>> Announcer: Live from San Diego, California it's theCUBE, covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. >> Welcome back to theCUBE, day two of our coverage of Cisco Live. We are live also from San Diego. I'm Lisa Martin, Stu Miniman is my co-host. And one of our alumni is back with us, Eric Herzog, the CMO of IBM Storage. >> Great, thank you for having us. >> Welcome back. So, lots of buzz, we're in the DevNet Zone. This has been, I hear, one of the busiest expos at Cisco Live this year. The community is, I'm hearing, approaching 600,000 strong. Yesterday we were talking a lot about the big waves of innovation, one of them being GPU's everywhere, AI, but also some of the challenges with respect to data, that companies are generally getting less than 1% of that data to really extract insights from it. So let's talk about what IBM is doing with respect to AI and big data, and really helping customers really turn that dial up on getting more value out of what they have. >> Well, so we're doing a lot in that space. First of all, when you're running AI in particular, if you're really going to do something like run a robotic factory, you'd better make sure the storage doesn't fail. But that's sort of, you know, the checkbox item, just the way a car always has a spare tire. So the real differentiator, from a storage perspective, is what do you do to help the data prep, what do you help to do to make sure that the data is always in the right kind of pipeline? For example, just like a human always learns, right, at least smart humans always learn, so you learned certain things when you were seven or eight, they might've changed by the time you were in college, by the time you have your first kid they might be different again, and by the time you're getting ready to retire, but it could be still the same topic and the data's recycling, and then you learn new things about that topic. So in the case of a data workload, what you need to do is make sure you have data prep along the entire pipeline. And that's what we've done with a whole bunch of software that we offer for the big data and AI workloads and applications. >> So, Eric, we've talked with you many times about what's happening in the multi-cloud world. It feels like IBM and Cisco are on similar, parallel paths as to the move from, traditionally we think about boxes, and from a Cisco standpoint it's ports, and, you know, more and more it's about the software. So can you talk a little bit about that software-defined world in where IBM and Cisco are going together along that journey. >> So, one of the things that we've done from a storage division perspective, we do what we call the VersaStack. It's a converge infrastructure that includes Cisco UCS, our all-flash arrays, but it's packed with a bunch of software. So we can use that to transparently move block data out to a cloud, any cloud, IBM cloud, Amazon, Azure. We could move it out to a block store or to an object store. Now obviously to move it out to an object store, that can help you, can prevent ransomware and malware. And it's all automated. We've done the same thing with Scale-Out File, where we just see cloud as just a tier, and we've done the same thing with object storage. So the big thing we see from a hybrid, multi-cloud perspective at the IBM storage division, is everything needs to be able to have the data easily portable, easily migrateable, and easily replicable back, and constantly moving back and forth, not just going out to the cloud and staying there. So we've done that from our software-defined portfolio. But we also did it with our modern data protection portfolio, Spectrum Protect, which is one of the most award-winning products in the backup space. We've got over 400 small-medium cloud providers where their backup-as-a-service offering is based on Spectrum Protect. So if they go to Wikibon and Wikibon says, we want to back up to the cloud and you're using Tectrade or Cloud Temple or i-Virtualize, all those cloud providers, the backup-as-a-service they sell you is based on IBM Spectrum Protect. So for us cloud is just another tier. Just like hard drives and flash and tape, cloud's just the new tier. >> So in this pivot towards software-defined everything, with, say, VersaStack for example, give us one of your favorite customer success stories that really highlights the value of what IBM and your partnerships deliver. >> Sure, sure. So one of them would be Tectrade. So Tectrade is one of our public references. They only do PCI data. So, Wikibon couldn't be a customer, IBM can't be a customer, theCube can't be a customer, Cisco can't be, because we don't specialize, as you know, in financial-centric data. So they back up about, they do about two million backups a day, all of financial data across Europe and into North America, and they've got a VersaStack that happens to run Spectrum Protect on it. It's all flash, so they're not worried about performance. And then they back up to giant hard drive farms that they've also bought from IBM. But the real thing on the VersaStack is having that very fast edge, and then having the software that allows them to A, control the storage side, but then run Spectrum Protect to do backup. So if you were a bank, if theCUBE was a bank, then you guys could use Tectrade and they use a VersaStack for backing up data as a service. That's a perfect example of what we've done with the VersaStack solution, in this case in a hybrid cloud scenario. >> What are some of the business impacts that they have achieved so far? Are they finding new revenue streams, are they unlocking more valuable data to be more competitive? >> So, what they do is obviously in the PCI world. They're very centered, you can't lose anything. Because it's financial data. So for them, it's all about the security of the data, making sure the data gets there, the data's encrypted in flight, they know that the customers can do a lot of different things, because Spectrum tech is very much a big enterprise package that's very strong in the global Fortune 2000. So they like it for that. Now, we've had some other customers, and their the value has been things like the return on investment. For example, the second-largest dating site on the planet uses VersaStack. And they got a four month return on investment. They bought it, and in four months it paid for themselves, so they bought like four or five more. We had another customer who saved, and this is also a cloud service provider by the way, so they saved the equivalent of five full-time employees that were writing custom code and managing stuff, and they used Spectrum Protect also for backup. But in this case you and I could use them because they're not specialists like Tectrade is, and they'll back up anybody's data. And they saved five full-time equivalents. So they've now redeployed those full-time employees to do something else. So those are just examples from three different companies of ways that they've saved money and really driven a business value, not just about the data, and yeah, the data's fast, but really, if you're a storage guy, been doing it as long as I have, the data's always fast and it just gets faster every generation, so okay, it's fast. And in this case it's really about business value, about the value of the data, not about the storage. >> Eric, you mentioned security. Of course security is one of those topics that's hitting all of the environments here at Cisco, but bring us inside, especially from a storage division, modern data protection and how that's getting involved in the security discussion. >> Sure, so what we've done across the portfolio, even in primary storage, is made sure that we've done all sorts of things that help you against a ransomware or malware attack, keep the data encrypted. I think the key point actually, I think Silicon Angle wrote about this, something like 98% of all enterprises are going to get broken into anyway. So it's great that you've got security software on the edge, whether that be IBM or RSA or BlueCoat or Checkpoint, or who cares who you buy the software from. But when they're in, they're stealing. And sometimes, some accounts have told us that they can track them down in a day, but if you're a giant global Fortune 500 with data centers up, it might take you a week. They could be stealing stuff right and left. So we've done everything from, we have write-once technology, so it's immutable data, you can't change it. We've got encryption, so if they steal it, guess what, they can't use it. But the other thing we've done is real protection against ransomware and malware. So I am going to attack Wikibon, theCUBE, and I am going to charge you $10 million, and I'm going to steal every video you've ever created and hold it for ransom. So the way I would do that is I look at your snapshots, your replicas, and your backups first. So what do we do? We can actually snapshot a replica out to an object store, and ransomware and malware, at least today, doesn't attack object storage. So that way, when I'm talking to you or Stu and said I want $10 million, you start laughing, and go, what are you talking about? We replicate every night. Okay, we lose one day of data. He can't get half the $10 million. So that's ransomware or malware protection. We've also built that into Spectrum Protect, because what happens is when you're starting to, if you will, look at that data to get it wrapped up in the ransomware or malware, you have a whole bunch of extra activity around the backup data sets, so we send an alert. We'd send an alert to you, Lisa, and you would say, oh my god, what's going on? Why is all this activity going on the backup set? Because the backup's not scheduled, let's say, for tonight. And we would send you a note now, at two o'clock, that there's all kinds of activity, and you would go, what is going on, and you would check it out. So we can help with ransomware and malware, encryption on primary data. So we've really integrated across the portfolio, whether it be primary storage or secondary storage. And by the way, almost nobody thinks about storage. They always say, whose security package should I buy? And they never say okay, I'm going to buy it, but I, might buy some security for the storage, too. No one ever talks like that, which is why we're bringing up, and we actually launched a sales play for the field, all around storage for cyber resiliency. >> And how is that going, if you're saying it's-- >> It's actually gone incredibly well. We started with a product called Safeguarded Copy on the mainframe, and we actually got, in the first four months, almost $60 million a pipeline in the first four months of the product shipping. And now we've got it all over the whole portfolio, so we tried it just when we first got started, and now we're now talking about the ransomware and malware stuff, which by the way we've had for three years, but we were never emphasizing it to the end user. Now we're saying, by the way, has it happened or are you worried about it? Well guess what, if you're backing up with Spectrum Protect, we'll warn you. Why don't you go out to tape and air gap? Or why you don't go out to the cloud and we can do essentially a cloud air gap to object storage? And we weren't really talking like that until really we started doing it in Q4 and then really expanded it in Q1, so it's been very, very successful. The end users love it, our business partners who sell to the end users, they're loving it. And by the way, no one else is really talking about it. It's all about the security software company. So we're going beyond that. >> So, Eric, you talked about some of the products with Cisco and IBM working together. I wonder if you can up-level a little bit. You're a great watcher of the industry out there. Chuck Robbins, now four years into his tenure as CEO, Wall Street's doing well with the stock on there, finances look well. IBM and Cisco, two of the bellwethers in tech out there. How's Cisco doing? When you talk to your customers, what are they liking about Cisco, what do they want to see more from Cisco, are they aware of the transformation that Cisco's going through? >> Well, I think there's a couple things. First of all, IBM and Cisco have a mutual relationship that spans billions of dollars. Whether that be, for example, as they publicly have disclosed, IBM is the biggest customer for WebEx on the planet, and they talked about that. There's products that we sell to them that they're one of our biggest customers in the world as well. But then beyond that, whether it's common end users or common channel partners, we make sure that we deliver the right solutions together. So I think the feedback I get from both the end users and the partners is that Cisco's back. Right when Chuck came in, said, oh, what's going on with Cisco? They're still big, but the big sometimes fall over big, right? Like in the beanstalk, the giant falls over, right? So that's what I think people were thinking four years, I don't think people are thinking that now. From our perspective, we've always kept working tightly with them, between our relationship with them as a customer and us as their customer. But more importantly, it's really the common customers we have and the common channel partners, and we've never wavered for that support from a Cisco perspective. But just sort of off the cuff, when people make a comment that's like, hey, those Cisco guys are back. And four years ago people were saying, ehh, what do you think about Cisco? My wife works at Cisco, and my ex-wife works at Cisco, so it's a little easier for them to ask me that. Because I'm a Cisco shareholder too. But now you don't hear that question. It's like Cisco's got their act together, they're doing all the right stuff. So that's very good for me personally with my stock, but it's also good just for the industry. You know, you don't want someone to not be able to make the transition. And the valley's littered with that. DEC, Compaq, they're all gone. They're not the only guys that are gone. So Cisco's not going to go the way that other big companies have. They've made the transition and are transforming to what the end users really need. >> And I think the DevNet community growth is a great, speaks to the pivot that Cisco's making. DevNet has been in large part an accelerator of Cisco's transition from network appliance provider to more of a software services provider. But that community symbiosis with their end user customers, with their partners, and with their developer community, is really a driving force here. And I think just being in this DevNet Zone and how big it is, is a great example of how they're leveraging those other feedback channels to not just persist but be successful. So here we are, their Q3 2019 results are really strong, growth across all three business segments, we're in the middle of their fourth quarter. So for Cisco's FY 2020, what are some of the big bets that you can share with us that IBM and Cisco-- >> Well, the one we've done together has been one on security, so we have joint security products that we've done. We have a joint product on the system side with the VersaStack. We've done joint products with them also in the cloud solution area, both, if you think about hybrid cloud, but also in private cloud, so IBM Cloud Private for example is available on their HCI box, right, so their hyperconverged infrastructure solution includes an option for IBM Cloud Private. So IBM has made many bets with them in the security space, in the cloud space. Also, by the way, one of the biggest providers of service on Cisco solutions is actually IBM. So our services divisions do tons of business with Cisco, whether that's servicing the physical gear or servicing the software. And we've been doing that for years. So whether it be service, whether it be cloud, whether it be infrastructure, IBM is doing joint solutions across the board with the Cisco community. >> Got to ask you one last question, Eric. You've been in this industry a long time, you're a veteran extraordinaire. What keeps you excited about storage? >> Storage always change. Storage is not boring. Storage is boring for the uneducated. It is the most exciting thing, it changes all the time. I remember one of the good things about IBM was not just an array, come here, we only just do backup software, we've got high-end storage arrays, we still do tape. We're by far the dominant player, and we're having a huge resurgence there with hyperscalers and cloud providers. We're going crazy with tape because, for them, they're all about saving money for backup and archive, and we're critical to that. We are the number two storage software company in the world, all of our software works off of our gear. Some of the other guys that sell lots of software, yeah, they sell lots, but it only works on their products. Our software works with all of our competitor's products. So that makes everything exciting. I've done this now for 35 years. I've seen hard drives that were the size of a dishwasher to now flash that fits into your phone, or my MacBook, I've got five terabytes of flash. So, you know, to me that's all exciting. And the software is where it really matters. You know, we've gone from bare metal to virtualization, now to containers and cloud. So there's always new stuff going on. But I really think part of the problem with storage is everybody takes it for granted and doesn't realize, if your storage doesn't work, isn't performing, isn't reliable, and isn't available, basically your entire infrastructure caves in. I don't care whether you're in the cloud, whether you're in a virtual world, or you're still doing it really old hat with bare metal, the storage doesn't work, you're shutting down your company until that storage is back up and running again. So it is the critical foundation for every application workload and use case, in any company, big, medium, or small. And it's always evolving. So to me it's very exciting, although some people think storage is boring. I'd say networking is boring. That, to me, is boring. (Lisa laughs) Storage is exciting. >> Stu: Don't say that too loud, here. (Eric laughs) >> That's true, storage is sexy. Well Eric, it's been a pleasure to have you back on theCUBE once again, and we very much appreciate your time. >> Great, well thank you for having us. >> Our pleasure. For Stu Miniman, I'm Lisa Martin. You're watching theCUBE live, from Cisco Live in San Diego.

>> Host: Live from San Diego, California, it's the CUBE, covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. >> Hi, welcome back to the CUBE, Lisa Martin with Stu Miniman, covering day one of Cisco Live from sunny San Diego. We're pleased to welcome back a couple of our alumni. To my right Eric Herzog, CMO of IBM Storage. Eric it's always great to have you. >> Great. >> And you fashion choices on the CUBE. >> Always wear a Hawaiian shirt for the CUBE. >> I know, it's a thing. And we've also got Evaristus Mainsah, General Manager of IBM Cloud Private Ecosystem. Evaristus it's great to have you back on the program. >> Thank you very much, delighted to be here. >> So guys here we are, we're in the dove nut zone. Lots of collaboration, lots of conversations day one of Cisco Live. But this events been around for 30 years. Long time, I think Chuck Robins said this morning what also turned 30 this year is Tetris. Anybody a big fan of Tetris? So, so much progress, so much change. I know you've seen a lot of it. Eric lets start with you. The global economy, what are the impacts it's having on IT? >> Well I'd say the number one thing is everyone is recognized the most valuable asset is data. It's not gold, it's not silver, it's not plutonium and it definitely isn't oil, it's all about data. And whether it be a global Fortune 500, a midsize company or Herzogs Bar & Grill, data is your most valuable asset. So at IBM Storage, what we've done is making sure that our focus is on being data-driven. It's all about solutions, it's not about speeds and feeds. Of course, having done this for 35 years I could have whacked poetically on speeds and feeds. And even if you have some speeds and feeds that Stu may not even remember anymore. That said, it's really about data, it's not about storage speeds and feeds. How really storage is that critical foundation for applications, workloads and use cases. And that's what's most important. >> Yeah, so Eric, when they rolled out on stage this morning that 30 year old box with ribbon cable, yeah, that predated a little bit when I was looking at IT. But, I remember when I started in IT, when we talked about security, the main thing was lock the door of the cabinet that everything was in there, because it was kind of self-contained. Security's gone through a few changes in the last you know 20 25 years though. Maybe you could talk a little bit about that kind of security resiliency. Obviously, something that's impacted the network for a long time, something that IBM sees front and center. >> What I think the big deal is what most people think when they think of security, is I got to buy security software. So I got to call up IBM Security or RSA or the Intel Security Division and buy some security software. And while that's great the reality is as many people have written about, in fact Wikibon SiliconANGLE's written about it. Close to 98% of all enterprises, and I mean big enterprises now are going to get to be broken into. And you've seen this all over the news. So the key thing is once they're inside, storage can help you with a cyber resiliency play. And at IBM Storage whether that be data at rest encryption. Whether that be malware or ransomware protection. We put together a whole set of technology that when the bad guys in the house they can't steal the TV. Because we've locked it down. It's almost as if it was in a safe. Maybe it's almost like the cloak in science fiction where you can't even see the Romulan ship, because it's cloaked. Well guess what, that's what IBM storage can do for your data and it is your most valuable asset. So critical to cyber resiliency. >> So helping customers go from reactive to this expectation breach has happened very very frequently every few seconds to being proactive? >> Yeah, I mean. >> Eventually predictive? >> Well what we do is for example with our Spectrum Protect software. When there's a malware or ransomware attack, what happens is they always go after you're secondary data sets first. I know that sounds weird but they go after your backups, your snapshots and your replicas. 'Cause when they attack your primary data, if they've you can just recover from a backup they can't hold you for $10 million of ransom. So our Spectrum Protect software for example, when it sees anomalous activity in backup data sets, sends an email on a warning out to all the admins and says you have weird activity going on, you might want to check it out and that way you would know. Because secondarity is attacked first in a cyber resiliency strategy. >> You know, the other thing we're seeing a lot is just the scope of what's happening in IT. When you talk about things like scale and you talk about you know edge computing and so much change going on. There's got to be AI in there or machine learning to help us because humans alone can't keep up with what's going on here. Tell us a little bit about that Eric. >> So Big data and AI is like the hot topic right now. Cyber resiliency is important 'cause people obviously have been buying security software for a while. So it's more what we do is really an adjunct to that. In the case of Big data and AI, it's a brand new open field. Everyone is looking for solutions in both of those spaces. We have created a complete set of data infrastructure we've called the AI pipeline. It involves not only physical storage arrays but a whole bunch of software. In fact our Spectrum Discover software which allows you to create metadata catalogs about file and object data is being expanded. And we already publicly said this in the second half To include EMC and Netapp and AWS, not just IBM Storage. So it's a critical thing, you've got to make sure the other thing is when you're using AI. Let's say you're going to use AI to run a factory. If the storage goes down, those robots aren't working. So storage is that critical underlying foundation. A in a Big data network load to be able to have this pipeline to get the data. But if you don't have the resiliency, the performance and the availability of the underlying storage everything shuts down if the storage fails. 'Cause the AI software won't run. So that's how we see fitting in to their both the critical foundation also this AI data pipeline with all of our software. >> So before we get in to this Cisco partnership with Evaristus, it's one more question Eric for you. As Chief Marketing Officer, you talk about the customers all of the time. In that example that you just gave about the criticality of storage for AI where are you having conversations within customer organizations. Is it at the level of the storage girls and guys or has it gone up to lines of business to executives. >> Yeah so, from an AI perspective it runs a gamut. It could be sometimes the storage people. Sometimes the infrastructure people. A lot of times it's actually in the line of business or at the data scientist level. On the Big data side it's a little bit more mature so people know they need to do analytics versus AI. And so when you look at it from that perspective on that side it's often the storage guy but it's also the data scientist as well. So that's who we talk to to get things rolling. And it's not, we don't just talk to the storage admin for either of them, because they're both so new and they have such a big impact on the data scientists and the analytic engine committees inside of those giant enterprises. >> I can imagine eventually maybe question for you. Of that conversation elevating it up to the sweet sweet. Because if you can't access the data, if it can't be protected, what good is it? Right, it's really, to say it's the lifeblood is a silly thing, but we say it all the time. But it's critical, it's table stakes. >> Well one of the things that's interesting is I just got my Fortune 500 magazine at home, that had the Fortune 500 list in it. And there was an interesting article on AI and the enterprise. And they did a survey according to Fortune magazine, 50% of the CIO's that are in the Fortune 500 said they're using AI and Big data of some type. So it's sweeping the world. And it started of course in HPC in the academics. But now it's going into all enterprises of all types. >> Alright so we've talked a few years about the Versastack Partnership. But the last year or so we've really been talking about where Hybrid cloud and multi-cloud fit in to this. We talked a little bit at IBM Think. Evaristus we talked at another show about some of the IBM Cloud Private. Give us the update where we are with customers and how that fits, Eric lets start with you and Evaristus just go into the partnership. >> Sure from a storage version perspective, we've been talking about a Hybrid multi-cloud now for several years. And in fact I did a presentation two years ago at Cisco Live on Hybrid cloud using Versastack. Today I gave one on the data driven enterprise and why hybrid multi-cloud is important to use. So that was the 30 minutes presentation I did today. So I think the key thing is we make sure that we A our Hybrid it's not going to all public or all private. And we can move data seamlessly back and forth. And then also multi-cloud. When you look at enterprise shops, they're not just going to use IBM Cloud. I wish they would I'm an IBM shareholder but they're not. They use IBM, they're going to use ABS, they're going to use Amazon and in many cases they're going to use some smaller cloud provider. So we make sure that we can move data around across any multi-cloud of various different providers to accompany. But also Hybrid cloud as well. >> So the status talk to use about you know from a partnership Cisco IBM Cloud Private perspective, what's going on there Evaristus? >> Well Thank you very much. Well IBM and Cisco have been partners for a long long time. And what we are doing now is given the realities, the fact that those clients have found themselves in a multi-cloud environment, >> Hybrid multi-cloud environment. What we can do to help clients so they can develop they can test, they can manage the applications in a consistent manner, whether they are on prime or in the cloud. And there are a couple of initiatives that we are announcing. One of them is that IBM Cloud Private is going to run on Hyperflex, so Cisco's Hyperflex. As well as hyperflex, hyper-conversed infrastructure. What it means is a client who currently has hyperflex can have IBM Cloud Private on it. Which effectively means they have themselves a Private Cloud environment that also connects to other public cloud environments and allows you to really begin to work within a Hybrid cloud environment the way that most clients need to. The second initiative is that we will have ACI pods or V pods, virtual ACI, running in the IBM public cloud. Which basically means that again, Cisco customers, ACI Network customers who currently use the produce on Prime will be able to use exactly you know the same control pane to manage their deployments and to manage their security preferences on Prime as they do in the cloud. And this again surrounding the Public Cloud is running on bare metal on the IBM Cloud. >> Alright, Evaristus can you bring us inside a little bit the applications you know. Eric talked about you know data we know is so important. Really it's the applications that are driving that. It's where we're seeing the most change in customers, as to how they're moving or building new applications. And in Hyber cloud it's one of the biggest questions for customers is what do they do with that application portfolio? >> Yes so what we're seeing is clearly because you know. Clients have now lots of different Public clouds. They also have Private clouds to deal with them. They have lots of applications that are currently that need to move right. We believe 20% of those applications have moved, the remaining 80% are still on Prime. And so the trend that we are really seeing is applications moving to the cloud. And the two ways of doing it you could do this by simply lifting and shifting on VM, you get the contraction benefit of your stack right. So you can some cost impacts. But the really interesting way that you see lots of clients moving is modernizing the applications. Because the real valued driver with infinite cloud is not so much cost as innovation. And when you convert those applications into Microsoft this is the right and let me run them in containers it gives them plenty of flexibility. And wasting lots of clients that want to use IBM Cloud Private as a platform to enable that modernization journey. >> So as every industry is living in this Hybrid multi-cloud world for many reasons. But it sounds like to me is that the IBM Cisco relationship is deepening as a result to enable these organizations that are in these very amorphous environments. You know as we see the explosion of Edge and Mobile, that's what it sounds like to me. Is that this long standing partnership is getting deeper and maybe a stronger foundation. To help customers not just live in this Hybrid multi-cloud world but be successful so that their businesses gain competitive advantage. They can identify new products and services and revenue streams. >> Yeah, I think multi-cloud and Hybrid cloud actually requires partnerships. Because as Eric said later on of course you like everybody to be on the IBM Cloud and it's a great cloud. But we recognize that many clients who have a variety of different plights to deal with. They have a variety of different infrastructures. And that's why when you look at IBM Cloud Private which is you know our offering that really enables that Hybrid cloud. It is designed to managed that. So It is multi-model, so if you want to run it as a VM you can, you want to run your containers, you can run serverless, you can run them bare metal. But also, it supports a range of different infrastructure. So not only does it run on Z, it runs on power, it runs on Spectrum Storage. We announce running now on Hyperflex. It also runs on other peoples Public clouds. It runs on Azure, it runs on Amazon web services, it runs on Google Cloud platform, it runs on the IBM Cloud. And the intent here is to enable clients to basically manage and work with that infrastructure as if it was one. The way that Stu said in the data center where you locked everything up. Well it's not like that anymore. But the most that we can do is to enable clients to treat all of that infrastructure as one. And that's what sort of aim to do with our platforms. >> Alright, I guess last question I'd like to get both of your comments on. Is your advice for customers, you know, customers have that they have a lot of you know existing things that they have to deal with, that they're looking to modernize. What advice do you give them? Where do you start them you know I guess you know one of the things you're starting where they are. But you know what are some of the first steps and recommendations that you have for customers today? >> We have a process that works really well, which is called the IBM Garage. Which is effectively a way that we used to co-create with our clients to solve the immediate problems. So a client for example, who is looking at app modernization but isn't sure where to start, which app. What we do is we get their teams together with our teams line of business together with IT and our teams and we spend a couple of days in a design thinking workshop to identify a minimum viable product. Which is something that solves a problem not big enough that it will take forever, but big enough to matter. Then we get our teams to work side-by-side, we code it, we test it, we deploy it, we'll run it in the IBM Cloud. We manage it, at like in one week sprints. And then you spend another few days at the end of week four or five to do a see retrospective to see whether it solved the problem as you expected. And if it did, you pick the next piece of work to continue your journey. So before you know, five weeks in, you have your first application modernized. Or you have your first cloud negative ready. >> Now from a storage perspective it's a little bit easier. We supported storage on bare metal. We supported storage in all the virtual environments. KVM, OVM, obviously VM we're in Hyper V. And now, we've been supporting containers for over two years. So we say is leave no data behind. If certain data needs to stay on bare metal, that's fine we can support that. But we can also transparently migrate data back and forth between the various tiers of container-based virtualization-based or the old style bare metal. So from our perspective, we help them move data around where they need it. And if they're still running in a hybridized world in this case, containers, virtual and bare metal that's fine. If they just go containers that's fine. If they just go virtual it's fine. So for us, because of what we've been supporting now for several years, we can help them on that journey. And traverse from any one of those three layers, which is where data sits in today's data centers and cloud environments. >> So overall a lot of collaboration, a lot of customer choice. Gentlemen, Thank you for joining Stu and me the program this afternoon, great to have you back. >> Thank you >> Great, Thank you. Glad to be on the CUBE. >> Oooh our pleasure. For Stu Miniman, I am Lisa Martin. You're watching the CUBE, live from day one of our coverage on Cisco Live. Thanks for watching. (energetic music)

