>> From The Cube studios in Palo Alto, in Boston, bringing you data driven insights from the cube and ETR. This is breaking analysis with Dave Vellante. >> Last year, we noted in a breaking analysis that the cloud ecosystem is innovating beyond the idea or notion of multi-cloud. We've said for years that multi-cloud is really not a strategy but rather a symptom of multi-vendor. And we coined this term supercloud to describe an abstraction layer that lives above the hyperscale infrastructure that hides the underlying complexities, the APIs, and the primitives of each of the respective clouds. It interconnects whether it's On-Prem, AWS, Azure, Google, stretching out to the edge and creates a value layer on top of that. So our vision is that supercloud is more than running an individual service in cloud native mode within an individual individual cloud rather it's this new layer that builds on top of the hyperscalers. And does things irrespective of location adds value and we'll get into that in more detail. Now it turns out that we weren't the only ones thinking about this, not surprisingly, the majority of the technology ecosystem has been working towards this vision in various forms, including some examples that actually don't try to hide the underlying primitives. And we'll talk about that, but give a consistent experience across the DevSecOps tool chain. Hello, and welcome to this week's Wikibon, Cube insights powered by ETR. In this breaking analysis, we're going to share some recent examples and direct quotes about supercloud from the many Cube guests that we've had on over the last several weeks and months. And we've been trying to test this concept of supercloud. Is it technically feasible? Is it business rational? Is there business case for it? And we'll also share some recent ETR data to put this into context with some of the players that we think are going after this opportunity and where they are in their supercloud build out. And as you can see I'm not in the studio, everybody's got COVID so the studios shut down temporarily but breaking analysis continues. So here we go. Now, first thing is we uncovered an article from earlier this year by Lori MacVittie, is entitled, Supercloud: The 22 Answer to Multi-Cloud Challenges. What a great title. Of course we love it. Now, what really interested us here is not just the title, but the notion that it really doesn't matter what it's called, who cares? Supercloud, distributed cloud, someone even called it Metacloud recently, and we'll get into that. But Lori is a technologist. She's a developer by background. She works at F-Five and she's partial to the supercloud definition that was put forth by Cornell. You can see it here. That's a cloud architecture that enables application migration as a service across different availability zones or cloud providers, et cetera. And that the supercloud provides interfaces to allocate, migrate and terminate resources... And can span all major public cloud providers as well as private clouds. Now, of course, we would take that as well to the edge. So sure. That sounds about right and provides further confirmation that something new is really happening out there. And that was our initial premise when we put this fourth last year. Now we want to dig deeper and hear from the many Cube guests that we've interviewed recently probing about this topic. We're going to start with Chuck Whitten. He's Dell's new Co-COO and most likely part of the Dell succession plan, many years down the road hopefully. He coined the phrase multi-cloud by default versus multi-cloud by design. And he provides a really good business perspective. He's not a deep technologist. We're going to hear from Chuck a couple of times today including one where John Furrier asks him about leveraging hyperscale CapEx. That's an important concept that's fundamental to supercloud. Now, Ashesh Badani heads products at Red Hat and he talks about what he calls Metacloud. Again, it doesn't matter to us what you call it but it's the ecosystem gathering and innovating and we're going to get his perspective. Now we have a couple of clips from Danny Allan. He is the CTO of Veeam. He's a deep technologist and super into the weeds, which we love. And he talks about how Veeam abstracts the cloud layer. Again, a concept that's fundamental to supercloud and he describes what a supercloud is to him. And we also bring with Danny the edge discussion to the conversation. Now the bottom line from Danny is we want to know is supercloud technically feasible? And is it a thing? And then we have Jeff Clarke. Jeff Clark is the Co-COO and Vice Chairman of Dell super experienced individual. He lays out his vision of supercloud and what John Furrier calls a business operating system. You're going to hear from John a couple times. And he, Jeff Clark has a dropped the mic moment, where he says, if we can do this X, we'll describe what X is, it's game over. Okay. So of course we wanted to then go to HPE, one of Dell's biggest competitors and Patrick Osborne is the vice president of the storage business unit at Hewlett Packet Enterprise. And so given Jeff Clarke's game over strategy, we want to understand how HPE sees supercloud. And the bottom line, according to Patrick Osborne is that it's real. So you'll hear from him. And now Raghu Raghuram is the CEO of VMware. He threw a curve ball at this supercloud concept. And he flat out says, no, we don't want to hide the underlying primitives. We want to give developers access to those. We want to create a consistent developer experience in that DevsSecOps tool chain and Kubernetes runtime environments, and connect all the elements in the application development stack. So that's a really interesting perspective that Raghu brings. And then we end on Itzik Reich. Itzik is a technologist and a technical team leader who's worked as a go between customers and product developers for a number of years. And we asked Itzik, is supercloud technically feasible and will it be a reality? So let's hear from these experts and you can decide for yourselves how real supercloud is today and where it is, run the sizzle >> Operative phrase is multi-cloud by default that's kind of the buzz from your keynote. What do you mean by that? >> Well, look, customers have woken up with multiple clouds, multiple public clouds, On-Premise clouds increasingly as the edge becomes much more a reality for customers clouds at the edge. And so that's what we mean by multi-cloud by default. It's not yet been designed strategically. I think our argument yesterday was, it can be and it should be. It is a very logical place for architecture to land because ultimately customers want the innovation across all of the hyperscale public clouds. They will see workloads and use cases where they want to maintain an On-Premise cloud, On-Premise clouds are not going away, I mentioned edge clouds, so it should be strategic. It's just not today. It doesn't work particularly well today. So when we say multi-cloud by default we mean that's the state of the world today. Our goal is to bring multi-cloud by design as you heard. >> Really great question, actually, since you and I talked, Dave, I've been spending some time noodling just over that. And you're right. There's probably some terminology, something that will get developed either by us or in collaboration with the industry. Where we sort of almost have the next almost like a Metacloud that we're working our way towards. >> So we manage both the snapshots and we convert it into the Veeam portable data format. And here's where the supercloud comes into play. Because if I can convert it into the Veeam portable data format, I can move that OS anywhere. I can move it from physical to virtual, to cloud, to another cloud, back to virtual, I can put it back on physical if I want to. It actually abstracts the cloud layer. There are things that we do when we go between cloud some use BIOS, some use UEFI, but we have the data in backup format, not snapshot format, that's theirs, but we have it in backup format that we can move around and abstract workloads across all of the infrastructure. >> And your catalog is control in control of that. Is that right? Am I thinking about that the right way? >> Yeah it is, 100%. And you know what's interesting about our catalog, Dave, the catalog is inside the backup. Yes. So here's, what's interesting about the edge, two things, on the edge you don't want to have any state, if you can help it. And so containers help with that You can have stateless environments, some persistent data storage But we not not only provide the portability in operating systems, we also do this for containers. And that's true. If you go to the cloud and you're using say EKS with relational database services RDS for the persistent data later, we can pick that up and move it to GKE or move it to OpenShift On-Premises. And so that's why I call this the supercloud, we have all of this data. Actually, I think you termed the term supercloud. >> Yeah. But thank you for... I mean, I'm looking for a confirmation from a technologist that it's technically feasible. >> It is technically feasible and you can do it today. >> You said also technology and business models are tied together and enabler. If you believe that then you have to believe that it's a business operating system that they want. They want to leverage whatever they can. And at the end of the day, they have to differentiate what they do. >> Well, that's exactly right. If I take that in what Dave was saying and I summarize it the following way, if we can take these cloud assets and capabilities, combine them in an orchestrated way to deliver a distributed platform, game over. >> We have a number of platforms that are providing whether it's compute or networking or storage, running those workloads that they plum up into the cloud they have an operational experience in the cloud and they now they have data services that are running in the cloud for us in GreenLake. So it's a reality, we have a number of platforms that support that. We're going to have a a set of big announcements coming up at HPE Discover. So we led with Electra and we have a block service. We have VM backup as a service and DR on top of that. So that's something that we're providing today. GreenLake has over, I think it's actually over 60 services right now that we're providing in the GreenLake platform itself. Everything from security, single sign on, customer IDs, everything. So it's real. We have the proofpoint for it. >> Yeah. So I want to clarify something that you said because this tends to be very commonly confused by customers. I use the word abstraction. And usually when people think of abstraction, they think it hides capabilities of the cloud providers. That's not what we are trying to do. In fact, that's the last thing we are trying to do. What we are trying to do is to provide a consistent developer experience regardless of where you want to build your application. So that you can use the cloud provider services if that's what you want to use. But the DevSecOp tool chain, the runtime environment which turns out to be Kubernetes and how you control the Kubernetes environment, how do you manage and secure and connect all of these things. Those are the places where we are adding the value. And so really the VMware value proposition is you can build on the cloud of your choice but providing these consistent elements, number one, you can make better use of us, your scarce developer or operator resources and expertise. And number two, you can move faster. And number three, you can just spend less as a result of this. So that's really what we are trying to do. We are not... So I just wanted to clarify the word abstraction. In terms of where are we? We are still, I would say, in the early stages. So if you look at what customers are trying to do, they're trying to build these greenfield applications. And there is an entire ecosystem emerging around Kubernetes. There is still, Kubernetes is not a developer platform. The developer experience on top of Kubernetes is highly inconsistent. And so those are some of the areas where we are introducing new innovations with our Tanzu Application Platform. And then if you take enterprise applications, what does it take to have enterprise applications running all the time be entirely secure, et cetera. >> Well, look, the multi-cloud by default today are isolated clouds. They don't work together. Your data is siloed. It's locked up and it is expensive to move and make sense of it. So I think the word you and I were batting around before, this is an interconnected tissue. That's what the world needs. They need the clouds to work together as a single platform. That's the problem that we're trying to solve. And you saw it in some of our announcements here that we're starting to make steps on that journey to make multi-cloud work together much simpler. >> It's interesting, you mentioned the hyperscalers and all that CapEx investments. Why wouldn't you want to take advantage of a cloud and build on the CapEx and then ultimately have the solutions machine learning as one area. You see some specialization with the clouds. But you start to see the rise of superclouds, Dave calls them, and that's where you can innovate on a cloud then go to the multiple clouds. Snowflakes is one, we see a lot of examples of supercloud... >> Project Alpine was another one. I mean, it's early, but it's its clearly where you're going. The technology is just starting to come around. I mean it's real. >> Yeah. I mean, why wouldn't you want to take advantage of all of the cloud innovation out there? >> Is that something that's, that supercloud idea is a reality from a technologist perspective. >> I think it is. So for example Katie Gordon, which I believe you've interviewed earlier this week, was demonstrating the Kubernetes data mobility aspect which is another project. That's exactly part of the it's rationale, the rationale of customers being able to move some of their Kubernetes workloads to the cloud and back and between different clouds. Why are we doing? Because customers wants to have the ability to move between different cloud providers, using a common API that will be able to orchestrate all of those things with a self-service that may be offered via the APEX console itself. So it's all around enabling developers and meeting them where they are today and also meeting them into tomorrow's world where they actually may have changed their mind to do those things. So yes we are walking on all of those different aspects. >> Okay. Let's take a quick look at some of the ETR data. This is an X-Y graph. You've seen it a number of times on breaking analysis, it plots the net score or spending momentum on the Y-axis and overlap or pervasiveness in the ETR dataset on the X-axis, used to be called market share. I think that term was off putting to