(upbeat music) >> Hey guys, welcome back to the show floor of KubeCon + CloudNativeCon '22 North America from Detroit, Michigan. Lisa Martin here with John Furrier. This is day one, John at theCUBE's coverage. >> CUBE's coverage. >> theCUBE's coverage of KubeCon. Try saying that five times fast. Day one, we have three wall-to-wall days. We've been talking about Kubernetes, containers, adoption, cloud adoption, app modernization all morning. We can't talk about those things without addressing security. >> Yeah, this segment we're going to hear container and Kubernetes security for modern application 'cause the enterprise are moving there. And this segment with Red Hat's going to be important because they are the leader in the enterprise when it comes to open source in Linux. So this is going to be a very fun segment. >> Very fun segment. Two guests from Red Hat join us. Please welcome Doron Caspin, Senior Principal Product Manager at Red Hat. Michael Foster joins us as well, Principal Product Marketing Manager and StackRox Community Lead at Red Hat. Guys, great to have you on the program. >> Thanks for having us. >> Thank you for having us. >> It's awesome. So Michael StackRox acquisition's been about a year. You got some news? >> Yeah, 18 months. >> Unpack that for us. >> It's been 18 months, yeah. So StackRox in 2017, originally we shifted to be the Kubernetes-native security platform. That was our goal, that was our vision. Red Hat obviously saw a lot of powerful, let's say, mission statement in that, and they bought us in 2021. Pre-acquisition we were looking to create a cloud service. Originally we ran on Kubernetes platforms, we had an operator and things like that. Now we are looking to basically bring customers in into our service preview for ACS as a cloud service. That's very exciting. Security conversation is top notch right now. It's an all time high. You can't go with anywhere without talking about security. And specifically in the code, we were talking before we came on camera, the software supply chain is real. It's not just about verification. Where do you guys see the challenges right now? Containers having, even scanning them is not good enough. First of all, you got to scan them and that may not be good enough. Where's the security challenges and where's the opportunity? >> I think a little bit of it is a new way of thinking. The speed of security is actually does make you secure. We want to keep our images up and fresh and updated and we also want to make sure that we're keeping the open source and the different images that we're bringing in secure. Doron, I know you have some things to say about that too. He's been working tirelessly on the cloud service. >> Yeah, I think that one thing, you need to trust your sources. Even if in the open source world, you don't want to copy paste libraries from the web. And most of our customers using third party vendors and getting images from different location, we need to trust our sources and we have a really good, even if you have really good scanning solution, you not always can trust it. You need to have a good solution for that. >> And you guys are having news, you're announcing the Red Hat Advanced Cluster Security Cloud Service. >> Yes. >> What is that? >> So we took StackRox and we took the opportunity to make it as a cloud services so customer can consume the product as a cloud services as a start offering and customer can buy it through for Amazon Marketplace and in the future Azure Marketplace. So customer can use it for the AKS and EKS and AKS and also of course OpenShift. So we are not specifically for OpenShift. We're not just OpenShift. We also provide support for EKS and AKS. So we provided the capability to secure the whole cloud posture. We know customer are not only OpenShift or not only EKS. We have both. We have free cloud or full cloud. So we have open. >> So it's not just OpenShift, it's Kubernetes, environments, all together. >> Doron: All together, yeah. >> Lisa: Meeting customers where they are. >> Yeah, exactly. And we focus on, we are not trying to boil the ocean or solve the whole cloud security posture. We try to solve the Kubernetes security cluster. It's very unique and very need unique solution for that. It's not just added value in our cloud security solution. We think it's something special for Kubernetes and this is what Red that is aiming to. To solve this issue. >> And the ACS platform really doesn't change at all. It's just how they're consuming it. It's a lot quicker in the cloud. Time to value is right there. As soon as you start up a Kubernetes cluster, you can get started with ACS cloud service and get going really quickly. >> I'm going to ask you guys a very simple question, but I heard it in the bar in the lobby last night. Practitioners talking and they were excited about the Red Hat opportunity. They actually asked a question, where do I go and get some free Red Hat to test some Kubernetes out and run helm or whatever. They want to play around. And do you guys have a program for someone to get start for free? >> Yeah, so the cloud service specifically, we're going to service preview. So if people sign up, they'll be able to test it out and give us feedback. That's what we're looking for. >> John: Is that a Sandbox or is that going to be in the cloud? >> They can run it in their own environment. So they can sign up. >> John: Free. >> Doron: Yeah, free. >> For the service preview. All we're asking for is for customer feedback. And I know it's actually getting busy there. It's starting December. So the quicker people are, the better. >> So my friend at the lobby I was talking to, I told you it was free. I gave you the sandbox, but check out your cloud too. >> And we also have the open source version so you can download it and use it. >> Yeah, people want to know how to get involved. I'm getting a lot more folks coming to Red Hat from the open source side that want to get their feet wet. That's been a lot of people rarely interested. That's a real testament to the product leadership. Congratulations. >> Yeah, thank you. >> So what are the key challenges that you have on your roadmap right now? You got the products out there, what's the current stake? Can you scope the adoption? Can you share where we're at? What people are doing specifically and the real challenges? >> I think one of the biggest challenges is talking with customers with a slightly, I don't want to say outdated, but an older approach to security. You hear things like malware pop up and it's like, well, really what we should be doing is keeping things into low and medium vulnerabilities, looking at the configuration, managing risk accordingly. Having disparate security tools or different teams doing various things, it's really hard to get a security picture of what's going on in the cluster. That's some of the biggest challenges that we talk with customers about. >> And in terms of resolving those challenges, you mentioned malware, we talk about ransomware. It's a household word these days. It's no longer, are we going to get hit? It's when? It's what's the severity? It's how often? How are you guys helping customers to dial down some of the risk that's inherent and only growing these days? >> Yeah, risk, it's a tough word to generalize, but our whole goal is to give you as much security information in a way that's consumable so that you can evaluate your risk, set policies, and then enforce them early on in the cluster or early on in the development pipeline so that your developers get the security information they need, hopefully asynchronously. That's the best way to do it. It's nice and quick, but yeah. I don't know if Doron you want to add to that? >> Yeah, so I think, yeah, we know that ransomware, again, it's a big world for everyone and we understand the area of the boundaries where we want to, what we want to protect. And we think it's about policies and where we enforce it. So, and if you can enforce it on, we know that as we discussed before that you can scan the image, but we never know what is in it until you really run it. So one of the thing that we we provide is runtime scanning. So you can scan and you can have policy in runtime. So enforce things in runtime. But even if one image got in a way and get to your cluster and run on somewhere, we can stop it in runtime. >> Yeah. And even with the runtime enforcement, the biggest thing we have to educate customers on is that's the last-ditch effort. We want to get these security controls as early as possible. That's where the value's going to be. So we don't want to be blocking things from getting to staging six weeks after developers have been working on a project. >> I want to get you guys thoughts on developer productivity. Had Docker CEO on earlier and since then I had a couple people messaging me. Love the vision of Docker, but Docker Hub has some legacy and it might not, has does something kind of adoption that some people think it does. Are people moving 'cause there times they want to have these their own places? No one place or maybe there is, or how do you guys see the movement of say Docker Hub to just using containers? I don't need to be Docker Hub. What's the vis-a-vis competition? >> I mean working with open source with Red Hat, you have to meet the developers where they are. If your tool isn't cutting it for developers, they're going to find a new tool and really they're the engine, the growth engine of a lot of these technologies. So again, if Docker, I don't want to speak about Docker or what they're doing specifically, but I know that they pretty much kicked off the container revolution and got this whole thing started. >> A lot of people are using your environment too. We're hearing a lot of uptake on the Red Hat side too. So, this is open source help, it all sorts stuff out in the end, like you said, but you guys are getting a lot of traction there. Can you share what's happening there? >> I think one of the biggest things from a developer experience that I've seen is the universal base image that people are using. I can speak from a security standpoint, it's awesome that you have a base image where you can make one change or one issue and it can impact a lot of different applications. That's one of the big benefits that I see in adoption. >> What are some of the business, I'm curious what some of the business outcomes are. You talked about faster time to value obviously being able to get security shifted left and from a control perspective. but what are some of the, if I'm a business, if I'm a telco or a healthcare organization or a financial organization, what are some of the top line benefits that this can bubble up to impact? >> I mean for me, with those two providers, compliance is a massive one. And just having an overall look at what's going on in your clusters, in your environments so that when audit time comes, you're prepared. You can get through that extremely quickly. And then as well, when something inevitably does happen, you can get a good image of all of like, let's say a Log4Shell happens, you know exactly what clusters are affected. The triage time is a lot quicker. Developers can get back to developing and then yeah, you can get through it. >> One thing that we see that customers compliance is huge. >> Yes. And we don't want to, the old way was that, okay, I will provision a cluster and I will do scans and find things, but I need to do for PCI DSS for example. Today the customer want to provision in advance a PCI DSS cluster. So you need to do the compliance before you provision the cluster and make all the configuration already baked for PCI DSS or HIPAA compliance or FedRAMP. And this is where we try to use our compliance, we have tools for compliance today on OpenShift and other clusters and other distribution, but you can do this in advance before you even provision the cluster. And we also have tools to enforce it after that, after your provision, but you have to do it again before and after to make it more feasible. >> Advanced cluster management and the compliance operator really help with that. That's why OpenShift Platform Plus as a bundle is so popular. Just being able to know that when a cluster gets provision, it's going to be in compliance with whatever the healthcare provider is using. And then you can automatically have ACS as well pop up so you know exactly what applications are running, you know it's in compliance. I mean that's the speed. >> You mentioned the word operator, I get triggering word now for me because operator role is changing significantly on this next wave coming because of the automation. They're operating, but they're also devs too. They're developing and composing. It's almost like a dashboard, Lego blocks. The operator's not just manually racking and stacking like the old days, I'm oversimplifying it, but the new operators running stuff, they got observability, they got coding, their servicing policy. There's a lot going on. There's a lot of knobs. Is it going to get simpler? How do you guys see the org structures changing to fill the gap on what should be a very simple, turn some knobs, operate at scale? >> Well, when StackRox originally got acquired, one of the first things we did was put ACS into an operator and it actually made the application life cycle so much easier. It was very easy in the console to go and say, Hey yeah, I want ACS my cluster, click it. It would get provisioned. New clusters would get provisioned automatically. So underneath it might get more complicated. But in terms of the application lifecycle, operators make things so much easier. >> And of course I saw, I was lucky enough with Lisa to see Project Wisdom in AnsibleFest. You going to say, Hey, Red Hat, spin up the clusters and just magically will be voice activated. Starting to see AI come in. So again, operations operator is got to dev vibe and an SRE vibe, but it's not that direct. Something's happening there. We're trying to put our finger on. What do you guys think is happening? What's the real? What's the action? What's transforming? >> That's a good question. I think in general, things just move to the developers all the time. I mean, we talk about shift left security, everything's always going that way. Developers how they're handing everything. I'm not sure exactly. Doron, do you have any thoughts on that. >> Doron, what's your reaction? You can just, it's okay, say what you want. >> So I spoke with one of our customers yesterday and they say that in the last years, we developed tons of code just to operate their infrastructure. That if developers, so five or six years ago when a developer wanted VM, it will take him a week to get a VM because they need all their approval and someone need to actually provision this VM on VMware. And today they automate all the way end-to-end and it take two minutes to get a VM for developer. So operators are becoming developers as you said, and they develop code and they make the infrastructure as code and infrastructure as operator to make it more easy for the business to run. >> And then also if you add in DataOps, AIOps, DataOps, Security Ops, that's the new IT. It seems to be the new IT is the stuff that's scaling, a lot of data's coming in, you got security. So all that's got to be brought in. How do you guys view that into the equation? >> Oh, I mean you become big generalists. I think there's a reason why those cloud security or cloud professional certificates are becoming so popular. You have to know a lot about all the different applications, be able to code it, automate it, like you said, hopefully everything as code. And then it also makes it easy for security tools to come in and look and examine where the vulnerabilities are when those things are as code. So because you're going and developing all this automation, you do become, let's say a generalist. >> We've been hearing on theCUBE here and we've been hearing the industry, burnout, associated with security professionals and some DataOps because the tsunami of data, tsunami of breaches, a lot of engineers getting called in the middle of the night. So that's not automated. So this got to get solved quickly, scaled up quickly. >> Yes. There's two part question there. I think in terms of the burnout aspect, you better send some love to your security team because they only get called when things get broken and when they're doing a great job you never hear about them. So I think that's one of the things, it's a thankless profession. From the second part, if you have the right tools in place so that when something does hit the fan and does break, then you can make an automated or a specific decision upstream to change that, then things become easy. It's when the tools aren't in place and you have desperate environments so that when a Log4Shell or something like that comes in, you're scrambling trying to figure out what clusters are where and where you're impacted. >> Point of attack, remediate fast. That seems to be the new move. >> Yeah. And you do need to know exactly what's going on in your clusters and how to remediate it quickly, how to get the most impact with one change. >> And that makes sense. The service area is expanding. More things are being pushed. So things will, whether it's a zero day vulnerability or just attack. >> Just mix, yeah. Customer automate their all of things, but it's good and bad. Some customer told us they, I think Spotify lost the whole a full zone because of one mistake of a customer because they automate everything and you make one mistake. >> It scale the failure really. >> Exactly. Scaled the failure really fast. >> That was actually few contact I think four years ago. They talked about it. It was a great learning experience. >> It worked double edge sword there. >> Yeah. So definitely we need to, again, scale automation, test automation way too, you need to hold the drills around data. >> Yeah, you have to know the impact. There's a lot of talk in the security space about what you can and can't automate. And by default when you install ACS, everything is non-enforced. You have to have an admission control. >> How are you guys seeing your customers? Obviously Red Hat's got a great customer base. How are they adopting to the managed service wave that's coming? People are liking the managed services now because they maybe have skills gap issues. So managed service is becoming a big part of the portfolio. What's your guys' take on the managed services piece? >> It's just time to value. You're developing a new application, you need to get it out there quick. If somebody, your competitor gets out there a month before you do, that's a huge market advantage. >> So you care how you got there. >> Exactly. And so we've had so much Kubernetes expertise over the last 10 or so, 10 plus year or well, Kubernetes for seven plus years at Red Hat, that why wouldn't you leverage that knowledge internally so you can get your application. >> Why change your toolchain and your workflows go faster and take advantage of the managed service because it's just about getting from point A to point B. >> Exactly. >> Well, in time to value is, you mentioned that it's not a trivial term, it's not a marketing term. There's a lot of impact that can be made. Organizations that can move faster, that can iterate faster, develop what their customers are looking for so that they have that competitive advantage. It's definitely not something that's trivial. >> Yeah. And working in marketing, whenever you get that new feature out and I can go and chat about it online, it's always awesome. You always get customers interests. >> Pushing new code, being secure. What's next for you guys? What's on the agenda? What's around the corner? We'll see a lot of Red Hat at re:Invent. Obviously your relationship with AWS as strong as a company. Multi-cloud is here. Supercloud as we've been saying. Supercloud is a thing. What's next for you guys? >> So we launch the cloud services and the idea that we will get feedback from customers. We are not going GA. We're not going to sell it for now. We want to get customers, we want to get feedback to make the product as best what we can sell and best we can give for our customers and get feedback. And when we go GA and we start selling this product, we will get the best product in the market. So this is our goal. We want to get the customer in the loop and get as much as feedback as we can. And also we working very closely with our customers, our existing customers to announce the product to add more and more features what the customer needs. It's all about supply chain. I don't like it, but we have to say, it's all about making things more automated and make things more easy for our customer to use to have security in the Kubernetes environment. >> So where can your customers go? Clearly, you've made a big impact on our viewers with your conversation today. Where are they going to be able to go to get their hands on the release? >> So you can find it on online. We have a website to sign up for this program. It's on my blog. We have a blog out there for ACS cloud services. You can just go there, sign up, and we will contact the customer. >> Yeah. And there's another way, if you ever want to get your hands on it and you can do it for free, Open Source StackRox. The product is open source completely. And I would love feedback in Slack channel. It's one of the, we also get a ton of feedback from people who aren't actually paying customers and they contribute upstream. So that's an awesome way to get started. But like you said, you go to, if you search ACS cloud service and service preview. Don't have to be a Red Hat customer. Just if you're running a CNCF compliant Kubernetes version. we'd love to hear from you. >> All open source, all out in the open. >> Yep. >> Getting it available to the customers, the non-customers, they hopefully pending customers. Guys, thank you so much for joining John and me talking about the new release, the evolution of StackRox in the last season of 18 months. Lot of good stuff here. I think you've done a great job of getting the audience excited about what you're releasing. Thank you for your time. >> Thank you. >> Thank you. >> For our guest and for John Furrier, Lisa Martin here in Detroit, KubeCon + CloudNativeCon North America. Coming to you live, we'll be back with our next guest in just a minute. (gentle music)

(cheerful music) >> Hello everyone, welcome to today's session of theCUBE's presentation of AWS Startup Showcase, New Breakthroughs in DevOps, Data Analytics, Cloud Management Tools, featuring Okera from the cloud management migration track. I'm John Furrier, your host. We've got two great special guests today, Nong Li, founder and CTO of Okera, and Sanjeev Mohan, principal @SanjMo, and former research vice president of big data and advanced analytics at Gartner. He's a legend, been around the industry for a long time, seen the big data trends from the past, present, and knows the future. Got a great lineup here. Gentlemen, thank you for this, so, life in the trenches, lessons learned across compliance, cloud migration, analytics, and use cases for Fortune 1000s. Thanks for joining us. >> Thanks for having us. >> So Sanjeev, great to see you, I know you've seen this movie, I was saying that in the open, you've at Gartner seen all the visionaries, the leaders, you know everything about this space. It's changing extremely fast, and one of the big topics right out of the gate is not just innovation, we'll get to that, that's the fun part, but it's the regulatory compliance and audit piece of it. It's keeping people up at night, and frankly if not done right, slows things down. This is a big part of the showcase here, is to solve these problems. Share us your thoughts, what's your take on this wide-ranging issue? >> So, thank you, John, for bringing this up, and I'm so happy you mentioned the fact that, there's this notion that it can slow things down. Well I have to say that the old way of doing governance slowed things down, because it was very much about control and command. But the new approach to data governance is actually in my opinion, it's liberating data. If you want to democratize or monetize, whatever you want to call it, you cannot do it 'til you know you can trust said data and it's governed in some ways, so data governance has actually become very interesting, and today if you want to talk about three different areas within compliance regulatory, for example, we all know about the EU GDPR, we know California has CCPA, and in fact California is now getting even a more stringent version called CPRA in a couple of years, which is more aligned to GDPR. That is a first area we know we need to comply to that, we don't have any way out. But then, there are other areas, there is insider trading, there is how you secure the data that comes from third parties, you know, vendors, partners, suppliers, so Nong, I'd love to hand it over to you, and see if you can maybe throw some light into how our customers are handling these use cases. >> Yeah, absolutely, and I love what you said about balancing agility and liberating, in the face of what may be seen as things that slow you down. So we work with customers across verticals with old and new regulations, so you know, you brought up GDPR. One of our clients is using this to great effect to power their ecosystem. They are a very large retail company that has operations and customers across the world, obviously the importance of GDPR, and the regulations that imposes on them are very top of mind, and at the same time, being able to do effective targeting analytics on customer information is equally critical, right? So they're exactly at that spot where they need this customer insight for powering their business, and then the regulatory concerns are extremely prevalent for them. So in the context of GDPR, you'll hear about things like consent management and right to be forgotten, right? I, as a customer of that retailer should say "I don't want my information used for this purpose," right? "Use it for this, but not this." And you can imagine at a very, very large scale, when you have a billion customers, managing that, all the data you've collected over time through all of your devices, all of your telemetry, really, really challenging. And they're leveraging Okera embedded into their analytics platform so they can do both, right? Their data scientists and analysts who need to do everything they're doing to power the business, not have to think about these kind of very granular customer filtering requirements that need to happen, and then they leverage us to do that. So that's kind of new, right, GDPR, relatively new stuff at this point, but we obviously also work with customers that have regulations from a long long time ago, right? So I think you also mentioned insider trading and that supply chain, so we'll talk to customers, and they want really data-driven decisions on their supply chain, everything about their production pipeline, right? They want to understand all of that, and of course that makes sense, whether you're the CFO, if you're going to make business decisions, you need that information readily available, and supply chains as we know get more and more and more complex, we have more and more integrated into manufacturing and other verticals. So that's your, you're a little bit stuck, right? You want to be data-driven on those supply chain analytics, but at the same time, knowing the details of all the supply chain across all of your dependencies exposes your internal team to very high blackout periods or insider trading concerns, right? For example, if you knew Apple was buying a bunch of something, that's maybe information that only a select few people can have, and the way that manifests into data policies, 'cause you need the ability to have very, very scalable, per employee kind of scalable data restriction policies, so they can do their job easier, right? If we talk about speeding things up, instead of a very complex process for them to get approved, and approved on SEC regulations, all that kind of stuff, you can now go give them access to the part of the supply chain that they need, and no more, and limit their exposure and the company's exposure and all of that kind of stuff. So one of our customers able to do this, getting two orders of magnitude, a 100x reduction in the policies to manage the system like that. >> When I hear you talking like that, I think the old days of "Oh yeah, regulatory, it kind of slows down innovation, got to go faster," pretty basic variables, not a lot of combination of things to check. Now with cloud, there seems to be combinations, Sanjeev, because how complicated has the regulatory compliance and audit environment gotten in the past few years, because I hear security in a supply chain, I hear insider threats, I mean these are security channels, not just compliance department G&A kind of functions. You're talking about large-scale, potentially combinations of access, distribution, I mean it seems complicated. How much more complicated is it now, just than it was a few years ago? >> So, you know the way I look at it is, I'm just mentioning these companies just as an example, when PayPal or Ebay, all these companies started, they started in California. Anybody who ever did business on Ebay or PayPal, guess where that data was? In the US in some data center. Today you cannot do it. Today, data residency laws are really tough, and so now these organizations have to really understand what data needs to remain where. On top of that, we now have so many regulations. You know, earlier on if you were healthcare, you needed to be HIPAA compliant, or banking PCI DSS, but today, in the cloud, you really need to know, what data I have, what sensitive data I have, how do I discover it? So that data discovery becomes really important. What roles I have, so for example, let's say I work for a bank in the US, and I decide to move to Germany. Now, the old school is that a new rule will be created for me, because of German... >> John: New email address, all these new things happen, right? >> Right, exactly. So you end up with this really, a mass of rules and... And these are all static. >> Rules and tools, oh my god. >> Yeah. So Okera actually makes a lot of this dynamic, which reduces your cloud migration overhead, and Nong used some great examples, in fact, sorry if I take just a second, without mentioning any names, there's one of the largest banks in the world is going global in the digital space for the first time, and they're taking Okera with them. So... >> But what's the point? This is my next topic in cloud migration, I want to bring this up because, complexity, when you're in that old school kind of data center, waterfall, these old rules and tools, you have to roll this out, and it's a pain in the butt for everybody, it's a hassle, huge hassle. Cloud gives the agility, we know that, and cloud's becoming more secure, and I think now people see the on-premise, certainly things that'd be on-premises for secure things, I get that, but when you start getting into agility, and you now have cloud regions, you can start being more programmatic, so I want to get you guys' thoughts on the cloud migration, how companies who are now lifting and shifting, replatforming, what's the refactoring beyond that, because you can replatform in the cloud, and still some are kind of holding back on that. Then when you're in the cloud, the ones that are winning, the companies that are winning are the ones that are refactoring in the cloud. Doing things different with new services. Sanjeev, you start. >> Yeah, so you know, in fact lot of people tell me, "You know, we are just going to lift and shift into the cloud." But you're literally using cloud as a data center. You still have all the, if I may say, junk you had on-prem, you just moved it into the cloud, and now you're paying for it. In cloud, nothing is free. Every storage, every processing, you're going to pay for it. The most successful companies are the ones that are replatforming, they are taking advantage of the platform as a service or software as a service, so that includes things like, you pay as you go, you pay for exactly the amount you use, so you scale up and scale down or scale out and scale in, pretty quickly, you know? So you're handling that demand, so without replatforming, you are not really utilizing your- >> John: It's just hosting. >> Yeah, you're just hosting. >> It's basically hosting if you're not doing anything right there. >> Right. The reason why people sometimes resist to replatform, is because there's a hidden cost that we don't really talk about, PaaS adds 3x to IaaS cost. So, some organizations that are very mature, and they have a few thousand people in the IT department, for them, they're like "No, we just want to run it in the cloud, we have the expertise, and it's cheaper for us." But in the long run, to get the most benefit, people should think of using cloud as a service. >> Nong what's your take, because you see examples of companies, I'll just call one out, Snowflake for instance, they're essentially a data warehouse in the cloud, they refactored and they replatformed, they have a competitive advantage with the scale, so they have things that others don't have, that just hosting. Or even on-premise. The new model developing where there's real advantages, and how should companies think about this when they have to manage these data lakes, and they have to manage all these new access methods, but they want to maintain that operational stability and control and growth? >> Yeah, so. No? Yeah. >> There's a few topics that are all (indistinct) this topic. (indistinct) enterprises moving to the cloud, they do this maybe for some cost savings, but a ton of it is agility, right? The motor that the business can run at is just so much faster. So we'll work with companies in the context of cloud migration for data, where they might have a data warehouse they've been using for 20 years, and building policies over that time, right? And it's taking a long time to go proof of access and those kind of things, made more sense, right? If it took you months to procure a physical infrastructure, get machines shipped to your data center, then this data access taking so long feels okay, right? That's kind of the same rate that everything is moving. In the cloud, you can spin up new infrastructure instantly, so you don't want approvals for getting policies, creating rules, all that stuff that Sanjeev was talking about, that being slow is a huge, huge problem. So this is a very common environment that we see where they're trying to do that kind of thing. And then, for replatforming, again, they've been building these roles and processes and policies for 20 years. What they don't want to do is take 20 years to go migrate all that stuff into the cloud, right? That's probably an experience nobody wants to repeat, and frankly for many of them, people who did it originally may or may not be involved in this kind of effort. So we work with a lot of companies like that, they have their, they want stability, they got to have the business running as normal, they got to get moving into the new infrastructure, doing it in a new way that, you know, with all the kind of lessons learned, so, as Sanjeev said, one of these big banks that we work with, that classical story of on-premise data warehousing, maybe a little bit of Hadoop, moved onto AWS, S3, Snowflake, that kind of setup, extremely intricate policies, but let's go reimagine how we can do this faster, right? What we like to talk about is, you're an organization, you need a design that, if you onboarded 1000 more data users, that's got to be way, way easier than the first 10 you onboarded, right? You got to get it to be easier over time, in a really, really significant way. >> Talk about the data authorization safety factor, because I can almost imagine all the intricacies of these different tools creates specialism amongst people who operate them. And each one might have their own little authorization nuance. Trend is not to have that siloed mentality. What's your take on clients that want to just "Hey, you know what? I want to have the maximum agility, but I don't want to get caught in the weeds on some of these tripwires around access and authorization." >> Yeah, absolutely, I think it's real important to get the balance of it, right? Because if you are an enterprise, or if you have diversive teams, you want them to have the ability to use tools as best of breed for their purpose, right? But you don't want to have it be so that every tool has its own access and provisioning and whatever, that's definitely going to be a security, or at least, a lot of friction for you to get things going. So we think about that really hard, I think we've seen great success with things like SSO and Okta, right? Unifying authentication. We think there's a very, very similar thing about to happen with authorization. You want that single control plane that can integrate with all the tools, and still get the best of what you need, but it's much, much easier (indistinct). >> Okta's a great example, if people don't want to build their own thing and just go with that, same with what you guys are doing. That seems to be the dots that are connecting you, Sanjeev. The ease of use, but yet the stability factor. >> Right. Yeah, because John, today I may want to bring up a SQL editor to go into Snowflake, just as an example. Tomorrow, I may want to use the Azure Bot, you know? I may not even want to go to Snowflake, I may want to go to an underlying piece of data, or I may use Power BI, you know, for some reason, and come from Azure side, so the point is that, unless we are able to control, in some sort of a centralized manner, we will not get that consistency. And security you know is all or nothing. You cannot say "Well, I secured my Snowflake, but if you come through HTFS, Hadoop, or some, you know, that is outside of my realm, or my scope," what's the point? So that is why it is really important to have a watertight way, in fact I'm using just a few examples, maybe tomorrow I decide to use a data catalog, or I use Denodo as my data virtualization and I run a query. I'm the same identity, but I'm using different tools. I may use it from home, over VPN, or I may use it from the office, so you want this kind of flexibility, all encompassed in a policy, rather than a separate rule if you do this and this, if you do that, because then you end up with literally thousands of rules. >> And it's never going to stop, either, it's like fashion, the next tool's going to come out, it's going to be cool, and people are going to want to use it, again, you don't want to have to then move the train from the compliance side this way or that way, it's a lot of hassle, right? So we have that one capability, you can bring on new things pretty quickly. Nong, am I getting it right, this is kind of like the trend, that you're going to see more and more tools and/or things that are relevant or, certain use cases that might justify it, but yet, AppSec review, compliance review, I mean, good luck with that, right? >> Yeah, absolutely, I mean we certainly expect tools to continue to get more and more diverse, and better, right? Most innovation in the data space, and I think we... This is a great time for that, a lot of things that need to happen, and so on and so forth. So I think one of the early goals of the company, when we were just brainstorming, is we don't want data teams to not be able to use the tools because it doesn't have the right security (indistinct), right? Often those tools may not be focused on that particular area. They're great at what they do, but we want to make sure they're enabled, they do some enterprise investments, they see broader adoption much easier. A lot of those things. >> And I can hear the sirens in the background, that's someone who's not using your platform, they need some help there. But that's the case, I mean if you don't get this right, there are some consequences, and I think one of the things I would like to bring up on next track is, to talk through with you guys is, the persona pigeonhole role, "Oh yeah, a data person, the developer, the DevOps, the SRE," you start to see now, developers and with cloud developers, and data folks, people, however they get pigeonholed, kind of blending in, okay? You got data services, you got analytics, you got data scientists, you got more democratization, all these things are being kicked around, but the notion of a developer now is a data developer, because cloud is about DevOps, data is now a big part of it, it's not just some department, it's actually blending in. Just a cultural shift, can you guys share your thoughts on this trend of data people versus developers now becoming kind of one, do you guys see this happening, and if so, how? >> So when, John, I started my career, I was a DBA, and then a data architect. Today, I think you cannot have a DBA who's not a developer. That's just my opinion. Because there is so much of CICD, DevOps, that happens today, and you know, you write your code in Python, you put it in version control, you deploy using Jenkins, you roll back if there's a problem. And then, you are interacting, you're building your data to be consumed as a service. People in the past, you would have a thick client that would connect to the database over TCP/IP. Today, people don't want to connect over TCP/IP necessarily, they want to go by HTTP. And they want an API gateway in the middle. So, if you're a data architect or DBA, now you have to worry about, "I have a REST API call that's coming in, how am I going to secure that, and make sure that people are allowed to see that?" And that was just yesterday. >> Exactly. Got to build an abstraction layer. You got to build an abstraction layer. The old days, you have to worry about schema, and do all that, it was hard work back then, but now, it's much different. You got serverless, functions are going to show way... It's happening. >> Correct, GraphQL, and semantic layer, that just blows me away because, it used to be, it was all in database, then we took it out of database and we put it in a BI tool. So we said, like BusinessObjects started this whole trend. So we're like "Let's put the semantic layer there," well okay, great, but that was when everything was surrounding BusinessObjects and Oracle Database, or some other database, but today what if somebody brings Power BI or Tableau or Qlik, you know? Now you don't have a semantic layer access. So you cannot have it in the BI layer, so you move it down to its own layer. So now you've got a semantic layer, then where do you store your metrics? Same story repeats, you have a metrics layer, then the data centers want to do feature engineering, where do you store your features? You have a feature store. And before you know, this stack has disaggregated over and over and over, and then you've got layers and layers of specialization that are happening, there's query accelerators like Dremio or Trino, so you've got your data here, which Nong is trying really hard to protect, and then you've got layers and layers and layers of abstraction, and networks are fast, so the end user gets great service, but it's a nightmare for architects to bring all these things together. >> How do you tame the complexity? What's the bottom line? >> Nong? >> Yeah, so, I think... So there's a few things you need to do, right? So, we need to re-think how we express security permanence, right? I think you guys have just maybe in passing (indistinct) talked about creating all these rules and all that kind of stuff, that's been the way we've done things forever. We get to think about policies and mechanisms that are much more dynamic, right? You need to really think about not having to do any additional work, for the new things you add to the system. That's really, really core to solving the complexity problem, right? 