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Arvind Krishna, IBM | Red Hat Summit 2019


 

>> Announcer: Live from Boston, Massachusetts. It's theCUBE, covering Red Hat Summit 2019. Brought to you by Red Hat. >> And welcome back to Boston. Here on theCUBE we continue our coverage of Red Hat Summit 2019. We just had Jim Whitehurst on, President and CEO, along with Stu Miniman, I'm John Walls. And now, we turn to the IBM side of the equation. Arvind Krishna is with us, the SVP of Cloud and Cognitive Software at IBM. Arvind, good to see you this morning. >> My pleasure to be here, what a great show. >> Yeah, absolutely, it has been. I was telling Jim he couldn't have a better week, right? Monday had good news, Tuesday great kick off, today again following through great key notes. We were talking briefly, a year ago you were with us on theCUBE and talking about IBM and its forward plans, so on and so forth. What a difference a year makes, right? (laughs) >> We couldn't predict that you'd be in the position that you are in now, so just if you can summarize the last year and maybe the last six months for you. >> Sure, and I think it's more building on what I talked to you about a year ago, I remember last May, May of 2018, in San Francisco. So I was exposing very heavily, look the world's going to move towards containers, the world has already embraced Linux, this is the time to have a new architecture that enables hybrid, much along the lines that Jim and all of the clients as well as Ginni and Satya were talking about on stage yesterday. So you put all that together and you say that is what we mentioned last year and we were clear, that is where the world is gonna go. Now you step forward a few months from there into October of 2018 and on the 29th October we announced that IBM intends to acquire Red Hat, so then you say wow, we put actually our money where our mouth was. We were talking about the strategy, we were talking about Linux containers, OpenShift, the partnership we announced last May was IBM software products together with OpenShift. We already believed in that. But now this allows us coming together, it's more like a marriage than sort of loose partners passing each other in the middle of the night. >> Right. >> And that then goes forward, you mention the news on Monday so for our viewers that don't know it, that's the news that the United States Department of Justice approved merger with no conditions. So now we've got to wait on a few other jurisdictions and then hopefully we can get together really soon. >> John: Right, right. >> So, I think back to looking at IBM over my career. I think the first time I heard the word coopetition it was related to IBM because IBM, big ego system, lots of innovation over its long history but as we know the bigger you get, the more chance that your partners are also going to overlap with you. Seeing Ginni up on stage and a little bit later seeing Satya up on stage is really interesting. You look at the public, multicloud environment, everybody doesn't need to work together, you talk to your customers, and I'm sure you find today it's not the future is hybrid and multicloud, that's where they are today even if they're trying to get their arms around all of it. So I'd love to hear your, with the mega trend of Cloud, what you're seeing that competitive but partnering dynamic. >> Look, I want to step back to just give it a little bit of context. So when you talk about companies, let's go back to the beginning of computing, of PC. The PC came from IBM operating system, DOS came from Microsoft. Then you had Windows setting up the IBM PC. So that's coopetition or is that pure partnership? Right, I mean you can take your pick of those words. Our value has always been that we, IBM, come to clients and we try to service problems that actually help them in their business outcomes. Then whoever they have inside their IT shops, that they depend upon, has to be a part of that answer. You cannot say oh, so and so is bad, they're out. So it always had to be coopetition from the lengths that we came to with our clients. We always build originally computers, other people's software are on those computers, other people provided services around it. As we went into certain software space, ISVs and so on came together. So now that you come to the world of Cloud, we hold a very fundamental belief and I think we heard a number of the clients talk about this. They are going to be on multiple public Clouds. If they are going to be on multiple public Clouds, they are also going to have traditional IT and they are also going to have private Clouds. That's the world to live in if I look at it from the viewpoint of that infrastructure. To now come to your direct question, so if that's the world they're going to live in hopefully one of those public Clouds is ours but the others are from other people. The private Cloud, we believe the standard for that should be OpenShift and should be containers. So as we go down that path, then you say if you want to take that environment and also run it on the other publics. That's good for the client, that's good for the publics, that's good for us. It's really a win, win, win. And so I think the ability to go do this and to make that play out, it really goes back to my thesis from more than a year ago where we talk about this is a new set of standards and a new set of technical protocols emerging. >> I want you to take us inside the conversations you're having with CIOs when you talk about Cloud because when Cloud first came out, it was well, the sins of IT is this heterogeneous mess and it's complex and expensive. Cloud's going to be simple, homogeneous and cheap. I look at Cloud of 2019 and I don't think I would use any of those adjectives to define what most people have for Cloud. Where are they today? Where do we need to go as an industry? >> Glass house computing, all centralized, all homogeneous, not all at heterogeneous. Oops, 15 flavors of Unix, all different, none of them really talk to each other. Oops let's go to desktop computing, we begin with a pure architecture, maybe Novell which doesn't exist, maybe it does, I don't even know. Oops, back to this complete sprawl of client server. Okay let's go to Cloud back to centralized glass house. >> You're making me dizzy. >> Oops, let's go to-- (laughing) >> Let's go to lots of public, lots of SaaS, lots of private, back to this thing. So, in each of these a different answer came on how to unite them. I think when we look at that Unix and client server sprawl, I think TCP/IP and the internet came together so that you could have all these islands talk to each other and be able to communicate. All right, great, we've got 20 years of victory on that. Now you're getting these things, how do you begin to workload across because that becomes the next level of values. Not enough to communicate. Can I really take a workload? A workload is not just a VM or just one container, it's a collection of these things integrated together in a pretty tight and complex way. And can we take it from one place and move it to the other? Because that goes to the write once, run anywhere mantra which by the way also we come to about every 20 years. I think that's the magic of this moment and if we succeed in making that happen, which I have complete conviction we will, especially together, then I think we give a huge value back and we give freedom to every CTO and every CIO. >> You paint this really interesting whoops picture, I love that, it's really a back and forth, right, we're swinging and almost there's a cyclical nature to this is what you're I think implying. What's to say in your mind that this isn't just another whoops as opposed to this being a permanent shift in the paradigm? >> I think it's, the reason I think that it's going to be cyclical is we tend to, you know whether you go to construction and real estate, you talk about capacity and factories. You see an opportunity and people tend to go one way. The only way to correct culture if you're sitting in one place is to sort of over-correct the other way, now you're over-corrected. Now you have to come back. And always when you over-correct one way, then suddenly all those other benefits you've lost, so then you've got to come back to get those benefits. After about 10 years, probably, you can debate 10 or 15, you're done. You've exploited all those benefits, now you need to go get those benefits. Because the technologies have changed, it's not just that you're going back to what was. We're going very conceptually from centralized to distributed, to centralized to distributed. And by the way, another one that's getting out from pure centralized is also Edge. Edge in effect is another distributed, so you put those together and you say I went there, but then I lost all this stuff, now I need to get back to that stuff. If you've got too much there, you'll say, no, no, no, I need to get some of this back. So it's going to go that way I think for every, if you look at it, the big arcs are back, the pendulum, what do you call it, the pendulum swing, is I think about 20 years it looks like, right? 1960, centralized, 1980, PC, 2000, you could say was the peak of the internet. Hey, 2020, we're in Cloud. So looks like about 20 years, looks like. >> All right, so, I like what you were saying when you talk about that multicloud environment, the application is really central there. IBM, of course, has a strong history, not just in middleware but in applications. What do you think will differentiate this kind of next wave of multicloud, how will the leaders emerge? >> Right, so if you look at it today, you run infrastructure. I think OpenShift has done a great job of how you help run their infrastructure. The value in our eyes in putting the services on top, both coming from open source as well as other companies that are running like an integrated package. This is all about taking the cost out of how do you deploy and develop. And if we can take the cost out of that, you're not talking about that five to 10 X as we heard a couple of the clients up on stage yesterday with Jim talk about. If we give that to everybody, you can sort of say that 70% which goes into managing your current and only 30% on innovation. Can you shift that paradigm completely? That's the big business outcome that you get. As you begin to deliver these towers of function on top of the base. You need to start at base, without one base, you don't know how to say, I can't deal with these towers of function on thirty different things underneath. That engineering answer is a terrible one. >> In terms of the infrastructure market, things keep changing, right? Consolidating, EMC doing what they're, you know what happened there. How do you see your play in that market? First off, how do you see infrastructure evolving? And then how do you see your play in that going forward? >> Infrastructure has always been big, in the end all the stuff you talk about has to run on infrastructure. I'd say the consumption model of how you get infrastructure is changing. So it used to be that many years ago, people bought all their own infrastructures. They bought boxes, they put in boxes, they did all the integration. And what came from the vendor was just a box. Then you went to, all right you can get it as a managed service or you can get it in Cloud which is also a pay by the drink but you can now turn it up and down also. So it's not a either or, people want all of these models. And so our role in infrastructure, certain things we will provide. When it comes to running really high mission critical workloads, think mainframe, think big Unix, think storage, of that ilk; we'll keep providing that. We believe there's a lot of value in that. We see the value, our clients appreciate that value. That workload turns up, but it's the mission critical part of the workload. Then in turn we also provide the more commodity infrastructure but as a service. We supply a large amount of it to our clients. It comes sometimes wrapped in a managed service, it sometimes comes wrapped as a Cloud. And we will also consume infrastructure from other Cloud providers because if people are providing base computer, network and storage, there is no reason to presume that our capabilities wouldn't run on top. If I go back to just February, we announced that Watson will now run. We said we used the moniker Watson Anywhere to make the assertion that we will run Watson anywhere that we can run the correct containerized infrastructure. >> So, Arvind, what's the single most pressing issue that you hear from organizations with respect to their technology strategy and how's IBM helping there? >> I think modernizing applications is the biggest one. So people have, typically a large enterprise will have anywhere from 3,000 to 15,000 applications. That's what runs the enterprise. We talk about everyone's becoming a software company, right, I mean that was one of the quotes and everybody is becoming a tech company that was I think what one of the clients said, hey, we think you're a bank, you're actually a tech company. What that says is that you're capturing the essence of all the business processes. You're capturing the essence of the experiences. The essence of what regulators need, the essence of how you maintain customer and customer of our clients, trust, back to them. It's maintained through this collection of applications. Now if you say I want to go change, I want to become even more client centric, I want to insert AI into the middle of my business process, I want to become more digital. All of that is modernizing applications. The big pinpoint they all have is how do I modernize them? What becomes that fabric in which I modernize? How do I know I'm not locked into yet another spaghetti mess if I go down this path? Because we've seen that movie also. So they're interested in, hey, I want to be clean at the end of this. I want freedom to be able to move it. And that is why I'm so passionate about, the fabric is based on open source, the fabric's got to be based on open standards. If you go there, there is no lock-in, and it's not a spaghetti mess, it is actually clean. Much cleaner than any other option that we can dream of is going to be. And so if we go down this path, now you can open yourself up to a much faster velocity of how you deliver innovation and value back to the business. >> Okay, so, I'd agree first of all when you talk about modernization, the applications that they have, that's the long pole in the tent. We understand compared to all the other digitization, modernization, this is the toughest challenge here. I'm a little surprised though that I didn't hear the word data because they don't necessarily articulate it but the biggest opportunity that they have has to be tied to data. >> Well to me, when I use the word application here, and you heard me use the word AI, can I insert AI in the context of an application? Now, why is it not being done today? To get the value out of AI, the data that powers the AI is stuck in all the silos, all over the place. So you've got to have, as you do this modernization, it's imperative to put the correct data architecture so that now you can do the governance, so that you can choose to unlock the appropriate parts of the data. It's really important to say the appropriate parts because neither do you want data sort of free floating around the globe, because that is the value of a company at the end of the day. And so that unlocking of that value is a huge part of this. So you're absolutely right to ask me to express it more strongly when I use the word application, I'm inclusive of not just runtime but always of the data that powers that application. >> Arvind, it was again a year ago that we were talking to you out in San Francisco and you made some rather strong thematic predictions that turned out well. I'm not going to put you on the spot here, but I can't wait to see next year. And see how this turns out. >> I can't let him go before, we had the CIO of Delta who we had on our program. >> Oh, right, right. >> In the key note, made a question about licensing, of course Jim Whitehurst said we don't have licensing but what's your answer? >> I'm willing to offer a deal to Samant. So I think that both IBM and Red Hat do a fair amount of air travel. We'll give him a common license if he can just include Red Hat for whatever IBM pays, just include all the Red Hat travel that is needed on Delta. (laughing) You know just so that the business models become clear and we can go have a robust discussion. >> Out of Raleigh that's a good deal. >> For us. >> That's what I'm saying. That is a good deal. All right, the ball is in your court, or on your runway. Whatever the case may be. Arvind, thanks for being with us. >> My pleasure. >> We appreciate it. And we'll let you know if we hear back from Rahul on that good deal. TheCUBE continues live from Boston right after this. (upbeat music)

Published Date : May 8 2019

SUMMARY :

Brought to you by Red Hat. Arvind, good to see you this morning. you were with us on theCUBE and talking about IBM that you are in now, so just if you can summarize that IBM intends to acquire Red Hat, so then you say that's the news that the United States Department of Justice the bigger you get, the more chance that your partners So as we go down that path, then you say if you want to take I want you to take us inside the conversations none of them really talk to each other. so that you could have all these islands What's to say in your mind that this isn't the pendulum, what do you call it, the pendulum swing, All right, so, I like what you were saying That's the big business outcome that you get. And then how do you see your play in that going forward? to make the assertion that we will run Watson anywhere And so if we go down this path, now you can open yourself up that I didn't hear the word data so that now you can do the governance, so that you can that we were talking to you out in San Francisco I can't let him go before, we had the CIO of Delta who we You know just so that the business models become clear All right, the ball is in your court, or on your runway. And we'll let you know if we hear back

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Arvind Krishna, IBM | IBM Think 2019


 

>> 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.

Published Date : Feb 12 2019

SUMMARY :

It's the cue covering Man in charge of all the cloud products cloud everywhere. You essentially laid out the vision for So on the simple simple. than it was to keep Watson to yourself. I think that every company that survives a long term learns that choice to a customer is really important from a customer statement, just get the facts right on the hard news. Which means even if you do things one place you build up more than one place, for pulling that end to end a I anywhere on multiple clouds, on premises and through the workloads. So going to the common services on a Cuban Eddie's in a container layer that is common across Now you got data everywhere you got cloud everywhere. So so that's one piece of it, the next part of is IBM over the years has made you know many efforts took to court developers. So it's the network effect really. What's the opportunity for partners? the management expertise, the operational expertise, printable technologies, perhaps that we provide. enterprise start to think, you know, cohesive set of services across on Prem multiple clouds. seventy percent of the total cost and people are tied up in maintaining what you have. And how do you respond to that? What started the architecture that let you do the hardest off later? What's the most important story people should pay attention to this year and IBM think in San Francisco? That is the evolution that is giving greater business value for using the word More live coverage after this short break state with the cube dot net is where you find the

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Arvind Krishna, IBM | Red Hat Summit 2018


 

>> [Announcer] 18, brought to you by Red Hat >> Well, welcome back everyone. This is theCUBE's exclusive coverage here in San Francisco, California, for Red Hat Summit 2018. I am John Furrier, co-host of theCUBE with my analyst co-host this week, John Troyer, co-founder of the TechReckoning advisory services. And our next guest is Arvind Krishna, who is the Senior Vice President of Hybrid Cloud at IBM and Director of IBM Research. Welcome back to theCUBE, good to see you. >> Thanks John and John great to meet you guys here. >> You can't get confused here you've got two John's here. Great to have you on because, you guys have been doing some deals with Red Hat, obviously the leader at open storage. You guys are one of them as well contributing to Linuxes well documented in the IBM history books on your role and relationship to Linux so check, check. But you guys are doing a lot of work with cloud, in a way that, frankly, is very specific to IBM but also has a large industry impact, not like the classic cloud. So I want to tie the knot here and put that together. So first I got to ask you, take a minute to talk about why you're here with Red Hat, what's the update with IBM with Red Hat? >> Great John, thanks for giving me the time. I'm going to talk about it in two steps: One, I'm going to talk about a few common tenets between IBM and Red Hat. Then I'll go from there to the specific news. So for the context, we both believe in Linux, I think that easy to state. We both believe in containers, I think that is the next thing to state. We'll come back talk about containers because this is a world, containers are linked to Linux containers are linked to these technologies called Kubernetes. Containers are linked to how you make workloads portable across many different environments, both private and public. Then I go on from there to say, that we both believe in hybrid. Hybrid meaning that people want the ability to run their workload, where ever they want. Be it on a private cloud, be it on a public cloud. And do it without having to rewrite everything as you go across. Okay, so let's establish, those are the market needs. So then you come back and say. And IBM has a great portfolio of Middleware, names like WebSphere and DB2 and I can go on and on. And Red Hat has a great footprint of Linux, in the Enterprise. So now you say, we've got the market need of hybrid. We've got these two thing, which between them are tens of millions, maybe hundreds of millions of end points. How do you make that need get fulfilled by this? And that's what we just announced here. So we announced that IBM Middleware will run containerized on Red Hat containers, on Red Hat Enterprise Linux. In addition, we said IBM Cloud Private, which is the ability to bring all of the IBM Middleware in a sort of a cloud-friendly form. Right you click and you install it, it keep it self up, it doesn't go down, it's elastic in a set of technologies we call IBM Cloud Private, running in turn on Red Hat OpenShift Container service on Red Hat Linux. So now for the first time, if you say I want private, I want public, I want to go here, I want to go there. You have a complete certified stack, that is complete. I think I can say, we're a unique in the industry, in giving you this. >> And this is where, kind of where, the fruit comes off the tree, for you guys. Because, we've been following you guys for years, and everyone's: Where's the cloud strategy? And first of all, it's not, you don't have a cloud strategy you have cloud products. Right, so you have delivered the goods. You got the, so just to replay. The market need we all know is the hybrid cloud, multi-cloud, choice et cetera, et cetera. >> You take Red Hat's footprint, your capabilities, your combined install base, is foundational. >> [Arvind] Right >> So, nothing needs to change. There's no lift and shift, there's no rip and replace, >> you can, it's out there it's foundational. Now on top of it, is where the action is. That where you're kind of getting at, right? >> That's correct, so we can go into somebody running, let's say, a massive online banking application or they're running a reservation system. It's using technologies from us, it's using Linux underneath and today it's all a bunch of piece pods, you have a huge complex stuff it's all hard-wired and rigidly nailed down to the floor in a few places and now you can say: Hey, I'll take the application. I don't have to rewrite the application. I can containerize it, I can put it here. And that same app now begins to work but in a way that's a lot more fluid and elastic. Or my other way: I want to do a bit more work. I want to expose a bit of it up as microservices. I want to insert some IA. You can go do that. You want to fully make it microservices enabled to be able to make it into little components >> and ultimately you can do that. >> So you can take it in sort of bite size chunks and go from one to other, at the pace that you want. >> [John F.] Now that's game changing. >> Yeah, that's what I really like about this announcement. It really brings best of breed together. You know, there is a lot of talk about containers. Legacy and we've been talking about what goes where? And do you have to break everything up? Like you were just saying. But the announcement today, WebSphere, the battle tested huge enterprise scale component, DB2, those things containerized and also in a frame work like with IBM, either with IBM microservices and application development things or others right, that's a huge endorsement for OpenShift as a platform. >> Absolutely, it is and look, we would be remiss if we didn't talk a little bit. I mean we use the word containers and containerized a lot. Yes, you're right. Containers are a really, really important technology but what containers enable is much more than prior attempts such as VM's and all have done. Containers really allow you to say: Hey, I solved the security problem, I solved the patching problem, the restart problem, all those problems that lie around the operations of a typical enterprise, can get solved with containers. VM's solved a lot about isolating the infrastructure but it didn't solve, as John was saying, the top half of the stack. And that's I think the huge power here. >> Yeah, I want to just double click on that because I think the containers thing is instrumental. Because it, first of all, being in the media and loving what we do. We're kind of a new kind of media company but traditional media is been throwing IBM under the bus since saying: Wow old guard and all these things. Here's the thing, you don't have to change anything. You got containers you can essentially wrap it up and then bring a microservice architecture into it. So you can actually leverage at cloud scale. So what interests me is that you can move instantly, >> value proposition wise, pre-existing market, cloudify it, if you will, with operational capabilities. >> Right. >> This is where I like the Cloud Private. So I want to kind of go there for a second. If I have a need to take what I have at IBM, whether it is WebSphere. Now I got developers, I got installed base. I don't have to put a migration plan away. I containerize it. Thank you very much. I do some cloud native stuff but I want to make it private. My use case is very specific, maybe it's confidential, maybe it's like a government region, Whatever. I can create a cloud operations, is that right? I can cloudify it, and run it? >> Absolutely correct, so when you look at Cloud Private, to go down that path, we said Cloud Private allows you to run on your private infrastructure but I want all these abilities you just described John. I want to be able to do microservices. I want to be able to scale up and down. I want to be able to say operations happen automatically. But it gives you all that but in the private without it having to go all the way to the public. If you cared a lot about, your in a regulated industry, you went down government or confidential data. Or you say this data is so sensitive, I don't really, I am not going to take the risk of it being anywhere else. It absolutely gives you that ability to go do that and that is what brought Cloud Private to the market for and then you combine that with OpenShift and now you get the powers of both together. >> See you guys essentially have brought to the table the years of effort with Bluemix, all that good stuff going on, you can bring it in and actually run this in any industry vertical. Pretty much, right? >> Absolutely, so if you look at part what the past has been for the entire industry. It has been a lot about constructing a public cloud. Not just us, but us and our competition. And a public cloud has certain capabilities and it has certain elasticity, it has a global footprint. But it doesn't have a footprint that is in every zip code or in every town or in every city. That's not what happens to a public cloud. So we say. It's a hybrid world meaning that you're going to run some workloads on a public cloud, I'd like to run some workloads on a private and I'd like to have the ability that I don't have to pre decide which is where. And that is what the containers and microservices, the OpenShift that combination all give you to say you don't need to pre decide. You rewrite the workload onto this and then you can decide where it runs. >> Well I was having this conversation with some folks at a recent Amazon Web services conference. Well, if you go to cloud operations, then the on premise is essentially the edge. It's not necessarily. Then the definition of on premise, really doesn't even exist. >> So if you have cloud operations, in a way, what is the data center then? It's just a connected issue. >> That's right, it's the infrastructure which is set up and then, at that point, the Software Manger, at the data center, as opposed to anything else. And that's kind of been the goal that we're all been wanting. >> Sounds like this is visibly at IBM's essentially execution plan from day one. We've been seeing it and connecting the dots. Having the ability to take either pre-existing resources, foundational things like Red Hat or what not in the enterprise. Not throwing it away. Building on top of it and having a new operating model, with software, with elastic scale, horizontally scalable, Synchronous, all these good things. Enabling microservices, with Kubernetes and containers. Now for the first time, >> I can roll out new software development life cycles in a cloud native environment without forgoing legacy infrastructure and investment. >> Absolutely, and one more element. And if you want to insert some cloud service into the environment, be it in private or in public, you can go do that. For example, you want to insert a couple of AI services >> into the middle of your application you could go do that. So the environment allows you to, do what you described and these additionals. >> I want to talk about people for a second. The titles that we haven't mentioned CIO, Business Leader, Business Unit Leaders, how are they looking at >> digital transformation and business transformation in your client bases you go out and talk to them. >> Let's take a hypothetical bank. And every bank today is looking about simple questions. How do I improve my customer experience? And everybody want, when they say customer experience, really do mean digital customer experience to make it very tangible. And what they mean by that is how do I get my end customer engaged with me through an app. The app is probably in a device like this. Some smart phone, we won't say what it is, and so how do you do that? And so they say: Well, all obviously to check your balance. You obviously want to check your credit card. You want to do all those things. The same things we do today. So that application exists, there is not much point in rewriting it. You might do the UI up but it's an app that exists. Then you say but I also want to give you information that's useful to you in the context to what you're doing. I want say, you can get a 10 second loan, not a 30 day loan, but a 10 second loan. I want to make a offer to you in the middle of you browsing credit card. All those are new customergistics, where do you construct those apps? How do you mix and match it? How do you use all the capabilities along with the data you've got to go do that? And what we're trying to now say, here is a platform that you can go, do all that on. Right, that complete lifecycle you mentioned, the development lifecycle but I got to add to it >> the data lifecycle, as well as, here is the versioning, here are my AI models, all those things, built in, into one platform. >> And scales are huge, the new competitive advantage. You guys are enabling that. So I got to ask you a question on multi cloud. Obviously, as people start building out the cloud on PRIM and with Public Cloud and the things you're laying out. I can see that going on for a while, a lot of work being done there. We're seeing that Wikibon had a true Private Cloud report what I thought was truly telling. A lot of growth there, still not going away. Public Cloud's certainly grown in numbers are clear. However, the word multicloud's being kicked around I think it's more of a future stay obviously but people have multiple clouds Will have relationships with multiple clouds. No one's going to have one cloud. It's not a winner take all game. Winner take most but you know you're have multiple clouds. What does multi cloud mean to you guys in your architecture? Is that moving workloads in real time based upon spot pricing indexes or is that just co-locating on clouds and saying I got this app on this cloud, that app on that cloud, control plane it. These are architectural questions. What the hell is multicloud? >> So there's a today, then there is a tomorrow, then there is a long future state, right? So let's take today, let's take IBM. We're on Salesforce, we're on ServiceNow, we're on Workday, we're on SuccessFactors, well all of there are different clouds. We run our own public cloud, we run our own private cloud and we have Judicial Data Center. And we might have some of the other clouds also through apps that we barter we don't even know. Okay, so that's just us. I think everyone of our clients are like this. The multicloud is here today. I begin with that first, simple statement. And I need to connect the data and can connect when thing go where. The next step, I think people, nobody's going to have even one public cloud. Even amongst the big public clouds, most people are going to have two if not more That's today and tomorrow. >> Your channel partners have clouds, by the way, your Global SI's all have clouds, theCUBE is a cloud for crying out load. >> Right, so then you go into the aspirational state and that may be the one you said, where people just spot pricing. But even if I stay back from spot pricing and completely (mumbles) I make. And I'm worrying about network and I'm worrying about radio reach. If I just backup around to but I may decide I have this app, I run it on private, well, but I don't have all the infrastructures I want to burst it today and I, where do I burst it? I got to decide which public and how do I go there? >> And that's a problem of today and we're doing that and that is why I think multicloud is here now. >> Not some point in the future. >> The prime statement there is latency, managing, service level agreements between clouds and so on and so forth. >> Access control on governance, Where does my data go? Because there may be regulatory reasons to decide where the data can flow and all those things. >> Great point about the cloud. I never thought about it that way. It is a good illustration. I would also say that, I see the same arguments in the data base world. Not everyone has DB2, not everyone has Oracle, not everyone has, databases are everywhere, you have databases part of IoT devices now. So like no one makes a decision on the database. Similar with clouds, you see a similar dynamic. It's the glue layer that, interest me. As you, how do you bring them together? So holistically looking at the 20 miles stare in the future, what is the integration strategy long-term? If you look at distributed system or an operating system there has to be an architectural guiding principle for integration, your thoughts. >> This has been a world 30 years in the making. We can say networking, everyone had their own networking standard and the, let's say the '80s probably goes back to the '70s right? You had SNA, you had TCP/IP, you had NetBIO's-- >> DECnet. DECnet. You can on and on and in the end it's TCP/IP that won out as the glue. Others by the way, survived but in packets and then TCP/IP was the glue. Then you can fast forward 15 years beyond that and HTTP became the glue, we call that the internet. Then you can fast forward and you can say, now how do I make applications portable? And I will turn round and tell you that containers on Linux with Kubernetes as orchestration is that glue layer. Now in order to make it so, just like TCP/IP, it wasn't enough to say TCP/IP you needed routing tables, you needed DNS, you needed name repository, you needed all those things. Similarly, you need all those here are called the scatlog and automation, so that's the glue layer that makes all of this work >> This is important, I love this conversation because I have been ranting on theCUBE for years. You nailed it. A new stack is developing and DNS's are old and internet infrastructure, cloud infrastructure at the global scale is seeing things like network effect, okay we see blockchain in token economics, databases, multiple databases, on structure day >> a new plethora of new things are happening that are building on top of say HTTP >> [Arvind] Correct! >> And this is the new opportunity. >> This is the new platform which is emerging and it is going to enable business to operate, as you said, >> at scale, to be very digital, to be very nimble. Application life cycles aren't always going to be months, they're going to come down to days and this is what gets enabled >> So I what you to give your opinion, personal or IBM or whatever perspective because I think you nailed the glue layer on Kubernetes, Docker, this new glue layer that and you made references to, things like HTTP and TCP, which changed the industry landscape, wealth creation, new brands emerged, companies we never heard of emerged out of this and we're all using them today. We expect a new set of brands are going to emerge, new technologies are going to emerge. In your expert opinion, how gigantic is this swarm of new innovation going to be? Just, 'cause you've seen many ways before. In you view, your minds eye, what are you expecting? >> Share your insight into how big of a shift and wave is this going to be and add some color to that. >> I think that if I take a shorter and then a longer term view. in the short term, I think that we said, that this is in the order of $100 billion, that's not just our estimate, I think even Gartner has estimated about the same number. That will be the amount of opportunity for new technologies in what we've been describing. And that is I think short term. If I go longer term, I think as much as a half but at least a fourth of the complete IT market is going to shift round to these technologies. So then the winners of those that make the shift and then by conclusion, the losers are those who don't make the shift fast enough. If half the market moves, that's huge. >> It's interesting we used to look at certain segments going back years just company, oh this company's replatformizing, >> replatforming their op lift and shift and all this stuff. What you're talking about here is so game changing because the industry is replatforming >> That's correct. It's not a company. >>It's an industry! That's right. And I think the internet era of 1995, to put that point, is perhaps the easiest analogy to what is happening. >> Not the emergence of cloud, not the emergence of all that I think that was small steps. >> What we are talking about now is back to the 1995 statement >> [John] Every vertical is upgrading their stack across what from e-commerce to whatever. >> That's right. >> It's completely modernizing. >> Correct. Around cloud. >> What we call digital transformation in a sense, yes >> I'm not a big fan of the word but I understand what you mean. Great insight Arvind, thanks for coming on theCUBE and sharing. We didn't even get to some of the other good stuff. But IBM and Red Hat doing some great stuff obviously foundational, I mean, Red Hat, Tier one, first class citizen in every single enterprise and software environment you know, now OpenSource runs the world. You guys are no stranger to Linux being the first billion dollar investment going back >> so you guys have a heritage there so congratulations on the relationship. >> I mean 18 years ago, if I remember 1999. >> I love the strategy, hybrid cloud here at IBM and Red Hat. This is theCUBE, bringing all the action here in San Francisco. I am John Furrier, John Troyer. More live coverage. Stay with us, here in theCUBE. We'll be right back. (upbeat music)

Published Date : May 9 2018

SUMMARY :

co-founder of the TechReckoning advisory services. Great to have you on because, So for the context, we both believe in Linux, So now for the first time, if you say I want private, the fruit comes off the tree, for you guys. You take Red Hat's footprint, your capabilities, So, nothing needs to change. you can, it's out there it's foundational. and now you can say: and go from one to other, at the pace that you want. And do you have to break everything up? Hey, I solved the security problem, Here's the thing, you don't have to change anything. if you will, with operational capabilities. I don't have to put a migration plan away. and then you combine that with OpenShift all that good stuff going on, you can bring it in the OpenShift that combination all give you to say Well, if you go to cloud operations, So if you have cloud operations, in a way, at the data center, as opposed to anything else. Having the ability to take either pre-existing resources, I can roll out new software development life cycles And if you want to insert some cloud service So the environment allows you to, do what you described I want to talk about people for a second. in your client bases you go out and talk to them. I want to make a offer to you in the middle the data lifecycle, as well as, here is the versioning, So I got to ask you a question on multi cloud. And I need to connect the data and can connect Your channel partners have clouds, by the way, and that may be the one you said, and that is why I think multicloud is here now. and so on and so forth. Because there may be regulatory reasons to decide I see the same arguments in the data base world. let's say the '80s probably goes back to the '70s right? And I will turn round and tell you cloud infrastructure at the global scale and this is what gets enabled So I what you to give your opinion, personal or IBM and add some color to that. a fourth of the complete IT market is going to shift round because the industry is replatforming It's not a company. is perhaps the easiest analogy to what is happening. Not the emergence of cloud, not the emergence of all that what from e-commerce to whatever. and software environment you know, so you guys have a heritage there I love the strategy, hybrid cloud here at IBM and Red Hat.

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OLD VERSION | Arvind Krishna, IBM | Red Hat Summit 2018


 

brought to you by Red Hat well welcome back everyone this two cubes exclusive coverage here in San Francisco California for Red Hat summit 20:18 I'm John Ferreira co-host of the cube with my analyst co-host this week John Troy year co-founder of The Reckoning advisory services and our next guest is Arvind Krishna who's the senior vice president of hybrid cloud at IBM Reese and director of IBM Research welcome back to the cube good to see you hey John and John Wade you guys just kick it confuse get to John's here great to have you on because you guys are doing some deals with Red Hat obviously the leader at open source you guys are one of them as well contributing to Linux it's well documented the IBM has three books on your role relationship to Linux so yeah check check but you guys are doing a lot of work with cloud in a way that you know frankly is very specific to IBM but also has a large industry impact not like the classic cloud so I want to get who tie the knot here and put that together so first I got to ask you take a minute to talk about why you're here with red hat what's the update with IBM with Red Hat yeah great John thanks and thanks for giving me the time I'm going to talk about it in two steps one I'm going to talk about a few common Tenace between IBM and Red Hat and then I'll go from there to the specific news so for the context we both believe in Linux I think that's easy to state we both believe in containers I think that's the next thing to state and we'll come back and talk about containers because this is a world containers are linked to Linux containers are linked to these technologies called kubernetes containers are linked to how you make workloads portable across many different environments both private and public then I go on from there to say and we both believe in hybrid hybrid meaning that people want the ability to run their workload wherever they want beat on a private cloud beat on a public cloud and do it without having to rewrite everything as you go across okay so let's just average those are the market needs so then you come back and say an IBM as a great portfolio of middleware names like WebSphere and db2 and I can go on and on and rather has a great footprint of Linux in the enterprise so now you say we got the market need of hybrid we got these two things which between them of tens of millions maybe hundreds of millions of endpoints how do you make that need get fulfilled by this and that's what we just announced here so we announced that IBM middleware will run containerized on RedHat containers on Red Hat Enterprise Linux in addition we said IBM cloud private which is the ability to bring all of the IBM middleware in a sort of a cloud friendly form right you click and you install it keeps itself up it doesn't go down it's elastic in a set of technologies we call IBM cloud private running in turn on Red Hat open shift container service on Red Hat Linux so now for the first time if you say I want private I want public I want to go here I want to go there you have a complete certified stack that is complete I think I can say we are unique in the industry and giving you this this and this is where this is kind of where the fruit comes on the tree off the tree for you guys you know we've been good following you guys for years you know every where's the cloud strategy and first well it's not like you don't have a cloud strategy you have cloud products right so you have to deliver the goods you've got the system replays the market need we all knows the hybrid cloud multi-cloud choice cetera et cetera right you take Red Hat's footprint your capabilities your combined install base is foundational right so and nothing needs to change there's no lifting shift there's no rip and replace you can it's out there it's foundational now on top of it is where the action is that's what we're that's what were you kind of getting at right that's correct so so we can go into somebody there running let's say a massive online banking application or the running a reservation system is using technologies from Asus using Linux underneath and today it's all a bunch of piece parts you have a huge complex stuff it's all hard wired and rigidly nailed down to the floor in a few places and I can say hey I'll take the application I don't have to rewrite the application I can containerize it I can put it here and that same app now begins to work but in a way that's a lot more fluid in elastic well by the way I want to do a bit more work I want to expose a bit of it up as micro-services I want search Samia you can go do that you want to fully make it microservices enable to be able to make it as little components and digestible you can do that so you can take it in sort of bite-sized chunks and go from one to the other at the pace that you want and that's game-changing yeah that's what I really like about this announcement it really brings the best of breed together right you did you know there's a lot of talk about containers and legacy and we you know we've been talking about what goes where and do you have to break everything up like you were just saying but the the announcement today you know WebSphere the this the you know a battle-tested huge enterprise scale component db2 those things containerized and also in a framework like with IBM we either with IBM Microsoft things or others right that's um that's a huge endorsement for open shipped as a platform absolutely it is and look we would be remiss if we didn't talk a little bit I mean we use the word containers and containers a lot yes you're right containers is a really really important technology but what containers enable is much more than prior attempts such as vm's and all have done containers really allow you to say hey I saw the security problem I solved the patching problem the restart problem all those problems that lie around the operations of a typical enterprise can get solved with containers VM sold a lot about isolating the infrastructure but they didn't solve as John was saying the top half of the stack and that's I think the huge power here yeah I want to just double click on that because I think the containers thing is instrument because you know first of all being in the media and loving what we do we're kind of a new kind of media company but traditional media has been throwing IBM under the bus and saying oh you know old guard and all these things but here's the thing you don't have to change anything you could containers you can essentially wrap it up and then bring a micro-services architecture into it so you can actually leverage at cloud scale so what interests me is is that you can move instantly value proposition wise pre-existing market cloud if I if you will with operational capabilities and this is where I like the cloud private so I want to kind of go with the ever second if I have a need to take what I have an IBM when it's WebSphere now I got developers I got installed base I'd have to put a migration plan away I containerize it thank you very much I do some cloud native stuff but I want to make it private my use case is very specific maybe it's confidential maybe it's like a government region whatever I can create a cloud operations is that right I can cloud apply it and run it absolutely correct so when you look at about private to go down that path we said well private allows you to run on your private infrastructure but I want all these abilities you just described John I want to be able to do micro services I want to be able to scale up and down I want to be able to say operations happen automatically so it gives you all that but in the private without having to go all the way to the public so if you cared a lot about you're in a regulated industry because you went down government or confidential data or you say this data is so sensitive I don't really I'm not going to take the risk of it being anywhere else it absolutely gives you that ability to go do that and and that is what we brought to our private to the market for and then you combine it with open shift and now you get the powers of both together so you guys essentially have brought to the table the years of effort with bluemix all that good stuff going on you can bring any he'd actually run this in any industry vertical pretty much right absolutely so if you look at what what the past has been for the entire industry it has been a lot about constructing a public cloud not just to us but us and our competition and a public cloud has certain capabilities and it has certain elasticity it has a global footprint but it does not have a footprint that's in every zip code or in every town or in every city that song ought to happen to the public cloud so we say it's a hybrid world meaning that you're going to run some bulk loads on a public cloud and like to run some bulk loads on a private and I'd like to have the ability that I don't have to pre decide which is where and that is what the containers the micro services the open ship that combination all gives you to say you don't need to pre decide you fucker you rewrite the workload on to this and then you can decide where it runs well I was having this conversation with some folks at and recent Amazon Web Services conference to say well if you go to cloud operations then the on-prem is essentially the edge it's not necessary then the definition of on-premise really doesn't even exist so if you have cloud operations in a way what is the data center then it's just a connected tissue that's right it's the infrastructure which you set up and then at that point the software manages the data center as opposed to anything else and that's kind of being the goal that we are all being wanted it sounds like this is visibility into IBM's essentially execution plan from day one we've been seeing in connecting the dots having the ability to take either pre-existing resources foundational things like red hat or whatnot in the enterprise not throwing it away building on top of it and having a new operating model with software with elastic scale horizontally scalable synchronous all those good things enabling micro search with kubernetes and containers now for the first time I could roll out new software development life cycles in a cloud native environment without foregoing legacy infrastructure and investment absolutely and one more element and if you want to insert some public cloud services into the environment beat in private or in public you can go do that for example you want to insert a couple of AI services into your middle of your application you can go do that so the environment allows you to do what he described and these additions we're talking about people for a second though the the titles that we haven't mentioned CIO you know business leader business unit leaders how are they looking at the digital transformation and business transformation in your client base as you go out and talk to us so let's take a hypothetical back and every bank today is looking about at simple questions how do i improve my customer experience and everyone in this a customer experience really do mean digital customer experience to make it very tangible and what they mean by that is how I get my end customer engaged with me through an app the apps probably on a device like this some smartphone we won't say what it is and and so how do you do that and so they say well well you were to check your balance you obviously want to maybe look at your credit card you want to do all those things the same things we do today so that application exists there is not much point in rewriting it you might do the UI up but it's an app that exists then you say but I also want to give you information that's useful to you in the context of what you're doing I want to say you can get a 10 second not a not a 30-day load but a ten-second law I want to make it offer to you in the middle of you browsing credit cards all those are new customer this thinks are hot where do you construct those apps how do you mix and match it how do you use all the capabilities along with the data you got to go do that and what we are trying to now say here is a platform that you can go all that do all that on right to that complete lifecycle you mentioned the development lifecycle but I got to add to the the data lifecycle as well as here is the versioning here are my area models all those things built in into one platform and scales are huge the new competitive advantage you guys are enabling that so I got to ask you on the question on on multi cloud I'll see as people start building out the cloud on pram and with public cloud the things you're laying out I can see that going on for a while a lot of work being done there we seeing that wiki bond had a true private cloud before I thought was truly telling a lot of growth they're still not going away public cloud certainly has grown the numbers are clear however the word multi clouds being kicked around I think it's more of a future state obviously but people have multiple clouds will have relationships with multiple clouds no one's gonna have one Klaus not a winner-take-all game winner take most but you're gonna have multiple clouds what does multi-cloud mean to you guys in your architecture because is that moving workloads in real time based upon spot pricing indexes or is that just co-locating on clouds and saying I got this SAP on that cloud that app on that cloud control plane did these are architectural questions it's the thing hell is multi cloud so these are today and then there is a tomorrow and then there is a long future state right so let's take today let's check IBM we're on Salesforce we're on service now we're on workday we're on SuccessFactors well all these are different clouds we run our own public cloud we run our own private cloud and we have traditional data center and we might have some of the other clouds also through apps that we bought that we don't even know okay so let's just toss I think every one of our clients is like this so multi cloud is here today I begin with that first simple statement and I need to connect the data and it comes connect when things go away the next step I think people nobody's gonna have only one even public cloud I think the big public clouds most people are gonna have to if not more that's today and tomorrow your channel partners have clouds by the way your global s lies all have clouds there's a cloud for crying out loud right so then you go into the aspirational state and that may be the one he said where people do spot pricing but even if I stay back from spot pricing and completely dynamic and of worrying about network and I'm worrying about video reach I just back up on to but I may decide it I have this app I run it on private well but I don't have all the infrastructures I want to bust it today and I've very robust it to I got to decide which public and how do I go there and that's a problem of today and we're doing that and that is why I think multi-cloud is here now not some pointed problem the problem statement there is latency managing you know service level agreements between clouds and so on and so forth governance where does my data go because there may be regulate regulate through reasons to decide where the data can flow and all the great point about the cloud I never thought about that way it's a good good illustration I would also say that I see the same argument of database world not everyone has db2 that everyone has Oracle number one has databases are everywhere you have databases part of IOT devices now so like no one makes a decision on the database similar was proud you're seeing a similar dynamic it's the glue layer that to me interest me as you how do you bring them together so holistically looking at the 20 mile stare in the future what is the integration strategy long term if you look at a distributed system or an operating system there has to be an architectural guiding principle for absolute integration you know well that's 30 years now in the making so we can say networking everybody had their own networking standards and the let's say the 80s though it probably goes back to the 70s right yeah an SN a tcp/ip you had NetBIOS TechNet deck that go on and on and in the end is tcp/ip that one out as the glue others by the way survived but in pockets and then tcp/ip was the glue then you can fast forward 15 years beyond that an HTTP became the glue we call that the internet then you can fast forward you can say now how to make applications portable and I would turn around and tell you that containers on linux with kubernetes as orchestration is that glue layer now in order to make it so just like in tcp/ip it wasn't enough to say tcp/ip you needed routing tables you needed DNS you needed name repositories you needed all those things similarly you need all those here I've called those catalogs and automation so that's the glue layer that makes all of this work this is important I love this conversation because I've been ranting on this in the queue for years you're nailed it a new stack is development DNS this is olden Internet infrastructure cloud infrastructure at the global scale is seeing things like Network effect okay we see blockchain in token economics like databases multiple database on structured data a new plethora of new things are happening that are building on top of say HTTP correct and this is the new opportunity this is the new the new platform which is emerging and it's going to enable businesses to operate you said at scale to be very digital to be very nimble application life cycles are not always going to be months they're gonna come down to days and this is what gets enabled so I want you to give your opinion personal or IBM or whatever perspective because I think you nailed the glue layer on cue and a stalker and these this new glue layer that and you made reference system things like HTTP and TCP which changed the industry landscape wealth creation new up new new brands emerged companies we've never heard of emerged out of this and we're all using them today we expect a new set of brands are gonna emerge new technologies and emerge in your expert opinion how gigantic is this swarm of new innovation gonna be just because you've seen many ways before in your view your mind's eye what are you expecting wouldn't share your your insight into how big of a shift and wave is this is going to be and add some color to that I think that if I take a take a shorter and then a longer term view in the short term I think that we said that this is on the order of 100 billion dollars that's not just our estimate I think even Gartner estimated about the same number that'll be the amount of opportunity for new technologies in what we've been describing and that is I think short term if I go longer term I think as much as 1/2 but at least 1/4 of the complete ID market is going to shift onto these technologies so then the winners are those that make the shift and then bye-bye clusion the losers of those who don't make this shift faster Afghan and stop the market moves that's that's he was interesting we used to like look at certain segments going back years oh this companies reap platform Ising we platforming they're their operative lift and shift and all this stuff what you're talking about here is so game-changing because the industries Reap lat forming that's a company that's it's an industry that's right any and I think the the the Internet era of 1995 to put that point it's perhaps the easiest analogy to what is happening not the not the emergence of cloud not the emergence of all that I think that was small steps what we're talking about now is back to the 1995 statement every vertical is upgrading their stack across the board from e-commerce to whatever that's right it's completely modernizing correct around cloud what we call digital transformation in a sense yes what not a big fan of the word but I lied I understand what you mean great insight our thanks for coming on the Kuban Sharon because we even get to some of the other good stuff but IBM and Red Hat doing some great stuff obviously foundational I mean Red Hat Tier one first-class citizen in every single enterprise and software environment you know now saw open source runs the world you guys you guys are no stranger to Linux being the first billion dollar investment going back so you guys have a heritage there so congratulations on the relationships that go around about ninety nine nine yeah and and I love the strategy hybrid cloud here at IBM and right at this the cube bring you all the action here in San Francisco I'm John for John Troy you're more live covers stay with us here in the cube Willie right back

