In his famous book “Mythical Man Month,” Fred Brooks says, “Techniques proven and routine in other engineering disciplines are considered radical innovations in software engineering.”
While being very fond of engineering on the big scale, such as building millions of high-end and yet individually configured cars or double-deck aircraft or space ships, for example, I have always asked myself, why the most promising industry—software engineering—is so often not capable of doing engineering on that scale, too? Or, why are so many big enterprise IT projects painful in so many ways?
With these questions that nobody seemed to be really interested in on my mind, one day I met some higher corporate management, who wondered why the IT department would be so reluctant to follow their lean transformation advice and instead talked about some agile and continuous integration thingy.
From that moment, I understood that everything necessary to radically upgrade software engineering was already there! The biggest problem was that we do not communicate enough—and furthermore, there is no holistic view on the complete IT value chain.
By that I mean we need to create awareness for the value chain, starting with digitized formal models of business processes and written business requirements.
That was how the following chart came to existence, and I still love it. Apparently, most awesome things happen on the borders of separated knowledge domains; you need just to talk to colleagues from departments you’d never talk to! What if we would mix knowledge from big industry, best available process improvement and quality assurance methodology, and apply all this to how we design, build and deliver software?
At first I thought I had found a new perspective on DevOps, but now I believe there could be more to it. Well, now the door to the radical innovation is open! Just imagine: What if we would apply the Internet of Things approach to our industry? Maybe we could close the loop of process improvement in software development and test, moving it to real time and running optimization not by ambiguous frameworks but by hard facts coming from virtual sensors, with unprecedented levels of transparency?
This was how a couple of friends and I came to the idea of our foundation we call SIGSPL (Special Interest Group for Software Production Lines). This public organization is a non-profit think tank, built around three generic domains—Labor Automation, Analysis and Advanced Visualization—which we consider to be the three pillars of the upcoming convergent software engineering in the post DevOps era.
We are sure this sort of thing inevitably will happen, but our mission is to catalyze these processes to make radical innovation happen intentionally and faster, so we all can build information technology that rocks!
We are a small team of six with some infrastructure, publications at our blog and a well-established yet growing knowledge base. We would like to reach out to more like-minded people to let this idea grow and change the world. Our plan is to foster further exchange and discussions between DevOps experts and other specialists “unexpected” in this context, such as production lines and supply chain management experts, Six Sigma Black Belts, 3D artists, hackers, venture capitalists and many, many others.
Our proof that we are not ponding to nowhere is our magic triangle diagram, showing some well-known tools we map to the three generic domains, which are also of high interest for venture capital. Our question to the world is, What would appear in the middle of this triangle in, say, five years?
About the Author/Peter Muryshkin
Peter studied M.Sc. in Applied Computer Science and works in management consulting roles focusing on complex analysis and customer satisfaction, including IT Business Analyst and Change Manager. His current scientific research focus is digital transformation applied to the field of software engineering in large distributed organizations.