'Cause that gets you those orders of magnitude reduction, system's got to be more expressive and map to those policies. That's one. And then second, it's got to be implemented at the right layer, right, to Sanjeev's point, close to the data, and it can service all of those applications and use cases at the same time, and have that uniformity and breadth of support. So those two things have to happen. >> Love this universal data authorization vision that you guys have. Super impressive, we had a CUBE Conversation earlier with Nick Halsey, who's a veteran in the industry, and he likes it. That's a good sign, 'cause he's seen a lot of stuff, too, Sanjeev, like yourself. This is a new thing, you're seeing compliance being addressed, and with programmatic, I'm imagining there's going to be bots someday, very quickly with AI that's going to scale that up, so they kind of don't get in the innovation way, they can still get what they need, and enable innovation. You've got cloud migration, which is only going faster and faster. Nong, you mentioned speed, that's what CloudOps is all about, developers want speed, not things in days or hours, they want it in minutes and seconds. And then finally, ultimately, how's it scale up, how does it scale up for the people operating and/or programming? These are three major pieces. What happens next? Where do we go from here, what's, the customer's sitting there saying "I need help, I need trust, I need scale, I need security." >> So, I just wrote a blog, if I may diverge a bit, on data observability. And you know, so there are a lot of these little topics that are critical, DataOps is one of them, so to me data observability is really having a transparent view of, what is the state of your data in the pipeline, anywhere in the pipeline? So you know, when we talk to these large banks, these banks have like 1000, over 1000 data pipelines working every night, because they've got that hundred, 200 data sources from which they're bringing data in. Then they're doing all kinds of data integration, they have, you know, we talked about Python or Informatica, or whatever data integration, data transformation product you're using, so you're combining this data, writing it into an analytical data store, something's going to break. So, to me, data observability becomes a very critical thing, because it shows me something broke, walk me down the pipeline, so I know where it broke. Maybe the data drifted. And I know Okera does a lot of work in data drift, you know? So this is... Nong, jump in any time, because I know we have use cases for that. >> Nong, before you get in there, I just want to highlight a quick point. I think you're onto something there, Sanjeev, because we've been reporting, and we believe, that data workflows is intellectual property. And has to be protected. Nong, go ahead, your thoughts, go ahead. >> Yeah, I mean, the observability thing is critically important. I would say when you want to think about what's next, I think it's really effectively bridging tools and processes and systems and teams that are focused on data production, with the data analysts, data scientists, that are focused on data consumption, right? I think bridging those two, which cover a lot of the topics we talked about, that's kind of where security almost meets, that's kind of where you got to draw it. I think for observability and pipelines and data movement, understanding that is essential. And I think broadly, on all of these topics, where all of us can be better, is if we're able to close the loop, get the feedback loop of success. So data drift is an example of the loop rarely being closed. It drifts upstream, and downstream users can take forever to figure out what's going on. And we'll have similar examples related to buy-ins, or data quality, all those kind of things, so I think that's really a problem that a lot of us should think about. How do we make sure that loop is closed as quickly as possible? >> Great insight. Quick aside, as the founder CTO, how's life going for you, you feel good? I mean, you started a company, doing great, it's not drifting, it's right in the stream, mainstream, right in the wheelhouse of where the trends are, you guys have a really crosshairs on the real issues, how you feeling, tell us a little bit about how you see the vision. >> Yeah, I obviously feel really good, I mean we started the company a little over five years ago, there are kind of a few things that we bet would happen, and I think those things were out of our control, I don't think we would've predicted GDPR security and those kind of things being as prominent as they are. Those things have really matured, probably as best as we could've hoped, so that feels awesome. Yeah, (indistinct) really expanded in these years, and it feels good. Feels like we're in the right spot. >> Yeah, it's great, data's competitive advantage, and certainly has a lot of issues. It could be a blocker if not done properly, and you're doing great work. Congratulations on your company. Sanjeev, thanks for kind of being my cohost in this segment, great to have you on, been following your work, and you continue to unpack it at your new place that you started. SanjMo, good to see your Twitter handle taking on the name of your new firm, congratulations. Thanks for coming on. >> Thank you so much, such a pleasure. >> Appreciate it. Okay, I'm John Furrier with theCUBE, you're watching today's session presentation of AWS Startup Showcase, featuring Okera, a hot startup, check 'em out, great solution, with a really great concept. Thanks for watching. (calm music)

(upbeat music) >> Hello and welcome today's session of the cube presentation of the 80 best startup showcase. The next big thing in security featuring Anitian for the security track. I'm your host John Furrier. We're here with the CEO of Anitian, Rakesh Narasimhan, and Aditya Muppavarapu global segment leader of Dev ops for 80 minutes partner network, Rakesh, Aditya, Thanks for coming on. Appreciate it. >> Thank you very much, John. Pleasure is mine. >> So this is the track session. We're going to get into the, the into the details on the leadership of digital transformation and dev sec ops automation, cloud security and compliance. So let's get started. But first Rakesh, we last talked you guys had some awards, RSA conference, 2021, virtual. You guys got some serious awards. Give us the update. >> Yeah, thank you very much, John. Yeah, we were, you know, humbled to be recognized. You know, industry recognition is always a great thing. We deliver value for customers and the industry is recognizing it. So at the RSA conference, we got seven different awards you know, very excited that we were chosen for, you know publishers choice and security company of the year editor's choice and blood security and heart company in cloud security automation. So really thrilled about the recognition thanks. >> Awesome. Seven awards. I mean, RSA is obviously a show that's in transition itself. They're transforming no longer part of Dell technologies now kind of on their own kind of speaks to the wave we're in. So congratulations on the success. They're hot startup here in security track. Give us a quick overview what you guys are enabling because this transformation is everywhere. It's in every sector, it's in every vertical dev sec ops shifting left, you know day two operations get ops. All. This is all talking to one thing, developer, productivity programmable infrastructure with security. Rakesh give us a quick overview of >> Yeah. Exactly. Right. John, I think there's a big shift happening obviously to the cloud and, you know, affects every one of our lives in productivity in enterprise applications, consumers you name it. There's a huge change happening, but central to that theme is security. And so it's one of the areas we focus on Anitian is the fastest way for both existing and new applications to be developed in the cloud. And so we make sure that you can get there fastest time to value and time to revenue pretty quickly by providing the best secure and compliance environment for you. That's really the core of what we do as a company. And we look forward to helping all of our customers and the industry >> Aditya you're a global segment lead at AWS partner network. You seeing on successful companies, you've got a winner here, obviously a success story. I want to get your take on this because this is a trend in cloud native scale, you know, heart, you know horizontally scalable, large scale, but shifting left, okay. Get ops big topics where code is being inspected in real time. People want automation. So I've got to ask you, what does shift left mean to to being out there and this in the security world? What does that mean? >> So, instead of applying your security and compliance guard rails only in production, we also need to apply them across your application development and delivery cycles. Instead of having one gate that becomes a bottleneck we should have multiple checkpoints at various stages. This provides a fast feedback for the developers while they're still in the context of developing that feature. So it's easier and less expensive fix the issues and what it is not is this doesn't mean you move all your focus to dev and ignore production. It also doesn't mean developers are now responsible for security and you can get rid of your security teams. We needed a process and a mechanism in place to leverage the expertise off the security teams and offer their services to the developers very early on in the development cycles, thereby enabling and empowering developers to write secure and compliant code >> I mean, to me not to put my old school hat on, but it's, you know I think to me, I view it as security at the point of coding right at the point of, I don't want to say point of sale but the point of writing the code and the old days it used to be like a patches and getting updates and provisioned into, into production. Same that kind of concept. But as a developer, that's kind of the focus is getting the latest knowledge either through tools and technologies to make it easier for me as a developer to inject at the point of code. Is that right? >> That's right. Yeah. >> So what makes Anitian so different and what's successful within AWS? That's, what's the why the success there? Can you share with us why they're so unique in AWS? >> So I think the biggest case for that is really you know, security, oftentimes security is thought of as an impediment sometimes actually believe it or not. So the configuration, the management, the deployment all of that, you got to be able to do and you got to be able to do that at scale. The great thing about the cloud at is scale and a big portion of that is automation. So what we at Anitian have done is taken that lifecycle of taking, you know applications on a variety of states. If you will, if you're trying to get to production you're trying to do one of two things. You're either you're trying to get into a compliance standard, like Fed Ramp you want a very predictable process, or you're just trying to get an application secure pretty quickly. So how can you do either one of those things becomes the challenge and we help you do that by having a pre-engineered environment where configuration defining deployment all that becomes very consistent and very predictable which means we've automated it in a way that it can scale. You can sort of almost have this regularly happening and not just one application with multiple applications for any company. That is, I think the biggest obstacle that has happened for a lot of folks in the enterprise for sure, to try to get to production and keep that cycle going continuously. And we help with that in a big way. That's one of the reasons why we're having a lot of adoption customers working with partners of course and getting industry recognition for it. >> Yeah. I mean, this is one of the benefits of cloud. I want to get you guys both reaction to this, where as things get going, it's kind of like that, you're you you got to take advantage. You can take advantage of all these solutions. So how many of his customer, I want to look for solutions that help me move the ball forward, not backwards right? So, or help me move the ball forward without building anything that I don't need or that's already been built. So here it sounds like if I get this right Anitian is saying, Hey if you're an Amazon customer I can accelerate you with Fed Ramp compliance. So you don't have to spend all these cycle times getting ready or hiring or operationalizing it is that right? I mean, is that the value proposition? >> They're very accurate, John. So what happens is, you know, we're working with Amazon web services, who's really innovated quite a bit in building all the building blocks, if you will. And so, you know, we're standing on the shoulders of giants if you will, to basically get the max level of automation and acceleration happen. So that just like customers have gotten used to not having to buy servers, but guide, compute and storage. If you will, now they're able to secure and also become compliant with the services that we offer. That level of acceleration I think is needed. If you believe that there's going to be a lot more cloud applications, lot more cloud. If you're going to achieve scale, you've got to automate. And if you want to automate, but secure as well you need a mechanism to doing that. That's really where Anitian comes in, if you will. >> Yeah. And I think Fedramp to me is just a great low hanging fruit example because everyone wants to get into the public sector market. They know how hard it is. Kind of like, you know, we want to do it, but stand in line we've got to get some resources. I'm not kind of get that. But the question I want to get to you Rakesh and Aditya is the bigger picture, which is, as you said more cloud applications are coming. So customers in the enterprise have, have or are building fast dev ops teams accelerate the security paradigm. How do you help those, those folks? Because that's really kind of where the action's going. The puck is going to go there too. Right? So beyond Fed Ramp there's other things >> Right? So I think, I think the way we approached it is really, there's like at least two different sets of customers, right? In the federal market itself. You just think about a commercial SAS companies who are trying to enter the, the, the, the the public sector market. Well, you need to clear a standard like Fed Ramp. So we're the fastest way to not just complete it but be able to start selling and producing revenue. That'd be market per using that functionality. If you will, to that market. Similarly, there's a lot of public sector organizations who are trying to move to the cloud because they have traditionally developed applications and architectures based on what they've done over the last 20 plus years. Well guess what, they're also trying to migrate. So how do you help both commercial companies as well as public sector companies transition, if you will to the cloud in a secure way, but also meeting a public standard. We're helping both those organizations to do that migration and that journey if you will, but it's premised on with pre-engineered it, it's the fastest way for you to get there for you to be able to provide your capability and functionality to the larger marketplace. That's one of the main reasons why I think the productivity jump is enormously high because that's how you get to larger marketplace, if you will, to serve that market >> Aditya. So they have to change your title from global segment leader, dev ops to dev sec ops 80 of his partner network here with this solution in a way it's kind of becoming standard. >> Yeah. Security is getting him embedded into all of your development and delivery life cycle. So that dev sec Ops is becoming more and more critical with customers migrating to the cloud and modernizing their applications. >> How much has automation playing into this? Because one of the things we're talking about fueling digital transformation is the automation component of the security piece here Rakesh How important is automation and what how do you set yourself up for that to be successful? >> That's big question. I think that the big key to that is automation. I think automation is there in general in the cloud space. People expect it, frankly. But I think that the key thing what we have done is pre-integrated not just our platform but a variety of the partner ecosystem are on AWS. And so when a customer is looking forward to taking an application and going to the cloud they're not just getting functionality from us and AWS but also a lot of partner functionality around it so that they don't have to build it. Remember this discussion we had earlier about how do you jumpstart that? Well, it's, it's, it's really, instead of them having the best of breed assemble we've pre done it for them, which means it's predictable, it's consistent it's configured correctly. They can rely on it. That allows us to be able to help them move faster which means they can go serve larger markets and obviously make money around it. >> Rakesh, I got to follow up on that and ask you specifically around this business model. Obviously cloud has become great service. Everyone kind of knows that and then kind of sees the edge coming next and all these other issues that are going to provide more opportunities. But I got to ask you for your company what industries and business models are you disrupting? >> Yeah, I think primarily to we're a classic example of software eating the world, right? Primarily what happens is most of the folks that certainly in the compliance arena are really trying to figure out how to do it themselves, right? And then that's primarily the group of people who are sort of trying to figure that out. And then there's a class of who do consulting who are trying to consult with you and what you should do. And we have taken a very software oriented approach built on Amazon that we will not only help you fast forward that but also, you know, get you compliant but also keep you compliant because it's a cycle much like in other industries you've seen there used to be a time when people that email and they used to run email servers and ran the email servers and backups and things of that nature that transitioned over time where people procure that service from somebody else. And it's still a secure, it's still a scalable and they can rely on that service without having to be in that business if you will. So we see us disrupting the consulting and do it yourself world to actually providing a dependable service out there that you can rely on for security and compliance. >> Awesome. Aditya, I got to ask you on the Amazon side obviously you see a lot of it there. What are some of the challenges that you see with security? >> One of the main challenges I see that is that the landscape itself is rapidly changing. As customers are migrating to the cloud and modernizing what used to be a simple monolithic application running on a server and a office or a data center is now distributed hybrid and spans across development practices like microservices managed services, packaged applications, et cetera and also in the infrastructure platform choices have dramatically increased to from on-prem to call data centers, to edge computing, IOT VMs containers, serverless a lot more options. All these leads to more complexity and it increased the number of threat vectors exponentially though this advancement was great from a usability perspective. It now created a whole slew of challenges. This, this is complex. It's very hard to keep up. It's not something you set and forget. One needs to make sure you have the right guardrails in place to make sure you're continuously compliant with with your own policies are also with regulatory compliance frameworks that are needed for your business. Like GDPR, PCI, DSS, Nast, HIPAA Sox, Fed Ramp, et cetera >> For Rakesh. We're specifically on the dev ops efficiency with Amazon. What do you guys, what's your top few value proposition points? You say >> Biggest value proposition honestly is keeping and maintaining security while you're in compliance at scale with speed. I think those are big issues for companies. Like if you, if you're a company you're trying to be in the cloud, you want to enter the federal market. For example, you got to get that quickly. So what could take a lot of money? 18 - 24 months, our prawn malleable we've just completely automated back. And so within a quarter, depending on quickly the two organizations can work. We can get you into the marketplace. That that speed is of enormous value to companies. But also to remember that as Aditya pointed out there's a lot of complexity in the kind of architecture that is evolved but we have to feel like people like in the issue of what we can help customers would is as much as you take advantage of all the cloud style architecture providing the simplicity of providing security consistently and providing compliance consistently quickly. I think there'll always be a value for that because people are always trying to get faster and cheaper quicker. And I think we're able to do that. But remember, security is not just about fast. It's got to be secure, right? We got to be effective, not just efficient but I think that's a big value prop that we're able to bring to the table on AWS. >> Well I want to go, I got you here. I'll see what showcasing you guys as the hot startup who is your customer on Amazon? I'll see, you have customers that sell in marketplace for fedramp. That's a huge, that's the people who are in business to sell software but also other enterprises as well. Right? So could you just quickly break down your customers? And then when do they know it's time to call a Anitian? >> Yeah, so we have two large groups of customers. If you will. Certainly the commercial segment, as well as in the public sector and the commercial side, you have lots of companies in the cyber security enterprise collaboration as a little robotic process automation, all those categories of companies in the commercial environment they're trying to enter the public sector federal market to go sell their services. Well, you have to get compliant. We are the fastest path to get you there time to value type of revenue we can accomplish for you. That's a group of customers we, we have in market. And then we have the other side, which is a lot of government agencies who are themselves trying to migrate to the cloud. So if you're trying to get your applications for sure once on hybrid or on-premise, and you're trying to go to the AWS cloud, well, we're a great way for you to have a pre-engineered environment into which you can move in. So not only are you secure it's, pre-built, it can scale to the cloud that you're in front of migrate to. So we have both those particular sites if you will, of the marketplace. And then in market, we have lots of agencies, big and small and the government side, but also all these categories in the commercial side that I mentioned >> For Rakesh, Anitian's helping a lot of companies sell them to the public sector market. How big is the public sector federal market >> Right? Yeah. Billions of dollars. More than $250 billion is what people say but it's a very large market, but, but remember it's any any commercial SAS company who's trying to go into that federal market is a target market. We can help that customer get in into that market. >> And just real quick, their choice alternative to not working with the Anitian is what? months the pain. And what's the heavy lift as Andy Jassy would say the heavy lifting, undifferentiated lifting a lot of paperwork, a lot of hoops to jump through. Good. Can you just paint a picture of the paths with, and without >> There's three key areas that I think customers or, you know companies have to do, A. they have to understand the standard B. They have to really figure out the technology the integration, the partners, and the platform itself. It's a lift to basically get all of that together and then actually produce the documentation produce all the configuration and in a repeatable way. And that's just to get one application up there. Well, guess what? Not only do you need to get that up there you need to keep that compliant. And then our future standards come in. You need to go upgrade to that. So the best way for me to describe that is either you you come to the Anitian and we make that age just a service that is subscribed to to keep you compliant and grow or you can try to build it yourself, or you try to go get consulting companies to tell you what to do. You still have to do the work. So those are your sort of choices, if you will, which is one of the reasons why we're enjoying the growth we are because we're making it easy and productive for for companies to get there faster. >> Aditya, I want to get to you real quick. Obviously AWS partnering, they're also known as APN. You guys see some of the best hot startups. They all kind of have the same pattern like this. They do something that's hard. They make it easier. They go faster, more. Cost-effective what's the pattern in this cloud-scale world as startups. We're going to be featuring, you know, every as much as we can hot startups coming out of your network, there's a pattern here. What would you say? They are? Well as the DevOps obviously cloud native, besides iterate, move faster. What's the pattern you're seeing for the successful companies. >> It's like, like Andy's says, it's figuring out how to continuously reinvent yourself is the key to stay successful in this market. >> Awesome. For Rakesh, real big success. Congratulations on your awards. I got to ask you, we're asking all the, all the companies this question, what is your defining contribution to the future of cloud scale? >> Great question. I think when I think about what can be accomplished in the future, not just in the past, I think cloud is a huge phenomenon that has completely up-ended the architecture for all sorts of things commercial government, you know, consumer and enterprise. If you will, I would think we would be humbly the people who will ensure that lots of B2B companies and government organizations are able to move to the cloud and are able to be secure and compliant because I believe that there'll be more and more of that happening in the cloud. And the more that is available, just like the commercial world is takes advantage of all those features. I feel like public government organizations also can accomplish the same things very quickly because of folks like us, which means you have a larger segment of population that you can support. That's only going to make the planet more successful. I'm a big optimist when it comes to tech. I know there's a lot of folks who would look down upon tech or I'll think about it as not great. I'm a very big optimist around tech improving people's lives. And I think we have our own humble role in enabling that to happen in the security and compliance >> Well, anything, in my opinion I'm really a big fan of your work and your team. Anything that could bring great innovation into the public sector faster and more effective as good win for society. So I think it's a great mission. Thanks for, for sharing and congratulations on your awards and thanks for being part of our 80 best startup showcase. Appreciate it Rakesh thank you >> Thank you. >> Okay. This is the cube coverage of 80 startup showcase. I'm John for your host of the cube. This is the next big thing in security Anitian in the security track. Thanks for watching. (Up beat music)

>> Hello. My name is Ron Kafka, and I'm the senior director for Partner Scale Initiatives for HBE Ezmeral. Thanks for joining us today at Analytics Unleashed. By now, you've heard a lot about the Ezmeral portfolio and how it can help you accomplish objectives around big data analytics and containerization. I want to shift gears a bit and then discuss our Ezmeral Technology Partner Program. I've got two great guest speakers here with me today. And together, We're going to discuss how jointly we are solving data analytic challenges for our customers. Before I introduce them, I want to take a minute to talk to provide a little bit more insight into our ecosystem program. We've created a program with a realization based on customer feedback that even the most mature organizations are struggling with their data-driven transformation efforts. It turns out this is largely due to the pace of innovation with application vendors or ICS supporting data science and advanced analytic workloads. Their advancements are simply outpacing organization's ability to move workloads into production rapidly. Bottom line, organizations want a unified experience across environments where their entire application portfolio in essence provide a comprehensive application stack and not piece parts. So, let's talk about how our ecosystem program helps solve for this. For starters, we were leveraging HPEs long track record of forging technology partnerships and it created a best in class ISB partner program specific for the Ezmeral portfolio. We were doing this by developing an open concept marketplace where customers and partners can explore, learn, engage and collaborate with our strategic technology partners. This enables our customers to adopt, deploy validated applications from industry leading software vendors on HPE Ezmeral with a high degree of confidence. Also, it provides a very deep bench of leading ISVs for other groups inside of HPE to leverage for their solutioning efforts. Speaking of industry leading ISV, it's about time and introduce you to two of those industry leaders right now. Let me welcome Daniel Hladky from Dataiku, and Omri Geller from Run:AI. So I'd like to introduce Daniel Hladky. Daniel is with Dataiku. He's a great partner for HPE. Daniel, welcome. >> Thank you for having me here. >> That's great. Hey, would you mind just talking a bit about how your partnership journey has been with HPE? >> Yes, pleasure. So the journey started about five years ago and in 2018 we signed a worldwide reseller agreement with HPE. And in 2020, we actually started to work jointly on the integration between the Dataiku Data Science Studio called DSS and integrated that with the Ezmeral Container platform, and was a great success. And it was on behalf of some clear customer projects. >> It's been a long partnership journey with you for sure with HPE. And we welcome your partnership extremely well. Just a brief question about the Container Platform and really what that's meant for Dataiku. >> Yes, Ron. Thanks. So, basically I'd like the quote here Florian Douetteau, which is the CEO of Dataiku, who said that the combination of Dataiku with the HPE Ezmeral Container Platform will help the customers to successfully scale and put machine learning projects into production. And this basically is going to deliver real impact for their business. So, the combination of the two of us is a great success. >> That's great. Can you talk about what Dataiku is doing and how HPE Ezmeral Container Platform fits in a solution offering a bit more? >> Great. So basically Dataiku DSS is our product which is a end to end data science platform, and basically brings value to the project of customers on their past enterprise AI. In simple ways, we can say it could be as simple as building data pipelines, but it could be also very complex by having machine and deep learning models at scale. So the fast track to value is by having collaboration, orchestration online technologies and the models in production. So, all of that is part of the Data Science Studio and Ezmeral fits perfectly into the part where we design and then basically put at scale those project and put it into product. >> That's perfect. Can you be a bit more specific about how you see HPE and Dataiku really tightening up a customer outcome and value proposition? >> Yes. So what we see is also the challenge of the market that probably about 80% of the use cases really never make it to production. And this is of course a big challenge and we need to change that. And I think the combination of the two of us is actually addressing exactly this need. What we can say is part of the MLOps approach, Dataiku and the Ezmeral Container Platform will provide a frictionless approach, which means without scripting and coding, customers can put all those projects into the productive environment and don't have to worry any more and be more business oriented. >> That's great. So you mentioned you're seeing customers be a lot more mature with their AI workloads and deployment. What do you suggest for the other customers out there that are just starting this journey or just thinking about how to get started? >> Yeah. That's a very good question, Ron. So what we see there is actually the challenge that people need to go on a pass of maturity. And this starts with a simple data pipelines, et cetera, and then basically move up the ladder and basically build large complex project. And here I see a very interesting offer coming now from HPE which is called D3S, which is the data science startup pack. That's something I discussed together with HPE back in early 2020. And basically, it solves the three stages, which is explore, experiment and evolve and builds quickly MVPs for the customers. By doing so, basically you addressed business objectives, lay out in the proper architecture and also setting up the proper organization around it. So, this is a great combination by HPE and Dataiku through the D3S. >> And it's a perfect example of what I mentioned earlier about leveraging the ecosystem program that we built to do deeper solutioning efforts inside of HPE in this case with our AI business unit. So, congratulations on that and thanks for joining us today. I'm going to shift gears. I'm going to bring in Omri Geller from Run:AI. Omri, welcome. It's great to have you. You guys are killing it out there in the market today. And I just thought we could spend a few minutes talking about what is so unique and differentiated from your offerings. >> Thank you, Ron. It's a pleasure to be here. Run:AI creates a virtualization and orchestration layer for AI infrastructure. We help organizations to gain visibility and control over their GPO resources and help them deliver AI solutions to market faster. And we do that by managing granular scheduling, prioritization, allocation of compute power, together with the HPE Ezmeral Container Platform. >> That's great. And your partnership with HPE is a bit newer than Daniel's, right? Maybe about the last year or so we've been working together a lot more closely. Can you just talk about the HPE partnership, what it's meant for you and how do you see it impacting your business? >> Sure. First of all, Run:AI is excited to partner with HPE Ezmeral Container Platform and help customers manage appeals for their AI workloads. We chose HPE since HPE has years of experience partnering with AI use cases and outcomes with vendors who have strong footprint in this markets. HPE works with many partners that are complimentary for our use case such as Nvidia, and HPE Container Platform together with Run:AI and Nvidia deliver a world class solutions for AI accelerated workloads. And as you can understand, for AI speed is critical. Companies want to gather important AI initiatives into production as soon as they can. And the HPE Ezmeral Container Platform, running IGP orchestration solution enables that by enabling dynamic provisioning of GPU so that resources can be easily shared, efficiently orchestrated and optimal used. >> That's great. And you talked a lot about the efficiency of the solution. What about from a customer perspective? What is the real benefit that our customers are going to be able to gain from an HPE and Run:AI offering? >> So first, it is important to understand how data scientists and AI researchers actually build solution. They do it by running experiments. And if a data scientist is able to run more experiments per given time, they will get to the solution faster. With HPE Ezmeral Container Platform, Run:AI and users such as data scientists can actually do that and seamlessly and efficiently consume large amounts of GPU resources, run more experiments or given time and therefore accelerate their research. Together, we actually saw a customer that is running almost 7,000 jobs in parallel over GPUs with efficient utilization of those GPUs. And by running more experiments, those customers can be much more effective and efficient when it comes to bringing solutions to market >> Couldn't agree more. And I think we're starting to see a lot of joint success together as we go out and talk to the story. Hey, I want to thank you both one last time for being here with me today. It was very enlightening for our team to have you as part of the program. And I'm excited to extend this customer value proposition out to the rest of our communities. With that, I'd like to close today's session. I appreciate everyone's time. And keep an eye out on our ISP marketplace for Ezmeral We're continuing to expand and add new capabilities and new partners to our marketplace. We're excited to do a lot of great things and help you guys all be successful. Thanks for joining. >> Thank you, Ron. >> What a great panel discussion. And these partners they really do have a good understanding of the possibilities, working on the platform, and I hope and expect we'll see this ecosystem continue to grow. That concludes the main program, which means you can now pick one of three live demos to attend and chat live with experts. Now those three include day in the life of IT Admin, day in the life of a data scientist, and even a day in the life of the HPE Ezmeral Data Fabric, where you can see the many ways the data fabric is used in your life today. Wish you could attend all three, no worries. The recordings will be available on demand for you and your teams. Moreover, the show doesn't stop here, HPE has a growing and thriving tech community, you should check it out. It's really a solid starting point for learning more, talking to smart people about great ideas and seeing how Ezmeral can be part of your own data journey. Again, thanks very much to all of you for joining, until next time, keep unleashing the power of your data.

