Robert Nishihara, Anyscale | CUBE Conversation
(upbeat instrumental) >> Hello and welcome to this CUBE conversation. I'm John Furrier, host of theCUBE, here in Palo Alto, California. Got a great conversation with Robert Nishihara who's the co-founder and CEO of Anyscale. Robert, great to have you on this CUBE conversation. It's great to see you. We did your first Ray Summit a couple years ago and congratulations on your venture. Great to have you on. >> Thank you. Thanks for inviting me. >> So you're first time CEO out of Berkeley in Data. You got the Databricks is coming out of there. You got a bunch of activity coming from Berkeley. It's like a, it really is kind of like where a lot of innovations going on data. Anyscale has been one of those startups that has risen out of that scene. Right? You look at the success of what the Data lakes are now. Now you've got the generative AI. This has been a really interesting innovation market. This new wave is coming. Tell us what's going on with Anyscale right now, as you guys are gearing up and getting some growth. What's happening with the company? >> Yeah, well one of the most exciting things that's been happening in computing recently, is the rise of AI and the excitement about AI, and the potential for AI to really transform every industry. Now of course, one of the of the biggest challenges to actually making that happen is that doing AI, that AI is incredibly computationally intensive, right? To actually succeed with AI to actually get value out of AI. You're typically not just running it on your laptop, you're often running it and scaling it across thousands of machines, or hundreds of machines or GPUs, and to, so organizations and companies and businesses that do AI often end up building a large infrastructure team to manage the distributed systems, the computing to actually scale these applications. And that's a, that's a, a huge software engineering lift, right? And so, one of the goals for Anyscale is really to make that easy. To get to the point where, developers and teams and companies can succeed with AI. Can build these scalable AI applications, without really you know, without a huge investment in infrastructure with a lot of, without a lot of expertise in infrastructure, where really all they need to know is how to program on their laptop, how to program in Python. And if you have that, then that's really all you need to succeed with AI. So that's what we've been focused on. We're building Ray, which is an open source project that's been starting to get adopted by tons of companies, to actually train these models, to deploy these models, to do inference with these models, you know, to ingest and pre-process their data. And our goals, you know, here with the company are really to make Ray successful. To grow the Ray community, and then to build a great product around it and simplify the development and deployment, and productionization of machine learning for, for all these businesses. >> It's a great trend. Everyone wants developer productivity seeing that, clearly right now. And plus, developers are voting literally on what standards become. As you look at how the market is open source driven, a lot of that I love the model, love the Ray project love the, love the Anyscale value proposition. How big are you guys now, and how is that value proposition of Ray and Anyscale and foundational models coming together? Because it seems like you guys are in a perfect storm situation where you guys could get a real tailwind and draft off the the mega trend that everyone's getting excited. The new toy is ChatGPT. So you got to look at that and say, hey, I mean, come on, you guys did all the heavy lifting. >> Absolutely. >> You know how many people you are, and what's the what's the proposition for you guys these days? >> You know our company's about a hundred people, that a bit larger than that. Ray's been going really quickly. It's been, you know, companies using, like OpenAI uses Ray to train their models, like ChatGPT. Companies like Uber run all their deep learning you know, and classical machine learning on top of Ray. Companies like Shopify, Spotify, Netflix, Cruise, Lyft, Instacart, you know, Bike Dance. A lot of these companies are investing heavily in Ray for their machine learning infrastructure. And I think it's gotten to the point where, if you're one of these, you know type of businesses, and you're looking to revamp your machine learning infrastructure. If you're looking to enable new capabilities, you know make your teams more productive, increase, speed up the experimentation cycle, you know make it more performance, like build, you know, run applications that are more scalable, run them faster, run them in a more cost efficient way. All of these types of companies are at least evaluating Ray and Ray is an increasingly common choice there. I think if they're not using Ray, if many of these companies that end up not using Ray, they often end up building their own infrastructure. So Ray has been, the growth there has been incredibly exciting over the, you know we had our first in-person Ray Summit just back in August, and planning the next one for, for coming September. And so when you asked about the value proposition, I think there's there's really two main things, when people choose to go with Ray and Anyscale. One reason is about moving faster, right? It's about developer productivity, it's about speeding up the experimentation cycle, easily getting their models in production. You know, we hear many companies say that they, you know they, once they prototype a model, once they develop a model, it's another eight weeks, or 12 weeks to actually get that model in production. And that's a reason they talk to us. We hear companies say that, you know they've been training their models and, and doing inference on a single machine, and they've been sort of scaling vertically, like using bigger and bigger machines. But they, you know, you can only do that for so long, and at some point you need to go beyond a single machine and that's when they start talking to us. Right? So one of the main value propositions is around moving faster. I think probably the phrase I hear the most is, companies saying that they don't want their machine learning people to have to spend all their time configuring infrastructure. All this is about productivity. >> Yeah. >> The other. >> It's the big brains in the company. That are being used to do remedial tasks that should be automated right? I mean that's. >> Yeah, and I mean, it's hard stuff, right? It's also not these people's area of expertise, and or where they're adding the most value. So all of this is around developer productivity, moving faster, getting to market faster. The other big value prop and the reason people choose Ray and choose Anyscale, is around just providing superior infrastructure. This is really, can we scale more? You know, can we run it faster, right? Can we run it in a more cost effective way? We hear people saying that they're not getting good GPU utilization with the existing tools they're using, or they can't scale beyond a certain point, or you know they don't have a way to efficiently use spot instances to save costs, right? Or their clusters, you know can't auto scale up and down fast enough, right? These are all the kinds of things that Ray and Anyscale, where Ray and Anyscale add value and solve these kinds of problems. >> You know, you bring up great points. Auto scaling concept, early days, it was easy getting more compute. Now it's complicated. They're built into more integrated apps in the cloud. And you mentioned those companies that you're working with, that's impressive. Those are like the big hardcore, I call them hardcore. They have a good technical teams. And as the wave starts to move from these companies that were hyper scaling up all the time, the mainstream are just developers, right? So you need an interface in, so I see the dots connecting with you guys and I want to get your reaction. Is that how you see it? That you got the alphas out there kind of kicking butt, building their own stuff, alpha developers and infrastructure. But mainstream just wants programmability. They want that heavy lifting taken care of for them. Is that kind of how you guys see it? I mean, take us through that. Because to get crossover to be democratized, the automation's got to be there. And for developer productivity to be in, it's got to be coding and programmability. >> That's right. Ultimately for AI to really be successful, and really you know, transform every industry in the way we think it has the potential to. It has to be easier to use, right? And that is, and being easier to use, there's many dimensions to that. But an important one is that as a developer to do AI, you shouldn't have to be an expert in distributed systems. You shouldn't have to be an expert in infrastructure. If you do have to be, that's going to really limit the number of people who can do this, right? And I think there are so many, all of the companies we talk to, they don't want to be in the business of building and managing infrastructure. It's not that they can't do it. But it's going to slow them down, right? They want to allocate their time and their energy toward building their product, right? To building a better product, getting their product to market faster. And if we can take the infrastructure work off of the critical path for them, that's going to speed them up, it's going to simplify their lives. And I think that is critical for really enabling all of these companies to succeed with AI. >> Talk about the customers you guys are talking to right now, and how that translates over. Because I think you hit a good thread there. Data infrastructure is critical. Managed services are coming online, open sources continuing to grow. You have these people building their own, and then if they abandon it or don't scale it properly, there's kind of consequences. 'Cause it's a system you mentioned, it's a distributed system architecture. It's not as easy as standing up a monolithic app these days. So when you guys go to the marketplace and talk to customers, put the customers in buckets. So you got the ones that are kind of leaning in, that are pretty peaked, probably working with you now, open source. And then what's the customer profile look like as you go mainstream? Are they looking to manage service, looking for more architectural system, architecture approach? What's the, Anyscale progression? How do you engage with your customers? What are they telling you? >> Yeah, so many of these companies, yes, they're looking for managed infrastructure 'cause they want to move faster, right? Now the kind of these profiles of these different customers, they're three main workloads that companies run on Anyscale, run with Ray. It's training related workloads, and it is serving and deployment related workloads, like actually deploying your models, and it's batch processing, batch inference related workloads. Like imagine you want to do computer vision on tons and tons of, of images or videos, or you want to do natural language processing on millions of documents or audio, or speech or things like that, right? So the, I would say the, there's a pretty large variety of use cases, but the most common you know, we see tons of people working with computer vision data, you know, computer vision problems, natural language processing problems. And it's across many different industries. We work with companies doing drug discovery, companies doing you know, gaming or e-commerce, right? Companies doing robotics or agriculture. So there's a huge variety of the types of industries that can benefit from AI, and can really get a lot of value out of AI. And, but the, but the problems are the same problems that they all want to solve. It's like how do you make your team move faster, you know succeed with AI, be more productive, speed up the experimentation, and also how do you do this in a more performant way, in a faster, cheaper, in a more cost efficient, more scalable way. >> It's almost like the cloud game is coming back to AI and these foundational models, because I was just on a podcast, we recorded our weekly podcast, and I was just riffing with Dave Vellante, my co-host on this, were like, hey, in the early days of Amazon, if you want to build an app, you just, you have to build a data center, and then you go to now you go to the cloud, cloud's easier, pay a little money, penny's on the dollar, you get your app up and running. Cloud computing is born. With foundation models in generative AI. The old model was hard, heavy lifting, expensive, build out, before you get to do anything, as you mentioned time. So I got to think that you're pretty much in a good position with this foundational model trend in generative AI because I just looked at the foundation map, foundation models, map of the ecosystem. You're starting to see layers of, you got the tooling, you got platform, you got cloud. It's filling out really quickly. So why is Anyscale important to this new trend? How do you talk to people when they ask you, you know what does ChatGPT mean for Anyscale? And how does the financial foundational model growth, fit into your plan? >> Well, foundational models are hugely important for the industry broadly. Because you're going to have these really powerful models that are trained that you know, have been trained on tremendous amounts of data. tremendous amounts of computes, and that are useful out of the box, right? That people can start to use, and query, and get value out of, without necessarily training these huge models themselves. Now Ray fits in and Anyscale fit in, in a number of places. First of all, they're useful for creating these foundation models. Companies like OpenAI, you know, use Ray for this purpose. Companies like Cohere use Ray for these purposes. You know, IBM. If you look at, there's of course also open source versions like GPTJ, you know, created using Ray. So a lot of these large language models, large foundation models benefit from training on top of Ray. And, but of course for every company training and creating these huge foundation models, you're going to have many more that are fine tuning these models with their own data. That are deploying and serving these models for their own applications, that are building other application and business logic around these models. And that's where Ray also really shines, because Ray you know, is, can provide common infrastructure for all of these workloads. The training, the fine tuning, the serving, the data ingest and pre-processing, right? The hyper parameter tuning, the and and so on. And so where the reason Ray and Anyscale are important here, is that, again, foundation models are large, foundation models are compute intensive, doing you know, using both creating and using these foundation models requires tremendous amounts of compute. And there there's a big infrastructure lift to make that happen. So either you are using Ray and Anyscale to do this, or you are building the infrastructure and managing the infrastructure yourself. Which you can do, but it's, it's hard. >> Good luck with that. I always say good luck with that. I mean, I think if you really need to do, build that hardened foundation, you got to go all the way. And I think this, this idea of composability is interesting. How is Ray working with OpenAI for instance? Take, take us through that. Because I think you're going to see a lot of people talking about, okay I got trained models, but I'm going to have not one, I'm going to have many. There's big debate that OpenAI is going to be the mother of all LLMs, but now, but really people are also saying that to be many more, either purpose-built or specific. The fusion and these things come together there's like a blending of data, and that seems to be a value proposition. How does Ray help these guys get their models up? Can you take, take us through what Ray's doing for say OpenAI and others, and how do you see the models interacting with each other? >> Yeah, great question. So where, where OpenAI uses Ray right now, is for the training workloads. Training both to create ChatGPT and models like that. There's both a supervised learning component, where you're pre-training this model on doing supervised pre-training with example data. There's also a reinforcement learning component, where you are fine-tuning the model and continuing to train the model, but based on human feedback, based on input from humans saying that, you know this response to this question is better than this other response to this question, right? And so Ray provides the infrastructure for scaling the training across many, many GPUs, many many machines, and really running that in an efficient you know, performance fault tolerant way, right? And so, you know, open, this is not the first version of OpenAI's infrastructure, right? They've gone through iterations where they did start with building the infrastructure themselves. They were using tools like MPI. But at some point, you know, given the complexity, given the scale of what they're trying to do, you hit a wall with MPI and that's going to happen with a lot of other companies in this space. And at that point you don't have many other options other than to use Ray or to build your own infrastructure. >> That's awesome. And then your vision on this data interaction, because the old days monolithic models were very rigid. You couldn't really interface with them. But we're kind of seeing this future of data fusion, data interaction, data blending at large scale. What's your vision? How do you, what's your vision of where this goes? Because if this goes the way people think. You can have this data chemistry kind of thing going on where people are integrating all kinds of data with each other at large scale. So you need infrastructure, intelligence, reasoning, a lot of code. Is this something that you see? What's your vision in all this? Take us through. >> AI is going to be used everywhere right? It's, we see this as a technology that's going to be ubiquitous, and is going to transform every business. I mean, imagine you make a product, maybe you were making a tool like Photoshop or, or whatever the, you know, tool is. The way that people are going to use your tool, is not by investing, you know, hundreds of hours into learning all of the different, you know specific buttons they need to press and workflows they need to go through it. They're going to talk to it, right? They're going to say, ask it to do the thing they want it to do right? And it's going to do it. And if it, if it doesn't know what it's want, what it's, what's being asked of it. It's going to ask clarifying questions, right? And then you're going to clarify, and you're going to have a conversation. And this is going to make many many many kinds of tools and technology and products easier to use, and lower the barrier to entry. And so, and this, you know, many companies fit into this category of trying to build products that, and trying to make them easier to use, this is just one kind of way it can, one kind of way that AI will will be used. But I think it's, it's something that's pretty ubiquitous. >> Yeah. It'll be efficient, it'll be efficiency up and down the stack, and will change the productivity equation completely. You just highlighted one, I don't want to fill out forms, just stand up my environment for me. And then start coding away. Okay well this is great stuff. Final word for the folks out there watching, obviously new kind of skill set for hiring. You guys got engineers, give a plug for the company, for Anyscale. What are you looking for? What are you guys working on? Give a, take the last minute to put a plug in for the company. >> Yeah well if you're interested in AI and if you think AI is really going to be transformative, and really be useful for all these different industries. We are trying to provide the infrastructure to enable that to happen, right? So I think there's the potential here, to really solve an important problem, to get to the point where developers don't need to think about infrastructure, don't need to think about distributed systems. All they think about is their application logic, and what they want their application to do. And I think if we can achieve that, you know we can be the foundation or the platform that enables all of these other companies to succeed with AI. So that's where we're going. I think something like this has to happen if AI is going to achieve its potential, we're looking for, we're hiring across the board, you know, great engineers, on the go-to-market side, product managers, you know people who want to really, you know, make this happen. >> Awesome well congratulations. I know you got some good funding behind you. You're in a good spot. I think this is happening. I think generative AI and foundation models is going to be the next big inflection point, as big as the pc inter-networking, internet and smartphones. This is a whole nother application framework, a whole nother set of things. So this is the ground floor. Robert, you're, you and your team are right there. Well done. >> Thank you so much. >> All right. Thanks for coming on this CUBE conversation. I'm John Furrier with theCUBE. Breaking down a conversation around AI and scaling up in this new next major inflection point. This next wave is foundational models, generative AI. And thanks to ChatGPT, the whole world's now knowing about it. So it really is changing the game and Anyscale is right there, one of the hot startups, that is in good position to ride this next wave. Thanks for watching. (upbeat instrumental)
SUMMARY :
Robert, great to have you Thanks for inviting me. as you guys are gearing up and the potential for AI to a lot of that I love the and at some point you need It's the big brains in the company. and the reason people the automation's got to be there. and really you know, and talk to customers, put but the most common you know, and then you go to now that are trained that you know, and that seems to be a value proposition. And at that point you don't So you need infrastructure, and lower the barrier to entry. What are you guys working on? and if you think AI is really is going to be the next And thanks to ChatGPT,
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Unpacking Palo Alto Networks Ignite22 | Palo Alto Networks Ignite22
>> Announcer: TheCUBE presents Ignite '22, brought to you by Palo Alto Networks. >> Welcome back to Las Vegas. It's theCUBE covering Palo Alto Networks '22, from the MGM Grand, Lisa Martin with Dave Vellante. Dave, we are going to unpack in the next few minutes what we heard and saw at day one of Palo Alto Networks, Ignite. A lot of great conversations, some great guests on the program today. >> Yeah last event, CUBE event of the year. Probably last major tech event of the year. It's kind of an interesting choice of timing, two weeks after reInvent. But you know, this crowd is it's a lot of like network engineers, SecOps pros. There's not a lot of suits here. I think they were here yesterday, all the partners. >> Yeah. >> We talked to Carl Sunderland about, Hey, these, these guys want to know how do I grow my business? You know, so it was a lot of C level executives talking about their business, and how they partner with Palo Alto to grow. The crowd today is really, you know hardcore security professionals. >> Yeah. >> So we're hearing a story of consolidation. >> Yes. >> No surprise. We've talked about that and reported on it, you know, quite extensively. The one big takeaway, and I want, I came in, as you know, wanting to understand, okay, can you through m and a maintain, you know, build a suite of great, big portfolio and at the same time maintain best of breed? And the answer was consistent. We heard it from Nikesh, we heard it from Nir Zuk. The answer was you can't be best of breed without having that large portfolio, single data lake, you know? Single version of the truth, of there is such a thing. That was interesting, that in security, you have to have that visibility. I would imagine, that's true for a lot of things. Data, see what Snowflake and Databricks are both trying to do, now AWS. So to join, we heard that last week, so that was one of the big takeaways. What were your, some of your thoughts? >> Just impressed with the level of threat intelligence that Unit 42 has done. I mean, we had Wendy Whitmer on, and she was one of the alumni, great guest. The landscape has changed so dramatically. Every business, in any industry, nobody's safe. They have such great intelligence on what's going on with malware, with ransomware, with Smishing, that they're able to get, help organizations on their way to becoming cyber resilient. You know, we've been talking a lot about cyber resiliency lately. I always want to understand, well what does it mean? How do different organizations and customers define it? Can they actually really get there? And Wendy talked about yes, it is a journey, but organizations can achieve cyber resiliency. But they need to partner with Palo Alto Networks to be able to understand the landscape and ensure that they've got security established across their organization, as it's now growingly Multicloud. >> Yeah, she's a blonde-haired Wonder Woman, superhero. I always ask security pros that question. But you know, when you talk to people like Wendy Whitmore, Kevin Mandy is somebody else. And the people at AWS, or the big cloud companies, who are on the inside, looking at the threat intelligence. They have so much data, and they have so much knowledge. They can, they analyze, they could identify the fingerprints of nation states, different, you know, criminal organizations. And the the one thing, I think it was Wendy who said, maybe it was somebody else, I think it was Wendy, that they're they're tearing down and reforming, right? >> Yes. >> After they're discovered. Okay, they pack up and leave. They're like, you know, Oceans 11. >> Yep. >> Okay. And then they recruit them and bring them back in. So that was really fascinating. Nir Zuk, we'd never had him on theCUBE before. He was tremendous founder and and CTO of Palo Alto Networks, very opinionated. You know, very clear thinker, basically saying, look you're SOC is going to be run by AI >> Yeah. >> within the next five years. And machines are going to do things that humans can't do at scale, is really what he was saying. And then they're going to get better at that, and they're going to do other things that you have done well that they haven't done well, and then they're going to do well. And so, this is an interesting discussion about you know, I remember, you know we had an event with MIT. Eric Brynjolfsson and Andy McAfee, they wrote the book "Second Machine Age." And they made the point, machines have always replaced humans. This is the first time ever that machines are replacing humans in cognitive functions. So what does that mean? That means that humans have to rely on, you know, creativity. There's got to be new training, new thinking. So it's not like you're going to be out of a job, you're just going to be doing a different job. >> Right. I thought Nir Zuk did a great job of explaining that. We often hear people that are concerned with machines taking jobs. He did a great job of, and you did a great recap, of articulating the value that both bring, and the opportunities to the humans that the machines actually deliver as well. >> Yeah so, you know, we didn't, we didn't get deep into the products today. Tomorrow we're going to have a little bit more deep dive on products. We did, we had some partners on, AWS came on, talked about their ecosystem. BJ Jenkins so, you know, BJ Jenkins again I mean super senior executive. And if I were Nikesh, he's doing exactly what I would do. Putting him on a plane and saying, go meet with customers, go make rain, right? And that's what he's doing is, he's an individual who really knows how to interact with the C-suite, has driven value, you know, over the years. So they've got that angle goin', they're driving go to market. They've got the technology piece and they've, they got to build out the ecosystem. That I think is the big opportunity for them. You know, if they're going to double as a company, this ecosystem has to quadruple. >> Yeah, yeah. >> In my opinion. And I, we saw the same thing at CrowdStrike. We said the same thing about Service Now in 2013. And so, what's happened is the GSIs, the global system integrators start to get involved. They start to partner with them and then they get to get that flywheel effect. And then there's a supercloud, I think that, you know I think Nir Zuk said, Hey, we are basically building out that, he didn't use the term supercloud. But, we're building out that cross cloud capability. You don't need another stove pipe for the edge. You know, so they got on-prem, they got AWS, Azure, you said you have to, absolutely have to run on Microsoft. 'Cause I don't believe today, right? Today they run on, I heard somebody say they run on AWS and Google. >> Yeah. >> I haven't heard much about Microsoft. >> Right. >> Both AWS and Google are here. Microsoft, the bigger competitor in security, but Nir Zuk was unequivocal. Yes, of course you have to run, you got to run it on an Alibaba cloud. He didn't say that, but if you want to secure the China cloud, you got to run on Alibaba. >> Absolutely. >> And Oracle he said. Didn't mention IBM, but no reason they can't run on IBM's cloud. But unless IBM doesn't want 'em to. >> Well they're very customer focused and customer first. So it'll be interesting to see if customers take them in that direction. >> Well it's a good point, right? If customers say, Hey we want you running in this cloud, they will. And, but he did call out Oracle, which I thought was interesting. And so, Oracle's all about mission critical data, mission critical apps. So, you know, that's a good sign. You know, I mean there's so much opportunity in cyber, but so much confusion. You know, sneak had a raise today. It was a down round, no surprise there. But you know, these companies are going to start getting tight on cash, and you've seen layoffs, right? And so, I dunno who said it, I think it was Carl at the end said in a downturn, the strongest companies come out stronger. And that's generally, generally been the case. That kind of rich get richer. We see that in the last downturn? Yes and no, to a certain extent. It's still all about execution. I mean I think about EMC coming out of the last downturn. They did come out stronger and then they started to rocket, but then look what happened. They couldn't remain independent. They were just using m and a as a technique to hide the warts. You know so, what Nir Zuk said that was most interesting to me is when we acquire, we acquire with the intent of integrating. ServiceNow has a similar philosophy. I think that's why they've been somewhat successful. And Oracle, for sure, has had a similar philosophy. So, and that idea of shifting labor into vendor R and D has always been a winning formula. >> I think we heard that today. Excited for day two tomorrow. We've got some great conversations. We're going to be able to talk with some customers, the chief product officer is on. So we have more great content coming from our last live show over the year. Dave, it's been great co-hosting day one with you. Look forward to doing it tomorrow. >> Yeah, thanks for doing this. >> All right. >> All right. For Dave Vellante, I'm Lisa Martin. You've been watching theCUBE, the leader in live enterprise and emerging tech coverage. See you tomorrow. (gentle music fades)
SUMMARY :
brought to you by Palo Alto Networks. in the next few minutes CUBE event of the year. We talked to Carl Sunderland So we're hearing a And the answer was consistent. that they're able to But you know, when you talk to people They're like, you know, Oceans 11. And then they recruit them and then they're going to do well. and the opportunities to the humans You know, if they're going to double I think that, you know Yes, of course you have to run, And Oracle he said. So it'll be interesting to see We see that in the last downturn? I think we heard that today. See you tomorrow.