some people, but anyway it's an indicator of presence in the dataset. Now that red dotted line that's rarefied air where anything above that line is considered highly elevated. Now you can see we've plotted Azure and AWS in the upper right. GCP is in there and Kubernetes. We've done that as reference points. They're not necessarily building supercloud platforms. We'll see if they ever want to do so. And Kubernetes of course not a company, but we put 'em in there for context. And we've cherry picked a few players that we believe are building out or are important for supercloud build out. Let's start with Snowflake. We've talked a lot about this company. You can see they're highly elevated on the vertical axis. We see the data cloud as a supercloud in the making. You've got pure storage in there. They made the public, the early part of its supercloud journey at Accelerate 2019 when it unveiled a hybrid block storage service inside of AWS, it connects its On-Prem to AWS and creates that singular experience for pure customers. We see Hashi, HashiCorp as an enabling infrastructure, as code. So they're enabling infrastructure as code across different clouds and different locations. You see Nutanix. They're embarking on their multi-cloud strategy but it's doing so in a way that we think is supercloud, like now. Now Veeam, we were just at VeeamON. And this company has tied Dell for the number one revenue player in data protection. That's according to IDC. And we don't think it won't be long before it holds that position alone at the top as it's growing faster than in Dell in the space. We'll see, Dell is kind of waking up a little bit and putting more resource on that. But Veeam, they're a pure play vendor in data protection. And you heard their CTO, Danny Allan's view on Supercloud, they're doing it today. And we heard extensive comments as well from Dell that's clearly where they're headed, project Alpine was an early example from Dell technologies world of Supercloud in our view. And HPE with GreenLake. Finally beginning to talk about that cross cloud experience. I think it in initially HPE has been more focused on the private cloud, we'll continue to probe. We'll be at HPE discover later on the spring, actually end of June. And we'll continue to probe to see what HPE is doing specifically with GreenLake. Now, finally, Cisco, we put them on the chart. We don't have direct quotes from recent shows and events but this data really shows you the size of Cisco's footprint within the ETR data set that's on the X-axis. Now the cut of this ETR data includes all sectors across the ETR taxonomy which is not something that we commonly show but you can see the magnitude of Cisco's presence. It's impressive. Now, they had better, Cisco that is, had better be building out a supercloud in our view or they're going to be left behind. And I'm quite certain that they're actually going to do so. So we have a lot of evidence that we're putting forth here and seeing in the marketplace what we said last year, the ecosystem is take taking shape, supercloud is forming and becoming a thing. And really in our view, is the future of cloud. But there are always risks to these predictive scenarios and we want to acknowledge those. So first, look, we could end up with a bunch of bespoke superclouds. Now one supercloud is better than three separate cloud native services that do fundamentally the same thing from the same vendor. One for AWS, one for GCP and one for Azure. So maybe that's not all that bad. But to point number two, we hope there evolves a set of open standards for self-service infrastructure, federated governance, and data sharing that will evolve as a horizontal layer versus a set of proprietary vendor specific tools. Now, maybe a company like Veeam will provide that as a data management layer or some of Veeam's competitors or maybe it'll emerge again as open source. As well, and this next point, we see the potential for edge disruptions, changing the economics of the data center. Edge in fact could evolve on its own, independent of the cloud. In fact, David Floria sees the edge somewhat differently from Danny Allan. Floria says he sees a requirement for distributed stateful environments that are ephemeral where recovery is built in. And I said, David, stateful? Ephemeral? Stateful ephemeral? Isn't that an oxymoron? And he responded that, look, if it's not ephemeral the costs are going to be prohibitive. He said the biggest mistake the companies could make is thinking that the edge is simply an extension of their current cloud strategies. We're seeing that a lot. Dell largely talks about the edge as retail. Now, and Telco is a little bit different, but back to Floria's comments, he feels companies have to completely reimagine an integrated file and recovery system which is much more data efficient. And he believes that the technology will evolve with massive volumes and eventually seep into enterprise cloud and distributed data centers with better economics. In other words, as David Michelle recently wrote, we're about 15 years into the most recent cloud cycle and history shows that every 15 years or so, something new comes along that is a blind spot and highly disruptive to existing leaders. So number four here is really important. Remember, in 2007 before AWS introduced the modern cloud, IBM outpost, sorry, IBM outspent Amazon and Google and RND and CapEx and was really comparable to Microsoft. But instead of inventing cloud, IBM spent hundreds of billions of dollars on stock buybacks and dividends. And so our view is that innovation rewards leaders. And while it's not without risks, it's what powers the technology industry it always has and likely always will. So we'll be watching that very closely, how companies choose to spend their free cash flow. Okay. That's it for now. Thanks for watching this episode of The Cube Insights, powered by ETR. Thanks to Stephanie Chan who does some of the background research? Alex Morrison is on production and is going to compile all this stuff. Thank you, Alex. We're all remote this week. Kristen Nicole and Cheryl Knight do Cube distribution and social distribution and get the word out, so thank you. Robert Hof is our editor in chief. Don't forget the checkout etr.ai for all the survey action. Remember I publish each week on wikibon.com and siliconangle.com and you can check out all the breaking analysis podcasts. All you can do is search breaking analysis podcast so you can pop in the headphones and listen while you're on a walk. You can email me at david.vellante@siliconangle.com. If you want to get in touch or DM me at DVellante, you can always hit me up into a comment on our LinkedIn posts. This is Dave Vellante. Thank you for watching this episode of break analysis, stay safe, be well and we'll see you next time. (upbeat music)

>> From theCUBE studios in Palo Alto and Boston, connecting with thought-leaders all around the world, this is a Cube Conversation. >> Hi everybody, this is Dave Vellante. Welcome to this Cube Conversation. We're really excited to have Wim Coekaerts in, he is the senior vice-president of software development at Oracle. Wim, it's great to have you on, and, you know I often say I wish we were face-to-face but if we were you'd have to cut off my tie, cause developers and ties just don't go together. >> No, I know, and this is my normal outfit, so this is me wherever I go. Hi again, good to see you. >> Yeah, great to see you. So, of course, you know a lot of people are confused about Oracle, and open-source, they say "Oracle? Open-source? What is that all about?" But I think you're misunderstood. People don't, first of all, realize you as the leader of the software-development community inside of Oracle, I mean, you've been involved in Linux since the early 90s. But you guys have a lot of committers, you do a lot. I want to talk about that. What is up with Oracle, and open-source? >> Ah, well, it's a broad question. So, you know, a couple of things. One is, we have many different areas within the company that are dealing with open-source. So we have the cloud team doing a lot of stuff around cloud SDKs and support for different languages like Python and Go, and of course Java and so forth, so they do a lot around ensuring that the Oracle ecosystem is integrated in the open-source tools that customers use, or developers use, Terraform companies and so forth. And then you have the Java team, and so forth. Java is open-source and then the Graal project, GraalVM which is a polyglot compiler that can run Java, and Python, and Javascript and so forth together in one. VM do really cool optimizations, that's an open-source project, also on GitHub. There's of course MySQL, which is along with Java, they're probably the two most popular and widely used open-source projects out there. There's VirtualBox which is of course also a very popular project that's open-source. There's all the work we do around Linux. And I think one of the things is that, when you have so many different areas, doing things that are for that area, then as a developer or as a customer, you typically just deal with that group. And what you see is, oh you're talking to the Java developers, so you know what's going on around Java. The Java developers might not necessarily say, "Oh well we also do MySQL, and we do Linux and VirtualBox and so forth," and so you get a rather myopic, narrow view of the larger company. When you add all these things up, and there will be one big slide that says "This is Oracle, these are all these open source projects," and there's multiple ways. One is, we have projects that we've open-sourced and all the code came from us and we made it publicly available, we're the main contributor and we get contributions back. There are other projects where we contribute to third-party in terms of enhancing things, like I said with the Cloud Team, and then in general something like Linux where we're part of an external project and we participate in development of that project at large. And so there's these three different ways, when you count up all the developers that we have that deal with open-source on a daily basis. And in terms of contributions, in terms of bug fixes, testing, and so forth, it's thousands, literally, full-time paid developers. And of course, all the projects are all either on GitHub or similar sites that are very popular. So yeah, I think the misunderstood is probably a lack of knowledge of the breadth of what we do. And, you know, our primary goal is to provide services and products to customers, and so the open-source part is sort of embedded in a development methodology. But that's not something we sell or market separately, we just work with customers and products and services, and so in some cases it's not well-understood. >> Yeah. Well, we're talking of course, we're talking about the state of the penguin, I think it's important for people to understand, Oracle got into the Linux game in the 90s, maybe the latter part of the 90s and Oracle, of course, wants to make Linux-- wants to make Oracle, it's applications and database run better on Linux, but as you're pointing out, your Linux distro, full support, end-to-end, thousands of people in your open-source community, and the contributions that you make to Linux, many if not most, they go upstream, everybody can benefit from those, but of course you want an Oracle distro that is going to make Oracle stuff run better, that's always kind of been the Oracle way. >> Well, so, yes, two things though. One is, so everything we do is upstream. So we have no Linux patches that are not contributed upstream; There's no proprietary code in Oracle Linux at all, it's all completely open, publicly available: the source code, the change log, all the commits, it's fully open and public, which sometimes is not well-understood, but it's completely open. And, everything we do in terms of feature development or functionality or bug fixes goes upstream to the Linux kernel mail-list. It's actually, it's the only way to be able to manage a Linux distribution and be a Linux vendor is to live in that eco-system. Otherwise, the cost of maintaining your own fork, so to speak, is very high and it doesn't really solve the problem. Now, the functionality we work on obviously is focused on making Oracle products run better, making Oracle Cloud run better, and so forth. However, again, what's important to understand, though, is an Oracle database is a program running on an operating system. It does IO, it does networking, it deals with memory management, lots of processing. So, for the most part, the things that we work on to improve that helps everyone out, right? It helps every other database run better, or helps every other language run better. So none of these changes are specific to Oracle, they're just things that we found doing performance benchmarks and testing and so forth, where we say "Hey, if Linux did the following, it would make boot-up faster. Now boot-up has nothing to do with the database. But our customers run on 1-terabyte, 4-terabyte, 8-terabyte systems, and so booting up, and Linux starting up, and cleaning up memory takes a long time. So we want to reduce that from an availability point of view. So here, we're now talking about just enterprise for you. So there's this broad set of things we work on that definitely help us, but they're actually really completely generic and help everyone out. >> Yeah, that's great. So I wanted to kind of get that out of the way and help our audience understand that. So let's get into it a little bit; What are you seeing, what's going on in IT, pick your observation space and your vision of what you see happening out there. >> Well, you know, it's very interesting, it's sort of, there's two... there's sort of two worlds, right, there's the cloud world and the move to cloud, and there's the on-premises world, where people run their systems on their own. And, one of the things that we've learned is, when you talk about machine-learning, obviously, is something that's very popular these days, and automation. And so in order to rely on machine-learning well, and have algorithms that are very effective, you need lots of data. And so being a cloud vendor, and having Linux in our cloud on tens of thousands, or hundreds of thousands of servers, or more, allows us to have a view of how an operating system works across an incredibly large scale. So we get lots of data. And so for us to figure out which algorithms work well in terms of how can we do network optimizations, how can we discover anomalies on the storage site, and deal with it and so forth, we can do that at scale. And what's interesting is, how do we then bring that on-prem? Well, if we can get the data and the learning done, the training done, in our cloud directly, then when we provide that service also for people running Oracle Linux on premises then that will