Published Date : May 8 2018

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Itamar Ankorion, Attunity & Arvind Rajagopalan, Verizon - #DataWorks - #theCUBE


 

>> Narrator: Live from San Jose in the heart of Silicon Valley, it's the CUBE covering DataWorks Summit 2017 brought to you by Hortonworks. >> Hey, welcome back to the CUBE live from the DataWorks Summit day 2. We've been here for a day and a half talking with fantastic leaders and innovators, learning a lot about what's happening in the world of big data, the convergence with Internet of Things Machine Learning, artificial intelligence, I could go on and on. I'm Lisa Martin, my co-host is George Gilbert and we are joined by a couple of guys, one is a Cube alumni, Itamar Ankorion, CMO of Attunity, Welcome back to the Cube. >> Thank you very much, good to be here, thank you Lisa and George. >> Lisa: Great to have you. >> And Arvind Rajagopalan, the Director of Technology Services for Verizon, welcome to the Cube. >> Thank you. >> So we were chatting before we went on, and Verizon, you're actually going to be presenting tomorrow, at the DataWorks summit, tell us about building... the journey that Verizon has been on building a Data Lake. >> Oh, Verizon is over the last 20 years, has been a large corporation, made up of a lot of different acquisitions and mergers, and that's how it was formed in 20 years back, and as we've gone through the journey of the mergers and the acquisitions over the years, we had data from different companies come together and form a lot of different data silos. So the reason we kind of started looking at this, is when our CFO started asking questions around... Being able to answer One Verizon questions, it's as simple as having Days Payable, or Working Capital Analysis across all the lines of businesses. And since we have a three-major-ERP footprint, it is extremely hard to get that data out, and there was a lot of manual data prep activities that was going into bringing together those One Verizon views. So that's really what was the catalyst to get the journey started for us. >> And it was driven by your CFO, you said? >> Arvind: That's right. >> Ah, very interesting, okay. So what are some of the things that people are going to hear tomorrow from your breakout session? >> Arvind: I'm sorry, say that again? >> Sorry, what are some of the things that the people, the attendees from your breakout session, are going to learn about the steps and the journey? >> So I'm going to primarily be talking about the challenges that we ran into, and share some around that, and also talk about some of the factors, such as the catalysts and what drew us to sort of moving in that direction, as well as getting to some architectural components, from high-level standpoint, talk about certain partners that we work with, the choices we made from an architecture perspective and the tools, as well as to kind of close the loop on, user adoption and what users are seeing in terms of business value, as we start centralizing all of the data at Verizon from a backoff as Finance and Supply Chains standpoint. So that's kind of what I'm looking at talking tomorrow. >> Arvind, it's interesting to hear you talk about sort of collecting data from essentially backoff as operational systems in a Data Lake. Were there... I assume that the state is sort of more refined and easily structured than the typical stories we hear about Data Lakes. Were there challenges in making it available for exploration and visualization, or were all the early-use cases really just Production Reporting? >> So standard reporting across the ERP systems is very mature and those capabilities are there, but then you look at across-ERP systems and we have three major ERP systems for each of the lines of businesses, when you want to look at combining all of the data, it's very hard, and to add to that, you pointed on self-service discovery, and visualization across all three datas, that's even more challenging, because it takes a lot of heavy lift, to normalize all of the data and bring it into one centralized platform, and we started off the journey with Oracle, and then we had SAP HANA, we were trying to bring all the data together, but then we were looking at systems in our non-SAP ERP systems and bringing that data into a SAP-kind of footprint, one, the cost was tremendously high, also there was a lot of heavy lift and challenges in terms of manually having to normalize the data and bring it into the same kind of data models. And even after all of that was done, it was not very self-service oriented for our users and Finance and Supply Chain. >> Let me drill into two of those things. So it sounds like the ETL process of converting it into a consumable format was very complex, and then it sounds like also, the discoverability, like where a tool, perhaps like Elation, might help, which is very, very immature right now, or maybe not immature, it's still young. Is that what was missing, or why was the ETL process so much more heavyweight than with a traditional data warehouse? >> The ETL processes, there's a lot of heavy lifting there involved, because of the proprietary data structures of the ERP systems, especially SAP is... The data structures and how the data is used across clustered and pool tables, is very proprietary. And on top of that, bringing the data formats and structures from a PeopleSoft ERP system which are supporting different lines of businesses, so there are a lot of customization that's gone into place, there are specific things that we use in the ERPs, in terms of the modules and how the processes are modeled in each of the lines of businesses, complicates things a lot. And then you try and bring all these three different ERPs, and the nuances that they have over the years, try and bring them together, it actually makes it very complex. >> So tell us then, help us understand, how the Data Lake made that easier. Was it because you didn't have to do all the refinement before it got there. And tell us how Attunity helped make that possible. >> Oh absolutely, so I think that's one of the big things, why we picked the Hortonworks as one of our key partners in terms of buidling out the Data Lake, it just came on greed, you aren't necessarily worried about doing a whole lot of ETL before you bring the data in, and it also provides with the tools and the technologies from a lot other partners. We have a lot of maturity now, better provided self-service discovery capabilities for ad hoc analysis and reporting. So this is helpful to the users because now they don't have to wait for prolonged IT development cycles to model the data, do the ETL and build reports for the to consume, which sometimes could take weeks and months. Now in a matter of days, they're able to see the data they're looking for and they're able to start the analysis, and once they start the analysis and the data is accessible, it's a matter of minutes and seconds looking at the different tools, how they want to look at it, how they want to model it, so it's actually being a huge value from the perspective of the users and what they're looking to do. >> Speaking of value, one of the things that was kind of thematic yesterday, we see enterprises are now embracing big data, they're embracing Hadoop, it's got to coexist within our ecosystem, and it's got to inter-operate, but just putting data in a Data Lake or Hadoop, that's not the value there, it's being able to analyze that data in motion, at rest, structured, unstructured, and start being able to glean or take actionable insights. From your CFO's perspective, where are you know of answering some of the questions that he or she had, from an insights perspective, with the Data Lake that you have in place? >> Yeah, before I address that, I wanted to quickly touch upon and wrap up George's question, if you don't mind. Because one of the key challenges, and I do talk about how Attunity helped. I was just about to answer the question before we moved on, so I just want to close the loop on that a little bit. So in terms of bringing the data in, the data acquisition or ingestion is key aspect of it, and again, looking at the proprietary data structures from the ERP systems is very complex, and involves a multi-step process to bring the data into a strange environment, and be able to put it in the swamp bring it into the Lake. And what Attunity has been able to help us with is, it has the intelligence to look at and understand the proprietary data structures of the ERPs, and it is able to bring all the data from the ERP source systems directly into Hadoop, without any stops, or staging data bases along the way. So it's been a huge value from that standpoint, I'll get into more details around that. And to answer your question, around how it's helping from a CFO standpoint, and the users in Finance, as I said, now all the data is available in one place, so it's very easy for them to consume the data, and be able to do ad hoc analysis. So if somebody's looking to, like I said earlier, want to look at and calculate base table, as an example, or they want to look at working capital, we are actually moving data using Attunity, CDC replicate product, we're getting data in real-time, into the Data Lake. So now they're able to turn things around, and do that kind of analysis in a matter of hours, versus overnight or in a matter of days, which was the previous environment. >> And that was kind of one of the things this morning, is it's really about speed, right? It's how fast can you move and it sounds like together with Attunity, Verizon is really not only making things simpler, as you talked about in this kind of model that you have, with different ERP systems, but you're also really able to get information into the right hands much, much faster. >> Absolutely, that's the beauty of the near real-time, and the CDC architecture, we're able to get data in, very easily and quickly, and Attunity also provides a lot of visibility as the data is in flight, we're able to see what's happening in the source system, how many packets are flowing through, and to a point, my developers are so excited to work with a product, because they don't have to worry about the changes happening in the source systems in terms of DDL and those changes are automatically understood by the product and pushed to the destination of Hadoop. So it's been a game-changer, because we have not had any downtime, because when there are things changing on the source system side, historically we had to take downtime, to change those configurations and the scripts, and publish it across environments, so that's been huge from that standpoint as well. >> Absolutely. >> Itamar, maybe, help us understand where Attunity can... It sounds like there's greatly reduced latency in the pipeline between the operational systems and the analytic system, but it also sounds like you still need to essentially reformat the data, so that it's consumable. So it sounds like there's an ETL pipeline that's just much, much faster, but at the same time, when it's like, replicate, it sounds like that goes without transformations. So help us sort of understand that nuance. >> Yeah, that's a great question, George. And indeed in the past few years, customers have been focused predominantly on getting the data to the Lake. I actually think it's one of the changes in the fame, we're hearing here in the show and the last few months is, how do we move to start using the data, the great applications on the data. So we're kind of moving to the next step, in the last few years we focused a lot on innovating and creating the solutions that facilitate and accelerate the process of getting data to the Lake, from a large scope of systems, including complex ones like SAP, and also making the process of doing that easier, providing real-time data that can both feed streaming architectures as well as batch ones. So once we got that covered, to your question, is what happens next, and one of the things we found, I think Verizon is also looking at it now and are being concomitant later. What we're seeing is, when you bring data in, and you want to adopt the streaming, or a continuous incremental type of data ingestion process, you're inherently building an architecture that takes what was originally a database, but you're kind of, in a sense, breaking it apart to partitions, as you're loading it over time. So when you land the data, and Arvind was referring to a swamp, or some customers refer to it as a landing zone, you bring the data into your Lake environment, but at the first stage that data is not structured, to your point, George, in a manner that's easily consumable. Alright, so the next step is, how do we facilitate the next step of the process, which today is still very manual-driven, has custom development and dealing with complex structures. So we actually are very excited, we've introduced, in the show here, we announced a new product by Attunity, Compose for Hive, which extends our Data Lake solutions, and what Compose of Hive is exactly designed to do, is address part of the problem you just described, where's when the data comes in and is partitioned, what Compose for Hive does, is it reassembles these partitions, and it then creates analytic-ready data sets, back in Hive, so it can create operational data stores, it can create historical data stores, so then the data becomes formatted, in a matter that's more easily accessible for users, who want to use analytic tools, VI-tools, Tableau, Qlik, any type of tool that can easily access a database. >> Would there be, as a next step, whether led by Verizon's requirements or Attunity's anticipation of broader customer requirements, something where, there's a, if not near real-time, but a very low latency landing and transformation, so that data that is time-sensitive can join the historical data. >> Absolutely, absolutely. So what we've done, is focus on real-time availability of data. So when we feed the data into the Data Lake, we fit it into ways, one is directly into Hive, but we also go through a streaming architecture, like Kafka, in the case of Hortonworks, can also fit also very well into HDF. So then the next step in the process, is producing those analytic data sets, or data source, out of it, which we enable, and what we do is design it together with our partners, with our inner customers. So again when we work on Replicate, then we worked on Compose, we worked very close with Fortune companies trying to deal with these challenges, so we can design a product. In the case of Compose for Hive for example, we have done a lot of collaboration, at a product engineering level, with Hortonworks, to leverage the latest and greatest in Hive 2.2, Hive LLAP, to be able to push down transformations, so those can be done faster, including real-time, so those datasets can be updated on a frequent basis. >> You talked about kind of customer requirements, either those specific or not, obviously talking to telecommunications company, are you seeing, Itamar, from Attunity's perspective, more of this need to... Alright, the data's in the Lake, or first it comes to the swamp, now it's in the Lake, to start partitioning it, are you seeing this need driven in specific industries, or is this really pretty horizontal? >> That's a good question and this is definitely a horizontal need, it's part of the infrastructure needs, so Verizon is a great customer, and we even worked similarly in telecommunications, we've been working with other customers in other industries, from manufacturing, to retail, to health care, to automotive and others, and in all of those cases it's on a foundation level, it's very similar architectural challenges. You need to ingest the data, you want to do it fast, you want to do it incrementally or continuously, even if you're loading directly into Hadoop. Naturally, when you're loading the data through a Kafka, or streaming architecture, it's a continuous fashon, and then you partition the data. So the partitioning of the data is kind of inherent to the architecture, and then you need to help deal with the data, for the next step in the process. And we're doing it both with Compose for Hive, but also for customers using streaming architectures like Kafka, we provide the mechanisms, from supporting or facilitating things like schema unpollution, and schema decoding, to be able to facilitate the downstream process of processing those partitions of data, so we can make the data available, that works both for analytics and streaming analytics, as well as for scenarios like microservices, where the way in which you partition the data or deliver the data, allows each microservice to pick up on the data it needs, from the relevant partition. >> Well guys, this has been a really informative conversation. Congratulations, Itamar, on the new announcement that you guys made today. >> Thank you very much. >> Lisa: Arvin, great to hear the use case and how Verizon really sounds quite pioneering in what you're doing, wish you continued success there, we look forward to hearing what's next for Verizon, we want to thank you for watching the CUBE, we are again live, day two, of the DataWorks summit, #DWS17, before me my co-host George Gilbert, I am Lisa Martin, stick around, we'll be right back. (relaxed techno music)

Published Date : Jun 14 2017

SUMMARY :

in the heart of Silicon Valley, and we are joined by a couple of guys, Thank you very much, good to be here, the Director of Technology Services for Verizon, at the DataWorks summit, So the reason we kind of started looking at this, that people are going to hear tomorrow and the tools, as well as to kind of close the loop on, than the typical stories we hear about Data Lakes. and bring it into the same kind of data models. So it sounds like the ETL process and the nuances that they have over the years, how the Data Lake made that easier. do the ETL and build reports for the to consume, and it's got to inter-operate, and it is able to bring all the data and it sounds like together with Attunity, and the CDC architecture, we're able to get data in, and the analytic system, getting the data to the Lake. can join the historical data. like Kafka, in the case of Hortonworks, Alright, the data's in the Lake, You need to ingest the data, you want to do it fast, Congratulations, Itamar, on the new announcement Lisa: Arvin, great to hear the use case

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Breaking Analysis: AI Goes Mainstream But ROI Remains Elusive


 

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> A decade of big data investments combined with cloud scale, the rise of much more cost effective processing power. And the introduction of advanced tooling has catapulted machine intelligence to the forefront of technology investments. No matter what job you have, your operation will be AI powered within five years and machines may actually even be doing your job. Artificial intelligence is being infused into applications, infrastructure, equipment, and virtually every aspect of our lives. AI is proving to be extremely helpful at things like controlling vehicles, speeding up medical diagnoses, processing language, advancing science, and generally raising the stakes on what it means to apply technology for business advantage. But business value realization has been a challenge for most organizations due to lack of skills, complexity of programming models, immature technology integration, sizable upfront investments, ethical concerns, and lack of business alignment. Mastering AI technology will not be a requirement for success in our view. However, figuring out how and where to apply AI to your business will be crucial. That means understanding the business case, picking the right technology partner, experimenting in bite-sized chunks, and quickly identifying winners to double down on from an investment standpoint. Hello and welcome to this week's Wiki-bond CUBE Insights powered by ETR. In this breaking analysis, we update you on the state of AI and what it means for the competition. And to do so, we invite into our studios Andy Thurai of Constellation Research. Andy covers AI deeply. He knows the players, he knows the pitfalls of AI investment, and he's a collaborator. Andy, great to have you on the program. Thanks for coming into our CUBE studios. >> Thanks for having me on. >> You're very welcome. Okay, let's set the table with a premise and a series of assertions we want to test with Andy. I'm going to lay 'em out. And then Andy, I'd love for you to comment. So, first of all, according to McKinsey, AI adoption has more than doubled since 2017, but only 10% of organizations report seeing significant ROI. That's a BCG and MIT study. And part of that challenge of AI is it requires data, is requires good data, data proficiency, which is not trivial, as you know. Firms that can master both data and AI, we believe are going to have a competitive advantage this decade. Hyperscalers, as we show you dominate AI and ML. We'll show you some data on that. And having said that, there's plenty of room for specialists. They need to partner with the cloud vendors for go to market productivity. And finally, organizations increasingly have to put data and AI at the center of their enterprises. And to do that, most are going to rely on vendor R&D to leverage AI and ML. In other words, Andy, they're going to buy it and apply it as opposed to build it. What are your thoughts on that setup and that premise? >> Yeah, I see that a lot happening in the field, right? So first of all, the only 10% of realizing a return on investment. That's so true because we talked about this earlier, the most companies are still in the innovation cycle. So they're trying to innovate and see what they can do to apply. A lot of these times when you look at the solutions, what they come up with or the models they create, the experimentation they do, most times they don't even have a good business case to solve, right? So they just experiment and then they figure it out, "Oh my God, this model is working. Can we do something to solve it?" So it's like you found a hammer and then you're trying to find the needle kind of thing, right? That never works. >> 'Cause it's cool or whatever it is. >> It is, right? So that's why, I always advise, when they come to me and ask me things like, "Hey, what's the right way to do it? What is the secret sauce?" And, we talked about this. The first thing I tell them is, "Find out what is the business case that's having the most amount of problems, that that can be solved using some of the AI use cases," right? Not all of them can be solved. Even after you experiment, do the whole nine yards, spend millions of dollars on that, right? And later on you make it efficient only by saving maybe $50,000 for the company or a $100,000 for the company, is it really even worth the experiment, right? So you got to start with the saying that, you know, where's the base for this happening? Where's the need? What's a business use case? It doesn't have to be about cost efficient and saving money in the existing processes. It could be a new thing. You want to bring in a new revenue stream, but figure out what is a business use case, how much money potentially I can make off of that. The same way that start-ups go after. Right? >> Yeah. Pretty straightforward. All right, let's take a look at where ML and AI fit relative to the other hot sectors of the ETR dataset. This XY graph shows net score spending velocity in the vertical axis and presence in the survey, they call it sector perversion for the October survey, the January survey's in the field. Then that squiggly line on ML/AI represents the progression. Since the January 21 survey, you can see the downward trajectory. And we position ML and AI relative to the other big four hot sectors or big three, including, ML/AI is four. Containers, cloud and RPA. These have consistently performed above that magic 40% red dotted line for most of the past two years. Anything above 40%, we think is highly elevated. And we've just included analytics and big data for context and relevant adjacentness, if you will. Now note that green arrow moving toward, you know, the 40% mark on ML/AI. I got a glimpse of the January survey, which is in the field. It's got more than a thousand responses already, and it's trending up for the current survey. So Andy, what do you make of this downward trajectory over the past seven quarters and the presumed uptick in the coming months? >> So one of the things you have to keep in mind is when the pandemic happened, it's about survival mode, right? So when somebody's in a survival mode, what happens, the luxury and the innovations get cut. That's what happens. And this is exactly what happened in the situation. So as you can see in the last seven quarters, which is almost dating back close to pandemic, everybody was trying to keep their operations alive, especially digital operations. How do I keep the lights on? That's the most important thing for them. So while the numbers spent on AI, ML is less overall, I still think the AI ML to spend to sort of like a employee experience or the IT ops, AI ops, ML ops, as we talked about, some of those areas actually went up. There are companies, we talked about it, Atlassian had a lot of platform issues till the amount of money people are spending on that is exorbitant and simply because they are offering the solution that was not available other way. So there are companies out there, you can take AoPS or incident management for that matter, right? A lot of companies have a digital insurance, they don't know how to properly manage it. How do you find an intern solve it immediately? That's all using AI ML and some of those areas actually growing unbelievable, the companies in that area. >> So this is a really good point. If you can you bring up that chart again, what Andy's saying is a lot of the companies in the ETR taxonomy that are doing things with AI might not necessarily show up in a granular fashion. And I think the other point I would make is, these are still highly elevated numbers. If you put on like storage and servers, they would read way, way down the list. And, look in the pandemic, we had to deal with work from home, we had to re-architect the network, we had to worry about security. So those are really good points that you made there. Let's, unpack this a little bit and look at the ML AI sector and the ETR data and specifically at the players and get Andy to comment on this. This chart here shows the same x y dimensions, and it just notes some of the players that are specifically have services and products that people spend money on, that CIOs and IT buyers can comment on. So the table insert shows how the companies are plotted, it's net score, and then the ends in the survey. And Andy, the hyperscalers are dominant, as you can see. You see Databricks there showing strong as a specialist, and then you got to pack a six or seven in there. And then Oracle and IBM, kind of the big whales of yester year are in the mix. And to your point, companies like Salesforce that you mentioned to me offline aren't in that mix, but they do a lot in AI. But what are your takeaways from that data? >> If you could put the slide back on please. I want to make quick comments on a couple of those. So the first one is, it's surprising other hyperscalers, right? As you and I talked about this earlier, AWS is more about logo blocks. We discussed that, right? >> Like what? Like a SageMaker as an example. >> We'll give you all the components what do you need. Whether it's MLOps component or whether it's, CodeWhisperer that we talked about, or a oral platform or data or data, whatever you want. They'll give you the blocks and then you'll build things on top of it, right? But Google took a different way. Matter of fact, if we did those numbers a few years ago, Google would've been number one because they did a lot of work with their acquisition of DeepMind and other things. They're way ahead of the pack when it comes to AI for longest time. Now, I think Microsoft's move of partnering and taking a huge competitor out would open the eyes is unbelievable. You saw that everybody is talking about chat GPI, right? And the open AI tool and ChatGPT rather. Remember as Warren Buffet is saying that, when my laundry lady comes and talk to me about stock market, it's heated up. So that's how it's heated up. Everybody's using ChatGPT. What that means is at the end of the day is they're creating, it's still in beta, keep in mind. It's not fully... >> Can you play with it a little bit? >> I have a little bit. >> I have, but it's good and it's not good. You know what I mean? >> Look, so at the end of the day, you take the massive text of all the available text in the world today, mass them all together. And then you ask a question, it's going to basically search through that and figure it out and answer that back. Yes, it's good. But again, as we discussed, if there's no business use case of what problem you're going to solve. This is building hype. But then eventually they'll figure out, for example, all your chats, online chats, could be aided by your AI chat bots, which is already there, which is not there at that level. This could build help that, right? Or the other thing we talked about is one of the areas where I'm more concerned about is that it is able to produce equal enough original text at the level that humans can produce, for example, ChatGPT or the equal enough, the large language transformer can help you write stories as of Shakespeare wrote it. Pretty close to it. It'll learn from that. So when it comes down to it, talk about creating messages, articles, blogs, especially during political seasons, not necessarily just in US, but anywhere for that matter. If people are able to produce at the emission speed and throw it at the consumers and confuse them, the elections can be won, the governments can be toppled. >> Because to your point about chatbots is chatbots have obviously, reduced the number of bodies that you need to support chat. But they haven't solved the problem of serving consumers. Most of the chat bots are conditioned response, which of the following best describes your problem? >> The current chatbot. >> Yeah. Hey, did we solve your problem? No. Is the answer. So that has some real potential. But if you could bring up that slide again, Ken, I mean you've got the hyperscalers that are dominant. You talked about Google and Microsoft is ubiquitous, they seem to be dominant in every ETR category. But then you have these other specialists. How do those guys compete? And maybe you could even, cite some of the guys that you know, how do they compete with the hyperscalers? What's the key there for like a C3 ai or some of the others that are on there? >> So I've spoken with at least two of the CEOs of the smaller companies that you have on the list. One of the things they're worried about is that if they continue to operate independently without being part of hyperscaler, either the hyperscalers will develop something to compete against them full scale, or they'll become irrelevant. Because at the end of the day, look, cloud is dominant. Not many companies are going to do like AI modeling and training and deployment the whole nine yards by independent by themselves. They're going to depend on one of the clouds, right? So if they're already going to be in the cloud, by taking them out to come to you, it's going to be extremely difficult issue to solve. So all these companies are going and saying, "You know what? We need to be in hyperscalers." For example, you could have looked at DataRobot recently, they made announcements, Google and AWS, and they are all over the place. So you need to go where the customers are. Right? >> All right, before we go on, I want to share some other data from ETR and why people adopt AI and get your feedback. So the data historically shows that feature breadth and technical capabilities were the main decision points for AI adoption, historically. What says to me that it's too much focus on technology. In your view, is that changing? Does it have to change? Will it change? >> Yes. Simple answer is yes. So here's the thing. The data you're speaking from is from previous years. >> Yes >> I can guarantee you, if you look at the latest data that's coming in now, those two will be a secondary and tertiary points. The number one would be about ROI. And how do I achieve? I've spent ton of money on all of my experiments. This is the same thing theme I'm seeing across when talking to everybody who's spending money on AI. I've spent so much money on it. When can I get it live in production? How much, how can I quickly get it? Because you know, the board is breathing down their neck. You already spend this much money. Show me something that's valuable. So the ROI is going to become, take it from me, I'm predicting this for 2023, that's going to become number one. >> Yeah, and if people focus on it, they'll figure it out. Okay. Let's take a look at some of the top players that won, some of the names we just looked at and double click on that and break down their spending profile. So the chart here shows the net score, how net score is calculated. So pay attention to the second set of bars that Databricks, who was pretty prominent on the previous chart. And we've annotated the colors. The lime green is, we're bringing the platform in new. The forest green is, we're going to spend 6% or more relative to last year. And the gray is flat spending. The pinkish is our spending's going to be down on AI and ML, 6% or worse. And the red is churn. So you don't want big red. You subtract the reds from the greens and you get net score, which is shown by those blue dots that you see there. So AWS has the highest net score and very little churn. I mean, single low single digit churn. But notably, you see Databricks and DataRobot are next in line within Microsoft and Google also, they've got very low churn. Andy, what are your thoughts on this data? >> So a couple of things that stands out to me. Most of them are in line with my conversation with customers. Couple of them stood out to me on how bad IBM Watson is doing. >> Yeah, bring that back up if you would. Let's take a look at that. IBM Watson is the far right and the red, that bright red is churning and again, you want low red here. Why do you think that is? >> Well, so look, IBM has been in the forefront of innovating things for many, many years now, right? And over the course of years we talked about this, they moved from a product innovation centric company into more of a services company. And over the years they were making, as at one point, you know that they were making about majority of that money from services. Now things have changed Arvind has taken over, he came from research. So he's doing a great job of trying to reinvent themselves as a company. But it's going to have a long way to catch up. IBM Watson, if you think about it, that played what, jeopardy and chess years ago, like 15 years ago? >> It was jaw dropping when you first saw it. And then they weren't able to commercialize that. >> Yeah. >> And you're making a good point. When Gerstner took over IBM at the time, John Akers wanted to split the company up. He wanted to have a database company, he wanted to have a storage company. Because that's where the industry trend was, Gerstner said no, he came from AMEX, right? He came from American Express. He said, "No, we're going to have a single throat to choke for the customer." They bought PWC for relatively short money. I think it was $15 billion, completely transformed and I would argue saved IBM. But the trade off was, it sort of took them out of product leadership. And so from Gerstner to Palmisano to Remedi, it was really a services led company. And I think Arvind is really bringing it back to a product company with strong consulting. I mean, that's one of the pillars. And so I think that's, they've got a strong story in data and AI. They just got to sort of bring it together and better. Bring that chart up one more time. I want to, the other point is Oracle, Oracle sort of has the dominant lock-in for mission critical database and they're sort of applying AI there. But to your point, they're really not an AI company in the sense that they're taking unstructured data and doing sort of new things. It's really about how to make Oracle better, right? >> Well, you got to remember, Oracle is about database for the structure data. So in yesterday's world, they were dominant database. But you know, if you are to start storing like videos and texts and audio and other things, and then start doing search of vector search and all that, Oracle is not necessarily the database company of choice. And they're strongest thing being apps and building AI into the apps? They are kind of surviving in that area. But again, I wouldn't name them as an AI company, right? But the other thing that that surprised me in that list, what you showed me is yes, AWS is number one. >> Bring that back up if you would, Ken. >> AWS is number one as you, it should be. But what what actually caught me by surprise is how DataRobot is holding, you know? I mean, look at that. The either net new addition and or expansion, DataRobot seem to be doing equally well, even better than Microsoft and Google. That surprises me. >> DataRobot's, and again, this is a function of spending momentum. So remember from the previous chart that Microsoft and Google, much, much larger than DataRobot. DataRobot more niche. But with spending velocity and has always had strong spending velocity, despite some of the recent challenges, organizational challenges. And then you see these other specialists, H2O.ai, Anaconda, dataiku, little bit of red showing there C3.ai. But these again, to stress are the sort of specialists other than obviously the hyperscalers. These are the specialists in AI. All right, so we hit the bigger names in the sector. Now let's take a look at the emerging technology companies. And one of the gems of the ETR dataset is the emerging technology survey. It's called ETS. They used to just do it like twice a year. It's now run four times a year. I just discovered it kind of mid-2022. And it's exclusively focused on private companies that are potential disruptors, they might be M&A candidates and if they've raised enough money, they could be acquirers of companies as well. So Databricks would be an example. They've made a number of investments in companies. SNEAK would be another good example. Companies that are private, but they're buyers, they hope to go IPO at some point in time. So this chart here, shows the emerging companies in the ML AI sector of the ETR dataset. So the dimensions of this are similar, they're net sentiment on the Y axis and mind share on the X axis. Basically, the ETS study measures awareness on the x axis and intent to do something with, evaluate or implement or not, on that vertical axis. So it's like net score on the vertical where negatives are subtracted from the positives. And again, mind share is vendor awareness. That's the horizontal axis. Now that inserted table shows net sentiment and the ends in the survey, which informs the position of the dots. And you'll notice we're plotting TensorFlow as well. We know that's not a company, but it's there for reference as open source tooling is an option for customers. And ETR sometimes like to show that as a reference point. Now we've also drawn a line for Databricks to show how relatively dominant they've become in the past 10 ETS surveys and sort of mind share going back to late 2018. And you can see a dozen or so other emerging tech vendors. So Andy, I want you to share your thoughts on these players, who were the ones to watch, name some names. We'll bring that data back up as you as you comment. >> So Databricks, as you said, remember we talked about how Oracle is not necessarily the database of the choice, you know? So Databricks is kind of trying to solve some of the issue for AI/ML workloads, right? And the problem is also there is no one company that could solve all of the problems. For example, if you look at the names in here, some of them are database names, some of them are platform names, some of them are like MLOps companies like, DataRobot (indistinct) and others. And some of them are like future based companies like, you know, the Techton and stuff. >> So it's a mix of those sub sectors? >> It's a mix of those companies. >> We'll talk to ETR about that. They'd be interested in your input on how to make this more granular and these sub-sectors. You got Hugging Face in here, >> Which is NLP, yeah. >> Okay. So your take, are these companies going to get acquired? Are they going to go IPO? Are they going to merge? >> Well, most of them going to get acquired. My prediction would be most of them will get acquired because look, at the end of the day, hyperscalers need these capabilities, right? So they're going to either create their own, AWS is very good at doing that. They have done a lot of those things. But the other ones, like for particularly Azure, they're going to look at it and saying that, "You know what, it's going to take time for me to build this. Why don't I just go and buy you?" Right? Or or even the smaller players like Oracle or IBM Cloud, this will exist. They might even take a look at them, right? So at the end of the day, a lot of these companies are going to get acquired or merged with others. >> Yeah. All right, let's wrap with some final thoughts. I'm going to make some comments Andy, and then ask you to dig in here. Look, despite the challenge of leveraging AI, you know, Ken, if you could bring up the next chart. We're not repeating, we're not predicting the AI winter of the 1990s. Machine intelligence. It's a superpower that's going to permeate every aspect of the technology industry. AI and data strategies have to be connected. Leveraging first party data is going to increase AI competitiveness and shorten time to value. Andy, I'd love your thoughts on that. I know you've got some thoughts on governance and AI ethics. You know, we talked about ChatGBT, Deepfakes, help us unpack all these trends. >> So there's so much information packed up there, right? The AI and data strategy, that's very, very, very important. If you don't have a proper data, people don't realize that AI is, your AI is the morals that you built on, it's predominantly based on the data what you have. It's not, AI cannot predict something that's going to happen without knowing what it is. It need to be trained, it need to understand what is it you're talking about. So 99% of the time you got to have a good data for you to train. So this where I mentioned to you, the problem is a lot of these companies can't afford to collect the real world data because it takes too long, it's too expensive. So a lot of these companies are trying to do the synthetic data way. It has its own set of issues because you can't use all... >> What's that synthetic data? Explain that. >> Synthetic data is basically not a real world data, but it's a created or simulated data equal and based on real data. It looks, feels, smells, taste like a real data, but it's not exactly real data, right? This is particularly useful in the financial and healthcare industry for world. So you don't have to, at the end of the day, if you have real data about your and my medical history data, if you redact it, you can still reverse this. It's fairly easy, right? >> Yeah, yeah. >> So by creating a synthetic data, there is no correlation between the real data and the synthetic data. >> So that's part of AI ethics and privacy and, okay. >> So the synthetic data, the issue with that is that when you're trying to commingle that with that, you can't create models based on just on synthetic data because synthetic data, as I said is artificial data. So basically you're creating artificial models, so you got to blend in properly that that blend is the problem. And you know how much of real data, how much of synthetic data you could use. You got to use judgment between efficiency cost and the time duration stuff. So that's one-- >> And risk >> And the risk involved with that. And the secondary issues which we talked about is that when you're creating, okay, you take a business use case, okay, you think about investing things, you build the whole thing out and you're trying to put it out into the market. Most companies that I talk to don't have a proper governance in place. They don't have ethics standards in place. They don't worry about the biases in data, they just go on trying to solve a business case >> It's wild west. >> 'Cause that's what they start. It's a wild west! And then at the end of the day when they are close to some legal litigation action or something or something else happens and that's when the Oh Shit! moments happens, right? And then they come in and say, "You know what, how do I fix this?" The governance, security and all of those things, ethics bias, data bias, de-biasing, none of them can be an afterthought. It got to start with the, from the get-go. So you got to start at the beginning saying that, "You know what, I'm going to do all of those AI programs, but before we get into this, we got to set some framework for doing all these things properly." Right? And then the-- >> Yeah. So let's go back to the key points. I want to bring up the cloud again. Because you got to get cloud right. Getting that right matters in AI to the points that you were making earlier. You can't just be out on an island and hyperscalers, they're going to obviously continue to do well. They get more and more data's going into the cloud and they have the native tools. To your point, in the case of AWS, Microsoft's obviously ubiquitous. Google's got great capabilities here. They've got integrated ecosystems partners that are going to continue to strengthen through the decade. What are your thoughts here? >> So a couple of things. One is the last mile ML or last mile AI that nobody's talking about. So that need to be attended to. There are lot of players in the market that coming up, when I talk about last mile, I'm talking about after you're done with the experimentation of the model, how fast and quickly and efficiently can you get it to production? So that's production being-- >> Compressing that time is going to put dollars in your pocket. >> Exactly. Right. >> So once, >> If you got it right. >> If you get it right, of course. So there are, there are a couple of issues with that. Once you figure out that model is working, that's perfect. People don't realize, the moment you decide that moment when the decision is made, it's like a new car. After you purchase the value decreases on a minute basis. Same thing with the models. Once the model is created, you need to be in production right away because it starts losing it value on a seconds minute basis. So issue number one, how fast can I get it over there? So your deployment, you are inferencing efficiently at the edge locations, your optimization, your security, all of this is at issue. But you know what is more important than that in the last mile? You keep the model up, you continue to work on, again, going back to the car analogy, at one point you got to figure out your car is costing more than to operate. So you got to get a new car, right? And that's the same thing with the models as well. If your model has reached a stage, it is actually a potential risk for your operation. To give you an idea, if Uber has a model, the first time when you get a car from going from point A to B cost you $60. If the model decayed the next time I might give you a $40 rate, I would take it definitely. But it's lost for the company. The business risk associated with operating on a bad model, you should realize it immediately, pull the model out, retrain it, redeploy it. That's is key. >> And that's got to be huge in security model recency and security to the extent that you can get real time is big. I mean you, you see Palo Alto, CrowdStrike, a lot of other security companies are injecting AI. Again, they won't show up in the ETR ML/AI taxonomy per se as a pure play. But ServiceNow is another company that you have have mentioned to me, offline. AI is just getting embedded everywhere. >> Yep. >> And then I'm glad you brought up, kind of real-time inferencing 'cause a lot of the modeling, if we can go back to the last point that we're going to make, a lot of the AI today is modeling done in the cloud. The last point we wanted to make here, I'd love to get your thoughts on this, is real-time AI inferencing for instance at the edge is going to become increasingly important for us. It's going to usher in new economics, new types of silicon, particularly arm-based. We've covered that a lot on "Breaking Analysis", new tooling, new companies and that could disrupt the sort of cloud model if new economics emerge. 'Cause cloud obviously very centralized, they're trying to decentralize it. But over the course of this decade we could see some real disruption there. Andy, give us your final thoughts on that. >> Yes and no. I mean at the end of the day, cloud is kind of centralized now, but a lot of this companies including, AWS is kind of trying to decentralize that by putting their own sub-centers and edge locations. >> Local zones, outposts. >> Yeah, exactly. Particularly the outpost concept. And if it can even become like a micro center and stuff, it won't go to the localized level of, I go to a single IOT level. But again, the cloud extends itself to that level. So if there is an opportunity need for it, the hyperscalers will figure out a way to fit that model. So I wouldn't too much worry about that, about deployment and where to have it and what to do with that. But you know, figure out the right business use case, get the right data, get the ethics and governance place and make sure they get it to production and make sure you pull the model out when it's not operating well. >> Excellent advice. Andy, I got to thank you for coming into the studio today, helping us with this "Breaking Analysis" segment. Outstanding collaboration and insights and input in today's episode. Hope we can do more. >> Thank you. Thanks for having me. I appreciate it. >> You're very welcome. All right. I want to thank Alex Marson who's on production and manages the podcast. Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and our newsletters. And Rob Hoof is our editor-in-chief over at Silicon Angle. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, all you got to do is search "Breaking Analysis" podcast. I publish each week on wikibon.com and silicon angle.com or you can email me at david.vellante@siliconangle.com to get in touch, or DM me at dvellante or comment on our LinkedIn posts. Please check out ETR.AI for the best survey data and the enterprise tech business, Constellation Research. Andy publishes there some awesome information on AI and data. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody and we'll see you next time on "Breaking Analysis". (gentle closing tune plays)

Published Date : Dec 29 2022

SUMMARY :

bringing you data-driven Andy, great to have you on the program. and AI at the center of their enterprises. So it's like you found a of the AI use cases," right? I got a glimpse of the January survey, So one of the things and it just notes some of the players So the first one is, Like a And the open AI tool and ChatGPT rather. I have, but it's of all the available text of bodies that you need or some of the others that are on there? One of the things they're So the data historically So here's the thing. So the ROI is going to So the chart here shows the net score, Couple of them stood out to me IBM Watson is the far right and the red, And over the course of when you first saw it. I mean, that's one of the pillars. Oracle is not necessarily the how DataRobot is holding, you know? So it's like net score on the vertical database of the choice, you know? on how to make this more Are they going to go IPO? So at the end of the day, of the technology industry. So 99% of the time you What's that synthetic at the end of the day, and the synthetic data. So that's part of AI that blend is the problem. And the risk involved with that. So you got to start at data's going into the cloud So that need to be attended to. is going to put dollars the first time when you that you can get real time is big. a lot of the AI today is I mean at the end of the day, and make sure they get it to production Andy, I got to thank you for Thanks for having me. and manages the podcast.

