Cloud costs
September 28, 2022
min read

Cycle Time is Not Lead Time


In the DevOps world, metrics rule. After all, progress and success cannot be measured without comprehensive data collection. Engineering leaders often turn to frameworks like DORA to set and track goals for their DevOps teams. DORA focuses on delivery performance by measuring lead time, deployment frequency, mean time to restore, and change. Chief among DORA metrics is Software Delivery Lead Time, or the amount of time it takes a code commit to reach production. Lead time is often confused with Cycle Time, simply because Cycle Time (the number of times code, in general, is shipped to production) can be easier to calculate. 

Knowing your lead time can help you to understand where your development team struggles and excels. Tracking lead time is critical to reducing it, and with shorter lead times, you can deploy to production more frequently in smaller deployments. The main issue with tracking lead time is beginning to do so: properly configuring and monitoring an accurate lead time. Many engineering teams mistake cycle time for lead time and therefore receive skewed data that misrepresents their current development process.

What is Cycle Time, and How Does it Differ from Lead Time?

Cycle time measures only pull requests and merge time. Think about the process you currently have in place to review PRs, then think about the beginning of that process to the end as the cycle time. While cycle time helps identify bottlenecks in the PR review process, the reality is that this is just a small portion of the SDLC. 

Lead time seeks a holistic view of your SDLC and measures the total time from the beginning of the development process to production release. DORA lead time further specifies this timeframe by defining it as the time the first code commits to deployment. 

The reality is that it is much easier to measure Cycle Time than Lead Time. Most, if not all, source control management tools (GitHub, Bitbucket, etc) automatically provide cycle time as a preconfigured metric for your development efficiency. Computing Lead Time, however, can be very tricky. The majority of Engineering teams have a distributed tech stack spanning the beginning to the end of the SDLC process. All DevOps processes differ from Jira to Aha! to SCMs and CI/CD processes. Some teams are fully automated, some teams are still integrating or deploying manually, and others employ a mix of both techniques.

In many cases, particularly for companies with legacy or on-premise applications, there is no direct link between all these applications. Calculating Lead Time may seem daunting or even impossible without a fully integrated and automated SDLC process. After all, most development teams are already working at capacity with an ever-increasing backlog.

Calculate Lead Time Easily with Harness Software Engineering Insights

Automating processes is the most obvious solution for companies looking to improve development efficiency and quickly calculate/analyze DevOps metrics. The reality, however, is that automation takes time and resources that most companies do not have. This is where Harness comes in. 

Harness meets your business where it is currently. By seamlessly integrating with DevOps toolings like Jira, Jenkins, GitHub, and more, Harness Software Engineering Insights can quickly create a comprehensive overview of your processes and products using dashboards to help visualize insights. In addition to calculating Lead Time, Harness can also aid in quantifying development velocity, data hygiene, software quality, and software security. 

You may ask yourself how it’s possible to receive detailed insights with minimal configuration; this is where the Engineering Knowledge Graph (EKG) comes in. A mature, well-documented EKG provides a clear picture of each system or tool employed by your organization and how they all relate. 

An accurate EKG can answer all of the following questions: 

  • Who owns what?
  • Where are system bottlenecks?
  • What metrics need to be collected that are not currently being collected?
  • Which workflows should be automated first? 

Perhaps the most crucial question an EKG aids in answering is: What is my product’s actual lead time, NOT just my cycle time? 

Lead time is a business measure. Improving lead time is about enhancing business productivity, which cannot be done without thoroughly understanding each process and how it relates to the rest of these processes. An EKG is a key to unlocking this information. Since DORA defines lead time as the time from the first code commit to deployment, this is essentially just a measurement of engineering efficiency; and engineering efficiency is Harness’ specialty. 

What if I Need to Calculate Lead Times Outside of DORA’s Definition?

DORA is just one set of countless metrics Harness Software Engineering Insights provides to customers. After all, each business is unique and therefore requires unique insights. Take lead time, for example; this term can mean: 

  • Lead time to release a new strategic feature - How long is a feature in design, research, development, and staging before being released?
  • Lead time to release a customer-requested improvement - How long is a requested improvement in the backlog before it is addressed? How long does the average improvement take to address and release?
  • Lead time to fix a security issue or vulnerability - What is the time from vulnerability detection to complete resolution of the issue?

Harness can also help you with these expanded use cases by providing user-customized metrics in addition to those pre-defined. 


Utilizing a platform such as the Harness Software Engineering Insights can provide support for the diverse DevOps toolsets along with the flexibility to adapt, combine and formulate analytics appropriate to each given audience. Harness offers out-of-the-box dashboards for standardized software metrics such as DORA, and it also provides the flexibility and adaptability to not only visualize the metrics required in your organizations but also provide predictive analytics and orchestration to take action upon those analytics.

Check out a live demo of how we can help you transform your engineering organization!

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