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The Truth About MySQL HeatWave
>>When Oracle acquired my SQL via the Sun acquisition, nobody really thought the company would put much effort into the platform preferring to focus all the wood behind its leading Oracle database, Arrow pun intended. But two years ago, Oracle surprised many folks by announcing my SQL Heatwave a new database as a service with a massively parallel hybrid Columbia in Mary Mary architecture that brings together transactional and analytic data in a single platform. Welcome to our latest database, power panel on the cube. My name is Dave Ante, and today we're gonna discuss Oracle's MySQL Heat Wave with a who's who of cloud database industry analysts. Holgar Mueller is with Constellation Research. Mark Stammer is the Dragon Slayer and Wikibon contributor. And Ron Westfall is with Fu Chim Research. Gentlemen, welcome back to the Cube. Always a pleasure to have you on. Thanks for having us. Great to be here. >>So we've had a number of of deep dive interviews on the Cube with Nip and Aggarwal. You guys know him? He's a senior vice president of MySQL, Heatwave Development at Oracle. I think you just saw him at Oracle Cloud World and he's come on to describe this is gonna, I'll call it a shock and awe feature additions to to heatwave. You know, the company's clearly putting r and d into the platform and I think at at cloud world we saw like the fifth major release since 2020 when they first announced MySQL heat wave. So just listing a few, they, they got, they taken, brought in analytics machine learning, they got autopilot for machine learning, which is automation onto the basic o l TP functionality of the database. And it's been interesting to watch Oracle's converge database strategy. We've contrasted that amongst ourselves. Love to get your thoughts on Amazon's get the right tool for the right job approach. >>Are they gonna have to change that? You know, Amazon's got the specialized databases, it's just, you know, the both companies are doing well. It just shows there are a lot of ways to, to skin a cat cuz you see some traction in the market in, in both approaches. So today we're gonna focus on the latest heat wave announcements and we're gonna talk about multi-cloud with a native MySQL heat wave implementation, which is available on aws MySQL heat wave for Azure via the Oracle Microsoft interconnect. This kind of cool hybrid action that they got going. Sometimes we call it super cloud. And then we're gonna dive into my SQL Heatwave Lake house, which allows users to process and query data across MyQ databases as heatwave databases, as well as object stores. So, and then we've got, heatwave has been announced on AWS and, and, and Azure, they're available now and Lake House I believe is in beta and I think it's coming out the second half of next year. So again, all of our guests are fresh off of Oracle Cloud world in Las Vegas. So they got the latest scoop. Guys, I'm done talking. Let's get into it. Mark, maybe you could start us off, what's your opinion of my SQL Heatwaves competitive position? When you think about what AWS is doing, you know, Google is, you know, we heard Google Cloud next recently, we heard about all their data innovations. You got, obviously Azure's got a big portfolio, snowflakes doing well in the market. What's your take? >>Well, first let's look at it from the point of view that AWS is the market leader in cloud and cloud services. They own somewhere between 30 to 50% depending on who you read of the market. And then you have Azure as number two and after that it falls off. There's gcp, Google Cloud platform, which is further way down the list and then Oracle and IBM and Alibaba. So when you look at AWS and you and Azure saying, hey, these are the market leaders in the cloud, then you start looking at it and saying, if I am going to provide a service that competes with the service they have, if I can make it available in their cloud, it means that I can be more competitive. And if I'm compelling and compelling means at least twice the performance or functionality or both at half the price, I should be able to gain market share. >>And that's what Oracle's done. They've taken a superior product in my SQL heat wave, which is faster, lower cost does more for a lot less at the end of the day and they make it available to the users of those clouds. You avoid this little thing called egress fees, you avoid the issue of having to migrate from one cloud to another and suddenly you have a very compelling offer. So I look at what Oracle's doing with MyQ and it feels like, I'm gonna use a word term, a flanking maneuver to their competition. They're offering a better service on their platforms. >>All right, so thank you for that. Holger, we've seen this sort of cadence, I sort of referenced it up front a little bit and they sat on MySQL for a decade, then all of a sudden we see this rush of announcements. Why did it take so long? And and more importantly is Oracle, are they developing the right features that cloud database customers are looking for in your view? >>Yeah, great question, but first of all, in your interview you said it's the edit analytics, right? Analytics is kind of like a marketing buzzword. Reports can be analytics, right? The interesting thing, which they did, the first thing they, they, they crossed the chasm between OTP and all up, right? In the same database, right? So major engineering feed very much what customers want and it's all about creating Bellevue for customers, which, which I think is the part why they go into the multi-cloud and why they add these capabilities. And they certainly with the AI capabilities, it's kind of like getting it into an autonomous field, self-driving field now with the lake cost capabilities and meeting customers where they are, like Mark has talked about the e risk costs in the cloud. So that that's a significant advantage, creating value for customers and that's what at the end of the day matters. >>And I believe strongly that long term it's gonna be ones who create better value for customers who will get more of their money From that perspective, why then take them so long? I think it's a great question. I think largely he mentioned the gentleman Nial, it's largely to who leads a product. I used to build products too, so maybe I'm a little fooling myself here, but that made the difference in my view, right? So since he's been charged, he's been building things faster than the rest of the competition, than my SQL space, which in hindsight we thought was a hot and smoking innovation phase. It kind of like was a little self complacent when it comes to the traditional borders of where, where people think, where things are separated between OTP and ola or as an example of adjacent support, right? Structured documents, whereas unstructured documents or databases and all of that has been collapsed and brought together for building a more powerful database for customers. >>So I mean it's certainly, you know, when, when Oracle talks about the competitors, you know, the competitors are in the, I always say they're, if the Oracle talks about you and knows you're doing well, so they talk a lot about aws, talk a little bit about Snowflake, you know, sort of Google, they have partnerships with Azure, but, but in, so I'm presuming that the response in MySQL heatwave was really in, in response to what they were seeing from those big competitors. But then you had Maria DB coming out, you know, the day that that Oracle acquired Sun and, and launching and going after the MySQL base. So it's, I'm, I'm interested and we'll talk about this later and what you guys think AWS and Google and Azure and Snowflake and how they're gonna respond. But, but before I do that, Ron, I want to ask you, you, you, you can get, you know, pretty technical and you've probably seen the benchmarks. >>I know you have Oracle makes a big deal out of it, publishes its benchmarks, makes some transparent on on GI GitHub. Larry Ellison talked about this in his keynote at Cloud World. What are the benchmarks show in general? I mean, when you, when you're new to the market, you gotta have a story like Mark was saying, you gotta be two x you know, the performance at half the cost or you better be or you're not gonna get any market share. So, and, and you know, oftentimes companies don't publish market benchmarks when they're leading. They do it when they, they need to gain share. So what do you make of the benchmarks? Have their, any results that were surprising to you? Have, you know, they been challenged by the competitors. Is it just a bunch of kind of desperate bench marketing to make some noise in the market or you know, are they real? What's your view? >>Well, from my perspective, I think they have the validity. And to your point, I believe that when it comes to competitor responses, that has not really happened. Nobody has like pulled down the information that's on GitHub and said, Oh, here are our price performance results. And they counter oracles. In fact, I think part of the reason why that hasn't happened is that there's the risk if Oracle's coming out and saying, Hey, we can deliver 17 times better query performance using our capabilities versus say, Snowflake when it comes to, you know, the Lakehouse platform and Snowflake turns around and says it's actually only 15 times better during performance, that's not exactly an effective maneuver. And so I think this is really to oracle's credit and I think it's refreshing because these differentiators are significant. We're not talking, you know, like 1.2% differences. We're talking 17 fold differences, we're talking six fold differences depending on, you know, where the spotlight is being shined and so forth. >>And so I think this is actually something that is actually too good to believe initially at first blush. If I'm a cloud database decision maker, I really have to prioritize this. I really would know, pay a lot more attention to this. And that's why I posed the question to Oracle and others like, okay, if these differentiators are so significant, why isn't the needle moving a bit more? And it's for, you know, some of the usual reasons. One is really deep discounting coming from, you know, the other players that's really kind of, you know, marketing 1 0 1, this is something you need to do when there's a real competitive threat to keep, you know, a customer in your own customer base. Plus there is the usual fear and uncertainty about moving from one platform to another. But I think, you know, the traction, the momentum is, is shifting an Oracle's favor. I think we saw that in the Q1 efforts, for example, where Oracle cloud grew 44% and that it generated, you know, 4.8 billion and revenue if I recall correctly. And so, so all these are demonstrating that's Oracle is making, I think many of the right moves, publishing these figures for anybody to look at from their own perspective is something that is, I think, good for the market and I think it's just gonna continue to pay dividends for Oracle down the horizon as you know, competition intens plots. So if I were in, >>Dave, can I, Dave, can I interject something and, and what Ron just said there? Yeah, please go ahead. A couple things here, one discounting, which is a common practice when you have a real threat, as Ron pointed out, isn't going to help much in this situation simply because you can't discount to the point where you improve your performance and the performance is a huge differentiator. You may be able to get your price down, but the problem that most of them have is they don't have an integrated product service. They don't have an integrated O L T P O L A P M L N data lake. Even if you cut out two of them, they don't have any of them integrated. They have multiple services that are required separate integration and that can't be overcome with discounting. And the, they, you have to pay for each one of these. And oh, by the way, as you grow, the discounts go away. So that's a, it's a minor important detail. >>So, so that's a TCO question mark, right? And I know you look at this a lot, if I had that kind of price performance advantage, I would be pounding tco, especially if I need two separate databases to do the job. That one can do, that's gonna be, the TCO numbers are gonna be off the chart or maybe down the chart, which you want. Have you looked at this and how does it compare with, you know, the big cloud guys, for example, >>I've looked at it in depth, in fact, I'm working on another TCO on this arena, but you can find it on Wiki bod in which I compared TCO for MySEQ Heat wave versus Aurora plus Redshift plus ML plus Blue. I've compared it against gcps services, Azure services, Snowflake with other services. And there's just no comparison. The, the TCO differences are huge. More importantly, thefor, the, the TCO per performance is huge. We're talking in some cases multiple orders of magnitude, but at least an order of magnitude difference. So discounting isn't gonna help you much at the end of the day, it's only going to lower your cost a little, but it doesn't improve the automation, it doesn't improve the performance, it doesn't improve the time to insight, it doesn't improve all those things that you want out of a database or multiple databases because you >>Can't discount yourself to a higher value proposition. >>So what about, I wonder ho if you could chime in on the developer angle. You, you followed that, that market. How do these innovations from heatwave, I think you used the term developer velocity. I've heard you used that before. Yeah, I mean, look, Oracle owns Java, okay, so it, it's, you know, most popular, you know, programming language in the world, blah, blah blah. But it does it have the, the minds and hearts of, of developers and does, where does heatwave fit into that equation? >>I think heatwave is gaining quickly mindshare on the developer side, right? It's not the traditional no sequel database which grew up, there's a traditional mistrust of oracles to developers to what was happening to open source when gets acquired. Like in the case of Oracle versus Java and where my sql, right? And, but we know it's not a good competitive strategy to, to bank on Oracle screwing up because it hasn't worked not on Java known my sequel, right? And for developers, it's, once you get to know a technology product and you can do more, it becomes kind of like a Swiss army knife and you can build more use case, you can build more powerful applications. That's super, super important because you don't have to get certified in multiple databases. You, you are fast at getting things done, you achieve fire, develop velocity, and the managers are happy because they don't have to license more things, send you to more trainings, have more risk of something not being delivered, right? >>So it's really the, we see the suite where this best of breed play happening here, which in general was happening before already with Oracle's flagship database. Whereas those Amazon as an example, right? And now the interesting thing is every step away Oracle was always a one database company that can be only one and they're now generally talking about heat web and that two database company with different market spaces, but same value proposition of integrating more things very, very quickly to have a universal database that I call, they call the converge database for all the needs of an enterprise to run certain application use cases. And that's what's attractive to developers. >>It's, it's ironic isn't it? I mean I, you know, the rumor was the TK Thomas Curian left Oracle cuz he wanted to put Oracle database on other clouds and other places. And maybe that was the rift. Maybe there was, I'm sure there was other things, but, but Oracle clearly is now trying to expand its Tam Ron with, with heatwave into aws, into Azure. How do you think Oracle's gonna do, you were at a cloud world, what was the sentiment from customers and the independent analyst? Is this just Oracle trying to screw with the competition, create a little diversion? Or is this, you know, serious business for Oracle? What do you think? >>No, I think it has lakes. I think it's definitely, again, attriting to Oracle's overall ability to differentiate not only my SQL heat wave, but its overall portfolio. And I think the fact that they do have the alliance with the Azure in place, that this is definitely demonstrating their commitment to meeting the multi-cloud needs of its customers as well as what we pointed to in terms of the fact that they're now offering, you know, MySQL capabilities within AWS natively and that it can now perform AWS's own offering. And I think this is all demonstrating that Oracle is, you know, not letting up, they're not resting on its laurels. That's clearly we are living in a multi-cloud world, so why not just make it more easy for customers to be able to use cloud databases according to their own specific, specific needs. And I think, you know, to holder's point, I think that definitely lines with being able to bring on more application developers to leverage these capabilities. >>I think one important announcement that's related to all this was the JSON relational duality capabilities where now it's a lot easier for application developers to use a language that they're very familiar with a JS O and not have to worry about going into relational databases to store their J S O N application coding. So this is, I think an example of the innovation that's enhancing the overall Oracle portfolio and certainly all the work with machine learning is definitely paying dividends as well. And as a result, I see Oracle continue to make these inroads that we pointed to. But I agree with Mark, you know, the short term discounting is just a stall tag. This is not denying the fact that Oracle is being able to not only deliver price performance differentiators that are dramatic, but also meeting a wide range of needs for customers out there that aren't just limited device performance consideration. >>Being able to support multi-cloud according to customer needs. Being able to reach out to the application developer community and address a very specific challenge that has plagued them for many years now. So bring it all together. Yeah, I see this as just enabling Oracles who ring true with customers. That the customers that were there were basically all of them, even though not all of them are going to be saying the same things, they're all basically saying positive feedback. And likewise, I think the analyst community is seeing this. It's always refreshing to be able to talk to customers directly and at Oracle cloud there was a litany of them and so this is just a difference maker as well as being able to talk to strategic partners. The nvidia, I think partnerships also testament to Oracle's ongoing ability to, you know, make the ecosystem more user friendly for the customers out there. >>Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able to be best of breed. That's the kind of surprising thing that I'm hearing about, about heatwave. I want to, I want to talk about Lake House because when I think of Lake House, I think data bricks, and to my knowledge data bricks hasn't been in the sites of Oracle yet. Maybe they're next, but, but Oracle claims that MySQL, heatwave, Lakehouse is a breakthrough in terms of capacity and performance. Mark, what are your thoughts on that? Can you double click on, on Lakehouse Oracle's claims for things like query performance and data loading? What does it mean for the market? Is Oracle really leading in, in the lake house competitive landscape? What are your thoughts? >>Well, but name in the game is what are the problems you're solving for the customer? More importantly, are those problems urgent or important? If they're urgent, customers wanna solve 'em. Now if they're important, they might get around to them. So you look at what they're doing with Lake House or previous to that machine learning or previous to that automation or previous to that O L A with O ltp and they're merging all this capability together. If you look at Snowflake or data bricks, they're tacking one problem. You look at MyQ heat wave, they're tacking multiple problems. So when you say, yeah, their queries are much better against the lake house in combination with other analytics in combination with O ltp and the fact that there are no ETLs. So you're getting all this done in real time. So it's, it's doing the query cross, cross everything in real time. >>You're solving multiple user and developer problems, you're increasing their ability to get insight faster, you're having shorter response times. So yeah, they really are solving urgent problems for customers. And by putting it where the customer lives, this is the brilliance of actually being multicloud. And I know I'm backing up here a second, but by making it work in AWS and Azure where people already live, where they already have applications, what they're saying is, we're bringing it to you. You don't have to come to us to get these, these benefits, this value overall, I think it's a brilliant strategy. I give Nip and Argo wallet a huge, huge kudos for what he's doing there. So yes, what they're doing with the lake house is going to put notice on data bricks and Snowflake and everyone else for that matter. Well >>Those are guys that whole ago you, you and I have talked about this. Those are, those are the guys that are doing sort of the best of breed. You know, they're really focused and they, you know, tend to do well at least out of the gate. Now you got Oracle's converged philosophy, obviously with Oracle database. We've seen that now it's kicking in gear with, with heatwave, you know, this whole thing of sweets versus best of breed. I mean the long term, you know, customers tend to migrate towards suite, but the new shiny toy tends to get the growth. How do you think this is gonna play out in cloud database? >>Well, it's the forever never ending story, right? And in software right suite, whereas best of breed and so far in the long run suites have always won, right? So, and sometimes they struggle again because the inherent problem of sweets is you build something larger, it has more complexity and that means your cycles to get everything working together to integrate the test that roll it out, certify whatever it is, takes you longer, right? And that's not the case. It's a fascinating part of what the effort around my SQL heat wave is that the team is out executing the previous best of breed data, bringing us something together. Now if they can maintain that pace, that's something to to, to be seen. But it, the strategy, like what Mark was saying, bring the software to the data is of course interesting and unique and totally an Oracle issue in the past, right? >>Yeah. But it had to be in your database on oci. And but at, that's an interesting part. The interesting thing on the Lake health side is, right, there's three key benefits of a lakehouse. The first one is better reporting analytics, bring more rich information together, like make the, the, the case for silicon angle, right? We want to see engagements for this video, we want to know what's happening. That's a mixed transactional video media use case, right? Typical Lakehouse use case. The next one is to build more rich applications, transactional applications which have video and these elements in there, which are the engaging one. And the third one, and that's where I'm a little critical and concerned, is it's really the base platform for artificial intelligence, right? To run deep learning to run things automatically because they have all the data in one place can create in one way. >>And that's where Oracle, I know that Ron talked about Invidia for a moment, but that's where Oracle doesn't have the strongest best story. Nonetheless, the two other main use cases of the lake house are very strong, very well only concern is four 50 terabyte sounds long. It's an arbitrary limitation. Yeah, sounds as big. So for the start, and it's the first word, they can make that bigger. You don't want your lake house to be limited and the terabyte sizes or any even petabyte size because you want to have the certainty. I can put everything in there that I think it might be relevant without knowing what questions to ask and query those questions. >>Yeah. And you know, in the early days of no schema on right, it just became a mess. But now technology has