The Main Scoop, Episode 12: Is Cloud at an Inflection Point?

The Main Scoop, Episode 12: Is Cloud at an Inflection Point?

Today’s headlines are awash with reports of cloud repatriation. Some surveys show over 70% of IT respondents move some workloads, or data, back to on-premise infrastructure. Many business and technology considerations underpin this trend. Join Greg and Daniel as they host David Linthicum from Deloitte Consulting to unpack what’s behind these headlines and the impact on overall IT architecture decision-making.

It was a great conversation and one you don’t want to miss. Like what you’ve heard? Check out Episode One of The Main Scoop, Episode Two of the Main ScoopEpisode Three of The Main ScoopEpisode Four of The Main ScoopEpisode Five of The Main Scoop,  Episode Six of The Main ScoopEpisode Seven of The Main ScoopEpisode Eight of The Main Scoop, Episode Nine of The Main Scoop, Episode Ten of The Main Scoop, and Episode Eleven of The Main Scoop. Be sure to subscribe to never miss an episode of The Main Scoop series.

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Greg Lotko: Hey folks, welcome to our next episode of the Main Scoop. I’m Greg Lotko. I’m joined by my co-host Daniel Newman. Nice to see you.

Daniel Newman: Greg, it’s good to be back. Love being here with you on the main scoop. So much to talk about tech industry is ripping and roaring. Changes are everywhere, whether it’s from the cloud, whether it’s security, whether it’s AI, whether it’s the mainframe, Greg, there’s never a lack of things for us to talk about here on the show.

Greg Lotko: I agree. Let’s get into today’s topic. Let’s talk about cloud and focus on that. Do we believe it’s at an inflection point? We see a lot going on relative to cloud adoption and modernization, but are we at an inflection point?

Daniel Newman: Well, I think we have settled to some extent now. Vernacular is fluid, Greg, but you got hybrid, you got hybrid multi, you got multi, you’ve got varying definitions of multi. You got some people that multi is multiple hyperscaler. Others say multi is multiple clouds that could include private and edge and telco and everything else.

But what we have hit is a point where I think largely the world agrees that not every workload’s going into the public cloud. And everyone also agrees that not everything’s staying on prem. We are in an inflection. But now it’s almost coming down to a conversation, Greg, about distribution, meaning every organization, every entity’s looking across a continuum of on-prem to hyperscale and public clouds and saying, “Where do our workloads live across this continuum?”

Greg Lotko: And I think it’s funny, because I asked if we’re at an inflection point. We’re talking about cloud, and then you could easily jump down into a litany of a list of ways to refer to cloud, ways to refer to the different environments. And the idea that not everybody is going there with everything. That’s why we ended up having to talk about and have the term hybrid, about where different workloads are going to be. When we talk about modernization now, we’re not talking about cloud or some endpoint of the cloud being the way to modernize, we’re talking about modernizing IT and we’re talking about it holistically across your whole IT environment.

Daniel Newman: Yeah. I think what we will see is we’ll see different industries. You’re going to see different industry-led clouds. You’re going to see companies continually coming to a set of conclusions. And I think it’s going to be very fluid. I don’t think it’s going to be like, oh my gosh, we have the final destination is going to be 81% of our workloads will be here in 19%. I think it’s going to be very dependent. You’re going to have global data, you’re going to have data residency, sovereignty, compliance, you’re going to have this AI boom, you’re going to have security privacy. These are all going to play a role, Greg. And I think what would be amazing is perhaps bringing in someone that literally spends all their time all day long thinking about the cloud.

Greg Lotko: I agree. And I think we’ve set it up so that the conversation isn’t about cloud being everything as much of as it is about modernization and modernizing IT environments. But absolutely, let’s pull in David Linthicum, he’s from Deloitte, he’s chief cloud strategy officer, so he’s got it right there in his title. And he’s also an author and a cloud thought leader. David, let’s pull you in here. Tell us what you’re thinking about relative to modernization, and is it all about cloud, or?

David Linthicum: No, modernization is the ability to put workloads on the platforms where they’re going to be mostly fully optimized. That can’t be force fit cloud. Sometimes it’s edge and IOT, traditional mainframe systems, traditional core systems. And those could be in CoLOS or managed service providers or even on traditional data centers. The big thing now is trying to get technologists to open their minds up and close their magazines.

Greg Lotko: We’ve had a lot of people in the industry that had a cloud first mindset. But what you’re saying is, it’s about the data, it’s about the workloads, it’s about the business. Have a business first application, what it is you’re trying to accomplish, as the first mindset, right?

