(electronic music) >> Hi everybody, welcome back to Supercloud 2. I'm Dave Vellante with my co-host John Furrier. We're here at our tricked out Palo Alto studio. We're going live wall to wall all day. We're inserting a number of pre-recorded interviews, folks like Walmart. We just heard from Nir Zuk of Palo Alto Networks, and I'm really pleased to welcome in David Flynn. David Flynn, you may know as one of the people behind Fusion-io, completely changed the way in which people think about storing data, accessing data. David Flynn now the founder and CEO of a company called Hammerspace. David, good to see you, thanks for coming on. >> David: Good to see you too. >> And Dr. Nelu Mihai is the CEO and founder of Cloud of Clouds. He's actually built a Supercloud. We're going to get into that. Nelu, thanks for coming on. >> Thank you, Happy New Year. >> Yeah, Happy New Year. So I'm going to start right off with a little debate that's going on in the community if you guys would bring out this slide. So Bob Muglia early today, he gave a definition of Supercloud. He felt like we had to tighten ours up a little bit. He said a Supercloud is a platform, underscoring platform, that provides programmatically consistent services hosted on heterogeneous cloud providers. Now, Nelu, we have this shared doc, and you've been in there. You responded, you said, well, hold on. Supercloud really needs to be an architecture, or else we're going to have this stove pipe of stove pipes, really. And then you went on with more detail, what's the information model? What's the execution model? How are users going to interact with Supercloud? So I start with you, why architecture? The inference is that a platform, the platform provider's responsible for the architecture? Why does that not work in your view? >> No, the, it's a very interesting question. So whenever I think about platform, what's the connotation, you think about monolithic system? Yeah, I mean, I don't know whether it's true or or not, but there is this connotation of of monolithic. On the other hand, if you look at what's a problem right now with HyperClouds, from the customer perspective, they're very complex. There is a heterogeneous world where actually every single one of this HyperClouds has their own architecture. You need rocket scientists to build a cloud applications. Always there is this contradiction between cost and performance. They fight each other. And I'm quoting here a former friend of mine from Bell Labs who work at AWS who used to say "Cloud is cheap as long as you don't use it too much." (group chuckles) So clearly we need something that kind of plays from the principle point of view the role of an operating system, that seats on top of this heterogeneous HyperCloud, and there's nothing wrong by having these proprietary HyperClouds, think about processors, think about operating system and so on, so forth. But in order to build a system that is simple enough, I think we need to go deeper and understand. >> So the argument, the counterargument to that, David, is you'll never get there. You need a proprietary system to get to market sooner, to solve today's problem. Now I don't know where you stand on this platform versus architecture. I haven't asked you, but. >> I think there are aspects of both for sure. I mean it needs to be an architecture in the sense that it's broad based and open and so forth. But you know, platform, you could say as long as people can instantiate it themselves, on their own infrastructure, as long as it's something that can be deployed as, you know, software defined, you don't want the concept of platform being the monolith, you know, combined hardware and software. So it really depends on what you're focused on when you're saying platform, you know, I'd say as long as they software defined thing, to where it can literally run anywhere. I mean, because I really think what we're talking about here is the original concept of cloud computing. The ability to run anything anywhere, without having to care about the physical infrastructure. And what we have today is not that, the cloud today is a big mainframe in the sky, that just happens to be large enough that once you select which region, generally you have enough resources. But, you know, nowadays you don't even necessarily have enough resources in one region. and then you're kind of stuck. So we haven't really gotten to that utility model of computing. And you're also asked to rewrite your application, you know, to abandon the conveniences of high performance file access. You got to rewrite it to use object storage stuff. We have to get away from that. >> Okay, I want to just drill on that, 'cause I think I like that point about, there's not enough availability, but on the developer cloud, the original AWS premise was targeting developers, 'cause at that time, you have to provision a Sun box get a Cisco DSU/CSU, now you get on the cloud. But I think you're giving up the scale question, 'cause I think right now, scale is huge, enterprise grade versus cloud for developers. >> That's Right. >> Because I mean look at, Amazon, Azure, they got compute, they got storage, they got queuing, and some stuff. If you're doing a startup, you throw your app up there, localhost to cloud, no big deal. It's the scale thing that gets me- >> And you can tell by the fact that, in regions that are under high demand, right, like in London or LA, at least with the clients we work with in the median entertainment space, it costs twice as much for the exact same cloud instances that do the exact same amount of work, as somewhere out in rural Canada. So why is it you have such a cost differential, it has to do with that supply and demand, and the fact that the clouds aren't really the ability to run anything anywhere. Even within the same cloud vendor, you're stuck in a specific region. >> And that was never the original promise, right? I mean it was, we turned it into that. But the original promise was get rid of the heavy lifting of IT. >> Not have to run your own, yeah, exactly. >> And then it became, wow, okay I can run anywhere. And then you know, it's like web 2.0. You know people say why Supercloud, you and I talked about this, why do you need a name for Supercloud? It's like web 2.0. >> It's what Cloud was supposed to be. >> It's what cloud was supposed to be, (group laughing and talking) exactly, right. >> Cloud was supposed to be run anything anywhere, or at least that's what we took it as. But you're right, originally it was just, oh don't have to run your own infrastructure, and you can choose somebody else's infrastructure. >> And you did that >> But you're still bound to that. >> Dave: And People said I want more, right? >> But how do we go from here? >> That's, that's actually, that's a very good point, because indeed when the first HyperClouds were designed, were designed really focus on customers. I think Supercloud is an opportunity to design in the right way. Also having in mind the computer science rigor. And we should take advantage of that, because in fact actually, if cloud would've been designed properly from the beginning, probably wouldn't have needed Supercloud. >> David: You wouldn't have to have been asked to rewrite your application. >> That's correct. (group laughs) >> To use REST interfaces to your storage. >> Revisist history is always a good one. But look, cloud is great. I mean your point is cloud is a good thing. Don't hold it back. >> It is a very good thing. >> Let it continue. >> Let it go as as it is. >> Yeah, let that thing continue to grow. Don't impose restrictions on the cloud. Just refactor what you need to for scale or enterprise grade or availability. >> And you would agree with that, is that true or is it problem you're solving? >> Well yeah, I mean it, what the cloud is doing is absolutely necessary. What the public cloud vendors are doing is absolutely necessary. But what's been missing is how to provide a consistent interface, especially to persistent data. And have it be available across different regions, and across different clouds. 'cause data is a highly localized thing in current architecture. It only exists as rendered by the storage system that you put it in. Whether that's a legacy thing like a NetApp or an Isilon or even a cloud data service. It's localized to a specific region of the cloud in which you put that. We have to delocalize data, and provide a consistent interface to it across all sites. That's high performance, local access, but to global data. >> And so Walmart earlier today described their, what we call Supercloud, they call it the Walmart cloud native platform. And they use this triplet model. They have AWS and Azure, no, oh sorry, no AWS. They have Azure and GCP and then on-prem, where all the VMs live. When you, you know, probe, it turns out that it's only stateless in the cloud. (John laughs) So, the state stuff- >> Well let's just admit it, there is no such thing as stateless, because even the application binaries and libraries are state. >> Well I'm happy that I'm hearing that. >> Yeah, okay. >> Because actually I have a lot of debate (indistinct). If you think about no software running on a (indistinct) machine is stateless. >> David: Exactly. >> This is something that was- >> David: And that's data that needs to be distributed and provided consistently >> (indistinct) >> Across all the clouds, >> And actually, it's a nonsense, but- >> Dave: So it's an illusion, okay. (group talks over each other) >> (indistinct) you guys talk about stateless. >> Well, see, people make the confusion between state and persistent state, okay. Persistent state it's a different thing. State is a different thing. So, but anyway, I want to go back to your point, because there's a lot of debate here. People are talking about data, some people are talking about logic, some people are talking about networking. In my opinion is this triplet, which is data logic and connectivity, that has equal importance. And actually depending on the application, can have the center of gravity moving towards data, moving towards what I call execution units or workloads. And connectivity is actually the most important part of it. >> David: (indistinct). >> Some people are saying move the logic towards the data, some other people, and you are saying actually, that no, you have to build a distributed data mesh. What I'm saying is actually, you have to consider all these three variables, all these vector in order to decide, based on application, what's the most important. Because sometimes- >> John: So the application chooses >> That's correct. >> Well it it's what operating systems were in the past, was principally the thing that runs and manages the jobs, the job scheduler, and the thing that provides your persistent data (indistinct). >> Okay. So we finally got operating system into the equation, thank you. (group laughs) >> Nelu: I actually have a PhD in operating system. >> Cause what we're talking about is an operating system. So forget platform or architecture, it's an operating environment. Let's use it as a general term. >> All right. I think that's about it for me. >> All right, let's take (indistinct). Nelu, I want ask you quick, 'cause I want to give a, 'cause I believe it's an operating system. I think it's going to be a reset, refactored. You wrote to me, "The model of Supercloud has to be open theoretical, has to satisfy the rigors of computer science, and customer requirements." So unique to today, if the OS is going to be refactored, it's not going to be, may or may not be Red Hat or somebody else. This new OS, obviously requirements are for customers too but is what's the computer science that is needed? Where are we, what's the missing? Where's the science in this shift? It's not your standard OS it's not like an- (group talks over each other) >> I would beg to differ. >> (indistinct) truly an operation environment. But the, if you think about, and make analogies, what you need when you design a distributed system, well you need an information model, yeah. You need to figure out how the data is located and distributed. You need a model for the execution units, and you need a way to describe the interactions between all these objects. And it is my opinion that we need to go deeper and formalize these operations in order to make a step forward. And when we design Supercloud, and design something that is better than the current HyperClouds. And actually that is when we design something better, you make a system more efficient and it's going to be better from the cost point of view, from the performance point of view. But we need to add some math into all this customer focus centering and I really admire AWS and their executive team focusing on the customer. But now it's time to go back and see, if we apply some computer science, if you try to formalize to build a theoretical model of cloud, can we build a system that is better than existing ones? >> So David, how do you- >> this is what I'm saying. >> That's a good question >> How do You see the operating system of a, or operating environment of a decentralized cloud? >> Well I think it's layered. I mean we have operating systems that can run systems quite efficiently. Linux has sort of one in the data center, but we're talking about a layer on top of that. And I think we're seeing the emergence of that. For example, on the job scheduling side of things, Kubernetes makes a really good example. You know, you break the workload into the most granular units of compute, the containerized microservice, and then you use a declarative model to state what is needed and give the system the degrees of freedom that it can choose how to instantiate it. Because the thing about these distributed systems, is that the complexity explodes, right? Running a piece of hardware, running a single server is not a problem, even with all the many cores and everything like that. It's when you start adding in the networking, and making it so that you have many of them. And then when it's going across whole different data centers, you know, so, at that level the way you solve this is not manually (group laughs) and not procedurally. You have to change the language so it's intent based, it's a declarative model, and what you're stating is what is intended, and you're leaving it to more advanced techniques, like machine learning to decide how to instantiate that service across the cluster, which is what Kubernetes does, or how to instantiate the data across the diverse storage infrastructure. And that's what we do. >> So that's a very good point because actually what has been neglected with HyperClouds is really optimization and automation. But in order to be able to do both of these things, you need, I'm going back and I'm stubborn, you need to have a mathematical model, a theoretical model because what does automation mean? It means that we have to put machines to do the work instead of us, and machines work with what? Formula, with algorithms, they don't work with services. So I think Supercloud is an opportunity to underscore the importance of optimization and automation- >> Totally agree. >> In HyperCloud, and actually by doing that, we can also have an interesting connotation. We are also contributing to save our planet, because if you think right now. we're consuming a lot of energy on this HyperClouds and also all this AI applications, and I think we can do better and build the same kind of application using less energy. >> So yeah, great point, love that call out, the- you know, Dave and I always joke about the old, 'cause we're old, we talk about, you know, (Nelu Laughs) old history, OS/2 versus DOS, okay, OS's, OS/2 is silly better, first threaded OS, DOS never went away. So how does legacy play into this conversation? Because I buy the theoretical, I love the conversation. Okay, I think it's an OS, totally see it that way myself. What's the blocker? Is there a legacy that drags it back? Is the anchor dragging from legacy? Is there a DOS OS/2 moment? Is there an opportunity to flip the script? This is- >> I think that's a perfect example of why we need to support the existing interfaces, Operating Systems, real operating systems like Linux, understands how to present data, it's called a file system, block devices, things that that plumb in there. And by, you know, going to a REST interface and S3 and telling people they have to rewrite their applications, you can't even consume your application binaries that way, the OS doesn't know how to pull that sort of thing. So we, to get to cloud, to get to the ability to host massive numbers of tenants within a centralized infrastructure, you know, we abandoned these lower level interfaces to the OS and we have to go back to that. It's the reason why DOS ultimately won, is it had the momentum of the install base. We're seeing the same thing here. Whatever it is, it has to be a real file system and not a come down file system >> Nelu, what's your reaction, 'cause you're in the theoretical bandwagon. Let's get your reaction. >> No, I think it's a good, I'll give, you made a good analogy between OS/2 and DOS, but I'll go even farther saying, if you think about the evolution operating system didn't stop the evolution of underlying microprocessors, hardware, and so on and so forth. On the contrary, it was a catalyst for that. So because everybody could develop their own hardware, without worrying that the applications on top of operating system are going to modify. The same thing is going to happen with Supercloud. You're going to have the AWSs, you're going to have the Azure and the the GCP continue to evolve in their own way proprietary. But if we create on top of it the right interface >> The open, this is why open is important. >> That's correct, because actually you're going to see sometime ago, everybody was saying, remember venture capitals were saying, "AWS killed the world, nobody's going to come." Now you see what Oracle is doing, and then you're going to see other players. >> It's funny, Amazon's trying to be more like Microsoft. Microsoft's trying to be more like Amazon and Google- Oracle's just trying to say they have cloud. >> That's, that's correct, (group laughs) so, my point is, you're going to see a multiplication of this HyperClouds