Measuring and Tracking DevOps Performance With Metrics and KPIs

With digital technologies transforming industries, companies adopt Agile and other practices to gain a competitive advantage. DevOps is one such method that has changed software development as we know it. The new-age approach helps accelerate productivity and also enables better collaboration between the development and operation teams.

But the biggest benefit of adopting DevOps is faster time-to-market. It has helped around 83% of organizations unlock business value and deliver customer value faster. However, the brutal reality is that not all DevOps initiatives are successful.

Even the most advanced organizations face challenges when it comes to implementing, measuring, and tracking DevOps initiatives.

Thankfully, DevOps metrics have helped resolve this problem.

Here are some key metrics to understand what prevents your teams from adopting the DevOps culture.

Top 6 DevOps Metrics You Should Know to Maximize the Impact of Your Initiatives

As companies aim to release software updates frequently, the entire development process needs to be streamlined to eradicate risks and vulnerabilities.

DevOps metrics are KPIs and productivity indicators that help organizations understand where they are going wrong. By leveraging these metrics, organizations can improve their software development and delivery process, strengthen security measures, and ultimately, deliver high-quality products faster.

Let’s review the top DevOps metrics you should consider to accelerate your development process.

1. Lead Time

This metric undertakes the time it takes to implement a change from deployment to production. It helps teams to track the efficiency of their processes.

The longer the lead time, the more time and resources it requires to deliver changes to production, resulting in higher costs, longer wait times, and decreased customer satisfaction.

On the other hand, a shorter lead time allows teams to release new features and updates more frequently, leading to faster feedback and more responsive development cycles.

2. Deployment Frequency

It is critical to measure how often a team can release new features and how many were successfully perceived. The metric analyzes the number of times a new product version from deployed to production.

Frequent deployments mean changes are being tested and released, making it easier to fix issues quickly. This can lead to higher-quality software and fewer defects.

3. Mean Time to Recovery (MTTR)

MTTR is the average time the development team takes to restore a system or service to normalcy after a failure. It helps understand the team’s ability to respond to issues and how long it takes to restore services.

It calculates the total downtime caused by an incident and divides it by the number of incidents occurring during a given period. For example, if an application experiences three incidents during a month and the total downtime for those incidents is six hours, the MTTR would be two hours.

4. Change the Failure Rate

It is the percentage of deployments that fail. You can calculate it by dividing the number of changes that fail by the total number of changes deployed during a given period.

The metric helps in enhancing the system’s reliability and stability. This leads to increased confidence in the team’s ability to deploy changes with minimal disruption for better business outcomes.

5. Customer Satisfaction (CSAT)

At the heart of the development process is customer satisfaction. It helps the development team understand how satisfied customers are with a product or service and measure the overall success of a DevOps approach.

Calculating CSAT involves gathering data from surveys, feedback forums, and questionnaires and analyzing customer experiences associated with the product or service. CSAT is often regarded as a benchmark against industry standards and competitors and helps teams make informed decisions around product development.

6. Mean Time Between Failures (MTBF)

MTBF is the average time between system or service failures. This metric estimates the probability of a failure occurring during a specific period and helps to determine maintenance schedules and reliability requirements. A higher MTBF indicates a more reliable product or system, while a lower MTBF indicates reliability issues.

What Can Be Done to Improve Workflows?

Based on the insights from the above metrics, companies can take action to address the workflow. This may involve implementing new tools and processes or streamlining the development and delivery process.

Many companies are using Machine learning and low-code automation tools to cut down the time taken for delivery.

On the other hand, companies are also using rigorous testing and quality assurance processes to ensure that defects and vulnerabilities do not slip in. While the improvement scenarios may differ for each company, leaders should encourage teams to utilize DevOps metrics and analytics dashboards for informed decision-making.

It’s Time to Move Toward Agility 

At its core, DevOps is all about creating an environment where development, operations, and quality assurance teams share responsibility and accountability. And that’s why it is overwhelming to implement, as it requires a complete culture shift. In addition, DevOps also involves complex technical processes, such as continuous integration and delivery, automated testing, and infrastructure as code, requiring specialized skills and knowledge.

The absolute metrics can help you collect the data, get a sense of the dip in performance from the early stages, and create a solid foundation to mitigate it. Obviously ‘DevOps’ is complex and requires digging deeper. But knowing which metrics to track is a great way to kickstart your DevOps journey.