>> Hello. My name is Ron Kafka, and I'm the senior director for Partner Scale Initiatives for HBE Ezmeral. Thanks for joining us today at Analytics Unleashed. By now, you've heard a lot about the Ezmeral portfolio and how it can help you accomplish objectives around big data analytics and containerization. I want to shift gears a bit and then discuss our Ezmeral Technology Partner Program. I've got two great guest speakers here with me today. And together, We're going to discuss how jointly we are solving data analytic challenges for our customers. Before I introduce them, I want to take a minute to talk to provide a little bit more insight into our ecosystem program. We've created a program with a realization based on customer feedback that even the most mature organizations are struggling with their data-driven transformation efforts. It turns out this is largely due to the pace of innovation with application vendors or ICS supporting data science and advanced analytic workloads. Their advancements are simply outpacing organization's ability to move workloads into production rapidly. Bottom line, organizations want a unified experience across environments where their entire application portfolio in essence provide a comprehensive application stack and not piece parts. So, let's talk about how our ecosystem program helps solve for this. For starters, we were leveraging HPEs long track record of forging technology partnerships and it created a best in class ISB partner program specific for the Ezmeral portfolio. We were doing this by developing an open concept marketplace where customers and partners can explore, learn, engage and collaborate with our strategic technology partners. This enables our customers to adopt, deploy validated applications from industry leading software vendors on HPE Ezmeral with a high degree of confidence. Also, it provides a very deep bench of leading ISVs for other groups inside of HPE to leverage for their solutioning efforts. Speaking of industry leading ISV, it's about time and introduce you to two of those industry leaders right now. Let me welcome Daniel Hladky from Dataiku, and Omri Geller from Run:AI. So I'd like to introduce Daniel Hladky. Daniel is with Dataiku. He's a great partner for HPE. Daniel, welcome. >> Thank you for having me here. >> That's great. Hey, would you mind just talking a bit about how your partnership journey has been with HPE? >> Yes, pleasure. So the journey started about five years ago and in 2018 we signed a worldwide reseller agreement with HPE. And in 2020, we actually started to work jointly on the integration between the Dataiku Data Science Studio called DSS and integrated that with the Ezmeral Container platform, and was a great success. And it was on behalf of some clear customer projects. >> It's been a long partnership journey with you for sure with HPE. And we welcome your partnership extremely well. Just a brief question about the Container Platform and really what that's meant for Dataiku. >> Yes, Ron. Thanks. So, basically I like the quote here Florian Douetteau, which is the CEO of Dataiku, who said that the combination of Dataiku with the HPE Ezmeral Container Platform will help the customers to successfully scale and put machine learning projects into production. And this basically is going to deliver real impact for their business. So, the combination of the two of us is a great success. >> That's great. Can you talk about what Dataiku is doing and how HPE Ezmeral Container Platform fits in a solution offering a bit more? >> Great. So basically Dataiku DSS is our product which is a end to end data science platform, and basically brings value to the project of customers on their past enterprise AI. In simple ways, we can say it could be as simple as building data pipelines, but it could be also very complex by having machine and deep learning models at scale. So the fast track to value is by having collaboration, orchestration online technologies and the models in production. So, all of that is part of the Data Science Studio and Ezmeral fits perfectly into the part where we design and then basically put at scale those project and put it into product. >> That's perfect. Can you be a bit more specific about how you see HPE and Dataiku really tightening up a customer outcome and value proposition? >> Yes. So what we see is also the challenge of the market that probably about 80% of the use cases really never make it to production. And this is of course a big challenge and we need to change that. And I think the combination of the two of us is actually addressing exactly this need. What we can say is part of the MLOps approach, Dataiku and the Ezmeral Container Platform will provide a frictionless approach, which means without scripting and coding, customers can put all those projects into the productive environment and don't have to worry any more and be more business oriented. >> That's great. So you mentioned you're seeing customers be a lot more mature with their AI workloads and deployment. What do you suggest for the other customers out there that are just starting this journey or just thinking about how to get started? >> Yeah. That's a very good question, Ron. So what we see there is actually the challenge that people need to go on a pass of maturity. And this starts with a simple data pipelines, et cetera, and then basically move up the ladder and basically build large complex project. And here I see a very interesting offer coming now from HPE which is called D3S, which is the data science startup pack. That's something I discussed together with HPE back in early 2020. And basically, it solves the three stages, which is explore, experiment and evolve and builds quickly MVPs for the customers. By doing so, basically you addressed business objectives, lay out in the proper architecture and also setting up the proper organization around it. So, this is a great combination by HPE and Dataiku through the D3S. >> And it's a perfect example of what I mentioned earlier about leveraging the ecosystem program that we built to do deeper solutioning efforts inside of HPE in this case with our AI business unit. So, congratulations on that and thanks for joining us today. I'm going to shift gears. I'm going to bring in Omri Geller from Run:AI. Omri, welcome. It's great to have you. You guys are killing it out there in the market today. And I just thought we could spend a few minutes talking about what is so unique and differentiated from your offerings. >> Thank you, Ron. It's a pleasure to be here. Run:AI creates a virtualization and orchestration layer for AI infrastructure. We help organizations to gain visibility and control over their GPO resources and help them deliver AI solutions to market faster. And we do that by managing granular scheduling, prioritization, allocation of compute power, together with the HPE Ezmeral Container Platform. >> That's great. And your partnership with HPE is a bit newer than Daniel's, right? Maybe about the last year or so we've been working together a lot more closely. Can you just talk about the HPE partnership, what it's meant for you and how do you see it impacting your business? >> Sure. First of all, Run:AI is excited to partner with HPE Ezmeral Container Platform and help customers manage appeals for their AI workloads. We chose HPE since HPE has years of experience partnering with AI use cases and outcomes with vendors who have strong footprint in this markets. HPE works with many partners that are complimentary for our use case such as Nvidia, and HPE Ezmeral Container Platform together with Run:AI and Nvidia deliver a word about solution for AI accelerated workloads. And as you can understand, for AI speed is critical. Companies want to gather important AI initiatives into production as soon as they can. And the HPE Ezmeral Container Platform, running IGP orchestration solution enables that by enabling dynamic provisioning of GPU so that resources can be easily shared, efficiently orchestrated and optimal used. >> That's great. And you talked a lot about the efficiency of the solution. What about from a customer perspective? What is the real benefit that our customers are going to be able to gain from an HPE and Run:AI offering? >> So first, it is important to understand how data scientists and AI researchers actually build solution. They do it by running experiments. And if a data scientist is able to run more experiments per given time, they will get to the solution faster. With HPE Ezmeral Container Platform, Run:AI and users such as data scientists can actually do that and seamlessly and efficiently consume large amounts of GPU resources, run more experiments or given time and therefore accelerate their research. Together, we actually saw a customer that is running almost 7,000 jobs in parallel over GPUs with efficient utilization of those GPUs. And by running more experiments, those customers can be much more effective and efficient when it comes to bringing solutions to market >> Couldn't agree more. And I think we're starting to see a lot of joint success together as we go out and talk to the story. Hey, I want to thank you both one last time for being here with me today. It was very enlightening for our team to have you as part of the program. And I'm excited to extend this customer value proposition out to the rest of our communities. With that, I'd like to close today's session. I appreciate everyone's time. And keep an eye out on our ISP marketplace for Ezmeral We're continuing to expand and add new capabilities and new partners to our marketplace. We're excited to do a lot of great things and help you guys all be successful. Thanks for joining. >> Thank you, Ron. (bright upbeat music)

>> Announcer: From around the globe, it's theCUBE presenting Enterprise Digital Resilience on Hybrid and multicloud brought to you by io/tahoe >> Hello everyone, and welcome to our continuing series covering data automation brought to you by io/tahoe. Today we're going to look at how to ensure enterprise resilience for hybrid and multicloud, let's welcome in Ajay Vohora who's the CEO of io/tahoe Ajay, always good to see you again, thanks for coming on. >> Great to be back David, pleasure. >> And he's joined by Fadzi Ushewokunze, who is a global principal architect for financial services, the vertical of financial services at Red Hat. He's got deep experiences in that sector. Welcome Fadzi, good to see you. >> Thank you very much. Happy to be here. >> Fadzi, let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and how it works. >> Sure, Yeah. So, a hybrid cloud is an IT architecture that incorporates some degree of workload portability, orchestration and management across multiple clouds. Those clouds could be private clouds or public clouds or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand allocation of resources across clouds. And separate clouds can become hybrid when you're seamlessly interconnected. And it is that interconnectivity that allows the workloads to be moved and how management can be unified and orchestration can work. And how well you have these interconnections has a direct impact of how well your hybrid cloud will work. >> Okay, so well Fadzi, staying with you for a minute. So, in the early days of cloud that term private cloud was thrown around a lot. But it often just meant virtualization of an on-prem system and a network connection to the public cloud. Let's bring it forward. What, in your view does a modern hybrid cloud architecture look like? >> Sure, so, for modern hybrid clouds we see that teams or organizations need to focus on the portability of applications across clouds. That's very important, right. And when organizations build applications they need to build and deploy these applications as a small collections of independently loosely coupled services. And then have those things run on the same operating system, which means in other words, running it all Linux everywhere and building cloud native applications and being able to manage it and orchestrate these applications with platforms like Kubernetes or Red Hat OpenShift, for example. >> Okay, so, Fadzi that's definitely different from building a monolithic application that's fossilized and doesn't move. So, what are the challenges for customers, you know, to get to that modern cloud is as you've just described it as it skillsets, is it the ability to leverage things like containers? What's your View there? >> So, I mean, from what we've seen around the industry especially around financial services where I spend most of my time. We see that the first thing that we see is management, right. Now, because you have all these clouds, you know, all these applications. You have a massive array of connections, of interconnections. You also have massive array of integrations portability and resource allocation as well. And then orchestrating all those different moving pieces things like storage networks. Those are really difficult to manage, right? So, management is the first challenge. The second one is workload placement. Where do you place this cloud? How do you place these cloud native operations? Do you, what do you keep on site on prem and what do you put in the cloud? That is the other challenge. The major one, the third one is security. Security now becomes the key challenge and concern for most customers. And we're going to talk about how to address that. >> Yeah, we're definitely going to dig into that. Let's bring Ajay into the conversation. Ajay, you know, you and I have talked about this in the past. One of the big problems that virtually every company face is data fragmentation. Talk a little bit about how io/tahoe, unifies data across both traditional systems, legacy systems and it connects to these modern IT environments. >> Yeah, sure Dave. I mean, a Fadzi just nailed it there. It used to be about data, the volume of data and the different types of data, but as applications become more connected and interconnected the location of that data really matters. How we serve that data up to those apps. So, working with Red Hat and our partnership with Red Hat. Being able to inject our data discovery machine learning into these multiple different locations. whether it be an AWS or an IBM cloud or a GCP or on prem. Being able to automate that discovery and pulling that single view of where is all my data, then allows the CIO to manage cost. They can do things like, one, I keep the data where it is, on premise or in my Oracle cloud or in my IBM cloud and connect the application that needs to feed off that data. And the way in which we do that is machine learning that learns over time as it recognizes different types of data, applies policies to classify that data and brings it all together with automation. >> Right, and one of the big themes that we've talked about this on earlier episodes is really simplification, really abstracting a lot of that heavy lifting away. So, we can focus on things Ajay, as you just mentioned. I mean, Fadzi, one of the big challenges that of course we all talk about is governance across these disparate data sets. I'm curious as your thoughts how does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations? Which of course are particularly acute within financial services. >> Oh yeah, yes. So, for banks and payment providers like you've just mentioned there. Insurers and many other financial services firms, you know they have to adhere to a standard such as say a PCI DSS. And in Europe you've got the GDPR, which requires stringent tracking, reporting, documentation and, you know for them to, to remain in compliance. And the way we recommend our customers to address these challenges is by having an automation strategy, right. And that type of strategy can help you to improve the security on compliance of of your organization and reduce the risk out of the business, right. And we help organizations build security and compliance from the start with our consulting services, residencies. We also offer courses that help customers to understand how to address some of these challenges. And there's also, we help organizations build security into their applications with our open source middleware offerings and even using a platform like OpenShift, because it allows you to run legacy applications and also containerized applications in a unified platform. Right, and also that provides you with, you know with the automation and the tooling that you need to continuously monitor, manage and automate the systems for security and compliance purposes. >> Ajay, anything, any color you could add to this conversation? >> Yeah, I'm pleased Fadzi brought up OpenShift. I mean we're using OpenShift to be able to take that security application of controls to the data level and it's all about context. So, understanding what data is there, being able to assess it to say, who should have access to it, which application permission should be applied to it. That's a great combination of Red Hat and io/tahoe. >> Fadzi, what about multi-cloud? Doesn't that complicate the situation even further, maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi-cloud as well. >> Yeah, sure, yeah. So, the right automation solution, you know can be the difference between, you know cultivating an automated enterprise or automation carries. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So, that means have an automation solution that provides, you know, promotes IT availability and reliability with your platform so that, you can provide enterprise grade support, including security and testing integration and clear roadmaps. The second thing is vendor interoperability in that, you are going to be integrating multiple clouds. So, you're going to need a solution that can connect to multiple clouds seamlessly, right? And with that comes the challenge of maintainability. So, you're going to need to look into a automation solution that is easy to learn or has an easy learning curve. And then, the fourth idea that we tell our customers is scalability. In the hybrid cloud space, scale is the big, big deal here. And you need to deploy an automation solution that can span across the whole enterprise in a consistent manner, right. And then also that allows you finally to integrate the multiple data centers that you have. >> So, Ajay, I mean, this is a complicated situation for if a customer has to make sure things work on AWS or Azure or Google. They're going to spend all their time doing that. What can you add to really just simplify that multi-cloud and hybrid cloud equation. >> Yeah, I can give a few customer examples here. One being a manufacturer that we've worked with to drive that simplification. And the real bonuses for them has been a reduction in cost. We worked with them late last year to bring the cost spend down by $10 million in 2021. So, they could hit that reduced budget. And, what we brought to that was the ability to deploy using OpenShift templates into their different environments, whether it was on premise or in, as you mentioned, AWS. They had GCP as well for their marketing team and across those different platforms, being able to use a template, use prebuilt scripts to get up and running and catalog and discover that data within minutes. It takes away the legacy of having teams of people having to jump on workshop calls. And I know we're all on a lot of teams zoom calls. And in these current times. They're just simply using enough hours of the day to manually perform all of this. So, yeah, working with Red Hat, applying machine learning into those templates, those little recipes that we can put that automation to work regardless which location the data's in allows us to pull that unified view together. >> Great, thank you. Fadzi, I want to come back to you. So, the early days of cloud you're in the Big Apple, you know financial services really well. Cloud was like an evil word and within financial services, and obviously that's changed, it's evolved. We talk about the pandemic has even accelerated that. And when you really dug into it, when you talk to customers about their experiences with security in the cloud, it was not that it wasn't good, it was great, whatever, but it was different. And there's always this issue of skill, lack of skills and multiple tools, set up teams. are really overburdened. But in the cloud requires, you know, new thinking you've got the shared responsibility model. You've got to obviously have specific corporate, you know requirements and compliance. So, this is even more complicated when you introduce multiple clouds. So, what are the differences that you can share from your experiences running on a sort of either on prem or on a mono cloud or, you know, versus across clouds? What, do you suggest there? >> Sure, you know, because of these complexities that you have explained here mixed configurations and the inadequate change control are the top security threats. So, human error is what we want to avoid, because as you know, as your clouds grow with complexity then you put humans in the mix. Then the rate of errors is going to increase and that is going to expose you to security threats. So, this is where automation comes in, because automation will streamline and increase the consistency of your infrastructure management also application development and even security operations to improve in your protection compliance and change control. So, you want to consistently configure resources according to a pre-approved, you know, pre-approved policies and you want to proactively maintain them in a repeatable fashion over the whole life cycle. And then, you also want to rapidly the identify system that require patches and reconfiguration and automate that process of patching and reconfiguring. So that, you don't have humans doing this type of thing, And you want to be able to easily apply patches and change assistance settings according to a pre-defined base like I explained before, you know with the pre-approved policies. And also you want ease of auditing and troubleshooting, right. And from a Red Hat perspective we provide tools that enable you to do this. We have, for example a tool called Ansible that enables you to automate data center operations and security and also deployment of applications. And also OpenShift itself, it automates most of these things and obstruct the human beings from putting their fingers and causing, you know potentially introducing errors, right. Now, in looking into the new world of multiple clouds and so forth. The differences that we're seeing here between running a single cloud or on prem is three main areas, which is control, security and compliance, right. Control here, it means if you're on premise or you have one cloud you know, in most cases you have control over your data and your applications, especially if you're on prem. However, if you're in the public cloud, there is a difference that the ownership it is still yours, but your resources are running on somebody else's or the public clouds, EWS and so forth infrastructure. So, people that are going to do these need to really, especially banks and governments need to be aware of the regulatory constraints of running those applications in the public cloud. And we also help customers rationalize some of these choices. And also on security, you will see that if you're running on premises or in a single cloud you have more control, especially if you're on prem. You can control the sensitive information that you have. However, in the cloud, that's a different situation especially from personal information of employees and things like that. You need to be really careful with that. And also again, we help you rationalize some of those choices. And then, the last one is compliance. As well, you see that if you're running on prem on single cloud, regulations come into play again, right? And if you're running on prem, you have control over that. You can document everything, you have access to everything that you need, but if you're going to go to the public cloud again, you need to think about that. We have automation and we have standards that can help you you know, address some of these challenges. >> So, that's really strong insights, Fadzi. I mean, first of all Ansible has a lot of market momentum, you know, Red Hat's done a really good job with that acquisition. Your point about repeatability is critical, because you can't scale otherwise. And then, that idea you're putting forth about control, security and compliance. It's so true, I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe AWS is going to physically secure the you know, the S3, but in the bucket but we saw so many misconfigurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So, this all sounds great. Ajay, you're sharp, financial background. What about the economics? You know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. I mean, especially when you think about the work from home pivot and all the areas that they had to, the holes that they had to fill there, whether it was laptops, you know, new security models, et cetera. So, how to organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs, so I can pay it forward or there's a there's a risk reduction angle. What can you share there? >> Yeah, I mean, that perspective I'd like to give here is not being multi-cloud as multi copies of an application or data. When I think back 20 years, a lot of the work in financial services I was looking at was managing copies of data that were feeding different pipelines, different applications. Now, what we're seeing at io/tahoe a lot of the work that we're doing is reducing the number of copies of that data. So that, if I've got a product lifecycle management set of data, if I'm a manufacturer I'm just going to keep that at one location. But across my different clouds, I'm going to have best of breed applications developed in-house, third parties in collaboration with my supply chain, connecting securely to that single version of the truth. What I'm not going to do is to copy that data. So, a lot of what we're seeing now is that interconnectivity using applications built on Kubernetes that are decoupled from the data source. That allows us to reduce those copies of data within that you're gaining from a security capability and resilience, because you're not leaving yourself open to those multiple copies of data. And with that come cost of storage and a cost to compute. So, what we're saying is using multi-cloud to leverage the best of what each cloud platform has to offer. And that goes all the way to Snowflake and Heroku on a cloud managed databases too. >> Well and the people cost too as well. When you think about, yes, the copy creep. But then, you know, when something goes wrong a human has to come in and figure it out. You know, you brought up Snowflake, I get this vision of the data cloud, which is, you know data. I think we're going to be rethinking Ajay, data architectures in the coming decade where data stays where it belongs, it's distributed and you're providing access. Like you said, you're separating the data from the applications. Applications as we talked about with Fadzi, much more portable. So, it's really the last 10 years it'd be different than the next 10 years ago Ajay. >> Definitely, I think the people cost reduction is used. Gone are the days where you needed to have a dozen people governing, managing byte policies to data. A lot of that repetitive work, those tasks can be in part automated. We're seen examples in insurance where reduced teams of 15 people working in the back office, trying to apply security controls, compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDPR and CCPA. Last year, very much the economic effect to reduce head counts and enterprises running lean looking to reduce that cost. This year, we can see that already some of the more proactive companies are looking at initiatives, such as net zero emissions. How they use data to understand how they can become more, have a better social impact and using data to drive that. And that's across all of their operations and supply chain. So, those regulatory compliance issues that might have been external. We see similar patterns emerging for internal initiatives that are benefiting that environment, social impact, and of course costs. >> Great perspectives. Jeff Hammerbacher once famously said, the best minds of my generation are trying to get people to click on ads and Ajay those examples that you just gave of, you know social good and moving things forward are really critical. And I think that's where data is going to have the biggest societal impact. Okay guys, great conversation. Thanks so much for coming to the program. Really appreciate your time. >> Thank you. >> Thank you so much, Dave. >> Keep it right there, for more insight and conversation around creating a resilient digital business model. You're watching theCube. (soft music)

>> Announcer: From around the globe, it's theCUBE presenting Enterprise Digital Resilience on Hybrid and multicloud brought to you by io/tahoe >> Hello everyone, and welcome to our continuing series covering data automation brought to you by io/tahoe. Today we're going to look at how to ensure enterprise resilience for hybrid and multicloud, let's welcome in Ajay Vohora who's the CEO of io/tahoe Ajay, always good to see you again, thanks for coming on. >> Great to be back David, pleasure. >> And he's joined by Fadzi Ushewokunze, who is a global principal architect for financial services, the vertical of financial services at Red Hat. He's got deep experiences in that sector. Welcome Fadzi, good to see you. >> Thank you very much. Happy to be here. >> Fadzi, let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and how it works. >> Sure, Yeah. So, a hybrid cloud is an IT architecture that incorporates some degree of workload portability, orchestration and management across multiple clouds. Those clouds could be private clouds or public clouds or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand allocation of resources across clouds. And separate clouds can become hybrid when you're seamlessly interconnected. And it is that interconnectivity that allows the workloads to be moved and how management can be unified and orchestration can work. And how well you have these interconnections has a direct impact of how well your hybrid cloud will work. >> Okay, so well Fadzi, staying with you for a minute. So, in the early days of cloud that term private cloud was thrown around a lot. But it often just meant virtualization of an on-prem system and a network connection to the public cloud. Let's bring it forward. What, in your view does a modern hybrid cloud architecture look like? >> Sure, so, for modern hybrid clouds we see that teams or organizations need to focus on the portability of applications across clouds. That's very important, right. And when organizations build applications they need to build and deploy these applications as a small collections of independently loosely coupled services. And then have those things run on the same operating system, which means in other words, running it all Linux everywhere and building cloud native applications and being able to manage it and orchestrate these applications with platforms like Kubernetes or Red Hat OpenShift, for example. >> Okay, so, Fadzi that's definitely different from building a monolithic application that's fossilized and doesn't move. So, what are the challenges for customers, you know, to get to that modern cloud is as you've just described it as it skillsets, is it the ability to leverage things like containers? What's your View there? >> So, I mean, from what we've seen around the industry especially around financial services where I spend most of my time. We see that the first thing that we see is management, right. Now, because you have all these clouds, you know, all these applications. You have a massive array of connections, of interconnections. You also have massive array of integrations portability and resource allocation as well. And then orchestrating all those different moving pieces things like storage networks. Those are really difficult to manage, right? So, management is the first challenge. The second one is workload placement. Where do you place this cloud? How do you place these cloud native operations? Do you, what do you keep on site on prem and what do you put in the cloud? That is the other challenge. The major one, the third one is security. Security now becomes the key challenge and concern for most customers. And we're going to talk about how to address that. >> Yeah, we're definitely going to dig into that. Let's bring Ajay into the conversation. Ajay, you know, you and I have talked about this in the past. One of the big problems that virtually every company face is data fragmentation. Talk a little bit about how io/tahoe, unifies data across both traditional systems, legacy systems and it connects to these modern IT environments. >> Yeah, sure Dave. I mean, a Fadzi just nailed it there. It used to be about data, the volume of data and the different types of data, but as applications become more connected and interconnected the location of that data really matters. How we serve that data up to those apps. So, working with Red Hat and our partnership with Red Hat. Being able to inject our data discovery machine learning into these multiple different locations. whether it be an AWS or an IBM cloud or a GCP or on prem. Being able to automate that discovery and pulling that single view of where is all my data, then allows the CIO to manage cost. They can do things like, one, I keep the data where it is, on premise or in my Oracle cloud or in my IBM cloud and connect the application that needs to feed off that data. And the way in which we do that is machine learning that learns over time as it recognizes different types of data, applies policies to classify that data and brings it all together with automation. >> Right, and one of the big themes that we've talked about this on earlier episodes is really simplification, really abstracting a lot of that heavy lifting away. So, we can focus on things Ajay, as you just mentioned. I mean, Fadzi, one of the big challenges that of course we all talk about is governance across these disparate data sets. I'm curious as your thoughts how does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations? Which of course are particularly acute within financial services. >> Oh yeah, yes. So, for banks and payment providers like you've just mentioned there. Insurers and many other financial services firms, you know they have to adhere to a standard such as say a PCI DSS. And in Europe you've got the GDPR, which requires stringent tracking, reporting, documentation and, you know for them to, to remain in compliance. And the way we recommend our customers to address these challenges is by having an automation strategy, right. And that type of strategy can help you to improve the security on compliance of of your organization and reduce the risk out of the business, right. And we help organizations build security and compliance from the start with our consulting services, residencies. We also offer courses that help customers to understand how to address some of these challenges. And there's also, we help organizations build security into their applications with our open source middleware offerings and even using a platform like OpenShift, because it allows you to run legacy applications and also containerized applications in a unified platform. Right, and also that provides you with, you know with the automation and the tooling that you need to continuously monitor, manage and automate the systems for security and compliance purposes. >> Ajay, anything, any color you could add to this conversation? >> Yeah, I'm pleased Fadzi brought up OpenShift. I mean we're using OpenShift to be able to take that security application of controls to the data level and it's all about context. So, understanding what data is there, being able to assess it to say, who should have access to it, which application permission should be applied to it. That's a great combination of Red Hat and io/tahoe. >> Fadzi, what about multi-cloud? Doesn't that complicate the situation even further, maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi-cloud as well. >> Yeah, sure, yeah. So, the right automation solution, you know can be the difference between, you know cultivating an automated enterprise or automation carries. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So, that means have an automation solution that provides, you know, promotes IT availability and reliability with your platform so that, you can provide enterprise grade support, including security and testing integration and clear roadmaps. The second thing is vendor interoperability in that, you are going to be integrating multiple clouds. So, you're going to need a solution that can connect to multiple clouds seamlessly, right? And with that comes the challenge of maintainability. So, you're going to need to look into a automation solution that is easy to learn or has an easy learning curve. And then, the fourth idea that we tell our customers is scalability. In the hybrid cloud space, scale is the big, big deal here. And you need to deploy an automation solution that can span across the whole enterprise in a consistent manner, right. And then also that allows you finally to integrate the multiple data centers that you have. >> So, Ajay, I mean, this is a complicated situation for if a customer has to make sure things work on AWS or Azure or Google. They're going to spend all their time doing that. What can you add to really just simplify that multi-cloud and hybrid cloud equation. >> Yeah, I can give a few customer examples here. One being a manufacturer that we've worked with to drive that simplification. And the real bonuses for them has been a reduction in cost. We worked with them late last year to bring the cost spend down by $10 million in 2021. So, they could hit that reduced budget. And, what we brought to that was the ability to deploy using OpenShift templates into their different environments, whether it was on premise or in, as you mentioned, AWS. They had GCP as well for their marketing team and across those different platforms, being able to use a template, use prebuilt scripts to get up and running and catalog and discover that data within minutes. It takes away the legacy of having teams of people having to jump on workshop calls. And I know we're all on a lot of teams zoom calls. And in these current times. They're just simply using enough hours of the day to manually perform all of this. So, yeah, working with Red Hat, applying machine learning into those templates, those little recipes that we can put that automation to work regardless which location the data's in allows us to pull that unified view together. >> Great, thank you. Fadzi, I want to come back to you. So, the early days of cloud you're in the Big Apple, you know financial services really well. Cloud was like an evil word and within financial services, and obviously that's changed, it's evolved. We talk about the pandemic has even accelerated that. And when you really dug into it, when you talk to customers about their experiences with security in the cloud, it was not that it wasn't good, it was great, whatever, but it was different. And there's always this issue of skill, lack of skills and multiple tools, set up teams. are really overburdened. But in the cloud requires, you know, new thinking you've got the shared responsibility model. You've got to obviously have specific corporate, you know requirements and compliance. So, this is even more complicated when you introduce multiple clouds. So, what are the differences that you can share from your experiences running on a sort of either on prem or on a mono cloud or, you know, versus across clouds? What, do you suggest there? >> Sure, you know, because of these complexities that you have explained here mixed configurations and the inadequate change control are the top security threats. So, human error is what we want to avoid, because as you know, as your clouds grow with complexity then you put humans in the mix. Then the rate of errors is going to increase and that is going to expose you to security threats. So, this is where automation comes in, because automation will streamline and increase the consistency of your infrastructure management also application development and even security operations to improve in your protection compliance and change control. So, you want to consistently configure resources according to a pre-approved, you know, pre-approved policies and you want to proactively maintain them in a repeatable fashion over the whole life cycle. And then, you also want to rapidly the identify system that require patches and reconfiguration and automate that process of patching and reconfiguring. So that, you don't have humans doing this type of thing, And you want to be able to easily apply patches and change assistance settings according to a pre-defined base like I explained before, you know with the pre-approved policies. And also you want ease of auditing and troubleshooting, right. And from a Red Hat perspective we provide tools that enable you to do this. We have, for example a tool called Ansible that enables you to automate data center operations and security and also deployment of applications. And also OpenShift itself, it automates most of these things and obstruct the human beings from putting their fingers and causing, you know potentially introducing errors, right. Now, in looking into the new world of multiple clouds and so forth. The differences that we're seeing here between running a single cloud or on prem is three main areas, which is control, security and compliance, right. Control here, it means if you're on premise or you have one cloud you know, in most cases you have control over your data and your applications, especially if you're on prem. However, if you're in the public cloud, there is a difference that the ownership it is still yours, but your resources are running on somebody else's or the public clouds, EWS and so forth infrastructure. So, people that are going to do these need to really, especially banks and governments need to be aware of the regulatory constraints of running those applications in the public cloud. And we also help customers rationalize some of these choices. And also on security, you will see that if you're running on premises or in a single cloud you have more control, especially if you're on prem. You can control the sensitive information that you have. However, in the cloud, that's a different situation especially from personal information of employees and things like that. You need to be really careful with that. And also again, we help you rationalize some of those choices. And then, the last one is compliance. As well, you see that if you're running on prem on single cloud, regulations come into play again, right? And if you're running on prem, you have control over that. You can document everything, you have access to everything that you need, but if you're going to go to the public cloud again, you need to think about that. We have automation and we have standards that can help you you know, address some of these challenges. >> So, that's really strong insights, Fadzi. I mean, first of all Ansible has a lot of market momentum, you know, Red Hat's done a really good job with that acquisition. Your point about repeatability is critical, because you can't scale otherwise. And then, that idea you're putting forth about control, security and compliance. It's so true, I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe AWS is going to physically secure the you know, the S3, but in the bucket but we saw so many misconfigurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So, this all sounds great. Ajay, you're sharp, financial background. What about the economics? You know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. I mean, especially when you think about the work from home pivot and all the areas that they had to, the holes that they had to fill there, whether it was laptops, you know, new security models, et cetera. So, how to organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs, so I can pay it forward or there's a there's a risk reduction angle. What can you share there? >> Yeah, I mean, that perspective I'd like to give here is not being multi-cloud as multi copies of an application or data. When I think back 20 years, a lot of the work in financial services I was looking at was managing copies of data that were feeding different pipelines, different applications. Now, what we're seeing at io/tahoe a lot of the work that we're doing is reducing the number of copies of that data. So that, if I've got a product lifecycle management set of data, if I'm a manufacturer I'm just going to keep that at one location. But across my different clouds, I'm going to have best of breed applications developed in-house, third parties in collaboration with my supply chain, connecting securely to that single version of the truth. What I'm not going to do is to copy that data. So, a lot of what we're seeing now is that interconnectivity using applications built on Kubernetes that are decoupled from the data source. That allows us to reduce those copies of data within that you're gaining from a security capability and resilience, because you're not leaving yourself open to those multiple copies of data. And with that come cost of storage and a cost to compute. So, what we're saying is using multi-cloud to leverage the best of what each cloud platform has to offer. And that goes all the way to Snowflake and Heroku on a cloud managed databases too. >> Well and the people cost too as well. When you think about, yes, the copy creep. But then, you know, when something goes wrong a human has to come in and figure it out. You know, you brought up Snowflake, I get this vision of the data cloud, which is, you know data. I think we're going to be rethinking Ajay, data architectures in the coming decade where data stays where it belongs, it's distributed and you're providing access. Like you said, you're separating the data from the applications. Applications as we talked about with Fadzi, much more portable. So, it's really the last 10 years it'd be different than the next 10 years ago Ajay. >> Definitely, I think the people cost reduction is used. Gone are the days where you needed to have a dozen people governing, managing byte policies to data. A lot of that repetitive work, those tasks can be in part automated. We're seen examples in insurance where reduced teams of 15 people working in the back office, trying to apply security controls, compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDPR and CCPA. Last year, very much the economic effect to reduce head counts and enterprises running lean looking to reduce that cost. This year, we can see that already some of the more proactive companies are looking at initiatives, such as net zero emissions. How they use data to understand how they can become more, have a better social impact and using data to drive that. And that's across all of their operations and supply chain. So, those regulatory compliance issues that might have been external. We see similar patterns emerging for internal initiatives that are benefiting that environment, social impact, and of course costs. >> Great perspectives. Jeff Hammerbacher once famously said, the best minds of my generation are trying to get people to click on ads and Ajay those examples that you just gave of, you know social good and moving things forward are really critical. And I think that's where data is going to have the biggest societal impact. Okay guys, great conversation. Thanks so much for coming to the program. Really appreciate your time. >> Thank you. >> Thank you so much, Dave. >> Keep it right there, for more insight and conversation around creating a resilient digital business model. You're watching theCube. (soft music)

>> Announcer: From around the globe, it's theCUBE presenting Enterprise Digital Resilience on Hybrid and multicloud brought to you by io/tahoe >> Hello everyone, and welcome to our continuing series covering data automation brought to you by io/tahoe. Today we're going to look at how to ensure enterprise resilience for hybrid and multicloud, let's welcome in Ajay Vohora who's the CEO of io/tahoe Ajay, always good to see you again, thanks for coming on. >> Great to be back David, pleasure. >> And he's joined by Fadzi Ushewokunze, who is a global principal architect for financial services, the vertical of financial services at Red Hat. He's got deep experiences in that sector. Welcome Fadzi, good to see you. >> Thank you very much. Happy to be here. >> Fadzi, let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and how it works. >> Sure, Yeah. So, a hybrid cloud is an IT architecture that incorporates some degree of workload portability, orchestration and management across multiple clouds. Those clouds could be private clouds or public clouds or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand allocation of resources across clouds. And separate clouds can become hybrid when you're seamlessly interconnected. And it is that interconnectivity that allows the workloads to be moved and how management can be unified and orchestration can work. And how well you have these interconnections has a direct impact of how well your hybrid cloud will work. >> Okay, so well Fadzi, staying with you for a minute. So, in the early days of cloud that term private cloud was thrown around a lot. But it often just meant virtualization of an on-prem system and a network connection to the public cloud. Let's bring it forward. What, in your view does a modern hybrid cloud architecture look like? >> Sure, so, for modern hybrid clouds we see that teams or organizations need to focus on the portability of applications across clouds. That's very important, right. And when organizations build applications they need to build and deploy these applications as a small collections of independently loosely coupled services. And then have those things run on the same operating system, which means in other words, running it all Linux everywhere and building cloud native applications and being able to manage it and orchestrate these applications with platforms like Kubernetes or Red Hat OpenShift, for example. >> Okay, so, Fadzi that's definitely different from building a monolithic application that's fossilized and doesn't move. So, what are the challenges for customers, you know, to get to that modern cloud is as you've just described it as it skillsets, is it the ability to leverage things like containers? What's your View there? >> So, I mean, from what we've seen around the industry especially around financial services where I spend most of my time. We see that the first thing that we see is management, right. Now, because you have all these clouds, you know, all these applications. You have a massive array of connections, of interconnections. You also have massive array of integrations portability and resource allocation as well. And then orchestrating all those different moving pieces things like storage networks. Those are really difficult to manage, right? So, management is the first challenge. The second one is workload placement. Where do you place this cloud? How do you place these cloud native operations? Do you, what do you keep on site on prem and what do you put in the cloud? That is the other challenge. The major one, the third one is security. Security now becomes the key challenge and concern for most customers. And we're going to talk about how to address that. >> Yeah, we're definitely going to dig into that. Let's bring Ajay into the conversation. Ajay, you know, you and I have talked about this in the past. One of the big problems that virtually every company face is data fragmentation. Talk a little bit about how io/tahoe, unifies data across both traditional systems, legacy systems and it connects to these modern IT environments. >> Yeah, sure Dave. I mean, a Fadzi just nailed it there. It used to be about data, the volume of data and the different types of data, but as applications become more connected and interconnected the location of that data really matters. How we serve that data up to those apps. So, working with Red Hat and our partnership with Red Hat. Being able to inject our data discovery machine learning into these multiple different locations. whether it be an AWS or an IBM cloud or a GCP or on prem. Being able to automate that discovery and pulling that single view of where is all my data, then allows the CIO to manage cost. They can do things like, one, I keep the data where it is, on premise or in my Oracle cloud or in my IBM cloud and connect the application that needs to feed off that data. And the way in which we do that is machine learning that learns over time as it recognizes different types of data, applies policies to classify that data and brings it all together with automation. >> Right, and one of the big themes that we've talked about this on earlier episodes is really simplification, really abstracting a lot of that heavy lifting away. So, we can focus on things Ajay, as you just mentioned. I mean, Fadzi, one of the big challenges that of course we all talk about is governance across these disparate data sets. I'm curious as your thoughts how does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations? Which of course are particularly acute within financial services. >> Oh yeah, yes. So, for banks and payment providers like you've just mentioned there. Insurers and many other financial services firms, you know they have to adhere to a standard such as say a PCI DSS. And in Europe you've got the GDPR, which requires stringent tracking, reporting, documentation and, you know for them to, to remain in compliance. And the way we recommend our customers to address these challenges is by having an automation strategy, right. And that type of strategy can help you to improve the security on compliance of of your organization and reduce the risk out of the business, right. And we help organizations build security and compliance from the start with our consulting services, residencies. We also offer courses that help customers to understand how to address some of these challenges. And there's also, we help organizations build security into their applications with our open source middleware offerings and even using a platform like OpenShift, because it allows you to run legacy applications and also containerized applications in a unified platform. Right, and also that provides you with, you know with the automation and the tooling that you need to continuously monitor, manage and automate the systems for security and compliance purposes. >> Ajay, anything, any color you could add to this conversation? >> Yeah, I'm pleased Fadzi brought up OpenShift. I mean we're using OpenShift to be able to take that security application of controls to the data level and it's all about context. So, understanding what data is there, being able to assess it to say, who should have access to it, which application permission should be applied to it. That's a great combination of Red Hat and io/tahoe. >> Fadzi, what about multi-cloud? Doesn't that complicate the situation even further, maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi-cloud as well. >> Yeah, sure, yeah. So, the right automation solution, you know can be the difference between, you know cultivating an automated enterprise or automation carries. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So, that means have an automation solution that provides, you know, promotes IT availability and reliability with your platform so that, you can provide enterprise grade support, including security and testing integration and clear roadmaps. The second thing is vendor interoperability in that, you are going to be integrating multiple clouds. So, you're going to need a solution that can connect to multiple clouds seamlessly, right? And with that comes the challenge of maintainability. So, you're going to need to look into a automation solution that is easy to learn or has an easy learning curve. And then, the fourth idea that we tell our customers is scalability. In the hybrid cloud space, scale is the big, big deal here. And you need to deploy an automation solution that can span across the whole enterprise in a consistent manner, right. And then also that allows you finally to integrate the multiple data centers that you have. >> So, Ajay, I mean, this is a complicated situation for if a customer has to make sure things work on AWS or Azure or Google. They're going to spend all their time doing that. What can you add to really just simplify that multi-cloud and hybrid cloud equation. >> Yeah, I can give a few customer examples here. One being a manufacturer that we've worked with to drive that simplification. And the real bonuses for them has been a reduction in cost. We worked with them late last year to bring the cost spend down by $10 million in 2021. So, they could hit that reduced budget. And, what we brought to that was the ability to deploy using OpenShift templates into their different environments, whether it was on premise or in, as you mentioned, AWS. They had GCP as well for their marketing team and across those different platforms, being able to use a template, use prebuilt scripts to get up and running and catalog and discover that data within minutes. It takes away the legacy of having teams of people having to jump on workshop calls. And I know we're all on a lot of teams zoom calls. And in these current times. They're just simply using enough hours of the day to manually perform all of this. So, yeah, working with Red Hat, applying machine learning into those templates, those little recipes that we can put that automation to work regardless which location the data's in allows us to pull that unified view together. >> Great, thank you. Fadzi, I want to come back to you. So, the early days of cloud you're in the Big Apple, you know financial services really well. Cloud was like an evil word and within financial services, and obviously that's changed, it's evolved. We talk about the pandemic has even accelerated that. And when you really dug into it, when you talk to customers about their experiences with security in the cloud, it was not that it wasn't good, it was great, whatever, but it was different. And there's always this issue of skill, lack of skills and multiple tools, set up teams. are really overburdened. But in the cloud requires, you know, new thinking you've got the shared responsibility model. You've got to obviously have specific corporate, you know requirements and compliance. So, this is even more complicated when you introduce multiple clouds. So, what are the differences that you can share from your experiences running on a sort of either on prem or on a mono cloud or, you know, versus across clouds? What, do you suggest there? >> Sure, you know, because of these complexities that you have explained here mixed configurations and the inadequate change control are the top security threats. So, human error is what we want to avoid, because as you know, as your clouds grow with complexity then you put humans in the mix. Then the rate of errors is going to increase and that is going to expose you to security threats. So, this is where automation comes in, because automation will streamline and increase the consistency of your infrastructure management also application development and even security operations to improve in your protection compliance and change control. So, you want to consistently configure resources according to a pre-approved, you know, pre-approved policies and you want to proactively maintain them in a repeatable fashion over the whole life cycle. And then, you also want to rapidly the identify system that require patches and reconfiguration and automate that process of patching and reconfiguring. So that, you don't have humans doing this type of thing, And you want to be able to easily apply patches and change assistance settings according to a pre-defined base like I explained before, you know with the pre-approved policies. And also you want ease of auditing and troubleshooting, right. And from a Red Hat perspective we provide tools that enable you to do this. We have, for example a tool called Ansible that enables you to automate data center operations and security and also deployment of applications. And also OpenShift itself, it automates most of these things and obstruct the human beings from putting their fingers and causing, you know potentially introducing errors, right. Now, in looking into the new world of multiple clouds and so forth. The differences that we're seeing here between running a single cloud or on prem is three main areas, which is control, security and compliance, right. Control here, it means if you're on premise or you have one cloud you know, in most cases you have control over your data and your applications, especially if you're on prem. However, if you're in the public cloud, there is a difference that the ownership it is still yours, but your resources are running on somebody else's or the public clouds, EWS and so forth infrastructure. So, people that are going to do these need to really, especially banks and governments need to be aware of the regulatory constraints of running those applications in the public cloud. And we also help customers rationalize some of these choices. And also on security, you will see that if you're running on premises or in a single cloud you have more control, especially if you're on prem. You can control the sensitive information that you have. However, in the cloud, that's a different situation especially from personal information of employees and things like that. You need to be really careful with that. And also again, we help you rationalize some of those choices. And then, the last one is compliance. As well, you see that if you're running on prem on single cloud, regulations come into play again, right? And if you're running on prem, you have control over that. You can document everything, you have access to everything that you need, but if you're going to go to the public cloud again, you need to think about that. We have automation and we have standards that can help you you know, address some of these challenges. >> So, that's really strong insights, Fadzi. I mean, first of all Ansible has a lot of market momentum, you know, Red Hat's done a really good job with that acquisition. Your point about repeatability is critical, because you can't scale otherwise. And then, that idea you're putting forth about control, security and compliance. It's so true, I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe AWS is going to physically secure the you know, the S3, but in the bucket but we saw so many misconfigurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So, this all sounds great. Ajay, you're sharp, financial background. What about the economics? You know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. I mean, especially when you think about the work from home pivot and all the areas that they had to, the holes that they had to fill there, whether it was laptops, you know, new security models, et cetera. So, how to organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs, so I can pay it forward or there's a there's a risk reduction angle. What can you share there? >> Yeah, I mean, that perspective I'd like to give here is not being multi-cloud as multi copies of an application or data. When I think back 20 years, a lot of the work in financial services I was looking at was managing copies of data that were feeding different pipelines, different applications. Now, what we're seeing at io/tahoe a lot of the work that we're doing is reducing the number of copies of that data. So that, if I've got a product lifecycle management set of data, if I'm a manufacturer I'm just going to keep that at one location. But across my different clouds, I'm going to have best of breed applications developed in-house, third parties in collaboration with my supply chain, connecting securely to that single version of the truth. What I'm not going to do is to copy that data. So, a lot of what we're seeing now is that interconnectivity using applications built on Kubernetes that are decoupled from the data source. That allows us to reduce those copies of data within that you're gaining from a security capability and resilience, because you're not leaving yourself open to those multiple copies of data. And with that come cost of storage and a cost to compute. So, what we're saying is using multi-cloud to leverage the best of what each cloud platform has to offer. And that goes all the way to Snowflake and Heroku on a cloud managed databases too. >> Well and the people cost too as well. When you think about, yes, the copy creep. But then, you know, when something goes wrong a human has to come in and figure it out. You know, you brought up Snowflake, I get this vision of the data cloud, which is, you know data. I think we're going to be rethinking Ajay, data architectures in the coming decade where data stays where it belongs, it's distributed and you're providing access. Like you said, you're separating the data from the applications. Applications as we talked about with Fadzi, much more portable. So, it's really the last 10 years it'd be different than the next 10 years ago Ajay. >> Definitely, I think the people cost reduction is used. Gone are the days where you needed to have a dozen people governing, managing byte policies to data. A lot of that repetitive work, those tasks can be in part automated. We're seen examples in insurance where reduced teams of 15 people working in the back office, trying to apply security controls, compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDPR and CCPA. Last year, very much the economic effect to reduce head counts and enterprises running lean looking to reduce that cost. This year, we can see that already some of the more proactive companies are looking at initiatives, such as net zero emissions. How they use data to understand how they can become more, have a better social impact and using data to drive that. And that's across all of their operations and supply chain. So, those regulatory compliance issues that might have been external. We see similar patterns emerging for internal initiatives that are benefiting that environment, social impact, and of course costs. >> Great perspectives. Jeff Hammerbacher once famously said, the best minds of my generation are trying to get people to click on ads and Ajay those examples that you just gave of, you know social good and moving things forward are really critical. And I think that's where data is going to have the biggest societal impact. Okay guys, great conversation. Thanks so much for coming to the program. Really appreciate your time. >> Thank you. >> Thank you so much, Dave. >> Keep it right there, for more insight and conversation around creating a resilient digital business model. You're watching theCube. (soft music)

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. >>Welcome back to the cubes live coverage of AWS reinvent 2020 I'm Lisa Martin and I have with me a cube alumni back, please. Welcome Scott Mullins, the worldwide financial services business development leader at AWS. Scott. Welcome back. Great to have you joining us, >>Lisa. It's great to be back on the cube and to be visiting with you today from virtual re-invent 2020. >>Yes. Reinventing reinvent. The last show that I got to host in-person for the cube was reinvent last year. And here we have this three week virtual event that started last week. So lots more even going on. I think I even saw a hundred thousand or so registered, so massive event, lots of news. So walk us through some of the highlights that have been announced at reinvent this year and some of the things that you're seeing the most interest from customers in. >>Well, I think one of the big highlights is 500,000 registrants that are reinvented 50,000 attendees last year to reinvent or 50,000 or so to 500,000 re registered for the event. So that's, that's, that's worth talking about in its own. Right. But I think, you know, one of the things, and you mentioned this, you know, more re-invent three weeks, uh, this year, as opposed to the four days that we normally spend in Las Vegas together, physically, when you do, when you do it digitally, you have the ability to actually include more things and more leaders talking about things. And so when we think about the announcements that are having impacts, uh, with financial services customers specifically I'd point to a couple of things and, you know, they're obviously gonna mention Andy's keynote, but there's going to be some things that you might go wait a minute. >>I didn't even see that announcement. Uh, and then maybe I could point you and the viewers to some other, other, um, keynotes or some other sessions that were announced. So obviously I think, uh, first and foremost in Andy's keynote, uh, hybrid, uh, was something that was a very, uh, big focus for him and I for a very long time, we've had the messaging of the right tool for the right job when it comes to any of your services. I think you could alter that today to say it's the right tool for the right job at the right time and in the right place. That makes sense for you and especially for financial institutions. Um, you could look at the announcements around containers, the announcements around Amazon EKS, distro, Amazon EKS, anywhere, and then also Amazon ECS anywhere, which allows our customers to actually, uh, put AWS container technology anywhere they would like to put it. >>You could look also at the additions of the one you and two you form factors to outposts. So no longer do you have to do the, the, the large for you, uh, foreign factor for outposts, smaller outposts for smaller spaces, uh, that particular will play well in the financial service industry. You may not have necessarily as much room for a full cabinet. You could also look from the hybrid perspective in the announcement we made, um, around red hat OpenShift on AWS, all of are giving customers the ability to choose how they actually want to deploy, um, and pursue a hybrid. I'd also point to some announcements we made around management and governance in the financial services, industry governance, uh, is a very important topic. Uh, we announced the management and government lens for the AWS well architected, um, uh, program, uh, that is focused on breath practices for evolving governance for the cloud. >>It has recommended combination of AWS services integrations with our partner network and vetted reference architectures and guidance for addressing regulatory obligations as well. I'd also point to some things we made around audits. I was specifically in Steve Smith's, um, session today, he talked about AWS audit manager. That's a new tool for continually assessing areas and environments for controls or risk compliance. That includes prebuilt compliance frameworks for things like PCI DSS and GDPR, uh, two things that are very important in the financial services industry and last, but certainly not least I'd point to the announcement around the AWS audit Academy. This is training for auditors to actually be able to audit clouds from an agnostic perspective. Any cloud, not specifically AWS that's tree, uh, digital training to do that. And then also an instructor led course specifically on how to audit AWS. So some very key announcements, both from the standpoint of services, uh, as well as additional layers of helping customers in the financial services industry in regulated industries actually use our services. >>So typical, re-invent typical in a lot of news, a lot of announcements, the 500,000 Mark in terms of registering. I hadn't heard that. That's amazing. Let's talk that this has been an Andy. Jassy had an exclusive with John furrier just a couple of weeks ago before. I think it was last week, actually. And we've been talking about this acceleration of digital business transformation because of COVID we've been talking about it, the entire pandemic on the virtual cube, talking about how companies it's really about right now, surviving and thriving to be able to go forward and companies that haven't accelerated are probably in some trouble. Talk to me about how AWS has been working with your financial services customers to help them pivot and move to the cloud faster, really to not just help them survive now, but thrive in the long-term. >>Yeah. Immediately when COVID hit and it hit at different times in different, in different parts of the world. Immediately when COVID hit, we saw the conversation that we were having turning from, Hey, what's my digital strategy to immediately, what are my digital capabilities? And what that really means is what do I have the ability to do tomorrow? Because tomorrow is going to really matter. I don't have necessarily the time to plan for the next several quarters or the next several years, what can I do tomorrow to, um, really, uh, support my, my own workforce and support my own customers and the obligations I have as a financial institution. The first thing we saw people do was to try and make sure that those who financial services work can work. You can look at the adoption of Amazon workspaces, as well as our, uh, Amazon connect, uh, call centers as a service. >>As two examples there at the RBL bank in India was able to move to Amazon workspaces in just 10 days to enable its teams to actually work remotely from home. When they couldn't come into the office, you can look at Barclays. Barclays is actually a presenter at re-invent this year. They'll have a session on how they use Amazon connect, which again is our call center as a service offering to enable 25,000 contacts and our agents to work from home when they can no longer work out of the, out of their traditional contact center. The second thing we saw a financial institutions joining was making sure that customer engagements could still be meaningful when digital was the only option, um, specifically here in the U S you could look at the work that each of us did with FinTech companies like biz two X or fins Zack, or BlueVine Stripe and cabbage in support of the care act in the U S you might remember that the cares act, um, hasn't provisions for funding for small businesses. >>This small business administration had a program called the paycheck protection program, and those organizations were active in providing funding, uh, to small businesses. Uh, through that program. I'll give you an example of cabbage cabbage had previously not been an SBA lender, um, but they were able to, in two weeks build a fully automated system for small businesses to access PPP funding using Amazon text track, to extract information from documentation that those folks submitted to get alone. That reduced approval times from multiple days to about a median of four hours to actually get approval, to get funding through the PPP program. And then just four months cabbage became the second largest PPP lender. They lent over $7 billion in funding, which was twice the amount of funding that they went last year in 2019 loans. So we were happy to support organizations like cabbage and those other FinTech companies, as they help small businesses in the U S get access to funding, uh, during this critical time. >>And as we know, as you said, critical time, but really life or death for a lot of businesses. And as we continue to go through these ways, but it's interesting that you talked about that the speed of facilitation that during such unprecedented times, AWS and this massive machine was able to continue moving at full speed ahead and helping those customers to pivot. You talked about the cloud connect. I had a conversation with a guest on the queue last week about that. And, and I now think about if I have to call in a contact center and that person might be from home. So, you know, we're fortunate that the cloud computing technology and people like you and AWS, or are able to power that because it's, it's literally essential, which is probably one of the words of the year, but being able to keep the machinery going and innovate at the same time has been, make or break for a lot of businesses. >>Absolutely. And you, you look at, you know, kind of one of the last year is that I'll point to is, um, financial institutions. Uh, anti-virus, we're were very much focused on making sure that that cannot fail, that they scaled. And so you can look at the work we did with, uh, with the, with FINRA FINRA is the primary capital markets regulator here in the U S and on a daily basis frame or processes about 400 billion market events on every night to do surveillance on our markets, that when COVID hit, we had unprecedented volume and volatility in the market. And FINRA was, was, um, looking at processing, uh, anywhere from two to three times, their normal daily market volumes that's anywhere from 800 billion market events to 1.2 trillion a night. And if you look at how they were able to scale, they're actually able to scale up compute resources in AWS. We're on a nightly basis. They're able to automatically turn on and off up to a hundred thousand compute nodes in a single day. That automatic ability to scale is, is the power you're talking about. Being able to actually turn things up when you needed it and turn things down when you, when you don't need it based on the volumes. >>Well, and that's going to be something key going forward. As we know that there will be one thing I think that I always say we can count on right now is uncertainty and continued uncertainty, but we've also seen I'm calling them COVID catalysts. You know, the, what you talked about with cabbage, for example, and how that business pivoted quickly, because of the power of cloud computing and emerging technologies, what are some of the things that you think as we go into 2021 in the financial services arena, what are some of the big tech trends that you think were maybe born during COVID that are going to be critical going forward? >>Well, you know, you, you, you had Melanie Frank from capital one on cube a couple of days ago, and she was talking about, you know, their shift to cloud and what that's really enabled, and it, and she kind of sums it up nicely. She says, look, we want to give our customers experience that are real time, and that are intelligent. And you just can't do that with legacy technology. That's sitting in, you know, kind of a legacy data center. And so I think that's going to be kind of the, the, the all encompassing statement for what's happening in the financial services industry. As I mentioned, you know, organizations overnight said, okay, wait a minute, let's take that strategy. And then let's put it aside. Let's talk about capabilities. What can we do? And I think, you know, necessity is the mother of invention. Um, and when you're faced with limitations and challenges, like we all have been faced with around the world and not just in the financial services industry, it, it breeds, um, invention and the, and the desire and the need to actually meet those challenges head on, in very engineered of ways. >>And I think you're going to see more invention and specifically more invention from the established players in the financial services industry. Cloud use is not just experimental on the edges anymore. You're going to see more organizations coming out of COVID. Um, having had those experiences where they actually stood up a context center and scaled it. And, and just a matter of a few days to, to thousands of agents, you're going to find, um, organizations saying, wait a minute, we, we can do remote work. We could, we have access to things like Amazon workspaces. So I think you're, you're gonna, you're going to see that, uh, be a, be a trend. I think you're also gonna see, um, w what Lori beer said in the keynote with Andy, you know, she, she made a very, very astute statement, and I don't know if people caught it, cause it's kind of neat in the middle of her conversation. >>She said, look, we're trying to infuse analytics into everything that we do at JP Morgan. I think you're going to see more and more financial institutions looking to do that, to actually leverage the power of analytics, to power everything we do as a financial institution. So I think those, those are a couple of things that you're going to see. Um, and then, you know, looking, uh, you know, kind of around the corner, I think you're going to continue to see more re-invention within the industry. And what I mean by that is you've seen many financial institutions over the last week, uh, with, uh, re-invent making announcements, you saw bank and we towel saying, Hey, look, we are completely transforming ourselves with AWS. Uh, just a few weeks before we even saw standard charter, the same thing HSBC said, the same thing, global payments earlier in the year said the same thing. And you're going to see more and more organizations coming out and talking about these strategic decisions to reinvent everything that they do to make the financial systems of the world work. And so we're really pleased to be partnering with those organizations to make those transformations possible. We're seeing a lot of invention within the industry, and we're very pleased to be a part of the reinvention of the financial systems around the world. >>It's interesting to hear that you, you see, even the JP Morgan, some of those legacy, big houses are going to be really pivoting. They have to, to be competitive and to be able to utilize analytics, to deliver those real-time services. Because as we all know, as consumers, our patients is wearing thin these days, but I agree with you. I think there's a lot of opportunity there that innovation is exciting and there will have to be reinvention of entire industries, but I think there's a lot of silver linings there. Scott. I wish we had more time, cause I know we could keep talking, but thank you for sharing your insights on this reinvented reinvent this year. >>I appreciate it. Thank you, Lisa. It's always a pleasure to be on the cube. >>Chris Scott Mullins, I'm Lisa Martin. You're watching the cubes coverage of AWS reinvent 2020.