>> Live from Miami Beach, Florida, it's the CUBE, covering VeeamON2019. Brought to you by Veeam. >> Welcome back to Miami everybody. This is Dave Vellate with Peter Burris here. Day One of VeeamOn2019, at the Fontainebleau Hotel in Miami. Rat Pack used to hang out here Which is kind of the big theme of the reception last night. Dale Hoffman is here. He's the Director of Offering Management for VMWare Solutions at IBM. Dale, thanks for coming to the group. >> Thanks, David. It's a pleasure to be here and Peter, nice to meet you. >> Okay, yeah, pleasure to meet you as well. So lets unpack the sort of notion of Offering Management that sort of people generally refer to as Product Management. IBM calls it Offering Management. So you are focused on the public cloud, but specific to the VMWare swimlane. Is that right? >> Yeah, that is correct. So, if you think about it I own the VMWare Offering Solutions on our cloud. So, that is everything associated with the whole VMWare software defined data center stack, but also a lot of our partner solutions. Many solutions in the security space. Many solutions in the business resiliency space. And that's kind of where Veeam had came in on that aspect. >> So the first public cloud deal that VMWare did, correct me if I'm wrong, was with IBM, was it not? >> Yeah, so if you just go back a little bit in time, IBM itself is probably the largest, if not the largest, provider of VMWare workloads. And mainly that's due to a lot of our GTS services business. But back in 2016, this looked like a great opportunity to actually go on the public cloud and actually stand up a software defined data center stack from VMWare. So, we started on that in that partnership with VMware and started to just basically grow that business. That business has been growing at about a 75% CAGR, and then that was kind of like step one, get the stack, and then step two was how do you get those security services in, and some of those business resiliency services in. And that's where we started to go in and do a real deep partnership with Veeam and happy to say that we started that in 2017 and we have about 12,000 plus VMs, both bare metal and also on virtualized VMWare on our cloud. Its been about 170% year to year growth rate. So Veeam's killing it on our cloud. They really are. >> And your scope is anything in the IBM cloud that's VMWare related so it could be >> That is correct. >> Data base services, it could be >> Absolutely. >> Object stores, obviously data protection with Veeam. What do you think is driving the Veeam-IBM momentum? >> Well, I think what's driving it is if you think about a lot of these, you know, critical customers, first thing they're going to want to do is take advantage of a lot of things that you get with the cloud. Whether its moving from a capex to an opex model with being able to get that capacity expansion. And there's a whole bunch of different use cases that you've got, but one of the key things to them is this whole business continuity. The ability to make sure that I can back it up, I can recover as quickly as I possibly can, and maybe more importantly, we have about 60 data centers worldwide. And being able to, essentially, have that geographic span is a huge advantage. And also the, fact that, just take backup as a simple example. When I back up I may be moving data back and forth in a particular region. I'm looking for some latency. And not to be able to be charged for that is a powerful value proposition for the customer. So, we don't charge for any type of data movement inside our cloud. And also, when you go outside, maybe for high availability, outside into the geographic reach, the same thing happens. So I think those are some very key things. That it's the security, the very fast backup and recovery, and knowing that you're not getting charged for that private secure network. It brings a real good value proposition to our customers that are leveraging Veeam and other services. >> So we think that we're now entering into a third era of cloud where the first one was basically makers, companies that created SAS companies, gaming companies, and then people moved analytics into there for a variety of reasons. Now the enterprise seems to be getting in it in a big way. Certainly at the large size. But that's starting to move down into the mid-range as well. Your advantage, IBM's advantage, has always been your ability to engage and bind with your customer base. How are you, how is IBM helping to move these customers forward, and what is the backup restore conversation in that process? Is it an afterthought? Is it something that's becoming more central to their thinking? How is it working? >> Yeah, so that's a great question, Peter. So, the way I think we in IBM cloud have thought about this is we've kind of divided the journey to cloud into two pieces. The 20% that are there, they weren't the real I'll call them business critical type of workloads that are going on, but that next 80% that's where we really see a huge advantage to us. Its out enterprise relationships. Its what we do from a security aspect on the cloud, and how easily we could help them, what we call lift and shift and migrate things over. And then once you're there, how can I help give you that assurance that we're going to give you the best backup, the best recovery in the event of a disaster, something that can, if you do see a failure, being able to have a very fast recovery point, you know, objective, and get you knowing that everything is secure and backed up and has this wide geographic spread. And even think about in the areas of compliance these days. GDPR. I mean, you have to have these data centers worldwide and sometimes they have to be you know, fixed. So, we provide that whole value proposition, I think, to those clients, in that essence. And I think the business critical, and, eventually, what we call mission critical workloads that will eventually move over, its probably the best choice to be able to have that trusted place to put workloads. >> So, the other, related to that, is you've got customers who are now moving and we're going to see them moving at varieties of speeds, but increasingly, the enterprises are going to move faster to do this than they've done in almost anything previously. And you've got Veeam, a very hard charging vendor, that has a reputation for great quality stuff, but a lot of innovation, moving very quickly. How is, how are you ensuring that there's no impedance mismatch between you, IBM, IBM customers, and Veeam and the technology vectors that it's on. >> Yeah, well first of all, its a very, very deep partnership. I mean very, very6 close relationship with them. This is not a vendor supplier relationship. This is a very, very deep partnership. And the other thing is, from a technology standpoint, one of our big differentiators on the cloud is, we actually provide that access all the way down to the hypervisor level. So, you have full freedom of action to do whatever you want to be able to do. So, from a Veeam standpoint, since its really based on a hypervisor type of technology, that gives us a real big advantage, because let's say, David, you're using Veeam on-prem. I give it the exact same look and feel as if you're off-prem, and I essentially make that data center look like an extension, like it was just in the next building and such. >> It's just another group, it's just another pool of VMs. >> Absolutely. And that whole, control and management of that gives you extreme flexibility that you really can't get in any other type of cloud. I like to say that You can come in and custom build your infrastructure, your VMWare software defined data center stack, your services such as Veeam. You custom build it any way that you want. It's like leasing a car. After you custom built that car, we hand you the keys. It's client managed. You go out and do whatever you want with that. And if you don't like it you can turn those keys back in, because we just do things not on a long term commitment, but on monthly commitments and such. >> And I want to, I want to maybe drill down on that a little bit, Dale. >> Sure. >> And try to better understand some of the flexibility that I'm inferring from your statement. So, you're a mainframer. You remember the days of SMS, and one of the things about it was that I could set policy for data protection, for backup, based upon the workload. I could say back this up once a week or back this up every day or back this up every hour or what is was. I had a granular level of capability. It was mainframe so it was, you know, big stuff. A lot of the challenges within, certainly the mid-size and smaller businesses, it's like one size fits all. This has been a, you know, a problem for everybody for years. Danny Allen, this morning, in the analyst and media session was talking about... >> This is the products guy here at VM. >> Yeah, yeah, yeah. Talking about the ability to sort of set granular levels, the pressures of RPO and RTO. And I want to sort of test how challenging it is to do that by workload or by application, and how IBM and Veeam are supporting that. How complicated is it? Are your clients doing it or is it still kind of a one size fits all world. >> I wouldn't say its one size fits all, but what I would say is by giving the clients full control and having the freedom and flexibility to do things that they want, the tight integration of this Veeam technology into the V-Center console and such, it gives them the ability, I like to say, do it at your own pace. Do it when you want to. Even something as simple as, lets say, managing VMWare and patching it, instead of having somebody else do it for you at their pace, we essentially allow you to do it at your pace when you want to. And its the same thing with the backup. You do it when you want to, at your frequency, what regions you want to go, or your whole geographic spread. And we try to provide the maximum flexibility and control to our mutual clients to enable that. >> And on the automation scale, or you know, the 9-inning game of automation, where are we? How, how automated can I make that, but more importantly, how fast are customers adopting that sort of automation scenario. >> Yeah, so you're experience when you come into our, our cloud, and essentially you click on "I want to go to the cloud," you click on the VMWare offering, its a very simple menu. You pick your infrastructure, compu... network storage. I'll keep it simple for now. You pick your software defined data center stack and we even enable a BYOL. A lot of people have their own Vsphere licenses. We enable them to go in and insert their key which is a cost advantage to them. Then you pick your partner services and such. So you pick your Veeam, and then you go in there and say "Well, where do I want to put it? Do I want to put it into Vsan? Do I want to put it into a file based storage?" And I think what we're really excited about is, we just recently announced being able to put this into IBM's cloud object storage. And that's huge, because, if you think about it, we all live in this area of regulatory and compliance and you can't throw anything away and the data is just exploding all over the place. So, having that ability to put it into a lower cost storage and all automated and essentially Veeam can essentially point to any of those multiple storage tiers. It gives our customers a big advantage so that they could essentially, I'll call it right-tune what they want to do and where they want to do their backups. So, they want something there quick or they say "Nah, you know, that could be a cold vault. I can keep that out there for a while and when I need it I'll go back and get it." So a lot of flexibility on storage options, a lot of flexibility on the pricing. But Veeam essentially is that powerhouse behind it that's actually interfacing that VMWare world as well as on the bare metal side over to those various levels of storage. >> So David, to answer your question, where are we in that 9 innings. I would have said bottom of the 1st, 1 out, 2 men on, 1 of them is Manny Ramirez. [Laughter] Because you just don't know what's going to happen next, and that's what I want to bring up. Veeam talked about... >> Is he a Boston fan? >> No, I'm not. [Laughter] I'm not. But Veeam talked about the "with Veeam" and I'm wondering how IBM sees it bringing its, this massive innovation, you still are one of the leading generators of patents in certainly the tech industry, but globally. How do you see IBM bringing IBM intellectual property, IBM invention, to this "with Veeam" platform to increase the degree to which it can serve a broader range of customers of different sizes, different geographies, and different workload forms. How do you see IBM participating in that process? >> Yeah, let me give you a couple examples. So, let me just take a non-Veeam example, just to talk about some IBM innovation. So, about a month ago we actually introduced something called hyperprotect cryptoservices. That's a big word there. Basically, it is, it's the same technology that we have in system Z, that's used by our large enterprise customers that gives you that, that FIPS 140-2, level 4. We are the only cloud in the world that has that technology that's on there. Basically, once you put your keys in there nobody's going to get to them at all. And it's an innovation of taking something that was done in a different division within IBM and now making that as an endpoint service within our cloud. Now, let me give you an example of doing a little bit of innovation even with Veeam. So, one of the things that we're trying to do is, you know, we started out hey, let's lay down the software data center stack, let's lay down partner services. Now, let's focus on what's that solution layer on top of it. How do we add more value into our clients? So, just take SAP, for example. We just recently announced both on a bare metal and also on our VMWare side, to be able to have a, we're the only cloud that has a certified SAP server in the cloud. And what we've just recently done is, we've integrated and put Veeam as that backup choice for that. So, now what that really enables everyone to do is leverage a lot of innovative work that Veeam was doing to make sure that you can back up SAP correctly. We married that with our infrastructure and our bare metal/VMWare stack with Veeam as that backup. And just a little bit of foreshadowing in the future, we're going to look at ways to further automate a lot of that SAP landscape so that our clients see, you know, a much better automated solution so that they essentially, using your baseball analogy, are going to see that full range of automation and say "Wow. I think we're at the end of the game here. This thing truly is automated, easy to consume, and I'll have the confidence of the security and the business resiliency knowing that it's got the trusted IBM name behind it. >> You know, give us the summary of 2019. Maybe some of the first half highlights and maybe show a little leg for the second half. >> Sure, sure. Why not? >> What can we expect leading up to IBM thing. >> So, I mentioned a few things about what we did in the security space already. So, we've enabled, besides our, what we've done with high trust, with data and key protection. We've also enabled IBM's key protect services. We brought the System Z hyperprotect services into the mix. We've enabled things like cavionics to bring the risk foresight. So, now, we can monitor a lot of compliance and keep things in compliance and monitor that for you. We brought some app modernization to essentially help people on their journey modernize their apps, leveraging both a tight integration of VMWare and what we call ICP-hosted or IBM Cloud Private hosted to get that tight integration and such. But moving forward I see a couple big things, and I'll try to maybe put them in the Veeam perspective and such. You heard me mention before about this 80% of that real key workload coming over to the cloud that, you know, business critical or mission critical. We announced last year something called mission critical VMWare, and basically what it is, it's two, two active, active type of sites with a witness site and you essentially are moving things back and forth so if you have a failure within a region you instantly can go in and switch over. And the idea is to give you the highest availability into the cloud. And Veeam is a very much integral part of that solution in the sense that it'll be our backup. And then since you said do a little bit of foreshadowing, say what's coming in the future. We have a very very strong single tenant VMWare offering on the cloud. Like I was saying, you know, it's client managed, the hypervisor access. You've got that extreme flexibility and control. But what we like to do is kind of look into a little bit more of that multi-tenant type of space. And we think it opens up a whole new market segment for us in that emerging market and commercial market space. Guess who's going to be our partner in that to make the backup happen? That's going to be Veeam. >> Cool. Dale Hoffman, thanks so much for coming to the CUBE and sharing. >> Oh, thank you for having me. >> Some of the ways in which IBM is differentiating, not doing infrastructure service and just racing to zero, but really trying to pick your spots and I really appreciate your insights and thanks again. >> Okay, thank you. >> Alright, keep it right there everybody. This is Dave Vellante with Peter Burris. Day one at VeeamON2019, and from Miami you're watching the CUBE. We'll be right back.

>> Live from San Francisco, it's theCUBE, covering IBM Think 2019. Brought to you by IBM. >> Hey, welcome back everyone this is theCUBE's live coverage in San Francisco, California Moscone Center for IBM Think 2019. It's the wrap up of our four days of wall-to-wall live coverage. All the publishing on Siliconangle.com. I've got the journalism team cranking it out. Dave Vellante just put up a post on Forbes, check that out. And Stu's got the team cranking on the videos. Stu and Dave, four days, team's done a great job. Tons of video, tons of content, tons of data coming through theCUBE. We're sharing that live, we're sharing it on Twitter, we're sharing it everywhere on LinkedIn. What's going on with the data? Let's synthesize, let's extract the signal from the noise, let's assess IBM's prospects in this chapter two, as Ginni says. A lot of A.I., lot of data, I mean IBM is an old company that has so much business, so many moving parts and they've been working years to kind of pivot themselves into a position to run the table on the Modern Era of computing and software. So, what do you think, Dave? >> Well, I mean, this has been a long time coming and we're here, you pointed out John, to me privately that IBM's taking a playbook similar to Microsoft in that they're cloudifying everything. But there's differences, right? There's a bigger emphasis on A.I. than when, not that Microsoft's not in A.I. they of course are, but when Microsoft cloudified itself there wasn't as much of an emphasis on A.I. Ginni Rometty said, "Well, the first chapter was only about 20%, the remaining 80% is going to be chapter two. We're going hard after that." I wrote in that post today that, in 2013, IBM had a wake-up call. They lost that deal to Amazon at the C.I.A. They had to go out and buy Softlayer because their product was deficient, their cloud product was deficient. >> And by the way it looks like they're going to lose the JEDI Contract by the D.O.D., another agency that's a 10 billion dollar contract. >> So we can talk about they're going to lose that one too. >> We can talk about is Amazon's lead extending in Cloud? And so, IBM cannot take on Amazon head-to-head in infrastructures of service period, the end. It doesn't have the volume, >> And they know that, I think. >> It doesn't have the margins, and they know that. They got to rely on it's, as a service business it's SaaS, it's data, it's data platforms, obviously A.I. and now Red Hat. The fact that IBM had to spend, or spent, 34 billion dollars on Red Hat, to me underscores the fact that it's Cloud and it's 10-year attempt to commercialize Watson, isn't enough. It needs more to be a leader in hybrid. >> And let's talk about the Red Hat acquisition because Ray Wang on theCUBE yesterday and said, "Oh, P.E., private equity prices are driving up 34 billion dollars, pretty much market in today's world." He thinks they overpaid and could have used those services. You debated that, you've heard me say that, hey I could have used that 34 billion dollars of cobbled-together stuff, but you made a comment around speed. They don't have the gestation period there to do it. So, if you take market price for Red Hat, Stu, with open shifts accelerated success since Kubernetes really accelerated its adoption. You got IBM now with a mechanism to address the legacy on premise into Cloud Modern, and you got with this Cloud Private, Stu, this really is a secret weapon for IBM and to me, what I'm pulling out of all the data is that Rob Thomas at Interpol, the CDO have a great data A.I. strategy as a group. They have a team that's one team and this Cloud Private is a secret weapon for them. I think it's going to be a very key product and not a lot of people are talking about it. >> Well John, it shouldn't be a secret weapon for IBM because of course IBM has a strong legacy in the data center. We've talked about Z this week, you talk about power, talk about all the various pieces. Red Hat absolutely can help that a lot. What we noticed is there wasn't a lot of talk about Red Hat here just because it's going through the final pieces. We expect later this year to come out, but it's about the developers. That is where Red Hat is going to be successful, where they are successful and where they should be able to help IBM leverage that going forward. The concern we have is culture. IBM says that Red Hat will be separate. There will be no layoffs, they'll keep that alone but when I wrote about the acquisition I said, we should be able to see, for this to really be a successful acquisition, we should be able to see the Red Hat culture actually influence what's happening at IBM. And to be honest when I talk to people around this show, they're like, "That's never going to happen, Stu." >> I just want to make a point about the price. Ray was saying how they overpaid and made the private equity thing. IBM's paying a hundred and ninety dollars a share. If you dial back to June of '18, Stu you and I talked about this in our offices, Red Hat was trading at one seventy five a share. So they're paying an 8 1/2% premium over that price. Yes, when they made the deal in the fall you're talking about a 60% premium. So, the premium is really single digits over what it was just a few months earlier. >> And Cisco, Google, >> It was competitive, right. >> Microsoft all could have gone after that. I think it's a great buy for IBM. >> That's what they had to pay to get it. >> And definitely it helped there. So from my stand-point, looking at the show this week, first of all I was impressed to see really that data strategy and how that's pervasive through the company and A.I. is something that everyone's talking about how it fits in. John you commented a bunch of times Ginni mentioned Kubernetes two times in her Keynote. So, they're in these communities, they're working on all these environments. The concern I have is if this is chapter two and if A.I. is one of the battlefields, Amazon's all deep into A.I. I think heavily about Google when I talk about that. When I talk to Microsoft people they're like, "Satya Nadella is Mr. A.I.", that's all they care about. >> I don't think Microsoft has a lot of meat on the A.I. bone either. >> Really? >> No look it, here's the bottom line. A.I. is a moonshot it is an aspirational marketplace. It's about machine learning and using data. A.I.'s been around for a while and whoever can take advantage of that is going to be about this low-hanging use cases of deterministic processes that you throw machine learning at no problem. Doing cognition and reasoning a whole 'nother ballgame. You got state, this is where the Cloud Native piece is important as a lynch-pin to future growth because that wave is coming. And I think it's not going to impact IBM so much now, as it is in the future, because you got developers with Red Hat and you got the enablement for Cloud growth, Modern Cloud, stuff in any Cloud. But IBM has a zillion customers Dave, they have a business, they have mission critical workloads. And you pointed out in the Forbes post that we posted and on the Silicon Angle, that I.T. Economics are changing. And that the cloud services market is growing, so IBM has pre existing, big mission critical companies that they're serving. So, you can't just throw Kubernetes at that and say lift and shift. Z's there, you got other things happening. So, to me, that is IBM's focus, they nail their bread and butter, they bring multi-cloud from the table. Throw hybrid at it with Private Cloud and they're stable. Everything else I think is window dressing in my mind, because I think you're going to see that adoption more downstream. >> Well, the other thing you gave me for the piece actually, you helped me understand that IBM with Red Hat can use Cloud Native techniques and apply them to its customer base and to really create a new breed of business developers, right? Probably not the hoodie crowd necessarily, but business developers that are driving value apps based on mission critical apps and using Cloud Native techniques. Your thoughts on that? >> The difference between Oracle and IBM is the following, Oracle has no traction in developers in Cloud Native, IBM now with Red Hat can take the Cloud Native growth and use containers and Kubernetes and these new technologies to essentially containerize legacy workloads and make them compatible with modern technologies. Which means, if you're in business or in I.T. or running a lot of big shops, you don't have to kill the old to bring in the new. That's one factor. The other factor is the model's flipped. Applications are dictating architecture. It used to be infrastructure dictates what applications can do, it's completely reversed. We've heard this time and time again from the leading platforms, the ones that are looking at the applications with data as a fabric in there will dictate resource, Whether it's one Cloud or multiple Clouds or whatever architecture that's the fundamental shift. The people who get that will win and the people who don't won't. >> And the other thing I've pointed out in that article is that Ginny kept saying it's not backend loaded, The Red Hat deal, it's not back end loaded. IBM has about a 20 billion dollar business, captive business, in outsourcing, application management, application modernization and they can just point Red Hat right at that base, bring it's services business, Stu you've made this point, it's about scaling Red Hat. Red Hat's what, about a three and a half billion dollar company? >> Yeah >> And so that really is, she was explaining the business case for the acquisition. >> Yeah absolutely, I mean we've watched IBM for years, Bluemix had a little bit of traction but really faltered after a while, that application modernization. You hear from IBM, similar to what we've heard from Cisco a few weeks ago, meet customers where they are and help them move forward. We did a nice interview this week with a UK financial services company talking about how they've modernized what they're doing. Things like I.T. ops, new ops, these environments that are helping people with that app development. 'Cause IBM does have a good application work flow. There's lots of the infrastructure companies don't have apps and that's a big strength. >> When was the last, I got a direct message from the crowd, I want to get to Stu, but I want to ask you guys a question. When was the last time you saw a real innovation and disruption in a positive way around business applications. We're talking about business applications, not a software app, that's in a created category. We're talking about blocking and tackling business applications. When have you seen any kind of large scale transition innovation. Transition and innovation at the business application level? >> Google Docs? I mean >> I mean think about it. >> Right? >> So I think this is where IBM has an opportunity. I think the data science piece is going to transform into a business app marketplace and I think that's where their value is. >> Workday? >> Service Now. >> It's a sass ification of everything. >> Salesforce? >> Service Now, features become products. Products become companies. I mean this a big debate. I mean you can win on >> But that's not, Service Now really not a business, I mean it is a business app but it's more of an I.T. app. Alright Workday I'd say is an example. Salesforce I guess. >> And look here's one of the flaws in that multi-cloud picture, is it's I'm going to take all this heterogeneous environment and I'm going to give you a multi-Cloud manager. We've seen that single pane of glass discussion my entire career and it never works. So I'm a little concerned about that. >> So Andy Jassy makes the case that multi-cloud is less secure, more complex, more expensive. It's a strong case that he makes. Now of course my argument is that it's multi-vendor. It's not really multi-cloud. >> Well here's the Silicon Valley >> So he didn't have any control over that. It's not a procurement thing, it's just the way that people go by. >> The world has changed with cloud and I'll give you a Silicon Valley example anecdote. It used to be an expression in Silicon Valley, in venture capital community if you were a start-up or entrepreneur you'd build a platform. And there was an old expression, that's a feature, not a company. Kind of a joke within the VC community and that's how they would vet deals. Oh, that's a good feature" >> "Oh it's a feature company." >> "That's a great idea." Now with Cloud as a platform and now with all the stuff that's coming to bear, horizontally scalable, all the things that IBM's rolling out, sets the table for a feature to be a company. Where you have an innovation at the business model level, you don't really need tech anymore other than to scale up build it out and that's all done for you by other people. So people who are innovating on say an idea, well let's change this little feature in HR app or, that could meet up to Workday. Or let's change this feature. Features can become companies now so I think that's my observation. >> I think it's really interesting >> It could live in the cloud marketplaces too. It's so easy to get that scale if I could plug into all those marketplaces. IBM for years has had thousands of partners in their ecosystem. Of course Amazon's Marketplace, growing like gangbusters. >> But this is what Jerry Chen said when we were at Reinvent last year and we were asking him about Amazon, will it go up the stack, will it develop applications? He said, well, look but then what we got to do is give people a platform for application developers to build those features to disrupt, to your point, the core enterprise apps. Now, can IBM get there before Amazon, who knows? I mean its. >> Alright guys let's look at the big picture, zoom out. Your thoughts on Think 2019 IBM Think, Stu what's your final thoughts? >> Yeah, final thoughts is, I think IBM first of all is coming together. Just as this show was six shows and last year it was in two locations, there's cohesion. I heard the four days of interviews, we saw a lot of different pieces. Everything from talking about augmented reality through storage and we talked about the Z, and those pervasive themes of data, A.I., Dave what do you call it, It's the innovation cocktail now in Cloud. Data A.I. in cloud, put those three together. >> Innovation sandwich, innovation cocktail. Got to have a cocktail with a sandwich. That's your big take away? Okay, my take away Dave is that the, you nailed it in your post I thought, you should go to Forbes and check out, search on IBM Think you'll find the post by me and Dave Vellante but it's really written by Dave. I think to me IBM can change the game on two fronts. I learned and I walked away with a learning this week about these business apps. To me, my walk away is there's going to be innovation at a new genre of developers. I think you're going to see IBM target, they should target these business app ties as well as with the Could Native in Red Hat. I really think highly of that acquisition. From a speed stand point, I think the culture of Red Hat, although different, will be a nice check against IBM's naturally ability to blue-wash it. Which means you don't want to lose the innovation. I think Ginni saying Kubernetes twice on stage, is a sign that she sees this path, I think the Cloud Private opportunity could be a nice lever to bring open shifts and Kubernetes into that growth. And I think A.I. is going to be one of those things where they're either going to go big or go home. I think it's going to be one of those things. >> My take, love the venue, way better than last year in terms of the logistics. I like the new Moscone, easy to get around. May next year, May 2020 is going to be better than February here. I would've liked to see Ginni sell harder. She laid out a vision, she talked about a lot of sort of of high level things. I would have liked to seen her sell the new IBM and Red Hat harder. I guess they couldn't do that because they're worried about compliance. >> Quiet Period? >> Yeah right, you know monopolistic behavior I guess. But that I'm really excited to hear that story and a harder sell on the new IBM. >> I think if they can take the Microsoft playbook of cloudifying everything going with the open source with Red Hat and then just getting the great Sass if app revenue up, they're going to, can do well. >> Alright guys, great job. Thanks for hosting this week. Lisa Martin's not here today. Want to thank Lisa Martin if you're out there watching, great time. Guys, thanks to the crew. Thanks to IBM. Thanks to all of our sponsors that make theCUBE do what we do and thanks for all of your support to the community. I'm John Furrier along with Stu Miniman. Thanks for watching. See you next time. (pulsing electronic music)