evolved to allow us to actually get more value out of that data. Data lake. Data swamp is, you know, not much more, more, more, more logical. But, and I want to get in, in a moment, I want to come back to how you think the competitors are gonna respond. Are they gonna have to sort of do a more of a converged approach? AWS in particular? But before I do, Ron, I want to ask you a question about autopilot because I heard Larry Ellison's keynote and he was talking about how, you know, most security issues are human errors with autonomy and autonomous database and things like autopilot. We take care of that. It's like autonomous vehicles, they're gonna be safer. And I went, well maybe, maybe someday. So Oracle really tries to emphasize this, that every time you see an announcement from Oracle, they talk about new, you know, autonomous capabilities. It, how legit is it? Do people care? What about, you know, what's new for heatwave Lakehouse? How much of a differentiator, Ron, do you really think autopilot is in this cloud database space? >>Yeah, I think it will definitely enhance the overall proposition. I don't think people are gonna buy, you know, lake house exclusively cause of autopilot capabilities, but when they look at the overall picture, I think it will be an added capability bonus to Oracle's benefit. And yeah, I think it's kind of one of these age old questions, how much do you automate and what is the bounce to strike? And I think we all understand with the automatic car, autonomous car analogy that there are limitations to being able to use that. However, I think it's a tool that basically every organization out there needs to at least have or at least evaluate because it goes to the point of it helps with ease of use, it helps make automation more balanced in terms of, you know, being able to test, all right, let's automate this process and see if it works well, then we can go on and switch on on autopilot for other processes. >>And then, you know, that allows, for example, the specialists to spend more time on business use cases versus, you know, manual maintenance of, of the cloud database and so forth. So I think that actually is a, a legitimate value proposition. I think it's just gonna be a case by case basis. Some organizations are gonna be more aggressive with putting automation throughout their processes throughout their organization. Others are gonna be more cautious. But it's gonna be, again, something that will help the overall Oracle proposition. And something that I think will be used with caution by many organizations, but other organizations are gonna like, hey, great, this is something that is really answering a real problem. And that is just easing the use of these databases, but also being able to better handle the automation capabilities and benefits that come with it without having, you know, a major screwup happened and the process of transitioning to more automated capabilities. >>Now, I didn't attend cloud world, it's just too many red eyes, you know, recently, so I passed. But one of the things I like to do at those events is talk to customers, you know, in the spirit of the truth, you know, they, you know, you'd have the hallway, you know, track and to talk to customers and they say, Hey, you know, here's the good, the bad and the ugly. So did you guys, did you talk to any customers my SQL Heatwave customers at, at cloud world? And and what did you learn? I don't know, Mark, did you, did you have any luck and, and having some, some private conversations? >>Yeah, I had quite a few private conversations. The one thing before I get to that, I want disagree with one point Ron made, I do believe there are customers out there buying the heat wave service, the MySEQ heat wave server service because of autopilot. Because autopilot is really revolutionary in many ways in the sense for the MySEQ developer in that it, it auto provisions, it auto parallel loads, IT auto data places it auto shape predictions. It can tell you what machine learning models are going to tell you, gonna give you your best results. And, and candidly, I've yet to meet a DBA who didn't wanna give up pedantic tasks that are pain in the kahoo, which they'd rather not do and if it's long as it was done right for them. So yes, I do think people are buying it because of autopilot and that's based on some of the conversations I had with customers at Oracle Cloud World. >>In fact, it was like, yeah, that's great, yeah, we get fantastic performance, but this really makes my life easier and I've yet to meet a DBA who didn't want to make their life easier. And it does. So yeah, I've talked to a few of them. They were excited. I asked them if they ran into any bugs, were there any difficulties in moving to it? And the answer was no. In both cases, it's interesting to note, my sequel is the most popular database on the planet. Well, some will argue that it's neck and neck with SQL Server, but if you add in Mariah DB and ProCon db, which are forks of MySQL, then yeah, by far and away it's the most popular. And as a result of that, everybody for the most part has typically a my sequel database somewhere in their organization. So this is a brilliant situation for anybody going after MyQ, but especially for heat wave. And the customers I talk to love it. I didn't find anybody complaining about it. And >>What about the migration? We talked about TCO earlier. Did your t does your TCO analysis include the migration cost or do you kind of conveniently leave that out or what? >>Well, when you look at migration costs, there are different kinds of migration costs. By the way, the worst job in the data center is the data migration manager. Forget it, no other job is as bad as that one. You get no attaboys for doing it. Right? And then when you screw up, oh boy. So in real terms, anything that can limit data migration is a good thing. And when you look at Data Lake, that limits data migration. So if you're already a MySEQ user, this is a pure MySQL as far as you're concerned. It's just a, a simple transition from one to the other. You may wanna make sure nothing broke and every you, all your tables are correct and your schema's, okay, but it's all the same. So it's a simple migration. So it's pretty much a non-event, right? When you migrate data from an O LTP to an O L A P, that's an ETL and that's gonna take time. >>But you don't have to do that with my SQL heat wave. So that's gone when you start talking about machine learning, again, you may have an etl, you may not, depending on the circumstances, but again, with my SQL heat wave, you don't, and you don't have duplicate storage, you don't have to copy it from one storage container to another to be able to be used in a different database, which by the way, ultimately adds much more cost than just the other service. So yeah, I looked at the migration and again, the users I talked to said it was a non-event. It was literally moving from one physical machine to another. If they had a new version of MySEQ running on something else and just wanted to migrate it over or just hook it up or just connect it to the data, it worked just fine. >>Okay, so every day it sounds like you guys feel, and we've certainly heard this, my colleague David Foyer, the semi-retired David Foyer was always very high on heatwave. So I think you knows got some real legitimacy here coming from a standing start, but I wanna talk about the competition, how they're likely to respond. I mean, if your AWS and you got heatwave is now in your cloud, so there's some good aspects of that. The database guys might not like that, but the infrastructure guys probably love it. Hey, more ways to sell, you know, EC two and graviton, but you're gonna, the database guys in AWS are gonna respond. They're gonna say, Hey, we got Redshift, we got aqua. What's your thoughts on, on not only how that's gonna resonate with customers, but I'm interested in what you guys think will a, I never say never about aws, you know, and are they gonna try to build, in your view a converged Oola and o LTP database? You know, Snowflake is taking an ecosystem approach. They've added in transactional capabilities to the portfolio so they're not standing still. What do you guys see in the competitive landscape in that regard going forward? Maybe Holger, you could start us off and anybody else who wants to can chime in, >>Happy to, you mentioned Snowflake last, we'll start there. I think Snowflake is imitating that strategy, right? That building out original data warehouse and the clouds tasking project to really proposition to have other data available there because AI is relevant for everybody. Ultimately people keep data in the cloud for ultimately running ai. So you see the same suite kind of like level strategy, it's gonna be a little harder because of the original positioning. How much would people know that you're doing other stuff? And I just, as a former developer manager of developers, I just don't see the speed at the moment happening at Snowflake to become really competitive to Oracle. On the flip side, putting my Oracle hat on for a moment back to you, Mark and Iran, right? What could Oracle still add? Because the, the big big things, right? The traditional chasms in the database world, they have built everything, right? >>So I, I really scratched my hat and gave Nipon a hard time at Cloud world say like, what could you be building? Destiny was very conservative. Let's get the Lakehouse thing done, it's gonna spring next year, right? And the AWS is really hard because AWS value proposition is these small innovation teams, right? That they build two pizza teams, which can be fit by two pizzas, not large teams, right? And you need suites to large teams to build these suites with lots of functionalities to make sure they work together. They're consistent, they have the same UX on the administration side, they can consume the same way, they have the same API registry, can't even stop going where the synergy comes to play over suite. So, so it's gonna be really, really hard for them to change that. But AWS super pragmatic. They're always by themselves that they'll listen to customers if they learn from customers suite as a proposition. I would not be surprised if AWS trying to bring things closer together, being morely together. >>Yeah. Well how about, can we talk about multicloud if, if, again, Oracle is very on on Oracle as you said before, but let's look forward, you know, half a year or a year. What do you think about Oracle's moves in, in multicloud in terms of what kind of penetration they're gonna have in the marketplace? You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at the, the Microsoft Azure deal. I think that's really interesting. I've, I've called it a little bit of early days of a super cloud. What impact do you think this is gonna have on, on the marketplace? But, but both. And think about it within Oracle's customer base, I have no doubt they'll do great there. But what about beyond its existing install base? What do you guys think? >>Ryan, do you wanna jump on that? Go ahead. Go ahead Ryan. No, no, no, >>That's an excellent point. I think it aligns with what we've been talking about in terms of Lakehouse. I think Lake House will enable Oracle to pull more customers, more bicycle customers onto the Oracle platforms. And I think we're seeing all the signs pointing toward Oracle being able to make more inroads into the overall market. And that includes garnishing customers from the leaders in, in other words, because they are, you know, coming in as a innovator, a an alternative to, you know, the AWS proposition, the Google cloud proposition that they have less to lose and there's a result they can really drive the multi-cloud messaging to resonate with not only their existing customers, but also to be able to, to that question, Dave's posing actually garnish customers onto their platform. And, and that includes naturally my sequel but also OCI and so forth. So that's how I'm seeing this playing out. I think, you know, again, Oracle's reporting is indicating that, and I think what we saw, Oracle Cloud world is definitely validating the idea that Oracle can make more waves in the overall market in this regard. >>You know, I, I've floated this idea of Super cloud, it's kind of tongue in cheek, but, but there, I think there is some merit to it in terms of building on top of hyperscale infrastructure and abstracting some of the, that complexity. And one of the things that I'm most interested in is industry clouds and an Oracle acquisition of Cerner. I was struck by Larry Ellison's keynote, it was like, I don't know, an hour and a half and an hour and 15 minutes was focused on healthcare transformation. Well, >>So vertical, >>Right? And so, yeah, so you got Oracle's, you know, got some industry chops and you, and then you think about what they're building with, with not only oci, but then you got, you know, MyQ, you can now run in dedicated regions. You got ADB on on Exadata cloud to customer, you can put that OnPrem in in your data center and you look at what the other hyperscalers are, are doing. I I say other hyperscalers, I've always said Oracle's not really a hyperscaler, but they got a cloud so they're in the game. But you can't get, you know, big query OnPrem, you look at outposts, it's very limited in terms of, you know, the database support and again, that that will will evolve. But now you got Oracle's got, they announced Alloy, we can white label their cloud. So I'm interested in what you guys think about these moves, especially the industry cloud. We see, you know, Walmart is doing sort of their own cloud. You got Goldman Sachs doing a cloud. Do you, you guys, what do you think about that and what role does Oracle play? Any thoughts? >>Yeah, let me lemme jump on that for a moment. Now, especially with the MyQ, by making that available in multiple clouds, what they're doing is this follows the philosophy they've had the past with doing cloud, a customer taking the application and the data and putting it where the customer lives. If it's on premise, it's on premise. If it's in the cloud, it's in the cloud. By making the mice equal heat wave, essentially a plug compatible with any other mice equal as far as your, your database is concern and then giving you that integration with O L A P and ML and Data Lake and everything else, then what you've got is a compelling offering. You're making it easier for the customer to use. So I look the difference between MyQ and the Oracle database, MyQ is going to capture market more market share for them. >>You're not gonna find a lot of new users for the Oracle debate database. Yeah, there are always gonna be new users, don't get me wrong, but it's not gonna be a huge growth. Whereas my SQL heatwave is probably gonna be a major growth engine for Oracle going forward. Not just in their own cloud, but in AWS and in Azure and on premise over time that eventually it'll get there. It's not there now, but it will, they're doing the right thing on that basis. They're taking the services and when you talk about multicloud and making them available where the customer wants them, not forcing them to go where you want them, if that makes sense. And as far as where they're going in the future, I think they're gonna take a page outta what they've done with the Oracle database. They'll add things like JSON and XML and time series and spatial over time they'll make it a, a complete converged database like they did with the Oracle database. The difference being Oracle database will scale bigger and will have more transactions and be somewhat faster. And my SQL will be, for anyone who's not on the Oracle database, they're, they're not stupid, that's for sure. >>They've done Jason already. Right. But I give you that they could add graph and time series, right. Since eat with, Right, Right. Yeah, that's something absolutely right. That's, that's >>A sort of a logical move, right? >>Right. But that's, that's some kid ourselves, right? I mean has worked in Oracle's favor, right? 10 x 20 x, the amount of r and d, which is in the MyQ space, has been poured at trying to snatch workloads away from Oracle by starting with IBM 30 years ago, 20 years ago, Microsoft and, and, and, and didn't work, right? Database applications are extremely sticky when they run, you don't want to touch SIM and grow them, right? So that doesn't mean that heat phase is not an attractive offering, but it will be net new things, right? And what works in my SQL heat wave heat phases favor a little bit is it's not the massive enterprise applications which have like we the nails like, like you might be only running 30% or Oracle, but the connections and the interfaces into that is, is like 70, 80% of your enterprise. >>You take it out and it's like the spaghetti ball where you say, ah, no I really don't, don't want to do all that. Right? You don't, don't have that massive part with the equals heat phase sequel kind of like database which are more smaller tactical in comparison, but still I, I don't see them taking so much share. They will be growing because of a attractive value proposition quickly on the, the multi-cloud, right? I think it's not really multi-cloud. If you give people the chance to run your offering on different clouds, right? You can run it there. The multi-cloud advantages when the Uber offering comes out, which allows you to do things across those installations, right? I can migrate data, I can create data across something like Google has done with B query Omni, I can run predictive models or even make iron models in different place and distribute them, right? And Oracle is paving the road for that, but being available on these clouds. But the multi-cloud capability of database which knows I'm running on different clouds that is still yet to be built there. >>Yeah. And >>That the problem with >>That, that's the super cloud concept that I flowed and I I've always said kinda snowflake with a single global instance is sort of, you know, headed in that direction and maybe has a league. What's the issue with that mark? >>Yeah, the problem with the, with that version, the multi-cloud is clouds to charge egress fees. As long as they charge egress fees to move data between clouds, it's gonna make it very difficult to do a real multi-cloud implementation. Even Snowflake, which runs multi-cloud, has to pass out on the egress fees of their customer when data moves between clouds. And that's really expensive. I mean there, there is one customer I talked to who is beta testing for them, the MySQL heatwave and aws. The only reason they didn't want to do that until it was running on AWS is the egress fees were so great to move it to OCI that they couldn't afford it. Yeah. Egress fees are the big issue but, >>But Mark the, the point might be you might wanna root query and only get the results set back, right was much more tinier, which been the answer before for low latency between the class A problem, which we sometimes still have but mostly don't have. Right? And I think in general this with fees coming down based on the Oracle general E with fee move and it's very hard to justify those, right? But, but it's, it's not about moving data as a multi-cloud high value use case. It's about doing intelligent things with that data, right? Putting into other places, replicating it, what I'm saying the same thing what you said before, running remote queries on that, analyzing it, running AI on it, running AI models on that. That's the interesting thing. Cross administered in the same way. Taking things out, making sure compliance happens. Making sure when Ron says I don't want to be American anymore, I want to be in the European cloud that is gets migrated, right? So tho those are the interesting value use case which are really, really hard for enterprise to program hand by hand by developers and they would love to have out of the box and that's yet the innovation to come to, we have to come to see. But the first step to get there is that your software runs in multiple clouds and that's what Oracle's doing so well with my SQL >>Guys. Amazing. >>Go ahead. Yeah. >>Yeah. >>For example, >>Amazing amount of data knowledge and, and brain power in this market. Guys, I really want to thank you for coming on to the cube. Ron Holger. Mark, always a pleasure to have you on. Really appreciate your time. >>Well all the last names we're very happy for Romanic last and moderator. Thanks Dave for moderating us. All right, >>We'll see. We'll see you guys around. Safe travels to all and thank you for watching this power panel, The Truth About My SQL Heat Wave on the cube. Your leader in enterprise and emerging tech coverage.
SUMMARY :
Always a pleasure to have you on. I think you just saw him at Oracle Cloud World and he's come on to describe this is doing, you know, Google is, you know, we heard Google Cloud next recently, They own somewhere between 30 to 50% depending on who you read migrate from one cloud to another and suddenly you have a very compelling offer. All right, so thank you for that. And they certainly with the AI capabilities, And I believe strongly that long term it's gonna be ones who create better value for So I mean it's certainly, you know, when, when Oracle talks about the competitors, So what do you make of the benchmarks? say, Snowflake when it comes to, you know, the Lakehouse platform and threat to keep, you know, a customer in your own customer base. And oh, by the way, as you grow, And I know you look at this a lot, to insight, it doesn't improve all those things that you want out of a database or multiple databases So what about, I wonder ho if you could chime in on the developer angle. they don't have to license more things, send you to more trainings, have more risk of something not being delivered, all the needs of an enterprise to run certain application use cases. I mean I, you know, the rumor was the TK Thomas Curian left Oracle And I think, you know, to holder's point, I think that definitely lines But I agree with Mark, you know, the short term discounting is just a stall tag. testament to Oracle's ongoing ability to, you know, make the ecosystem Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able So when you say, yeah, their queries are much better against the lake house in You don't have to come to us to get these, these benefits, I mean the long term, you know, customers tend to migrate towards suite, but the new shiny bring the software to the data is of course interesting and unique and totally an Oracle issue in And the third one, lake house to be limited and the terabyte sizes or any even petabyte size because you want keynote and he was talking about how, you know, most security issues are human I don't think people are gonna buy, you know, lake house exclusively cause of And then, you know, that allows, for example, the specialists to And and what did you learn? The one thing before I get to that, I want disagree with And the customers I talk to love it. the migration cost or do you kind of conveniently leave that out or what? And when you look at Data Lake, that limits data migration. So that's gone when you start talking about So I think you knows got some real legitimacy here coming from a standing start, So you see the same And you need suites to large teams to build these suites with lots of functionalities You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at Ryan, do you wanna jump on that? I think, you know, again, Oracle's reporting I think there is some merit to it in terms of building on top of hyperscale infrastructure and to customer, you can put that OnPrem in in your data center and you look at what the So I look the difference between MyQ and the Oracle database, MyQ is going to capture market They're taking the services and when you talk about multicloud and But I give you that they could add graph and time series, right. like, like you might be only running 30% or Oracle, but the connections and the interfaces into You take it out and it's like the spaghetti ball where you say, ah, no I really don't, global instance is sort of, you know, headed in that direction and maybe has a league. Yeah, the problem with the, with that version, the multi-cloud is clouds And I think in general this with fees coming down based on the Oracle general E with fee move Yeah. Guys, I really want to thank you for coming on to the cube. Well all the last names we're very happy for Romanic last and moderator. We'll see you guys around.