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Snowflake is not going to grow into its valuation by stealing the croissant from the breakfast table of the on-prem data warehouse vendors. Look, even if snowflake got 100% of the data warehouse business, it wouldn't come close to justifying its market cap. Rather Snowflake has to create an entirely new market based on completely changing the way organizations think about monetizing data. Every organization I talk to says it wants to be, or many say they already are data-driven. why wouldn't you aspire to that goal? There's probably nothing more strategic than leveraging data to power your digital business and creating competitive advantage. But many businesses are failing, or I predict, will fail to create a true data-driven culture because they're relying on a flawed architectural model formed by decades of building centralized data platforms. Welcome everyone to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, I want to share some new thoughts and fresh ETR data on how organizations can transform their businesses through data by reinventing their data architectures. And I want to share our thoughts on why we think Snowflake is currently in a very strong position to lead this effort. Now, on November 17th, theCUBE is hosting the Snowflake Data Cloud Summit. Snowflake's ascendancy and its blockbuster IPO has been widely covered by us and many others. Now, since Snowflake went public, we've been inundated with outreach from investors, customers, and competitors that wanted to either better understand the opportunities or explain why their approach is better or different. And in this segment, ahead of Snowflake's big event, we want to share some of what we learned and how we see it. Now, theCUBE is getting paid to host this event, so I need you to know that, and you draw your own conclusions from my remarks. But neither Snowflake nor any other sponsor of theCUBE or client of SiliconANGLE Media has editorial influence over Breaking Analysis. The opinions here are mine, and I would encourage you to read my ethics statement in this regard. I want to talk about the failed data model. The problem is complex, I'm not debating that. Organizations have to integrate data and platforms with existing operational systems, many of which were developed decades ago. And as a culture and a set of processes that have been built around these systems, and they've been hardened over the years. This chart here tries to depict the progression of the monolithic data source, which, for me, began in the 1980s when Decision Support Systems or DSS promised to solve our data problems. The data warehouse became very popular and data marts sprung up all over the place. This created more proprietary stovepipes with data locked inside. The Enron collapse led to Sarbanes-Oxley. Now, this tightened up reporting. The requirements associated with that, it breathed new life into the data warehouse model. But it remained expensive and cumbersome, I've talked about that a lot, like a snake swallowing a basketball. The 2010s ushered in the big data movement, and Data Lakes emerged. With a dupe, we saw the idea of no schema online, where you put structured and unstructured data into a repository, and figure it all out on the read. What emerged was a fairly complex data pipeline that involved ingesting, cleaning, processing, analyzing, preparing, and ultimately serving data to the lines of business. And this is where we are today with very hyper specialized roles around data engineering, data quality, data science. There's lots of batch of processing going on, and Spark has emerged to improve the complexity associated with MapReduce, and it definitely helped improve the situation. We're also seeing attempts to blend in real time stream processing with the emergence of tools like Kafka and others. But I'll argue that in a strange way, these innovations actually compound the problem. And I want to discuss that because what they do is they heighten the need for more specialization, more fragmentation, and more stovepipes within the data life cycle. Now, in reality, and it pains me to say this, it's the outcome of the big data movement, as we sit here in 2020, that we've created thousands of complicated science projects that have once again failed to live up to the promise of rapid cost-effective time to insights. So, what will the 2020s bring? What's the next silver bullet? You hear terms like the lakehouse, which Databricks is trying to popularize. And I'm going to talk today about data mesh. These are other efforts they look to modernize datalakes and sometimes merge the best of data warehouse and second-generation systems into a new paradigm, that might unify batch and stream frameworks. And this definitely addresses some of the gaps, but in our view, still suffers from some of the underlying problems of previous generation data architectures. In other words, if the next gen data architecture is incremental, centralized, rigid, and primarily focuses on making the technology to get data in and out of the pipeline work, we predict it's going to fail to live up to expectations again. Rather, what we're envisioning is an architecture based on the principles of distributed data, where domain knowledge is the primary target citizen, and data is not seen as a by-product, i.e, the exhaust of an operational system, but rather as a service that can be delivered in multiple forms and use cases across an ecosystem. This is why we often say the data is not the new oil. We don't like that phrase. A specific gallon of oil can either fuel my home or can lubricate my car engine, but it can't do both. Data does not follow the same laws of scarcity like natural resources. Again, what we're envisioning is a rethinking of the data pipeline and the associated cultures to put data needs of the domain owner at the core and provide automated, governed, and secure access to data as a service at scale. Now, how is this different? Let's take a look and unpack the data pipeline today and look deeper into the situation. You all know this picture that I'm showing. There's nothing really new here. The data comes from inside and outside the enterprise. It gets processed, cleanse or augmented so that it can be trusted and made useful. Nobody wants to use data that they can't trust. And then we can add machine intelligence and do more analysis, and finally deliver the data so that domain specific consumers can essentially build data products and services or reports and dashboards or content services, for instance, an insurance policy, a financial product, a loan, that these are packaged and made available for someone to make decisions on or to make a purchase. And all the metadata associated with this data is packaged along with the dataset. Now, we've broken down these steps into atomic components over time so we can optimize on each and make them as efficient as possible. And down below, you have these happy stick figures. Sometimes they're happy. But they're highly specialized individuals and they each do their job and they do it well to make sure that the data gets in, it gets processed and delivered in a timely manner. Now, while these individual pieces seemingly are autonomous and can be optimized and scaled, they're all encompassed within the centralized big data platform. And it's generally accepted that this platform is domain agnostic. Meaning the platform is the data owner, not the domain specific experts. Now there are a number of problems with this model. The first, while it's fine for organizations with smaller number of domains, organizations with a large number of data sources and complex domain structures, they struggle to create a common data parlance, for example, in a data culture. Another problem is that, as the number of data sources grows, organizing and harmonizing them in a centralized platform becomes increasingly difficult, because the context of the domain and the line of business gets lost. Moreover, as ecosystems grow and you add more data, the processes associated with the centralized platform tend to get further genericized. They again lose that domain specific context. Wait (chuckling), there are more problems. Now, while in theory organizations are optimizing on the piece parts of the pipeline, the reality is, as the domain requires a change, for example, a new data source or an ecosystem partnership requires a change in access or processes that can benefit a domain consumer, the reality is the change is subservient to the dependencies and the need to synchronize across these discrete parts of the pipeline or actually, orthogonal to each of those parts. In other words, in actuality, the monolithic data platform itself remains the most granular part of the system. Now, when I complain about this faulty structure, some folks tell me this problem has been solved. That there are services that allow new data sources to really easily be added. A good example of this is Databricks Ingest, which is, it's an auto loader. And what it does is it simplifies the ingestion into the company's Delta Lake offering. And rather than centralizing in a data warehouse, which struggles to efficiently allow things like Machine Learning frameworks to be incorporated, this feature allows you to put all the data into a centralized datalake. More so the argument goes, that the problem that I see with this, is while the approach does definitely minimizes the complexities of adding new data sources, it still relies on this linear end-to-end process that slows down the introduction of data sources from the domain consumer beside of the pipeline. In other words, the domain experts still has to elbow her way into the front of the line or the pipeline, in this case, to get stuff done. And finally, the way we are organizing teams is a point of contention, and I believe is going to continue to cause problems down the road. Specifically, we've again, we've optimized on technology expertise, where for example, data engineers, well, really good at what they do, they're often removed from the operations of the business. Essentially, we created more silos and organized around technical expertise versus domain knowledge. As an example, a data team has to work with data that is delivered with very little domain specificity, and serves a variety of highly specialized consumption use cases. All right. I want to step back for a minute and talk about some of the problems that people bring up with Snowflake and then I'll relate it back to the basic premise here. As I said earlier, we've been hammered by dozens and dozens of data points, opinions, criticisms of Snowflake. And I'll share a few here. But I'll post a deeper technical analysis from a software engineer that I found to be fairly balanced. There's five Snowflake criticisms that I'll highlight. And there are many more, but here are some that I want to call out. Price transparency. I've had more than a few customers telling me they chose an alternative database because of the unpredictable nature of Snowflake's pricing model. Snowflake, as you probably know, prices based on consumption, just like AWS and other cloud providers. So just like AWS, for example, the bill at the end of the month is sometimes unpredictable. Is this a problem? Yes. But like AWS, I would say, "Kill me with that problem." Look, if users are creating value by using Snowflake, then that's good for the business. But clearly this is a sore point for some users, especially for procurement and finance, which don't like unpredictability. And Snowflake needs to do a better job communicating and managing this issue with tooling that can predict and help better manage costs. Next, workload manage or lack thereof. Look, if you want to isolate higher performance workloads with Snowflake, you just spin up a separate virtual warehouse. It's kind of a brute force approach. It works generally, but it will add expense. I'm kind of reminded of Pure Storage and its approach to storage management. The engineers at Pure, they always design for simplicity, and this is the approach that Snowflake is taking. Usually, Pure and Snowflake, as I have discussed in a moment, is Pure's ascendancy was really based largely on stealing share from Legacy EMC systems. Snowflake, in my view, has a much, much larger incremental market opportunity. Next is caching architecture. You hear this a lot. At the end of the day, Snowflake is based on a caching architecture. And a caching architecture has to be working for some time to optimize performance. Caches work well when the size of the working set is small. Caches generally don't work well when the working set is very, very large. In general, transactional databases have pretty small datasets. And in general, analytics datasets are potentially much larger. Is it Snowflake in the analytics business? Yes. But the good thing that Snowflake has done is they've enabled data sharing, and it's caching architecture serves its customers well because it allows domain experts, you're going to hear this a lot from me today, to isolate and analyze problems or go after opportunities based on tactical needs. That said, very big queries across whole datasets or badly written queries that scan the entire database are not the sweet spot for Snowflake. Another good example would be if you're doing a large audit and you need to analyze a huge, huge dataset. Snowflake's probably not the best solution. Complex joins, you hear this a lot. The working set of complex joins, by definition, are larger. So, see my previous explanation. Read only. Snowflake is pretty much optimized for read only data. Maybe stateless data is a better way of thinking about this. Heavily right intensive workloads are not the wheelhouse of Snowflake. So where this is maybe an issue is real-time decision-making and AI influencing. A number of times, Snowflake, I've talked about this, they might be able to develop products or acquire technology to address this opportunity. Now, I want to explain. These issues would be problematic if Snowflake were just a data warehouse vendor. If that were the case, this company, in my opinion, would hit a wall just like the NPP vendors that proceeded them by building a better mouse trap for certain use cases hit a wall. Rather, my promise in this episode is that the future of data architectures will be really to move away from large centralized warehouses or datalake models to a highly distributed data sharing system that puts power in the hands of domain experts at the line of business. Snowflake is less computationally efficient and less optimized for classic data warehouse work. But it's designed to serve the domain user much more effectively in our view. We believe that Snowflake is optimizing for business effectiveness, essentially. And as I said before, the company can probably do a better job at keeping passionate end users from breaking the bank. But as long as these end users are making money for their companies, I don't think this is going to be a problem. Let's look at the attributes of what we're proposing around this new architecture. We believe we'll see the emergence of a total flip of the centralized and monolithic big data systems that we've known for decades. In this architecture, data is owned by domain-specific business leaders, not technologists. Today, it's not much different in most organizations than it was 20 years ago. If I want to create something of value that requires data, I need to cajole, beg or bribe the technology and the data team to accommodate. The data consumers are subservient to the data pipeline. Whereas in the future, we see the pipeline as a second class citizen, with a domain expert is elevated. In other words, getting the technology and the components of the pipeline to be more efficient is not the key outcome. Rather, the time it takes to envision, create, and monetize a data service is the primary measure. The data teams are cross-functional and live inside the domain versus today's structure where the data team is largely disconnected from the domain consumer. Data in this model, as I said, is not the exhaust coming out of an operational system or an external source that is treated as generic and stuffed into a big data platform. Rather, it's a key ingredient of a service that is domain-driven and monetizable. And the target system is not a warehouse or a lake. It's a collection of connected domain-specific datasets that live in a global mesh. What is a distributed global data mesh? A data mesh is a decentralized architecture that is domain aware. The datasets in the system are purposely designed to support a data service or data product, if you prefer. The ownership of the data resides with the domain experts because they have the most detailed knowledge of the data requirement and its end use. Data in this global mesh is governed and secured, and every user in the mesh can have access to any dataset as long as it's governed according to the edicts of the organization. Now, in this model, the domain expert has access to a self-service and obstructed infrastructure layer that is supported by a cross-functional technology team. Again, the primary measure of success is the time it takes to conceive and deliver a data service that could be monetized. Now, by monetize, we mean a data product or data service that it either cuts cost, it drives revenue, it saves lives, whatever the mission is of the organization. The power of this model is it accelerates the creation of value by putting authority in the hands of those individuals who are closest to the customer and have the most intimate knowledge of how to monetize data. It reduces the diseconomies at scale of having a centralized or a monolithic data architecture. And it scales much better than legacy approaches because the atomic unit is a data domain, not a monolithic warehouse or a lake. Zhamak Dehghani is a software engineer who is attempting to popularize the concept of a global mesh. Her work is outstanding, and it's strengthened our belief that practitioners see this the same way that we do. And to paraphrase her view, "A domain centric system must be secure and governed with standard policies across domains." It has to be trusted. As I said, nobody's going to use data they don't trust. It's got to be discoverable via a data catalog with rich metadata. The data sets have to be self-describing and designed for self-service. Accessibility for all users is crucial as is interoperability, without which distributed systems, as we know, fail. So what does this all have to do with Snowflake? As I said, Snowflake is not just a data warehouse. In our view, it's always had the potential to be more. Our assessment is that attacking the data warehouse use cases, it gave Snowflake a straightforward easy-to-understand narrative that allowed it to get a foothold in the market. Data warehouses are notoriously expensive, cumbersome, and resource intensive, but they're a critical aspect to reporting and analytics. So it was logical for Snowflake to target on-premise legacy data warehouses and their smaller cousins, the datalakes, as early use cases. By putting forth and demonstrating a simple data warehouse alternative that can be spun up quickly, Snowflake was able to gain traction, demonstrate repeatability, and attract the capital necessary to scale to its vision. This chart shows the three layers of Snowflake's architecture that have been well-documented. The separation of compute and storage, and the outer layer of cloud services. But I want to call your attention to the bottom part of the chart, the so-called Cloud Agnostic Layer that Snowflake introduced in 2018. This layer is somewhat misunderstood. Not only did Snowflake make its Cloud-native database compatible to run on AWS than Azure in the 2020 GCP, what Snowflake has done is to obstruct cloud infrastructure complexity and create what it calls the data cloud. What's the data cloud? We don't believe the data cloud is just a marketing term that doesn't have any substance. Just as SAS is Simplified Application Software and iOS made it possible to eliminate the value drain associated with provisioning infrastructure, a data cloud, in concept, can simplify data access, and break down fragmentation and enable shared data across the globe. Snowflake, they have a first mover advantage in this space, and we see a number of fundamental aspects that comprise a data cloud. First, massive scale with virtually unlimited compute and storage resource that are enabled by the public cloud. We talk about this a lot. Second is a data or database architecture that's built to take advantage of native public cloud services. This is why Frank Slootman says, "We've burned the boats. We're not ever doing on-prem. We're all in on cloud and cloud native." Third is an obstruction layer that hides the complexity of infrastructure. and fourth is a governed and secured shared access system where any user in the system, if allowed, can get access to any data in the cloud. So a key enabler of the data cloud is this thing called the global data mesh. Now, earlier this year, Snowflake introduced its global data mesh. Over the course of its recent history, Snowflake has been building out its data cloud by creating data regions, strategically tapping key locations of AWS regions and then adding Azure and GCP. The complexity of the underlying cloud infrastructure has been stripped away to enable self-service, and any Snowflake user becomes part of this global mesh, independent of the cloud that they're on. Okay. So now, let's go back to what we were talking about earlier. Users in this mesh will be our domain owners. They're building monetizable services and products around data. They're most likely dealing with relatively small read only datasets. They can adjust data from any source very easily and quickly set up security and governance to enable data sharing across different parts of an organization, or, very importantly, an ecosystem. Access control and governance is automated. The data sets are addressable. The data owners have clearly defined missions and they own the data through the life cycle. Data that is specific and purposely shaped for their missions. Now, you're probably asking, "What happens to the technical team and the underlying infrastructure and the cluster it's in? How do I get the compute close to the data? And what about data sovereignty and the physical storage later, and the costs?" All these are good questions, and I'm not saying these are trivial. But the answer is these are implementation details that are pushed to a self-service layer managed by a group of engineers that serves the data owners. And as long as the domain expert/data owner is driving monetization, this piece of the puzzle becomes self-funding. As I said before, Snowflake has to help these users to optimize their spend with predictive tooling that aligns spend with value and shows ROI. While there may not be a strong motivation for Snowflake to do this, my belief is that they'd better get good at it or someone else will do it for them and steal their ideas. All right. Let me end with some ETR data to show you just how Snowflake is getting a foothold on the market. Followers of this program know that ETR uses a consistent methodology to go to its practitioner base, its buyer base each quarter and ask them a series of questions. They focus on the areas that the technology buyer is most familiar with, and they ask a series of questions to determine the spending momentum around a company within a specific domain. This chart shows one of my favorite examples. It shows data from the October ETR survey of 1,438 respondents. And it isolates on the data warehouse and database sector. I know I just got through telling you that the world is going to change and Snowflake's not a data warehouse vendor, but there's no construct today in the ETR dataset to cut a data cloud or globally distributed data mesh. So you're going to have to deal with this. What this chart shows is net score in the y-axis. That's a measure of spending velocity, and it's calculated by asking customers, "Are you spending more or less on a particular platform?" And then subtracting the lesses from the mores. It's more granular than that, but that's the basic concept. Now, on the x-axis is market share, which is ETR's measure of pervasiveness in the survey. You can see superimposed in the upper right-hand corner, a table that shows the net score and the shared N for each company. Now, shared N is the number of mentions in the dataset within, in this case, the data warehousing sector. Snowflake, once again, leads all players with a 75% net score. This is a very elevated number and is higher than that of all other players, including the big cloud companies. Now, we've been tracking this for a while, and Snowflake is holding firm on both dimensions. When Snowflake first hit the dataset, it was in the single digits along the horizontal axis and continues to creep to the right as it adds more customers. Now, here's another chart. I call it the wheel chart that breaks down the components of Snowflake's net score or spending momentum. The lime green is new adoption, the forest green is customers spending more than 5%, the gray is flat spend, the pink is declining by more than 5%, and the bright red is retiring the platform. So you can see the trend. It's all momentum for this company. Now, what Snowflake has done is they grabbed a hold of the market by simplifying data warehouse. But the strategic aspect of that is that it enables the data cloud leveraging the global mesh concept. And the company has introduced a data marketplace to facilitate data sharing across ecosystems. This is all about network effects. In the mid to late 1990s, as the internet was being built out, I worked at IDG with Bob Metcalfe, who was the publisher of InfoWorld. During that time, we'd go on speaking tours all over the world, and I would listen very carefully as he applied Metcalfe's law to the internet. Metcalfe's law states that the value of the network is proportional to the square of the number of connected nodes or users on that system. Said another way, while the cost of adding new nodes to a network scales linearly, the consequent value scores scales exponentially. Now, apply that to the data cloud. The marginal cost of adding a user is negligible, practically zero, but the value of being able to access any dataset in the cloud... Well, let me just say this. There's no limitation to the magnitude of the market. My prediction is that this idea of a global mesh will completely change the way leading companies structure their businesses and, particularly, their data architectures. It will be the technologists that serve domain specialists as it should be. Okay. Well, what do you think? DM me @dvellante or email me at david.vellante@siliconangle.com or comment on my LinkedIn? Remember, these episodes are all available as podcasts, so please subscribe wherever you listen. I publish weekly on wikibon.com and siliconangle.com, and don't forget to check out etr.plus for all the survey analysis. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching. Be well, and we'll see you next time. (upbeat music)

>>From the cube studios in Palo Alto and Boston gets the Q covering IBM thing brought to you by IBM. >>Welcome back to our coverage of IBM think 2020 the digital version of IBM. Thank, my name is Dave Vellante and you're watching the cube. Hillary Hunter is here. She's the vice president and CTO of IBM cloud and also an IBM fellow. Hillary, thanks for coming on. Good to see you. >>Thanks so much for having me today. >>All right, let's get really, let's get into it. We want to focus on security and compliance. It's a key, obviously a key aspect and consideration for customers. But I have to start by asking you, there's this sort of the age old conflict between being secure and then having the flexibility and agility and speed that business people need. How does IBM clouds sort of square that circle? >>Yeah, you know, it's, it's really interesting because cloud itself is detained, um, designed to deliver agility, um, and speed. And that's everything from the release cadence to being able to consume things as APIs. And so when we say cloud and security, it's about the things that we implement as a cloud provider and the services that we stand up. And all of that is API driven. Um, all of that is intended to enable, you know, data protection through API APIs intended to enable security monitoring through PIs and dashboards and other things like that. And so actually when delivered as cloud services, security functions can actually even go more quickly and can facilitate that speed and agility in and of themselves. So it's really interesting that the means of delivering cloud capabilities actually can facilitate that agility in the security area. >>Yeah, I mean I think it's, especially in these times with COBIT 19 a lot of why is that? We're talking, you were saying, Hey, yeah, we're really going harder, uh, for the cloud because the downturns have been actually pretty good for them. For the cloud. I presume you're sort of seeing the same thing, but if you think about the cost of a breach, it's millions of millions of dollars on average. And think about the time it takes for an organization to identify when there's been an infiltration. Mmm. I know small companies like ours, we feel good that we can tap into, you know, cloud infrastructure. what are your thoughts? Oh, on sort of that whole notion cloud essentially maybe even having better security in a way, but however you define better. >>Yeah. You know, I, I actually agree with those statements and I think it's played out in many of our client engagements. Um, because when you are talking about cloud and you're talking about security, we have the opportunity to present to you a proactive approach, right? Where we're saying, okay, leverage this type of technology in order to do your key management or data encryption. It is up by us already fully as a service. You consume it API driven. Um, and so we are able to say that this will enable you to have end to end data encryption or corruption according to some standard or key management, um, where the keys remained in your hands or you know, use these things that are security services so that there isn't, um, there doesn't have to be, um, as detailed of a conversation. Um, as you often have to have in your solution, in your own it. >>You can say, okay, what's the objective we're trying to get to what is the net security and compliance posture? And we as a cloud provider can be proactive and telling you, Hey, therefore then use this combination of services and use them in this following way and that will enable you to reach those outcomes. And so moving past, um, you know, being fully self service where you have to configure hundreds and hundreds of things yourselves. To me being more prescriptive and proactive and goal oriented and outcome oriented, um, is an opportunity that we have in cloud where we're standing up Janning up capabilities. And so we really tried to talk to clients about, okay, what's the, what are you trying to accomplish? Are you concerned about control over your it? Are you concerned about meeting particular documentation on particular regulatory compliance? What's the point? And then how does that relate into a conversation about data compute, networking, et cetera, and then what does that matter too in terms of how you should then use certain cloud capabilities. >>I want to follow up on that, Hillary, because I want to see it. If I can discern, maybe there's some difference in the way IBM approaches this. I've often said in the cube that bad user behavior trumps good security every time. And of course you've got multiple layers, you've got IBM securing, you know it's infrastructure and it's cloud. You've got it in whatever role there and you've got the end user now. Yeah. Somebody fishes the end user or end user admin. Okay. There are things you can do fine. Hmm. But there's also the, it kind of in the middle you mentioned managed services is IBM's approach, you know, somewhat different >>no >>cloud suppliers. Maybe you could elaborate on that. >>Yeah. So, you know, we really look to protect the services that we're standing up, whether it's infrastructure services, where it's yeah, networking, whether or not it's container service or you know, other services that we're providing. We're looking to protect it, those, you know, down to the core of what that service is and how it works and, and how it provides security and then the technologies that that service integrates into. Right? So services seamlessly integrating into bring your own key and our, um, FIPs one 40 dash two level four baths, um, keep your own key, et cetera. So, so we take other things for our clients and then in doing so, we enable end to end the client to understand both what the status of the service itself is as well as, um, you know, how they use it in order to take into account other security considerations. >>And, and I think it is a fundamentally different, um, approach then one takes for, you know, your own it, you're responsible end to end for everything. In this case, you know, we a secure what we're doing. And then we enable through things like our security advisor, um, to do configurations in such that, that governed the developer behavior and ensure that overall together between us and the client, the posture, even of what the developers and such is understood and can be monitored and ensured that it is secure and compliant. Okay. So I just want to take an example of that. So you are responsible for let's say, securing the object store as an example, but yet at the same time the clients it organization policies that map to the edict of their organization. So they've got flexibility sort of a partnership. Okay. Am I understanding that correctly? >>Yeah, absolutely. And the question is then that it organization that's taken policies, um, we then enable our clients to use tools, everything from things that can be integrated into the dev sec ops pipeline of red hat, you know, and initiatives that are going on. We had CNCF and NIST and other places like that. Yeah. So how can they translate their risk, insecurity, postures into concrete tools? That's that we deliver, right? Everything from dev, sec ops and OpenShift. So then tools and dashboards that we have, like security advisor, um, so that they can then most effectively implement the entirety of what constitutes security on in public cloud environment with confidence. Yeah. So security in compliance slash privacy or sort of two sides of the same coin. So I want to understand, Oh, IBM cloud is approaching, Oh, compliance, obviously GDPR, yeah, yeah. Whatever. They may have, I guess 2018 in terms of the fines. >>Oh, the, the California consumer privacy act. Everybody sort of has their own little GDPR now States and regions and countries, et cetera. How is IBM supporting clients in regard to Oh, compliance such initiatives? Yeah. You know, and this is an area where, you know, again, we are working to make it as easy as possible for our clients to not only see our status on certain compliance areas, which is visible through our website on compliance, but also to achieve compliance is where there is some joint or shared responsibility. So for example, in Europe with the European banking 30, we have kind of an industry unique position and enabling clients you achieve, um, what is needed. And so we provide proactive, you know, guidance. I'm on European banking authority or a PCI DSS or other things like that. So we really are trying to take a very proactive approach to Mmm, uh, providing the guidance that clients need and meeting them in that journey over all. >>We, in addition have a specific program for financial services, um, where we announced our partnership back in November with the bank of America for financial services for a very significant control setting compliance, um, that is not just a of a bunch of little existing things, but it really is a tailored control set for the financial services industry. Um, that acknowledges the fact that, you know, getting compliance in that space can be particularly, ah, particularly challenging. So we are, are taking a very proactive approach, do helping our clients across different doctors, um, deal with those changing, you know, postures and internally as a cloud organization. Um, we are advised also by IBM Promitory, which, um, it has extensive background over 70 jurisdictions globally, changes in all these postures and in compliance and rules and such like that, that they consistently and continuously monitor. Um, and help us design the right cloud moving forward. Cause is compliance as you said is it's very much a dynamic and changing landscape. >>You know, when you talk to chief information security officers and ask them what their biggest challenges, they'll tell you. Yeah. The lack of skills. Uh, and so they're looking to automation. It really helped close that gap. And clearly cloud is sort of all about automation. So I wonder if you could just talk a little bit about what you're seeing with regard to automation generally, but specifically how it's helping, you know, close that skills gap. >>Yeah, you know, it, the, the, the topic of automation is so interesting when it intersects security because I really view this, um, transition to cloud and the use of cloud native and the use of containers and such actually is an opportunity again, yet again to improve security and compliance posture. Um, because cloud, um, and uh, the dev ops and CICB pipelines, um, and all of that of, of a cloud native build and a containerized build give you a certain opportunity both to prevent a bunch of behaviors as well as to collect certain information that may become useful later on. Um, I think actually called modernization because of the automation it brings, um, is a really, really topic for both CSOs and risk officers right now because it can not just improve the agility that you started with as a motivation to go to cloud, but it can also improve visibility into what's going on with all your workloads. >>You know, to know that a developer used a particular library and then you see, oops, maybe there's a concern about that library and you instantly know where across the entirety of your IOT that that's been deployed. That's a tremendous amount of knowledge. Um, and you can take either, you know, immediate action on that or you can through automation push out changes and things like that. Um, we use internally as a cloud provider the best of SRE and automation practices to keep our estate patched and other things like that. And that can also then translate into people's own workloads, which I think is a really exciting opportunity of cloud. >>You know, we're out of time, but I want to close and asking you sort of what we should look at 42, we had a great conversation earlier, well with Jamie Thomas about, about quantum and she talked about ideas. You get that on the IBM what what should we look forward to sort of in the coming months and even years in IBM cloud. >>Yeah. You know, we're really excited about that agility, that cloud itself for us as a company and provides, right? Like you said with quantum, it is the place that we can bring out the latest and greatest things, um, in, you know, uh, for our clients to use and experiment with and adopt their algorithms and such juice. So you're going to continue to see us taking a very aggressive posture in turning the latest and open source and technologies into cloud delivered fully managed services. Um, and so, you know, everything from what we've done already with, um, Istio is a service and can native as a server, a service and quantum as a service, et cetera. Um, you'll continue to see us take that approach that, um, you know, we want to be a fresh and vital environment for developers to consume the latest and greatest that's out there. Um, but yet as an enterprise focused company and a company, you know, very much focused on security and compliance, you'll continue to see us back those things with our own efforts to secure and then enable security, um, on our environment. >>Well, Hillary, thanks so much for coming on the cube. It's always great to have experts like yourself, uh, share with, uh, with our community. Appreciate it. >>Great. Thank you so much for having me. >>And so we're seeing cloud acceleration as a result of covert 19, but it's always been a, a real wave for the last 10 years. We're just seeing it again, accelerate even faster. This is Dave Volante for the cube. You're watching the cubes, continuous coverage of IBM thing, digital thing, 2020 people right there, but right back, right after this short, >>right.

>> Live from Las Vegas. It's The Cube. Covering Dell Technologies World 2019. Brought to you by Dell Technologies and it's ecosystem partners. >> Welcome back to Las Vegas, here at the Sands Convention Center at Dell Technologies World 2019. I'm Stu Miniman, my cohost here is David Vellante. Two sets, five hosts, three days, wall to wall coverage. All of the action for Dell Technologies, all the component pieces. Happy to welcome back to the program Ashley Gorakhpurwalla, who's the president of the server and infrastructure services at Dell EMC. Ashley, thanks so much for joining us. >> Thanks for having me. >> Good to see you. >> Alright, so we actually had Sam Grocott on and we were talking about all the product lines. And he said he's the father of power going across the line. He did admit that the power line goes back to PowerEdge, which, of course, is your baby. >> That's right. >> Give us the update, lots of discussion at the keynote. Always change in your world, so give us the latest and greatest. >> Sure, we're about 25 years old now. So PowerEdge has lived on for quite a while. We've got to be over 30 million servers out there by now. So we had a really good Dell Technology World so far. More to come, but some of the lists, real quick, of announcements that we've had and we can talk a little bit more about them. In servers, we actually went a little bit early from Dell Technology World and lined up with Intel to launch Cascade Lake, bringing Optane into server class memory. I think the industry's been waiting for it. We're ready to deliver now. And so that was earlier this month. We've put quite a bit of advancements and enhancements in our open manage enterprise and in securing the platforms. We also this week talked about a PowerEdge that's not called a PowerEdge. So we call it the DSS 8440, and really a capstone product to our AI ML portfolio. So today we already support one, two, three, four accelerators per server. Now we can go up to 10. We can support the latest Nvidia B100 tensor core GPUs, and it's really a unique system within the industry. That's going to help customers scale their training loads further and further, faster performance, more mips, very, very intense box, but one that's going to be, I think, well received within the marketplace. >> Did you say bits? >> I said Mips. >> I like that term,. >> So actually, we've got a lot of pieces that your solutions fit, but you mentioned one item, that I wonder if you could just explain to our audience the importance of SEM, is something that how does that impact solutions, the applications. It's something that a lot of times get lost in the whole general storage discussion. So maybe explain the importance of SEM in the marketplace today. >> Sure. So it's a game changer, it really will be, but it'll have to go, in our mind, through the technology adoption curve that a game changer deserves. So it's been a long time coming. We've been working on it, the industry's been working on it. Intel has been working on it for more than a decade. And if you think through it, we see customers using it in two different ways. In memory mode, expanding the capacity within nodes to levels that you can't reach with DRAM today at almost DRAM-like levels and performance, is something that a lot of customers already have models for. They can think through TCO, they can think through their performance characteristics, and it really becomes something they can consider to enhance their portfolio today, at mode, a little bit different. As we think through software from the OS level: kernel, hypervisor, application, cache, log, database, all these levels, we're going to have software that has to catch up and allow this to be the game changer it is. But already, I'll tell you the demand for systems that we're providing customers to begin their evaluations, they proof of concepts, their software development has actually doubled what we thought it would be, and we were pretty ambitious. So I think the demand is there, and we're going to see that adoption curve when the software catches up. >> And any specific use cases you're seeing early on? >> Well like I said, memory mode, I think people can get their heads around already, is are they performance, or are they capacity bound by DRAM. Start to do the economics, does it make sense. At mode, caching for sure, putting log, changing kind of the structure of how you do logs, and database is really going to be the killer app when we get there. Across the different vendors already we've seen pretty significant increases in performance, and we're early still. But I think there's a few things that our customers want to get through, and we're trying to help them with. If you have persistence in the system, you have a new level of something you have to secure, and so we're spending a lot of time with our customers helping them develop technology methodologies to say wait a minute, information, I turned the machine off and there's still information besides the hard drive or the SSD. Also can I trust the data even though it's persistent? Or do I have to have storage services at that level that help me with things like replication or snapshot or archive. So we've got a long way to go, but we're really, we believe this is a game changer, and we're developing towards that. >> And cost-wise you're sayin' slightly more expensive than DRAM. >> Probably a little bit more than slightly. >> Yeah, okay, more expensive than DRAM, and relative to flash, obviously more expensive than flash, but much higher performance, right? >> Much higher performance, and so it's just a modeling exercise, but it'll reach levels we haven't had before. And then from a software developer point of view as you go forward, you can really think about scale out systems differently. If your application was bound by capacity of DRAM or memory, this changes it quite a bit. >> So you're talking about new programming model, essentially right, that's why it's going to take some time, but you would expect maybe uptake in financial services early on. Is that fair, Or not necessarily? Healthcare? >> All solid verticals. I think it's going to be where enhancement or performance can, you know, if you pay three, four, five x the cost, but you get three, four, or five x the capability, or even less, you have to think about it, but there's some applications where latency, where performance of the database are so sensitive, and such the bottleneck today, that it's well worth it. >> When you look at the innovation pie that's going on in servers, how much is architecture, hardware architecture, versus sort of software and management? Can you sort of, I know it's a sort of general question, but give us a sense. >> Sure, I think it's interesting, is we are investing as we go forward, I think into a brand new era. So I mentioned earlier we made it to 25 years old, what's going to happen over the next 25 years. So I think most of the architectures that we develop today are highly, highly optimized for bringing data into a processor, calculating, storing. And we have very balanced, efficient, high-performance systems for that today. What are we doing going forward? Well, we're not necessarily bringing the data, describing the rules, called software, and then getting the answers anymore, right? Now what we want to do in a lot of situations, we want to bring the data, which is the most valuable asset, we actually kind of know the answers already. We want it to calculate rules for us, and that's the output. That's a different architecture. That's a different way of computing, and that's why you're seeing these heterogeneous architectures starting to form, accelerators, a lot of technology going, and innovation, and venture capital, and talent going towards really building that new model going forward for the next two decades. >> Okay, actually we've had a lot about cloud this week. When I looked at many of the solutions underneath, I kept hearing the same answer. VxRail, VxRail, I've talked to some of the team, there is more than just VxRail and some of these solutions. Sammon looked at some of the other pieces, but VxRail has been a rocket ship for the last couple of years, and of course, you know, the servers underneath driving a lot of that. Can you talk about how that plays into your portfolio and some of the architectural discussion we were seeing. How does that bleed into the HCI and hyper cloud discussions? >> Sure, so if you think of the journey we're on, 10 years ago perhaps, maybe even more recently than that, customers really were making two different choices. As a matter of fact, you guys know as well. I was organized into two different organizations. One to deal with hyper-scale, and one to deal with enterprise capability, and customers can see that. They want to be able to operate in both domains, but even we were organized differently. And if you go maybe five years ago when people started talking about software defined and HCI we finally had a mechanism to say you can build scale out of architectures. We can automate this capability for you. You don't have to actually spend all your opexs, you administration, your talent, and your time, just keeping the infrastructure up and running. And so people broke out of IT by project by Gantt chart, and into flexible architectures, right. Next thing they said is but we still aren't really operating. We're operating in silos of very flexible architecture here in my data center, very flexible architecture in the colo, very flexible architecture in software defined or SAS or cloud. How do I bring it together? So we believe there's a consistency of platform and infrastructure that allows us to move to a consistency of operations. VxRail offers that today, because we uniquely can integrate with VMWare and V Cloud Foundation, to build where now we can take care of the automation, the lifecycle management of the hardware. VMWare together integrated now can take care of the lifecycle of the software stack, all the way up to the IAS layer or beyond, and now we have the ability to say you can look upwards, you can develop, you can build on that, and even more so, if you want to then stitch that together, and have that be the control plane, you can now build that out to other native public clouds, now you have the hybrid cloud. We can actually get there, we can actually organize around it, build it. I mean it's a breakthrough for our customers. And then add on that, some customers have come back to us and said, you have the expertise to do all this for us, can I just consume it? I don't actually need to control it. And in that case we can offer it as a service, and we previewed that as Project Dimension last year, and now the teams are really happy to bring it to fruition all the way to beta with customers today, and really give customers kind of that choice. >> So what's behind that? I mean you've got a team of people sort of monitoring everything, obviously a lot of automation. What's the customer conversation like? I mean it's the early days, but what do they want to know about, do they always just want to say hey you take care of it? Or do they want to peel the layers and say okay, I want to peek behind the curtain before I sign up for this. >> Yeah, so on the platform side, customers want to know how does the integration work. Really where do I have to spend time, energy? Can I really live at this IAS layer, can I live at the PAS layer with pivotal, can I live above that? How do my workflows get managed? And when you say, we're kind of in the environment and the methodologies you already use today with V Center and V Motion and PKS. Then I think you see a light bulb go off of okay, I can really lead the administration to the machines, and the automation. Then the customer who's interested in moving everything maybe to a consumption model, then they have the next question which is can I have consistency not only of infrastructure operation, but of consumption? And that's where as a service offering, really starts to highlight the fact that we can meet you on your journey wherever you are. Some customers aren't ready for that, some are just right there saying that's really the model I want to move to for digital transformation. >> Okay, you got roughly a 20 billion dollar business growing at almost 20 percent a year, so pretty good year last year. Give us the update on your business, why are you being so successful, and I got a follow up question on component, so the supply with. >> Okay sure. So we did have a pretty good year last year. We don't break out servers, but servers are networking as you said, but about 20 billion dollars growing at 28 percent. Why? Well I think we have one of the most capable portfolios of infrastructure. We're uniquely trying to make sure that we are operating within the Dell Technologies portfolio. And so most customers, Dave, have not come to us and said you know what I'd like to do, I'd like to have like 10 more of you guys come meet with me and talk to me about a portion of my business. They said why can't you come and provide all of my needs? But I don't want to compromise. I don't want to have one best of class, and then have to compromise across my other needs. So really building kind of number one all in one place, is that promise that you don't have to compromise. Really it's changed the dynamic with a lot of customers being able to say this is my essential IT infrastructure provider. They have what I need. So that's helped quite a bit. The nature of our business I think is that we are operating from the smallest customer, you need one, all the way up to customers who need a million servers, and we're able to operate in a consistent PowerEdge tenent across all of that space. Then the, I think, and you didn't mention it, but in hyper converged, we're seeing growth rates that kind of put the server business to shame, with we were 65 percent in Q4 in an industry that's growing 40 percent that's on fire. It's a new business model, it's still emerging, but customers, the demand for hyper converged continues to go forward, because that operating model, simplicity, elastic, scale out, automated, is extremely powerful. >> And component supply right now, component pricing, is a tail wind for you. For years it's been a head wind. Is that right, it's flipped? Or not so much >> Certainly, yeah certainly the last two years has been sort of an unprecedented rise in some of our commodities in terms of cost. We're seeing that be deflationary or stable at this point, so it's really changed a little bit of the dynamic of how customers were operating within their own budgets. So now I think we're more in what we're used to in the beginning 23 years as we go forward. >> So actually, last thing, you talked about you used to have kind of a hyper-scale business. Just give us the update. I saw a quote out there that Dell puts more gear out there in hyper-scale environments, than anyone. Can you just give us a little context as to what that means? >> Sure, you know as we go forward, I think we've seen others say that they don't operate in certain businesses, they don't want to be in tier one, and you won't hear that from us. I think where we can add value, and we have incredible assets in terms of engineering, modular data center capability, capability at the edge, real assets like software supply chain delivery, across the board. We want to be able to help customers build their infrastructures. And in the service provider community, I think we've already built up relationships, credibility, and technology, to help them compete. Our standard is if you do business with us, we want you to win in your segment. We want you to transform faster than your competition, and we think we can do that for people, and I think we continue to see quite a bit of success in the service provider's space. >> Well really appreciate the updates, and congratulations on all of the progress you've made Ashley. >> Thank you, great job thanks for having me guys. >> Alright, for Dave Vellante, I'm Stu Miniman, gettin' towards the end of day two, three days wall to wall coverage. Thank you as always for watching The Cube.

