>>Hey guys. Welcome back to Detroit, Michigan. Lisa Martin and John Furrier here live with the cube at Coan Cloud Native Con North America. John, it's been a great day. This is day one of our coverage of three days of coverage. Kubernetes is growing up. Yeah, it's maturing. >>Yeah. We got three days of wall to wall coverage, all about Kubernetes. We about security, large scale, cloud native at scale. That's the big focus. This next segment's gonna be really awesome. You have a fast growing private company and a practitioner, big name, blue chip practitioner, building out next NextGen Cloud first, transforming, then building out the next level. This is classic of what we call super cloud-like, like interview. It's gonna be great. I'm looking forward >>To this anytime we can talk about Super Cloud. All right, please welcome back. One of our alumni, Bani is here, the CEO of Rafe. Great to see you Santos. Ula also joins us, the global head of Cloud SRE at Mass Mutual. Ge. Great to have you on the program. Thanks >>For having us. Thank you for having me. >>So Steve, you've been on the queue many times. You were on just recently with the momentum that that's around us today with the maturation of Kubernetes, the collaboration of the community, the recognition of the community. What are some of the things that you're excited about with on, on day one of the show? >>Wow, so many new companies. I mean, there are companies that I don't know who are here. And I, I, I live in this industry and I'm seeing companies that I don't know, which is a good thing. I mean, it means that the, the community's growing. But at the same time, I'm also seeing another thing, which is I have met more enterprise representatives at this show than other coupons. Like when we hung out at, you know, in Valencia for example, or even, you know, other places. It hasn't been this many people, which means, and this is, this is a good thing that enterprises are now taking Kubernetes seriously. It's not a toy. It's not just for developers. It's enterprises who are now investing in Kubernetes as a foundational component, right. For their applications going forward. And that to me is very, very good. >>Definitely becoming foundational. >>Yep. Well, you guys got a great traction. We had many interviews at the Cube and you got a practitioner here with you. You guys are both pioneering kind of what I call the next gen cloud. First you gotta get through gen one, which you guys done at Mass Mutual, extremely well, take us through the story of your transformation. Cause you're on the, at the front end now of that next inflection point. But take us through how you got here. You had a lot of transformation success at Mass Mutual. >>So I was actually talking about this topic few, few minutes back, right? And, and the whole cloud journey in big companies, large financial institutions, healthcare industry or, or our insurance sector. It takes generations of leadership to get, to get to that perfection level. And, and ideally the, the, the cloud for strategy starts in, and then, and then how do you, how do you standardize and optimize cloud, right? You know, that that's, that's the second gen altogether. And then operationalization of the cloud. And especially if, you know, if you're talking about Kubernetes, you know, in the traditional world, you know, almost every company is running middleware and their applications in middleware. And then containerization is a topic that come, that came in. And docker is, is you know, basically the runtime containerization. So that came in first and from Docker, you know, eventually when companies started adopting Docker, Docker Swarm is one of the technologies that they adopted. And eventually when, when, when we were taking it to a more complicated application implementations or modernization efforts, that's when Kubernetes played a key role. And, and Hasi was pointing out, you know, like you never saw so many companies working on Kubernetes. So that should tell you one story, right? How fast Kubernetes is growing and how important it is for your cloud strategy. So, >>And your success now, and what are you thinking about now? What's on your agenda now as you look forward? What's on your plate? What are you guys doing right now? >>So we are, we are past the stage of, you know, proof of concepts, proof of technologies, pilot implementations. We are actually playing it, you know, the real game now. So in the past I used the quote, you know, like, hello world to real world. So we are actually playing in the real world, not, not in the hello world anymore. Now, now this is where the real time challenges will, will pop up, right? So if you're talking about standardizing it and then optimizing the cloud and how do you put your governance structure in place? How do you make sure your regulations are met? You know, the, the, the demands that come out of regulations are met and, and how, how are you going to scale it and, and, and while scaling, however you wanna to keep up with all the governance and regulations that come with it. So we are in that stage today. >>Has Steve talked about, you talked about the great evolution of what's going on at Mass Mutual has talked a little bit about who, you mentioned one of the things that's surprising you about this Coan and Detroit is that you're seeing a lot more enterprise folks here who, who's deciding in the organization and your customer conversations, Who are the deci decision makers in terms of adoption of Kubernetes these days? Is that elevating? >>Hmm. Well this guy, >>It's usually, you know, one of the things I'm seeing here, and John and I have talked about this in the past, this idea of a platform organization and enterprises. So consistently what I'm seeing is, you know, somebody, a cto, CIO level, you know, individual is making a determin decision. I have multiple internal buss who are now modernizing applications. They're individually investing in DevOps. And this is not a good investment for my business. I'm going to centralize some of this capability so that we can all benefit together. And that team is essentially a platform organization and they're making Kubernetes a shared services platform so that everybody else can come and, and, and sort of, you know, consume it. So what that means to us is our customer is a platform organization and their customer is a developer. So we have to make two constituencies successful. Our customer who's providing a multi-tenant platform, and then their customer who's a developer, both have to be happy. If you don't solve for both, you know, constituencies, you're not gonna be >>Successful. You're targeting the builder of the infrastructure and the consumer of that infrastructure. >>Yes sir. It has to be both. Exactly. Right. Right. So, so that look, honestly, that it, it, you know, it takes iterations to figure these things out, right? But this is a consistent theme that I am seeing. In fact, what I would argue now is that every enterprise should be really stepping back and thinking about what is my platform strategy. Cuz if you don't have a platform strategy, you're gonna have a bunch of different teams who are doing different things and some will be successful and look, some will not be. And that is not good for business. >>Yeah. And, and stage, I wanna get to you, you mentioned that your transformation was what you look forward and your title, global head of cloud sre. Okay, so sre, we all know came from Google, right? Everyone wants to be like Google, but no one wants to be like Google, right? And no one is Google, Google's a unique thing. It's only one Google. But they had the dynamic and the power dynamic of one person to large scale set of servers or infrastructure. But concept is, is, is can be portable, but, but the situation isn't. So board became Kubernetes, that's inside baseball. So you're doing essentially what Google did at their scale you're doing for Mass Mutual. That's kind of what's happening. Is that kind of how I see it? And you guys are playing in there partnering. >>So I I totally agree. Google introduce, sorry, Ty engineering. And, and if you take, you know, the traditional transformation of the roles, right? In the past it was called operations and then DevOps ops came in and then SRE is is the new buzzword. And the future could be something like product engineering, right? And, and, and in this journey, you know, here is what I tell, you know, folks on my side like what worked for Google might not work for a financial company, might not work for an insurance company. So, so, so it's, it's okay to use the word sre, but but the end of the day that SRE has to be tailored down to, to your requirements and and, and the customers that you serve and the technology that you serve. Yep. >>And this is, this is why I'm coming back, this platform engineering. At the end of the day, I think SRE just translates to, you're gonna have a platform engineering team cuz you gotta enable developers to be producing more code faster, better, cheaper guardrails policy. So this, it's kind of becoming the, you serve the business, which is now the developers it used to serve the business Yep. Back in the old days. Hey, the, it serves the business. Yep. Which is a terminal, >>Which is actually true >>Now it the new, it serves the developers, which is the business. Which is the business. Because if digital transformation goes to completion, the company is the app. Yep. >>And the, you know, the, the hard line between development and operations, right? So, so that's thining down over the time, you know, like that that line might disappear. And, and, and that's where asari is fitting in. >>Yeah. And they're building platforms to scale the enablement up that what is, so what is the key challenges you guys are, are both building out together this new transformational direction? What's new and what's the same, The same is probably the business results, but what's the new dynamic involved in rolling it out and making people successful? You got the two constituents, the builders of the infrastructures and the consumers of the services on the other side. What's the new thing? >>So the new thing if, if I may go fast these, so the faster market to, you know, value, right? That we are bringing to the table. That's, that's very important. You know, business has an idea. How do you get that idea implemented in terms of technology and, and take it into real time. So that journey we have cut down, right? Technology is like Kubernetes. It makes, it makes, you know, an IT person's life so easy that, that they can, they can speed up the process in, in, in a traditional way. What used to take like an year or six months can be done in a month today or or less than that, right? So, so there's definitely the losses, speed, velocity, agility in general, and then flexibility. And then the automation that we put in, especially if you have to maintain like thousands of clusters, you know, these, these are today like, you know, it is possible to, to make that happen with a click off a button. In the past it used to take like, you know, probably, you know, a hundred, a hundred percent team and operational team to do it. And a lot of time. But, but, but that automation is happening. You know, and we can get into the technology as much as possible. But, but, you know, blueprinting and all that stuff made >>It possible. Well say that for another interview, we'll do it take time. >>But the, the end user on the other end, the consumer doesn't have the patience that they once had. Right? Right. It's, I want this in my lab now. Now, how does the culture of Mass Mutual, how is it evolv to be able to deliver the velocity that your customers are demanding? >>So if once in a while, you know, it's important to step yourself into the customer's shoes and think it from their, from their, from their perspective, business does not care how you're running your IT shop. What they care about is your stability of the product and the efficiencies of the product and, and, and how, how, how easy it is to reach out to the customers and how well we are serving the customers, right? So whether I'm implementing Docker in the background, Dr. Swam or es you know, business doesn't even care about it. What they really care about it is if your environment goes down, it's a problem. And, and, and if you, if your environment or if your solution is not as efficient as the business needs, that's the problem, right? So, so at that point, the business will step in. So our job is to make sure, you know, from an, from a technology perspective, how fast you can make implement it and how efficiently you can implement it. And at the same time, how do you play within the guardrails of security and compliance. >>So I was gonna ask you if you have VMware in your environment, cause a lot of clients compare what vCenter does for Kubernetes is really needed. And I think that's what you guys got going on. I I can say that you're the v center of Kubernetes. I mean, as a, as an as an metaphor, a place to manage it all is all 1, 1 1 paint of glass, so to speak. Is that how you see success in your environment? >>So virtualization has gone a long way, you know where we started, what we call bare metal servers, and then we virtualized operating systems. Now we are virtualizing applications and, and we are virtualizing platforms as well, right? So that's where Kubernetes basically got. >>So you see the need for a vCenter like thing for Uber, >>Definitely a need in the market in the way you need to think is like, you know, let's say there is, there is an insurance company who actually mented it and, and they gain the market advantage. Right? Now the, the the competition wants to do it as well, right? So, so, so there's definitely a virtualization of application layer that, that, that's very critical and it's, it's a critical component of cloud strategy as >>A whole. See, you're too humble to say it. I'll say you like the V center of Kubernetes, Explain what that means and your turn. If I said that to you, what would you react? How would you react to that? Would say bs or would you say on point, >>Maybe we should think about what does vCenter do today? Right? It's, it's so in my opinion, by the way, well vCenter in my opinion is one of the best platforms ever built. Like ha it's the best platform in my opinion ever built. It's, VMware did an amazing job because they took an IT engineer and they made him now be able to do storage management, networking management, VMs, multitenancy, access management audit, everything that you need to run a data center, you can do from a single, essentially single >>Platform, from a utility standpoint home >>Run. It's amazing, right? Yeah, it is because you are now able to empower people to do way more. Well why are we not doing that for Kubernetes? So the, the premise man Rafa was, well, oh, bless, I should have IT engineers, same engineers now they should be able to run fleets of clusters. That's what people that mass major are able to do now, right? So to that end, now you need cluster management, you need access management, you need blueprinting, you need policy management, you need ac, you know, all of these things that have happened before chargebacks, they used to have it in, in V center. Now they need to happen in other platforms. But for es so should do we do many of the things that vCenter does? Yes. >>Kind >>Of. Yeah. Are we a vCenter for es? Yeah, that is a John Forer question. >>All right, well, I, I'll, the speculation really goes back down to the earlier speed question. If you can take away the, the complexity and not make it more steps or change a tool chain or do something, then the devs move faster and the service layer that serves the business, the new organization has to enable speed. So this, this is becoming a, a real discussion point in the industry is that, oh yeah, we've got new tool, look at the shiny new toy. But if it doesn't move the needle, does it help productivity for developers? And does it actually scale up the enablement? That's the question. So I'm sure you guys are thinking about this a lot, what's your reaction? >>Yeah, absolutely. And one thing that just, you know, hit my mind is think about, you know, the hoteling industry before Airbnb and after Airbnb, right? Or, or, or the taxi industry, you know, before Uber and after Uber, right? So if I'm providing a platform, a Kubernetes platform for my application folks or for my application partners, they have everything ready. All they need to do is like, you know, build their application and deployed and running, right? They, they, they don't have to worry about provisioning of the servers and then building the middleware on top of it and then, you know, do a bunch of testing to make sure, you know, they, they, they iron out all the, all the compatible issues and whatnot. Yeah. Now, now, today, all I, all I say is like, hey, you have, we have a platform built for you. You just build your application and then deploy it in a development environment. That's where you put all the pieces of puzzle together, make sure you see your application working, and then the next thing that, that you do is like, you know, you know, build >>Production, chip, build production, go and chip release it. Yeah, that's the nirvana. But then we're there. I mean, we're there now we're there. So we see the future. Because if you, if that's the case, then the developers are the business. They have to be coding more features, they have to react to customers. They might see new business opportunities from a revenue standpoint that could be creatively built, got low code, no code, headless systems. These things are happening where this I call the architectural list environment where it's like, you don't need architecture, it's already happening. >>Yeah. And, and on top of it, you know, if, if someone has an idea, they want to implement an idea real quick, right? So how do you do it? Right? And, and, and you don't have to struggle building an environment to implement your idea and testers in real time, right? So, so from an innovation perspective, you know, agility plays a key role. And, and that, that's where the Kubernetes platforms or platforms like Kubernetes >>Plays. You know, Lisa, when we talked to Andy Chasy, when he was the CEO of aws, either one on one or on the cube, he always said, and this is kind of happening, companies are gonna be builders where it's not just utility. You need that table stakes to enable that new business idea. And so he, this last keynote, he did this big thing like, you know, think like your developers are the next entrepreneurial revenue generators. And I think that, I think starting to see that, what do you think about that? You see that coming sooner than later? Or is that in, in sight or is that still ways away? >>I, I think it's already happening at a level, at a certain level now. Now the question comes back to, you know, taking it to the reality, right? Yeah. I mean, you can, you can do your proof of concept, proof of technologies, and then, and then prove it out. Like, Hey, I got a new idea. This idea is great. Yeah. And, and it's to the business advantage, right? But we really want to see it in production live where your customers are actually >>Using it and the board meetings, Hey, we got a new idea that came in, generating more revenue, where'd that come from? Agile developer. Again, this is real. Yeah, >>Yeah. >>Absolutely agree. Yeah. I think, think both of you gentlemen said a word in, in your, as you were talking, you used the word guardrails, right? I think, you know, we're talking about rigidity, but you know, the really important thing is, look, these are enterprises, right? They have certain expectations. Guardrails is key, right? So it's automation with the guardrails. Yeah. Guardrails are like children, you know, you know, shouldn't be hurt. You know, they're seen but not hurt. Developers don't care about guard rails. They just wanna go fast. They also bounce >>Around a little bit. Yeah. Off the guardrails. >>One thing we know that's not gonna slow down is, is the expectations, right? Of all the consumers of this, the Ds the business, the, the business top line, and of course the customers. So the ability to, to really, as your website says, let's see, make life easy for platform teams is not trivial. And clearly what you guys are talking about here is you're, you're really an enabler of those platform teams, it sounds like to me. Yep. So, great work, guys. Thank you so much for both coming on the program, talking about what you're doing together, how you're seeing the, the evolution of Kubernetes, why, and really what the focus should be on those platform games. We appreciate all your time and your insights. >>Thank you so much for having us. Thanks >>For our pleasure. For our guests and for John Furrier, I'm Lisa Martin. You're watching The Cube Live, Cobe Con, Cloud Native con from Detroit. We've out with our next guest in just a minute, so stick around.