and cloud technology. So, the system has to be open in order to accommodate what it is and what is going to come. Okay, so it's open. >> So the the legacy- so legacy is an opportunity, not a blocker in your mind. And you see- >> That's correct, I think we should allow them to continue to to to be their own actually. But maybe you're going to find a way to connect with it. >> Amazon's the processor, and they're on the 80 80 80 right? >> That's correct. >> You're saying you love people trying to get put to work. >> That's a good analogy. >> But, performance levels you say good luck, right? >> Well yeah, we have to be able to take traditional applications, high performance applications, those that consume file system and persistent data. Those things have to be able to run anywhere. You need to be able to put, put them onto, you know, more elastic infrastructure. So, we have to actually get cloud to where it lives up to its billing. >> And that's what you're solving for, with Hammerspace, >> That's what we're solving for, making it possible- >> Give me the bumper sticker. >> Solving for how do you have massive quantities of unstructured file data? At the end of the day, all data ultimately is unstructured data. Have that persistent data available, across any data center, within any cloud, within any region on-prem, at the edge. And have not just the same APIs, but have the exact same data sets, and not sucked over a straw remote, but at extreme high performance, local access. So how do you have local access to globally shared distributed data? And that's what we're doing. We are orchestrating data globally across all different forms of storage infrastructure, so you have a consistent access at the highest performance levels, at the lowest level innate built into the OS, how to consume it as (indistinct) >> So are you going into the- all the clouds and natively building in there, or are you off cloud? >> So This is software that can run on cloud instances and provide high performance file within the cloud. It can take file data that's on-prem. Again, it's software, it can run in virtual or on physical servers. And it abstracts the data from the existing storage infrastructure, and makes the data visible and consumable and orchestratable across any of it. >> And what's the elevator pitch for Cloud of Cloud, give that too. >> Well, Cloud of Clouds creates a theoretical model of cloud, and it describes every single object in the cloud. Where is data, execution units, and connectivity, with one single class of very simple object. And I can, I can give you (indistinct) >> And the problem that solves is what? >> The problem that solves is, it creates this mathematical model that is necessary in order to do other interesting things, such as optimization, using sata engines, using automation, applying ML for instance. Or deep learning to automate all this clouds, if you think about in the industrial field, we know how to manage and automate huge plants. Why wouldn't it do the same thing in cloud? It's the same thing you- >> That's what you mean by theoretical model. >> Nelu: That's correct. >> Lay out the architecture, almost the bones of skeleton or something, or, and then- >> That's correct, and then on top of it you can actually build a platform, You can create your services, >> when you say math, you mean you put numbers to it, you kind of index it. >> You quantify this thing and you apply mathematical- It's really about, I can disclose this thing. It's really about describing the cloud as a knowledge graph for every single object in the graph for node, an edge is a vector. And then once you have this model, then you can apply the field theory, and linear algebra to do operation with these vectors. And it's, this creates a very interesting opportunity to let the math do this thing for us. >> Okay, so what happens with hyperscale, or it's like AWS in your model. >> So in, in my model actually, >> Are they happy with this, or they >> I'm very happy with that. >> Will they be happy with you? >> We create an interface to every single HyperCloud. We actually, we don't need to interface with the thousands of APIs, but you know, if we have the 80 20 rule, and we map these APIs into this graph, and then every single operation that is done in this graph is done from the beginning, in an optimized manner and also automation ready. >> That's going to be great. David, I want us to go back to you before we close real quick. You've had a lot of experience, multiple ventures on the front end. You talked to a lot of customers who've been innovating. Where are the classic (indistinct)? Cause you, you used to sell and invent product around the old school enterprises with storage, you know that that trajectory storage is still critical to store the data. Where's the classic enterprise grade mindset right now? Those customers that were buying, that are buying storage, they're in the cloud, they're lifting and shifting. They not yet put the throttle on DevOps. When they look at this Supercloud thing, Are they like a deer in the headlights, or are they like getting it? What's the, what's the classic enterprise look like? >> You're seeing people at different stages of adoption. Some folks are trying to get to the cloud, some folks are trying to repatriate from the cloud, because they've realized it's better to own than to rent when you use a lot of it. And so people are at very different stages of the journey. But the one thing that's constant is that there's always change. And the change here has to do with being able to change the location where you're doing your computing. So being able to support traditional workloads in the cloud, being able to run things at the edge, and being able to rationalize where the data ought to exist, and with a declarative model, intent-based, business objective-based, be able to swipe a mouse and have the data get redistributed and positioned across different vendors, across different clouds, that, we're seeing that as really top of mind right now, because everybody's at some point on this journey, trying to go somewhere, and it involves taking their data with them. (John laughs) >> Guys, great conversation. Thanks so much for coming on, for John, Dave. Stay tuned, we got a great analyst power panel coming right up. More from Palo Alto, Supercloud 2. Be right back. (bouncy music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Recent conversations with IT decision makers show a stark contrast between exiting 2023 versus the mindset when we were leaving 2022. CIOs are generally funding new initiatives by pushing off or cutting lower priority items, while security efforts are still being funded. Those that enable business initiatives that generate revenue or taking priority over cleaning up legacy technical debt. The bottom line is, for the moment, at least, the mindset is not cut everything, rather, it's put a pause on cleaning up legacy hairballs and fund monetization. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we tap recent discussions from two primary sources, year-end ETR roundtables with IT decision makers, and CUBE conversations with data, cloud, and IT architecture practitioners. The sources of data for this breaking analysis come from the following areas. Eric Bradley's recent ETR year end panel featured a financial services DevOps and SRE manager, a CSO in a large hospitality firm, a director of IT for a big tech company, the head of IT infrastructure for a financial firm, and a CTO for global travel enterprise, and for our upcoming Supercloud2 conference on January 17th, which you can register free by the way, at supercloud.world, we've had CUBE conversations with data and cloud practitioners, specifically, heads of data in retail and financial services, a cloud architect and a biotech firm, the director of cloud and data at a large media firm, and the director of engineering at a financial services company. Now we've curated commentary from these sources and now we share them with you today as anecdotal evidence supporting what we've been reporting on in the marketplace for these last couple of quarters. On this program, we've likened the economy to the slingshot effect when you're driving, when you're cruising along at full speed on the highway, and suddenly you see red brake lights up ahead, so, you tap your own brakes and then you speed up again, and traffic is moving along at full speed, so, you think nothing of it, and then, all of a sudden, the same thing happens. You slow down to a crawl and you start wondering, "What the heck is happening?" And you become a lot more cautious about the rate of acceleration when you start moving again. Well, that's the trend in IT spend right now. Back in June, we reported that despite the macro headwinds, CIOs were still expecting 6% to 7% spending growth for 2022. Now that was down from 8%, which we reported at the beginning of 2022. That was before Ukraine, and Fed tightening, but given those two factors, you know that that seemed pretty robust, but throughout the fall, we began reporting consistently declining expectations where CIOs are now saying Q4 will come in at around 3% growth relative to last year, and they're expecting, or should we say hoping that it pops back up in 2023 to 4% to 5%. The recent ETR panelists, when they heard this, are saying based on their businesses and discussions with their peers, they could see low single digit growth for 2023, so, 1%, 2%, 3%, so, this sort of slingshotting, or sometimes we call it a seesaw economy, has caught everyone off guard. Amazon is a good example of this, and there are others, but Amazon entered the pandemic with around 800,000 employees. It doubled that workforce during the pandemic. Now, right before Thanksgiving in 2022, Amazon announced that it was laying off 10,000 employees, and, Jassy, the CEO of Amazon, just last week announced that number is now going to grow to 18,000. Now look, this is a rounding error at Amazon from a headcount standpoint and their headcount remains far above 2019 levels. Its stock price, however, does not and it's back down to 2019 levels. The point is that visibility is very poor right now and it's reflected in that uncertainty. We've seen a lot of layoffs, obviously, the stock market's choppy, et cetera. Now importantly, not everything is on hold, and this downturn is different from previous tech pullbacks in that the speed at which new initiatives can be rolled out is much greater thanks to the cloud, and if you can show a fast return, you're going to get funding. Organizations are pausing on the cleanup of technical debt, unless it's driving fast business value. They're holding off on modernization projects. Those business enablement initiatives are still getting funded. CIOs are finding the money by consolidating redundant vendors, and they're stealing from other pockets of budget, so, it's not surprising that cybersecurity remains the number one technology priority in 2023. We've been reporting that for quite some time now. It's specifically cloud, cloud native security container and API security. That's where all the action is, because there's still holes to plug from that forced march to digital that occurred during COVID. Cloud migration, kind of showing here on number two on this chart, still a high priority, while optimizing cloud spend is definitely a strategy that organizations are taking to cut costs. It's behind consolidating redundant vendors by a long shot. There's very little evidence that cloud repatriation, i.e., moving workloads back on prem is a major cost cutting trend. The data just doesn't show it. What is a trend is getting more real time with analytics, so, companies can do faster and more accurate customer targeting, and they're really prioritizing that, obviously, in this down economy. Real time, we sometimes lose it, what's real time? Real time, we sometimes define as before you lose the customer. Now in the hiring front, customers tell us they're still having a hard time finding qualified site reliability engineers, SREs, Kubernetes expertise, and deep analytics pros. These job markets remain very tight. Let's stay with security for just a moment. We said many times that, prior to COVID, zero trust was this undefined buzzword, and the joke, of course, is, if you ask three people, "What is zero trust?" You're going to get three different answers, but the truth is that virtually every security company that was resisting taking a position on zero trust in an attempt to avoid... They didn't want to get caught up in the buzzword vortex, but they're now really being forced to go there by CISOs, so, there are some good quotes here on cyber that we want to share that came out of the recent conversations that we cited up front. The first one, "Zero trust is the highest ROI, because it enables business transformation." In other words, if I can have good security, I can move fast, it's not a blocker anymore. Second quote here, "ZTA," zero trust architecture, "Is more than securing the perimeter. It encompasses strong authentication and multiple identity layers. It requires taking a software approach to security instead of a hardware focus." The next one, "I'd love to have a security data lake that I could apply to asset management, vulnerability management, incident management, incident response, and all aspects for my security team. I see huge promise in that space," and the last one, I see NLP, natural language processing, as the foundation for email security, so, instead of searching for IP addresses, you can now read emails at light speed and identify phishing threats, so, look at, this is a small snapshot of the mindset around security, but I'll add, when you talk to the likes of CrowdStrike, and Zscaler, and Okta, and Palo Alto Networks, and many other security firms, they're listening to these narratives around zero trust. I'm confident they're working hard on skating to this puck, if you will. A good example is this idea of a security data lake and using analytics to improve security. We're hearing a lot about that. We're hearing architectures, there's acquisitions in that regard, and so, that's becoming real, and there are many other examples, because data is at the heart of digital business. This is the next area that we want to talk about. It's obvious that data, as a topic, gets a lot of mind share amongst practitioners, but getting data right is still really hard. It's a challenge for most organizations to get ROI and expected return out of data. Most companies still put data at the periphery of their businesses. It's not at the core. Data lives within silos or different business units, different clouds, it's on-prem, and increasingly it's at the edge, and it seems like the problem is getting worse before it gets better, so, here are some instructive comments from our recent conversations. The first one, "We're publishing events onto Kafka, having those events be processed by Dataproc." Dataproc is a Google managed service to run Hadoop, and Spark, and Flank, and Presto, and a bunch of other open source tools. We're putting them into the appropriate storage models within Google, and then normalize the data into BigQuery, and only then can you take advantage of tools like ThoughtSpot, so, here's a company like ThoughtSpot, and they're all about simplifying data, democratizing data, but to get there, you have to go through some pretty complex processes, so, this is a good example. All right, another comment. "In order to use Google's AI tools, we have to put the data into BigQuery. They haven't integrated in the way AWS and Snowflake have with SageMaker. Moving the data is too expensive, time consuming, and risky," so, I'll just say this, sharing data is a killer super cloud use case, and firms like Snowflake are on top of it, but it's still not pretty across clouds, and Google's posture seems to be, "We're going to let our database product competitiveness drive the strategy first, and the ecosystem is going to take a backseat." Now, in a way, I get it, owning the database is critical, and Google doesn't want to capitulate on that front. Look, BigQuery is really good and competitive, but you can't help but roll your eyes when a CEO stands up, and look, I'm not calling out Thomas Kurian, every CEO does this, and talks about how important their customers are, and they'll do whatever is right by the customer, so, look, I'm telling you, I'm rolling my eyes on that. Now let me also comment, AWS has figured this out. They're killing it in database. If you take Redshift for example, it's still growing, as is Aurora, really fast growing services and other data stores, but AWS realizes it can make more money in the long-term partnering with the Snowflakes and Databricks of the world, and other ecosystem vendors versus sub optimizing their relationships with partners and customers in order to sell more of their own homegrown tools. I get it. It's hard not to feature your own product. IBM chose OS/2 over Windows, and tried for years to popularize it. It failed. Lotus, go back way back to Lotus 1, 2, and 3, they refused to run on Windows when it first came out. They were running on DEC VAX. Many of you young people in the United States have never even heard of DEC VAX. IBM wanted to run every everything only in its cloud, the same with Oracle, originally. VMware, as you might recall, tried to build its own cloud, but, eventually, when the market speaks and reveals what seems to be obvious to analysts, years before, the vendors come around, they face reality, and they stop wasting money, fighting a losing battle. "The trend is your friend," as the saying goes. All right, last pull quote on data, "The hardest part is transformations, moving traditional Informatica, Teradata, or Oracle infrastructure to something more modern and real time, and that's why people still run apps in COBOL. In IT, we rarely get rid of stuff, rather we add on another coat of paint until the wood rots out or the roof is going to cave in. All right, the last key finding we want to highlight is going to bring us back to the cloud repatriation myth. Followers of this program know it's a real sore spot with us. We've heard the stories about repatriation, we've read the thoughtful articles from VCs on the subject, we've been