>>From around the globe. It's the cube presenting cube on cloud brought to you by Silicon angle. >>Welcome back to coupon cloud I'm Paul Gillan enterprise editor of Silicon angle. You know, as we look ahead at what is in store for the cloud this year, one of the intriguing possibilities that has emerged is the rise of vertical clouds. IBM has been a leader in this area with its launch in late 19 of the IBM financial services cloud. That's a services ready public cloud with exceptional security, as well as Polly, a policy framework for certifying compliance and services from the IBM subsidiary. Promintory now with the IBM financial services cloud, uh, that has been a major focus of our next guest, Hillary Hunter. She is the vice president and CTO of IBM cloud and IBM fellow and a veteran of, I believe, three previous appearances on the cube. Am I right Hillary? >>Yep. Sounds about right. Great to be back here today. >>Thanks for joining us. So let's start with getting an update on the IBM financial services cloud. What progress have you made in signing up customers and your ecosystem of partners? >>Yeah, you know, we've made really significant progress, uh, progress in advancing the IBM cloud for financial services since we last talked, you know, and, and we're really at that place of establishing a trusted platform for the industry, just in, you know, some specifics in addition to bank of America, which we had talked about as our us anchor partner for the program. Um, we've announced several global banks, um, that are partnering with us for the global expansion of the program, including BNP party, you know, which is one of Europe's largest banks. Um, more than 70 ASVs are signed up with us now as part of the program and adopting IBM cloud for financial services, this level of sort of ecosystem is, is exciting because it means that, you know, banks will have the opportunity to, to transform what they're doing, but do so in a way, which is driven by security and compliance, um, so that they can be confident in those deployments on IBM cloud for financial services. >>We also released the IBM cloud policy framework for financial services. This is both the sort of security and compliance posture of the environment, as well as, you know, guidance on controls, reference architectures automation to help people on board. And so both ISBNs and banks now are able to, um, onboard to this environment and offer their wares and deploy their workloads. So it's a really exciting state for us on the program. And we're really in a place where there'll be, you know, an ongoing cadence of, you know, additional releases and announcements of additional partnerships and clients. So it's an exciting time in the program. >>Uh, one of the distinctive features I think of this, uh, of this launch is that you're working actively with your customers. They're working with you on building policy frameworks, as well as I imagined the features that you're offering on the cloud. How do you orchestrate all of these different customers and get them involved and actually co-development >>Yeah. You know, it's the ecosystem conversation and the partnership conversation are two of the fundamental aspects of the program. Like you said, this isn't, you know, just us sitting off in a bubble, inventing the future. Um, you know, we're working internally with partners, uh, within IBM like IBM Promintory, um, which is a consultancy that has deep, deep regulatory expertise and in jurisdictions globally with IBM security services. And then with these individual partners and banks and clients, one of the ways that we bring everything together is through our councils. So our council, our cloud council for financial services, um, it's where we have global systemically important financial institutions partnered with us and, and working together with one another. And, and that covers, you know, CIO is it covers chief security officers, risk officers, et cetera. Um, so we have some formality around how we work with, um, all of these partners, uh, really as a body and as a group. >>And what have you learned from this experience? I mean, if you were to go into the, uh, into other vertical clouds, what have been the lessons >>Ecosystem is so important, right? It's as I look at this space, I see that, you know, everyone has an existing business, they have a platform they're running, they have clients they're trying to service. Um, but those, the software providers into this space are looking themselves to transform their they're looking to transform from being a software vendors, to being SAS providers, the banks and financial institutions themselves are looking to transform from working on their own premises to benefit from the Alaska city and the scale and the optionality of, you know, that being in public cloud provides. So there's a lot of, um, parties themselves that are trying to transform and a lot of vendors into the financial space that are looking to transform. And in that time of a lot of change ecosystem is, is absolutely key. And so, um, the ISE and SAS providers, you know, providing their wares on the cloud for financial services is, is really just as important as those financial services institutions so that everyone can make that transition together. Um, and so that banks that are looking to digitally transform can, can leverage partners that are really at the forefront of that change in that innovation and in platforms for the industry. >>Would you say that there are, is this the first of many, I mean, are there going to be other vertical financial or other vertical IBM clouds or is the range of industries that really need that kind of specificity limited? >>I think it's, it's actually not limited, you know, though, I will say that within the space of industries that are heavily regulated, there's obviously a deeper need for sort of specific cloud embodiments and cloud implementation. So regulated industries like insurance, like telco healthcare, et cetera. Um, these are the ones I think, where there's the greatest opportunity to do verticals that are specific to industry. Um, but you know, as we look at this, this is absolutely part of an IBM cloud strategy to deliver industry specific clouds. And, and, and this comes from our decades of expertise, right? Even in financial services, being able to leverage, you know, those other entities within IBM that I mentioned, right. You know, our, our regulatory, um, background with companies, you know, having helped them address regulatory needs for specific industries, and then translating that into cloud and cloud technologies. Right. And, and then coming up from the other side, you know, in terms of the technologies themselves, we've partnered with key industries, um, to deliver security and data protection and cryptography technologies and such on premises. And we're contextualizing that now for cloud and public cloud deployments. And so it kind of brings together the pieces of decades of expertise and platforms and technology and regulations and contextualizes it into cloud. And I absolutely think that's, you know, an opportunity for, for other industries as well. >>Can you give us a bit of a preview? I mean, do you have specific industries in mind? Is there a time? >>Yeah, so, so, uh, late last year we did announce a second industry specific cloud initiative and that was IBM cloud for telco. So we have in that ecosystem now over 40 partners that are announced, that are working with IBM and with red hat, especially with, um, clients and partners that are looking to help with that transition into 5g and increasing use of IOT. 5g is really this disruptive opportunity for that industry. And, and also just for many other different types of companies and institutions that are looking to deploy with more efficiency, better operational efficiency, deploy with AI capabilities, really being able to do things that like cellular network edge, um, and the places that they're doing business using IOT devices and 5g will enable much of that to really transform and flourish. So a couple of the partners, initially, in addition to that ecosystem that I mentioned in cloud for telco, um, you know, we've got Samsung working with us, Nokia ATNT, et cetera. Um, and so, you know, these, these partnerships and, and capabilities around network edge, um, and specific capabilities in cloud for telco, um, are sort of that second, you know, public announcement that we've made around industry specific cloud, >>As far as your competitive