>>From around the globe, but it's the cube presenting active DQ, intelligent automation for data quality brought to you by IO Tahoe. >>Now we're going to look at the role automation plays in mobilizing your data on snowflake. Let's welcome. And Duncan Turnbull who's partner sales engineer at snowflake and AIG Vihara is back CEO of IO. Tahoe is going to share his insight. Gentlemen. Welcome. >>Thank you, David. Good to have you back. Yeah, it's great to have you back >>A J uh, and it's really good to CIO Tao expanding the ecosystem so important. Um, now of course bringing snowflake and it looks like you're really starting to build momentum. I mean, there's progress that we've seen every month, month by month, over the past 12, 14 months, your seed investors, they gotta be happy. >>They are all that happy. And then I can see that we run into a nice phase of expansion here and new customers signing up. And now you're ready to go out and raise that next round of funding. I think, um, maybe think of a slight snowflake five years ago. So we're definitely on track with that. A lot of interest from investors and, um, we're right now trying to focus in on those investors that can partner with us, understand AI data and, and automation. >>So personally, I mean, you've managed a number of early stage VC funds. I think four of them, uh, you've taken several comp, uh, software companies through many funding rounds and growth and all the way to exit. So, you know how it works, you have to get product market fit, you know, you gotta make sure you get your KPIs, right. And you gotta hire the right salespeople, but, but what's different this time around, >>Uh, well, you know, the fundamentals that you mentioned though, those are never change. And, um, what we can say, what I can say that's different, that's shifted, uh, this time around is three things. One in that they used to be this kind of choice of, do we go open source or do we go proprietary? Um, now that has turned into, um, a nice hybrid model where we've really keyed into, um, you know, red hat doing something similar with Santos. And the idea here is that there is a core capability of technology that independence a platform, but it's the ability to then build an ecosystem around that made a pervade community. And that community may include customers, uh, technology partners, other tech vendors, and enabling the platform adoption so that all of those folks in that community can build and contribute, um, while still maintaining the core architecture and platform integrity, uh, at the core of it. >>And that's one thing that's changed was fitting a lot of that type of software company, um, emerge into that model, which is different from five years ago. Um, and then leveraging the cloud, um, every cloud snowflake cloud being one of them here in order to make use of what customers, uh, and customers and enterprise software are moving towards. Uh, every CIO is now in some configuration of a hybrid. Um, it is state whether those cloud multi-cloud on prem. That's just the reality. The other piece is in dealing with the CIO is legacy. So the past 15, 20 years they've purchased many different platforms, technologies, and some of those are still established and still, how do you, um, enable that CIO to make purchase while still preserving and in some cases building on and extending the, the legacy, um, material technology. So they've invested their people's time and training and financial investment into solving a problem, customer pain point, uh, with technology, but, uh, never goes out of fashion >>That never changes. You have to focus like a laser on that. And of course, uh, speaking of companies who are focused on solving problems, don't can turn bill from snowflake. You guys have really done a great job and really brilliantly addressing pain points, particularly around data warehousing, simplified that you're providing this new capability around data sharing, uh, really quite amazing. Um, Dunkin AAJ talks about data quality and customer pain points, uh, in, in enterprise. It, why is data quality been such a problem historically? >>Oh, sorry. One of the biggest challenges that's really affected by it in the past is that because to address everyone's need for using data, they've evolved all these kinds of different places to store all these different silos or data marts or all this kind of clarification of places where data lives and all of those end up with slightly different schedules to bringing data in and out. They end up with slightly different rules for transforming that data and formatting it and getting it ready and slightly different quality checks for making use of it. And this then becomes like a big problem in that these different teams are then going to have slightly different or even radically different ounces to the same kinds of questions, which makes it very hard for teams to work together, uh, on their different data problems that exist inside the business, depending on which of these silos they end up looking at and what you can do. If you have a single kind of scalable system for putting all of your data into it, you can kind of sidestep along to this complexity and you can address the data quality issues in a, in a single and a single way. >>Now, of course, we're seeing this huge trend in the market towards robotic process automation, RPA, that adoption is accelerating. Uh, you see, in UI paths, I IPO, you know, 35 plus billion dollars, uh, valuation, you know, snowflake like numbers, nice cops there for sure. Uh, agent you've coined the phrase data RPA, what is that in simple terms? >>Yeah, I mean, it was born out of, uh, seeing how in our ecosystem concern community developers and customers, uh, general business users for wanting to adopt and deploy a tar hose technology. And we could see that, um, I mean, there's not monkeying out PA we're not trying to automate that piece, but wherever there is a process that was tied into some form of a manual overhead with handovers and so on. Um, that process is something that we were able to automate with, with our ties technology and, and the deployment of AI and machine learning technologies specifically to those data processes almost as a precursor to getting into financial automation that, um, that's really where we're seeing the momentum pick up, especially in the last six months. And we've kept it really simple with snowflake. We've kind of stepped back and said, well, you know, the resource that a snowflake can leverage here is, is the metadata. So how could we turn snowflake into that repository of being the data catalog? And by the way, if you're a CIO looking to purchase a data catalog tool stop, there's no need to, um, working with snowflake, we've enable that intelligence to be gathered automatically and to be put, to use within snowflake. So reducing that manual effort, and I'm putting that data to work. And, um, and that's where we've packaged this with, uh, AI machine learning specific to those data tasks. Um, and it made sense that's, what's resonated with, with our customers. >>You know, what's interesting here, just a quick aside, as you know, I've been watching snowflake now for awhile and, and you know, of course the, the competitors come out and maybe criticize why they don't have this feature. They don't have that feature. And it's snowflake seems to have an answer. And the answer oftentimes is, well, its ecosystem ecosystem is going to bring that because we have a platform that's so easy to work with though. So I'm interested Duncan in what kind of collaborations you are enabling with high quality data. And of course, you know, your data sharing capability. >>Yeah. So I think, uh, you know, the ability to work on, on datasets, isn't just limited to inside the business itself or even between different business units. And we were kind of discussing maybe with their silos. Therefore, when looking at this idea of collaboration, we have these where we want to be >>Able to exploit data to the greatest degree possible, but we need to maintain the security, the safety, the privacy, and governance of that data. It could be quite valuable. It could be quite personal depending on the application involved. One of these novel applications that we see between organizations of data sharing is this idea of data clean rooms. And these data clean rooms are safe, collaborative spaces, which allow multiple companies or even divisions inside a company where they have particular, uh, privacy requirements to bring two or more data sets together for analysis. But without having to actually share the whole unprotected data set with each other, and this lets you to, you know, when you do this inside of snowflake, you can collaborate using standard tool sets. You can use all of our SQL ecosystem. You can use all of the data science ecosystem that works with snowflake. >>You can use all of the BI ecosystem that works with snowflake, but you can do that in a way that keeps the confidentiality that needs to be presented inside the data intact. And you can only really do these kinds of, uh, collaborations, especially across organization, but even inside large enterprises, when you have good reliable data to work with, otherwise your analysis just isn't going to really work properly. A good example of this is one of our large gaming customers. Who's an advertiser. They were able to build targeting ads to acquire customers and measure the campaign impact in revenue, but they were able to keep their data safe and secure while doing that while working with advertising partners, uh, the business impact of that was they're able to get a lifted 20 to 25% in campaign effectiveness through better targeting and actually, uh, pull through into that of a reduction in customer acquisition costs because they just didn't have to spend as much on the forms of media that weren't working for them. >>So, ha I wonder, I mean, you know, with, with the way public policy shaping out, you know, obviously GDPR started it in the States, you know, California, consumer privacy act, and people are sort of taking the best of those. And, and, and there's a lot of differentiation, but what are you seeing just in terms of, you know, the government's really driving this, this move to privacy, >>Um, government public sector, we're seeing a huge wake up an activity and, uh, across the whole piece that, um, part of it has been data privacy. Um, the other part of it is being more joined up and more digital rather than paper or form based. Um, we've all got stories of waiting in line, holding a form, taking that form to the front of the line and handing it over a desk. Now government and public sector is really looking to transform their services into being online, to show self service. Um, and that whole shift is then driving the need to, um, emulate a lot of what the commercial sector is doing, um, to automate their processes and to unlock the data from silos to put through into those, uh, those processes. Um, and another thing I can say about this is they, the need for data quality is as a Dunkin mentions underpins all of these processes, government pharmaceuticals, utilities, banking, insurance, the ability for a chief marketing officer to drive a, a loyalty campaign. >>They, the ability for a CFO to reconcile accounts at the end of the month. So do a, a, uh, a quick, accurate financial close. Um, also the, the ability of a customer operations to make sure that the customer has the right details about themselves in the right, uh, application that they can sell. So from all of that is underpinned by data and is effective or not based on the quality of that data. So whilst we're mobilizing data to snowflake cloud, the ability to then drive analytics, prediction, business processes off that cloud, um, succeeds or fails on the quality of that data. >>I mean it, and, you know, I would say, I mean, it really is table stakes. If you don't trust the data, you're not gonna use the data. The problem is it always takes so long to get to the data quality. There's all these endless debates about it. So we've been doing a fair amount of work and thinking around this idea of decentralized data, data by its very nature is decentralized, but the fault domains of traditional big data is that everything is just monolithic and the organizations monolithic technology's monolithic, the roles are very, you know, hyper specialized. And so you're hearing a lot more these days about this notion of a data fabric or what calls a data mesh. Uh, and we've kind of been leaning in to that and the ability to, to connect various data capabilities, whether it's a data warehouse or a data hub or a data Lake that those assets are discoverable, they're shareable through API APIs and they're governed on a federated basis. And you're using now bringing in a machine intelligence to improve data quality. You know, I wonder Duncan, if you could talk a little bit about Snowflake's approach to this topic. >>Sure. So I'd say that, you know, making use of all of your data, is there a key kind of driver behind these ideas that they can mesh into the data fabrics? And the idea is that you want to bring together not just your kind of strategic data, but also your legacy data and everything that you have inside the enterprise. I think I'd also like to kind of expand upon what a lot of people view as all of the data. And I think that a lot of people kind of miss that there's this whole other world of data they could be having access to, which is things like data from their business partners, their customers, their suppliers, and even stuff that's more in the public domain, whether that's, you know, demographic data or geographic or all these kinds of other types of data sources. And what I'd say to some extent is that the data cloud really facilitates the ability to share and gain access to this both kind of between organizations inside organizations. >>And you don't have to, you know, make lots of copies of the data and kind of worry about the storage and this federated, um, you know, idea of governance and all these things that it's quite complex to kind of manage this. Uh, you know, the snowflake approach really enables you to share data with your ecosystem all the world, without any latency with full control over what's shared without having to introduce new complexities or having complex attractions with APIs or software integration. The simple approach that we provide allows a relentless focus on creating the right data product to meet the challenges facing your business today. >>So, Andrea, the key here is to don't get to talking about it in my mind. Anyway, my cake takeaway is to simplicity. If you can take the complexity out of the equation, we're going to get more adoption. It really is that simple. >>Yeah, absolutely. Do you think that that whole journey, maybe five, six years ago, the adoption of data lakes was, was a stepping stone. Uh, however, the Achilles heel there was, you know, the complexity that it shifted towards consuming that data from a data Lake where there were many, many sets of data, um, to, to be able to cure rate and to, um, to consume, uh, whereas actually, you know, the simplicity of being able to go to the data that you need to do your role, whether you're in tax compliance or in customer services is, is key. And, you know, listen for snowflake by auto. One thing we know for sure is that our customers are super small and they're very capable. They're they're data savvy and know, want to use whichever tool and embrace whichever, um, cloud platform that is gonna reduce the barriers to solving. What's complex about that data, simplifying that and using, um, good old fashioned SQL, um, to access data and to build products from it to exploit that data. So, um, simplicity is, is key to it to allow people to, to, to make use of that data. And CIO is recognize that >>So Duncan, the cloud obviously brought in this notion of dev ops, um, and new methodologies and things like agile that brought that's brought in the notion of data ops, which is a very hot topic right now. Um, basically dev ops applies to data about how D how does snowflake think about this? How do you facilitate that methodology? >>Yeah, sorry. I agree with you absolutely. That they drops takes these ideas of agile development of >>Agile delivery and of the kind of dev ops world that we've seen just rise and rise, and it applies them to the data pipeline, which is somewhere where it kind of traditionally hasn't happened. And it's the same kinds of messages as we see in the development world, it's about delivering faster development, having better repeatability and really getting towards that dream of the data-driven enterprise, you know, where you can answer people's data questions, they can make better business decisions. And we have some really great architectural advantages that allow us to do things like allow cloning of data sets without having to copy them, allows us to do things like time travel so we can see what data looked like at some point in the past. And this lets you kind of set up both your own kind of little data playpen as a clone without really having to copy all of that data. >>So it's quick and easy, and you can also, again, with our separation of storage and compute, you can provision your own virtual warehouse for dev usage. So you're not interfering with anything to do with people's production usage of this data. So the, these ideas, the scalability, it just makes it easy to make changes, test them, see what the effect of those changes are. And we've actually seen this. You were talking a lot about partner ecosystems earlier. Uh, the partner ecosystem has taken these ideas that are inside snowflake and they've extended them. They've integrated them with, uh, dev ops and data ops tooling. So things like version control and get an infrastructure automation and things like Terraform. And they've kind of built that out into more of a data ops products that, that you can, you can make yourself so we can see there's a huge impact of, of these ideas coming into the data world. >>We think we're really well-placed to take advantage to them. The partner ecosystem is doing a great job with doing that. And it really allows us to kind of change that operating model for data so that we don't have as much emphasis on like hierarchy and change windows and all these kinds of things that are maybe use as a lot of fashioned. And we kind of taking the shift from this batch data integration into, you know, streaming continuous data pipelines in the cloud. And this kind of gets you away from like a once a week or once a month change window, if you're really unlucky to, you know, pushing changes, uh, in a much more rapid fashion as the needs of the business change. >>I mean, those hierarchical organizational structures, uh, w when we apply those to begin to that, what it actually creates the silos. So if you're going to be a silo Buster, which aji look at you guys in silo busters, you've got to put data in the hands of the domain experts, the business people, they know what data they want, if they have to go through and beg and borrow for a new data sets, et cetera. And so that's where automation becomes so key. And frankly, the technology should be an implementation detail, not the dictating factor. I wonder if you could comment on this. >>Yeah, absolutely. I think, um, making the, the technologies more accessible to the general business users >>Or those specialists business teams that, um, that's the key to unlocking is it is interesting to see is as people move from organization to organization where they've had those experiences operating in a hierarchical sense, I want to break free from that and, um, or have been exposed to, um, automation, continuous workflows, um, change is continuous in it. It's continuous in business, the