>> Live, from San Francisco, it's theCUBE covering IBM Think 2019. Brought to you by IBM. >> Hello everyone, welcome back to theCUBE's live coverage here in San Francisco for IBM Think 2019. I'm John Furrier, Stu Miniman with theCUBE. Stu, it's been a great day. We're on our fourth day of four days of wall to wall coverage. A theme of AI, large scale compute with Cloud and data that's great. Great topics. Got two great guests here. Rohit Badlaney, who's the director of IBM Z As a Service, IBM Systems. Real great to see you. And Nataraj Nagaratnam, Distinguished Engineer and CTO and Director of Cloud Security at IBM and Hybrid Cloud, thanks for joining us. >> Glad to be here. >> So, the subtext to all the big messaging around AI and multi-cloud is that you need power to run this. Horsepower, you need big iron, you need the servers, you need the storage, but software is in the heart of all this. So you guys had some big announcements around capabilities. The Hyper Protect was a big one on the securities side but now you've got Z As a Service. We've seen Linux come on Z. So it's just another network now. It's just network computing is now tied in with cloud. Explain the offering. What's the big news? >> Sure, so two major announcements for us this week. One's around our private cloud capabilities on the platform. So we announced our IBM Cloud Private set of products fully supported on our LinuxOne systems, and what we've also announced is the extensions of those around hyper-secure workloads through a capability called the Secure Services Container, as well as giving our traditional z/OS clients cloud consumption through a capability called the z/OS Cloud Broker. So it's really looking at how do we cloudify the platform for our existing base, as well as clients looking to do digital transformation projects on-premise. How do we help them? >> This has been a key part of this. I want to just drill down this cloudification because we've been talking about how you guys are positioned for growth. All the REORG's are done. >> Sure, yeah >> The table's all set. Products have been modernized, upgraded. Now the path is pretty clear. Kind of like what Microsoft's playbook was. Build the core cloudification. Get your core set of products cloudified. Target your base of customers. Grow that and expand into the modern era. This is a key part of the strategy, right? >> Absolutely right. A key part of our private cloud strategy is targeted to our existing base and moving them forward on their cloud journey, whether they're looking to modernize parts of their application. Can we start first with where they are on-premise is really what we're after. >> Alright, also you have the Hyper Protect. >> Correct. >> What is that announcement? Can you explain Hyper Protect? >> Absolutely. Like Rohit talked about, taking our LinuxOne capabilities, now that enterprise trusts the level of assurance, the level of security that they're dependent on, on-premise and now in private cloud. We are taking that further into the public cloud offering as Hyper Protect services. So these are set of services that leverage the underlyings of security hardening that nobody else has the level of control that you can get and offering that as a service so you don't need to know Z or LinuxOne from a consumption perspective. So I'll take two examples. Hyper Protect Crypto Service is about exposing the level of control. That you can manage they keys. What we call "keep your own keys" because encryption is out there but it's all about key management so we provide that with the highest level of security that LinuxOne servers from us offer. Another example is database as a service, which runs in this Hyper Secure environment. Not only encryption and keys, but leveraging down the line pervasive encryption capabilities so nobody can even get into the box, so to say. >> Okay, so I get the encryption piece. That's solid, great. Internet encryption is always good. Containers, there's been discussions at the CNCF about containers not being part of the security boundaries and putting a VMware around it. Different schools of thought there. How do you guys look at the containerization? Does that fit into Secure Protect? Talk about that dynamic because encryption I get, but are you getting containers? >> Great question because it's about the workload, right? When people are modernizing their apps or building cloud-native apps, it's built on Kubernetes and containers. What we have done, the fantastic work across both the IBM Cloud Private on Z, as well as Hyper Protect, underlying it's all about containers, right? So as we deliver these services and for customers also to build data services as containers or VM's, they can deploy on this environment or consume these as a compute. So fundamentally it's kubernetes everywhere. That's a foundational focus for us. When it can go public, private and multicloud, and we are taking that journey into the most austere environment with a performance and scale of Z and LinuxONE. >> Alright, so Rohit, help bring us up to date. We've been talking about this hybrid and multi-cloud stuff for a number of years, and the idea we've heard for many years is, "I want to have the same stack on both ends. I want encryption all the way down to the chip set." I've heard of companies like Oracle, like IBM say, "We have resources in both. We want to do this." We understand kubernetes is not a magic layer, it takes care of a certain piece you know and we've been digging in that quite a bit. Super important, but there's more than that and there still are differences between what I'm doing in the private cloud and public cloud just naturally. Public cloud, I'm really limited to how many data centers, private cloud, everything's different. Help us understand what's the same, what's different. How do we sort that out in 2019? >> Sure, from a brand perspective we're looking at private cloud in our IBM Cloud Private set of products and standardizing on that from a kubernetes perspective, but also in a public cloud, we're standardizing on kubernetes. The key secret source is our Secure Services Container under there. It's the same technology that we use under our Blockchain Platform. Right, it brings the Z differentiation for hyper-security, lockdown, where you can run the most secure workloads, and we're standardizing that on both public and private cloud. Now, of course, there are key differences, right? We're standardizing on a different set of workloads on-premise. We're focusing on containerizing on-premise. That journey to move for the public cloud, we still need to get there. >> And the container piece is super important. Can you explain the piece around, if I've got multi-cloud going on, Z becomes a critical node on the network because if you have an on-premise base, Z's been very popular, LinuxONE has been really popular, but it's been for the big banks, and it seems like the big, you know, it's big ire, it's IBM, right? But it's not just the mainframe. It's not proprietary software anymore, it's essentially large-scale capability. >> Right. >> So now, when that gets factored into the pool of resources and cloud, how should customers look at Z? How should they look at the equation? Because this seems to me like an interesting vector into adding more head room for you guys, at least on the product side, but for a customer, it's not just a use case for the big banks, or doing big backups, it seems to have more legs now. Can you explain where this fits into the big picture? Because why wouldn't someone want to have a high performant? >> Why don't I use a customer example? I had a great session this morning with Brad Chun from Shuttle Fund, who joined us on stage. They know financial industry. They are building a Fintech capability called Digital Asset Custody Services. It's about how you digitize your asset, how do you tokenize them, how you secure it. So when they look at it from that perspective, they've been partnering with us, it's a classic hybrid workload where they've deployed some of the apps on the private cloud and on-premise with Z/LinuxONE and reaching out to the cloud using the Hyper Protect services. So when they bring this together, built on Blockchain under the covers, they're bringing the capability being agile to the market, the ability for them to innovate and deliver with speed, but with the level of capability. So from that perspective, it's a Fintech, but they are not the largest banks that you may know of, but that's the kind of innovation it enables, even if you don't have quote, unquote a mainframe or a Z. >> This gives you guys more power, and literally, sense of pretty more reach in the market because what containers and now these kubernetes, for example, Ginni Rometty said "kubernetes" twice in her keynote. I'm like, "Oh my God. The CEO of IBM said 'kubernetes' twice." We used to joke about it. Only geeks know about kubernetes. Here she is talking about kubernetes. Containers, kubernetes, and now service missions around the corner give you guys reach into the public cloud to extend the Z capability without foreclosing the benefits of Z. So that seems to be a trend. Who's the target for that? Give me an example of who's the customer or use case? What's the situation that would allow me to take advantage of cloud and extend the capability to Z? >> If you just step back, what we're really trying to do is create a higher shorten zone in our cloud called Hyper Protect. It's targeted to our existing Z base, who want to move on this enterprise out journey, but it's also targeted to clients like Shuttle Fund and DAX that Raj talked about that are building these hyper secure apps in the cloud and want the capabilities of the platform, but wanted more cloud-native style. It's the breadth of moving our existing base to the cloud, but also these new security developers who want to do enterprise development in the cloud. >> Security is key. That's the big drive. >> And that's the beauty of Z. That's what it brings to the table. And to a cloud is the hyper lockdown, the scale, the performance, all those characteristics. >> We know that security is always an on-going journey, but one of the ones that has a lot of people concerned is when we start adding IoT into the mix. It increased the surface area by orders of magnitude. How do those type of applications fit into these offerings? >> Great question. As a matter of fact, I didn't give you the question by the way, but this morning, KONE joined me on stage. >> We actually talked about it on Twitter. (laughs) >> KONE joined us on stage. It's about in the residential workflow, how they're enabling here their integration, access, and identity into that. As an example, they're building on our IoT platform and then they integrate with security services. That's the beauty of this. Rohit talked about developers, right? So when developers build it, our mission is to make it simple for a developer to build secure applications. With security skill shortage, you can't expect every developer to be a security geek, right? So we're making it simple, so that you can kind of connect your IoT to your business process and your back-end application seamlessly in a multi-cloud and hybrid-cloud fashion. That's where both from a cloud native perspective comes in, and building some of these sensitive applications on Hyper Protect or Z/LinuxONE and private cloud enables that end to end. >> I want to get you guys take while you're here because one of the things I've observed here at Think, which is clearly the theme is Cloud AI and developers all kind of coming together. I mean, AI, Amazon's event, AI, AI, AI, in cloud scale, you guys don't have that. But developer angle is really interesting. And you guys have a product called IBM Cloud Private, which seems to be a very big centerpiece of the strategy. What is this product? Why is it important? It seems to be part of all the key innovative parts that we see evolving out of the thing. Can you explain what is the IBM Cloud Private and how does it fit into the puzzle? >> Let me take a pass at it Raj. In a way it is, well, we really see IBM Cloud Private as that key linchpin on-premise. It's a Platform as a Service product on-premise, it's built on kubernetes and darker containers, but what it really brings is that standardized cloud consumption for containerized apps on-premise. We've expanded that, of course, to our Z footprint, and let me give you a use case of clients and how they use it. We're working with a very big, regulated bank that's looking to modernize a massive monolithic piece of WebSphere application server on-premise and break it down into micro-services. They're doing that on IBM Cloud Private. They've containerized big parts of the application on WebSphere on-premise. Now they've not made that journey to the cloud, to the public cloud, but they are using... How do you modernize your existing footprint into a more containerized micro-services one? >> So this is the trend we're seeing, the decomposition of monolithic apps on-premise is step one. Let's get that down, get the culture, and attract the new, younger people who come in, not the older guys like me, mini-computer days. Really make it ready, composable, then they're ready to go to the cloud. This seems to be the steps. Talk about that dynamic, Raj, from a technical perspective. How hard is it to do that? Is it a heavy lift? Is it pretty straight-forward? >> Great question. IBM, we're all about open, right? So when it comes to our cloud strategy open is the centerpiece offered, that's why we have banked on kubernetes and containers as that standardization layer. This way you can move a workflow from private to public, even ICP can be on other cloud vendors as well, not just IBM Cloud. So it's a private cloud that customers can manage, or in the public cloud or IBM kubernetes that we manage for them. Then it's about the app, the containerized app that can be moved around and that's where our announcements about Multicloud Manager, that we made late last year come into play, which helps you seamlessly move and integrate applications that are deployed on communities across private, public or multicloud. So that abstraction venire enables that to happen and that's why the open... >> So it's an operational construct? Not an IBM product, per say, if you think about it that way. So the question I have for you, I know Stu wants to jump in, he's got some questions. I want to get to this new mindset. The world's flipped upside down. The applications and workloads are dictating architecture and programmability to the DevOps, or infrastructure, in this case, Z or cloud. This is changing the game on how the cloud selection is. So we've been having a debate on theCUBE here, publicly, that in some cases it's the best cloud for the job decision, not a procurement, "I need multi-vendor cloud," versus I have a workload that runs best with this cloud. And it might be as if you're running 365, or G Suite as Google, Amazon's got something so it seems to be the trend. Do you agree with that? And certainly, there'll be many clouds. We think that's true, it's already happened. Your thoughts on this workload driving the requirements for the cloud? Whether it's a sole purpose cloud, meaning for the app. >> That's right. I'll start and Rohit will add in as well. That's where this chapter two comes into play, as we call Chapter Two of Cloud because it is about how do you take enterprise applications, the mission-critical complex workloads, and then look for the enablers. How do you make that modernization seamless? How do you make the cloud native seamless? So in that particular journey, is where IBM cloud and our Multicloud and Hybrid Cloud strategy come into play to make that transition happen and provide the set of capabilities that enterprises are looking for to move their critical workloads across private and public in bit much more assurance and performance and scale, and that's where the work that we are doing with Z, LinuxONE set of as an underpinning to embark on the journey to move those critical workloads to their cloud. So you're absolutely right. When they look at which cloud to go, it's about capabilities, the tools, the management orchestration layers that a cloud provider or a cloud vendor provide and it's not only just about IBM Public Cloud, but it's about enabling the enterprises to provide them the choice and then offer. >> So it's not multicloud for multicloud sake, it's multicloud, that's the reality. Workload drives the functionality. >> Absolutely. We see that as well. >> Validated on theCUBE by the gurus of IBM. The cloud for the job is the best solution. >> So I guess to kind of put a bow on this, the journey we're having is talking about distributed architectures, and you know, we're down on the weeds, we've got micro-services architectures, containerization, and we're working at making those things more secure. Obviously, there's still a little bit more work to do there, but what's next is we look forward, what are the challenges customers have. They live in this, you know, heterogeneous multicloud world. What do we have to do as an industry? Where is IBM making sure that they have a leadership position? >> From my perspective, I think really the next big wave of cloud is going to be looking at those enterprise workloads. It's funny, I was just having a conversation with a very big bank in the Netherlands, and they were, of course, a very big Z client, and asking us about the breadth of our cloud strategy and how they can move forward. Really looking at a private cloud strategy helping them modernize, and then looking at which targeted workloads they could move to public cloud is going to be the next frontier. And those 80 percent of workloads that haven't moved. >> An integration is key, and for you guys competitive strategy-wise, you've got a lot of business applications running on IBM's huge customer base. Focus on those. >> Yes. >> And then give them the path to the cloud. The integration piece is where the linchpin is and OSSI secure. >> Enterprise out guys. >> Love encryption, love to follow up more on the secure container thing, I think that's a great topic. We'll follow-up after this show Raj. Thanks for coming on. theCUBE coverage here. I'm John Furrier, Stu Miniman. Live coverage, day four, here live in San Francisco for IBM Think 2019. Stay with us more. Our next guests will be here right after a short break. (upbeat music)

