Project Insights Data

With the number of issues that we have, there is a lot of surrounding data that we can use to discover trends and patterns. We can use scripts to generate the same data month on month to understand how things are changing as the product becomes more popular.

• Burn rate
• Issues Closed vs Issues Opened
• Closed issues per day
• Total of open issue per day
• Total of gitlab-triage~2677487 issue per day
• Periods
• When are most issues raised
• When are most issues closed
• New issues per day / New gitlab-triage~2677487 issues per day
• Topics
• Which features are issues mostly raised about
• Votes/Comments
• Are we closing issues with the most votes
• Which issues are consistently being voted on
• Which issues are consistently being commented on
• General Issue Hygiene:
• How quickly are we triaging and closing bugs
• Total of unlabeled issues per day
• The number of un-triaged bugs
• Releases
• The number of issues per release
• The number of issues by where they were found
• The number of issues per weight
• Tests
• Unit test coverage
• Time to run all tests
• Flaky Tests
• Total number of flaky tests
• Average time that tests are flaky
• Worst offenders (tests)
• Worst offenders (features/modules)
• Merge Requests
• Average age of MRs
• MRs opened per day
• Total open MRs per day
• Average size of MRs
• Average time to merge (from MR opened to MR merged)