DORA metrics: How to measure DevOps performance

DevOps accelerates modern software development by automating processes and breaking down silos between development and operations teams. This paradigm shift emphasizes continuous integration (CI) and continuous delivery (CD) to speed time to market, facilitate higher-quality releases, and improve customer satisfaction.

To fully realize the benefits of your DevOps initiatives, it’s important to ground them in measurable outcomes. The most commonly used framework for measuring DevOps performance is the four metrics identified by the DevOps Research and Assessment (DORA) team: deployment frequency, lead time for changes, change failure rate, and time to restore service. Collectively, the DORA metrics provide a balanced view of both the velocity and stability of software delivery processes, enabling organizations to assess their performance comprehensively and pinpoint areas for improvement.

In this blog post, we’ll explore the core components of DORA metrics, their benefits, and how they can guide your organization toward more efficient and reliable software delivery.

DORA background

The DORA metrics originated with research conducted by Nicole Forsgren, Jez Humble, and Gene Kim. In 2014, the DORA team set out to provide a scientific system for measuring the effectiveness of DevOps practices in software organizations.

One of the DORA team’s key findings, detailed in their 2018 book Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations, is that software delivery performance is directly correlated with business performance: top performers on DORA metrics are twice as likely to meet or exceed organizational performance goals. This discovery was a major milestone in legitimizing DevOps as a driver of both software quality and business value.

Building on these findings, the DORA team’s research has since expanded to encompass broader aspects of DevOps practices, including collaboration, automation, and cultural factors. But the four original DORA metrics remain essential tools for benchmarking organizational performance and driving improvement efforts in DevOps adoption.

What are the DORA metrics?

The DORA metrics consist of four key performance indicators that provide insight into the effectiveness and efficiency of an organization’s DevOps practices. These metrics are:

• Deployment frequency: How often code changes are deployed into production. A high deployment frequency indicates agility and the ability to respond quickly to customer needs and market demands.

• Lead time for changes: The time from committing a code change to its deployment into production. A shorter lead time signifies faster delivery of features and enhancements. It also reduces bottlenecks and accelerates your time to market.

• Change failure rate: The percentage of code changes resulting in failure or requiring post-deployment remediation. A lower change failure rate indicates the stability and quality of the development and deployment processes.

• Time to restore service — Measures the time to recover from a service outage or incident. A shorter time to restore service reflects robust incident response procedures and enhanced system reliability and availability.

The four DORA metrics are often grouped into two categories:

1. Velocity metrics, including deployment frequency and lead time for changes, focus on the speed and efficiency of software development and deployment processes.
2. Stability metrics, including change failure rate and time to restore service, assess the reliability and robustness of the software delivery process.

It’s important to note that velocity and stability are not mutually exclusive outcomes. In fact, in a well-implemented DevOps environment, they enhance one other. By shortening lead times and making smaller, more frequent deployments, teams reduce the likelihood of introducing defects and simplify error recovery. Likewise, by maintaining a stable, deploy-ready codebase, teams can stay productive and in flow.

Benefits of DORA metrics

Measuring and tracking DORA metrics brings numerous productivity and quality-related benefits. Let’s look at a few below.

Enhanced visibility

DORA metrics offer a comprehensive view of the software delivery lifecycle, helping you pinpoint bottlenecks and inefficiencies more easily. This information helps engineering teams make informed decisions around resource allocation, workflow optimization, and process improvements.

Increased standardization

DORA metrics establish a common framework for measuring DevOps performance, encouraging standardization across teams, projects, and organizations. As a result, you can identify best practices more easily and benchmark performance against industry standards.

Continuous improvement

DORA metrics help identify areas and processes that would benefit from refinement and optimization. This data-driven approach empowers you to continuously fine-tune your processes and adjust your strategies to better serve the needs of stakeholders.

Alignment with business goals

DORA metrics provide invaluable insights into the impact of software delivery practices on overarching business objectives. Correlating metrics with outcomes such as customer satisfaction, revenue growth, and market competitiveness lets you align your DevOps initiatives with strategic priorities, ensuring that software delivery efforts contribute directly to business success and sustainability.

Measuring and managing DORA performance

Tracking DORA metrics requires a combination of tools and techniques. Then, you can implement strategies that enhance performance and improve your DORA metric score.

Let’s review how to measure each DORA metric and use them to improve performance.

• Deployment frequency: Using version control systems like Git alongside CI/CD tools helps automate build, test, and deployment processes, allowing you to accurately track the frequency of your code deployments.

  To improve your deployment frequency, implement automated testing alongside continuous delivery for faster, more reliable releases. You can also use feature flags to enable safe and frequent deployments and invest in infrastructure as code (IaC) to promote consistency and stability.

• Lead time for changes: Tools that provide end-to-end visibility into the software delivery pipeline can capture data from the initiation of a change request to its deployment, letting you measure the duration of each stage of the process.