work. The alternative is to have point solutions where you provide something to a customer, and he needs to learn something from small amounts of data. That doesn't work so well. So I think having both worlds, on-prem and cloud directly, allows us to kind of benefit from that. And I think that's important, because lots of customers are interested in going to cloud. Many of the enterprises have not yet. You know, they're starting, but there's still a huge on-premises space that's important. And so by being able to get them familiar with how these things work at scale, autonomy is again important, right, Autonomous Database is incredibly popular and so forth, that allows us to then say, "Here, try these things out here, it's a service. We can show you the benefits right away," and then as that improves we bring that, to a certain extent, on-premises as well. And then they can have it in both places. And that, I think, is something, again, that's relatively unique but also very important, is that we want to provide services and products that act similarly on-premises as well as in cloud, because at some point when people move we want to make that transition seamless. And what you have today for the most part is one world that's on-prem, and then the cloud world is completely different. And that is a big barrier of moving, and so we want to reduce that, we can run the same operating system local as well as cloud, you can the same functionality, and then that helps transition people over much easier. >> Yeah, well Oracle actually was one of the -- I think Oracle was the first company to actually market same-same, you actually used that term. Others put forth that concept, but Oracle was the first to announce products like Cloud at Customer, that were same-same, now it took some time to actually get it perfected, and get it to market, but the point is, and we've written about this, is Oracle, because of the ascendancy of cloud, flipped and has a cloud-first mentality, and you just kind of referenced that, you just said, "And you can bring that to on-prem." So I wonder if you could talk about that cloud-first mentality, and the impact on hybrid. >> So yeah, I think the cloud-first part is of course in cloud we work on services moreso than products that we deliver. And there's a number of things that are happening. So one is that we obviously continue to provide products to customers, you can download Oracle Linux, you can download the database and what not, you can install it on your own, you can do the traditional way of working. Then in the cloud-world, what typically happens is "Oh, I use a database service. I'm not installing anything, I push a button and I get an IP address and a SQL that connects extremely quickly to the database." And we take care of everything underneath that is on this database. Now, in order to do that, you need a whole infrastructure in place, you need log-in agents, you need a back-end that captures all that stuff, you need monitoring tools, you need all the automation scripts for bringing the service up and monitor it. And so, that takes a lot of time to do right, and we learn a lot by doing this. And so the cloud-first part of these services means that we get to experience this ourselves with direct access to everything. Now taking that service with all of the additional features like autonomy, and bringing that to an on-premises world, we have to make sure we can package that so that all these pieces around it go along with it. And that takes a little bit more time, so we can do everything at the same time. And so what we've done with Autonomous Database is we created everything in Oracle Cloud, we have the whole system running really well, and then we've been able to sort of package that and shrink it into something that can be installed on-premises, but then connected into Oracle Cloud again. And so that way we can get all the telemetry over the metric, and that allows us to scale. Because part of providing a cloud service that runs on-prem in the customer environment is that we need to be able to remotely manage that similar to how that runs in our own cloud. Right, otherwise it doesn't scale. And so that takes a little bit of time, but we've done all that work, and now with Cloud at Customer Database that's really in place. >> Yeah, you really want to have that same cloud experience, whether with on-prem, in the public cloud, hybrid, et cetera. So, I want to explore a little bit more who is using Oracle Linux, and what's the driver for using it. Can you describe maybe some of the types of customers and why they buy? >> Sure, so we started this fourteen years ago, in 2006, October 25th, 2006. I remember that day very well; Penguins on stage and a big launch for Oracle Linux in San Francisco Moscone Center. So, look, the initial driver for Oracle Linux was to ensure that Oracle database customers or Oracle product customers had a good operating system experience, and the ability to be able to handle critical issues when that occurs, because typically a database runs the company's critical data: the most essential stuff that a company has is typically in a database, an Oracle database. And so when that thing has issues with the operating system, you don't want just to talk to multiple vendors and have finger-pointing, and having to explain to an operating system vendor how the database works. In the Unix world, we had a good relationship with the OS vendors, and the hardware vendors, they were the same. And they knew our products really well, and in the Linux world, that was very different. The OS vendor basically did not want to understand or learn anything about the products living on top. And so while to a certain extent that makes sense, it's an enterprise world where time is of the essence, and downtime needs to be limited absolutely. We can't have these arguments and such. And that was the driver, initially, for doing Oracle Linux. It was to ensure there was a Linux distribution really backed by us, that we could fix, that we could fully support. That was completely the original intent. And so the early customer base was database customers. Database and middleware. Mostly database. But that has then evolved quickly, and so what happened was, people say "Look, I have a thousand servers, a hundred run Oracle, so we'll run Oracle Linux on those hundred, and we'll run something else on those other nine-hundred." Now after a year or so, they realize that our support is really good; We fix all these issues, and so then they're like "Why are we having two Linux distributions? This thing works really well, it runs any application, it's fully compatible, so we'll do a thousand with Oracle Linux." And so the early days, the first few years, was definitely Oracle Database as the core driver, and then it sort of expanded to the rest of the estate. And over the years, we've added lots of features and functionality, like Ksplice, and so forth. We have an attractive pricing model for running on servers, and so now lots of our customers have a very small Oracle percentage running and many other things running. So it's really become a all-or-nothing play in the Linux space, and we're well-known now, so it's actually very good. >> You just mentioned Ksplice. We've been talking about cloud, and on-prem, and hybrid. Let's talk about security, because security really is a differentiator, particularly if you're going to start to put stuff in the cloud. Talk about Ksplice specifically, but generally security and your policy there. >> So, "Security first" is sort of what you hear us say and do, in everything we do. The database obviously security, on the Linux site security matters. Ksplice as a technology is there to do critical bug-fixing and make sure that we can apply security vulnerability fixes without affecting the customer, and not have downtime. And if you look at most of the cases or many of the cases where you have security vulnerabilities and exploits, it tends to be because systems were not patched. Why were they not patched? Well not that our customer doesn't understand that it's important, but it's a whole train of events that needs to happen. You have to, you get notified that there's a security issue in your operating system or application. Then, well, an application typically means it's a multi-layered setup. So if you have to bring your database server down, then you first have to coordinate with the application users to bring the app server down, cause that talks to the database. So to patch one system, you basically have to bring down the whole application stack. You have to negotiate with the DBAs, you have to negotiate with the app admins, you have to negotiate with the user. It takes weeks to do that and find time. Well during that time, you're vulnerable. So the only way, really, to address security in a scalable and reducing that window of time is to do it without affecting the customer. And so Casewise is something that, it's a company we acquired in 2009, and have since evolved in terms of capabilities, and so it allows us to patch the Linux terminal without downtime. We lock the kernel for 8 microseconds. It's literally no downtime. You don't have to bring down applications, the user doesn't see it, there's no hang, there's no delay. And so by doing that, you can run a Linux operating system, or gLinux, and you can be fully patched on a system that hasn't rebooted for 3 years. You don't even know it. And so by doing that type of stuff, it makes customers more secure, and it avoids them-- It saves them a lot of money in terms of dealing with project management and so forth, but it really keeps them secure. And so we do that for the Linux kernel, we do that for some of the libraries on top that are critical like OpenSSL and 2 LVC, and, you know one example-- I can give you two examples. So one example is, Heartbleed was this bug in OpenSSL a number of years ago. And so everyone had to patch their SSH server. And that meant, basically, systems around the world had to reboot. Like a whole IT reboot across the world. With Ksplice today, if Heartbleed were to happen tomorrow, we would be able to patch this online for all the Oracle Linux customers without any downtime. No reboots, no restarting of applications, everything keeps running. The amount of money saved would be massive, and also, of course, the headache. Another example is, and this was in Oracle Cloud, when some of these CPU bugs that happened a few years ago that were rather damaging on the cloud side, where you could basically see memory potentially of other CPUs running, the cloud is incredibly critical. We were basically able to basically patch our entire cloud in four hours. And the customer didn't know, right, a hundred and twenty million patches, or something, that we applied within four hours, all online, without any downtime. And so that technology has been really helpful, both for us to run our cloud, but the exact same patches and same fixes go to customers on-premises as well. But this comes back to the whole, what we do in cloud we also do for customer. And I think that's a unique thing that we have at Oracle which is quite fascinating. The operating system we run for our customers, the operating system that's the host part of VMs, is the exact same binary and source code that we make available, just to be clear, the exact same binaries are the ones that you run as a customer on-premises. So if you run Oracle Linux with KVM, you run VMs, you're actually running the exact same stuff as we run underneath our customer's stuff. Nobody else does that, everyone else has a black box. So I think that helps a little bit with transparency as well. >> Yeah, and that homogeneity just creates an environment, you're talking about that sort of security mindset, it's critical, you're not just bolting it on, it's part of the culture. But you started your career, and then of course you were a Linux person when you came to Oracle, but then I think you spent some time in database, back in the day when there were serious database wars going on, before Oracle became the king of database. So now you've got, obviously, this great portfolio, and a lot of really sharp software developers; What should we expect going forward, from Oracle? What should we look for? >> You know, I was talking to some, I was welcoming some interns to the company, for their summer internship yesterday, and one of the things I mentioned to them was that -- so cloud obviously gives us a lot of opportunities, but there's a number of things. One is, we have such a breadth of applications and software and hardware together. We have the servers, we have the storage, we have the operating systems, we have the database layer and so forth, and we have the cloud side, and one of the great opportunities, and I think we've shown a lot of this happening with the ability to create something like Autonomous Database, is to combine all these things. Right, we have such a broad portfolio of really cool technology that by itself is okay, but if you combine the things it really becomes awesome. You cannot create autonomous database without having autonomous learning. You cannot create those two and make them really safe without also controlling the firmware on the hardware and so forth. So by being able to combine all these layers, and by having a really great relationship across the teams within the company, that opens up a lot of opportunities to do stuff really quickly. And having the scale for that. I think that has been, for the last few years, a really great thing, but I can see that being one of the advantages that we have going forward. We have Oracle Fusion Applications, which is incredibly popular, and has great growth, and then we have that running on Oracle Cloud, that talks to Oracle Autonomous Database, so we bring all these pieces together. And no other SaaS vendor can do that, because they don't have these other pieces. They have one area, we have all of them. And so that's the exciting part for me, it's not so much about making my own world better, and having Linux be better, and Casewise and so forth, which is important, but that becoming part of the bigger picture. And that's the exciting part. >> Well, Oracle's always invested in RND, we've made that point many, many times. Whether it's database, you know Fusion was a painful but worthy effort, the whole public cloud piece, obviously many acquisitions, but the investments that you've made in open-source as well, Wim, you're a great spokesperson, and a great representative of the open-source community generally, and then Oracle specifically, so thanks very much for coming on theCUBE and sharing with us the state of the penguin, and best of luck. >> You're welcome. Thank you, thanks for having me. >> Alright, and thank you for watching, everybody. This is Dave Vellante for theCUBE. We'll see you next time. (cheerful music).