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Day 4 Keynote Analysis | AWS re:Invent 2022


 

(upbeat music) >> Good morning everybody. Welcome back to Las Vegas. This is day four of theCUBE's wall-to-wall coverage of our Super Bowl, aka AWS re:Invent 2022. I'm here with my co-host, Paul Gillin. My name is Dave Vellante. Sanjay Poonen is in the house, CEO and president of Cohesity. He's sitting in as our guest market watcher, market analyst, you know, deep expertise, new to the job at Cohesity. He was kind enough to sit in, and help us break down what's happening at re:Invent. But Paul, first thing, this morning we heard from Werner Vogels. He was basically given a masterclass on system design. It reminded me of mainframes years ago. When we used to, you know, bury through those IBM blue books and red books. You remember those Sanjay? That's how we- learned back then. >> Oh God, I remember those, Yeah. >> But it made me think, wow, now you know IBM's more of a systems design, nobody talks about IBM anymore. Everybody talks about Amazon. So you wonder, 20 years from now, you know what it's going to be. But >> Well- >> Werner's amazing. >> He pulled out a 24 year old document. >> Yup. >> That he had written early in Amazon's evolution about synchronous design or about essentially distributed architectures that turned out to be prophetic. >> His big thing was nature is asynchronous. So systems are asynchronous. Synchronous is an illusion. It's an abstraction. It's kind of interesting. But, you know- >> Yeah, I mean I've had synonyms for things. Timeless architecture. Werner's an absolute legend. I mean, when you think about folks who've had, you know, impact on technology, you think of people like Jony Ive in design. >> Dave: Yeah. >> You got to think about people like Werner in architecture and just the fact that Andy and the team have been able to keep him engaged that long... I pay attention to his keynote. Peter DeSantis has obviously been very, very influential. And then of course, you know, Adam did a good job, you know, watching from, you know, having watched since I was at the first AWS re:Invent conference, at time was President SAP and there was only a thousand people at this event, okay? Andy had me on stage. I think I was one of the first guest of any tech company in 2011. And to see now this become like, it's a mecca. It's a mother of all IT events, and watch sort of even the transition from Andy to Adam is very special. I got to catch some of Ruba's keynote. So while there's some new people in the mix here, this has become a force of nature. And the last time I was here was 2019, before Covid, watched the last two ones online. But it feels like, I don't know 'about what you guys think, it feels like it's back to 2019 levels. >> I was here in 2019. I feel like this was bigger than 2019 but some people have said that it's about the same. >> I think it was 60,000 versus 50,000. >> Yes. So close. >> It was a little bigger in 2019. But it feels like it's more active. >> And then last year, Sanjay, you weren't here but it was 25,000, which was amazing 'cause it was right in that little space between Omicron, before Omicron hit. But you know, let me ask you a question and this is really more of a question about Amazon's maturity and I know you've been following them since early days. But the way I get the question, number one question I get from people is how is Amazon AWS going to be different under Adam than it was under Andy? What do you think? >> I mean, Adam's not new because he was here before. In some senses he knows the Amazon culture from prior, when he was running sales and marketing prior. But then he took the time off and came back. I mean, this will always be, I think, somewhat Andy's baby, right? Because he was the... I, you know, sent him a text, "You should be really proud of what you accomplished", but you know, I think he also, I asked him when I saw him a few weeks ago "Are you going to come to re:Invent?" And he says, "No, I want to leave this to be Adam's show." And Adam's going to have a slightly different view. His keynotes are probably half the time. It's a little bit more vision. There was a lot more customer stories at the beginning of it. Taking you back to the inspirational pieces of it. I think you're going to see them probably pulling up the stack and not just focused in infrastructure. Many of their platform services are evolved. Many of their, even application services. I'm surprised when I talk to customers. Like Amazon Connect, their sort of call center type technologies, an app layer. It's getting a lot. I mean, I've talked to a couple of Fortune 500 companies that are moving off Ayer to Connect. I mean, it's happening and I did not know that. So it's, you know, I think as they move up the stack, the platform's gotten more... The data centric stack has gotten, and you know, in the area we're working with Cohesity, security, data protection, they're an investor in our company. So this is an important, you know, both... I think tech player and a partner for many companies like us. >> I wonder the, you know, the marketplace... there's been a big push on the marketplace by all the cloud companies last couple of years. Do you see that disrupting the way softwares, enterprise software is sold? >> Oh, for sure. I mean, you have to be a ostrich with your head in the sand to not see this wave happening. I mean, what's it? $150 billion worth of revenue. Even though the growth rates dipped a little bit the last quarter or so, it's still aggregatively between Amazon and Azure and Google, you know, 30% growth. And I think we're still in the second or third inning off a grand 1 trillion or 2 trillion of IT, shifting not all of it to the cloud, but significantly faster. So if you add up all of the big things of the on-premise world, they're, you know, they got to a certain size, their growth is stable, but stalling. These guys are growing significantly faster. And then if you add on top of them, platform companies the data companies, Snowflake, MongoDB, Databricks, you know, Datadog, and then apps companies on top of that. I think the move to the Cloud is inevitable. In SaaS companies, I don't know why you would ever implement a CRM solution on-prem. It's all gone to the Cloud. >> Oh, it is. >> That happened 15 years ago. I mean, begin within three, five years of the advent of Salesforce. And the same thing in HR. Why would you deploy a HR solution now? You've got Workday, you've got, you know, others that are so some of those apps markets are are just never coming back to an on-prem capability. >> Sanjay, I want to ask you, you built a reputation for being able to, you know, forecast accurately, hit your plan, you know, you hit your numbers, you're awesome operator. Even though you have a, you know, technology degree, which you know, that's a two-tool star, multi-tool star. But I call it the slingshot economy. This is like, I mean I've seen probably more downturns than anybody in here, you know, given... Well maybe, maybe- >> Maybe me. >> You and I both. I've never seen anything like this, where where visibility is so unpredictable. The economy is sling-shotting. It's like, oh, hurry up, go Covid, go, go go build, build, build supply, then pull back. And now going forward, now pulling back. Slootman said, you know, on the call, "Hey the guide, is the guide." He said, "we put it out there, We do our best to hit it." But you had CrowdStrike had issues you know, mid-market, ServiceNow. I saw McDermott on the other day on the, on the TV. I just want to pay, you know, buy from the guy. He's so (indistinct) >> But mixed, mixed results, Salesforce, you know, Octa now pre-announcing, hey, they're going to be, or announcing, you know, better visibility, forward guide. Elastic kind of got hit really hard. HPE and Dell actually doing really well in the enterprise. >> Yep. >> 'Course Dell getting killed in the client. But so what are you seeing out there? How, as an executive, do you deal with such poor visibility? >> I think, listen, what the last two or three years have taught us is, you know, with the supply chain crisis, with the surge that people thought you may need of, you know, spending potentially in the pandemic, you have to start off with your tech platform being 10 x better than everybody else. And differentiate, differentiate. 'Cause in a crowded market, but even in a market that's getting tougher, if you're not differentiating constantly through technology innovation, you're going to get left behind. So you named a few places, they're all technology innovators, but even if some of them are having challenges, and then I think you're constantly asking yourselves, how do you move from being a point product to a platform with more and more services where you're getting, you know, many of them moving really fast. In the case of Roe, I like him a lot. He's probably one of the most savvy operators, also that I respect. He calls these speedboats, and you know, his core platform started off with the firewall network security. But he's built now a very credible cloud security, cloud AI security business. And I think that's how you need to be thinking as a tech executive. I mean, if you got core, your core beachhead 10 x better than everybody else. And as you move to adjacencies in these new platforms, have you got now speedboats that are getting to a point where they are competitive advantage? Then as you think of the go-to-market perspective, it really depends on where you are as a company. For a company like our size, we need partners a lot more. Because if we're going to, you know, stand on the shoulders of giants like Isaac Newton said, "I see clearly because I stand on the shoulders giants." I need to really go and cultivate Amazon so they become our lead partner in cloud. And then appropriately Microsoft and Google where I need to. And security. Part of what we announced last week was, last month, yeah, last couple of weeks ago, was the data security alliance with the biggest security players. What was I trying to do with that? First time ever done in my industry was get Palo Alto, CrowdStrike, Wallace, Tenable, CyberArk, Splunk, all to build an alliance with me so I could stand on their shoulders with them helping me. If you're a bigger company, you're constantly asking yourself "how do you make sure you're getting your, like Amazon, their top hundred customers spending more with that?" So I think the the playbook evolves, and I'm watching some of these best companies through this time navigate through this. And I think leadership is going to be tested in enormously interesting ways. >> I'll say. I mean, Snowflake is really interesting because they... 67% growth, which is, I mean, that's best in class for a company that's $2 billion. And, but their guide was still, you know, pretty aggressive. You know, so it's like, do you, you know, when it when it's good times you go, "hey, we can we can guide conservatively and know we can beat it." But when you're not certain, you can't dial down too far 'cause your investors start to bail on you. It's a really tricky- >> But Dave, I think listen, at the end of the day, I mean every CEO should not be worried about the short term up and down in the stock price. You're building a long-term multi-billion dollar company. In the case of Frank, he has, I think I shot to a $10 billion, you know, analytics data warehousing data management company on the back of that platform, because he's eyeing the market that, not just Teradata occupies today, but now Oracle occupies or other databases, right? So his tam as it grows bigger, you're going to have some of these things, but that market's big. I think same with Palo Alto. I mean Datadog's another company, 75% growth. >> Yeah. >> At 20% margins, like almost rule of 95. >> Amazing. >> When they're going after, not just the observability market, they're eating up the sim market, security analytics, the APM market. So I think, you know, that's, you look at these case studies of companies who are going from point product to platforms and are steadily able to grow into new tams. You know, to me that's very inspiring. >> I get it. >> Sanjay: That's what I seek to do at our com. >> I get that it's a marathon, but you know, when you're at VMware, weren't you looking at the stock price every day just out of curiosity? I mean listen, you weren't micromanaging it. >> You do, but at the end of the day, and you certainly look at the days of earnings and so on so forth. >> Yeah. >> Because you want to create shareholder value. >> Yeah. >> I'm not saying that you should not but I think in obsession with that, you know, in a short term, >> Going to kill ya. >> Makes you, you know, sort of myopically focused on what may not be the right thing in the long term. Now in the long arc of time, if you're not creating shareholder value... Look at what happened to Steve Bomber. You needed Satya to come in to change things and he's created a lot of value. >> Dave: Yeah, big time. >> But I think in the short term, my comments were really on the quarter to quarter, but over a four a 12 quarter, if companies are growing and creating profitable growth, they're going to get the valuation they deserve. >> Dave: Yeah. >> Do you the... I want to ask you about something Arvind Krishna said in the previous IBM earnings call, that IT is deflationary and therefore it is resistant to the macroeconomic headwinds. So IT spending should actually thrive in a deflation, in a adverse economic climate. Do you think that's true? >> Not all forms of IT. I pay very close attention to surveys from, whether it's the industry analysts or the Morgan Stanleys, or Goldman Sachs. The financial analysts. And I think there's a gluc in certain sectors that will get pulled back. Traditional view is when the economies are growing people spend on the top line, front office stuff, sales, marketing. If you go and look at just the cloud 100 companies, which are the hottest private companies, and maybe with the public market companies, there's way too many companies focused on sales and marketing. Way too many. I think during a downsizing and recession, that's going to probably shrink some, because they were all built for the 2009 to 2021 era, where it was all about the top line. Okay, maybe there's now a proposition for companies who are focused on cost optimization, supply chain visibility. Security's been intangible, that I think is going to continue to an investment. So I tell, listen, if you are a tech investor or if you're an operator, pay attention to CIO priorities. And right now, in our business at Cohesity, part of the reason we've embraced things like ransomware protection, there is a big focus on security. And you know, by intelligently being a management and a security company around data, I do believe we'll continue to be extremely relevant to CIO budgets. There's a ransomware, 20 ransomware attempts every second. So things of that kind make you relevant in a bank. You have to stay relevant to a buying pattern or else you lose momentum. >> But I think what's happening now is actually IT spending's pretty good. I mean, I track this stuff pretty closely. It's just that expectations were so high and now you're seeing earnings estimates come down and so, okay, and then you, yeah, you've got the, you know the inflationary factors and your discounted cash flows but the market's actually pretty good. >> Yeah. >> You know, relative to other downturns that if this is not a... We're not actually not in a downturn. >> Yeah. >> Not yet anyway. It may be. >> There's a valuation there. >> You have to prepare. >> Not sales. >> Yeah, that's right. >> When I was on CNBC, I said "listen, it's a little bit like that story of Joseph. Seven years of feast, seven years of famine." You have to prepare for potentially your worst. And if it's not the worst, you're in good shape. So will it be a recession 2023? Maybe. You know, high interest rates, inflation, war in Russia, Ukraine, maybe things do get bad. But if you belt tightening, if you're focused in operational excellence, if it's not a recession, you're pleasantly surprised. If it is one, you're prepared for it. >> All right. I'm going to put you in the spot and ask you for predictions. Expert analysis on the World Cup. What do you think? Give us the breakdown. (group laughs) >> As my... I wish India was in the World Cup, but you can't get enough Indians at all to play soccer well enough, but we're not, >> You play cricket, though. >> I'm a US man first. I would love to see one of Brazil, or Argentina. And as a Messi person, I don't know if you'll get that, but it would be really special for Messi to lead, to end his career like Maradonna winning a World Cup. I don't know if that'll happen. I'm probably going to go one of the Latin American countries, if the US doesn't make it far enough. But first loyalty to the US team, and then after one of the Latin American countries. >> And you think one of the Latin American countries is best bet to win or? >> I don't know. It's hard to tell. They're all... What happens now at this stage >> So close, right? >> is anybody could win. >> Yeah. You just have lots of shots of gold. I'm a big soccer fan. It could, I mean, I don't know if the US is favored to win, but if they get far enough, you get to the finals, anybody could win. >> I think they get Netherlands next, right? >> That's tough. >> Really tough. >> But... The European teams are good too, but I would like to see US go far enough, and then I'd like to see Latin America with team one of Argentina, or Brazil. That's my prediction. >> I know you're a big Cricket fan. Are you able to follow Cricket the way you like? >> At god unearthly times the night because they're in Australia, right? >> Oh yeah. >> Yeah. >> I watched the T-20 World Cup, select games of it. Yeah, you know, I'm not rapidly following every single game but the World Cup games, I catch you. >> Yeah, it's good. >> It's good. I mean, I love every sport. American football, soccer. >> That's great. >> You get into basketball now, I mean, I hope the Warriors come back strong. Hey, how about the Warriors Celtics? What do we think? We do it again? >> Well- >> This year. >> I'll tell you what- >> As a Boston Celtics- >> I would love that. I actually still, I have to pay off some folks from Palo Alto office with some bets still. We are seeing unprecedented NBA performance this year. >> Yeah. >> It's amazing. You look at the stats, it's like nothing. I know it's early. Like nothing we've ever seen before. So it's exciting. >> Well, always a pleasure talking to you guys. >> Great to have you on. >> Thanks for having me. >> Thank you. Love the expert analysis. >> Sanjay Poonen. Dave Vellante. Keep it right there. re:Invent 2022, day four. We're winding up in Las Vegas. We'll be right back. You're watching theCUBE, the leader in enterprise and emerging tech coverage. (lighthearted soft music)

Published Date : Dec 1 2022

SUMMARY :

When we used to, you know, Yeah. So you wonder, 20 years from now, out to be prophetic. But, you know- I mean, when you think you know, watching from, I feel like this was bigger than 2019 I think it was 60,000 But it feels like it's more active. But you know, let me ask you a question So this is an important, you know, both... I wonder the, you I mean, you have to be a ostrich you know, others that are so But I call it the slingshot economy. I just want to pay, you or announcing, you know, better But so what are you seeing out there? I mean, if you got core, you know, pretty aggressive. I think I shot to a $10 billion, you know, like almost rule of 95. So I think, you know, that's, I seek to do at our com. I mean listen, you and you certainly look Because you want to Now in the long arc of time, on the quarter to quarter, I want to ask you about And you know, by intelligently But I think what's happening now relative to other downturns It may be. But if you belt tightening, to put you in the spot but you can't get enough Indians at all But first loyalty to the US team, It's hard to tell. if the US is favored to win, and then I'd like to see Latin America the way you like? Yeah, you know, I'm not rapidly I mean, I love every sport. I mean, I hope the to pay off some folks You look at the stats, it's like nothing. talking to you guys. Love the expert analysis. in enterprise and emerging tech coverage.

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Alan Bivens & Becky Carroll, IBM | AWS re:Invent 2022


 

(upbeat music) (logo shimmers) >> Good afternoon everyone, and welcome back to AWS re Invent 2022. We are live here from the show floor in Las Vegas, Nevada, we're theCUBE, my name is Savannah Peterson, joined by John Furrier, John, are you excited for the next segment? >> I love the innovation story, this next segment's going to be really interesting, an example of ecosystem innovation in action, it'll be great. >> Yeah, our next guests are actually award-winning, I am very excited about that, please welcome Alan and Becky from IBM. Thank you both so much for being here, how's the show going for ya? Becky you got a, just a platinum smile, I'm going to go to you first, how's the show so far? >> No, it's going great. There's lots of buzz, lots of excitement this year, of course, three times the number of people, but it's fantastic. >> Three times the number of people- >> (indistinct) for last year. >> That is so exciting, so what is that... Do you know what the total is then? >> I think it's over 55,000. >> Ooh, loving that. >> John: A lot. >> It's a lot, you can tell by the hallways- >> Becky: It's a lot. >> John: It's crowded, right. >> Yeah, you can tell by just the energy and the, honestly the heat in here right now is pretty good. Alan, how are you feeling on the show floor this year? >> Awesome, awesome, we're meeting a lot of partners, talking to a lot of clients. We're really kind of showing them what the new IBM, AWS relationship is all about, so, beautiful time to be here. >> Well Alan, why don't you tell us what that partnership is about, to start us off? >> Sure, sure. So the partnership started with the relationship in our consulting services, and Becky's going to talk more about that, right? And it grew, this year it grew into the IBM software realm where we signed an agreement with AWS around May timeframe this year. >> I love it, so, like you said, you're just getting started- >> Just getting started. >> This is the beginning of something magic. >> We're just scratching the surface with this right? >> Savannah: Yeah. >> But it represents a huge move for IBM to meet our clients where they are, right? Meet 'em where they are with IBM technology, enterprise technology they're used to, but with the look and feel and usage model that they're used to with AWS. >> Absolutely and so to build on that, you know, we're really excited to be an AWS Premier Consulting Partner. We've had this relationship for a little over five years with AWS, I'd say it's really gone up a notch over the last year or two as we've been working more and more closely, doubling down on our investments, doubling down on our certifications, we've got over 15,000 people certified now, almost 16,000 actually- >> Savannah: Wow. >> 14 competencies, 16 service deliveries and counting. We cover a mass of information and services from Data Analytics, IoT, AI, all the way to Modernization, SAP, Security Services, right. So it's pretty comprehensive relationship, but in addition to the fantastic clients that we both share, we're doing some really great things around joint industry solutions, which I'll talk about in a few minutes and some of those are being launched at the conference this year, so that's even better. But the most exciting thing to me right now is that we just found out that we won the Global Innovator Partner of the Year award, and a LATAM Partner of the Year award. >> Savannah: Wow. >> John: That's (indistinct) >> So, super excited for IBM Consulting to win this, we're honored and it's just a great, exciting part to the conference. >> The news coming out of this event, we know tomorrow's going to be the big keynote for the new Head of the ecosystem, Ruba. We're hearing that it's going to be all about the ecosystem, enabling value creation, enabling new kinds of solutions. We heard from the CEO of AWS, this nextGen environment's upon us, it's very solution-oriented- >> Becky: Absolutely. >> A lot of technology, it's not an either or, it's an and equation, this is a huge new shift, I won't say shift, a continuation for AWS, and you guys, we've been covering, so you got the and situation going on... Innovation solutions and innovation technology and customers can choose, build a foundation or have it out of the box. What's your reaction to that? Do you think it's going to go well for AWS and IBM? >> I think it fits well into our partnership, right? The the thing you mentioned that I gravitate to the most is the customer gets to choose and the thing that's been most amazing about the partnership, both of these companies are maniacally focused on the customer, right? And so we've seen that come about as we work on ways the customer to access our technology, consume the technology, right? We've sold software on-prem to customers before, right, now we're going to be selling SaaS on AWS because we had customers that were on AWS, we're making it so that they can more easily purchase it by being in the marketplace, making it so they can draw down their committed spin with AWS, their customers like that a lot- [John] Yeah. >> Right. We've even gone further to enable our distributor network and our resellers, 'cause a lot of our customers have those relationships, so they can buy through them. And recently we've enabled the customer to leverage their EDP, their committed spend with AWS against IBM's ELA and structure, right, so you kind of get a double commit value from a customer point of view, so the amazing part is just been all about the customers. >> Well, that's interesting, you got the technology relationship with AWS, you mentioned how they're engaging with the software consumption in marketplace, licensed deals, there's all kinds of new business model innovations on top of the consumption and building. Then you got the consulting piece, which is again, a big part of, Adam calls it "Business transformation," which is the result of digital transformation. So digital transformation is the process, the outcome is the business transformation, that's kind of where it all kind of connects. Becky, what's your thoughts on the Amazon consulting relationships? Obviously the awards are great but- >> They are, no- >> What's the next step? Where does it go from here? >> I think the best way for me to describe it is to give you some rapid flyer client examples, you know, real customer stories and I think that's where it really, rubber meets the road, right? So one of the most recent examples are IBM CEO Arvind Krishna, in his three key results actually mentioned one of our big clients with AWS which is the Department of Veterans Affairs in the US and is an AI solution that's helped automate claims processing. So the veterans are trying to get their benefits, they submit the claims, snail mail, phone calls, you know, some in person, some over email- >> Savannah: Oh, it gives me all the feels hearing you talk about this- >> It's a process that used to take 25 to 30 days depending on the complexity of the claims, we've gotten it down with AWS down to within 24 hours we can get the veterans what they need really quickly so, I mean, that's just huge. And it's an exciting story that includes data analytics, AI and automation, so that's just one example. You know, we've got examples around SAP where we've developed a next generation SAP for HANA Platform for Phillips Carbon Black hosted on AWS, right? For them, it created an integrated, scalable, digital business, that cut out a hundred percent the capital cost from on-prem solutions. We've got security solutions around architectures for telecommunications advisors and of course we have lots of examples of migration and modernization and moving workloads using Red Hat to do that. So there's a lot of great client examples, so to me, this is the heart of what we do, like you said, both companies are really focused on clients, Amazon's customer-obsessed, and doing what we can for our clients together is where we get the impact. >> Yeah, that's one of the things that, it sounds kind of cliche, "Oh we're going to work backwards from the customer," I know Amazon says that, they do, you guys are also very customer-focused but the customers are changing. So I'd love to get your reaction because we're now in that cloud 2.0, I call that 2.0 or you got the Amazon Classic, my word, and then Next Gen Cloud coming, the customers are different, they're transforming because IT's not a department anymore, it's in the DevOps pipeline. The developers are driving a lot of IT but security and on DataOps, it's the structural change happening at the customer, how do you guys see that at IBM? I know we cover a lot of Red Hat and Arvind talks to us all the time, meeting the customer where they are, where are they? Where are the customers? Can you share your perspective on where they are? >> It's an astute observation, right, the customer is changing. We have both of those sets of customers, right, we still have the traditional customer, our relationship with Central IT, right, and driving governance and all of those things. But the folks that are innovating many times they're in the line of business, they're discovering solutions, they're building new things. And so we need our offerings to be available to them. We need them to understand how to use them and be convenient for these guys and take them through that process. So that change in the customer is one that we are embracing by making our offerings easy to consume, easy to use, and easy to build into solutions and then easy to parlay into what central IT needs to do for governance, compliance, and these types of things, it's becoming our new bread and butter. >> And what's really cool is- >> Is that easy button- >> We've been talking about- >> It's the easy button. >> The easy button a lot on the show this week and if you just, you just described it it's exactly what people want, go on Becky. >> Sorry about that, I was going to say, the cool part is that we're co-creating these things with our clients. So we're using things like the Amazon Working Backward that you just mentioned.` We're using the IBM garage methodology to get innovative to do design working, design thinking workshops, and think about where is that end user?, Where is that stakeholder? Where are they, they thinking, feeling, doing, saying how do we make the easier? How do we get the easy button for them so that they can have the right solutions for their businesses. We work mostly with lines of business in my part of the organization, and they're hungry for that. >> You know, we had a quote on theCUBE yesterday, Savannah remember one of our guests said, you know, back in the, you know, 1990s or two 2000s, if you had four production apps, it was considered complex >> Savannah: Yeah. >> You know, now you got hundreds of workloads, thousands of workloads, so, you know, this end-to-end vision that we heard that's playing out is getting more complex, but the easy button is where these abstraction layers and technology could come in. So it's getting more complex because there's more stuff but it's getting easier because- >> Savannah: What is the magnitude? >> You can make it easier. This is a dynamic, share your thoughts on that. >> It's getting more complex because our clients need to move faster, right, they need to be more agile, right, so not only are there thousands of applications there are hundreds of thousands microservices that are composing those applications. So they need capabilities that help them not just build but govern that structure and put the right compliance over that structure. So this relationship- >> Savannah: Lines of governance, yeah- >> This relationship we built with AWS is in our key areas, it's a strategic move, not a small thing for us, it covers things like automation and integration where you need to build that way. It covers things like data and AI where you need to do the analytics, even things like sustainability where we're totally aligned with what AWS is talking about and trying to do, right, so it's really a good match made there. >> John: It really sounds awesome. >> Yeah, it's clear. I want to dig in a little bit, I love the term, and I saw it in my, it stuck out to me in the notes right away, getting ready for you all, "maniacal", maniacal about the customer, maniacal about the community, I think that's really clear when we're talking about 24 days to 24 hours, like the veteran example that you gave right there, which I genuinely felt in my heart. These are the types of collaborations that really impact people's lives, tell me about some of the other trends or maybe a couple other examples you might have because I think sometimes when our head's in the clouds, we talk a lot about the tech and the functionality, we forget it's touching every single person walking around us, probably in a different way right now than we may even be aware- >> I think one of the things that's been, and our clients have been asking us for, is to help coming into this new era, right, so we've come out of a pandemic where a lot of them had to do some really, really basic quick decisions. Okay, "Contact Center, everyone work from home now." Okay, how do we do that? Okay, so we cobbled something together, now we're back, so what do we do? How do we create digital transformation around that so that we are going forward in a really positive way that works for our clients or for our contact center reps who are maybe used to working from home now versus what our clients need, the response times they need, and AWS has all the technology that we're working with like Amazon Connect to be able to pull those things together with some of our software like Watson Assistant. So those types of solutions are coming together out of that need and now we're moving into the trend where economy's getting tougher, right? More cost cutting potentially is coming, right, better efficiencies, how do we leverage our solutions and help our clients and customers do that? So I think that's what the customer obsession's about, is making sure we really understand where their pain points are, and not just solve them but maybe get rid of 'em. >> John: Yeah, great one. >> Yeah. And not developing in a silo, I mean, it's a classic subway problem, you got to be communicating with your community if you want to continue to serve them. And IBM's been serving their community for a very long time, which is super impressive, do you think they're ready for the challenge? >> Let's do it. >> So we have a new thing on theCUBE. >> Becky: Oh boy. >> We didn't warn you about this, but here we go. Although you told, Alan, you've mentioned you're feeling very cool with the microphone on, so I feel like, I'm going to put you in the hot seat first on this one. Not that I don't think Becky's going to smash it, but I feel like you're channeling the power of the microphone. New challenges, treat it like a 32nd Instagram reel-style story, a hot take, your thought leadership, money clip, you know, this is your moment. What is the biggest takeaway, most important thing happening at the show this year? >> Most important thing happening at the show? Well, I'm glad you mentioned it that way, because earlier you said we may have to sing (presenters and guests all laughing) >> So this is much better than- >> That's actually part of the close. >> John: Hey, hey. >> Don't worry, don't worry, I haven't forgotten that, it's your Instagram reel, go. (Savannah laughs) >> Original audio happening here on theCUBE, courtesy of Alan and IBM, I am so here for it. >> So what my takeaway and what I would like for the audience to take away, out of this conversation especially, but even broadly, the IBM AWS relationship is really like a landmark type of relationship, right? It's one of the biggest that we've established on both sides, right- >> Savannah: It seems huge, okay you are too monolith in the world of companies, like, yeah- >> Becky: Totally. >> It's huge. And it represents a strategic change on both sides, right? With that customer- >> Savannah: Fundamentally- >> In the middle right? >> Savannah: Yeah. >> So we're seeing things like, you know, AWS is working with us to make sure we're building products the way that a AWS client likes to consume them, right, so that we have the right integration, so they get that right look and feel, but they still get the enterprise level capabilities they're used to from IBM, right? So the big takeaway I like for people to take, is this is a new IBM, it's a new AWS and IBM relationship, and so expect more of that goodness, more of those new things coming out of it. [John] Excellent, wow. >> That was great, well done, you nailed it. and you're going to finish with some acapella, right? (Alan laughs) >> You got a pitch pipe ready? (everyone laughs) >> All right Becky, what about you? Give us your hot take. >> Well, so for me, the biggest takeaway is just the way this relationship has grown so much, so, like you said, it's the new IBM it's the new AWS, we were here last year, we had some good things, this year we're back at the show with joint solutions, have been jointly funded and co-created by AWS and IBM. This is huge, this is a really big opportunity and a really big deal that these two companies have come together, identified joint customer needs and we're going after 'em together and we're putting 'em in the booth. >> Savannah: So cool. And there's things like smart edge for welding solutions that are out there. >> Savannah: Yes. >> You know, I talked about, and it's, you know you wouldn't think, "Okay, well what's that?" There's a lot to that, a lot of saving when you look at how you do welding and if you apply things like visual AI and auditory AI to make sure a weld is good. I mean, I think these are, these things are cool, I geek out on these things- >> John: Every vertical. >> I'm geeking out with you right now, just geeking- >> Yeah, yeah, yeah, so- >> Every vertical is infected. >> They are and it's so impactful to have AWS just in lockstep with us, doing these solutions, it's so different from, you know, you kind of create something that you think your customers like and then you put it out there. >> Yeah, versus this moment. >> Yeah, they're better together. >> It's strategic partnership- >> It's truly a strategic partnership. and we're really bringing that this year to reinvent and so I'm super excited about that. >> Congratulations. >> Wow, well, congratulations again on your awards, on your new partnership, I can't wait to hear, I mean, we're seven months in, eight months in to this this SaaS side of the partnership, can't wait to see what we're going to be talking about next year when we have you back on theCUBE. >> I know. >> and maybe again in between now and then. Alan, Becky, thank you both so much for being here, this was truly a joy and I'm sure you gave folks a taste of the new IBM, practicing what you preach. >> John: Great momentum. >> And I'm just, I'm so impressed with the two companies collaborating, for those of us OGs in tech, the big companies never collaborated before- >> Yeah. >> John: Yeah. Joint, co-created solutions. >> And you have friction between products and everything else. I mean's it's really, co-collaboration is, it's a big theme for us at all the shows we've been doing this year but it's just nice to see it in practice too, it's an entirely different thing, so well done. >> Well it's what gets me out of the bed in the morning. >> All right, congratulations. >> Very clearly, your energy is contagious and I love it and yeah, this has been great. Thank all of you at home or at work or on the International Space Station or wherever you might be tuning in from today for joining us, here in Las Vegas at AWS re Invent where we are live from the show floor, wall-to-wall coverage for three days with John Furrier. My name is Savannah Peterson, we're theCUBE, the source for high tech coverage. (cheerful upbeat music)

Published Date : Nov 29 2022

SUMMARY :

We are live here from the show I love the innovation story, I'm going to go to you the number of people, Do you know what the total is then? on the show floor this year? so, beautiful time to be here. So the partnership started This is the beginning to meet our clients where they are, right? Absolutely and so to and a LATAM Partner of the Year award. to the conference. for the new Head of the ecosystem, Ruba. or have it out of the box. is the customer gets to choose the customer to leverage on the Amazon consulting relationships? is to give you some rapid flyer depending on the complexity of the claims, Yeah, that's one of the things that, So that change in the customer on the show this week the cool part is that we're but the easy button is where This is a dynamic, share and put the right compliance where you need to build that way. I love the term, and I saw and AWS has all the technology ready for the challenge? at the show this year? it's your Instagram reel, go. IBM, I am so here for it. With that customer- So the big takeaway I you nailed it. All right Becky, what about you? Well, so for me, the that are out there. and if you apply things like it's so different from, you know, and so I'm super excited about that. going to be talking about of the new IBM, practicing John: Yeah. at all the shows we've of the bed in the morning. or on the International Space Station

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Breaking Analysis: Survey Says! Takeaways from the latest CIO spending data


 

>> From theCUBE Studios in Palo Alto and Boston, bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> The technology spending outlook is not pretty and very much unpredictable right now. The negative sentiment is of course being driven by the macroeconomic factors in earnings forecasts that have been coming down all year in an environment of rising interest rates. And what's worse, is many people think earnings estimates are still too high. But it's understandable why there's so much uncertainty. I mean, technology is still booming, digital transformations are happening in earnest, leading companies have momentum and they got cash runways. And moreover, the CEOs of these leading companies are still really optimistic. But strong guidance in an environment of uncertainty is somewhat risky. Hello and welcome to this week's Wikibon CUBE Insights Powered by ETR. In this breaking analysis, we share takeaways from ETR'S latest spending survey, which was released to their private clients on October 21st. Today, we're going to review the macro spending data. We're going to share where CIOs think their cloud spend is headed. We're going to look at the actions that organizations are taking to manage uncertainty and then review some of the technology companies that have the most positive and negative outlooks in the ETR data set. Let's first look at the sample makeup from the latest ETR survey. ETR captured more than 1300 respondents in this latest survey. Its highest figure for the year and the quality and seniority of respondents just keeps going up each time we dig into the data. We've got large contributions as you can see here from sea level executives in a broad industry focus. Now the survey is still North America centric with 20% of the respondents coming from overseas and there is a bias toward larger organizations. And nonetheless, we're still talking well over 400 respondents coming from SMBs. Now ETR for those of you who don't know, conducts a quarterly spending intention survey and they also do periodic drilldowns. So just by the way of review, let's take a look at the expectations in the latest drilldown survey for IT spending. Before we look at the broader technology spending intentions survey data, followers of this program know that we reported on this a couple of weeks ago, spending expectations that peaked last December at 8.3% are now down to 5.5% with a slight uptick expected for next year as shown here. Now one CIO in the ETR community said these figures could be understated because of inflation. Now that's an interesting comment. Real GDP in the US is forecast to be around 1.5% in 2022. So these figures are significantly ahead of that. Nominal GDP is forecast to be significantly higher than what is shown in that slide. It was over 9% in June for example. And one would interpret that survey respondents are talking about real dollars which reflects inflationary factors in IT spend. So you might say, well if nominal GDP is in the high single digits this means that IT spending is below GDP which is usually not the case. But the flip side of that is technology tends to be deflationary because prices come down over time on a per unit basis, so this would be a normal and even positive trend. But it's mixed right now with prices on hard to find hardware, they're holding more firms. Software, you know, software tends to be driven by lock in and competition and switching costs. So you have those countervailing factors. Services can be inflationary, especially now as wages rise but certain sectors like laptops and semis and NAND are seeing less demand and maybe even some oversupply. So the way to look at this data is on a relative basis. In other words, IT buyers are reporting 280 basis point drop in spending sentiment from the end of last year. Now, something that we haven't shared from the latest drilldown survey which we will now is how IT bar buyers are thinking about cloud adoption. This chart shows responses from 419 IT execs from that drilldown and depicts the percentage of workloads their organizations have in the cloud today and what the expectation is through years from now. And you can see it's 27% today and it's nearly 50% in three years. Now the nuance is if you look at the question, that ETRS, it's they asked about IaaS and PaaS, which to some could include on-prem. Now, let me come back to that. In particular, financial services, IT, telco and retail and services industry cited expectations for the future for three years out that we're well above the average of the mean adoption levels. Regardless of how you interpret this data there's most certainly plenty of public cloud in the numbers. And whether you believe cloud is an operating environment or a place out there in the cloud, there's plenty of room for workloads to move into a cloud model well beyond mid this decade. So you know, as ho hum as we've been toward recent as-a-service models announced from the likes of HPE with GreenLake and Dell with APEX, the timing of those offerings may be pretty good actually. Now let's expand on some of the data that we showed a couple weeks ago. This chart shows responses from 282 execs on actions their organizations are taking over the next three months. And the Deltas are quite traumatic from the early part of this charter than the left hand side. The brown line is hiring freezes, the black line is freezing IT projects, and the green line is hiring increases and that red line is layoffs. And we put a box around the sort of general area of the isolation economy timeframe. And you can see the wild swings on this chart. By mid last summer, people were kickstarting things and more hiring was going on and the black line shows IT project freezes, you know, came way down. And now, or on the way back up as our hiring freezes. So we're seeing these wild swings in organizational actions and strategies which underscores the lack of predictability. As with supply chains around the world, this is likely due to the fact that organizations, pre pandemic they were optimized for efficiency, not a lot of waste rather than business resilience. Meaning, you know, there's again not a lot of fluff in the system or if there was it got flushed out during the pandemic. And so the need for productivity and automation is becoming increasingly important, especially as actions that solely rely on headcount changes are very, very difficult to manage. Now, let's dig into some of the vendor commentary and take a look at some of the names that have momentum and some of the others possibly facing headwinds. Here's a list of companies that stand out in the ETR survey. Snowflake, once again leads the pack with a positive spending outlook. HashiCorp, CrowdStrike, Databricks, Freshworks and ServiceNow, they round out the top six. Microsoft, they seem to always be in the mix, as do a number of other security and related companies including CyberArk, Zscaler, CloudFlare, Elastic, Datadog, Fortinet, Tenable and to a certain extent Akamai, you can kind of put them sort of in that group. You know, CDN, they got to worry about security. Everybody worries about security, but especially the CDNs. Now the other software names that are highlighted here include Workday and Salesforce. On the negative side, you can see Dynatrace saw some negatives in the latest survey especially around its analytics business. Security is generally holding up better than other sectors but it's still seeing greater levels of pressure than it had previously. So lower spend. And defections relative to its observability peers, that's really for Dynatrace. Now the other one that was somewhat surprising is IBM. You see the IBM was sort of in that negative realm here but IBM reported an outstanding quarter this past week with double digit revenue growth, strong momentum in software, consulting, mainframes and other infrastructure like storage. It's benefiting from the Kyndryl restructuring and it's on track IBM to deliver 10 billion in free cash flow this year. Red Hat is performing exceedingly well and growing in the very high teens. And so look, IBM is in the midst of a major transformation and it seems like a company that is really focused now with hybrid cloud being powered by Red Hat and consulting and a decade plus of AI investments finally paying off. Now the other big thing we'll add is, IBM was once an outstanding acquire of companies and it seems to be really getting its act together on the M&A front. Yes, Red Hat was a big pill to swallow but IBM has done a number of smaller acquisitions, I think seven this year. Like for example, Turbonomic, which is starting to pay off. Arvind Krishna has the company focused once again. And he and Jim J. Kavanaugh, IBM CFO, seem to be very confident on the guidance that they're giving in their business. So that's a real positive in our view for the industry. Okay, the last thing we'd like to do is take 12 of the companies from the previous chart and plot them in context. Now these companies don't necessarily compete with each other, some do. But they are standouts in the ETR survey and in the market. What we're showing here is a view that we like to often show, it's net score or spending velocity on the vertical axis. And it's a measure, that's a measure of the net percentage of customers that are spending more on a particular platform. So ETR asks, are you spending more or less? They subtract less from the mores. I mean I'm simplifying, but that's what net score is. Now in the horizontal axis, that is a measure of overlap which is which measures presence or pervasiveness in the dataset. So bigger the better. We've inserted a table that informs how the dots in the companies are positioned. These companies are all in the green in terms of net score. And that right most column in the table insert is indicative of their presence in the dataset, the end. So higher, again, is better for both columns. Two other notes, the red dotted line there you see at 40%. Anything over that indicates an highly elevated spending momentum for a given platform. And we purposefully took Microsoft out of the mix in this chart because it skews the data due to its large size. Everybody else would cluster on the left and Microsoft would be all alone in the right. So we take them out. Now as we noted earlier, Snowflake once again leads with a net score of 64%, well above the 40% line. Having said that, while adoption rates for Snowflake remains strong the company's spending velocity in the survey has come down to Earth. And many more customers are shifting from where they were last year and the year before in growth mode i.e. spending more year to year with Snowflake to now shifting more toward flat spending. So a plus or minus 5%. So that puts pressure on Snowflake's net score, just based on the math as to how ETR calculates, its proprietary net score methodology. So Snowflake is by no means insulated completely to the macro factors. And this was seen especially in the data in the Fortune 500 cut of the survey for Snowflake. We didn't show that here, just giving you anecdotal commentary from the survey which is backed up by data. So, it showed steeper declines in the Fortune 500 momentum. But overall, Snowflake, very impressive. Now what's more, note the position of Streamlit relative to Databricks. Streamlit is an open source python framework for developing data driven, data science oriented apps. And it's ironic that it's net score and shared in is almost identical to those of data bricks, as the aspirations of Snowflake and Databricks are beginning to collide. Now, however, the Databricks net score has held up very well over the past year and is in the 92nd percentile of its machine learning and AI peers. And while it's seeing some softness, like Snowflake in the Fortune 500, Databricks has steadily moved to the right on the X axis over the last several surveys even though it was unable to get to the public markets and do an IPO during the lockdown tech bubble. Let's come back to the chart. ServiceNow is impressive because it's well above the 40% mark and it has 437 shared in on this cut, the largest of any company that we chose to plot here. The only real negative on ServiceNow is, more large customers are keeping spending levels flat. That's putting a little bit pressure on its net score, but that's just conservatives. It's kind of like Snowflakes, you know, same thing but in a larger scale. But it's defections, the ServiceNow as in Snowflake as well. It's defections remain very, very low, really low churn below 2% for ServiceNow, in fact, within the dataset. Now it's interesting to also see Freshworks hit the list. You can see them as one of the few ITSM vendors that has momentum and can potentially take on ServiceNow. Workday, on this chart, it's the other big app player that's above the 40% line and we're only showing Workday HCM, FYI, in this graphic. It's Workday Financials, that offering, is below the 40% line just for reference. Now let's talk about CrowdStrike. We attended Falcon last month, CrowdStrike's user conference and we're very impressed with the product visio, the company's execution, it's growing partnerships. And you can see in this graphic, the ETR survey data confirms the company's stellar performance with a net score at 50%, well above the 40% mark. And importantly, more than 300 mentions. That's second only to ServiceNow, amongst the 12 companies that we've chosen to highlight here. Only Microsoft, which is not shown here, has a higher net score in the security space than CrowdStrike. And when it comes to presence, CrowdStrike now has caught up to Splunk in terms of pervasion in the survey. Now CyberArk and Zscaler are the other two security firms that are right at that 40% red dotted line. CyberArk for names with over a hundred citations in the security sector, is only behind Microsoft and CrowdStrike. Zscaler for its part in the survey is seeing strong momentum in the Fortune 500, unlike what we said for Snowflake. And its pervasion on the X-axis has been steadily increasing. Again, not that Snowflake and CrowdStrike compete with each other but they're too prominent names and it's just interesting to compare peers and business models. Cloudflare, Elastic and Datadog are slightly below the 40% mark but they made the sort of top 12 that we showed to highlight here and they continue to have positive sentiment in the survey. So, what are the big takeaways from this latest survey, this really quick snapshot that we've taken. As you know, over the next several weeks we're going to dig into it more and more. As we've previously reported, the tide is going out and it's taking virtually all the tech ships with it. But in many ways the current market is a story of heightened expectations coming down to Earth, miscalculations about the economic patterns and the swings and imperfect visibility. Leading Barclays analyst, Ramo Limchao ask the question to guide or not to guide in a recent research note he wrote. His point being, should companies guide or should they be more cautious? Many companies, if not most companies, are actually giving guidance. Indeed, when companies like Oracle and IBM are emphatic about their near term outlook and their visibility, it gives one confidence. On the other hand, reasonable people are asking, will the red hot valuations that we saw over the last two years from the likes of Snowflake, CrowdStrike, MongoDB, Okta, Zscaler, and others. Will they return? Or are we in for a long, drawn out, sideways exercise before we see sustained momentum? And to that uncertainty, we add elections and public policy. It's very hard to predict right now. I'm sorry to be like a two-handed lawyer, you know. On the one hand, on the other hand. But that's just the way it is. Let's just say for our part, we think that once it's clear that interest rates are on their way back down and we'll stabilize it under 4% and we have clarity on the direction of inflation, wages, unemployment and geopolitics, the wild swings and sentiment will subside. But when that happens is anyone's guess. If I had to peg, I'd say 18 months, which puts us at least into the spring of 2024. What's your prediction? You know, it's almost that time of year. Let's hear it. Please keep in touch and let us know what you think. Okay, that's it for now. Many thanks to Alex Myerson. He is on production and he manages the podcast for us. Ken Schiffman as well is our newest addition to the Boston Studio. Kristin Martin and Cheryl Knight, they help get the word out on social media and in our newsletters. And Rob Hoff is our EIC, editor-in-chief over at SiliconANGLE. He does some wonderful editing for us. Thank you all. Remember all these episodes, they are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me at david.vellante@siliconangle.com or DM me @dvellante. Or feel free to comment on our LinkedIn posts. And please do check out etr.ai. They've got the best survey data in the enterprise tech business. If you haven't checked that out, you should. It'll give you an advantage. This is Dave Vellante for theCUBE Insights Powered by ETR. Thanks for watching. Be well and we'll see you next time on Breaking Analysis. (soft upbeat music)

Published Date : Oct 23 2022

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Scott Baker, IBM Infrastructure | VMware Explore 2022


 