position is concerned. I mean, are, are you taking away business from your competitors when you partner with these, these telcos and these banks, or is this an entirely new line of business that was not previously in the cloud? >>Yeah. You know, these are really, I think in, by and large new opportunities as we look at, you know, for example, how we as customers expect to engage with, um, you know, our bank, right. You know, we are looking to increasingly engage with a bank in a digital way, use our applications, use mobile devices. We're looking for, you know, individual bank outlets, uh, branch outlets of, of a banking institution to be increasingly smart, to service our needs, you know, more quickly, et cetera. Um, and so as we look at, you know, 5g and telco edge, it's about delivery of sort of smarter capabilities and such. I think much of it really is about in this digital transformation space about, you know, creating new capabilities, creating new experiences, creating new ways of engagement, um, and engagement and an opportunity to customize and personalize. Um, I think most of those are sort of new experiences and new capabilities for most companies. >>So speak about IBM's positioning right now. I mean, you're not one of the big three cloud providers to, to become one. Uh, but you do have as a big cloud business and, uh, you've, you've got the verticals, you've got the multi-cloud, uh, I know IBM is big, has been a big champion of multi-cloud. I mean, how is IBM distinctively positioned in the cloud market right now? >>Yeah. You know, we are all in, on hybrid cloud and AI. And if you listened to our CEO and chairman, you'll hear that it is a really consistent message. And he, since he came into his role as, as our CEO, um, so being all in, on hybrid cloud and AI, you know, we really are looking to help our clients transform into holistic cloud architecture. Right? So, so when I say all in, on hybrid cloud, I mean that, you know, it's, there's been a lot of sort of, I jokingly say random acts of cloud usage, right? People have ended up using cloud because there's some SAS function that they want, or some particular line of business has been highly motivated to pursue some service on a particular cloud. And hybrid cloud is really about taking a step back, having a holistic architecture for cloud consumption. And in that sense, you know, uh, clouds, uh, are IBM's partners. >>Um, and we're really looking to enable our clients to have consistency in their deployments to consolidate across their it estate and across their cloud deployments so that they can have, um, a common platform, so they can have efficiency in how their developers to like capabilities. So they can deploy more quickly with security and compliance patterns and have oversight over everything that's going on in a consistent way that really enables them to have that velocity in their business. And so when we then, you know, positioned things like industry cloud, we're leveraging IBM specific technologies to deliver differentiated capabilities and data privacy, data protection, security compliance, where these industries in public cloud. Yes. But it's in the context of helping our clients overall across all the different things. Some of which may not need all of that data privacy or, or, or be leveraging particular SAS content we're looking to help them really have cloud architecture have a holistic conversation across hybrid cloud. Um, and yet to still be able to choose particular cloud deployments on our cloud for industries, um, that enables data protection and policy for the most sensitive and, and enterprise grade things that they're looking to do at the core of their business. >>So speaking of hybrid hybrid cloud, I mean the major cloud providers, Amazon, Microsoft, Google, Oracle, and other one all have on premises offerings right now. Uh, several of them are working with telcos to expand their reach out into, uh, into co-location and into telecom, uh, data centers. Uh, all of these things were to enable is this distributed cloud fabric kind of a hybrid cloud fabric what's, IBM's play in this area. Uh, do you have a similar strategy or is it different? >>I really think, and I think you maybe wanted to get a little bit into sort of, you know, trends and predictions here in this conversation and, and, and, you know, we, we absolutely see that need for distributed cloud for cloud to really kind of be alive in all the places where it needs to be in, in all the places that someone is doing business and in a consistent way across cloud environments, um, to be one of those major trends, that's emerging as a really hot conversation. We have introduced IBM cloud satellite, um, that is IBM's hybrid cloud as a service platform, um, and enables our clients to leverage, um, uh, OpenShift and Kubernetes environments, developer tooling, uh, consistency in a cloud catalog, visibility and control over all their resources, um, across different environments. And to be able to run end, to end with consistency from on-premises to edge to different public cloud providers. >>Um, and this is absolutely something that across industries, but, you know, within also those industries that we're focused on in particular, um, that we're seeing a lot of interesting conversations emerge because if cloud is sort of everywhere, if cloud is distributed and can be on premises and in public cloud, it enables this consistency in this parody, um, really that sort of brings together that, that seamlessness, not just the random acts cloud usage, right? I mean, it means that using cloud, um, can be something that, that drives, you know, speed of release of new product. It means that you can deliver more capability and functionality into, you know, a retail outlet where you're doing business or a banking, you know, brick and mortar location. Um, you can have, you know, AI for it ops and understand what's going on across those different environments and ensure things are kept secure and patched and updated, and you're responding to incidents in efficient ways. Um, and so really having a consistent cloud environment and a distributed cloud environment across different locations, um, it's really key to leveraging the promises of what everyone had originally hoped to get out of out of cloud computing. >>Of course, one of IBM's distinctive, uh, advantages of this area is you've got a huge hardware install base out there. I mean, how do all those three 60 mainframes figuring it out, figure into this, >>Um, with the OpenShift capabilities in our Clara operations with red hat in this area, we are able to actually help our clients leverage Kubernetes and Linux and all those things, even on the mainframe. So across the mainframe family, the IBM power family, um, you know, where folks may also have AIX or IBMI deployments, people can now do Lennox, they can do open shifts, they can do Coopernetti's. Um, and we have core technologies that enable that really to be stitched together. And I think that's one of the unique perspectives that IBM has in this whole conversation about hybrid cloud. Um, there are many different definitions of hybrid cloud, but we really view it as stretching from the traditional enterprise. It, like you said, there's a lot of it out there and being able to also incorporate OpenShift and Kubernetes in a common cloud platform, um, on traditional enterprise, it on private cloud, on fresh deployments, on private cloud, Amazon public cloud, that really is the whole it estate. So when we talk about hybrid cloud, when we talk about distributed cloud, really talking about the entirety of VIT state, not just sort of new deployments of, of SAS or something like that. >>So as someone who's on the front lines of, you know, what customers are asking about cloud, do you see customer the questions that they're asking changing? Are they, are they their decision criteria changing for how they choose a cloud provider? >>Yeah. You know, I think that, um, there's definitely a lot more conversation, especially in this current era where there's an accelerated rate of cloud adoption. Um, there's a lot more conversation around things like security, um, data protection, data, privacy, being able to run in an environment that you trust, not just is it a cloud and what does it do, but can I trust it? Do I understand how my data is protected, how my workloads are secured? Um, you know, that's really why we started cloud for financial services because that industry shepherds such vital