>> From theCUBE studios in Palo Alto and Boston, connecting with thought-leaders all around the world, this is a Cube Conversation. >> Hi everybody, this is Dave Vellante. Welcome to this Cube Conversation. We're really excited to have Wim Coekaerts in, he is the senior vice-president of software development at Oracle. Wim, it's great to have you on, and, you know I often say I wish we were face-to-face but if we were you'd have to cut off my tie, cause developers and ties just don't go together. >> No, I know, and this is my normal outfit, so this is me wherever I go. Hi again, good to see you. >> Yeah, great to see you. So, of course, you know a lot of people are confused about Oracle, and open-source, they say "Oracle? Open-source? What is that all about?" But I think you're misunderstood. People don't, first of all, realize you as the leader of the software-development community inside of Oracle, I mean, you've been involved in Linux since the early 90s. But you guys have a lot of committers, you do a lot. I want to talk about that. What is up with Oracle, and open-source? >> Ah, well, it's a broad question. So, you know, a couple of things. One is, we have many different areas within the company that are dealing with open-source. So we have the cloud team doing a lot of stuff around cloud SDKs and support for different languages like Python and Go, and of course Java and so forth, so they do a lot around ensuring that the Oracle ecosystem is integrated in the open-source tools that customers use, or developers use, Terraform companies and so forth. And then you have the Java team, and so forth. Java is open-source and then the Graal project, GraalVM which is a polyglot compiler that can run Java, and Python, and Javascript and so forth together in one. VM do really cool optimizations, that's an open-source project, also on GitHub. There's of course MySQL, which is along with Java, they're probably the two most popular and widely used open-source projects out there. There's VirtualBox which is of course also a very popular project that's open-source. There's all the work we do around Linux. And I think one of the things is that, when you have so many different areas, doing things that are for that area, then as a developer or as a customer, you typically just deal with that group. And what you see is, oh you're talking to the Java developers, so you know what's going on around Java. The Java developers might not necessarily say, "Oh well we also do MySQL, and we do Linux and VirtualBox and so forth," and so you get a rather myopic, narrow view of the larger company. When you add all these things up, and there will be one big slide that says "This is Oracle, these are all these open source projects," and there's multiple ways. One is, we have projects that we've open-sourced and all the code came from us and we made it publicly available, we're the main contributor and we get contributions back. There are other projects where we contribute to third-party in terms of enhancing things, like I said with the Cloud Team, and then in general something like Linux where we're part of an external project and we participate in development of that project at large. And so there's these three different ways, when you count up all the developers that we have that deal with open-source on a daily basis. And in terms of contributions, in terms of bug fixes, testing, and so forth, it's thousands, literally, full-time paid developers. And of course, all the projects are all either on GitHub or similar sites that are very popular. So yeah, I think the misunderstood is probably a lack of knowledge of the breadth of what we do. And, you know, our primary goal is to provide services and products to customers, and so the open-source part is sort of embedded in a development methodology. But that's not something we sell or market separately, we just work with customers and products and services, and so in some cases it's not well-understood. >> Yeah. Well, we're talking of course, we're talking about the state of the penguin, I think it's important for people to understand, Oracle got into the Linux game in the 90s, maybe the latter part of the 90s and Oracle, of course, wants to make Linux-- wants to make Oracle, it's applications and database run better on Linux, but as you're pointing out, your Linux distro, full support, end-to-end, thousands of people in your open-source community, and the contributions that you make to Linux, many if not most, they go upstream, everybody can benefit from those, but of course you want an Oracle distro that is going to make Oracle stuff run better, that's always kind of been the Oracle way. >> Well, so, yes, two things though. One is, so everything we do is upstream. So we have no Linux patches that are not contributed upstream; There's no proprietary code in Oracle Linux at all, it's all completely open, publicly available: the source code, the change log, all the commits, it's fully open and public, which sometimes is not well-understood, but it's completely open. And, everything we do in terms of feature development or functionality or bug fixes goes upstream to the Linux kernel mail-list. It's actually, it's the only way to be able to manage a Linux distribution and be a Linux vendor is to live in that eco-system. Otherwise, the cost of maintaining your own fork, so to speak, is very high and it doesn't really solve the problem. Now, the functionality we work on obviously is focused on making Oracle products run better, making Oracle Cloud run better, and so forth. However, again, what's important to understand, though, is an Oracle database is a program running on an operating system. It does IO, it does networking, it deals with memory management, lots of processing. So, for the most part, the things that we work on to improve that helps everyone out, right? It helps every other database run better, or helps every other language run better. So none of these changes are specific to Oracle, they're just things that we found doing performance benchmarks and testing and so forth, where we say "Hey, if Linux did the following, it would make boot-up faster. Now boot-up has nothing to do with the database. But our customers run on 1-terabyte, 4-terabyte, 8-terabyte systems, and so booting up, and Linux starting up, and cleaning up memory takes a long time. So we want to reduce that from an availability point of view. So here, we're now talking about just enterprise for you. So there's this broad set of things we work on that definitely help us, but they're actually really completely generic and help everyone out. >> Yeah, that's great. So I wanted to kind of get that out of the way and help our audience understand that. So let's get into it a little bit; What are you seeing, what's going on in IT, pick your observation space and your vision of what you see happening out there. >> Well, you know, it's very interesting, it's sort of, there's two... there's sort of two worlds, right, there's the cloud world and the move to cloud, and there's the on-premises world, where people run their systems on their own. And, one of the things that we've learned is, when you talk about machine-learning, obviously, is something that's very popular these days, and automation. And so in order to rely on machine-learning well, and have algorithms that are very effective, you need lots of data. And so being a cloud vendor, and having Linux in our cloud on tens of thousands, or hundreds of thousands of servers, or more, allows us to have a view of how an operating system works across an incredibly large scale. So we get lots of data. And so for us to figure out which algorithms work well in terms of how can we do network optimizations, how can we discover anomalies on the storage site, and deal with it and so forth, we can do that at scale. And what's interesting is, how do we then bring that on-prem? Well, if we can get the data and the learning done, the training done, in our cloud directly, then when we provide that service also for people running Oracle Linux on premises then that will work. The alternative is to have point solutions where you provide something to a customer, and he needs to learn something from small amounts of data. That doesn't work so well. So I think having both worlds, on-prem and cloud directly, allows us to kind of benefit from that. And I think that's important, because lots of customers are interested in going to cloud. Many of the enterprises have not yet. You know, they're starting, but there's still a huge on-premises space that's important. And so by being able to get them familiar with how these things work at scale, autonomy is again important, right, Autonomous Database is incredibly popular and so forth, that allows us to then say, "Here, try these things out here, it's a service. We can show you the benefits right away," and then as that improves we bring that, to a certain extent, on-premises as well. And then they can have it in both places. And that, I think, is something, again, that's relatively unique but also very important, is that we want to provide services and products that act similarly on-premises as well as in cloud, because at some point when people move we want to make that transition seamless. And what you have today for the most part is one world that's on-prem, and then the cloud world is completely different. And that is a big barrier of moving, and so we want to reduce that, we can run the same operating system local as well as cloud, you can the same functionality, and then that helps transition people over much easier. >> Yeah, well Oracle actually was one of the -- I think Oracle was the first company to actually market same-same, you actually used that term. Others put forth that concept, but Oracle was the first to announce products like Cloud at Customer, that were same-same, now it took some time to actually get it perfected, and get it to market, but the point is, and we've written about this, is Oracle, because of the ascendancy of cloud, flipped and has a cloud-first mentality, and you just kind of referenced that, you just said, "And you can bring that to on-prem." So I wonder if you could talk about that cloud-first mentality, and the impact on hybrid. >> So yeah, I think the cloud-first part is of course in cloud we work on services moreso than products that we deliver. And there's a number of things that are happening. So one is that we obviously continue to provide products to customers, you can download Oracle Linux, you can download the database and what not, you can install it on your own, you can do the traditional way of working. Then in the cloud-world, what typically happens is "Oh, I use a database service. I'm not installing anything, I push a button and I get an IP address and a SQL that connects extremely quickly to the database." And we take care of everything underneath that is on this database. Now, in order to do that, you need a whole infrastructure in place, you need log-in agents, you need a back-end that captures all that stuff, you need monitoring tools, you need all the automation scripts for bringing the service up and monitor it. And so, that takes a lot of time to do right, and we learn a lot by doing this. And so the cloud-first part of these services means that we get to experience this ourselves with direct access to everything. Now taking that service with all of the additional features like autonomy, and bringing that to an on-premises world, we have to make sure we can package that so that all these pieces around it go along with it. And that takes a little bit more time, so we can do everything at the same time. And so what we've done with Autonomous Database is we created everything in Oracle Cloud, we have the whole system running really well, and then we've been able to sort of package that and shrink it into something that can be installed on-premises, but then connected into Oracle Cloud again. And so that way we can get all the telemetry over the metric, and that allows us to scale. Because part of providing a cloud service that runs on-prem in the customer environment is that we need to be able to remotely manage that similar to how that runs in our own cloud. Right, otherwise it doesn't scale. And so that takes a little bit of time, but we've done all that work, and now with Cloud at Customer Database that's really in place. >> Yeah, you really want to have that same cloud experience, whether with on-prem, in the public cloud, hybrid, et cetera. So, I want to explore a little bit more who is using Oracle Linux, and what's the driver for using it. Can you describe maybe some of the types of customers and why they buy? >> Sure, so we started this fourteen years ago, in 2006, October 25th, 2006. I remember that day very well; Penguins on stage and a big launch for Oracle Linux in San Francisco Moscone Center. So, look, the initial driver for Oracle Linux was to ensure that Oracle database customers or Oracle product customers had a good operating system experience, and the ability to be able to handle critical issues when that occurs, because typically a database runs the company's critical data: the most essential stuff that a company has is typically in a database, an Oracle database. And so when that thing has issues with the operating system, you don't want just to talk to multiple vendors and have finger-pointing, and having to explain to an operating system vendor how the database works. In the Unix world, we had a good relationship with the OS vendors, and the hardware vendors, they were the same. And they knew our products really well, and in the Linux world, that was very different. The OS vendor basically did not want to understand or learn anything about the products living on top. And so while to a certain extent that makes sense, it's an enterprise world where time is of the essence, and downtime needs to be limited absolutely. We can't have these arguments and such. And that was the driver, initially, for doing Oracle Linux. It was to ensure there was a Linux distribution really backed by us, that we could fix, that we could fully support. That was completely the original intent. And so the early customer base was database customers. Database and middleware. Mostly database. But that has then evolved quickly, and so what happened was, people say "Look, I have a thousand servers, a hundred run Oracle, so we'll run Oracle Linux on those hundred, and we'll run something else on those other nine-hundred." Now after a year or so, they realize that our support is really good; We fix all these issues, and so then they're like "Why are we having two Linux distributions? This thing works really well, it runs any application, it's fully compatible, so we'll do a thousand with Oracle Linux." And so the early days, the first few years, was definitely Oracle Database as the core driver, and then it sort of expanded to the rest of the estate. And over the years, we've added lots of features and functionality, like Ksplice, and so forth. We have an attractive pricing model for running on servers, and so now lots of our customers have a very small Oracle percentage running and many other things running. So it's really become a all-or-nothing play in the Linux space, and we're well-known now, so it's actually very good. >> You just mentioned Ksplice. We've been talking about cloud, and on-prem, and hybrid. Let's talk about security, because security really is a differentiator, particularly if you're going to start to put stuff in the cloud. Talk about Ksplice specifically, but generally security and your policy there. >> So, "Security first" is sort of what you hear us say and do, in everything we do. The database obviously security, on the Linux site security matters. Ksplice as a technology is there to do critical bug-fixing and make sure that we can apply security vulnerability fixes without affecting the customer, and not have downtime. And if you look at most of the cases or many of the cases where you have security vulnerabilities and exploits, it tends to be because systems were not patched. Why were they not patched? Well not that our customer doesn't understand that it's important, but it's a whole train of events that needs to happen. You have to, you get notified that there's a security issue in your operating system or application. Then, well, an application typically means it's a multi-layered setup. So if you have to bring your database server down, then you first have to coordinate with the application users to bring the app server down, cause that talks to the database. So to patch one system, you basically have to bring down the whole application stack. You have to negotiate with the DBAs, you have to negotiate with the app admins, you have to negotiate with the user. It takes weeks to do that and find time. Well during that time, you're vulnerable. So the only way, really, to address security in a scalable and reducing that window of time is to do it without affecting the customer. And so Casewise is something that, it's a company we acquired in 2009, and have since evolved in terms of capabilities, and so it allows us to patch the Linux terminal without downtime. We lock the kernel for 8 microseconds. It's literally no downtime. You don't have to bring down applications, the user doesn't see it, there's no hang, there's no delay. And so by doing that, you can run a Linux operating system, or gLinux, and you can be fully patched on a system that hasn't rebooted for 3 years. You don't even know it. And so by doing that type of stuff, it makes customers more secure, and it avoids them-- It saves them a lot of money in terms of dealing with project management and so forth, but it really keeps them secure. And so we do that for the Linux kernel, we do that for some of the libraries on top that are critical like OpenSSL and 2 LVC, and, you know one example-- I can give you two examples. So one example is, Heartbleed was this bug in OpenSSL a number of years ago. And so everyone had to patch their SSH server. And that meant, basically, systems around the world had to reboot. Like a whole IT reboot across the world. With Ksplice today, if Heartbleed were to happen tomorrow, we would be able to patch this online for all the Oracle Linux customers without any downtime. No reboots, no restarting of applications, everything keeps running. The amount of money saved would be massive, and also, of course, the headache. Another example is, and this was in Oracle Cloud, when some of these CPU bugs that happened a few years ago that were rather damaging on the cloud side, where you could basically see memory potentially of other CPUs running, the cloud is incredibly critical. We were basically able to basically patch our entire cloud in four hours. And the customer didn't know, right, a hundred and twenty million patches, or something, that we applied within four hours, all online, without any downtime. And so that technology has been really helpful, both for us to run our cloud, but the exact same patches and same fixes go to customers on-premises as well. But this comes back to the whole, what we do in cloud we also do for customer. And I think that's a unique thing that we have at Oracle which is quite fascinating. The operating system we run for our customers, the operating system that's the host part of VMs, is the exact same binary and source code that we make available, just to be clear, the exact same binaries are the ones that you run as a customer on-premises. So if you run Oracle Linux with KVM, you run VMs, you're actually running the exact same stuff as we run underneath our customer's stuff. Nobody else does that, everyone else has a black box. So I think that helps a little bit with transparency as well. >> Yeah, and that homogeneity just creates an environment, you're talking about that sort of security mindset, it's critical, you're not just bolting it on, it's part of the culture. But you started your career, and then of course you were a Linux person when you came to Oracle, but then I think you spent some time in database, back in the day when there were serious database wars going on, before Oracle became the king of database. So now you've got, obviously, this great portfolio, and a lot of really sharp software developers; What should we expect going forward, from Oracle? What should we look for? >> You know, I was talking to some, I was welcoming some interns to the company, for their summer internship yesterday, and one of the things I mentioned to them was that -- so cloud obviously gives us a lot of opportunities, but there's a number of things. One is, we have such a breadth of applications and software and hardware together. We have the servers, we have the storage, we have the operating systems, we have the database layer and so forth, and we have the cloud side, and one of the great opportunities, and I think we've shown a lot of this happening with the ability to create something like Autonomous Database, is to combine all these things. Right, we have such a broad portfolio of really cool technology that by itself is okay, but if you combine the things it really becomes awesome. You cannot create autonomous database without having autonomous learning. You cannot create those two and make them really safe without also controlling the firmware on the hardware and so forth. So by being able to combine all these layers, and by having a really great relationship across the teams within the company, that opens up a lot of opportunities to do stuff really quickly. And having the scale for that. I think that has been, for the last few years, a really great thing, but I can see that being one of the advantages that we have going forward. We have Oracle Fusion Applications, which is incredibly popular, and has great girth, and then we have that running on Oracle Cloud, that talks to Oracle Autonomous Database, so we bring all these pieces together. And no other SaaS vendor can do that, because they don't have these other pieces. They have one area, we have all of them. And so that's the exciting part for me, it's not so much about making my own world better, and having Linux be better, and Casewise and so forth, which is important, but that becoming part of the bigger picture. And that's the exciting part. >> Well, Oracle's always invested in RND, we've made that point many, many times. Whether it's database, you know Fusion was a painful but worthy effort, the whole public cloud piece, obviously many acquisitions, but the investments that you've made in open-source as well, Wim, you're a great spokesperson, and a great representative of the open-source community generally, and then Oracle specifically, so thanks very much for coming on theCUBE and sharing with us the state of the penguin, and best of luck. >> You're welcome. Thank you, thanks for having me. >> Alright, and thank you for watching, everybody. This is Dave Vellante for theCUBE. We'll see you next time. (cheerful music).