>> Live from San Francisco, it's theCUBE covering IBM Think 2019, brought to you by IBM. >> Hey, welcome back everyone. We're here live at theCUBE in Moscone North in San Francisco, for IBM Think 2019. I'm John Furrier with Stu Miniman, talking to all the top executives, top people here at IBM, getting the scoop on cloud and AI. Our next guest, Jason Gardner, Vice President of Worldwide Sales for Hybrid Cloud at IBM, manages key product, which is part of the IBM Cloud Private, big part of the announcements, big Cloud story here. It's multi-cloud, it's hybrid. Welcome back. >> It's hybrid multi-cloud. Thank you, for having me back. >> CUBE Alumni been on as early, going back as 2012. Now, one big event. >> I can't believe it's been that long. But yeah, I'm happy to be back and I can't believe I've been on theCUBE for so long. >> Talk about your new role, and you had previous roles within IBM dealing with the kind of clients and integration. Your role now is worldwide sales. You're taking this Cloud Private offering, bringing the customers, being as the linchpin for integration. Talk about what you do and some of the engagements you have. >> Yeah, previously, I was really focused in on development and offering management on, point products and how they help clients move to the Cloud. Things such as our Pure Business, our Spare Business, and now I've actually been able to move into a much more horizontal role, where I have the portfolio across the Hybrid Cloud integration side, so everything from our Websphere family, which includes IBM Cloud Private, straight to the integration challenges that that brings as well as our digital business automation portfolio. >> Yeah, I have a personal joy. Stu knows I'm fanatic about Kubernetes, and when I heard Ginni Rometty say Kubernetes twice in a CNBC interview you know it's made it. >> Yes. >> Kubernetes is a big part of cloud native containers, really now has created the connective tissue to make cloud and multi cloud viable. This is a key part of it. I want you to talk about the context of these trends and unpack this Cloud Private offering. Because it's instrumental in seems in the news. >> It is, it is. >> What is it about? >> It is, it really creates that ubiquitous layer I think that we've all been searching for. That next generation of virtualization and connective tissue as you call it. And as you begin to unpack that it really kind of starts with the rise of microservices and the need to be able to pack them very tightly into containers. That's really the birth of Kubernetes, was the ability to orchestrate those containers. So Kubernetes becomes that ubiquitous layer in there. But, IBM Cloud Private takes that and takes it to the next level, right. And, really what it is, it's the services on top of that, the cloud services which enable those containers to work together. And, it is a lot of open source capabilities such as Helm, Prometheus, Kibana and some of those core services that those microservices require in order to be able to run efficiently. >> So, Jason, we know it's a multicloud world. Everybody out there would love to say, oh yes, there's one cloud, I can simplify it. I'd like to get to a nice scalable model that's simple. But, the reality is customers choose lots of different solutions because they have different needs. The Private Cloud piece is not really well understood. I'd love you to take us inside your users. Because they say okay, I'm using Amazon, I'm using Microsoft Business Services. There are certain data things that Google has. IBM has AI and business productivity and database offerings. That Cloud Private, what are the services, what are the use cases, what are the reasons why I'm buying this and being part of my overall portfolio. >> Yeah, Ginni called it Cloud 2.0, right. 1.0 was about lifting shift, it was about cloud native, and that really got us about 20% of the way there. It's at 80%, that's the real challenge, that's really where the complication comes into play. That's really what Private Cloud is about. Because not everybody can be able to take their applications, throw them away, build cloud native, or lift and shift them. If you think of big regulated industries like banking, insurance, healthcare, government. They really need to be able to have that level of security and assurances that they need within there. And, that's really where private cloud comes into play, is those really tough, challenging problems in the industry. >> Yeah, I love that. A trend I've heard from a number of customers, you talk about them getting to containerization and multifactor services, is, step one is, I've got to modernize the platform-- >> Absolutely. >> Then I can modernize the applications on top it. Is that the trend you're seeing? >> Yeah, definitely. We've been building on microservices and modernization, it's a journey right, and it's a journey of discovery I think for a lot of clients out there. And, we'd all love to be able to say, OK this is my platform and now I'm going to work on the applications. But really, sometimes the starting point may be one or the another, and it usually comes in a space of a digital requirement, and so they begin to out modernize the application and then realize, jeez! I need to be able to manage all of this, I need to be able to deploy it all, and that's when the platform comes into play and all the other services, I should say, that come along with it. >> Stu, I think you coined the term Private Cloud. I think wasn't it? >> The true private cloud. >> True private cloud. So the private cloud, again, it's all cloud operations, so I kind of disagree on this whole point about one cloud or multi-cloud. Because I think, yes multi-cloud, but you see people use cloud for workloads, right? So pick the right cloud for the right application. So this basically says, okay, if you want to use Amazon, use Amazon if that's what you want, but if you are going to use 365, maybe use Azure. >> Yep. >> If you are going to use G Suite, use Google. You guys kind of have the business apps nailed down. >> Right. >> So If you're going to use your business apps, maybe IBM. This is your opportunity. >> This is our opportunity. >> Talk about specifically the kinds of apps that you guys will power with your cloud, because multi-cloud certainly makes sense for you guys. It's multi-cloud, you won't that portability and interoperability, but the apps that you're going to power with IBM Cloud. Talk about what they are, how-- >> Yeah, if you look at, from a language perspective over the last, jeez it's been 23 years I think, since the rise of Java, right? And 1995, when the first app servers came out. Those app servers, that is really where ore applications really run on top of. And, it's those core Java applications, that are now needing that facelift, right? They need to be able to be injected with new forms of AI, new types of integrations, new types of personalization of that digital transformation that's driving it, and that's really the core suite, right? And if I look at that core suite in there, and then what do you do to modernize a Java application, and what kind of tools are available to you. How do you then manage, how do you distribute, and how do you scale those applications. It's very important. >> What is the adoption of the private cloud or the Cloud Private product. >> Yeah. >> Talk about some of the trends, how is it being used, be specific on how customers are using it. What are some of the use cases? >> Yeah, so the primary use case is to increase the agility, lower cost on the overall managing of them. But it's the increase in the agility, which is really hard to measure. Because clients want to be able to react very fast to it. And so as they build up microservices, microservices then become independent with one another. You can then update ones, very quickly and easily. They manage and they run independently, and they scale independently, and so Cloud Private provides you with all those services to able to run those microservices as containers, but then be able to tie them together in a much more comprehensive enterprise suite. You know, a core technology like Helm, I'm waiting for Ginni to say that one on stage. But a core technology like Helm, really provides that robust, enterprise class distribution for scalability and high availability of a microservice based application. >> Jason, can you bring us inside the organization of the customers your selling to? It used to be, it was the refresh cycle. It's like OK, my X86 refresh, or you know, the budget cycles that I had. Cloud is quite a bit different. >> It is. >> Private Cloud is kind of straddling between the old world and the new world. What are the dynamics you're seeing as to who controls the purse strings? Are they moving faster to that opex model. >> You know, there's no one person who owns the purse strings on it, but it does float between the infrastructure team, knows that they need to do something different, the developers or the application development team, and really the strategy, the Chief Strategy Officer, in that IT organization is really where it's coming together. Because one thing I think that we've all learned is that developers will find the easiest, fastest way to do something. No matter what rules or policies we put down. And this is about providing them with an environment that has guardrails, for them to be able to innovate as fast as they want, use the tools that they want, that their most comfortable with. Really, it's a grass roots kind of movement into these microservices, led by the developers. But the purse strings are still held at the CTO side. >> That's always a fascinating interest, because the developers they're going to go do it, but they're not usually the ones with the budget. >> That's right. >> But when do the ops people get involved, the business people, to make sure that IT manages it, gets rid of like stealth IT? >> And a lot of clients have learned to listen to the developers, because the early days of cloud, they didn't, and developers found ways through it, no matter what. And so that's really what it's about. It's like a game of bumper cars, right? You got to make sure they stay within the ring of what's safe. And, especially in this day and age of the security requirements that are out there, it's more important today than ever before. >> Jason, can you share some data around some observations that you've noticed on trends around industry uptake or is there any patterns in terms of the customer base? Obviously, people aren't going to going to cloud operations. Just, Ginni mentioned 60/40, 80/20, the ratios. What does that all mean? And, just share the trend data around adoption and patterns? >> Probably the biggest onE in there, is the 80/20, right? That there's still 80% of the applications left in the world are still locked behind the brick and mortar. That's probably our biggest piece of our opportunity, and providing clients with a way to lift them up and be able to modernize them. I think is where the huge opportunity is. But then looking at where do they land, it's not all going to public cloud, right. So private cloud it's a huge business. I think a lot of us underestimated how large that business really is, and depending on the industry, you'll see 50/50, 60/40, 40/60 split, depending on the regulations within that industry, that country, the geography, of where they really want to go to. And, a lot of our clients are asking us for solutions around that private side, but yet be able to have the flexibility to be able to-- >> So you're seeing friction on the public cloud, mainly that's inherent from either regulatory compliance, or just technical challenges. Is that kind of the vibe? >> That's probably the first one. I think there's still that regulatory requirements of data residency, and how do I get my data to application. I can build all the applications I want in the cloud, but how do I get my data there? How do I synchronize it? My lineage of my data. So they really challenged her on that. But, then on the other side of it, is around the cost, right. And, if you wanted to rebuild all of your applications, as true cloud native, from scratch. It will take you a very long time and be very, very expensive. And so, there's also a cost element and speed. You can modernize something much more quickly, and be able to get it to that same level of service, without having to start over. >> We had Arvind on earlier, yesterday, and I want to get your thoughts on the impact of the Red Hat acquisition news, because if you look at what Open Shift is doing with Cloud Private. Arvind was saying yesterday that, Arvind Krishna, he's like, this is really enabling a lot of the acceleration for the modernization of the new cloud stuff, and keeping the legacy stuff and/or transition out on different timetables. Your thought on that? >> Absolutely right, Open Shift is going to be a critical component for our overall hybrid strategy. I'm very excited about it and really looking forward to it. And, Cloud Private and the services that I talked about, run in Open Shift today. That was part of our partnership agreement. I think that you guys were at, that Arvind talked about at that time. But, it provides the platform, for all of those traditional applications, which we've modernized. And the interesting thing is that we've actually modernized ourselves. We've modernized our middle-ware. We've modernized some of those products that are you know, 10, 20 years old. Everything from WebSphere, to MQ, to BPM. They've all been modernized in that same fashion. >> Yeah, Jason, speaking of modernization. Bring us inside you're sales force a little bit. How do they keep up, and what's the skill set that you're looking for, on your team to sell on this. You know, they need to understand Helm and Kubernetes, and all these microservice architecture, where five years ago, it was a totally different world. >> Absolutely, you know I think that if I look at a, it's not a skill, it's passion, right? It's that never give up type of mentality, I think that we look for, in a sales force and I never give up attitude really provides you with that foundation, for never stop learning, right. If anything that you've guys have noticed here over the last ten years in your guys' journey, is that this industry just changes so repidly, all the time. And, so as a sales force, you can't just acquire skills. You don't go out and hire skills. You hire people and you hire passion, and you hire people with that never give up attitude. I've been going around. We've been doing our sales kick-offs. I've done two out of the three now, so far. I tell you they are energized. They love it. They are energized about the Red Hat Acquisition. It shows that IBM really gets it. They've been telling me, does IBM really get it? And now they're like wow, we really do get it? And, they're really energized, because all of the pieces are falling into place, around this modernization, and clients, and we're hitting the timeing. >> It's time to hit that pedal to the metal, put the gas on-- >> They always say, there's no speed limit on sales. >> (laughs) Exactly. OK, first of all great, great conversation, and thanks for waiting out our journey. Stu, I would say that the salespeople got to watch all theCube videos, because all of the best content is coming out of theCube here, and great to have you on. But, quick plug, I'll give you the last word. What's the pitch, share the pitch for the Hybrid Cloud, what your team is offering? What's the, the core pitch for your customers, when you go to them? >> I think the core pitch is around modernization. It's the journey that clients are on, from application development, to how you build your apps, and how you build the microservices. How you integrate those applications, what's your API strategy, how do you move that data around securely, and then how do you manage all of those pieces together in that new modern world. And then, really looking your overall processes, and can you modernize your overall processes, add AI capabilities into that. So, it's that modernization journey. That's really what I talk to them about, and you don't have to do everything, right? Start small, start as a pinpointed piece, and we'll help you along that journey. And it becomes a journey of self-discovery, but we're there the whole way. We're a partner, that's really what it's about. >> Jason Gardner, Vice President of Worldwide Sales with Hybrid Cloud at IBM. TheCube, bringing all the data here, from IBM Think 2019. This is day three, of four days of coverage, here in Moscone live in San Francisco. We'll be right back with more, after this short break. (upbeat music)

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Okay. Welcome back, everyone. He live in San Francisco. Here on Mosconi St for the cubes. Exclusive coverage of IBM. Think twenty nineteen. I'm Jeffrey David Long. Four days of coverage bringing on all the action talking. The top executives, entrepreneurs, ecosystem partners and everyone who can bring the signal from the noise here on the Q and excuses. Rob Thomas, general manager, IBM Data and a I with an IBM Cube Alumni. Great to see you again. >> Great. There you go. >> You read a >> book yet? This year we've written ten books on a data. Your general manager. There's >> too much work. Not enough time >> for that's. Good sign. It means you're working hard. Okay. Give us give us the data here because a I anywhere in the center of the announcements we have a story up on. Slick earnings have been reported on CNBC. John Ford was here earlier talking to Ginny. This is a course centerpiece of it. Aye, aye. On any cloud. This highlights the data conversation you've been part of. Now, I think what seven years seems like more. But this is now happening. Give us your thoughts. >> Go back to basics. I've shared this with you before. There's no AI without IA, meaning you need an information architecture to support what you want to do in AI. We started looking into that. Our thesis became so clients are buying into that idea. The problem is their data is everywhere onpremise, private cloud, multiple public clouds. So our thesis became very simple. If we can bring AI to the data, it will make Watson the leading AI platform. So what we announced wtih Watson Anywhere is you could now have it wherever your data is public, private, any public cloud, build the models, run them where you want. I think it's gonna be amazing >> data everywhere and anywhere. So containers are big role in This is a little bit of a deb ops. The world you've been living in convergence of data cloud. How does that set for clients up? What are they need to know about this announcement? Was the impact of them if any >> way that we enable Multi Cloud and Watson anywhere is through IBM cloud private for data? That's our data Micro services architectural writing on Cooper Netease that gives you the portability so that it can run anywhere because, in addition Teo, I'd say, Aye, aye, ambitions. The other big client ambition is around how we modernize to cloud native architectures. Mohr compose herbal services, so the combination gets delivered. Is part of this. >> So this notion of you can't have a eye without a it's It's obviously a great tagline. You use it a lot, but it's super important because there's a gap between those who sort of have a I chops and those who don't. And if I understand what you're doing is you're closing that gap by allowing you to bring you call that a eye to the data is it's sort of a silo buster in regard. Er yeah, >> the model we use. I called the eye ladder. So they give it as all the levels of sophistication an organization needs to think about. From how you collect data, how you organize data, analyze data and then infused data with a I. That's kind of the model that we used to talk about. Talk to clients about that. What we're able to do here is same. You don't have to move your data. The biggest problem Modi projects is the first task is OK move a bunch of data that takes a lot of time. That takes a lot of money. We say you don't need to do that. Leave your data wherever it is. With Cloud private for data, we can virtualized data from any source. That's kind of the ah ha moment people have when they see that. So we're making that piece really >> easy. What's the impact this year and IBM? Think to the part product portfolio. You You had data products in the past. Now you got a eye products. Any changes? How should people live in the latter schism? A kind of a rubric or a view of where they fit into it? But what's up with the products and he changes? People should know about? >> Well, we've brought together the analytics and I units and IBM into this new organization we call Dayton ay, ay, that's a reflection of us. Seen that as two sides of the same coin. I really couldn't really keep them separate. We've really simplified how we're going to market with the Watson products. It's about how you build run Manager II watching studio Watson Machine Learning Watson Open scale. That's for clients that want to build their own. Aye, aye. For clients that wants something out of the box. They want an application. We've got Watson assistant for customer service. Watson Discovery, Watson Health Outset. So we've made it really easy to consume Watson. Whether you want to build your own or you want an application designed for the line of business and then up and down the data, stack a bunch of different announcements. We're bringing out big sequel on Cloudera as part of our evolving partnership with the new Cloudera Horn Works entity. Virtual Data Pipeline is a partnership that we've built with active fio, so we're doing things at all layers of the last. >> You're simplifying the consumption from a client, your customer perspective. It's all data. It's all Watson's, the umbrella for brand for everything underneath that from a tizzy, right? >> Yeah, Watson is the Aye, aye, brand. It is a technology that's having an impact. We have amazing clients on stage with this this week talking about, Hey, Eyes No longer. I'd like to say I was not magic. It's no longer this mystical thing. We have clients that are getting real outcomes. Who they II today we've got Rollback of Scotland talking about how they've automated and augmented forty percent of their customer service with watching the system. So we've got great clients talking about other using >> I today. You seen any patterns, rob in terms of those customers you mentioned, some customers want to do their own. Aye, aye. Some customers wanted out of the box. What? The patterns that you're seeing in terms of who wants to do their own. Aye. Aye. Why do they want to do their own, eh? I do. They get some kind of competitive advantage. So they have additional skill sets that they need. >> It's a >> It's a maker's mark. It is how I would describe it. There's a lot of people that want to make their own and try their own. Ugh. I think most organizations, they're gonna end up with hundreds of different tools for building for running. This is why we introduced Watson Open Scale at the end of last year. That's How would you manage all of your A II environments? What did they come from? IBM or not? Because you got the and the organization has to have this manageable. Understandable, regardless of which tool they're using. I would say the biggest impact that we see is when we pick a customer problem. That is widespread, and the number one right now is customer service. Every organization, regardless of industry, wants to do a better job of serving clients. That's why Watson assistant is taking off >> this's. Where? Data The value of real time data. Historical data kind of horizontally. Scaleable data, not silo data. We've talked us in the past. How important is to date a quality piece of this? Because you have real time and you have a historical date and everything in between that you had to bring to bear at low ladened psi applications. Now we're gonna have data embedded in them as a feature. Right. How does this change? The workloads? The makeup of you? Major customer services? One piece, the low hanging fruit. I get that. But this is a key thing. The data architecture more than anything, isn't it? >> It is. Now remember, there's there's two rungs at the bottom of the ladder on data collection. We have to build a collect data in any form in any type. That's why you've seen us do relationships with Mongo. D B. Were they ship? Obviously with Claude Era? We've got her own data warehouse, so we integrate all of that through our sequel engine. That thing gets to your point around. Are you gonna organize the data? How are you going to curate it? We've got data catalogue. Every client will have a data catalogue for many dollar data across. Clouds were now doing automated metadata creation using a I and machine learning So the organization peace. Once you've collected it than the organization, peace become most important. Certainly, if you want to get to self service analytics, you want to make data available to data scientists around the organization. You have to have those governance pieces. >> Talk about the ecosystem. One of the things that's been impressive IBM of the years is your partnerships. You've done good partners. Partnership of relationships now in an ecosystem is a lot of building blocks. There's more complexity requires software to distract him away. We get that. What's opportunities for you to create new relationships? Where are the upper opportunities for someone a developer or accompanied to engage with you guys? Where's the white spaces? Where is someone? Take advantage of your momentum and you're you're a vision. >> I am dying for partners that air doing domain specific industry specific applications to come have them run on IBM cloud private for data, which unleashes all the data they need to be a valuable application. We've already got a few of those data mirrors. One sensing is another one that air running now as industry applications on top of IBM Club private for data. I'd like to have a thousand of these. So all comers there. We announced a partnership with Red Hat back in May. Eventually, that became more than just a partnership. But that was about enabling Cloud Private, for data on red had open shift, So we're partnered at all layers of the stack. But the greatest customer need is give me an industry solution, leveraging the best of my data. That's why I'm really looking for Eyes V. Partners to run on Ivan clubs. >> What's your pitch to those guys? Why, why I should be going. >> There is no other data platform that will connect to all your data sources, whether they're on eight of us as your Google Cloud on premise. So if you believe data is important to your application. There's simply no better place to run than IBM. Claude Private for data >> in terms of functionality, breath o r. Everything >> well, integrating with all your data. Normally they have to have the application in five different places. We integrate with all the data we build the data catalogue. So the data's organized. So the ingestion of the data becomes very easy for the Iast V. And by the way, thirdly, IBM has got a pretty good reach. Globally, one hundred seventy countries, business partners, resellers all over the world, sales people all over the world. We will help you get your product to market. That's a pretty good value >> today. We talk about this in the Cube all the time. When the cloud came, one of the best things about the cloud wasn't allowed. People to put applications go there really quickly. Stand them up. Startups did that. But now, in this domain world of of data with the clouds scale, I think you're right. I think domain X expertise is the top of the stack where you need specially special ism expertise and you don't build the bottom half out. What you're getting at is of Europe. If you know how to create innovation in the business model, you could come in and innovate quickly >> and vertical APS don't scale enough for me. So that's why focus on horizontal things like customer service. But if you go talk to a bank, sometimes customer service is not in office. I want to do something in loan origination or you're in insurance company. I want to use their own underwriting those air, the solutions that will get a lot of value out of running on an integrated data start >> a thousand flowers. Bloom is kind of ecosystem opportunity. Looking forward to checking in on that. Thoughts on on gaps. For that you guys want to make you want to do em in a on or areas that you think you want to double down on. That might need some help, either organic innovation or emanate what areas you looking at. Can you share a little bit of direction on that? >> We have, >> ah, a unique benefit. And IBM because we have IBM research. One of their big announcement this week is what we call Auto Way I, which is basically automating the process of feature engineering algorithm selection, bringing that into Watson Studio and Watson Machine learning. I am spending most of my time figure out howto I continue to bring great technology out of IBM research and put in the hand of clients through our products. You guys solve the debaters stuff yesterday. We're just getting started with that. We've got some pretty exciting organic innovation happen in IBM. >> It's awesome. Great news for startups. Final question for you. For the folks watching who aren't here in San Francisco, what's the big story here? And IBM think here in San Francisco. Big event closing down the streets here in Howard Street. It's huge. What's the big story? What's the most important things happening? >> The most important thing to me and the customer stories >> here >> are unbelievable. I think we've gotten past this point of a eyes, some idea for the future we have. Hundreds of clients were talking about how they did an A I project, and here's the outcome they got. It's really encouraging to see what I encourage. All clients, though, is so build your strategy off of one big guy. Project company should be doing hundreds of Aye, aye projects. So in twenty nineteen do one hundred projects. Half of them will probably fail. That's okay. The one's that work will more than make up for the ones that don't work. So we're really encouraging mass experimentation. And I think the clients that air here are, you know, creating an aspirational thing for things >> just anecdotally you mentioned earlier. Customer service is a low hanging fruit. Other use cases that are great low hanging fruit opportunities for a >> data discovery data curation these air really hard manual task. Today you can start to automate some of that. That has a really big impact. >> Rob Thomas, general manager of the data and a I groupie with an IBM now part of a bigger portfolio. Watson Rob. Great to see you conventionally on all your success. But following you from the beginning. Great momentum on the right way. Thanks. Gradually. More cute coverage here. Live in San Francisco from Mosconi North. I'm John for Dave A lot. They stay with us for more coverage after this short break

