10 Key DevOps Metrics to Manage Deployment Pipeline

With the continuous development in DevOps practice and its unparalleled benefits, now every organization wants to embed it in their software development lifecycle to make the deployment of software even faster and more efficient.

DevOps is all about evolving an IT organization to seamlessly integrate development, operations, and quality assurance teams, and also provide continuous deployment and delivery of software. With the proper implementation of DevOps, it can deliver high-quality software at faster rates, ensuring that customer requirements are met, hence improving the overall customer experience.

But here comes the major challenge, after the successful integration of DevOps in your software development process, how would you determine whether it is yielding the desired outcomes or not? How would you identify the gaps and improve the overall customer experience?

Productivity in software development has always been a complex component to measure and monitoring DevOps performance is pivotal to ensuring that the outcomes are never compromised and always helps boost the software development lifecycle.

The key solution to determine the robustness of the DevOps operations is to create – ‘metrics’. With the help of DevOps metrics, you can easily quantify the efficiency, reliability, and performance of any software project. It’ll provide data-driven insights on how IT processes are being operated in order to make informed decisions for the better quality of services and also to uncover areas for improvement and innovation.

This informative article will discuss 10 crucial DevOps metrics that will allow you to determine whether your existing DevOps implementation is providing optimum outcomes or not.  

10 Crucial DevOps Metrics You Need to Start Measuring:

There is no one-size-fits-all metric to track and analyze the performance of every component involved in the software development process. Every metric is designed to operate differently. Depending on the context, some are more useful than others. The goal is to choose the metrics that fit right with your organization’s requirements and will answer the questions that are most crucial to your enterprise – those that focus on specific business outcomes.

For instance, if efficiency is a key focus, then you would focus on more cost-centric measurements. On the other hand, if customer satisfaction is a priority then opting for a Net Promoter Score would be more appropriate. These DevOps metrics are a great way to monitor how seamlessly your teams are implementing the DevOps approach and its principles. This is why choosing the right metrics is a significant task. Here are ten DevOps metrics that will benefit your business –

1. Deployment Frequency-

The deployment frequency is one of the most fundamental metrics that show how frequently an organization deploys code to production successfully. It reflects the stability and quality of your software engineering teams and the speed at which they work.

It is important to increase the deployment frequency rates as it helps in the improvement of existing software by identifying the underlying bugs that may be causing delays in release or service. This also allows the organization to measure the short-term as well as long-term efficiency of their DevOps team.

The higher the deployment frequencies, the more the team releases high-quality code. Whereas, lower deployment frequencies indicate a bottleneck somewhere within the DevOps team workflow.

At one of the DevOps Con Berlin Conferences, software engineers suggested that enterprises having a deployment frequency of 13 per day are in a pretty good state. Moreover, it’s better to have more deployments with fewer changes instead of having fewer deployments with significant changes because it’s convenient for engineers to manage and integrate into applications.

According to DevOps Research and Assessment (DORA) metric Standard:

2. Lead Time for Changes

The Lead time for Changes measures the time it takes for a code (such as a bug fix or new feature) to move from commit to reach production.

This metric is an indicator to track the capacity of the software development team on how quickly they react to code changes and fix bugs. It depicts their effectiveness in adapting to change as projects evolve to meet users’ ever-changing requirements.

Usually, long lead times indicate inefficient processes and low team productivity whereas short lead times reflect an overall smooth DevOps implementation. This metric also facilitates enterprises with data-driven insights into how much their development team has to work in order to decrease the delivery time.

However, this is not applicable to every project. Complex projects may require more than the usual average time. It does not necessarily mean that the team is inefficient.

To measure the lead time for changes, there is a specific formula as well –

According to DevOps Research and Assessment (DORA) metric Standard:

 3. MTTR (Mean Time To Recover)

Every organization’s aim is to experience minimum failures and to recover from them as quickly as possible. This metric is used to measure the average time it takes for a team to fix a bug after it’s been detected. This period also covers the time taken to identify a failure and then taking the required action to restore normal functions.

This is one of the DevOps metrics that developers should keep as low as possible. As a high MTTR indicates your team is struggling to keep up with customer requirements, while a low MTTR suggests that you’re able to quickly identify and correct issues.

This metric is crucial for businesses that want to evaluate the capabilities of their teams and also ensure that their customers have a positive experience.

