Challenges of Evolving Traditional IT to Hybrid Cloud and Enterprise AI
Analyst Jean S. Bozman, president of Cloud Architect Advisors, explains how evolving traditional IT to hybrid cloud and enterprise AI forces IT teams them to manage complexity, acquire new skills and manage a myriad of costs.
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Transcript:
Jean Bozman: It’s amazingly well accepted. It’s not controversial. Hybrid multi-cloud. You cannot almost go to a tech person that wouldn’t agree with that statement. There’ve been different terms. There was hybrid cloud than they said because there were multi-cloud. It’s hybrid, multicloud. I think it’s an admission. That data is everywhere. And so I’ve distributed data and that was fed by the fact that we had the hyperscaler guys. Some people call ’em CSPs hyperscale, where the big guys know who they are. And the data is not just sitting in one monolithic place, it’s sitting here, there, and everywhere. And even the people who used to think that it would just be on one or two systems, it is not that way anymore. Anyway, so it is a fact of life, but the question is how do you live with it? It’s that way. How do you live with it? How do you get the two things that have been running in parallel, which is distributed, we know that’s happening, but also the traditional enterprise stuff. How do you get those things to sync up and work together? And I think a lot of what we’ve heard here is about how do you get those enterprise capabilities, manageability, all the things we’ve always had to have and how do you make that happen in a world that may otherwise seem chaotic?
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This is a challenge for the enterprise where people say, Hey, that’s not how I’ve been doing things for 20 years, or Hey, I didn’t learn how to do this, or I need these new skills. So there is a skills challenge and there’s also a cost challenge because we know what we were doing and the thing we are doing seems additive, but now we really want to kind of embrace everything and do it all at the same time. People were living separately, right? You had the people who always advocated for distributed and lots of little databases here and there, and that was cool. Especially forgive me for my sins, but the open source movement. So fun. But it’s okay to have fun, but you also need to run a company. So you need to put those business best practices. I want to say the best practices to work and that’s what could be a chaotic environment, but should be a smoothly running, unified environment.
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A lot of the AI stuff comes out of the same kind of people that have been doing the open work, but it’s applying, I think a new rigor to it. And also there is the demographic piece. I’m absolutely going to talk about that. Where traditional IT has been running for, what, 40 years or something like that. A lot of these things are a sudden shock to systems that have been reliably in place when you talk about let’s do backups, let’s do security. It was done a certain way. All that’s having to be adjusted, I think, and that’s clear to people.
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AI was kind of, I don’t know, it was almost a shock to people. All of a sudden, it’s in your face now what do I do? I’ve got lots of data. I’ve got these models. I know other people here. We’re talking about the models and where they are and who’s going to do it. And there’s a very big difference in training the models, which takes up a lot of CPUs, GPUs, software. But there’s also the inference stuff, and that can be customized to your business. Healthcare, retail, finance, it’s customized. And also it’s easier to get your arms around it than trying to take in everything that was ever written just to write a haiku. That’s not an enterprise thing by itself. It can fit into the enterprise. People writing things, people being creative, but it’s not enough. There’s a lot of rigor that has to come around that controls guideposts and all of that.
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All the things we were always careful for all these years. So AI is tremendously exciting to people. By the way, I’ll give you my controversial statements, which is Tech GT is great, but AI is much, much bigger. We had ai. AI was in the background doing data management, finding financial fraud, looking at medical records. That wasn’t sexy enough. But now it is more sexy. It’s in my office, I can see, oh ai, that’s great, but it’s not enough. It has to blend in. Great tool, wonderful to learn about and use. Very useful, but it needs to mix in with everything else that’s been developing over the last 10 years.
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Artificial Intelligence, Cloud Computing, Tech Barometer - From The Forecast by Nutanix, Video Podcast