(upbeat music) >> Welcome back everyone to theCUBEs live coverage in San Francisco for VMware Explorer. I'm John Furrier with my host, Dave Vellante. Two sets, three days of wall to wall coverage. This is day two. We got a great guest, Scott Baker, CMO at IBM, VP of Infrastructure at IBM. Great to see you. Thanks for coming on. >> Hey, good to see you guys as well. It's always a pleasure. >> ()Good time last night at your event? >> Great time last night. >> It was really well-attended. IBM always has the best food so that was good and great props, magicians, and it was really a lot of fun, comedians. Good job. >> Yeah, I'm really glad you came on. One of the things we were chatting, before we came on camera was, how much changed. We've been covering IBM storage days, back on the Edge days, and they had the event. Storage is the center of all the conversations, cyber security- >> ()Right? >> ... But it's not just pure cyber. It's still important there. And just data and the role of multi-cloud and hybrid cloud and data and security are the two hottest areas, that I won't say unresolved, but are resolving themselves. And people are talking. It's the most highly discussed topics. >> Right. >> ()Those two areas. And it's just all on storage. >> Yeah, it sure does. And in fact, what I would even go so far as to say is, people are beginning to realize the importance that storage plays, as the data custodian for the organization. Right? Certainly you have humans that are involved in setting strategies, but ultimately whatever those policies are that get applied, have to be applied to a device that must act as a responsible custodian for the data it holds. >> So what's your role at IBM and the infrastructure team? Storage is one only one of the areas. >> ()Right. >> You're here at VMware Explore. What's going on here with IBM? Take us through what you're doing there at IBM, and then here at VMware. What's the conversations? >> Sure thing. I have the distinct pleasure to run both product marketing and strategy for our storage line. That's my primary focus, but I also have responsibility for the mainframe software, so the Z System line, as well as our Power server line, and our technical support organization, or at least the services side of our technical support organization. >> And one of the things that's going on here, lot of noise going on- >> Is that a bird flying around? >> Yeah >> We got fire trucks. What's changed? 'Cause right now with VMware, you're seeing what they're doing. They got the Platform, Under the Hood, Developer focus. It's still an OPS game. What's the relationship with VMware? What are you guys talking about here? What are some of the conversations you're having here in San Francisco? >> Right. Well, IBM has been a partner with VMware for at least the last 20 years. And VMware does, I think, a really good job about trying to create a working space for everyone to be an equal partner with them. It can be challenging too, if you want to sort of throw out your unique value to a customer. So one of the things that we've really been working on is, how do we partner much stronger? When we look at the customers that we support today, what they're looking for isn't just a solid product. They're looking for a solid ecosystem partnership. So we really lean in on that 20 years of partnership experience that we have with IBM. So one of the things that we announced was actually being one of the first VMware partners to bring both a technical innovation delivery mechanism, as well as technical services, alongside VMware technologies. I would say that was one of the first things that we really leaned in on, as we looked out at what customers are expecting from us. >> So I want to zoom out a little bit and talk about the industry. I've been following IBM since the early 1980s. It's trained in the mainframe market, and so we've seen, a lot of things you see come back to the mainframe, but we won't go there. But prior to Arvind coming on, it seemed like, okay, storage, infrastructure, yeah it's good business, and we'll let it throw off some margin. That's fine. But it's all about services and software. Okay, great. With Arvind, and obviously Red Hat, the whole focus shift to hybrid. We were talking, I think yesterday, about okay, where did we first hear hybrid? Obviously we heard that a lot from VMware. I heard it actually first, early on anyway, from IBM, talking hybrid. Some of the storage guys at the time. Okay, so now all of a sudden there's the realization that to make hybrid work, you need software and hardware working together. >> () Right. So it's now a much more fundamental part of the conversation. So when you look out, Scott, at the trends you're seeing in the market, when you talk to customers, what are you seeing and how is that informing your strategy, and how are you bringing together all the pieces? >> That's a really awesome question because it always depends on who, within the organization, you're speaking to. When you're inside the data center, when you're talking to the architects and the administrators, they understand the value in the necessity for a hybrid-cloud architecture. Something that's consistent. On The Edge, On-Prem, in the cloud. Something that allows them to expand the level of control that they have, without having to specialize on equipment and having to redo things as you move from one medium to the next. As you go upstack in that conversation, what I find really interesting is how leaders are beginning to realize that private cloud or on-prem, multi cloud, super cloud, whatever you call it, whatever's in the middle, those are just deployment mechanisms. What they're coming to understand is it's the applications and the data that's hybrid. And so what they're looking for IBM to deliver, and something that we've really invested in on the infrastructure side is, how do we create bidirectional application mobility? Making it easy for organizations, whether they're using containers, virtual machines, just bare metal, how do they move that data back and forth as they need to, and not just back and forth from on-prem to the cloud, but effectively, how do they go from cloud to cloud? >> Yeah. One of the things I noticed is your pin, says I love AI, with the I next to IBM and get all these (indistinct) in there. AI, remember the quote from IBM is, "You can't have AI without IA." Information architect. >> () Right. >> () Rob Thomas. >> Rob Thomas (indistinct) the sound bites. But that brings up the point about machine learning and some of these things that are coming down the like, how is your area devolving the smarts and the brains around leveraging the AI in the systems itself? We're hearing more and more softwares being coded into the hardware. You see Silicon advances. All this is kind of, not changing it, but bringing back the urgency of, hardware matters. >> That's right. >> () At the same time, it's still software too. >> That's right. So let's connect a couple of dots here. We talked a little bit about the importance of cyber resiliency, and let's talk about a little bit on how we use AI in that matter. So, if you look at the direct flash modules that are in the market today, or the SSDs that are in the market today, just standard-capacity drives. If you look at the flash core modules that IBM produces, we actually treat that as a computational storage offering, where you store the data, but it's got intelligence built into the processor, to offload some of the responsibilities of the controller head. The ability to do compression, single (indistinct), deduplication, you name it. But what if you can apply AI at the controller level, so that signals that are being derived by the flash core module itself, that look anomalous, can be handed up to an intelligence to say, "Hey, I'm all of a sudden getting encrypted rights from a host that I've never gotten encrypted rights for. Maybe this could be a problem." And then imagine if you connect that inferencing engine to the rest of the IBM portfolio, "Hey, Qradar. Hey IBM Guardian. What's going on on the network? Can we see some correlation here?" So what you're going to see IBM infrastructure continue to do is invest heavily into entropy and the ability to measure IO characteristics with respect to anomalous behavior and be able to report against that. And the trick here, because the array technically doesn't know if it's under attack or if the host just decided to turn on encryption, the trick here is using the IBM product relationships, and ecosystem relationships, to do correlation of data to determine what's actually happening, to reduce your false positives. >> And have that pattern of data too. It's all access to data too. Big time. >> That's right. >> And that innovation comes out of IBM R&D? Does it come out of the product group? Is it IBM research that then trickles its way in? Is it the storage innovation? Where's that come from? Where's that bubble up? That partnership? >> Well, I got to tell you, it doesn't take very long in this industry before your counterpart, your competitor, has a similar feature. Right? So we're always looking for, what's the next leg? What's the next advancement that we can make? We knew going into this process, that we had plenty of computational power that was untapped on the FPGA, the processor running on the flash core module. Right? So we thought, okay, well, what should we do next? And we thought, "Hey, why not just set this thing up to start watching IO patterns, do calculations, do trending, and report that back?" And what's great about what you brought up too, John, is that it doesn't stay on the box. We push that upstack through the AIOPS architecture. So if you're using Turbonomic, and you want to look applications stack down, to know if you've got threat potential, or your attack surface is open, you can make some changes there. If you want to look at it across your infrastructure landscape with a storage insight, you could do that. But our goal here is to begin to make the machine smarter and aware of impacts on the data, not just on the data they hold onto, but usage, to move it into the appropriate tier, different write activities or read activities or delete activities that could indicate malicious efforts that are underway, and then begin to start making more autonomous, how about managed autonomous responses? I don't want to turn this into a, oh, it's smart, just turn it on and walk away and it's good. I don't know that we'll ever get there just yet, but the important thing here is, what we're looking at is, how do we continually safeguard and protect that data? And how do we drive features in the box that remove more and more of the day to day responsibility from the administrative staff, who are technically hired really, to service and solve for bigger problems in the enterprise, not to be a specialist and have to manage one box at a time. >> Dave mentioned Arvind coming on, the new CEO of IBM, and the Red Hat acquisition and that change, I'd like to get your personal perspective, or industry perspective, so take your IBM-hat off for a second and put the Scott-experience-in-the-industry hat on, the transformation at the customer level right now is more robust, to use that word. I don't want to say chaotic, but it is chaotic. They say chaos in the cloud here at VM, a big part of their messaging, but it's changing the business model, how things are consumed. You're seeing new business models emerge. So IBM has this lot of storage old systems, you're transforming, the company's transforming. Customers are also transforming, so that's going to change how people market products. >> () Right. >> For example, we know that developers and DevOps love self-service. Why? Because they don't want to install it. Let me go faster. And they want to get rid of it, doesn't work. Storage is infrastructure and still software, so how do you see, in your mind's eye, with all your experience, the vision of how to market products that are super important, that are infrastructure products, that have to be put into play, for really new architectures that are going to transform businesses? It's not as easy as saying, "Oh, we're going to go to market and sell something." The old way. >> () Right. >> This shifting happening is, I don't think there's an answer yet, but I want to get your perspective on that. Customers want to hear the storage message, but it might not be speeds and fees. Maybe it is. Maybe it's not. Maybe it's solutions. Maybe it's security. There's multiple touch points now, that you're dealing with at IBM for the customer, without becoming just a storage thing or just- >> () Right. >> ... or just hardware. I mean, hardware does matter, but what's- >> Yeah, no, you're absolutely right, and I think what complicates that too is, if you look at the buying centers around a purchase decision, that's expanded as well, and so as you engage with a customer, you have to be sensitive to the message that you're telling, so that it touches the needs or the desires of the people that are all sitting around the table. Generally what we like to do when we step in and we engage, isn't so much to talk about the product. At some point, maybe later in the engagements, the importance of speeds, feeds, interconnectivity, et cetera, those do come up. Those are a part of the final decision, but early on it's really about outcomes. What outcomes are you delivering? This idea of being able to deliver, if you use the term zero trust or cyber-resilient storage capability as a part of a broader security architecture that you're putting into place, to help that organization, that certainly comes up. We also hear conversations with customers about, or requests from customers about, how do the parts of IBM themselves work together? Right? And I think a lot of that, again, continues to speak to what kind of outcome are you going to give to me? Here's a challenge that I have. How are you helping me overcome it? And that's a combination of IBM hardware, software, and the services side, where we really have an opportunity to stand out. But the thing that I would tell you, that's probably most important is, the engagement that we have up and down the stack in the market perspective, always starts with, what's the outcome that you're going to deliver for me? And then that drags with it the story that would be specific to the gear. >> Okay, so let's say I'm a customer, and I'm buying it to zero trust architecture, but it's going to be somewhat of a long term plan, but I have a tactical need. I'm really nervous about Ransomware, and I don't feel as though I'm prepared, and I want an outcome that protects me. What are you seeing? Are you seeing any patterns? I know it's going to vary, but are you seeing any patterns, in terms of best practice to protect me? >> Man, the first thing that we wanted to do at IBM is divorce ourselves from the company as we thought through this. And what I mean by that is, we wanted to do what's right, on day zero, for the customer. So we set back using the experience that we've been able to amass, going through various recovery operations, and helping customers get through a Ransomware attack. And we realized, "Hey. What we should offer is a free cyber resilience assessment." So we like to, from the storage side, we'd like to look at what we offer to the customer as following the NIST framework. And most vendors will really lean in hard on the response and the recovery side of that, as you should. But that means that there's four other steps that need to be addressed, and that free cyber-resilience assessment, it's a consultative engagement that we offer. What we're really looking at doing is helping you assess how vulnerable you are, how big is that attack surface? And coming out of that, we're going to give you a Vendor Agnostic Report that says here's your situation, here's your grade or your level of risk and vulnerability, and then here's a prioritized roadmap of where we would recommend that you go off and start solving to close up whatever the gaps or the risks are. Now you could say, "Hey, thanks, IBM. I appreciate that. I'm good with my storage vendor today. I'm going to go off and use it." Now, we may not get some kind of commission check. We may not sell the box. But what I do know is that you're going to walk away knowing the risks that you're in, and we're going to give you the recommendations to get started on closing those up. And that helps me sleep at night. >> That's a nice freebie. >> Yeah. >> Yeah, it really is, 'cause you guys got deep expertise in that area. So take advantage of that. >> Scott, great to have you on. Thanks for spending time out of your busy day. Final question, put a plug in for your group. What are you communicating to customers? Share with the audience here. You're here at VMware Explorer, the new rebranded- >> () Right? >> ... multi-cloud, hybrid cloud, steady state. There are three levels of transformation, virtualization, hybrid cloud, DevOps, now- >> Right? >> ... multi-cloud, so they're in chapter three of their journey- >> That's right. >> Really innovative company, like IBM, so put the plugin. What's going on in your world? Take a minute to explain what you want. >> Right on. So here we are at VMware Explorer, really excited to be here. We're showcasing two aspects of the IBM portfolio, all of the releases and announcements that we're making around the IBM cloud. In fact, you should come check out the product demonstration for the IBM Cloud Satellite. And I don't think they've coined it this, but I like to call it the VMware edition, because it has all of the VMware services and tools built into it, to make it easier to move your workloads around. We certainly have the infrastructure side on the storage, talking about how we can help organizations, not only accelerate their deployments in, let's say Tanzu or Containers, but even how we help them transform the application stack that's running on top of their virtualized environment in the most consistent and secure way possible. >> Multiple years of relationships with VMware. IBM, VMware together. Congratulations. >> () That's right. >> () Thanks for coming on. >> Hey, thanks (indistinct). Thank you very much. >> A lot more live coverage here at Moscone west. This is theCUBE. I'm John Furrier with Dave Vellante. Thanks for watching. Two more days of wall-to-wall coverage continuing here. Stay tuned. (soothing music)

Published Date : Aug 31 2022

SUMMARY :

Great to see you. Hey, good to see you guys as well. IBM always has the best One of the things we were chatting, And just data and the role of And it's just all on storage. for the data it holds. and the infrastructure team? What's the conversations? so the Z System line, as well What's the relationship with VMware? So one of the things that we announced and talk about the industry. of the conversation. and having to redo things as you move from AI, remember the quote from IBM is, but bringing back the () At the same time, that are in the market today, And have that pattern of data too. is that it doesn't stay on the box. and the Red Hat acquisition that have to be put into play, for the customer, ... or just hardware. that are all sitting around the table. and I'm buying it to that need to be addressed, expertise in that area. Scott, great to have you on. There are three levels of transformation, of their journey- Take a minute to explain what you want. because it has all of the relationships with VMware. Thank you very much. Two more days of wall-to-wall

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Breaking Analysis: How the cloud is changing security defenses in the 2020s


 

>> Announcer: From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> The rapid pace of cloud adoption has changed the way organizations approach cybersecurity. Specifically, the cloud is increasingly becoming the first line of cyber defense. As such, along with communicating to the board and creating a security aware culture, the chief information security officer must ensure that the shared responsibility model is being applied properly. Meanwhile, the DevSecOps team has emerged as the critical link between strategy and execution, while audit becomes the free safety, if you will, in the equation, i.e., the last line of defense. Hello, and welcome to this week's, we keep on CUBE Insights, powered by ETR. In this "Breaking Analysis", we'll share the latest data on hyperscale, IaaS, and PaaS market performance, along with some fresh ETR survey data. And we'll share some highlights and the puts and takes from the recent AWS re:Inforce event in Boston. But first, the macro. It's earning season, and that's what many people want to talk about, including us. As we reported last week, the macro spending picture is very mixed and weird. Think back to a week ago when SNAP reported. A player like SNAP misses and the Nasdaq drops 300 points. Meanwhile, Intel, the great semiconductor hope for America misses by a mile, cuts its revenue outlook by 15% for the year, and the Nasdaq was up nearly 250 points just ahead of the close, go figure. Earnings reports from Meta, Google, Microsoft, ServiceNow, and some others underscored cautious outlooks, especially those exposed to the advertising revenue sector. But at the same time, Apple, Microsoft, and Google, were, let's say less bad than expected. And that brought a sigh of relief. And then there's Amazon, which beat on revenue, it beat on cloud revenue, and it gave positive guidance. The Nasdaq has seen this month best month since the isolation economy, which "Breaking Analysis" contributor, Chip Symington, attributes to what he calls an oversold rally. But there are many unknowns that remain. How bad will inflation be? Will the fed really stop tightening after September? The Senate just approved a big spending bill along with corporate tax hikes, which generally don't favor the economy. And on Monday, August 1st, the market will likely realize that we are in the summer quarter, and there's some work to be done. Which is why it's not surprising that investors sold the Nasdaq at the close today on Friday. Are people ready to call the bottom? Hmm, some maybe, but there's still lots of uncertainty. However, the cloud continues its march, despite some very slight deceleration in growth rates from the two leaders. Here's an update of our big four IaaS quarterly revenue data. The big four hyperscalers will account for $165 billion in revenue this year, slightly lower than what we had last quarter. We expect AWS to surpass 83 billion this year in revenue. Azure will be more than 2/3rds the size of AWS, a milestone from Microsoft. Both AWS and Azure came in slightly below our expectations, but still very solid growth at 33% and 46% respectively. GCP, Google Cloud Platform is the big concern. By our estimates GCP's growth rate decelerated from 47% in Q1, and was 38% this past quarter. The company is struggling to keep up with the two giants. Remember, both GCP and Azure, they play a shell game and hide the ball on their IaaS numbers, so we have to use a survey data and other means of estimating. But this is how we see the market shaping up in 2022. Now, before we leave the overall cloud discussion, here's some ETR data that shows the net score or spending momentum granularity for each of the hyperscalers. These bars show the breakdown for each company, with net score on the right and in parenthesis, net score from last quarter. lime green is new adoptions, forest green is spending up 6% or more, the gray is flat, pink is spending at 6% down or worse, and the bright red is replacement or churn. Subtract the reds from the greens and you get net score. One note is this is for each company's overall portfolio. So it's not just cloud. So it's a bit of a mixed bag, but there are a couple points worth noting. First, anything above 40% or 40, here as shown in the chart, is considered elevated. AWS, as you can see, is well above that 40% mark, as is Microsoft. And if you isolate Microsoft's Azure, only Azure, it jumps above AWS's momentum. Google is just barely hanging on to that 40 line, and Alibaba is well below, with both Google and Alibaba showing much higher replacements, that bright red. But here's the key point. AWS and Azure have virtually no churn, no replacements in that bright red. And all four companies are experiencing single-digit numbers in terms of decreased spending within customer accounts. People may be moving some workloads back on-prem selectively, but repatriation is definitely not a trend to bet the house on, in our view. Okay, let's get to the main subject of this "Breaking Analysis". TheCube was at AWS re:Inforce in Boston this week, and we have some observations to share. First, we had keynotes from Steven Schmidt who used to be the chief information security officer at Amazon on Web Services, now he's the CSO, the chief security officer of Amazon. Overall, he dropped the I in his title. CJ Moses is the CISO for AWS. Kurt Kufeld of AWS also spoke, as did Lena Smart, who's the MongoDB CISO, and she keynoted and also came on theCUBE. We'll go back to her in a moment. The key point Schmidt made, one of them anyway, was that Amazon sees more data points in a day than most organizations see in a lifetime. Actually, it adds up to quadrillions over a fairly short period of time, I think, it was within a month. That's quadrillion, it's 15 zeros, by the way. Now, there was drill down focus on data protection and privacy, governance, risk, and compliance, GRC, identity, big, big topic, both within AWS and the ecosystem, network security, and threat detection. Those are the five really highlighted areas. Re:Inforce is really about bringing a lot of best practice guidance to security practitioners, like how to get the most out of AWS tooling. Schmidt had a very strong statement saying, he said, "I can assure you with a 100% certainty that single controls and binary states will absolutely positively fail." Hence, the importance of course, of layered security. We heard a little bit of chat about getting ready for the future and skating to the security puck where quantum computing threatens to hack all of the existing cryptographic algorithms, and how AWS is trying to get in front of all that, and a new set of algorithms came out, AWS is testing. And, you know, we'll talk about that maybe in the future, but that's a ways off. And by its prominent presence, the ecosystem was there enforced, to talk about their role and filling the gaps and picking up where AWS leaves off. We heard a little bit about ransomware defense, but surprisingly, at least in the keynotes, no discussion about air gaps, which we've talked about in previous "Breaking Analysis", is a key factor. We heard a lot about services to help with threat detection and container security and DevOps, et cetera, but there really wasn't a lot of specific talk about how AWS is simplifying the life of the CISO. Now, maybe it's inherently assumed as AWS did a good job stressing that security is job number one, very credible and believable in that front. But you have to wonder if the world is getting simpler or more complex with cloud. And, you know, you might say, "Well, Dave, come on, of course it's better with cloud." But look, attacks are up, the threat surface is expanding, and new exfiltration records are being set every day. I think the hard truth is, the cloud is driving businesses forward and accelerating digital, and those businesses are now exposed more than ever. And that's why security has become such an important topic to boards and throughout the entire organization. Now, the other epiphany that we had at re:Inforce is that there are new layers and a new trust framework emerging in cyber. Roles are shifting, and as a direct result of the cloud, things are changing within organizations. And this first hit me in a conversation with long-time cyber practitioner and Wikibon colleague from our early Wikibon days, and friend, Mike Versace. And I spent two days testing the premise that Michael and I talked about. And here's an attempt to put that conversation into a graphic. The cloud is now the first line of defense. AWS specifically, but hyperscalers generally provide the services, the talent, the best practices, and automation tools to secure infrastructure and their physical data centers. And they're really good at it. The security inside of hyperscaler clouds is best of breed, it's world class. And that first line of defense does take some of the responsibility off of CISOs, but they have to understand and apply the shared responsibility model, where the cloud provider leaves it to the customer, of course, to make sure that the infrastructure they're deploying is properly configured. So in addition to creating a cyber aware culture and communicating up to the board, the CISO has to ensure compliance with and adherence to the model. That includes attracting and retaining the talent necessary to succeed. Now, on the subject of building a security culture, listen to this clip on one of the techniques that Lena Smart, remember, she's the CISO of MongoDB, one of the techniques she uses to foster awareness and build security cultures in her organization. Play the clip >> Having the Security Champion program, so that's just, it's like one of my babies. That and helping underrepresented groups in MongoDB kind of get on in the tech world are both really important to me. And so the Security Champion program is purely purely voluntary. We have over 100 members. And these are people, there's no bar to join, you don't have to be technical. If you're an executive assistant who wants to learn more about security, like my assistant does, you're more than welcome. Up to, we actually, people grade themselves when they join us. We give them a little tick box, like five is, I walk on security water, one is I can spell security, but I'd like to learn more. Mixing those groups together has been game-changing for us. >> Now, the next layer is really where it gets interesting. DevSecOps, you know, we hear about it all the time, shifting left. It implies designing security into the code at the dev level. Shift left and shield right is the kind of buzz phrase. But it's getting more and more complicated. So there are layers within the development cycle, i.e., securing the container. So the app code can't be threatened by backdoors or weaknesses in the containers. Then, securing the runtime to make sure the code is maintained and compliant. Then, the DevOps platform so that change management doesn't create gaps and exposures, and screw things up. And this is just for the application security side of the equation. What about the network and implementing zero trust principles, and securing endpoints, and machine to machine, and human to app communication? So there's a lot of burden being placed on the DevOps team, and they have to partner with the SecOps team to succeed. Those guys are not security experts. And finally, there's audit, which is the last line of defense or what I called at the open, the free safety, for you football fans. They have to do more than just tick the box for the board. That doesn't cut it anymore. They really have to know their stuff and make sure that what they sign off on is real. And then you throw ESG into the mix is becoming more important, making sure the supply chain is green and also secure. So you can see, while much of this stuff has been around for a long, long time, the cloud is accelerating innovation in the pace of delivery. And so much is changing as a result. Now, next, I want to share a graphic that we shared last week, but a little different twist. It's an XY graphic with net score or spending velocity in the vertical axis and overlap or presence in the dataset on the horizontal. With that magic 40% red line as shown. Okay, I won't dig into the data and draw conclusions 'cause we did that last week, but two points I want to make. First, look at Microsoft in the upper-right hand corner. They are big in security and they're attracting a lot of dollars in the space. We've reported on this for a while. They're a five-star security company. And every time, from a spending standpoint in ETR data, that little methodology we use, every time I've run this chart, I've wondered, where the heck is AWS? Why aren't they showing up there? If security is so important to AWS, which it is, and its customers, why aren't they spending money with Amazon on security? And I asked this very question to Merrit Baer, who resides in the office of the CISO at AWS. Listen to her answer. >> It doesn't mean don't spend on security. There is a lot of goodness that we have to offer in ESS, external security services. But I think one of the unique parts of AWS is that we don't believe that security is something you should buy, it's something that you get from us. It's something that we do for you a lot of the time. I mean, this is the definition of the shared responsibility model, right? >> Now, maybe that's good messaging to the market. Merritt, you know, didn't say it outright, but essentially, Microsoft they charge for security. At AWS, it comes with the package. But it does answer my question. And, of course, the fact is that AWS can subsidize all this with egress charges. Now, on the flip side of that, (chuckles) you got Microsoft, you know, they're both, they're competing now. We can take CrowdStrike for instance. Microsoft and CrowdStrike, they compete with each other head to head. So it's an interesting dynamic within the ecosystem. Okay, but I want to turn to a powerful example of how AWS designs in security. And that is the idea of confidential computing. Of course, AWS is not the only one, but we're coming off of re:Inforce, and I really want to dig into something that David Floyer and I have talked about in previous episodes. And we had an opportunity to sit down with Arvind Raghu and J.D. Bean, two security experts from AWS, to talk about this subject. And let's share what we learned and why we think it matters. First, what is confidential computing? That's what this slide is designed to convey. To AWS, they would describe it this way. It's the use of special hardware and the associated firmware that protects customer code and data from any unauthorized access while the data is in use, i.e., while it's being processed. That's oftentimes a security gap. And there are two dimensions here. One is protecting the data and the code from operators on the cloud provider, i.e, in this case, AWS, and protecting the data and code from the customers themselves. In other words, from admin level users are possible malicious actors on the customer side where the code and data is being processed. And there are three capabilities that enable this. First, the AWS Nitro System, which is the foundation for virtualization. The second is Nitro Enclaves, which isolate environments, and then third, the Nitro Trusted Platform Module, TPM, which enables cryptographic assurances of the integrity of the Nitro instances. Now, we've talked about Nitro in the past, and we think it's a revolutionary innovation, so let's dig into that a bit. This is an AWS slide that was shared about how they protect and isolate data and code. On the left-hand side is a classical view of a virtualized architecture. You have a single host or a single server, and those white boxes represent processes on the main board, X86, or could be Intel, or AMD, or alternative architectures. And you have the hypervisor at the bottom which translates instructions to the CPU, allowing direct execution from a virtual machine into the CPU. But notice, you also have blocks for networking, and storage, and security. And the hypervisor emulates or translates IOS between the physical resources and the virtual machines. And it creates some overhead. Now, companies like VMware have done a great job, and others, of stripping out some of that overhead, but there's still an overhead there. That's why people still like to run on bare metal. Now, and while it's not shown in the graphic, there's an operating system in there somewhere, which is privileged, so it's got access to these resources, and it provides the services to the VMs. Now, on the right-hand side, you have the Nitro system. And you can see immediately the differences between the left and right, because the networking, the storage, and the security, the management, et cetera, they've been separated from the hypervisor and that main board, which has the Intel, AMD, throw in Graviton and Trainium, you know, whatever XPUs are in use in the cloud. And you can see that orange Nitro hypervisor. That is a purpose-built lightweight component for this system. And all the other functions are separated in isolated domains. So very strong isolation between the cloud software and the physical hardware running workloads, i.e., those white boxes on the main board. Now, this will run at practically bare metal speeds, and there are other benefits as well. One of the biggest is security. As we've previously reported, this came out of AWS's acquisition of Annapurna Labs, which we've estimated was picked up for a measly $350 million, which is a drop in the bucket for AWS to get such a strategic asset. And there are three enablers on this side. One is the Nitro cards, which are accelerators to offload that wasted work that's done in traditional architectures by typically the X86. We've estimated 25% to 30% of core capacity and cycles is wasted on those offloads. The second is the Nitro security chip, which is embedded and extends the root of trust to the main board hardware. And finally, the Nitro hypervisor, which allocates memory and CPU resources. So the Nitro cards communicate directly with the VMs without the hypervisors getting in the way, and they're not in the path. And all that data is encrypted while it's in motion, and of course, encryption at rest has been around for a while. We asked AWS, is this an, we presumed it was an Arm-based architecture. We wanted to confirm that. Or is it some other type of maybe hybrid using X86 and Arm? They told us the following, and quote, "The SoC, system on chips, for these hardware components are purpose-built and custom designed in-house by Amazon and Annapurna Labs. The same group responsible for other silicon innovations such as Graviton, Inferentia, Trainium, and AQUA. Now, the Nitro cards are Arm-based and do not use any X86 or X86/64 bit CPUs. Okay, so it confirms what we thought. So you may say, "Why should we even care about all this technical mumbo jumbo, Dave?" Well, a year ago, David Floyer and I published this piece explaining why Nitro and Graviton are secret weapons of Amazon that have been a decade in the making, and why everybody needs some type of Nitro to compete in the future. This is enabled, this Nitro innovations and the custom silicon enabled by the Annapurna acquisition. And AWS has the volume economics to make custom silicon. Not everybody can do it. And it's leveraging the Arm ecosystem, the standard software, and the fabrication volume, the manufacturing volume to revolutionize enterprise computing. Nitro, with the alternative processor, architectures like Graviton and others, enables AWS to be on a performance, cost, and power consumption curve that blows away anything we've ever seen from Intel. And Intel's disastrous earnings results that we saw this past week are a symptom of this mega trend that we've been talking about for years. In the same way that Intel and X86 destroyed the market for RISC chips, thanks to PC volumes, Arm is blowing away X86 with volume economics that cannot be matched by Intel. Thanks to, of course, to mobile and edge. Our prediction is that these innovations and the Arm ecosystem are migrating and will migrate further into enterprise computing, which is Intel's stronghold. Now, that stronghold is getting eaten away by the likes of AMD, Nvidia, and of course, Arm in the form of Graviton and other Arm-based alternatives. Apple, Tesla, Amazon, Google, Microsoft, Alibaba, and others are all designing custom silicon, and doing so much faster than Intel can go from design to tape out, roughly cutting that time in half. And the premise of this piece is that every company needs a Nitro to enable alternatives to the X86 in order to support emergent workloads that are data rich and AI-based, and to compete from an economic standpoint. So while at re:Inforce, we heard that the impetus for Nitro was security. Of course, the Arm ecosystem, and its ascendancy has enabled, in our view, AWS to create a platform that will set the enterprise computing market this decade and beyond. Okay, that's it for today. Thanks to Alex Morrison, who is on production. And he does the podcast. And Ken Schiffman, our newest member of our Boston Studio team is also on production. Kristen Martin and Cheryl Knight help spread the word on social media and in the community. And Rob Hof is our editor in chief over at SiliconANGLE. He does some great, great work for us. Remember, all these episodes are available as podcast. Wherever you listen, just search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me directly at David.Vellante@siliconangle.com or DM me @dvellante, comment on my LinkedIn post. And please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. Be well, and we'll see you next time on "Breaking Analysis." (upbeat theme music)

Published Date : Jul 30 2022

SUMMARY :

This is "Breaking Analysis" and the Nasdaq was up nearly 250 points And so the Security Champion program the SecOps team to succeed. of the shared responsibility model, right? and it provides the services to the VMs.

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Wrap with Stephanie Chan | Red Hat Summit 2022


 

(upbeat music) >> Welcome back to theCUBE. We're covering Red Hat Summit 2022. We're going to wrap up now, Dave Vellante, Paul Gillin. We want to introduce you to Stephanie Chan, who's our new correspondent. Stephanie, one of your first events, your very first CUBE event. So welcome. >> Thank you. >> Up from NYC. Smaller event, but intimate. You got a chance to meet some folks last night at some of the after parties. What are your overall impressions? What'd you learn this week? >> So this has been my first in-person event in over two years. And even though, like you said, is on the smaller scale, roughly around 1000 attendees, versus it's usual eight to 10,000 attendees. There's so much energy, and excitement, and openness in these events and sessions. Even before and after the sessions people have been mingling and socializing and hanging out. So, I think a lot of people appreciate these in-person events and are really excited to be here. >> Cool. So, you also sat in some of the keynotes, right? Pretty technical, right? Which is kind of new to sort of your genre, right? I mean, I know you got a financial background but, so what'd you think of the keynotes? What'd you think of the format, the theater in the round? Any impressions of that? >> So, I think there's three things that are really consistent in these Red Hat Summit keynotes. There's always a history lesson. There's always, you know, emphasis in the culture of openness. And, there's also inspirational stories about how people utilize open source. And I found a lot of those examples really compelling and interesting. For instance, people use open source in (indistinct), and even in space. So I really enjoyed, you know, learning about all these different people and stories. What about you guys? What do you think were the big takeaways and the best stories that came out of the keynotes? >> Paul, want to start? >> Clearly the Red Hat Enterprise Linux 9 is a major rollout. They do that only about every three years. So that's a big deal to this audience. I think what they did in the area of security, with rolling out sigstore, which is a major new, I think an important new project that was sort of incubated at Red Hat. And they're trying to put in to create an open source ecosystem around that now. And the alliances. I'm usually not that much on partnerships, but the Accenture and the Microsoft partnerships do seem to be significant to the company. And, finally, the GM partnership which I think was maybe kind of the bombshell that they sort of rushed in at the last minute. But I think has the biggest potential impact on Red Hat and its partner ecosystem that is really going to anchor their edge architecture going forward. So I didn't see it so much on the product front, but the sense of Red Hat spreading its wings, and partnering with more companies, and seeing its itself as really the center of an ecosystem indicates that they are, you know, they're in a very solid position in their business. >> Yeah, and also like the pandemic has really forced us into this new normal, right? So customer demand is changing. There has been the shift to remote. There's always going to be a new normal according to Paul, and open source carries us through that. So how do you guys think Red Hat has helped its portfolio through this new normal and the shift? >> I mean, when you think of Red Hat, you think of Linux. I mean, that's where it all started. You think OpenShift which is the application development platforms. Linux is the OS. OpenShift is the application development platform for Kubernetes. And then of course, Ansible is the automation framework. And I agree with you, ecosystem is really the other piece of this. So, I mean, I think you take those three pieces and extend that into the open source community. There's a lot of innovation that's going around each of those, but ecosystems are the key. We heard from Stefanie Chiras, that fundamental, I mean, you can't do this without those gap fillers and those partnerships. And then another thing that's notable here is, you know, this was, I mean, IBM was just another brand, right? I mean, if anything it was probably a sub-brand, I mean, you didn't hear much about IBM. You certainly had no IBM presence, even though they're right across the street running Think. No Arvind present, no keynote from Arvind, no, you know, Big Blue washing. And so, I think that's a testament to Arvind himself. We heard that from Paul Cormier, he said, hey, this guy's been great, he's left us alone. And he's allowed us to continue innovating. It's good news. IBM has not polluted Red Hat. >> Yes, I think that the Red Hat was, I said at the opening, I think Red Hat is kind of the tail wagging the dog right now. And their position seems very solid in the market. Clearly the market has come to them in terms of their evangelism of open source. They've remained true to their business model. And I think that gives them credibility that, you know, a lot of other open source companies have lacked. They have stuck with the plan for over 20 years now and have really not changed it, and it's paying off. I think they're emerging as a company that you can trust to do business with. >> Now I want to throw in something else here. I thought the conversation with IDC analyst, Jim Mercer, was interesting when he said that they surveyed customers and they wanted to get the security from their platform vendor, versus having to buy these bespoke tools. And it makes a lot of sense to me. I don't think that's going to happen, right? Because you're going to have an identity specialist. You're going to have an endpoint specialist. You're going to have a threat detection specialist. And they're going to be best of breed, you know, Red Hat's never going to be all of those things. What they can do is partner with those companies through APIs, through open source integrations, they can add them in as part of the ecosystem and maybe be the steward of that. Maybe that's the answer. They're never going to be the best at all those different security disciplines. There's no way in the world, Red Hat, that's going to happen. But they could be the integration point. And that would be, that would be a simplifying layer to the equation. >> And I think it's smart. You know, they're not pretending to be an identity in access management or an anti-malware company, or even a zero trust company. They are sticking to their knitting, which is operating system and developers. Evangelizing DevSecOps, which is a good thing. And, that's what they're going to do. You know, you have to admire this company. It has never gotten outside of its swim lane. I think it's understood well really what it wants to be good at. And, you know, in the software business knowing what not to do is more important than knowing what to do. Is companies that fail are usually the ones that get overextended, this company has never overextended itself. >> What else do you want to know? >> And a term that kept popping up was multicloud, or otherwise known as metacloud. We know what the cloud is, but- >> Oh, supercloud, metacloud. >> Supercloud, yeah, here we go. We know what the cloud is but, what does metacloud mean to you guys? And why has it been so popular in these conversations? >> I'm going to boot this to Dave, because he's the expert on this. >> Well, expert or not, but I mean, again, we've coined this term supercloud. And the idea behind the supercloud or what Ashesh called metacloud, I like his name, cause it allows Web 3.0 to come into the equation. But the idea is that instead of building on each individual cloud and have compatibility with that cloud, you build a layer across clouds. So you do the hard work as a platform supplier to hide the underlying primitives and APIs from the end customer, or the end developer, they can then add value on top of that. And that abstraction layer spans on-prem, clouds, across clouds, ultimately out to the edge. And it's new, a new value layer that builds on top of the hyperscale infrastructure, or existing data center infrastructure, or emerging edge infrastructure. And the reason why that is important is because it's so damn complicated, number one. Number two, every company's becoming a software company, a technology company. They're bringing their services through digital transformation to their customers. And you've got to have a cloud to do that. You're not going to build your own data center. That's like Charles Wang says, not Charles Wang. (Paul laughing) Charles Phillips. We were just talking about CA. Charles Phillips. Friends don't let friends build data centers. So that supercloud concept, or what Ashesh calls metacloud, is this new layer that's going to be powered by ecosystems and platform companies. And I think it's real. I think it's- >> And OpenShift, OpenShift is a great, you know, key card for them or leverage for them because it is perhaps the best known Kubernetes platform. And you can see here they're really doubling down on adding features to OpenShift, security features, scalability. And they see it as potentially this metacloud, this supercloud abstraction layer. >> And what we said is, in order to have a supercloud you got to have a superpaz layer and OpenShift is that superpaz layer. >> So you had conversations with a lot of people within the past two days. Some people include companies, from Verizon, Intel, Accenture. Which conversation stood out to you the most? >> Which, I'm sorry. >> Which conversation stood out to you the most? (Paul sighs) >> The conversation with Stu Miniman was pretty interesting because we talked about culture. And really, he has a lot of credibility in that area because he's not a Red Hat. You know, he hasn't been a Red Hat forever, he's fairly new to the company. And got a sense from him that the culture there really is what they say it is. It's a culture of openness and that's, you know, that's as important as technology for a company's success. >> I mean, this was really good content. I mean, there were a lot, I mean Stefanie's awesome. Stefanie Chiras, we're talking about the ecosystem. Chris Wright, you know, digging into some of the CTO stuff. Ashesh, who coined metacloud, I love that. The whole in vehicle operating system conversation was great. The security discussion that we just had. You know, the conversations with Accenture were super thoughtful. Of course, Paul Cormier was a highlight. I think that one's going to be a well viewed interview, for sure. And, you know, I think that the customer conversations are great. Red Hat did a really good job of carrying the keynote conversations, which were abbreviated this year, to theCUBE. >> Right. >> I give 'em a lot of kudos for that. And because, theCUBE, it allows us to double click, go deeper, peel the onion a little bit, you know, all the buzz words, and cliches. But it's true. You get to clarify some of the things you heard, which were, you know, the keynotes were, were scripted, but tight. And so we had some good follow up questions. I thought it was super useful. I know I'm leaving somebody out, but- >> We're also able to interview representatives from Intel and Nvidia, which at a software conference you don't typically do. I mean, there's the assimilation, the combination of hardware and software. It's very clear that, and this came out in the keynote, that Red Hat sees hardware as matter. It matters. It's important again. And it's going to be a source of innovation in the future. That came through clearly. >> Yeah. The hardware matters theme, you know, the old days you would have an operating system and the hardware were intrinsically linked. MVS in the mainframe, VAX, VMS in the digital mini computers. DG had its own operating system. Wang had his own operating system. Prime with Prime OS. You remember these days? >> Oh my God. >> Right? (Paul laughs) And then of course Microsoft. >> And then x86, everything got abstracted. >> Right. >> Everything became x86 and now it's all atomizing again. >> Although WinTel, right? I mean, MS-DOS and Windows were intrinsically linked for many, many years with Intel x86. And it wasn't until, you know, well, and then, you know, Sun Solaris, but it wasn't until Linux kind of blew that apart. And the internet is built on the lamp stack. And of course, Linux is the fundamental foundation for Red Hat. So my point is, that the operating system and the hardware have always been very closely tied together. Whether it's security, or IO, or registries and memory management, everything controlled by the OS are very close to the hardware. And so that's why I think you've got an affinity in Red Hat to hardware. >> But Linux is breaking that bond, don't you think? >> Yes, but it still has to understand the underlying hardware. >> Right. >> You heard today, how taking advantage of Nvidia, and the AI capabilities. You're seeing that with ARM, you're seeing that with Intel. How you can optimize the operating system to take advantage of new generations of CPU, and NPU, and CPU, and PU, XPU, you know, across the board. >> Yep. >> Well, I really enjoyed this conference and it really stressed how important open source is to a lot of different industries. >> Great. Well, thanks for coming on. Paul, thank you. Great co-hosting with you. And thank you. >> Always, Dave. >> For watching theCUBE. We'll be on the road, next week we're at KubeCon in Valencia, Spain. We're at VeeamON. We got a ton of stuff going on. Check out thecube.net. Check out siliconangle.com for all the news. Wikibon.com. We publish there weekly, our breaking analysis series. Thanks for watching everybody. Dave Vellante, for Paul Gillin, and Stephanie Chan. Thanks to the crew. Shout out, Andrew, Alex, Sonya. Amazing job, Sonya. Steven, thanks you guys for coming out here. Mark, good job corresponding. Go to SiliconANGLE, Mark's written some great stuff. And thank you for watching. We'll see you next time. (calm music)

Published Date : May 11 2022

SUMMARY :

We're going to wrap up now, at some of the after parties. And even though, like you I mean, I know you got And I found a lot of those examples indicates that they are, you know, There has been the shift to remote. and extend that into the Clearly the market has come to them And it makes a lot of sense to me. And I think it's smart. And a term that kept but, what does metacloud mean to you guys? because he's the expert on this. And the idea behind the supercloud And you can see here and OpenShift is that superpaz layer. out to you the most? that the culture there really I think that one's going to of the things you heard, And it's going to be a source and the hardware were And then of course Microsoft. And then x86, And it wasn't until, you know, well, the underlying hardware. and PU, XPU, you know, across the board. to a lot of different industries. And thank you. And thank you for watching.