According to DevOps Research and Assessment (DORA) metric Standard:

 4. Change Failure Rate

The Change Failure Rate metric measures the number of times deployments have caused a failure in production and require further solutions. Failure is usually caused by data loss, inadequate testing, incorrect behavior, or an application outage.

This metric is used to identify all the changes that were implemented, and then determine how many of them failed. A high rate of change failure impacts the end-user experience and constantly requires admins to invest additional time to troubleshoot issues and fix bugs.

The change failure rate is crucial for organizations as it analyzes how the development team manages deployments and improves the overall change success rate. It also provides businesses with a comprehensive measurement of a team’s performance and if they have been successful in ensuring software functionality and stability.

According to DevOps Research and Assessment (DORA) metric Standard:

5. Change Volume

The metric for deployment frequency can be confusing if you’re not also measuring the volume of change between deployments. For instance, if 100 deployments take place, but with only a few changes or 8-9 lines of new code, it does not mean much for team efficiency. In that case, these deployments are so insignificant that they hardly have any positive impact on the project as a whole.

Change volume is another vital DevOps metric that shows how much code is not being changed during those deployments instead of the amount of code being changed regularly. To succeed with frequent deployments, there should not be any significant increase in change volume.

The key focus should be making impactful updates that provide a better experience with less disruption instead of having minor insignificant changes.

6. Availability

Every enterprise aims to achieve high quality and speed for its software, but application downtime is an inevitable factor. It is thus necessary to have a metric that will indicate the application’s availability and uptime to plan maintenance.

This application availability metric acts as an indicator that shows the time duration in which an app is fully functional and accessible to all its end users in a given period of time. It helps the team to take necessary actions during downtime to resolve the outage. For any organization, it is essential to keep their services online as much as possible, which creates uptime goals as high as 99.999%.

7. Customer Ticket Volume

The success of your application is directly linked to customer satisfaction. Customer Ticket Volume is an effective way to measure end-user experience. This metric is used to analyze the performance of your application and the state of end-user satisfaction.

The customer ticket volume gives you an idea about the bugs that must have slipped through the cracks in the testing cycle. This metric is a vital indicator of application reliability, and making the tickets based on their priority increases the chances of user satisfaction in the long run.

A high ticket volume reflects an underlying issue with the code that should be fixed immediately whereas a low ticket volume indicates application robustness. Developers can apply this metric to identify and fix bugs that were not detected during the testing stage.

8. Application Performance

The application performance metric is used to measure and quantify how efficiently software performs. It is crucial to monitor the software performance before and after deployment as some of the performance parameters such as SQL queries, and other dependencies can change after application deployment.

This metric can help identify any underlying errors or obscure bugs, allowing the program to become more stable, reliable, and efficient with its features.  Therefore, It is a good practice to look for hidden errors, or any other potential issues before deploying an application.

9. Defect Escape Rate

Every software will have certain bugs or errors during its SDLC process. It’s the task of the testing team to detect the issues during the testing stage of the pipeline. Sometimes, these bugs can go undetected through this testing stage and may reach the end-users.

The defect escape rate is a metric that detects all such bugs that bypass the testing phase – usually during regression or acceptance testing after a software feature has been deployed into production.

This DevOps metric also makes you aware of the condition of test automation tools and whether it is required to slow down the testing process or not.

A high defect escape rate indicates loopholes in code review and inefficiency in QA testing.

10. Unplanned Work

This DevOps metric is about analyzing the time consumed by the DevOps team on unplanned work. This metric helps track the overall productivity of the team. To measure this KPI, the team must quantify the amount of work aligned for a release at the beginning of the cycle, and compare that to the actual work necessary to complete the deployment.

The more time teams spend on unplanned work, such as detecting and then resolving bugs in production, the more likely there’s an issue present in the DevOps approach. It is also required to keep the track of insufficient testing practices, or any discontinued tasks for proper analysis. So, in order to decrease the risk of IT burnout, the team should avoid spending their time on unnecessary work.

The Bottom Line: Choose the Right KPI for Your Enterprise

With all this information, now you have better insights into various metrics that are required in the DevOps CI/CD pipeline. Implementing a successful DevOps process enables organizations to build, test, deploy, and monitor applications faster and more efficiently. These DevOps metrics help businesses to measure the performance of their team and ensure agility and transparency in organizations.

If you want a technology partner to help you implement the right DevOps metrics for your project then Daffodil is the right place for your organization. Our  DevOps experts will understand your requirements and goals to deliver an entirely customized roadmap for your specific business need.