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Luis Ceze, OctoML | Amazon re:MARS 2022
(upbeat music) >> Welcome back, everyone, to theCUBE's coverage here live on the floor at AWS re:MARS 2022. I'm John Furrier, host for theCUBE. Great event, machine learning, automation, robotics, space, that's MARS. It's part of the re-series of events, re:Invent's the big event at the end of the year, re:Inforce, security, re:MARS, really intersection of the future of space, industrial, automation, which is very heavily DevOps machine learning, of course, machine learning, which is AI. We have Luis Ceze here, who's the CEO co-founder of OctoML. Welcome to theCUBE. >> Thank you very much for having me in the show, John. >> So we've been following you guys. You guys are a growing startup funded by Madrona Venture Capital, one of your backers. You guys are here at the show. This is a, I would say small show relative what it's going to be, but a lot of robotics, a lot of space, a lot of industrial kind of edge, but machine learning is the centerpiece of this trend. You guys are in the middle of it. Tell us your story. >> Absolutely, yeah. So our mission is to make machine learning sustainable and accessible to everyone. So I say sustainable because it means we're going to make it faster and more efficient. You know, use less human effort, and accessible to everyone, accessible to as many developers as possible, and also accessible in any device. So, we started from an open source project that began at University of Washington, where I'm a professor there. And several of the co-founders were PhD students there. We started with this open source project called Apache TVM that had actually contributions and collaborations from Amazon and a bunch of other big tech companies. And that allows you to get a machine learning model and run on any hardware, like run on CPUs, GPUs, various GPUs, accelerators, and so on. It was the kernel of our company and the project's been around for about six years or so. Company is about three years old. And we grew from Apache TVM into a whole platform that essentially supports any model on any hardware cloud and edge. >> So is the thesis that, when it first started, that you want to be agnostic on platform? >> Agnostic on hardware, that's right. >> Hardware, hardware. >> Yeah. >> What was it like back then? What kind of hardware were you talking about back then? Cause a lot's changed, certainly on the silicon side. >> Luis: Absolutely, yeah. >> So take me through the journey, 'cause I could see the progression. I'm connecting the dots here. >> So once upon a time, yeah, no... (both chuckling) >> I walked in the snow with my bare feet. >> You have to be careful because if you wake up the professor in me, then you're going to be here for two hours, you know. >> Fast forward. >> The average version here is that, clearly machine learning has shown to actually solve real interesting, high value problems. And where machine learning runs in the end, it becomes code that runs on different hardware, right? And when we started Apache TVM, which stands for tensor virtual machine, at that time it was just beginning to start using GPUs for machine learning, we already saw that, with a bunch of machine learning models popping up and CPUs and GPU's starting to be used for machine learning, it was clear that it come opportunity to run on everywhere. >> And GPU's were coming fast. >> GPUs were coming and huge diversity of CPUs, of GPU's and accelerators now, and the ecosystem and the system software that maps models to hardware is still very fragmented today. So hardware vendors have their own specific stacks. So Nvidia has its own software stack, and so does Intel, AMD. And honestly, I mean, I hope I'm not being, you know, too controversial here to say that it kind of of looks like the mainframe era. We had tight coupling between hardware and software. You know, if you bought IBM hardware, you had to buy IBM OS and IBM database, IBM applications, it all tightly coupled. And if you want to use IBM software, you had to buy IBM hardware. So that's kind of like what machine learning systems look like today. If you buy a certain big name GPU, you've got to use their software. Even if you use their software, which is pretty good, you have to buy their GPUs, right? So, but you know, we wanted to help peel away the model and the software infrastructure from the hardware to give people choice, ability to run the models where it best suit them. Right? So that includes picking the best instance in the cloud, that's going to give you the right, you know, cost properties, performance properties, or might want to run it on the edge. You might run it on an accelerator. >> What year was that roughly, when you were going this? >> We started that project in 2015, 2016 >> Yeah. So that was pre-conventional wisdom. I think TensorFlow wasn't even around yet. >> Luis: No, it wasn't. >> It was, I'm thinking like 2017 or so. >> Luis: Right. So that was the beginning of, okay, this is opportunity. AWS, I don't think they had released some of the nitro stuff that the Hamilton was working on. So, they were already kind of going that way. It's kind of like converging. >> Luis: Yeah. >> The space was happening, exploding. >> Right. And the way that was dealt with, and to this day, you know, to a large extent as well is by backing machine learning models with a bunch of hardware specific libraries. And we were some of the first ones to say, like, know what, let's take a compilation approach, take a model and compile it to very efficient code for that specific hardware. And what underpins all of that is using machine learning for machine learning code optimization. Right? But it was way back when. We can talk about where we are today. >> No, let's fast forward. >> That's the beginning of the open source project. >> But that was a fundamental belief, worldview there. I mean, you have a world real view that was logical when you compare to the mainframe, but not obvious to the machine learning community. Okay, good call, check. Now let's fast forward, okay. Evolution, we'll go through the speed of the years. More chips are coming, you got GPUs, and seeing what's going on in AWS. Wow! Now it's booming. Now I got unlimited processors, I got silicon on chips, I got, everywhere >> Yeah. And what's interesting is that the ecosystem got even more complex, in fact. Because now you have, there's a cross product between machine learning models, frameworks like TensorFlow, PyTorch, Keras, and like that and so on, and then hardware targets. So how do you navigate that? What we want here, our vision is to say, folks should focus, people should focus on making the machine learning models do what they want to do that solves a value, like solves a problem of high value to them. Right? So another deployment should be completely automatic. Today, it's very, very manual to a large extent. So once you're serious about deploying machine learning model, you got a good understanding where you're going to deploy it, how you're going to deploy it, and then, you know, pick out the right libraries and compilers, and we automated the whole thing in our platform. This is why you see the tagline, the booth is right there, like bringing DevOps agility for machine learning, because our mission is to make that fully transparent. >> Well, I think that, first of all, I use that line here, cause I'm looking at it here on live on camera. People can't see, but it's like, I use it on a couple couple of my interviews because the word agility is very interesting because that's kind of the test on any kind of approach these days. Agility could be, and I talked to the robotics guys, just having their product be more agile. I talked to Pepsi here just before you came on, they had this large scale data environment because they built an architecture, but that fostered agility. So again, this is an architectural concept, it's a systems' view of agility being the output, and removing dependencies, which I think what you guys were trying to do. >> Only part of what we do. Right? So agility means a bunch of things. First, you know-- >> Yeah explain. >> Today it takes a couple months to get a model from, when the model's ready, to production, why not turn that in two hours. Agile, literally, physically agile, in terms of walk off time. Right? And then the other thing is give you flexibility to choose where your model should run. So, in our deployment, between the demo and the platform expansion that we announced yesterday, you know, we give the ability of getting your model and, you know, get it compiled, get it optimized for any instance in the cloud and automatically move it around. Today, that's not the case. You have to pick one instance and that's what you do. And then you might auto scale with that one instance. So we give the agility of actually running and scaling the model the way you want, and the way it gives you the right SLAs. >> Yeah, I think Swami was mentioning that, not specifically that use case for you, but that use case generally, that scale being moving things around, making them faster, not having to do that integration work. >> Scale, and run the models where they need to run. Like some day you want to have a large scale deployment in the cloud. You're going to have models in the edge for various reasons because speed of light is limited. We cannot make lights faster. So, you know, got to have some, that's a physics there you cannot change. There's privacy reasons. You want to keep data locally, not send it around to run the model locally. So anyways, and giving the flexibility. >> Let me jump in real quick. I want to ask this specific question because you made me think of something. So we're just having a data mesh conversation. And one of the comments that's come out of a few of these data as code conversations is data's the product now. So if you can move data to the edge, which everyone's talking about, you know, why move data if you don't have to, but I can move a machine learning algorithm to the edge. Cause it's costly to move data. I can move computer, everyone knows that. But now I can move machine learning to anywhere else and not worry about integrating on the fly. So the model is the code. >> It is the product. >> Yeah. And since you said, the model is the code, okay, now we're talking even more here. So machine learning models today are not treated as code, by the way. So do not have any of the typical properties of code that you can, whenever you write a piece of code, you run a code, you don't know, you don't even think what is a CPU, we don't think where it runs, what kind of CPU it runs, what kind of instance it runs. But with machine learning model, you do. So what we are doing and created this fully transparent automated way of allowing you to treat your machine learning models if you were a regular function that you call and then a function could run anywhere. >> Yeah. >> Right. >> That's why-- >> That's better. >> Bringing DevOps agility-- >> That's better. >> Yeah. And you can use existing-- >> That's better, because I can run it on the Artemis too, in space. >> You could, yeah. >> If they have the hardware. (both laugh) >> And that allows you to run your existing, continue to use your existing DevOps infrastructure and your existing people. >> So I have to ask you, cause since you're a professor, this is like a masterclass on theCube. Thank you for coming on. Professor. (Luis laughing) I'm a hardware guy. I'm building hardware for Boston Dynamics, Spot, the dog, that's the diversity in hardware, it's tends to be purpose driven. I got a spaceship, I'm going to have hardware on there. >> Luis: Right. >> It's generally viewed in the community here, that everyone I talk to and other communities, open source is going to drive all software. That's a check. But the scale and integration is super important. And they're also recognizing that hardware is really about the software. And they even said on stage, here. Hardware is not about the hardware, it's about the software. So if you believe that to be true, then your model checks all the boxes. Are people getting this? >> I think they're starting to. Here is why, right. A lot of companies that were hardware first, that thought about software too late, aren't making it. Right? There's a large number of hardware companies, AI chip companies that aren't making it. Probably some of them that won't make it, unfortunately just because they started thinking about software too late. I'm so glad to see a lot of the early, I hope I'm not just doing our own horn here, but Apache TVM, the infrastructure that we built to map models to different hardware, it's very flexible. So we see a lot of emerging chip companies like SiMa.ai's been doing fantastic work, and they use Apache TVM to map algorithms to their hardware. And there's a bunch of others that are also using Apache TVM. That's because you have, you know, an opening infrastructure that keeps it up to date with all the machine learning frameworks and models and allows you to extend to the chips that you want. So these companies pay attention that early, gives them a much higher fighting chance, I'd say. >> Well, first of all, not only are you backable by the VCs cause you have pedigree, you're a professor, you're smart, and you get good recruiting-- >> Luis: I don't know about the smart part. >> And you get good recruiting for PhDs out of University of Washington, which is not too shabby computer science department. But they want to make money. The VCs want to make money. >> Right. >> So you have to make money. So what's the pitch? What's the business model? >> Yeah. Absolutely. >> Share us what you're thinking there. >> Yeah. The value of using our solution is shorter time to value for your model from months to hours. Second, you shrink operator, op-packs, because you don't need a specialized expensive team. Talk about expensive, expensive engineers who can understand machine learning hardware and software engineering to deploy models. You don't need those teams if you use this automated solution, right? Then you reduce that. And also, in the process of actually getting a model and getting specialized to the hardware, making hardware aware, we're talking about a very significant performance improvement that leads to lower cost of deployment in the cloud. We're talking about very significant reduction in costs in cloud deployment. And also enabling new applications on the edge that weren't possible before. It creates, you know, latent value opportunities. Right? So, that's the high level value pitch. But how do we make money? Well, we charge for access to the platform. Right? >> Usage. Consumption. >> Yeah, and value based. Yeah, so it's consumption and value based. So depends on the scale of the deployment. If you're going to deploy machine learning model at a larger scale, chances are that it produces a lot of value. So then we'll capture some of that value in our pricing scale. >> So, you have direct sales force then to work those deals. >> Exactly. >> Got it. How many customers do you have? Just curious. >> So we started, the SaaS platform just launched now. So we started onboarding customers. We've been building this for a while. We have a bunch of, you know, partners that we can talk about openly, like, you know, revenue generating partners, that's fair to say. We work closely with Qualcomm to enable Snapdragon on TVM and hence our platform. We're close with AMD as well, enabling AMD hardware on the platform. We've been working closely with two hyperscaler cloud providers that-- >> I wonder who they are. >> I don't know who they are, right. >> Both start with the letter A. >> And they're both here, right. What is that? >> They both start with the letter A. >> Oh, that's right. >> I won't give it away. (laughing) >> Don't give it away. >> One has three, one has four. (both laugh) >> I'm guessing, by the way. >> Then we have customers in the, actually, early customers have been using the platform from the beginning in the consumer electronics space, in Japan, you know, self driving car technology, as well. As well as some AI first companies that actually, whose core value, the core business come from AI models. >> So, serious, serious customers. They got deep tech chops. They're integrating, they see this as a strategic part of their architecture. >> That's what I call AI native, exactly. But now there's, we have several enterprise customers in line now, we've been talking to. Of course, because now we launched the platform, now we started onboarding and exploring how we're going to serve it to these customers. But it's pretty clear that our technology can solve a lot of other pain points right now. And we're going to work with them as early customers to go and refine them. >> So, do you sell to the little guys, like us? Will we be customers if we wanted to be? >> You could, absolutely, yeah. >> What we have to do, have machine learning folks on staff? >> So, here's what you're going to have to do. Since you can see the booth, others can't. No, but they can certainly, you can try our demo. >> OctoML. >> And you should look at the transparent AI app that's compiled and optimized with our flow, and deployed and built with our flow. That allows you to get your image and do style transfer. You know, you can get you and a pineapple and see how you look like with a pineapple texture. >> We got a lot of transcript and video data. >> Right. Yeah. Right, exactly. So, you can use that. Then there's a very clear-- >> But I could use it. You're not blocking me from using it. Everyone's, it's pretty much democratized. >> You can try the demo, and then you can request access to the platform. >> But you get a lot of more serious deeper customers. But you can serve anybody, what you're saying. >> Luis: We can serve anybody, yeah. >> All right, so what's the vision going forward? Let me ask this. When did people start getting the epiphany of removing the machine learning from the hardware? Was it recently, a couple years ago? >> Well, on the research side, we helped start that trend a while ago. I don't need to repeat that. But I think the vision that's important here, I want the audience here to take away is that, there's a lot of progress being made in creating machine learning models. So, there's fantastic tools to deal with training data, and creating the models, and so on. And now there's a bunch of models that can solve real problems there. The question is, how do you very easily integrate that into your intelligent applications? Madrona Venture Group has been very vocal and investing heavily in intelligent applications both and user applications as well as enablers. So we say an enable of that because it's so easy to use our flow to get a model integrated into your application. Now, any regular software developer can integrate that. And that's just the beginning, right? Because, you know, now we have CI/CD integration to keep your models up to date, to continue to integrate, and then there's more downstream support for other features that you normally have in regular software development. >> I've been thinking about this for a long, long, time. And I think this whole code, no one thinks about code. Like, I write code, I'm deploying it. I think this idea of machine learning as code independent of other dependencies is really amazing. It's so obvious now that you say it. What's the choices now? Let's just say that, I buy it, I love it, I'm using it. Now what do I got to do if I want to deploy it? Do I have to pick processors? Are there verified platforms that you support? Is there a short list? Is there every piece of hardware? >> We actually can help you. I hope we're not saying we can do everything in the world here, but we can help you with that. So, here's how. When you have them all in the platform you can actually see how this model runs on any instance of any cloud, by the way. So we support all the three major cloud providers. And then you can make decisions. For example, if you care about latency, your model has to run on, at most 50 milliseconds, because you're going to have interactivity. And then, after that, you don't care if it's faster. All you care is that, is it going to run cheap enough. So we can help you navigate. And also going to make it automatic. >> It's like tire kicking in the dealer showroom. >> Right. >> You can test everything out, you can see the simulation. Are they simulations, or are they real tests? >> Oh, no, we run all in real hardware. So, we have, as I said, we support any instances of any of the major clouds. We actually run on the cloud. But we also support a select number of edge devices today, like ARMs and Nvidia Jetsons. And we have the OctoML cloud, which is a bunch of racks with a bunch Raspberry Pis and Nvidia Jetsons, and very soon, a bunch of mobile phones there too that can actually run the real hardware, and validate it, and test it out, so you can see that your model runs performant and economically enough in the cloud. And it can run on the edge devices-- >> You're a machine learning as a service. Would that be an accurate? >> That's part of it, because we're not doing the machine learning model itself. You come with a model and we make it deployable and make it ready to deploy. So, here's why it's important. Let me try. There's a large number of really interesting companies that do API models, as in API as a service. You have an NLP model, you have computer vision models, where you call an API and then point in the cloud. You send an image and you got a description, for example. But it is using a third party. Now, if you want to have your model on your infrastructure but having the same convenience as an API you can use our service. So, today, chances are that, if you have a model that you know that you want to do, there might not be an API for it, we actually automatically create the API for you. >> Okay, so that's why I get the DevOps agility for machine learning is a better description. Cause it's not, you're not providing the service. You're providing the service of deploying it like DevOps infrastructure as code. You're now ML as code. >> It's your model, your API, your infrastructure, but all of the convenience of having it ready to go, fully automatic, hands off. >> Cause I think what's interesting about this is that it brings the craftsmanship back to machine learning. Cause it's a craft. I mean, let's face it. >> Yeah. I want human brains, which are very precious resources, to focus on building those models, that is going to solve business problems. I don't want these very smart human brains figuring out how to scrub this into actually getting run the right way. This should be automatic. That's why we use machine learning, for machine learning to solve that. >> Here's an idea for you. We should write a book called, The Lean Machine Learning. Cause the lean startup was all about DevOps. >> Luis: We call machine leaning. No, that's not it going to work. (laughs) >> Remember when iteration was the big mantra. Oh, yeah, iterate. You know, that was from DevOps. >> Yeah, that's right. >> This code allowed for standing up stuff fast, double down, we all know the history, what it turned out. That was a good value for developers. >> I could really agree. If you don't mind me building on that point. You know, something we see as OctoML, but we also see at Madrona as well. Seeing that there's a trend towards best in breed for each one of the stages of getting a model deployed. From the data aspect of creating the data, and then to the model creation aspect, to the model deployment, and even model monitoring. Right? We develop integrations with all the major pieces of the ecosystem, such that you can integrate, say with model monitoring to go and monitor how a model is doing. Just like you monitor how code is doing in deployment in the cloud. >> It's evolution. I think it's a great step. And again, I love the analogy to the mainstream. I lived during those days. I remember the monolithic propriety, and then, you know, OSI model kind of blew it. But that OSI stack never went full stack, and it only stopped at TCP/IP. So, I think the same thing's going on here. You see some scalability around it to try to uncouple it, free it. >> Absolutely. And sustainability and accessibility to make it run faster and make it run on any deice that you want by any developer. So, that's the tagline. >> Luis Ceze, thanks for coming on. Professor. >> Thank you. >> I didn't know you were a professor. That's great to have you on. It was a masterclass in DevOps agility for machine learning. Thanks for coming on. Appreciate it. >> Thank you very much. Thank you. >> Congratulations, again. All right. OctoML here on theCube. Really important. Uncoupling the machine learning from the hardware specifically. That's only going to make space faster and safer, and more reliable. And that's where the whole theme of re:MARS is. Let's see how they fit in. I'm John for theCube. Thanks for watching. More coverage after this short break. >> Luis: Thank you. (gentle music)
SUMMARY :
live on the floor at AWS re:MARS 2022. for having me in the show, John. but machine learning is the And that allows you to get certainly on the silicon side. 'cause I could see the progression. So once upon a time, yeah, no... because if you wake up learning runs in the end, that's going to give you the So that was pre-conventional wisdom. the Hamilton was working on. and to this day, you know, That's the beginning of that was logical when you is that the ecosystem because that's kind of the test First, you know-- and scaling the model the way you want, not having to do that integration work. Scale, and run the models So if you can move data to the edge, So do not have any of the typical And you can use existing-- the Artemis too, in space. If they have the hardware. And that allows you So I have to ask you, So if you believe that to be true, to the chips that you want. about the smart part. And you get good recruiting for PhDs So you have to make money. And also, in the process So depends on the scale of the deployment. So, you have direct sales How many customers do you have? We have a bunch of, you know, And they're both here, right. I won't give it away. One has three, one has four. in Japan, you know, self They're integrating, they see this as it to these customers. Since you can see the booth, others can't. and see how you look like We got a lot of So, you can use that. But I could use it. and then you can request But you can serve anybody, of removing the machine for other features that you normally have It's so obvious now that you say it. So we can help you navigate. in the dealer showroom. you can see the simulation. And it can run on the edge devices-- You're a machine learning as a service. know that you want to do, I get the DevOps agility but all of the convenience it brings the craftsmanship for machine learning to solve that. Cause the lean startup No, that's not it going to work. You know, that was from DevOps. double down, we all know the such that you can integrate, and then, you know, OSI on any deice that you Professor. That's great to have you on. Thank you very much. Uncoupling the machine learning Luis: Thank you.