>> Jeff: Hello everybody and thank you for joining us today for the Virtual VERTICA BDC 2020. Today's breakout session has been titled, "VERTICA Database Designer Today and Tomorrow." I'm Jeff Healey, Product VERTICA Marketing, I'll be your host for this breakout session. Joining me today is Yuanzhe Bei, Senior Technical Manager from VERTICA Engineering. But before we begin, (clearing throat) I encourage you to submit questions or comments during the virtual session. You don't have to wait, just type your question or comment in the question box below the slides and click Submit. As always, there will be a Q&A session at the end of the presentation. We'll answer as many questions, as we're able to during that time, any questions we don't address, we'll do our best to answer them offline. Alternatively, visit VERTICA forums at forum.vertica.com to post your questions there after the session. Our engineering team is planning to join the forums, to keep the conversation going. Also, a reminder that you can maximize your screen by clicking the double arrow button at the lower right corner of the slides. And yes, this virtual session is being recorded and will be available to view on demand this week. We will send you a notification as soon as it's ready. Now let's get started. Over to you Yuanzhe. >> Yuanzhe: Thanks Jeff. Hi everyone, my name is Yuanzhe Bei, I'm a Senior Technical Manager at VERTICA Server RND Group. I run the query optimizer, catalog and the disaggregated engine team. Very glad to be here today, to talk about, the "VERTICA Database Designer Today and Tomorrow". This presentation will be organized as the following; I will first refresh some knowledge about, VERTICA fundamentals such as Tables and Projections, which will bring to the question, "What is Database Designer?" and "Why we need this tool?". Then I will take you through a deep dive, into a Database Designer or we call DBD, and see how DBD's internals works, after that I'll show you some exciting DBD improvements, we have planned for 10.0 release and lastly, I will share with you, some DBD future roadmap we planned next. As most of you should already know, VERTICA is built on a columnar architecture. That means, data is stored column wise. Here we can see a very simple example, of table with four columns, and the many of you may also know, table in VERTICA is a virtual concept. It's just a logical representation of data, which means user can write SQL query, to reference the table names and column, just like other relational database management system, but the actual physical storage of data, is called Projection. A Projection can reference a subset, or all of the columns all to its anchor table, and must be sorted by at least one column. Each table need at least one C for projection which reference all the columns to the table. If you load data to a table with no projection, and automated, auto production will be created, which will be arbitrarily assorted by, the first couple of columns in the table. As you can imagine, even though such other production, can be used to answer any query, the performance is not optimized in most cases. A common practice in VERTICA, is to create multiple projections, contain difference step of column, and sorted in different ways on the same table. When query is sent to the server, the optimizer will pick the projection, that can answer the query in the most efficient way. For example, here you can say, let's say you have a query, that select columns B, D, C and sorted by B and D, the third projection will be ideal, because the data is already sorted, so you can save the sorting costs while executing the query. Basically when you choose the design of the projection, you need to consider four things. First and foremost, of course the sort order. The data already sorted in the right way, can benefit quite a lot of the query actually, like Ordered by, Group By, Analytics, Merge, Join, Predicates and so on. The select column group is also important, because the projection must contain, all the columns referenced by your workflow query. Even missing one column in the projection, this projection cannot be used for a particular query. In addition, VERTICA is the distributed database, and allow projection to be segmented, based on the hash of a set of columns, which is beneficial if the segmentation merged, the join keys or group keys. And finally encoding of each per columns is also part of the design, because the data is sorted in different way, may completely change the optimal encoding for each column. This example only show the benefit of the first two, but you can imagine the rest too are also important. But even for that, it doesn't sound that hard, right? Well I hope you change your mind already when you see this, at least I do. These machine generated queries, really beats me. It will probably take an experienced DBA hours, to figure out which projection can be benefit these queries, not even mentioning there could be hundreds of such queries, in the regular work logs in the real world. So what can we do? That's why we need DBD. DBD is a tool integrated in the VERTICA server, that it can help DBA to perform an access, on their work log query, tabled schema and data, and then automatically figure out, the most optimized projection design for their workload. In addition, DBD also a sophisticated tool, that can take customize by a user, by sending a lot of parameters objectives and so on. And lastly, DBD has access to the optimizer, so DB knows what kind of attribute, the projection need to have, in order to have the optimizer to benefit from them. DBD has been there for years, and I'm sure there are plenty of materials available online, to show you how DBD can be used in different scenarios, whether to achieve the query optimize, or load optimize, whether it's the comprehensive design, or the incremental design, whether it's a dumping deployment script, and manual deployment later, or let the DBD do the order deployment for you, and the many other options. I'm not planning to talk about this today, instead, I will take the opportunity today, to open this black box DBD, and show you what exactly hide inside. DBD is a complex tool and I have tried my best to summarize the DBD design process into seven steps; Extract, Permute, Prune, Build, Score, Identify and Encode. What do they mean? Don't worry, I will show you step by step. The first step is Extract. Extract Interesting Columns. In this step, DBD pass the design queries, and figure out the operations that can be benefited, by the potential projection design, and extract the corresponding columns, as interesting columns. So Predicates, Group By, Order By, Joint Condition, and analytics are all interesting Column to the DBD. As you can see this three simple sample queries, DBD can extract the interest in column sets on the right. Some of these column sets are unordered. For example, the green one for Group By a1 and b1, the DBD extracts the interesting column set, and put them in the own orders set, because either data sorted by a1 first or b1 first, can benefit from this Group By operation. Some of the other sets are ordered, and the best example is here, order by clause a2 and b2, and obviously you cannot sort it by b2 and then a2. These interesting columns set will be used as if, to extend to actual projection sort order candidates. The next step is Permute, once DBD extract all the C's, it will enumerate sort order using C, and how does DBD do that? I'm starting with a very simple example. So here you can see DBD can enumerate two sort orders, by extending d1 with the unordered set a1, b1, and the derived at two sort order candidates, d1, a1, b1, and d1, b1, a1. This sort order can benefit queries with predicate on d1, and also benefit queries by Group By a1, b1, when a1, sorry when d1 is constant. So with the same idea, DBD will try to extend other States with each other, and populate more sort order permutations. You can imagine that how many of them, there could be many of them, these candidates, based on how many queries you have in the design and that can be handled of the sort order candidates. That comes to the third step, which is Pruning. This step is to limit the candidates sort order, so that the design won't be running forever. DBD uses very simple capping mechanism. It sorts all the, sort all the candidates, are ranked by length, and only a certain number of the sort order, with longest length, will be moved forward to the next step. And now we have all the sort orders candidate, that we want to try, but whether this sort order candidate, will be actually be benefit from the optimizer, DBD need to ask the optiizer. So this step before that happens, this step has to build those projection candidate, in the catalog. So this step will build, will generates the projection DBL's, surround the sort order, and create this projection in the catalog. These projections won't be loaded with real data, because that takes a lot of time, instead, DBD will copy over the statistic, on existing projections, to this projection candidates, so that the optimizer can use them. The next step is Score. Scoring with optimizer. Now projection candidates are built in the catalog. DBD can send a work log queries to optimizer, to generate a query plan. And then optimizer will return the query plan, DBD will go through the query plan, and investigate whether, there are certain benefits being achieved. The benefits list have been growing over time, when optimizer add more optimizations. Let's say in this case because the projection candidates, can be sorted by the b1 and a1, it is eligible for Group By Pipe benefit. Each benefit has a preset score. The overall benefit score of all design queries, will be aggregated and then recorded, for each projection candidate. We are almost there. Now we have all the total benefit score, for the projection candidates, we derived on the work log queries. Now the job is easy. You can just pick the sort order with the highest score as the winner. Here we have the winner d1, b1 and a1. Sometimes you need to find more winners, because the chosen winner may only benefit a subset, of the work log query you provided to the DBD. So in order to have the rest of the queries, to be also benefit, you need more projections. So in this case, DBD will go to the next iteration, and let's say in this case find to another winner, d1, c1, to benefit the work log queries, that cannot be benefit by d1, b1 and a1. The number of iterations and thus the winner outcome, DBD really depends on the design objective that uses that. It can be load optimized, which means that only one, super projection winner will be selected, or query optimized, where DBD try to create as many projections, to cover most of the work log queries, or somewhat balance an objective in the middle. The last step is to decide encoding, for each projection columns, for the projection winners. Because the data are sorted differently, the encoding benefits, can be very different from the existing projection. So choose the right projection encoding design, will save the disk footprint a significant factor. So it's worth the effort, to find out the best thing encoding. DBD picks the encoding, based on the actual sampling the data, and measure the storage footprint. For example, in this case, the projection winner has three columns, and say each column has a few encoding options. DBD will write the sample data in the way this projection is sorted, and then you can see with different encoding, the disk footprint is different. DBD will then compare the disk footprint of each, of different options for each column, and pick the best encoding options, based on the one that has the smallest storage footprint. Nothing magical here, but it just works pretty well. And basic that how DBD internal works, of course, I think we've heard it quite a lot. For example, I didn't mention how the DBD handles segmentation, but the idea is similar to analyze the sort order. But I hope this section gave you some basic idea, about DBD for today. So now let's talk about tomorrow. And here comes the exciting part. In version 10.0, we significantly improve the DBD in many ways. In this talk I will highlight four issues in old DBD and describe how the 10.0 version new DBD, will address those issues. The first issue is that a DBD API is too complex. In most situations, what user really want is very simple. My queries were slow yesterday, with the new or different projection can help speed it up? However, to answer a simple question like this using DBD, user will be very likely to have the documentation open on the side, because they have to go through it's whole complex flow, from creating a projection, run the design, get outputs and then create a design in the end. And that's not there yet, for each step, there are several functions user need to call in order. So adding these up, user need to write the quite long script with dozens of functions, it's just too complicated, and most of you may find it annoying. They either manually tune the projection to themselves, or simply live with the performance and come back, when it gets really slow again, and of course in most situations, they never come back to use the DBD. In 10.0 VERTICA support the new simplified API, to run DBD easily. There will be just one function designer_single_run and one argument, the interval that you think, your query was slow. In this case, user complained about it yesterday. So what does this user to need to do, is just specify one day, as argument and run it. The user don't need to provide anything else, because the DBD will look up his query or history, within that time window and automatically populate design, run design and export the projection design, and the clean up, no user intervention needed. No need to have the documentation on the side and carefully write a script, and a debug, just one function call. That's it. Very simple. So that must be pretty impressive, right? So now here comes to another issue. To fully utilize this single round function, users are encouraged to run DBD on the production cluster. However, in fact, VERTICA used to not recommend, to run a design on a production cluster. One of the reasons issue, is that DBD picks massive locks, both table locks and catalog locks, which will badly interfere the running workload, on a production cluster. As of 10.0, we eliminated all the table and ten catalog locks from DBD. Yes, we eliminate 100% of them, simple improvement, clear win. The third issue, which user may not be aware of, is that DBD writes intermediate result. into real VERTICA tables, the real DBD have to do that is, DBD is the