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Keynote Analysis | Red Hat Summit 2022


 

[Music] thecube's coverage of red hat summit 2022 thecube has been covering red hat summit for a number of years of course the last two years were virtual coverage now the red hat summit is one of the industry's most premier events and and typically red hat summits are many thousands of people i think the last one i went to was eight or nine thousand people very heavy developer conference this year red hat has taken a different approach it's a hybrid event it's kind of a vip event at the westin in boston with a lot more executives here than we would normally expect versus developers but a huge virtual audience my name is dave vellante i'm here with my co-host paul gillin paul this is a location that you and i have broadcast from many times and um of course 2019 the summer of 2019 ibm acquired red hat and um we of course we did red hat summit that year but now we're seeing a completely new red hat and a new ibm and you wouldn't know ibm owned red hat for what they've been talking about at this conference we just came out of the keynote where uh in the in the hour-long keynote ibm was not mentioned once and only appeared the logo only appeared once on the screen in fact so this is uh very much red hat being red hat not being a subsidiary at ibm and perhaps that's justified given that ibm's track record with acquisitions is that they gradually envelop the acquired company and and it becomes part of the ibm board yeah they blue wash the whole thing right it's ironic because ibm think is going on right across the street arvin krishna is here but no presence here and i think that's by design i mean it reminds me of when you know emc owned vmware you know the vmware team didn't want to publicize that they had an ecosystem of partners that they wanted to cater to and they wanted to treat everybody equally even though perhaps behind the scenes they were forced to do certain things that they might not have necessarily wanted to because they were owned by another company and i think that you know certainly ibm's done a good job of leaving the brand separate but when they talk about the con the conference calls ibm's earnings calls you certainly get a heavy dose of red hat when red hat was acquired by ibm it was just north of three billion dollars in revenue obviously ibm paid 34 billion dollars for the company actually by today's valuations probably a bargain you know despite the market sell-off in the last several months uh but now we've heard public statements from arvind kushner that that red hat is a 5 billion plus revenue company it's a little unclear what's in there of course when you listen to ibm earnings you know consulting is their big business red hat's growing at 21 but when i remember paul when red hat was acquired stu miniman and i did a session and i said this is not about cloud this is about consulting and modernizing applications and sure there's some cloud in there with openshift but from a financial standpoint ibm was able to take red hat and jam it right into its application modernization initiatives so it's hard to tell how much of that 5 billion is actually you know legacy red hat but i guess it doesn't matter anymore it's working ibm mathematics is notoriously opaque they if the business isn't going well it'll tend to be absorbed into another number in the in the earnings report that that does show some growth so we've heard uh certainly ibm talks a lot about red hat on its earnings calls it's very clear that red hat is the growth engine within ibm i'd say it's a bit of the tail wagging the dog right now where red hat really is dictating where ibm goes with its hypercloud strategy which is the foundation not only of its technology portfolio but of its consulting business and so red hat is really in the driver's seat of of hybrid cloud and that's the future for ibm and you see that very much at this conference where uh red hat is putting out its uh series of announcements today about improvements to his hybrid cloud the new release of route 9 red hat enterprise linux 9 improvements to its hybrid cloud portfolio it very much is going its own way with that and i sense that ibm is going to go along with wherever red hat chooses to go yeah i think you're absolutely right if by the way if you go to siliconangle.com paul just published a piece on red hat reds hats their roll out of their parade which of course is as you pointed out led by enterprise linux but to your point about hybrid cloud it is the linchpin of of certainly ibm strategy but many companies hybrid cloud strategies if you think about it openshift in particular it's it's the modern application development environment for kubernetes you can get kubernetes you can buy eks you can get that for free in a lot of places but you have to do dozens and dozens of things and acquire dozens of services to do what openshift does to get the reliability the recoverability the security and that's really red hat's play and they're the the thing about red hat combining with linux their linux heritage they're doing that everywhere it's going to open shift everywhere red hat everywhere whether it's on-prem in aws azure google out to the edge you heard paul cormier today saying he expects that in the next several years hardware is going to become one of the most important you know factors i agree i think we're going to enter a hardware renaissance you've seen the work that we've done on arm i think 2017 was when red hat and arm announced kind of their initial collaboration could have even been before that today we're hearing a lot about intel and nvidia and so affinity with all of these alternative processes i think they did throw in today in the keynote power and so i think i heard that that was the other ibm branding they sort of tucked that in there but the point is red hat runs everywhere so it's fundamental to building out hybrid cloud and that is fundamental to a lot of company strategies and red hat has been all over kubernetes with openshift it's i mean it's a drum beat here uh the openshift strategy is what really makes hybrid cloud possible because kubernetes is what makes it possible to shift workloads seamlessly from platform to platform you make an interesting point about hardware we have seen kind of a renaissance in hardware these last couple of years as these specific chipsets and uh and even full-scale processors have come to market we're seeing several in the ai area right now where startups are developing full-blown chipsets and and systems uh just for ai processing and nvidia of course that's that's really kind of their stock and trade these days so uh a a company that can run across all of those different platforms a platform like like rel which can run all across those different platforms is going to have a leg up on on anybody else and the implications for application development are considerable when you when you think about we talk about a lot about these alternative processes when flash replaced the spinning disk that had a huge impact on how applications are developed developers now didn't have to wait for that that disc to spin even though it's spinning very fast it's mechanical compared to electrons forget it and and the second big piece here is how memory is actually utilized the x86 you know traditional x86 you know memory everything goes through that core processor intel for years grabbed more and more function and you're seeing now that function become dispersed in fact a lot of people think we're moving from a processor-centric world to a connect centric world meaning connecting all these piece parts alternative processors memory controllers you know storage controllers io network interface cards smartnics and things like that where the communication across those resources is now where a lot of the innovation is going you see you're seeing a lot of that and now of course applications can take advantage of that especially now at the edge which is just a whole new frontier the edge certainly is part of that equation when you look at machine learning at training machine learning models the cpu actually does relatively little work most of it is happening in gpus in these parallel processes that are going on and the cpu is kind of acting as a traffic cop and you see that in the edge as well it's the same model at the edge where more of the intelligence is going to be out in discrete devices spread across the network and the cpu is going to be less of a uh you know less of a engine of intelligence at the same time though we've got cpus with we've got 100 core cpus are on the horizon and there are even 200 and 300 core cpus that we may see in the next uh in the next couple of years so cpus aren't standing still they are evolving to become really kind of super traffic cops for all of these other processors out in the network and on the edge so it's a very exciting time to be in hardware because so much innovation is happening really at the microprocessor level well we saw this you and i lived through the pc era and we saw a whole raft of applications come about as a result of the microprocessor the shift of the microprocessor-based economy we're going to see so we are seeing something similar with mobile and the edge you know just think about some of the numbers if you think about the traditional moore's law doubling a number of transistors every let's call it two years 18 to 24 months pat gelsinger at intel promises that intel is on that pace still but if you look at the apple m1 ultra they increased the transistor density 6x in the last 15 months okay so where is this another data point is the historical moore's law curve is 40 that's moderating to somewhere down you know down in the low 30s if you look at the apple a series i mean that thing is on average increasing performance at 110 a year when you add up into the combinatorial factors of the cpu the neural processing unit the gpu all the accelerators so we are seeing a new era the thing i i i wanted to bring up paul is you mentioned ai much of the ai work that's done today is modeling that's done in the cloud and when we talk about edge we think that the future of ai is ai inferencing in real time at the edge so you may not even be persisting that data but you're going to create a lot of data you're going to be operating on that data in streams and it's going to require a whole new new architectural thinking of hardware very low cost very low power very high performance to drive all that intelligence at the edge and a lot of that data is going to stay at the edge and and that's we're going to talk about some of that today with some of the ev innovations and the vehicle innovations and the intelligence in these vehicles yeah and in talking in its edge strategy which it outlined today and the announcements that are made today red hat very much uh playing to the importance of being able to run red hat enterprise linux at the edge the idea is you do these big machine learning models centrally and then you you take the you take what results from that and you move it out to smaller processors it's the only way we can cope with it with the explosion of data that will be uh that these sensors and other devices will be generating so some of the themes we're hearing in the uh announcements today that you wrote about paul obviously rel9 is huge uh red hat enterprise linux version nine uh new capabilities a lot of edge a lot of security uh new cross portfolio capabilities for the edge security in the software supply chain that's a big conversation especially post solar winds managed ansible when you think about red hat you really i think anyway about three things rel which is such as linux it powers the internet powers everything uh you think of openshift which is application development you think about ansible which is automation so itops so that's one of the announcements ansible on azure and then a lot of hybrid cloud talk and you're gonna hear a lot of talk this week about red hat's cloud services portfolio packaging red hat as services as managed services that's you know a much more popular delivery mechanism with clients because they're trying to make it easy and this is complicated stuff and it gets more complicated the more features they add and the more the more components of the red hat portfolio are are available it's it's gonna be complex to build these hybrid clouds so like many of these so thecube started doing physical events last summer by the way and so this is this is new to a lot of people uh they're here for the first time people are really excited we've definitely noticed a trend people are excited to be back together paul cormier talked about that he talked about the new normal you can define the new normal any way you want so paul cormier gave the uh the the intro keynote bidani interviewed amex stephanie cheris interviewed accenture both those firms are coming out stephanie's coming on with the in accenture as well matt hicks talked about product innovation i loved his reference to ada lovelace that was very cool he talked about uh serena uh ramyanajan a famous mathematician who nobody knew about when he was just a kid these were ignored individuals in the 1800s for years and years and years in the case of ada lovelace for a century even he asked the question what if we had discovered them earlier and acted on them and been able to iterate on them earlier and his point tied that to open source very brilliantly i thought and um keynotes which i appreciate are much shorter much shorter intimate they did a keynote in the round this time uh which i haven't seen before there's maybe a thousand people in there so a much smaller group much more intimate setting not a lot of back and forth but uh but there is there is a feeling of a more personal feel to this event than i've seen it past red hat summits yeah and i think that's a trend that we're going to see more of where the live audience is kind of the on the ground it's going to the vip audience but still catering to the virtual audience you don't want to lose them so that's why the keynotes are a lot tighter okay paul thank you for setting up red hat summit 2022 you're watching the cube's coverage we'll be right back wall-to-wall coverage for two days right after this short break [Music] you

Published Date : May 11 2022

SUMMARY :

the numbers if you think about the

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Breaking Analysis: What to Expect in Cloud 2022 & Beyond


 

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante you know we've often said that the next 10 years in cloud computing won't be like the last ten cloud has firmly planted its footprint on the other side of the chasm with the momentum of the entire multi-trillion dollar tech business behind it both sellers and buyers are leaning in by adopting cloud technologies and many are building their own value layers on top of cloud in the coming years we expect innovation will continue to coalesce around the three big u.s clouds plus alibaba in apac with the ecosystem building value on top of the hardware saw tooling provided by the hyperscalers now importantly we don't see this as a race to the bottom rather our expectation is that the large public cloud players will continue to take cost out of their platforms through innovation automation and integration while other cloud providers and the ecosystem including traditional companies that buy it mine opportunities in their respective markets as matt baker of dell is fond of saying this is not a zero sum game welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll update you on our latest projections in the cloud market we'll share some new etr survey data with some surprising nuggets and drill into this the important cloud database landscape first we want to take a look at what people are talking about in cloud and what's been in the recent news with the exception of alibaba all the large cloud players have reported earnings google continues to focus on growth at the expense of its profitability google reported that it's cloud business which includes applications like google workspace grew 45 percent to five and a half billion dollars but it had an operating loss of 890 billion now since thomas curion joined google to run its cloud business google has increased head count in its cloud business from 25 000 25 000 people now it's up to 40 000 in an effort to catch up to the two leaders but playing catch up is expensive now to put this into perspective let's go back to aws's revenue in q1 2018 when the company did 5.4 billion so almost exactly the same size as google's current total cloud business and aws is growing faster at the time at 49 don't forget google includes in its cloud numbers a big chunk of high margin software aws at the time had an operating profit of 1.4 billion that quarter around 26 of its revenues so it was a highly profitable business about as profitable as cisco's overall business which again is a great business this is what happens when you're number three and didn't get your head out of your ads fast enough now in fairness google still gets high marks on the quality of its technology according to corey quinn of the duck bill group amazon and google cloud are what he called neck and neck with regard to reliability with microsoft azure trailing because of significant disruptions in the past these comments were made last week in a bloomberg article despite some recent high-profile outages on aws not surprisingly a microsoft spokesperson said that the company's cloud offers industry-leading reliability and that gives customers payment credits after some outages thank you turning to microsoft and cloud news microsoft's overall cloud business surpassed 22 billion in the december quarter up 32 percent year on year like google microsoft includes application software and sas offerings in its cloud numbers and gives little nuggets of guidance on its azure infrastructure as a service business by the way we estimate that azure comprises about 45 percent of microsoft's overall cloud business which we think hit a 40 billion run rate last quarter microsoft guided in its earning call that recent declines in the azure growth rates will reverse in q1 and that implies sequential growth for azure and finally it was announced that the ftc not the doj will review microsoft's announced 75 billion acquisition of activision blizzard it appears ftc chair lena khan wants to take this one on herself she of course has been very outspoken about the power of big tech companies and in recent a recent cnbc interview suggested that the u.s government's actions were a meaningful contributor back then to curbing microsoft's power in the 90s i personally found that dubious just ask netscape wordperfect novell lotus and spc the maker of harvard presentation graphics how effective the government was in curbing microsoft power generally my take is that the u s government has had a dismal record regulating tech companies most notably ibm and microsoft and it was market forces company hubris complacency and self-inflicted wounds not government intervention these were far more effective than the government now of course if companies are breaking the law they should be punished but the u.s government hasn't been very productive in its actions and the unintended consequences of regulation could be detrimental to the u.s competitiveness in the race with china but i digress lastly in the news amazon announced earnings thursday and the company's value increased by 191 billion dollars on friday that's a record valuation gain for u.s stocks aws amazon's profit engine grew 40 percent year on year for the quarter it closed the year at 62 billion dollars in revenue and at a 71 billion dollar revenue run rate aws is now larger than ibm which without kindrel is at a 67 billion dollar run rate just for context ibm's revenue in 2011 was 107 billion dollars now there's a conversation going on in the media and social that in order to continue this growth and compete with microsoft that aws has to get into the sas business and offer applications we don't think that's the right strategy for amp from for amazon in the near future rather we see them enabling developers to compete in that business finally amazon disclosed that 48 of its top 50 customers are using graviton 2 instances why is this important because aws is well ahead of the competition in custom silicon chips is and is on a price performance curve that is far better than alternatives especially those based on x86 this is one of the reasons why we think this business is not a race to the bottom aws is being followed by google microsoft and alibaba in terms of developing custom silicon and will continue to drive down their internal cost structures and deliver price performance equal to or better than the historical moore's law curves so that's the recent news for the big u.s cloud providers let's now take a look at how the year ended for the big four hyperscalers and look ahead to next year here's a table we've shown this view before it shows the revenue estimates for worldwide is and paths generated by aws microsoft alibaba and google now remember amazon and alibaba they share clean eye ass figures whereas microsoft and alphabet only give us these nuggets that we have to interpret and we correlate those tidbits with other data that we gather we're one of the few outlets that actually attempts to make these apples to apples comparisons there's a company called synergy research there's another firm that does this but i really can't map to their numbers their gcp figures look far too high and azure appears somewhat overestimated and they do include other stuff like hosted private cloud services but it's another data point that you can use okay back to the table we've slightly adjusted our gcp figures down based on interpreting some of alphabet's statements and other survey data only alibaba has yet to announce earnings so we'll stick to a 2021 market size of about 120 billion dollars that's a 41 growth rate relative to 2020 and we expect that figure to increase by 38 percent to 166 billion in 2022 now we'll discuss this a bit later but these four companies have created an opportunity for the ecosystem to build what we're calling super clouds on top of this infrastructure and we're seeing it happen it was increasingly obvious at aws re invent last year and we feel it will pick up momentum in the coming months and years a little bit more on that later now here's a graphical view of the quarterly revenue shares for these four companies notice that aws has reversed its share erosion and is trending up slightly aws has accelerated its growth rate four quarters in a row now it accounted for 52 percent of the big four hyperscaler revenue last year and that figure was nearly 54 in the fourth quarter azure finished the year with 32 percent of the hyper scale revenue in 2021 which dropped to 30 percent in q4 and you can see gcp and alibaba they're neck and neck fighting for the bronze medal by the way in our recent 2022 predictions post we said google cloud platform would surpass alibaba this year but given the recent trimming of our numbers google's got some work to do for that prediction to be correct okay just to put a bow on the wikibon market data let's look at the quarterly growth rates and you'll see the compression trends there this data tracks quarterly revenue growth rates back to 20 q1 2019 and you can see the steady downward trajectory and the reversal that aws experienced in q1 of last year now remember microsoft guided for sequential growth and azure so that orange line should trend back up and given gcp's much smaller and big go to market investments that we talked about we'd like to see an acceleration there as well the thing about aws is just remarkable that it's able to accelerate growth at a 71 billion run rate business and alibaba you know is a bit more opaque and likely still reeling from the crackdown of the chinese government we're admittedly not as close to the china market but we'll continue to watch from afar as that steep decline in growth rate is somewhat of a concern okay let's get into the survey data from etr and to do so we're going to take some time series views on some of the select cloud platforms that are showing spending momentum in the etr data set you know etr uses a metric we talked about this a lot called net score to measure that spending velocity of products and services netscore basically asks customers are you spending more less or the same on a platform and a vendor and then it subtracts the lesses from the moors and that yields a net score this chart shows net score for five cloud platforms going back to january 2020. note in the table that the table we've inserted inside that chart shows the net score and shared n the latter metric indicates the number of mentions in the data set and all the platforms we've listed here show strong presence in the survey that red dotted line at 40 percent that indicates spending is at an elevated level and you can see azure and aws and vmware cloud on aws as well as gcp are all nicely elevated and bounding off their october figures indicating continued cloud momentum overall but the big surprise in these figures is the steady climb and the steep bounce up from oracle which came in just under the 40 mark now one quarter is not necessarily a trend but going back to january 2020 the oracle peaks keep getting higher and higher so we definitely want to keep watching this now here's a look at some of the other cloud platforms in the etr survey the chart here shows the same time series and we've now brought in some of the big hybrid players notably vmware cloud which is vcf and other on-prem solutions red hat openstack which as we've reported in the past is still popular in telcos who want to build their own cloud we're also starting to see hpe with green lake and dell with apex show up more and ibm which years ago acquired soft layer which was really essentially a bare metal hosting company and over the years ibm cobbled together its own public cloud ibm is now racing after hybrid cloud using red hat openshift as the linchpin to that strategy now what this data tells us first of all these platforms they don't have the same presence in the data set as do the previous players vmware is the one possible exception but other than vmware these players don't have the spending velocity shown in the previous chart and most are below the red line hpe and dell are interesting and notable in that they're transitioning their early private cloud businesses to dell gr sorry hpe green lake and dell apex respectively and finally after years of kind of staring at their respective navels in in cloud and milking their legacy on-prem models they're finally building out cloud-like infrastructure for their customers they're leaning into cloud and marketing it in a more sensible and attractive fashion for customers so we would expect these figures are going to bounce around for a little while for those two as they settle into a groove and we'll watch that closely now ibm is in the process of a complete do-over arvin krishna inherited three generations of leadership with a professional services mindset now in the post gerschner gerstner era both sam palmisano and ginny rometty held on far too long to ibm's service heritage and protected the past from the future they missed the cloud opportunity and they forced the acquisition of red hat to position the company for the hybrid cloud remedy tried to shrink to grow but never got there krishna is moving faster and with the kindred spin is promising mid-single-digit growth which would be a welcome change ibm is a lot of work to do and we would expect its net score figures as well to bounce around as customers transition to the future all right let's take a look at all these different players in context these are all the clouds that we just talked about in a two-dimensional view the vertical axis is net score or spending momentum and the horizontal axis is market share or presence or pervasiveness in the data set a couple of call-outs that we'd like to make here first the data confirms what we've been saying what everybody's been saying aws and microsoft stand alone with a huge presence many tens of billions of dollars in revenue yet they are both well above the 40 line and show spending momentum and they're well ahead of gcp on both dimensions second vmware while much smaller is showing legitimate momentum which correlates to its public statements alibaba the alibaba in this survey really doesn't have enough sample to make hardcore conclusions um you can see hpe and dell and ibm you know similarly they got a little bit more presence in the data set but they clearly have some work to do what you're seeing there is their transitioning their legacy install bases oracle's the big surprise look what oracle was in the january survey and how they've shot up recently now we'll see if this this holds up let's posit some possibilities as to why it really starts with the fact that oracle is the king of mission critical apps now if you haven't seen video on twitter you have to check it out it's it's hilarious we're not going to run the video here but the link will be in our post but i'll give you the short version some really creative person they overlaid a data migration narrative on top of this one tooth guy who speaks in spanish gibberish but the setup is he's a pm he's a he's a a project manager at a bank and aws came into the bank this of course all hypothetical and said we can move all your apps to the cloud in 12 months and the guy says but wait we're running mission critical apps on exadata and aws says there's nothing special about exadata and he starts howling and slapping his knee and laughing and giggling and talking about the 23 year old senior engineer who says we're going to do this with microservices and he could tell he was he was 23 because he was wearing expensive sneakers and what a nightmare they encountered migrating their environment very very very funny video and anyone who's ever gone through a major migration of mission critical systems this is gonna hit home it's funny not funny the point is it's really painful to move off of oracle and oracle for all its haters and its faults is really the best environment for mission critical systems and customers know it so what's happening is oracle's building out the best cloud for oracle database and it has a lot of really profitable customers running on-prem that the company is migrating to oracle cloud infrastructure oci it's a safer bet than ripping it and putting it into somebody else's cloud that doesn't have all the specialized hardware and oracle knowledge because you can get the same integrated exadata hardware and software to run your database in the oracle cloud it's frankly an easier and much more logical migration path for a lot of customers and that's possibly what's happening here not to mention oracle jacks up the license price nearly doubles the license price if you run on other clouds so not only is oracle investing to optimize its cloud infrastructure it spends money on r d we've always talked about that really focused on mission critical applications but it's making it more cost effective by penalizing customers that run oracle elsewhere so this possibly explains why when the gartner magic quadrant for cloud databases comes out it's got oracle so well positioned you can see it there for yourself oracle's position is right there with aws and microsoft and ahead of google on the right-hand side is gartner's critical capabilities ratings for dbms and oracle leads in virtually all of the categories gartner track this is for operational dvms so it's kind of a narrow view it's like the red stack sweet spot now this graph it shows traditional transactions but gartner has oracle ahead of all vendors in stream processing operational intelligence real-time augmented transactions now you know gartner they're like old name framers and i say that lovingly so maybe they're a bit biased and they might be missing some of the emerging opportunities that for example like snowflake is pioneering but it's hard to deny that oracle for its business is making the right moves in cloud by optimizing for the red stack there's little question in our view when it comes to mission critical we think gartner's analysis is correct however there's this other really exciting landscape emerging in cloud data and we don't want it to be a blind spot snowflake calls it the data cloud jamactagani calls it data mesh others are using the term data fabric databricks calls it data lake house so so does oracle by the way and look the terminology is going to evolve and most of the action action that's happening is in the cloud quite frankly and this chart shows a select group of database and data warehouse companies and we've filtered the data for aws azure and gcp customers accounts so how are these accounts or companies that were showing how these vendors were showing doing in aws azure and gcp accounts and to make the cut you had to have a minimum of 50 mentions in the etr survey so unfortunately data bricks didn't make it just not enough presence in the data set quite quite yet but just to give you a sense snowflake is represented in this cut with 131 accounts aws 240 google 108 microsoft 407 huge [ __ ] 117 cloudera 52 just made the cut ibm 92 and oracle 208. again these are shared accounts filtered by customers running aws azure or gcp the chart shows a net score lime green is new ads forest green is spending more gray is flat spending the pink is spending less and the bright red is defection again you subtract the red from the green and you get net score and you can see that snowflake as we reported last week is tops in the data set with a net score in the 80s and virtually no red and even by the way single digit flat spend aws google and microsoft are all prominent in the data set as is [ __ ] and snowflake as i just mentioned and they're all elevated over the 40 mark cloudera yeah what can we say once they were a high flyer they're really not in the news anymore with anything compelling other than they just you know took the company private so maybe they can re-emerge at some point with a stronger story i hope so because as you can see they actually have some new additions and spending momentum in the green just a lot of customers holding steady and a bit too much red but they're in the positive territory at least with uh plus 17 percent unlike ibm and oracle and this is the flip side of the coin ibm they're knee-deep really chest deep in the middle of a major transformation we've said before arvind krishna's strategy and vision is at least achievable prune the portfolio i.e spin out kindrel sell watson health hold serve with the mainframe and deal with those product cycles shift the mix to software and use red hat to win the day in hybrid red hat is working for ibm's growing well into the double digits unfortunately it's not showing up in this chart with little database momentum in aws azure and gcp accounts zero new ads not enough acceleration and spending a big gray middle in nearly a quarter of the base in the red ibm's data and ai business only grew three percent this last quarter and the word database wasn't even mentioned once on ibm's earnings call this has to be a concern as you can see how important database is to aws microsoft google and the momentum it's giving companies like snowflake and [ __ ] and others which brings us to oracle with a net score of minus 12. so how do you square the momentum in oracle cloud spending and the strong ratings and databases from gartner with this picture good question and i would say the following first look at the profile people aren't adding oracle new a large portion of the base 25 is reducing spend by 6 or worse and there's a decent percentage of the base migrating off oracle with a big fat middle that's flat and this accounts for the poor net score overall but what etr doesn't track is how much is being spent rather it's an account based model and oracle is heavily weighted toward big spenders running mission critical applications and databases oracle's non-gaap operating margins are comparable to ibm's gross margins on a percentage basis so a very profitable company with a big license and maintenance in stall basin oracle has focused its r d investments into cloud erp database automation they've got vertical sas and they've got this integrated hardware and software story and this drives differentiation for the company but as you can see in this chart it has a legacy install base that is constantly trying to minimize its license costs okay here's a little bit of different view on the same data we expand the picture with the two dimensions of net score on the y-axis and market share or pervasiveness on the horizontal axis and the table insert is how the data gets plotted y and x respectively not much to add here other than to say the picture continues to look strong for those companies above the 40 line that are focused and their focus and have figured out a clear cloud strategy and aren't necessarily dealing with a big install base the exception of course is is microsoft and the ones below the line definitely have parts of their portfolio which have solid momentum but they're fighting the inertia of a large install base that moves very slowly again microsoft had the advantage of really azure and migrating those customers very quickly okay so let's wrap it up starting with the big three cloud players aws is accelerating and innovating great example is custom silicon with nitro and graviton and other chips that will help the company address concerns related to the race to the bottom it's not a race to zero aws we believe will let its developers go after the sas business and for the most part aws will offer solutions that address large vertical markets think call centers the edge remains a wild card for aws and all the cloud players really aws believes that in the fullness of time all workloads will run in the public cloud now it's hard for us to imagine the tesla autonomous vehicles running in the public cloud but maybe aws will redefine what it means by its cloud microsoft well they're everywhere and they're expanding further now into gaming and the metaverse when he became ceo in 2014 many people said that satya should ditch xbox just as an aside the joke among many oracle employees at the time was that safra katz would buy her kids and her nieces and her nephews and her kids friends everybody xbox game consoles for the holidays because microsoft lost money for everyone that they shipped well nadella has stuck with it and he sees an opportunity to expand through online gaming communities one of his first deals as ceo was minecraft now the acquisition of activision will make microsoft the world's number three gaming company by revenue behind only 10 cent and sony all this will be powered by azure and drive more compute storage ai and tooling now google for its part is battling to stay relevant in the conversation luckily it can afford the massive losses it endures in cloud because the company's advertising business is so profitable don't expect as many have speculated that google is going to bail on cloud that would be a huge mistake as the market is more than large enough for three players which brings us to the rest of the pack cloud ecosystems generally and aws specifically are exploding the idea of super cloud that is a layer of value that spans multiple clouds hides the underlying complexity and brings new value that the cloud players aren't delivering that's starting to bubble to the top and legacy players are staying close to their customers and fighting to keep them spending and it's working dell hpe cisco and smaller predominantly on-plan prem players like pure storage they continue to do pretty well they're just not as sexy as the big cloud players the real interesting activity it's really happening in the ecosystem of companies and firms within industries that are transforming to create their own digital businesses virtually all of them are running a portion of their offerings on the public cloud but often connecting to on-premises workloads and data think goldman sachs making that work and creating a great experience across all environments is a big opportunity and we're seeing it form right before our eyes don't miss it okay that's it for now thanks to my colleague stephanie chan who helped research this week's topics remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcast check out etr's website at etr dot ai and also we publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me email me at david.velante siliconangle.com you can dm me at divalante or comment on my linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time [Music] you

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Breaking Analysis: The Hybrid Cloud Tug of War Gets Real


 

>> From the theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> Well, it looks like hybrid cloud is finally here. We've seen a decade of posturing, marchitecture, slideware and narrow examples of hybrid cloud, but there's little question that the definition of cloud is expanding to include on-premises workloads in hybrid models. Now depending on which numbers you choose to represent IT spending, public cloud only accounts for actually less than 5% of the total pie. So the big question is, how will this now evolve? Customers want control, they want governance, they want security, flexibility and a feature-rich set of services to build their digital businesses. It's unlikely that they can buy all that, so they're going to have to build it with partners, specifically vendors, SI's, consultancies and their own developers. The tug of war to win the new cloud day has finally started in earnest between the hyperscalers and the largest enterprise tech companies in the world. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we'll walk you through how we see the battle for hybrid cloud, how we got here, where we are and where it's headed. First, I want to go back to 2009, in a blog post by a man named Chuck Hollis. Chuck Hollis, at the time, was a CTO and marketing guru inside of EMC who, remember, owned VMware. Chuck was kind of this hybrid, multi-tool player, pun intended. EMC at the time had a big stake, a lot at stake, as the ascendancy of AWS was threatening the historical models, which had defined enterprise IT. Now around that time, NIST published its first draft of a cloud computing definition which, as I recall, included language, something to the effect of accessing remote services over the public network, i.e., public IP networks. Now, NIST has essentially or since evolved that definition, but the original draft was very favorable to the public cloud. And the vendor community, the traditional vendor community, said hang on, we're in this game too. So that was 2009 when Chuck Hollis published this slide. He termed it Private Cloud, a term which he saw buried inside of a Gartner research post or research note that was not really fleshed out and defined. The idea was pretty compelling. The definition of cloud centered on control, where you, as the customer, had on-prem workloads that could span public and on-prem clouds, if you will, with federated security and a data plan that spanned the states. Essentially, you had an internal and an external cloud with a single point of control. This is basically what the hybrid cloud vision has become. An abstraction layer that spans on-prem and public clouds and we can extend that across clouds and out to the edge, where a customer has a single point of control and federated governance and security. Now we know this is still aspirational, but we're now seeing vendor offerings that put forth this promise and a roadmap to get there from different points of view, that we're going to talk about today. The NIST definition now reads cloud computing is a model for enabling ubiquitous, convenient on-demand network access to a shared pool of configurable computing resources, e.g., network server storage, applications and services, that can be rapidly provisioned and released with minimal management effort or service provider interaction. So there you have it, that is inclusive of on-prem, but it took the industry a decade plus to actually get where we are today. And they did so by essentially going to school with the public cloud offerings. Now in 2018, AWS announced Outposts and that was another wake up call to the on-prem community. Externally, they pointed to the validation that hybrid cloud was real. Hey, AWS is doing it so clearly they've capitulated, but most on-prem vendors at the time didn't have a coherent offering for hybrid, but the point is the on-prem vendors responded as they saw AWS moving past the demilitarized zone into enemy lines. And here's what the competitive landscape of hybrid offerings looks like today. All three US-based hyperscalers have an offering or multiple offerings in various forms, Outposts from Amazon and other services that they offer, Google Anthos and Azure Arc, they're all so prominent, but the real action today is coming from the on-prem vendors. Every major company has an offering. Now most of these stemmed from services-led and finance-led initiatives, but they're evolving to true Azure Service models. HPE GreenLake is prominent and the company's CEO, Antonio Neri, is putting the whole company behind Azure Service. HPE claims to be the first, it uses that in its marketing, with such an Azure Service offering, but actually Oracle was their first with Cloud@Customer. You know, possibly Microsoft could make a claim to being early as well, but it really doesn't matter. Let's see, Dell has responded with Apex and is going hard after this opportunity. Cisco has Cisco Plus and Lenovo has TruScale. IBM also has a long services and finance-led history and has announced pockets of Azure Service in areas like storage. And Pure Storage is an example that we chose of a segment player, of course within storage, that has a strong Azure Service offering, and there are others like that. So the landscape is getting very busy. And so, let's break this down a bit. AWS is bringing its programmable infrastructure model and its own hardware to what it calls the edge. And it looks at on-prem data centers as just another edge node. So that's how they're de-positioning the on-prem crowd, but the fact is, when you really look at what Outposts can do today, it's limited, but AWS will move quickly so expect a continued rapid evolution of their model and the services that are supported on Outposts. Azure gets its hardware from partners and has relationships with virtually everyone that matters. Anthos is, as well, a software layer and Google created Kubernetes as the great equalizer in cloud. And it was a nice open source gift to the industry and has obviously taken off. So the cloud guys have the advantage of owning a cloud. The pure on-prem players, they don't, but the on-prem crowd has rich stacks, much richer and more mature in a lot of areas, as it relates to supporting on-premises workloads and much more so than the cloud players, but they don't have mature cloud stacks. They're kind of just getting started with things like subscription billing and API-based microservices offerings. They got to figure out Salesforce compensation and just the overall Azure service mentality versus the historical product box mentality, and that takes time. And they're each coming at this from their respective different points of view and points of strength. HPE is doing a very good job of marketing and go-to market. It probably has the cleanest model, enabled by the company's split from HP, but it has some gaps that it's needed to fill and it's doing so through acquisitions. Ezmeral, for example, is it's new data play. It just bought Zerto to facilitate backup as a service. And it's expanded partnerships to fill gaps in the portfolio. Some partnerships, which they couldn't do before because it created conflicts inside of HPE or HP. Dell is all about the portfolio, the breadth of the portfolio, the go-to-market prowess and its supply chain advantage. It's very serious about Azure Service with Apex and it's driving hard to win that day. Cisco comes at this from a huge portfolio and of course, a point of strength and networking, which maybe is a bit tougher to offer as a service, but Cisco has a large and fast growing subscription business in collaborations, security and other areas, so it's cloud-like in that regard. And Oracle, of course, has the huge advantage of an extremely rich functional stack and it owns a cloud, which has dramatically improved in the past few years, but Oracle is narrow to the red stack, at least today. Oracle, if it wanted to, we think, could dominate the database cloud, it could be the database cloud, especially if it decided to open its cloud to competitive database offerings and run them in the Oracle cloud. Hmm. Wonder if Oracle will ever move in that direction. Now a big part of this shift is the appeal of OPEX versus CAPEX. Let's take a look at some ETR data that digs a bit deeper into this topic. This data is from an August ETR drill down, asking CIOs and IT buyers how their budgets are split between OPEX and CAPEX. The mid point of the yellow line shows where we are today, 57% OPEX, expecting to grow to 63% one year from now. That's not a huge difference, there's not a huge difference when you drill into global 2000, which kind of surprised me. I thought global 2000 would be heavier CAPEX, but they seem to be accelerating the shift to OPEX slightly faster than the overall base, but not really in a meaningful way. So I didn't really discern big differences there. Now, when you dig further into industries and look at subscription versus consumption models for OPEX, you see about 60/40 favoring subscription models, with most industry slowly moving toward consumption or usage based models over time. There are a couple of outliers, but generally speaking, that's the trend. What's perhaps more interesting is when you drill into subscription versus usage based models by product area, and that's what this chart shows. It shows by tech segment, the percent subscription, that's the blue, versus consumption or usage based, that's the gray bars, yellow being indifferent or maybe it's I don't know. What stands out are two areas that are more usage heavy, consumption heavy. That's database, data warehousing, and IS. So database is surely weighted by companies like Snowflake and offerings like Redshift and other cloud databases from Azure and Google and other managed services, but the IS piece, while not surprising, is, we think, relevant because most of the legacy vendor Azure Service offerings are borrowing from a SaaS-oriented subscription model with a hardware twist. In other words, as a customer, you're committing to a term and a minimum spend over the life of that term. You're locked in for a year or three years, whatever it is, to account for the hardware and headroom the vendor has to install because they want to allow you to increase your usage. So that's the usage based model. See, you're then paying by the drink for that consumption above that minimum threshold. So it's a hybrid subscription consumption model, which is actually quite interesting. And we've been saying, what would really be cool is if one of the on-prem penguins on the iceberg would actually jump in and offer a true consumption model right out of the box, as a disruptive move to the industry and to the cloud players, and take that risk. And I think that might happen once they feel comfortable with the financial model and they have nailed the product market fit, but right now, the model is what it is. And even AWS without post requires a threshold and a minimum commitment. So we'd love to see someone take that chance and offer true cloud consumption pricing to facilitate more experimentation and lower risk for the customer entry points. Now let's take a look at some of these players and see what kind of spending momentum they have. This is our popular XY chart-view that plots net score or spending velocity on the x-axis and market share or pervasiveness in the data set on the... Oh, sorry, net score or spending momentum on the y-axis and pervasiveness or market share on the x-axis. Now this is cut by cloud computing vendors, as defined by the customers responding. There were nearly 1500 respondents in the ETR survey, so a couple of points here. Note the red line is the elevated line. In other words, anything above that is considered really robust momentum. And no surprise, Azure, AWS and Google are above that line. Azure and AWS always battle it out for top share of voice in the x-axis in this survey. Now this, remember, is the July survey, but ETR, they gave me a sneak peek at the October results that they're going to be releasing in the coming week and Dell cloud and VMware cloud, which is VCF and maybe some other components, not VMware cloud and AWS, that's a separate beast, but those two are moving up in the y-axis. So they're demonstrating spending momentum. IBM is moving down and Oracle is at a respectable 20% on the y-axis. Now, interestingly, HPE and Lenovo don't show up in the cloud taxonomy, in that cloud cut, and neither does Cisco. I believe I'm correct in that this is an open-ended question, i.e., who are your cloud suppliers? So the customers are not resonating with that messaging yet, but I'm going to double check on that. Now to widen the aperture a bit, we said let's do a cut of the on-prem and cloud players within cloud accounts, so we can include HPE and Cisco and see how they're doing inside of cloud accounts. So that's what this chart does. It's a filter on 975 customers who identify themselves as cloud accounts. So here we were able to add in Cisco and HPE. Now, Lenovo still doesn't show up on the data. It shows up in laptops and desktops, but not as prominent in the enterprise, not prominent at all, but HPE Ezmeral did show up and it's moving forward in the October survey, again, part of the sneak peek. Ezmeral is HPE's data platform that they've introduced, combining the assets of MapR, BlueData and some other organic development. Now, as you can see, HPE and Cisco, they show up on the chart, as I said, and you can see the rope in the tug of war is starting to get a little bit more taut. The cloud guys have momentum and big account presence, but the on-prem folks also have big footprints, rich stacks and many have strong services arms, and a lot of customer affinity. So let's wrap with some comments about how this will shake out and what's some of the markers we can watch. Now, the first thing I'll say is we're starting to hear the right language come out of the vendor community. The idea that they're investing in a layer to abstract the underlying complexity of the clouds and on-prem infrastructure and turning the world into, essentially, a programmable interface to resources. The question is, what about giving access through that layer to underlying primitives in the public cloud? VMware has been very clear on this. They will facilitate that access. I believe Red Hat as well. So watch to the degree in which the large on-prem players are enabling that access for developers. We believe this is the right direction overall, but it's also very hard and it's going to require lots of resources and R & D. I would say at this point that each company has its respective strengths and weaknesses. I see HPE mostly focused today on making its on-prem offerings work like a cloud, whereas some of the others, VMware, Dell and Cisco, are stressing to a greater degree, in my view, enabling multi-cloud and edge connections, cross connections. Not that HPE isn't open to that when you ask them about it, but its marketing is more on-prem leaning, in my opinion. Now all of the traditional vendors, in my view, are still defensive about the cloud, although I would say much less so each day. Increasingly, they look at the public cloud as an opportunity to build value on top of that abstraction layer, if you will. As I said earlier, these on-prem guys, they all have ways to go. They're in the early stages of figuring out what a cloud operating model looks like, how it works, what services to offer, how to pay sellers and partners, but the public cloud vendors, they're miles ahead in that regard, but at the same time, they're navigating into on-prem territory. And they're very immature, in most cases. So how do they service all this stuff? How do they establish partnerships and so forth? And how do they build stacks on prem that are as rich as they are in the cloud? And what's their motivation to do that? Are they getting pulled, digging their heels in? Or are they really serious about it? Now, in some respects, Oracle is in the best position here in terms of hybrid maturity, but again, it's narrowly focused on the Red Stack. I would say the same for Pure Storage, more mature as a service, but narrowly focused, of course, on storage. Let's talk marketplace and ecosystems. One of the hallmarks of public clouds is optionality of tooling. Just all you do is go to the AWS Marketplace and you'll see what I mean. It's got this endless bevy of choices. It's got one of everything in there and you can buy directly from your AWS Console. So watch how the hybrid cloud plays out in terms of partner inclusion and ease of doing business, that's another sign of maturity. Let's talk developers and edge. This is by far the most important and biggest hole in the hybrid portfolios, outside the public cloud players. If you're going to build infrastructure as code, who do you expect to code it? How are the on-prem players cultivating developer communities? IBM paid 34 billion to buy its way in. Actually, in today's valuation terms, you might say that's looking like a good play, but still, that cash outlay is equal to one third of IBM's revenue. So big, big bet on OpenShift, but IBM's infrastructure strategy is fragmented and its cloud business, as IBM reports in its financial statements, is a services-heavy, kitchen sink set of offerings. It's very confusing. So they got to still do some clean up there, but they're serious about the architectural battle for hybrid cloud, as Arvind Krishna calls it. Now VMware, by cobbling together the misfit developer toys of the remnants from the EMC Federation, including Pivotal, is trying to get there. You know, but when you talk to customers, they're still not all in on VMware's developer affinity. Now Cisco has DevNet, but that's basically CCIE's and other trained networking engineers learning to code in languages like Python. It's not necessarily true devs, although they're upskilling. It's a start and they're investing, Cisco, that is, investing in the community, leveraging their champions, and I would say Dell could do the same with, for example, the numerous EMC storage admins that are out there. Now Oracle bought Sun to get Java, and that's a large community of developers, but even so, when you compare AWS and Microsoft ecosystems to the others, it's not even close in terms of developer affinity. So lots of work to be done there. One other point is Pure's acquisition of Portworx, again, while narrowly focused, is a good move and instructive of the changes going on in infrastructure. Now how does this all relate to the edge? Well, I'm not going to talk much about that today, but suffice to say, developers, in our view, will win the edge. And right now, they're coding in the cloud. Now they're often coding in the cloud and moving work on prem, wrapping them in containers, but watch how sticky that model is for the respective players. The other thing to watch is cadence of offerings. Another hallmark of cloud is a rapid expansion of features. The public cloud players don't appear to be slowing down and the on-prem folks seem to be accelerating. I've been watching HPE and GreenLake and their cadence of offerings, and watch how quickly the newbies of Azure Service can add functionality, I have no doubt Dell is going to be right there as well, as is Cisco and others. Also pay attention to financial metrics, watch how Azure Service impacts the income statements and how the companies deal with that because as you shift to deferred revenue models, it's going to hurt profitability. And I'm not worried about that at all because it won't hurt cashflow, or at least it shouldn't. As long as the companies communicate to Wall Street and they're transparent, i.e., they don't shift reporting definitions every year and a half or two years, but watch for metrics around retention and churn, RPO or Remaining Performance Obligations, billing versus bookings, increased average contract values, cohort selling, the impact on both gross margin and operating margin. These are the things you watch with SaaS companies and essentially, these big hardware players are becoming Azure Service slash SaaS companies. These are going to be the key indicators of success and the proof in the pudding of the transition to Azure Service. It should be positive for these companies, assuming they get the product market fit right, and can create a flywheel effect with their respective ecosystems and partner channels. Now I'm sure you can think of other important factors to watch, but I'm going to leave it here for now. Remember these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis podcast and please subscribe, check out ETR's website at etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can get in touch with me, email david.vellante@siliconangle.com or you can DM me @dvellante. You can comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week, everybody, stay safe, be well. And we'll see you next time. (soft music)

Published Date : Oct 15 2021

SUMMARY :

From the theCUBE Studios and a data plan that spanned the states.