data, right? So the reason that they are highly regulated is because of the importance of what they are stewarding very important data and financial information. Um, so, you know, we began there with the cloud for regulated industries there with, with financial services, but I see that across all industries, I was participating on a panel, um, that was, uh, with a bunch of CEOs. >>And I was there interviewing some CEOs who were from a much more sort of consumer facing and also from, from foods industry, et cetera. And their conversation was exactly the same as I have with many other clients, which is that their cloud choices, their efficiency and cloud deployment now are largely driven by the ability to get to a secure posture and the ability to demonstrate their, to their internal security and risk teams that they understand their data protection, data, privacy posture. So we are seeing lots of pickup and, and conversation opportunity around confidential competing specifically. Um, and you know, that's really about enabling, uh, our clients to have full authority and privacy in their computing, in their code and their data, even when running in a cloud environment. And so I do see a shift everyone's more concerned about security, and I think we have great technologies and we've been working with core partners to establish and harden and, and create, um, generations of technology that can really answer those questions. >>I have to ask you about that term confidential computing. I haven't heard that before. What, what does that involve? >>Yeah. You know, it's, it is a buzzword to watch out here for an in 2021. So confidential computing means being able to run in an environment where there are others in a, in a cloud computing environment, for example, um, but still have full privacy and authority over what you're doing. So you are effectively in an enclave, uh, imagine yourself sort of protected and secured. And so our confidential competing technologies, um, we're actually on basically our fourth generation of, of, of the hardware and software technologies to create that strong degree of isolation. Um, this enables us to deliver a really rich portfolio. Um, frankly, the, the, the richest portfolio in the industry of actuals services delivered, um, using confidential, competing and secure enclaves. And so we can enable our customers to solution things in a way, for example, where their data, you know, can not even be visible to our cloud operators or where they, uh, retain, you know, full control over, you know, a database and have full privacy as they're running in that environment. Um, these are really great, um, you know, considerations, but they impact everything from health care financial services. Uh, we have other partners and clients who are working to protect consumer data, um, you know, through these means et cetera. And so, um, across different industries, everyone's really looking at this topic of data, privacy, data protection. Um, and so we have a whole suite and whole family of confidential competing based, uh, services that we're able to offer to, uh, offer those assurances and that privacy to them in their cloud competing. >>I do have to ask you about the multi-cloud because this is a topic of constant debate in the industry of whether customers want to move shift workloads across multiple clouds to protect themselves from lock-in. I mean, is that a fantasy? Is that real? Is that a too restrictive? Uh, this has been a key part of IBM strategy is enabling the multi-cloud. How do you see customer attitudes developing right now? How do they want to use multiple clouds or in fact, do they, are they, are they, uh, concentrating perhaps more of their workloads in one or two? >>Yeah. You know, we believe vendor locking goes against the true spirit of hybrid cloud, right. Um, that desire to have consistency across environments, um, that desire to, uh, and the business need to have, you know, continuity and resiliency and operations, et cetera. Um, and so I do see this as a really important topic, um, from the perspective of, you know, managing environments, I think in multi-cloud, um, I think folks are starting to realize that multicloud isn't necessarily a strategy. It's a reality. Um, people have deployments in lots of different cloud environments, um, that happened somewhat organically in many cases. And so the key question is how to then get to visibility and control over those resources. Um, I think kind of two of the, the, the core topics in that are multicloud management, um, you know, being able to understand, you know, clusters and virtual machines and other things that are deployed across different environments and manage them with a common set of policies, for example. >>Um, and then in addition to multicloud management, um, I, for it, operations is another really important topic in, in multi-cloud being able to respond to incidents, understand and analyze and leverage AI, um, for what's going on for understanding what's going on across those environments, um, is another really core topic. And then as you said, you know, distributed cloud is a means of getting that consistency, having a common, you know, control and deployment plane across those different environments, um, can help it not just be sort of accidental usage of multiple cloud environments, but very intentional deployment based on the needs of particular workloads to the environment that they're best suited to. Um, and, and that's really what you want to aim for. Um, not that multi-cloud is necessarily, um, you know, uh, uh, I guess I would say is, is it is a, um, it is a complexity that is manageable, um, through these, you know, new types of technologies and multicloud management and such like that, and cloud >>Well, uh, Hillary TIS, the season for predictions is January, uh, everyone's prognostic table of what the future will look like. What do you think are going to be the main trend lines in cloud this year? Yeah, >>You know, I, I sort of sprinkled a few in there as we were talking, but I really do think that, um, the conversation around hybrid cloud number one, how to have an open innovation ecosystem for cloud, where, um, you have a consistency across environments, you know, not just random acts of cloud usage, but intentional and holistic architecture. Um, I really see that as the transition to sort of the second wave of, of cloud adoption. Um, and then secondly, as we were talking earlier about security, right, everyone is wondering about data policy and data privacy. Um, we've always taken a strong stance that, you know, our client's data is, is, is their data. We are not going to be using their data to, you know, further develop our, um, you know, AI services on our cloud or something. Um, we have deployed technologies and confidential computing that enabled them to keep full control over their keys so that, you know, even our caught operators center have access to data, um, competing in secure enclaves, where they have a strong degree of isolation and full privacy and authority over their workload. >>I really think, you know, these two topics open and secure hybrid computing and with consistency across environments, but distributed cloud technology. Um, and secondly, security, I think these are really important topics for 2021, and they may seem a little bit obvious, but I think it's important as people look at this to look for technologies that are multiple generations into this journey, right. Um, you know, partner with, um, folks who, um, are, you know, committed, uh, very clearly to an open ecosystem and open source innovation on the one hand. Um, and secondly, you know, um, when we talk about security and data protection, you want to know that that provider is several generations into that journey. Um, you know, so you really know that that technology has been vetted out is that production scale and has the stable basis. And so I think this is the year when folks are transitioning from cloud adoption, uh, to consistency in cloud and security and privacy in cloud >>Final question. And it has nothing to do with cloud. You're an IBM fellow. And I see that term, uh, turn up occasionally with other other people I've spoken to from IBM, what is it? IBM fellow, how do you become one and what right. Privileges and responsibilities as an entail. >>Yeah. You know, it's an exciting opportunity to be an IBM fellow. There's about a hundred active IBM fellows, um, right now. Um, so there aren't too many of us, but there is a small