Lab: Measure your DORA metrics from Git

What you will learn in this TP

• Simulate a release history
• Compute frequency and lead time
• Interpret the results

Measure to improve #

What you will learn in this section

• Simulate a release history
• Compute frequency and lead time
• Interpret the results

Context. "We want to ship faster" is a vague goal. DORA metrics make it measurable: deployment frequency and lead time. You compute them straight from Git history, with no extra tooling.

Prerequisites: Git, a terminal  ·  Estimated time: 30 min

Tags stand for deployments.

1. 1. Simulate a history

   Why? A controlled history gives known results: you can check your calculations before applying them to a real repository.

   Create a repository with commits and version tags.

2. 2. Deployment frequency

   Why? Tags stand for deployments: counting them per week gives frequency, the first indicator of flow.

   Count tags per week.

3. 3. Lead time for changes

   Why? The delay between first commit and release reveals batch size and process queues.

   For each tag, compute time since the first undeployed commit.

4. 4. Interpret

   Why? A metric without action is useless: interpretation links the number to concrete improvement levers.

   Which levers reduce lead time: batch size, tests, review?

Difficulty level : ●●○○○ (2/5)