Measuring DevOps: Key ‘Metrics’ and ‘KPIs’ That Drive Success!

By Veritis

DevOps Key Metrics and KPIs

DevOps, the word that needs no introduction in a software environment! Making its entry as a process to streamline software delivery, DevOps emerged to become a whole and sole for most organizations.

Not just impacting the software delivery, DevOps best practices brought about an all-round cultural transformation filling the void among teams. Some of the DevOps automation tools include Ansible, Jenkins, Git, Kubernetes, Splunk, Docker, etc.

Standing as a key to the digital transformation, DevOps capabilities has also been successful in driving the desired Return on Investment and 100% customer satisfaction for many businesses.

All these advantages with DevOps don’t so come easily and the secret lies in the understanding of a few metrics and Key Performance Indicators (KPIs). CI/CD KPIs and SLAs are typically defined for this service, as they are for other company services, if a company runs CI/CD as a central service.

It’s critical to carefully consider the metrics you need to monitor and keep in mind that there is no one solution that works for all situations. The goal is to select the metrics that will provide the most relevant information for your company, preferably those that concentrate on particular business results.

Here, we bring the ‘Key DevOps Metrics and KPIs’ that stand crucial to successful DevOps journey:

Key DevOps Metrics and KPIs

1) Time and Frequency of Deployment

A single/bulky deployment for a more extended period is the old concept. In the DevOps transformation steps, more deployments get you more releases and improve your business interaction with the end-user. Tracking the frequency of deployments keeps you on track and helps you plan smaller deployments that ultimately reflect improved test and release cycles.

This will also cut down deployment time, which would often result in a lot of investigation time.

2) Change Volume

Code is the deciding factor here. Change Volume refers to the lines of code you push to production per deployment. Measuring this is crucial to measuring the success of deployment in terms of value, time and frequency.

3) Meantime To Failure

This is also referred to as the failed deployment rate and also related to change the volume. Increasing the meantime to failure and the low change volume causes process dysfunction, leading to delay in the workflow.

4) Meantime to Detection and Recovery

Meantime to Recovery (MTTR) is the time required to recover from a failed instance. This defines your organizational ability to face and address failures. This is one of the most popular DevOps automation metrics. Meanwhile, Mean time to Detection (MTTD) refers to the time you take to identify an issue, which requires application monitoring to identify at an early stage.

5) Change Failure Rate

Change failure rate is something that explains the extent of release failure caused by unexpected outages or other failures. A low change failure rate means faster and timely deployments. Whereas the high side of it means poor application performance impacting end-user satisfaction.

6) Lead Time

This is crucial if the end goal is ‘faster shipping’. This is measured as a time that the change process takes to happen, from start to the deployment phase. This helps you make estimates about the overall time a specific task will take to get into production.

7) Early Detection of Failure

This is as important as executing the process. Any unexpected failure may stall the process. Early detection of failure helps you find appropriate solutions without any delays and recover faster to get on track. It also helps you assess if the implemented response measures are enough.

8) Customer Feedback

More product feedbacks or alerts from your customer support team means more gaps in your business at the customer end. The worst thing that a business never expects is terrible feedback from the end-user. Given this factor, customer feedback (positive or negative) makes one of the most reliable metrics for DevOps services.

9) Automated Test Cases

Automated test cases have to be used to the maximum to derive better performance results in the DevOps strategy. Extensive usage of unit and functional testing naturally boosts the workflow velocity. Keep a close watch on code changes and their impact on test cases. Ensure automated tests run perfectly!

10) Service Level Agreements (SLAs)

Ensure to be compliant with your SLAs. Any disagreement with SLAs causes issues at a later stage hampering the workflow. It’s important to operate in line with your SLAs. In the absence of SLAs, make sure to stand in line with the set application requirements.

11) Availability

This refers to the presence of service during the downtime. It is usually in two ways as partial (read-only) and complete (read and write) availability. Less downtime results in more availability. However, 100 percent availability is unrealistic as planned downtimes would be required to conduct scheduled maintenance activity.

12) Unplanned Work Rate

This is another crucial DevOps metric that speaks the effective utilization of efforts. This calculates tracks the time spent on an unplanned work to that spent on a planned one. The unplanned work rate is often compared with the rework rate, which is linked to the efforts caused in addressing feedback.

13) Defect Volume and Escape Rate

This rate examines how often the defects are identified and uncovered at the pre-production phase compared to the production phase. The defect escape rate reflects the core principle that defects are a natural part of a software development cycle and should be identified early in the process.

14) Application Performance

Best practice is to check the application performance well before its deployment. There are specific tools that can help you trace performance issues, hidden errors and gaps within an application. This monitoring of application performance has to happen even after deployment.

15) Process Cycle Time

This KPI measures the total time taken from the stage of ideation to ending with user feedback. This metric presents a broader view of application deployment. Shorter cycles are highly recommended but not at the cost of defects.

[MUST READ: How to talk to CEOs, CFOs, CTOs about DevOps?]

Steps to Implementing DevOps ‘KPIs’

While we have seen a list of key metrics and KPIs, it’s equally important to know how they develop in a DevOps implementation process.

5 Steps to Implementing DevOps KPIs

The implementation of DevOps KPIs is built on five steps:

1) Identify

Identify the set of KPIs to be tracked for your organization

2) Create

Prepare dashboards to view or list KPI results

3) Evaluate

See how successful these KPIs are in meeting business goals

4) Change

Plan strategies for performance improvement in respective areas

5) Assess

Cross-check if KPIs meet the desired objectives and make changes, if necessary

These five steps help you in effective implementation of the identified KPIs and metrics to drive your DevOps success.

[MUST READ: DevOps Frequently Asked Questions]

In Conclusion

There are many such KPIs and metrics that contribute to DevOps success. Wait no more! Use these metrics and effectively implement them to witness the next levels of your DevOps journey! Veritis, the Stevie Award winner, offers DevOps consulting services to clients with services encompassing multiple capabilities including iterative and incremental development, on-demand workload management, lightweight architecture, DevOps security, and automated testing methodologies.

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