Skip to main content
Version: 2.0

DORA Metrics Overview

For years, speed has been prioritized in the tech world. While remaining crucial, simply moving isn’t enough. We need to move effectively. That’s where DORA metrics come in. As engineering leaders, we’re responsible not just for what our teams build, but how they build it. DORA metrics provide a surprisingly powerful lens into that “how,” giving us actionable data to improve performance, reduce risk, and ultimately, deliver more value to our users.

This isn’t about adding another number to track. It's about shifting our focus from output (lines of code, story points) to outcomes – how quickly and reliably we deliver value to our stakeholders.

What are DORA Metrics?​

The DORA (DevOps Research and Assessment) metrics, popularized by the annual 'Accelerate State of DevOps report', aren’t just arbitrary KPIs. They’re based on years of research analyzing the performance of thousands of software development teams. The core four metrics are:

  • Deployment Frequency: How often does your team successfully release code to production? (e.g., daily, weekly, monthly)
  • Lead Time for Changes: How long does it take a code change to go from commit to successfully running in production? (measured in hours or days)
  • Change Failure Rate: What percentage of deployments cause a failure in production requiring immediate remediation (e.g., rollback, hotfix)?
  • Time to Restore Service: How long does it take to restore service when a production incident does occur? (measured in hours)

Why Should I Care as an Engineering Leader?​

Many engineering leaders face a constant struggle: balancing the need for speed with the need for stability, and demonstrating value to stakeholders. It’s easy to feel overwhelmed tracking metrics when you’re already juggling multiple priorities. DORA metrics aren’t about adding to that overwhelm—they’re about making your existing work smarter. Here’s how:

  • Predictive Power: Teams with high performance on DORA metrics are demonstrably more likely to achieve organizational goals, like increased profitability and market share. This isn’t just correlation; the research strongly suggests a causal relationship.
  • Early Warning System: Declining metrics aren’t just numbers going down. They signal underlying problems – technical debt, broken processes, lack of automation, or even team morale issues. Addressing these before they lead to major incidents is invaluable.
  • Targeted Improvement: Instead of guessing where to focus improvement efforts, DORA metrics highlight specific areas that need attention. A high change failure rate points to quality issues. Long lead times suggest process bottlenecks.
  • Data-Driven Conversations: Moving beyond subjective assessments ("we're moving slow!") to objective data (“our lead time has increased by 20% in the last month”) fosters more constructive and effective team discussions.

How to Get Started – And What to Avoid​

Implementing DORA metrics doesn’t require a massive overhaul. Here’s a practical approach:

  1. Start Small: Don’t try to track everything at once. Pick one or two metrics to focus on initially. Deployment Frequency and Lead Time are often good starting points.
  2. Automate Data Collection: Manual data collection is unsustainable. Leverage your CI/CD pipeline, issue tracking system, and monitoring tools to automate the process. Tools like Yandex.Metrica, Mixpanel, or even dedicated API analytics platforms like Moesif can help.
  3. Establish Baselines: Before making any changes, establish a baseline for your current performance. This provides a clear benchmark for measuring improvement.
  4. Focus on Trends, Not Just Numbers: A single data point isn't meaningful. Look for trends over time to identify patterns and assess the impact of your improvement efforts.
  5. Avoid Blame: This is critical. DORA metrics are not about evaluating individual performance. They’re about identifying systemic issues and improving processes. Focus on what happened, not who is to blame.

Beyond the Numbers: Visualizing Your Delivery Pipeline​

While the core DORA metrics are fantastic, understanding why they are what they are is key. To uncover deeper insights, consider visualizing your software delivery pipeline to identify bottlenecks and dependencies.

Tools like Kumu.io can help you map your delivery pipeline, identify bottlenecks that contribute to long lead times, and ultimately improve your DORA metrics.

Final Thoughts​

DORA metrics are more than just numbers; they’re a lens into the health of your software delivery process. By focusing on outcomes, automating data collection, and avoiding blame, you can leverage these metrics to improve performance, reduce risk, and deliver more value to your users. As engineering leaders, our responsibility isn’t just to build things; it’s to build them effectively. DORA metrics give us the data we need to do just that.