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DevOps metrics
DevOps metrics are data points that directly reveal the performance of a DevOps software development pipeline and help quickly identify and remove any bottlenecks in the process. These metrics can be used to track both technical capabilities and team processes.
At its core, DevOps focuses on blurring the line between development and operations teams, enabling greater collaboration between developers and system administrators. Metrics allows DevOps teams to measure and assess collaborative workflows and track progress of achieving high-level goals including increased quality, faster release cycles, and improved application performance.
Four critical DevOps metrics
Though there are numerous metrics used to measure DevOps performance, the following are four key metrics every DevOps team should measure.
Four critical DevOps metrics
Deployment automation is critical to a continuous integration and continuous delivery (CI/CD) pipeline. CI/CD pipelines automate integrating, testing, and releasing code changes faster. It moves the changes into different environments, such as testing and production, progressing the updated code safely toward end users. Automating deployments ensures new code goes live quickly and reliably.
DevOps comprises software development practices for building, testing, and releasing software faster and more reliably. Deployment automation removes manual process bottlenecks and aligns with DevOps practices.
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Other related metrics
Another relevant metric is cycle time, which is the time a team spends working on an item until it is ready for shipment. In the development world, cycle time is the time from when developers make a commit to the moment it's deployed to production. This key DevOps metric helps project leads and engineering managers better understand what works well in the development pipeline. As a result, they can better align their work with the expectations of stakeholders and customers, ensuring their team's ship faster.
Cycle time reports allow project leads to establish a baseline for the development pipeline that can be used to evaluate future processes. When teams optimize for cycle time, developers typically have less work in progress and fewer inefficient workflows.
In Lean product management, there is a focus on value stream mapping , which is a visualization of the flow from product or feature concept to delivery. DevOps metrics provide many of the essential data points for effective value stream mapping and management but should be enhanced with other business and product metrics for a true end-to-end evaluation. For example, sprint burndown charts give insight into the efficacy of estimation and planning processes, while a Net Promoter Score indicates whether the final deliverable meets customers’ needs.
How to execute automated deployment
Automated deployments are vital in streamlining the DevOps pipeline. They help to reduce human errors, increase team productivity, and shorten iteration cycles.
The process includes critical steps such as code building, testing, and deployment. Shorter iteration times help teams improve and respond quickly to customer feedback.
Automated software deployment consists of the following steps:
- Commit code changes to a version control system such as Git.
- The code commit triggers an automated build process.
- Automatically test the new build artifacts.
- If tests are successful, deploy the build artifacts into a staging environment for further testing.
- After approval, deploy changes to the production environment.
- Collect metrics to track the deployment.
Open DevOps and Bitbucket Pipelines further streamline the process. Open DevOps provides a comprehensive automation framework that fosters collaboration. It can accommodate increasingly complex projects while mitigating the risk of human error and improving productivity.
Bitbucket Pipelines offers continuous integration with Bitbucket repositories. It supports configuration as code for versioning. Built-in integration within the Bitbucket environment supports streamlined collaboration and code traceability.
Other related metrics
Another relevant metric is cycle time, which is the time a team spends working on an item until it is ready for shipment. In the development world, cycle time is the time from when developers make a commit to the moment it's deployed to production. This key DevOps metric helps project leads and engineering managers better understand what works well in the development pipeline. As a result, they can better align their work with the expectations of stakeholders and customers, ensuring their team's ship faster.
Cycle time reports allow project leads to establish a baseline for the development pipeline that can be used to evaluate future processes. When teams optimize for cycle time, developers typically have less work in progress and fewer inefficient workflows.
In Lean product management, there is a focus on value stream mapping , which is a visualization of the flow from product or feature concept to delivery. DevOps metrics provide many of the essential data points for effective value stream mapping and management but should be enhanced with other business and product metrics for a true end-to-end evaluation. For example, sprint burndown charts give insight into the efficacy of estimation and planning processes, while a Net Promoter Score indicates whether the final deliverable meets customers’ needs.
In conclusion…
Continuous improvement is a core tenet of teams practicing DevOps. The ability to measure and track performance across lead time for changes, change failure rate, deployment frequency, and MTTR allows teams to accelerate velocity and increase quality. Learn more about how Atlassian helps you deliver better and faster value to customers with Code in Jira and Deployments in Jira.
In conclusion…
Continuous improvement is a core tenet of teams practicing DevOps. The ability to measure and track performance across lead time for changes, change failure rate, deployment frequency, and MTTR allows teams to accelerate velocity and increase quality. Learn more about how Atlassian helps you deliver better and faster value to customers with Code in Jira and Deployments in Jira.
In conclusion…
Continuous improvement is a core tenet of teams practicing DevOps. The ability to measure and track performance across lead time for changes, change failure rate, deployment frequency, and MTTR allows teams to accelerate velocity and increase quality. Learn more about how Atlassian helps you deliver better and faster value to customers with Code in Jira and Deployments in Jira.
How to measure, use, and improve DevOps metrics
Lead time for changes
High-performing teams typically measure lead times in hours, versus medium and low-performing teams who measure lead times in days, weeks, or even months.
Test automation, trunk-based development, and working in small batches are key elements to improve lead time. These practices enable developers to receive fast feedback on the quality of the code they commit so they can identify and remediate any defects. Long lead times are almost guaranteed if developers work on large changes that exist on separate branches, and rely on manual testing for quality control.
Change failure rate
High-performing teams have change failure rates in the 0-15 percent range.
The same practices that enable shorter lead times — test automation, trunk-based development, and working in small batches — correlate with a reduction in change failure rates. All these practices make defects much easier to identify and remediate.
Tracking and reporting on change failure rates isn’t only important for identifying and fixing bugs, but to ensure that new code releases meet security requirements.
Deployment frequency
High-performing teams can deploy changes on demand, and often do so many times a day. Lower-performing teams are often limited to deploying weekly or monthly.
The ability to deploy on demand requires an automated deployment pipeline that incorporates the automated testing and feedback mechanisms referenced in the previous sections, and minimizes the need for human intervention.
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