Using DORA Metrics to Measure DevOps Success

That said, if you compare this year’s Low, Medium, and High clusters with last year’s, you’ll see that there is a shift toward slightly higher software delivery performance overall. This year’s High performers are performing better – their performance is a blend of last year’s High and Elite. Low performers are also performing better than last year – this year’s it consulting rates Low performers are a blend of last year’s Low and Medium. Looking at these five metrics, respondents fell into three clusters – High, Medium and Low. When it came to software delivery performance, this year’s High cluster is a blend of last year’s High and Elite clusters. It is a useful DevOps metric to measure the efficiency of your deployment pipelines.

  • With the help of DORA metrics for DevOps success measurement, organizations can identify Elite, High, Medium, and Low performing teams and accordingly modify operations to increase productivity and service deliverables.
  • 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.
  • Variations in tools used from team to team can further complicate collecting and consolidating this data.
  • DevOps metrics and DevOps KPIs are essential for ensuring your DevOps processes, pipelines, and tooling meet their intended goal.
  • They recognized the value of using a single platform to overcome roadblocks in velocity and innovation.

This delivers continuous improvement and progress towards business goals, promoting a collaborative culture across the organization. Lead time for changes measures the time needed to take a committed code to successfully run in production. Some organizations approach DORA metrics and other OKRs as productivity benchmarks that can be wielded against individual engineers. Yet Google research demonstrates DORA metrics are most successful when adopted by high-trust, low-blame cultures. In these enterprises, DORA metrics reveal organizational opportunities for improvement—never should they reveal lagging individual performers or provide reasons for unnecessary busy work. By tracking some or all of these metrics, you’ll start to gain a better
understanding of how well your monitoring and observability systems are working
for your organization.

Myths About DORA Metrics

Despite the availability of these metrics, most engineering teams still struggle to utilize them effectively, resulting in unnecessary challenges and missed prospects. The change failure rate metric measures the percentage of changes that fail in production. It’s calculated by the number of deployment failures / total number of deployments. In essence, it measures the reliability of your software development and deployment processes.

dora devops metrics

Flow metrics are a framework for measuring how much value is being delivered by a product value stream and the rate at which it is delivered from start to finish. While traditional performance metrics focus on specific processes and tasks, flow metrics measure the end-to-end flow of business and its results. This helps organizations see where obstructions exist in the value stream that are preventing desired outcomes. Cycle time measures the time between the start of working on a specific item and when it becomes ready for end-users.

DevOps metrics for a variety of practices

The same system that is
responsible for user requests is monitored by the blackbox system. A blackbox
system can also provide coverage of the target system’s surface area. You might also consider a
representative mixture of requests to better mimic actual customer behavior. In the next section, we’ll demonstrate how to configure DevLake to implement DORA metrics for the aforementioned example team. In the Four Keys scripts, Deployment Frequency falls into the Daily bucket when the median number of days per week with at least one successful deployment is equal to or greater than three.

This metric enables them to identify transactions that can fail and defects when the system is under load. Then, they can optimize the code before deploying and provide a consistent user experience. This metric evaluates how the application performs under stress and various user loads. Teams must carry out these tests before deploying to production in a pre-deployment environment equivalent to production. A well-known set of DevOps metrics are from DORA, Google’s DevOps Research and Assessment (DORA) team. Over the years, DORA has identified what distinguishes high-performing DevOps teams.

The Ultimate Guide to DORA Metrics for DevOps

DORA’s Four Keys make a good foundation to improve the performance of your development practices, but they are only a start. 3/ Make sure you have an established workflow with DevOps teams before implementing the DORA model and all your CI/CD tools in place, so you can get the most out of applying these metrics. MTTR can be improved by investing in the right incident management software such as Zenduty. B.Low deployment frequency means lower iteration which might not be suited if you’re a fast growing team. Deployment frequency is inversely proportional to the time it takes to deploy.

dora devops metrics

Additionally, several other DevOps metrics have been identified related to key tasks of a software delivery pipeline, including deployment, testing, monitoring and end-user experiences. These metrics can ensure successful business outcomes by measuring them with the DevOps processes organizations have implemented. Therefore, companies must link their software development process with DORA metrics to understand their pain points and areas of excellence. However, to ensure swift, reliable, and resilient product delivery, you must align DORA metrics with your business goals and customers’ ever-changing needs.