market's continuously changing. So having that flow across the organization of work, using key components, such as get hub, similar to what you drive process Terraform to build in, um, code into the process, um, and automation and with a high Tahoe leveraging all the metadata from across those fragmented sources is, is, is good to say how those things are coming together. And watching people move from organization to organization say, Hey, okay, I've got a new start. I've got my first hundred days to impress my, my new manager. >>Uh, what kind of an impact can I, um, bring to this? And quite often we're seeing that as, you know, let me take away the good learnings from how to do it, or how not to do it from my previous role. And this is an opportunity for me to, to bring in automation. And I'll give you an example, David, you know, recently started working with a, a client in financial services. Who's an asset manager, uh, managing financial assets. They've grown over the course of the last 10 years through M and a, and each of those acquisitions have bought with it tactical data. It's saying instead of data of multiple CRM systems now multiple databases, multiple bespoke in-house created applications. And when the new CIO came in and had a look at those well, you know, yes, I want to mobilize my data. Yes, I need to modernize my data state because my CEO is now looking at these crypto assets that are on the horizon and the new funds that are emerging that around digital assets and crypto assets. >>But in order to get to that where absolutely data underpins and is the core asset, um, cleaning up that, that legacy situation mobilizing the relevant data into the Safelite cloud platform, um, is where we're giving time back, you know, that is now taking a few weeks, whereas that transitioned to mobilize that data, start with that, that new clean slate to build upon a new business as a, a digital crypto asset manager, as well as the legacy, traditional financial assets, bonds stocks, and fixed income assets, you name it, uh, is where we're starting to see a lot of innovation. >>Yeah. Tons of innovation. I love the crypto examples and FTS are exploding and, you know, let's face it, traditional banks are getting disrupted. Uh, and so I also love this notion of data RPA. I, especially because I've done a lot of work in the RPA space. And, and I want to, what I would observe is that the, the early days of RPA, I call it paving the cow path, taking existing processes and applying scripts, get letting software robots, you know, do its thing. And that was good because it reduced, you know, mundane tasks, but really where it's evolved is a much broader automation agenda. People are discovering new, new ways to completely transform their processes. And I see a similar, uh, analogy for data, the data operating model. So I'm wonder whenever you think about that, how a customer really gets started bringing this to their ecosystem, their data life cycles. >>Sure. Yeah. So step one is always the same is figuring out for the CIO, the chief data officer, what data do I have, um, and that's increasingly something that they want towards a mate, so we can help them there and, and do that automated data discovery, whether that is documents in the file, share backup archive in a relational data store, in a mainframe really quickly hydrating that and bringing that intelligence, the forefront of, of what do I have, and then it's the next step of, well, okay. Now I want to continually monitor and curate that intelligence with the platform that I've chosen. Let's say snowflake, um, in order such that I can then build applications on top of that platform to serve my, my internal, external customer needs and the automation around classifying data reconciliation across different fragmented data silos, building that in those insights into snowflake. >>Um, as you say, a little later on where we're talking about data quality, active DQ, allowing us to reconcile data from different sources, as well as look at the integrity of that data. Um, so they can go on to remediation, you know, I, I wanna, um, harness and leverage, um, techniques around traditional RPA. Um, but to get to that stage, I need to fix the data. So remediating publishing the data in snowflake, uh, allowing analysis to be formed performance snowflake. Th those are the key steps that we see and just shrinking that timeline into weeks, giving the organization that time back means they're spending more time on their customer and solving their customer's problem, which is where we want them to be. >>This is the brilliance of snowflake actually, you know, Duncan is, I've talked to him, then what does your view about this and your other co-founders and it's really that focus on simplicity. So, I mean, that's, you, you picked a good company to join my opinion. So, um, I wonder if you could, you know, talk about some of the industry sectors that are, again, going to gain the most from, from data RPA, I mean, traditional RPA, if I can use that term, you know, a lot of it was back office, a lot of, you know, financial w what are the practical applications where data RPA is going to impact, you know, businesses and, and the outcomes that we can expect. >>Yes, sir. So our drive is, is really to, to make that, um, business general user's experience of RPA simpler and, and using no code to do that, uh, where they've also chosen snowflake to build that their cloud platform. They've got the combination then of using a relatively simple script scripting techniques, such as SQL, uh, without no code approach. And the, the answer to your question is whichever sector is looking to mobilize their data. Uh, it seems like a cop-out, but to give you some specific examples, David, um, in banking where, uh, customers are looking to modernize their banking systems and enable better customer experience through, through applications and digital apps. That's where we're, we're seeing a lot of traction, uh, and this approach to, to pay RPA to data, um, health care, where there's a huge amount of work to do to standardize data sets across providers, payers, patients, uh, and it's an ongoing, um, process there for, for retail, um, helping to, to build that immersive customer experience. >>So recommending next best actions, um, providing an experience that is going to drive loyalty and retention, that's, that's dependent on understanding what that customer's needs intent, uh, being out to provide them with the content or the outfit at that point in time, or all data dependent utilities is another one great overlap there with, with snowflake where, you know, helping utilities, telecoms energy, water providers to build services on that data. And this is where the ecosystem just continues to, to expand. If we, if we're helping our customers turn their data into services for, for their ecosystem, that's, that's exciting. And they were more so exciting than insurance, which we always used to, um, think back to, uh, when insurance used to be very dull and mundane, actually, that's where we're seeing a huge amounts of innovation to create new flexible products that are priced to the day to the situation and, and risk models being adaptive when the data changes, uh, on, on events or circumstances. So across all those sectors that they're all mobilizing that data, they're all moving in some way, shape or form to a, a multi-cloud, um, set up with their it. And I think with, with snowflake and without Tahoe, being able to accelerate that and make that journey simple and as complex is, uh, is why we found such a good partner here. >>All right. Thanks for that. And then thank you guys. Both. We gotta leave it there. Uh, really appreciate Duncan you coming on and Aja best of luck with the fundraising. >>We'll keep you posted. Thanks, David. All right. Great. >>Okay. Now let's take a look at a short video. That's going to help you understand how to reduce the steps around your data ops. Let's watch.

>>Good afternoon and welcome back to our audience here in Asia pacific This is Sandeep again uh from my home studio in Singapore, I hope you found the session to be insightful. I thought it was a key takeaway in terms of how you know the the world is going through a massive transformation, driven by underpinning the workload optimized solutions around up by round of security, 3 60 degree security. As Neil Mcdonald talked about underpinned by the scale, you know, whether you're on exa scale, compute public cloud or on the edge and that's kind of underpinning the digital transformation that our customers are going to go through. I have two special guests with me. Uh let me just quickly introduce them Santos restaurant martin who uh is the Managing director for intel in A P. K. And Dorinda Kapoor, Managing Director for HB Initial pacific So, good afternoon, both you gentlemen. >>Good afternoon. >>So Santos. My first question is to you, first of all, a comment, you know, the passion at which uh, pad Kill Singer talked through the four superpowers. That was amazing. You know, I could see that passion comes through the screen. You know, I think everybody in the audience could relate with that. We are like, you know, as you know, on the words of the launch, the gentle plus by power, but it's isolate processor from intel, what are you seeing and what do our customers should expect improvements, especially with regard to the business outcomes. >>Yeah, So first of all, thank you so much for having me in this session and, and as you said, Sandeep, I mean, you could really see how energized we are. And you heard that from pad as well. Uh, so we launched the third gen, intel, Xeon processors or isolate, you know about a couple of weeks ago and I'm sure, you know, there's lots of benefits that you get in these new products. But I thought what I'll do is I'll try and summarize them in three key buckets. The first one is about the performance benefits that these new products bring in. The 2nd 1 is the value of platforms and I think the last pieces about the partnerships and how it makes deployment really easy and simple for our customers. Let me start with the first one which is about performance and the and the big jump that we're staying. It's about a 46% performance, increased generation over generation. It's flexible, it's optimized performance from the edge to the cloud where you would see about 1.5 to 1.7 X improvements on key war clouds like the cloud five G I O D HPC and AI that are so critical all around us. It's probably the only data center processor that has built in A I acceleration that helps with faster analytics. It's got security optimist on intel SGX that basically gives you a secure on cliff when when sensitive data is getting transacted and it also has crypto acceleration that reduces any performance impact because of the pervasive encryption that we have all around us. Now The second key benefit is about platform and if you remember when we launch sky lake in 2017, we laid out a strategy that said that we are here to help customers >>move, >>store and process data. So it's not just the CPU that we announced with the third genitals, jOHn Announcements. We also announce products like the obtained persistent memory, 200 cds That gives you about a 32 higher memory bandwidth and six terabytes of memory capacity on stock. It the obtain S S D S, the intel internet, 800 cities adapter that gives you about 200 Gbps per port, which means you can move data much more faster and you have the intellectual X F P G s that gives you about a double the better fabric performance for what? Which means if there's key workloads that you want to go back and offloaded to a to a steak or a specific uh CPU then you have the F P G s that can really help you there Now. What does the platform do for our customers? It helps them build higher application and system level performance that they can all benefit from the last b which is the partnerships area is a critical one because we've had decades of experience of solution delivery with a broad ecosystem and with partners like HP and we build elements like the Intel select solution and the market ready solution that makes it so much more easier for our customers to deploy with Over 50 million Xeon scalable processes that is shipped around the world. A billion Xeon cores that are powering the cloud since 2013 customers have really a proven solution that they can work with. So in summary, I want you to remember the three key piece that can really >>help you be >>successful with these new products, the performance uplifted, you get generation over generation, the platform benefits. So it's not just the CPU but it's things around that that makes the system and the application work way better. And then the partnerships that give you peace of mind because you can go deploy proven solutions that you can go and implement in your organization and serve your customers better. >>Thanks. Thanks thanks and Tosha for clearly outlining, you know, the three PS and kind of really resonates well. Um, so let me just uh turn over you know, to Dorinda there in the hot, you know, there's a lot of new solutions, you're our new treaties that santos talked about security, you get a lot of performance benefits and yet our customers have to go through a massive amount of change from a digital transformation perspective in order that they take all the advantages in state competitive. We're using HP Iran addressing the needs for the challenges of our customers and how we really helping them accelerate their transformation journey. >>Yeah, sure. Sandeep, thanks a lot for the question. And you are right. Most of the businesses actually need to go uh digital transformation in order to stay relevant in the current times. And in fact actually COVID-19 has further accelerated the pace of digital transformation for uh most of our customers. And actually the digital transformation is all about delivering differentiated experiences and outcomes at the age by converting data collected from multiple different sources to insights and actions. So we actually an HP believe that enterprise of the future is going to be eight centric data driven and cloud enabled And with our strategy of providing H2 cloud platform and having a complete portfolio of uh software, networking computer and the storage solutions both at the age and court uh to of course collect, transmit secure, analyze and store data. I believe we are in the best position to help our customers start and execute on their transformation journey. Now reality is various enterprises are at different stages of their transformation journey. You know, uh we in HP are able to help our customers who are at the early stage or just starting the transformation journey to to help build their transformation broad maps with the help of our advisory teams and uh after that helped them to execute on the same with our professional services team. While for the customers who are already midway in the transformation journey, we have been helping them to differentiate themselves by delivering workload optimized solutions which provide latency, flexibility and performance. They need to turn data into insights and innovations to help their business. Now, speaking of the workload optimized solutions, HP has actually doubled down in this area with the help of our partners like Intel, which powers our latest Gentlemen plus platform. This brings more compute power, memory and storage capacity which our customers need as they process more data and solve more complex challenges within their business. >>Thank you. Thanks. And er in there I think that's really insightful. Hopefully you know our customer base, I will start joined in here, can hear that and take advantage of you know, how HP is helping you know, fast track the exploration. I come back to you something you don't like during the talk about expanding capacities and we saw news about you know Intel invest $20 billion dollars or so, something like that in terms of you know, adding capacities or manufacturing. So I'd like to hear from your perspective, you know how this investments which intel is putting is a kind of a game changer, how you're shaping the industry as we move forward. >>Yeah, I mean as we all know, I think there's accelerated demand for semiconductors across the world digitization especially in an environment that we're that we're going through has really made computing pervasive and it's it's becoming a foundation of every industry and our society, the world just needs more semiconductors. Intel is in a unique position to rise to that occasion and meet the growing demand for semiconductors given our advanced manufacturing scale that we have. So the intel foundry services and the that you mentioned is is part of the Intel's new I. D. M. Torrado strategy that Bad announced which is a differentiated winning formula that will really deliver the new era of innovation, manufacturing and product leadership. We will expand our manufacturing capacity as you mentioned with that 20 billion investments and building to fabs in Arizona. But there's more to come in the year ahead and these fans will support the expanding requirements of our current products and also provide committed capacity for our foundry customers. Our foundry customers will also be able to leverage our leading edge process, the treaty packaging technology, a world class I. P. Portfolio. So >>I'm really really >>excited. I think it's a truly exciting time for our industry. The world requires more semiconductors and Intel is stepping in to help build the same. >>Fantastic, fantastic. Thank you. Some potion is really heartening to know and we really cherish the long partnership, HP and Intel have together. I look forward that you know with this gentleman plus launch and the partnership going forward. You know, we have only motivation and work together. Really appreciate your taking the time and joining and thank you very much for joining us. >>Thank you. >>Thanks. >>Okay, so with that I will move on to our second segment and in white, another special guest and this is Pete Chambers who is the managing director for A N D N A P K. Good afternoon Pete. You can hear us Well >>I can. Thank you. Sandy, Great to be >>here. Good and thanks for joining me. Um I thought I just opened up, you know, like a comment around the 19 world Records uh, am D. N. H. We have together and it's a kind of a testament to the joint working model and relationship and the collaboration. And so again, really thank you for the partnership. We have any change. Uh, let me just quickly get to the first question. You know, when it comes to my mind listening over to what Antonio and Liza were discussing, you know, they're talking about there's a huge amount of flow of data. You know, the technology and the compute needs to be closer to where the data is being generated and how is A. M. D. You know, helping leverage some of those technologies to bring feature and benefits and driving outcome for customers here in asia. >>Yeah, as lisa mentioned, we're now in a high performance computing mega cycle driven by cloud computing, digital transformation five DNA. Which means that everyone needs and wants more computer IDC predicts that by 20 23/65 percent of the impact GDP will be digitized. So there's an inflection coming with digital transformation at the fall, businesses are ever increasingly looking for trusted partners like HP and HP and and to help them address and adapt to these complex emerging technologies while keeping their IT infrastructure highly efficient, you know, and is helping enable this transformation by bringing leadership performance such as high court densities, high PC and increased I. O. But at the same time offering the best efficiency and performance for what all third gen Epic. CPU support 100 and 28 lanes of superfast