background task. So the intermediate results, some user needs to monitor it, the progress of the DBD in concurrent session. For complex design, the intermediate result can be quite massive, and as a result, many lost files will be created, and written to the disk, and we should both stress, the catalog, and that the disk can slow down the design. For ER mode, it's even worse because, the table are shared on communal storage. So writing to the regular table, means that it has to upload the data, to the communal storage, which is even more expensive and disruptive. In 10.0, we significantly restructure the intermediate results buffer, and make this shared in memory data structure. Monitoring queries will go directly look up, in memory data structure, and go through the system table, and return the results. No Intermediate Results files will be written anymore. Another expensive lubidge of local disk for DBD is encoding design, as I mentioned earlier in the deep dive, to determine which encoding works the best for the new projection design, there's no magic way, but the DBD need to actually write down, the sample data to the disk, using the different encoding options, and to find out which ones have the smallest footprint, or pick it as the best choice. These written sample data will be useless after this, and it will be wiped out right away, and you can imagine this is a huge waste of the system resource. In 10.0 we improve this process. So instead of writing, the different encoded data on the disk, and then read the file size, DBD aggregate the data block size on-the-fly. The data block will not be written to the disk, so the overall encoding and design is more efficient and non-disruptive. Of course, this is just about the start. The reason why we put a significant amount of the resource on the improving the DBD in 10.0, is because the VERTICA DBD, as essential component of the out of box performance design campaign. To simply illustrate the timeline, we are now on the second step, where we significantly reduced, the running overhead of the DBD, so that user will no longer fear, to run DBD on their production cluster. Please be noted that as of 10.0, we haven't really started changing, how DBD design algorithm works, so that what we have discussed in the deep dive today, still holds. For the next phase of DBD, we will briefly make the design process smarter, and this will include better enumeration mechanism, so that the pruning is more intelligence rather than brutal, then that will result in better design quality, and also faster design. The longer term is to make DBD to achieve the automation. What entail automation and what I really mean is that, instead of having user to decide when to use DBD, until their query is slow, VERTICA have to know, detect this event, and have have DBD run automatically for users, and suggest the better projections design, if the existing projection is not good enough. Of course, there will be a lot of work that need to be done, before we can actually fully achieve the automation. But we are working on that. At the end of day, what the user really wants, is the fast database, right? And thank you for listening to my presentation. so I hope you find it useful. Now let's get ready for the Q&A.

>> Live from Washington, D.C., it's theCUBE. Covering Inforum, DC 2018. Brought to you by Infor. >> We are back this afternoon here in Washington, D.C., at the Walter Washington Convention Center. As we continue our coverage here of Inforum 2018 along with Dave Vellante, I'm John Walls, and we now welcome Mr. Cormack Watters to the program today, EVP of Emea and APAC at Infor. Cormack, good to see you sir. >> Nice to be here. >> So, we're going to talk about Guinness, over in Ireland (chuckling). Cormack's from Dublin, so we had a little conversation. We're getting a primer here. >> It's actually the best conversation we should have, right? >> Right, we'll save that for the end. How about that? So, you're fairly new, right? About a year or so. >> Ten months or so, not that I'm counting it by the day >> No no no, always going forward, never backward. But a big plate you have, right, with EMEA and APAC? Different adoptions, different viewpoints, different perspectives... We've talked a lot really kind of focusing domestically here for the past couple of days. Your world's a little different than that though, right? >> It is. It is. And it's very good that you've actually recognized it because that's actually the biggest challenge that we have. To be a little bit humble about it, I think we've got world-class products and solutions. I actually fundamentally believe that. But we have lots of different languages, cultures, and localization requirements in the multiple Countries that we look after. So, it's great to have great products, but it needs to be in French, Spanish, Portuguese, Italian, Swedish, Norwegian, Finish, Arabic, which most of them are. Customers realize that we are actually international and localized for many, many markets. But now we've become an intriguing option for them, if you're a multi-national business, with subsidiaries all over the world. So, it's good that Infor is big enough to do that. We need to do a better job of letting everybody know that we've done that, if that makes any sense. >> Sure. >> So what's happening in Europe? Europe's always pockets, there's no..I mean.. Yes, EU but there's really still no one Europe. What's going on? Obviously, we have Brexit hanging over our head. I felt like U.S. markets are maybe a little bit overheated in Europe has potential upside. >> Yeah >> And it seems like others seem to agree with that. What happening on the ground? Any specific, interesting areas? Is Southern Europe still a concern? Maybe you can give us an update? >> Yeah, so Brexit is quite a dominant conversation. I am from Ireland. I live in Dublin, but I'm working all over Europe, the Middle East, Africa and the Far East. So, I don't get to be at home very often, except the weekends. London is really our regional headquarters from a European perspective, and Brexit is on everybody's mind. Interestingly, when you go outside the UK, Brexit is not such a big topic because... That's Europe. And they kind of go, "Well if you don't want to be here, then you don't need to be here." Right? So it's a little bit of that, and they're saying, "Well, we'd like for them to stay, but if they don't want to stay, well, don't wait around." But in the UK, it's causing a lot of uncertainty. And the UK's one of our biggest markets. It's a lot of uncertainty, and what would be best is if we just knew what was going to happen, and then we could deal with it. And actually, once we know what's going to happen, that's going to bring a degree of change. And change, from our industry perspective means there's going to be some requirements that emerge. So, we need to be ready to serve those, which is opportunity. But the uncertainty is just slowing down investment. So, we need that to be resolved. >> So, clarity obviously is a good thing obviously a good thing in any market. Are there any hotspots? >> Yeah, actually for us, we're doing, for us the Hotspots right now, we're doing incredibly well in Germany. Which, one of our lesser known competitors is a small Company called SAP. And they're headquartered in Germany. It's quite interesting to see that we're actually taking a lot of market there in Germany, which is fantastic. That's a little bit unexpected, but it's going very well right now. We're seeing a ton of activity in the Asia Pacific, I would say that region is probably our fastest growing in all of Infor. And consistently so for several quarters and maybe past a year at this point. So Asia Pacific, Germany, U.K., and then as it happens, we are doing very well in Southern Europe, which is a combination of countries really. France, Italy, Spain, Portugal and Greece. Hard to put it down to which particular Country is doing well, but there seems to be a general uplift in that region. Because they were hit the hardest, arguably, by the crash back in 2008. So they've definitely come out of that now. >> And when they come out, excuse me I'm sorry John, but, they come out, Cloud becomes more important to them, Right? >> Yeah, I mean, absolutely. Anyone who's been delaying investment for years, can actually leapfrog what's been happening and jump straight to what you might call the future. So lots of Companies, lots of our Customers, are trying to simplify their Business. So Cloud is a great equalizer. We believe in your, what we call Last Mile of Functionality per industry. And that should make the projects shorter, more compact more predictable and the infrastructure worries go away, because that's our responsibility to the Customers. >> We definitely so that in the U.S., 2008-2009, CFO's came in said shift to the Cloud, because we want to shift Capx to Opx, and when we came out of the downturn, they said "wow this stuff works pretty well, double down on it" and then there were other business benefits that they wanted to accelerate, and so maybe Southern Europe was a little bit behind >> I think that may be the case right, and they are picking up. And what we're seeing are a lot of other advantages. Not to make this a sale's pitch, but, I am here so >> Go for it >> You've got a microphone >> I've got a microphone and I'm Irish, so I've got to talk right? What the Cloud is actually doing is, lots of Companies have put in big ERP over the years, the decades. And then they get stuck at various points and maybe years behind, because upgrades become painful and really want to avoid them. So what they're seeing is, if they can get onto the Cloud, they never need to upgrade again. Because it's always current, because we upgrade it every week, or every month and they're never falling behind. So they want to be ready to take advantage of the innovations that they know about and those that they don't even know about. So by keeping on the latest version, that opportunities open to them. Also, there's a big issue in Europe specifically about a thing called GDPR, which is data protection. Security. So we believe that we can do a better job of providing that, than any individual Company. Because we provide it for everybody, our resources can be deployed once and then deployed many times. Where as if you're an individual customer, you've got to have that speciality and put it in place. So GDPR is a genuine issue in Europe, because, the fines are absolutely huge if a Company is found to breach it. >> It's become a template for the globe now, California's started moving in that direction, GDPR has set the frame work. >> Well and just to follow up on that, and now you're dealing with a very different regulatory climate, then certainly here in the United States. And many U.S. Companies are finding that out, as we know. Overseas right now. So how do you deal with that in terms of, this kind of balkanized approach that you have, that you know that what's working here doesn't necessarily translate to overseas, and plus you have, you know, you're serving many masters and not just one or two. >> What's happening is the guys in our RND have done very well, is they understand the requirement of, in this instance, GDPR. They look at the other regulatory requirements, lets say in Australia, which is subtly different, but it is different, and they can take, well what do we have to do? What's the most extreme we have to achieve? And if we do that across our suite into our platform suite, the N4RS, that can then be applied to all the applications. And then becomes relevant to the U.S. So it's almost like some requirement across the seas, being deployed then becoming really relevant back here because over here you do need to be aware of the data protection, as well, it's just not as formalized yet. >> It's coming >> A Brewing issue right? >> What about Asia Pacific? So you have responsibility for Japan, and China, and the rest of the region. >> Right >> Which you are sort of re-distinct... >> Really are right? There are several sub regions in the one region. The team down there, as I say, arguably the most successful team in Infor right now, so Helen and the crew. So you see Australia, New Zealand then you see Southeast Asia, then you see China, Japan and so on. So different dynamics and different markets, some more mature than others, Japan is very developed by very specific. You do need very specialized local skills to succeed. Arguably Australia, New Zealand is not that similar from say some of the European Countries. Even though there are differences and I would never dream to tell an Australian or a New Zealander that they are the same as Europeans, cuz I get it. I smile when people say "you're from the U.K and you're not from Ireland?" I understand the differentiation. (laugher) And Southeast Asia, there's a ton of local custom, local language, local business practice that needs to be catered for. We seem to be doing okay down there. As I say, fastest growing market at scale. It's not like it's growing ridiculously fast but from a small base. It's as a big market already and growing the fastest. >> And China, what's that like? You have to partner up? >> Oh yeah >> To the JV in China? >> You have to partner up, there are several of the key growth markets that it's best to go in with partners. Customers like to see we've got a presence. So that they can touch and feel that Infor entity. We can't achieve the scale we need, and the growth we want fast enough without partnering. So we have to go with partners to get us the resources that we need. >> And in the Middle East, so my business partner, Co-Host, John Furrier, is on a Twenty Hour flight to Bahrain. The Cube Bahrain. Bahrain was the first Country in the Middle East to declare Cloud first. AWS is obviously part of that story, part of your story. So what's going on over there? Is it a growing market? Is it sort of something you're still cracking? >> No, no, again it's growing. We have several key markets down there, big in hospitality in that part of the world. Hotels, tourism obviously. Shopping, very interesting markets, and Healthcare, interestingly enough. I think arguably some of the worlds best Hospitals are in that region. Definitely the best funded Hospitals. >> Probably the most comfortable. (laughter) >> So again part of our stent is the number of industries we serve, so if you can put in our platform as it were, then you could have multiple of the industry flavors applied. Because what's interesting in that part of World, there seem to be a number of, I guess we call them conglomerates. So maybe family owned, or region owned, and they have just a different array of