  You can improve performance by streamlining approval workflows, reducing batch sizes through microservices architecture, and implementing IaC to automate provisioning processes.

• Time to restore service: Implementing monitoring tools helps track system health metrics and provides alerts in case of incidents. Additionally, incident management platforms aid in coordinating responses and more accurately measuring your time to restore service.

  You can reduce your time to restore service by investing in automated incident response tools, conducting post-incident reviews to identify root causes, and implementing chaos engineering practices to test system resilience proactively.

• Change failure rate: Version control systems and CI platforms can track change failure rates by capturing data on failed builds or deployments. Additionally, deployment automation platforms help you maintain consistent and reliable configurations across environments, reducing the likelihood of failures.

  You can improve your change failure rate by conducting blameless retrospectives, implementing blue-green or canary deployments for risk mitigation, and increasing collaboration between development and operations teams through shared responsibility.

Challenges with implementing DORA

Although DORA metrics offer invaluable insights into DevOps performance, organizations often face challenges in capturing and analyzing software delivery data.

Data collection can be difficult due to the need to capture information across disparate tools and data sources. Tool integration itself can be complex, requiring careful configuration to ensure accurate metric generation.

Moreover, once you have tools and processes to collect performance-related data, interpreting the data requires expertise. You need to effectively contextualize and carefully analyze these metrics to avoid misinterpretation or skewed results.

Finally, aligning the metrics and performance-related data with meaningful, real-world outcomes can be difficult. They may not always correlate directly with desired business objectives. You need a thoughtful approach to metric selection and evaluation to ensure what you measure — and your subsequent actions — reflect KPIs that drive value.

Overcoming these hurdles requires organizational commitment, investment in tooling and expertise, and a holistic understanding of how metrics contribute to overarching goals.

Measuring DevOps performance with CI/CD

Implementing a complete DORA tracking system from scratch can be a daunting process, but there are several ways you can start tracking important delivery metrics with relative ease. One of the fastest and most effective ways is to leverage data from your CI/CD pipeline.

CI/CD supports rapid and reliable code delivery — vital for achieving the velocity and stability outcomes championed by DORA. By closely monitoring pipeline performance, you can gauge metrics like deployment frequency, lead time, and change failure rate, aligning with DORA principles.

CircleCI’s Insights dashboard capture, monitor, and share key performance metrics that align with DORA. It includes time series and aggregated data on usage, success rates, and pipeline duration across all branches or a specific branch of a particular project workflow.

Let’s review some of the metrics the Insights dashboard highlights — and how they can support your DORA implementation.

Duration

Duration measures the average time required to complete a CI/CD workflow. This measurement helps you understand the efficiency and performance of your CI/CD processes.

Duration directly correlates with DORA’S lead time for changes metric. Tracking the duration of CI/CD workflows enables you to optimize your processes to minimize lead time, thereby accelerating the delivery of changes to production, enhancing agility, and improving overall performance.

Throughput

Throughput measures the number of CI/CD workflows of any status performed each day. For teams implementing CI/CD practices, a proportion of these workflows pertain to deploying changes to production environments. Enhanced throughput directly correlates with increased deployment frequency.

Aligning with DORA metrics, higher throughput signifies the ability to deliver changes to production rapidly, fostering agility and responsiveness.

Monitoring CI/CD workflow volume via the Insights dashboard becomes instrumental in evaluating and optimizing deployment pipelines for efficient software delivery in modern development workflows.

Mean time to recovery

Mean time to recovery (MTTR) tracks the average time between CI/CD build failures and subsequent successful runs. This metric reflects your team’s efficiency in detecting and resolving errors in the development processes.

By measuring this time gap, teams can gauge their responsiveness to issues, which directly impacts the time to restore service metric. A shorter average time between failure and successful run signifies a team’s ability to swiftly identify and rectify errors, leading to faster service restoration and ultimately improving overall software reliability and user experience.

Success rate

Success rate shows the percentage of successful CI/CD workflows in relation to the total workflows executed. This data directly impacts DORA’s change failure rate.

Successful build, test, and deploy workflows, backed by comprehensive test coverage and feedback loops, significantly enhance deployment quality. These workflows mitigate risks associated with production failures, lowering your change failure rate. A higher percentage of successful workflows indicates a smoother development pipeline, reflecting improved code stability and reliability.

Next steps

DORA metrics are instrumental in cultivating excellence within your DevOps practices. Quantifying KPIs like deployment frequency, lead time, change failure rate, and time to restore service is a proven method for gaining actionable insights into organizational efficiency and resilience.

Diving deeper into these DORA metrics allows you to iterate, adapt, and evolve your DevOps processes, driving sustained progress and competitive advantage.

To learn more about how software delivery teams harness core CI/CD metrics to drive operational and DevOps performance, download the 2024 State of Software Delivery Report. When you’re ready to start optimizing your own DevOps processes, sign up for a free CircleCI account and take your first step toward operational excellence.