PC for connectivity to four terabytes of memory and multiple layers of security. You know, we've heard from our customers that security continues to be a key consideration, you know? And he continues to listen. And with third gen, Epic, we're providing a multitude of security features such as secure root of trust at the bios level which we work very closely with HP on secure encrypted virtualization, secure memory encryption and secure nested paging to really giving the customers confidence when designing Epic. We look very closely at the key workloads that our customers will be looking to enable. And we've designed Epic from the ground up to deliver superior experience. So high performance computing is growing in this region and our leadership per socket core density of up to 64 cause along with leading IO and high memory bandwidth provides a compelling solution to help solve customers most complex computational problems faster. New HP Apollo 6500 and 10 systems featuring third gen, Epic are also optimist for artificial intelligence capabilities to improve training and increased accuracy and results. And we also now support up to eight and instinct accelerators. In each of these systems, hyper converged infrastructure continues to gain momentum in today's modern data center and our superior core density helps deliver more VMS per CPU supported by a multitude of security virtualization features to provide peace of mind and works very closely with industry leaders in HD like HP but also Nutanix and VM ware to help simplify the customers infrastructure. And in recent times we've seen video. I have a resurgence as companies have looked to empower their remote employee remote employees. Third gen, Epic enables more video sessions per CPU providing a more cost optimized solution, simply put Epics higher core density per CPU means customers need fewer service. That means less space required, lower power and cooling expenditure and as a result, a tangibly lower total cost of ownership add to this the fact, as you mentioned that Andy Epic with HP of 19 world records across virtualization, energy efficiency, decision support, database workloads, etc. And service side java. And it all adds up to a very strong value proposition to encourage Cdos to embark on their next upgrade cycle with HP and Epic >>Interstate. Thank you Peter and really quite insightful. And I've just done that question over to Narendra Pete talked about great new technologies, new solution, new areas that are going to benefit from these technology enhancements at the same time. You know, if I'm a customer, I look at every time we talk about technology, you know, you need to invest and where is you know, the bigger concern for customers always wears this money will come from. So I want to uh, you know, uh, the if you share your insights, how is actually helping customers to be able to implement these technology solutions, giving them a financial flexibility so that they can drive business outcomes. >>Yes, and the very important point, you know, from how HP is able to help our customers from their transformation. Now, reality is that most of the traditional enterprises are being challenged by this new digital bond businesses who have no doubt of funding and very low expectation of profitability. But in reality, majority of the capital of these traditional enterprises has uh tied up in their existing businesses as they do need to keep current operations running while starting their digital transformation at the same time. This of course creates real challenges and funding their transformation. Now with HP, with our Green Lake Cloud services, we are able to help customers fund their transformation journey. Were instead of buying up front, customers pay only for what they consume as the scale. We are not only able to offer flexible consumption model for new investments but are also able to help our customers, you know, for monetize their capital, which is tied up in the old ICT infrastructure because we can buy back that old infrastructure and convert that into conception of frank. So while customers can continue to use those assets to run their current business and reality is HIV is the leader in the this as a service space and probably the only vendor to be able to offer as a service offering for all of our portfolio. Uh, if you look at the ideas prediction, 70 of the applications are not ready for public cloud and will continue to run in private environments in addition. And everybody talked about the beef for a I and you know, HPC as well as the edge and more and more workloads are actually moving to the edge where the public cloud will have for less and less a role to play. But when you look at the customers, they are more and more looking for a cloud, like business model for all the workloads, uh, that they're running outside the public cloud. Now, with our being like offering, we are able to take away all the complexity from customers, allowing them to run the workloads wherever they want. That means that the edge in the data center or in the cloud and consume in the way they want. In other words, we're able to provide cloud, like experience anytime, anywhere to our customers. And of course, all these Green Lake offerings are powered by our latest compute capabilities that HP has to offer. >>Thank you. Thank you, surrender. That's really, really, very insightful. I have a minute or two, so let me try to squeeze another question from your feet, you know, MD is just now introduced the third generation of epics and congratulations on that. How are you seeing that? Excellent. Helping you accelerate in this growth, in the impact? Uh, you know, the geography as as such. >>Sure, great question. And as I mentioned, you know, third gen Epic with me and and once again delivers industry leading solutions, bending the curve on performance efficiency and TCO helping more than ever to deliver along with HP the right technologies for today and tomorrow. You know, in the service space, it's not just about what you can offer today. You need to be able to predictably deliver innovation over the long term. And we are committed to doing just that, you know, and strategy is to focus on the customer. We continue to see strong growth both globally and in a pack in HPC cloud and Web tech manufacturing, Fc telco and public and government sectors are growth plan is focused on getting closer to our customers directly, engaging with HP and our partners and the end customer to help guide them on the best solution and assist them in solving their computing pain points cost effectively. A recent example of this is our partnership with palsy supercomputing center in Australia, where HP and M. D will be helping to provide some 200,000 cause across 1600 nodes and over 750 radio on instinct accelerators empowering scientists to solve today's most challenging problems. We have doubled ourselves and F8 teams in the region over the past year and will continue to invest in additional customer facing sales and technical people through 2021, you know, and has worked very closely with HP to co design and co developed the best technologies for our customers needs. We joined forces over seven years ago to prepare for the first generation of Epic at launch and you fast forward to today and it's great to see that HP now has a very broad range of Andy Epic servers spanning from the edge two extra scale. So we are truly excited about what we can offer the market in partnership with HP and feel that we offer a very strong foundation of differentiation for our channel partners to address their customers need to accelerate accelerate their digital transformation. Thank you. Sandy, >>thank you. Thanks Peter. And really it's been amazing partnering with the NDP here and thanks for your sponsorship on that. And together we want to work with you to create another 19 world records right from here in the issue. Absolutely. So with that we are coming to the end of the event. Really thanks for coming pete and to our audience here because the pig is being a great a couple of hours. I hope you all found these sessions very, very insightful. You heard from our worldwide experts as to where, you know, divorce, moving in terms of the transformation, what your hp is bringing to our compute workload optimized solutions which are going to go from regardless of what scale of computing you're using and wrapped around 3 60 security and then offer truly as a service experience. But before you drop off, I would like to request you to please scan the QR code you see on your screen and fill in the feedback form we have, you know, lucky draw for some $50 worth of vultures for the five lucky winners today. So please click up your phone and, you know, spend a minute or two and give us a feedback and thank you very much again for this wonderful day. And I wish everybody a great day. Thank you.

>>From around the globe covering Google cloud. Next on there. >>Hi, I'm Stu Miniman and this is the cube coverage of Google cloud. Next 20 on air it's week seven of nine. Google of course took their event that was supposed to be in person and Moscone, spread it out online. It's all available on demand. Every Tuesday they've been dropping it in the cube. We've got a great lineup that we're going to share with you of our coverage thought event. This is our analysis segment, joining me to help dig into where Google cloud is. Everything happening in the ecosystem. Having to bring in Dave Alante and John furrier, our co-founders co-CEOs and, uh, always hosts of the program, John and Dave. Uh, it was, uh, it was great last year being in the middle of the show floor, uh, with the whole team and the great glam beautiful booth that Google built well, we're remote, but we're still in the middle of all the topics, the big waves and everything like that. So thanks so much for joining me and look forward to digging into it. >>Hey Stu, great to see you remotely. We got to get these events back. His virtual events are nine weeks, three weeks for Ws all day events. DockerCon virtual orders, nobody ecosystem support. I mean, this is really an interesting time and I think Google has laid out an interesting experiment with their multi. I call it summer of cloud program nine weeks with just a sustained demand for your attention. It's going to been a challenge. >>The question always, John, can they keep their attention? John, you laid out, you know, the cube three 65 were, there is 365 days a year, help extract the signal from the noise, help engage with the community. So absolutely want to kind of peel back the onion and see what we think of the event. But let let's, let's start with Google. Dave, you know, you've been digging through the numbers as you always do. Uh, we're we're more than a year since Thomas Kurian came in and you know, what are you hearing? What's the data showing you as to, you know, where Google really sits in the marketplace? How are they doing >>Well still you're right. I mean, Thomas curious now I think he's about 18 months in and in one of my previous breaking analysis, I kind of laid out a four point plan for, for Google. And we can talk about sort of how they're doing there, but, but really the first one is product maturity and there's, there's a number of things that we can assess as it relates to product maturity. The second we talk about it all the time is, is, is go to market. I think the third one is really around differentiation. How does Google uniquely differentiate from the other cloud service providers? And I think the fourth and we saw this earlier this year with Looker is, you know, Google's got a war chest and you know, they can use that to really beef up the cloud. And I think if, if, if you, if you look at it, you know, Google's done a pretty good job with things like fed ramp. >>I mean, these are table stakes in the big cloud. You know, they're starting to do more things around SAP of VMware, uh, windows. I mean, again, these are basic things that you have to do as part of any large cloud provider. I think the other thing we talked about go to market, they've done a number of things there. Karen's really focused on partnerships. He wants to be a hundred percent channel, uh, at the same time they're hiring salespeople. I think they're up over 1500 salespeople right now, uh, which is, you know, we're getting there. I think it was less than that. Obviously when he came on, that's kind of the benchmark, although we don't really know exactly what, what the numbers are. They've kind of launched into public sector. They see what's happening with Amazon there, they see great opportunities. They see, you know, what, what Microsoft is doing. And so public sector, they have to put out bakeoffs so you gotta be in there and at differentiations still a lot of, okay, how can we leverage alphabet our search business and retail, our business and healthcare, um, and edge things like autonomous vehicles. There's, there's some opportunities there. And then as I said, they're doing some M and a two plus billion dollars for Looker, you know, great capability. So I think they're, they're executing on those four and we can talk about what that means in terms of, you know, revenue and position in the market. >>Well, yeah, Dave, maybe it makes sense to let let's, let's walk through the revenue, just so that people understand, you know, where they sit for the longest time it's been, you know, the number three or the number four where Alibaba said, uh, compared to them, but they are still far behind, uh, AWS and Azure. Uh, and have they been closing the gap at all? >>Well, if guys, if you could bring up that chart, that first one, uh, this is are, we really are estimates. You remember now AWS, every quarter gives us a clean number for their infrastructure as a service. And what we've got here is an estimate for full year 2018, 2019 that's calendar year, the growth rates, and then, uh, with a trailing 12 month view. And I think there's a couple of points here. One is you can see the growth. Google grew 89% last year. They were 70% in Q one 59% in Q two. So, so even though it's somewhat declining, they're growing faster than both Azure and AWS, of course, from a smaller base. I think the other thing, if you, if you go back and look at 2019, relative to AWS, Google was one 10th, the size of AWS. Now they're, you know, there's only eight X, so they're starting to close that gap, but still very much a, a quite a distance from the leaders. >>Yeah. Uh, John, maybe if we look at Google under Thomas Currian, of course there's been a real, uh, growth in hiring. So, you know, you're there in the Valley, John, we know lots of really smart people that have joined Google's great enterprise, uh, you know, pedigrees there as well as the ecosystem, uh, that, that wants to be able to partner with Google. You know, what are you seeing? What are you hearing? I like one of the interviews that you did, uh Suneel prody, uh, it was, it was the number two over at Nutanix. Uh, and now we've got an important role in Google cloud, >>Google hiring great people. I got to say, one of the things I'm impressed with is I've always liked the product people. They have great product chops. I'll ask the Google has come from a position of strength on the tech side being Google. Um, and, but the enterprise business is hard too, and they got to hire more enterprise DNA. They're trying to do that at the same time. They're trying to make the table stakes stuff done, move fast during the product side. And then at the same time, create the game changing product with like ant those for instance, um, and then have all those new features. So they're running as fast as they can. Um, they're building product as fast as they can. So you got, you know, developer and operator efficiency, which I love the strategy. However, when you run that fast, there's definitely debt. >>You take on both technical and market debt around trying to make a shortcut. So Google to me, the word in the Valley is great stuff with the people. Product is awesome, getting better, good product people, but still those enterprise features product reliability in terms of not sunsetting products early to, you know, making sure the right support levels are there. These are like the little details that make the difference between an enterprise player and someone who is essentially, you know, moving too fast, get new products being to agile. So yeah, it's a double edged sword for Google. We've said this all the time, but overall I'd give them a solid number three position and still haven't seen the breakout yet. I think ant those can be that if they keep pushing on this operator efficiency, but I just don't think the enterprise is ready for Google yet. And I think there's issues there. >>Yeah. John, you bring up a great point. I know the last couple of times we've been at the show, I feel like I'm scratching my head. It was like, wait, when did lift and shift become sexy? Yes, you want to meet the enterprises where they are, but how is that different from the message that we hear from Microsoft that we hear from AWS? Uh, one of the bigger announcements during the infrastructure week, uh, was about a new program, the rapid assessment and migration plan or ramp, uh, to help customers get from where they are, where they need to be. Uh, it's interesting because of course, if you, you know, for reinvent for years, we had all the systems integrators, helping customers move and migrate, uh, both AWS and Azure have lots of migration solutions out there. So, you know, how will Google differentiate themselves and make different there? >>Well, they don't, they don't really know. I mean, they have put stuff down on paper, but here's the problem that Google has to overcome to make it a truly a fast growing cloud player. They got to nail the product features that they need to be in the marketplace. And the ecosystem really wants to work with Google. I see retail is lay up for them and they're doubling down on that. They've got smart people working on this, but the ecosystem and adding product features are two major heavy lifts ecosystems about moneymaking. At the end of the day. I know that sounds kind of greedy in this era of empathy and missions and values, but at the end of the day, if you're not making your ecosystem money, which means keep products around support for a certain number of >>Years and have incentives economically for people to build software. They're not going to work on your platform. And I think Google needs to understand that. Clearly. I just don't see it. I mean, I just don't see people saying, I love Google so much. I'm making so much cash and success. Um, and they got some good products. You know, I, like I said, products on ecosystem are things they're going to ratchet up super fast. Well, there's a couple of places, a couple of partners they violated, like I said, durian wants to be a hundred percent channel-based channel fulfillment. And when you talk to the channel, they do tell you, yo Google there they're being aggressive. Deloitte, you know, they chart chart out as a big partner HCL. Now of course, those guys are all working with everybody, but they're starting to put resources around that in terms of training and certification. >>And of course, other, you know, much smaller resellers and partners. So that's, that's interesting, right? That being really super channel friendly, that's a differentiator to your point, John, that's making be do that because they're not coming from a position of strength channel. No, they are channel friendly. Can, you can say you're channel friendly, but if your product doesn't work, the channel will reject you instantly. They're, they're a, they're a tough critic and they need to have reliability. So again, this is not really a problem with Google. It's just a product is evolving fast at