whispered to by vendors that you should investigate this trend. It's really happening, but the data simply doesn't support it. Here's the question that was posed to these practitioners. If you had unlimited budget and the economy miraculously flipped, what initiatives would you tackle first? Where would you really lean into? The first answer, "I'd rip out legacy on-prem infrastructure and move to the cloud even faster," so, the thing here is, look, maybe renting infrastructure is more expensive than owning, maybe, but if I can optimize my rental with better utilization, turn off compute, use things like serverless, get on a steeper and higher performance over time, and lower cost Silicon curve with things like Graviton, tap best of breed tools in AI, and other areas that make my business more competitive. Move faster, fail faster, experiment more quickly, and cheaply, what's that worth? Even the most hard-o CFOs understand the business benefits far outweigh the possible added cost per gigabyte, and, again, I stress "possible." Okay, other interesting comments from practitioners. "I'd hire 50 more data engineers and accelerate our real-time data capabilities to better target customers." Real-time is becoming a thing. AI is being injected into data and apps to make faster decisions, perhaps, with less or even no human involvement. That's on the rise. Next quote, "I'd like to focus on resolving the concerns around cloud data compliance," so, again, despite the risks of data being spread out in different clouds, organizations realize cloud is a given, and they want to find ways to make it work better, not move away from it. The same thing in the next one, "I would automate the data analytics pipeline and focus on a safer way to share data across the states without moving it," and, finally, "The way I'm addressing complexity is to standardize on a single cloud." MonoCloud is actually a thing. We're hearing this more and more. Yes, my company has multiple clouds, but in my group, we've standardized on a single cloud to simplify things, and this is a somewhat dangerous trend, because it's creating even more silos and it's an opportunity that needs to be addressed, and that's why we've been talking so much about supercloud is a cross-cloud, unifying, architectural framework, or, perhaps, it's a platform. In fact, that's a question that we will be exploring later this month at Supercloud2 live from our Palo Alto Studios. Is supercloud an architecture or is it a platform? And in this program, we're featuring technologists, analysts, practitioners to explore the intersection between data and cloud and the future of cloud computing, so, you don't want to miss this opportunity. Go to supercloud.world. You can register for free and participate in the event directly. All right, thanks for listening. That's a wrap. I'd like to thank Alex Myerson, who's on production and manages our podcast, Ken Schiffman as well, Kristen Martin and Cheryl Knight, they helped get the word out on social media, and in our newsletters, and Rob Hof is our editor-in-chief over at siliconangle.com. He does some great editing. Thank you, all. Remember, all these episodes are available as podcasts wherever you listen. All you've got to do is search "breaking analysis podcasts." I publish each week on wikibon.com and siliconangle.com where you can email me directly at david.vellante@siliconangle.com or DM me, @Dante, or comment on our LinkedIn posts. By all means, check out etr.ai. They get the best survey data in the enterprise tech business. We'll be doing our annual predictions post in a few weeks, once the data comes out from the January survey. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, everybody, and we'll see you next time on "Breaking Analysis." (upbeat music)

>> From the CUBE studios in Palo Alto in Boston, bringing you data-driven insights from the CUBE in ETR. This is breaking analysis with Dave Vellante. >> Earlier these week, the U S department of justice, along with attorneys general from 11 States filed a long expected antitrust lawsuit, accusing Google of being a monopoly gatekeeper for the internet. The suit draws on section two of the Sherman antitrust act, which makes it illegal to monopolize trade or commerce. Of course, Google is going to fight the lawsuit, but in our view, the company has to make bigger moves to diversify its business and the answer we think lies in the cloud and at the edge. Hello everyone. This is Dave Vellante and welcome to this week's Wiki Bond Cube insights powered by ETR. In this Breaking Analysis, we want to do two things. First we're going to review a little bit of history, according to Dave Vollante of the monopolistic power in the computer industry. And then next, we're going to look into the latest ETR data. And we're going to make the case that Google's response to the DOJ suit should be to double or triple its focus on cloud and edge computing, which we think is a multi-trillion dollar opportunity. So let's start by looking at the history of monopolies in technology. We start with IBM. In 1969 the U S government filed an antitrust lawsuit against Big Blue. At the height of its power. IBM generated about 50% of the revenue and two thirds of the profits for the entire computer industry, think about that. IBM has monopoly on a relative basis, far exceeded that of the virtual Wintel monopoly that defined the 1990s. IBM had 90% of the mainframe market and controlled the protocols to a highly vertically integrated mainframe stack, comprising semiconductors, operating systems, tools, and compatible peripherals like terminal storage and printers. Now the government's lawsuit dragged on for 13 years before it was withdrawn in 1982, IBM at one point had 200 lawyers on the case and it really took a toll on IBM and to placate the government during this time and someone after IBM made concessions such as allowing mainframe plug compatible competitors to access its code, limiting the bundling of application software in fear of more government pressure. Now the biggest mistake IBM made when it came out of antitrust was holding on to its mainframe past. And we saw this in the way it tried to recover from the mistake of handing its monopoly over to Microsoft and Intel. The virtual monopoly. What it did was you may not remember this, but it had OS/2 and Windows and it said to Microsoft, we'll keep OS/2 you take Windows. And the mistake IBM was making with sticking to the PC could be vertically integrated, like the main frame. Now let's fast forward to Microsoft. Microsoft monopoly power was earned in the 1980s and carried into the 1990s. And in 1998 the DOJ filed the lawsuit against Microsoft alleging that the company was illegally thwarting competition, which I argued at the time was the case. Now, ironically, this is the same year that Google was started in a garage. And I'll come back to that in a minute. Now, in the early days of the PC, Microsoft they were not a dominant player in desktop software, you had Lotus 1-2-3, WordPerfect. You had this company called Harvard Presentation Graphics. These were discreet products that competed very effectively in the market. Now in 1987, Microsoft paid $14 million for PowerPoint. And then in 1990 launched Office, which bundled Spreadsheets, Word Processing, and presentations into a single suite. And it was priced far more attractively than the some of the alternative point products. Now in 1995, Microsoft launched Internet Explorer, and began bundling its browser into windows for free. Windows had a 90% market share. Netscape was the browser leader and a high flying tech company at the time. And the company's management who pooed Microsoft bundling of IE saying, they really weren't concerned because they were moving up the stack into business software, now they later changed that position after realizing the damage that Microsoft bundling would do to its business, but it was too late. So in similar moves of ineptness, Lotus refuse to support Windows at its launch. And instead it wrote software to support the (indistinct). A mini computer that you probably have never even heard of. Novell was a leader in networking software at the time. Anyone remember NetWare. So they responded to Microsoft's move to bundle network services into its operating systems by going on a disastrous buying spree they acquired WordPerfect, Quattro Pro, which was a Spreadsheet and a Unix OS to try to compete with Microsoft, but Microsoft turned the volume and kill them. Now the difference between Microsoft and IBM is that Microsoft didn't build PC hardware rather it partnered with Intel to create a virtual monopoly and the similarities between IBM and Microsoft, however, were that it fought the DOJ hard, Okay, of course. But it made similar mistakes to IBM by hugging on to its PC software legacy. Until the company finally pivoted to the cloud under the leadership of Satya Nadella, that brings us to Google. Google has a 90% share of the internet search market. There's that magic number again. Now IBM couldn't argue that consumers weren't hurt by its tactics. Cause they were IBM was gouging mainframe customers because it could on pricing. Microsoft on the other hand could argue that consumers were actually benefiting from lower prices. Google attorneys are doing what often happens in these cases. First they're arguing that the government's case is deeply flawed. Second, they're saying the government's actions will cause higher prices because they'll have to raise prices on mobile software and hardware, Hmm. Sounds like a little bit of a threat. And of course, it's making the case that many of its services are free. Now what's different from Microsoft is Microsoft was bundling IE, that was a product which was largely considered to be crap, when it first came out, it was inferior. But because of the convenience, most users didn't bother switching. Google on the other hand has a far superior search engine and earned its rightful place at the top by having a far better product than Yahoo or Excite or Infoseek or even Alta Vista, they all wanted to build portals versus having a clean user experience with some non-intrusive of ads on the side. Hmm boy, is that part changed, regardless? What's similar in this case with, as in the case with Microsoft is the DOJ is arguing that Google and Apple are teaming up with each other to dominate the market and create a monopoly. Estimates are that Google pays Apple between eight and $11 billion annually to have its search engine embedded like a tick into Safari and Siri. That's about one third of Google's profits go into Apple. And it's obviously worth it because according to the government's lawsuit, Apple originated search accounts for 50% of Google search volume, that's incredible. Now, does the government have a case here? I don't know. I'm not qualified to give a firm opinion on this and I haven't done enough research yet, but I will say this, even in the case of IBM where the DOJ eventually dropped the lawsuit, if the U S government wants to get you, they usually take more than a pound of flesh, but the DOJ did not suggest any remedies. And the Sherman act is open to wide interpretation so we'll see. What I am suggesting is that Google should not hang too tightly on to it's search and advertising past. Yes, Google gives us amazing free services, but it has every incentive to appropriate our data. And there are innovators out there right now, trying to develop answers to that problem, where the use of blockchain and other technologies can give power back to us users. So if I'm arguing that Google shouldn't like the other great tech monopolies, hang its hat too tightly on the past, what should Google do? Well, the answer is obvious, isn't it? It's cloud and edge computing. Now let me first say that Google understandably promotes G Suite quite heavily as part of its cloud computing story, I get that. But it's time to move on and aggressively push into the areas that matters in cloud core infrastructure, database, machine intelligence containers and of course the edge. Not to say that Google isn't doing this, but there are areas of greatest growth potential that they should focus on. And the ETR data shows it. But let me start with one of our favorite graphics, which shows the breakdown of survey respondents used to derive net score. Net score remembers ETR's quarterly measurement of spending velocity. And here we show the breakdown for Google cloud. The lime green is new adoptions. The forest green is the percentage of customers increasing spending more than 5%. The gray is flat and the pinkish is decreased by 6% or more. And the bright red is we're replacing or swapping out the platform. You subtract the reds from the greens and you get a net score at 43%, which is not off the charts, but it's pretty good. And compares quite favorably to most companies, but not so favorite with AWS, which is at 51% and Microsoft which is at 49%, both AWS and Microsoft red scores are in the single digits. Whereas Google's is at 10%, look all three are down since January, thanks to COVID, but AWS and Microsoft are much larger than Google. And we'd like to see stronger across the board scores from Google. But there's good news in the numbers for Google. Take a look at this chart. It's a breakdown of Google's net scores over three survey snapshots. Now we skip January in this view and we do that to provide a year of a year context for October. But look at the all important database category. We've been watching this very closely, particularly with the snowflake momentum because big query generally is considered the other true cloud native database. And we have a lot of respect for what Google is doing in this area. Look at the areas of strength highlighted in the green. You've got machine intelligence where Google is a leader AI you've got containers. Kubernetes was an open source gift to the industry, and linchpin of Google's cloud and multi-cloud strategy. Google cloud is strong overall. We were surprised to see some deceleration in Google cloud functions at 51% net scores to be on honest with you, because if you look at AWS Lambda and Microsoft Azure functions, they're showing net scores in the mid to high 60s. But we're still elevated for Google. Now. I'm not that worried about steep declines, and Apogee and Looker because after an acquisitions things kind of get spread out around the ETR taxonomy so don't be too concerned about that. But as I said earlier, G Suite may just not that compelling relative to the opportunity in other areas. Now I won't show the data, but Google cloud is showing good momentum across almost all interest industries and sectors with the exception of consulting and small business, which is understandable, but notable deceleration in healthcare, which is a bit of a concern. Now I want to share some customer anecdotes about Google. These comments come from an ETR Venn round table. The first comment comes from an architect who says that "it's an advantage that Google is "not entrenched in the enterprise." Hmm. I'm not sure I agree with that, but anyway, I do take stock in what this person is saying about Microsoft trying to lure people away from AWS. And this person is right that Google essentially is exposed its internal cloud to the world and has ways to go, which is why I don't agree with the first statement. I think Google still has to figure out the enterprise. Now the second comment here underscores a point that we made earlier about big query customers really like the out of the box machine learning capabilities, it's quite compelling. Okay. Let's look at some of the data that we shared previously, we'll update this chart once the company's all report earnings, but here's our most recent take on the big three cloud vendors market performance. The key point here is that our data and the ETR data reflects Google's commentary in its earning statements. And the GCP is growing much faster than its overall cloud business, which includes things that are not apples to apples with AWS the same thing is true with Azure. Remember AWS is the only company that provides clear data on its cloud business. Whereas the others will make comments, but not share the data explicitly. So these are estimates based on those comments. And we also use, as I say, the ETR survey data and our own intelligence. Now, as one of the practitioners said, Google has a long ways to go as buddy an eighth of the size of AWS and about a fifth of the size of Azure. And although it's growing faster at this size, we feel that its growth should be even higher, but COVID is clear a factor here so we have to take that into consideration. Now I want to close by coming back to antitrust. Google spends a lot on R&D, these are quick estimates but let me give you some context. Google shells out about $26 billion annually on research and development. That's about 16% of revenue. Apple spends less about 16 billion, which is about 6% of revenue, Amazon 23 billion about 8% of the top line, Microsoft 19 billion or 13% of revenue and Facebook 14 billion or 20% of revenue, wow. So Google for sure spends on innovation. And I'm not even including CapEx in any of these numbers and the hype guys as you know, spend tons on CapEx building data centers. So I'm not saying Google cheaping out, they're not. And I got plenty of cash in there balance sheet. They got to run 120 billion. So I can't criticize they're roughly $9 billion in stock buybacks the way I often point fingers at what I consider IBM's overly wall street friendly use of cash, but I will say this and it was Jeff Hammerbacher, who I spoke with on the Cube in the early part of last decade at a dupe world, who said "the best minds of my generation are spending there time, "trying to figure out how to get people to click on ads." And frankly, that's where much of Google's R&D budget goes. And again, I'm not saying Google doesn't spend on cloud computing. It does, but I'm going to make a prediction. The post cookie apocalypse is coming soon, it may be here. iOS 14 makes you opt in to find out everything about you. This is why it's such a threat to Google. The days when Google was able to be the keeper of all of our data and to house it and to do whatever it likes with that data that ended with GDPR. And that was