businesses all under the one ownership. So you would have a retailer that's also doing some tourism, that's also doing some manufacturing. So we can put our platform in, and then those industry flavors they can get one solution to cover it all. Which is a little bit unusual, and works for us. >> Your scope is enormous. I mean essentially you're the head of Non-U.S. I mean is that right? >> Yeah, and Latin America as well. >> That's part of it? That's not... >> Excluding the Americas. So there's Americas and then everything else, and you're everything else. >> I missed a meeting you see so they just gave it to me >> What you raised your hand at the wrong time? >> I wasn't there (laughter) >> So how do you organize to be successful? You obviously have to have strong people in the region. >> Right. So the key is people, right. We organize somewhat differently to over here. We've gone for a regional model, so I have six sub-regions, that I worry about. So four in Europe, the Nordic Countries. Scandinavian, Sweden, Norway, Finland, Denmark. We call Western, which is Ireland, U.K. and the Benelux. Germany is Central and East, and then Southern is the Latin Country, Spain, Portugal, Greece and so. Then we've got the Middle East, and Africa, and then we got Asia Pacific. I've got six regional teams, all headed by a regional leader, and each of them are trying to be as self contained as they can. And where we see we've got an opportunity to move into something new, we've got one team working with me directly as an incubator. For example, we're driving a specific focus on Healthcare, in our part of the world, because it's very big over here. We haven't quite cracked the code over there. When we get some scale, then it'll move into the regions, but for now that's incubating under me. >> And, what about in Country? Do you have Country Managers? One in the U.K., one in France, one in Germany. >> We have what we call local leaders, right? So in some cases it could be a sales oriented individual, it could be consulting, others it could be the local HR guy. So that's more for us to make sure we're building a sense of community within Infor. Rather than it being more customer facing. We're still trying to make sure that there is a reasonably scarcity of senior skills. So regionalizing lets us deploy across several Countries, and that works with the customer base, but for employees we need local leaders to give them a sense of feeling home and attached. >> So the regions are kind of expertise centers if you will? >> Yes >> So I was going to ask about product expertise, where does that come from? It's not parachuted in from the U.S. I presume? >> No, we're pretty much self-sufficient actually, which is great. So from both what we call solution consulting, which is the product expertise, and then consulting which is the product deployment. And we're doing more and more of our deployments with Partners. As I say, we need to really rapidly embrace that partner ecosystem to give us the growth opportunity. RND, is all over the World. That's not under my direct control. So for a major suites, take for example, LN, happens to be headquartered out of Barneveld, in the Netherlands. From a Historic perspective, which is great. And Stockholm, which is also great. But a lot of the development resource room in Nila and in India. So we work closely with the guys, even though they don't actually report to me. >> And out of the whole area, the area of your responsibility what's the best growth opportunity? We all think of China, but that's been fits and starts for a lot of people. >> Yeah, yeah I think we've got multiple opportunities, you can look at it a few ways. You can look at it geographically, and you would say China. You can look at Eastern Europe, and you can look at Africa. There's a ton of opportunity in those regions, geographically. Interestingly we are also at a point where I think the Nordics, and we've got a very solid base Historically, and so on. But we probably haven't put enough focus on there in recent times, that the opportunities are really scaled in Nordics is really quite significant. And then they can look at it from a Product Perspective. So for example, we have, what we believe to be World Leading, and actually a Company called Gartner would equally agree with us. Enterprise Asset Management, EAM, that's a product suite that can fit across all of our industries. I think that could well be the significant growth area for us across the entire six regions. And it's a huge focus for us here at the conference actually. So we can do it by product, EAM, Healthcare, or by Region. I think Eastern Europe, China, and Africa, as well as the Nordics. >> And the other big opportunity is just share gains, market share gains, particularly in Europe, I would think, with your background. >> Yup. Completely, I mean, that's why I said, it's really interesting that we are winning market share in Germany. Who'd of thought that a few years ago? That's a big market, I mean, Germany, U.K., France, Italy. They're huge. Right, I mean U.K., is what, Sixty-Five Million People? It's a big economy, so we've got many of the worlds G7, in our backyard. So we just really need to double down on those, and give them the opportunities to grow that we need. >> And just back to Japan for a second. Japan has traction, it takes a long time to crack Japan. I know it first from personal experiences. >> Yeah, Okay, Interesting. >> Yeah you just got to go many many times and meet people. >> That's it, Right. And it's a different culture, of when you think they're saying yes and you think they're there, that's just yes to the next step. (laughter) >> Alright, so it does take time to get there. We've actually cracked it to some extent, that we've now got some solid referenceability, and some good wind. We need local leaders in Japan, to really crack the code there. >> And then once you're in, you're in. >> I think that once you've proven yourself, it's a lot of word of mouth and referencing. >> Well I hope you get home this weekend. Are you headed home? >> Yes! Actually I'm lucky enough. My Wife is originally from Chicago. So she and our Daughter have come over for the weekend, to go sight seeing in Washington. So that'll be fun. So we'll be going home on Sunday. >> Your adopted home for the weekend then. >> That's exactly right. >> Well we'll talk Guinness in just a bit. Thanks for the time though, we appreciate it. >> Thank you Gentlemen. >> Good to see you, Sir. Alright, back with more here from Inforum 2018, and you're watching Live, on theCube, here in D.C. (electronic music)

>> live from Boston, Massachusetts. It's the Cube covering IBM Chief Data Officer Strategy Summit brought to you by IBM. Now, here are your hosts. Day Volante and Stew Minimum. >> Welcome back to Boston, everybody. This is the Cube, the worldwide leader in live tech coverage. Stillman and I have pleased to have Jean Kolker on a Cuba lem. Uh, he's IBM vice president and chief data officer of the Global Technology Services division. And Seth Dobrin who's the Director of Digital Strategies. That Monsanto. You may have seen them in the news lately. Gentlemen. Welcome to the Cube, Jean. Welcome back. Good to see you guys again. Thanks. Thank you. So let's start with the customer. Seth, Let's, uh, tell us about what you're doing here, and then we'll get into your role. >> Yes. So, you know, the CDO summit has been going on for a couple of years now, and I've been lucky enoughto be participating for a couple of a year and 1/2 or so, Um, and you know, really, the nice thing about the summit is is the interaction with piers, um, and the interaction and networking with people who are facing similar challenges from a similar perspective. >> Yes, kind of a relatively new Roland topic, one that's evolved, Gene. We talked about this before, but now you've come from industry into, ah, non regulated environment. Now what's happened like >> so I think the deal is that way. We're developing some approaches, and we get in some successes in regulated environment. Right? And now I feel with And we were being client off IBM for years, right? Using their technology's approaches. Right? So and now I feel it's time for me personally to move on something different and tried to serve our power. I mean, IBM clients respected off in this striking from healthcare, but their approaches, you know, and what IBM can do for clients go across the different industries, right? And doing it. That skill that's very beneficial, I think, for >> clients. So Monsanto obviously guys do a lot of stuff in the physical world. Yeah, you're the head of digital strategy. So what does that entail? What is Monte Santo doing for digital? >> Yes, so, you know, for as head of digital strategies for Monsanto, really? My role is to number one. Help Monsanto internally reposition itself so that we behave and act like a digital companies, so leveraging data and analytics and also the cultural shifts associated with being more digital, which is that whole kind like you start out this conversation with the whole customer first approach. So what is the real impact toe? What we're doing to our customers on driving that and then based on on those things, how can we create new business opportunities for us as a company? Um, and how can we even create new adjacent markets or new revenues in adjacent areas based on technologies and things we already have existing within the company? >> It was the scope of analytics, customer engagement of digital experiences, all of the above, so that the scope is >> really looking at our portfolio across the gamut on DH, seeing how we can better serve our customers and society leveraging what we're doing today. So it's really leveraging the re use factor of the whole digital concept. Right? So we have analytics for geospatial, right? Big part of agriculture is geospatial. Are there other adjacent areas that we could apply some of that technology? Some of that learning? Can we monetize those data? We monetize the the outputs of those models based on that, Or is there just a whole new way of doing business as a company? Because we're in this digital era >> this way? Talked about a lot of the companies that have CEOs today are highly regulated. What are you learning from them? What's what's different? Kind of a new organization. You know, it might be an opportunity for you that they don't have. And, you know, do you have a CDO yet or is that something you're planning on having? >> Yes, So we don't have a CDO We do have someone acts as an essential. he's a defacto CEO, he has all of the data organizations on his team. Um, it's very recent for Monsanto, Um, and and so I think, you know, in terms of from the regular, what can we learn from, you know, there there are. It's about half financial people have non financial people, are half heavily regulated industries, and I think, you know, on the surface you would. You would think that, you know, there was not a lot of overlap, but I think the level of rigor that needs to go into governance in a financial institution that same thought process. Khun really be used as a way Teo really enable Maur R and D. Mohr you know, growth centered companies to be able to use data more broadly and so thinking of governance not as as a roadblock or inhibitor, but really thinking about governance is an enabler. How does it enable us to be more agile as it enable us to beam or innovative? Right? If if people in the company there's data that people could get access to by unknown process of known condition, right, good, bad, ugly. As long as people know they can do things more quickly because the data is there, it's available. It's curated. And if they shouldn't have access it under their current situation, what do they need to do to be able to access that data? Right. So if I would need If I'm a data scientist and I want to access data about my customers, what can I can't? What can and can't I do with that data? Number one doesn't have to be DEA Nana Mayes, right? Or if I want to access in, it's current form. What steps do I need to go through? What types of approval do I need to do to do to access that data? So it's really about removing roadblocks through governance instead of putting him in place. >> Gina, I'm curious. You know, we've been digging into you know, IBM has a very multifaceted role here. You know how much of this is platforms? How much of it is? You know, education and services. How much of it is, you know, being part of the data that your your customers you're using? >> Uh so I think actually, that different approaches to this issues. My take is basically we need Teo. I think that with even cognitive here, right and data is new natural resource worldwide, right? So data service, cognitive za za service. I think this is where you know IBM is coming from. And the BM is, you know, tradition. It was not like that, but it's under a lot of transformation as we speak. A lot of new people coming in a lot off innovation happening as we speak along. This line's off new times because cognitive with something, really you right, and it's just getting started. Data's a service is really new. It's just getting started. So there's a lot to do. And I think my role specifically global technology services is you know, ah, largest by having your union that IBM, you're 30 plus 1,000,000,000 answered You okay? And we support a lot of different industries basically going across all different types of industries how to transition from offerings to new business offerings, service, integrated services. I think that's the key for us. >> Just curious, you know? Where's Monsanto with kind of the adoption of cognitive, You know what? Where are you in that journey? >> Um, so we are actually a fairly advanced in the journey In terms of using analytics. I wouldn't say that we're using cognitive per se. Um, we do use a lot of machine learning. We have some applications that on the back end run on a I So some form of artificial or formal artificial intelligence, that machine learning. Um, we haven't really gotten into what, you know, what? IBM defined his cognitive in terms of systems that you can interact with in a natural, normal course of doing voice on DH that you spend a whole lot of time constantly teaching. But we do use like I said, artificial intelligence. >> Jean I'm interested in the organizational aspects. So we have Inderpal on before. He's the global CDO, your divisional CDO you've got a matrix into your leadership within the Global Services division as well as into the chief date officer for all of IBM. Okay, Sounds sounds reasonable. He laid out for us a really excellent sort of set of a framework, if you