the same time, they're trying to roll out a channel. So if you want to have a good rental strategy, you gotta have a good one posture and programs, but the product has to be enabling and reliable. And if someone's building software on top of a cloud platform and stuff doesn't work or changes, that's more cost more cost means more training, more hiring. >>If someone leaves, how does it scale? These are like really important things around channel. Cause they have to sell to the customer and support their name's on the line. So again, channels and easy to say thing to do, but to actually do it with a product is hard. And I think Google has that challenge. And again, it's a challenge that they overcome. It will be a great opportunity. Well, and I think that's a good point because it wasn't, it was 2019 when I was like VMware SAP, full blown windows support. I mean, that's, that's really late to the game. And so as I say, product maturity is critical, but there are some, some winners there obviously in analytics, uh, I think big query as get, gets very, very high marks. So there's, there's some real pockets of, of, of positive positivity there. But you know, I would agree though, the maturity is a key factor for the channel to really go on. >>Well, right. If you look, John, you mentioned anthro Santos was the story last year. Uh, and it's, we're all talking about multicloud. Uh, much of the multi-cloud discussion has been, uh, due to Kubernetes. And if it wasn't for Google, we wouldn't have Kubernetes. The concern of course, is that Google took it, it open source. The CNCF took it as a foundation and customers went nuts with it and the other public cloud and even, you know, smaller cloud providers are getting as if not more value than Google is. So what you hear in the back channels, when you say, boy, Google brought this technology out district really help enable their platform. Well, AWS is still winning. AWS has plenty of solutions. They've got interesting things to get, you know, deep solutions, leveraging Kubernetes. Uh, and if you look at Google, they announced anthros last year, it's gone through some updates this year. >>Uh, you know, you both mentioned, uh, working with the partners. One of the things that jumped out at me, uh, there's now something called ant those attached clusters, which means that if I have somebody else's, you know, Kubernetes that is fully certified, I can, I can plug that in and work with Anthem. It was one of the gaps that I saw last year. You hear Google saying, we're partnering with VMware, we're partnering pivotal, but here's. And if you want to use OpenShift or PKS, you know, you need to come over to work with Anthem here. We are understanding that customers are going to have multiple environments and often multiple different Kubernetes solutions out there. Uh, you know, Dave, you mentioned like VMware, of course is a really important solution. VMware moving along and supporting more Kubernetes. Uh, and the, the update for the solution is the Google cloud VMware engine. >>And absolutely the number one use case they talked about is take your VMs, get them in the cloud and then start using those data and analytic services that are in the public cloud. So we're seeing some maturity here, but you know, Dave, if we look at the multicloud market, you know, it, Google's not the first company that typically comes to mind, you know, VMware, red hat, even Microsoft probably are a little bit higher on people's thoughts. You know, what have you been seeing? It's an area we've been spending a lot of time last couple of years hybrid and multicloud. >>Well, we have some data on this guys, if you would pull up that next graphic and this, this is observing data from our data partner ETR and what this shows on the vertical axis is the spending momentum. So are you spending more or less? And then it's really a net score, which in other words, to subtract the less from the morning when we have leftover that's, the vertical axis high is higher, is better. And then the horizontal axis is markets, bear really presence in the data set, and you can see the hyperscaler guys, you know, that's where you want to be Microsoft AWS. They're always sort of separating from the pack. You'd love to see Google. Is there a hyperscaler out there with those guys, but they're not one of the interesting things that we're seeing in the dataset Stu and John VMware cloud on AWS has really popped up. >>So this thing of this notion of hybrid as part of the cloud ecosystem and multi-cloud is really starting to have legs. And you can also see red hat with, with open shift and believe it or not even OpenStack as a telco, you see in that pop up as well as VMware cloud, which is comprises cloud foundation and other components. So you see that hybrid and multicloud zone. And I think, I think you got to put Google, you know, right there, you can see where IBM and Oracle are for just for context, they don't have the momentum, they don't have the market presence in cloud, but they have a cloud. So that's kind of how the landscape is. And I think Google, from a standpoint of ant dos, they, again, they have to be trying to be open, leverage their Coopernetties chops and try to differentiate from certainly AWS. I think your point is right on, I think Microsoft has a pretty strong story there, but Google's got a clean story and they're investing and I think it's a good position for them. Not as, not as good as the other two, but you're when you're coming from behind, you have to try to differentiate and they are. >>Yeah, well, Dave, you've always said the rich get richer when these markets, but now with COVID that they are getting richer. Amazon honestly, stock I'm billion trillion, $2 billion valuation for Apple Google on the cloud side. This is, I think that if they had more product leadership in certain areas, I think they'd be doing more, more with their cloud, but they have some IP that could come out of this post COVID growth strategy for them, where it could be a game changer. So if you look at security and you look at identity, and one of the things that caught my attention in the anthesis announcement was this, uh, this, uh, identity service that they have, which is like, uh, open ID kind of connect thing. Identity will be critical because Google has so much IP around, um, you know, um, user login information around the mobile on the mobile side. >>I mean, Jennifer Lynn on this many times that they could leverage that and really helped the edge secure. And from a user access standpoint, having identification in the Anthem would be great. And this whole modern application trend is kind of where the puck is going. So you're there kind of skating to that puck area. And also they're focused on operators. This multicloud thing hits a home run with operators, because if you can create an abstraction layer between multiple clouds and have this modern kind of top layer to it, you're in a good position, but the insiders here in Silicon Valley and in the industry that I talked, they were all saying that Google has huge IP in their network. They have a very solid network. So what's interesting to me, as a Google can take leverage some of those network pain points and then bring anthesis that connective tissue. They got a real opportunity, but they've got to pull it off, right? So covert hitting, probably the worst thing that could have happened to Google because they were just a couple feet from the goal line on this, on this market in terms of really exploding. But I think they're well positioned. I'm not down on Google at all. >>I think that, you know, I'm glad you brought that up, John, because I think Cove was a two edged sword for them. I just published last week in my breaking analysis this weekend, actually that there were three big tailwinds insecurity as a result of coal go away. And identity was one of those cloud of course, was, was the other one. And then endpoint security was the third. And so that's a, that's, that's a, you know, kind of good news for, for, for identity. The flip side of it is if you go back and look at where Amazon and Microsoft were in terms of their growth, relative to where Google is now, Amazon and Microsoft appear to have been growing larger. Now these things go in an S curve, you know, it's kind of an old guy that starts out slow and then gets really steep. So we may actually see Google accelerate. Uh, but >>I think you wait in that it may have to wait until after COVID. So it's really a Jewish store, good news on the identity side. And Google's well positioned, but necessarily bad news from a growth standpoint. Well, there's three areas to that. You know, you and I have been riffing on lately and we've, haven't published a lot yet because we're going to wait until we have our event cube con event in October. But there's three areas, I think ant those points too. And they even say this kind of in their own way, um, multicloud, which is customers, connecting customers anywhere and finding device and whatnot. So customer connection points, customer enterprises, improved developer, modernized developer, the developer market, and then three operators, three areas that are all moving trains. They're all shifting under their feet. So I think they're doing great on developer side because they have great traction. >>We've covered that with coop con and other areas have done amazing work operator efficiency, no problem. I think they got a lot of great credit there and are building and adding new stuff. It's the customer piece that's weak. They, I think they really got to continue to double down on what is the customer deployment, because let's face it, enterprise customers aren't as savvy as Google or the hyperscaler. So when you roll into main street enterprise, especially with Cova Dave, as you pointed out, are they sitting there really grokking Coobernetti's on bare metal? And at those they're like, shit, how do I keep my network alive? So it, I just think isn't a long yet operationally on the customer side. And I think that is a weakness, um, and on Google's formula and they got to just make that easier. >>Yeah, no, no great, great points there. Absolutely. In, in talking to a lot of the cloud customers, if they already have an existing relationship that's expanding or accelerating, that is a lot easier than choosing a new environment. So as Dave said, the rich get richer. Um, I mentioned that at, at the start, this is week seven of nine of what Google is doing. Um, we want to get both your, your viewpoints on this event, how they laid it out nine weeks, it's all done on demand. I know when they had the opening keynote, there was a decent rally point. You saw the usual Twitter stream out there. They had a nice median analyst program that kicked off at the beginning. For me personally, there's been some stuff that I've gone back infrastructure week. I watch this week for app modernization. There's definitely some announcements that I'm digging into, but I think overall what I see out there is people rallied at the beginning and then they kind of forgot that the event was going on. Um, you know, what are you seeing? You know, what, what's the new best practice on, you know, how long should an event be? How do you deliver it? How do you get engagement? >>Well, I mean, just to, you know, Tim, Dave will weigh in, but I'm pretty hardcore on my criticism of most of these virtual events, mainly because virtual event platforms and virtual event executions or whatnot, well known as a first kind of generation problem. No one's really been under this kind of disruption when they got to replicate their business value as quickly in an environment they weren't optimized or have the personnel for. So you're seeing a lot of gaps in these virtuals, kinda like multi-cloud and high, where you have tens of different definitions of how to do it. I think Google went to nine weeks cause they really didn't know what to do. And they left a lot of their ecosystem hanging out there because normally Google next is a huge show with great content presentations. Everything's up on YouTube anyway. So on demand is not a build value. >>The real value of Google next was the face to face interactions. The show floor, the ecosystem, the expo hall that is completely absent from the show here. And this is consistent with other events. And honestly, it's over nine weeks, Amazon re-invent, it's going to be over three weeks. And last year they had a music festival. How are they going to replicate that again, this is a huge negative shift for these vendors because they rely so much on these events to get the word out. So it's really hard. Um, so I, I I'm really impressed with the nine week program and the sense of kind of staging it out and kind of the summer of cloud, I would have done things a little bit differently if I was them in terms of making it more exciting, but it's just really difficult to command attention for the audience over nine weeks. >>And I think that's, if they had to go back and do a Mulligan, I would've, they would've probably would've done more activation around the digital rather than a bunch of on demand video. So at least I did something and didn't cancel now the good news is there's a slew of news. We can collaborate on, um, the virtual spaces, the internet. So people are talking, it's just that it's all distributed. No one knows who's there, right? So it's not like an industry event. It's just an online collection of videos like on YouTube. So I felt that lack of intimacy was probably my, my biggest critique. Um, but again, I think he just wanted to move forward and get this behind them. >>I think you nailed it, John. I mean, on the one hand they made it harder for themselves stretching it out over nine weeks. On the other hand, they kind of took the easy way out is putting it up on all on demand. I guess they have analyst programs too, but I felt like they, weren't certainly not even close to what you have in physical. And it's really hard to obviously replicate physical, but I've seen other programs where the intimacy with the analyst and the journalist was much higher and opportunities to have interactions with executives. I felt it was just a little bit removed, actually quite a bit removed would have loved to have seen just a more intimate one-on-one activity. Maybe not one-on-one, but, but one, one to many with a smaller group of analysts and journalists, I think that would have gone a long way. Um, and that, that was missing for me anyway. >>I mean, they could have done nine micro events every week with like a rallying point is to pointed out, um, just really a difficult, I mean, who, who was executing this event? I mean, they have an events team that's used to doing physical events, Moscone and whatever. It's just, they didn't, I don't think had the time to figure it out. Be honest with you. I mean, Google is a company known for search relevance, find what you're looking for and uh, organizing content. I just think they didn't do a good job at all. And I think I didn't have any much attention cycles to it because I was kind of keying in the news, but I didn't know where my friends were. Who's rallying is Stu there. I didn't even, do's tweeting, I'm not following it. Or I missed his tweet. So there's a lot of asynchronous, um, stuff going on with was no, you know, gravity around a community or ecosystem kind of moment where I could schedule an hour at 10 o'clock or multiple times >>Does the day to check in and go to the watering hole or some stuff, >>You know, hub or instance like that. So, you know, something that we're thinking a lot about David's, you know, and I think this is a moving, moving target, but what's clear is that you can create synchronicity and still have the asynchronous programs. So at least we learned that with the Docker con event that we did and the software that we're building. So, you know, virtual events, isn't about just the events, but what happens on inside the event, outside the event, after the event, I think people are too hung up on this. I got to have a portal walled garden model. So I think it's going to be a learning curve for everybody. And I think Google may or may not do nine weeks. We'll see what re-invent does with three weeks. How do you keep people's attention? But three weeks when they're not in Vegas? >>Well, you know, no, I think that physical or virtual, it's your opportunity to write the narrative, to set the tone or set the narrative. And you're seeing this with the conventions, with the political conventions, you know, they're, they're actually, you know, you don't necessarily watch the whole thing, but you get a good sense, you know, post virtual event, what the narrative is. And I think that's cause you know, the media picks it up and I think it's, it's imperative to really do a good job of interacting with the media. You know, the analysts, the ecosystem, the partners, I haven't talked to a ton of partners who have been totally engaged other than, you know, their one-on-one activity. So I think there's an opportunity there to, to really write that narrative, to set that narrative and keep it alive and that, that entices people to go back and watch the man. Then I didn't feel that hook here. >>Yeah, here's the problem that I see with has Google has this problem and Docker con did not have the problem and you know, self-serving, we did that software, but we designed it for this purpose. When I go to an event, you do guys too. But personally, when I go to an event face to face, I like to get a sense of what the collective group at the event is thinking. I fly there, I'm present. I can see the presentation. I can see the pack breakout sessions. I know it's not back. I can get a sense visually. And with my senses on what the collective voice of the group is at an event, does it suck? Is it good? How's the band? What it's, what's the hallway conversation. So I can feel that I had none of that with Google next. Okay. Like, I didn't know, five, no, I had no other than some random things on Twitter, I had no sense what the collective ecosystem thought of the event. >>And I think a lot of the events have that problem where you can do both. You could have the rallying moment where there's a group collective coming together and send people to do that and still have the asynchronous consumption, organizing the content. But that's one of the main benefits. What is what's, what's going on with it? What's the voice of this collective? How are people thinking about this? And who's there? Who can I connect with and maybe follow up with, I didn't feel that this was simply a bunch of videos posted fundamental. Yeah, absolutely. John, >>If you can't feel that energy, is there a Slack channel, is there some chat group, uh, is there some way that, that you can be involved? Uh, definitely a missed opportunity, especially Google's got great collaboration tools. They're tied into all of our calendars would have been something that they could, uh, make ways that we could engage and find out. All right, John and Dave, thank you so much for helping us, uh, you know, really dig through a lot, going on. As we said, this nine week event, uh, we we've got a playlist, uh, that we're, we're going to be broadcasting for some of the key executives. Got, got a lot of the news here. And after this week, which was at modernization, we do have a couple other interviews that will be, uh, coming out, uh, when we have them, but be sure to check out the cube.net, uh, for all the upcoming, as well as search, to be able to find the previous, uh, content there, reach out to at furrier at diva launch date, or meet at Stu for any feedback or comments. We'd love to get your feedback, especially in these times when we can't all be together. So thanks John and Dave for joining and I'm Stu Miniman. Thank you for watching the cube.