just the beginning of the end. This decade is going to see massive changes in public policy that will directly affect Google and other consumer facing technology companies. So my premise is that Google needs to step up its game and enterprise cloud and the edge much more than it's doing today. And I like what Thomas Kurian is doing, but Google's undervalued relative to some of the other big tech names. And I think it should tell wall street that our future is in enterprise cloud and edge computing. And we're going to take a hit to our profitability and go big in those areas. And I would suggest a few things, first ramp up R&D spending and acquisitions even more. Go on a mission to create cloud native fabric across all on-prem and the edge multicloud. Yes, I know this is your strategy, but step it up even more forget satisfying investors. You're getting dinged in the market anyway. So now's the time the moon wall street and attack the opportunity unless you don't see it, but it's staring you right in the face. Second, get way more cozy with the enterprise players that are scared to death of the cloud generally. And they're afraid of AWS in particular, spend the cash and go way, way deeper with the big tech players who have built the past IBM, Dell, HPE, Cisco, Oracle, SAP, and all the others. Those companies that have the go to market shops to help you win the day in enterprise cloud. Now, I know you partner with these companies already, but partner deeper identify game-changing innovations that you can co-create with these companies and fund it with your cash hoard. I'm essentially saying, do what you do with Apple. And instead of sucking up all our data and getting us to click on ads, solve really deep problems in the enterprise and the edge. It's all about actually building an on-prem to cloud across cloud, to the edge fabric and really making that a unified experience. And there's a data angle too, which I'll talk about now, the data collection methods that you've used on consumers, it's incredibly powerful if applied responsibly and correctly for IOT and edge computing. And I don't mean to trivialize the complexity at the edge. There really isn't one edge it's Telcos and factories and banks and cars. And I know you're in all these places Google because of Android, but there's a new wave of data coming from machines and cars. And it's going to dwarf people's clicks and believe me, Tesla wants to own its own data and Google needs to put forth a strategy that's a win-win. And so far you haven't done that because your head is an advertising. Get your heads out of your ads and cut partners in on the deal. Next, double down on your open source commitment. Kubernetes showed the power that you have in the industry. Ecosystems are going to be the linchpin of innovation over the next decade and transcend products and platforms use your money, your technology, and your position in the marketplace to create the next generation of technology leveraging the power of the ecosystem. Now I know Google is going to say, we agree, this is exactly what we're doing, but I'm skeptical. Now I think you see either the cloud is a tiny little piece of your business. You have to do with Satya Nadella did and completely pivot to the new opportunity, make cloud and the edge your mission bite the bullet with wall street and go dominate a multi-trillion dollar industry. Okay, well there you have it. Remember, all these episodes are available as podcasts, so please subscribe wherever you listen. I publish weekly on Wikibond.com and Siliconangle.com and I post on LinkedIn each week as well. So please comment or DM me @DVollante, or you can email me @David.Vollante @Siliconangle.com. And don't forget to check out etr.plus that's where all the survey action is. This is Dave Vollante for the Cube Insights powered by ETR. Thanks for watching everybody be well. And we'll see you next. (upbeat instrumental)

[Music] [Music] [Music] [Music] ladies and gentlemen please welcome Red Hat senior vice president of engineering Matt Hicks [Music] welcome back I hope you're enjoying your first day of summit you know for us it is a lot of work throughout the year to get ready to get here but I love the energy walking into someone on that first opening day now this morning we kick off with Paul's keynote and you saw this morning just how evolved every aspect of open hybrid cloud has become based on an open source innovation model that opens source the power and potential of open source so we really brought me to Red Hat but at the end of the day the real value comes when were able to make customers like yourself successful with open source and as much passion and pride as we put into the open source community that requires more than just Red Hat given the complexity of your various businesses the solution set you're building that requires an entire technology ecosystem from system integrators that can provide the skills your domain expertise to software vendors that are going to provide the capabilities for your solutions even to the public cloud providers whether it's on the hosting side or consuming their services you need an entire technological ecosystem to be able to support you and your goals and that is exactly what we are gonna talk about this afternoon the technology ecosystem we work with that's ready to help you on your journey now you know this year's summit we talked about earlier it is about ideas worth exploring and we want to make sure you have all of the expertise you need to make those ideas a reality so with that let's talk about our first partner we have him today and that first partner is IBM when I talk about IBM I have a little bit of a nostalgia and that's because 16 years ago I was at IBM it was during my tenure at IBM where I deployed my first copy of Red Hat Enterprise Linux for a customer it's actually where I did my first professional Linux development as well you and that work on Linux it really was the spark that I had that showed me the potential that open source could have for enterprise customers now iBM has always been a steadfast supporter of Linux and a great Red Hat partner in fact this year we are celebrating 20 years of partnership with IBM but even after 20 years two decades I think we're working on some of the most innovative work that we ever have before so please give a warm welcome to Arvind Krishna from IBM to talk with us about what we are working on Arvind [Applause] hey my pleasure to be here thank you so two decades huh that's uh you know I think anything in this industry to going for two decades is special what would you say that that link is made right Hatton IBM so successful look I got to begin by first seeing something that I've been waiting to say for years it's a long strange trip it's been and for the San Francisco folks they'll get they'll get the connection you know what I was just thinking you said 16 it is strange because I probably met RedHat 20 years ago and so that's a little bit longer than you but that was out in Raleigh it was a much smaller company and when I think about the connection I think look IBM's had a long long investment and a long being a long fan of open source and when I think of Linux Linux really lights up our hardware and I think of the power box that you were showing this morning as well as the mainframe as well as all other hardware Linux really brings that to life and I think that's been at the root of our relationship yeah absolutely now I alluded to a little bit earlier we're working on some new stuff and this time it's a little bit higher in the software stack and we have before so what do you what would you say spearheaded that right so we think of software many people know about some people don't realize a lot of the words are called critical systems you know like reservation systems ATM systems retail banking a lot of the systems run on IBM software and when I say IBM software names such as WebSphere and MQ and db2 all sort of come to mind as being some of that software stack and really when I combine that with some of what you were talking about this morning along hybrid and I think this thing called containers you guys know a little about combining the two we think is going to make magic yeah and I certainly know containers and I think for myself seeing the rise of containers from just the introduction of the technology to customers consuming at mission-critical capacities it's been probably one of the fastest technology cycles I've ever seen before look we completely agree with that when you think back to what Paul talks about this morning on hybrid and we think about it we are made of firm commitment to containers all of our software will run on containers and all of our software runs Rell and you put those two together and this belief on hybrid and containers giving you their hybrid motion so that you can pick where you want to run all the software is really I think what has brought us together now even more than before yeah and the best part I think I've liked we haven't just done the product in downstream alignment we've been so tied in our technology approach we've been aligned all the way to the upstream communities absolutely look participating upstream participating in these projects really bringing all the innovation to bear you know when I hear all of you talk about you can't just be in a single company you got to tap into the world of innovation and everybody should contribute we firmly believe that instead of helping to do that is kind of why we're here yeah absolutely now the best part we're not just going to tell you about what we're doing together we're actually going to show you so how every once you tell the audience a little bit more about what we're doing I will go get the demo team ready in the back so you good okay so look we're doing a lot here together we're taking our software and we are begging to put it on top of Red Hat and openshift and really that's what I'm here to talk about for a few minutes and then we go to show it to you live and the demo guard should be with us so it'll hopefully go go well so when we look at extending our partnership it's really based on three fundamental principles and those principles are the following one it's a hybrid world every enterprise wants the ability to span across public private and their own premise world and we got to go there number two containers are strategic to both of us enterprise needs the agility you need a way to easily port things from place to place to place and containers is more than just wrapping something up containers give you all of the security the automation the deploy ability and we really firmly believe that and innovation is the path forward I mean you got to bring all the innovation to bear whether it's around security whether it's around all of the things we heard this morning around going across multiple infrastructures right the public or private and those are three firm beliefs that both of us have together so then explicitly what I'll be doing here number one all the IBM middleware is going to be certified on top of openshift and rel and through cloud private from IBM so that's number one all the middleware is going to run in rental containers on OpenShift on rail with all the cloud private automation and deployability in there number two we are going to make it so that this is the complete stack when you think about from hardware to hypervisor to os/2 the container platform to all of the middleware it's going to be certified up and down all the way so that you can get comfort that this is certified against all the cyber security attacks that come your way three because we do the certification that means a complete stack can be deployed wherever OpenShift runs so that way you give the complete flexibility and you no longer have to worry about that the development lifecycle is extended all the way from inception to production and the management plane then gives you all of the delivery and operation support needed to lower that cost and lastly professional services through the IBM garages as well as the Red Hat innovation labs and I think that this combination is really speaks to the power of both companies coming together and both of us working together to give all of you that flexibility and deployment capabilities across one can't can't help it one architecture chart and that's the only architecture chart I promise you so if you look at it right from the bottom this speaks to what I'm talking about you begin at the bottom and you have a choice of infrastructure the IBM cloud as well as other infrastructure as a service virtual machines as well as IBM power and IBM mainframe as is the infrastructure choices underneath so you choose what what is best suited for the workload well with the container service with the open shift platform managing all of that environment as well as giving the orchestration that kubernetes gives you up to the platform services from IBM cloud private so it contains the catalog of all middle we're both IBM's as well as open-source it contains all the deployment capability to go deploy that and it contains all the operational management so things like come back up if things go down worry about auto scaling all those features that you want come to you from there and that is why that combination is so so powerful but rather than just hear me talk about it I'm also going to now bring up a couple of people to talk about it and what all are they going to show you they're going to show you how you can deploy an application on this environment so you can think of that as either a cloud native application but you can also think about it as how do you modernize an application using micro services but you don't want to just keep your application always within its walls you also many times want to access different cloud services from this and how do you do that and I'm not going to tell you which ones they're going to come and tell you and how do you tackle the complexity of both hybrid data data that crosses both from the private world to the public world and as well as target the extra workloads that you want so that's kind of the sense of what you're going to see through through the demonstrations but with that I'm going to invite Chris and Michael to come up I'm not going to tell you which one's from IBM which runs from Red Hat hopefully you'll be able to make the right guess so with that Chris and Michael [Music] so so thank you Arvind hopefully people can guess which ones from Red Hat based on the shoes I you know it's some really exciting stuff that we just heard there what I believe that I'm I'm most excited about when I look out upon the audience and the opportunity for customers is with this announcement there are quite literally millions of applications now that can be modernized and made available on any cloud anywhere with the combination of IBM cloud private and OpenShift and I'm most thrilled to have mr. Michael elder a distinguished engineer from IBM here with us today and you know Michael would you maybe describe for the folks what we're actually going to go over today absolutely so when you think about how do I carry forward existing applications how do I build new applications as well you're creating micro services that always need a mixture of data and messaging and caching so this example application shows java-based micro services running on WebSphere Liberty each of which are then leveraging things like IBM MQ for messaging IBM db2 for data operational decision manager all of which is fully containerized and running on top of the Red Hat open chip container platform and in fact we're even gonna enhance stock trader to help it understand how you feel but okay hang on so I'm a little slow to the draw sometimes you said we're gonna have an application tell me how I feel exactly exactly you think about your enterprise apps you want to improve customer service understanding how your clients feel can't help you do that okay well this I'd like to see that in action all right let's do it okay so the first thing we'll do is we'll actually take a look at the catalog and here in the IBM cloud private catalog this is all of the content that's available to deploy now into this hybrid solution so we see workloads for IBM will see workloads for other open source packages etc each of these are packaged up as helm charts that are deploying a set of images that will be certified for Red Hat Linux and in this case we're going to go through and start with a simple example with a node out well click a few actions here we'll give it a name now do you have your console up over there I certainly do all right perfect so we'll deploy this into the new old namespace and will deploy notate okay alright anything happening of course it's come right up and so you know what what I really like about this is regardless of if I'm used to using IBM clout private or if I'm used to working with open shift yeah the experience is well with the tool of whatever I'm you know used to dealing with on a daily basis but I mean you know I got to tell you we we deployed node ourselves all the time what about and what about when was the last time you deployed MQ on open shift you never I maybe never all right let's fix that so MQ obviously is a critical component for messaging for lots of highly transactional systems here we'll deploy this as a container on the platform now I'm going to deploy this one again into new worlds I'm gonna disable persistence and for my application I'm going to need a queue manager so I'm going to have it automatically setup my queue manager as well now this will deploy a couple of things what do you see I see IBM in cube all right so there's your stateful set running MQ and of course there's a couple of other components that get stood up as needed here including things like credentials and secrets and the service etc but all of this is they're out of the box ok so impressive right but that's the what I think you know what I'm really looking at is maybe how a well is this running you know what else does this partnership bring when I look at IBM cloud private windows inches well so that's a key reason about why it's not just about IBM middleware running on open shift but also IBM cloud private because ultimately