DORA Metrics: The 4 Key Indicators of Elite DevOps Performance

This information can be used to identify teams that are performing well and to learn from their best practices. Another challenge in tracking DORA metrics is cultural resistance to change. Some organizations may be resistant to changing their existing processes and workflows in order to track DORA metrics. While teams realize the benefits of using DORA for improving software delivery, they still lack a holistic understanding of what DORA exactly is. Teams can make use of DORA to continuously assess their progress, pinpoint areas of weakness, and adopt workflows that enhance overall team effectiveness.

• Start tracking the metrics over time and identify areas where you can improve.
• This metric measures the time passed between an issue being triggered to the moment the change that fixes it is shipped into production.
• This way, potential issues can be identified and managed faster before they are released to production.
• It should also display metrics clearly in easily digestible formats so teams can quickly extract insights, identify trends and draw conclusions from the data.
• And DORA software metrics help companies leverage the principles of value stream management to bridge the gap between development efforts and business goals.

The way DevOps team can use this metric varies significantly depending on the service-level indicators or service-level objectives (SLI/SLO). 5/ Constantly assessing DevOps teams’ performance can create a more motivating work environment by stimulating team members to strive for better results. This entails identifying work practices that create delays and finding ways of overcoming them. Sometimes there’s a particular repo/developer falling off the guardrail which should be spotted and rectified. Executive buy-in is essential for the successful implementation of any new initiative, including tracking DORA metrics.

Lead time for change

Those who fall into the elite categories can leverage DORA metrics to continue improving services and gain an edge over competitors. As the State of DevOps report reveals, the group of elite performers is rapidly growing (from 7% in 2018 to 26% in 2021), so DORA metrics can provide valuable insights for this group. Because there are several phases between the initiation and deployment of a change, it’s wise to define each step of the process and track how long each takes. Examine the cycle time for a thorough picture of how the team functions and further insight into where they can save time. If a higher measure of lead time shifts, DevOps teams can streamline processes, and break down products and features into smaller, more manageable code.

You can calculate MTTR by considering the time an incident occurred and the time it took to resolve it. Partner with us to effectively navigate the complexities of your software development process and unlock the full potential of DORA metrics for DevOps success measurement. Use these DORA metrics for DevOps to analyze the effectiveness of your software development, delivery pipelines and the performance of your DevOps team spread worldwide. Measuring the progress of DevOps teams is essential to understand how they are performing and how efficiently they can deliver applications. After all, without evaluating the performance, you can’t figure out where to pay attention and what to iterate to provide effective customer service.

Challenges in Implementing DORA Metrics

I encourage leaders who implement DORA metrics into their benchmarking to take results seriously. Interrogate your current developer workflow—and actively take steps to address issues through developer-first solutions. Doing so will not only improve your organization’s software delivery capabilities but also foster a culture of continuous learning and improvement. High-performing teams reliably achieve faster time-to-market by removing menial tasks from their workload and expediting the development and deployment processes. Elite teams provide a better customer experience, deploy robust code faster and maintain better availability. And engineering teams that codify their procedures and track using DORA metrics are more likely to achieve these results in a shorter time frame.

The book was thus published in 2018, and it provides the data collected from their State of DevOps annual Reports starting from their early research in 2014 up to the moment of publication. You can find out how long it takes to fix things after they break by adding up all the times they were broken and dividing it by how many times things broke in a specific time. The number of deployments made in a given period, such as a month, can be divided by the number of days in that period to determine the frequency of deployment. Deployment frequency is one metric that can be used to assess a DevOps team’s performance.

Increased delivery speed

To increase deployment frequency, it’s essential to have an efficient and reliable deployment process in place. To minimize the impact of degraded service on your value stream, there should be as little downtime as possible. If it’s taking your team more than a day to restore services, you should consider utilizing feature flags so you can quickly disable a change without causing too much disruption.

Once these bottlenecks have been identified, teams can implement changes to improve their efficiency and speed up the delivery of new features and updates. When you develop a new product, you can trade stability to get fast, high-value learning cycles. Or, if you intend to retire a product, you’re likely to reduce the development frequency as you’ll no longer make improvements or introduce new features – only resolve critical issues. Though performance clusters from the annual report are useful to see how you compare to the industry, your goal isn’t elite performance. Instead, look at what your cross-functional team aims to achieve and set an appropriate ambition for their performance. There’s more information on this in the operational performance section below.

Metrics

On the other hand, a longer lead time may imply delays and inefficiencies that hinder delivery performance. The quality of your internal documentation will be a key to high performance against the reliability metric. Teams with high-quality documentation were more than twice as likely to meet or exceed their targets. You should measure reliability against the service level objectives of your software.

Even when you have all the data at hand, implementing change at an organizational level is no easy task, and the founders of DORA suggest that doing this dramatically and suddenly is the wrong way to go about it. Instead, they propose using an individualized approach based on an analysis of the particularities of each organization. In other words, when it comes to software delivery performance, no one-size-fits-all model can be applied to every organization with it consulting rates resounding success. DORA encourages using personalized improvement models based on exact data and the experience of industry practitioners. Using DORA metrics enables teams to gain insights into their DevOps performance, identify bottlenecks and areas for improvement, make data-driven decisions, and drive continuous improvement. These metrics help teams enhance their software delivery processes, increase efficiency, and achieve better business outcomes.

DevOps & DORA Metrics: The Complete Guide

It would be simple and straightforward to show daily deployment volume or to grab the average number of deployments per week, but the metric is deployment frequency, not volume. In 2021, more than 22 billion records were exposed because of data breaches, with several huge companies falling victim. Between that and other malicious attacks, security continues to be top of mind for organizations as they work to keep customer data safe and their businesses up and running.

Outcome metrics, on the other hand, measure the overall performance and success of the process, including factors like customer satisfaction with the product and the frequency of successful deployments. It’s important to understand the differences between these two categories of metrics to get an accurate picture of the impact of your software delivery processes. Companies in virtually any industry can use DORA metrics to measure and improve their software development and delivery performance.

GitLab’s 3 steps to optimizing software value streams

For the first time, we measured the quality of internal documentation and its effect on other capabilities and practices. We found documentation is foundational for successfully implementing DevOps capabilities. Teams with high-quality documentation are 3.8x more likely to implement security best practices and 2.5x more likely to fully leverage the cloud to its fullest potential. Each of these examples demonstrates how OKRs can be applied to set clear, measurable objectives and define specific outcomes to gauge progress. Through OKRs, organizations can create a focused roadmap and align team efforts towards shared goals. 2/ Having decentralized data – if you collect data from multiple areas in a disparate way, you can actually do more harm than good and become very overwhelmed and confused.

This involves celebrating successes, fail-forward learning, experimentation, and embracing a ‘fail fast’ attitude. Moreover, encouraging team training, sharing of knowledge, respect, and transparency boosts motivation and engagement. When teams combine DevOps, and agile together, they create room for more iterative processes. Using DORA metrics on top of your agile+automation combination can help teams build better workflows. Although the metrics offer a good base for assessing DevOps performance, they shouldn’t be the sole source of truth for your team.

Lead time for changes is a key indicator because the shorter the amount of time that elapses, the greater the organization’s ability to get timely feedback from customers. This often leads to additional improvements to the software based on that feedback. For instance, suppose that you’re focusing on the number of deployments per month and your team deployed code 10 times a month during a 31-day month.