David Linthicum: Yeah. How can it be any other way? Sometimes I get frustrated when people lead with technologies. In other words, they’re trying to move to a cloud migration project or calling someone after a cloud provider that, this is where they’re moving to, and they don’t understand the issues around their own workloads, and what the profiles are there, and have done a true triage as to where these applications should exist. In many instances, they should exist on public cloud providers because of the attributes of those applications, the economies of running them, the ability to scale up and scale down and lots of things that cloud providers provide.

But if you’re dealing with very simple, repeatable processes and very static and slow growing storage loads, then on premise systems may be a better opportunity. If you’re getting into high performance computing, those still may be, on premise is a better opportunity dealing with legal and compliance issues as far as localizing the systems and data sovereignty stuff. All these things really come to bear in your ability to pick the platforms where they need to run. And one of the things we need to do as technologists is open our mind as to what they are, understanding the attributes, and understand we’re going to make these decisions downstream of the understanding the requirements and what the data sets and what the workloads are.

Daniel Newman: David, you heard me in the preamble, and I talked a little bit about this continuum. We talked to, as analysts, hundreds of CIOs every year, not to mention all the vendors and we do the back and forth. And I think there was a time when it was like, oh my gosh, everything’s going to the public cloud. And I think, thankfully, we’ve come to our senses. I think hybrid has become a bit of a panacea. I say hybrid multi because it’s almost like people want to call them different things, and in some ways, it might be if you’re using one public cloud and you’re using one on-prem, but that’s really not the reality of any enterprise anymore.

People have gotten to this, hybrid is the panacea. You spend a lot of time … At Deloitte, you’re spending time consulting and working closely with the world’s largest enterprises on building an operating model around cloud. I have to imagine that’s a big part of what you do. What are you finding is the reality as you help these companies finding their way? What are they learning? Is hybrid the panacea?

David Linthicum: Yeah, it’s really the fact that we’re not trying to back ourselves into an existing architecture. I agree with you 100% that we’re moving into a hybrid multi kind of environment. So we’re dealing with more plural public cloud providers as well as perhaps leftover private clouds on the enterprise space, and traditional systems, and even core cores. And the ability to … and edge computing and IOT really come into play there. And the ability to make all these things work and play well together really seems to be the challenges that enterprises are facing now.

And there’s really two tiers there. In other words, how do we mitigate the complexity that we’re building to make these things work at a rate that’s going to bring the maximum amount of value back to the business? Is the old IT problem. And opening our minds about the solutions to make it happen. The other issue you brought up was the ability to deal with culture and people, and understanding how this stuff is going to work, and understanding that it’s not going to be one direction, it’s not going to be as simple as that. We’re going to move in a variety of different directions and that’s for the benefit of the business. And we have to set up our operating models to set up our cultures, set up our skill sets, set up a skills array around making that happen moving forward.

Greg Lotko: I think it’s really interesting there, when you talk about opening up. And I think about everything we talk about in the technology space, it’s opening up processes, people, and technology. We think about opening up with APIs or using open source capabilities, it is opening up people’s minds to the awareness of what’s out there, the capabilities of different platforms and different technologies, opening up those workloads and allowing them to interconnect so that you’re leveraging the best technology for the best piece of the problem, but tying it together in an efficient and effective way to reduce complexity, but leverage the power and strength of the different platforms at the same time.

David Linthicum: Yeah, it’s absolutely got to be that way. Because I think we’ve understood for the last 40 years as IT’s progressed and evolved that it’s never going to be moving into one particular direction, that it’s going to be a panacea for the application hosting and system. It’s going to be a large variety of weapons that we have in our arsenal that we’re able to deploy in certain situations. Cloud really added lots of good weapons in how we store data and advanced analytics and some of the AI processing, and reasons why we want to put things there.

But every system and every deployment pattern is really going to have a value in your ability to make all these things work and play well together. And also, understanding that we’re coming from an environment, we have an as-is state. Considering what those are and moving to the 2B state, and how much cost and risk it’s going to put upon us, all those things need to be considered. It gets down to the answer that people hate from consultants: it depends. It depends on your as is state, it depends on your workloads, it depends on your security profile, your industry, all these really things.

Daniel Newman: What you’re trying to accomplish, right.

David Linthicum: What you’re trying to accomplish, right, to get to something that’s going to be close to being fully optimized as we can. I tell this to people all the time: I can solve most problems with any technology if I have enough time. But the reality is, I’m only going to find one solution that’s going to be as close to being 100% optimized as I can. We’re never going to be 100% optimized. We’re getting close. What does that solution, what does that configuration look like? And how are we going to make these things work and play well to get to the core reason we exist: to put value back to the business and provable value?