you need that common management plane when you deploy a container the next thing you have to worry about is how do I get its logs how do I manage its help how do I manage license consumption how do I have a common security plan right so cloud private is that enveloping wrapper around IBM middleware to provide those capabilities in a common way and so here we'll switch over to our dashboard this is our Griffin and Prometheus stack that's deployed also now on cloud private running on OpenShift and we're looking at a different namespace we're looking at the stock trader namespace we'll go back to this app here momentarily and we can see all the different pieces what if you switch over to the stock trader workspace on open shipped yeah I think we might be able to do that here hey there it is alright and so what you're gonna see here all the different pieces of this op right there's d b2 over here I see the portfolio Java microservice running on Webster Liberty I see my Redis cash I see MQ all of these are the components we saw in the architecture picture a minute ago ya know so this is really great I mean so maybe let's take a look at the actual application I see we have a fine stock trader app here now we mentioned understanding how I feel exactly you know well I feel good that this is you know a brand new stock trader app versus the one from ten years ago that don't feel like we used forever so the key thing is this app is actually all of those micro services in addition to things like business rules etc to help understand the loyalty program so one of the things we could do here is actually enhance it with a a AI service from Watson this is tone analyzer it helps me understand how that user actually feels and will be able to go through and submit some feedback to understand that user ok well let's see if we can take a look at that so I tried to click on youth clearly you're not very happy right now here I'll do one quick thing over here go for it we'll clear a cache for our sample lab so look you guys don't actually know as Michael and I just wrote this no js' front end backstage while Arvin was actually talking with Matt and we deployed it real-time using continuous integration and continuous delivery that we have available with openshift well the great thing is it's a live demo right so we're gonna do it all live all the time all right so you mentioned it'll tell me how I'm feeling right so if we look at so right there it looks like they're pretty angry probably because our cache hadn't been cleared before we started the demo maybe well that would make me angry but I should be happy because I mean I have a lot of money well it's it's more than I get today for sure so but you know again I don't want to remain angry so does Watson actually understand southern I know it speaks like eighty different languages but well you know I'm from South Carolina to understand South Carolina southern but I don't know about your North Carolina southern alright well let's give it a go here y'all done a real real know no profanity now this is live I've done a real real nice job on this here fancy demo all right hey all right likes me now all right cool and the key thing is just a quick note right it's showing you've got a free trade so we can integrate those business rules and then decide to I do put one trade if you're angry give me more it's all bringing it together into one platform all running on open show yeah and I can see the possibilities right of we've not only deployed services but getting that feedback from our customers to understand well how well the services are being used and are people really happy with what they have hey listen Michael this was amazing I read you joining us today I hope you guys enjoyed this demo as well so all of you know who this next company is as I look out through the crowd based on what I can actually see with the sun shining down on me right now I can see their influence everywhere you know Sports is in our everyday lives and these guys are equally innovative in that space as they are with hybrid cloud computing and they use that to help maintain and spread their message throughout the world of course I'm talking about Nike I think you'll enjoy this next video about Nike and their brand and then we're going to hear directly from my twitting about what they're doing with Red Hat technology new developments in the top story of the day the world has stopped turning on its axis top scientists are currently racing to come up with a solution everybody going this way [Music] the wrong way [Music] please welcome Nike vice president of infrastructure engineering Mike witig [Music] hi everybody over the last five years at Nike we have transformed our technology landscape to allow us to connect more directly to our consumers through our retail stores through Nike comm and our mobile apps the first step in doing that was redesigning our global network to allow us to have direct connectivity into both Asia and AWS in Europe in Asia and in the Americas having that proximity to those cloud providers allows us to make decisions about application workload placement based on our strategy instead of having design around latency concerns now some of those workloads are very elastic things like our sneakers app for example that needs to burst out during certain hours of the week there's certain moments of the year when we have our high heat product launches and for those type of workloads we write that code ourselves and we use native cloud services but being hybrid has allowed us to not have to write everything that would go into that app but rather just the parts that are in that application consumer facing experience and there are other back-end systems certain core functionalities like order management warehouse management finance ERP and those are workloads that are third-party applications that we host on relevent over the last 18 months we have started to deploy certain elements of those core applications into both Azure and AWS hosted on rel and at first we were pretty cautious that we started with development environments and what we realized after those first successful deployments is that are the impact of those cloud migrations on our operating model was very small and that's because the tools that we use for monitoring for security for performance tuning didn't change even though we moved those core applications into Azure in AWS because of rel under the covers and getting to the point where we have that flexibility is a real enabler as an infrastructure team that allows us to just be in the yes business and really doesn't matter where we want to deploy different workload if either cloud provider or on-prem anywhere on the planet it allows us to move much more quickly and stay much more directed to our consumers and so having rel at the core of our strategy is a huge enabler for that flexibility and allowing us to operate in this hybrid model thanks very much [Applause] what a great example it's really nice to hear an IQ story of using sort of relish that foundation to enable their hybrid clout enable their infrastructure and there's a lot that's the story we spent over ten years making that possible for rel to be that foundation and we've learned a lot in that but let's circle back for a minute to the software vendors and what kicked off the day today with IBM IBM s one of the largest software portfolios on the planet but we learned through our journey on rel that you need thousands of vendors to be able to sport you across all of your different industries solve any challenge that you might have and you need those vendors aligned with your technology direction this is doubly important when the technology direction is changing like with containers we saw that two years ago bread had introduced our container certification program now this program was focused on allowing you to identify vendors that had those shared technology goals but identification by itself wasn't enough in this fast-paced world so last year we introduced trusted content we introduced our container health index publicly grading red hats images that form the foundation for those vendor images and that was great because those of you that are familiar with containers know that you're taking software from vendors you're combining that with software from companies like Red Hat and you are putting those into a single container and for you to run those in a mission-critical capacity you have to know that we can both stand by and support those deployments but even trusted content wasn't enough so this year I'm excited that we are extending once again to introduce trusted operations now last week we announced that cube con kubernetes conference the kubernetes operator SDK the goal of the kubernetes operators is to allow any software provider on kubernetes to encode how that software should run this is a critical part of a container ecosystem not just being able to find the vendors that you want to work with not just knowing that you can trust what's inside the container but knowing that you can efficiently run that software now the exciting part is because this is so closely aligned with the upstream technology that today we already have four partners that have functioning operators specifically Couchbase dynaTrace crunchy and black dot so right out of the gate you have security monitoring data store options available to you these partners are really leading the charge in terms of what it means to run their software on OpenShift but behind these four we have many more in fact this morning we announced over 60 partners that are committed to building operators they're taking their domain expertise and the software that they wrote that they know and extending that into how you are going to run that on containers in environments like OpenShift this really brings the power of being able to find the vendors being able to trust what's inside and know that you can run their software as efficiently as anyone else on the planet but instead of just telling you about this we actually want to show you this in action so why don't we bring back up the demo team to give you a little tour of what's possible with it guys thanks Matt so Matt talked about the concept of operators and when when I think about operators and what they do it's taking OpenShift based services and making them even smarter giving you insight into how they do things for example have we had an operator for the nodejs service that I was running earlier it would have detected the problem and fixed itself but when we look at it what really operators do when I look at it from an ecosystem perspective is for ISVs it's going to be a catalyst that's going to allow them to make their services as manageable and it's flexible and as you know maintainable as any public cloud service no matter where OpenShift is running and to help demonstrate this I've got my buddy Rob here Rob are we ready on the demo front we're ready awesome now I notice this screen looks really familiar to me but you know I think we want to give folks here a dev preview of a couple of things well we want to show you is the first substantial integration of the core OS tectonic technology with OpenShift and then the other thing is we are going to dive in a little bit more into operators and their usefulness so Rob yeah so what we're looking at here is the service catalog that you know and love and openshift and we've got a few new things in here we've actually integrated operators into the Service Catalog and I'm going to take this filter and give you a look at some of them that we have today so you can see we've got a list of operators exposed and this is the same way that your developers are already used to integrating with products they're right in your catalog and so now these are actually smarter services but how can we maybe look at that I mentioned that there's maybe a new view I'm used to seeing this as a developer but I hear we've got some really cool stuff if I'm the administrator of the console yeah so we've got a whole new side of the console for cluster administrators to get a look at under the infrastructure versus this dev focused view that we're looking at today today so let's go take a look at it so the first thing you see here is we've got a really rich set of monitoring and health status so we can see that we've got some alerts firing our control plane is up and we can even do capacity planning anything that you need to do to maintenance your cluster okay so it's it's not only for the the services in the cluster and doing things that you know I may be normally as a human operator would have to do but this this console view also gives me insight into the infrastructure itself right like maybe the nodes and maybe handling the security context is that true yes so these are new capabilities that we're bringing to open shift is the ability to do node management things like drain and unscheduled nodes to do day-to-day maintenance and then as well as having security constraints and things like role bindings for example and the exciting thing about this is this is a view that you've never been able to see before it's cross-cutting across namespaces so here we've got a number of admin bindings and we can see that they're connected to a number of namespaces and these would represent our engineering teams all the groups that are using the cluster and we've never had this view before this is a perfect way to audit your security you know it actually is is pretty exciting I mean I've been fortunate enough to be on the up and shift team since day one and I know that operations view is is something that we've you know strived for and so it's really exciting to see that we can offer that now but you know really this was a we want to get into what operators do and what they can do for us and so maybe you show us what the operator console looks like yeah so let's jump on over and see all the operators that we have installed on the cluster you can see that these mirror what we saw on the Service Catalog earlier now what we care about though is this Couchbase operator and we're gonna jump into the demo namespace as I said you can share a number of different teams on a cluster so it's gonna jump into this namespace okay cool so now what we want to show you guys when we think about operators you know we're gonna have a scenario here where there's going to be multiple replicas of a Couchbase service running in the cluster and then we're going to have a stateful set and what's interesting is those two things are not enough if I'm really trying to run this as a true service where it's highly available in persistent there's things that you know as a DBA that I'm normally going to have to do if there's some sort of node failure and so what we want to demonstrate to you is where operators combined with the power that was already within OpenShift are now coming together to keep this you know particular database service highly available and something that we can continue using so Rob what have you got there yeah so as you can see we've got our couch based demo cluster running here and we can see that it's up and running we've got three members we've got an off secret this is what's controlling access to a UI that we're gonna look at in a second but what really shows the power of the operator is looking at this view of the resources that it's managing you can see that we've got a service that's doing load balancing into the cluster and then like you said we've got our pods that are actually running the software itself okay so that's cool so maybe for everyone's benefit so we can show that this is happening live could we bring up the the Couchbase console please and keep up the openshift console both sides so what we see there we go so what we see on the on the right hand side is obviously the same console Rob was working in on the left-hand side as you can see by the the actual names of the pods that are there the the couch based services that are available and so Rob maybe um let's let's kill something that's always fun to do on stage yeah this is the power of the operator it's going to recover it so let's browse on over here and kill node number two so we're gonna forcefully kill this and kick off the recovery and I see right away that because of the integration that we have with operators the Couchbase console immediately picked up that something has changed in the environment now why is that important normally a human being would have to get that alert right and so with operators now we've taken that capability and we've realized that there has been a new event within the environment this is not something that you know kubernetes or open shipped by itself would be able to understand now I'm presuming we're gonna end up doing something else it's not just seeing that it failed and sure enough there we go remember when you have a stateful application rebalancing that data and making it available is just as important as ensuring that the disk is attached so I mean Rob thank you so much for you know driving this for us today and being here I mean you know not only Couchbase but as was mentioned by matt we also have you know crunchy dynaTrace and black duck I would encourage you all to go visit their booths out on the floor today and understand what they have available which are all you know here with a dev preview and then talk to the many other partners that we have that are also looking at operators so again rub thank you for joining us today Matt come on out okay this is gonna make for an exciting year of just what it means to consume container base content I think containers change how customers can get that I believe operators are gonna change how much they can trust running that content let's circle back to one more partner this next partner we have has changed the landscape of computing specifically with their work on hardware design work on core Linux itself you know in fact I think they've become so ubiquitous with computing that we often overlook the technological marvels that they've been able to overcome now for myself I studied computer engineering so in the late 90s I had the chance to study processor design I actually got to build one of my own processors now in my case it was the