Increased delivery speed

In this case, your team’s deployment frequency would be 10 divided by 31, or 0.32 deployments per day. DORA has since become a standardized framework focused on the stability and velocity of development processes, one that avoids the more controversial aspects of productivity and individual performance measures. The time it takes to restore a failure in production, where a failure can be an unplanned outage or a service failure. Service failures and outages can be of different types and severity, which can make it tricky to measure. The time from when development teams start working on a feature to the time the feature gets deployed. Understanding the pace of delivery and aiming for smaller, frequent deployments can help you get quicker feedback.

These specific metrics not only give tech leaders a means for assessing performance but also provide a comprehensive guide for data-driven decisions to implement changes that will drive the organization’s success. DORA Metrics is a concept developed to assess performance in engineering teams that helps categorize them from” low performers” to” elite performers” within the industry. The concept derives from Lean manufacturing principles, and it’s best compatible with DevOps practices. Track DORA metrics consistently and over time, using tools to automate data collection and reporting.


When you measure recovery times for your team, you should plot all values on a scatter chart rather than aggregating to a mean or median value. Aggregation hides outliers that could spark a conversation that leads to improvement. It’s also useful to review restore times for change failures separately from those caused by unexpected Production environment issues. Teams with shorter lead times tend to fix faults quickly because a resolution in the code won’t get stuck in a long deployment pipeline. A well-oiled deployment pipeline reduces the need to fast-track a fix, reducing the risk of knock-on problems caused by skipping key steps.

dora devops metrics

Teams that prioritize both delivery and operational excellence report the highest organizational performance. Over the past seven years, more than 32,000 professionals worldwide have taken part in the Accelerate State of DevOps reports, making it the largest and longest-running research of its kind. That is why Google Cloud’s DevOps Research and Assessment (DORA) team is very excited to announce our 2021 Accelerate State of DevOps Report. DORA metrics for DevOps offer an array of advantages to organizations, aligning their development goals with business goals. For product managers, these metrics help get a look into how and when the DevOps team can meet customer needs. For engineers and leaders, DORA metrics implementation streamlines software development and delivery processes, making it more visible and tangible.

Lead time to changes (LT)

Conversely, a longer time to restore service may indicate areas for improvement in incident management and response processes. Based on survey responses, DORA grouped organizations into performance levels. Organizations in the higher performance groups not only have better software delivery, they often achieve better outcomes at an organizational level. Each report groups respondents to the annual survey, meaning industry trends show alongside demographic changes.

How DORA metrics and feature flags work together

Share the results with the team and stakeholders to identify areas for improvement and make changes to your DevOps performance. For example, if you have a high change failure rate, you can investigate why this is happening and make changes to your testing and deployment processes to reduce the number of failures. Value stream management is a process for optimizing the flow of value through an organization. DORA metrics can be used to identify bottlenecks and inefficiencies in the software delivery process. A shorter lead time indicates a streamlined and efficient delivery process, allowing organizations to respond quickly to market demands and customer needs.

To learn more about how to apply DevOps practices to improve your software delivery performance, visit And be on the lookout for a follow-up post on gathering DORA metrics for applications that are hosted entirely in Google Cloud. Flow metrics help organizations see what flows across their entire software delivery process from both a customer and business perspective, regardless of what software delivery methodologies it uses. This provides a clearer view of how their software delivery impacts business results. Change failure rate (CFR) is a valuable metric that captures the percentage of deployments to production that result in severe errors, rollbacks, or any type of production failure that requires immediate attention.






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