community of us. Um, IBM fellow is IBM's highest technical designation within our technical population. Um, so I do have a role within our cloud business. Um, but as one of our technical leaders, um, get to interact with the other fellows, um, you know, work on strategy for IBM in technology overall as a company. Um, and I also get to sort of be a trusted advisor to many of our clients. And so, um, I get to with CTOs and CEOs and VP of application development, um, you know, kind of, kind of profiles and VP of, of it and things like that, um, in our different clients and really help them wrestle through those struggles, um, of, you know, future it transformation. >>And so, um, you know, part of what I enjoy most about sort of the role and, and the fellow role is, is being able to kind of be that trusted advisor to many of our clients. There's been so much change in this last year for everyone. Um, and being able to, you know, also, you know, help our technical population through that, you know, in various means and then help our clients, um, through all of that change and really being able to take and grasp onto the opportunities, um, that this last year has had in the way that we work has changed. And the way that companies are looking to deliver capabilities has changed. Um, so that's, for me, the exciting part of, of the role, >>Or you're wondering a hundred then, and you do a great job of articulating the IBM strategy and also the, uh, the cloud landscape, Hillary Hunter, VP and CTO, excuse me, CTO of IBM cloud. Thank you so much for joining us today on Cuban cloud. >>Thanks so much for having me. It was a pleasure. >>I'm Paul Gillan stick with us.

(energetic music) >> Hi, and welcome to another Cube conversation, where we go in-depth with the thought leaders in the industry that are making significant changes to how we conduct digital business and the likelihood of success with digital business transformations. I'm Peter Burris. Every organization today has some experience with the power of analytics. But, they're also warning that the value of their analytics systems are, in part, constrained and determined by their access to core information. Some of the most important information that any business can start to utilize within their new advanced analytic systems, quite frankly, is that operational business information, that the business has been using to run the business on for years. Now, we've looked at that as silos and maybe it is. Although, partly, that's in response to the need to have good policy, good governance, and good certainty and practicably in how the system behaves and how secure it's going to be. So, the question is, how do we marry the new world of advanced analytics with the older, but, nonetheless, extremely valuable world of operational processing to create new types of value within digital business today? It's a great topic and we've got a great conversation. Tendu Yogurtcu is the CTO of Syncsort. Tendu, welcome back to The Cube! >> Hi Peter. It's great to be back here in The Cube. >> Excellent! So, look, let's start with the, let's start with a quick update on Syncsort. How are you doing, what's going on? >> Oh, it's been really exciting time at Syncsort. We have seen a tremendous growth in the last three years. We quadrupled our revenue, and also number of employees, through both organic innovation and growth, as well as through acquisitions. So, we now have 7,000 plus customers in over 100 countries, and, we still have the eight 40 Fortune 100, serving large enterprises. It's been a really great journey. >> Well, so, let's get into the specific distinction that you guys have. At Wikibon theCube, we've observed, we predicted that 1919, 2019 rather, 2019 was going to be the year that the enterprise assert itself in the cloud. We had seen a lot of developers drive cloud forward. We've seen a lot of analytics drive cloud forward. But, now as enterprises are entering into cloud in a big way, they're generating, or bringing with them, new types of challenges and issues that have to be addressed. So, when you think about where we are in the journey to more advanced analytics, better operational certainty, greater use of information, what do you think the chief challenges that customers face today are? >> Of course, as you mentioned, that everybody, every organization is trying to take advantage of the data. Data is the core. And, take advantage of the digital transformation to enable them for taking, getting more value out of their data. And, in doing so, they are moving into cloud, into hybrid cloud architectures. We have seen early implementations, starting with the data lake. Everybody started creating the centralized data hub, enabling advanced analytics and creating a data marketplace for their internal, or external clients. And, the early data lakes were for utilizing Hadoop on premise architectures. Now, we are also seeing data lakes, sometimes, expanding over hybrid or cloud architectures. The challenges that these organizations also started realizing is around, once I create this data marketplace, the access to the data, critical customer data, critical product data, >> Order data. >> Order data, is a bigger challenge than I thought that it would be in the pilot project. Because, these critical data sets, and core data sets, often in financial services, banking and insurance, and health care, are in environments, data platforms that these companies have invested over multiple decades. And, I'm not referring to that as legacy because definition of legacy changes. These environment's platforms have been holding this current critical data assets for decades successfully. So-- >> We call them high-value traditional applications. >> High-valude traditional sounds great. >> Because, they're traditional. We know what they do, and there's a certain operational certainty, and we've built up the organization around them to take care of those assets. >> But, they still are very very high-value. >> Exactly. And, making those applications and data available for next generation, next wave platforms, is becoming a challenge, for couple of different reasons. One, accessing this data. And, accessing this data, making sure the policies and the security, and the privacy around these data stores are preserved when the data is available for advanced analytics. Whether it's in the cloud or on premise deployments. >> So, before we go to the second one, I want to make sure I'm understanding that, because it seems very very important. >> Yes. >> That, what you're saying is, if I may, the data is not just the ones and the zeroes in the file. The data really start, needs to start being thought of as the policies, the governance, the security, and all the other attributes and elements, the metadata, if you will, has to be preserved as the data's getting used. >> Absolutely. And, there are challenges around that, because now you have to have skill sets to understand the data in those different types of stores. Relational data warehouses. Mainframe, IBMI, SQL, Oracle. Many different data owners, and different teams in the organization. And, then, you have to make sense of it and preserve the policies around each of these data assets, while bringing it to the new analytics environments. And, make sure that everybody's aligned with the access to privacy, and the policies, and the governance around that data. And also, mapping to metadata, to the target systems, right? That's a big challenge, because somebody who understands these data sets in a mainframe environment is not necessarily understanding the cloud data stores or the new data formats. So, how do you, kind of, bridge that gap, and map into the target-- >> And, vice-versa, right? >> Yes. >> So. >> Likewise, yes. >> So, this is where Syncsort starts getting really interesting. Because, as you noted, a lot of the folks in the mainframe world may not have the familiarity of how the cloud works, and a lot of the folks, at least from a data standpoint. >> Yes. >> And, a lot of the folks in the cloud that have been doing things with object stores and whatnot, may not, and Hadoop, may not have the knowledge of how the mainframe works. And, so, those two sides are seeing silos, but, the reality is, both sides have set up policies and governance models, and security regimes, and everything else, because it works for the workloads that are in place on each side. So, Syncsort's an interesting company, because, you guys have experience of crossing that