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Breaking Analysis Rethinking Data Protection in the 2020s


 

>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Techniques to protect sensitive data have evolved over thousands of years literally. The pace of modern data protection is rapidly accelerating and presents both opportunities and threats for organizations. In particular, the amount of data stored in the cloud combined with hybrid work models, the clear and present threat of cyber crime, regulatory edicts and the ever expanding edge and associated use cases should put CXOs on notice that the time is now to rethink your data protection strategies. Hello, and welcome to this week's Wikibon theCUBE Insights powered by ETR. In this Breaking Analysis, we're going to explore the evolving world of data protection and share some information on how we see the market changing in the competitive landscape for some of the top players. Steve Kenniston AKA the Storage Alchemist shared a story with me and it was pretty clever. Way back in 4,000 BC the Sumerians invented the first system of writing. Now they used clay tokens to represent transactions at that time. Now, to prevent messing with these tokens, they sealed them in clay jars to ensure that the tokens or either data would remain secure with an accurate record, let's call it quasi immutable and lived in a clay vault. Since that time, we've seen quite an evolution in data protection. Tape, of course, was the main means of protecting data, backing data up during most of the mainframe era and that carried into client server computing, which really accentuated and underscored the issues around backup windows and challenges with RTO, Recovery Time Objective and RPO, Recovery Point Objective, and just overall recovery nightmares. Then in the 2000s data reduction made displace backup more popular and push tape into an archive last resort media data domain then EMC now Dell still sell many purpose built backup appliances as do others as a primary backup target disc base. The rise of virtualization brought more changes in backup and recovery strategies as a reduction in physical resources squeezed the one application that wasn't under utilizing compute i.e backup. And we saw the rise of Veeam, the cleverly named company that became synonymous with data protection for virtual machines. Now the cloud has created new challenges related to data sovereignty, governance latency, copy creep, expense, et cetera but more recently cyber threats have elevated data protection to become a critical adjacency to information security. Cyber resilience to specifically protect against ransomware attacks as the new trend being pushed by the vendor community as organizations are urgently looking for help with this insidious threat. Okay, so there are two major disruptors that we're going to talk about today, the cloud and cyber crime, especially around ransoming your data. Every customer is using the cloud in some way, shape or form. Around 76% are using multiple clouds that's according to a recent study by HashiCorp. We've talked extensively about skill shortages on theCUBE and data protection and security concerns are really key challenges to address given that skill shortage is a real talent gap in terms of being able to throw people at solving this problem. So what customers are doing they're either building out or they're buying, really mostly building abstraction layers to hide the underlying cloud complexity. So, what this does, the good news is it simplifies provisioning and management but it creates problems around opacity. In other words, you can't see sometimes what's going on with the data, these challenges fundamentally become data problems in our view. Things like fast, accurate, and complete backup recovery, compliance, data sovereignty, data sharing, I mentioned copy creep, cyber resiliency, privacy protections these are all challenges brought to fore by the cloud, the advantages, the pros and the cons. Now, remote workers are especially vulnerable and as clouds expand rapidly data protection technologies are struggling to keep pace. So let's talk briefly about the rapidly expanding public cloud. This chart shows worldwide revenue for the big four hyperscalers, as you can see we projected they're going to surpass $115 billion in revenue in 2021, that's up from 86 billion last year. So it's a huge market, it's growing in the 35% range. The interesting thing is last year, 80 plus billion dollars in revenue but a 100 billion dollars was spent last year by these firms in CapEx. So they're building out infrastructure for the industry. This is a gift to the balance of the industry. Now to date legacy vendors and their surrounding community have been pretty defensive around the cloud, "Oh, not everything is going to move to the cloud, it's not a zero sum game we here." And while that's all true the narrative was really kind of a defense posture and that's starting to change as large tech companies like Dell, IBM, Cisco, HPE, and others see opportunities to build on top of this infrastructure. You certainly see that with Arvind Krishna's comments at IBM, Cisco obviously leaning in from a networking and security perspective. HPE using language that is very much cloud-like with its GreenLake strategy. And of course, Dell is all over this. Let's listen to how Michael Dell is thinking about this opportunity when he was questioned on theCUBE by John Furrier about the cloud. Play the clip. >> Well, clouds are infrastructure, right? So you can have a public cloud, you can have an edge cloud, a private cloud, a Telco cloud, a hybrid cloud, multicloud, here cloud, there cloud, everywhere cloud, cloud. Yet, they'll all be there, but it's basically infrastructure. And how do you make that as easy to consume and create the flexibility that enables everything. >> Okay, so in my view, Michael nailed it, the cloud is everywhere. You have to make it easy and you have to admire the scope of his comments. We know this guy, he thinks big, right? He said enables everything. What he's basically saying is that, technology is at the point where it has the potential to touch virtually every industry, every person, every problem, everything. So let's talk about how this informs the changing world of data protection. Now, we've seen with the pandemic there's an acceleration toward digital and that has caused an escalation if you will, in the data protection mandate. So essentially what we're talking about here is the application of Michael Dell's cloud everywhere comments. You've got on-prem, private clouds, hybrid clouds, you've got public clouds across AWS, Azure, Google, Alibaba, really those big four hyperscalers. You got many clouds that are popping up all over the place, but multicloud to that HashiCorp data point, 75, 76%, and then you now see the cloud expanding out to the edge, programmable infrastructure heading out to the edge. So the opportunity here to build the data protection cloud is to have the same experiences across all these estates with automation and orchestration in that cloud, that data protection cloud if you will. So think of it as an abstraction layer that hides that underlying complexity, you log into that data protection cloud it's the same experience. So you've got backup, you've got recovery, you can handle bare-metal, you can do virtualized backups and recoveries, any cloud, any OS, out to the edge, Kubernetes and container use cases, which is an emerging data protection requirement and you've got analytics, perhaps you've got PII, Personally Identifiable Information protection in there. So the attributes of this data protection cloud, again, it abstracts the underlying cloud primitives, takes care of that. It also explodes cloud native technologies. In other words, it takes advantage of whether it's machine learning, which all the big cloud players have expertise in, new processor models things like Graviton and other services that are in the cloud natively. It doesn't just wrap it's on-prem stack in a container and shove it into the cloud, no, it actually re architects or architects around those cloud native services and it's got distributed metadata to track files and volumes and any organizational data irrespective of location. And it enables sets of services to intelligently govern in a federated governance manner while ensuring data integrity and all this is automated and orchestrated to help with the skills gap. Now, as it relates to cyber recovery, air gap solutions must be part of the portfolio, but managed outside of that data protection cloud that we just briefly described. The orchestration and the management must also be gapped if you will, otherwise, you don't have an air gap. So all of this is really a cohort to cyber security or your cybersecurity strategy and posture, but you have to be careful here because your data protection strategy could get lost in this mess. So you want to think about the data protection cloud as again, an adjacency or maybe an overlay to your cybersecurity approach, not a bolt on it's got to be fundamentally architectured from the bottom up. And yes, this is going to maybe create some overheads and some integration challenges but this is the way in which we think you should think about it. So you'll likely need a partner to do this, again, we come back to the skills gap if were seeing the rise of MSPs, managed service providers and specialist service providers, not public cloud providers, people are concerned about lock-in and that's really not their role. They're not high touch services company, probably not your technology arms dealer, excuse me, they're selling technology to these MSPs. So the MSPs, they have intimate relationships with their customers. They understand their business and specialize in architecting solutions to handle these difficult challenges. So let's take a look at some of the risk factors here and dig a little bit into the cyber threat that organizations face. This is a slide that, again, the Storage Alchemists, Steve Kenniston shared with me, it's based on a study that IBM funds with the Panama Institute, which is a firm that studies these things like cost of breaches and has for many, many, many years. The slide shows the total cost of a typical breach within each dot and on the Y-axis and the frequency in percentage terms on the horizontal axis. Now it's interesting, the top two are compromised credentials and fishing, which once again proves that bad user behavior trumps good security every time. But the point here is that the adversary's attack vectors are many and specific companies often specialize in solving these problems often with point products, which is why the slide that we showed from Optiv earlier, that messy slide looks so cluttered. So it's a huge challenge for companies, and that's why we've seen the emergence of cyber recovery solutions from virtually all the major players. Ransomware and the SolarWinds hack have made trust the number one issue for CEOs and CSOs and boards of directors, shifting CSO spending patterns are clear. Shifting largely because they're catalyzed by the work from home. But outside of the moat to endpoint security identity and access management, cloud security, the horizontal network security. So security priorities and spending are changing that's why you see the emergence of disruptors like we've covered extensively, Okta, Crowdstrike, Zscaler. And cyber resilience is top of mind and robust solutions are required and that's why companies are building cyber recovery solutions that are most often focused on the backup corpus because that's a target for the bad guys. So there is an opportunity, however to expand from just the backup corpus to all data and protect this kind of 3-2-1, or maybe it's 3-2-1-1, three copies, two backups, a backup in the cloud and one that's air gapped. So this can be extended to primary storage, copies, snaps, containers, data in motion, et cetera, to have a comprehensive data protection strategy. Customers as I said earlier, increasingly looking to manage service providers and specialists because of that skills gap and that's a big reason why automation is so important in orchestration. And automation and orchestration I'll emphasize on the air gap solutions should be separated physically and logically. All right, now let's take a look at some of the ETR data and some of the players. This is a chart that we like to show often, it's a X, Y axis, and the Y-axis is net score, which is a measure of spending momentum and the horizontal axis is market share. Now market share is an indicator of pervasiveness in the survey. It's not spending market share, it's not market share of the overall market, it's a term that ETR uses. It's essentially market share of the responses within the survey set, think of it as mind share. Okay, you've got the pure plays here on this slide in the storage category, there is no data protection or backup category so what we've done is we've isolated the pure plays or close to pure plays in backup and data protection. Notice that red line, that red line is kind of our subjective view of anything that's over that 40% line is elevated, you can see only rubric in the July survey is over that 40% line. I'll show you the ends in a moment. Smaller ends, but still rubric is the only one. Now look at Cohesity and rubric in the January, 2020. So last year pre-pandemic Cohesity and Rubrik they've come well off their peaks for net score. Look at Veeam, Veeam having studied this data for the last say 24 plus months, Veeam has been Steady Eddie. It is really always in the mid to high 30s, always shows a large shared end so it's coming up in the survey, customers are mentioning Veeam and it's got a very solid net score. It's not above that 40% line but it's hovering just below consistently, that's very impressive. Commvault has steadily been moving up. Sanjay Mirchandani has made some acquisitions, he did the Hedvig acquisition. They launched metallic that's driving cloud affinity within a Commvault large customer base so it's a good example of a legacy player, pivoting and evolving and transforming itself. Veritas continues to underperform in the ETR surveys relative to the other players. Now, for context, let's say add IBM and Dell to the chart. Now just note, this is IBM and Dell's full storage portfolio. The category in the taxonomy at ETR is all storage. Okay, this previous slide I isolated on the pure plays, but this now adds in IBM and Dell. It probably representative of where they would be, probably Dell larger on the horizontal axis than IBM, of course and you could see the spending momentum in accordingly. So you could see that in the data chart that we've inserted. So smaller ends for Rubrik and Cohesity, but still enough to pay attention, it's not like one or two when you're 20 plus, 15 plus, 25 plus you can start to pay attention to trends. Veeam again is very impressive. Its net score is solid, it's got a consistent presence in the dataset, it's clear leader here. SimpliVity is small but it's improving relative to last several surveys and we talked about Commvault. Now, I want to emphasize something that we've been hitting on for quite some time now and that's the renaissance that's coming in compute. Now we all know about Moore's law, the doubling of transistor density every two years, 18 to 24 months and that leads to a doubling of performance in that time frame. X86, that X86 curve is in the blue and if you do the math, this is expressed in trillions of operations per second. The orange line is a representative of Apple's A series culminating in the A-15 most recently, the A series is what Apple is now... It's the technology basis for what's inside, and one the new Apple laptops, which is replacing Intel. That's that orange line there we'll come back to that. So go back to the blue line for a minute. If you do the math on doubling performance every 24 months, it comes out to roughly 40% annual improvement in processing power per year. That's now moderated. So Moore's law is waning in one sense so we wrote a piece Moore's law is not dead so I'm sort of contradicting myself there, but the traditional Moore's law curve on X86 is waning. It's probably now down to around 30%, low 30s, but look at the orange line. Again, using the A series as an indicator, if you combine the CPU, the NPU, which is the neural processing unit, XPU, pick whatever PU you want, the accelerators, the DSPs, that line is growing at a 100% plus per year. It's probably more accurately around 110% a year. So there's a new industry curve occurring and it's being led by the Arm ecosystem. The other key factor there you see in a lot of use cases, a lot of consumer use cases Apple is an example but you're also seeing it in things like Tesla, Amazon with AWS Graviton, the Annapurna acquisition, building out Graviton and Nitro that's based on Arm. You can get from design to tape out in less than two years Whereas the Intel cycles we know they've been running it four to five years now, maybe Pat Gelsinger is compressing those, but Intel is behind. So, organizations that are on that orange curve are going to see faster acceleration, lower cost, lower power, et cetera. All right, so what's the tie to data protection? I'm going to leave you with this chart. Arm has introduced it's confidential compute architecture, and is ushering in a new era of security and data protection. Zero Trust is the new mandate and what Arm has done with what they call realms is create physical separation of the vulnerable components by creating essentially physical buckets to put code in and to put data in separate from the OS. Remember the OS is the most valuable entry point for hackers or one of them because it contains privileged access and it's a weak link because of things like memory leakages and vulnerabilities. And malicious code can be placed by bad guys within data in the OS and appear benign even though it's anything but. So in this architecture, all the OS does is create API calls to the realm controller. That's the only interaction. So it makes it much harder for bad actors to get access to the code and the data. And importantly, very importantly, it's an end-to-end architecture so there's protection throughout if you're pulling data from the edge and bringing it back to on-prem and the cloud you've got that end-to-end architecture and protection throughout. So the link to data protection is that backup software vendors need to be the most trusted of applications. Backup software needs to be the most trusted of applications because it's one of the most targeted areas in the cyber attack. Realms provide an end-to-end separation of data and code from the OS and is a better architectural construct to support Zero Trust and confidential computing and critical use cases like data protection/backup and other digital business apps. So our call to action is backup software vendors you can lead the charge. Arm is several years ahead at the moment, head of Intel in our view. So you got to pay attention to that, research that, we're not saying over rotate, but go investigate that. And use your relationships with Intel to accelerate its version of this architecture or ideally the industry should agree on common standards and solve this problem together. Pat Gelsinger told us in theCUBE that if it's the last thing he's going to do in his industry life he's going to solve this security problem. That's when he was at VMware. Well, Pat you're even in a better place to do it now, you don't have to solve it yourself, you can't and you know that. So while you're going about your business saving Intel, look to partner with Arm I know it sounds crazy to use these published APIs and push to collaborate on an open source architecture that addresses the cyber problem. If anyone can do it, you can. Okay, that's it for today. Remember, these episodes are all available as podcasts all you got to do is search Breaking Analysis podcast, I publish weekly on Wikibon.com and SiliconANGLE.com. Or you can reach me at dvellante on Twitter, email me at Dave.Vellante@SiliconANGLE.com. And don't forget to check out ETR.plus for all the survey and data action. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody, be well and we'll see you next time. (upbeat music)

Published Date : Aug 14 2021

SUMMARY :

bringing you data-driven that the time is now to rethink and create the flexibility So the link to data protection is that

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Breaking Analysis: Rethinking Data Protection in the 2020s


 

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is braking analysis with Dave Vellante. >> Techniques to protect sensitive data have evolved over thousands of years, literally. The pace of modern data protection is rapidly accelerating and presents both opportunities and threats for organizations. In particular, the amount of data stored in the cloud combined with hybrid work models, the clear and present threat of cyber crime, regulatory edicts, and the ever expanding edge and associated use cases should put CXOs on notice that the time is now to rethink your data protection strategies. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we're going to explore the evolving world of data protection and share some information on how we see the market changing in the competitive landscape for some of the top players. Steve Kenniston, AKA the Storage Alchemist, shared a story with me, and it was pretty clever. Way back in 4000 BC, the Sumerians invented the first system of writing. Now, they used clay tokens to represent transactions at that time. Now, to prevent messing with these tokens, they sealed them in clay jars to ensure that the tokens, i.e the data, would remain secure with an accurate record that was, let's call it quasi, immutable, and lived in a clay vault. And since that time, we've seen quite an evolution of data protection. Tape, of course, was the main means of protecting data and backing data up during most of the mainframe era. And that carried into client server computing, which really accentuated and underscored the issues around backup windows and challenges with RTO, recovery time objective and RPO recovery point objective. And just overall recovery nightmares. Then in the 2000's data reduction made disk-based backup more popular and pushed tape into an archive last resort media. Data Domain, then EMC, now Dell still sell many purpose-built backup appliances as do others as a primary backup target disc-based. The rise of virtualization brought more changes in backup and recovery strategies, as a reduction in physical resources squeezed the one application that wasn't under utilizing compute, i.e, backup. And we saw the rise of Veem, the cleverly-named company that became synonymous with data protection for virtual machines. Now, the cloud has created new challenges related to data sovereignty, governance, latency, copy creep, expense, et cetera. But more recently, cyber threats have elevated data protection to become a critical adjacency to information security. Cyber resilience to specifically protect against attacks is the new trend being pushed by the vendor community as organizations are urgently looking for help with this insidious threat. Okay, so there are two major disruptors that we're going to talk about today, the cloud and cyber crime, especially around ransoming your data. Every customer is using the cloud in some way, shape, or form. Around 76% are using multiple clouds, that's according to a recent study by Hashi Corp. We've talked extensively about skill shortages on theCUBE, and data protection and security concerns are really key challenges to address, given that skill shortage is a real talent gap in terms of being able to throw people at solving this problem. So what customers are doing, they're either building out or they're buying really mostly building abstraction layers to hide the underlying cloud complexity. So what this does... The good news is it's simplifies provisioning and management, but it creates problems around opacity. In other words, you can't see sometimes what's going on with the data. These challenges fundamentally become data problems, in our view. Things like fast, accurate, and complete backup recovery, compliance, data sovereignty, data sharing. I mentioned copy creep, cyber resiliency, privacy protections. These are all challenges brought to fore by the cloud, the advantages, the pros, and the cons. Now, remote workers are especially vulnerable. And as clouds span rapidly, data protection technologies are struggling to keep pace. So let's talk briefly about the rapidly-expanding public cloud. This chart shows worldwide revenue for the big four hyperscalers. As you can see, we projected that they're going to surpass $115 billion in revenue in 2021. That's up from 86 billion last year. So it's a huge market, it's growing in the 35% range. The interesting thing is last year, 80-plus billion dollars in revenue, but 100 billion dollars was spent last year by these firms in cap ex. So they're building out infrastructure for the industry. This is a gift to the balance of the industry. Now to date, legacy vendors and the surrounding community have been pretty defensive around the cloud. Oh, not everything's going to move to the cloud. It's not a zero sum game we hear. And while that's all true, the narrative was really kind of a defensive posture, and that's starting to change as large tech companies like Dell, IBM, Cisco, HPE, and others see opportunities to build on top of this infrastructure. You certainly see that with Arvind Krishna comments at IBM, Cisco obviously leaning in from a networking and security perspective, HPE using language that is very much cloud-like with its GreenLake strategy. And of course, Dell is all over this. Let's listen to how Michael Dell is thinking about this opportunity when he was questioned on the queue by John Furrier about the cloud. Play the clip. So in my view, Michael nailed it. The cloud is everywhere. You have to make it easy. And you have to admire the scope of his comments. We know this guy, he thinks big. He said, "Enables everything." He's basically saying is that technology is at the point where it has the potential to touch virtually every industry, every person, every problem, everything. So let's talk about how this informs the changing world of data protection. Now, we all know, we've seen with the pandemic, there's an acceleration in toward digital, and that has caused an escalation, if you will, in the data protection mandate. So essentially what we're talking about here is the application of Michael Dell's cloud everywhere comments. You've got on-prem, private clouds, hybrid clouds. You've got public clouds across AWS, Azure, Google, Alibaba. Really those are the big four hyperscalers. You got many clouds that are popping up all their place. But multi-cloud, to that Hashi Corp data point, 75, 70 6%. And then you now see the cloud expanding out to the edge, programmable infrastructure heading out to the edge. So the opportunity here to build the data protection cloud is to have the same experiences across all these estates with automation and orchestration in that cloud, that data protection cloud, if you will. So think of it as an abstraction layer that hides that underlying complexity, you log into that data protection cloud, it's the same experience. So you've got backup, you've got recovery, you can handle bare metal. You can do virtualized backups and recoveries, any cloud, any OS, out to the edge, Kubernetes and container use cases, which is an emerging data protection requirement. And you've got analytics, perhaps you've got PII, personally identifiable information protection in there. So the attributes of this data protection cloud, again, abstracts the underlying cloud primitives, takes care of that. It also explodes cloud native technologies. In other words, it takes advantage of whether it's machine learning, which all the big cloud players have expertise in, new processor models, things like graviton, and other services that are in the cloud natively. It doesn't just wrap it's on-prem stack in a container and shove it into the cloud, no. It actually re architects or architects around those cloud native services. And it's got distributed metadata to track files and volumes and any organizational data irrespective of location. And it enables sets of services to intelligently govern in a federated governance manner while ensuring data integrity. And all this is automated and an orchestrated to help with the skills gap. Now, as it relates to cyber recovery, air-gap solutions must be part of the portfolio, but managed outside of that data protection cloud that we just briefly described. The orchestration and the management must also be gaped, if you will. Otherwise, (laughs) you don't have an air gap. So all of this is really a cohort to cyber security or your cybersecurity strategy and posture, but you have to be careful here because your data protection strategy could get lost in this mess. So you want to think about the data protection cloud as again, an adjacency or maybe an overlay to your cybersecurity approach. Not a bolt on, it's got to be fundamentally architectured from the bottom up. And yes, this is going to maybe create some overheads and some integration challenges, but this is the way in which we think you should think about it. So you'll likely need a partner to do this. Again, we come back to the skill skills gap if we're seeing the rise of MSPs, managed service providers and specialist service providers. Not public cloud providers. People are concerned about lock-in, and that's really not their role. They're not high-touch services company. Probably not your technology arms dealer, (clear throat) excuse me, they're selling technology to these MSPs. So the MSPs, they have intimate relationships with their customers. They understand their business and specialize in architecting solutions to handle these difficult challenges. So let's take a look at some of the risk factors here, dig a little bit into the cyber threat that organizations face. This is a slide that, again, the Storage Alchemists, Steve Kenniston, shared with me. It's based on a study that IBM funds with the Panmore Institute, which is a firm that studies these things like cost of breaches and has for many, many, many years. The slide shows the total cost of a typical breach within each dot and on the Y axis and the frequency in percentage terms on the horizontal axis. Now, it's interesting. The top two compromise credentials and phishing, which once again proves that bad user behavior trumps good security every time. But the point here is that the adversary's attack vectors are many. And specific companies often specialize in solving these problems often with point products, which is why the slide that we showed from Optiv earlier, that messy slide, looks so cluttered. So there's a huge challenge for companies. And that's why we've seen the emergence of cyber recovery solutions from virtually all the major players. Ransomware and the solar winds hack have made trust the number one issue for CIOs and CISOs and boards of directors. Shifting CISO spending patterns are clear. They're shifting largely because they're catalyzed by the work from home. But outside of the moat to endpoint security, identity and access management, cloud security, the horizontal network security. So security priorities and spending are changing. And that's why you see the emergence of disruptors like we've covered extensively, Okta, CrowdStrike, Zscaler. And cyber resilience is top of mind, and robust solutions are required. And that's why companies are building cyber recovery solutions that are most often focused on the backup corpus because that's a target for the bad guys. So there is an opportunity, however, to expand from just the backup corpus to all data and protect this kind of 3, 2, 1, or maybe it's 3, 2, 1, 1, three copies, two backups, a backup in the cloud and one that's air gaped. So this can be extended to primary storage, copies, snaps, containers, data in motion, et cetera, to have a comprehensive data protection strategy. And customers, as I said earlier, are increasingly looking to manage service providers and specialists because of that skills gap. And that's a big reason why automation is so important in orchestration. And automation and orchestration, I'll emphasize, on the air gap solutions should be separated physically and logically. All right, now let's take a look at some of the ETR data and some of the players. This is a chart that we like to show often. It's a X-Y axis. And the Y axis is net score, which is a measure of spending momentum. And the horizontal axis is market share. Now, market share is an indicator of pervasiveness in the survey. It's not spending market share, it's not market share of the overall market, it's a term that ETR uses. It's essentially market share of the responses within the survey set. Think of it as mind share. Okay, you've got the pure plays here on this slide, in the storage category. There is no data protection or backup category. So what we've done is we've isolated the pure plays or close to pure plays in backup and data protection. Now notice that red line, that red is kind of our subjective view of anything that's over that 40% line is elevated. And you can see only Rubrik, and the July survey is over that 40% line. I'll show you the ends in a moment. Smaller ends, but still, Rubrik is the only one. Now, look at Cohesity and Rubrik in the January 2020. So last year, pre-pandemic, Cohesity and Rubrik, they've come well off their peak for net score. Look at Veeam. Veeam, having studied this data for the last say 24 hours months, Veeam has been steady Eddy. It is really always in the mid to high 30s, always shows a large shared end, so it's coming up in the survey. Customers are mentioning Veeam. And it's got a very solid net score. It's not above that 40% line, but it's hovering just below consistently. That's very impressive. Commvault has steadily been moving up. Sanjay Mirchandani has made some acquisitions. He did the Hedvig acquisition. They launched Metallic, that's driving cloud affinity within Commvault's large customer base. So it's good example of a legacy player pivoting and evolving and transforming itself. Veritas, it continues to under perform in the ETR surveys relative to the other players. Now, for context, let's add IBM and Dell to the chart. Now just note, this is IBM and Dell's full storage portfolio. The category in the taxonomy at ETR is all storage. Just previous slide, I isolated on the pure plays. But this now adds in IBM and Dell. It probably representative of where they would be. Probably Dell larger on the horizontal axis than IBM, of course. And you could see the spending momentum accordingly. So you can see that in the data chart that we've inserted. So some smaller ends for Rubrik and Cohesity. But still enough to pay attention, it's not like one or two. When you're 20-plus, 15-plus 25-plus, you can start to pay attention to trends. Veeam, again, is very impressive. It's net score is solid, it's got a consistent presence in the dataset, it's clear leader here. SimpliVity is small, but it's improving relative to last several surveys. And we talked about Convolt. Now, I want to emphasize something that we've been hitting on for quite some time now. And that's the Renaissance that's coming in compute. Now, we all know about Moore's Law, the doubling of transistor density every two years, 18 to 24 months. And that leads to a doubling of performance in that timeframe. X86, that x86 curve is in the blue. And if you do the math, this is expressed in trillions of operations per second. The orange line is representative of Apples A series, culminating in the A15, most recently. The A series is what Apple is now... Well, it's the technology basis for what's inside M1, the new Apple laptops, which is replacing Intel. That's that that orange line there, we'll come back to that. So go back to the blue line for a minute. If you do the math on doubling performance every 24 months, it comes out to roughly 40% annual improvement in processing power per year. That's now moderated. So Moore's Law is waning in one sense, so we wrote a piece Moore's Law is not dead. So I'm sort of contradicting myself there. But the traditional Moore's Law curve on x86 is waning. It's probably now down to around 30%, low 30s. But look at the orange line. Again, using the A series as an indicator, if you combine then the CPU, the NPU, which neuro processing unit, XPU, pick whatever PU you want, the accelerators, the DSPs, that line is growing at 100% plus per year. It's probably more accurately around 110% a year. So there's a new industry curve occurring, and it's being led by the Arm ecosystem. The other key factor there, and you're seeing this in a lot of use cases, a lot of consumer use cases, Apple is an example, but you're also seeing it in things like Tesla, Amazon with AWS graviton, the Annapurna acquisition, building out graviton and nitro, that's based on Arm. You can get from design to tape out in less than two years. Whereas the Intel cycles, we know, they've been running it four to five years now. Maybe Pat Gelsinger is compressing those. But Intel is behind. So organizations that are on that orange curve are going to see faster acceleration, lower cost, lower power, et cetera. All right, so what's the tie to data protection. I'm going to leave you with this chart. Arm has introduced it's confidential, compute architecture and is ushering in a new era of security and data protection. Zero trust is the new mandate. And what Arm has it's done with what they call realms is create physical separation of the vulnerable components by creating essentially physical buckets to put code in and to put data in, separate from the OS. Remember, the OS is the most valuable entry point for hackers or one of them because it contains privileged access, and it's a weak link because of things like memory leakages and vulnerabilities. And malicious code can be placed by bad guys within data in the OS and appear benign, even though it's anything but. So in this, all the OS does is create API calls to the realm controller. That's the only interaction. So it makes it much harder for bad actors to get access to the code and the data. And importantly, very importantly, it's an end-to-end architecture. So there's protection throughout. If you're pulling data from the edge and bringing it back to the on-prem or the cloud, you've got that end to end architecture and protection throughout. So the link to data protection is that backup software vendors need to be the most trusted of applications. Backup software needs to be the most trusted of applications because it's one of the most targeted areas in a cyber attack. Realms provide an end-to-end separation of data and code from the OS and it's a better architectural construct to support zero trust and confidential computing and critical use cases like data protection/backup and other digital business apps. So our call to action is backup software vendors, you can lead the charge. Arm is several years ahead at the moment, ahead of Intel, in our view. So you've got to pay attention to that, research that. We're not saying over rotate, but go investigate that. And use your relationships with Intel to accelerate its version of this architecture. Or ideally, the industry should agree on common standards and solve this problem together. Pat Gelsinger told us in theCUBE that if it's the last thing he's going to do in his industry life, he's going to solve this security problem. That's when he was at VMware. Well, Pat, you're even in a better place to do it now. You don't have to solve it yourself, you can't, and you know that. So while you're going about your business saving Intel, look to partner with Arm. I know it sounds crazy to use these published APIs and push to collaborate on an open source architecture that addresses the cyber problem. If anyone can do it, you can. Okay, that's it for today. Remember, these episodes are all available as podcasts. All you got to do is search Braking Analysis Podcast. I publish weekly on wikibond.com and siliconangle.com. Or you can reach me @dvellante on Twitter, email me at david.vellante@siliconangle.com. And don't forget to check out etr.plus for all the survey and data action. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching, everybody. Be well, and we'll see you next time. (gentle music)

Published Date : Aug 13 2021

SUMMARY :

This is braking analysis So the link to data protection

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Ankit Goel, Aravind Jagannathan, & Atif Malik


 

>>From around the globe. It's the cube covering data citizens. 21 brought to you by Colibra >>Welcome to the cubes coverage of Collibra data citizens 21. I'm Lisa Martin. I have three guests with me here today. Colibra customer Freddie Mac, please welcome JAG chief data officer and vice president of single family data and decisions. Jog. Welcome to the cube. >>Thank you, Lisa. Look forward to be, >>Uh, excellent on Kiko LSU as well. Vice president data transformation and analytics solution on Kay. Good to have you on the program. >>Thank you, Lisa. Great to be here and >>A teeth Malik senior director from the single family division at Freddie Mac is here as well. A team welcome. So we have big congratulations in order. Uh, pretty Mac was just announced at data citizens as the winners of the Colibra excellence award for data program of the year. Congratulations on that. We're going to unpack that. Talk about what that means, but I'd love to get familiar with the 3d Jack. Start with you. Talk to me a little bit about your background, your current role as chief data officer. >>Appreciate it, Lisa, thank you for the opportunity to share our story. Uh, my name is Arvind calls me Jack. And as you said, I'm just single-family chief data officer at Freddie Mac, but those that don't know, Freddie Mac is a Garland sponsored entity that supports the U S housing finance system and single family deals with the residential side of the marketplace, as CDO are responsible for our managed content data lineage, data governance, business architecture, which Cleaver plays a integral role, uh, in, in depth, that function as well as, uh, support our shared assets across the enterprise and our data monetization efforts, data, product execution, decision modeling, as well as our business intelligence capabilities, including AI and ML for various use cases as a background, starting my career in New York and then moved to Boston and last 20 years of living in the Northern Virginia DC area and fortunate to have been responsible for business operations, as well as led and, um, executed large transformation efforts. That background has reinforced the power of data and how, how it's so critical to meeting our business objectives. Look forward to our dialogue today, Lisa, once again. >>Excellent. You have a great background and clearly not a dull moment in your job with Freddy, Matt. And tell me a little bit about your background, your role, what you're doing at Freddie >>Mac. Definitely. Um, hi everyone. I'm,, I'm vice president of data transformation and analytics solutions. And I worked for JAG. I'm responsible for many of the things he said, including leading our transformation to the cloud and migrating all our existing data assets front of that transformation journey. I'm also responsible for our business information and business data architecture, decision modeling, business intelligence, and some of the analytics and artificial intelligence. I started my career back in the day as a computer engineer, but I've always been in the financial industry up in New York. And now in the Northern Virginia area, I called myself that bridge between business and technology. And I would say, I think over the last six years with data found that perfect spot where business and technology actually come together to solve real problems and, and really lead, um, you know, businesses to the next stage of, so thank you Lisa for the opportunity today. Excellent. >>And we're going to unpack you call yourself the bridge between business and it that's always such an important bridge. We're going to talk about that in just a minute, but I want to get your background, tell our audience about you. >>Uh, I'm Alec Malek, I'm senior director of business, data architecture, data transformation, and Freddie Mac. Uh, I'm responsible for the overall business data architecture and transformation of the existing data onto the cloud data lake. Uh, my team is responsible for the Kleberg platform and the business analysts that are using and maintaining the data in Libra and also driving the data architecture in close collaboration with our engineering teams. My background is I'm a engineer at heart. I still do a lot of development. This is my first time as of crossing over onto the bridge onto business side of maintaining data and working with data teams. >>Jan, let's talk about digital transformation. Freddie Mac is a 50 year old and growing company. I always love talking with established businesses about digital transformation. It's pretty challenging. Talk to me about your initial plan and what some of the main challenges were that you were looking to solve. >>Uh, great question, Lisa, and, uh, it's definitely pertinent as you say, in our digital world or figuring out how we need to accomplish it. If I look at our data, modernization is it is a major program and, uh, effort, uh, in, in our, in our division, what started as a reducing cost or looking at an infrastructure play, moving from physical data assets to the cloud, as well as enhancing our resiliency as quickly morphed into meeting business demand and objectives, whether it be for sourcing, servicing or securitization of our loan products. So where are we as we think about creating this digital data marketplace, we are, we are basically forming, empowering a new data ecosystem, which Columbia is definitely playing a major role. It's more than just a cloud native data lake, but it's bringing in some of our current assets and capabilities into this new data landscape. >>So as we think about creating an information hub, part of the challenges, as you say, 50 years of having millions of loans and millions of data across multiple assets, it's frigging out that you still have to care and feed legacy while you're building the new highway and figuring out how you best have to transform and translate and move data and assets to this new platform. What we've been striving for is looking at what is the business demand or what is the business use case, and what's the value to help prioritize that transformation. Exciting part is, as you think about new uses of acquiring and distribution of data, as well as news new use cases for prescriptive and predictive analytics, the power of what we're building in our daily, this new data ecosystem, we're feeling comfortable, we'll meet the business demand, but as any CTO will tell you demand is always, uh, outpaces our capacity. And that's why we want to be very diligent in terms of our execution plan. So we're very excited as to what we've accomplished so far this year and looking forward as we offered a remainder year. And as you go into 2022. Excellent, >>Thanks JAG. Uh, two books go to you. As I mentioned in the intro of that Freddie Mac has won the Culebra excellence award for data program of the year. Again, congratulations on that, but I'd love to understand the Kleber center of excellence that you're building at Freddie Mac. First of all, define what a center of excellence is to Freddie Mac and then what you're specifically building. Yeah, sure. >>So the Cleaver center of excellence provides us the overall framework from a people and process standpoint to focus in on our use of Colibra and for adopting best practices. Uh, we can have teams that are focused just on developing best practices and implementing workflows and lineage within Collibra and implementing and adopting a number of different aspects of Libra. It provides the central hub of people being domain experts on the tool that can then be leveraged by different groups within the organization to maintain, uh, the tool. >>Put another follow on question a T for you. How does Freddie Mac define, uh, dated citizens as anybody in finance or sales or marketing or operations? What does that definition of data citizen? >>It's really everyone it's within the organization. They all consume data in different ways and we provide a way of governing data and for them to get a better understanding of data from Collibra itself. So it's really everyone within the organization that way. >>Excellent. Okay. Let's go over to you a big topic at data citizens. 21 is collaboration. That's probably a word that we used a ton in the last 15 plus months or so it was every business really pivoted quickly to figure out how do we best collaborate. But something that you talked about in your intro is being the bridge between business and it, I want to understand from your perspective, how can data teams help to drive improved collaboration between business and it, >>The collaboration between business and technology have been a key focus area for us over the last few years, we actually started an agile transformation journey two years ago that we called modern delivery. And that was about moving away from project teams to persistent product teams that brought business and technology together. And we've really been able to pioneer that in the data space within Freddie Mac, where we have now teams with product owners coming from the data team and then full stack ID developers with them creating these combined teams to meet the business needs. We found that bringing these teams together really remove the barriers that were there in the interaction and the employee satisfaction has been high. And like you said, over the last 16 months with the pandemic, we've actually seen the productivity stay same or even go up because the teams were all working together, they work as a unit and they all have the sense of ownership versus working on a project that has a finite end date to fail. So we've, um, you know, we've been really lucky with having started this two years ago. Well, and >>That's great. And congratulations about either maintaining productivity or having it go up during the last 16 months, which had been incredibly challenging. Jack. I want to ask you what does winning this award from Collibra what does this mean to you and your team and does this signify that you're really establishing a data first culture? >>Great question, Lisa again. Um, I think winning the award, uh, just from a team standpoint, it's a great honor. Uh, Kleber has been a fantastic partner. And when I think about the journey of going from spread sheets, right, that all of us had in the past to now having all our business class returns lineage, and really being at the forefront of our data monetization. So as we think about moving to the cloud Beliebers step in step with us in terms of our integral part of that holistic delivery model, when I ultimately, as a CDO, it's really the team's honor and effort, cause this has been a multi-year journey to get here. And it's great that Libra as a, as a partner has helped us achieve some of these goals, but also recognized, um, where we are in terms of, uh, as looking at data as a product and some of our, um, leading forefront and using that holistic delivery, uh, to, uh, to meet our business objectives. So overall poorly jazzed when, uh, we've been found that we wanted the data program here at Collibra and very honored, um, uh, to, to win this award. That's >>Where we got to bring back I'm jazzed. I liked that jug sticking with you, let's unpack a little bit, some of those positive results, those business outcomes that you've seen so far from the data program. What are those? >>Yeah. So again, if you were thinking about a traditional CDO model, what were the terms that would have been used few years ago? It was around governance and may have been viewed as an oversight. Um, maybe less talking, um, monetization of what it was, the business values that you needed to accomplish collectively. It's really those three building blocks managing content. You got to trust the source, but ultimately it's empowering the business. So the best success that I could say at Freddy, as you're moving to this digital world, it's really empowering the business to figure out the new capabilities and demand and objectives that we're meeting. We're not going to be able to transform the mortgage industry. We're not going to be able or any, any industry, if we're still stuck in old world thinking, and ultimately data is going to be the blood that has to enable those capabilities. >>So if you tell me the business best success, we're no longer talking a okay, I got my data governance, what do we have to do? It's all embedded together. And as I alluded to that partnership between business and it informing that data is a product where you now you're delivering capabilities holistically from program teams all across data. It's no longer an afterthought. As I said, a few minutes ago, you're able to then meet the demand what's current. And how do we want to think about going forward? So it's no longer buzzwords of digital data marketplace. What is the value of that? And that's what the success, I think if our group collectively working across the organization, it's just not one team it's across the organization. Um, and we have our partners, our operations, everyone from business owners, all swimming in the same direction with, and I would say critical management support. So top of the house, our, our head of business, my, my boss was the COO full supportive in terms of how we're trying to execute and I've makes us, um, it's critical because when there is a potential, trade-offs, we're all looking at it collectively as an organization, >>Right. And that's the best viewpoint to have is that sort of centralized unified vision. And as you say, JAG, the support from, from up top, uh, I'd see if I want to ask you, you establish the Culebra center of excellence. What are you focused on now? >>So we really focused in allowing our users to consume data and understand data and really democratizing data so that they can really get a better understanding of that. So that's a lot of our focus and engaging with Collibra and getting them to start to define things in Colibra law form. That's a lot of focus right now. >>Excellent. Want to stay with you one more question and take that I'm gonna ask to all of you, what are you most excited about a lot of success that you've talked about transforming a legacy institution? What are you most excited about and what are the next steps for the data program? Uh, teak what's are your thoughts? >>Yeah, so really modernizing onto, uh, onto a cloud data lake and allowing all of the users and, uh, Freddie Mac to consume data with the level of governance that we need around. It is a exciting proposition for me. >>What would you say is most exciting to you? >>I'm really looking forward to the opportunities that artificial intelligence has to offer, not just in the augmented analytics space, but in the overall data management life cycle. There's still a lot of things that are manual in the data management space. And, uh, I personally believe, uh, artificial intelligence has a huge role to play there. And Jackson >>Question to you, it seems like you have a really strong collaborative team. You have a very collaborative relationship with management and with Collibra, what are you excited about? What's coming down the pipe. >>So Lisa, if I look at it, you know, we sit back here June, 2021, where were we a year ago? And you think about a lot of the capabilities and some of the advancements that we may just in a year sitting virtually using that word jazzed or induced or feeling really great about. We made a lot of accomplishments. I'm excited what we're going to be doing for the next year. So there's other use cases, and I could talk about AIML and OCHA talks about, you know, our new ecosystem. Seeing those use cases come to fruition so that we're, we are contributing to value from a business standpoint. The organization is what really keeps me up. Uh, keeps me up at night. It gets me up in the morning and I'm really feeling dues for the entire division. Excellent. >>Well, thank you. I want to thank all three of you for joining me today. Talking about the successes that Freddie Mac has had transforming in partnership with Colibra again, congratulations on the Culebra excellence award for the data program. It's been a pleasure talking to all three of you. I'm Lisa Martin. You're watching the cubes coverage of Collibra data citizens 21.

Published Date : Jun 17 2021

SUMMARY :

21 brought to you by Colibra Welcome to the cubes coverage of Collibra data citizens 21. Good to have you on the program. but I'd love to get familiar with the 3d Jack. has reinforced the power of data and how, how it's so critical to And tell me a little bit about your background, your role, what you're doing at Freddie to solve real problems and, and really lead, um, you know, businesses to the next stage of, We're going to talk about that in just a minute, but I want to get your background, tell our audience about you. Uh, I'm responsible for the overall business data architecture and transformation Talk to me about your initial plan and what some of the main challenges were that Uh, great question, Lisa, and, uh, it's definitely pertinent as you say, building the new highway and figuring out how you best have to transform and translate As I mentioned in the intro of that Freddie Mac has won So the Cleaver center of excellence provides us the overall framework from a people What does that definition of data citizen? So it's really everyone within the organization is being the bridge between business and it, I want to understand from your perspective, over the last 16 months with the pandemic, we've actually seen the productivity this award from Collibra what does this mean to you and your team and the past to now having all our business class returns lineage, I liked that jug sticking with you, let's unpack a little bit, it's really empowering the business to figure out the new capabilities and demand and objectives that we're meeting. And as I alluded to And as you say, JAG, the support from, from up top, uh, I'd see if I want to ask you, So that's a lot of our focus and engaging with Collibra and getting them to Want to stay with you one more question and take that I'm gonna ask to all of you, what are you most excited all of the users and, uh, Freddie Mac to consume data with the I'm really looking forward to the opportunities that artificial intelligence has to offer, with Collibra, what are you excited about? So Lisa, if I look at it, you know, we sit back here June, 2021, where were we a year ago? congratulations on the Culebra excellence award for the data program.