(upbeat music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. >> Hello everyone, welcome to theCUBE studio here in Palo Alto. I'm John Furrier your host of theCUBE. We're here introducing a new format for CUBE panel discussions, it's called Around theCUBE and we have a special segment here called Get Smart: Unpacking AI with some great with some great guests in the industry. Gene Santos, Professor of Engineering in College of Engineering Dartmouth College. Bob Friday, Vice President CTO at Mist at Juniper Company. And Ed Henry, Senior Scientist and Distinguished Member of the Technical Staff for Machine Learning at Dell EMC. Guys this is a format, we're going to keep score and we're going to throw out some interesting conversations around Unpacking AI. Thanks for joining us here, appreciate your time. >> Yeah, glad to be here. >> Okay, first question, as we all know AI is on the rise, we're seeing AI everywhere. You can't go to a show or see marketing literature from any company, whether it's consumer or tech company around, they all have AI, AI something. So AI is on the rise. The question is, is it real AI, is AI relevant from a reality standpoint, what really is going on with AI, Gene, is AI real? >> I think a good chunk of AI is real there. It depends on what you apply it to. If it's making some sort of decisions for you, that is AI that's blowing into play. But there's also a lot of AI left out there potentially is just simply a script. So, you know, one of the challenges that you'll always have is that, if it were scripted, is it scripted because, somebody's already developed the AI and now just pulled out all the answers and just using the answers straight? Or is it active learning and changing on its own? I would tend to say that anything that's learning and changing on its own, that's where you're having the evolving AI and that's where you get the most power from. >> Bob what's your take on this, AI real? >> Yeah, if you look at Google, What you see is AI really became real in 2014. That's when the AI and ML really became a thing in the industry and when you look why did it become a thing in 2014? It's really back when we actually saw TensorFlow, open source technology really become available. It's all that Amazon Compute story. You know, you look what we're doing here at Mist, I really don't have to worry about compute storage, except for the Amazon bill I get every month now. So I think you're really seeing AI become real, because of some key turning points in the industry. >> Ed, your take, AI real? >> Yeah, so it depends on what lens you want to kind of look at it through. The notion of intelligence is something that's kind of ill defined and depending how how you want to interpret that will kind of guide whether or not you think it's real. I tend to all things AI if it has a notion of agency. So if it can navigate its problem space without human intervention. So, really it depends on, again, what lens you kind of want to look at it through? It's a set of moving goalposts, right? If you take your smartphone back to Turing When he was coming up with the Turing test and asked them if this intelligent, or some value intelligent device was AI, would that be AI, to him probably back then. So really it depends on how you kind of want to look at it. >> Is AI the same as it was in 1988? Or has it changed, what's the change point with AI because some are saying, AI's been around for a while but there's more AI now than ever before, Ed we'll start with you, what's different with AI now versus say in the late 80s, early 90s? >> See what's funny is some of the methods that we're using aren't different, I think the big push that happened in the last decade or so has been the ability to store as much data as we can along with the ability to have as much compute readily disposable as we have today. Some of the methodologies I mean there was a great Wired article that was published and somebody referenced called, method called Eigenvector Decomposition they said it was from quantum mechanic, that came out in 1888 right? So it really a lot of the methodologies that we're using aren't much different, it's the amount of data that we have available to us that represents reality and the amount of compute that we have. >> Bob. >> Yeah so for me back in the 80s when I did my masters I actually did a masters on neural networks so yeah it's been around for a while but when I started Mist what really changed was a couple things. One is this modern cloud stack right so if you're going to have to build an AI solution really have to have all the pieces ingest tons of data and process it in real time so that is one big thing that's changed that we didn't have 20 years ago. The other big thing is we had access to all this open source TensorFlow stuff right now. People like Google and Facebook have made it so easy for the average person to actually do an AI project right? You know anyone here, anyone in the audience here could actually train a machine learning model over the weekend right now, you just have to go to Google, you have to find kind of the, you know they have the data sets you want to basically build a model to recognize letters and numbers, those data sets are on the internet right now and you personally yourself could go become a data scientist over the weekend. >> Gene, your take. >> Yeah I think also on top of that because of all that availability on the open software anybody can come in and start playing with AI, it's also building a really large experience base of what works and what doesn't work and because they have that now you can actually better define the problem you're shooting for and when you do that you increase you know what's going to work, what's not going to work and people can also tell you that on the part that's not going to work, how's it going to expand but I think overall though this comes back to the question of when people ask what is AI, and a lot of that is just being focused on machine learning and if it's just machine learning that's kind of a little limited use in terms of what you're classifying or not. Back in the early 80s AI back then is really what people are trying to call artificial general intelligence nowadays but it's that all encompassing piece. All the things that you know us humans can do, us humans can reason about, all the decision sequences that we make and so you know that's the part that we haven't quite gotten to but there is all the things that's why the applications that the AI with machine learning classification has gotten us this far. >> Okay machine learning is certainly relevant, it's been one of the most hottest, the hottest topic I think in computer science and with AI becoming much more democratized you guys mentioned TensorFlow, a variety of other open source initiatives been a great wave of innovation and again motivation, younger generations is easier to code now than ever before but machine learning seems to be at the heart of AI and there's really two schools of thought in the machine learning world, is it just math or is there more of a cognition learning machine kind of a thing going on? This has been a big debate in the industry, I want to get your guys' take on this, Gene is machine learning just math and running algorithms or is there more to it like cognition, where do you guys fall on this, what's real? >> If I look at the applications and look what people are using it for it's mostly just algorithms it's mostly that you know you've managed to do the pattern recognition, you've managed to compute out the things and find something interesting from it but then on the other side of it the folks working in say neurosciences, the first people working in cogno-sciences. You know I have the interest in that when we look at that, that machine learning does it correspond to what we're doing as human beings, now because the reason I fall more on the algorithm side is that a lot of those algorithms they don't match what we're often thinking so if they're not matching that it's like okay something else is coming up but then what do we do with it, you know you can get an answer and work from it but then if we want to build true human intelligence how does that all stack together to get to the human intelligence and I think that's the challenge at this point. >> Bob, machine learning, math, cognition is there more to do there, what's your take? >> Yeah I think right now you look at machine learning, machine learning are the algorithms we use, I mean I think the big thing that happened to machine learning is the neural network and deep learning, that was kind of a mild stepping stone where we got through and actually building kind of these AI behavior things. You know when you look what's really happening out there you look at the self driving car, what we don't realize is like it's kind of scary right now, you go to Vegas you can actually get on a driving bus now, you know so this AI machine learning stuff is starting to happen right before our eyes, you know when you go to the health care now and you get your diagnosis for cancer right, we're starting to see AI in image recognition really start to change how we get our diagnosis. And that's really starting to affect people's lives. So those are cases where we're starting to see this AI machine learning stuff is starting to make a difference. When we think about the AI singularity discussion right when are we finally going to build something that really has human behavior. I mean right now we're building AI that can actually play Jeopardy right, and that was kind of one of the inspirations for my company Mist was hey, if they can build something to play Jeopardy we should be able to build something answer questions on par with network domain experts. So I think we're seeing people build solutions now that do a lot of behaviors that mimic humans. I do think we're probably on the path to building something that is truly going to be on par with human thinking right, you know whether it's 50 years or a thousand years I think it's inevitable on how man is progressing right now if you look at the technologically exponential growth we're seeing in human evolution. >> Well we're going to get to that in the next question so you're jumping ahead, hold that thought. Ed, machine learning just math, pattern recognition or is there more cognition there to be had? Where do fall in this? >> Right now it's, I mean it's all math, so we collect something some data set about the world and then we use algorithms and some representation of mathematics to find some pattern, which is new and interesting, don't get me wrong, when you say cognition though we have to understand that we have a fundamentally flawed perspective on how maybe the one guiding light that we have on what intelligence could be would be ourselves right. Computers don't work like brains, brains are what we determine embody our intelligence right, computers, our brains don't have a clock, there's no state that's actually between different clock cycles that light up in the brain so when you start using words like cognition we end up trying to measure ourselves or use ourselves as a ruler and most of the methodologies that we have today don't necessarily head down that path. So yeah that's kind of how I view it. >> Yeah I mean stateless those are API kind of mindsets, you can't run Kubernetes in the brain. Maybe we will in the future, stateful applications are always harder than stateless as we all know but again when I'm sleeping, I'm still dreaming. So cognition in the question of human replacement. This has been a huge conversation. This is one, the singularity conversation you know the fear of most average people and then some technical people as well on the job front, will AI replace my job will it take over the world is there going to be a Skynet Terminator moment? This is a big conversation point because it just teases out what could be and tech for good tech for bad. Some say tech is neutral but it can be shaped. So the question is will AI replace humans and where does that line come from. We'll start with Ed on this one. What do you see this singularity discussion where humans are going to be replaced with AI? >> So replace is an interesting term, so there I mean we look at the last kind of Industrial Revolution that happened and people I think are most worried about the potential of job loss and when you look at what happened during the Industrial Revolution this concept of creative destruction kind of came about and the idea is that yes technology has taken some jobs out of the market in some way shape or form but more jobs were created because of that technology, that's kind of our one again lighthouse that we have with respect to measuring that singularity in and of itself. Again the ill defined definition, or the ill defined notion of intelligence that we have today, I mean when you go back and you read some of the early papers from psychologists from the early 1900s the experiment specifically who came up with this idea of intelligence he uses the term general intelligence as kind of the first time that all of civilization has tried to assign a definition to what is intelligent right? And it's only been roughly 100 years or so or maybe a little longer since we have had this understanding that's been normalized at least within western culture of what this notion of intelligence is so singularity this idea of the singularity is interesting because we just don't understand enough about the one measure ruler or yardstick that we have that we consider intelligence ourselves to be able to go and then embed that inside of a thing. >> Gene what's your thoughts on this, reasoning is a big part of your research you're doing a lot of research around intent and contextual, all these cool behavioral things you know this is where machines are there to augment or replace, this is the conversation, your view on this? >> I think one of the things with this is that that's where the downs still lie, if we have bad intentions, if we can actually start communicating then we can start getting the general intelligence yeah I mean sort of like what Ed was referring to how people have been trying to define this but I think one of the problems that comes up is that computers and stuff like that don't really capture that at this time, the intentions that they have are still at a low level, but if we start tying it to you know the question of the terminator moment to the singularity, one of the things is that autonomy, you know how much autonomy that we give to the algorithm, how much does the algorithm have access to? Now there could be you know just to be on an extreme there could be a disaster situation where you know we weren't very careful and we provided an API that gives full autonomy to whatever AI we have to run it and so you can start seeing elements of Skynet that can come from that but I also tend to come to analysis that hey even with APIs, while it's not AI, APIs a lot of that also we have the intentions of what you're going to give us to control. Then you have the AI itself where if you've defined the intentions of what it is supposed to do then you can avoid that terminator moment in terms of that's more of an act. So I'm seeing it at this point. And so overall singularity I still think we're a ways off and you know when people worry about job loss probably the closest thing that I think that can match that in recent history is the whole thing on automation, I grew up at the time in Ohio when the steel industry was collapsing and that was a trade off between automation and what the current jobs are and if you have something like that okay that's one thing that we go forward dealing with and I think that this is something that state governments, our national government something we should be considering. If you're going to have that job loss you know what better study, what better form can you do from that and I've heard different proposals from different people like, well if we need to retrain people where do you get the resources from it could be something even like AI job pack. And so there's a lot of things to discuss, we're not there yet but I do believe the lower, repetitive jobs out there, I should say the things where we can easily define, those can be replaceable but that's still close to the automation side. >> Yeah and there's a lot of opportunities there. Bob, you mentioned in the last segment the singularity, cognition learning machines, you mentioned deep learning, as the machines learn this needs more data, data informs. If it's biased data or real data how do you become cognitive, how do you become human if you don't have the data or the algorithms? The data's the-- >> I mean and I think that's one of the big ethical debates going on right now right you know are we basically going to basically take our human biases and train them into our next generation of AI devices right. But I think from my point of view I think it's inevitable that we will build something as complex as the brain eventually, don't know if it's 50 years or 500 years from now but if you look at kind of the evolution of man where we've been over the last hundred thousand years or so, you kind of see this exponential rise in technology right from, you know for thousands of years our technology was relatively flat. So in the last 200 years where we've seen this exponential growth in technology that's taking off and you know what's amazing is when you look at quantum computing what's scary is, I always thought of quantum computing as being a research lab thing but when you start to see VC's and investing in quantum computing startups you know we're going from university research discussions to I guess we're starting to commercialize quantum computing, you know when you look at the complexity of what a brain does it's inevitable that we will build something that has basic complexity of a neuron and I think you know if you look how people neural science looks at the brain, we really don't understand how it encodes, but it's clear that it does encode memories which is very similar to what we're doing right now with our AI machine right? We're building things that takes data and memories and encodes in some certain way. So yeah I'm convinced that we will start to see more AI cognizance and it starts to really happen as we start with the next hundred years going forward. >> Guys, this has been a great conversation, AI is real based upon this around theCUBE conversation. Look at I mean you've seen the evidence there you guys pointed it out and I think cloud computing has been a real accelerant with the combination of machine learning and open source so you guys have illustrated and so that brings up kind of the final question I'd love to get each of you's thought on this because Bob just brought up quantum computing which as the race to quantum supremacy goes on around the world this becomes maybe that next step function, kind of what cloud computing did for revitalizing or creating a renaissance in AI. What does quantum do? So that begs the question, five ten years out if machine learning is the beginning of it and it starts to solve some of these problems as quantum comes in, more compute, unlimited resource applied with software, where does that go, five ten years? We'll go start with Gene, Bob, then Ed. Let's wrap this up. >> Yeah I think if quantum becomes a reality that you know when you have the exponential growth this is going to be exponential and exponential. Quantum is going to address a lot of the harder AI problems that were from complexity you know when you talk about this regular search regular approaches of looking up stuff quantum is the one that allows you now to potentially take something that was exponential and make it quantum. And so that's going to be a big driver. That'll be a big enabler where you know a lot of the problems I look at trying to do intentions is that I have an exponential