Managers and Tech Leads are (or should be) very concerned about code quality, and automated code review. Automatic code reviews allow engineers to focus on high-level discussions, which is excellent.

We were born as a code quality tool, and it is an essential part of our product. However, code quality by itself is not enough. Modern software development requires tools to visualize the big picture of development teams and how they work collaboratively.

That said, that’s why we expanded SourceLevel to be an Analytics for engineering teams. We want to provide valuable metrics for engineering managers, CTOs, VPs, or Directors of Engineering to see the big picture, spot bottlenecks, and, most importantly, act before they turn into a big issue.

About the metrics

SourceLevel collects data from GitHub activities on pull requests. We organize these data in charts, tables, and other relevant visualization strategies to provide insightful and straightforward information.

We released three charts. You can learn more about them on our dedicated page to engineering metrics. They are:

  • Throughput with Lead Time
  • Control Chart
  • Lead Time Histogram

Here are some screenshots:

Pull Requests needing attention

This table lists open pull requests from all the synced repositories. The list shows possible neglected work ordered by priority. To us, priority considers lead time, how many days pull requests are stale, number of reviews, number of comments, modified lines (added and deleted), and the number of changed files.

List of Pull Requests ordered by priority of attention

This information is handy for managers and teams. Teams can consult this table to have a broad view of work in progress in all the repositories. They can act on pull requests needing more attention first and prevent them to stale. It’s an efficient way to keep lead time under control.

Feedback appreciated

We love feedback! Let’s make SourceLevel better together! Don’t hesitate to tell us your thoughts on our latest releases!