Change Failure Rate (CFR) is one of the four key metrics introduced by DORA to measure software delivery performance. While metrics like deployment frequency or lead time for changes are straightforward to calculate, CFR often stands out as more nuanced and harder to measure. In the Engineering Success Podcast, Nathan Harvey and Rishi shared their thoughts on why CFR is unique and how teams can approach it effectively.

Why is the Change Failure Rate Different?

Nathan Harvey explains that CFR is often seen as the "cousin" metric among the four key DORA metrics:

"Deployment frequency, change lead time, and failed deployment recovery time are like siblings,closely related and easy to track. But CFR has always felt like the cousin. It's still connected, but there’s a slight distance."

This distinction stems from the complexity of defining what constitutes a "failure." Unlike deployment frequency, which is a countable event, CFR requires context to determine if a deployment actually failed and why.

Rishi highlighted this during the conversation:

"When I was managing teams, one of the hardest things was explaining to leadership why we were busy but not delivering. CFR adds to that challenge because there’s no universal definition or one-size-fits-all way to track it."

How to Measure Change Failure Rate

Nathan offered several practical approaches that teams can use to measure CFR:

1. Surveys: One straightforward way is to simply ask the team. Surveys can help gauge how often deployments result in rollbacks or hotfixes. While this method isn’t perfectly precise, it provides valuable insights.
   "A survey may not give you a number down to the hundredth decimal, but it’s a great way to get directional insight. Just ask the team responsible for the application," Nathan suggested.
2. Deployment Patterns: Observing deployment patterns can also reveal failures. If a second deployment closely follows a first one, it might indicate an issue with the earlier release.
   "Let’s say your team deploys every two weeks, but in March, there were six deployments,some just hours apart. That’s a signal something went wrong," Nathan explained. "You can also use this delta to calculate recovery time."
3. APIs for Marking Failures: Some teams have automated the process by introducing APIs that allow engineers to flag deployments as failed. This method minimizes manual overhead and provides real-time data.
   "An engineer could mark a deployment as ‘failed’ with a simple API call, and it’s logged. This adds clarity and consistency to tracking CFR," Nathan shared.

Why Context Matters

Both Nathan and Rishi emphasized the importance of tailoring CFR measurement to the team’s specific context:

"Every team has unique workflows. You can’t apply the same measurement method to a startup and an enterprise," said Rishi. "Even if you automate tracking, the definition of 'failure' might vary depending on your processes and goals."

Nathan added:

"CFR isn’t about finding someone to blame for a failure. It’s about understanding what went wrong so you can improve. The goal isn’t to avoid failure entirely, but to learn from it and make better decisions next time."

Key Takeaways

• Change Failure Rate is fundamentally different from other DORA metrics because it requires interpretation and context.
• Practical ways to measure CFR include surveys, analyzing deployment patterns, and using APIs to flag failed deployments.
• Teams should define "failure" based on their specific workflows and goals.
• Measuring CFR isn’t about precision,it’s about identifying trends and improving processes over time.

CFR may be the "cousin" metric among DORA’s measures, but it’s no less critical for understanding software delivery performance. By combining tailored measurement strategies with a focus on learning, teams can unlock valuable insights to improve their systems and processes.

Stay tuned for more blogs breaking down other topics from the Engineering Success Podcast!