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Breaking Analysis: Debunking the Cloud Repatriation Myth


 

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante cloud repatriation is a term often used by technology companies the ones that don't operate a public cloud the marketing narrative most typically implies that customers have moved work to the public cloud and for a variety of reasons expense performance security etc are disillusioned with the cloud and as a result are repatriating workloads back to their safe comfy and cost-effective on-premises data center while we have no doubt this does sometimes happen the data suggests that this is a single digit de minimis phenomenon hello and welcome to this week's wikibon cube insights powered by etr some have written about the repatriation myth but in this breaking analysis we'll share hard data that we feel debunks the narrative and is currently being promoted by some we'll also take this opportunity to do our quarterly cloud revenue update and share with you our latest figures for the big four cloud vendors let's start by acknowledging that the definition of cloud is absolutely evolving and in this sense much of the vendor marketing is valid no longer is cloud just a distant set of remote services that lives up there in the cloud the cloud is increasingly becoming a ubiquitous sensing thinking acting set of resources that touches nearly every aspect of our lives the cloud is coming on prem and work is being done to connect clouds to each other and the cloud is extending to the near and far edge there's little question about that today's cloud is not just compute storage connectivity and spare capacity but increasingly it's a variety of services to analyze data and predict slash anticipate changes monitor and interpret streams of information apply machine intelligence to data to optimize business outcomes it's tooling to share data protect data visualize data and bring data to life supporting a whole new set of innovative applications notice there's a theme there data increasingly the cloud is where the high value data lives from a variety of sources and it's where organizations go to mine it because the cloud vendors have the best platforms for data and this is part of why the repatriation narrative is somewhat dubious actually a lot dubious because the volume of data in the cloud is growing at rates much faster than data on prem at least by a couple thousand basis points by our estimates annually so cloud data is where the action is and we'll talk about the edge in a moment but a new era of application development is emerging with containers at the center the concept of write wants run anywhere allows developers to take advantage of systems that run on-prem say a transaction system and tap data from multiple sources in various locations there might be multiple clouds or at the edge or wherever and combine that with immense cheap processing power that we've discussed extensively in previous breaking analysis episodes and you see this new breed of apps emerging that's powered by ai those are hitting the market so this is not a zero-sum game the cloud vendors have given the world an infrastructure gift by spending like crazy on capex more than a hundred billion last year on capex for example for the big four and in our view the players that don't own a cloud should stop being so defensive about it they should thank the hyperscalers and lay out a vision as to how they'll create a new abstraction layer on top of the public cloud and you know that's what they're doing and they'll certainly claim to be actively working on this vision but consider the pace of play between the hyperscalers and their traditional on-prem providers we believe the innovation gap is actually widening meaning the public cloud players are accelerating their innovation lead and will 100 compete for hybrid applications they have the resources the developer affinity they're doing custom silicon and have the expertise there and the tam expansion goals that loom large so while it's not a zero-sum game and hybrid is definitely real we think the cloud vendors continue to gain share most rapidly unless the hybrid crowd can move faster now of course there's the edge and that is a wild card but it seems that again the cloud players are very well positioned to innovate with custom silicon programmable infrastructure capex build-outs at the edge and new thinking around system architectures but let's get back to the core story here and take a look at cloud adoptions you hear many marketing messages that call into question the public cloud at its recent think conference ibm ceo arvind krishna said that only about 25 of workloads had moved into the public cloud and he made the statement that you know this might surprise you implying you might think it should be much higher than that well we're not surprised by that figure especially especially if you narrow it to mission critical work which ibm does in its annual report actually we think that's probably high for mission critical work moving to the cloud we think it's a lot lower than that but regardless we think there are other ways to measure cloud adoption and this chart here from david michelle's book c seeing digital shows the adoption rates for major technological innovations over the past century and the number of years how many years it took to get to 50 percent household adoption electricity took a long time as did telephones had that infrastructure that last mile build out radios and tvs were much faster given the lower infrastructure requirements pcs actually took a long time and the web around nine years from when the mosaic browser was introduced we took a stab at estimating the pace of adoption of public cloud and and within a decade it reached 50 percent adoption in top enterprises and today that figures easily north of 90 so as we said at the top cloud adoption is actually quite strong and that adoption is driving massive growth for the public cloud now we've updated our quarterly cloud figures and want to share them with you here are our latest estimates for the big four cloud players with only alibaba left to report now remember only aws and alibaba report clean or relatively clean i ass figures so we use survey data and financial analysis to estimate the actual numbers for microsoft in google it's a subset of what they report in q121 we estimate that the big 4is and pas revenue approached 27 billion that's q121 that figure represents about 40 growth relative to q1 2020. so our trailing 12-month calculation puts us at 94 billion so we're now on roughly 108 billion dollar run rate as you may recall we've predicted that figure will surpass 115 billion by year end when it's all said and done aws it remains the leader amongst the big four with just over half of the market that's down from around 63 percent for the full year of 2018. unquestionably as we've reported microsoft they're everywhere they're ubiquitous in the market and they continue to perform very well but anecdotally customers and partners in our community continue to report to us that the quality of the aws cloud is noticeably better in terms of reliability and overall security etc but it doesn't seem to change the trajectory of the share movements as microsoft's software dominance makes doing business with azure really easy now as of this recording alibaba has yet to report but we'll update these figures once their earnings are released let's dig into the growth rates associated with these revenue figures and make some specific comments there this chart here shows the growth trajectory for each of the big four google trails the pack in revenue but it's growing faster than the others from of course a smaller base google is being very aggressive on pricing and customer acquisition to that we say good google needs to grow faster in our view and they most certainly can afford to be aggressive as we said combined the big four are growing revenue at 40 on a trailing 12-month basis and that compares with low single-digit growth for on-prem infrastructure and we just don't see this picture changing in the near to midterm like storage growth revenue from the big public cloud players is expected to outpace spending on traditional on on-prem platforms by at least 2 000 basis points for the foreseeable future now interestingly while aws is growing more slowly than the others from a much larger 54 billion run rate we actually saw sequential quarterly growth from aws and q1 which breaks a two-year trend from where aws's q1 growth rate dropped sequentially from q4 interesting now of course at aws we're watching the changing of the guards andy jassy becoming ceo of amazon adam silipsky boomeranging back to aws from a very successful stint at tableau and max peterson taking over for for aws public sector replacing teresa carlson who is now president and heading up go to market at splunk so lots of changes and we think this is actually a real positive for aws as it promotes from within we like that it taps previous amazon dna from tableau salesforce and it promotes the head of aws to run all of amazon a signal to us that amazon will dig its heels in and further resist calls to split aws from the mothership so let's dig in a little bit more to this repatriation mythbuster theme the revenue numbers don't tell the entire story so it's worth drilling down a bit more let's look at the demand side of the equation and pull in some etr survey data now to set this up we want to explain the fundamental method used by etr around its net score metric net score measures spending momentum and measures five factors as shown in this wheel chart that shows the breakdown of spending for the aws cloud it shows the percentage of customers within the platform that are either one adopting the platform new that's the lime green in this wheel chart two increasing spending by more than five percent that's the forest green three flat spending between plus or minus five percent that's the gray and four decreasing spend by six percent or more that's the pink and finally five replacing the platform that's the bright red now dare i say that the bright red is a proxy for or at least an indicator of repatriation sure why not let's say that now net score is derived by subtracting the reds from the greens anything above 40 percent we consider to be elevated aws is at 57 so very high not much sign of leaving the cloud nest there but we know it's nuanced and you can make an argument for corner cases of repatriation but come on the numbers just don't bear out that narrative let's compare aws with some of the other vendors to test this theory theory a bit more this chart lines up net score granularity for aws microsoft and google it compares that to ibm and oracle now other than aws and google these figures include the entire portfolio for each company but humor me and let's make an assumption that cloud defections are lower than the overall portfolio average because cloud has more momentum it's getting more spend spending so just stare at the red bars for a moment the three cloud players show one two and three percent replacement rates respectively but ibm and oracle while still in the single digits which is good show noticeably higher replacement rates and meaningfully lower new adoptions in the lime green as well the spend more category in the forest green is much higher within the cloud companies and the spend less in the pink is notably lower and you can see the sample sizes on the right-hand side of the chart we're talking about many hundreds over 1300 in the case of microsoft and if we look if we put hpe or dell in the charts it would say several hundred responses many hundreds it would look similar to ibm and oracle where you have higher reds a bigger fat middle of gray and lower greens it's just the way it is it shouldn't surprise anyone and it's you know these are respectable but it's just what happens with mature companies so if customers are repatriating there's little evidence here we believe what's really happening is that vendor marketing people are talking to customers who are purposefully spinning up test and dev work in the cloud with the intent of running a workload or portions of that workload on prem and when they move into production they're counting that as repatriation and they're taking liberties with the data to flood the market okay well that's fair game and all's fair in tech marketing but that's not repatriation that's experimentation or sandboxing or testing and deving it's not i'm leaving the cloud because it's too expensive or less secure or doesn't perform for me we're not saying that those things don't happen but it's certainly not visible in the numbers as a meaningful trend that should factor into buying decisions now we perfectly recognize that organizations can't just refactor their entire applications application portfolios into the cloud and migrate and we also recognize that lift and shift without a change in operating model is not the best strategy in real migrations they take a long time six months to two years i used to have these conversations all the time with my colleague stu miniman and i spoke to him recently about these trends and i wanted to see if six months at red hat and ibm had changed his thinking on all this and the answer was a clear no but he did throw a little red hat kool-aid at me saying saying that the way they think about the cloud blueprint is from a developer perspective start by containerizing apps and then the devs don't need to think about where the apps live whether they're in the cloud whether they're on prem where they're at the edge and red hat the story is brings a consistency of operations for developers and operators and admins and the security team etc or any plat on any platform but i don't have to lock in to a platform and bring that everywhere with me i can work with anyone's platform so that's a very strong story there and it's how arvin krishna plans to win what he calls the architectural battle for hybrid cloud okay so let's take a take a look at how the big cloud vendors stack up with the not so big cloud platforms and all those in between this chart shows one of our favorite views plotting net score or spending velocity on the vertical axis and market share or pervasiveness in the data set on the horizontal axis the red shaded area is what we call the hybrid zone and the dotted red lines that's where the elite live anything above 40 percent net score on the on on the vertical axis we consider elevated anything to the right of 20 on the horizontal axis implies a strong market presence and by those kpis it's really a two horse race between aws and microsoft now as we suggested google still has a lot of work to do and if they're out buying market share that's a start now you see alibaba shown in the upper left hand corner high spending momentum but from a small sample size as etr's china respondent level is obviously much lower than it is in the u.s and europe and the rest of apac now that shaded res red zone is interesting and gives credence to the other big non-cloud owning vendor narrative that is out there that is the world is hybrid and it's true over the past several quarters we've seen this hybrid zone performing well prominent examples include vmware cloud on aws vmware cloud which would include vcf vmware cloud foundation dell's cloud which is heavily based on vmware and red hat open shift which perhaps is the most interesting given its ubiquity as we were talking about before and you can see it's very highly elevated on the net score axis right there with all the public cloud guys red hat is essentially the switzerland of cloud which in our view puts it in a very strong position and then there's a pack of companies hovering around the 20 vertical axis level that are hybrid that by the way you see openstack there that's from a large telco presence in the data set but any rate you see hpe oracle and ibm ibm's position in the cloud just tells you how important red hat is to ibm and without that acquisition you know ibm would be far less interesting in this picture oracle is oracle and actually has one of the strongest hybrid stories in the industry within its own little or not so little world of the red stack hpe is also interesting and we'll see how the big green lake ii as a service pricing push will impact its momentum in the cloud category remember the definition of cloud here is whatever the customer says it is so if a cio says we're buying cloud from hpe or ibm or cisco or dell or whomever we take her or his word for it and that's how it works cloud is in the eye of the buyer so you have the cloud expanding into the domain of on-premises and the on-prem guys finally getting their proverbial acts together with hybrid that they've been talking about since 2009 but it looks like it's finally becoming real and look it's true you're not going to migrate everything into the cloud but the cloud folks are in a very strong position they are on the growth flywheel as we've shown they each have adjacent businesses that are data based disruptive and dominant whether it's in retail or search or a huge software estate they are winning the data wars as well that seems to be pretty clear to us and they have a leg up in ai and i want to look at that can we all agree that ai is important i think we can machine intelligence is being infused into every application and today much of the ai work is being done in the cloud as modeling but in the future we see ai moving to the edge in real time and real-time inferencing is a dominant workload but today again 90 of it is building models and analyzing data a lot of that work happens in the cloud so who has the momentum in ai let's take a look here's that same xy graph with the net score against market share and look who has the dominant mind share and position and spending momentum microsoft aws and google you can see in the table insert in the lower right hand side they're the only three in the data set of 1 500 responses that have more than 100 n aws and microsoft have around 200 or even more in the case of microsoft and their net scores are all elevated above the 60 percent level remember that 40 percent that red line indicates the elevation mark the high elevation mark so the hyperscalers have both the market presence and the spend momentum so we think the rich get richer now they're not alone there are several companies above the 40 line databricks is bringing ai and data science to the world of data lakes with its managed services and it's executing very well salesforce is infusing infusing ai into its platform via einstein you got sap on there anaconda is kind of the gold standard that platform for data science and you can see c3 dot ai is tom siebel's company going after enterprise ai and data robot which like c3 ai is a small sample in the data set but they're highly elevated and they're simplifying machine learning now there's ibm watson it's actually doing okay i mean sure we'd like to see it higher given that ginny rometty essentially bet ibm's future on watson but it has a decent presence in the market and a respectable net score and ibm owns a cloud so okay at least it's a player not the dominance that many had hoped for when watson beat ken jennings in jeopardy back 10 years ago but it's okay and then is oracle they're now getting into the act like it always does they want they watched they waited they invested they spent money on r d and then boom they dove into the market and made a lot of noise and acted like they invented the concept oracle is infusing ai into its database with autonomous database and autonomous data warehouse and look that's what oracle does it takes best of breed industry concepts and technologies to make its products better you got to give oracle credit it invests in real tech and it runs the most mission critical apps in the world you can hate them if you want but they smoke everybody in that game all right let's take a look at another view of the cloud players and see how they stack up and where the big spenders live in the all-important fortune 500 this chart shows net score over time within the fortune 500 aws is particularly interesting because its net score overall is in the high 50s but in this large big spender category aws net score jumps noticeably to nearly 70 percent so there's a strong indication that aws the largest player also has momentum not just with small companies and startups but where it really counts from a revenue perspective in the largest companies so we think that's a very positive sign for aws all right let's wrap the realities of cloud repatriation are clear corner cases exist but it's not a trend to take to the bank although many public cloud users may think about repatriation most will not act on it those that do are the exception not the rule and the etr data shows that test and dev in the clouds is part of the cloud operating model even if the app will ultimately live on prem that's not repatriation that's just smart development practice and not every workload is will or should live in the cloud hybrid is real we agree and the big cloud players know it and they're positioning to bring their stacks on prem and to the edge and despite the risk of a lock-in and higher potential monthly bills and concerns over control the hyperscalers are well com positioned to compete in hybrid to win hybrid the legacy vendors must embrace the cloud and build on top of those giants and add value where the clouds aren't going to or can't or won't they got to find places where they can move faster than the hyperscalers and so far they haven't shown a clear propensity to do that hey that's how we see it what do you think okay well remember these episodes are all available as podcasts wherever you listen you do a search breaking analysis podcast and please subscribe to the series check out etr's website at dot plus we also publish a full report every week on wikibon.com and siliconangle.com a lot of ways to get in touch you can email me at david.velante at siliconangle.com or dm me at dvalante on twitter comment on our linkedin post i always appreciate that this is dave vellante for the cube insights powered by etr have a great week everybody stay safe be well and we'll see you next time you

Published Date : May 15 2021

SUMMARY :

and the spend momentum so we think the

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Christian Craft, Oracle | CUBE Conversation


 

(upbeat music) >> Hello everyone, and welcome to this Cube conversation. We're going to dig into some of the more specific and sometimes gory details of managing the nuances of database, database management systems. You know, it's a lot of fun to get it to the daily buzz of cloud and database competition and get a little snarky on Twitter, but there are a lot of mundane issues that you have to address to really do proper database sizing, capacity planning, and you know whether or not database consolidation makes sense. These are not trivial issues. And decades ago they spawned an entire role around the database administrator. They had to do the dirty work of database management so that users and customers would be satisfied. And while automation and cloud are changing that role, at the end of the day, somebody actually has to make the databases work in the cloud and make sure that the business doesn't feel any impact on the transition along the way. So on that note, we have with us Oracle senior director of product management for mission critical databases. He works in Juan Loaiza's group, Chris Craft, and Steve Zivanic whom we know well on the cube says this guy is the Jedi master when it comes to consolidating databases in the cloud. Nobody knows more on the face of the planet Earth. So we're really excited Chris, to have you inside the Cube. Welcome. >> Thanks, thanks Dave. >> That's a very humble thanks. So when it comes to running databases in the cloud can you explain the difference between sizing and capacity planning? Aren't they two sides of the same coin? >> Yeah, you know, they really are. It's like, you know sizing is really part of capacity to planning. It's really, I look at sizing as a one-time effort whereas capacity planning is more your ongoing. You perform sizing initially when the application is deployed. And then, then when you're changing platforms, like going from on-prem to the Cloud you're going to go through a sizing exercise 'cause you're looking at going to a new platform. That's more of a one-time effort, and then ongoing, you're looking at your capacity management over time. So yeah, they are very related so. >> Okay, thank you. So we're going to talk about database consolidation. A lot of people would say, look the cloud makes consolidating databases maybe not irrelevant, but maybe not the best strategy because I got all these different purpose-built databases. Why consolidate databases if they're already going to consolidate it in the cloud in one location? >> Yeah. So, so we're really talking about in in the cloud, you're running virtual machines but consolidation still applies on the virtual machines. So if you have a virtual machine that's dedicated to a database that database is that server, that virtual machine is going to be under utilized over time. So what we're doing with consolidation is running multiple databases within a virtual machine or what it, Oracle virtual cluster. We do everything on clusters. So multiple machines multiple databases within that will drive up the utilization and improve your cost structure. So it's a sizing it's it's absolutely critical on even in the cloud. >> Okay. But, but wouldn't it, I might say to that, wouldn't it be better to have each database have a dedicated VM? I mean, from a performance perspective, it doesn't try to make the database do too much affect performance. >> Yeah. It, so whenever, so we know historically that a database on a dedicated server back in the day that was a physical server, today it's a virtual machine. When you do that, your utilization will be in the range of 15 to 20%. And that's, you know very highly under utilized systems when you do that. So we don't need to isolate things onto dedicated virtual machines for a performance perspective. There are other ways that we can manage that we have resource management built into Oracle and the Oracle database. And then on Exadata we have an integrated IO resource management as well so we can deal with that different ways. >> Okay. So you're basically proposing that you're putting these databases onto a single VM and managing it accordingly. Is there additional details you can provide on that? >> So, you know, we don't put everything into you know, literally one, one VM. You want to have some isolation built in there, but see and take a more pragmatic approach. You know, like every single database in one VM that's the wrong way to go. Each database in a dedicated VM is also the other extreme, also the wrong way to go. So we're kind of right down the middle and be more pragmatic about it, and do some level of consolidation to drive up utilization. >> I remember when I first started following tech I was studying up on, you know kind of how disc drives work and so forth. And there was probably like I can't even remember what it was. It was like probably like 10 megabytes under an actuator. And people were saying, Oh my God, that's so much data. You, you got your blast radius is, is so big. You got to split that up. So it's the same concept, apply with availability. Some would say, there's a problem because you're consolidating all this data and you've got this blast radius that increases. How do you address that? >> And so, you know, redundancy. So we have redundancy at all levels. So if you look at a single, so we're talking about Exadata here, taught in an Exadata machine we can lose up to 24 disc drives out of 30. 30 machines with 36 disc drives, we can use 24 of those. So that'd be 12 per storage cell. You can lose two storage cells as 24 out of 36 drives so we can lose and keep on running. We can also, we also cluster, we also do clustering. So the database servers are clustered together for high availability. So we can take, we can suffer multiple simultaneous failures and keep on running without performance impact either. So it's, so recovery, we handle that in different ways. So it's, look at blast radius from a standpoint, you want some, some isolation for blast radius but we have physical failures is just not something that we're concerned with. >> Why do you deal with taking down a VM? Doesn't that normally mean there's going to be some kind of disruption? >> Oh, so you know, the, so Oracle database, you're talking about real application clusters on on Oracle database, on Exadata. We've got, we have a very fast detection of of failures and then resolution of the failure. So we're looking at a small blip in performance, you know we're looking at a few milliseconds to detect failure and then maybe up around three seconds to actually affect the failover. So the applications that are not getting disconnected, they continue operating in the, in that kind of condition. So that's kind of unique to the Exadata platform. And so, you know, in our cloud, we're running Exadata. We have this built in there. So we're, we're resilient to that type of failure, so. >> And sorry, you mentioned real application clusters. You're saying because you're running real application clusters that's how you're able to become more resilient? >> So yeah, so we have, so Oracle database real application clusters runs on top of a clustered virtual machines on Exadata. We have integration then optimizes the fail over times of that clustering. So it's, it's not the cluster same, it's the optimizations are only built into Exadata. So we have much much faster, much better tighter integration, so much more scalability because of that, that integration that we have. >> Can I run rack in other clouds? Can I put that into Amazon's cloud? >> So, so real application clusters requires two things. It's a, you require shared storage in a fast interconnect, a fast networking interconnecting. And those things just don't exist in the other clouds. We have those built into Exadata in our cloud. And we also, we also allow real application clusters in our relational database, our database cloud service offering as well. But it's, really the highest implementation of that is in Exadata. >> Well, of course I was tongue in cheek joking but this is, this is why, you know, I was listening to Arvind Krishna the other day in IBM Think. And he was saying only 25% of mission critical applications have moved into the cloud. I didn't think it's that high. I mean, but, but what you're doing is basically building a mission critical, you know, cloud or a cloud for mission critical databases. And that's, that's unique. I mean, I would expect other cloud vendors that eventually you know, are going to get there, but you're kind of starting with the hard stuff and working backwards. But, that is what I've always interpreted is unique to Oracle, but how does that affect cost? Isn't that more expensive? >> Actually, no. We're taking services that that start out at a very similar price point. And then we drive. So what we've seen from other customers that are running in like Amazon, for example, we see databases on dedicated virtual machines that run anywhere from 15 to 20% utilization. So what we do is, that low, low utilization, what we do is take that and triple that. So we run, so we run maybe 50% utilization. At that point we still have full redundancy, but we've now made the service one third of the cost. So we're starting at a third, we're starting at a very similar cost. And then we drive it to, you know three times a utilization. This is not crazy numbers. This is, you know, 50% is, is fine and retain the redundancy at that level as well. >> Got it, well so. >> What we've seen is about a third the cost. >> Really? Okay. Well, so, but, what about, like for instance, on AWS, couldn't I run this in a multi availability zone, running RDS or some other cloud database? >> So, so you can run a Multi-AZ environment like in in Amazon, for example, you can run locals. That's what we call local standby. If you do that, you're now instead of being one third, instead of being three times more expensive, you're now six times more expensive. Because that is another copy of the entire platform, the entire instance, the storage, everything on the other availability zone instead of being three times more, it's now six. >> Because you're essentially replicating everything in a brute force mode, right? >> Yeah. It's a data guard standby, local standby in another AZ, or what we call availability domain in our cloud. >> So let's maybe geek out a little bit. So, let's talk more about availability. You know, for years, I mean, I remember going back to reading about this stuff with tandem computers, you know, coincident failures. How are you dealing with those in today's modern world? >> So what we call simultaneous failures is, so we, we deal with that with redundancy in the system. So we have redundancy at all layers in the storage. Like I said earlier, we can take across, you know, two storage cells and each storage cell has a dozen drives. So that's 24 disc drives. That's eight flashcard failures simultaneously. And we keep on running no data loss, no loss of service. That's at the storage layer. We have multiple, multiple redundant networking switches at that, at the networking layer, the internal network. Then we go up into the database server. We then have redundancy across the nodes of a cluster. You have multiple virtual machines that comprise a virtual cluster. So it's at each and every level, we have redundancy. And then we drive the redundancy into the application using what's called application continuity. So the application connections have knowledge of the failure, failure modes of the database. They can follow to the surviving node, and continue operating. >> And you do this with math, you're doing some kind of magic bit slicing, or how do you do that? >> That, so that is that particular thing, application continuity, so technology that's been built into Oracle database since, since 12c, and that it's been around for quite a long time. And it allows the application to follow the rack cluster, any kind of issues with the rack cluster. We can drain connections off. It's very well-proven technology in, you know, prior to to proactive maintenance, we can drain connections over and then it will also handle a failure of a connection as well. And the application following that, yes. >> I learned from my old mainframe days and hanging around with David Floyer. It's always ask, what happens when something goes wrong and it's all about recovery. And you guys have the gold standard there. I mean, we've talked about this a lot. So you got Exadata. That's what is behind your Exadata cloud service, X8M I think you call it, and you've got autonomous database. I'm not great with model numbers, but, but talk about the way you can handle simultaneous failures. I mean, are there like triple redundancies that you've built in? >> Yeah. So everything what we do in our cloud is everything is triple redundancy by default. So we, you can suffer, that way we can suffer two failures and continue operating. So the, the other thing, so recovery, if you look at transaction recovery, when a failure occurs a transaction will flip that session, will flip to the machine that keeps running. It'll reposition all in the work that's in flight, any kind of inflight transactions, any in flight queries that are going on, reposition and continue operating. >> So you've essentially created like the old three site data centers, but you're in a single platform because you're synchronous. But, that same concept in a package. >> It's, you know, it's a lot of times you show a picture of an Exadata. It looks like a single box, but in the box there's some redundancy built in the box. And in fact, in the cloud it's actually across an entire aisle. So it's, we kind of obscure that a little bit, from your provisioning, you know, our database nodes and our storage cells and in the cloud but it's actually across an entire aisle of a dataset. >> Okay, and of course, that's within a synchronous location. Let's talk about disaster recovery, and what you're doing in that area, around Oracle Cloud What are my options there? What's different from other cloud providers we were talking earlier about, AZs, how are you different and what are you doing there? >> Yeah, so we, we talked earlier about the Multi-AZ deployment, what we call it availability domain, AD, so a little different terminology. But we can deploy another, another copy of the database into another availability domain, if you like. It's not often that you lose an entire AZ or AD, it's more, we're protecting from regional failures. So across another region. And that's where we look at, we really look at that as that technology, as a standby, as a data, disaster recovery solution not for HA. HA, we build HA into the machine itself. >> So you're saying, we were talking earlier about AZ, you're saying that's for HA versus DR. Is that, is that what you're contending? >> Yeah, like, you know again, pick on Amazon for a second here. Amazon uses a standby database. What we would normally use for disaster recovery, they're using that for availability. And you're looking at a few minutes of time to flip over to another AZ, whereas within an Exadata frame, we can flip over in milliseconds. We keep continue running. There is no loss of conductivity. And then we use the standby in another region for disaster. That's a true disaster solution. >> As opposed to incurring that penalty of latency, or whatever, to spin up the other resource. >> Right, right. >> Okay, so that's clear how kind of you guys address that, that challenge. Last question, maybe you could give us your take, again folks, coming out of Oracle's mouth, but what's the bottom line cost Delta based on your experience between your service and competitive services? I love these conversations because you're not afraid to talk about the competition, so bring it on. >> I've seen, so we've just based on what we've seen with customers deploying databases in Amazon, versus what, you know we've replaced that within, in our cloud service. We're seeing from just a list price perspective. Now, you know, we discount, I know Amazon discounts, but the only thing I can really speak to is list price perspective. It's about a third the cost. So we're talking about a more powerful platform, runs faster. We get these incredible, we haven't even talked about performance here. Talk about availability, performance where we're getting IO rates, IO latencies in the 19 microsecond range. Now with Exadata, that's going to be 50 times faster than what you get with these traditional cloud vendors. So much, much faster, and a third the cost. >> So talk about discounts, I mean, I know Oracle discounts, Oracle from list price, Oracle provides significant discounts. I'm not as familiar with your cloud pricing but I mean, Amazon's discounts are really in the form of like reserved instances. Is your pricing similar in that regard or different? I mean, if I'm just paying on demand, I'm paying through the nose. I presume it's same with you. If I, but if I buy in bulk getting a discount, is that what you mean by discount? Or is it more similar to the way you've traditionally discounted, you know large customers, the more you spend, the more you you get kind of thing. >> It's a, there's a discount structure. So it's, we don't have the same kind of lock-in like with reserved instance structure, but yeah, it's, there are discounts and that's going to be very customer specific. >> Right. >> So, but I think that the end result we're starting at, a three X differential on the price. >> But the reason I'm asking the question is that the stats you gave me are for list price, right? >> Yeah, yes, yeah. >> Okay, and sure, you're saying that at list price you're, you're less expensive. I, and again, my contention would be just by experiences that your discounts would be more aggressive traditionally in Oracle's traditional business. You know, I've done a lot of Oracle negotiation in my days. And if you're, you know, if you're a big customer you can get good deals. And again, I'm not as familiar with the cloud pricing, but still that's, that's good. If you're doing it on a list price basis, to me, that's a conservative statement if that makes any sense. >> Right, that's where it starts. We know that's where it's starting out. So I, you know, once you get into discounts, it's very customer specific. >> Right. >> We know the starting point is at three X differential. Before you do something in the Multi-AZ would be a six X differential, by the way, so. >> Yeah, okay. All right, Chris. Well, Hey, I appreciate you taking us through this, good stuff, and best of luck, good work. You know, you guys keep, I always say Oracle invest you guys spend a lot of money in RD and, and, you know you're quiet for a while in the cloud and all of a sudden you came out like you invented it. So good job! >> All right. >> All right, thanks. Thanks for coming on. All right. >> Thanks. >> Thank you for watching everybody. This is Dave Vellante for Cube conversations. We'll see you next time. (upbeat music)

Published Date : May 14 2021

SUMMARY :

So on that note, we have with databases in the cloud Yeah, you know, they really are. maybe not the best strategy So if you have a virtual I might say to that, in the range of 15 to 20%. you can provide on that? So, you know, we So it's the same concept, So if you look at a So the applications that are And sorry, you mentioned So it's, it's not the cluster exist in the other clouds. building a mission critical, you know, And then we drive it to, you know about a third the cost. Well, so, but, what If you do that, you're now or what we call availability you know, coincident failures. So the application And it allows the application about the way you can handle So we, you can suffer, like the old three site data And in fact, in the cloud what are you doing there? It's not often that you So you're saying, we were Yeah, like, you know again, that penalty of latency, kind of you guys address that, but the only thing I can really speak to is that what you mean by discount? So it's, we don't have the So, but I think that the you can get good deals. So I, you know, once We know the starting point and all of a sudden you came Thanks for coming on. Thank you for watching everybody.

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Kirsten Craft, Prolifics | IBM Think 2021


 

>> Narrator: From around the globe, it's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> Hello, everyone. Welcome back to theCUBE's coverage of IBM Think virtual 2021. I'm John Furrier, your host of theCUBE. We're here with Kirsten Craft, who's the global head of business development and marketing at Prolifics. Kirsten, great to see you. Thanks for coming on theCUBE. >> Thanks so much, John. It's great to be here. >> I love the fact that we're getting the content out there. We're still remote. Soon in real life's coming back, but what a time it's been in the past year and a half or so. A lot of change, a lot of action. You guys are in the middle of it here at IBM Think. Let's get into it. But first, take a minute to explain what you guys do at Prolifics, and your business model. >> Sure. So thanks, John. So Prolifics... We've been in business, actually, for over 40 years, which is pretty amazing when you think about technology and everything that's happened in 40 years. We are a global service provider. We've got over 1,000 people worldwide. And we are 100% focused on software, and almost 100% focused on IBM, right? Of course, nobody's focused on a single technology stack these days, so we work with our customers across many different products, but we've been with IBM for a very long time. When we look at our business model, when we talk with our clients, we find that organizations today, they've got really complex challenges, especially now, right, in what all is happening right now. They've got a lot of really interesting opportunities, as well as problems that they have to solve in front of them. And those types of situations, they can't just be addressed by just buying a product. And Prolifics' approach is we work with our clients to get really above the technology conversation, and to really understand what are they trying to accomplish, right? At the end of the day, why is this an important initiative for you? And we help them develop roadmaps, and then we help them get there. So of course we're selling technology along the way, and in that implementation path. So I would say from a business model perspective, we're very services focused. We're very consultative. And of course our resulting technologies are running on IBM. >> About eight years ago, Dave Vellante and I started a little small little section of SiliconANGLE called ServicesANGLE, and our premise was is that services were going to be a big driver. Now, what we missed was cloud had to set up first, and it did, and now we're seeing a boom in services, but cloud services, you're seeing new kinds of services with the edge and other things. So what's your take on this? Because now IBM has this global view. The pandemic has proven that the scale of virtual and digital is so much more compelling. No one's going back. The economics are too good. The value is being realized as clear visibility and to unit economics of projects. Projects, some are obvious double down on. Some not to, maybe. So a lot of these things are going on. What's your take on all this? >> So it is interesting, cause that is both an opportunity as well as a challenge, right, for clients. At Prolifics, we've been-- We were actually pretty blessed because we're very virtual. We're a virtual company anyway, right? So we didn't have one facility where all of our developers are housed. So it was really kind of business as usual for us in terms of how we work with our customers, with the exception of the fact we couldn't go into their offices, right, anymore, which is a bit of a challenge. But as they look at how do they really harness the cloud, how do they harness those technologies? IBM, as well as business partners like Prolifics, we're in a great position to help them with that, because a lot of where IBM is going with cloud packs and containerization, that's where our customers want to be. Now, some of them are a little bit more aggressive than others in terms of how quickly they want to adopt that technology, which is where road mapping comes into place, and helping them really set up, not just for short-term, how do they solve what's in front of their face, but let's look a year or two years down the line. How do you make sure that you're really building an agile type of environment that's going to work across data, which is really the center of all things nowadays, as well as working across other systems. >> I've been covering IBM for very long time. Actually was once an employee as a co-op student back in college. Remember those glory days. (chuckles) And you mentioned you guys have been with IBM for a very, very long time. You got to.... They've always had a business focus. They've always had great technology. They got great technologists and experts there, but I think now more than ever you're seeing the theme at the show this year as hybrid cloud edge data AI as a kind of a underlying system software for business. So you're starting to see a new era of software driving business at a level that's been completely transformed. As an IBM platform software provider, you've been there for all the IBM over the years. What's it like? What's your... What's your take on this? What opportunities do you see with the hybrid cloud? You got Red Hat now under the covers. You've got, you mentioned, containers. Is it a pinch-me moment where people were like, "Wow. There's so much here to integrate," or cloud is going to provide a new clean sheet of paper to do things. What's your... What's the vibe? What's the sentiment? >> It's interesting. We're actually seeing more customers starting to look at themselves as technology companies. So even companies that don't think that historically they're not in a technology industry, they're now identifying internally. They're talking to their staff about... We don't sell widgets. We're a technology company that happens to sell widgets. So it's really an interesting dynamic, and I would also mention that one of the themes we're seeing across a lot of customers, almost all of our customers, is this insane focus on data. I say insane in like a good way, right? So how do we use our data to help inform our processes? How do we make sure that we're sharing data effectively and efficiently with all of our trading partners? We're seeing a lot of modernization when it comes to integration, but again, integration is all about exchanging data. We're seeing customers start to dabble more with AI in terms of how can we get smarter by using the data that we have available to us? Again, I think that's going to be the next wave, because we're seeing a lot of our customers start to dabble in that but not fully embrace it just yet. But they really want to get that underlying platform around data and integration ready to go so that they can do some amazing things in the future. >> How is the hybrid cloud and data impacting Prolifics business? Where does this take you guys for the next chapter? >> Well, it's actually... (chuckles) It's actually perfect for us, because that's almost 100% of what we do. So we... As I mentioned earlier, we are 100% focused on software, right? Software and software-based solutions. We're not a hardware provider. We don't have a data center, but we help customers design and implement software-based systems. And our expertise is squarely in data, business intelligence, analytics, AI, and also integration and business process automation. Those are really our core, especially as it comes to IBM technology. Now, we also have a testing practice, which is technology agnostic, but it's really critical as you... Especially as you look at rapid development cycles, cause that's another theme we're seeing with customers, right? Nobody's got the patience to go through a long waterfall model, right? You've got to get into production. It's the Apple model, right? Get it into production, get feedback, make modifications, and go. But if it gets out there and it's completely broken. Guess what? You just stepped all over yourself. So we integrate testing into everything that we do as well. But the data and the hybrid cloud message, and all of the innovation that IBM is doing, it fits perfectly in with what we're seeing with our customers and where we've invested for so long as far as skills and expertise. >> That testing example really kind of speaks to what's state-of-the-art right now, because people can get into production with the cloud and then they realize that they're adding services pretty quickly and things break. They call it "day-two operations," is a term that there've been kicking around. I call it essentially DevSecOps, but there's a lot of kind of new things that you just got to kind of watch, which recently, IT-like functions that are now cloud ops, cloud operations, so super new. How are you guys seeing that with the customer base that you guys have? As they start to see benefits, does it impact their staffing, their support levels? What's the impact to the customer when they start to realize some of these benefits, but then understanding that with scale comes a whole nother set of operating challenges. >> Yeah. It is interesting. With that scale, it does... It does present other challenges, as you mentioned, from an operations perspective. And we have seen customers that go out there, go live. Well, you remember the commercial? I think there was a commercial many, many years ago back when the internet was kind of a new thing where it was a startup company, and they put an e-commerce site out there, right? And they were like, "Oh, yay! We got our first order." And they're like, "Yay! We have 10. Oh, crap! We have 10,000." Right? So you see customers like this, they get excited to put something out there, but they haven't fully performance tested it, right? So that's... That's also where we try to help our customers take that step back and say, "Okay. How are you going to actually plan, not just for day one, to get it out there, but longer term?" And that's where we also put our performance testing as a part of all of our solutions, because you know that yes, it's a good problem to have, but you really don't want to have that problem in the first place, so how do you make sure that you plan and prepare for that, and incrementally deploy, and make sure that your underlying technology is prepared to support that kind of volume. >> So Kirsten, I want to ask you kind of the important question this day and age in the modern era with cloud and now this new cloud scale, and it's always kind of been true in the past. But now more than ever you're starting to see the role of the ecosystem of partners as super important, because now integrations are happening. You're bringing point solutions into a platform where tools are integrating with other tools. So as a partner of IBM, how is the ecosystem role that you guys are playing, and how important is that, and what are the new things that are needed to be successful in the ecosystem with the premise that rising tide floats all boats, which is kind of... Well, we're seeing that happen now. Certainly, coming out of the pandemic it's going to be a whole new game, but there are ecosystems that are now evolving around IBM, around these big mega trends like cloud edge and data. What's your take? >> Mm-hm. Mm-hm. So first of all, you mentioned IBM's focus on ecosystem, right? And so Arvind has been very vocal about the importance of the ecosystem and how he really wants to change IBM's model out there to embrace partners. And I have to say, I think that's... That's one of the smartest things I think I've heard IBM say in years. And I know that that sounds self-serving because we are a partner, but the reality is there's several different layers where that's really important. One is the value of the partner. And you mentioned that there's a need to integrate across different systems, right? So IBM is not... Gone are the days when customers only have IBM technology. It's just not a thing. And so partners have the ability to work across different vendors, very hybrid, very unique types of environments, and make sure that the IBM interest, the IBM footprint, is well-deployed, well-represented, and set up for future success so that customer's going to want to buy more in the future, but in the context of what that customer's overall landscape is. So that's a big reason why IBM wants business partners involved with customers, and we're a little bit more... Or at least we can work with customers from a consultative perspective, right, and make sure that they are comfortable with the decisions that they're making. That isn't just the manufacturer telling them to buy our stuff. From a partners perspective, one of the biggest things that we struggle with in the marketplace is being known, right? I mean, we're... We're a decent-sized partner with over 1,000 employees, but at the end of the day, how many people know Prolifics as a brand name versus how many people know IBM? So opening those doors, partnering with the IBM sellers that have kind of an easier way in to introduce a partner and give us the credibility that, "Hey. We know Prolifics. We've seen them be successful and help very large companies that are just like you be successful with our technology. Let them help you end to end," is a... It's just a really good synergy as far as how you can actually, how IBM can scale with their customers, and how customers can realize that benefit of a broader ecosystem as well, and skillsets. >> Yeah. Great point. Arvind is very savvy on cloud. I know he loves hybrid cloud. He loves the cloud model. He's changing it with Red Hat. I think you're so smart and accurate on this whole changeover around network effects, organic ecosystems playing a power dynamic in how people buy and nurture themselves. So I think there's going to be a nice change over there. I think you're onto something pretty big with that, because look it, it's multi-vendor at many levels now. IBM has to integrate here, and you're a partner. You're well-known now. You're on theCUBE. So we're going to get the word out here. But it's- (chuckles) You're on a team. It's a group. It's not just... It's about the customer. This is now a different mindset. This is what customers want, because they're out in the organic field too. They're not just getting the emails sent to them. They're out and engaging. This is a new model. >> And one of the things that's interesting that we're seeing from our customers as well is they're no longer looking to buy a product and then have somebody come in, install, and implement. They're actually looking for guidance, right? They want ideas. "Here's what I'm trying to do with my business. How can you help me?" They're looking for an answer to that, and that requires a very different skillset, right? It's not just somebody who knows how to come in and spin up CDs and do some configurations. It's somebody who's worked in their industry before, has worked with similar types of customers, has a little bit of that road rash, can provide some of that guidance. And in order to really do that, you can't find that just in one organization. So I would tell you, actually, I mean Prolifics is a... We're a pretty good-sized company with a wide skillset, but even we partner. We also partner with other partners to help complement our skills when there's a particular expertise that's needed. So it really is a very interesting ecosystem development, and a different way of thinking, that it's not just about you and being able to do everything. It's about you being able to bring the right solution and the right ideas to a customer, and to help them be successful for the long-term. >> Awesome insight, Kirsten Craft, global head of business development and marketing at Prolifics. Great to have you on, and power of networks, power of partnerships, power of the ecosystem. The new world is here. Thanks for coming on theCUBE. >> Thank you. Great to be here. >> Okay. This is IBM Think 2021 coverage. I'm John Furrier, host of theCUBE. Thanks for watching. (smooth music)

Published Date : May 12 2021

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Robin Hernandez, IBM | IBM Think 2021


 

