What Are the DORA Metrics?
The DevOps Research and Assessment (DORA) group published its State of DevOps report with insights from six years of research.
It identified four key metrics for measuring DevOps performance, known as the DORA metrics:
- Deployment frequency
- Lead time for changes
- Change failure rate
- Mean time to recover
According to DORA’s research, high performing DevOps teams are those who optimize for these metrics. Organizations can use the metrics to measure performance of software development teams and improve the effectiveness of DevOps operations.
DORA started as an independent DevOps research group and was acquired by Google in 2018. Beyond the DORA Metrics, DORA provides DevOps best practices that help organizations improve software development and delivery through data-driven insights. DORA continues to publish DevOps studies and reports for the general public, and supports the Google Cloud team to improve software delivery for Google customers.
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The 4 DORA Metrics
DORA Group research found that the most successful DevOps teams are those who optimize for the following metrics:
1. Deployment Frequency
This metric refers to how often an organization deploys code to production or to end users. Successful teams deploy on-demand, often multiple times per day, while underperforming teams deploy monthly or even once every several months.
This metric stresses the value of continuous development, which implies a high frequency of deployment. Teams should aim to deploy on-demand to get consistent feedback and deliver value faster to end users.
Deployment frequency might be defined differently in different organizations, depending on what is considered a successful deployment.
2. Change Lead Time
This metric measures the total time between the receipt of a change request and deployment of the change to production, meaning it is delivered to the customer. Delivery cycles help understand the effectiveness of the development process. Long lead times (typically measured in weeks) can be the result of process inefficiencies or bottlenecks in the development or deployment pipeline. Good lead times (typically around 15 minutes) indicate an efficient development process.
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3. Change Failure Rate
The change failure rate measures the rate at which changes in production result in a rollback, failure, or other production incident. This measures the quality of code teams are deploying to production. The lower the percentage the better, with the ultimate goal being to improve failure rate over time as skills and processes improve. DORA research shows high performing DevOps teams have a change failure rate of 0-15%.
4. Mean Time to Recover
This metric measures the time it takes for a service to recover from a failure. In all DevOps teams, no matter how effective, unplanned outages and incidents will happen. Because failures are unavoidable, the time it takes to restore a system or application is critical to DevOps success.
When companies have short recovery times, leadership has more confidence to support innovation. This creates a competitive advantage and improves business profits. On the contrary, when failure is expensive and difficult to recover from, leadership will tend to be more conservative and inhibit new development.
This metric is important because it encourages engineers to build more robust systems. This is usually calculated by tracking the average time from reporting a bug to deploying a bug fix. According to DORA research, successful teams have an MTTR of around five minutes, while MTTR of hours or more is considered sub-par.
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