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-around cultural transformation, filling the void among teams. DevOps automation tools include Ansible, Jenkins, Git, Kubernetes, Splunk, Docker, etc.

Implementing the DevOps methodology has demonstrated substantial success within IT organizations, with 99% of companies reporting significant growth. Even though DevOps is a relatively recent approach, industry leaders such as IBM, Microsoft, and Atlassian have wholeheartedly embraced DevOps practices throughout their operations.

However, it’s important to note that DevOps is not a one-size-fits-all solution that automatically guarantees improved and expedited deliverables. Instead, it necessitates diligent tracking of metrics to optimize operational DevOps processes and ensure the successful delivery of products.

In this context, measuring key performance indicators (KPIs) becomes crucial to assess the return on investment (ROI). This is especially pertinent because DevOps professionals command high salaries, necessitating the assurance that their efforts genuinely enhance an organization’s development and operational aspects.

As crucial to the digital transformation, DevOps capabilities have also successfully driven the desired Return on Investment and 100% customer satisfaction for many businesses.

All these advantages with DevOps don’t come quickly, and the secret lies in understanding a few metrics and Key Performance Indicators (KPIs). CI/CD KPIs and SLAs are typically defined for this service, as 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 remember that no one solution 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.

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What Are DevOps Metrics?

A DevOps metric is a data-driven indicator or a small dataset employed to quantify, monitor, evaluate, and compare various aspects of a process, performance, or production within a DevOps context. These metrics offer insights into your software development pipeline’s efficiency, effectiveness, and reliability, enabling bottlenecks’ prompt identification, isolation, and resolution.

DevOps metrics encompass a broad spectrum, covering technical capabilities, team DevOps processes, and cultural aspects. They serve as valuable DevOps automation tools for gauging incremental changes, including enhancements in software quality, accelerated release cycles, and improvements in application performance.

Below, we highlight some pivotal DevOps metrics and Key Performance Indicators (KPIs) that merit close tracking. It’s important to note that the specific choice of critical metrics to measure and act upon will vary depending on the unique DevOps challenges an organization seeks to address.

The benefits of DevOps ultimately lead to increased customer satisfaction. These include swifter and improved product delivery, expedited issue resolution and reduced complexity, enhanced scalability and availability, more stable operational environments, optimized resource utilization, heightened automation, improved visibility into system outcomes, and a greater emphasis on innovation.


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Metrics Types

Metrics Types

Key Performance Indicators (KPIs) are categorized into four primary groups within the realm of DevOps:

1) Efficiency and Effectiveness Metrics

Traditionally, these metrics encompassed the conventional assessment of development capacity and operational capabilities, often involving metrics like server-to-admin ratios. Recently, there has been a shift towards incorporating more customer-centric ratios, such as Full-Time Equivalents (FTEs) to customers, to gauge how efficiently and effectively an organization serves its clientele.

2) Velocity Metrics

The acceleration of application delivery is a pivotal driver of successful DevOps practices. Tracking velocity metrics assesses the organization’s ability to improve application delivery by emphasizing IT’s responsiveness to improving business demands. These metrics highlight the extent to which the IT organization has embraced automation and eliminated manual or isolated tasks, ultimately reducing time-to-market significantly.

3) Quality Metrics

Puppet’s State of DevOps report highlights that the pressure to deploy faster and more frequently often leads lower-performing IT teams to neglect the importance of building quality into their software. In contrast, high-performing teams recognize that speed and stability are not mutually exclusive. They understand that quality is a shared responsibility throughout the software delivery DevOps life cycle and should be integrated into the development process from its early stages.

4) Culture, Collaboration, and Sharing Metrics

Effective communication, collaboration, and integration between development and operations are vital for DevOps. It’s not solely about having the right DevOps processes and technology but also about evaluating the human element within the organization. Metrics focused on culture, collaboration, and sharing provide insights into the acceptance or resistance to DevOps practices. This shift in approach is pivotal for adopting agile methodologies, continuous delivery, and deployment, necessitating the early involvement of Operations in the software DevOps life cycle and a heightened focus on application support within Development.


Useful Link: Derive ‘ROI’ from ‘DevOps’: An Overview of Performance and Metrics


Key DevOps Metrics and KPI’s that stand crucial to a successful DevOps lifecycle journey:

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

1) Time and Frequency of Deployment

The old concept is a single/bulky deployment for extended periods. 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 reflect improved test and release cycles.

This will also reduce deployment time, often resulting in much 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 is also related to changes in the volume. Increasing the meantime to failure and the low change volume causes process dysfunction, leading to delays 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 explains the extent of release failure caused by unexpected outages or other failures. A low change failure rate means faster and more timely deployments. At the same time, the high side 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 the time the change process takes from the start to the deployment phase. This helps you estimate a specific task’s time 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 feedback or alerts from your customer support team means more gaps in your business at the customer end. The worst thing a business ever 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.


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9) Automated Test Cases

Automated test cases must 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 essential to operate in line with your SLAs. In the absence of SLAs, meet the set application requirements.

11) Availability

This refers to the presence of service during the downtime. It is usually in two ways: 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 to 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 in 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.

14) Application Performance

The best practice is to check the application’s performance before deployment. There are specific DevOps automation 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 ideation stage to the end with user feedback. This metric presents a broader view of application deployment. Shorter DevOps life cycles are highly recommended, but not at the cost of defects.

16) Rate of Security Test Passes

This DevOps Key Performance Indicator (KPI) revolves around adopting secure practices and assessing a test’s feasibility for integration.

Identifying several unsuccessful security tests during the build phase is a critical indicator of potential flaws, effectively averting the deployment of faulty releases into the production or live environment. To enhance your team’s proficiency in this regard, obtaining a DevOps Fundamentals Certification can be a highly beneficial strategy.

17) Deployment Success Rate

The metric in focus here is the “Deployment Success Rate,” a crucial parameter often overlooked as engineering managers and CTOs strive to accelerate deployment speed and frequency. In this pursuit, some may unintentionally forsake established best practices, leading to eventual repercussions from deployment failures and software defects.

To avert such pitfalls, it becomes imperative for managers to meticulously monitor the Deployment Success Rate, which entails assessing the ratio of successful deployments to those failing.

However, the initial step in this process involves formulating precise criteria for defining what constitutes success. For instance, the successful execution of a rollback procedure might be considered a success, even if it means the primary deployment was not completed as intended. Conversely, a deployment could be categorized as unsuccessful if a variable, such as the presence of a rollback procedure, impedes the progression of the deployment process. Establishing these criteria is pivotal for an accurate evaluation of deployment success.


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Steps to Implementing DevOps ‘KPIs’

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

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 effectively implement the identified DevOps KPIs and metrics to drive your DevOps success.


MUST READ: DevOps Frequently Asked Questions


Conclusion

Many such KPIs and metrics contribute to DevOps success. Wait no more! Use these metrics and effectively implement them to witness the following levels of your DevOps lifecycle journey! Veritis, the Stevie Award, and Globee Business 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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