The Ultimate Guide to DevOps Metrics

Measuring outcomes is an important aspect of DevOps culture. Software Delivery metrics play an important role in DevOps. Even though DevOps has been around for quite a while now, many teams are still finding it difficult to adopt the practices and principles.

One of the main benefits of DevOps is the continuous optimization of software through measurements. These measurements are the metrics. Understanding these metrics can be a challenging topic to understand.

In this blog, we will take a look at some important metrics to track and

What are DevOps metrics?

DevOps metrics are data points that are used to measure the progress of a software delivery. These metrics reveal the performance of a DevOps software development pipeline and help quickly identify and remove any bottlenecks in the process.

These metrics are used to measure the progress of software delivery as a whole, monitor processes, and aid in the decision-making process. They are also used to measure the overall health of the project. DevOps metrics help in identifying and removing any bottlenecks.

Why are DevOps metrics important?

DevOps metrics or indicator must have following 5 characteristcs, which can help you provide insights about the progress of a DevOps initiative or the performance of DevOps teams:

Measurable—metrics must have standardized values that are consistent over time.
Relevant—metrics should measure aspects that are important to the business.
Reliable—team members cannot affect or “game” the measurement.
Actionable—long-term analysis of the metric should provide insights into possible improvements in systems, workflows, strategies, etc.
Traceable—the metrics should point directly to a root cause, not just allude to a general problem.

Metrics are important because they help measure the performance of software delivery. Without metrics, there is no way to know whether or not your project or program is going in the right direction. Without metrics, you would have no idea if your product is meeting customer needs, if the development teams are making progress, and if the company is making money. Metrics are important because they help project owners, executives, and managers make decisions about how to allocate resources. Without metrics, it would be tough to make data-driven decisions.

What are the key metrics?

DORA helped identify key metrics as critical data points that are considered targeted and easy to implement in most situations. There are four such measurements that are often used as KPIs to help capture overall software delivery performance.

Deployment Frequency

One of the first principles of DevOps is to deploy often. This is a method to show the value of your automation and various integrations with anything from the code repository to the deployment target. The information for this metric is usually derived from the software used to deploy. In most cases, the major build and deploy products in the market have built-in reporting available for such data. Using just this data point may show your DevOps has progressed to a higher level of performance. However, as with most metrics, it needs to be examined alongside other data to ensure that deployment frequency isn’t being increased due to a desire to show progress when there isn’t one.

Lead Time

The span of time starting from the moment a developer commits their changes to the moment where it is running in a production environment is called lead time. Lead time is a quick indicator that shows how well your DevOps automation is going. Long lead times could mean there are more areas to improve as far as automation opportunities and efficiency. The lead time metric is a good indicator of how rapidly the team can respond to feedback and feature requests. It might be hard to set a target for this measure, however, the goal that you should strive for is seeing improvement over time.

Mean Time To Recover

This is a metric that shows the amount of time taken to recover from a failure. Collecting this data will show how well a team is able to respond to a deflect, reconfiguration, or other troubleshooting actions. With multiple things to consider, the information gathered may be one that deserves multiple points to be calculated, eg- does the value consider the time taken to recover in deployment vs. production?

A calculation of this metric can be constructed by using data from service tickets for both internal external customers, The ticket and SLA metrics are measured against other metrics such as “lead time” to understand the “time to recover”. Means and Averages will allow for a metric that has a targetable aspect. The main question is how quickly the team is able to recognize the root cause, understand it, solve it and deploy the solution when a problem arises.

Change Failure Rate

This metric captures the rate of failures, this metric is centered around the quality of code being deployed towards production and also the quality of your DevOps gates. At first, you may believe that a failure rate of zero would be better, but that is not possible in a real scenario, and in most cases, it would not point to a high development quality but a low quality of DevOps gates. A high amount of change failure rate will show that your automation is working properly as designed, but you may have a problem with your developer, or you could be missing prior gates. If there is a high change failure rate, things are not good, even if DevOps is doing its best. Using release management software, this metric can be found easily.

Other potential DevOps Metrics to track

Failed Deployments

This metric is about how many deployments failed when they were attempted, this metric should not be mistaken for failed releases. This metric indicates an unstable release environment, but it could also be configuration errors in the way builds and releases are being executed. If you have issues with failed deployments be sure to track them over time.

Deployment Time

Tracking how long it takes to do an actual deployment is another good metric. This metric is either very important or not as critical as it may be for other teams. This metric could suggest that more resources are needed to build agents. This measure is a subset of Lead Time, focusing only on the deployment part, without the CI pipeline part of building and testing.

App Availability

App availability measures the proportion of time an application is completely functional and available to meet user needs. To accurately measure application availability, first, you should make sure that you can accurately measure the user experience, not just the network statistics. While teams don’t always anticipate downtime, they often plan for it because of maintenance. Planned downtime makes communication between DevOps and SRE team members crucial to settle unanticipated failures and ensure both frontend and backend operate smoothly.

App Usage Insights

App usage and traffic monitor the total number of users accessing your system. Once you’ve deployed your software, It’s crucial to know how many users access your software and the number of transactions occurring to ensure everything is operating smoothly. These metrics are useful for indirect feedback, they also help in informing other important metrics. App usage and traffic monitor the number of users accessing your system and inform many other metrics, including system uptime. This metric can help the DevOps team to make sure that all systems operate as they should resulting in the happiness of the user.

Conclusion

Continuous improvement is a core principle of DevOps teams. The ability to track and measure performance lets the team accelerate speed and improve the quality. For high performance, a team must understand the continuous improvement areas and metrics to provide a data driven view of decision making.

We hope this blog has helped you assess your DevOps initiative and you can leverage the metrics to drive data driven decisions. Our DevOps Transformation Consulting experts can help you define your DevOps strategy/ roadmap, work with you to implement and rollout DevOps metrics and also help you understand the overall DevOps culture.