>> Live from San Francisco. It's the cue covering IBM thing twenty nineteen brought to you by IBM. >> Clever and welcome to the live coverage here. The Cube in San Francisco for IBM. Think twenty nineteen day Volonte where he with Urban Krishna, senior vice president of cloud and cognitive software at IBM. Man in charge of all the cloud products cloud everywhere. Aye, aye. Anywhere are great to see you. Thanks for spending time. Know you're super busy. Thanks for spending time. >> I'm ready to be here right >> now. So we talked at the Red Hat Summit last year. You essentially laid out the vision for micro Services. Coup Burnett is how this always kind of coming together than the redhead acquisition. And now you're seeing big news here at IBM. Think setting the stage here in San Francisco for a I anywhere, which is cognitive kind of all over the clouds, and then really clarity around cloud multi cloud strategy end to end workloads all kind of tied together on premise in the clouds. Super important for IBM. Explain and unpacked that force. What does it mean, >> Right? So I'm going to begin unpacking it from where actually I left off last year. So if I just for ten seconds, last year, we talked a lot about containerized platforms are going to become the future that'll be the fabric on which every enterprise is going to build their IT and their future. OK, we talked about that last year, and I think with the announced acquisition of Red Hat that gets cemented and that'll go further once that closes. Now you take that and now you take it to the next level of value. So take Watson. Watson runs as a containerized set of services. If it's a containerized set of services, it could run on what we call Cloud Private. Cloud Private in turn runs on top of OpenShift. So then you say, wherever OpenShift runs, I can run this entire stack. Where does OpenShift run today? It runs on Amazon. It runs on the IBM cloud and runs on Azure. It runs on your premise. So on the simple simple. I always like things that are simple. So Watson runs on Cloud Private runs and OpenShift runs on all these infrastructures I just mentioned that gives you Watson anywhere. You want it close to your data run it on-prem. You want to run it on Azure, run it there. You want to run it on the IBM cloud you run it there. And hence that's the complete story. >> says it was more important for you to give customers choice >> than it was to keep Watson to yourself. To try to sell >> more cloud. >> I think that every company that survives a long term learns that choice to a customer is really important and forcing customers to do things only one way is jelly in the long term. A bad strategy. So >> from a customer statement, just get the facts right on the hard news. Watson. Anywhere. Now I can run Watson via containers. Asian Open ship Things you mentioned on a ws as sheer Microsoft azure and IBM cloud cloud private. All that >> on on premise >> and on premise, all cohesively enter end. >> Correct in an identical way. Which means even if you do things one place you build up more than one place, you could go deploy a moral in another place gives you that flexibility also. >> So I'm Akash Mercy over This sounds too crazy Is too hard to do that. I've tried all this multi cloud stuff. Got all this stuff. Why is it easier? How do how do you guys make this happen? What's the key secret sauce for pulling that end to end a I anywhere on multiple clouds, on premises and through the workloads. >> Two levels. One. We go to a container infrastructure as that common layer that isolates out what is the bottom infrastructure from everything that runs on top. So going to the common services on a Cuban Eddie's in a container layer that is common across all these environments, does the isolation off the bottom infrastructure? That's hard engineering, but we do that engineering. The second piece is you've taken the Watson set of capabilities and also put them into just three pieces. What's in studio? What's an ML from water machine learning and what's an open scale? And there you have the complete set that you go need to run everywhere. So we have done that engineering as well. >> Congratulations. Get the cloud anywhere. I mean, it's cloud. It's essentially everything's every anywhere. Now you got data everywhere you got cloud everywhere. Cloud operations. Where's the multi cloud and hybrid fit in? Because now, if I could do a I anywhere via container ization, shouldn't I built? Run any workload on premise and in multiple clouds. >> So we fundamentally believe that when I was here last time, we talked about the container fabrics. And I do believe that we need to get to the point where these can run anywhere. So you take the container fabric and you can go run that anywhere, right? So so that's one piece of it, the next part of is but I now need to integrate. So I now need to bring in all my pieces. How I integrate this application with another? It's the old problem of integration back again. So whether you want to use MQ or you want to use Kafka or you want to use one of these technologies? How do we get them to couple one work flow to another work flow? How do I get them to be secure? How do I get them to be resilient in the presence of crashes in the presence of latency and all that? So that's another big piece of announcements that we're making. You can take that complete set off integration technologies, and those can run anywhere on any cloud. Again, using the same partner describes. I'm not going to go into that again. And on premise. So you can knit all of those together. >> How can you talk about the rationale for the Red Hat acquisition? Specifically in the context of developers, IBM over the years has made you know many efforts took to court developers. Now, with the redhead acquisition, it's eight million developers and talk about specifically the importance of developers and how that's changed >> your strategy or enhance your >> strategy. I'm an enhancement. It's not really a change. I think we all acknowledge developers have always been important and will remain important. I mean, IBM has done a great job, I think, over the last twenty years and both helping create the whole developer ecosystem, for example, around Job. We were a very big piece of that, not the only participant in there. There were others, but we were a big piece of that. So you not take red hat on Lenox and Open shit and Open source and J. Boss and all of these technologies. There's a big ecosystem of developers. You mentioned eight million number. But why did that set of people come along? They come along because they get a lot of value from developing on top of something that in turn has so many other people on top. I think there's half a million pieces of software which use redhead as the primary infrastructure on which they develop. So it's the network effect really. Is that value andan Africa can only come from you, keep it open, You keep it running on the widest possible base, and then they get the value that if they develop on that digger access to that and US base on which Red Hat Franz >> are, we have >> evidence that >> totally makes sense. But I want to get one dig deeper that we cover a lot of developer, the business side of developers. Not so much, no ins and outs, so developer tools and stuff. There's a lot of stack overflow. Variety of sources do that, So developers want to things they want to be in the right wave. You laying out a great platform for that, then this monetization Amazon has seen massive growth on their partner network. You guys haven't ecosystem. You mentioned that. How does this anywhere philosophy impact ecosystem because they want to party with IBM? Where's the white spaces? What's the opportunity for partners? How should they evolve with IBM? What's your What's your direction on that? >> Okay, so two kinds of partners one there's a set of partners will bring a huge set of value to their clients because they actually provide the domain knowledge. The application specify acknowledged the management expertise, the operational expertise, printable technologies, perhaps that we provide. That's what a partner's is always gonna have. Value talked yesterday at a portable conference about what, cognizant? Who's a bigger part. They do. They built a self service application for patients off a medical provider to be able to get remote access to doctors when they couldn't get enough. And that was not life threatening immediately. Well, that's a huge sort of valley that they provide built on top of our technologies and products. A second kind of partner you went on developers is people who do open those packages. I think we've been quite good. We don't tend to cannibalize our partners, unlike some others we can talk about. So for those partners who have that value, we can put our investment in other places. But we could help maybe give access to the enterprise market for those developers, which I think opens up. A lot of you >> guys make the martyr for developers. That's right. I want to ask you a question. You guys are all sleep in all in on Cooper Netease. Red hat made a great bed on Cooper Netease on. Now that you're harvesting that with the requisition, huge growth there containers. Everyone saw containers. That was kind of a no brainer. Technical world developers are. What's the importance of uber Netease? As you see Kou Bernetti starting to shrink the abstraction software overlay. In the end, this new complexity where Cooper needs a running great value. What does that mean? This trend mean for CEOs CTO CSOs as enterprise start to think, you know, cohesive set of services across on Prem multiple clouds. Cooper Nettie seems to be a key point. What is the impact of it? What does it mean? >> I think I'll go to the business. Benefit Secure binaries. In the end is an orchestration. Later takes over management complexity. It takes away the cost of doing operations in a large cluster ofthe physical resource is, I think the value for the CIA level is the following today, on average, seventy percent of the total cost and people are tied up in maintaining what you have. Thirty percent is on new. That's rough rule of Tom Technologies like communities have taken to where we wanted to go and flipped out to thirty seventy. We need to spend only thirty percent maintaining what you have. And he could then go spend seventy percent on doing innovation, which is going to make inclined, happier and your business happier. Your team's had a couple of announcements today. One was hyper protect, and the other is a lot of services to facilitate. Hybrid. Can you talk about those brats up to date on a quick one, so hyper protect means. So where do you put your data in the cloud everybody gets worried about? Well, if it's in the clear, it could get stolen. C Togo to encryption. Typically, encryption is then down with the key. Well, who manages that cake? The hyper protect services are all about that key. Management is comin across. Both are getting hybrid world across both your premise and in the cloud. And nobody in the cloud, not even our deepest system administrator in the cloud, can get access to the key. That's pretty remarkable when you think about it, and so that provide the level of safety and encryption that should give you a lot of reassurance that nobody can get hold of that data that's hyper protect. And then if I go to all of the other services were doing, sometimes I see a lot of help. Someone advice. Look, in the three client meeting I just had every one of them was asking what should keep regarded watching I slightly more nice. What should I write knew? That means a whole lot of advice that you need and how to assess what you have in what should be a correct strategy. Then once you do that, somebody will say will help me move it. Others will say, Help me manage it So all the services to go do that is a big piece of what we're announcing it end and to end in addition to but into end. But also you can cover it up. Not only give me advice, I know I got buying strategy laid out, helping move it on Oprah's do boards for me or help you manage it after I move it except >> armor. When you sit in customer meetings. Big clients write me, and when they say we want to modernize, what does that mean to you? And how do you respond to that? >> Well, some organizes. Normally today it means that you've got to bring cloud technologies. You gotta bring air technologies. You got to bring what is called digital transformation all to bear. It's got to be in the service of either client intimacy, or it's got to be in terms ofthe doing straight through processing, as opposed to the old way of doing all the business processes that you have and then you get into always got to begin with some easy wind. So I always say, Begin with the easy stuff, not begin with the harder stuff. What started the architecture that let you do the hardest off later? It's not throw away, and those are all the discussions that we have, which are always a mixture of this people process technology. That world has not changed. We need to worry about. All >> three are thanks for spending your valuable time coming on the Q. Bree. We appreciate the insight. I know you're super busy. Final question. Take take a minute. To explain this year. Think What's the core theme? What's the most important story people should pay attention to this year and IBM think in San Francisco? >> I think this two things and the borders. That is the evolution that is giving greater business value for using the word that is Chapter two off the cloud journey. And it's Chapter two off a cognitive enterprise. Chapter two means that you're not getting into solving really mission critical workloads, and that's what is happening there. And that's enabled through the mixture of what we're calling hybrid on multi cloud strategies and then the cognitive enterprises all around. How can you bring air to power every workflow? It's not a little shiny Tonda. Besides, it's in the very heart off every confirmation. >> The word of the day. Here's anywhere cloud anywhere, data anywhere. Aye, aye, anywhere that's a cube were everywhere and anywhere we could go to get the signal from the noise. Arvin Krista, senior vice president, cloud and cognitive software's new title man Architect in the Red Hat Acquisition in the cloud Multi cloud DNA. Congratulations on your success. Looking forward to following your journey. Thanks for coming on, thanks Thanks. Safe. Okay. More live coverage after this short break state with the cube dot net is where you find the videos were in San Francisco. Live here in Mosconi, North and south, bringing the IBM think twenty nineteen. Stay with us.

>> Live from San Francisco, it's theCUBE. Covering IBM Think 2019. Brought to you by IBM. >> Welcome back to San Francisco, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante and I'm with my cohost, Stu Minman, Lisa Martin is also here. John Furrier'll be up tomorrow. This is day one of IBM Think. Kind of the pregame, Stu. The festivities kick off tomorrow, they're building out the Solutions Center, they got Howard Street takeover. We're in Moscone North, stop by and see us. Daniel Berg is here. He's a distinguished engineer with IBM Cloud Kubernetes service IBM, of course. Dan, great to see you again. >> Thank you. Thank you very much. >> Thanks for coming on. So everybody's got a Kubernetes story these days. What's IBM's Kubernetes story? >> So, IBM has taken a big bet on Kubernetes, two, two and a half years ago. Never really looked back, it's our primary foundation for our platform services. And we have two key distributions for the Kubernetes service, we have IBM Cloud Private, which is a software distribution for on premises, set up your own private cloud based on Kubernetes, behind your firewall. And then we have a manage service in the public cloud. So you're moving to public cloud, doing cloud native, grab an API, CLI, you get a cluster. >> So a lot of people think Kubernetes, oh, I can be able to move it anywhere, private cloud, public cloud. But there are other benefits of just, say, for instance, a private cloud. Maybe explain those. >> Yeah, I mean the biggest benefit for us is that we're able to give you the IBM cloud experience and IBM cloud content, so IBM content, middleware, things that you've been using for a decade. We've modernized it, put it in containers, install it and manage it on Kubernetes. The nice thing is that content, you can bring on premises where it's needed the most, and run it in ICP, IBM Cloud Private, and also take that and run it in our public cloud, as you migrate and move those workloads into the public sector. >> Dan, one of the things we've been watching is, you talk about a hybrid cloud or a multi-cloud world. There's a lot of pieces and it can be complicated. >> Yes. >> Now, Kubernetes itself, not exactly the simplest solution out there, but when you can deliver it as a service, but you can take a certain piece of your environment and IBM helps to simplify that. Maybe explain what it simplifies and, you know, what still are some of the hard places that we have to play at in these environments? >> Yeah, definitely. So, I mean, the IBM cloud Kubernetes service, we, anyone that has dealt with Kubernetes knows it's easy to install , pretty easy to set up, and basically easy to get started. It's the day two, it's the operations, it's the long pull. It's doing all the updates, the maintenance, the security patches, the securing it. Making it highly available, that's hard. And that's hard over time, and it takes a lot of resources. So IKS is a service that, we do that. Let the experts do it, is basically what we tell people. We are experts at managing Kubernetes. We do this as our day job, 24/7, right? Literally, because we manage a 24/7 service. So we operate it 24/7 and we keep it updated. That allows our customers to focus on their business problem. Focus on their app, not building the platform. But there are still some complexities, because you have, you don't have just one cluster. If you only had one cluster, it'd be no big deal. I probably wouldn't have a job. But you have many clusters. You've got development clusters, you've got test clusters. But if you're doing a global service, you've got many clusters throughout the world. Highly available clusters. You put clusters in various data centers for keeping your data in one location, right? So you've got many clusters, so it gets complicated to manage all of those clusters. So, with Kubernetes service we provide all the capabilities to manage and set up and secure your cluster, but then the content, like, moving and configuring things across all those clusters, becomes complicated. And that's where we released recently a new product called Multicloud Manager. >> Tell us, you know, tell us more. (laughter) >> I thought you were going to ask a question. (laughs) So, Multicloud Manager, what it basically does is it provides a control plane that allows you to manage, and today it manages resources, Kubernetes resources, across many different clouds, across many different cloud platforms. So it works with our Cloud Private, which runs on premises, but it also works with our public cloud, IKS. And it can work with other cloud providers, it can work with Amazon, it can work with Google, it can work with Azure. And it works with OpenShift, as well, obviously. So those, having that one tool, then, gives you the mechanism to drive consistency of the resources across all of those distribution of Kubernetes clusters that you have. And another big thing that it does, and it helps with, is security compliance. So it has ability to define security postures that you need to have across your clusters, and then apply it and run it in both a check mode, to see is that policy, or, provided across all your clusters, and where do you have gaps? And then it also has a setting to do enforcement. So, if it's not there, it'll make it there, it'll make it so. >> So, IBM hides all that complexity from the customer. >> Yes. >> But I'm curious as to what the conversations are like, Dan, with the customer. In other words, you're basically figuring out how to do it. Customer knows what it's doing. Do you ever get into a situation, no, of course, at scale you wan consistency and standards. So, do you ever get into a situation where a customer says, well, I'd like you to do it this way, and what's that conversation like? >> Yeah, so that's where, and that's where it's nice having multiple distributions, right? So having, so in our public cloud with IKS, having variations and unique configurations for each and every customer, I don't, we don't do that, right? It's a service. And services scale and provide value by doing consistency, right? So we consistently set up and manage clusters, thousands of, tens of thousands of clusters that way. But if you need something that's highly, highly specific to a given use case or you have differences in your infrastructure that you need to have more flexibility, that's where IBM Cloud Private comes in. And we do have customers like, especially on premises, right? On premises, those ae unique beasts, right? The infrastructure, the hardware, the network. You got to have a custom configuration. So coupling our ICP production with global services team, they can come in and they can customize it to suit any customer's needs. >> So, Dan, you talked about living in multiple environments, whether that be public cloud, your private cloud, you also mentioned Red Hat, I think, in there. Tell us where customers are today with OpenShift, where that fits, and give as a little bit compare contrast as to what IBM's doing today. >> Yeah, definitely. So, and it's interesting, watching what's hapepening in the industry, because there's the whole push to cloud, and everybody knows they want to get there, but trying to get there all in one fell swoop with all the workloads that you have on premises is quite complicated and difficult and almost impossible to do on day one. So, the story is all about how do I modernize what I have today, on premises? And how does IBM help with that in my journey to move into public cloud? And that's where, I know it's a buzzword, but hybrid cloud comes in. But for me, the hybrid cloud, and what our customers are saying, is that I want to modernize what I have, so give me a platform there. And ICP, IBM Cloud Private, and OpenShift are the two best products in the market, bar none, that provide that experience there. And our ICP runs on top of OpenShift, so for those customers that have already been invested in the OpenShift space, you still get the value of IBM's content and integrated monitoring, integrated logging, right there in that product space, on the platform for which they're already standardized. >> How do you define best? What are the attributes of high quality and best? >> So, I guess best is (laughs) kind of difficult to really define. But for us it's all about ensuring that we have a solid platform, a solid strategy and technology set that we're building our offerings from. And we gain a lot of experience from our public cloud. Because we built and standardized on Kubernetes, we provide Kubernetes service, and we do that at scale and secure as well as highly available. We take a lot of those same lessons, because we have hundreds of customers running on it at scale. We take those lessons and we help evolve our private cloud offering as well. So we bring those down, we provide a very tuned somewhat customizable, but, highly tuned supporting IBM content in that environment. So when I say best, it is definitely the best platform for running IBM content, right? It's tuned for running IBM content, bare none. >> Okay, and my other question is, you know, you'd mentioned hybrid, said it was a buzzword, okay, fine. But at least we know what hybrid is. You got resources on pram, you've got resources in the public cloud, multi cloud is the other buzzword. Sometimes we worry that companies that are, vendors like yourselves going after this multi cloud opportunity, which is, you know, clearly a large opportunity and one that's needed, because I want a consistent way of managing at scale. But there seems to be a lot of different initiatives within organizations. There might be different lines of business, there might be, you know, international people. Are you seeing any hope or sense that the customer constituents are getting together? The different constituents saying, hey, this is the strategy that we want to use to manage all of our clouds. Or is sort of, you know, fiefdoms that are popping up? What do you see there? >> Yeah, so it's funny, when you do go into a large organization, a large enterprise. You're having a conversation, they've made a choice down one path using, let's say, IKS as an example. But then you realize you're having another conversation with another group that hasn't made any choices. I don't think that within an organization, within a large enterprise, coming together and saying we're all going to go down one path with one tool to rule them all. I just don't, I just don't see it, right? And also, even just going down the path of saying, I'm only going to stick and use one cloud vendor. That's also somewhat a thing of the past, you don't see that anymore, at least where customers are moving, so within an organization, yes, you still have the lines of businesses, and they might have different tools and they might decide on different tools and how they manage their environments. But the thing that customers do need to look at, and what they do need to standardize across an enterprise, is just some of the core tenets and the core technologies. So, for example, if they're moving the cloud, whether it's one premises or off premises, what's the platform that you're going to build to so you have portability? It's got to be Kubernetes, right? That is a decision that as an organization, as an enterprise, you've got to agree on as you move forward. Because, whether you use the same provider or the same set of tools doesn't matter as much. It'd be nice. But you got to have some agreement on the core technologies and platforms. >> Because ultimately you can get there. It might be a little harder, but still, if you're core Kubernetes, it's not, it's going to be easier than different flavors of UNIOS, for example. (laughs) >> There's path, >> there's at least a path that as they mature and as they simplify and they converge, they can do that seamlessly. >> Dan, back to the cloud monitoring tool that IBM has. Who's the constituency, who uses that? And give us a little bit of color inside, you know, kind of the administrator, developer, you know cloud architect, you know, what do you see? >> Well, yeah, so that's a great one. The cloud monitoring, IBM cloud monitoring provides visibility into your workloads within your environment. And that's not specific to just Kubernetes, either, right? There's Kubernetes, but then there's VMs and bare metal workloads, more traditional workloads that the monitoring service works just fine. The, our developers, have to have a monitoring solution. You can't build a cloud native solution without monitoring, right? Monitoring and log, they, it's like peanut butter and jelly. You got to have 'em. And if you're building a cloud native solution, you're building Kubernetes, you're dealing with multiple clusters, like I said earlier. Hundreds, if not thousands, of workloads. You can't log into each one of 'em. You need, you need a system where you can monitor and log. So the monitoring service is necessary here for simple developers to understand what's happening in their environment. And our partnership STEG provides us with a very rich monitoring solution, which we've done extensive integration in IBM cloud to make it simple for even developers. They don't have to go and install and set up STEG themselves. All they do is a simple I want a new instance. Directly in the IBM cloud catalog they get a new instance of STEG and it gets installed into their cluster and they're off and running. Simple as that. >> And we're talking, we're talking visibility on things like performance management, security? >> Network. >> Problem, change management. >> Yes, yes, absolutely. So you get, and obviously that's all configurable, but what's nice with STEG and one of the reasons I like it, especially as a developer, as soon as you turn it on for one of your clusters, there's so much rich data that's available there, just out of the box. And they support other projects too and provide integration, deep integration, like the Istio project, for example. Great little project for service mesh. STEG supports that out of the box as well. Built in polling metrics, dashboards built specifically for Istio, and I don't have to do anything as a developer. I just turn it on, and then I start watching. (laughs) Seeing all the metrics coming. >> So it's kind of day zero here at IBM Think. Dan, what are some of the things that you're hoping to accomplish this week? I know you've got a bunch of customer meetings. Some of the things you're excited about. >> Yeah, definitely, lots of sessions, great sessions. But it is the customer meetings I'm most excited about. I have a large number of 'em. I want to hear what they're doing, right? I want to understand a little bit better what they would like us to do, and moving forward, how can we help them? How can we help accelerate their adoption of cloud? Get on the cloud native, and obviously, I'm here to talk Kubernetes and containers, so the more I get to talk about that, the happier I'm going to be. >> Well, it's a hot space. We're bringing you theCUBE inside of our little container here. Dan Berg, thanks very much for coming on today. >> Thank you. >> All right, Dave Vellante for Stu Miniman. You're watching theCUBE from IBM Think, day one. We'll be right back right after this short break. (light music)