>> Narrator: From around the globe It's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome back everyone to theCUBE's coverage of IBM Think 2021 virtual, I'm John Furrier, your host. I've got a great guest here Robin Hernandez, vice president Hybrid Cloud Management and Watson AIOps. Robin, great to see you. Thanks for coming on theCUBE. >> Thanks so much for having me, John. >> You know, Hybrid Cloud, the CEO of IBM Arvind loves Cloud. We know that we've talked to him all the time about it. And Cloud is now part of the entire DNA of the company. Hybrid Cloud is validated multi clouds around the corner. This is the underlying pinnings of the new operating system of business. And with that, that's massive change that we've seen IT move to large scale. You're seeing transformation, driving innovation, driving scale, and AI is the center of it. So AIOps is a huge topic. I want to jump right into it. Can you just tell me about your day to day IT operations teams what you guys are doing? How are you guys organized? How you guys bring in value to the customers? What are your teams responsible for? >> Yeah, so for a few years we've been working with our IT customers, our enterprise customers in this transformation that they're going through. As they move more workloads to cloud, and they still have some of their workloads on premise, or they have a strategy of using multiple public clouds, each of those cloud vendors have different tools. And so they're forced with, how do I keep up with the changing rate and pace of this technology? How do I build skills on a particular public cloud vendor when, you know, maybe six months from now we'll have another cloud vendor that will be introduced or another technology that will be introduced. And it's almost impossible for an it team to keep up with the rate and pace of the change. So we've really been working with IT operations in transforming their processes and their skills within their teams and that looking at what tools do they use to move to this cloud operations model. And then as part of that, how do they leverage the benefits of AI and make that practical and purposeful in this new mode of cloud operations >> And the trend that's been booming is this idea of a site reliability engineer. It's really an IT operations role. It's become kind of a new mix between engineering and IT and development. I mean, classic DevOps, we've seen, you know dev and ops, right? You got to operate the developers and the software modern apps are coming in that's infrastructure as course has been around for a while. But now as the materialization of things like Kubernetes and microservices, people are programming the infrastructure. And so the scale is there, and that's been around for a while. Now it's going to go to a whole enterprise level with containers and other things. How is the site reliability engineering persona if you will, or ITOps changed specifically because that's where the action is. And that's where you hear things like observability and I need more data, break down the silos. What's this all about? What's your view? >> Yeah, so site reliability engineering or SRE practices as we call it has really not changed the processes per se that IT has to do, but it's more accelerated at an enormous rate and pace. Those processes and the tools as you mentioned, the cloud native tools like Kubernetes have accelerated how those processes are executed. Everything from releasing new code and how they work with development to actually code the infrastructure and the policies in that development process to maintaining and observing over the life cycle of an application, the performance, the availability, the response time, and the customer experience. All of those processes that used to happen in silos with separate teams and sort of a waterfall approach, with SRE practices now, they're happening instantaneously. They're being scaled out. They're being... Failback is happening much more quickly so that applications didn't do not have outages. And the rate and pace of this has just accelerated so quickly. This is the transformation of what we call cloud operations. And we believe that as IT teams work more closely with developers and they moved towards this SRE model, that they cannot just do this with their personnel and changing skills and changing tools. They have to do this with modernized tools like AI. And this is where we are recommending applying AI to those processes so that you can then get automation out of the back end that you would not think about in a traditional IT operations, or even in an SRE practice. You have to leverage capabilities and new technologies like AI to even accelerate further. >> Let's unpack the AI operations piece because I think that's where I think I'm in hearing. I'd love you to clarify this because it becomes I think the key important point but also kind of confusing to some folks because IT operations people see that changing. You just pointed out why, honestly, the tools and the culture is changing, but AI becomes a scale point because of the automation piece you mentioned. How does that thread together? How does AIOps specifically change the customer's approach in terms of how they work with their teams and how that automation is being applied? 'Cause I think that's the key thread, right? 'Cause everyone kind of gets the cultural shifts and the tools, if they're not living it and putting it in place, but now they want to scale it. That's where automation comes in. Is that right? Is that the right way to think about it? What's your view on this? This is important. >> It's absolutely right. And I always like to talk about AI in other industries before we apply it to IT to help IT understand. Because a lot of times, IT looks at AI as a buzzword and they say, "Oh, you know, yes, sure. "This is going to help me." But if you think about... We've been doing AI for a long time at many different companies not just at IBM, but if you think about the other industries where we've applied it, healthcare in particular is so tangible for most people, right? It didn't replace a doctor but it helps a doctor see the things that would take them weeks and months of studying and analyzing different patients to say, "Hey, John, I think this may be a symptom "that we overlooked or didn't think about "or a diagnosis that we didn't think about," without manually looking at all this research. AI can accelerate that so rapidly for a doctor, the same notion for IT. If we apply AI properly to IT, we can accelerate things like remediating incidents or finding a performance problem that may take your eye months or weeks or even hours to find, AI applied properly find those issues and diagnose just like they could in healthcare it diagnoses issues correctly much more rapidly. >> Now again, I want to get your thoughts on something while you're here 'cause you've been in the business for many, many decades 20 years experience, you know, cloud cold, you know the new modern area you're managing it now. Clients are having a scenario where they, "Okay, I'm changing over the culture." I'm "Okay, I got some cloud, I got some public "and I got some hybrid and man, "we did some agile things. "We're provisioned, it's all done. "It's out there." And all of a sudden someone adds something new and it crashes (chuckles) And now I've got to get in, "Where's the risks? where's the security holes?" They're seeing this kind of day two operations as some people call, another buzz word but it's becoming more of, "Okay, we got it up and running "but we still now going to still push some code "and things are starting to break. "and that's net new thing." So it's kind of like they're out of their comfort zone. This is where I kind of see the AIOps evolving quickly because there's kind of a DevSecOps piece. There's also data involved, observability. How do you talk to that scenario? Where, okay, you sold me on cloud, I've been doing it. I did some projects. We're not been running. We got a production system and we added something new. Something maybe trivial and it breaks stuff? >> Yes. Yeah, so with the new cloud operations and SRE, the IT teams are much more responsible for business outcomes. And not just as you say, the application being deployed and the application being available, but the life cycle of that application and the results that it's bringing to the end users and the business. And what this means is that it needs to partner much more closely with development. And it is hard for them to keep up with the tools that are being used and the new code and the architectures of microservices that developers are using. So we like to apply AI on what we call the change risk management process. And so everyone's familiar with change management that means a new piece of code is being released. You have to maintain where that code is being released to was part of the application architecture and make sure that it's scaled out and rolled out properly within your enterprise policies. When we apply AI, we then apply what we call a risk factor to that change because we know so often, application outages occur not something new within the environment. So by applying AI, we can then give you a risk rating that says, "There's an 80% probability "that this change that you're about to roll out, "a code change is going to cause a problem "in this application." So it allows you to then go back and work with the development team and say, "Hey, how do we reduce this risk?" Or decide to take that calculated risk and put into the visibility of where those risks may occur. So this is a great example, change risk management of how applying AI can make you more intelligent in your decisions much more tied to the business and tied to the application release team. >> That's awesome. Well, I got you here on this point of change management. The term "Shift Left" has come up a lot in the industry. I'd love to get your quick definition of what that is in your mind. What does Shift Left mean for Ops teams with AIOps? >> Yeah, so in the early days of IT there was a hard line definitely between your development and IT team. It was kind of we always said throwing it over the fence, right? The developers would throw the code over the fence and say, good luck IT, you know, figure out how to deploy it where it needs to be deployed and cross your fingers that nothing bad happens. Well, Shift Left is really about a breaking down that fence. And if you think of your developers on your left-hand side you'd being the IT team, it's really shifting more towards that development team and getting involved in that code release process, getting involved in their CI/CD pipeline to make sure that all of your enterprise policies and what that code needs to run effectively in your enterprise application and architecture, those pieces are coded ahead of time with the developer. So it's really about partnering between it and development, shifting left to have a more collaboration versus throwing things over the fence and playing the blame game, which is what happens a lot in the early days IT. >> Yeah, and you get a smarter team out of it, great point. That's great insight. Thanks for sharing that. I think it's super relevant. That's the hot trend right now making dealers more productive, building security from the beginning. While they're doing it code it right in, make it a security proof if you will. I got to ask you one of the organizational questions as IBM leader. What are some of the roadblocks that you see in organizations that when they embrace AIOps, are trying to embrace AI ops are trying to scale it and how they can overcome those blockers. What are some of the things you're seeing that you could share with other folks that are maybe watching and trying to solve this problem? >> Yeah, so you know, AI in any industry or discipline is only as good as the data you feed it. AI is about learning from past trends and creating a normal baseline for what is normal in your environment. What is most optimal in your environment this being your enterprise application running in steady state. And so if you think back to the healthcare example, if we only have five or six pieces of patient data that we feed the AI, then the AI recommendation to the doctor is going to be pretty limited. We need a broad set of use cases across a wide demographic of people in the healthcare example, it's the same with IT, applying AI to IT. You need a broad set of data. So one of the roadblocks that we hear from many customers is, well I using an analytics tool already and I'm not really getting a lot of good recommendations or automation out of that analytics tool. And we often find it's because they're pulling data from one source, likely they're pulling data from performance metrics, performance of what's happening with the infrastructure, CPU utilization or memory utilization, storage utilization. And those are all good metrics, but without the context of everything else in your environment, without pulling in data from what's happening in your logs, pulling in data from unstructured data, from things like collaboration tools, what are your team saying? What are the customers saying about the experience with your application? You have to pull in many different data sets across IT and the business in order to make that AI recommendation the most useful. And so we recommend a more holistic true AI platform versus a very segregated data approach to applying and eating the analytics or AI engine. >> That's awesome, it's like a masterclass right there. Robin, great stuff. Great insight. We'll quickly wrap. I would love to you to take a quick minute to explain and share what are some of the use cases to get started and really get into AIOps system successes for people that want to explore more, dig in, and get into this fast, what are some use case, what's some low hanging fruit? What would you share? >> Yeah, we know that IT teams like to see results and they hate black boxes. They like to see into everything that's happening and understand deeply. And so this is one of our major focus areas as we do. We say, we're making AI purposeful for IT teams but some of the low hanging fruits, we have visions. And lots of our enterprise customers have visions of applying AI to everything from a customer experience of the application, costs management of the application and infrastructure in many different aspects. But some of the low hanging fruit is really expanding the availability and the service level agreements of your applications. So many people will say, you know I have a 93% uptime availability or an agreement with my business that this application will be up 93% of the time. Applying AI, we can increase those numbers to 99.9% of the time because it learns from past problems and it creates that baseline of what's normal in your environment. And then we'll tell you before an application outage occurs. So avoiding application outages, and then improving performance, recommendations and scalability. What's the number of users coming in versus your normal scale rate and automating that scalability. So, performance improvements and scalability is another low-hanging fruit area where many IT teams are starting. >> Yeah, I mean, why wouldn't you want to have the AIOps? They're totally cool, very relevant. You know, you're seeing hybrid cloud, standardized all across business. You've got to have that data and you got to have that incident management work there. Robin, great insight. Thank you for sharing. Robin Hernandez, vice president of Hybrid Cloud Management in Watson AIOps. Thanks for coming on theCUBE. >> Thank you so much for having me John. >> Okay, this theCUBE's coverage of IBM Think 2021. I'm John Furrier your host. Thanks for watching. (bright upbeat music)

Published Date : May 12 2021

SUMMARY :

Brought to you by IBM. Robin, great to see you. And Cloud is now part of the and that looking at what tools do they use and the software modern apps are coming in and the policies in and the tools, if they're not living it but it helps a doctor see the things "Okay, I'm changing over the culture." and the results that it's bringing I'd love to get your quick definition and playing the blame game, I got to ask you one across IT and the business the use cases to get started and the service level and you got to have that coverage of IBM Think 2021.

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Jamie Thomas, IBM | IBM Think 2021


 

>> Narrator: From around the globe, it's the CUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome back to IBM Think 2021, the virtual edition. This is the CUBEs, continuous, deep dive coverage of the people, processes and technologies that are really changing our world. Right now, we're going to talk about modernization and what's beyond with Jamie Thomas, general manager, strategy and development, IBM Enterprise Security. Jamie, always a pleasure. Great to see you again. Thanks for coming on. >> It's great to see you, Dave. And thanks for having me on the CUBE is always a pleasure. >> Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM is focused on hybrid cloud, Arvind Krishna says we must win the architectural battle for hybrid cloud. I love that. We've been hearing a lot about AI. And I wonder if you could talk about IBM Systems and how it plays into that strategy? >> Sure, well, it's a great time to have this discussion Dave. As you all know, IBM Systems Technology is used widely around the world, by many, many 1000s of clients in the context of our IBM System Z, our power systems and storage. And what we have seen is really an uptake of monetization around those workloads, if you will, driven by hybrid cloud, the hybrid cloud agenda, as well as an uptake of Red Hat OpenShift, as a vehicle for this modernization. So it's pretty exciting stuff, what we see as many clients taking advantage of OpenShift on Linux, to really modernize these environments, and then stay close, if you will, to that systems of record database and the transactions associated with it. So they're seeing a definite performance advantage to taking advantage of OpenShift. And it's really fascinating to see the things that they're doing. So if you look at financial services, for instance, there's a lot of focus on risk analytics. So things like fraud, anti money laundering, mortgage risk, types of applications being done in this context, when you look at our retail industry clients, you see also a lot of customer centricity solutions, if you will, being deployed on OpenShift. And once again, having Linux close to those traditional LPARs of AIX, I-Series, or in the context of z/OS. So those are some of the things we see happening. And it's quite real. >> Now, you didn't mention power, but I want to come back and ask you about power. Because a few weeks ago, we were prompted to dig in a little bit with the when Arvind was on with Pat Kessinger at Intel and talking about the relationship you guys have. And so we dug in a little bit, we thought originally, we said, oh, it's about quantum. But we dug in. And we realized that the POWER10 is actually the best out there and the highest performance in terms of disaggregating memory. And we see that as a future architecture for systems and actually really quite excited about it about the potential that brings not only to build beyond system on a chip and system on a package, but to start doing interesting things at the Edge. You know, what do you what's going on with power? >> Well, of course, when I talked about OpenShift, we're doing OpenShift on power Linux, as well as Z Linux, but you're exactly right in the context for a POWER10 processor. We couldn't be more we're so excited about this processor. First of all, it's our first delivery with our partner Samsung with a seven nanometer form factor. The processor itself has only 18 billion transistors. So it's got a few transistors there. But one of the cool inventions, if you will, that we have created is this expansive memory region as part of this design point, which we call memory inception, it gives us the ability to reach memory across servers, up to two petabytes of memory. Aside from that, this processor has generational improvements and core and thread performance, improved energy efficiency. And all of this, Dave is going to give us a lot of opportunity with new workloads, particularly around artificial intelligence and inferencing around artificial intelligence. I mean, that's going to be that's another critical innovation that we see here in this POWER10 processor. >> Yeah, processor performance is just exploding. We're blowing away the historical norms. I think many people don't realize that. Let's talk about some of the key announcements that you've made in quantum last time we spoke on the qubit for last year, I think we did a deeper dive on quantum. You've made some announcements around hardware and software roadmaps. Give us the update on quantum please. >> Well, there is so much that has happened since we last spoke on the quantum landscape. And the key thing that we focused on in the last six months is really an articulation of our roadmaps, so the roadmap around hardware, the roadmap around software, and we've also done quite a bit of ecosystem development. So in terms of the roadmap around hardware, we put ourselves out there we've said we were going to get to over 1000 qubit machine and in 2023, so that's our milestone. And we've got a number of steps we've outlined along that way, of course, we have to make progress, frankly, every six months in terms of innovating around the processor, the electronics and the fridge associated with these machines. So lots of exciting innovation across the board. We've also published a software roadmap, where we're articulating how we improve a circuit execution speeds. So we hope, our plan to show shortly a 100 times improvement in circuit execution speeds. And as we go forward in the future, we're modifying our Qiskit programming model to not only allow a easily easy use by all types of developers, but to improve the fidelity of the entire machine, if you will. So all of our innovations go hand in hand, our hardware roadmap, our software roadmap, are all very critical in driving the technical outcomes that we think are so important for quantum to become a reality. We've deployed, I would say, in our quantum cloud over, you know, over 20 machines over time, we never quite identify the precise number because frankly, as we put up a new generation machine, we often retire when it's older. So we're constantly updating them out there, and every machine that comes on online, and that cloud, in fact, represents a sea change and hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. >> That's key, the developer angle you got redshift running on quantum yet? >> Okay, I mean, that's a really good question, you know, as part of that software roadmap in terms of the evolution and the speed of that circuit execution is really this interesting marriage between classical processing and quantum processing and bring those closer together. And in the context of our classical operations that are interfacing with that quantum processor, we're taking advantage of OpenShift, running on that classical machine to achieve that. And once again, if, as you can imagine, that'll give us a lot of flexibility in terms of where that classical machine resides and how we continue the evolution the great marriage, I think that's going to that will exist that does exist and will exist between classical computing and quantum computing. >> I'm glad I asked it was kind of tongue in cheek. But that's a key thread to the ecosystem, which is critical to obviously, you know, such a new technology. How are you thinking about the ecosystem evolution? >> Well, the ecosystem here for quantum is infinitely important. We started day one, on this journey with free access to our systems for that reason, because we wanted to create easy entry for anyone that really wanted to participate in this quantum journey. And I can tell you, it really fascinates everyone, from high school students, to college students, to those that are PhDs. But during this journey, we have reached over 300,000 unique users, we have now over 500,000 unique downloads of our Qiskit programming model. But to really achieve that is his back plane by this ongoing educational thrust that we have. So we've created an open source textbook, around Qiskit that allows organizations around the world to take advantage of it from a curriculum perspective. We have over 200 organizations that are using our open source textbook. Last year, when we realized we couldn't do our in person programming camps, which were so exciting around the world, you can imagine doing an in person programming camp and South Africa and Asia and all those things we did in 2019. Well, we had just like you all, we had to go completely virtual, right. And we thought that we would have a few 100 people sign up for our summer school, we had over 4000 people sign up for our summer school. And so one of the things we had to do is really pedal fast to be able to support that many students in this summer school that kind of grew out of our proportions. The neat thing was once again, seeing all the kids and students around the world taking advantage of this and learning about quantum computing. And then I guess that the end of last year, Dave, to really top this off, we did something really fundamentally important. And we set up a quantum center for historically black colleges and universities, with Howard University being the anchor of this quantum center. And we're serving 23 HBCUs now, to be able to reach a new set of students, if you will, with STEM technologies, and most importantly, with quantum. And I find, you know, the neat thing about quantum is is very interdisciplinary. So we have quantum physicist, we have electrical engineers, we have engineers on the team, we have computer scientists, we have people with biology and chemistry and financial services backgrounds. So I'm pretty excited about the reach that we have with quantum into HBCUs and even beyond right I think we can do some we can have some phenomenal results and help a lot of people on this journey to quantum and you know, obviously help ourselves but help these students as well. >> What do you see in people do with quantum and maybe some of the use cases. I mean you mentioned there's sort of a connection to traditional workloads, but obviously some new territory what's exciting out there? >> Well, there's been a really a number of use cases that I think are top of mind right now. So one of the most interesting to me has been one that showed us a few months ago that we talked about in the press actually a few months ago, which is with Exxon Mobil. And they really started looking at logistics in the context of Maritime shipping, using quantum. And if you think of logistics, logistics are really, really complicated. Logistics in the face of a pandemic are even more complicated and logistics when things like the Suez Canal shuts down, are even more complicated. So think about, you know, when the Suez Canal shut down, it's kind of like the equivalent of several major airports around the world shutting down and then you have to reroute all the traffic, and that traffic and maritime shipping is has to be very precise, has to be planned the stops are plan, the routes are plan. And the interest that ExxonMobil has had in this journey is not just more effective logistics, but how do they get natural gas shipped around the world more effectively, because their goal is to bring energy to organizations into countries while reducing CO2 emissions. So they have a very grand vision that they're trying to accomplish. And this logistics operation is just one of many, then we can think of logistics, though being a being applicable to anyone that has a supply chain. So to other shipping organizations, not just Maritime shipping. And a lot of the optimization logic that we're learning from that set of work also applies to financial services. So if we look at optimization, around portfolio pricing, and everything, a lot of the similar characteristics will also go be applicable to the financial services industry. So that's one big example. And I guess our latest partnership that we announced with some fanfare, about two weeks ago, was with the Cleveland Clinic, and we're doing a special discovery acceleration activity with the Cleveland Clinic, which starts prominently with artificial intelligence, looking at chemistry and genomics, and improve speed around machine learning for all of the the critical healthcare operations that the Cleveland Clinic has embarked on but as part of that journey, they like many clients are evolving from artificial intelligence, and then learning how they can apply quantum as an accelerator in the future. And so they also indicated that they will buy the first commercial on premise quantum computer for their operations and place that in Ohio, in the the the years to come. So it's a pretty exciting relationship. These relationships show the power of the combination, once again, of classical computing, using that intelligently to solve very difficult problems. And then taking advantage of quantum for what it can uniquely do in a lot of these use cases. >> That's great description, because it is a strong connection to things that we do today. It's just going to do them better, but then it's going to open up a whole new set of opportunities. Everybody wants to know, when, you know, it's all over the place. Because some people say, oh, not for decades, other people say I think it's going to be sooner than you think. What are you guys saying about timeframe? >> We're certainly determined to make it sooner than later. Our roadmaps if you note go through 2023. And we think the 2023 is going to will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kind of use cases and this intense working with these clients, 'cause when they work with us, they're giving us feedback on everything that we've done, how does this programming model really help me solve these problems? What do we need to do differently? In the case of Exxon Mobil, they've given us a lot of really great feedback on how we can better fine tune all elements of the system to improve that system. It's really allowed us to chart a course for how we think about the programming model in particular in the context of users. Just last week, in fact, we announced some new machine learning applications, which these applications are really to allow artificial intelligence users and programmers to get take advantage of quantum without being a quantum physicist or expert, right. So it's really an encapsulation of a composable elements so that they can start to use, using an interface allows them to access through PyTorch into the quantum computer, take advantage of some of the things we're doing around neural networks and things like that, once again, without having to be experts in quantum. So I think those are the kind of things we're learning how to do better, fundamentally through this co-creation and development with our quantum network. And our quantum network now is over 140 unique organizations and those are commercial, academic, national laboratories and startups that we're working with. >> The picture started become more clear, we're seeing emerging AI applications, a lot of work today in AI is in modeling. Over time, it's going to shift toward inference and real time and practical applications. Everybody talks about Moore's law being dead. Well, in fact, the yes, I guess, technically speaking, but the premise or the outcome of Moore's law is actually accelerating, we're seeing processor performance, quadrupling every two years now, when you include the GPU along with the CPU, the DSPs, the accelerators. And so that's going to take us through this decade, and then then quantum is going to power us, you know, well beyond who can even predict that. It's a very, very exciting time. Jamie, I always love talking to you. Thank you so much for coming back on the CUBE. >> Well, I appreciate the time. And I think you're exactly right, Dave, you know, we talked about POWER10, just for a few minutes there. But one of the things we've done in POWER10, as well as we've embedded AI into every core that processor, so you reduce that latency, we've got a 10 to 20 times improvement over the last generation in terms of artificial intelligence, you think about the evolution of a classical machine like that state of the art, and then combine that with quantum and what we can do in the future, I think is a really exciting time to be in computing. And I really appreciate your time today to have this dialogue with you. >> Yeah, it's always fun and it's of national importance as well. Jamie Thomas, thanks so much. This is Dave Vellante with the CUBE keep it right there our continuous coverage of IBM Think 2021 will be right back. (gentle music) (bright music)

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>> (lively music) >> Narrator: From around the globe it's theCUBE, with digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome to theCUBE's coverage of IBM Think 2021, the digital event experience. I'm your host, Lisa Martin. I've got an alumni joining me and a brand new guest to the CUBE please welcome Paul Papas, the Global Managing Partner, for IBM Global Business Services, this is transformation services. Paul, welcome back to the virtual CUBE. >> Thanks Lisa great to be here with you today. And Dominique Dubois is here as well. She is the Global Strategy and Offerings Leader in business transformation services or BTS at IBM. Dominique, welcome to the program. >> Thanks Lisa, great to be here. So, we're going to be talking about accelerating business transformation with intelligent workflows. We're going to break through all that, but Paul we're going to start with you. Since we last got together with IBM, a lot has changed so much transformation, so much acceleration of transformation. Talk to me from your perspective, how have you seen the way that businesses running change and what some of the changes in the future are going to be? >> Well, you hit on two key words there Lisa and thanks so much for that question. Two key words that you hit on were change and acceleration. And that's exactly what we see. We were seeing this before the pandemic and if anything, with the pandemic did when things started started kind of spreading around the world late or early last year, around January, February timeframe we saw that word acceleration really take hold. Every one of our clients were looking for new ways to accelerate the change that they had already planned to adapt to this new, this new normal or this new abnormal, depending on how you view it. In fact, we did a study recently, an IBV study that's our Institute of Business Value and found that six out of 10 organizations were accelerating all of their transformation initiatives they had already planned. And that's exactly what we're seeing happening right now in all parts of the world and across all industries. This acceleration to transform. >> So, one of the things that we've talked about for years, Paul, before the pandemic was even a thing, is that there was a lot of perceived technical barriers in terms of like the tech maturity for organizations and employees being opposed to change. People obviously it can be a challenge. They're used to doing things the way they are. But as you just said, in that IBV survey, nearly 60% of businesses say we have to accelerate our transformation due to COVID, probably initially to survive and then thrive. Talk to me about some of those, those barriers that were there a little over a year ago and how businesses 60 plus percent of them have moved those out of the way. >> You know at IBM we've got a 109 year history of being a technology innovation company. And the rate of pace of technical change is always increasing. It's something that we love and that we're comfortable with. But the rate and pace of change is always unsettling. And there's always a human element for change. And the human element is always the rate, the rate setter in terms of the amount of change that you can have in an organization. Our former chairman Ginni Rometty, used to say that growth and comfort cannot co-exist. And it's so true because changing is uncomfortable. It's unsettling. It can be, it can be nerve-racking. It can instill fear and fear can be paralyzing in terms of driving change. And what we also see is there's a disconnect, a lot of times and that IBV study that I was referring to before, we saw results coming back where 78% of executives feel that they have provided the training and enablement to help their employees transform to new required skills and new ways of working but only half of the people surveyed felt the same way. Similarly, we saw a disconnect in terms of companies feeling that they're providing the right level of health and wellness support during the pandemic. And only half of the employees responded back they feel that they're getting that level of support. So, the people change aspect of doing a transformation or adapting to new circumstances is always the most critical component and always the hardest component. And when we talk about helping our clients do that in IBM that's our service as organization. That's the organization that Dominique Dubois is representing here today. I'm responsible for business transformation services within our organization. We help our clients adapt using new technologies, transforming the way they work, but also addressing the people change elements that could be so difficult and hitting them head on so that they can make sure that they can survive and thrive in a meaningful and lasting way in this new world. >> One of the hardest things is that cultural transformation regardless of a pandemic. So, I can't imagine I'd love to get one more thing, Paul from you before we head over to Dominique. IBM is on 109 year old organization. Talk to me about the IBM pledge. This is something that came up last year, huge organization massive changes last year, not just the work from home that the mental concerns and issues that people had. What did IBM do like as a grassroots effort that went viral? >> Yeah, so, it's really great. So, when the pandemic started, we all have to shift it, We all have to shift to working from home. And as you mentioned, IBM's 109 year old company, we have over 300,000 employees working in 170 countries. So, we had to move this entire workforce. It's 370,000 humans to working in a new way that many of which have never done before. And when we started experiencing, the minute we did that, within a few weeks, my team and I were talking Dominique is on my team and we were having conversations where we were feeling really exhausted. Just a few weeks into this and it was because we were constantly on Webex, we were constantly connected and we're all used to working really hard. We travel a lot, we're always with our clients. So, it wasn't that, you have a team that is adapting to like working more hours or longer hours, but this was fundamentally different. And we saw that with schools shutting down and lock downs happening in different of the world the home life balance was getting immediately difficult to impossible to deal with. We have people that are taking care of elderly parents, people that are homeschooling children, other personal life situations that everyone had to navigate in the middle of a pandemic locked at home with different restrictions on when you can go out and get things done. So, we got together as a group and we just started talking about how can we help? How can we help make life just a little bit easier for all of our people? And we started writing down some things that we would, we would commit to doing with each other. How we would address each other. And when that gave birth to was what we call the IBM Work From Home Pledge. And it's a set of principles, all grounded in the belief that, if we act this way, we might just be able to make life just a little bit easier for each other and it's grounded in empathy. And there are parts of the Plex that are pledging to be kind. Recognizing that in this new digital world that we're showing up on camera inside of everyone's home. We're guests in each other's homes. So, let's make sure that we act appropriately as guests at each other's home. So, if children run into the frame during the middle of a meeting or dog started barking during the middle of a meeting, just roll with it. Don't call out attention to it. Don't make people feel self-conscious about it. Pledged the support so your fellow IBM by making time for personal needs. So, if someone has to, do homeschooling in the middle of the day, like Dominique's got triplets she's got to do homeschooling in the middle of the day. Block that time off and we will respect that time on your calendar. And just work around it and just deal with it. There are other things like respecting that camera ready time. As someone who's now been on camera every day it feels like for the last 14 months we want to respect the time that people when they have their cameras off. And not pressure them to put their cameras on saying things like, Hey, I can't see you. There's no reason to add more pressure to everyone's life, if someone's camera's off, it's all for a reason. And then other things like pledging to checking on each other, pledging to set boundaries and tend to our own self-care. So, we published that as a group, we just again and we put it on a Slack channel. So it's kind of our communication method inside the company. It was just intended to be for my organization but it started going viral and tens of thousands of IBM members started taking, started taking the pledge and ultimately caught the attention of our CEO and he loved it, shared it with his leadership team, which I'm a part of. And then also then went on LinkedIn and publicly took the pledge as well. Which then also got more excitement and interaction with other companies as well. So, grassroots effort all grounded in showing empathy and helping to make life just a little bit easier for everyone. >> So important, I'm going to look that up and I'm going to tell you as a person who speaks with many tech companies a week. A lot of businesses could take a lead from that and it gets really important and we are inviting each other into our homes and I see you're a big Broadway fan I'll have to ask you that after we wrap (giggles) Dominique I don't know how you're doing any of this with triplets. I only have two dogs (Dominique laughs) but I'd love to know this sense of urgency, that is everywhere you're living it. Paul talked about it with respect to the acceleration of transformation. How from your lens is IBM and IBM helping customers address the urgency, the need to pivot, the need to accelerate, the need to survive and thrive with respect to digital transformation actually getting it done? >> Right, thanks Lisa, so true our clients are really needing to and ready to move with haste. That that sense of urgency can be felt I think across every country, every market, every industry. And so we're really helping our clients accelerate their digital transformations and we do that through something that we call intelligent workflows. And so workflows in and of themselves are basically how organizations get work done. But intelligent workflows are how we infuse; predictive properties, automation, transparency, agility, end to end across a workflow. So, pulling those processes together so they're not solid anymore and infusing. So, simply put we bring intelligent workflows to our clients and it fundamentally reinvents how they're getting work done from a digital perspective, from a predictive perspective, from a transparency perspective. And I think what really stands apart when we deliver this with our clients in partnership with our clients is how it not only delivers value to the bottom line, to the top line it also actually delivers greater value to their employees, to the customers, to the partner to their broader ecosystem. And intelligent workflows are really made up of three core elements. The first is around better utilizing data. So, aggregating, analyzing, getting deeper insight out of data, and then using that insight not just for employees to make better decisions, but actually to support for emerging technologies to leverage. So we talked about AI, automation, IOT, blockchain, all of these technologies require vast amounts of data. And what we're able to bring both on the internal and external source from a data perspective really underpins what these emerging technologies can do. And then the third area is skills. Our skills that we bring to the table, but also our clients deep, deep expertise, partner expertise, expertise from the ecosystem at large and pulling all of that together, is how we're really able to help our clients accelerate their digital transformations because we're helping them shift, from a set of siloed static processes to an end-to-end workflow. We're helping them make fewer predictions based on the past historical data and actually taking more real-time action with real time insights. So, it really is a fundamental shift and how your work is getting done to really being able to provide that emerging technologies, data, deep skills-based end to end workflow. >> That word fundamental has such gravity. and I know we say data has gravity being fundamental in such an incredibly dynamic time is really challenging but I was looking through some of the notes that you guys provided me with. And in terms of what you just talked about, Dominique versus making a change to a silo, the benefits and making changes to a spectrum of integrated processes the values can be huge. In fact, I was reading that changing a single process like billing, for example might deliver up to 20% improved results. But integrating across multiple processes, like billing, collections, organizations can achieve double that up to 40%. And then there's more taking the intelligent workflow across all lead to cash. This was huge. Clients can get 50 to 70% more value from that. So that just shows that fundamental impact that intelligent workflows can make. >> Right, I mean, it really is when we see it really is about unlocking exponential value. So, when you think about crossing end to end workflow but also, really enhancing what clients are doing and what companies are doing today with those exponential technologies from kind of single use the automation POC here and AI application POC here, actually integrating those technologies together and applying them at scale. When I think intelligent workflows I think acceleration. I think exponential value. But I also really think about at scale. Because it's really the ability to apply these technologies the expertise at scale that allows us to start to unlock a lot of that value. >> So let's go over Paul, in the last few minutes that we have here I want to talk about IBM garage and how this is helping clients to really transform those workflows. Talk to me a little bit about what IBM garage is. I know it's not IBM garage band and I know it's been around since before the pandemic but help us understand what that is and how it's delivering value to customers. >> Well, first I'm going to be the first to invite you to join the IBM garage band, Lisa so we'd love to have you >> I'm in. no musical experience required... >> I like to sing, all right I mean (laughs) We're ready, we're ready for. So, let me talk to you about IBM garage and I do want to key on two words that Dominique was mentioning speed and scale. Because that's what our clients are really looking for when they're doing transformations around intelligent workflows. How can you transform at scale, but do that with speed. And that really becomes the critical issue. As Dominique mentioned, there's a lot of companies that can help you do a proof of concept do something in a few weeks that you can test an idea out and have something that's kind of like a throw away piece of work that maybe proves a point or just proves a point. But even if it does prove the point at that point you'd have to restart a new, to try to get something that you could actually scale either in the production technology environment or scale as a change across an organization. And that's where IBM garage comes in. It's all a way of helping our clients co-create, co-execute and then cooperate, innovating at scale. So, we use methods like design thinking inside of IBM we've trained several hundred thousand people on design thinking methods. We use technologies like neural and other things that help our clients co-create in a dynamic environment. And what's amazing for me is that, the cause of the way we were, we were doing work with clients in a garage with using IBM garage in a garage environment before the pandemic. And one of our clients Frito-Lay of North America, is an example where we've helped them innovate at scale and speed using IBM garage over a long period of time. And when the pandemic hit, we in fact were running 11 garages across 11 different workflow areas for them the pandemic hit and everyone was sent home. So, we all instantly overnight had to work from home together with relay. And what was great is that we were able to quickly adapt the garage method to working in a virtual world. To being able to run that same type of innovation and then use that innovation at scale in a virtual world, we did that overnight. And since that time which happened, that happened back in March of last year throughout the pandemic, we've run over 1500 different garage engagements with all of our clients all around the world in a virtual, in a virtual environment. It's just an incredible way, like I said to help our clients innovate at scale. >> That's fantastic, go ahead Dominique. >> Oh, sorry, was just said it's a great example, we partnered with FlightSafety International, they train pilots. And I think a great example of that speed and scale right is in less than 12 weeks due to the garage methodology and the partnership with FlightSafety, we created with them and launched an adaptive learning solution. So, a platform as well as a complete change to their training workflow such that they had personalized kind of real-time next best training for how they train their pilots for simulators. So, reducing their cycle time but also improving the training that their pilots get, which as people who normally travel, it's really important to us and everyone else. So, just a really good example, less than 12 weeks start to start to finish. >> Right, talk about acceleration. Paul, last question for you, we've got about 30 seconds left I know this is an ecosystem effort of IBM, it's ecosystem partners, it's Alliance partners. How are you helping align right partner with the right customer, the right use case? >> Yeah, it's great. And our CEO Arvind Krishna has really ushered in this era where we are all about the open ecosystem here at IBM and working with our ecosystem partners. In our services business we have partnerships with all the major, all the major technology players. We have a 45 year relationship with SAP. We've done more SAP S 400 implementations than anyone in the world. We've got the longest standing consulting relationship with Salesforce, we've got a unique relationship with Adobe, they're only services and technology partner in the ecosystem. And we just recently won three, procedures Partner Awards, with them and most recently we announced a partnership with Celonis which is an incredible process execution software company, process mining software company that's going to help us transform intelligent workflows in an accelerated way, embedded in our garage environment. So, ecosystem is critical to our success but more importantly, it's critical to our client success. We know that no one alone has the answers and no one alone can help anyone change. So, with this open ecosystem approach that we take and global business services and our business transformation services organization, we're able to make sure that we bring our clients the best of everyone's capabilities. Whether it's our technology, partners, our services IBM's own technology capabilities, all in the mix, all orchestrated in service to our client's needs all with the goal of driving superior business outcomes for them. >> And helping those customers in any industry to accelerate their business transformation with those intelligent workloads and a very dynamic time. This is a topic we could keep talking about unfortunately, we are out of time but thank you both for stopping by and sharing with me what's going on with respect to intelligent workflows. How the incremental exponential value it's helping organizations to deliver and all the work that IBM is doing to enable its customers to be thrivers of tomorrow. We appreciate talking to you >> Paul: Thanks Lisa. >> Dominique: Thank you >> For Paul Papas and Dominique Dubois I'm Lisa Martin. You're watching the CUBE's coverage of IBM Think the digital event experience. (gentle music)

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Octavian Tanase, NetApp and Jason McGee, IBM | IBM Think 2021


 

>> Narrator: From around the globe, It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Hi, welcome back to theCUBE's coverage of IBM Think 2021 virtual. We're not yet in real life. We're doing another remote interviews with two great guests Cube Alumni. Of course, I'm John Furrier your host of theCUBE. We've got Jason McGee, IBM fellow VP and CTO of IBM's cloud platform and Octavian the Nazis senior vice president Hybrid Cloud engineering at NetApp. Both Cube alumni, is great to see you both. Thanks for coming on theCUBE >> Yeah, great to be here. >> Thanks for having us. >> So we were just talking before we came on camera that, it feels like we've had this conversation, a long time ago we have, Hybrid Cloud has been on a trajectory for both of you guys in many times on theCUBE. So now it's mainstream, it's here in the real world. Everyone gets it. There's no real debate. Now multicloud that's people are debating that which means that's right around the corner. So Hybrid Cloud is here and now Jason this is really the focus. And this is also brings together the NetApp in your partnership and talk about the relationship first with Hybrid Cloud. >> Yeah, I mean, you know look we've talked a number of times together. I think in the industry, maybe a few years ago people were debating whether Hybrid Cloud was a real thing. We don't have that conversation anymore. I think, you know, enterprises today, especially maybe in the face of COVID and kind of how we work differently now realize that their cloud journey is going to be a mix of on-prem and off-prem systems probably going to be a mix of multiple public cloud providers. And what they're looking for now is how do I do that? And how do I manage that hybrid environment? How do I have a consistent platform across the different environments I want to operate in? And then how do I get more and more of my workload into those environments? And it's been interesting. I think the first waves of cloud were infrastructure centric and externally application focused they were easier things. And now we're moving into more mission critical more stateful, more data oriented workloads. And that brings with a new challenges on where applications run and how we leverage the club. >> Octavian, you guys had a great relationship with IBM over the years, data centric company NetApp has always been great engineering team. You're on the cloud, Hybrid Cloud engineering. What's the current status of the relationship. Give us an update on how it's vectoring into the Hybrid Cloud since you're a senior vice president of Hybrid Cloud engineering. >> Well, so first of all, I want to recognize 20 years of a successful partnership with IBM. I think NetApp and IBM have been companies that have embraced digital transformation and technology trends to enable that digital transformation for our customers. And we've been very successful. I think there is a very strong joint Hybrid Cloud value proposition for customers on NetApps storage and data services compliment what IBM does in terms of products and solutions both for on-premise deployments in the cloud. I think together we can build more complete solutions, solutions that span data mobility, data governance for the new workrooms that Jason has talked about. >> And how has some of the customer challenges that you're seeing obviously software defined networking software defined storage, DevOps is now turned into DevSecOps. So you have now that programmability requirement with for dynamic applications, applications driven, infrastructure, all these buzz words point to one thing, the infrastructure has to be resilient and respond to the applications. >> Yeah, I would say infrastructure will continue to be top of mind for everybody, whether they're building a private cloud or whether they we're trying to leverage, something like IBM cloud. I think, you know, people want to consume, infrastructure is an API. I think they want to simplicity, security. I think they want to manage their costs very well. I think we're very proud to be partnering with IBM cloud to build such capabilities. >> Jason how are you guys helping some of these customers as they look at new things and sometimes retrofitting and refactoring previous stuff during transforming, but also innovating at the same time. There's a lot of that going on. What are you guys doing to help with the Hybrid challenges? >> Yeah, I mean, you know, there's a lot of dimensions to that problem but the one that I think has been kind of most interesting over the last year has been how kind of the consumption model of public cloud, API driven, self service, capabilities operated for you how that consumption model is starting to spread because I think one of the challenges with hybrid and one of the challenges as customers are looking at these, more mission critical data centric kind of workloads was well, I can't always move that application to the public cloud data center or I need that application to live out on the network, closer to my end users. So, you know, out where data is being generated, maybe in an IOT context and when you had those requirements you had to kind of switch operating models. You, you had to kind of move away from a public cloud service consumption model to a software deployment model. And we have a common platform and things like open shift that can run everywhere but the missing piece was how do I consume everything as a service everywhere? And so recently we launched this thing called IBM been satellite, which we've been working with Octavian and his team on, on how we can actually extend the public cloud experience back into the data center, out to the edge and allow people to kind of mix both location flexibility with public cloud consumption. And when you do that, you of course running a much more diverse infrastructure environment. You have to integrate with different storage environments and you wind up with like multi-tiered applications you know, some stuff on the edge and some stuff in the core. And so data replication and data management start to become really interesting because you're kind of distributing your workloads across this complex environment. >> Here we've seen that relationship between compute and storage change a lot over the past decade as the evolution goes. Octavian, I got to ask you this is critical path for companies. They want the storage ready infrastructure. You guys have been doing that for many decades pardon me with IBM, for sure. But now they're all getting Hybrid Cloud big time and it's not, it's attributed computing. It's what it is. It's the operating model. When someone asks you guys what your capabilities are how do you answer that in today's world? Because you have storage as well known. You got a great product people know that. But what is NetApp's capabilities? When I say I'm going all in and Hybrid Cloud complete changeover. >> So what we have been doing is basically rewriting a lot of our software with a few design points in mind. The software-defined has been definitely one of the key design points. The second is the Hybrid Cloud in the containerization of our operating systems. So they can run both in traditional environments as well as in the cloud. I think the last thing that we wanted to do it's enabled the speed of scale. And that has been by building, you know intrinsically in the product, both support or in also using Kubernetes as an infrastructure to achieve that agility, that scale. >> So how about this data fabric vision? Because to me, this is comes up all the time in my conversations with practitioners the number one problem at their, and problem that they're to solve in the conversation tends to I hear what was that control plane Kubernetes, horizontally scalable this all points to data being available., So how do you create that availability? What is data fabric mean? What does all this mean in a hybrid context? >> Well if you think about it, data fabric it's a Hybrid Cloud concept, right? This is about enabling data governance, data, mobility data security in an environment where some of the applications were run on premises or at the edge or the smart edge and many of the, perhaps data links and analytics, and services, rich services will be in a central locations or many or perhaps some large know data centers. So you need to have, the type of capabilities data services to enable that mobility that governance, that security across this continuum that spans the edge, the core and the cloud. >> Jason, you mentioned satellite before Cloud Satellite. Could you go into more detail on that? I know it's kind of a new product, what is that about and tell me what's the benefits and why is it exist and what problems does it solve? >> Yeah, so in the most simple terms, Cloud Satellite is the capability to extend IBM's, public cloud into on-prem infrastructure at the edge or in a multicloud context to other public cloud infrastructures. And so you can consume all the services in the public cloud that you need to to build your application, OpenShift as a service database, as DevTools, AI capabilities instead of being limited to only being able to consume those services in IBM's re you know, cloud regions you can now add your private data center or add your Metro provider, or add your AWS or Azure accounts and now consume those services consistently across all those environments. And that really allows you to kind of combine the benefits of public cloud with kind of location independence you see in hybrid and lets us solve new problems. Like, you know, it's really interesting. We're seeing like AI and data being a primary driver. You know I need my application to live in a certain country or to live next to my mainframe or to live like, in a Metro because all of my, I'm doing like video analytics on a bunch of cameras and I'm not going to stream all that data back to halfway across the country to some cloud region. And so it lets you extend out in that way. And when you do that, of course, you now move the cloud into a more diverse infrastructure environment. And so like we've been working with NetApp on how do we then expose NetApp storage into this environment when I'm running in the data center or I'm running at the edge and I need to store that data replicate the data, secure it. Well, how do I kind of plug those two things together? I think John, at the beginning you kind of alluded to this idea of, things are becoming more application centric, right? And we're trying to run a IT architecture that's more centered around the application. Well, by combining clouds knowledge of kind of where everything's running with that common platform like OpenShift with Kubernetes aware of data fabric and storage layer, you really can achieve that. You can have an application centric kind of management that spans those environments. >> Yeah, I'm want to come back to that whole impact on IT because this has come up as a major theme here. Think at the it transformation is going to be more about cloud scale, but I want to get to Octavian on the satellite on NetApp's role and how you compliment that. How do you guys fit in? He just mentioned that you guys are playing with Cloud Satellite. Obviously this looks like an operating model. How does NetApp fit in. >> Simply put we extend and enable the capabilities that IBM satellite platform provides. I think Jason referred to the storage aspects and you know what we are doing it's enabling not only storage but rich data services around new theory based on temperature, or replicated snapshots or capabilities around, you know, caching, high availability, encryption and so forth. So we believe that our technology integrate very well with red hat openShift and the Kubernetes aspect enable the application mobility in that translation of really distributed computing at scale, from the traditional data center to the edge and to the massive Ops that IBM is building. >> You know, I got to say, but watching you guys work together for many decades now and covering you with theCUBE for the past 10 years or 11 years now been a great partnership. I got to say one thing, that's obvious to me and our team and mainly the world is now you've got a new CEO over at IBM you have a Cloud Focus that's on unwavering. Arvind loves the cloud we all know that. Ecosystems are changing without, you already had a big ecosystem and partnerships. Now it seems to be moving to a level where you got to have that ecosystem really thrive in the cloud. So I guess we'll use the last couple of minutes. If you guys don't mind explaining how the IBM NetApp relationship in the new context of this new partnership new ecosystem or a new kind of world helps customers and how you guys are working together. >> Yeah, I mean, I could start, I mean I think you're right, that cloud is all about platforms and about kind of the overall environment people operate in and the ecosystem is really critical. And I think things like satellite have given us new ways to work together. I mean, IBM and NetApp, as we said I've been working together for a long time. We rely on them all in our public cloud, for example, in our storage tiers. But with the kind of idea of distributed cloud in the boundaries of public cloud spreading to all of these new environments, those were just new places where we can build really interesting valuable integrations for our clients so that they can deal with data, deal with these more complex apps, in all the places that they exist. So I think it's been actually really exciting to kind of leverage that opportunity to find, new ways to work together and deliver solutions for our clients. >> Octavian. >> I will say that data is the ecosystem and we all know that there's more data right now being created outside of the traditional data center be it in the cloud or at the edge. So our mission is to enable that, Hybrid Cloud or data mobility and enabled persistence rich data, storage services, whatever data is being created. I think IBM's new satellite platform, comes in and broadens the aperture of people being able to consume IBM's services at the edge and or a remote office and I think that's very exciting. >> You guys are both experts and solely season executives to DevOps, DevSecOps, DataOps, whatever you want to call data's here, ecosystems. Guys thanks for coming on theCUBE Really appreciate the insight. >> Thank you. >> Thank you. >> Okay, IBM Think CUBE coverage. I'm John Furrier, your host. Thanks for watching. (upbeat music) (tranquil music)

Published Date : May 12 2021

SUMMARY :

brought to you by IBM. great to see you both. for both of you guys in and kind of how we work differently of the relationship. deployments in the cloud. the infrastructure has to be resilient I think, you know, people want to consume, Jason how are you guys back into the data center, out to the edge a lot over the past decade Cloud in the containerization in the conversation tends to that spans the edge, I know it's kind of a new product, in the public cloud that you need to Octavian on the satellite and enable the capabilities and mainly the world is and about kind of the overall environment of people being able to Really appreciate the insight. I'm John Furrier, your host.

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