Itâs that time of year when pundits start to crank out their predictions for the next twelve months! Iâve been asked to contribute to a private group (and occasionally, Techstrong Group asks me to contribute to their annual list), so I wonât thrill you with my predictions just yet; but I will discuss the cycles and trends that previous predictions have shown.
Back when I was testing physical servers, we thought of throughput bottlenecks in terms of where the problem was. The circle would go disk->memory-> CPU, and in the case of things like NAS, insert network in there somewhere, too. When one bottleneck was resolved, another would crop up. And users will always seem to be pushed to the next bottleneck.
We see similar cycles in DevOps. First, Agile made development faster, and that caused us issues throughout the rest of the process. Then, DevOps helped with the build and a little with the testing and deployment steps, but in the early days it was more standardization than speeding up. And since then, we have been in that cycle. Weâre seeing GitOps speed up and automate deployment and upgradesâbased upon the automation that came beforeâweâre seeing test and security tools feeding directly into the IDE to speed resolution, weâre seeing container automation cause âcloud-first developmentâ (I hate that name; Kubernetes has cloud-like interfaces, but is not precisely cloud) to be fully automated, and thus faster.
And weâre looking at that cycle continuing. No doubt you will hear a lot of predictions that start with âAI âŚâ For the most part, AI is a tool and/or technique. Listen for what it is improving because it is doing very little that’s actually new. (Delete list of things that sounded alarmingly like those predictions I said I wouldnât make.)
All in all, we are still living in a very cool technological time. We can have a tool generate code snippets of the dull work for us so we can focus on the important bits. Some shy away from this use of âAI,â but honestly, we already use libraries to do the grunt workâI havenât written to a screen buffer in foreverâbecause we donât have to. Same storyâuse the tools that make you productive. Some of the more obscure bits of Linux command lines are far better dealt with by asking an AI to give me examples than searching through tons of docs across several platforms. Never was much of a fan of man output for complex commands, this makes it easier. The nice bit is that bash and UNIX utilities donât change much over time, so answers can be a bit dated and perfectly accurate. Thatâs not true for much of IT.
The environment has consistently gotten more complex, while the building blocks have gotten easier to use. This allows things to keep moving and changing while it offers us better ways to serve the organizationâs needs. This does change at some pointâinfinite change is indeed a thing, but any technology does have its limitsâbut I honestly canât see the point at which we are content with our IT tools and stop looking for more. Oh, most organizations go through those cyclesâorganizationally, once an infrastructure and process works correctly, it is likely to hang around until better is foundâbut the industry will keep changing.
And youâll keep learning and changing. Thatâs one prediction I will make for next year. Teams and IT staff will grow and learn new things, because at its heart, that is what we do. We learn new things and keep the lights on. In good years, we offer sweet new tools and functionality to the company or our customers. But either way, we keep things online. Year after year. You all rock, so thatâs an easy prediction.