most trivial processor that you could imagine it was an 8-bit subtractor which means it can subtract two numbers 256 or smaller but in that process I learned the sheer complexity that goes into processor design things like wire placements that are so close that electrons can cut through the insulation in short and then doing those wire placements across three dimensions to multiple layers jamming in as many logic components as you possibly can and again in my case this was to make a processor that could subtract two numbers but once I was done with this the second part of the course was studying the Pentium processor now remember that moment forever because looking at what the Pentium processor was able to accomplish it was like looking at alien technology and the incredible thing is that Intel our next partner has been able to keep up that alien like pace of innovation twenty years later so we're excited have Doug Fisher here let's hear a little bit more from Intel for business wide open skies an open mind no matter the context the idea of being open almost only suggests the potential of infinite possibilities and that's exactly the power of open source whether it's expanding what's possible in business the science and technology or for the greater good which is why-- open source requires the involvement of a truly diverse community of contributors to scale and succeed creating infinite possibilities for technology and more importantly what we do with it [Music] you know what Intel one of our core values is risk-taking and I'm gonna go just a bit off script for a second and say I was just backstage and I saw a gentleman that looked a lot like Scott Guthrie who runs all of Microsoft's cloud enterprise efforts wearing a red shirt talking to Cormier I'm just saying I don't know maybe I need some more sleep but that's what I saw as we approach Intel's 50th anniversary these words spoken by our co-founder Robert Noyce are as relevant today as they were decades ago don't be encumbered by history this is about breaking boundaries in technology and then go off and do something wonderful is about innovation and driving innovation in our industry and Intel we're constantly looking to break boundaries to advance our technology in the cloud in enterprise space that is no different so I'm going to talk a bit about some of the boundaries we've been breaking and innovations we've been driving at Intel starting with our Intel Xeon platform Orion Xeon scalable platform we launched several months ago which was the biggest and mark the most advanced movement in this technology in over a decade we were able to drive critical performance capabilities unmatched agility and added necessary and sufficient security to that platform I couldn't be happier with the work we do with Red Hat and ensuring that those hero features that we drive into our platform they fully expose to all of you to drive that innovation to go off and do something wonderful well there's taking advantage of the performance features or agility features like our advanced vector extensions or avx-512 or Intel quick exist those technologies are fully embraced by Red Hat Enterprise Linux or whether it's security technologies like txt or trusted execution technology are fully incorporated and we look forward to working with Red Hat on their next release to ensure that our advancements continue to be exposed and their platform and all these workloads that are driving the need for us to break boundaries and our technology are driving more and more need for flexibility and computing and that's why we're excited about Intel's family of FPGAs to help deliver that additional flexibility for you to build those capabilities in your environment we have a broad set of FPGA capabilities from our power fish at Mac's product line all the way to our performance product line on the 6/10 strat exten we have a broad set of bets FPGAs what i've been talking to customers what's really exciting is to see the combination of using our Intel Xeon scalable platform in combination with FPGAs in addition to the acceleration development capabilities we've given to software developers combining all that together to deliver better and better solutions whether it's helping to accelerate data compression well there's pattern recognition or data encryption and decryption one of the things I saw in a data center recently was taking our Intel Xeon scalable platform utilizing the capabilities of FPGA to do data encryption between servers behind the firewall all the while using the FPGA to do that they preserve those precious CPU cycles to ensure they delivered the SLA to the customer yet provided more security for their data in the data center one of the edges in cyber security is innovation and route of trust starts at the hardware we recently renewed our commitment to security with our security first pledge has really three elements to our security first pledge first is customer first urgency we have now completed the release of the micro code updates for protection on our Intel platforms nine plus years since launch to protect against things like the side channel exploits transparent and timely communication we are going to communicate timely and openly on our Intel comm website whether it's about our patches performance or other relevant information and then ongoing security assurance we drive security into every one of our products we redesigned a portion of our processor to add these partition capability which is adding additional walls between applications and user level privileges to further secure that environment from bad actors I want to pause for a second and think everyone in this room involved in helping us work through our security first pledge this isn't something we do on our own it takes everyone in this room to help us do that the partnership and collaboration was next to none it's the most amazing thing I've seen since I've been in this industry so thank you we don't stop there we continue to advance our security capabilities cross-platform solutions we recently had a conference discussion at RSA where we talked about Intel Security Essentials where we deliver a framework of capabilities and the end that are in our silicon available for those to innovate our customers and the security ecosystem to innovate on a platform in a consistent way delivering that assurance that those capabilities will be on that platform we also talked about things like our security threat technology threat detection technology is something that we believe in and we launched that at RSA incorporates several elements one is ability to utilize our internal graphics to accelerate some of the memory scanning capabilities we call this an accelerated memory scanning it allows you to use the integrated graphics to scan memory again preserving those precious cycles on the core processor Microsoft adopted this and are now incorporated into their defender product and are shipping it today we also launched our threat SDK which allows partners like Cisco to utilize telemetry information to further secure their environments for cloud workloads so we'll continue to drive differential experiences into our platform for our ecosystem to innovate and deliver more and more capabilities one of the key aspects you have to protect is data by 2020 the projection is 44 zettabytes of data will be available 44 zettabytes of data by 2025 they project that will grow to a hundred and eighty s data bytes of data massive amount of data and what all you want to do is you want to drive value from that data drive and value from that data is absolutely critical and to do that you need to have that data closer and closer to your computation this is why we've been working Intel to break the boundaries in memory technology with our investment in 3d NAND we're reducing costs and driving up density in that form factor to ensure we get warm data closer to the computing we're also innovating on form factors we have here what we call our ruler form factor this ruler form factor is designed to drive as much dense as you can in a 1u rack we're going to continue to advance the capabilities to drive one petabyte of data at low power consumption into this ruler form factor SSD form factor so our innovation continues the biggest breakthrough and memory technology in the last 25 years in memory media technology was done by Intel we call this our 3d crosspoint technology and our 3d crosspoint technology is now going to be driven into SSDs as well as in a persistent memory form factor to be on the memory bus giving you the speed of memory characteristics of memory as well as the characteristics of storage given a new tier of memory for developers to take full advantage of and as you can see Red Hat is fully committed to integrating this capability into their platform to take full advantage of that new capability so I want to thank Paul and team for engaging with us to make sure that that's available for all of you to innovate on and so we're breaking boundaries and technology across a broad set of elements that we deliver that's what we're about we're going to continue to do that not be encumbered by the past your role is to go off and doing something wonderful with that technology all ecosystems are embracing this and driving it including open source technology open source is a hub of innovation it's been that way for many many years that innovation that's being driven an open source is starting to transform many many businesses it's driving business transformation we're seeing this coming to light in the transformation of 5g driving 5g into the networked environment is a transformational moment an open source is playing a pivotal role in that with OpenStack own out and opie NFV and other open source projects were contributing to and participating in are helping drive that transformation in 5g as you do software-defined networks on our barrier breaking technology we're also seeing this transformation rapidly occurring in the cloud enterprise cloud enterprise are growing rapidly and innovation continues our work with virtualization and KVM continues to be aggressive to adopt technologies to advance and deliver more capabilities in virtualization as we look at this with Red Hat we're now working on Cube vert to help move virtualized workloads onto these platforms so that we can now have them managed at an open platform environment and Cube vert provides that so between Intel and Red Hat and the community we're investing resources to make certain that comes to product as containers a critical feature in Linux becomes more and more prevalent across the industry the growth of container elements continues at a rapid rapid pace one of the things that we wanted to bring to that is the ability to provide isolation without impairing the flexibility the speed and the footprint of a container with our clear container efforts along with hyper run v we were able to combine that and create we call cotta containers we launched this at the end of last year cotta containers is designed to have that container element available and adding elements like isolation both of these events need to have an orchestration and management capability Red Hat's OpenShift provides that capability for these workloads whether containerized or cube vert capabilities with virtual environments Red Hat openshift is designed to take that commercial capability to market and we've been working with Red Hat for several years now to develop what we call our Intel select solution Intel select solutions our Intel technology optimized for downstream workloads as we see a growth in a workload will work with a partner to optimize a solution on Intel technology to deliver the best solution that could be deployed quickly our effort here is to accelerate the adoption of these type of workloads in the market working with Red Hat's so now we're going to be deploying an Intel select solution design and optimized around Red Hat OpenShift we expect the industry's start deploying this capability very rapidly I'm excited to announce today that Lenovo is committed to be the first platform company to deliver this solution to market the Intel select solution to market will be delivered by Lenovo now I talked about what we're doing in industry and how we're transforming businesses our technology is also utilized for greater good there's no better example of this than the worked by dr. Stephen Hawking it was a sad day on March 14th of this year when dr. Stephen Hawking passed away but not before Intel had a 20-year relationship with dr. Hawking driving breakthrough capabilities innovating with him driving those robust capabilities to the rest of the world one of our Intel engineers an Intel fellow which is the highest technical achievement you can reach at Intel got to spend 10 years with dr. Hawking looking at innovative things they could do together with our technology and his breakthrough innovative thinking so I thought it'd be great to bring up our Intel fellow Lema notch Minh to talk about her work with dr. Hawking and what she learned in that experience come on up Elina [Music] great to see you Thanks something going on about the breakthrough breaking boundaries and Intel technology talk about how you use that in your work with dr. Hawking absolutely so the most important part was to really make that technology contextually aware because for people with disability every single interaction takes a long time so whether it was adapting for example the language model of his work predictor to understand whether he's gonna talk to people or whether he's writing a book on black holes or to even understand what specific application he might be using and then making sure that we're surfacing only enough actions that were relevant to reduce that amount of interaction so the tricky part is really to make all of that contextual awareness happen without totally confusing the user because it's constantly changing underneath it so how is that your work involving any open source so you know the problem with assistive technology in general is that it needs to be tailored to the specific disability which really makes it very hard and very expensive because it can't utilize the economies of scale so basically with the system that we built what we wanted to do is really enable unleashing innovation in the world right so you could take that framework you could tailor to a specific sensor for example a brain computer interface or something like that where you could actually then support a different set of users so that makes open-source a perfect fit because you could actually build and tailor and we you spoke with dr. Hawking what was this view of open source is it relevant to him so yeah so Stephen was adamant from the beginning that he wanted a system to benefit the world and not just himself so he spent a lot of time with us to actually build this system and he was adamant from day one that he would only engage with us if we were commit to actually open sourcing the technology that's fantastic and you had the privilege of working with them in 10 years I know you have some amazing stories to share so thank you so much for being here thank you so much in order for us to scale and that's what we're about at Intel is really scaling our capabilities it takes this community it takes this community of diverse capabilities it takes two births thought diverse thought of dr. Hawking couldn't be more relevant but we also are proud at Intel about leading efforts of diverse thought like women and Linux women in big data other areas like that where Intel feels that that diversity of thinking and engagement is critical for our success so as we look at Intel not to be encumbered by the past but break boundaries to deliver the technology that you all will go off and do something wonderful with we're going to remain committed to that and I look forward to continue working with you thank you and have a great conference [Applause] thank God now we have one more customer story for you today when you think about customers challenges in the technology landscape it is hard to ignore the public cloud these days public cloud is introducing capabilities that are driving the fastest rate of innovation that we've ever seen in our industry and our next customer they actually had that same challenge they wanted to tap into that innovation but they were also making bets for the long term they wanted flexibility and providers and they had to integrate to the systems that they already have and they have done a phenomenal job in executing to this so please give a warm welcome to Kerry Pierce from Cathay Pacific Kerry come on thanks very much Matt hi everyone thank you for giving me the opportunity to share a little bit about our our cloud journey let me start by telling you a little bit about Cathay Pacific we're an international airline based in Hong Kong and we serve a passenger and a cargo network to over 200 destinations in 52 countries and territories in the last seventy years and years seventy years we've made substantial investments to develop Hong Kong as one of the world's leading transportation hubs we invest in what matters most to our customers to you focusing on our exemplary service and our great product and it's both on the ground and in the air we're also investing and expanding our network beyond our multiple frequencies to the financial districts such as Tokyo New York and London and we're connecting Asia and Hong Kong with key tech hubs like San Francisco where we have multiple flights daily we're also connecting Asia in Hong Kong to places like Tel Aviv and our upcoming destination of Dublin in fact 2018 is actually going to be one of our biggest years in terms of network expansion and capacity growth and we will be launching in September our longest flight from Hong Kong direct to Washington DC and that'll be using a state-of-the-art Airbus a350 1000 aircraft so that's a little bit about Cathay Pacific let me tell you about our journey through the cloud I'm not going to go into technical details there's far smarter people out in the audience who will be able to do that for you just focus a little bit about what we were trying to achieve and the people side of it that helped us get there we had a couple of