{"id":21216,"date":"2018-11-01T08:09:55","date_gmt":"2018-11-01T13:09:55","guid":{"rendered":"https:\/\/blog.planview.com\/mining-the-ground-truth-of-enterprise-toolchains\/"},"modified":"2018-11-01T08:09:55","modified_gmt":"2018-11-01T13:09:55","slug":"mining-the-ground-truth-of-enterprise-toolchains","status":"publish","type":"post","link":"https:\/\/blog.planview.com\/mining-the-ground-truth-of-enterprise-toolchains\/","title":{"rendered":"Project to Product: Mining the Ground Truth of Enterprise Toolchains"},"content":{"rendered":"
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To learn more<\/span> about what works and what doesn’t in large-scale DevOps and agile deployments, we need data. The problem is, that data is notoriously difficult to get ahold of because much of it lies hidden across numerous private repositories.<\/span><\/p>\n

Efforts such as <\/span>The State of DevOps reports<\/span><\/a> have helped us gain some understanding by using survey data to answer questions about practices such as the frequency of deployments in a team or organization. However, survey data has its limitations, as Nicole Forsgren and I described in “DevOps Metrics,” which we wrote to clarify the trade-offs of system and survey data collection.<\/span>1 <\/sup>Today, our understanding of DevOps practices is based largely on this survey data and on anecdotal evidence. Is there a way to expand our view of DevOps to include studies of system data of DevOps at work?<\/span><\/p>\n

One approach is to examine publicly available repositories, such as those hosted by GitHub or the Eclipse and Apache foundations. However, the conclusions from this research are limited to how open source projects work. Large-scale and enterprise software delivery differs considerably from open source delivery in terms of the scale, scope, and type of work.<\/span><\/p>\n

In my PhD research, I initially studied open source developers.2 <\/sup><\/span>Gail Murphy, my supervisor, pushed me to expand my study to professional developers in enterprise settings. Having spent most of my career doing open source development, I was shocked at how different the work was. The most interesting thing I learned was the additional complexity with which the professional developers worked on a daily basis. The number of applications, systems, processes, and requirements dwarfed anything I encountered in the much more elegant world of open source.<\/span><\/p>\n

In my article “The End of the Manufacturing Line Analogy<\/a>“, I discussed how advanced car manufacturing relates to software production.<\/span>3 <\/sup>One of the amazing things about car manufacturing is that the “ground truth” of production is visible on the factory floor. Walking the assembly line provides an instant view of the workflow. Where can we find the ground truth of enterprise software delivery? How might that ground truth change our understanding of what works and what fails in software delivery at scale?<\/span><\/p>\n

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