>> Live from Seattle, Washington it's theCUBE covering KubeCon and CloudNativeCon North America 2018 brought to you by Red Hat the Cloud Native Computing Foundation and it's Ecosystem Partners. >> Well, everyone welcome back to theCube's live coverage here in Seattle for KubeCon and CloudNativeCon 2018. I'm John Furrier with Stu Miniman. Three days of coverage around the Cloud Native growth, around the Ecosystem around open source, and the role of micro servers in the cloud. Our next guest is Roland Barcia who's the IBM Distinguished Engineer for IBM's Hybrid Cloud. Welcome to theCube. >> Thank you, glad to be here. >> Thanks for joining us. Being a Distinguished Engineer of IBM is a pretty big honor so congratulations. >> Thank you. >> it means you got technical chops so we can get down and dirty if we want to. >> Sure. >> I want to get your take on this because a lot of companies in IT are transforming and then that's been called digital transformation, it's happening and cloud has developed scale. And the wish list if you had the magic wand that could make things do better is actually happening. Supernetting's actually creating some goodness that if you had the magic wand, if I asked that question three years ago, if you had a magic wand what would an environment look like? Seamless operations around the cloud, so it's kind of happening. How are you guys positioned for this? Talk about the IBM cloud, what you're doing here, and how you see this cloud native market exploding. It's almost 8,000 people here up from 4,000 last year. >> Yeah, that's a great question I think. I work a lot with our enterprise clients. I'm part of what's called the IBM Cloud Garage, so I'm very customer facing. And often times, we're seeing that there is different paces of a journey. And so for example, I worked with a client that started building a cloud native application. They built about 60 micro services. And at the end of that, they were deploying it as one job which means they defeated the whole purpose of micro service architecture. And so what we really need to think about is an end to end journey. I think the developers are probably the more modern role in an enterprise, but we're starting to see modernization of an operations team for example, and adopting culture, and cutting down the walls of IT organizational groups into mixed squads, adopting something like a Spotify model. And I think a lot of the challenges in adopting kubernetes is really in cultural aspects and in enterprise. Does that make sense? >> Yeah. And because network guys are different than the app guys, and now they have policy knobs on kubernetes they can play with. Network guys love policy. >> Yeah, and they're fighting over ownership, right? >> Roland indeed. We look at that modernization, the application modernization really is that long home intent. And what we hear here is you need to be able to meet customers where they are. Sure, there's some stuff they're building shiny and new and have the developers, but enterprises have a lot of application and therefore there's a grand spectrum. What do you hear from customers? What's the easy part and where's the parts they're getting stuck? >> Yeah, so I think the easy part is writing the application. I think where they're getting stuck is really scaling it to the enterprise, doing the operations, doing the DevOps. I always tell people that a modernization journey might be better started by taking a certain class of applications like middleware where we have a WebSphere heritage from IBM, and saying why don't we take a look at containerizing that. We've built tools like Transformation Advisor that'll scan your WebSphere applications and tell you what do you need to change in that middleware application to make it behave well in a containerized platform. Then from there, you build your DevOps engine, your DevOps pipeline and you really start to get your operations teams going in delivering containers, delivering applications as containers. And then getting your policies and your standards in place. Then you can start opening up around innovation and start really driving towards building cloud native new applications in addition to that. >> One of those areas we've been talking about in the industry for decades is automation. The conversation's a little bit different these days. Maybe you can bring us up to speed about what's different than say it was earlier days. >> Yeah, I think IT organizations have always done a bit of automation. I think they write scripts, they automate builds. I think the mantra that I use is automate everything, right? Organizations need to really start to automate in a new way. How I deliver containers, but delivering the app is not enough. I need to automate all levels of testing in a modern way. Test driven development is big. At the IBM Cloud Garage, we have something we call the IBM Cloud Garage Method which really takes a set of practices like test driven development, pair programming, things out of lean startup, extreme programming, and really start to help enterprises adopt those practices. So I say why can't we automate end to end performance testing in the pipeline, and functional testing, and writing them early and in the beginning of projects? That way, as I'm deploying containers which are very dynamic, along with configuration, and along with policy you're testing it continuously. And I think that level of automation is what we need to get to. >> Talk about security as well 'cause security's one of those things where it's got to be baked in upfront. You got to think about it holistically. It's also now being pulled out of IT, it's more of a board function because the risk management is one hack you could get crushed. And so you got to have security. And the container there's a security boundary issue, so it's important. >> Last week we met with an insurance company. We did a workshop. And they walked us through all the compliant steps that they need to go through today. How they do it with traditional middleware and virtual machines and hardware and it was a very, what I'm going to say governance driven process. And so a lot of checks and balances, stop don't move forward, which is really the industry for developing and innovating is going the opposite way: self service and enabling. And there's a lot of risk with that. And so what we're really trying to do with technology is like Multicloud Manager, technology we have around multicluster, management is how do I do things like I want to check which clusters are Hipaa compliant and which ones are out. How do i force that policy? >> That's smart. >> Now that everything is software driven, software developed, there's an opportunity to really automate those checks. >> So your point automate everything. >> Yeah, I want to automate everything. >> Governance is a service. (laughing) >> Yeah, that's right. And actually, that can help get away from error prone human checks where they had all these tons of documents of all different policies they have to go through can now be automated in a seamless way. >> So compliance and governance could be a stumbling block or it can be just part of the software. That's what you're getting at here. >> That's right, that's what I'm getting at. I think the transition is look at it as an opportunity now that everything is software driven, use software disciplines that developers are used to in those security roles and those CSO roles, etc. >> So I want to ask you a question. So one of the things we're seeing obviously with the cloud is it's great for certain things, and then on premises it has latency issues. We saw Amazon essentially endorse this by saying RDS on VMware on premises. They announced Outpost had reinvent oh, latency. Things aren't moving into the cloud as fast. So you're going to see this hybrid environment. So hybrids, we get that, it's been around, check. No real discussion other than it's happening. The real trend is multicloud, right? >> That' right. >> And so multicloud is just a modern version of the word multi vendor about the client server days. So systems were a multi vendor man choice. This is a fundamental thing. It's not so much about multicloud as it is about choice. How do you guys see that? You are in an environment where you have a lot of customers who don't have one cloud, so this is a big upcoming trend in 2019. >> Most of our clients have at least five different clouds that they deal with, whether it be an IaaS, a PaaS, a SaaS base solution. What we're seeing as a trend is we talked about on premise and private and enterprise is I think is 80% of workloads are still in the data center. And so they want to build that private cloud environment as a transitionary point to public, but what we're seeing across the multicloud space is I'm going to say a new integration space. So if you really think 15 years ago, SOA and enterprise service bosses in a very centralized fashion, I think there's a new opportunity for integration across clouds and on-prem in a more decentralized way. So I think integration is kind of the next trend that we're seeing in this multicloud space because the new applications that we're seeing with cognitive data AI are mixing data sources from multiple clouds and on-prem and needing to control that in a hybrid control plane is key. >> It's funny, the industry always talks about these buzzwords, multicloud. If we're talkin' about multicloud, then it's a problem. The idea of infrastructure as code it's not even use the word multicloud. I mean, if you think about it, if you're programming the infrastructure and enabling the stuff under the covers, why even talk about cloud? It should be automated, so that's the future state, but in reality, that's kind of what enterprisers are tryin' to think about. >> They are, and I think it's a tension between innovation and moving fast and control, right? The enterprisers want to move fast, but they want to make sure that they don't break security protocol, that they don't break resiliency that they're maybe have used to with their existing customers and applications. I do think the challenge is how operations teams and management teams start to act like developers to get to that point. And I think that's part of the journey. >> Open source obviously a big part of this show, and that's open source, people contribute upstream It's great stuff. IBM is a big contributor, and it'll be even more when Red Hat gets into the mix. So upstream's great, but as you got 8,000 people here, you're startin' to see people talkin' about business issues, and other things. One of the downstream impacts of this conference being so open source centric is the IT equation and then just the classic developer. So you have multiple personas now kind of interacting. You got the developer, you got the IT architect, cloud architect pro whatever, and then you got the open source community members. Melting pot: good, challenges, thoughts? >> So I think it's so developers love that, right? I think from an enterprise perspective, there are issues. We're seeing a lot of our clients with our private cloud platform ask us to build out what's called air gapped environment which is how do I build up an open source style ecosystem within my enterprise. So things like getting an artifactory registry or a Docker registry or whatever type of registry where I get certified, open source packages in my enterprise that I've gone and done security vulnerability scans with, or that I've made sure that I look at every layer from the Linux kernel all the way up to whatever software is included. So what we're seeing is how do I open the aperture a bit, but do it in a more responsible fashion I think is the key. >> Yeah, and that's for stability, right? So Stu, one of things I've been talkin' about and want to get your thoughts on this role is that you got the cloud as a scalable system then one of the things that's being discussed in Silicon Valley now for the first time, we've been sitting on theCube for years, is the cloud's a system. It's just some architecture, it's network distributing, computing, art paradigm, all that computer science has been around for awhile, right? >> Yes, yes. >> So if you've been a systems person whether hardware or whatever, operating systems, you get cloud. But also you got the horizontal specialism of applications that are using machine learning and data and applications which is unique on top. So you have the collision of those two worlds. This is kind of a modern version of two worlds that we used to call systems and apps, but they're happening in a real dynamic way. What's your thoughts on this? Because you got the benefits of horizontally scalable cloud and you now have the ability to power that so we're seeing things like AI, which has been around for a long, long time, have a renaissance because now you got a lot of compute. >> That's right, and I think data is the real big challenge we're seeing with a lot of our clients. They have a lot of it in their enterprise, they don't want to unlock it all right away. We recently did what's called IBM Cloud Private for Data, in which we brought in a set of technologies around our AI, our Watson core to really start leveraging some of those tools in a private manner. And then what we're seeing is a lot of applications that are moving to the cloud have a data drag. It might start as something as simple as caching data and no SQL databases, but very quickly they want to learn a lot more about that data. So we're seeing that mix happening all the time. >> We've had it, we've had someone say in theCube ML's the new SQL. >> Yeah. >> Because you're starting to see SQL abstraction layers are a beautiful thing if they're connected. So I want to get your thoughts on this because everyone's kind of in discovery mode right now. Learning, there's a lot of education. I mean, we're talkin' about real, big time players. Architects are becoming cloud architects. Sysadmins are becoming operators for large infrastructure scale. You see network guys goin' wait a minute, if I don't get on the new network programmable model I'm going to be irrelevant. So a lot of persona changes in the enterprise. How are you guys handling that with customers? I know you guys have the expert program. Comment on that dynamic. >> I think what we're doing is we use the IBM Cloud Garage to bring in practices like the Spotify method where we start pushing things like >> What's the Spotify method? >> Spotify method is a way of doing kind of development where rather than having your disciplines of architects, development, operations, we're now splitting teams, let's say functionally, where I have mixed disciplines in a squad and maybe saying hey, the person building the account team has an SRE, an ops guy, a dev guy all within their same squad. And then maybe have guilds across disciplines, right? And so what we do at the Garage is we bring 'em in to one of the Garages. We have four team locations worldwide. Maybe do your first project. Then we build enablement and education around that, bring it back to the enterprise and start making that viral. And that's what we're doing in the IBM Cloud Garage. >> So not a monolithic thing, breakin' it down, integrating multiple disciplines, kind of like a playlist. >> Yeah, that's right. And I think the best way to do it is to practice it, right, in action. Let's pick a project rather than talking about it. >> If I had to ask you in 2019, what is the IT investment going to look like with kubernetes impact? How does kubernetes change the IT priorities and investments for an enterprise? >> Yeah, so I think you'll see kubernetes become a vehicle for enterprises to deliver content. So one, the whole area around helm and other package managers as a way to bundle software. I think as people build more clusters, multicluster management is going to be the big trend of how do I deal now with clusters that I have in public cloud and private cloud, all different clouds? And I think that integration layer that I talked about where what does modern integration look like across kubernetes based applications. >> Someone asked me last week at Reinvent hey, can't we just automate kubernetes? And then I was like, well it's kind of automated now. What's your thoughts on that? >> So I think when someone asks a question what does it mean to automate that I think the kubernetes stack really sits on top of IaaS infrastructure. And so for example, our IBM Cloud Private you can run it on zLinux or Power. And we have a lot of IBM folks that run multi architecture clusters. And therefore, they still need a level of automating how I create clusters over IaaS and there's technologies like Terraform and others that help with that, but then there's also automating standing up the DevOps stack, automating deployment of the applications over that stack. And I think they mean automating how I use kubernetes in an environment. >> So 2019, the year of programmability and automation creating goodness around kubernetes. >> Yeah, absolutely, >> Roland, thanks for comin' >> Thank you, it was great. >> on theCube, thanks for that smart insight. TheCube coverage here, day two winding down. We got day three tomorrow. This is theCube covering KubeCon and CloudNativeCon 2018. We'll be right back with more day two coverage after this short break. (happy electronic music)

(upbeat techo music) >> Covering Kubecon and CloudNativeCon North America 2018 brought to you by RedHat, The Cloud Native Computing Foundation, and its ecosystem partners. (upbeat techno music) >> Okay welcome back everyone, we're live here in Seattle for KubeCon 2018, CloudNativeCon, I'm John Furrier with theCUBE coverage, three days. Our next guest is Chris Rosen who's the Program Director for Offering Management, for Kubernetes, IBM's Kubernetes Service. Chris, welcome to theCUBE thanks for joining us. >> Thank you very much, glad to be here. >> We always love covering IBM. Think is coming up this year. It's going to be in San Francisco. Want to get that out there because we're psyched it's in our backyard. It's always been in Vegas. We've been covering IBM's events for a long time. We've seen the evolution of Cloud, you know, Bluemix, SoftLayer all coming together. Kubernetes, actually the timing of Kubernetes couldn't have been better. >> Absolutely. >> With all the software investments in Bluemix, all the customers that you guys have, now with scale and choice with CNCF. Kind of a perfect storm for you guys, explain kind of what's going on, your role and how it's all kind of clicking together. >> Sure, so it is, you're exactly right it's an exciting time to be there. There's a lot of change. Everyone here at the conference, so excited there is so much new going on. About 2 1/2 years ago, IBM went all in on Kubernetes for our Cloud as well as for on-prem offerings to leverage and provide flexibility, portability, eliminating vendor lock-in, all those things that our customers asked us for and then adding capabilities on top of it. So, we are really excited to kind of grow and participate in the ecosystem. >> So, I hear a lot of people talk about Kubernetes. First of all, we love covering it, but the language around what is Kubernetes, they're even doing children's books, stories, trying to break it down. The rise of Kubernetes kind of has gone mainstream, but I hear things like the Kubernetes stack, the CNCF stack. I mean, it's not necessarily a stack per se. Could you break down, 'cause a lot of people are going to CNCF for a variety of other things. >> Right. >> With Kubernetes, at the core, describe how you talk to customers, how do you explain it. Unpack the positioning of Kubernetes at the core, and the CNCF offerings, or what do people call it? The stack, the CNCF stack? Or, how does this all break down? >> Yeah, so you're right. It's a very complex stack and that's where the complexity comes in that we're trying to eliminate for our customers is to simplify managing that stack. So, at the top of the stack, of course we've got Kubernetes for the orchestration layer. Below that, we've got the engine. We're using containerd now but we also have Prometheus, Fluentd, Calico, it's a very complex stack. And, when you think about managing that and a new version comes out from Kubernetes, how does that effect anything else in that stack? >> Chris, wonder if you can explain a little bit what IBM's doing here because some people I've heard, they've said, ah, there's like over 70 different you know, platforms with Kubernetes, oh they're all trying to sell me a Kubernetes distribution. >> Right. >> I don't believe that's the case. So, maybe you just explain what bakes into your products, what IBM bakes into the community. >> Right. >> And your role, yeah. >> Well, you're exactly right. So we're not forking and doing anything IBM-esk with Kubernetes. >> Right We have core maintainers that live out there. That's their job, is to focus upstream. We think that's very important to be agnostic and to participate in these communities. Now, what we do is, we build our solutions on top of these open source projects, adding value, simplifying the management of those solutions. So, you think about the CNCF conformance testing, IBM participates. We typically are the first public cloud to add support for a new version of Kubernetes. So we're really excited to do that, and the only way we can do that is by actively participating in the community. >> The upstream dynamic is important. Just talk about that for a second because this is, I think why one of the reasons it's been so successful is the upstream contribution is not your IBM perspective, it's just pure contribution for the benefit of the community then downstream, you guys are productizing that piece. >> Right. >> That is kind of, that is the purpose of open source. >> Exactly, exactly, and you hear time and time again at these conferences that the power of the community is so much greater than one individual company. So, let's work together as a community, build that solid foundation at the open source level and then IBM's going to add things that we think are differentiating and unique to our offering. >> What's the number one end-user conversation, problem that's being solved with the evolution of CNCF and Kubernetes at the core? Obviously, choice is one, but when specifically as you talk to customers, what is the big nead? What's the conversations like? Can you share some input into, insight into the customer equation? >> Probably the biggest request is around security, and that's a couple of fronts. One, maybe this is my first step into public cloud, so how do I ensure, in a multi-tenant world, that I am secure in isolation and all of those things. But then also, thinking about maybe I'm just starting with containers and microservices. So, this is a completely different mental paradigm in how I'm developing code, running code, and to explain to them how IBM is helping simplify that security aspect along that entire journey. >> So talk about the auto-scaling security piece, because, again, the touch points, it's interesting about Cloud, the entry point is multiple avenues for a customer could be workload, portability. It could be for a native application in the Cloud. Where's the scale come in? How do you guys see the scale picture developing? >> Right, so again, scaling comes kind of two factors. One, Pod Autoscaling from Kubernetes. So, you can define, let your application scale out when it needs to, but then there is also the Infrastructure side. So, I need to be able to set parameters to scale up when I need to and then scale back down to kind of meet my requirements as well as managing my cost. >> Well IBM Think's coming up on February 15th, just a plug for theCUBE. We'll be there, obviously register but IBM Think is a big conference. How much of Kubernetes will be at the center of IBM Think? >> Kubernetes will be a huge part at Think. We encourage everyone listening to come sign up and join us. There will be a range from hands-on for your Developer focus or your Operators. We'll have much larger business benefits for our C-level participants. So, a lot of activities, a lot of fun, a lot to learn at IBM Think 2019 in San Francisco. >> What's the biggest story here at KubeCon, CloudNative conference for the folks not here, or watching, or maybe are wait-listed in the lobby-con (Chris laughs) that's happening in Seattle? What's the biggest story? >> The biggest story is the vibrant ecosystem. When you look at the amount of people that are here, the chatter, the booths are packed, the sessions are packed, the keynotes are packed. It's great, everyone wants to share a story, learn from each other. It's a fantastic community to be a part of. >> I got to ask you the programmability piece, because, one of the things that people look for is virtual private networks, they're using VPNing, they want to take VPNs to the next level, SD-WAN, super-hot trend that's kicking back up, people want to program networks. >> Right. >> They don't want to have to actually provision networks anymore. this is DevOps but now it's also the network layer. Storage and compute looking good? >> Right. >> Network is evolving, how do you guys see that picture? Can you comment on that, it's a hot area. I just want to get your perspective. >> Yeah, definitely evolving just like the rest of the space. So, we are excited to work with various vendors here. IBM has our own point of view of what virtual private cloud means supporting, bring your own IP, private end-points, private cluster, so that way, if I only want connectivity inside my backbone network, I can configure my networks that way, creating a VPN tunnel back to my resources on-prem, and just have it completely isolated from the rest of the world. >> You see a lot of on-premises activity, Azure stack, Amazon announces this Outposts Cloud Sys supposed to be about a year away, and their whole message is latency. >> Right. >> Workloads need certain things, some of them need low-latency. >> Right. >> Some need more security. Just a, is that just a course of business now, that customers have to have these diverse sets of needs met? >> Absolutely, so IBM has two offerings, IBM Cloud Private for on-prem with multi-cloud manager that's really focused at managing in that hybrid or multi-cloud world. How do we simplify resources that are running on-prem, IBM Cloud, other Clouds, and how do we do so efficiently? So, we definitely see a lot of hybrid, hybrid architectures, whether that's on-prem to IBM Cloud, IBM Cloud to other Clouds, and latency really becomes a minimal factor. >> And what's your to do list on Kubernetes as you look at this event, obviously continuing to grow, the international piece is pretty compelling as well, growth in China, we're seeing that. What's your plans for IBM Kubernetes offering, what's the roadmap look like, what can you share some insight into what's next for you guys? >> Absolutely, so we're definitely focused on security, continues to be paramount, even though we think we are a very secure offering already, but continuing to expand on that. The private endpoints that I mentioned, the private connectivity, isolating network traffic is a huge piece of it, staying compliant and up to date with Kubernetes versions as they come out, making sure that they're scalable, performant, upgradeable, and then making those available to our users. >> IBM continuing to transform obviously the big news we saw with the RedHat acquisition, you know, obviously you've been in the Cloud for a while, everyone knows that with Bluemix, maybe not get to know as much work that went into Bluemix for instance, a lot of great stuff. You guys have built, you know, the Developer side within Cloud. IBM Think is February 15th, it's going to be in San Francisco. theCUBE will be there. Check these guys out. They're going to have a lot of workshops we're excited to see how the evolution of IBM and IBM Cloud continues. Chris coming on theCUBE, appreciate it. >> Thank you very much. >> theCUBE coverage, I'm John Furrier, Stu Miniman, stay with us for more coverage, here in Seattle, after this short break. (upbeat techno music)

(digital music) >> From Yorktown Heights, New York It's theCUBE! Covering IBM Cloud Innovation Day. Brought to you by IBM. >> Hi, it's Wikibon's Peter Burris again. We're broadcasting on The Cube from IBM Innovation Day at the Thomas J Watson Research Laboratory in Yorktown Heights, New York. Have a number of great conversations, and we got a great one right now. Rob Thomas, who's the General Manager of IBM Analytics, welcome back to theCUBE. >> Thanks Peter, great to see you. Thanks for coming out here to the woods. >> Oh, well it's not that bad. I actually live not to far from here. Interesting Rob, I was driving up the Taconic Parkway and I realized I hadn't been on it in 40 years, so. >> Is that right? (laugh) >> Very exciting. So Rob let's talk IBM analytics and some of the changes that are taking place. Specifically, how are customers thinking about achieving their AI outcomes. What's that ladder look like? >> Yeah. We call it the AI ladder. Which is basically all the steps that a client has to take to get to get to an AI future, is the best way I would describe it. From how you collect data, to how you organize your data. How you analyze your data, start to put machine learning into motion. How you infuse your data, meaning you can take any insights, infuse it into other applications. Those are the basic building blocks of this laddered AI. 81 percent of clients that start to do something with AI, they realize their first issue is a data issue. They can't find the data, they don't have the data. The AI ladder's about taking care of the data problem so you can focus on where the value is, the AI pieces. >> So, AI is a pretty broad, hairy topic today. What are customers learning about AI? What kind of experience are they gaining? How is it sharpening their thoughts and their pencils, as they think about what kind of outcomes they want to achieve? >> You know, its... For some reason, it's a bit of a mystical topic, but to me AI is actually quite simple. I'd like to say AI is not magic. Some people think it's a magical black box. You just, you know, put a few inputs in, you sit around and magic happens. It's not that, it's real work, it's real computer science. It's about how do I put, you know, how do I build models? Put models into production? Most models, when they go into production, are not that good, so how do I continually train and retrain those models? Then the AI aspect is about how do I bring human features to that? How do I integrate that with natural language, or with speech recognition, or with image recognition. So, when you get under the covers, it's actually not that mystical. It's about basic building blocks that help you start to achieve business outcomes. >> It's got to be very practical, otherwise the business has a hard time ultimately adopting it, but you mentioned a number of different... I especially like the 'add the human features' to it of the natural language. It also suggests that the skill set of AI starts to evolve as companies mature up this ladder. How is that starting to change? >> That's still one of the biggest gaps, I would say. Skill sets around the modern languages of data science that lead to AI: Python, AR, Scala, as an example of a few. That's still a bit of a gap. Our focus has been how do we make tools that anybody can use. So if you've grown up doing SPSS or SaaS, something like that, how do you adopt those skills for the open world of data science? That can make a big difference. On the human features point, we've actually built applications to try to make that piece easy. Great example is with Royal Bank of Scotland where we've created a solution called Watson Assistant which is basically how do we arm their call center representatives to be much more intelligent and engaging with clients, predicting what clients may do. Those types of applications package up the human features and the components I talked about, makes it really easy to get AI into production. >> Now many years ago, the genius Turing, noted the notion of the Turing machine where you couldn't tell the difference between the human and a machine from an engagement standpoint. We're actually starting to see that happen in some important ways. You mentioned the call center. >> Yep. >> How are technologies and agency coming together? By that I mean, the rate at which businesses are actually applying AI to act as an agent for them in front of customers? >> I think it's slow. What I encourage clients to do is, you have to do a massive number of experiments. So don't talk to me about the one or two AI projects you're doing, I'm thinking like hundreds. I was with a bank last week in Japan, and they're comment was in the last year they've done a hundred different AI projects. These are not one year long projects with hundreds of people. It's like, let's do a bunch of small experiments. You have to be comfortable that probably half of your experiments are going to fail, that's okay. The goal is how do you increase your win rate. Do you learn from the ones that work, and from the ones that don't work, so that you can apply those. This is all, to me at this stage, is about experimentation. Any enterprise right now, has to be thinking in terms of hundreds of experiments, not one, not two or 'Hey, should we do that project?' Think in terms of hundreds of experiments. You're going to learn a lot when you do that. >> But as you said earlier, AI is not magic and it's grounded in something, and it's increasingly obvious that it's grounded in analytics. So what is the relationship between AI analytics, and what types of analytics are capable of creating value independent of AI? >> So if you think about how I kind of decomposed AI, talked about human features, I talked about, it kind of starts with a model, you train the model. The model is only as good as the data that you feed it. So, that assumes that one, that your data's not locked into a bunch of different silos. It assumes that your data is actually governed. You have a data catalog or that type of capability. If you have those basics in place, once you have a single instantiation of your data, it becomes very easy to train models, and you can find that the more that you feed it, the better the model's going to get, the better your business outcomes are going to get. That's our whole strategy around IBM Cloud Private for Data. Basically, one environment, a console for all your data, build a model here, train it in all your data, no matter where it is, it's pretty powerful. >> Let me pick up on that where it is, 'cause it's becoming increasingly obvious, at least to us and our clients, that the world is not going to move all the data over to a central location. The data is going to be increasingly distributed closer to the sources, closer to where the action is. How does AI and that notion of increasing distributed data going to work together for clients. >> So we've just released what's called IBM Data Virtualization this month, and it is a leapfrog in terms of data virtualization technology. So the idea is leave your data where ever it is, it could be in a data center, it could be on a different data center, it could be on an automobile if you're an automobile manufacturer. We can federate data from anywhere, take advantage of processing power on the edge. So we're breaking down that problem. Which is, the initial analytics problem was before I do this I've got to bring all my data to one place. It's not a good use of money. It's a lot of time and it's a lot of money. So we're saying leave your data where it is, we will virtualize your data from wherever it may be. >> That's really cool. What was it called again? >> IBM Data Virtualization and it's part of IBM Cloud Private for Data. It's a feature in that. >> Excellent, so one last question Rob. February's coming up, IBM Think San Francisco thirty plus thousand people, what kind of conversations do you anticipate having with you customers, your partners, as they try to learn, experiment, take away actions that they can take to achieve their outcomes? >> I want to have this AI experimentation discussion. I will be encouraging every client, let's talk about hundreds of experiments not 5. Let's talk about what we can get started on now. Technology's incredibly cheap to get started and do something, and it's all about rate and pace, and trying a bunch of things. That's what I'm going to be encouraging. The clients that you're going to see on stage there are the ones that have adopted this mentality in the last year and they've got some great successes to show. >> Rob Thomas, general manager IBM Analytics, thanks again for being on theCUBE. >> Thanks Peter. >> Once again this is Peter Buriss of Wikibon, from IBM Innovation Day, Thomas J Watson Research Center. We'll be back in a moment. (techno beat)