We’re not just giving them a configuration that we think is right, but I can mathematically prove that this is something that’s going to be close to being fully optimized versus the other thousand 10-factorial solution patterns that we have, which all work by the way. That’s where it gets dangerous because people say, “Well, it works.” It may work, but it’s costing you 100% more per year to maintain and operate these systems. We got to start thinking that way, start thinking in a selfish way to make sure that we’re maximizing the investment in terms of the value that’s coming back to the business.

Daniel Newman: David, the only person that likes to say “it depends” more than a consultant is an analyst, by the way. And I also start all my sentences by saying, “I believe,” because that way, you’re never too definitive. But in all serious, how do you get a customer to make those decisions? Like okay, you can say “it depends,” but at some point it depends on something. You take them through a process and then they ultimately do have to place the workload. How do you work them through that process of say … Is it cost? Is it agility long term is do you have to match it to some sort of business strategy document? Is it the corporate earnings promises that they’ve made to their shareholders? What drives the ultimate placement of that workload?

David Linthicum: I think it really comes down to soft and hard values. One of the things we just did at Deloitte, we did a study to look at digital transformations as it relates to the value of the business, and we found there’s a direct correlation with people who are successful with digital transformations as it relates to increasing the value of the business. Which means that, basically, if you automate better and innovate better, you’re going to have a business that’s going to be more valuable. Who’d have thunk that?

This is really about hard and soft values, number one. And I think that’s where we went off kilter first with cloud. In other words, we went to hard values, which were discernible operational cost savings that we could create from cloud … which were very hard to find by the way and hard to find now … and then the soft values. And looking at each workload with those kinds of lenses, if you get into multiple metrics where you’re looking at agility and different metrics and things like that, this is a little bit more easy to understand.

If I put this workload on this particular platform, how much hard value, operational cost savings, are going to come back over the years? And how much soft value I’m able to create: agility, the ability to move quicker, the ability to fund innovation, all those sorts of things. And looking at just those two dimensions, it’s pretty apparent as to where these platforms or where these application workloads and data dataset should reside. And the next thing also, and we just hit upon it earlier, is the culture of the organization. Sometimes organizations, they can’t handle the cloud, to quote A Few Good Men.

Your ability to understand your cultural ability to get into this series of stuff, your skill sets, your operational capabilities, all those things are germane to this. Because in many instances I may find the perfect platform or an application workload and a data set that’s going to provide the best value back to the business. They may not know how to operate it, have the skills around to make it happen, or even are going to maintain it fully moving forward because they just don’t have the culture to make that happen.

Greg Lotko: Back to your A Few Good Men there, sometimes businesses, they can’t handle the truth. They know in their deepest, darkest hearts they want a mainframe running somewhere in the background, because they know it’s not going to go down. It’s going to do those high throughputs, those high workloads, the chatty workloads that are interacting with storage a lot. Really good conversation. Makes a lot of sense.

Daniel Newman: Greg, I see a skit in the future of an SKO where you’re like, “Keep the workload on the mainframe. You can’t handle the cloud,” something like that. It’s going to have to come out, and then you’ll have to give David a cheer at some point in front of an audience, and I’m sure he won’t mind that. This is the Main Scoop. So one of the things, David, is you work with a lot of highly regulated industry clients. You know all of the kind of rhetoric about mainframe. Mainframe’s still massively critical in many industries.

It’s still a huge business. It’s still very important. It seems that there’s a lot of work being done on finding ways to have mainframe and cloud work, very interoperably and very interdependently. Talk a little bit about what you’re seeing in your role as the relationship between mainframe and what’s becoming this hybrid and multi-cloud architecture of most enterprises.

David Linthicum: Yeah, it’s fairly easy: it’s the ability to have these things work and play well together. And that always should have been on the radar screen. In many instances, they were looking at IT cloud as a replacement strategy for existing mainframe systems and it was really more or less an augmentation strategy. So again, to the workload stuff, if we find that some workloads are going to be better to run on the cloud and some run better on the mainframe, then you really need to focus on the connective tissue in between these two environments and make sure they seamlessly are able to work together, understanding that either isn’t going to go away.

Your strategy should be coexistence, your strategy should be devaluing, your strategy should be the ability to take advantage of each other’s platform’s capabilities and not focused on a migration strategy or a sunsetting strategy. We’re never going to have everything fully on cloud, we’re never going to have things fully on premise anymore, so what does that environment look like? Well, that looks like your ability to have a consistent control plane in dealing with security and dealing with management and dealing with data and dealing with metadata and dealing with governance.

