While it’s a difficult idea to pin down succinctly, the definition of DevOps is perhaps best broken into broad and narrow interpretations. Broadly, it’s the philosophy of promoting collaboration between development and IT teams. More narrowly, it refers to the adoption of software development and tech tools to improve operations. The actual purpose of DevOps, however, can more or less be boiled down to teams’ effort to deploy, operate, monitor, and improve applications — with data being the driving force that keeps the cycle going.
In other words, DevOps revolves to some extent around the gathering, interpretation, and use of data in service of improving further development. To better understand the benefit of data with regard to DevOps though, it’s necessary to consider what types of data teams can gather through this philosophy and practice.
Estimated Lead Time
The concept of lead time is, like DevOps in general, a little bit ill-defined. But in the context of data, it is essentially a measurement of the time elapsed between when a coding project begins and when a version of the code is in use. Teams employing DevOps philosophies and tools will typically gain a clearer picture of operations with respect to timing, and can use more precise estimations of lead time to plan future processes more accurately.
With the amount of investment that goes into development projects these days, and the complexity that can quickly arise with regard to capital usage, a lot of teams are now looking to employ financial analysts — or at least consult with external experts on the subject. This can certainly make sense in some situations, even with DevOps processes are at play. However, DevOps can also produce date relating to risks that disrupt or delay software development and hold up projects. Because such risks ultimately lead to financial waste, spotting and addressing them can not only keep projects running more smoothly, but also mitigate financial difficulties in doing so.
Causes of Bottlenecks & Recovery Time
On a similar note to that of recognizing and mitigating risks, DevOps can also provide data that reveals bottlenecks in the development process — as well as how long it takes the process to recover from them. This is best done by organizing projects into request, coding, testing, development, and deployment stages (sometimes with more specific steps worked in) and assessing the time it takes to progress from one step to the next. With the data on hand to gain a clear picture of all of this, teams can recognize where disproportionate or unusual hold-ups are occurring, and thus recognize where to look to address bottlenecks.
There is also a predictive aspect to all of this. Recognizing where to look for bottlenecks can certainly improve efficiency in addressing issues. But with adequate data concerning how often certain mistakes occur, and how long they take to correct, teams can also begin to predict the timelines within which mistakes are likely to occur, and thus be better prepared to address them.
Talk of data collection and application often revolves around external or project-oriented practices. That said, internal team data is also important. The vast usefulness of data analytics across industries today has resulted in a lot of targeted education aimed at preparation for specific roles. And with much of that education occurring via internet degree and certification programs it’s noteworthy that “Operations Research Analyst,” “Management Analyst,” and “Program Analyst” are included among the primary jobs for specialists with online masters degrees in business data analytics. These are largely internal data jobs, and speak to the importance of assessing information with regard to team performance as well. This applies to development teams employing DevOps in that the processes will also clarify ways that teams can more effectively be managed and made to collaborate.
Additionally, and arguably even more importantly, data concerning team performance can be used to assess the wellness and happiness of members. Measuring these factors will allow management to make any necessary adjustments in the name of "team health" rather than just performance and efficiency.
Integrated, Real-Time Insights
Finally, in an all-encompassing sense, DevOps processes and tools can also provide teams with the kind of integrated, real-time insights they wouldn’t always get otherwise. One of the problems when development and IT operations teams collaborate in general is that it’s hard for everyone involved to be on the same page. Once an issue arises with a given step in the process, said process has moved on, and it’s challenging to address problems in a timely manner. Through DevOps, teams can enjoy more in-the-moment monitoring of progress and difficulties, and collaborate more effectively as a result.
All in all, DevOps is still a complicated concept, and one that will look a little bit different for each company or development team. Its chief benefit in the end however is the way in which it will produce data that can further optimize processes. Through all of the benefits discussed above, harvesting information from DevOps improves teams and makes projects more precise and efficient.
So, how can you put all of this into action and begin to improve your team? To some extent it depends on the nature of said team and the work you do! But just to get started, try breaking your next development project down into clearly defined steps, from the time an order for a project or application is made to the time at which said project or application is live. Measure the time it takes to progress from one step to the next, and you'll essentially have the beginnings of a DevOps practice — as well as a preliminary picture of how to improve efficiency the next time around.
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Prepared by Alicia Archer
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