>> Live from Boston, it's theCUBE covering IBM Chief Data Officer Summit. Brought to you by IBM. >> Welcome back everyone to theCUBE's live coverage of the IBM CDO Summit here in beautiful Boston, Massachusetts. I'm your host, Rebecca Knight, along with my co-host Paul Gillin. We have two guests for this segment, we have Susan Wagner, who is the VP Data Artificial Intelligence and Governance at Deutsche Telekom and Madhu Kochar, whose the Vice President Analytics Product Development at IBM. Thank you so much for coming on the show. >> Thank you. >> Happy to be here. Susan you're coming to us from Berlin, tell us a little bit about what you it's a relatively new job title and Paul was marveling before the cameras are rolling. Do you have artificial intelligence in your job title? Tell us a little bit about what you do at Deutsche Telekom. >> So we have a long history, working with data and this is a central role in the headquarter guiding the different data and artificial intelligence activities within Deutsche Telekom. So we have different countries, different business units, we have activities there. We have already use case catalog of 300,000 cases there and from a central point we are looking at it and saying, how are we able really to get the business benefit out of it. So we are looking at the different product, the different cases and looking for some help for the business units, how to scale things. For example, we have a case we implemented in one of our countries, it was about a call center to predict if someone calls the call center, if this is a problem, we would never have(laughing) at Deutsche Telekom but it could happen and then we open a ticket and we are working on it and then we're closing that ticket and but the problem is not solved, so the ticket comes again and the customer will call again and this is very bad for us bad for the customer and we did on AI project, there predicting what kind of tickets will come back in future and this we implemented in a way that we are able to use it not only in one country, but really give it to the next country. So our other business units other countries can take the code and use it in another country. That's one example. >> Wow. >> How would you define artificial intelligence? There's someone who has in your job-- (laughing) >> That's sometimes very difficult question I must admit. I'm normally if I would say from a scientific point, it's really to have a machine that works and feels and did everything like a human. If you look now at the hype, it's more about how we learn, how we do things and not about I would say it's about robotic and stuff like that but it's more how we are learning and the major benefit we are getting now out of artificial intelligence is really that we are able now to really work on data. We have great algorithm and a lot of progress there and we have the chips that develops so far that we are able to do that. It's far away from things like a little kid can do because little kid can just, you show them an apple and then it knows an apple is green. It's were-- >> A little kid can't open a support ticket. (laughing) >> Yeah, but that's very special, so in where we special areas, we are already very, very good in things, but this is an area, for example, if you have an (mumbles) who is able like we did to predict this kind of tickets this agreement is not able at the moment to say this as an apple and this is an orange, so you need another one. So we are far away from really having something like a general intelligence there. >> Madhu do I want to bring you into this conversation. (laughing) And a little bit just in terms of what Susan was saying the sort of the shiny newness of it all. Where do you think we are in terms of thinking about the data getting in the weeds of the data and then also sort of the innovations that we saw, dream about really impacting the bottom line and making the customer experience better and also the employee experience better? >> Yeah, so from IBM perspective, especially coming from data and analytics, very simple message, right? We have what we say your letter to AI. Everybody like Susan and every other company who is part of doing any digital transformation or modernization is talking about Ai. So our message is very simple, in order to get to the letter of AI, the most critical part is that you have access to data, right? You can trust your data, so this way you can start using it in terms of building models, not just predictive models but prescriptive and diagnostics. Everything needs to kind of come together, right? So that is what we are doing in data analytics. Our message is very, very simple. The innovations are coming in from the perspectives of machine learning, deep learning and making and to me that all equates to automation, right? A lot of this stuff data curation, I think you can Susan, tell how long and how manual the data curation aspects can be. Now with machine learning, getting to your latter of AI, You can do this in a matter of hours, right? And you can get to your business users, you can if your CHARM model, If your clients are not happy, your fraud, you have to detect in your bank or retail industry, it just applies to all the industry. So there is tons of innovation happening. We just actually announced a product earlier called IBM Cloud Private for Data. This is our the analytics platform which is ready with data built in governance to handle all your data curation and be building models which you can test it out, have all the DevOps and push it into production. Really, really trying to get clients like Deutsche Telekom to get their journey there faster. Very simple-- >> We've heard from many of our guests today about the importance of governance, of having good quality data before you can start building anything with it. What was that process like? How is the... what is the quality of data like at Deutsche Telekom and what work did it take to get it in that condition. >> So data quality is a major issue everywhere, because as Madhu that this is one of the essential things to really get into learning, if you want to learn, you need the data and we have in the different countries, different kind of majorities and what we are doing at the moment is that we are really doing it case by case because you cannot do everything from the beginning, so you start with one of the cases looking what to do there? How to define the quality? And then if the business asked for the next case, then you can integrate that, so you have the business impact, you have demand from the business and then you can integrate the data quality there and we are doing it really step by step because to bring it to the business from the beginning, it's very, very difficult. >> You mentioned, one of the new products that you announced just today, what are some of the-- (laughing) >> We announced it in may. >> Oh, okay, I'm sorry. >> It's okay still new. >> In terms of the other innovations in the pipeline, what I mean this is such a marvelous and exciting time for technology. What are some of the most exciting developments that you see? >> I think the most exciting, especially if I talk about what I do day out everything revolves around metadata, right? Used to be not a very sticky term, but it is becoming quite sexy all over again, right? And all the work in automatic metadata generation, understanding the lineage where the data is coming from. How easy, we can make it to the business users, then all the machine learning algorithms which we are doing in terms of our prescriptive models and predictive, right? Predictive maintenance is such a huge thing. So there's a lot of work going on there and then also one of the aspects is how do you build once and run anywhere, right? If you really look at the business data, it's behind the firewalls, Is in multicloud. How do you bring solutions which are going to be bringing all the data? Doesn't matter where it resides, right? And so there's a lot of innovation like that which we are working and bringing in onto our platform to make it really simple story make data easy access which you can trust. >> One of the remarkable things about machine learning is that the leading libraries have all been open source, Google, Facebook, eBay, others have open source their libraries. What impact do you think that has had on the speed with which machine learning is developed? >> Just amazing, right. I think that gives us that agility to quickly able to use it, enhance it, give it back to the community. That has been the one of the tenants for, I think that how everybody's out there, moving really really fast. Open source is going to play a very critical role for IBM, and we're seeing that with many of our clients as well. >> What tools are you using? >> We're using different kind of tools that depending on the departments, so the data scientists like to use our patents. (laughing) They are always use it, but we are using a lot like the Jupiter notebook, for example, to have different kind of code in there. We have in one of our countries, the classical things like thus there and the data scientists working with that one or we have the Cloud-R workbench to really bringing things into the business. We have in some business-- >> Data science experience. >> IBM, things integrated, so it it really depends a little bit on the different and that's a little bit the challenge because you really have to see how people working together and how do we really get the data, the models the sharing right. >> And then also the other challenges that all the CDOs face that we've been talking about today, the getting by in the-- >> Yes. >> The facing unrealistic expectations of what data can actually do. I mean, how would you describe how you are able to work with the business side? As a chief working in the chief data office. >> Yeah, so what I really like and what I'm always doing with the business that we are going to the business and doing really a joint approach having a workshop together like the design thinking workshop with the business and the demand has to come from the business. And then you have really the data scientists in there the data engineers best to have the operational people in there and even the controlling not all the time, but that it's really clear that all people are involved from the beginning and then you're really able to bring it into production. >> That's the term of DataOps, right? That's starting to become a big thing. DevOps was all about to agility. Now DataOps bring all these various groups together and yeah I mean that's how you we really move forward. >> So for organizations so that's both of you for organizations that are just beginning to go down the machine learning path that are excited by everything you've been hearing here. What advice would you have for them? They're just getting started. >> I think if you're just getting started to me, the long pole item is all about understanding where your data is, right? The data curation. I have seen over and over again, everybody's enthusiastic. They love the technology, but the... It just doesn't progress fast enough because of that. So invest in tooling where they have automation with machine learning where they can quickly understand it, right? Data virtualization, nobody's going to move data, right? They're sitting in bedrock systems access to that which I call dark data, is important because that is sometimes your golden nugget because that's going to help you make the decisions. So to me that's where I would focus first, everything else around it just becomes a lot easier. >> Great. >> So-- >> Do you have a best practice too? Yeah. >> Yeah. Focus on really bringing quick impact on some of the cases because they're like the management needs success, so you need some kind of quick access and then really working on the basics like Madhu said, you need to have access of the data because if you don't start work on that it will take you every time like half a year. We have some cases where we took finance department half a year to really get all that kind of data and you have to sharpen that for the future, but you need the fast equipments. You need to do both. >> Excellent advice. >> Right, well Susan and Madhu thank you so much for coming on theCUBE, it's been great having you. >> Thank you. >> Thank you. >> I'm Rebecca Knight for Paul Gillin we will have more from theCUBE's live coverage of the IBM CDO just after this. (upbeat music)

>> [Announcer] Live from Times Square in New York City, it's theCUBE covering IBM's Change the Game: Winning with AI, brought to you by IBM. >> Hello everybody, welcome to theCUBE's special presentation. We're covering IBM's announcements today around AI. IBM, as theCUBE does, runs of sessions and programs in conjunction with Strata, which is down at the Javits, and we're Rob Thomas, who's the General Manager of IBM Analytics. Long time Cube alum, Rob, great to see you. >> Dave, great to see you. >> So you guys got a lot going on today. We're here at the Westin Hotel, you've got an analyst event, you've got a partner meeting, you've got an event tonight, Change the game: winning with AI at Terminal 5, check that out, ibm.com/WinWithAI, go register there. But Rob, let's start with what you guys have going on, give us the run down. >> Yeah, it's a big week for us, and like many others, it's great when you have Strata, a lot of people in town. So, we've structured a week where, today, we're going to spend a lot of time with analysts and our business partners, talking about where we're going with data and AI. This evening, we've got a broadcast, it's called Winning with AI. What's unique about that broadcast is it's all clients. We've got clients on stage doing demonstrations, how they're using IBM technology to get to unique outcomes in their business. So I think it's going to be a pretty unique event, which should be a lot of fun. >> So this place, it looks like a cool event, a venue, Terminal 5, it's just up the street on the west side highway, probably a mile from the Javits Center, so definitely check that out. Alright, let's talk about, Rob, we've known each other for a long time, we've seen the early Hadoop days, you guys were very careful about diving in, you kind of let things settle and watched very carefully, and then came in at the right time. But we saw the evolution of so-called Big Data go from a phase of really reducing investments, cheaper data warehousing, and what that did is allowed people to collect a lot more data, and kind of get ready for this era that we're in now. But maybe you can give us your perspective on the phases, the waves that we've seen of data, and where we are today and where we're going. >> I kind of think of it as a maturity curve. So when I go talk to clients, I say, look, you need to be on a journey towards AI. I think probably nobody disagrees that they need something there, the question is, how do you get there? So you think about the steps, it's about, a lot of people started with, we're going to reduce the cost of our operations, we're going to use data to take out cost, that was kind of the Hadoop thrust, I would say. Then they moved to, well, now we need to see more about our data, we need higher performance data, BI data warehousing. So, everybody, I would say, has dabbled in those two area. The next leap forward is self-service analytics, so how do you actually empower everybody in your organization to use and access data? And the next step beyond that is, can I use AI to drive new business models, new levers of growth, for my business? So, I ask clients, pin yourself on this journey, most are, depends on the division or the part of the company, they're at different areas, but as I tell everybody, if you don't know where you are and you don't know where you want to go, you're just going to wind around, so I try to get them to pin down, where are you versus where do you want to go? >> So four phases, basically, the sort of cheap data store, the BI data warehouse modernization, self-service analytics, a big part of that is data science and data science collaboration, you guys have a lot of investments there, and then new business models with AI automation running on top. Where are we today? Would you say we're kind of in-between BI/DW modernization and on our way to self-service analytics, or what's your sense? >> I'd say most are right in the middle between BI data warehousing and self-service analytics. Self-service analytics is hard, because it requires you, sometimes to take a couple steps back, and look at your data. It's hard to provide self-service if you don't have a data catalog, if you don't have data security, if you haven't gone through the processes around data governance. So, sometimes you have to take one step back to go two steps forward, that's why I see a lot of people, I'd say, stuck in the middle right now. And the examples that you're going to see tonight as part of the broadcast are clients that have figured out how to break through that wall, and I think that's pretty illustrative of what's possible. >> Okay, so you're saying that, got to maybe take a step back and get the infrastructure right with, let's say a catalog, to give some basic things that they have to do, some x's and o's, you've got the Vince Lombardi played out here, and also, skillsets, I imagine, is a key part of that. So, that's what they've got to do to get prepared, and then, what's next? They start creating new business models, imagining this is where the cheap data officer comes in and it's an executive level, what are you seeing clients as part of digital transformation, what's the conversation like with customers? >> The biggest change, the great thing about the times we live in, is technology's become so accessible, you can do things very quickly. We created a team last year called Data Science Elite, and we've hired what we think are some of the best data scientists in the world. Their only job is to go work with clients and help them get to a first success with data science. So, we put a team in. Normally, one month, two months, normally a team of two or three people, our investment, and we say, let's go build a model, let's get to an outcome, and you can do this incredibly quickly now. I tell clients, I see somebody that says, we're going to spend six months evaluating and thinking about this, I was like, why would you spend six months thinking about this when you could actually do it in one month? So you just need to get over the edge and go try it. >> So we're going to learn more about the Data Science Elite team. We've got John Thomas coming on today, who is a distinguished engineer at IBM, and he's very much involved in that team, and I think we have a customer who's actually gone through that, so we're going to talk about what their experience was with the Data Science Elite team. Alright, you've got some hard news coming up, you've actually made some news earlier with Hortonworks and Red Hat, I want to talk about that, but you've also got some hard news today. Take us through that. >> Yeah, let's talk about all three. First, Monday we announced the expanded relationship with both Hortonworks and Red Hat. This goes back to one of the core beliefs I talked about, every enterprise is modernizing their data and application of states, I don't think there's any debate about that. We are big believers in Kubernetes and containers as the architecture to drive that modernization. The announcement on Monday was, we're working closer with Red Hat to take all of our data services as part of Cloud Private for Data, which are basically microservice for data, and we're running those on OpenShift, and we're starting to see great customer traction with that. And where does Hortonworks come in? Hadoop has been the outlier on moving to microservices containers, we're working with Hortonworks to help them make that move as well. So, it's really about the three of us getting together and helping clients with this modernization journey. >> So, just to remind people, you remember ODPI, folks? It was all this kerfuffle about, why do we even need this? Well, what's interesting to me about this triumvirate is, well, first of all, Red Hat and Hortonworks are hardcore opensource, IBM's always been a big supporter of open source. You three got together and you're proving now the productivity for customers of this relationship. You guys don't talk about this, but Hortonworks had to, when it's public call, that the relationship with IBM drove many, many seven-figure deals, which, obviously means that customers are getting value out of this, so it's great to see that come to fruition, and it wasn't just a Barney announcement a couple years ago, so congratulations on that. Now, there's this other news that you guys announced this morning, talk about that. >> Yeah, two other things. One is, we announced a relationship with Stack Overflow. 50 million developers go to Stack Overflow a month, it's an amazing environment for developers that are looking to do new things, and we're sponsoring a community around AI. Back to your point before, you said, is there a skills gap in enterprises, there absolutely is, I don't think that's a surprise. Data science, AI developers, not every company has the skills they need, so we're sponsoring a community to help drive the growth of skills in and around data science and AI. So things like Python, R, Scala, these are the languages of data science, and it's a great relationship with us and Stack Overflow to build a community to get things going on skills. >> Okay, and then there was one more. >> Last one's a product announcement. This is one of the most interesting product annoucements we've had in quite a while. Imagine this, you write a sequel query, and traditional approach is, I've got a server, I point it as that server, I get the data, it's pretty limited. We're announcing technology where I write a query, and it can find data anywhere in the world. I think of it as wide-area sequel. So it can find data on an automotive device, a telematics device, an IoT device, it could be a mobile device, we think of it as sequel the whole world. You write a query, you can find the data anywhere it is, and we take advantage of the processing power on the edge. The biggest problem with IoT is, it's been the old mantra of, go find the data, bring it all back to a centralized warehouse, that makes it impossible to do it real time. We're enabling real time because we can write a query once, find data anywhere, this is technology we've had in preview for the last year. We've been working with a lot of clients to prove out used cases to do it, we're integrating as the capability inside of IBM Cloud Private for Data. So if you buy IBM Cloud for Data, it's there. >> Interesting, so when you've been around as long as I have, long enough to see some of the pendulums swings, and it's clearly a pendulum swing back toward decentralization in the edge, but the key is, from what you just described, is you're sort of redefining the boundary, so I presume it's the edge, any Cloud, or on premises, where you can find that data, is that correct? >> Yeah, so it's multi-Cloud. I mean, look, every organization is going to be multi-Cloud, like 100%, that's going to happen, and that could be private, it could be multiple public Cloud providers, but the key point is, data on the edge is not just limited to what's in those Clouds. It could be anywhere that you're collecting data. And, we're enabling an architecture which performs incredibly well, because you take advantage of processing power on the edge, where you can get data anywhere that it sits. >> Okay, so, then, I'm setting up a Cloud, I'll call it a Cloud architecture, that encompasses the edge, where essentially, there are no boundaries, and you're bringing security. We talked about containers before, we've been talking about Kubernetes all week here at a Big Data show. And then of course, Cloud, and what's interesting, I think many of the Hadoop distral vendors kind of missed Cloud early on, and then now are sort of saying, oh wow, it's a hybrid world and we've got a part, you guys obviously made some moves, a couple billion dollar moves, to do some acquisitions and get hardcore into Cloud, so that becomes a critical component. You're not just limiting your scope to the IBM Cloud. You're recognizing that it's a multi-Cloud world, that' what customers want to do. Your comments. >> It's multi-Cloud, and it's not just the IBM Cloud, I think the most predominant Cloud that's emerging is every client's private Cloud. Every client I talk to is building out a containerized architecture. They need their own Cloud, and they need seamless connectivity to any public Cloud that they may be using. This is why you see such a premium being put on things like data ingestion, data curation. It's not popular, it's not exciting, people don't want to talk about it, but we're the biggest inhibitors, to this AI point, comes back to data curation, data ingestion, because if you're dealing with multiple Clouds, suddenly your data's in a bunch of different spots. >> Well, so you're basically, and we talked about this a lot on theCUBE, you're bringing the Cloud model to the data, wherever the data lives. Is that the right way to think about it? >> I think organizations have spoken, set aside what they say, look at their actions. Their actions say, we don't want to move all of our data to any particular Cloud, we'll move some of our data. We need to give them seamless connectivity so that they can leave their data where they want, we can bring Cloud-Native Architecture to their data, we could also help move their data to a Cloud-Native architecture if that's what they prefer. >> Well, it makes sense, because you've got physics, latency, you've got economics, moving all the data into a public Cloud is expensive and just doesn't make economic sense, and then you've got things like GDPR, which says, well, you have to keep the data, certain laws of the land, if you will, that say, you've got to keep the data in whatever it is, in Germany, or whatever country. So those sort of edicts dictate how you approach managing workloads and what you put where, right? Okay, what's going on with Watson? Give us the update there. >> I get a lot of questions, people trying to peel back the onion of what exactly is it? So, I want to make that super clear here. Watson is a few things, start at the bottom. You need a runtime for models that you've built. So we have a product called Watson Machine Learning, runs anywhere you want, that is the runtime for how you execute models that you've built. Anytime you have a runtime, you need somewhere where you can build models, you need a development environment. That is called Watson Studio. So, we had a product called Data Science Experience, we've evolved that into Watson Studio, connecting in some of those features. So we have Watson Studio, that's the development environment, Watson Machine Learning, that's the runtime. Now you move further up the stack. We have a set of APIs that bring in human features, vision, natural language processing, audio analytics, those types of things. You can integrate those as part of a model that you build. And then on top of that, we've got things like Watson Applications, we've got Watson for call centers, doing customer service and chatbots, and then we've got a lot of clients who've taken pieces of that stack and built their own AI solutions. They've taken some of the APIs, they've taken some of the design time, the studio, they've taken some of the Watson Machine Learning. So, it is really a stack of capabilities, and where we're driving the greatest productivity, this is in a lot of the examples you'll see tonight for clients, is clients that have bought into this idea of, I need a development environment, I need a runtime, where I can deploy models anywhere. We're getting a lot of momentum on that, and then that raises the question of, well, do I have expandability, do I have trust in transparency, and that's another thing that we're working on. >> Okay, so there's API oriented architecture, exposing all these services make it very easy for people to consume. Okay, so we've been talking all week at Cube NYC, is Big Data is in AI, is this old wine, new bottle? I mean, it's clear, Rob, from the conversation here, there's a lot of substantive innovation, and early adoption, anyway, of some of these innovations, but a lot of potential going forward. Last thoughts? >> What people have to realize is AI is not magic, it's still computer science. So it actually requires some hard work. You need to roll up your sleeves, you need to understand how I get from point A to point B, you need a development environment, you need a runtime. I want people to really think about this, it's not magic. I think for a while, people have gotten the impression that there's some magic button. There's not, but if you put in the time, and it's not a lot of time, you'll see the examples tonight, most of them have been done in one or two months, there's great business value in starting to leverage AI in your business. >> Awesome, alright, so if you're in this city or you're at Strata, go to ibm.com/WinWithAI, register for the event tonight. Rob, we'll see you there, thanks so much for coming back. >> Yeah, it's going to be fun, thanks Dave, great to see you. >> Alright, keep it right there everybody, we'll be back with our next guest right after this short break, you're watching theCUBE.