years ago no doubt the same issues that many of you do I don't think we're unique we had a traditional on-premise non-standardized fragile infrastructure it didn't meet our infrastructure needs and it didn't meet our development needs it was costly to maintain it was costly to grow and it really inhibited innovation most importantly it slowed the delivery of value to our customers at the same time you had the hype of cloud over the last few years cloud this cloud that clouds going to fix the world we were really keen on making sure we didn't get wound up and that so we focused on what we needed we started bottom up with a strategy we knew we wanted to be clouded Gnostic we wanted to have active active on-premise data centers with a single network and fabric and we wanted public clouds that were trusted and acted as an extension of that environment not independently we wanted to avoid single points of failure and we wanted to reduce inter dependencies by having loosely coupled designs and finally we wanted to be scalable we wanted to be able to cater for sudden surges of demand in a nutshell we kind of just wanted to make everything easier and a management level we wanted to be a broker of services so not one size fits all because that doesn't work but also not one of everything we want to standardize but a pragmatic range of services that met our development and support needs and worked in harmony with our public cloud not against it so we started on a journey with red hat we implemented Red Hat cloud forms and ansible to manage our hybrid cloud we also met implemented Red Hat satellite to maintain a manager environment we built a Red Hat OpenStack on crimson vironment to give us an alternative and at the same time we migrated a number of customer applications to a production public cloud open shift environment but it wasn't all Red Hat you love heard today that the Red Hat fits within an overall ecosystem we looked at a number of third-party tools and services and looked at developing those into our core solution I think at last count we had tried and tested somewhere past eight different tools and at the moment we still have around 62 in our environment that help us through that journey but let me put the technical solution aside a little bit because it doesn't matter how good your technical solution is if you don't have the culture and the people to get it right as a group we needed to be aligned for delivery and we focused on three core behaviors we focused on accountability agility and collaboration now I was really lucky we've got a pretty fantastic team for whom that was actually pretty easy but but again don't underestimate the importance of getting the culture and the people right because all the technology in the world doesn't matter if you don't have that right I asked the team what did we do differently because in our situation we didn't go out and hire a bunch of new people we didn't go out and hire a bunch of consultants we had the staff that had been with us for 10 20 and in some cases 30 years so what did we do differently it was really simple we just empowered and supported our staff we knew they were the smart ones they were the ones that were dealing with a legacy environment and they had the passion to make the change so as a team we encouraged suggestions and contributions from our overall IT community from the bottom up we started small we proved the case we told the story and then we got by him and only did did we implement wider the benefits the benefit through our staff were a huge increase in staff satisfaction reduction and application and platform outage support incidents risk free and failsafe application releases work-life balance no more midnight deployments and our application and infrastructure people could really focus on delivering customer value not on firefighting and for our end customers the people that travel with us it was really really simple we could provide a stable service that allowed for faster releases which meant we could deliver value faster in terms of stats we migrated 16 production b2c applications to a public cloud OpenShift environment in 12 months we decreased provisioning time from weeks or occasionally months we were waiting for hardware two minutes and we had a hundred percent availability of our key customer facing systems but most importantly it was about people we'd built a culture a culture of innovation that was built on a foundation of collaboration agility and accountability and that permeated throughout the IT organization not those just those people that were involved in the project everyone with an IT could see what good looked like and to see what it worked what it looked like in terms of working together and that was a key foundation for us the future for us you will have heard today everything's changing so we're going to continue to develop our open hybrid cloud onboard more public cloud service providers continue to build more modern applications and leverage the emerging technology integrate and automate everything we possibly can and leverage more open source products with the great support from the open source community so there you have it that's our journey I think we succeeded by not being over awed and by starting with the basics the technology was key obviously it's a cool component but most importantly it was a way we approached our transition we had a clear strategy that was actually developed bottom-up by the people that were involved day to day and we empowered those people to deliver and that provided benefits to both our staff and to our customers so thank you for giving the opportunity to share and I hope you enjoy the rest of the summer [Applause] I got one thanks what a great story would a great customer story to close on and we have one more partner to come up and this is a partner that all of you know that's Microsoft Microsoft has gone through an amazing transformation they've we've built an incredibly meaningful partnership with them all the way from our open source collaboration to what we do in the business side we started with support for Red Hat Enterprise Linux on hyper-v and that was truly just the beginning today we're announcing one of the most exciting joint product offerings on the market today let's please give a warm welcome to Paul correr and Scott Scott Guthrie to tell us about it guys come on out you know Scot welcome welcome to the Red Hat summer thanks for coming really appreciate it great to be here you know many surprises a lot of people when we you know published a list of speakers and then you rock you were on it and you and I are on stage here it's really really important and exciting to us exciting new partnership we've worked together a long time from the hypervisor up to common support and now around hybrid hybrid cloud maybe from your perspective a little bit of of what led us here well you know I think the thing that's really led us here is customers and you know Microsoft we've been on kind of a transformation journey the last several years where you know we really try to put customers at the center of everything that we do and you know as part of that you quickly learned from customers in terms of I'm including everyone here just you know you've got a hybrid of state you know both in terms of what you run on premises where it has a lot of Red Hat software a lot of Microsoft software and then really is they take the journey to the cloud looking at a hybrid of state in terms of how do you run that now between on-premises and a public cloud provider and so I think the thing that both of us are recognized and certainly you know our focus here at Microsoft has been you know how do we really meet customers with where they're at and where they want to go and make them successful in that journey and you know it's been fantastic working with Paul and the Red Hat team over the last two years in particular we spend a lot of time together and you know really excited about the journey ahead so um maybe you can share a bit more about the announcement where we're about to make today yeah so it's it's it's a really exciting announcement it's and really kind of I think first of its kind in that we're delivering a Red Hat openshift on Azure service that we're jointly developing and jointly managing together so this is different than sort of traditional offering where it's just running inside VMs and it's sort of two vendors working this is really a jointly managed service that we're providing with full enterprise support with a full SLA where the you know single throat to choke if you will although it's collectively both are choke the throats in terms of making sure that it works well and it's really uniquely designed around this hybrid world and in that it supports will support both Windows and Linux containers and it role you know it's the same open ship that runs both in the public cloud on Azure and on-premises and you know it's something that we hear a lot from customers I know there's a lot of people here that have asked both of us for this and super excited to be able to talk about it today and we're gonna show off the first demo of it just a bit okay well I'm gonna ask you to elaborate a bit more about this how this fits into the bigger Microsoft picture and I'll get out of your way and so thanks again thank you for coming here we go thanks Paul so I thought I'd spend just a few minutes talking about wouldn't you know that some of the work that we're doing with Microsoft Asher and the overall Microsoft cloud I didn't go deeper in terms of the new offering that we're announcing today together with red hat and show demo of it actually in action in a few minutes you know the high level in terms of you know some of the work that we've been doing at Microsoft the last couple years you know it's really been around this this journey to the cloud that we see every organization going on today and specifically the Microsoft Azure we've been providing really a cloud platform that delivers the infrastructure the application and kind of the core computing needs that organizations have as they want to be able to take advantage of what the cloud has to offer and in terms of our focus with Azure you know we've really focused we deliver lots and lots of different services and features but we focused really in particular on kind of four key themes and we see these four key themes aligning very well with the journey Red Hat it's been on and it's partly why you know we think the partnership between the two companies makes so much sense and you know for us the thing that we've been really focused on has been with a or in terms of how do we deliver a really productive cloud meaning how do we enable you to take advantage of cutting-edge technology and how do we kind of accelerate the successful adoption of it whether it's around the integration of managed services that we provide both in terms of the application space in the data space the analytic and AI space but also in terms of just the end-to-end management and development tools and how all those services work together so that teams can basically adopt them and be super successful yeah we deeply believe in hybrid and believe that the world is going to be a multi cloud and a multi distributed world and how do we enable organizations to be able to take the existing investments that they already have and be able to easily integrate them in a public cloud and with a public cloud environment and get immediate ROI on day one without how to rip and replace tons of solutions you know we're moving very aggressively in the AI space and are looking to provide a rich set of AI services both finished AI models things like speech detection vision detection object motion etc that any developer even at non data scientists can integrate to make application smarter and then we provide a rich set of AI tooling that enables organizations to build custom models and be able to integrate them also as part of their applications and with their data and then we invest very very heavily on trust Trust is sort of at the core of a sure and we now have more compliant certifications than any other cloud provider we run in more countries than any other cloud provider and we really focus around unique promises around data residency data sovereignty and privacy that are really differentiated across the industry and terms of where Iser runs today we're in 50 regions around the world so our region for us is typically a cluster of multiple data centers that are grouped together and you can see we're pretty much on every continent with the exception of Antarctica today and the beauty is you're going to be able to take the Red Hat open shift service and run it on ashore in each of these different locations and really have a truly global footprint as you look to build and deploy solutions and you know we've seen kind of this focus on productivity hybrid intelligence and Trust really resonate in the market and about 90 percent of Fortune 500 companies today are deployed on Azure and you heard Nike talked a little bit earlier this afternoon about some of their journeys as they've moved to a dot public cloud this is a small logo of just a couple of the companies that are on ashore today and what I do is actually even before we dive into the open ship demo is actually just show a quick video you know one of the companies thing there are actually several people from that organization here today Deutsche Bank who have been working with both Microsoft and Red Hat for many years Microsoft on the other side Red Hat both on the rel side and then on the OpenShift side and it's just one of these customers that have helped bring the two companies together to deliver this managed openshift service on Azure and so I'm just going to play a quick video of some of the folks that Deutsche Bank talking about their experiences and what they're trying to get out of it so we could roll the video that'd be great technology is at the absolute heart of Deutsche Bank we've recognized that the cost of running our infrastructure was particularly high there was a enormous amount of under utilization we needed a platform which was open to polyglot architecture supporting any kind of application workload across the various business lines of the third we analyzed over 60 different vendor products and we ended up with Red Hat openshift I'm super excited Microsoft or supporting Linux so strongly to adopting a hybrid approach we chose as here because Microsoft was the ideal partner to work with on constructs around security compliance business continuity as you as in all the places geographically that we need to be we have applications now able to go from a proof of concept to production in three weeks that is already breaking records openshift gives us given entities and containers allows us to apply the same sets of processes automation across a wide range of our application landscape on any given day we run between seven and twelve thousand containers across three regions we start see huge levels of cost reduction because of the level of multi-tenancy that we can achieve through containers open ship gives us an abstraction layer which is allows us to move our applications between providers without having to reconfigure or recode those applications what's really exciting for me about this journey is the way they're both Red Hat and Microsoft have embraced not just what we're doing but what each other are doing and have worked together to build open shift as a first-class citizen with Microsoft [Applause] in terms of what we're announcing today is a new fully managed OpenShift service on Azure and it's really the first fully managed service provided end-to-end across any of the cloud providers and it's jointly engineer operated and supported by both Microsoft and Red Hat and that means again sort of one service one SLA and both companies standing for a link firmly behind it really again focusing around how do we make customers successful and as part of that really providing the enterprise-grade not just isolates but also support and integration testing so you can also take advantage of all your rel and linux-based containers and all of your Windows server based containers and how can you run them in a joint way with a common management stack taking the advantage of one service and get maximum density get maximum code reuse and be able to take advantage of a containerized world in a better way than ever before and make this customer focus is very much at the center of what both companies are really centered around and so what if I do be fun is rather than just talk about openshift as actually kind of show off a little bit of a journey in terms of what this move to take advantage of it looks like and so I'd like to invite Brendan and Chris onstage who are actually going to show off a live demo of openshift on Azure in action and really walk through how to provision the service and basically how to start taking advantage of it using the full open ship ecosystem so please welcome Brendan and Chris we're going to join us on stage for a demo thanks God thanks man it's been a good afternoon so you know what we want to get into right now first I'd like to think Brandon burns for joining us from Microsoft build it's a busy week for you I'm sure your own stage there a few times as well you know what I like most about what we just announced is not only the business and technical aspects but it's that operational aspect the uniqueness the expertise that RedHat has for running OpenShift combined with the expertise that Microsoft has within Azure and customers are going to get this joint offering if you will with you know Red Hat OpenShift on Microsoft Azure and so you know kind of with that again Brendan I really appreciate you being here maybe talk to the folks about what we're going to show yeah so we're going to take a look at what it looks like to deploy OpenShift on to Azure via the new OpenShift service and the real selling point the really great part of this is the the deep integration with a cloud native app API so the same tooling that you would use to create virtual machines to create disks trade databases is now the tooling that you're going to use to create an open chip cluster so to show you this