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Bill Andrews, ExaGrid | VeeamON 2022
(upbeat music) >> We're back at VeeamON 2022. We're here at the Aria in Las Vegas Dave Vellante with Dave Nicholson. Bill Andrews is here. He's the president and CEO of ExaGrid, mass boy. Bill, thanks for coming on theCUBE. >> Thanks for having me. >> So I hear a lot about obviously data protection, cyber resiliency, what's the big picture trends that you're seeing when you talk to customers? >> Well, I think clearly we were talking just a few minutes ago, data's growing like crazy, right This morning, I think they said it was 28% growth a year, right? So data's doubling almost just a little less than every three years. And then you get the attacks on the data which was the keynote speech this morning as well, right. All about the ransomware attacks. So we've got more and more data, and that data is more and more under attack. So I think those are the two big themes. >> So ExaGrid as a company been around for a long time. You've kind of been the steady kind of Eddy, if you will. Tell us about ExaGrid, maybe share with us some of the differentiators that you share with customers. >> Sure, so specifically, let's say in the Veeam world you're backing up your data, and you really only have two choices. You can back that up to disc. So some primary storage disc from a Dell, or a Hewlett Packard, or an NetApp or somebody, or you're going to back it up to what's called an inline deduplication appliance maybe a Dell Data Domain or an HPE StoreOnce, right? So what ExaGrid does is we've taken the best of both those but not the challenges of both those and put 'em together. So with disc, you're going to get fast backups and fast restores, but because in backup you keep weekly's, monthly's, yearly retention, the cost of this becomes exorbitant. If you go to a deduplication appliance, and let's say the Dell or the HPs, the data comes in, has to be deduplicated, compare one backup to the next to reduce that storage, which lowers the cost. So fixes that problem, but the fact that they do it inline slows the backups down dramatically. All the data is deduplicated so the restores are slow, and then the backup window keeps growing as the data grows 'cause they're all scale up technologies. >> And the restores are slow 'cause you got to rehydrate. >> You got to rehydrate every time. So what we did is we said, you got to have both. So our appliances have a front end disc cache landing zone. So you're right directed to the disc., Nothing else happens to it, whatever speed the backup app could write at that's the speed we take it in at. And then we keep the most recent backups in that landing zone ready to go. So you want to boot a VM, it's not an hour like a deduplication appliance it's a minute or two. Secondly, we then deduplicate the data into a second tier which is a repository tier, but we have all the deduplicated data for the long term retention, which gets the cost down. And on top of that, we're scale out. Every appliance has networking processor memory end disc. So if you double, triple, quadruple the data you double, triple, quadruple everything. And if the backup window is six hours at 100 terabyte it's six hours at 200 terabyte, 500 terabyte, a petabyte it doesn't matter. >> 'Cause you scale out. >> Right, and then lastly, our repository tier is non-network facing. We're the only ones in the industry with this. So that under a ransomware attack, if you get hold of a rogue server or you hack the media server, get to the backup storage whether it's disc or deduplication appliance, you can wipe out all the backup data. So you have nothing to recover from. In our case, you wipe it out, our landing zone will be wiped out. We're no different than anything else that's network facing. However, the only thing that talks to our repository tier is our object code. And we've set up security policies as to how long before you want us to delete data, let's say 10 days. So if you have an attack on Monday that data doesn't get deleted till like a week from Thursday, let's say. So you can freeze the system at any time and do restores. And then we have immutable data objects and all the other stuff. But the culmination of a non-network facing tier and the fact that we do the delayed deletes makes us the only one in the industry that can actually truly recover. And that's accelerating our growth, of course. >> Wow, great description. So that disc cache layer is a memory, it's a flash? >> It's disc, it's spinning disc. >> Spinning disc, okay. >> Yeah, no different than any other disc. >> And then the tiered is what, less expensive spinning disc? >> No, it's still the same. It's all SaaS disc 'cause you want the quality, right? So it's all SaaS, and so we use Western Digital or Seagate drives just like everybody else. The difference is that we're not doing any deduplication coming in or out of that landing zone to have fast backups and fast restores. So think of it like this, you've got disc and you say, boy it's too expensive. What I really want to do then is put maybe a deduplication appliance behind it to lower the cost or reverse it. I've got a deduplication appliance, ugh, it's too slow for backups and restores. I really want to throw this in front of it to have fast backups first. Basically, that's what we did. >> So where does the cost savings, Bill come in though, on the tier? >> The cost savings comes in the fact that we got deduplication in that repository. So only the most recent backup >> Ah okay, so I get it. >> are the duplicated data. But let's say you had 40 copies of retention. You know, 10 weekly's, 36 monthly's, a few yearly. All of that's deduplicated >> Okay, so you're deduping the stuff that's not as current. >> Right. >> Okay. >> And only a handful of us deduplicate at the layer we do. In other words, deduplication could be anywhere from two to one, up to 50 to one. I mean it's all over the place depending on the algorithm. Now it's what everybody's algorithms do. Some backup apps do two to one, some do five to one, we do 20 to one as well as much as 50 to one depending on the data types. >> Yeah, so the workload is going to largely determine the combination >> The content type, right. with the algos, right? >> Yeah, the content type. >> So the part of the environment that's behind the illogical air gap, if you will, is deduped data. >> Yes. >> So in this case, is it fair to say that you're trading a positive economic value for a little bit longer restore from that environment? >> No, because if you think about backup 95% of the customers restores are from the most recent data. >> From the disc cache. >> 95% of the time 'cause you think about why do you need fast restores? Somebody deleted a file, somebody overwrote a file. They can't go work, they can't open a file. It's encrypted, it's corrupted. That's what IT people are trying to keep users productive. When do you go for longer-term retention data? It's an SEC audit. It's a HIPAA audit. It's a legal discovery, you don't need that data right away. You have days and weeks to get that ready for that legal discovery or that audit. So we found that boundary where you keep users productive by keeping the most recent data in the disc cache landing zone, but anything that's long term. And by the way, everyone else is long term, at that point. >> Yeah, so the economics are comparable to the dedupe upfront. Are they better, obviously get the performance advance? >> So we would be a lot looped. The thing we replaced the most believe it or not is disc, we're a lot less expensive than the disc. I was meeting with some Veeam folks this morning and we were up against Cisco 3260 disc at a children's hospital. And on our quote was $500,000. The disc was 1.4 million. Just to give you an example of the savings. On a Data Domain we're typically about half the price of a Data Domain. >> Really now? >> The reason why is their front end control are so expensive. They need the fastest trip on the planet 'cause they're trying to do inline deduplication. >> Yeah, so they're chasing >> They need the fastest memory >> on the planet. >> this chips all the time. They need SSD on data to move in and out of the hash table. In order to keep up with inline, they've got to throw so much compute at it that it drives their cost up. >> But now in the case of ransomware attack, are you saying that the landing zone is still available for recovery in some circumstances? Or are you expecting that that disc landing zone would be encrypted by the attacker? >> Those are two different things. One is deletion, one is encryption. So let's do the first scenario. >> I'm talking about malicious encryption. >> Yeah, absolutely. So the first scenario is the threat actor encrypts all your primary data. What's does he go for next? The backup data. 'Cause he knows that's your belt and suspend is to not pay the ransom. If it's disc he's going to go in and put delete commands at the disc, wipe out the disc. If it's a data domain or HPE StoreOnce, it's all going to be gone 'cause it's one tier. He's going to go after our landing zone, it's going to be gone too. It's going to wipe out our landing zone. Except behind that we have the most recent backup deduplicate in the repository as well as all the other backups. So what'll happen is they'll freeze the system 'cause we weren't going to delete anything in the repository for X days 'cause you set up a policy, and then you restore the most recent backup into the landing zone or we can restore it directly to your primary storage area, right? >> Because that tier is not network facing. >> That's right. >> It's fenced off essentially. >> People call us every day of the week saying, you saved me, you saved me again. People are coming up to me here, you saved me, you saved me. >> Tell us a story about that, I mean don't give me the names but how so. >> I'll actually do a funnier story, 'cause these are the ones that our vendors like to tell. 'Cause I'm self-serving as the CEO that's good of course, a little humor. >> It's your 15 minutes of job. >> That is my 15 minutes of fame. So we had one international company who had one ExaGrid at one location, 19 Data Domains at the other locations. Ransomware attack guess what? 19 Data Domains wiped out. The one ExaGrid, the only place they could restore. So now all 20 locations of course are ExaGrids, China, Russia, Mexico, Germany, US, et cetera. They rolled us out worldwide. So it's very common for that to occur. And think about why that is, everyone who's network facing you can get to the storage. You can say all the media servers are buttoned up, but I can find a rogue server and snake my way over the storage, I can. Now, we also of course support the Veeam Data Mover. So let's talk about that since we're at a Veeam conference. We were the first company to ever integrate the Veeam Data Mover. So we were the first actually ever integration with Veeam. And so that Veeam Data Mover is a protocol that goes from Veeam to the ExaGrid, and we run it on both ends. So that's a more secure protocol 'cause it's not an open format protocol like SaaS. So with running the Veeam Data Mover we get about 30% more performance, but you do have a more secure protocol layer. So if you don't get through Veeam but you get through the protocol, boom, we've got a stronger protocol. If you make it through that somehow, or you get to it from a rogue server somewhere else we still have the repository. So we have all these layers so that you can't get at it. >> So you guys have been at this for a while, I mean decade and a half plus. And you've raised a fair amount of money but in today's terms, not really. So you've just had really strong growth, sequential growth. I understand it, and double digit growth year on year. >> Yeah, about 25% a year right now >> 25%, what's your global strategy? >> So we have sales offices in about 30 countries already. So we have three sales teams in Brazil, and three in Germany, and three in the UK, and two in France, and a lot of individual countries, Chile, Argentina, Columbia, Mexico, South Africa, Saudi, Czech Republic, Poland, Dubai, Hong Kong, Australia, Singapore, et cetera. We've just added two sales territories in Japan. We're adding two in India. And we're installed in over 50 countries. So we've been international all along the way. The goal of the company is we're growing nicely. We have not raised money in almost 10 years. >> So you're self-funding. You're cash positive. >> We are cash positive and self-funded and people say, how have you done that for 10 years? >> You know what's interesting is I remember, Dave Scott, Dave Scott was the CEO of 3PAR, and he told me when he came into that job, he told the VCs, they wanted to give him 30 million. He said, I need 80 million. I think he might have raised closer to a hundred which is right around what you guys have raised. But like you said, you haven't raised it in a long time. And in today's terms, that's nothing, right? >> 100 is 500 in today's terms. >> Yeah, right, exactly. And so the thing that really hurt 3PAR, they were public companies so you could see all this stuff is they couldn't expand internationally. It was just too damn expensive to set up the channels, and somehow you guys have figured that out. >> 40% of our business comes out of international. We're growing faster internationally than we are domestically. >> What was the formula there, Bill, was that just slow and steady or? >> It's a great question. >> No, so what we did, we said let's build ExaGrid like a McDonald's franchise, nobody's ever done that before in high tech. So what does that mean? That means you have to have the same product worldwide. You have to have the same spares model worldwide. You have to have the same support model worldwide. So we early on built the installation. So we do 100% of our installs remotely. 100% of our support remotely, yet we're in large enterprises. Customers racks and stacks the appliances we get on with them. We do the entire install on 30 minutes to about three hours. And we've been developing that into the product since day one. So we can remotely install anywhere in the world. We keep spares depots all over the world. We can bring 'em up really quick. Our support model is we have in theater support people. So they're in Europe, they're in APAC, they're in the US, et cetera. And we assign customers to the support people. So they deal with the same support person all the time. So everything is scalable. So right now we're going to open up India. It's the same way we've opened up every other country. Once you've got the McDonald's formula we just stamp it all over the world. >> That's amazing. >> Same pricing, same product same model, same everything. >> So what was the inspiration for that? I mean, you've done this since day one, which is what like 15, 16 years ago. Or just you do engineering or? >> No, so our whole thought was, first of all you can't survive anymore in this world without being an international company. 'Cause if you're going to go after large companies they have offices all over the world. We have companies now that have 17, 18, 20, 30 locations. And there were in every country in the world, you can't go into this business without being able to ship anywhere in the world and support it for a single customer. You're not going into Singapore because of that. You're going to Singapore because some company in Germany has offices in the U.S, Mexico Singapore and Australia. You have to be international. It's a must now. So that was the initial thing is that, our goal is to become a billion dollar company. And we're on path to do that, right. >> You can see a billion. >> Well, I can absolutely see a billion. And we're bigger than everybody thinks. Everybody guesses our revenue always guesses low. So we're bigger than you think. The reason why we don't talk about it is we don't need to. >> That's the headline for our writers, ExaGrid is a billion dollar company and nobody's know about it. >> Million dollar company. >> On its way to a billion. >> That's right. >> You're not disclosing. (Bill laughing) But that's awesome. I mean, that's a great story. I mean, you kind of are a well kept secret, aren't you? >> Well, I dunno if it's a well kept secret. You know, smaller companies never have their awareness of big companies, right? The Dells of the world are a hundred billion. IBM is 70 billion, Cisco is 60 billion. Easy to have awareness, right? If you're under a billion, I got to give a funny story then I think we got to close out here. >> Oh go ahead please. >> So there's one funny story. So I was talking to the CIO of a super large Fortune 500 company. And I said to him, "Just so who do you use?" "I use IBM Db2, and I use, Cisco routers, and I use EMC primary storage, et cetera. And I use all these big." And I said, "Would you ever switch from Db2?" "Oh no, the switching costs would kill me. I could never go to Oracle." So I said to him, "Look would you ever use like a Pure Storage, right. A couple billion dollar company." He says, "Who?" >> Huh, interesting. >> I said to him, all right so skip that. I said, "VMware, would you ever think about going with Nutanix?" "Who?" Those are billion dollar plus companies. And he was saying who? >> Public companies. >> And he was saying who? That's not uncommon when I talk to CIOs. They see the big 30 and that's it. >> Oh, that's interesting. What about your partnership with Veeam? Tell us more about that. >> Yeah, so I would actually, and I'm going to be bold when I say this 'cause I think you can ask anybody here at the conference. We're probably closer first of all, to the Veeam sales force than any company there is. You talk to any Veeam sales rep, they work closer with ExaGrid than any other. Yeah, we are very tight in the field and have been for a long time. We're integrated with the Veeam Data Boomer. We're integrated with SOBR. We're integrated with all the integrations or with the product as well. We have a lot of joint customers. We actually do a lot of selling together, where we go in as Veeam ExaGrid 'cause it's a great end to end story. Especially when we're replacing, let's say a Dell Avamar to Dell Data Domain or a Dell Network with a Dell Data Domain, very commonly Veeam ExaGrid go in together on those types of sales. So we do a lot of co-selling together. We constantly train their systems engineers around the world, every given week we're training either inside sales teams, and we've trained their customer support teams in Columbus and Prague. So we're very tight with 'em we've been tight for over a decade. >> Is your head count public? Can you share that with us? >> So we're just over 300 employees. >> Really, wow. >> We have 70 open positions, so. >> Yeah, what are you looking for? Yeah, everything, right? >> We are looking for engineers. We are looking for customer support people. We're looking for marketing people. We're looking for inside sales people, field people. And we've been hiring, as of late, major account reps that just focus on the Fortune 500. So we've separated that out now. >> When you hire engineers, I mean I think I saw you were long time ago, DG, right? Is that true? >> Yeah, way back in the '80s. >> But systems guy. >> That's how old I am. >> Right, systems guy. I mean, I remember them well Eddie Castro and company. >> Tom West. >> EMV series. >> Tom West was the hero of course. >> The EMV 4000, the EMV 20,000, right? >> When were kids, "The Soul of a New Machine" was the inspirational book but anyway, >> Yeah Tracy Kidder, it was great. >> Are you looking for systems people, what kind of talent are you looking for in engineering? >> So it's a lot of Linux programming type stuff in the product 'cause we run on a Linux space. So it's a lot of Linux programs so its people in those storage. >> Yeah, cool, Bill, hey, thanks for coming on to theCUBE. Well learned a lot, great story. >> It's a pleasure. >> That was fun. >> Congratulations. >> Thanks. >> And good luck. >> All right, thank you. >> All right, and thank you for watching theCUBE's coverage of VeeamON 2022, Dave Vellante for Dave Nicholson. We'll be right back right after this short break, stay with us. (soft beat music)
SUMMARY :
We're here at the Aria in Las Vegas And then you get the attacks on the data You've kind of been the steady and let's say the Dell or And the restores are slow that's the speed we take it in at. and the fact that we So that disc cache layer No, it's still the same. So only the most recent backup are the duplicated data. Okay, so you're deduping the deduplicate at the layer we do. with the algos, right? So the part of the environment 95% of the customers restores 95% of the time 'cause you think about Yeah, so the economics are comparable example of the savings. They need the fastest trip on the planet in and out of the hash table. So let's do the first scenario. So the first scenario is the threat actor Because that tier day of the week saying, I mean don't give me the names but how so. 'Cause I'm self-serving as the CEO So if you don't get through Veeam So you guys have been The goal of the company So you're self-funding. what you guys have raised. And so the thing that really hurt 3PAR, than we are domestically. It's the same way we've Same pricing, same product So what was the inspiration for that? country in the world, So we're bigger than you think. That's the headline for our writers, I mean, you kind of are a The Dells of the world So I said to him, "Look would you ever I said, "VMware, would you ever think They see the big 30 and that's it. Oh, that's interesting. So we do a lot of co-selling together. that just focus on the Fortune 500. Eddie Castro and company. in the product 'cause thanks for coming on to theCUBE. All right, and thank you for watching
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Day 2 theCUBE Kickoff | UiPath FORWARD IV
>>From the Bellagio hotel in Las Vegas. It's the cube covering UI path forward for brought to you by UI path. >>Good morning. Welcome to the cubes coverage of UI path forward for day two. Live from the Bellagio in Las Vegas. I'm Lisa Martin with Dave Velante, Dave. We had a great action packed day yesterday. We're going to have another action packed day today. We've got the CEO coming on. We've got customers coming on, but there's been a lot in the news last 24 hours. Facebook, what are your thoughts? >>Yeah, so wall street journal today, headline Facebook hearing fuels call for rain in on big tech. All right, everybody's going after big tech. Uh, for those of you who missed it, 60 minutes had a, uh, an interview with the whistleblower. Her name is, uh, Francis Haugen. She's very credible, just a little background. I'll give you my take. I mean, she was hired to help set Facebook straight and protect privacy of individuals, of children. And I really feel like, again, she, she didn't come across as, as bitter or antagonistic, but, but I feel as though she feels betrayed, right, I think she was hired to do a job. They lured her in to say, Hey, this is again, just my take to say, Hey, we want your help in earnest to protect the privacy of our users, our citizens, et cetera. And I think she feels betrayed because she's now saying, listen, this is not cool. >>You hired us to do a job. We in earnest, went in and tried to solve this problem. And you guys kind of ignored it and you put profit ahead of safety. And I think that is the fundamental crux of this. Now she made a number of really good points in her hearing yesterday and I'll, and we'll try to summarize, I mean, there's a lot of putting advertising revenue ahead of children's safety and, and, and others. The examples they're using are during the 2020 election, they shut down any sort of negative conversations. They would be really proactive about that, but after the election, they turned it back on and you know, we all know what happened on January 6th. So there's sort of, you know, the senators are trying that night. Um, the second thing is she talked about Facebook as a wall garden, and she made the point yesterday at the congressional hearings that Google actually, you can data scientists, anybody can go download all the data that Google has on you. >>You and I can do that. Right? There's that website that we've gone to and you look at all the data Google has and you kind of freak out. Yeah, you can't do that with Facebook, right? It's all hidden. So it's kind of this big black box. I will say this it's interesting. The calls for breaking up big tech, Bernie Sanders tweeted something out yesterday said that, uh, mark Zuckerberg was worth, I don't know. I think 9 billion in 2007 or eight or nine, whatever it was. And he's worth 122 billion today, which of course is mostly tied up in Facebook stock, but still he's got incredible wealth. And then Bernie went on his red it's time to break up big tech. It's time to get people to pay their fair share, et cetera. I'm intrigued that the senators don't have as much vigilance around other industries, whether it's big pharma, food companies addicting children to sugar and the like, but that doesn't let Facebook. >>No, it doesn't, but, but you ha you bring up a good point. You and I were chatting about this yesterday. What the whistleblower is identifying is scary. It's dangerous. And the vast majority, I think of its users, don't understand it. They're not aware of it. Um, and why is big tech being maybe singled out and use as an example here, when, to your point, you know, the addiction to sugar and other things are, uh, have very serious implications. Why is big tech being singled out here as the poster child for what's going wrong? >>Well, and they're comparing it to big tobacco, which is the last thing you want to be compared to as big tobacco. But the, but the, but the comparison is, is valid in that her claim, the whistleblower's claim was that Facebook had data and research that it knew, it knows it's hurting, you know, you know, young people. And so what did it do? It created, you know, Instagram for kids, uh, or it had 600,000. She had another really interesting comment or maybe one