number of intentions that might be possible if I'm going to choose it as an explanation. But, quantum will allow me to narrow it down to one if that technology can work out and of course the real challenge if I can rephrase it into say a quantum program while doing it. But that's I think the advance is just beyond the step function. >> Beyond a step function you see. Okay Bob your take on this 'cause you brought it up, quantum step function revolution what's your view on this? >> I mean your quantum computing changes the whole paradigm right because it kind of goes from a paradigm of what we know, this binary if this then that type of computing. So I think quantum computing is more than just a step function, I think it's going to take a whole paradigm shift of you know and it's going to be another decade or two before we actually get all the tools we need to actually start leveraging quantum computing but I think that is going to be one of those step functions that basically takes our AI efforts into a whole different realm right? Let us solve another whole set of classic problems and that's why they're doing it right now because it starts to let you be able to crack all the encryption codes right? You know where you have millions of billions of choices and you have to basically find that one needle in the haystack so quantum computing's going to basically open that piece of the puzzle up and when you look at these AI solutions it's really a collection of different things going underneath the hood. It's not this one algorithm that you're doing and trying to mimic human behavior, so quantum computing's going to be yet one more tool in the AI toolbox that's going to move the whole industry forward. >> Ed, you're up, quantum. >> Cool, yeah so I think it'll, like Gene and Bob had alluded to fundamentally change the way we approach these problems and the reason is combinatorial problems that everybody's talking about so if I want to evaluate the state space of anything using modern binary based computers we have to kind of iteratively make that search over that search space where quantum computing allows you to kind of evaluate the entire search space at once. When you talk about games like AlphaGo, you talk about having more moves on a blank 19 by 19 AlphaGo board than you have if you put 1,000 universes on every proton of our universe. So the state space is absolutely massive so searching that is impossible. Using today's binary based computers but quantum computing allows you to evaluate kind of search spaces like that in one big chunk to really simplify the aspect but I think it will kind of change how we approach these problems to Bob and Gene's point with respect to how we approach, the technology once we crack that quantum nut I don't think will look anything like what we have today. >> Okay thank you guys, looks like we have a winner. Bob you're up by one point, we had a tie for second but Ed and Gene of course I'm the arbiter but I've decided Bob you nailed this one so since you're the winner, Gene you guys did a great job coming in second place, Ed good job, Bob you get the last word. Unpacking AI, what's the summary from your perspective as the winner of Around theCUBE. >> Yeah no I think you know from a societal point of view I think AI's going to be on par with kind of the internet. It's going to be one of these next big technology things. I think it'll start to impact our lives and people when you look around it it's kind of sneaking up on us, whether it's the self driving car the healthcare cancer, the self driving bus, so I think it's here, I think we're just at the beginnings of it. I think it's going to be one of these technologies that's going to basically impact our whole lives or our next one or two decades. Next 10, 20 years is just going to be exponentially growing everywhere in all our segments. >> Thanks so much for playing guys really appreciate it we have an inventor entrepreneur, Gene doing great research at Dartmouth check him out, Gene Santos at Dartmouth Computer Science. And Ed, technical genius at Dell, figuring out how to make those machines smarter and with the software abstractions growing you guys are doing some good work over there as well. Gentlemen thank you for joining us on this inaugural Around theCUBE unpacking AI Get Smart series, thanks for joining us. >> Thank you. >> Thank you. >> Okay, that's a wrap everyone this is theCUBE in Palo Alto, I'm John Furrier thanks for watching. (upbeat funk music)

>> live from Boston, Massachusetts. It's the queue covering your red. Have some twenty nineteen. You buy bread hat. >> Welcome back here to the >> B C E >> C. We're in Boston, Massachusetts, right. Had summit the six time around for us here. The Cube, proud to be a part of this event. Once again, along with student Eamon. I'm John Walls. And thank you for joining us here on the Cube. Continue our coverage. We're joined by Stormy Peters, who was the senior manager community lead at Red Hat and stormy. Good afternoon to you. Are you going after him? All right. So you think about you know I love that, you know, community lead. You know, in an open source based company. You like Red Hat. Your job is very simply expanded. Evolved ecosystem, Right? So So I mean, how are you? I guess using that that company culture that embedded culture to grow, I think it's already pretty well established. What are your reputation is for how open you guys are right to the community. And what have you What are you doing in terms of leveraging that and trying to expand on that reputation? >> Yeah. Our goal is to make sure we're supporting those upstream communities. So all of all of Red Hat software is open source, and we worked with a whole community of individuals and companies, and the upstream opens our software. And we want to make sure that we're not just contributing features that we want but that were a good player, that we're helping to make sure those communities air healthy. And so, for a number of the projects that were involved in, we actually assigned a fulltime community manager a community lead to help make sure that project is healthy. So we have someone on everything from stuff and Lester Toe fedora Toe Cooper Netease. I'm just making sure the community does, well, >> stormy. You actually did a session for analysts about about a month or so ago, and I've been involved with open source for about twenty years, and you said something that made me do a double take and had to rethink the way I look at this commune unity. And it was we used to think of open source as well. May be I worked on a project, or maybe I spent a little bit time on nights and weekends and it was just kind of giving of time. You said that a majority of people working in this, they've got day jobs that is contribution to this. It's, you know, we understand that companies like IBM and Red Hat and Google often will have that. But the majority of people that are contributing open source now that is their job or a major part of their job. Could you stand a little bit about You know, how we saw that shift? And it's just me that snuck up on. >> So I think it's stuck up on us, all of us. But I really do think it's a fundamental shift that we need to consider so that we can make sure that we're helping the ecosystem the best way possible. So when open Source first started, it was people in their free time. You know, Linus Torvalds had a project he wanted to work on. You had it, it's described. You wanted your desktop to run free software, and so you put your free time into it evenings and weekends. And if you've got a paid job, working on it like that was something to celebrate like that was everybody's dream. And these days, with software becoming more complicated, more complex, and the solutions are even bigger and greater with the cloud there more than a one person project. They're like multi people, multi company projects. And so more and more people are getting paid to work on them and they're getting forty hours a week paid time to work on these projects. They might give more, but they're getting a full time salary. And so how we include not just the individuals but the companies that are paying them to work on it, I think changes how our project's work. I think it's a huge opportunity, >> and I mean talk about that shift a little bit, if you would then and how that has, I would say mature the marketplace. But certainly it's altered the the flows of jobs and innovation and development and all that, because I kind of passed time before now full time and what comes with that? I mean, what challenges come with that we're all of a sudden It is Ah, little, it's it's a little more parent, if you will, right and that you're a little more evident in wherever you're working because it is a full time commitment outs no longer just a of casual or less than full time pursuit. >> Yeah, I think it's a good thing, but I do think adds challenges. So, for example, on boarding process, you used to know when you had an open source software project you've got. Someone was giving up on our two of their evening TTO. Learn your project so you had to make sure that getting started docks worked for them within twenty thirty minutes. Maybe these days, you know, it's really hard to install a lot of this software in twenty or thirty minutes, but someone's doing it is their day job. They're going to have a day or a week. So the on boarding process is different, which I think makes it harder for volunteers and easier for paid volunteers and paid so little a little hard to distinguish. But for people that have all day to do it, they have a little more time to get on board into the on boarding processes are take longer. I think the problem is that we can solve our more complex because someone can spend an entire week. They're not breaking their thought process up like evenings. They have, like, all day. They can work with teams across cos he can pull in lots more expertise. We have a special interest groups and projects like Santos on where we're pulling in different companies to work together. I'm so like we're working on an NFI save with Intel and others. I'm so you get you get more diversity of people that could work on it. That can dedicate more brainpower to in one one setting. >> You can't. Can you talk a little bit about? You've worked on foundations and you support foundations. Talk about special interest groups. It's pay broad and very diverse ecosystem. Sometimes the outside rose like, Oh, it's thie, open source community and like No, no, no. There is not the open source community, their communities and lots of overlap. And they work in Iraq, maybe give us a little bit of context and love to hear some examples of some of the things you're working on. >> Yes, I think the first point is like projects aren't there. How they worked. Their governance isn't isn't static like it's always changing, like you might start a project on your own in your free time and it grew and you convinced all of us to join you. And now there's twenty people working on it and you want to be able to go on vacation and then you want to leave somebody in charge. So do you give him maintainer status? Do you create a board and let people vote? So you create a foundation like someone offers you money? How do you take it like I do? You put it in your bank account. Er, do you have to start it like a nonprofit to take this money? So I think they're constantly evolving. So an example that I have is the foundation we created the set foundation thiss year last year. Recently, um, and stuff has been open. Source It was it was open source created by thinktank acquired by Red. How we created a board of advisors around it to keep all those companies involved. And it had evolved to the point where people wanted to give it money. And so it needed to be something. You know, these companies wanted to collaborate on marketing together, So we created this a foundation as ah directed funded clinics foundation and had, like thirty companies joined in the very beginning, so I think I don't know what the next stage herself will be, but they're always evolving like that. >> But so what does it do if you will? Self? How do you pick projects out if you have thirty? Voice is a lot of voice. Is a lot of people raising their hands and let's look at this. Look at that. You know how to govern that. How do you, ah, assign work? How does all that work in that kind of? That's a really open environment that you're trying to corral a little bit. >> So So we're not trying to corral. We're tryingto like we're >> organized. A better >> word. Better word. >> So that the foundation was was enable people to collaborate on the marketing side, mostly a money side they wanted to give money for, like Suffolk on event. That's happening in a couple of weeks. There's a big annual event they wanted to be able to do Seth days. I'm things that you want to give money to enable it was getting really complicated. Will you pay for the beer and I'LL pay for the food and you know we'LL do it that way. The stuff project technically is led by a group of volunteers will have paid jobs and there's a project lead person for each sub project. And then they have a monthly meeting of all of the the whole project. And then each of those sub projects has a weekly meeting and something that stuff doesn't I think, is really interesting as they record all of their team meetings like it's a video meeting and they record it and they put it on YouTube and people watch the like. I think that's awesome. But it helps them with the time zone problem to record the meeting and put it on YouTube. >> One of the other things that I find really fascinating is many enterprise Cos now you know, we know they're using open source, but they're contributing open source. I remember back the future of open source survey that was done is think it was like half of companies that you know we're using it are also contributing. What do you see? You know, we've talked to users of the show for many years, is toe You know why they see value and why'd you do it, but it would love to hear your take. >> So I do think cos air. They're using open source software, but they're contributing on DH. People talk about what you contribute, the features that you want to see, but I think you contribute to the things you find exciting and that you want to participate in contributions. Starts at like very beginning level of just filing a bug report when you see it are coming to an events and going to the happy hour for that for that project of seven Cluster have won this afternoon. This afternoon. You know there's different get togethers and you participate by meeting the people, telling them how you're using it. I'm telling them what you'd like to see What's cool. I think a lot of people in the open source world, there's an opportunity for the developers to be very close to the users in the way that's harder and proprietary software. And it's really exciting, like if you're working on something and someone comes up and says, Hey, I'm using it and here's what I like Peanuts. It's fun. >> It's working All right. >> How about career advancement? You know, everybody I know in the developer world. It's like, Well, get really is your resume these days? So I gotta imagine that just the skill set and the education is such a huge part for so many companies. >> Yeah, with more people getting paid to work on open source and they can show what they worked on on that it's more, not more coming. It's very easy to move to another job, taking your skill set with you and it's very valued and you even get to keep your community of people that you're working with as you move around and help different companies with that project. How do you >> divvy it up in a community where you know the workload is kind of equally shared? Or there's a fair share of work being done and you and you want to. Maybe some people have a different level of expertise on DH, so there's some policing that kind of has to be done or argus. Some responsibilities assign whatever >> that could be >> a little delicate. Sometimes candidates you won't get the right people doing the right things, and you'LL love, willingness and enthusiasm. But sometimes you do have to kind of decide are you gonna work on this? We're gonna work on that. >> So some projects have done a really excellent job of defining the rolls and assigning them and having like, a mentoring process to get new people there. So, for example, Cooper Netease on the release team, there's like people that worked on the release team. And then, if you're interested, you raise your hand and you like work with the the person that's in that role for, like, an entire release. And so you get like a whole released to be mentored and taught, and then the next year you're the person doing the release and you can mentor somebody else. So I think the process is help with that. And it's, I think there's some really great work. >> You're building the farm team basically right. You're bringing them along on training wheels to a certain degree and then let him ride the bike by themselves, yet makes sense. >> So speaking of getting people ready, there was something new announced this week that I'm hoping you could explain. The Red Hat Universal Base image was explained to me that this is really a subset, Terrell or being roll ready. What Does that mean? How is that going to impact developers? >> Yeah, the idea is to help developers developed in containers on Lenox and in a way that they can so the FBI is based on, Well, it's a subset of rela packages. It's a it's a container, so in the clouds face and that you can develop your app on it. And then you can share that container with anybody. Whether or not there are real user, I'm so you can share it with anybody in the world had them developed on it. But then, when you're done, it is supported on grell and open shift so you can have full enterprise support for that's >> a show like this. Inject new blood new perspective into what you do. But I would assume this is a pretty good recruiting opportunity to in a lot of respects. And you stay pretty busy over the course of these three days, meeting with a lot of new people, meeting a lot of new faces, getting a lot of new ideas, a house to show kind of fit into what you're going to do the other three hundred sixty two days in a year. >> Well, We look forward to this show for three hundred sixty four days a year, so we're always planning foreign prepping for it. It adds energy. It adds excitement. We get to connect with people. They're using the software. Hopefully, they do come to the happy hours or down to the booth and talk to us and say, Here's how we're using it. We hope to get more people involved. People that are using software that want to learn about it, get him more involved. >> Well, you've got a great job of pulling the community together. We wish you continued success in doing that. Thanks for the time today. Here in the Cube. Nice tohave you. >> Thank you very much for having >> that story. Peter is joining us from red hat back with more in just a little bit. You're watching the Red Hat Summit and you're watching exclusive coverage right here on the Q