will. This is interval. Yeah, I understand your data strategy. Identify your data store says, make those data sources trusted. And then those air sequential activities. And in parallel, uh, you have to partner with line of business. And then you got to get into the human resource planning and development piece that has to start right away. So that's the framework. Sensible framework. A lot of thought, I'm sure, went into it and a lot of depth and meaning behind it. How does that framework translate into the division? Is it's sort of a plug and play and or is there their divisional goals that are create dissonance? Can you >> basically, you know, I'm only 100 plus days in my journey with an IBM right? But I can feel that the global technology services is transforming itself into integrated services business. Okay, so it's thiss framework you just described is very applicable to this, right? So basically what we're trying to do, we're trying to become I mean, it was the case before for many industries, for many of our clients. But we I want to transform ourselves into trusted broker. So what they need to do and this framework help is helping tremendously, because again, there's things we can do in concert, you know, one after another, right to control other and things we can do in parallel. So we trying those things to be put on the agenda for our global technology services, okay. And and this is new for them in some respects. But some respects it's kind of what they were doing before, but with new emphasis on data's A service cognitive as a service, you know, major thing for one of the major things for global technology services delivery. So cognitive delivery. That's kind of new type off business offerings which we need to work on how to make it truly, you know, once a sense, you know, automated another sense, you know, cognitive and deliver to our clients some you value and on value compared to what was done up until recently. What >> do you mean by cognitive delivery? Explained that. >> Yeah, so basically in in plain English. So what's right now happening? Usually when you have a large systems  computer IT system, which are basically supporting lot of in this is a lot of organizations corporations, right? You know, it's really done like this. So it's people run technology assistant, okay? And you know what Of decisions off course being made by people, But some of the decisions can be, you know, simple decisions. Right? Decisions, which can be automated, can standardize, normalize can be done now by technology, okay and people going to be used for more complex decisions, right? It's basically you're going toe. It turned from people around technology assisted toa technology to technology around people assisted. OK, that's very different. Very proposition, right? So, again, it's not about eliminating jobs, it's very different. It's taken off, you know, routine and automata ble part off the business right to technology and given options and, you know, basically options to choose for more complex decision making to people. That's kind of I would say approach. >> It's about scale and the scale to, of course, IBM. When when Gerstner made the decision, Tio so organized as a services company, IBM came became a global leader, if not the global leader but a services business. Hard to scale. You could scare with bodies, and the bigger it gets, the more complicated it gets, the more expensive it gets. So you saying, If I understand correctly, the IBM is using cognitive and software essentially to scale its services business where possible, assisted by humans. >> So that's exactly the deal. So and this is very different. Very proposition, toe say, compared what was happening recently or earlier? Always. You know other. You know, players. We're not building your shiny and much more powerful and cognitive, you know, empowered mouse trap. No, we're trying to become trusted broker, OK, and how to do that at scale. That's an open, interesting question, but we think that this transition from you know people around technology assisted Teo technology around people assisted. That's the way to go. >> So what does that mean to you? How does that resonate? >> Yeah, you know, I think it brings up a good point actually, you know, if you think of the whole litany of the scope of of analytics, you have everything from kind of describing what happened in the past All that to cognitive. Um, and I think you need to I understand the power of each of those and what they shouldn't should be used for. A lot of people talk. You talk. People talk a lot about predictive analytics, right? And when you hear predictive analytics, that's really where you start doing things that fully automate processes that really enable you to replace decisions that people make right, I think. But those air mohr transactional type decisions, right? More binary type decisions. As you get into things where you can apply binary or I'm sorry, you can apply cognitive. You're moving away from those mohr binary decisions. There's more transactional decisions, and you're moving mohr towards a situation where, yes, the system, the silicon brain right, is giving you some advice on the types of decisions that you should make, based on the amount of information that it could absorb that you can't even fathom absorbing. But they're still needs really some human judgment involved, right? Some some understanding of the contacts outside of what? The computer, Khun Gay. And I think that's really where something like cognitive comes in. And so you talk about, you know, in this in this move to have, you know, computer run, human assisted right. There's a whole lot of descriptive and predictive and even prescriptive analytics that are going on before you get to that cognitive decision but enables the people to make more value added decisions, right? So really enabling the people to truly add value toe. What the data and the analytics have said instead of thinking about it, is replacing people because you're never going to replace you. Never gonna replace people. You know, I think I've heard people at some of these conferences talking about, Well, no cognitive and a I is going to get rid of data scientist. I don't I don't buy that. I think it's really gonna enable data scientist to do more valuable, more incredible things >> than they could do today way. Talked about this a lot to do. I mean, machines, through the course of history, have always replaced human tasks, right, and it's all about you know, what's next for the human and I mean, you know, with physical labor, you know, driving stakes or whatever it is. You know, we've seen that. But now, for the first time ever, you're seeing cognitive, cognitive assisted, you know, functions come into play and it's it's new. It's a new innovation curve. It's not Moore's law anymore. That's driving innovation. It's how we interact with systems and cognitive systems one >> tonight. And I think, you know, I think you hit on a good point there when you said in driving innovation, you know, I've run, you know, large scale, automated process is where the goal was to reduce the number of people involved. And those were like you said, physical task that people are doing we're talking about here is replacing intellectual tasks, right or not replacing but freeing up the intellectual capacity that is going into solving intellectual tasks to enable that capacity to focus on more innovative things, right? We can teach a computer, Teo, explain ah, an area to us or give us some advice on something. I don't know that in the next 10 years, we're gonna be able to teach a computer to innovate, and we can free up the smart minds today that are focusing on How do we make a decision? Two. How do we be more innovative in leveraging this decision and applying this decision? That's a huge win, and it's not about replacing that person. It's about freeing their time up to do more valuable things. >> Yes, sure. So, for example, from my previous experience writing healthcare So physicians, right now you know, basically, it's basically impossible for human individuals, right to keep up with spaced of changes and innovations happening in health care and and by medical areas. Right? So in a few years it looks like there was some numbers that estimate that in three days you're going to, you know, have much more information for several years produced during three days. What was done by several years prior to that point. So it's basically becomes inhuman to keep up with all these innovations, right? Because of that decision is going to be not, you know, optimal decisions. So what we'd like to be doing right toe empower individuals make this decision more, you know, correctly, it was alternatives, right? That's about empowering people. It's not about just taken, which is can be done through this process is all this information and get in the routine stuff out of their plate, which is completely full. >> There was a stat. I think it was last year at IBM Insight. Exact numbers, but it's something like a physician would have to read 1,500 periodic ALS a week just to keep up with the new data innovations. I mean, that's virtually impossible. That something that you're obviously pointing, pointing Watson that, I mean, But there are mundane examples, right? So you go to the airport now, you don't need a person that the agent to give you. Ah, boarding pass. It's on your phone already. You get there. Okay, so that's that's That's a mundane example we're talking about set significantly more complicated things. And so what's The gate is the gate. Creativity is it is an education, you know, because these are step functions in value creation. >> You know, I think that's ah, what? The gate is a question I haven't really thought too much about. You know, when I approach it, you know the thinking Mohr from you know, not so much. What's the gate? But where? Where can this ad the most value um So maybe maybe I have thought about it. And the gate is value, um, and and its value both in terms of, you know, like the physician example where, you know, physicians, looking at images. And I mean, I don't even know what the error rate is when someone evaluates and memory or something. And I probably don't want Oh, right. So, getting some advice there, the value may not be monetary, but to me, it's a lot more than monetary, right. If I'm a patient on DH, there's a lot of examples like that. And other places, you know, that are in various industries. That I think that's that's the gate >> is why the value you just hit on you because you are a heat seeking value missile inside of your organisation. What? So what skill sets do you have? Where did you come from? That you have this capability? Was your experience, your education, your fortitude, >> While the answer's yes, tell all of them. Um, you know, I'm a scientist by training my backgrounds in statistical genetics. Um, and I've kind of worked through the business. I came up through the RND organization with him on Santo over the last. Almost exactly 10 years now, Andi, I've had lots of opportunities to leverage. Um, you know, Data and analytics have changed how the company operates on. I'm lucky because I'm in a company right now. That is extremely science driven, right? Monsanto is a science based company. And so being in a company like that, you don't face to your question about financial industry. I don't think you face the same barriers and Monsanto about using data and analytics in the same way you may in a financial types that you've got company >> within my experience. 50% of diagnosis being proven incorrect. Okay, so 50% 05 0/2 summation. You go to your physician twice. Once you on average, you get in wrong diagnosis. We don't know which one, by the way. Definitely need some someone. Garrett A cz Individuals as humans, we do need some help. Us cognitive, and it goes across different industries. Right, technologist? So if your server is down, you know you shouldn't worry about it because there is like system, you know, Abbas system enough, right? So think about how you can do that scale, and then, you know start imagined future, which going to be very empowering. >> So I used to get a second opinion, and now the opinion comprises thousands, millions, maybe tens of millions of opinions. Is that right? >> It's a try exactly and scale ofthe data accumulation, which you're going to help us to solve. This problem is enormous. So we need to keep up with that scale, you know, and do it properly exactly for business. Very proposition. >> Let's talk about the role of the CDO and where you see that evolving how it relates to the role of the CIA. We've had this conversation frequently, but is I'm wondering if the narratives changing right? Because it was. It's been fuzzy when we first met a couple years ago that that was still a hot topic. When I first started covering this. This this topic, it was really fuzzy. Has it come in two more clarity lately in terms of the role of the CDO versus the CIA over the CTO, its chief digital officer, we starting to see these roles? Are they more than just sort of buzzwords or grey? You know, areas. >> I think there's some clarity happening already. So, for example, there is much more acceptance for cheap date. Office of Chief Analytics Officer Teo, Chief Digital officer. Right, in addition to CEO. So basically station similar to what was with Serious 20 plus years ago and CEO Row in one sentence from my viewpoint would be How you going using leverage in it. Empower your business. Very proposition with CDO is the same was data how using data leverage and data, your date and your client's data. You, Khun, bring new value to your clients and businesses. That's kind ofthe I would say differential >> last word, you know, And you think you know I'm not a CDO. But if you think about the concept of establishing a role like that, I think I think the name is great because that what it demonstrates is support from leadership, that this is important. And I think even if you don't have the name in the organization like it, like in Monsanto, you know, we still have that executive management level support to the data and analytics, our first class citizens and their important, and we're going to run our business that way. I think that's really what's important is are you able to build the culture that enable you to leverage the maximum capability Data and analytics. That's really what matters. >> All right, We'll leave it there. Seth Gene, thank you very much for coming that you really appreciate your time. Thank you. Alright. Keep it right there, Buddy Stew and I'll be back. This is the IBM Chief Data Officer Summit. We're live from Boston right back.