of the senators did. Facebook said, look, we scan our records and you know, kids lie. And we, uh, we kicked 600,000 kids off the network recently who were underaged. And the point was made if you have 600,000 people on your network that are underage, you have to go kill. That's a problem. Right? So now the flip side of this, again, trying to be balanced is Facebook shut down Donald Trump and his nonsense, uh, and basically took him off the platform. >>They kind of thwarted all the hunter Biden stuff, right. So, you know, they did do some, they did. It's not like they didn't take any actions. Uh, and now they're up, you know, in front of the senators getting hammered. But I think the Zuckerberg brings a lot of this on himself because he put out an Instagram he's on his yacht, he's drinking, he's having fun. It's like he doesn't care. And he, you know, who knows, he probably doesn't. She also made the point that he owns an inordinate percentage and controls an inordinate percentage of the stock, I think 52% or 53%. So he can kind of do what he wants. And I guess, you know, coming back to public policy, there's a lot of narrative of, I get the billionaires and I get that, you know, the Mo I'm all for billionaires paying more taxes. >>But if you look at the tax policies that's coming out of the house of representatives, it really doesn't hit the billionaires the way billionaires can. We kind of know the way that they protect their wealth is they don't sell and they take out low interest loans that aren't taxed. And so if you look at the tax policies that are coming out, they're really not going after the billionaires. It's a lot of rhetoric. I like to deal in facts. And so I think, I think there's, there's a lot of disingenuous discourse going on right now at the same time, you know, Facebook, they gotta, they gotta figure it out. They have to really do a better job and become more transparent, or they are going to get broken up. And I think that's a big risk to the, to their franchise and maybe Zuckerberg doesn't care. Maybe he just wants to give it a, give it to the government, say, Hey, are you guys are on? It >>Happens. What do you think would happen with Amazon, Google, apple, some of the other big giants. >>That's a really good question. And I think if you look at the history of the us government, in terms of ant anti monopolistic practices, it spent decade plus going after IBM, you know, at the end of the day and at the same thing with Microsoft at the end of the day, and those are pretty big, you know, high profiles. And then you look at, at T and T the breakup of at T and T if you take IBM, IBM and Microsoft, they were slowed down by the U S government. No question I've in particular had his hands shackled, but it was ultimately their own mistakes that caused their problems. IBM misunderstood. The PC market. It gave its monopoly to Intel and Microsoft, Microsoft for its part. You know, it was hugging windows. They tried to do the windows phone to try to jam windows into everything. >>And then, you know, open source came and, you know, the world woke up and said, oh, there's this internet that's built on Linux. You know, that kind of moderated by at T and T was broken up. And then they were the baby bells, and then they all got absorbed. And now you have, you know, all this big, giant telcos and cable companies. So the history of the U S government in terms of adjudicating monopolistic behavior has not been great at the same time. You know, if companies are breaking the law, they have to be held accountable. I think in the case of Amazon and Google and apple, they, a lot of lawyers and they'll fight it. You look at what China's doing. They just cut right to the chase and they say, don't go to the, they don't litigate. They just say, this is what we're doing. >>Big tech, you can't do a, B and C. We're going to fund a bunch of small startups to go compete. So that's an interesting model. I was talking to John Chambers about this and he said, you know, he was flat out that the Western way is the right way. And I believe in, you know, democracy and so forth. But I think if, to answer your question, I think they'll, they'll slow it down in courts. And I think at some point somebody's going to figure out a way to disrupt these big companies. They always do, you know, >>You're right. They always do >>Right. I mean, you know, the other thing John Chambers points out is that he used to be at 1 28, working for Wang. There is no guarantee that the past is prologue that because you succeeded in the past, you're going to succeed in the future. So, so that's kind of the Facebook break up big tech. I'd like to see a little bit more discussion around, you know, things like food companies and the, like >>You bring up a great point about that, that they're equally harmful in different ways. And yet they're not getting the visibility that a Facebook is getting. And maybe that's because of the number of users that it has worldwide and how many people depend on it for communication, especially in the last 18 months when it was one of the few channels we had to connect and engage >>Well. And, and the whistleblower's point, Facebook puts out this marketing narrative that, Hey, look at all this good we're doing in reality. They're all about the, the, the advertising profits. But you know, I'm not sure what laws they're breaking. They're a public company. They're, they're, they have a responsibility to shareholders. So that's, you know, to be continued. The other big news is, and the headline is banks challenge, apple pay over fees for transactions, right? In 2014, when apple came up with apple pay, all the banks lined up, oh, they had FOMO. They didn't want to miss out on this. So they signed up. Now. They don't like the fact that they have to pay apple fees. They don't like the fact that apple introduced its own credit card. They don't like the fact that they have to pay fees on monthly recurring charges on your, you know, your iTunes. >>And so we talked about this and we talk about it a lot on the cube is that, that in, in, in, in his book, seeing digital David, Michelle, or the author talked about Silicon valley broadly defined. So he's including Seattle, Microsoft, but more so Amazon, et cetera, has a dual disruption agenda. They're not only trying to disrupt horizontally the technology industry, but they're also disrupting industry. We talked about this yesterday, apple and finances. The example here, Amazon, who was a bookseller got into cloud and is in grocery and is doing content. And you're seeing these a large companies, traverse industry value chains, which have historically been very insulated right from that type of competition. And it's all because of digital and data. So it's a very, pretty fascinating trends going on. >>Well, from a financial services perspective, we've been seeing the unbundling of the banks for a while. You know, the big guys with B of A's, those folks are clearly concerned about the smaller, well, I'll say the smaller FinTech disruptors for one, but, but the non FinTech folks, the apples of the world, for example, who aren't in that industry who are now to your point, disrupting horizontally and now going after individual specific industries, ultimately I think as consumers we want, whatever is going to make our lives easier. Um, do you ever, ever, I always kind of scratch my nose when somebody doesn't take apple pay, I'm like, you don't take apple pay so easy. It's so easy to make this easy for me. >>Yeah. Yeah. So it's, it's going to be really interesting to see how this plays out. I, I do think, um, you know, it begs the question when will banks or Willbanks lose control of the payment systems. They seem to be doing that already with, with alternative forms of payment, uh, whether it's PayPal or Stripe or apple pay. And then crypto is, uh, with, with, with decentralized finance is a whole nother topic of disruption and innovation, >>Right? Well, these big legacy institutions, these organizations, and we've spoke with some of them yesterday, we're going to be speaking with some of them today. They need to be able to be agile, to transform. They have to have the right culture in order to do that. That's the big one. They have to be willing. I think an open to partner with the broader ecosystem to unlock more opportunities. If they want to be competitive and retain the trust of the clients that they've had for so long. >>I think every industry has a digital disruption scenario. We used to always use the, don't get Uber prized example Uber's coming on today, right? And, and there isn't an industry, whether it's manufacturing or retail or healthcare or, or government that isn't going to get disrupted by digital. And I think the unique piece of this is it's it's data, data, putting data at the core. That's what the big internet giants have done. That's what we're hearing. All these incumbents try to do is to put data. We heard this from Coca-Cola yesterday, we're putting data at the core of our company and what we're enabling through automation and other activities, uh, digital, you know, a company. And so, you know, can these, can these giants, these hundred plus year old giants compete? I think they can because they don't have to invent AI. They can work with companies like UI path and embed AI into their business and focused on, on what they do best. Now, of course, Google and Amazon and Facebook and Microsoft there may be going to have the best AI in the world. But I think ultimately all these companies are on a giant collision course, but the market is so huge that I think there's a lot of, >>There's a tremendous amount of opportunity. I think one of the things that was exciting about talking to one, the female CIO of Coca-Cola yesterday, a hundred plus old organization, and she came in with a very transformative, very different mindset. So when you see these, I always appreciate when I say legacy institutions like Coca-Cola or Merck who was on yesterday, blue cross blue shield who's on today, embracing change, cultural change going. We can't do things the way we used to do, because there are competitors in that review mirror who are smaller, they're more nimble, they're faster. They're going to be, they're going to take our customers away from us. We have to deliver this exceptional customer and employee experience. And Coca-Cola is a great example of one that really came in with CA brought in a disruptor in order to align digital with the CEO's thoughts and processes and organization. These are >>Highly capable companies. We heard from the head of finance at, at applied materials today. He was also coming on. I was quite, I mean, this is a applied materials is really strong company. They're talking about a 20 plus billion dollar company with $120 billion market cap. They supply semiconductor equipment and they're a critical component of the semiconductor supply chain. And we all know what's going on in semiconductors today with a huge shortage. So they're a really important company, but I was impressed with, uh, their finance leaders vision on how they're transforming the company. And it was not like, you know, 10 years out, these were not like aspirational goals. This is like 20, 19, 20, 22. Right. And, and really taking costs out of the business, driving new innovation. And, and it's, it was it's, it's refreshing to me Lisa, to see CFOs, you know, typically just bottom line finance focused on these industry transformations. Now, of course, at the end of the day, it's all about the bottom line, but they see technology as a way to get there. In fact, he put technology right in the middle of his stack. I want to ask him about that too. I actually want to challenge him a little bit on it because he had that big Hadoop elephant in the middle and this as an elephant in the room. And that picture, >>The strategy though, that applied materials had, it was very well thought out, but it was also to your point designed to create outcomes year upon year upon year. And I was looking at some of the notes. I took that in year one, alone, 274 automations in production. That's a lot, 150,000 in annual work hours automated 124 use cases they tackled in one year. >>So I want to, I want to poke at that a little bit too. And I, and I did yesterday with some guests. I feel like, well, let's see. So, um, I believe it was, uh, I forget what guests it was, but she said we don't put anything forward that doesn't hit the income statement. Do you remember that? Yes, it was Chevron because that was pushing her. I'm like, well, you're not firing people. Right. And we saw from IDC data today, only 13% of organizations are saying, or, or, or the organizations at 13% of the value was from reduction in force. And a lot of that was probably in plan anyway, and they just maybe accelerated it. So they're not getting rid of headcount, but they're counting hours saved. So that says to me, there's gotta be an normally or often CFOs say, well, it's that soft dollars because we're redeploying folks. But she said, no, it hits the income statement. So I don't, I want to push a little bit and see how they connect the dots, because if you're going to save hours, you're going to apply people to new work. And so either they're generating revenue or cutting costs somewhere. So, so there's another layer that I want to appeal to understand how that hits the income state. >>Let's talk about some of that IDC data. They announced a new white paper this morning sponsored by UI path. And I want to get your perspectives on some of the stats that they talked about. They were painting a positive picture, an optimistic picture. You know, we can't talk about automation without talking about the fear of job loss. They've been in a very optimistic picture for the actual gains over a few year period. What are your thoughts about that? Especially when we saw that stat 41% slowed hiring. >>Yeah. So, well, first of all, it's a sponsored study. So, you know, and of course the conferences, so it's going to be, be positive, but I will say this about IDC. IDC is a company I would put, you know, forest they're similar. They do sponsored research and they're credible. They don't, they, they have the answer to their audience, so they can't just out garbage. And so it has to be defensible. So I give them credit there that they won't just take whatever the vendor wants them to write and then write it. I've used to work there. And I, and I know the culture and there's a great deal of pride in being able to defend what you do. And if the answer doesn't come out, right, sorry, this is the answer. You know, you could pay a kill fee or I dunno how they handle it today. >>But, but, so my point is I think, and I know the people who did that study, many of them, and I think they're pretty credible. I, I thought by the way, you, to your 41% point. So the, the stat was 13% are gonna reduce head count, right? And then there were two in the middle and then 41% are gonna reduce or defer hiring in the future. And this to me, ties into the Erik Brynjolfsson and, and, and, uh, and, and McAfee work. Andy McAfee work from MIT who said, look, initially actually made back up. They said, look at machines, have always replaced humans. Historically this was in their book, the second machine age and what they said was, but for the first time in history, machines are replacing humans with cognitive functions. And this is sort of, we've never seen this before. It's okay. That's cool. >>And their, their research suggests that near term, this is going to be a negative economic impact, sorry, negative impact on jobs and salaries. And we've, we've generally seen this, the average salary, uh, up until recently has been flat in the United States for years and somewhere in the mid fifties. But longterm, their research shows that, and this is consistent. I think with IDC that it's going to help hiring, right? There's going to be a boost buddy, a net job creator. And there's a, there's a, there's a chasm you've got across, which is education training and skill skillsets, which Brynjolfsson and McAfee focused on things that humans can do that machines can't. And you have this long list and they revisited every year. Like they used to be robots. Couldn't walk upstairs. Well, you see robots upstairs all the time now, but it's empathy, it's creativity. It's things like that. >>Contact that humans are, are much better at than machines, uh, even, even negotiations. And, and so, so that's, those are skills. I don't know where you get those skills. Do you teach those and, you know, MBA class or, you know, there's these. So their point is there needs to be a new thought process around education, public policy, and the like, and, and look at it. You can't protect the past from the future, right? This is inevitable. And we've seen this in terms of economic activity around the world countries that try to protect, you know, a hundred percent employment and don't let competition, they tend to fall behind competitively. You know, the U S is, is not of that category. It's an open market. So I think this is inevitable. >>So a lot about upskilling yesterday, and the number of we talked with PWC about, for example, about what they're doing and a big focus on upscaling. And that was part of the IDC data that was shared this morning. For example, I'll share a stat. This was a survey of 518 people. 68% of upscaled workers had higher salaries than before. They also shared 57% of upskilled workers had higher roles and their enterprises then before. So some, again, two point it's a sponsored study, so it's going to be positive, but there, there was a lot of discussion of upskilling yesterday and the importance on that education, because to your point, we can't have one without the other. You can't give these people access to these tools and not educate them on how to use it and help them help themselves become more relevant to the organization. Get rid of the mundane tasks and be able to start focusing on more strategic business outcome, impacting processes. >>We talked yesterday about, um, I use the example of, of SAP. You, you couldn't have predicted SAP would have won the ERP wars in the early to mid 1990s, but if you could have figured out who was going to apply ERP to their businesses, you know what, you know, manufacturing companies and these global firms, you could have made a lot of money in the stock market by, by identifying those that were going to do that. And we used to say the same thing about big data, and the reason I'm bringing all this up is, you know, the conversations with PWC, Deloitte and others. This is a huge automation, a huge services opportunity. Now, I think the difference between this and the big data era, which is really driven by Hadoop is it was big data was so complicated and you had a lack of data scientists. >>So you had to hire these services firms to come in and fill those gaps. I think this is an enormous services opportunity with automation, but it's not because the software is hard to get to work. It's all around the organizational processes, rethinking those as people process technology, it's about the people in the process, whereas Hadoop and the big data era, it was all about the tech and they would celebrate, Hey, this stuff works great. There are very few companies really made it through that knothole to dominate as we've seen with the big internet giants. So you're seeing all these big services companies playing in this market because as I often say, they like to eat at the trough. I know it's kind of a pejorative, but it's true. So it's huge, huge market, but I'm more optimistic about the outcomes for a broader audience with automation than I was with, you know, big data slash Hadoop, because I think the software as much, as much more adoptable, easier to use, and you've got the cloud and it's just a whole different ball game. >>That's certainly what we heard yesterday from Chevron about the ease of use and that you should be able to see results and returns very quickly. And that's something too that UI path talks about. And a lot of their marketing materials, they have a 96, 90 7% retention rate. They've done a great job building their existing customers land and expand as we talked about yesterday, a great use case for that, but they've done so by making things easy, but hearing that articulated through the voice of their customers, fantastic validation. >>So, you know, the cube is like a little, it's like a interesting tip of the spirits, like a probe. And I will tell you when I, when we first started doing the cube and the early part of the last decade, there were three companies that stood out. It was Splunk service now and Tableau. And the reason they stood out is because they were able to get customers to talk about how great they were. And the light bulb went off for us. We were like, wow, these are three companies to watch. You know, I would tell all my wall street friends, Hey, watch these companies. Yeah. And now you see, you know, with Frank Slootman at snowflake, the war, the cat's out of the bag, everybody knows it's there. And they're expecting, you know, great things. The stock is so priced to perfection. You could argue, it's overpriced. >>The reason I'm bringing this up is in terms of customer loyalty and affinity and customer love. You're getting it here. Absolutely this ecosystem. And the reason I bring that up is because there's a lot of questions in the, in the event last night, it was walking around. I saw a couple of wall street guys who came up to me and said, Hey, I read your stuff. It was good. Let's, let's chat. And there's a lot of skepticism on, on wall street right now about this company. Right? And to me, that's, that's good news for you. Investors who want to do some research, because the words may be not out. You know, they, they, they gotta prove themselves here. And to me, the proof is in the customer and the lifetime value of that customer. So, you know, again, we don't give stock advice. We, we kind of give fundamental observations, but this stock, I think it's trading just about 50. >>Now. I don't think it's going to go to 30, unless the market just tanks. It could have some, you know, if that happens, okay, everything will go down. But I actually think, even though this is a richly priced stock, I think the future of this company is very bright. Obviously, if they continue to execute and we're going to hear from the CEO, right? People don't know Daniel, Denise, right? They're like, who is this guy? You know, he started this company and he's from Eastern Europe. And we know he's never have run a public company before, so they're not diving all in, you know? And so that to me is something that really pay attention to, >>And we can unpack that with him later today. And we've got some great customers on the program. You mentioned Uber's here. Spotify is here, applied materials. I feel like I'm announcing something on Saturday night. Live Uber's here. Spotify is here. All right, Dave, looking forward to a great action packed today. We're going to dig more into this and let's get going. Shall we let's do it. All right. For David Dante, I'm Lisa Martin. This is the cube live in Las Vegas. At the Bellagio. We are coming to you presenting UI path forward for come back right away. Our first guest comes up in just a second.
SUMMARY :
UI path forward for brought to you by UI path. Live from the Bellagio in Las Vegas. And I think she feels betrayed because she's now saying, So there's sort of, you know, the senators are trying that night. There's that website that we've gone to and you look at all the data Google has and you kind of freak out. And the vast majority, I think of its users, And the point was made if you have 600,000 I get the billionaires and I get that, you know, the Mo I'm all for billionaires paying more taxes. And I think that's a big risk to the, to their franchise and maybe Zuckerberg doesn't care. What do you think would happen with Amazon, Google, apple, some of the other big giants. And I think if you look at the history of the us You know, if companies are breaking the law, they have to be held accountable. And I believe in, you know, democracy and so forth. They always do I mean, you know, the other thing John Chambers points out is that he used to be at 1 28, And maybe that's because of the number of users that it has worldwide and how many They don't like the fact that they have to pay apple fees. And so we talked about this and we talk about it a lot on the cube is that, that in, You know, the big guys with B of A's, those folks are clearly concerned about the smaller, I, I do think, um, you know, it begs the question when will I think an open to partner and other activities, uh, digital, you know, a company. And Coca-Cola is a great example of one that really came in with CA Now, of course, at the end of the day, it's all about the bottom line, but they see technology as And I was looking at some of the notes. And a lot of that was probably in plan anyway, And I want to get your perspectives on some of the stats that they talked about. And I, and I know the culture and there's a great deal of pride in being And this to me, ties into the Erik Brynjolfsson And their, their research suggests that near term, this is going to be a negative economic activity around the world countries that try to protect, you know, a hundred percent employment and don't let competition, Get rid of the mundane tasks and be able to start focusing on more strategic business outcome, data, and the reason I'm bringing all this up is, you know, the conversations with PWC, and the big data era, it was all about the tech and they would celebrate, That's certainly what we heard yesterday from Chevron about the ease of use and that you should be able to see results and returns very And I will tell you when I, when we first started doing the cube and the early part And the reason I bring that up is because there's a lot of questions in the, in the event last night, And so that to me is something that really pay We are coming to you presenting UI path forward for come back right away.