divide. >> Absolutely. And, we see both the next phase, and the existing data platforms, as a moving, evolving target. Because, these challenges have existed 20 years ago, 10 years ago. It's just the platforms were different. The volume, the variety, complexity was different. However, Hadoop, five, ten years ago, was the next wave. Now, it's the cloud. Blockchain will be the next platform that we have to, still, kind of, adopt and make sure that we are advancing our data and creating value out of data. So, that's, accessing and preserving those policies is one challenge. And, then, the second challenge is that as you are making these data sets available for analytics, or machine learning, data science applications, deduplicating, standardizing, cleansing, making sure that you can deliver trusted data becomes a big challenge. Because, if you train the models with the bad data, if you create the models with the bad data, you have bad model, and then bad data inside. So, machine learning and artificial intelligence depends on the data, and the quality of the data. So, it's not just bringing all enterprise data for analytics. It's also making sure that the data is delivered in a trusted way. That's the big challenge. >> Yeah. Let me build on that, if I may, Tendu. Because, a lot of these tools involve black box belief in what the tool's performing. >> Correct. >> So, you really don't have a lot of visibility in the inner workings of how the algorithm is doing things. It's, you know, that's the way it is. So, in many respects, your only real visibility into the quality of the outcome of these tools is visibility into the quality of the data that's going into the building of these models. >> Correct. >> Have I got that right? >> Correct. And, in machine learning, the effect of bad data is, really, it multiplies. Because of the training of the model, as well as insights. And, with Blockchain, in the future, it will also become very critical because, once you load the data into Blockchain platform, it's immutable. So, data quality comes at a higher price, in some sense. That's another big challenge. >> Which is to say, that if you load bad data into a Blockchain, it's bad forever. >> Yes. That's very true. So, that's, obviously, another area that Syncsort, as we are accessing all of the enterprise data, delivering high-quality data, discovering and understanding the data, and delivering the duplicated standardized enriched data to the machine learning and AI pipeline, and analytics pipeline, is an area that we are focused with our products. And, a third challenge is that, as you are doing it, the speed starts mattering. Because, okay, I created the data lake or the data hub. The next big use case we started seeing is that, "Oh yeah, but I have 20 terabyte data, "only 10% is changing on a nightly basis. "So, how do I keep my data lake in sync? "Not only that, I want to keep my data lake in sync, "I also would like to feed that change data "and keep my downstream applications in sync. "I want to feed the change data to the microservices "in the cloud." That speed of delivery started really becoming a very critical requirement for the business. >> Speed, and the targeting of the delivery. >> Speed of the targeting, exactly. Because, I think the bottom line is, you really want to create an architecture that you can be agnostic. And, also be able to deliver at the speed the business is going to require at different times. Sometimes, it's near real-time, and at batch, sometimes it's real-time, and you have to feed the changes as quickly as possible to the consumer applications and the microservices in the cloud. >> Well, we've got a lot of CIO's who are starting to ask us questions about, especially, since they start thinking about Kubernetes, and Istio, and other types of platforms that are intended to facilitate the orchestration, and ultimately, the management of how these container-based applications work. And, we're starting to talk more about the idea of data assurance. Make sure the data's good. Make sure it's been high-quality. Make sure it's being taken care of. But, also make sure that it's targeted where it needs to be. Because, you don't want a situation where you spin up a new cluster, which you could do very quickly with Kubernetes. But, you haven't made the data available to that Kubernetes-based application, so that it can, actually, run. And, a lot of CIO's, and a lot of application development leaders, and a lot of business people, are now starting to think about that. "How do I make sure the data is where it needs to be, "so that the applications run when they need to run?" >> That's a great point. And, going back to your, kind of, comment around cloud, and taking advantage of cloud architectures. One of the things we have observed is organizations, for sure, looking at cloud, in terms of scalability, elasticity, and reducing costs. They did lift and shift of applications. And, not all applications can be taking advantage of cloud elasticity, then you do that. Most of these applications are created for the existing on-premise fixed architectures. So, they are not designed to take advantage of that. And, we are seeing a shift now. And, the shift is around, instead of, trying to, kind of, lift and shift existing applications. One, for new applications, let me try and adopt the technology assets, like you mentioned Kubernetes, that I can stay vendor-agnostic, for cloud vendors. But, more importantly, let me try to have some best practices in the organization. The new applications can be created to take advantage of the elasticity. Even though, they may not be running in the cloud yet. So, some organizations refer to this as cloud native, cloud first, some different terms. And, make the data. Because, the core asset here, is always the data. Make the data available, instead of going after the applications. Make the data from these existing on-premise and different platforms available for cloud. We are definitely seeing that the shift. >> Yeah, and make sure that it, and assure, that that data is high-quality, carries the policies, carries the governance, doesn't break in security models, all those other things. >> That is a big difference between how, actually, organizations ran into their Hadoop data lake implementations, versus the cloud architectures now. Because, when initial Hadoop data lake implementations happened, it was dump all the data. And, then, "Oh, I have to deal with the data quality now." >> It was also, "Oh, those mainframe people just would, "they're so difficult to work with." Meanwhile, you're still closing the books on a monthly basis, on a quarterly basis. You're not losing orders. Your customers aren't calling you on the phone angry. And, that, at the end of the day, is what a business has to do. You have to be able to extend what you can currently do, with a digital business approach. And, if you can replace certain elements of it, okay. But, you can't end up with less functionality as you move forward in the cloud. >> Absolutely. And, it's not just mainframe. It's IBMI, it's the Oracle, it's the teledata, it's the TDZa. It's growing rapidly, in terms of the complex stuff, that data infrastructure. And, for cloud, we are seeing now, a lot of pilots are happening with the cloud data warehouses. And, trying to see if the cloud data warehouses can accommodate some of these hybrid deployments. And, also, we are seeing, there's more focus, not after the fact, but, more focus on data quality from day one. "How am I going to ensure that "I'm delivering trusted data, and populating "the cloud data stores, or delivering trusted data "to microservices in the cloud?" There's greater focus for both governance and quality. >> So, high-quality data movement, that leads to high-quality data delivery, in ways that the business can be certain that whatever derivative work is done remains high-quality. >> Absolutely. >> Tendu Yogurtcu, thank you very much for being, once again, on The Cube. It's always great to have you here. >> Thank you Peter. It's wonderful to be here! >> Tandu Yogurtcu's the CTO of Syncsort, and once again, I want to thank you very much, for participating in this cloud, or this Cube conversation. Cloud on the mind, this Cube conversation. Until next time. (upbeat electronic music)

