DevOps Metrics and KPIs

DevOps Metrics and KPIs

DevOps seems promising, and lots of organizations have already integrated it or are planning to commit to it. But Gartner has predicted that through 2022, 75% of DevOps initiatives will fail to meet the expectations.

A bold prediction. Isn’t it?

Well, it is, as it puts a huge investment on the stake ( almost 2.9 billion USD).

So, should you use it or not?

Definitely. You should use DevOps because it has a lot more to offer than one might think, but instead of just focusing on the benefits alone, your focus should be on making it workable for your organization.

And one of the best ways to do it is by measuring DevOps performance through KPIs and metrics.

If you don’t know about DevOps KPIs and metrics, then keep reading this post.

What Are DevOps KPIs and Metrics?

The DevOps methodology involves lots of phases that are interdependent. If one collapses other follows. So it is better to track the performance of each stage through pre-defined KPIs and metrics.

KPIs and metrics are nothing but parameters that monitor the progress of the DevOps. If something is happening too often, and a particular metric suggests it is a bad sign for proceeding further, you should introspect and move ahead. If you overlook it, chances are you’re heading for a partial or complete failure.

Another significant thing is that there are lots of DevOps KPIs and metrics that you should consider for a comprehensive DevOps strategy.

Essential DevOps KPIs  and Metrics:

  • Deployment Frequency: Deployment frequency indicates how often new features are launched. This frequency can be measured on a daily or weekly basis. Many organizations prefer to track deployments daily to improve efficiency. In an ideal situation, the frequency of deployment should be stable or it can increase gradually. A sudden decrease in the deployment frequency indicates faults within the existing workflows. More deployments are considered better but to some extent. Higher frequency results in increased deployment time or higher failure rate. In that case, it is good to restrict deployment increases until the existing issues are resolved.
  • Change Volume: DevOps is known for making changes often, but these changes should be impactful, not incremental. In simple words, it does not matter whether you change or alter the functionality of a feature in a week or month, instead, it should create an impact, not a disturbance. Sometimes making changes too often points out the inefficiency of the development process that can be tracked by the change volume metric.
  • Deployment Time: It measures the application’s deployment time after it gets approval. If the deployment time increases, there should be a further investigation to check whether deployment volume is reduced or not. A shorter deployment is always preferred but it should not come at the cost of accuracy. If the number of errors is increased, it means that deployments occur too promptly.
  • Failed Deployment Rate: It monitors how many times the deployment led to outages or other issues. The failed deployment rate should be as low as possible as increasing failed deployment rate suggests the dysfunction in the workflow.
  • Change Failure Rate: The change failure rate refers to a release that leads to unexpected outages or other unplanned failures. A low change failure rate indicates that deployments are occurring regularly and quickly. Contrary, a high change failure rate suggests application instability that leads to a bad user experience.
  • Time to Detection: It’s important to know that a low change failure rate is not the indicator of an ideal application. The primary focus of the developer should be to search out for solutions to minimize or even eradicate failures. To do so they need to catch issues quickly as they arise. That’s why the time to detection KPI comes in handy as it determines whether current response efforts are adequate or not. If there is more involvement in time for detection it’s a clear sign that there are possible bottlenecks that could ruin the entire workflow.
  • Mean Time to Recovery: Once you detect the failed deployments or changes, you should also track the time taken to address the problems so that the entire application can get back on track. The mean time to recovery is an important metric that monitors your ability to respond appropriately to identified issues. Prompt detection means nothing if you are not able to correct the issue on time. That’s why MTTR is given preference in the DevOps community because it’s a key performance indicator metric.
  • Lead Time: Lead time is used to measure how long it takes for a change to occur. This metric can be used at various phases, from the beginning, which is the idea initiation, to the deployment, and production phase. Lead time offers significant insight into the efficiency of the entire development process. It measures the current ability to meet the customer demand. If there is a long lead time it indicates that there are some serious bottlenecks while a shorter time indicates that feedback is addressed quickly.
  • Defect Escape Rate: Each software deployment includes the risk of sparking new defects. These issues can be discovered with user acceptance testing but sometimes these errors are found by the end-user. Since errors are the natural part of the development process, the development team should plan to deal with these issues before the development process. Defect escape rate comes into play to deal with such scenarios. It monitors the reality by accepting that issues will arise and they should be discovered as early as possible. The defect escape rate checks how often defects are discovered in the preproduction phase versus during the production phase. This metric alone provides essential insights into the quality of software releases.
  • Defect Volume: This matrix is related to the previous metric but to some extent. Instead of focusing on the defects, it monitors the volume of defects. Some defects are expected but a sudden increase in the defects is not a good sign. If there is a sudden increase or a high volume of defects is monitored, it is the indicator that the development process or test data management may have some crucial issues to fix.
  • Availability: This metric measures the amount of downtime for a particular application. It can monitor the availability of a particular application as complete or partial. Less time downtime is always better. But some instances, planned or unplanned, may require you to spend time to correct the issues so the application can be available to the users once again. The availability metric tracks the downtime for both scenarios as the hundred percent availability for a particular application is not realistic.
  • Service Level Agreement Compliance: Most companies prefer to operate according to service level agreements. These agreements are held between the client and the service providers to increase transparency. The service level compliance KPIs provide necessary accountability so that it can ensure that the client’s expectations are met.
  • Unplanned Work: Due to some issues or problems you can encounter unplanned work. The unplanned work rate metric (UWR) measures how much time you dedicate to unplanned work. Generally, UWR will not exceed 25%. In case if there is a UWR it reveals that there has been time wasted on unexpected errors that were not detected in the workflow. Sometimes UWR and the rework rate RWR, both metrics are done together to know that how much time it took to address new tickets.
  • Customer Ticket Volume: Like the defect escape rate, API suggests that not all the defects are bad but they should be caught early. However, if the end-user is reporting any error and the customer ticket volume of such errors is high, it indicates that there are issues in production or testing.
  • Cycle Time: This metric tracks the functionality of an application on a border level. From the early stages to the user feedback, it tracks all the processes. Generally, a shorter cycle time is preferred but defects should also be discovered once they arise.


DevOps is creating a buzz but switching over technology is never easy. No doubt that it is helpful and better for scaling. However, it can also collapse like the other methodologies, still, you need not panic.

If you incorporate these DevOps KPIs and metrics into the practice, you avert the risk of failing.