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Clayton Coleman, Red Hat | Red Hat Summit 2021 Virtual Experience
>>mhm Yes, Welcome back to the cubes coverage of red hat summit 2021 virtual, which we were in person this year but we're still remote. We still got the Covid coming around the corner. Soon to be in post. Covid got a great guest here, Clayton Coleman architect that red hat cuba love and I've been on many times expanded role again this year. More cloud, more cloud action. Great, great to see you. Thanks for coming on. >>It's a pleasure >>to be here. So great to see you were just riffing before we came on camera about distributed computing uh and the future of the internet, how it's all evolving, how much fun it is, how it's all changing still. The game is still the same, all that good stuff. But here at Red had some and we're gonna get into that, but I want to just get into the hard news and the real big, big opportunities here you're announcing with red hat new managed cloud services portfolio, take us through that. >>Sure. We're continuing to evolve our open shift managed offerings which has grown now to include um the redhead open shift service on amazon to complement our as your redhead open shift service. Um that means that we have um along with our partnership on IBM cloud and open ship dedicated on both a W S and G C P. We now have um managed open shift on all of the major clouds. And along with that we are bringing in and introducing the first, I think really the first step what we see as uh huh growing and involving the hybrid cloud ecosystem on top of open shift and there's many different ways to slice that, but it's about bringing capabilities on top of open shift in multiple environments and multiple clouds in ways that make developers and operation teams more productive because at the heart of it, that's our goal for open shift. And the broader, open source ecosystem is do what makes all of us safer, more, uh, more productive and able to deliver business value? >>Yeah. And that's a great steak you guys put in the ground. Um, and that's great messaging, great marketing, great value proposition. I want to dig into a little bit with you. I mean, you guys have, I think the only native offering on all the clouds out there that I know of, is that true? I mean, you guys have, it's not just, you know, you support AWS as your and I B M and G C P, but native offerings. >>We do not have a native offering on GCPD offered the same service. And this is actually interesting as we've evolved our approach. You know, everyone, when we talk about hybrid, Hybrid is, um, you know, dealing with the realities of the computing world, We live in, um, working with each of the major clouds, trying to deliver the best immigration possible in a way that drives that consistency across those environments. And so actually are open shift dedicated on AWS service gave us the inspiration a lot of the basic foundations for what became the integrated Native service. And we've worked with amazon very closely to make sure that that does the right thing for customers who have chosen amazon. And likewise, we're trying to continue to deliver the best experience, the best operational reliability that we can so that the choice of where you run your cloud, um, where you run your applications, um, matches the decisions you've already made and where your future investments are gonna be. So we want to be where customers are, but we also want to give you that consistency. That has been a hallmark of um of open shift since the beginning. >>Yeah. And thanks for clarifying, I appreciate that because the manage serves on GCB rest or native. Um let me ask about the application services because Jeff Barr from AWS posted a few weeks ago amazon celebrated their 15th birthday. They're still teenagers uh relatively speaking. But one comment he made that he that was interesting to me. And this applies kind of this cloud native megatrend happening is he says the A. P. I. S are basically the same and this brings up the hybrid environment. You guys are always been into the api side of the management with the cloud services and supporting all that. As you guys look at this ecosystem in open source. How is the role of A PS and these integrations? Because without solid integration all these services could break down and certainly the open source, more and more people are coding. So take me through how you guys look at these applications services because many people are predicting more service is going to be on boarding faster than ever before. >>It's interesting. So um for us working across multiple cloud environments, there are many similarities in those mps, but for every similarity there is a difference and those differences are actually what dr costs and drive complexity when you're integrating. Um and I think a lot of the role of this is, you know, the irresponsible to talk about the role of an individual company in the computing ecosystem moving to cloud native because as many of these capabilities are unlocked by large cloud providers and transformations in the kinds of software that we run at scale. You know, everybody is a participant in that. But then you look at the broad swath of developer and operator ecosystem and it's the communities of people who paper over those differences, who write run books and build um you know, the policies and who build the experience and the automation. Um not just in individual products or an individual clouds, but across the open source ecosystem. Whether it's technologies like answerable or Terror form, whether it's best practices websites around running kubernetes, um every every part of the community is really involved in driving up uh driving consistency, um driving predictability and driving reliability and what we try to do is actually work within those constraints um to take the ecosystem and to push it a little bit further. So the A. P. I. S. May be similar, but over time those differences can trip you up. And a lot of what I think we talked about where the industry is going, where where we want to be is everyone ultimately is going to own some responsibility for keeping their services running and making sure that their applications and their businesses are successful. The best outcome would be that the A. P. R. S are the same and they're open and that both the cloud providers and the open source ecosystem and vendors and partners who drive many of these open source communities are actually all working together to have the most consistent environment to make portability a true strength. But when someone does differentiate and has a true best to bring service, we don't want to build artificial walls between those. I mean, I mean, that's hybrid cloud is you're going to make choices that make sense for you if we tell people that their choices don't work or they can't integrate or, you know, an open source project doesn't support this vendor, that vendor, we're actually leaving a lot of the complexity buried in those organizations. So I think this is a great time to, as we turn over for cloud. Native looking at how we, as much as possible try to drive those ap is closer together and the consistency underneath them is both a community and a vendor. And uh for red hat, it's part of what we do is a core mission is trying to make sure that that consistency is actually real. You don't have to worry about those details when you're ignoring them. >>That's a great point. Before I get into some architectural impact, I want to get your thoughts on um, the, this trends going on, Everyone jumps on the bandwagon. You know, you say, oh yeah, I gotta, I want a data cloud, you know, everything is like the new, you know, they saw Snowflake Apollo, I gotta have some, I got some of that data, You've got streaming data services, you've got data services and native into the, these platforms. But a lot of these companies think it's just, you're just gonna get a data cloud, just, it's so easy. Um, they might try something and then they get stuck with it or they have to re factor, >>how do you look >>at that as an architect when you have these new hot trends like say a data cloud, how should customers be thinking about kicking the tires on services like that And how should they think holistically around architect in that? >>There's a really interesting mindset is, uh, you know, we deal with this a lot. Everyone I talked to, you know, I've been with red hat for 10 years now in an open shift. All 10 years of that. We've gone through a bunch of transformations. Um, and every time I talked to, you know, I've talked to the same companies and organizations over the last 10 years, each point in their evolution, they're making decisions that are the right decision at the time. Um, they're choosing a new capability. So platform as a service is a great example of a capability that allowed a lot of really large organizations to standardize. Um, that ties into digital transformation. Ci CD is another big trend where it's an obvious wind. But depending on where you jumped on the bandwagon, depending on when you adopted, you're going to make a bunch of different trade offs. And that, that process is how do we improve the ability to keep all of the old stuff moving forward as well? And so open api is open standards are a big part of that, but equally it's understanding the trade offs that you're going to make and clearly communicating those so with data lakes. Um, there was kind of the 1st and 2nd iterations of data lakes, there was the uh, in the early days these capabilities were knew they were based around open source software. Um, a lot of the Hadoop and big data ecosystem, you know, started based on some of these key papers from amazon and google and others taking infrastructure ideas bringing them to scale. We went through a whole evolution of that and the input and the output of that basically let us into the next phase, which I think is the second phase of data leak, which is we have this data are tools are so much better because of that first phase that the investments we made the first time around, we're going to have to pay another investment to make that transformation. And so I've actually, I never want to caution someone not to jump early, but it has to be the right jump and it has to be something that really gives you a competitive advantage. A lot of infrastructure technology is you should make the choices that you make one or two big bets and sometimes people say this, you call it using their innovation tokens. You need to make the bets on big technologies that you operate more effectively at scale. It is somewhat hard to predict that. I certainly say that I've missed quite a few of the exciting transformations in the field just because, um, it wasn't always obvious that it was going to pay off to the degree that um, customers would need. >>So I gotta ask you on the real time applications side of it, that's been a big trend, certainly in cloud. But as you look at hybrid hybrid cloud environments, for instance, streaming data has been a big issue. Uh any updates there from you on your managed service? >>That's right. So one of we have to manage services um that are both closely aligned three managed services that are closely aligned with data in three different ways. And so um one of them is redhead open shift streams for Apache Kafka, which is managed cloud service that focuses on bringing that streaming data and letting you run it across multiple environments. And I think that, you know, we get to the heart of what's the purpose of uh managed services is to reduce operational overhead and to take responsibilities that allow users to focus on the things that actually matter for them. So for us, um managed open shift streams is really about the flow of data between applications in different environments, whether that's from the edge to an on premise data center, whether it's an on premise data center to the cloud. And increasingly these services which were running in the public cloud, increasingly these services have elements that run in the public cloud, but also key elements that run close to where your applications are. And I think that bridge is actually really important for us. That's a key component of hybrid is connecting the different locations and different footprints. So for us the focus is really how do we get data moving to the right place that complements our API management service, which is an add on for open ship dedicated, which means once you've brought the data and you need to expose it back out to other applications in the environment, you can build those applications on open shift, you can leverage the capabilities of open shift api management to expose them more easily, both to end customers or to other applications. And then our third services redhead open shift data science. Um and that is a, an integration that makes it easy for data scientists in a kubernetes environment. On open shift, they easily bring together the data to make, to analyze it and to help route it is appropriate. So those three facets for us are pretty important. They can be used in many different ways, but that focus on the flow of data across these different environments is really a key part of our longer term strategy. >>You know, all the customer checkboxes there you mentioned earlier. I mean I'll just summarize that that you said, you know, obviously value faster application velocity time to value. Those are like the checkboxes, Gardner told analysts check those lower complexity. Oh, we do the heavy lifting, all cloud benefits, so that's all cool. Everyone kind of gets that, everyone's been around cloud knows devops all those things come into play right now. The innovation focuses on operations and day to operations, becoming much more specific. When people say, hey, I've done some lift and shift, I've done some Greenfield born in the cloud now, it's like, whoa, this stuff, I haven't seen this before. As you start scaling. So this brings up that concept and then you add in multi cloud and hybrid cloud, you gotta have a unified experience. So these are the hot areas right this year, I would say, you know, that day to operate has been around for a while, but this idea of unification around environments to be fully distributed for developers is huge. >>How do you >>architect for that? This is the number one question I get. And I tease out when people are kind of talking about their environments that challenges their opportunities, they're really trying to architect, you know, the foundation that building to be um future proof, they don't want to get screwed over when they have, they realize they made a decision, they weren't thinking about day to operation or they didn't think about the unified experience across clouds across environments and services. This is huge. What's your take on this? >>So this is um, this is probably one of the hardest questions I think I could get asked, which is uh looking into the crystal ball, what are the aspects of today's environments that are accidental complexity? That's really just a result of the slow accretion of technologies and we all need to make bets when, when the time is right within the business, um and which parts of it are essential. What are the fundamental hard problems and so on. The accidental complexity side for red hat, it's really about um that consistent environment through open shift bringing capabilities, our connection to open source and making sure that there's an open ecosystem where um community members, users vendors can all work together to um find solutions that work for them because there's not, there's no way to solve for all of computing. It's just impossible. I think that is kind of our that's our development process and that's what helps make that accidental complexity of all that self away over time. But in the essential complexity data is tied the location, data has gravity data. Lakes are a great example of because data has gravity. The more data that you bring together, the bigger the scale the tools you can bring, you can invest in more specialized tools. I've almost do that as a specialization centralization. There's a ton of centralization going on right now at the same time that these new technologies are available to make it easier and easier. Whether that's large scale automation um with conflict management technologies, whether that's kubernetes and deploying it in multiple sites in multiple locations and open shift, bringing consistency so that you can run the apps the same way. But even further than that is concentrating, mhm. More of what would have typically been a specialist problem, something that you build a one off around in your organization to work through the problem. We're really getting to a point where pretty soon now there is a technology or a service for everyone. How do you get the data into that service out? How do you secure it? How do you glue it together? Um I think of, you know, some people might call this um you know, the ultimate integration problem, which is we're going to have all of this stuff and all of these places, what are the core concepts, location, security, placement, topology, latency, where data resides, who's accessing that data, We think of these as kind of the building blocks of where we're going next. So for us trying to make investments in, how do we make kubernetes work better across lots of environments. I have a coupon talk coming up this coupon, it's really exciting for me to talk about where we're going with, you know, the evolution of kubernetes, bringing the different pieces more closely together across multiple environments. But likewise, when we talk about our managed services, we've approached the strategy for managed services as it's not just the service in isolation, it's how it connects to the other pieces. What can we learn in the community, in our services, working with users that benefits that connectivity. So I mentioned the open shift streams connecting up environments, we'd really like to improve how applications connect across disparate environments. That's a fundamental property of if you're going to have data uh in one geographic region and you didn't move services closer to that well, those services I need to know and encode and have that behavior to get closer to where the data is, whether it's one data lake or 10. We gotta have that flexibility in place. And so those obstructions are really, and to >>your point about the building blocks where you've got to factor in those building blocks, because you're gonna need to understand the latency impact, that's going to impact how you're gonna handle the compute piece, that's gonna handle all these things are coming into play. So, again, if you're mindful of the building blocks, just as a cloud concept, um, then you're okay. >>We hear this a lot. Actually, there's real challenges in the, the ecosystem of uh, we see a lot of the problems of I want to help someone automate and improved, but the more balkanize, the more spread out, the more individual solutions are in play, it's harder for someone to bring their technology to bear to help solve the problem. So looking for ways that we can um, you know, grease the skids to build the glue. I think open source works best when it's defining de facto solutions that everybody agrees on that openness and the easy access is a key property that makes de facto standards emerged from open source. What can we do to grow defacto standards around multi cloud and application movement and application interconnect I think is a very, it's already happening and what can we do to accelerate it? That's it. >>Well, I think you bring up a really good point. This is probably a follow up, maybe a clubhouse talk or you guys will do a separate session on this. But I've been riffing on this idea of uh, today's silos, tomorrow's component, right, or module. If most people don't realize that these silos can be problematic if not thought through. So you have to kill the silos to bring in kind of an open police. So if you're open, not closed, you can leverage a monolith. Today's monolithic app or full stack could be tomorrow's building block unless you don't open up. So this is where interesting design question comes in, which is, it's okay to have pre existing stuff if you're open about it. But if you stay siloed, you're gonna get really stuck >>and there's going to be more and more pre existing stuff I think, you know, uh even the data lake for every day to lake, there is a huge problem of how to get data into the data lake or taking existing applications that came from the previous data link. And so there's a, there's a natural evolutionary process where let's focus on the mechanisms that actually move that day to get that data flowing. Um, I think we're still in the early phases of thinking about huge amounts of applications. Microservices or you know, 10 years old in the sense of it being a fairly common industry talking point before that we have service oriented architecture. But the difference now is that we're encouraging and building one developer, one team might run several services. They might use three or four different sas vendors. They might depend on five or 10 or 15 cloud services. Those integration points make them easier. But it's a new opportunity for us to say, well, what are the differences to go back to? The point is you can keep your silos, we just want to have great integration in and out of >>those. Exactly, they don't have to you have to break down the silos. So again, it's a tried and true formula integration, interoperability and abstracting away the complexity with some sort of new software abstraction layer. You bring that to play as long as you can paddle with that, you apply the new building blocks, you're classified. >>It sounds so that's so simple, doesn't it? It does. And you know, of course it'll take us 10 years to get there. And uh, you know, after cloud native will be will be galactic native or something like that. You know, there's always going to be a new uh concept that we need to work in. I think the key concepts we're really going after our everyone is trying to run resilient and reliable services and the clouds give us in the clouds take it away. They give us those opportunities to have some of those building blocks like location of geographic hardware resources, but they will always be data that spread. And again, you still have to apply those principles to the cloud to get the service guarantees that you need. I think there's a completely untapped area for helping software developers and software teams understand the actual availability and guarantees of the underlying environment. It's a property of the services you run with. If you're using a disk in a particular availability zone, that's a property of your application. I think there's a rich area that hasn't been mined yet. Of helping you understand what your effective service level goals which of those can be met. Which cannot, it doesn't make a lot of sense in a single cluster or single machine or a single location world the moment you start to talk about, Well I have my data lake. Well what are the ways my data leg can fail? How do we look at your complex web of interdependencies and say, well clearly if you lose this cloud provider, you're going to lose not just the things that you have running there, but these other dependencies, there's a lot of, there's a lot of next steps that we're just learning what happens when a major cloud goes down for a day or a region of a cloud goes down for a day. You still have to design and work around those >>cases. It's distributed computing. And again, I love the space where galactic cloud, you got SpaceX? Where's Cloud X? I mean, you know, space is the next frontier. You know, you've got all kinds of action happening in space. Great space reference there. Clayton, Great insight. Thanks for coming on. Uh, Clayton Coleman architect at red Hat. Clayton, Thanks for coming on. >>Pretty pleasure. >>Always. Great chat. I'm talking under the hood. What's going on in red hats? New managed cloud service portfolio? Again, the world's getting complex, abstract away. The complexities with software Inter operate integrate. That's the key formula with the cloud building blocks. I'm john ferry with the cube. Thanks for watching. Yeah.
SUMMARY :
We still got the Covid coming around the corner. So great to see you were just riffing before we came on camera about distributed computing in and introducing the first, I think really the first step what we see as uh I mean, you guys have, it's not just, you know, you support AWS as so that the choice of where you run your cloud, um, So take me through how you guys Um and I think a lot of the role of this is, you know, the irresponsible to I want a data cloud, you know, everything is like the new, you know, they saw Snowflake Apollo, I gotta have some, But depending on where you jumped on the bandwagon, depending on when you adopted, you're going to make a bunch of different trade offs. So I gotta ask you on the real time applications side of it, that's been a big trend, And I think that, you know, we get to the heart of what's the purpose of You know, all the customer checkboxes there you mentioned earlier. you know, the foundation that building to be um future proof, shift, bringing consistency so that you can run the apps the same way. latency impact, that's going to impact how you're gonna handle the compute piece, that's gonna handle all you know, grease the skids to build the glue. So you have to kill the silos to bring in kind and there's going to be more and more pre existing stuff I think, you know, uh even the data lake for You bring that to play as long as you can paddle with that, you apply the new building blocks, the things that you have running there, but these other dependencies, there's a lot of, there's a lot of next I mean, you know, space is the next frontier. That's the key formula with the cloud building blocks.