>> Live from San Jose, in the heart of Silicon Valley, It's theCUBE, covering DataWorks Summit 2018. Brought to you by Hortonworks. >> Welcome back to theCUBE's live coverage of DataWorks here in San Jose, California, I'm your host, along with my cohost, James Kobielus. We're joined by Tendu Yogurtcu, she is the CTO of Syncsort. Thanks so much for coming on theCUBE, for returning to theCUBE I should say. >> Thank you Rebecca and James. It's always a pleasure to be here. >> So you've been on theCUBE before and the last time you were talking about Syncsort's growth. So can you give our viewers a company update? Where you are now? >> Absolutely, Syncsort has seen extraordinary growth within the last the last three year. We tripled our revenue, doubled our employees and expanded the product portfolio significantly. Because of this phenomenal growth that we have seen, we also embarked on a new initiative with refreshing our brand. We rebranded and this was necessitated by the fact that we have such a broad portfolio of products and we are actually showing our new brand here, articulating the value our products bring with optimizing existing infrastructure, assuring data security and availability and advancing the data by integrating into next generation analytics platforms. So it's very exciting times in terms of Syncsort's growth. >> So the last time you were on the show it was pre-GT prop PR but we were talking before the cameras were rolling and you were explaining the kinds of adoption you're seeing and what, in this new era, you're seeing from customers and hearing from customers. Can you tell our viewers a little bit about it? >> When we were discussing last time, I talked about four mega trends we are seeing and those mega trends were primarily driven by the advanced business and operation analytics. Data governance, cloud, streaming and data science, artificial intelligence. And we talked, we really made a lot of announcement and focus on the use cases around data governance. Primarily helping our customers for the GDPR Global Data Protection Regulation initiatives and how we can create that visibility in the enterprise through the data by security and lineage and delivering trust data sets. Now we are talking about cloud primarily and the keynotes, this event and our focus is around cloud, primarily driven by again the use cases, right? How the businesses are adopting to the new era. One of the challenges that we see with our enterprise customers, over 7000 customers by the way, is the ability to future-proof their applications. Because this is a very rapidly changing stack. We have seen the keynotes talking about the importance of how do you connect your existing infrastructure with the future modern, next generation platforms. How do you future-proof the platform, make a diagnostic about whether it's Amazon, Microsoft of Google Cloud. Whether it's on-premise in legacy platforms today that the data has to be available in the next generation platforms. So the challenge we are seeing is how do we keep the data fresh? How do we create that abstraction that applications are future-proofed? Because organizations, even financial services customers, banking, insurance, they now have at least one cluster running in the public cloud. And there's private implementations, hybrid becomes the new standard. So our focus and most recent announcements have been around really helping our customers with real-time resilient changes that capture, keeping the data fresh, feeding into the downstream applications with the streaming and messaging data frames, for example Kafka, Amazon Kinesis, as well as keeping the persistent stores and how to Data Lake on-premise in the cloud fresh. >> Puts you into great alignment with your partner Hortonworks so, Tendu I wonder if we are here at DataWorks, it's Hortonworks' show, if you can break out for our viewers, what is the nature, the levels of your relationship, your partnership with Hortonworks and how the Syncsort portfolio plays with HDP 3.0 with Hortonworks DataFlow and the data plan services at a high level. >> Absolutely, so we have been a longtime partner with Hortonworks and a couple of years back, we strengthened our partnership. Hortonworks is reselling Syncsort and we have actually a prescriptive solution for Hadoop and ETL onboarding in Hadoop jointly. And it's very complementary, our strategy is very complementary because what Hortonworks is trying and achieving, is creating that abstraction and future-proofing and interaction consistency around referred as this morning. Across the platform, whether it's on-premise or in the cloud or across multiple clouds. We are providing the data application layer consistency and future-proofing on top of the platform. Leveraging the tools in the platform for orchestration, integrating with HTP, certifying with Trange or HTP, all of the tools DataFlow and at last of course for lineage. >> The theme of this conference is ideas, insights and innovation and as a partner of Hortonworks, can you describe what it means for you to be at this conference? What kinds of community and deepening existing relationships, forming new ones. Can you talk about what happens here? >> This is one of the major events around data and it's DataWorks as opposed to being more specific to the Hadoop itself, right? Because stack is evolving and data challenges are evolving. For us, it means really the interactions with the customers, the organizations and the partners here. Because the dynamics of the use cases is also evolving. For example Data Lake implementations started in U.S. And we started MER European organizations moving to streaming, data streaming applications faster than U.S. >> Why is that? >> Yeah. >> Why are Europeans moving faster to streaming than we are in North America? >> I think a couple of different things might participate. The open sources really enabling organizations to move fast. When the Data Lake initiative started, we have seen a little bit slow start in Europe but more experimentation with the Open Source Stack. And by that the more transformative use cases started really evolving. Like how do I manage interactions of the users with the remote controls as they are watching live TV, type of transformative use cases became important. And as we move to the transformative use cases, streaming is also very critical because lots of data is available and being able to keep the cloud data stores as well as on-premise data stores and downstream applications with fresh data becomes important. We in fact in early June announced that Syncsort's now's a part of Microsoft One Commercial Partner Program. With that our integrate solutions with data integration and data quality are Azure gold certified and Azure ready. We are in co-sale agreement and we are helping jointly a lot of customers, moving data and workloads to Azure and keeping those data stores close to platforms in sync. >> Right. >> So lots of exciting things, I mean there's a lot happening with the application space. There's also lots still happening connected to the governance cases that we have seen. Feeding security and IT operations data into again modern day, next generation analytics platforms is key. Whether it's Splunk, whether it's Elastic, as part of the Hadoop Stack. So we are still focused on governance as part of this multi-cloud and on-premise the cloud implementations as well. We in fact launched our Ironstream for IBMI product to help customers, not just making this state available for mainframes but also from IBMI into Splunk, Elastic and other security information and event management platforms. And today we announced work flow optimization across on-premise and multi-cloud and cloud platforms. So lots of focus across to optimize, assure and integrate portfolio of products helping customers with the business use cases. That's really our focus as we innovate organically and also acquire technologies and solutions. What are the problems we are solving and how we can help our customers with the business and operation analytics, targeting those mega trends around data governance, cloud streaming and also data science. >> What is the biggest trend do you think that is sort of driving all of these changes? As you said, the data is evolving. The use cases are evolving. What is it that is keeping your customers up at night? >> Right now it's still governance, keeping them up at night, because this evolving architecture is also making governance more complex, right? If we are looking at financial services, banking, insurance, healthcare, there are lots of existing infrastructures, mission critical data stores on mainframe IBMI in addition to this gravity of data changing and lots of data