first we're going to create a resource group here so we're going to create that resource group in East us using the AZ tool that's the the azure command-line tooling a resource group is sort of a folder on Azure that holds all of your stuff so that's gonna come back into the second I've created my resource group in East us and now we're gonna use that exact same tool calling into into Azure api's to provision an open shift cluster so here we go we have AZ open shift that's our new command line tool putting it into that resource group I'm gonna get into East us alright so it's gonna take a little bit of time to deploy that open shift cluster it's doing a bunch of work behind the scenes provisioning all kinds of resources as well as credentials to access a bunch of different as your API so are we actually able to see this to you yeah so we can cut over to in just a second we can cut over to that resource group in a reload so Brendan while relating the beauty of what you know the teams have been doing together already is the fact that now open shift is a first-class citizen as it were yeah absolutely within the agent so I presume not only can I do a deployment but I can do things like scale and check my credentials and pretty much everything that I could do with any other service with that that's exactly right so we can anything that you you were used to doing via the my computer has locked up there we go the demo gods are totally with me oh there we go oh no I hit reload yeah that was that was just evil timing on the house this is another use for operators as we talked about earlier today that's right my dashboard should be coming up do I do I dare click on something that's awesome that was totally it was there there we go good job so what's really interesting about this I've also heard that it deploys you know in as little as five to six minutes which is really good for customers they want to get up and running with it but all right there we go there it is who managed to make it see that shows that it's real right you see the sweat coming off of me there but there you can see the I feel it you can see the various resources that are being created in order to create this openshift cluster virtual machines disks all of the pieces provision for you automatically via that one single command line call now of course it takes a few minutes to to create the cluster so in order to show the other side of that integration the integration between openshift and Azure I'm going to cut over to an open shipped cluster that I already have created alright so here you can see my open shift cluster that's running on Microsoft Azure I'm gonna actually log in over here and the first sign you're gonna see of the integration is it's actually using my credentials my login and going through Active Directory and any corporate policies that I may have around smart cards two-factor off anything like that authenticate myself to that open chef cluster so I'll accept that it can access my and now we're gonna load up the OpenShift web console so now this looks familiar to me oh yeah so if anybody's used OpenShift out there this is the exact same console and what we're going to show though is how this console via the open service broker and the open service broker implementation for Azure integrates natively with OpenShift all right so we can go down here and we can actually see I want to deploy a database I'm gonna deploy Mongo as my key value store that I'm going to use but you know like as we talk about management and having a OpenShift cluster that's managed for you I don't really want to have to manage my database either so I'm actually going to use cosmos DB it's a native Azure service it's a multilingual database that offers me the ability to access my data in a variety of different formats including MongoDB fully managed replicated around the world a pretty incredible service so I'm going to go ahead and create that so now Brendan what's interesting I think to me is you know we talked about the operational aspects and clearly it's not you and I running the clusters but you do need that way to interface with it and so when customers are able to deploy this all of this is out of the box there's no additional contemporary like this is what you get when you create when you use that tool to create that open chef cluster this is what you get with all of that integration ok great step through here and go ahead don't have any IP ranges there we go all right and we create that binding all right and so now behind the scenes openshift is integrated with the azure api's with all of my credentials to go ahead and create that distributed database once it's done provisioning actually all of the credentials necessary to access the database are going to be automatically populated into kubernetes available for me inside of OpenShift via service discovery to access from my application without any further work so I think that really shows not only the power of integrating openshift with an azure based API but actually the power of integrating a Druze API is inside of OpenShift to make a truly seamless experience for managing and deploying your containers across a variety of different platforms yeah hey you know Brendan this is great I know you've got a flight to catch because I think you're back onstage in a few hours but you know really appreciate you joining us today absolutely I look forward to seeing what else we do yeah absolutely thank you so much thanks guys Matt you want to come back on up thanks a lot guys if you have never had the opportunity to do a live demo in front of 8,000 people it'll give you a new appreciation for standing up there and doing it and that was really good you know every time I get the chance just to take a step back and think about the technology that we have at our command today I'm in awe just the progress over the last 10 or 20 years is incredible on to think about what might come in the next 10 or 20 years really is unthinkable you even forget 10 years what might come in the next five years even the next two years but this can create a lot of uncertainty in the environment of what's going to be to come but I believe I am certain about one thing and that is if ever there was a time when any idea is achievable it is now just think about what you've seen today every aspect of open hybrid cloud you have the world's infrastructure at your fingertips and it's not stopping you've heard about this the innovation of open source how fast that's evolving and improving this capability you've heard this afternoon from an entire technology ecosystem that's ready to help you on this journey and you've heard from customer after customer that's already started their journey in the successes that they've had you're one of the neat parts about this afternoon you will aren't later this week you will actually get to put your hands on all of this technology together in our live audience demo you know this is what some it's all about for us it's a chance to bring together the technology experts that you can work with to help formulate how to pull off those ideas we have the chance to bring together technology experts our customers and our partners and really create an environment where everyone can experience the power of open source that same spark that I talked about when I was at IBM where I understood the but intial that open-source had for enterprise customers we want to create the environment where you can have your own spark you can have that same inspiration let's make this you know in tomorrow's keynote actually you will hear a story about how open-source is changing medicine as we know it and literally saving lives it is a great example of expanding the ideas it might be possible that we came into this event with so let's make this the best summit ever thank you very much for being here let's kick things off right head down to the Welcome Reception in the expo hall and please enjoy the summit thank you all so much [Music] [Music]

>> Live from Boston, Massachusetts, it's theCube, covering IBM Chief Data Officer Summit. Brought to you by IBM. >> Welcome back to theCube's live coverage of the IBM CDO Strategy Summit here in Boston, Massachusetts. I'm your host, Rebecca Knight, along with my cohost, Dave Vellante. We are here with Joseph Selle, he is the Cognitive Transformation Lead at IBM. Thanks so much for joining us, Joe. >> Hi, Rebecca, thank you. Hi, Dave. >> Good to see you, Joe. >> You, too. >> So, your job is to help drive the internal transformation of IBM. Tell our viewers what that means and then talk about your approach. >> Right, it a very exciting, frankly, it's one of the best jobs I've ever had personally. It's wonderful. We're transforming the company from the inside out. We're engaging with all of the functional areas within IBM's operations, and we're challenging those functional teams to breakdown their business process and reinvent it using some new tooling. And in this case, it's cognitive approaches to data analysis, and to crowd sourcing information, and systems that learn. We've talked a lot about at this conference, machine learning and deep learning. We're providing all of these tools to these functional teams so they can go reinvent HR and procurement, and even our M&A process, everything is fair game. So, it's very exciting and it really allows us to reinvent IBM. >> So, reinventing all of these individual functions, I mean, where to do you start? How do you begin to build the blueprint? >> Well, in our case, where we started was we had to get the whole company thinking about a large-scale enterprise, cultural transformation. We have a company of 300-some odd thousand people, employees, speaking all languages, all over the globe. So, how do you move that mass? So, we had cognitive jam, that's basically a technology enabled brainstorm session that spreads across the entire globe. And, by engaging about 300,000 IBM'ers, we were able to call and bring together all kinds of very disruptive, interesting ideas to remake all these business processes. We culled those ideas, and through some prioritization, almost a shark tank-like process, we ended up with a few that were really worthy, we felt, of investment. We've put money in, and our cognitive reinvention was born. Just like that. >> That's a lot of brain power. (laughs) >> Well, that's why it's wonderful to be at IBM, 'cause we have hundreds of thousands of brainy people working for us. >> You have talked about, when he was a controller during the Gerstner transformation, I don't know were you there back then? >> Yes, I was. >> Okay, so you guys were young pups back then, still young pups, I guess. But, he talked about, as the controller, he was an unhappy customer because he didn't have the data. So, can you talk about, sort of, what's different today? I mean, it's a lot different, obviously, the state of the industry, the technology, the amount of the data, et cetera. But, maybe talk about data as the starting point and how that was different from, maybe, the Gerstner transformation. >> The early days. >> Which was epic, by the way. You know, took IBM to new levels and be part of what the company is today. >> And this story that I'm going to tell you, is generally applicable to most any company that's global in nature. The data are not visible and they're not easy to see and discern any value from in the early stages of your transformation. So, when Jim was controller, he had data that was one, hard to get, and two, he had no tools to organize it except for, maybe, some smart people with Excel and, whatever it was back then, LotusPro, or something, I can't remember the name of that. (laughter) >> Something that ran on OS/2. >> There was no tooling, no approach. And, the whole idea of big data was not even around at that point. Because the data was organized and disorganized in little towers and databases all around, but there wasn't a flood of data. So, what's different between those days and this time period that we're in is, you can see data now and data are everywhere. And they're coming at us in high, high volumes and at high speeds. If you think about The Weather Company, one of the acquisitions we made two years ago, that is a stream of huge, big data, coming at us very fast. You can think about The Weather Company as a giant internet of things, device, which is pulling data from the sky and from people interacting with the environment, and bringing that all together. And now, what can we do with that data? Well, we can use it to help predict when we're going to have a supply chain disruption, or, I mean in an almost obvious sense, or we can use it when we're trying to respond to some sort of operational disturbance. If we're looking at where we can reroute things, or if we're trying to anticipate some sort of blockage on our supply chain, incoming supply chain, or outgoing supply chain of products. Very important, and we just see much more now then Jim ever could when he was a controller. >> In the scope of your data initiative, is everything, I mean, he's mentioned supply chain, you got customer data? >> It is, it is. But, I'll say that, you know, if a company's going to embark down this path, you don't want to try to boil the ocean at the start. You want to try to go after some selective business challenges, that are persistent challenges that you wish you had a way to solve because a lot of value's at play. So, you go in there and you solve a few problems. You deal with a data integrity and access problem, on a, sort of a, confined basis. And you do this, maybe, several times across different parts of your company. Then, once you've done that four or five times, or some small number of times, you begin to learn how to handle the problem more generally, and you can distill approaches and tools that can then be applied broadly. And where we are in our evolution, is that Inderpal and Jim, and the internal workings of IBM, were building a cognitive enterprise data platform. So, we're taking all of these point solutions that I just referred to, bringing them together onto a platform, and applying some common tooling to all of these common types of problems around data organization, and governance, and meta-data tagging, and all this geeky stuff that you have to be able to do if you're going to make any value. You know, if you're going to make an important, valuable business decision, based on a stream of data. >> So, where has it had tangible, measurable, business impact, this sort of cognitive initiative? >> Well, a couple of the areas where we're most mature, one would be in supply chain and procurement. We've been able to take jobs that, frankly, involve a lot of churning analysis, and be able to say to a procurement specialist, okay, what used to take you six hours, or an hour, or what ever the task was, we can shrink that down using a cognitive tool, down to just a few minutes. So, procurement, we've been able to get staffing efficiencies, and we've been able, even more importantly, to make sure that we're buying things at the best possible price. Because those same analysts want to know what's happening in the market, where's the market sentiment going? Is this market tightening or loosening? Is it a buyer or a seller market? If we're trolling the web, bringing back information on the micro-movements of all the regional markets in various electronics commodities, we know an aggregate, whether we should be hard bargainers or easy bargainers, essentially. So, that's procurement. But, you could talk about human resources, where the Watson tool can recommend a game plan for how you would manage the career of a person. You don't want to lose your star people. And it's wonderful that deep, subject matter experts in HR know how to anticipate what you're thinking, and those are the people you want in charge of HR. But, there's a lot of other people who aren't, maybe, as good as that one person at HR, now the system can help you by giving you a playbook, making you a better HR manager. So, that's HR, but I got one more that's really exciting that I'm working on right now in the area of M&A. So, IBM and any large company that has multiple offerings and geographies is involved in M&A. We're using cognition and big data to speed up our M&A process. Now, we have a small team of M&A, so we're not going to make millions of dollars of staffing efficiencies, but, if we can capture a company, if we can be the first one to make an offer on a company, rather than the third one, then we're going to get the best company. And if you can bring the best company in, like The Weather Company as an example in that space, or like any other type of data-mining company or something, you want the best company. And if you can use cognition to enhance your process to move very quickly, that's going to really help you. >> So, this is a huge transformation of the business model, but then you've also talked about the cultural transformation of IBM. How would you describe this new IBM, going through this transformation? How would you describe the culture and collaboration? >> So, luckily, we're pretty far along in the transformation and we're at a stage where we actually have a data platform that's been deployed internally. And, people know about the potential of cognition to redefine and remake their business processing, create all this value. So, now we're getting people to come on to the platform as citizen analysts, if you want to call them that, they're not operations PhD's, they're not necessarily data scientists, they're regular business analysts. They're coming onto the platform and they're finding data and they're finding tools to manipulate that data. They're coming in on a self-service model and being able to gain insights to bring back into their business decisions without the CIO office being involved. >> So that's a workbench on the Cloud, essentially, is that right? >> Yes, that it a good way to put it, yep. >> Workbench, we out of trademark that. (laughs) >> Let's do that. >> Good descriptor, I think. >> Well, Joe, thanks so much for joining us, it's been a pleasure talking to you. >> My pleasure, thank you. >> Thanks, thanks a lot. >> I'm Rebecca Knight, for Dave Vellante, we will have more from IBM CDO Summit just after this.