>> fly from San Francisco. It's the Cube covering Google Cloud next nineteen, brought to you by Google Cloud and its ecosystem partners. >> Welcome back. This is Day three of Google Cloud. Next, you're watching the Cube, the leader in live tech coverage. The cube goes out to the events. We extract the signal from the noise. My name is Dave Volante. I'm here with my co host to minimum. John Farrier has been here >> all week. Wall to wall >> coverage, three days. Check out cube dot net for all the videos. Silicon angle dot com For all the news, Eric Brewer is here is the vice president of Infrastructure and a Google fellow. Dr Breuer, Thanks for coming on The Cube. >> Happy to be here to see >> you. So tell us the story of sort of infrastructure and the evolution at Google. And then we'll talk about how you're you're taking what you've learned inside a googol and helping customers apply it. >> Yeah, one or two things about Google is it essentially makes no use of virtual machines internally. That's because Google started in nineteen ninety eight, which is the same year that VM where started it was kind of brought the modern virtual machine to bear. And so good infrastructure tends to be built really on kind of classic Unix processes on communication. And so scaling that up, you get a system that works a lot with just prophecies and containers. So kind of when I saw containers come along with Doctor who said, Well, that's a good model for us and we could take what we know internally, which was called Boring a big scheduler and we could turn that into Cooper Netease and we'LL open source it. And suddenly we have kind of a a cloud version of Google that works the way we would like it to work a bit more about the containers and AP eyes and services rather than kind of the low level infrastructure. >> Would you refer from from that comment that you essentially had a cleaner sheet of paper when when containers started to ascend, I >> kind of feel like it's not an accident. But Google influenced Lena Lennox's use of containers right, which influenced doctors use of containers, and we kind of merged the two concepts on. It became a good way to deploy applications that separates the application from the underlying machine instead of playing a machine and OS and application together, we'd actually like to separate those and say we'LL manage the Western machine and let's just deploy applications independent of machines. Now we can have lots of applications for machine improved realization. Improve your productivity. That's kind of way we're already doing internally what was not common in the traditional cloud. But it's actually a more productive way to work, >> Eric. My backgrounds and infrastructure. And, you know, I was actually at the first doctor. Calm back in twenty fourteen, only a few hundred of us, you know, right across the street from where we were here. And I saw the Google presentation. I was like, Oh, my gosh, I lived through that wave of virtual ization, and the nirvana we want is I want to just be able to build my application, not worry about all of those underlying pieces of infrastructure we're making progress for. We're not there. How are we doing as an industry as a whole? And, you know, get Teo, say it's where are we? And what Google looking that Cooper, Netease and all these other pieces to improve that. What do you still see is the the the room for growth. >> Well, it's pretty clear that you Burnett is one in the sense that if you're building new applications for enterprise, that's currently the way you would build them now. But it doesn't help you move your legacy stuff on it for, say, help you move to the cloud. It may be that you have worth loads on Crim that you would like to modernize their on V EMS or bare metal, their traditional kind of eighties APS in Java or whatever. And how does Cooper Netease affect those? That's that's actually still place where I think things are evolving. The good news now is much easier to mix kind of additional services and new services using SDO and other things on GC people contain arising workloads. But actually it would say most people are actually just do the new stuff in Cooper Netease and and wrapped the old stuff to make it look like a service that gets you pretty far. And then over time you khun containerized workloads that you really care about. You want to invest in and what's new with an so so you can kind of make some of those transitions on fram. Ifyou'd like separate from moving to the cloud and then you can decide. Oh, this workload goes in the cloud. This work load. I need to keep on priming for awhile, but I still want to modernize it of a lot more flexibility. >> Can you just parts that a little bit for us? You're talking about the migration service that that's that's coming out? Or is it part of >> the way the Val Estrada work, which is kind of can take a V M A. Converted to a container? It's a newer version of that which really kind of gives you a A manifest, essentially for the container. So you know what's inside it. You can actually use it as in the modern way. That's migration tool, and it's super useful. But I kind of feel like even just being able to run high call the Communities on Crim is a pretty useful step because you get to developer velocity, you get released frequency. You get more the coupling of operations and development, so you get a lot of benefits on treme. But also, when you move to cloud, you could go too geeky and get a you know, a great community experience whenever you're ready to make that transition. >> So it sounds like that what you described with Santos is particularly on from pieces like an elixir to help people you know more easily get to a cloud native environment and then, ultimately, Brigitte to the >> class. That's kind of like we're helping people get cloud native benefits where they are right now. On a day on their own time. Khun decide. You know not only when to move a workload, but even frankly, which cloud to move it to right. We prefer, obviously moved to Google Cloud, and we'LL take our chances because I think these cattle native applications were particularly good at. But it's more important that they are moving to this kind of modern platform but helps them, and it increases our impact on the Indus. Sory to have this happen. >> Help us understand the nuance there because there's obvious benefits of being in the public cloud. You know, being able to rent infrastructure op X versus cap packs and manage services, etcetera. But to the extent that you could bring that cloud experience, Tio, you're on premises to your data. That's what many people want to have that hybrid experience for sure. But but other than that, the obvious benefits that I get from a public cloud, what are the other nuances of actually moving into the public cloud from experience standpoint in the business value perspective? >> Well, one question is, how much rewriting do you have to do because it's a big transition? Moved a cloud that's also big transition to rewrite some of your applications. So in this model, we're actually separating those two steps, and you can do them in either order. You can lift and shift to move to cloud and then modernize it, but it's also perfectly fine. I'm gonna modernize on Graham, read my do my rewrites in a safe controlled environment that I understand this low risk for me. And then I'm going to move it to the cloud because now I have something that's really ready for the cloud and has been thought through carefully that way on that having those two options is actually an important change. With Anthony >> Wavered some stats. I think Thomas mentioned them that eighty percent of the workloads are still on prams way here. That all the time. And some portion of those workloads are mission critical workloads with a lot of custom code that people really don't want to necessarily freeze. Ah, and a lot of times, if you gonna migrate, you have to free. So my question is, can I bring some of those Antos on other Google benefits to on Prem and not have to freeze the code, not have to rewrite just kind of permanently essentially, uh, leave those there and it take my other stuff and move it into the cloud? Is that what people are doing? And can I >> work? Things mix. But I would say the beachhead is having well managed Cooper and his clusters on Prem. Okay, you can use for new development or a place to do your read rights or partial read writes. You convicts V EMS and mainframes and Cooper Netease. They're all mix herbal. It's not a big problem, especially this to where it could make him look like they're part of the same service >> on framework, Right? >> S o. I think it's more about having the ability to execute modern development on prim and feel like you're really being able to change those acts the way you want and on a good timeline. >> Okay, so I've heard several times this week that Santos is a game changer. That's how Google I think is looking at this. You guys are super excited about it. So one would presume then that that eighty percent on Prem is gonna just gonna really start to move. What your thoughts on that? >> I think the way to think about it is all the customs you talked to actually do want to move there were close to cloud. That's not really the discussion point anymore. It's more about reasons they can't, which could be. They already have a data center. They fully paid for two. There's regulatory issues they have to get resolved to. This workload is too messy. They don't want to touch it at all. The people that wrote it are here anymore. There's all kinds of reasons and so it's gone. I feel like the essence of it is let's just interacted the customer right now before they make a decision about their cloud on DH, help them and in exchange for that, I believe we have a much better chance to be their future clown, right? Right, Because we're helping them. But also, they're starting to use frameworks that were really good at all. Right, if they're betting on coordinates containers, I like our chances for winning their business down the road. >> You're earning their trust by providing those those capabilities. >> That's really the difference. We can interact with those eighty percent of workloads right now and make them better. >> Alright. So, Eric, with you, the term we've heard a bunch this meat, we because we're listening customers where we're meeting them where they are now. David Iran analyst. So we could tell customers they suck out a lot stuff. You should listen to Google. They're really smart, and they know how to do these things, right? Hopes up. Tell us some of those gaps there is to the learnings you've had. And we understand. You know, migrations and modernization is a really challenging thing, you know? What are some of those things that customers can do toe >> that's on the the basic issues. I would say one thing you get you noticed when using geeky, is that huh? The os has been passed for me magically. All right, We had these huge security issues in the past year, and no one on G had to do anything right. They didn't restart their servers. We didn't tell them. Oh, you get down time because we have to deal with these massive security tax All that was magically handled. Uh, then you say, Oh, I want to upgrade Cooper Netease. Well, you could do that yourself. Guess what? It's not that easy to do. Who Burnett is is a beast, and it's changing quickly every quarter. That's good in terms of velocity and trajectory, and it's the reason that so many people can participate at the same time. If you're a group trying to run communities on Prem, it's not that easy to do right, So there's a lot of benefit Justin saying We update Custer's all the time. Wear experts at this way will update your clusters, including the S and the Cuban A's version, and we can give you modern ing data and tell you how your clusters doing. Just stuff. It honestly is not core to these customers, right? They want to focus on there advertising campaign or their Their oil and gas were close. They don't want to focus on cluster management. So that's really the second thing >> they got that operating model. If I do Antos in my own data center of the same kind of environment, how do we deal with things like, Well, I need to worry about change management testing at all my other pieces Most of the >> way. The general answer to that is, you use many clusters. You could have a thousand clusters on time. If you want that, there's good reason to do that. But one reason is, well, upgrade the clusters individually so you could say, Let's make this cluster a test cluster We'LL upgrade it first and we'LL tell you what broke. If anything, if you give us tests we can run the test on then once we're comfortable that the upgrade is working, we'LL roll it out to all your clusters. Automatic thing with policy changes. You want to change your quota management or access control. We can roll up that change in a progressive way so that we do it first on clusters that are not so critical. >> So I gotta ask a question. You software guy, Uh and you're approaching this problem from a real software perspective. There are no box. I don't see a box on DH there. Three examples in the marketplace as your stack er, Oracle Clouded customer and Amazon Outpost Where there's a box. A box from Google. Pure software. Why no box? Do you need a box? The box Guys say you gotta have that. You have a box? Yes, you don't have a box, >> There's it's more like I would say, You don't have to have a box >> that's ever box. Okay, that's >> because again all these customers sorting the data center because they already have the hardware, right. If they're going to buy new hardware, they might as well move to cloud the police for some of the customers. And it turns out we can run on. Most of their hardware were leveraging VM wear for that with the partnership we announced here. So that's generally works. But that being said, we also now partnerships with Dell and others about if you want a box Cisco, Dell, HP. You can Actually, we'LL have offerings that way as well, and there's certainly good reason to do that. You can get up that infrastructure will know it works well. It's been tested, but the bottom line is, uh, we're going to do both models. >> Yeah, okay. So I could get a full stack from hardware through software. Yet through the partnerships on there's Your stack, >> Right And it'll always come from Partners were really working with a partner model for a lot of these things because we honestly don't have enough people to do all the things we would like to do with these customers. >> And how important is it that that on Prem Stack is identical from homogeneous with what's in the public cloud? Is it really? It sounds like you're cooking growing, but their philosophies well, the software components have to be >> really at least the core pieces to be the same, like Uber Netease studio on a policy management. If youse open source things like my sequel or Kafka or elastic, those auto operate the same way as well, right? So that when you're in different environments, you really kind of get the feeling of one environment one stroll plane used. Now that being said, if you want to use a special feature like I want to use big query that's only available on Google Cloud right, you can call it but that stuff won't be portable. Likewise is something you want to use on Amazon. You can use it, and that part will be portable. But at least you'LL get the most. Your infrastructure will be consistent across the platforms. >> How should we think about the future? You guys, I mean, just without giving away, you know, confidential information, obviously not going to do that, but just philosophically, Were you going when you talk to customers? What should their mindset be? How should they repeat preparing for the future? >> Well, I think it's a few bets were making. So you know, we're happy to work on kind of traditional cloud things with Bush machines and discs and lots of classic stuff that's still important. It's still needed. But I would say a few things that are interesting that we're pushing on pretty hard won in general. This move to a higher level stack about containers and AP eyes and services, and that's Cuba nowadays and SDO and its genre. But then the other thing I think interesting is we're making a pretty fundamental bit on open source, and it's a it's a deeper bad, then others air making right with partnerships with open source companies where they're helping us build the manage version of there of their product on. So I think that's that's really going to lead to the best experience for each of those packages, because the people that developed that package are working on it right, and we will share revenue with them. So it's it's, uh, Cooper. What is open source? Tension flows open. Source. This is kind of the way we're going to approach this thing, especially for a hybrid and mostly cloud where they're really in my mind is no other way to do multi cloud other than open source because it's the space is too fast moving. You're not going to say, Oh, here's a standard FBI for multi cloud because whatever a pair you define is going to be obsolete in a quarter or two, right? What we're saying is, the standard is not particular standard per se. It's the collection of open source software that evolves together, and that's how you get consistency across the environment is because the code is the same and in fact there is a standard. But we don't even know what it is exactly right. It's it's implicit in the code, >> Okay, but so any other competitors say, Okay, we love open source, too, will embrace open stores. What's different about Google's philosophy? >> Well, first of all, you could just look at a very high level of contribution back into the open source packages, not just the ones that were doing. You can see we've contributed things like the community's trademark so that that means it's actually not a Google thing anymore. Belonged to the proud Native Reading Foundation. But also, the way we're trying to partner with open source projects is really to give them a path to revenue. All right, give them a long term future on DH. Expectation is, that makes the products better. And it also means that, uh, we're implicitly preferred partner because we're the ones helping them. All >> right, Eric, One of things caught our attention this week really kind of extending containers with things like cloud code and cloud run. You speak a little bit to that and you know directionally where that's going, >> Yeah, crowd runs one of my favorite releases of this week. Both the one God code is great, also, especially, it's V s code integration which is really nice for developers. But I would say the cloud run kind of says we can take you know, any container that has a kind of a stateless thing inside and http interface and make it something we can run for you in a very clean way. What I mean by that is you pay per call and in particular Well, listen twenty four seven and case it call comes But if no call comes, we're going to charge you zero, right? So we'll eat the cost of listening for your package to arrive. But if a packet arrives for you, we will magically make sure you're there in time to execute it on. If you get a ton of connections, we'll scale you up. We could have a thousand servers running your cloud run containers. And so what you get is a very easy deployment model That is a generalization. Frankly, of functions, you can run a function, but you also run not only a container with kind of a managed run time ap engine style, but also any arbitrary container with your own custom python and image processing libraries. Whatever you want, >> here are our last guest at Google Cloud next twenty nineteen. So thank you. And so put a bow on the show this year. Obviously got the bigger, better shiny er Mosconi Center. It's awesome. Definitely bigger crowd. You see the growth here, but but tie a bow. Tell us what you think. Take us home. >> I have to say it's been really gratifying to see the reception that anthrax is getting. I do think it is a big shift for Google and a big shift for the industry. And, uh, you know, we actually have people using it, so I kind of feel like we're at the starting line of this change. But I feel like it's it's really resonated well this week, and it's been great to watch the reaction. >> Everybody wants their infrastructure to be like Google's. This is one of the people who made it happen. Eric, Thanks very much for coming in the Cube. Appreciate. Pleasure. All right, keep right, everybody. We'Ll be back to wrap up Google Cloud next twenty nineteen. My name is David. Dante. Student meant John Furry will be back on set. You're watching. The cube will be right back