What can you learn about devops and software delivery practices by looking at data from a platform with more than 300,000 developers, 25,000 organizations and 25+ million builds per month? As I recently joined CircleCI, I was interested in this new data set from a large SaaS developer platform and the kinds of questions that it could answer: What trends and patterns pop out from the data? Are they different than what is seen through surveys where responders opt-in to participating as compared to being aggregated through platform usage?

I wanted to use this data set in a behavioral economics methodology to see what reported behaviors are when compared actual behaviors across a large data set. In this talk, I’ll cover a view into anonymized team data from millions of builds to share insights, behaviors, and metrics that help teams build better software faster, and look into characteristics of success that we can measure through data. Finally, I’ll cover what we can infer from team behavior, callout a few tools, start a language war, and provide take-aways for you to benchmark with your own software delivery teams.