Dataset: Issues & Pull Requests
Entity: Pull Requests, Issues
Field ID: last_commit_at
Type: Datetime
Description: The datetime at which the last commit was made on a pull request. For issues, it is the timestamp of the newest commit across all resolving pull requests.
Source: Calculated from commits
Transformation logic:
Pull requests: It is the creation datetime of the last commit
Issues: It is the creation datetime of the newest commit across all resolving pull requests. Resolving pull requests are pull requests that reference the issue via auto-closing keywords.
From: |
|
Github (PRs, Issues) | Calculated |
Gitlab (PRs, Issues) | Calculated |
Bitbucket (PRs) | Calculated |
Azure DevOps (PRs, Issues) | Calculated |
JIRA (Issues) | Inferred from PRs |
ClickUp (Issues) | Inferred from PRs |
Trello (Issues) | Inferred from PRs |
Reporting Use Cases
The Last Commit At field is a critical timestamp that indicates the last time new code was pushed to a pull request. It effectively marks the end of the active coding phase, making it essential for analyzing the final stages of your review and merge pipeline, and for identifying stale or stalled work.
Calculating Final Review and Merge Duration: The time between the last code change and the final merge represents the last mile of your delivery process.
You can measure this "post-coding" duration with the custom formula
(merged_at - last_commit_at) / HOUR(). A high average value for this metric is a strong indicator of bottlenecks in your final review, QA, or deployment processes, as it shows that "finished" code is sitting idle before being released.
Filtering for Stale Pull Requests: This field is one of the best indicators of a pull request that has been abandoned or forgotten.
You can easily find stalled work by creating a report of open pull requests that have not had a commit in a long time, using a filter like
Last Commit At before 30 days ago and state = "OPEN". This is crucial for keeping your development pipeline clean.
Tracking Active Development: Conversely, you can use this field to focus on pull requests that are currently under active development.
A filter like
Last Commit At in the previous 3 dayswill show all PRs that have seen recent code changes, which is useful for daily stand-ups or for a manager to get a quick overview of current engineering activity.
Analyzing Development Patterns: By using this field as a dimension, you can understand when work is typically completed.
A column chart with a custom dimension like
DAY_OF_WEEK(last_commit_at)and aCOUNT()metric can reveal patterns, such as whether developers are frequently rushing to push their final commits at the end of the week.