I’ve been through multiple ‘reboots’ in my tech career. I started out initially doing networking on PCs (DOS/Win/Mac/Linux): installing network interface cards (NICs), configuring them, and then moving on to the next machine. It was a very dynamic and transformational period in the tech world. Then, I became a “systems administrator”, which at the time in the mid-90’s connoted a high degree of skill with UNIX and UNIX-like operating systems used for distributed applications like the brand new “World Wide Web” among other things. At the time, I was as enthusiastic as ever, but also now a bit seasoned, which gave me just enough bravado to advance my career into the private sector (after starting out exclusively in academia and higher-ed).
That was the biggest jump I’d experienced in my nascent tech career path, at a time when companies were hiring ALL THE PEOPLE who had remotely even heard something about this thing called the Internet. I was lucky, I had both knowledge and experience. As a grad student, before deciding to become a computer professional, in addition to reading journal articles for my doctoral program of study, I’d print out and read Internet RFCs. This was back when there were less than a few hundred or so of them, and you recognized a lot of the authors’ names because they were writing them all. This Internet thing was undeniably super cool and, like many of my peers, I could already sense that it was going to the world dramatically.
A few years before, I recall having a conversation with my major professor at one point (before leaving the academic world for the computing world), and describing to him this thing called The Well and proposing that we do some research into the influence of computer networks on human social behavior. Mind you, this was around 1990, still several years before the average person owned a computer or means of connecting to the Internet from home. I was envisioning an advanced network of social communication not unlike today’s social media platforms (my chosen field of study was called social cognition, and I focused on impression formation and attitude formation).
I think he laughed at me, because neither one of us at the time had any real grasp of the concept at that time. I had been on the Well, and using BBS’es a lot, was starting to explore FTP and Archie and Gopher. And, I had heard of HCI research (Human Computer Interaction) but was imagining something else as a field of study that didn’t exist, with an added social element that I thought was completely intriguing to consider. He didn’t really know where to go with my idea, so we dropped it and decided that it was really outside of what we were studying and trying to accomplish with our respective lines of research.
After making the jump to the private sector and privatization of Internet “sites”, most of my work was still in the sysadmin realm, but soon expanded to include both storage and networking on an enterprise scale. I wore whatever hat needed wearing on a given day in a given workplace, and grateful that my self-taught tech skills seem to allow me to progress in my career without many obstacles. As time marched on, problems with staffing became more of a scale issue: hire more and more engineers to get the infrastructure substrate solid and support application development faster.
Around 2005 or so, I began noticing a trend of people applying for systems and software engineering jobs with little to no experience and deep understanding, but plenty of technical training and certifications. Positions were starting to go unfilled but, also many new hires were simply not up to speed and often caused more problems than they solved. It didn’t matter what industry or the company, no workplace was immune to this problem it seemed.
Now, it seems this problem has become both chronic and more acute. I believe that’s part of the rise of DevOps. DevOps itself has resisted hard definitions, but I tend to think of it as basically adopting a more agile methodology for software development projects and infrastructure operations, by tapping people to do both development and operations work. It’s been embraced by organizations large and small, but it still remains early. And finding a good devops engineer, one that can effectively traverse the trees as well as the forest, so to speak, is even more difficult. Positions are still going unfilled and orgs are turning to trying to coach and train existing staff, to get them “up to speed” on devops practices.
And, lo and behold, guess what? It’s not working, except in the rarest of occasions in my experience. Yes, devops is expanding, but it’s dragging a lot of legacy cruft with it and dilutes the gains of the paradigm shift. I just recently read this article by James Beswick in which he describes almost exactly the same story I’ve been sharing with you here, but with the backdrop of cloud adoption and the role that automation is playing in eliminating human labor. It’s a real thing, I see it happening in many places.
To the extent that the cost-reduction process is the prime driver for cloud adoption, it’s natural to expect some sort of fallout like eliminating staff. However, and this is where my concern spikes a bit, companies seem to be risking the gains offered by devops in the cloud by an attitude of “Well, we can’t find the right person, so let’s just have our existing staff to get training and certifications and all will be well”. In all but the rarest of situations, that isn’t working. Many people are not able to make the jump, and it drags down the entire org which is still managing to operate in the field of the devops/cloud paradigm without realizing the essential benefits (streamlining of workflows, automation and code testing, rapid cut/release cycles, etc.).
It remains to be seen if we are simply at the bottom of the S-curve as Beswick suggests; it’s a compelling analogy, one that’s worked to describe technological bifurcation in the last 40 years or so. But, we clearly have a definite problem in terms of a lack of skills and capabilities in the existing labor supply that is being magnified with an insatiable demand by orgs to move faster and better daily. Is it simply a waiting game, whereby more automation will eventually fill in the skilled labor gaps? Machine learning and state machine processing can effectively replace many humans. Data mining is occurring on a level that is mind-boggling and, to be honest, downright frightening.
For example, Michael Bloomberg’s recent massive investment in a data mining approach to controlling the electorate does not bode well for you and I. While I applaud the goal, I am deeply afraid of the implications for what is left of consumer (i.e., voter) privacy. Where are the conversations about ethics and individual freedom and privacy? Where is the EFF or other orgs that normally care about such things? Have we all just given up any and all pretense of having privacy in this new world of data mining and individual profiling? We know where this can go, look at China’s recent ratcheting up of control over its citizens via massive investments in data-mining and facial recognition.
From a purely technological perspective, it’s nothing short of amazing how advances in cloud computing are removing barriers, sometimes daily, to processing what has always seemed like an infinite sea of data. Yet, at the same time, I am starting to feel a bit like how I think Bill Joy must have felt in the early 2000’s when he expressed regret over contributing indirectly to the rise of nanotechnology and what that meant for the future of humankind. My fearfulness is very real and legitimate, but at the end of the day, I don’t feel like I can stop the machine. I hope we survive this new period of even more rapid technological advancements in our culture and learn from it.