with the online businesses generated in the cloud. So how to govern that also while optimizing and making those data stores available for next generation analytics, makes the governance quite complex. So that really keeps and creates a lot of opportunity for the community, right? All of us here to address those challenges. >> Because it sounds to me, I'm hearing Splunk, Advanced Machine did it, I think of the internet of things and sensor grids. I'm hearing IBM mainframes, that's transactional data, that's your customer data and so forth. It seems like much of this data that you're describing that customers are trying to cleanse and consolidate and provide strict governance on, is absolutely essential for them to drive more artificial intelligence into end applications and mobile devices that are being used to drive the customer experience. Do you see more of your customers using your tools to massage the data sets as it were than data scientists then use to build and train their models for deployment into edge applications. Is that an emerging area where your customers are deploying Syncsort? >> Thank you for asking that question. >> It's a complex question. (laughing) But thanks for impacting it... >> It is a complex question but it's very important question. Yes and in the previous discussions, we have seen, and this morning also, Rob Thomas from IBM mentioned it as well, that machine learning and artificial intelligence data science really relies on high-quality data, right? It's 1950s anonymous computer scientist says garbage in, garbage out. >> Yeah. >> When we are using artificial intelligence and machine learning, the implications, the impact of bad data multiplies. Multiplies with the training of historical data. Multiplies with the insights that we are getting out of that. So data scientists today are still spending significant time on preparing the data for the iPipeline, and the data science pipeline, that's where we shine. Because our integrate portfolio accesses the data from all enterprise data stores and cleanses and matches and prepares that in a trusted manner for use for advanced analytics with machine learning, artificial intelligence. >> Yeah 'cause the magic of machine learning for predictive analytics is that you build a statistical model based on the most valid data set for the domain of interest. If the data is junk, then you're going to be building a junk model that will not be able to do its job. So, for want of a nail, the kingdom was lost. For want of a Syncsort, (laughing) Data cleansing and you know governance tool, the whole AI superstructure will fall down. >> Yes, yes absolutely. >> Yeah, good. >> Well thank you so much Tendu for coming on theCUBE and for giving us a lot of background and information. >> Thank you for having me, thank you. >> Good to have you. >> Always a pleasure. >> I'm Rebecca Knight for James Kobielus. We will have more from theCUBE's live coverage of DataWorks 2018 just after this. (upbeat music)

>> Narrator: Live, from Las Vegas, it's theCUBE. Covering IBM Think, 2018. Brought to you by IBM >> Hello everyone, welcome back to theCUBE, we are here on the floor at IBM Think 2018 in theCUBE studios, live coverage from IBM Think. I'm John Furrier, the host of theCUBE, and we're here with Stefanie Chiras, who is the Vice President of Offering Management IBM Cognitive Systems, that's Power Systems, a variety of other great stuff, real technology performance happening with Power, it's been a good strategic bet for IBM. Stefanie, great to see you again, thanks for coming back on theCUBE. >> Absolutely, I love to be on, John, thank you for inviting me. >> When we we had a brief (mumbles) Bob Picciano, who's heading up Power and that group, one of the things we learned is there's a lot of stuff going on that's really going to be impacting the performance of things. Just take a minute to explain what you guys are offering in this area. Where does it fit into the IBM portfolio? What's the customer use cases? Where does that offering fit in? >> Yeah, absolutely. So I think here at Think it's been a great chance for us to see how we have really transformed. You know, we have been known in the market for AIX and IBMI. We continue to drive value in that space. We just GA'd on, yesterday, our new systems, based Power9 Processor chip for AIX and IBMI in Linux. So that remains a strong strategic push. Enterprise Linux. We transformed in 2014 to embrace Linux wholeheartedly, so we really are going after now the Linux base. SAP HANA has been an incredible workload where over a thousand customers run in SAP HANA. And boy we are going after this cognitive and AI space with our performance and our acceleration capabilities, particularly around GPUs, so things like unique differentiation in our NVLink is driving our capabilities with some great announcements here that we've had in the last couple of days. >> Jamie Thomas was on earlier, and she and I were talking about some of the things around really the software stack and the hardware kind of coming together. Can you just break that out? Because I know Power, we've been covering it, Doug Balog's been on many times. A lot of great growth right out of the gate. Ecosystem formed right around it. What else has happened? And separate out where the hardware innovation is and technology and what's software and how the ecosystem and people are adopting it. Can you just take us through that? >> Yeah, absolutely. And actually I think it's an interesting question because the ecosystem actually has happened on both sides of the fence, with both the hardware side and the software side, so OpenPOWER has grown dramatically on the hardware side. We just released our Power9 processor chip, so here is our new baby. This is the Power9. >> Hold it up. >> So this is our Power9 here, 8 billion transistors, 14 miles of wiring and 17 layers of metal, I mean it's a technology wonder. >> The props are getting so small we can't even show on the camera. (laughing) >> This is the Moore's Law piece that Jenny was talking about in her keynote. >> That's exactly it. But what we have really done strategically is changed what gets delivered from the CPU to more what gets delivered at a system level, and so our IO capabilities. First chip to market, delivering the first systems to market with PCIe Gen 4. So able to connect to other things much faster. We have NVLink 2.0, which provides nearly 10x the bandwidth to transport data between this chip and a GPU. So Jensen was onstage yesterday from NVIDIA. He held up his chip proudly as well. The capabilities that are coming out from being able to transport data between the power CPU and the GPU is unbelievable. >> Talk about the relationship with NVIDIA for a second, 'cause that's also, NVIDIA stocks up a lot of (mumbles) the bitcoin mining graphics card, but this is, again, one use case, NVIDIA's been doing very well, they're doing really well in IOT, self-driving cars, where data performance is critical. How do you guys play in that? What's the relationship with NVIDIA? >> Yeah, so it has been a great partnership with NVIDIA. When we launched in 2013, right at the end of 2013 we launched OpenPOWER, NVIDIA was one of the five founding members with us, Google, Mellanox, and Tyan. So they clearly wanted to change the game at the systems value level. We launched into that with we went and jointly bid with NVIDIA and Mellanox, we jointly bid for the Department of Energy when we co-named it Coral. But that came to culmination at the end of last year when we delivered the Summit and Sierra supercomputers to Oak Ridge and Lawrence Livermore. We did that with innovation from both us and NVIDIA, and that's what's driving things like this capability. And now we bring in software that exploits it. So that NVLink connection between the CPU and the GPU, we deliver software called PowerAI, we've optimized the frameworks to take advantage of that data transport between that CPU and GPU so it makes it consumable. With all of these things it's not just about the technology, it's about is it easy to consume at the software level? So great announcement yesterday with the capabilities to do logistic regression. Unbelievable, taking the ability to do advertising analytics, taking it from 70 minutes to 1 and 1/2. >> I mean we're going to geek out here. But let's go under the hood for a second. This is a really kind of a high end systems product, at the kind of performance levels. Where does that connect to the go to market? Who's the buyer