(electronic dance music) (Intel Jingle) (ethereal electronic dance music) ♪ Okay ♪ (upbeat techno dance music) ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh oh ♪ ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh oh ♪ ♪ Take it back take it back ♪ ♪ Take it back ♪ ♪ Take it back take it back ♪ ♪ Take it back ♪ ♪ Take it back take it back ♪ ♪ Yeah everybody get loose yeah ♪ ♪ Yeah ♪ ♪ Ye-yeah yeah ♪ ♪ Yeah yeah ♪ ♪ Everybody everybody yeah ♪ ♪ Whoo whoo ♪ ♪ Whoo whoo ♪ ♪ Whoo yeah ♪ ♪ Everybody get loose whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ >> As a courtesy to the presenters and those around you, please silence all mobile devices, thank you. (electronic dance music) ♪ Everybody get loose ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ (upbeat salsa music) ♪ Ha ha ha ♪ ♪ Ah ♪ ♪ Ha ha ha ♪ ♪ So happy ♪ ♪ Whoo whoo ♪ (female singer scatting) >> Ladies and gentlemen, please take your seats. Our program will begin momentarily. ♪ Hey ♪ (female singer scatting) (male singer scatting) ♪ Hey ♪ ♪ Whoo ♪ (female singer scatting) (electronic dance music) ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ Red don't go ♪ ♪ All hands are in don't go ♪ ♪ In don't go ♪ ♪ Oh red go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are red don't go ♪ ♪ All hands are in red red red red ♪ ♪ All hands are in don't go ♪ ♪ All hands are in red go ♪ >> Ladies and gentlemen, there are available seats. Towards house left, house left there are available seats. If you are please standing, we ask that you please take an available seat. We will begin momentarily, thank you. ♪ Let go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ (upbeat electronic dance music) ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ I live ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Hey ♪ ♪ Yeah ♪ ♪ Oh ♪ ♪ Ah ♪ ♪ Ah ah ah ah ah ah ♪ ♪ Just make me ♪ ♪ Just make me ♪ (bouncy techno music) >> Ladies and gentlemen, once again we ask that you please take the available seats to your left, house left, there are many available seats. If you are standing, please make your way there. The program will begin momentarily, thank you. Good morning! This is Lenovo Transform 2.0! (keyboard clicks) >> Progress. Why do we always talk about it in the future? When will it finally get here? We don't progress when it's ready for us. We need it when we're ready, and we're ready now. Our hospitals and their patients need it now, our businesses and their customers need it now, our cities and their citizens need it now. To deliver intelligent transformation, we need to build it into the products and solutions we make every day. At Lenovo, we're designing the systems to fight disease, power businesses, and help you reach more customers, end-to-end security solutions to protect your data and your companies reputation. We're making IT departments more agile and cost efficient. We're revolutionizing how kids learn with VR. We're designing smart devices and software that transform the way you collaborate, because technology shouldn't just power industries, it should power people. While everybody else is talking about tomorrow, we'll keep building today, because the progress we need can't wait for the future. >> Please welcome to the stage Lenovo's Rod Lappen! (electronic dance music) (audience applauding) >> Alright. Good morning everyone! >> Good morning. >> Ooh, that was pretty good actually, I'll give it one more shot. Good morning everyone! >> Good morning! >> Oh, that's much better! Hope everyone's had a great morning. Welcome very much to the second Lenovo Transform event here in New York. I think when I got up just now on the steps I realized there's probably one thing in common all of us have in this room including myself which is, absolutely no one has a clue what I'm going to say today. So, I'm hoping very much that we get through this thing very quickly and crisply. I love this town, love New York, and you're going to hear us talk a little bit about New York as we get through here, but just before we get started I'm going to ask anyone who's standing up the back, there are plenty of seats down here, and down here on the right hand side, I think he called it house left is the professional way of calling it, but these steps to my right, your left, get up here, let's get you all seated down so that you can actually sit down during the keynote session for us. Last year we had our very first Lenovo Transform. We had about 400 people. It was here in New York, fantastic event, today, over 1,000 people. We have over 62 different technology demonstrations and about 15 breakout sessions, which I'll talk you through a little bit later on as well, so it's a much bigger event. Next year we're definitely going to be shooting for over 2,000 people as Lenovo really transforms and starts to address a lot of the technology that our commercial customers are really looking for. We were however hampered last year by a storm, I don't know if those of you who were with us last year will remember, we had a storm on the evening before Transform last year in New York, and obviously the day that it actually occurred, and we had lots of logistics. Our media people from AMIA were coming in. They took the, the plane was circling around New York for a long time, and Kamran Amini, our General Manager of our Data Center Infrastructure Group, probably one of our largest groups in the Lenovo DCG business, took 17 hours to get from Raleigh, North Carolina to New York, 17 hours, I think it takes seven or eight hours to drive. Took him 17 hours by plane to get here. And then of course this year, we have Florence. And so, obviously the hurricane Florence down there in the Carolinas right now, we tried to help, but still Kamran has made it today. Unfortunately, very tragically, we were hoping he wouldn't, but he's here today to do a big presentation a little bit later on as well. However, I do want to say, obviously, Florence is a very serious tragedy and we have to take it very serious. We got, our headquarters is in Raleigh, North Carolina. While it looks like the hurricane is just missing it's heading a little bit southeast, all of our thoughts and prayers and well wishes are obviously with everyone in the Carolinas on behalf of Lenovo, everyone at our headquarters, everyone throughout the Carolinas, we want to make sure everyone stays safe and out of harm's way. We have a great mixture today in the crowd of all customers, partners, industry analysts, media, as well as our financial analysts from all around the world. There's over 30 countries represented here and people who are here to listen to both YY, Kirk, and Christian Teismann speak today. And so, it's going to be a really really exciting day, and I really appreciate everyone coming in from all around the world. So, a big round of applause for everyone whose come in. (audience applauding) We have a great agenda for you today, and it starts obviously a very consistent format which worked very successful for us last year, and that's obviously our keynote. You'll hear from YY, our CEO, talk a little bit about the vision he has in the industry and how he sees Lenovo's turned the corner and really driving some great strategy to address our customer's needs. Kirk Skaugen, our Executive Vice President of DCG, will be up talking about how we've transformed the DCG business and once again are hitting record growth ratios for our DCG business. And then you'll hear from Christian Teismann, our SVP and General Manager for our commercial business, get up and talk about everything that's going on in our IDG business. There's really exciting stuff going on there and obviously ThinkPad being the cornerstone of that I'm sure he's going to talk to us about a couple surprises in that space as well. Then we've got some great breakout sessions, I mentioned before, 15 breakout sessions, so while this keynote section goes until about 11:30, once we get through that, please go over and explore, and have a look at all of the breakout sessions. We have all of our subject matter experts from both our PC, NBG, and our DCG businesses out to showcase what we're doing as an organization to better address your needs. And then obviously we have the technology pieces that I've also spoken about, 62 different technology displays there arranged from everything IoT, 5G, NFV, everything that's really cool and hot in the industry right now is going to be on display up there, and I really encourage all of you to get up there. So, I'm going to have a quick video to show you from some of the setup yesterday on a couple of the 62 technology displays we've got on up on stage. Okay let's go, so we've got a demonstrations to show you today, one of the greats one here is the one we've done with NC State, a high-performance computing artificial intelligence demonstration of fresh produce. It's about modeling the population growth of the planet, and how we're going to supply water and food as we go forward. Whoo. Oh, that is not an apple. Okay. (woman laughs) Second one over here is really, hey Jonas, how are you? Is really around virtual reality, and how we look at one of the most amazing sites we've got, as an install on our high-performance computing practice here globally. And you can see, obviously, that this is the Barcelona supercomputer, and, where else in New York can you get access to being able to see something like that so easily? Only here at Lenovo Transform. Whoo, okay. (audience applauding) So there's two examples of some of the technology. We're really encouraging everyone in the room after the keynote to flow into that space and really get engaged, and interact with a lot of the technology we've got up there. It seems I need to also do something about my fashion, I've just realized I've worn a vest two days in a row, so I've got to work on that as well. Alright so listen, the last thing on the agenda, we've gone through the breakout sessions and the demo, tonight at four o'clock, there's about 400 of you registered to be on the cruise boat with us, the doors will open behind me. the boat is literally at the pier right behind us. You need to make sure you're on the boat for 4:00 p.m. this evening. Outside of that, I want everyone to have a great time today, really enjoy the experience, make it as experiential as you possibly can, get out there and really get in and touch the technology. There's some really cool AI displays up there for us all to get involved in as well. So ladies and gentlemen, without further adieu, it gives me great pleasure to introduce to you a lover of tennis, as some of you would've heard last year at Lenovo Transform, as well as a lover of technology, Lenovo, and of course, New York City. I am obviously very pleasured to introduce to you Yang Yuanqing, our CEO, as we like to call him, YY. (audience applauding) (upbeat funky music) >> Good morning, everyone. >> Good morning. >> Thank you Rod for that introduction. Welcome to New York City. So, this is the second year in a row we host our Transform event here, because New York is indeed one of the most transformative cities in the world. Last year on this stage, I spoke about the Fourth Industrial Revolution, and our vision around the intelligent transformation, how it would fundamentally change the nature of business and the customer relationships. And why preparing for this transformation is the key for the future of our company. And in the last year I can assure you, we were being very busy doing just that, from searching and bringing global talents around the world to the way we think about every product and every investment we make. I was here in New York just a month ago to announce our fiscal year Q1 earnings, which was a good day for us. I think now the world believes it when we say Lenovo has truly turned the corner to a new phase of growth and a new phase of acceleration in executing the transformation strategy. That's clear to me is that the last few years of a purposeful disruption at Lenovo have led us to a point where we can now claim leadership of the coming intelligent transformation. People often asked me, what is the intelligent transformation? I was saying this way. This is the unlimited potential of the Fourth Industrial Revolution driven by artificial intelligence being realized, ordering a pizza through our speaker, and locking the door with a look, letting your car drive itself back to your home. This indeed reflect the power of AI, but it just the surface of it. The true impact of AI will not only make our homes smarter and offices more efficient, but we are also completely transformed every value chip in every industry. However, to realize these amazing possibilities, we will need a structure built around the key components, and one that touches every part of all our lives. First of all, explosions in new technology always lead to new structures. This has happened many times before. In the early 20th century, thousands of companies provided a telephone service. City streets across the US looked like this, and now bundles of a microscopic fiber running from city to city bring the world closer together. Here's what a driving was like in the US, up until 1950s. Good luck finding your way. (audience laughs) And today, millions of vehicles are organized and routed daily, making the world more efficient. Structure is vital, from fiber cables and the interstate highways, to our cells bounded together to create humans. Thankfully the structure for intelligent transformation has emerged, and it is just as revolutionary. What does this new structure look like? We believe there are three key building blocks, data, computing power, and algorithms. Ever wondered what is it behind intelligent transformation? What is fueling this miracle of human possibility? Data. As the Internet becomes ubiquitous, not only PCs, mobile phones, have come online and been generating data. Today it is the cameras in this room, the climate controls in our offices, or the smart displays in our kitchens at home. The number of smart devices worldwide will reach over 20 billion in 2020, more than double the number in 2017. These devices and the sensors are connected and generating massive amount of data. By 2020, the amount of data generated will be 57 times more than all the grains of sand on Earth. This data will not only make devices smarter, but will also fuel the intelligence of our homes, offices, and entire industries. Then we need engines to turn the fuel into power, and the engine is actually the computing power. Last but not least the advanced algorithms combined with Big Data technology and industry know how will form vertical industrial intelligence and produce valuable insights for every value chain in every industry. When these three building blocks all come together, it will change the world. At Lenovo, we have each of these elements of intelligent transformations in a single place. We have built our business around the new structure of intelligent transformation, especially with mobile and the data center now firmly part of our business. I'm often asked why did you acquire these businesses? Why has a Lenovo gone into so many fields? People ask the same questions of the companies that become the leaders of the information technology revolution, or the third industrial transformation. They were the companies that saw the future and what the future required, and I believe Lenovo is the company today. From largest portfolio of devices in the world, leadership in the data center field, to the algorithm-powered intelligent vertical solutions, and not to mention the strong partnership Lenovo has built over decades. We are the only company that can unify all these essential assets and deliver end to end solutions. Let's look at each part. We now understand the important importance data plays as fuel in intelligent transformation. Hundreds of billions of devices and smart IoTs in the world are generating better and powering the intelligence. Who makes these devices in large volume and variety? Who puts these devices into people's home, offices, manufacturing lines, and in their hands? Lenovo definitely has the front row seats here. We are number one in PCs and tablets. We also produces smart phones, smart speakers, smart displays. AR/VR headsets, as well as commercial IoTs. All of these smart devices, or smart IoTs are linked to each other and to the cloud. In fact, we have more than 20 manufacturing facilities in China, US, Brazil, Japan, India, Mexico, Germany, and more, producing various devices around the clock. We actually make four devices every second, and 37 motherboards every minute. So, this factory located in my hometown, Hu-fi, China, is actually the largest laptop factory in the world, with more than three million square feet. So, this is as big as 42 soccer fields. Our scale and the larger portfolio of devices gives us access to massive amount of data, which very few companies can say. So, why is the ability to scale so critical? Let's look again at our example from before. The early days of telephone, dozens of service providers but only a few companies could survive consolidation and become the leader. The same was true for the third Industrial Revolution. Only a few companies could scale, only a few could survive to lead. Now the building blocks of the next revolution are locking into place. The (mumbles) will go to those who can operate at the scale. So, who could foresee the total integration of cloud, network, and the device, need to deliver intelligent transformation. Lenovo is that company. We are ready to scale. Next, our computing power. Computing power is provided in two ways. On one hand, the modern supercomputers are providing the brute force to quickly analyze the massive data like never before. On the other hand the cloud computing data centers with the server storage networking capabilities, and any computing IoT's, gateways, and miniservers are making computing available everywhere. Did you know, Lenovo is number one provider of super computers worldwide? 170 of the top 500 supercomputers, run on Lenovo. We hold 89 World Records in key workloads. We are number one in x86 server reliability for five years running, according to ITIC. a respected provider of industry research. We are also the fastest growing provider of hyperscale public cloud, hyper-converged and aggressively growing in edge computing. cur-ges target, we are expand on this point soon. And finally to run these individual nodes into our symphony, we must transform the data and utilize the computing power with advanced algorithms. Manufactured, industry maintenance, healthcare, education, retail, and more, so many industries are on the edge of intelligent transformation to improve efficiency and provide the better products and services. We are creating advanced algorithms and the big data tools combined with industry know-how to provide intelligent vertical solutions for several industries. In fact, we studied at Lenovo first. Our IT and research teams partnered with our global supply chain to develop an AI that improved our demand forecasting accuracy. Beyond managing our own supply chain we have offered our deep learning supply focused solution to other manufacturing companies to improve their efficiency. In the best case, we have improved the demand, focused the accuracy by 30 points to nearly 90 percent, for Baosteel, the largest of steel manufacturer in China, covering the world as well. Led by Lenovo research, we launched the industry-leading commercial ready AR headset, DaystAR, partnering with companies like the ones in this room. This technology is being used to revolutionize the way companies service utility, and even our jet engines. Using our workstations, servers, and award-winning imaging processing algorithms, we have partnered with hospitals to process complex CT scan data in minutes. So, this enable the doctors to more successfully detect the tumors, and it increases the success rate of cancer diagnosis all around the world. We are also piloting our smart IoT driven warehouse solution with one of the world's largest retail companies to greatly improve the efficiency. So, the opportunities are endless. This is where Lenovo will truly shine. When we combine the industry know-how of our customers with our end-to-end technology offerings, our intelligent vertical solutions like this are growing, which Kirk and Christian will share more. Now, what will drive this transformation even faster? The speed at which our networks operate, specifically 5G. You may know that Lenovo just launched the first-ever 5G smartphone, our Moto Z3, with the new 5G Moto model. We are partnering with multiple major network providers like Verizon, China Mobile. With the 5G model scheduled to ship early next year, we will be the first company to provide a 5G mobile experience to any users, customers. This is amazing innovation. You don't have to buy a new phone, just the 5G clip on. What can I say, except wow. (audience laughs) 5G is 10 times the fast faster than 4G. Its download speed will transform how people engage with the world, driverless car, new types of smart wearables, gaming, home security, industrial intelligence, all will be transformed. Finally, accelerating with partners, as ready as we are at Lenovo, we need partners to unlock our full potential, partners here to create with us the edge of the intelligent transformation. The opportunities of intelligent transformation are too profound, the scale is too vast. No company can drive it alone fully. We are eager to collaborate with all partners that can help bring our vision to life. We are dedicated to open partnerships, dedicated to cross-border collaboration, unify the standards, share the advantage, and market the synergies. We partner with the biggest names in the industry, Intel, Microsoft, AMD, Qualcomm, Google, Amazon, and Disney. We also find and partner with the smaller innovators as well. We're building the ultimate partner experience, open, shared, collaborative, diverse. So, everything is in place for intelligent transformation on a global scale. Smart devices are everywhere, the infrastructure is in place, networks are accelerating, and the industries demand to be more intelligent, and Lenovo is at the center of it all. We are helping to drive change with the hundreds of companies, companies just like yours, every day. We are your partner for intelligent transformation. Transformation never stops. This is what you will hear from Kirk, including details about Lenovo NetApp global partnership we just announced this morning. We've made the investments in every single aspect of the technology. We have the end-to-end resources to meet your end-to-end needs. As you attend the breakout session this afternoon, I hope you see for yourself how much Lenovo has transformed as a company this past year, and how we truly are delivering a future of intelligent transformation. Now, let me invite to the stage Kirk Skaugen, our president of Data Center growth to tell you about the exciting transformation happening in the global Data C enter market. Thank you. (audience applauding) (upbeat music) >> Well, good morning. >> Good morning. >> Good morning! >> Good morning! >> Excellent, well, I'm pleased to be here this morning to talk about how we're transforming the Data Center and taking you as our customers through your own intelligent transformation journey. Last year I stood up here at Transform 1.0, and we were proud to announce the largest Data Center portfolio in Lenovo's history, so I thought I'd start today and talk about the portfolio and the progress that we've made over the last year, and the strategies that we have going forward in phase 2.0 of Lenovo's transformation to be one of the largest data center companies in the world. We had an audacious vision that we talked about last year, and that is to be the most trusted data center provider in the world, empowering customers through the new IT, intelligent transformation. And now as the world's largest supercomputer provider, giving something back to humanity, is very important this week with the hurricanes now hitting North Carolina's coast, but we take this most trusted aspect very seriously, whether it's delivering the highest quality products on time to you as customers with the highest levels of security, or whether it's how we partner with our channel partners and our suppliers each and every day. You know we're in a unique world where we're going from hundreds of millions of PCs, and then over the next 25 years to hundred billions of connected devices, so each and every one of you is going through this intelligent transformation journey, and in many aspects were very early in that cycle. And we're going to talk today about our role as the largest supercomputer provider, and how we're solving humanity's greatest challenges. Last year we talked about two special milestones, the 25th anniversary of ThinkPad, but also the 25th anniversary of Lenovo with our IBM heritage in x86 computing. I joined the workforce in 1992 out of college, and the IBM first personal server was launching at the same time with an OS2 operating system and a free mouse when you bought the server as a marketing campaign. (audience laughing) But what I want to be very clear today, is that the innovation engine is alive and well at Lenovo, and it's really built on the culture that we're building as a company. All of these awards at the bottom are things that we earned over the last year at Lenovo. As a Fortune now 240 company, larger than companies like Nike, or AMEX, or Coca-Cola. The one I'm probably most proud of is Forbes first list of the top 2,000 globally regarded companies. This was something where 15,000 respondents in 60 countries voted based on ethics, trustworthiness, social conduct, company as an employer, and the overall company performance, and Lenovo was ranked number 27 of 2000 companies by our peer group, but we also now one of-- (audience applauding) But we also got a perfect score in the LGBTQ Equality Index, exemplifying the diversity internally. We're number 82 in the top working companies for mothers, top working companies for fathers, top 100 companies for sustainability. If you saw that factory, it's filled with solar panels on the top of that. And now again, one of the top global brands in the world. So, innovation is built on a customer foundation of trust. We also said last year that we'd be crossing an amazing milestone. So we did, over the last 12 months ship our 20 millionth x86 server. So, thank you very much to our customers for this milestone. (audience applauding) So, let me recap some of the transformation elements that have happened over the last year. Last year I talked about a lot of brand confusion, because we had the ThinkServer brand from the legacy Lenovo, the System x, from IBM, we had acquired a number of networking companies, like BLADE Network Technologies, et cetera, et cetera. Over the last year we've been ramping based on two brand structures, ThinkAgile for next generation IT, and all of our software-defined infrastructure products and ThinkSystem as the world's highest performance, highest reliable x86 server brand, but for servers, for storage, and for networking. We have transformed every single aspect of the customer experience. A year and a half ago, we had four different global channel programs around the world. Typically we're about twice the mix to our channel partners of any of our competitors, so this was really important to fix. We now have a single global Channel program, and have technically certified over 11,000 partners to be technical experts on our product line to deliver better solutions to our customer base. Gardner recently recognized Lenovo as the 26th ranked supply chain in the world. And, that's a pretty big honor, when you're up there with Amazon and Walmart and others, but in tech, we now are in the top five supply chains. You saw the factory network from YY, and today we'll be talking about product shipping in more than 160 countries, and I know there's people here that I've met already this morning, from India, from South Africa, from Brazil and China. We announced new Premier Support services, enabling you to go directly to local language support in nine languages in 49 countries in the world, going directly to a native speaker level three support engineer. And today we have more than 10,000 support specialists supporting our products in over 160 countries. We've delivered three times the number of engineered solutions to deliver a solutions orientation, whether it's on HANA, or SQL Server, or Oracle, et cetera, and we've completely reengaged our system integrator channel. Last year we had the CIO of DXE on stage, and here we're talking about more than 175 percent growth through our system integrator channel in the last year alone as we've brought that back and really built strong relationships there. So, thank you very much for amazing work here on the customer experience. (audience applauding) We also transformed our leadership. We thought it was extremely important with a focus on diversity, to have diverse talent from the legacy IBM, the legacy Lenovo, but also outside the industry. We made about 19 executive changes in the DCG group. This is the most senior leadership team within DCG, all which are newly on board, either from our outside competitors mainly over the last year. About 50 percent of our executives were now hired internally, 50 percent externally, and 31 percent of those new executives are diverse, representing the diversity of our global customer base and gender. So welcome, and most of them you're going to be able to meet over here in the breakout sessions later today. (audience applauding) But some things haven't changed, they're just keeping getting better within Lenovo. So, last year I got up and said we were committed with the new ThinkSystem brand to be a world performance leader. You're going to see that we're sponsoring Ducati for MotoGP. You saw the Ferrari out there with Formula One. That's not a surprise. We want the Lenovo ThinkSystem and ThinkAgile brands to be synonymous with world record performance. So in the last year we've gone from 39 to 89 world records, and partners like Intel would tell you, we now have four times the number of world record workloads on Lenovo hardware than any other server company on the planet today, with more than 89 world records across HPC, Java, database, transaction processing, et cetera. And we're proud to have just brought on Doug Fisher from Intel Corporation who had about 10-17,000 people on any given year working for him in workload optimizations across all of our software. It's just another testament to the leadership team we're bringing in to keep focusing on world-class performance software and solutions. We also per ITIC, are the number one now in x86 server reliability five years running. So, this is a survey where CIOs are in a blind survey asked to submit their reliability of their uptime on their x86 server equipment over the last 365 days. And you can see from 2016 to 2017 the downtime, there was over four hours as noted by the 750 CXOs in more than 20 countries is about one percent for the Lenovo products, and is getting worse generation from generation as we went from Broadwell to Pearlie. So we're taking our reliability, which was really paramount in the IBM System X heritage, and ensuring that we don't just recognize high performance but we recognize the highest level of reliability for mission-critical workloads. And what that translates into is that we at once again have been ranked number one in customer satisfaction from you our customers in 19 of 22 attributes, in North America in 18 of 22. This is a survey by TVR across hundreds of customers of us and our top competitors. This is the ninth consecutive study that we've been ranked number one in customer satisfaction, so we're taking this extremely seriously, and in fact YY now has increased the compensation of every single Lenovo employee. Up to 40 percent of their compensation bonus this year is going to be based on customer metrics like quality, order to ship, and things of this nature. So, we're really putting every employee focused on customer centricity this year. So, the summary on Transform 1.0 is that every aspect of what you knew about Lenovo's data center group has transformed, from the culture to the branding to dedicated sales and marketing, supply chain and quality groups, to a worldwide channel program and certifications, to new system integrator relationships, and to the new leadership team. So, rather than me just talk about it, I thought I'd share a quick video about what we've done over the last year, if you could run the video please. Turn around for a second. (epic music) (audience applauds) Okay. So, thank you to all our customers that allowed us to publicly display their logos in that video. So, what that means for you as investors, and for the investor community out there is, that our customers have responded, that this year Gardner just published that we are the fastest growing server company in the top 10, with 39 percent growth quarter-on-quarter, and 49 percent growth year-on-year. If you look at the progress we've made since the transformation the last three quarters publicly, we've grown 17 percent, then 44 percent, then 68 percent year on year in revenue, and I can tell you this quarter I'm as confident as ever in the financials around the DCG group, and it hasn't been in one area. You're going to see breakout sessions from hyperscale, software-defined, and flash, which are all growing more than a 100 percent year-on-year, supercomputing which we'll talk about shortly, now number one, and then ultimately from profitability, delivering five consecutive quarters of pre-tax profit increase, so I think, thank you very much to the customer base who's been working with us through this transformation journey. So, you're here to really hear what's next on 2.0, and that's what I'm excited to talk about today. Last year I came up with an audacious goal that we would become the largest supercomputer company on the planet by 2020, and this graph represents since the acquisition of the IBM System x business how far we were behind being the number one supercomputer. When we started we were 182 positions behind, even with the acquisition for example of SGI from HP, we've now accomplished our goal actually two years ahead of time. We're now the largest supercomputer company in the world. About one in every four supercomputers, 117 on the list, are now Lenovo computers, and you saw in the video where the universities are said, but I think what I'm most proud of is when your customers rank you as the best. So the awards at the bottom here, are actually Readers Choice from the last International Supercomputing Show where the scientific researchers on these computers ranked their vendors, and we were actually rated the number one server technology in supercomputing with our ThinkSystem SD530, and the number one storage technology with our ThinkSystem DSS-G, but more importantly what we're doing with the technology. You're going to see we won best in life sciences, best in data analytics, and best in collaboration as well, so you're going to see all of that in our breakout sessions. As you saw in the video now, 17 of the top 25 research institutions in the world are now running Lenovo supercomputers. And again coming from Raleigh and watching that hurricane come across the Atlantic, there are eight supercomputers crunching all of those models you see from Germany to Malaysia to Canada, and we're happy to have a SciNet from University of Toronto here with us in our breakout session to talk about what they're doing on climate modeling as well. But we're not stopping there. We just announced our new Neptune warm water cooling technology, which won the International Supercomputing Vendor Showdown, the first time we've won that best of show in 25 years, and we've now installed this. We're building out LRZ in Germany, the first ever warm water cooling in Peking University, at the India Space Propulsion Laboratory, at the Malaysian Weather and Meteorological Society, at Uninett, at the largest supercomputer in Norway, T-Systems, University of Birmingham. This is truly amazing technology where we're actually using water to cool the machine to deliver a significantly more energy-efficient computer. Super important, when we're looking at global warming and some of the electric bills can be millions of dollars just for one computer, and could actually power a small city just with the technology from the computer. We've built AI centers now in Morrisville, Stuttgart, Taipei, and Beijing, where customers can bring their AI workloads in with experts from Intel, from Nvidia, from our FPGA partners, to work on their workloads, and how they can best implement artificial intelligence. And we also this year launched LICO which is Lenovo Intelligent Compute Orchestrator software, and it's a software solution that simplifies the management and use of distributed clusters in both HPC and AI model development. So, what it enables you to do is take a single cluster, and run both HPC and AI workloads on it simultaneously, delivering better TCO for your environment, so check out LICO as well. A lot of the customers here and Wall Street are very excited and using it already. And we talked about solving humanity's greatest challenges. In the breakout session, you're going to have a virtual reality experience where you're going to be able to walk through what as was just ranked the world's most beautiful data center, the Barcelona Supercomputer. So, you can actually walk through one of the largest supercomputers in the world from Barcelona. You can see the work we're doing with NC State where we're going to have to grow the food supply of the world by 50 percent, and there's not enough fresh water in the world in the right places to actually make all those crops grow between now and 2055, so you're going to see the progression of how they're mapping the entire globe and the water around the world, how to build out the crop population over time using AI. You're going to see our work with Vestas is this largest supercomputer provider in the wind turbine areas, how they're working on wind energy, and then with University College London, how they're working on some of the toughest particle physics calculations in the world. So again, lots of opportunity here. Take advantage of it in the breakout sessions. Okay, let me transition to hyperscale. So in hyperscale now, we have completely transformed our business model. We are now powering six of the top 10 hyperscalers in the world, which is a significant difference from where we were two years ago. And the reason we're doing that, is we've coined a term called ODM+. We believe that hyperscalers want more procurement power than an ODM, and Lenovo is doing about $18 billion of procurement a year. They want a broader global supply chain that they can get from a local system integrator. We're more than 160 countries around the world, but they want the same world-class quality and reliability like they get from an MNC. So, what we're doing now is instead of just taking off the shelf motherboards from somewhere, we're starting with a blank sheet of paper, we're working with the customer base on customized SKUs and you can see we already are developing 33 custom solutions for the largest hyperscalers in the world. And then we're not just running notebooks through this factory where YY said, we're running 37 notebook boards a minute, we're now putting in tens and tens and tens of thousands of server board capacity per month into this same factory, so absolutely we can compete with the most aggressive ODM's in the world, but it's not just putting these things in in the motherboard side, we're also building out these systems all around the