>> Live from Times Square in New York City, it's The Cube covering IBM's Change the Game: Winning with AI, brought to you by IBM. >> Hello everybody, welcome to The Cube's special presentation. We're covering IBM's announcements today around AI. IBM, as The Cube does, runs of sessions and programs in conjunction with Strata, which is down at the Javits, and we're Rob Thomas, who's the General Manager of IBM Analytics. Long time Cube alum, Rob, great to see you. >> Dave, great to see you. >> So you guys got a lot going on today. We're here at the Westin Hotel, you've got an analyst event, you've got a partner meeting, you've got an event tonight, Change the game: winning with AI at Terminal 5, check that out, ibm.com/WinWithAI, go register there. But Rob, let's start with what you guys have going on, give us the run down. >> Yeah, it's a big week for us, and like many others, it's great when you have Strata, a lot of people in town. So, we've structured a week where, today, we're going to spend a lot of time with analysts and our business partners, talking about where we're going with data and AI. This evening, we've got a broadcast, it's called Winning with AI. What's unique about that broadcast is it's all clients. We've got clients on stage doing demonstrations, how they're using IBM technology to get to unique outcomes in their business. So I think it's going to be a pretty unique event, which should be a lot of fun. >> So this place, it looks like a cool event, a venue, Terminal 5, it's just up the street on the west side highway, probably a mile from the Javits Center, so definitely check that out. Alright, let's talk about, Rob, we've known each other for a long time, we've seen the early Hadoop days, you guys were very careful about diving in, you kind of let things settle and watched very carefully, and then came in at the right time. But we saw the evolution of so-called Big Data go from a phase of really reducing investments, cheaper data warehousing, and what that did is allowed people to collect a lot more data, and kind of get ready for this era that we're in now. But maybe you can give us your perspective on the phases, the waves that we've seen of data, and where we are today and where we're going. >> I kind of think of it as a maturity curve. So when I go talk to clients, I say, look, you need to be on a journey towards AI. I think probably nobody disagrees that they need something there, the question is, how do you get there? So you think about the steps, it's about, a lot of people started with, we're going to reduce the cost of our operations, we're going to use data to take out cost, that was kind of the Hadoop thrust, I would say. Then they moved to, well, now we need to see more about our data, we need higher performance data, BI data warehousing. So, everybody, I would say, has dabbled in those two area. The next leap forward is self-service analytics, so how do you actually empower everybody in your organization to use and access data? And the next step beyond that is, can I use AI to drive new business models, new levers of growth, for my business? So, I ask clients, pin yourself on this journey, most are, depends on the division or the part of the company, they're at different areas, but as I tell everybody, if you don't know where you are and you don't know where you want to go, you're just going to wind around, so I try to get them to pin down, where are you versus where do you want to go? >> So four phases, basically, the sort of cheap data store, the BI data warehouse modernization, self-service analytics, a big part of that is data science and data science collaboration, you guys have a lot of investments there, and then new business models with AI automation running on top. Where are we today? Would you say we're kind of in-between BI/DW modernization and on our way to self-service analytics, or what's your sense? >> I'd say most are right in the middle between BI data warehousing and self-service analytics. Self-service analytics is hard, because it requires you, sometimes to take a couple steps back, and look at your data. It's hard to provide self-service if you don't have a data catalog, if you don't have data security, if you haven't gone through the processes around data governance. So, sometimes you have to take one step back to go two steps forward, that's why I see a lot of people, I'd say, stuck in the middle right now. And the examples that you're going to see tonight as part of the broadcast are clients that have figured out how to break through that wall, and I think that's pretty illustrative of what's possible. >> Okay, so you're saying that, got to maybe take a step back and get the infrastructure right with, let's say a catalog, to give some basic things that they have to do, some x's and o's, you've got the Vince Lombardi played out here, and also, skillsets, I imagine, is a key part of that. So, that's what they've got to do to get prepared, and then, what's next? They start creating new business models, imagining this is where the cheap data officer comes in and it's an executive level, what are you seeing clients as part of digital transformation, what's the conversation like with customers? >> The biggest change, the great thing about the times we live in, is technology's become so accessible, you can do things very quickly. We created a team last year called Data Science Elite, and we've hired what we think are some of the best data scientists in the world. Their only job is to go work with clients and help them get to a first success with data science. So, we put a team in. Normally, one month, two months, normally a team of two or three people, our investment, and we say, let's go build a model, let's get to an outcome, and you can do this incredibly quickly now. I tell clients, I see somebody that says, we're going to spend six months evaluating and thinking about this, I was like, why would you spend six months thinking about this when you could actually do it in one month? So you just need to get over the edge and go try it. >> So we're going to learn more about the Data Science Elite team. We've got John Thomas coming on today, who is a distinguished engineer at IBM, and he's very much involved in that team, and I think we have a customer who's actually gone through that, so we're going to talk about what their experience was with the Data Science Elite team. Alright, you've got some hard news coming up, you've actually made some news earlier with Hortonworks and Red Hat, I want to talk about that, but you've also got some hard news today. Take us through that. >> Yeah, let's talk about all three. First, Monday we announced the expanded relationship with both Hortonworks and Red Hat. This goes back to one of the core beliefs I talked about, every enterprise is modernizing their data and application of states, I don't think there's any debate about that. We are big believers in Kubernetes and containers as the architecture to drive that modernization. The announcement on Monday was, we're working closer with Red Hat to take all of our data services as part of Cloud Private for Data, which are basically microservice for data, and we're running those on OpenShift, and we're starting to see great customer traction with that. And where does Hortonworks come in? Hadoop has been the outlier on moving to microservices containers, we're working with Hortonworks to help them make that move as well. So, it's really about the three of us getting together and helping clients with this modernization journey. >> So, just to remind people, you remember ODPI, folks? It was all this kerfuffle about, why do we even need this? Well, what's interesting to me about this triumvirate is, well, first of all, Red Hat and Hortonworks are hardcore opensource, IBM's always been a big supporter of open source. You three got together and you're proving now the productivity for customers of this relationship. You guys don't talk about this, but Hortonworks had to, when it's public call, that the relationship with IBM drove many, many seven-figure deals, which, obviously means that customers are getting value out of this, so it's great to see that come to fruition, and it wasn't just a Barney announcement a couple years ago, so congratulations on that. Now, there's this other news that you guys announced this morning, talk about that. >> Yeah, two other things. One is, we announced a relationship with Stack Overflow. 50 million developers go to Stack Overflow a month, it's an amazing environment for developers that are looking to do new things, and we're sponsoring a community around AI. Back to your point before, you said, is there a skills gap in enterprises, there absolutely is, I don't think that's a surprise. Data science, AI developers, not every company has the skills they need, so we're sponsoring a community to help drive the growth of skills in and around data science and AI. So things like Python, R, Scala, these are the languages of data science, and it's a great relationship with us and Stack Overflow to build a community to get things going on skills. >> Okay, and then there was one more. >> Last one's a product announcement. This is one of the most interesting product annoucements we've had in quite a while. Imagine this, you write a sequel query, and traditional approach is, I've got a server, I point it as that server, I get the data, it's pretty limited. We're announcing technology where I write a query, and it can find data anywhere in the world. I think of it as wide-area sequel. So it can find data on an automotive device, a telematics device, an IoT device, it could be a mobile device, we think of it as sequel the whole world. You write a query, you can find the data anywhere it is, and we take advantage of the processing power on the edge. The biggest problem with IoT is, it's been the old mantra of, go find the data, bring it all back to a centralized warehouse, that makes it impossible to do it real time. We're enabling real time because we can write a query once, find data anywhere, this is technology we've had in preview for the last year. We've been working with a lot of clients to prove out used cases to do it, we're integrating as the capability inside of IBM Cloud Private for Data. So if you buy IBM Cloud for Data, it's there. >> Interesting, so when you've been around as long as I have, long enough to see some of the pendulums swings, and it's clearly a pendulum swing back toward decentralization in the edge, but the key is, from what you just described, is you're sort of redefining the boundary, so I presume it's the edge, any Cloud, or on premises, where you can find that data, is that correct? >> Yeah, so it's multi-Cloud. I mean, look, every organization is going to be multi-Cloud, like 100%, that's going to happen, and that could be private, it could be multiple public Cloud providers, but the key point is, data on the edge is not just limited to what's in those Clouds. It could be anywhere that you're collecting data. And, we're enabling an architecture which performs incredibly well, because you take advantage of processing power on the edge, where you can get data anywhere that it sits. >> Okay, so, then, I'm setting up a Cloud, I'll call it a Cloud architecture, that encompasses the edge, where essentially, there are no boundaries, and you're bringing security. We talked about containers before, we've been talking about Kubernetes all week here at a Big Data show. And then of course, Cloud, and what's interesting, I think many of the Hadoop distral vendors kind of missed Cloud early on, and then now are sort of saying, oh wow, it's a hybrid world and we've got a part, you guys obviously made some moves, a couple billion dollar moves, to do some acquisitions and get hardcore into Cloud, so that becomes a critical component. You're not just limiting your scope to the IBM Cloud. You're recognizing that it's a multi-Cloud world, that' what customers want to do. Your comments. >> It's multi-Cloud, and it's not just the IBM Cloud, I think the most predominant Cloud that's emerging is every client's private Cloud. Every client I talk to is building out a containerized architecture. They need their own Cloud, and they need seamless connectivity to any public Cloud that they may be using. This is why you see such a premium being put on things like data ingestion, data curation. It's not popular, it's not exciting, people don't want to talk about it, but we're the biggest inhibitors, to this AI point, comes back to data curation, data ingestion, because if you're dealing with multiple Clouds, suddenly your data's in a bunch of different spots. >> Well, so you're basically, and we talked about this a lot on The Cube, you're bringing the Cloud model to the data, wherever the data lives. Is that the right way to think about it? >> I think organizations have spoken, set aside what they say, look at their actions. Their actions say, we don't want to move all of our data to any particular Cloud, we'll move some of our data. We need to give them seamless connectivity so that they can leave their data where they want, we can bring Cloud-Native Architecture to their data, we could also help move their data to a Cloud-Native architecture if that's what they prefer. >> Well, it makes sense, because you've got physics, latency, you've got economics, moving all the data into a public Cloud is expensive and just doesn't make economic sense, and then you've got things like GDPR, which says, well, you have to keep the data, certain laws of the land, if you will, that say, you've got to keep the data in whatever it is, in Germany, or whatever country. So those sort of edicts dictate how you approach managing workloads and what you put where, right? Okay, what's going on with Watson? Give us the update there. >> I get a lot of questions, people trying to peel back the onion of what exactly is it? So, I want to make that super clear here. Watson is a few things, start at the bottom. You need a runtime for models that you've built. So we have a product called Watson Machine Learning, runs anywhere you want, that is the runtime for how you execute models that you've built. Anytime you have a runtime, you need somewhere where you can build models, you need a development environment. That is called Watson Studio. So, we had a product called Data Science Experience, we've evolved that into Watson Studio, connecting in some of those features. So we have Watson Studio, that's the development environment, Watson Machine Learning, that's the runtime. Now you move further up the stack. We have a set of APIs that bring in human features, vision, natural language processing, audio analytics, those types of things. You can integrate those as part of a model that you build. And then on top of that, we've got things like Watson Applications, we've got Watson for call centers, doing customer service and chatbots, and then we've got a lot of clients who've taken pieces of that stack and built their own AI solutions. They've taken some of the APIs, they've taken some of the design time, the studio, they've taken some of the Watson Machine Learning. So, it is really a stack of capabilities, and where we're driving the greatest productivity, this is in a lot of the examples you'll see tonight for clients, is clients that have bought into this idea of, I need a development environment, I need a runtime, where I can deploy models anywhere. We're getting a lot of momentum on that, and then that raises the question of, well, do I have expandability, do I have trust in transparency, and that's another thing that we're working on. >> Okay, so there's API oriented architecture, exposing all these services make it very easy for people to consume. Okay, so we've been talking all week at Cube NYC, is Big Data is in AI, is this old wine, new bottle? I mean, it's clear, Rob, from the conversation here, there's a lot of substantive innovation, and early adoption, anyway, of some of these innovations, but a lot of potential going forward. Last thoughts? >> What people have to realize is AI is not magic, it's still computer science. So it actually requires some hard work. You need to roll up your sleeves, you need to understand how I get from point A to point B, you need a development environment, you need a runtime. I want people to really think about this, it's not magic. I think for a while, people have gotten the impression that there's some magic button. There's not, but if you put in the time, and it's not a lot of time, you'll see the examples tonight, most of them have been done in one or two months, there's great business value in starting to leverage AI in your business. >> Awesome, alright, so if you're in this city or you're at Strata, go to ibm.com/WinWithAI, register for the event tonight. Rob, we'll see you there, thanks so much for coming back. >> Yeah, it's going to be fun, thanks Dave, great to see you. >> Alright, keep it right there everybody, we'll be back with our next guest right after this short break, you're watching The Cube.

>> Live from Times Square in New York City, it's theCUBE, covering IBM's Change the Game, Winning with AI, brought to you by IBM. >> Hi everybody, welcome back to theCUBE's special presentation. We're here at the Western Hotel and the theater district covering IBM's announcements. They've got an analyst meeting today, partner event. They've got a big event tonight. IBM.com/winwithAI, go to that website, if you're in town register. You can watch the webcast online. You'll see this very cool play of Vince Lombardy, one of his famous plays. It's kind of a power sweep right which is a great way to talk about sort of winning and with X's and O's. So anyway, Daniel Hernandez is here the vice president of IBM analytics, long time Cube along. It's great to see you again, thanks for coming on. >> My pleasure Dave. >> So we've talked a number of times. We talked earlier this year. Give us the update on momentum in your business. You guys are doing really well, we see this in the quadrants and the waves, but your perspective. >> Data science and AI, so when we last talked we were just introducing something called IBM Club Private for data. The basic idea is anybody that wants to do data science, data engineering or building apps with data anywhere, we're going to give them a single integrated platform to get that done. It's going to be the most efficient, best way to do those jobs to be done. We introduced it, it's been a resounding success. Been rolling that out with clients, that's been a whole lot of fun. >> So we talked a little bit with Rob Thomas about some of the news that you guys have, but this is really your wheelhouse so I'm going to drill down into each of these. Let's say we had Rob Beerden on yesterday on our program and he talked a lot about the IBM Red Hat and Hortonworks relationship. Certainly they talked about it on their earnings call and there seems to be clear momentum in the marketplace. But give us your perspective on that announcement. What exactly is it all about? I mean it started kind of back in the ODPI days and it's really evolved into something that now customers are taking advantage of. >> You go back to June last year, we entered into a relationship with Hortonworks where the basic primacy, was customers care about data and any data driven initiative was going to require data science. We had to do a better job bringing these eco systems, one focused on kind of Hadoop, the other one on classic enterprise analytical and operational data together. We did that last year. The other element of that was we're going to bring our data science and machine learning tools and run times to where the data is including Hadoop. That's been a resounding success. The next step up is how do we proliferate that single integrated stack everywhere including private Cloud or preferred Clouds like Open Shift. So there was two elements of the announcement. We did the hybrid Cloud architecture initiative which is taking the Hadoop data stack and bringing it to containers and Kubernetes. That's a big deal for people that want to run the infrastructure with Cloud characteristics. And the other was we're going to bring that whole stack onto Open Shift. So on IBM's side, with IBM Cloud Private for data we are driving certification of that entire stack on OpenShift so any customer that's betting on OpenShift as their Cloud infrastructure can benefit from that and the single integrated data stack. It's a pretty big deal. >> So OpenShift is really interesting because OpenShift was kind of quiet for awhile. It was quiest if you will. And then containers come on the scene and OpenShift has just exploded. What are your perspectives on that and what's IBM's angle on OpenShift? >> Containers of Kubernetes basically allow you to get Cloud characteristics everywhere. It used to be locked in to kind of the public Cloud or SCP providers that were offering as a service whether PAS OR IAS and Docker and Kubernetes are making the same underline technology that enabled elasticity, pay as you go models available anywhere including your own data center. So I think it explains why OpenShift, why IBM Cloud Private, why IBM Club Private for data just got on there. >> I mean the Core OS move by Red Hat was genius. They picked that up for the song in our view anyway and it's really helped explode that. And in this world, everybody's talking about Kubernetes. I mean we're here at a big data conference all week. It used to be Hadoop world. Everybody's talking about containers, Kubernetes and Multi cloud. Those are kind of the hot trends. I presume you've seen the same thing. >> 100 percent. There's not a single client that I know, and I spend the majority of my time with clients that are running their workloads in a single stack. And so what do you do? If data is an imperative for you, you better run your data analytic stack wherever you need to and that means Multi cloud by definition. So you've got a choice. You can say, I can port that workload to every distinct programming model and data stack or you can have a data stack everywhere including Multi clouds and Open Shift in this case. >> So thinking about the three companies, so Hortonworks obviously had duped distro specialists, open source, brings that end to end sort of data management from you know Edge, or Clouds on Prim. Red Hat doing a lot of the sort of hardcore infrastructure layer. IBM bringing in the analytics and really empowering people to get insights out of data. Is that the right way to think about that triangle? >> 100 percent and you know with the Hortonworks and IBM data stacks, we've got our common services, particularly you're on open meta data which means wherever your data is, you're going to know about it and you're going to be able to control it. Privacy, security, data discovery reasons, that's a pretty big deal. >> Yeah and as the Cloud, well obviously the Cloud whether it's on Prim or in the public Cloud expands now to the Edge, you've also got this concept of data virtualization. We've talked about this in the past. You guys have made some announcements there. But let's put a double click on that a little bit. What's it all about? >> Data virtualization been going on for a long time. It's basic intent is to help you access data through whatever tools, no matter where the data is. Traditional approaches of data virtualization are pretty limiting. So they work relatively well when you've got small data sets but when you've got highly fragmented data, which is the case in virtually every enterprise that exists a lot of the undermined technology for data virtualization breaks down. Data coming through a single headnote. Ultimately that becomes the critical issue. So you can't take advantage of data virtualization technologies largely because of that when you've got wide scale deployments. We've been incubating technology under this project codename query plex, it was a code name that we used internally and that we were working with Beta clients on and testing it out, validating it technically and it was pretty clear that this is a game changing method for data virtualization that allows you to drive the benefits of accessing your data wherever it is, pushing down queries where the data is and getting benefits of that through highly fragmented data landscape. And so what we've done is take that extremely innovated next generation data virtualization technology include it in our data platform called IBM Club Private for Data, and made it a critical feature inside of that. >> I like that term, query plex, it reminds me of the global sisplex. I go back to the days when actually viewing sort of distributed global systems was very, very challenging and IBM sort of solved that problem. Okay, so what's the secret sauce though of query plex and data virtualization? How does it all work? What's the tech behind it? >> So technically, instead of data coming and getting funneled through one node. If you ever think of your data as kind of a graph of computational data nodes. What query plex does is take advantage of that computational mesh to do queries and analytics. So instead of bringing all the data and funneling it through one of the nodes, and depending on the computational horsepower of that node and all the data being able to get to it, this just federates it out. It distributes out that workload so it's some magic behind the scenes but relatively simple technique. Low computing aggregate, it's probably going to be higher than whatever you can put into that single node. >> And how do customers access these services? How long does it take? >> It would look like a standard query interface to them. So this is all magic behind the scenes. >> Okay and they get this capability as part of what? IBM's >> IBM's Club Private for Data. It's going to be a feature, so this project query plex, is introduced as next generation data virtualization technology which just becomes a part of IBM Club Private for Data. >> Okay and then the other announcement that we talked to Rob, I'd like to understand a little bit more behind it. Actually before we get there, can we talk about the business impact of query plex and data virtualization? Thinking about it, it dramatically simplifies the processes that I have to go through to get data. But more importantly, it helps me get a handle on my data so I can apply machine intelligence. It seems like the innovation sandwich if you will. Data plus AI and then Cloud models for scale and simplicity and that's what's going to drive innovation. So talk about the business impact that people are excited about with regard to query plex. >> Better economics, so in order for you to access your data, you don't have to do ETO in this particular case. So data at rest getting consumed because of this online technology. Two performance, so because of the way this works you're actually going to get faster response times. Three, you're going to be able to query more data simply because this technology allows you to access all your data in a fragmented way without having to consolidate it. >> Okay, so it eliminates steps, right, and gets you time to value and gives you a bigger corporate of data that you can the analyze and drive inside. >> 100 percent. >> Okay, let's talk about stack overflow. You know, Rob took us through a little bit about what that's, what's going on there but why stack overflow, you're targeting developers? Talk to me more about that. >> So stack overflow, 50 million active developers each month on that community. You're a developer and you want to know something, you have to go to stack overflow. You think about data science and AI as disciplines. The idea that that is only dermained to AI and data scientists is very limiting idea. In order for you to actually apply artificial intelligence for whatever your use case is instead of a business it's going to require multiple individuals working together to get that particular outcome done including developers. So instead of having a distinct community for AI that's focused on AI machine developers, why not bring the artificial intelligence community to where the developers already are, which is stack overflow. So, if you go to AI.stackexchange.com, it's going to be the place for you to go to get all your answers to any question around artificial intelligence and of course IBM is going to be there in the community helping out. >> So it's AI.stackexchange.com. You know, it's interesting Daniel that, I mean to talk about digital transformation talking about data. John Furrier said something awhile back about the dots. This is like five or six years ago. He said data is the new development kit and now you guys are essentially targeting developers around AI, obviously a data centric. People trying to put data at the core of the organization. You see that that's a winning strategy. What do you think about that? >> 100 percent, I mean we're the data company instead of IBM, so you're probably asking the wrong guy if you think >> You're biased. (laughing) >> Yeah possibly, but I'm acknowledged. The data over opinions. >> Alright, tell us about tonight what we can expect? I was referencing the Vince Lombardy play here. You know, what's behind that? What are we going to see tonight? >> We were joking a little bit about the old school power eye formation, but that obviously works for your, you're a New England fan aren't you? >> I am actually, if you saw the games this weekend Pat's were in the power eye for quite a bit of the game which I know upset a lot of people. But it works. >> Yeah, maybe we should of used it as a Dallas Cowboy team. But anyways, it's going to be an amazing night. So we're going to have a bunch of clients talking about what they're doing with AI. And so if you're interested in learning what's happening in the industry, kind of perfect event to get it. We're going to do some expert analysis. It will be a little bit of fun breaking down what those customers did to be successful and maybe some tips and tricks that will help you along your way. >> Great, it's right up the street on the west side highway, probably about a mile from the Javis Center people that are at Strata. We've been running programs all week. One of the themes that we talked about, we had an event Tuesday night. We had a bunch of people coming in. There was people from financial services, we had folks from New York State, the city of New York. It was a great meet up and we had a whole conversation got going and one of the things that we talked about and I'd love to get your thoughts and kind of know where you're headed here, but big data to do all that talk and people ask, is that, now at AI, the conversation has moved to AI, is it same wine, new bottle, or is there something substantive here? The consensus was, there's substantive innovation going on. Your thoughts about where that innovation is coming from and what the potential is for clients? >> So if you're going to implement AI for let's say customer care for instance, you're going to be three wrongs griefs. You need data, you need algorithms, you need compute. With a lot of different structure to relate down to capture data wasn't captured until the traditional data systems anchored by Hadoop and big data movement. We landed, we created a data and computational grid for that data today. With all the advancements going on in algorithms particularly in Open Source, you now have, you can build a neuro networks, you can do Cisco machine learning in any language that you want. And bringing those together are exactly the combination that you need to implement any AI system. You already have data and computational grids here. You've got algorithms bringing them together solving some problem that matters to a customer is like the natural next step. >> And despite the skills gap, the skill gaps that we talked about, you're seeing a lot of knowledge transfer from a lot of expertise getting out there into the wild when you follow people like Kirk Born on Twitter you'll see that he'll post like the 20 different models for deep learning and people are starting to share that information. And then that skills gap is closing. Maybe not as fast as some people like but it seems like the industry is paying attention to this and really driving hard to work toward it 'cause it's real. >> Yeah I agree. You're going to have Seth Dulpren, I think it's Niagara, one of our clients. What I like about them is the, in general there's two skill issues. There's one, where does data science and AI help us solve problems that matter in business? That's really a, trying to build a treasure map of potential problems you can solve with a stack. And Seth and Niagara are going to give you a really good basis for the kinds of problems that we can solve. I don't think there's enough of that going on. There's a lot of commentary communication actually work underway in the technical skill problem. You know, how do I actually build these models to do. But there's not enough in how do I, now that I solved that problem, how do we marry it to problems that matter? So the skills gap, you know, we're doing our part with our data science lead team which Seth opens which is telling a customer, pick a hard problem, give us some data, give us some domain experts. We're going to be in the AI and ML experts and we're going to see what happens. So the skill problem is very serious but I don't think it's most people are not having the right conversations about it necessarily. They understand intuitively there's a tech problem but that tech not linked to a business problem matters nothing. >> Yeah it's not insurmountable, I'm glad you mentioned that. We're going to be talking to Niagara Bottling and how they use the data science elite team as an accelerant, to kind of close that gap. And I'm really interested in the knowledge transfer that occurred and of course the one thing about IBM and companies like IBM is you get not only technical skills but you get deep industry expertise as well. Daniel, always great to see you. Love talking about the offerings and going deep. So good luck tonight. We'll see you there and thanks so much for coming on theCUBE. >> My pleasure. >> Alright, keep it right there everybody. This is Dave Vellanti. We'll be back right after this short break. You're watching theCUBE. (upbeat music)