of it? Is it OEMs? Is it integrators? Is it new hardware devices? How do I get involved and who's the target customer? And what kind of developers are you reaching? Can you just take us through that who's buying this product? >> So this is no longer relegated to the elite set. What we did, and I think this is amazing, when we delivered the Summit and Sierra, right? Huge cluster of these nodes. We took that same node, we pulled it into our product line as the AC922, and we delivered a 4 GPU air-cooled version to market. On December 22nd we GA'd, of last year. And we sold to over 40 independent clients by the end of 2017, so that's a short runway. And most of it, honestly, is all driven around AI. The AI adoption, and it's a cross enterprise. Our goal is really to make sure that the enterprises who are looking at AI now with their developer are ready to take it into production. We offer support for the frameworks on the system so they know that when they do development on this infrastructure, they can take it to production later. So it's very much driven toward taking AI to the enterprise, and it's all over. It's insurance, it's financial services sector. It's those kinds of enterprise that are using AI. >> So IO sensitive, right? So IOT not a target or maybe? >> So you know when we talk out to edge it's a little bit different, right? So the IOT today for us is driving a lot of data, that's coming in, and then you know at different levels-- >> There's not a lot of (mumbles) power needed at the edge. >> There is not, there is not. And it kind of scales in. We are seeing, I would say, kind of progression of that compute moving out closer. Whether or not it's on, it doesn't all come home necessarily anymore. >> Compute is being pushed to where the data is. >> Stefanie: Absolutely right. >> That's head room for you guys. Not a priority now because there's not an intense (mumbles) compute can solve that. >> Stefanie: That's right. >> All right, so where does the Cloud fit into it? You guys powering IBMs Cloud? >> So IBM Cloud has been a great announcement this year as well. So you've seen the focus here around AI and Cloud. So we announced that HANA will come on Power into the Cloud, specializing in large memory sets, so 24 terabyte memory sets. For clients that's huge to be able to exploit that-- >> Is IBM Cloud using Power or not? >> That will be in IBM Cloud. So go to IBM Cloud, be able to deploy an SAP certified HANA on Power deployment for large memory installs, which is great. We also announced PowerAI access, on Power9 technology in IBM Cloud. So we definitely are partnering both with IMB Cloud as well as with the analytics pieces. Data Science Experience available on Power. And I think it's very important, what you said earlier, John, about you want to bring the capabilities to where the data is. So things like a lot of clients are doing AI on prem where we can offer a solution. You can augment that with capabilities like Watson, right? Off prem. You can also do dev ops now with AI in the IBM Cloud. So it really becomes both a deployment model, but the client needs to be able to choose how they want to do it. >> And the data can come from multiple sources. There's always going to be latencies. So what about blockchain? I want to get to blockchain. Are you guys doing anything in the blockchain ecosystem? Obviously one complaint we've been hearing, obviously, is some of these cryptocurrency chains like Ethereum, has performance issues, they got projects coming out. A lot of open source in there. Is Power even puttin' their toe in the water with blockchain? >> We have put our toe in the water. Blockchain runs on Power. From an IBM portfolio perspective-- >> IBM blockchain runs on Power or blockchain, or other blockchains? >> Like Hyperledger. Like Hyperledger will run. So open source, blockchain will run on Power, but if you look at the IBM portfolio, the security capabilities in Z14 that that brings and pulling that into IBM Cloud, our focus is really to be able to deliver that level of security. So we lead with system Z in that space, and Z has been incredible with blockchain. >> Z is pretty expensive to purchase, though. >> But now you can purchase it in the Cloud through IBM Cloud, which is great. >> Awesome, this is the benefit of the Cloud. Sounds like soft layer is moving towards more of a Z mainframe, Power, backend? >> I think the IBM Cloud is broadening the capabilities that it has, because the workloads demand different things. Blockchain demands security. Now you can get that in the Cloud through Z. AI demands incredible compute strength with GPU acceleration, Power is great for that. And now a client doesn't have to choose. They can use the Cloud and get the best infrastructure for the workload they want, and IBM Cloud runs it. >> You guys have been busy. >> We've been busy. (laughing) >> Bob Picciano's been bunkered in. You guys have been crankin' out... love to do a deeper dive on this, Stefanie, and so we'd love to follow up with you guys, and we told Bob we would dig into that, too. Question I have for you now is, how do you talk about this group that you're building together? You know, the names are all internal IBM names, Power... Is it like a group? Do you guys call yourself like the modern infrastructure group? Is it like, what is it called, if you had to explain it to outside IBM, AIs easy, I know what AI team does. You're kind of doing AI. You're enabling AI. Are you a modern infrastructure? What is the pillar are you under? >> Yeah, so we sit under IBM systems, and we are definitely systems proud, right? Everything runs on infrastructure somewhere. And then within that three spaces you certainly have Z storage, and we empower, since we've set our sites on AI and cognitive workloads, internally we're called IBM Cognitive Systems. And I think that's really two things, both a focus on the workloads and differentiation we want to bring to clients, but also the fact that it's not just about the hardware, we're now doing software with things like PowerAI software, optimized for our hardware. There's magic that happens when the software and the hardware are co-optimized. >> Well if you look, I mean systems proud, I love that conversation because you look at the systems revolution that I grew up in, the computer science generation of the 80s, that was the open movement, BSD, pre-Linux, and then now everything about the Cloud and what's going on with AI and what I call the innovation sandwich with data in the middle and blockchain and AI as bread. >> Stefanie: Yep. >> You have all the perfect elements of automation, you know, Cloud. That's all going to be powered by a system. >> Absolutely. >> Especially operating systems skills are super imprtant. >> Super important. Super important. >> This is the foundational elements. >> Absolutely, and I think your point on open, that has really come in and changed how quickly this innovation is happening, but completely agree, right? And we'll see more fit for purpose types of things, as you mentioned. More fit for purpose. Where the infrastructure and the OS are driving huge value at a workload level, and that's what the client needs. >> You know, what dev ops proved with the Cloud movement was you can have programmable infrastructure. And what we're seeing with blockchain and decentralized web and AI, is that the real value, intellectual property, is going to be the business logic. That is going to be dealing with now a whole 'nother layer of programmability. It used to be the other way around. The technology determined >> That's right. >> the core decision, so the risk was technology purchase. Now that this risk is business model decision, how do you code your business? >> And it's very challenging for any business because the efficiency happens when those decisions get made jointly together. That's when real business efficiency. If you make one decision on one side of the line or the other side of the line only, you're losing efficiency that can be driven. >> And open is big because you have consensus algorithms, you got regulatory issues, the more data you're exposed to, and more horsepower that you have, this is the future, perfect storm. >> Perfect storm. >> Stefanie, thanks for coming on theCUBE, >> It's exciting. >> Great to see you. >> Oh my pleasure John, great to see you. >> You're awesome. Systems proud here in theCUBE, we're sharing all the systems data here at IBM Think. I'm John Furrier, more live coverage after this short break. All right.