world, India, Brazil, Hungary, Mexico, China. This is an example of a new hyperscale customer we've had this last year, 34,000 servers we delivered in the first six months. The next 34,000 servers we delivered in 68 days. The next 34,000 servers we delivered in 35 days, with more than 99 percent on-time delivery to 35 data centers in 14 countries as diverse as South Africa, India, China, Brazil, et cetera. And I'm really ashamed to say it was 99.3, because we did have a forklift driver who rammed their forklift right through the middle of the one of the server racks. (audience laughing) At JFK Airport that we had to respond to, but I think this gives you a perspective of what it is to be a top five global supply chain and technology. So last year, I said we would invest significantly in IP, in joint ventures, and M and A to compete in software defined, in networking, and in storage, so I wanted to give you an update on that as well. Our newest software-defined partnership is with Cloudistics, enabling a fully composable cloud infrastructure. It's an exclusive agreement, you can see them here. I think Nag, our founder, is going to be here today, with a significant Lenovo investment in the company. So, this new ThinkAgile CP series delivers the simplicity of the public cloud, on-premise with exceptional support and a marketplace of essential enterprise applications all with a single click deployment. So simply put, we're delivering a private cloud with a premium experience. It's simple in that you need no specialists to deploy it. An IT generalist can set it up and manage it. It's agile in that you can provision dozens of workloads in minutes, and it's transformative in that you get all of the goodness of public cloud on-prem in a private cloud to unlock opportunity for use. So, we're extremely excited about the ThinkAgile CP series that's now shipping into the marketplace. Beyond that we're aggressively ramping, and we're either doubling, tripling, or quadrupling our market share as customers move from traditional server technology to software-defined technology. With Nutanix we've been public, growing about more than 150 percent year-on-year, with Nutanix as their fastest growing Nutanix partner, but today I want to set another audacious goal. I believe we cannot just be Nutanix's fastest growing partner but we can become their largest partner within two years. On Microsoft, we are already four times our market share on Azure stack of our traditional business. We were the first to launch our ThinkAgile on Broadwell and on Skylake with the Azure Stack Infrastructure. And on VMware we're about twice our market segment share. We were the first to deliver an Intel-optimized Optane-certified VSAN node. And with Optane technology, we're delivering 50 percent more VM density than any competitive SSD system in the marketplace, about 10 times lower latency, four times the performance of any SSD system out there, and Lenovo's first to market on that. And at VMworld you saw CEO Pat Gelsinger of VMware talked about project dimension, which is Edge as a service, and we're the only OEM beyond the Dell family that is participating today in project dimension. Beyond that you're going to see a number of other partnerships we have. I'm excited that we have the city of Bogota Columbia here, an eight million person city, where we announced a 3,000 camera video surveillance solution last month. With pivot three you're going to see city of Bogota in our breakout sessions. You're going to see a new partnership with Veeam around backup that's launching today. You're going to see partnerships with scale computing in IoT and hyper-converged infrastructure working on some of the largest retailers in the world. So again, everything out in the breakout session. Transitioning to storage and data management, it's been a great year for Lenovo, more than a 100 percent growth year-on-year, 2X market growth in flash arrays. IDC just reported 30 percent growth in storage, number one in price performance in the world and the best HPC storage product in the top 500 with our ThinkSystem DSS G, so strong coverage, but I'm excited today to announce for Transform 2.0 that Lenovo is launching the largest data management and storage portfolio in our 25-year data center history. (audience applauding) So a year ago, the largest server portfolio, becoming the largest fastest growing server OEM, today the largest storage portfolio, but as you saw this morning we're not doing it alone. Today Lenovo and NetApp, two global powerhouses are joining forces to deliver a multi-billion dollar global alliance in data management and storage to help customers through their intelligent transformation. As the fastest growing worldwide server leader and one of the fastest growing flash array and data management companies in the world, we're going to deliver more choice to customers than ever before, global scale that's never been seen, supply chain efficiencies, and rapidly accelerating innovation and solutions. So, let me unwrap this a little bit for you and talk about what we're announcing today. First, it's the largest portfolio in our history. You're going to see not just storage solutions launching today but a set of solution recipes from NetApp that are going to make Lenovo server and NetApp or Lenovo storage work better together. The announcement enables Lenovo to go from covering 15 percent of the global storage market to more than 90 percent of the global storage market and distribute these products in more than 160 countries around the world. So we're launching today, 10 new storage platforms, the ThinkSystem DE and ThinkSystem DM platforms. They're going to be centrally managed, so the same XClarity management that you've been using for server, you can now use across all of your storage platforms as well, and it'll be supported by the same 10,000 plus service personnel that are giving outstanding customer support to you today on the server side. And we didn't come up with this in the last month or the last quarter. We're announcing availability in ordering today and shipments tomorrow of the first products in this portfolio, so we're excited today that it's not just a future announcement but something you as customers can take advantage of immediately. (audience applauding) The second part of the announcement is we are announcing a joint venture in China. Not only will this be a multi-billion dollar global partnership, but Lenovo will be a 51 percent owner, NetApp a 49 percent owner of a new joint venture in China with the goal of becoming in the top three storage companies in the largest data and storage market in the world. We will deliver our R and D in China for China, pooling our IP and resources together, and delivering a single route to market through a complementary channel, not just in China but worldwide. And in the future I just want to tell everyone this is phase one. There is so much exciting stuff. We're going to be on the stage over the next year talking to you about around integrated solutions, next-generation technologies, and further synergies and collaborations. So, rather than just have me talk about it, I'd like to welcome to the stage our new partner NetApp and Brad Anderson who's the senior vice president and general manager of NetApp Cloud Infrastructure. (upbeat music) (audience applauding) >> Thank You Kirk. >> So Brad, we've known each other a long time. It's an exciting day. I'm going to give you the stage and allow you to say NetApp's perspective on this announcement. >> Very good, thank you very much, Kirk. Kirk and I go back to I think 1994, so hey good morning and welcome. My name is Brad Anderson. I manage the Cloud Infrastructure Group at NetApp, and I am honored and privileged to be here at Lenovo Transform, particularly today on today's announcement. Now, you've heard a lot about digital transformation about how companies have to transform their IT to compete in today's global environment. And today's announcement with the partnership between NetApp and Lenovo is what that's all about. This is the joining of two global leaders bringing innovative technology in a simplified solution to help customers modernize their IT and accelerate their global digital transformations. Drawing on the strengths of both companies, Lenovo's high performance compute world-class supply chain, and NetApp's hybrid cloud data management, hybrid flash and all flash storage solutions and products. And both companies providing our customers with the global scale for them to be able to meet their transformation goals. At NetApp, we're very excited. This is a quote from George Kurian our CEO. George spent all day yesterday with YY and Kirk, and would have been here today if it hadn't been also our shareholders meeting in California, but I want to just convey how excited we are for all across NetApp with this partnership. This is a partnership between two companies with tremendous market momentum. Kirk took you through all the amazing results that Lenovo has accomplished, number one in supercomputing, number one in performance, number one in x86 reliability, number one in x86 customers sat, number five in supply chain, really impressive and congratulations. Like Lenovo, NetApp is also on a transformation journey, from a storage company to the data authority in hybrid cloud, and we've seen some pretty impressive momentum as well. Just last week we became number one in all flash arrays worldwide, catching EMC and Dell, and we plan to keep on going by them, as we help customers modernize their their data centers with cloud connected flash. We have strategic partnerships with the largest hyperscalers to provide cloud native data services around the globe and we are having success helping our customers build their own private clouds with just, with a new disruptive hyper-converged technology that allows them to operate just like hyperscalers. These three initiatives has fueled NetApp's transformation, and has enabled our customers to change the world with data. And oh by the way, it has also fueled us to have meet or have beaten Wall Street's expectations for nine quarters in a row. These are two companies with tremendous market momentum. We are also building this partnership for long term success. We think about this as phase one and there are two important components to phase one. Kirk took you through them but let me just review them. Part one, the establishment of a multi-year commitment and a collaboration agreement to offer Lenovo branded flash products globally, and as Kurt said in 160 countries. Part two, the formation of a joint venture in PRC, People's Republic of China, that will provide long term commitment, joint product development, and increase go-to-market investment to meet the unique needs to China. Both companies will put in storage technologies and storage expertise to form an independent JV that establishes a data management company in China for China. And while we can dream about what phase two looks like, our entire focus is on making phase one incredibly successful and I'm pleased to repeat what Kirk, is that the first products are orderable and shippable this week in 160 different countries, and you will see our two companies focusing on the here and now. On our joint go to market strategy, you'll see us working together to drive strategic alignment, focused execution, strong governance, and realistic expectations and milestones. And it starts with the success of our customers and our channel partners is job one. Enabling customers to modernize their legacy IT with complete data center solutions, ensuring that our customers get the best from both companies, new offerings the fuel business success, efficiencies to reinvest in game-changing initiatives, and new solutions for new mission-critical applications like data analytics, IoT, artificial intelligence, and machine learning. Channel partners are also top of mind for both our two companies. We are committed to the success of our existing and our future channel partners. For NetApp channel partners, it is new pathways to new segments and to new customers. For Lenovo's channel partners, it is the competitive weapons that now allows you to compete and more importantly win against Dell, EMC, and HP. And the good news for both companies is that our channel partner ecosystem is highly complementary with minimal overlap. Today is the first day of a very exciting partnership, of a partnership that will better serve our customers today and will provide new opportunities to both our companies and to our partners, new products to our customers globally and in China. I am personally very excited. I will be on the board of the JV. And so, I look forward to working with you, partnering with you and serving you as we go forward, and with that, I'd like to invite Kirk back up. (audience applauding) >> Thank you. >> Thank you. >> Well, thank you, Brad. I think it's an exciting overview, and these products will be manufactured in China, in Mexico, in Hungary, and around the world, enabling this amazing supply chain we talked about to deliver in over 160 countries. So thank you Brad, thank you George, for the amazing partnership. So again, that's not all. In Transform 2.0, last year, we talked about the joint ventures that were coming. I want to give you a sneak peek at what you should expect at future Lenovo events around the world. We have this Transform in Beijing in a couple weeks. We'll then be repeating this in 20 different locations roughly around the world over the next year, and I'm excited probably more than ever about what else is coming. Let's talk about Telco 5G and network function virtualization. Today, Motorola phones are certified on 46 global networks. We launched the world's first 5G upgradable phone here in the United States with Verizon. Lenovo DCG sells to 58 telecommunication providers around the world. At Mobile World Congress in Barcelona and Shanghai, you saw China Telecom and China Mobile in the Lenovo booth, China Telecom showing a video broadband remote access server, a VBRAS, with video streaming demonstrations with 2x less jitter than they had seen before. You saw China Mobile with a virtual remote access network, a VRAN, with greater than 10 times the throughput and 10x lower latency running on Lenovo. And this year, we'll be launching a new NFV company, a software company in China for China to drive the entire NFV stack, delivering not just hardware solutions, but software solutions, and we've recently hired a new CEO. You're going to hear more about that over the next several quarters. Very exciting as we try to drive new economics into the networks to deliver these 20 billion devices. We're going to need new economics that I think Lenovo can uniquely deliver. The second on IoT and edge, we've integrated on the device side into our intelligent devices group. With everything that's going to consume electricity computes and communicates, Lenovo is in a unique position on the device side to take advantage of the communications from Motorola and being one of the largest device companies in the world. But this year, we're also going to roll out a comprehensive set of edge gateways and ruggedized industrial servers and edge servers and ISP appliances for the edge and for IoT. So look for that as well. And then lastly, as a service, you're going to see Lenovo delivering hardware as a service, device as a service, infrastructure as a service, software as a service, and hardware as a service, not just as a glorified leasing contract, but with IP, we've developed true flexible metering capability that enables you to scale up and scale down freely and paying strictly based on usage, and we'll be having those announcements within this fiscal year. So Transform 2.0, lots to talk about, NetApp the big news of the day, but a lot more to come over the next year from the Data Center group. So in summary, I'm excited that we have a lot of customers that are going to be on stage with us that you saw in the video. Lots of testimonials so that you can talk to colleagues of yourself. Alamos Gold from Canada, a Canadian gold producer, Caligo for data optimization and privacy, SciNet, the largest supercomputer we've ever put into North America, and the largest in Canada at the University of Toronto will be here talking about climate change. City of Bogota again with our hyper-converged solutions around smart city putting in 3,000 cameras for criminal detection, license plate detection, et cetera, and then more from a channel mid market perspective, Jerry's Foods, which is from my home state of Wisconsin, and Minnesota which has about 57 stores in the specialty foods market, and how they're leveraging our IoT solutions as well. So again, about five times the number of demos that we had last year. So in summary, first and foremost to the customers, thank you for your business. It's been a great journey and I think we're on a tremendous role. You saw from last year, we're trying to build credibility with you. After the largest server portfolio, we're now the fastest-growing server OEM per Gardner, number one in performance, number one in reliability, number one in customer satisfaction, number one in supercomputing. Today, the largest storage portfolio in our history, with the goal of becoming the fastest growing storage company in the world, top three in China, multibillion-dollar collaboration with NetApp. And the transformation is going to continue with new edge gateways, edge servers, NFV solutions, telecommunications infrastructure, and hardware as a service with dynamic metering. So thank you for your time. I've looked forward to meeting many of you over the next day. We appreciate your business, and with that, I'd like to bring up Rod Lappen to introduce our next speaker. Rod? (audience applauding) >> Thanks, boss, well done. Alright ladies and gentlemen. No real secret there. I think we've heard why I might talk about the fourth Industrial Revolution in data and exactly what's going on with that. You've heard Kirk with some amazing announcements, obviously now with our NetApp partnership, talk about 5G, NFV, cloud, artificial intelligence, I think we've hit just about all the key hot topics. It's with great pleasure that I now bring up on stage Mr. Christian Teismann, our senior vice president and general manager of commercial business for both our PCs and our IoT business, so Christian Teismann. (techno music) Here, take that. >> Thank you. I think I'll need that. >> Okay, Christian, so obviously just before we get down, you and I last year, we had a bit of a chat about being in New York. >> Exports. >> You were an expat in New York for a long time. >> That's true. >> And now, you've moved from New York. You're in Munich? >> Yep. >> How does that feel? >> Well Munich is a wonderful city, and it's a great place to live and raise kids, but you know there's no place in the world like New York. >> Right. >> And I miss it a lot, quite frankly. >> So what exactly do you miss in New York? >> Well there's a lot of things in New York that are unique, but I know you spent some time in Japan, but I still believe the best sushi in the world is still in New York City. (all laughing) >> I will beg to differ. I will beg to differ. I think Mr. Guchi-san from Softbank is here somewhere. He will get up an argue very quickly that Japan definitely has better sushi than New York. But obviously you know, it's a very very special place, and I have had sushi here, it's been fantastic. What about Munich? Anything else that you like in Munich? >> Well I mean in Munich, we have pork knuckles. >> Pork knuckles. (Christian laughing) Very similar sushi. >> What is also very fantastic, but we have the real, the real Oktoberfest in Munich, and it starts next week, mid-September, and I think it's unique in the world. So it's very special as well. >> Oktoberfest. >> Yes. >> Unfortunately, I'm not going this year, 'cause you didn't invite me, but-- (audience chuckling) How about, I think you've got a bit of a secret in relation to Oktoberfest, probably not in Munich, however. >> It's a secret, yes, but-- >> Are you going to share? >> Well I mean-- >> See how I'm putting you on the spot? >> In the 10 years, while living here in New York, I was a regular visitor of the Oktoberfest at the Lower East Side in Avenue C at Zum Schneider, where I actually met my wife, and she's German. >> Very good. So, how about a big round of applause? (audience applauding) Not so much for Christian, but more I think, obviously for his wife, who obviously had been drinking and consequently ended up with you. (all laughing) See you later, mate. >> That's the beauty about Oktoberfest, but yes. So first of all, good morning to everybody, and great to be back here in New York for a second Transform event. New York clearly is the melting pot of the world in terms of culture, nations, but also business professionals from all kind of different industries, and having this event here in New York City I believe is manifesting what we are trying to do here at Lenovo, is transform every aspect of our business and helping our customers on the journey of intelligent transformation. Last year, in our transformation on the device business, I talked about how the PC is transforming to personalized computing, and we've made a lot of progress in that journey over the last 12 months. One major change that we have made is we combined all our device business under one roof. So basically PCs, smart devices, and smart phones are now under the roof and under the intelligent device group. But from my perspective makes a lot of sense, because at the end of the day, all devices connect in the modern world into the cloud and are operating in a seamless way. But we are also moving from a device business what is mainly a hardware focus historically, more and more also into a solutions business, and I will give you during my speech a little bit of a sense of what we are trying to do, as we are trying to bring all these components closer together, and specifically also with our strengths on the data center side really build end-to-end customer solution. Ultimately, what we want to do is make our business, our customer's businesses faster, safer, and ultimately smarter as well. So I want to look a little bit back, because I really believe it's important to understand what's going on today on the device side. Many of us have still grown up with phones with terminals, ultimately getting their first desktop, their first laptop, their first mobile phone, and ultimately smartphone. Emails and internet improved our speed, how we could operate together, but still we were defined by linear technology advances. Today, the world has changed completely. Technology itself is not a limiting factor anymore. It is how we use technology going forward. The Internet is pervasive, and we are not yet there that we are always connected, but we are nearly always connected, and we are moving to the stage, that everything is getting connected all the time. Sharing experiences is the most driving force in our behavior. In our private life, sharing pictures, videos constantly, real-time around the world, with our friends and with our family, and you see the same behavior actually happening in the business life as well. Collaboration is the number-one topic if it comes down to workplace, and video and instant messaging, things that are coming from the consumer side are dominating the way we are operating in the commercial business as well. Most important beside technology, that a new generation of workforce has completely changed the way we are working. As the famous workforce the first generation of Millennials that have now fully entered in the global workforce, and the next generation, it's called Generation Z, is already starting to enter the global workforce. By 2025, 75 percent of the world's workforce will be composed out of two of these generations. Why is this so important? These two generations have been growing up using state-of-the-art IT technology during their private life, during their education, school and study, and are taking these learnings and taking these behaviors in the commercial workspace. And this is the number one force of change that we are seeing in the moment. Diverse workforces are driving this change in the IT spectrum, and for years in many of our customers' focus was their customer focus. Customer experience also in Lenovo is the most important thing, but we've realized that our own human capital is equally valuable in our customer relationships, and employee experience is becoming a very important thing for many of our customers, and equally for Lenovo as well. As you have heard YY, as we heard from YY, Lenovo is focused on intelligent transformation. What that means for us in the intelligent device business is ultimately starting with putting intelligence in all of our devices, smartify every single one of our devices, adding value to our customers, traditionally IT departments, but also focusing on their end users and building products that make their end users more productive. And as a world leader in commercial devices with more than 33 percent market share, we can solve problems been even better than any other company in the world. So, let's talk about transformation of productivity first. We are in a device-led world. Everything we do is connected. There's more interaction with devices than ever, but also with spaces who are increasingly becoming smart and intelligent. YY said it, by 2020 we have more than 20 billion connected devices in the world, and it will grow exponentially from there on. And users have unique personal choices for technology, and that's very important to recognize, and we call this concept a digital wardrobe. And it means that every single end-user in the commercial business is composing his personal wardrobe on an ongoing basis and is reconfiguring it based on the work he's doing and based where he's going and based what task he is doing. I would ask all of you to put out all the devices you're carrying in your pockets and in your bags. You will see a lot of you are using phones, tablets, laptops, but also cameras and even smartwatches. They're all different, but they have one underlying technology that is bringing it all together. Recognizing digital wardrobe dynamics is a core factor for us to put all the devices under one roof in IDG, one business group that is dedicated to end-user solutions across mobile, PC, but also software services and imaging, to emerging technologies like AR, VR, IoT, and ultimately a AI as well. A couple of years back there was a big debate around bring-your-own-device, what was called consumerization. Today consumerization does not exist anymore, because consumerization has happened into every single device we build in our commercial business. End users and commercial customers today do expect superior display performance, superior audio, microphone, voice, and touch quality, and have it all connected and working seamlessly together in an ease of use space. We are already deep in the journey of personalized computing today. But the center point of it has been for the last 25 years, the mobile PC, that we have perfected over the last 25 years, and has been the undisputed leader in mobility computing. We believe in the commercial business, the ThinkPad is still the core device of a digital wardrobe, and we continue to drive the success of the ThinkPad in the marketplace. We've sold more than 140 million over the last 26 years, and even last year we exceeded nearly 11 million units. That is about 21 ThinkPads per minute, or one Thinkpad every three seconds that we are shipping out in the market. It's the number one commercial PC in the world. It has gotten countless awards but we felt last year after Transform we need to build a step further, in really tailoring the ThinkPad towards the need of the future. So, we announced a new line of X1 Carbon and Yoga at CES the Consumer Electronics Show. And the reason is not we want to sell to consumer, but that we do recognize that a lot of CIOs and IT decision makers need to understand what consumers are really doing in terms of technology to make them successful. So, let's take a look at the video. (suspenseful music) >> When you're the number one business laptop of all time, your only competition is yourself. (wall shattering) And, that's different. Different, like resisting heat, ice, dust, and spills. Different, like sharper, brighter OLA display. The trackpoint that reinvented controls, and a carbon fiber roll cage to protect what's inside, built by an engineering and design team, doing the impossible for the last 25 years. This is the number one business laptop of all time, but it's not a laptop. It's a ThinkPad. (audience applauding) >> Thank you very much. And we are very proud that Lenovo ThinkPad has been selected as the best laptop in the world in the second year in a row. I think it's a wonderful tribute to what our engineers have been done on this one. And users do want awesome displays. They want the best possible audio, voice, and touch control, but some users they want more. What they want is super power, and I'm really proud to announce our newest member of the X1 family, and that's the X1 extreme. It's exceptionally featured. It has six core I9 intel chipset, the highest performance you get in the commercial space. It has Nvidia XTX graphic, it is a 4K UHD display with HDR with Dolby vision and Dolby Atmos Audio, two terabyte in SSD, so it is really the absolute Ferrari in terms of building high performance commercial computer. Of course it has touch and voice, but it is one thing. It has so much performance that it serves also a purpose that is not typical for commercial, and I know there's a lot of secret gamers also here in this room. So you see, by really bringing technology together in the commercial space, you're creating productivity solutions of one of a kind. But there's another category of products from a productivity perspective that is incredibly important in our commercial business, and that is the workstation business . Clearly workstations are very specifically designed computers for very advanced high-performance workloads, serving designers, architects, researchers, developers, or data analysts. And power and performance is not just about the performance itself. It has to be tailored towards the specific use case, and traditionally these products have a similar size, like a server. They are running on Intel Xeon technology, and they are equally complex to manufacture. We have now created a new category as the ultra mobile workstation, and I'm very proud that we can announce here the lightest mobile workstation in the industry. It is so powerful that it really can run AI and big data analysis. And with this performance you can go really close where you need this power, to the sensors, into the cars, or into the manufacturing places where you not only wannna read the sensors but get real-time analytics out of these sensors. To build a machine like this one you need customers who are really challenging you to the limit. and we're very happy that we had a customer who went on this journey with us, and ultimately jointly with us created this product. So, let's take a look at the video. (suspenseful music) >> My world involves pathfinding both the hardware needs to the various work sites throughout the company, and then finding an appropriate model of desktop, laptop, or workstation to match those needs. My first impressions when I first seen the ThinkPad P1 was I didn't actually believe that we could get everything that I was asked for inside something as small and light in comparison to other mobile workstations. That was one of the I can't believe this is real sort of moments for me. (engine roars) >> Well, it's better than general when you're going around in the wind tunnel, which isn't alway easy, and going on a track is not necessarily the best bet, so having a lightweight very powerful laptop is extremely useful. It can take a Xeon processor, which can support ECC from when we try to load a full car, and when we're analyzing live simulation results. through and RCFT post processor or example. It needs a pretty powerful machine. >> It's come a long way to be able to deliver this. I hate to use the word game changer, but it is that for us. >> Aston Martin has got a lot of different projects going. There's some pretty exciting projects and a pretty versatile range coming out. Having Lenovo as a partner is certainly going to ensure that future. (engine roars) (audience applauds) >> So, don't you think the Aston Martin design and the ThinkPad design fit very well together? (audience laughs) So if Q, would get a new laptop, I think you would get a ThinkPad X P1. So, I want to switch gears a little bit, and go into something in terms of productivity that is not necessarily on top of the mind or every end user but I believe it's on top of the mind of every C-level executive and of every CEO. Security is the number one threat in terms of potential risk in your business and the cost of cybersecurity is estimated by 2020 around six trillion dollars. That's more than the GDP of Japan and we've seen a significant amount of data breach incidents already this years. Now, they're threatening to take companies out of business and that are threatening companies to lose a huge amount of sensitive customer data or internal data. At Lenovo, we are taking security very, very seriously, and we run a very deep analysis, around our own security capabilities in the products that we are building. And we are announcing today a new brand under the Think umbrella that is called ThinkShield. Our goal is to build the world's most secure PC, and ultimately the most secure devices in the industry. And when we looked at this end-to-end, there is no silver bullet around security. You have to go through every aspect where security breaches can potentially happen. That is why we have changed the whole organization, how we look at security in our device business, and really have it grouped under one complete ecosystem of solutions, Security is always something where you constantly are getting challenged with the next potential breach the next potential technology flaw. As we keep innovating and as we keep integrating, a lot of our partners' software and hardware components into our products. So for us, it's really very important that we partner with companies like Intel, Microsoft, Coronet, Absolute, and many others to really as an example to drive full encryption on all the data seamlessly, to have multi-factor authentication to protect your users' identity, to protect you in unsecured Wi-Fi locations, or even simple things like innovation on the device itself, to and an example protect the camera, against usage with a little thing like a thinkShutter that you can shut off the camera. SO what I want to show you here, is this is the full portfolio of ThinkShield that we are announcing today. This is clearly not something I can even read to you today, but I believe it shows you the breadth of security management that we are announcing today. There are four key pillars in managing security end-to-end. The first one is your data, and this has a lot of aspects around the hardware and the software itself. The second is identity. The third is the security around online, and ultimately the device itself. So, there is a breakout on security and ThinkShield today, available in the afternoon, and encourage you to really take a deeper look at this one. The first pillar around productivity was the device, and around the device. The second major pillar that we are seeing in terms of intelligent transformation is the workspace itself. Employees of a new generation have a very different habit how they work. They split their time between travel, working remotely but if they do come in the office, they expect a very different office environment than what they've seen in the past in cubicles or small offices. They come into the office to collaborate, and they want to create ideas, and they really work in cross-functional teams, and they want to do it instantly. And what we've seen is there is a huge amount of investment that companies are doing today in reconfiguring real estate reconfiguring offices. And most of these kind of things are moving to a digital platform. And what we are doing, is we want to build an entire set of solutions that are just focused on making the workspace more productive for remote workforce, and to create technology that allow people to work anywhere and connect instantly. And the core of this is that we need to be, the productivity of the employee as high as possible, and make it for him as easy as possible to use these kind of technologies. Last year in Transform, I announced that we will enter the smart office space. By the end of last year, we brought the first product into the market. It's called the Hub 500. It's already deployed in thousands of our customers, and it's uniquely focused on Microsoft Skype for Business, and making meeting instantly happen. And the product is very successful in the market. What we are announcing today is the next generation of this product, what is the Hub 700, what has a fantastic audio quality. It has far few microphones, and it is usable in small office environment, as well as in major conference rooms, but the most important part of this new announcement is that we are also announcing a software platform, and this software platform allows you to run multiple video conferencing software solutions on the same platform. Many of you may have standardized for one software solution or for another one, but as you are moving in a world of collaborating instantly with partners, customers, suppliers, you always will face multiple software standards in your company, and Lenovo is uniquely positioned but providing a middleware platform for the device to really enable multiple of these UX interfaces. And there's more to come and we will add additional UX interfaces on an ongoing base, based on our customer requirements. But this software does not only help to create a better experience and a higher productivity in the conference room or the huddle room itself. It really will allow you ultimately to manage all your conference rooms in the company in one instance. And you can run AI technologies around how to increase productivity utilization of your entire conference room ecosystem in your company. You will see a lot more devices coming from the node in this space, around intelligent screens, cameras, and so on, and so on. The idea is really that Lenovo will become a core provider in the whole movement into the smart office space. But it's great if you have hardware and software that is really supporting the approach of modern IT, but one component that Kirk also mentioned is absolutely critical, that we are providing this to you in an as a service approach. Get it what you want, when you need it, and pay it in the amount that you're really using it. And within UIT there is also I think a new philosophy around IT management, where you're much more focused on the value that you are consuming instead of investing into technology. We are launched as a service two years back and we already have a significant number of customers running PC as a service, but we believe as a service will stretch far more than just the PC device. It will go into categories like smart office. It might go even into categories like phone, and it will definitely go also in categories like storage and server in terms of capacity management. I want to highlight three offerings that we are also displaying today that are sort of building blocks in terms of how we really run as a service. The first one is that we collaborated intensively over the last year with Microsoft to be the launch pilot for their Autopilot offering, basically deploying images easily in the same approach like