And the ability not necessarily to deal with each of these silos on their terms, but the ability to deal with all the various capabilities using a common layer of technology that sits above the various systems that we’re running to make these things in essence more valuable. Because who knows if you’re getting your data from a mainframe? It’s transparent to you as a customer.

Daniel Newman: It doesn’t matter as long as you’re getting it.

David Linthicum: Yeah, as long as you’re getting it. And your ability to operate these things under the same consistent logic, the same consistent technology, security governance, things like that, is really going to be the next problem to solve over the next few years.

Daniel Newman: Yeah, I think that’s a really good way to frame it, David. I’d love to spend the last couple of minutes we have together here to just look into the future. Six months ago, seven months ago, most of the industry didn’t see generative AI coming on with such a rapid onset, meaning, I think we all knew … People keep talking about it like it’s … Google Workspace has been finishing my sentences on my emails for two years now. This isn’t really new, and we’ve all been doing a little multi turn.

Greg Lotko: You don’t finish your own sentences, but Google does.

Daniel Newman: Well, that’s why. I lost the capability. I’m slowly but surely deteriorating to nothing more than Dan bot. You saw, I launched an AI.

Greg Lotko: I did.

Daniel Newman: I eventually intend to just sit here and let the technology work for me. But in serious, David, that’s one example of what I would say is a bullish trend for hybrid. Because things like governance and compliance and security and privacy are going to drive companies to want to build foundational models and generative tools, but they’re not necessarily going to want to put it all into the public cloud without a lot of assurances that that data is going to be walled from being utilized for training future LLMs, et cetera, et cetera.
But I’d love to just get your take. What are the drivers in your mind that are going to make hybrid and multicloud an even more rapidly onset investment and adoption across the enterprise?

David Linthicum: Yeah, you hit the nail on the head. It’s pervasiveness of data and your ability to leverage information and data where it best resides. But also, your ability to leverage this data in a way that doesn’t necessarily force relocation of information. In other words, data virtualization, abstraction, all these sorts of things really come into play. As we move into the generative AI stuff, we have a couple of problems to solve. Number one, we have a massive amount of storage and processing that needs to occur to make these things run. And you can do that a couple of ways. Number one, you can run on the cloud and pay the processing and storage bills to make that happen.

But in many instances, on-prem systems that are going to have static costs, and certainly dealing with cheaper storage devices in many instances, are going to be a much better economical way to do that. Also, you have compliance issues to deal with. Those come along. PII information. And also, we’re getting into this whole thing, your ability to derive information from anonymized information to become PII. In other words, we have the capabilities now with some of these AI engines, we’re able to take a multitude of very complex data sets and where, there unto themselves really don’t violate any laws, your ability to aggregate these things, and using a generative AI engine to understand the essence of what they are and assemble them into PII is becoming an issue now as well, so what do you do with that?

This is really is about, to the previous problem, looking at where we should optimize the data and where we should exist? And also, where you need to have the data exist around the privacy and ethical concerns that are coming up. And that seems to be something that’s off everybody’s radars.

Daniel Newman: Well Greg, did you want the truth?

Greg Lotko: I can handle the truth.

Daniel Newman: Well, but can you handle the cloud truth? That is TBD.

Greg Lotko: I can handle the cloud truth. I recognize that a hybrid cloud is made up of on-prem, off-prem, multi-cloud, distributed workloads, mainframe. It’s all about all your AI [inaudible 00:19:53] together.

David Linthicum: Your smartwatch, your phone, your car, your TV.

Greg Lotko: All of it.

David Linthicum: It’s all … Anything we can connect to process and store information is going to be part of what that is.

Daniel Newman: And it’s only going to get faster, the data’s going to be exponential, and it’s going to force all of us to be thinking about all the great insights, David, that you provided today. Greg, you provided a couple as well. But David, I want to thank you so much. This is a really important topic, and while we do like to smile and have a laugh here and occasionally try to get into character of very historical, relevant movies, the transition we’re making is going to be substantial. It’s going to continue to happen more quickly, and companies, whether large or small, are going to need to be really thinking about the architecture of choice to be able to deliver on the promise of data, keep their data secure, offer applications for the next generation.
And David, really want to just say thanks for joining the Main Scoop and thank you so much for the expertise that you provided us here today.

David Linthicum: Well, thank you. Appreciate you inviting me on.

Greg Lotko: Thanks a lot, David.

Daniel Newman: All right everybody, there you have it. That’s it for this episode of the Main Scoop. Hit that subscribe button. We would love to have you join us for each and every episode. We promise to keep it fresh and keep it interesting. But for this episode, for Greg Lotko and myself, it’s time to say goodbye. We’ll see you all later.

Author Information

Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.

From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.

A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.

An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.


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