DevOps is ubiquitous in software development. Today, around 83% of IT leaders report that their organization is adopting DevOps practices to boost productivity and collaboration. However, not all of them are successful in executing DevOps initiatives.
Even the most highly-evolved organizations face challenges in implementing, measuring, and tracking DevOps initiatives.
To understand what keeps your teams from embracing the DevOps culture, here are crucial metrics you should watch out for.
Top metrics you should know to measure and track DevOps initiatives!
DevOps metrics are data points and statistics that help leaders understand their DevOps initiatives’ performance, including how to identify and eliminate bottlenecks. While there are many metrics you can consider for your study, here are the top 5 that every DevOps team should use to evaluate the success of their initiatives.
1. Mean Time to Recover (MTTR)
This metric evaluates how efficient the organization is in resolving issues. It measures how long it takes for a deployed application to restore its functionalities after a system failure (usually technical or mechanical failures)
With this metric, you can gain insights into three crucial questions:
- What technical issue is stopping your software from recovering fast?
- How effective is your solution in comparison to your competitors?
- Does your team take too long to resolve system issues?
2. Deployment frequency
The ultimate goal of DevOps is to develop a culture so that development teams can deliver fast and satisfy customer needs. To do this, DevOps teams create a continuous delivery pipeline. But is this pipeline helping increase the deployment frequency of your application?
You can understand this through the deployment frequency metric.
It measures how often a software development team deploys changes or adds new features to production. A high deployment frequency indicates that a team is able to release changes to production frequently, while a low frequency suggests that the team may be experiencing issues that are slowing down the deployment process, such as manual processes, technical debt, or poor collaboration between teams.
3. Change Failure Rate (CFR)
CFR measures the frequency of errors that may arise for customers after the team adds changes from deployment to production. It is a critical indicator of the system’s stability and lets you track how often such errors occur.
You can calculate it by dividing the number of changes that fail in production by the total number of changes deployed. A high CFR indicates that changes are deployed without adequate testing. A low CFR suggests that the team is testing changes and validating before deployment, ensuring the system operates at maximum potential.
4. Lead time to change
Lead time to change helps you measure the time it takes for a code change to be developed, tested, and deployed into production. Although this metric is often confused with cycle time, they are different.
This metric is crucial because when teams implement DevOps automation practices to streamline processes or automate repetitive tasks, lead time to change allows the team to identify efficiencies and improve the team’s responsiveness.
5. Cycle time
Although the above DevOps Research and Association (DORA) metrics are critical, understanding cycle time helps you analyze the impact of your initiative.
Cycle time measures the time for a change or feature to be developed, tested, and deployed into production. Cycle time begins when you start designing the functionality and ends when it is released into production and available for end users.
The goal is to keep cycle times as short as possible and apply measures and tools that allow organizations to deliver new features and respond more rapidly to changing business needs.
Keep measuring and optimizing
The widespread adoption of DevOps has helped many organizations become Agile and embrace technologies like automation and AI like never before. But it is vital to realize that for any DevOps initiative to be successful, it has to be an enterprise-wide effort in which even mid-level managers participate.
These 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, as a concept ‘DevOps’ is complex and requires digging deeper and using advanced analytics dashboards. But knowing which metrics to track is a good way to kickstart your DevOps journey.