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Deployment Frequency

Template providing the average number of Pull Requests (PR) deployed daily.

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Automate Deployment Frequency (DF) Calculation from Your Git Pull Requests

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Deployment Frequency

Connect your Git repository to automatically monitor your team’s ability to ship features, enhancements, or fixes to users.

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Deployment FrequencyDeployment FrequencyDeployment Frequency

Understand the DF Metric Template

The DF metric template provides the average number of pull requests deployed daily.

What Good Looks Like for DF

Elite performers observe multiple or on-demand daily deployment according to the DORA metrics scale. High performers deploy weekly to monthly, while medium performers deploy for up to 6 months. Low performers reach over 6 months for this metric.

How to Improve Your DF Metric

  • Limit the PR size to ensure faster reviews, straightforward testing, and simpler releases.
  • To provide developers with immediate PR feedback on low-level issues, add linters and code analysis tools to shorten the feedback loop and save your reviewers' time.
  • By automating end-to-end testing, your QA and Product teams can focus on progressive rather than regression testing. 
  • Peer review bottlenecks are typically caused by busy senior and mid-level staff. Hire more senior-level personnel or give them more time to review pull requests.
  • Avoid back-and-forth development by involving your product team during development, not just after it's ready for testing in your staging environment.
Use Deployment Frequency Metric

Understand the DF Metric Template

The DF metric template provides the average number of pull requests deployed daily.

What Good Looks Like for DF

Elite performers observe multiple or on-demand daily deployment according to the DORA metrics scale. High performers deploy weekly to monthly, while medium performers deploy for up to 6 months. Low performers reach over 6 months for this metric.

How to Improve Your DF Metric

  • Limit the PR size to ensure faster reviews, straightforward testing, and simpler releases.
  • To provide developers with immediate PR feedback on low-level issues, add linters and code analysis tools to shorten the feedback loop and save your reviewers' time.
  • By automating end-to-end testing, your QA and Product teams can focus on progressive rather than regression testing. 
  • Peer review bottlenecks are typically caused by busy senior and mid-level staff. Hire more senior-level personnel or give them more time to review pull requests.
  • Avoid back-and-forth development by involving your product team during development, not just after it's ready for testing in your staging environment.
Use Deployment Frequency Metric