you would deploy a new phone on the network. The purpose really is to make new imaging and enabling new PC as seamless as it's used to be in the phone industry, and we have a complete set of offerings, and already a significant number customers have deployed Autopilot with Lenovo. The second major offering is Premier Support, like in the in the server business, where Premier Support is absolutely critical to run critical infrastructure, we see a lot of our customers do want to have Premier Support for their end users, so they can be back into work basically instantly, and that you have the highest possible instant repair on every single device. And then finally we have a significant amount of time invested into understanding how the software as a service really can get into one philosophy. And many of you already are consuming software as a service in many different contracts from many different vendors, but what we've created is one platform that really can manage this all together. All these things are the foundation for a device as a service offering that really can manage this end-to-end. So, implementing an intelligent workplace can be really a daunting prospect depending on where you're starting from, and how big your company ultimately is. But how do you manage the transformation of technology workspace if you're present in 50 or more countries and you run an infrastructure for more than 100,000 people? Michelin, famous for their tires, infamous for their Michelin star restaurant rating, especially in New York, and instantly recognizable by the Michelin Man, has just doing that. Please welcome with me Damon McIntyre from Michelin to talk to us about the challenges and transforming collaboration and productivity. (audience applauding) (electronic dance music) Thank you, David. >> Thank you, thank you very much. >> We on? >> So, how do you feel here? >> Well good, I want to thank you first of all for your partnership and the devices you create that helped us design, manufacture, and distribute the best tire in the world, okay? I just had to say it and put out there, alright. And I was wondering, were those Michelin tires on that Aston Martin? >> I'm pretty sure there is no other tire that would fit to that. >> Yeah, no, thank you, thank you again, and thank you for the introduction. >> So, when we talk about the transformation happening really in the workplace, the most tangible transformation that you actually see is the drastic change that companies are doing physically. They're breaking down walls. They're removing cubes, and they're moving to flexible layouts, new desks, new huddle rooms, open spaces, but the underlying technology for that is clearly not so visible very often. So, tell us about Michelin's strategy, and the technology you are deploying to really enable this corporation. >> So we, so let me give a little bit a history about the company to understand the daunting tasks that we had before us. So we have over 114,000 people in the company under 170 nationalities, okay? If you go to the corporate office in France, it's Clermont. It's about 3,000 executives and directors, and what have you in the marketing, sales, all the way up to the chain of the global CIO, right? Inside of the Americas, we merged in Americas about three years ago. Now we have the Americas zone. There's about 28,000 employees across the Americas, so it's really, it's really hard in a lot of cases. You start looking at the different areas that you lose time, and you lose you know, your productivity and what have you, so there, it's when we looked at different aspects of how we were going to manage the meeting rooms, right? because we have opened up our areas of workspace, our CIO, CEOs in our zones will no longer have an office. They'll sit out in front of everybody else and mingle with the crowd. So, how do you take those spaces that were originally used by an individual but now turn them into like meeting rooms? So, we went through a large process, and looked at the Hub 500, and that really met our needs, because at the end of the day what we noticed was, it was it was just it just worked, okay? We've just added it to the catalog, so we're going to be deploying it very soon, and I just want to again point that I know everybody struggles with this, and if you look at all the minutes that you lose in starting up a meeting, and we know you know what I'm talking about when I say this, it equates to many many many dollars, okay? And so at the end the day, this product helps us to be more efficient in starting up the meeting, and more productive during the meeting. >> Okay, it's very good to hear. Another major trend we are seeing in IT departments is taking a more hands-off approach to hardware. We're seeing new technologies enable IT to create a more efficient model, how IT gets hardware in the hands of end-users, and how they are ultimately supporting themselves. So what's your strategy around the lifecycle management of the devices? >> So yeah you mentioned, again, we'll go back to the 114,000 employees in the company, right? You imagine looking at all the devices we use. I'm not going to get into the number of devices we have, but we have a set number that we use, and we have to go through a process of deploying these devices, which we right now service our own image. We build our images, we service them through our help desk and all that process, and we go through it. If you imagine deploying 25,000 PCs in a year, okay? The time and the daunting task that's behind all that, you can probably add up to 20 or 30 people just full-time doing that, okay? So, with partnering with Lenovo and their excellent technology, their technical teams, and putting together the whole process of how we do imaging, it now lifts that burden off of our folks, and it shifts it into a more automated process through the cloud, okay? And, it's with the Autopilot on the end of the project, we'll have Autopilot fully engaged, but what I really appreciate is how Lenovo really, really kind of got with us, and partnered with us for the whole process. I mean it wasn't just a partner between Michelin and Lenovo. Microsoft was also partnered during that whole process, and it really was a good project that we put together, and we hope to have something in a full production mode next year for sure. >> So, David thank you very, very much to be here with us on stage. What I really want to say, customers like you, who are always challenging us on every single aspect of our capabilities really do make the big difference for us to get better every single day and we really appreciate the partnership. >> Yeah, and I would like to say this is that I am, I'm doing what he's exactly said he just said. I am challenging Lenovo to show us how we can innovate in our work space with your devices, right? That's a challenge, and it's going to be starting up next year for sure. We've done some in the past, but I'm really going to challenge you, and my whole aspect about how to do that is bring you into our workspace. Show you how we make how we go through the process of making tires and all that process, and how we distribute those tires, so you can brainstorm, come back to the table and say, here's a device that can do exactly what you're doing right now, better, more efficient, and save money, so thank you. >> Thank you very much, David. (audience applauding) Well it's sometimes really refreshing to get a very challenging customers feedback. And you know, we will continue to grow this business together, and I'm very confident that your challenge will ultimately help to make our products even more seamless together. So, as we now covered productivity and how we are really improving our devices itself, and the transformation around the workplace, there is one pillar left I want to talk about, and that's really, how do we make businesses smarter than ever? What that really means is, that we are on a journey on trying to understand our customer's business, deeper than ever, understanding our customer's processes even better than ever, and trying to understand how we can help our customers to become more competitive by injecting state-of-the-art technology in this intelligent transformation process, into core processes. But this cannot be done without talking about a fundamental and that is the journey towards 5G. I really believe that 5G is changing everything the way we are operating devices today, because they will be connected in a way like it has never done before. YY talked about you know, 20 times 10 times the amount of performance. There are other studies that talk about even 200 times the performance, how you can use these devices. What it will lead to ultimately is that we will build devices that will be always connected to the cloud. And, we are preparing for this, and Kirk already talked about, and how many operators in the world we already present with our Moto phones, with how many Telcos we are working already on the backend, and we are working on the device side on integrating 5G basically into every single one of our product in the future. One of the areas that will benefit hugely from always connected is the world of virtual reality and augmented reality. And I'm going to pick here one example, and that is that we have created a commercial VR solution for classrooms and education, and basically using consumer type of product like our Mirage Solo with Daydream and put a solution around this one that enables teachers and schools to use these products in the classroom experience. So, students now can have immersive learning. They can studying sciences. They can look at environmental issues. They can exploring their careers, or they can even taking a tour in the next college they're going to go after this one. And no matter what grade level, this is how people will continue to learn in the future. It's quite a departure from the old world of textbooks. In our area that we are looking is IoT, And as YY already elaborated, we are clearly learning from our own processes around how we improve our supply chain and manufacturing and how we improve also retail experience and warehousing, and we are working with some of the largest companies in the world on pilots, on deploying IoT solutions to make their businesses, their processes, and their businesses, you know, more competitive, and some of them you can see in the demo environment. Lenovo itself already is managing 55 million devices in an IoT fashion connecting to our own cloud, and constantly improving the experience by learning from the behavior of these devices in an IoT way, and we are collecting significant amount of data to really improve the performance of these systems and our future generations of products on a ongoing base. We have a very strong partnership with a company called ADLINK from Taiwan that is one of the leading manufacturers of manufacturing PC and hardened devices to create solutions on the IoT platform. The next area that we are very actively investing in is commercial augmented reality. I believe augmented reality has by far more opportunity in commercial than virtual reality, because it has the potential to ultimately improve every single business process of commercial customers. Imagine in the future how complex surgeries can be simplified by basically having real-time augmented reality information about the surgery, by having people connecting into a virtual surgery, and supporting the surgery around the world. Visit a furniture store in the future and see how this furniture looks in your home instantly. Doing some maintenance on some devices yourself by just calling the company and getting an online manual into an augmented reality device. Lenovo is exploring all kinds of possibilities, and you will see a solution very soon from Lenovo. Early when we talked about smart office, I talked about the importance of creating a software platform that really run all these use cases for a smart office. We are creating a similar platform for augmented reality where companies can develop and run all their argumented reality use cases. So you will see that early in 2019 we will announce an augmented reality device, as well as an augmented reality platform. So, I know you're very interested on what exactly we are rolling out, so we will have a first prototype view available there. It's still a codename project on the horizon, and we will announce it ultimately in 2019, but I think it's good for you to take a look what we are doing here. So, I just wanted to give you a peek on what we are working beyond smart office and the device productivity in terms of really how we make businesses smarter. It's really about increasing productivity, providing you the most secure solutions, increase workplace collaboration, increase IT efficiency, using new computing devices and software and services to make business smarter in the future. There's no other company that will enable to offer what we do in commercial. No company has the breadth of commercial devices, software solutions, and the same data center capabilities, and no other company can do more for your intelligent transformation than Lenovo. Thank you very much. (audience applauding) >> Thanks mate, give me that. I need that. Alright, ladies and gentlemen, we are done. So firstly, I've got a couple of little housekeeping pieces at the end of this and then we can go straight into going and experiencing some of the technology we've got on the left-hand side of the room here. So, I want to thank Christian obviously. Christian, awesome as always, some great announcements there. I love the P1. I actually like the Aston Martin a little bit better, but I'll take either if you want to give me one for free. I'll take it. We heard from YY obviously about the industry and how the the fourth Industrial Revolution is impacting us all from a digital transformation perspective, and obviously Kirk on DCG, the great NetApp announcement, which is going to be really exciting, actually that Twitter and some of the social media panels are absolutely going crazy, so it's good to see that the industry is really taking some impact. Some of the publications are really great, so thank you for the media who are obviously in the room publishing right no. But now, I really want to say it's all of your turn. So, all of you up the back there who are having coffee, it's your turn now. I want everyone who's sitting down here after this event move into there, and really take advantage of the 15 breakouts that we've got set there. There are four breakout sessions from a time perspective. I want to try and get you all out there at least to use up three of them and use your fourth one to get out and actually experience some of the technology. So, you've got four breakout sessions. A lot of the breakout sessions are actually done twice. If you have not downloaded the app, please download the app so you can actually see what time things are going on and make sure you're registering correctly. There's a lot of great experience of stuff out there for you to go do. I've got one quick video to show you on some of the technology we've got and then we're about to close. Alright, here we are acting crazy. Now, you can see obviously, artificial intelligence machine learning in the browser. God, I hate that dance, I'm not a Millenial at all. It's effectively going to be implemented by healthcare. I want you to come around and test that out. Look at these two guys. This looks like a Lenovo management meeting to be honest with you. These two guys are actually concentrating, using their brain power to race each others in cars. You got to come past and give that a try. Give that a try obviously. Fantastic event here, lots of technology for you to experience, and great partners that have been involved as well. And so, from a Lenovo perspective, we've had some great alliance partners contribute, including obviously our number one partner, Intel, who's been a really big loyal contributor to us, and been a real part of our success here at Transform. Excellent, so please, you've just seen a little bit of tech out there that you can go and play with. I really want you, I mean go put on those black things, like Scott Hawkins our chief marketing officer from Lenovo's DCG business was doing and racing around this little car with his concentration not using his hands. He said it's really good actually, but as soon as someone comes up to speak to him, his car stops, so you got to try and do better. You got to try and prove if you can multitask or not. Get up there and concentrate and talk at the same time. 62 different breakouts up there. I'm not going to go into too much detai, but you can see we've got a very, very unusual numbering system, 18 to 18.8. I think over here we've got a 4849. There's a 4114. And then up here we've got a 46.1 and a 46.2. So, you need the decoder ring to be able to understand it. Get over there have a lot of fun. Remember the boat leaves today at 4:00 o'clock, right behind us at the pier right behind us here. There's 400 of us registered. Go onto the app and let us know if there's more people coming. It's going to be a great event out there on the Hudson River. Ladies and gentlemen that is the end of your keynote. I want to thank you all for being patient and thank all of our speakers today. Have a great have a great day, thank you very much. 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>> Live from New York, it's The Cube, covering The Cube New York City 2018 brought to you by SiliconAngle Media and its Ecosystem partners. >> Okay, welcome back everyone, here live in New York City for Cube NYC, formally Big Data NYC, now called CubeNYC. The topic has moved beyond big data. It's about cloud, it's about data, it's also about potentially blockchain in the future. I'm John Furrier, Dave Vellante. We're happy to have a special guest here, Arun Murthy. He's the cofounder and chief product officer of Hortonworks, been in the Ecosystem from the beginning, at Yahoo, already been on the Cube many times, but great to see you, thanks for coming in, >> My pleasure, >> appreciate it. >> thanks for having me. >> Super smart to have you on here, because a lot of people have been squinting through the noise of the market place. You guys have been now for a few years on this data plan idea, so you guys have actually launched Hadoop with Cloudera, they were first. You came after, Yahoo became second, two big players. Evolved it quickly, you guys saw early on that this is bigger than Hadoop. And now, all the conversations on what you guys have been talking about three years ago. Give us the update, what's the product update? How is the hybrids a big part of that, what's the story? >> We started off being the Hadoop company, and Rob, our CEO who was here on Cube, a couple of hours ago, he calls it sort of the phase one of the company, where it were Hadoop company. Very quickly realized we had to help enterprises manage the entire life cycle data, all the way from the edge to the data center, to the cloud, and between, right. So which is why we did acquisition of YARN, we've been talking about it, which kind of became the basis of our Hot marks Data flow product. And then as we went through the phase of that journey it was quickly obvious to us that enterprises had to manage data and applications in a hybrid manner right which is both on prem And public load and increasingly Edge, which is really very we spend a lot of time these days With IOT and everything from autonomous cars to video monitoring to all these aspects coming in. Which is why we wanted to get to the data plan architecture it allows to get you to a consistent security governance model. There's a lot of, I'll call it a lot of, a lot of fight about Cloud being insecure and so on, I don't think there's anything inherently insecure about the Cloud. The issue that we see is lack of skills and our enterprises know how to manage the data on-prem they know how to do LDAP, groups, and curb rows, and AAD, and what have you, they just don't have the skill sets yet to be able to do it on the public load, which leads to mistakes occasionally. >> Um-hm. >> And Data breaches and so on. So we recognize really early that part of data plan was to get that consistent security in governance models, so you don't have to worry about how you set up IMRL's on Amazon versus LDAP on-prem versus something else on Google. >> It's operating consistency. >> It's operating, exactly. I've talked about this in the past. So getting that Data plan was that journey, and this week at Charlotte work week we announced was we wanted to take that step further we've been able to kind of allow enterprise to manage this hybrid architecture on prem, multiple public loads. >> And the Edge. >> In a connected manner, the issue we saw early on and it's something we've been working on for a long while. Is that we've been able to connect the architectures Hadoop when it started it was more of an on premise architecture right, and I was there in 2005, 2006 when it started, Hadoop's started was bought on the world wide web we had a gigabyte of ethernet and I was up to the rack. From the rack on we had only eight gigs up to the rack so if you have a 2000 or cluster your dealing with eight gigs of connection. >> Bottleneck >> Huge bottleneck, fast forward today, you have at least ten if not one hundred gigabits. Moving to one hundred to a terabyte architecture, for that standpoint, and then what's happening is everything in that world, if you had the opportunity to read things on the assumptions we have in Hadoop. And then the good news is that when Cloud came along Cloud already had decoupled storage and architecture, storage and compute architectures. As we've sort of helped customers navigate the two worlds, with data plan, it's been a journey that's been reasonably successful and I think we have an opportunity to kind of provide identical consistent architectures both on prem and on Cloud. So it's almost like we took Hadoop and adapted it to Cloud. I think we can adapt the Cloud architecture back on prem, too to have consistent architectures. >> So talk about the Cloud native architecture. So you have a post that just got published. Cloud native architecture for big data and the data center. No, Cloud native architecture to big data in the data center. That's hyrid, explain the hybrid model, how do you define that? >> Like I said, for us it's really important to be able to have consistent architectures, consistent security, consistent governance, consistent way to manage data, and consistent way to actually to double up and port applications. So portability for data is important, which is why having security and governance consistently is a key. And then portability for the applications themselves are important, which is why we are so excited to kind of be, kind of first to embrace the whole containerize the ecosystem initiative. We've announced the open hybrid architecture initiative which is about decoupling storage and compute and then leveraging containers for all the big data apps, for the entire ecosystem. And this is where we are really excited to be working with both IBM and Redhat especially Redhat given their sort of investments in Kubernetes and open ship. We see that much like you'll have S3 and EC2, S3 for storage, EC2 for compute, and same thing with ADLS and azure compute. You'll actually have the next gen HDFS and Kubernetives. So is this a massive architectural rewrite, or is it more sort of management around the core. >> Great question. So part of it is evolution of the architecture. We have to get, whether it's Spark or Kafka or any of these open source projects, we need to do some evolution in the architecture, to make them work in the ecosystem, in the containerized world. So we are containerizing every one of the 28 animals 30 animals, in the zoo, right. That's a lot of work, we are kind of you know, sort of do it, we've done it in the past. Along with your point it's not enough to just have the architecture, you need to have a consistent fabric to be able to manage and operate it, which is really where the data plan comes in again. That was really the point of data plane all the time, this is a multi-roadmap, you know when we sit down we are thinking about what we'll do in 22, and 23. But we really have to execute on a multi-roadmap. >> And Data plane was a lynch pin. >> Well it was just like the sharp edge of the sword. Right, it was the tip of the sphere, but really the idea was always that we have to get data plan in to kind of get that hybrid product out there. And then we can sort of get to a inter generational data plan which would work with the next generation of the big data ecosystem itself. >> Do you see Kubernetes and things like Kubernetes, you've got STO a few service meshes up the stack, >> Absolutely are going to play a pretty instrumental role around orchestrating work loads and providing new stateless and stateful application with data, so now data you've got more data being generated there. So this is a new dynamic, it sounds like that's a fit for what you guys are doing. >> Which is something we've seen for awhile now. Like containers are something we've tracked for a long time and really excited to see Docker and RedHat. All the work that they are doing with Redhat containers. Get the security and so on. It's the maturing of that ecosystem. And now, the ability to port, build and port applications. And the really cool part for me is that, we will definitely see Kubenetes and open shift, and prem but even if you look at the Cloud the really nice part is that each of the Cloud providers themselves, provide a Kubenesos. Whether it's GKE on Google or Fargate on Amazon or AKS on Microsoft, we will be able to take identical architectures and leverage them. When we containerize high mark aft or spark we will be able to do this with kubernetes on spark with open shift and there will be open shift on leg which is available in the public cloud but also GKE and Fargate and AKS. >> What's interesting about the Redhat relationship is that I think you guys are smart to do this, is by partnering with Redhat you can, customers can run their workloads, analytical workloads, in the same production environment that Redhat is in. But with kind of differentiation if you will. >> Exactly with data plane. >> Data plane is just a wonderful thing there. So again good move there. Now around the ecosystem. Who else are you partnering with? what else do you see out there? who is in your world that is important? >> You know again our friends at IBM, that we've had a long relationship with them. We are doing a lot of work with IBM to integrate, data plane and also ICPD, which is the IBM Cloud plane for data, which brings along all of the IBM ecosystem. Whether it's DBT or IGC information governance catalogs, all that kind of were back in this world. What we also believe this will give a flip to is the whole continued standardization of security and governance. So you guys remember the old dpi, it caused a bit of a flutter, a few years ago. (anxious laughing) >> We know how that turned out. >> What we did was we kind of said, old DPI was based on the old distributions, now it's DPI's turn to be more about merit and governance. So we are collaborating with IBM on DPI more on merit and governance, because again we see that as being very critical in this sort of multi-Cloud, on prem edge world. >> Well the narrative, was always why do you need it, but it's clear that these three companies have succeeded dramatically, when you look at the financials, there has been statements made about IBM's contribution to seven figure deals to you guys. We had Redhat on and you guys are birds of a feather. [Murhty] Exactly. >> It certainly worked for you three, which presumably means it confers value to your customers. >> Which is really important, right from a customer standpoint, what is something we really focus on is that the benefit of the bargain is that now they understand that some of their key vendor partners that's us and Ibm and Redhat, we have a shared roadmap so now they can be much more sure about the fact that they can go to containers and kubernetes and so on and so on. Because all of the tools that they depend on are and all the partners they depend on are working together. >> So they can place bets. >> So they can place bets, and the important thing is that they can place longer term bets. Not a quarter bet, we hear about customers talking about building the next gen data centers, with kubernetes in mind. >> They have too. >> They have too, right and it's more than just building machines up, because what happens is with this world we talked about things like networking the way you do networking in this world with kubernetes, is different than you do before. So now they have to place longer term bets and they can do this now with the guarantee that the three of us will work together to deliver on the architecture. >> Well Arun, great to have you on the Cube, great to see you, final question for you, as you guys have a good long plan which is very cool. Short term customers are realizing, the set-up phase is over, okay now they're in usage mode. So the data has got to deliver value, so there is a real pressure for ROI, we would give people a little bit of a pass earlier on because set-up everything, set-up the data legs, do all this stuff, get it all operationalized, but now, with the AI and the machine learning front and center that's a signal that people want to start putting this to work. What have you seen customers gravitate to from the product side? Where are they going, is it the streaming is it the Kafka, is it the, what products are they gravitating to? >> Yeah definitely, I look at these in my role, in terms of use cases, right, we are certainly seeing a continued push towards the real-time analytics space. Which is why we place a longer-term bet on HDF and Kafka and so on. What's been really heartening kind of back to your sentiment, is we are seeing a lot of push right now on security garments. That's why we introduced for GDPR, we introduced a bunch of cable readies and data plane, with DSS and James Cornelius wrote about this earlier in the year, we are seeing customers really push us for key aspects like GDPR. This is a reflection for me of the fact of the maturing of the ecosystem, it means that it's no longer something on the side that you play with, it's something that's more, the whole ecosystem is now more a system of record instead of a system of augmentation, so that is really heartening but also brings a sharper focus and more sort of responsibility on our shoulders. >> Awesome, well congratulations, you guys have stock prices at a 52-week high. Congratulations. >> Those things take care of themselves. >> Good products, and stock prices take care of themselves. >> Okay the Cube coverage here in New York City, I'm John Vellante, stay with us for more live coverage all things data happening here in New York City. We will be right back after this short break. 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>> Announcer: From Berlin, Germany, it's the Cube covering Datawork Summit Europe 2018. Brought to you by Hortonworks. (electronic music) >> Hello and welcome to the Cube on day two of Dataworks Summit 2018 from Berlin. It's been a great show so far. We have just completed the day two keynote and in just a moment I'll bring ya up to speed on the major points and the presentations from that. It's been a great conference. Fairly well attended here. The hallway chatter, discussion's been great. The breakouts have been stimulating. For me the takeaway is the fact that Hortonworks, the show host, has announced yesterday at the keynote, Scott Gnau, the CTO of Hortonworks announced Data Steward Studio, DSS they call it, part of the data plane, Hotronworks data plane services portfolio and it could not be more timely Data Steward Studio because we are now five weeks away from GDPR, that's the General Data Protection Regulation becoming the law of the land. When I say the land, the EU, but really any company that operates in the EU, and that includes many U.S. based and Apac based and other companies will need to comply with the GDPR as of May 25th and ongoing. In terms of protecting the personal data of EU citizens. And that means a lot of different things. Data Steward Studio announced yesterday, was demo'd today, by Hortonworks and it was a really excellent demo, and showed that it's a powerful solution for a number of things that are at the core of GDPR compliance. The demo covered the capability of the solution to discover and inventory personal data within a distributed data lake or enterprise data environment, number one. Number two, the ability of the solution to centralize consent, provide a consent portal essentially that data subjects can use then to review the data that's kept on them to make fine grain consents or withdraw consents for use in profiling of their data that they own. And then number three, the show, they demonstrated the capability of the solution then to execute the data subject to people's requests in terms of the handling of their personal data. The three main points in terms of enabling, adding the teeth to enforce GDPR in an operational setting in any company that needs to comply with GDPR. So, what we're going to see, I believe going forward in the, really in the whole global economy and in the big data space is that Hortonworks and others in the data lake industry, and there's many others, are going to need to roll out similar capabilities in their portfolios 'cause their customers are absolutely going to demand it. In fact the deadline is fast approaching, it's only five weeks away. One of the interesting take aways from the, the keynote this morning was the fact that John Kreisa, the VP for marketing at Hortonworks today, a quick survey of those in the audience a poll, asking how ready they are to comply with GDPR as of May 25th and it was a bit eye opening. I wasn't surprised, but I think it was 19 or 20%, I don't have the numbers in front of me, said that they won't be ready to comply. I believe it was something where between 20 and 30% said they will be able to comply. About 40% I'm, don't quote me on that, but a fair plurality said that they're preparing. So that, indicates that they're not entirely 100% sure that they will be able to comply 100% to the letter of the law as of May 25th. I think that's probably accurate in terms of ballpark figures. I think there's a lot of, I know there's a lot of companies, users racing for compliance by that date. And so really GDPR is definitely the headline banner, umbrella story around this event and really around the big data community world-wide right now in terms of enterprise, investments in the needed compliance software and services and capabilities are needed to comply with GDPR. That was important. That wasn't the only thing that was covered in, not only the keynotes, but in the sessions here so far. AI, clearly AI and machine learning are hot themes in terms of the innovation side of big data. There's compliance, there's GDPR, but really innovation in terms of what enterprises are doing with their data, with their analytics, they're building more and more AI and embedding that in conversational UIs and chatbots and their embedding AI, you know manner of e-commerce applications, internal applications in terms of search, as well as things like face recognition, voice recognition, and so forth and so on. So, what we've seen here at the show is what I've been seeing for quite some time is that more of the actual developers who are working with big data are the data scientists of the world. And more of the traditional coders are getting up to speed very rapidly on the new state of the art for building machine learning and deep learning AI natural language processing into their applications. That said, so Hortonworks has become a fairly substantial player in the machine learning space. In fact, you know, really across their portfolio many of the discussions here I've seen shows that everybody's buzzing about getting up to speed on frameworks for building and deploying and iterating and refining machine learning models in operational environments. So that's definitely a hot theme. And so there was an AI presentation this morning from the first gentleman that came on that laid out the broad parameters of what, what developers are doing and looking to do with data that they maintain in their lakes, training data to both build the models and train them and deploy them. So, that was also something I expected and it's good to see at Dataworks Summit that there is a substantial focus on that in addition of course to GDPR and compliance. It's been about seven years now since Hortonworks was essentially spun off of Yahoo. It's been I think about three years or so since they went IPO. And what I can see is that they are making great progress in terms of their growth, in terms of not just the finances, but their customer acquisition and their deal size and also customer satisfaction. I get a sense from talking to many of the attendees at this event that Hortonworks has become a fairly blue chip vendor, that they're really in many ways, continuing to grow their footprint of Hortonworks products and services in most of their partners, such as IBM. And from what I can see everybody was wrapped with intention around Data Steward Studio and I sensed, sort of a sigh of relief that it looks like a fairly good solution and so I have no doubt that a fair number of those in this hall right now are probably, as we say in the U.S., probably kicking the tires of DSS and probably going to expedite their adoption of it. So, with that said, we have day two here, so what we're going to have is Alan Gates, one of the founders of Hortonworks coming on in just a few minutes and I'll be interviewing him, asking about the vibrancy in the health of the community, the Hortonworks ecosystem, developers, partners, and so forth as well as of course the open source communities for Hadoop and Ranger and Atlas and so forth, the growing stack of open source code upon which Hortonworks has built their substantial portfolio of solutions. Following him we'll have John Kreisa, the VP for marketing. I'm going to ask John to give us an update on, really the, sort of the health of Hortonworks as a business in terms of the reach out to the community in terms of their messaging obviously and have him really position Hortonworks in the community in terms of who's he see them competing with. What segments is Hortonworks in now? The whole Hadoop segment increasingly... Hadoop is there. It's the foundation. The word is not invoked in the context of discussions of Hortonworks as much now as it was in the past. And the same thing for say Cloudera one of their closest to traditional rivals, closest in the sense that people associate them. I was at the Cloudera analyst event the other week in Santa Monica, California. It was the same thing. I think both of these vendors are on a similar path to become fairly substantial data warehousing and data governance suppliers to the enterprises of the world that have traditionally gone with the likes of IBM and Oracle and SAP and so forth. So I think they're, Hortonworks, has definitely evolved into a far more diversified solution provider than people realize. And that's really one of the take aways from Dataworks Summit. With that said, this is Jim Kobielus. I'm the lead analyst, I should've said that at the outset. I'm the lead analyst at SiliconANGLE's Media's Wikibon team focused on big data analytics. I'm your host this week on the Cube at Dataworks Summit Berlin. I'll close out this segment and we'll get ready to talk to the Hortonworks and IBM personnel. I understand there's a gentleman from Accenture on as well today on the Cube here at Dataworks Summit Berlin. (electronic music)