningful dashboard available on a DevOps platform. Contrary to having to customize your dashboard with widgets and charts, the Ozone dashboard comes pre-configured with metrics that depict both DORA metrics and deployment related insights.
In the top row, a summary of deployments, rollbacks, failure rates, and commits and pull requests is provided. Below, detailed DORA metrics are visually represented.
Users are able to view particular project insights by using the filters for deployments, microservices, and clusters.
By switching to “Deployments,” the screen is updated to show you a thorough real-time overview of every deployment you have.
A set of filters lets you select between deployments, runtime, clusters, status, and namespace for accurate reporting. The top row includes a summary of all deployments, followed by the live pipeline status and any relevant visuals.
DORA metrics have revolutionized the software delivery industry by providing objective measures for DevOps performance. Ozone allows teams to track their DORA metrics and fine-tune their software delivery pipelines for maximum effectiveness and quality. Ozone is a must-try for any team looking to enhance DevOps performance and speed up software delivery thanks to its distinctive features like intelligent automation, predictive analytics, and collaborative workflows. So why not give Ozone a shot and advance your software distribution?