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Breaking Analysis: Cloud Momentum & CIO Optimism Point to a 4% Rise in 2020 Tech Spending
>> From theCube studios in Palo Alto in Boston, bringing you data-driven insights from theCube in ETR. This is Breaking Analysis with Dave Vellante. >> New data suggests the tech spending will be higher than we previously thought for 2021. COVID learnings, a faster than expected vaccine rollout, productivity gains in the last 10 months, and broad-based cloud leverage lead us to raise our outlook for next year. We now expect a three to 5% increase in 2021 technology spending, roughly double our previously forecasted growth rate of 2%. Hello everyone and welcome to this week's we keep on Cube Insights powered by ETR. In this breaking analysis, we're going to share new spending data from ETR partners and take a preliminary look at which sectors and which companies are showing momentum heading into next year. Let's get right into it. The data is pointing to a strong 2021 rebound. A latest survey from ETR and the information from theCube Community suggests that the accelerated pace of the vaccine rollout pent up demand for normalcy and learnings from COVID will boost 2021 tech spending higher than previously anticipated. Now a key factor we've cited is that the forced March to digital transformation due to the pandemic created a massive proof of concept for what works and what doesn't in a digital business. CIOs are planning to bet on those sure things to drive continued productivity improvements and new business opportunities. Now, speaking of productivity, nearly 80% of respondents in the latest ETR survey indicate that productivity either stayed the same or improved over the past three months. Now of those, the vast majority, more than 80% cited improvements in productivity. This has been a common theme throughout the year. As well, the expectation among CIOs is that many workers will return to the office in the second half of the year, which we expect will drive new spending in the infrastructure needs of company HQs, which have been neglected over the past 10 months. Now, despite the expectation that many workers will return to the office, 2020 has shown us that working remotely, hey, it's here to stay, and a much larger number of employees are going to be permanently remote working than pre pandemic. ETR survey data shows that that number is going to be approximately double over the longterm. We'll look at some of that specific data. In addition, cloud computing, it became the staple of business viability in 2020. Those that were up the cloud adoption ramp, well, they benefited greatly, those that weren't well, they had to learn fast. Now, along with remote work cloud necessitated new thinking around network security, and as we've reported identity access management, endpoint security and cloud security with the beneficiaries. Companies like Okta, CrowdStrike, Zscaler, a number of others continue to ride this wave. Larger established security companies like Cisco, Palo Alto Networks, F5, Fortunate and others, they have major portions of their business that are benefiting from the tailwinds in the shift and network traffic, as a result of cloud and remote work. Now, despite all the momentum in the market and the expect of improvements in 2021, these tailwinds are not expected to be evenly distributed, far from it. We think Q4 is going to remain soft relative to last year and Q1 2021 is going to be flat, maybe up slightly. Remember the COVID impact was definitely felt in March of this year. So based on the earnings that we saw, there may be some upside in Q1, given that organizations are still being cautious in Q4, and really there's still some uncertainty in Q1. Let's look at some of the survey responses and you'll see why we're more optimistic than we've previously reported. This chart shows the responses to key questions around spending trajectories from the March, June, September, and December surveys of this year. Now it's no surprise that there's been little change in remote workers and limiting business travel. But look at the other categories, seeing a dramatic reduction in hiring freezes. The percentage of companies freezing new IT deployments continues to drop throughout the year. And then conversely, the percentage of companies accelerating new it deployments that's sharply up to 34% from the March low of 12%. And look at the headcount trends. The percentage of companies instituting layoffs. It continues its downward trajectory while accelerated hiring is now up to 17%. So there's a lot to be excited about in these results. Now let's look the remote worker trend. How do CIO see that shift in the near to midterm? This chart shows the work from home data and it's amazingly consistent from the September survey drill down. You can see CIO's is indicate that on average, 15 to 60% of workers were remote prior to the pandemic, and that jumped up to 72 to 73% currently, and is expected to stay in the high fifties until the summer of 2021. Thereafter, organizations expect that the number of employees that work remotely on a permanent basis is going to more than double to 34% long term. By the way, I've talked to a number of executives, CEOs, CIOs, and CFOs that expect that number to be higher than these especially in the technology sector. They expect more than half of their workers to be remote and are looking to consolidate facilities cost to save money. As we've said, cloud computing has been the most significant contributor to business resilience and digital transformation this year. So let's look at cloud strategies and see how CIOs expect those to evolve. This chart shows responses to how organizations see multi-cloud evolving. It's interesting to note the ETR call-out, which concludes that the narrative around multi-cloud multi-cloud is real, and it is. But I want to talk to you about a flip side to this notion in that, as many customers have, or are planning to increasingly concentrate workloads in the cloud. This actually makes some sense. Sure, virtually every major company uses multiple clouds, but more often than not, it concentrate work on a primary cloud. CIO strategies, they're not generally evenly distributed across clouds. The data shows that this is the case for less than 20% of the respondents, rather organizations are typically going to apply an 80, 20 or a 70, 30 rule for their multi-cloud approach. Meaning they pick a primary cloud on which most work is done, and then they use alternative clouds as either a hedge or maybe for specific workloads or maybe even data protection purposes. Now, if you think about it, optimizing on a primary cloud allows organizations to simplify their security and governance and consolidate their skills. At this point in the cloud evolution, it seems CIOs feel there's more value that is going to come from leveraging the cloud to change their operating models, and maybe broadly spreading the wealth to reduce risk or maybe cut costs, or maybe even to tap specialized capabilities. What's more in thinking about AWS and Microsoft respectively. Each can make a very strong case from MANO cloud. AWS has more features than any other cloud, and as such can handle most workloads. Microsoft can make a similar argument for its customers that have an affinity and a largest state of Microsoft software. The key for multi-cloud in our view will be the degree to which technology vendors can abstract the underlying cloud complexity and create a layer that floats above the clouds and adds incremental value. Snowflakes data cloud is one of the best examples of this, and we've covered that pretty extensively. Now, clearly VMware and Red Hat have aspirations at the infrastructure layer in a similar fashion. Pure storage, and NetApp are a couple of the largest storage players with similar visions. And then Qumulo and Clumio are two other examples with promising technologies, but they have a much smaller install base. Take a look at Cisco, Dell, IBM and HPE. They have a lot to gain and a lot to lose in this cloud game. So multi-cloud is an imperative for these leaders, but for them it's much more complicated because of the complexity and vastness of their portfolios. And notably Dell has VMware and IBM of course has Red Hat, which are key assets that can be leveraged for this multi-cloud game. HPE has a channel and a large install base, but all of these firms, they have to spread R&D much more thinly than some of these other companies that we mentioned for example. The bottom line is that multi-cloud has to be more than just plugging into an operating well on any of the clouds. It require... Which is by the way, this is mostly where we are today. It requires an incremental value proposition that solves a clear problem, and at the same time runs efficiently, meaning it takes advantage of cloud native services at scale. What sectors are showing momentum heading into 2021? And who are some of the names that are looking strong? We've reported a lot that cloud containers and container orchestration, machine intelligence and automation are by far the hottest sectors, the biggest areas of investment with the greatest spending momentum. Now we measure this in ETR parlance, remember by net score. But here's the good news, almost every other sector in the ETR taxonomy with the notable exception of IT outsourcing and IT consulting is showing positive spending momentum relative to previous surveys this year. Yeah, maybe not, it's not a shock, but it appears that the tech spending recovery will be broad-based. It's also worth noting that there are several vendors that stand out and we show a number of them here. CrowdStrike, Microsoft has had consistent performance in the dataset throughout this year. Okta, we called out those guys last year and they've clearly performed as you can see in their earnings reports. Pure storage, interestingly, big acceleration and a turnaround from last quarter in the dataset, and of course, snowflake has been off the charts as we reported many times. These guys are all seeing highly accelerated momentum. UiPath just announced its intent to IPO, AWS, Google, Zscaler, SailPoint, ServiceNow, and Elastic, these all continue to trend up. And so, there are some real positives that we're looking for a member of the ETR surveys, they're forward-looking. So we'll see, as we catch up next quarter. Now, before we wrap, I want to say a few words on security, and maybe it's a bit of a non-sequitur here, but I think it's relevant to the trends that we've been discussing, especially as we talk about moving to the cloud. And as you know, we've reported many times on the security space, basically updating you quarterly with our scenarios and the spending and the technology trends and highlighting our four-star companies. Four-star company's insecurity on those with both momentum and significant market presence. And last year we put CrowdStrike, Okta and Zscaler, and some others on the radar. And we've closely track the cyber business of larger companies with a security portfolio like Palo Alto and Cisco, and more recently, VMware has made some acquisitions. Now the government hacked that became news this week. It really underscores the importance of security. It remains the most challenging area for organizations because well, failure's not an option, skills are short, tools are abundant, the adversaries are very well-funded and extremely capable yet failure is common as we saw this week. And there's a misconception that cloud solves the security problem, and it's important to point out that it does not. Cloud is a shared responsibility model, meaning the cloud provider is going to secure the infrastructure for example, but it's up to you as the customer to configure things properly and deal with application security. It's ultimately on you. And the example of S3 is instructive because we've seen a number S3 breaches over the years where the customer didn't properly configure the S3 bucket. We're talking about companies like Honda and Capital One, not just small businesses that don't have the SecOps resources. And generally it was because a non-security person was configuring things. Maybe they were Or developers who are not focused on security, and perhaps permission set too broadly, and access was given to far too many people. Whatever the issue, it took some breaches and subsequent education to increase awareness of this problem and tighten it up. We see some similar trends occurring with new workloads, especially in cloud databases. It's becoming so easy to spin up new data warehouses for example, and we believe that there are exposures out there due the lack of awareness or inconsistent corporate governance being applied to these new data stores. As well, even though important areas like threat intelligence and database security are important, SecOps budgets are stretched thin. And when you ask companies where the priorities are, these fall lower down the list, these areas specifically have taken a back seat, the endpoint, identity and cloud security. And we bring this up because it's a potential blind spot as we saw this week with the US government hack. It was stealthy, it wasn't detected for many, many months. Who knows maybe even years. And not to be a buzzkill, but the point is, cloud enthusiasm has to be concompetent with security vigilant. Enough preaching, let's wrap up here. As we enter 2020, this year, we said the cloud was going to be the force that drove innovation along with data and AI. And as we look in the rear view mirror and put 2020 behind us, I know many of you want to do that, it was the cloud that enabled businesses to not only continue to operate, but to actually increase productivity. Nonetheless, we still see IT spending declines of four to 5% this year with an expectation of a tepid Q4 relative to the last year. We see Q1 slowly rebounding and kind of a swoosh, let me try that again, recovery in the subsequent quarters with tech spending rebounding in 2021 to a positive three to 5%, let's call it 4%. Now supporting us scenario, the pandemic forced a giant Petri dish for digital. And we see some real successes and learnings that organizations will apply in 2021 to bet on sure things. These are cloud, containers, AI, ML, machine intelligence pieces and automation. For sure, along with upticks for virtually every other sector of technology because spending has been so depressed. The two exceptions are outsourcing and IT consulting and related services which continue to be a drag on overall spending. Priorities must be focused on security and governance and further improvements in applying corporate edicts in a cloud world. We also see new data architectures emerging where domain knowledge becomes central to data platforms. We'll be covering this in more detail on top of the work that we've already done in this area. Now, automation is not only an opportunity, it's become a mandate. Yes, RPA, but also broader automation agendas be on point tools. And importantly, we're not talking about paving the cow path here by automating existing processes. Rather we're talking about rethinking processes across the entire organization for a new digital reality where many of these processes are being invented. The work of Erik Brynjolfsson and Andrew McAfee on the second machine age. It was pressured back in 2014 and the conclusions they drew, they're becoming increasingly important in the 2020s, meaning that look machines have always replaced humans throughout time. But for the first time in history, it's happening for cognitive functions, and a huge base of workers is going to be, or as being marginalized, unless they're retrained. Education and public policy that supports this transition is critical. And I for one would like to see a much more productive discussion that goes beyond the cult of break up big tech. Rather I'd like to see governments partner with big tech to truly do good and help drive the re-skilling of workers for the digital age. Now cloud remains the underpinning of the digital business mandate, but the path forward isn't really always crystal clear. This is evidenced by the virtual dead heat between those organizations that are consolidating workloads in a cloud workloads versus those that are hedging bets on a multi-cloud strategy. One thing is clear cloud is the linchpin for our growth scenarios and will continue to be the substrate for innovation in the coming decade. Remember, these episodes, they're all available as podcasts, wherever you listen, all you got to do is search Breaking Analysis podcast, and please subscribe to the series, appreciate that. Check out ETR's website at ETR.plus. We also publish full report every week on wikibond.com and siliconangle.com and get in touch with me at David.vallante, siliconangle.Com, you can DM me at D. Vellante. And please by all means comment on our LinkedIn posts. This is Dave Vellante for theCube Insights powered by ETR. Have a great week everybody, Merry Christmas, happy Hanukkah, happy Kwanzaa, or happy, whatever holiday you celebrate. Stay safe, be well, and we'll see you next time. (upbeat music)
SUMMARY :
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Hemanth Manda, IBM Cloud Pak
(soft electronic music) >> Welcome to this CUBE Virtual Conversation. I'm your host, Rebecca Knight. Today, I'm joined by Hermanth Manda. He is the Executive Director, IBM Data and AI, responsible for Cloud Pak for Data. Thanks so much for coming on the show, Hermanth. >> Thank you, Rebecca. >> So we're talking now about the release of Cloud Pak for Data version 3.5. I want to explore it for, from a lot of different angles, but do you want to just talk a little bit about why it is unique in the marketplace, in particular, accelerating innovation, reducing costs, and reducing complexity? >> Absolutely, Rebecca. I mean, this is something very unique from an IBM perspective. Frankly speaking, this is unique in the marketplace because what we are doing is we are bringing together all of our data and AI capabilities into a single offering, single platform. And we have continued, as I said, we made it run on any cloud. So we are giving customers the flexibility. So it's innovation across multiple fronts. It's still in consolidation. It's, in doing automation and infusing collaboration and also having customers to basically modernize to the cloud-native world and pick their own cloud which is what we are seeing in the market today. So I would say this is a unique across multiple fronts. >> When we talk about any new platform, one of the big concerns is always around internal skills and maintenance tasks. What changes are you introducing with version 3.5 that does, that help clients be more flexible and sort of streamline their tasks? >> Yeah, it's an interesting question. We are doing a lot of things with respect to 3.5, the latest release. Number one, we are simplifying the management of the platform, made it a lot simpler. We are infusing a lot of automation into it. We are embracing the concept of operators that are not open shelf has introduced into the market. So simple things such as provisioning, installation, upgrades, scaling it up and down, autopilot management. So all of that is taken care of as part of the latest release. Also, what we are doing is we are making the collaboration and user onboarding very easy to drive self service and use the productivity. So overall, this helps, basically, reduce the cost for our customers. >> One of the things that's so striking is the speed of the innovation. I mean, you've only been in the marketplace for two and a half years. This is already version 3.5. Can you talk a little bit about, about sort of the, the innovation that it takes to do this? >> Absolutely. You're right, we've been in the market for slightly over two and a half years, 3.5's our ninth release. So frankly speaking, for any company, or even for startups doing nine releases in 2.5 years is unheard of, and definitely unheard of at IBM. So we are acting and behaving like a startup while addressing the go to market, and the reach of IBM. So I would say that we are doing a lot here. And as I said before, we're trying to address the unique needs of the market, the need to modernize to the cloud-native architectures to move to the cloud also while addressing the needs of our existing customers, because there are two things we are trying to focus, here. First of all, make sure that we have a modern platform across the different capabilities in data and AI, that's number one. Number two is also how do we modernize our existing install base. We have six plus billion dollar business for data and AI across significant real estates. We're providing a platform through Cloud Pak for Data to those existing install base and existing customers to more nice, too. >> I want to talk about how you are addressing the needs of customers, but I want to delve into something you said earlier, and that is that you are behaving like a startup. How do you make sure that your employees have that kind of mindset that, that kind of experimental innovative, creative, resourceful mindset, particularly at a more mature company like IBM? What kinds of skills do you try to instill and cultivate in your, in your team? >> That's a very interesting question, Rebecca. I think there's no single answer, I would say. It starts with listening to the customers, trying to pay detailed attention to what's happening in the market. How competent is it reacting. Looking at the startups, themselves. What we did uniquely, that I didn't touch upon earlier is that we are also building an open ecosystem here, so we position ourselves as an open platform. Yes, there's a lot of IBM unique technology here, but we also are leveraging open source. We are, we have an ecosystem of 50 plus third party ISVs. So by doing that, we are able to drive a lot more innovation and a lot faster because when you are trying to do everything by yourself, it's a bit challenging. But when you're part of an open ecosystem, infusing open source and third party, it becomes a lot easier. In terms of culture, I just want to highlight one thing. I think we are making it a point to emphasize speed over being perfect, progress over perfection. And that, I think, that is something net new for IBM because at IBM, we pride ourselves in quality, scalability, trying to be perfect on day one. I think we didn't do that in this particular case. Initially, when we launched our offense two and a half years back, we tried to be quick to the market. Our time to market was prioritized over being perfect. But now that is not the case anymore, right? I think we will make sure we are exponentially better and those things are addressed for the past two and one-half years. >> Well, perfect is the enemy of the good, as we know. One of the things that your customers demand is flexibility when building with machine learning pipeline. What have you done to improve IBM machine learning tools on this platform? >> So there's a lot of things we've done. Number one, I want to emphasize our building AI, the initial problem that most of our customers concerned about, but in my opinion, that's 10% of the problem. Actually deploying those AI models or managing them and covering them at scales for the enterprise is a bigger challenge. So what we have is very unique. We have the end-to-end AI lifecycle, we have tools for all the way from building, deploying, managing, governing these models. Second is we are introducing net new capabilities as part of a latest release. We have this call or this new service called WMLA, Watson Machine Learning Accelerator that addresses the unique challenges of deep learning capabilities, managing GPUs, et cetera. We are also making the auto AI capabilities a lot more robust. And finally, we are introducing a net new concept called Federator Learning that allows you to build AI across distributed datasets, which is very unique. I'm not aware of any other vendor doing this, so you can actually have your data distributed across multiple clouds, and you can build an aggregated AI model without actually looking at the data that is spread across these clouds. And this concept, in my opinion, is going to get a lot more traction as we move forward. >> One of the things that IBM has always been proud of is the way it partners with ISVs and other vendors. Can you talk about how you work with your partners and foster this ecosystem of third-party capabilities that integrate into the platform? >> Yes, it's always a challenge. I mean, for this to be a platform, as I said before, you need to be open and you need to build an ecosystem. And so we made that a priority since day one and we have 53 third party ISVs, today. It's a chicken and egg problem, Rebecca, because you need to obviously showcase success and make it a priority for your partners to onboard and work with you closely. So, we obviously invest, we co-invest with our partners and we take them to market. We have different models. We have a tactical relationship with some of our third party ISVs. We also have a strategic relationship. So we partner with them depending on their ability to partner with us and we go invest and make sure that we are not only integrating them technically, but also we are integrating with them from a go-to-market perspective. >> I wonder if you can talk a little bit about the current environment that we're in. Of course, we're all living through a global health emergency in the form of the COVID-19 pandemic. So much of the knowledge work is being done from home. It is being done remotely. Teams are working asynchronously over different kinds of digital platforms. How have you seen these changes affect the team, your team at IBM, what kinds of new kinds of capabilities, collaborations, what kinds of skills have you seen your team have to gain and have to gain quite quickly in this environment? >> Absolutely. I think historically, IBM had quite a, quite a portion of our workforce working remotely so we are used to this, but not at the scale that the current situation has compelled us to. So we made a lot more investments earlier this year in digital technologies, whether it is Zoom and WebEx or trying to use tools, digital tools that helps us coordinate and collaborate effectively. So part of it is technical, right? Part of it is also a cultural shift. And that came all the way from our CEO in terms of making sure that we have the necessary processes in place to ensure that our employees are not in getting burnt out, that they're being productive and effective. And so a combination of what I would say, technical investments, plus process and leadership initiatives helped us essentially embrace the changes that we've seen, today. >> And I want you to close us out, here. Talk a little bit about the future, both for Cloud Pak for Data, but also for the companies and clients that you work for. What do you see in the next 12 to 24 months changing in the term, in terms of how we have re-imagined the future of work. I know you said this was already version nine. You've only been in the marketplace for, for not even three years. That's incredible innovation and speed. Talk a little bit about changes you see coming down the pike. >> So I think everything that we have done is going to get amplified and accelerated as we move forward, shift to cloud, embracing AI, adopting AI into business processes to automate and amplify new business models, collaboration, to a certain extent, consolidation of the different offerings into platforms. So all of this, we, I obviously see that being accelerated and that acceleration will continue as we move forward. And the real challenge I see with our customers and all the enterprises is, I see them in two buckets. There's one bucket which are resisting change, like to stick to the old concepts, and there's one bucket of enterprises who are embracing the change and moving forward, and actually get accelerating this transformation and change. I think it will be successful over the next one to five years. You know, it could be under the other bucket and if you're not, I think it's, you're going to get, you're going to miss out and that is getting amplified and accelerated, as we speak. >> So for those ones in the bucket that are resistant to the change, how do you get them onboard? I mean, this is classic change management that they teach at business schools around the world. But what are some advice that you would have to those who are resisting the change? >> So, and again, frankly speaking, we, at IBM, are going through that transition so I can speak from experience. >> Rebecca: You're drinking the Kool-Aid. >> Yeah, when, when I think, one way to address this is basically take one step at a time, like as opposed to completely revolutionizing the way you do your business. You can transform your business one step at a time while keeping the end objective as your goal, as your end goal. So, and it just want a little highlight that with full factor, that's exactly what we are enabling because what we do is we enable you to actually run anywhere you like. So if most of your systems, most of your data and your models, and analytics are on-premise, you can actually start your journey there while you plan for the future of a public cloud or a managed service. So my advice is pretty simple. You start the journey, but you can take, you can, you don't need to, you don't need to do it as a big bang. You, it could be a journey, it could be a gradual transformation, but you need to start the journey today. If you don't, you're going to miss out. >> Baby steps. Hey Hermanth Manda, thank you so much for joining us for this Virtual CUBE Conversation >> Thank you very much, Rebecca. >> I'm Rebecca Knight, stay tuned for more of theCUBE Virtual. (soft electronic music)
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CloudLive Great Cloud Debate with Corey Quinn and Stu Miniman
(upbeat music) >> Hello, and welcome to The Great Cloud Debate. I'm your moderator Rachel Dines. I'm joined by two debaters today Corey Quinn, Cloud Economist at the Duckbill Group and Stu Miniman, Senior Analyst and Host of theCube. Welcome Corey and Stu, this when you can say hello. >> Hey Rachel, great to talk to you. >> And it's better to talk to me. It's always a pleasure to talk to the fine folks over at CloudHealth at by VMware and less of the pleasure to talk to Stu. >> Smack talk is scheduled for later in the agenda gentlemen, so please keep it to a minimum now to keep us on schedule. So here's how today is going to work. I'm going to introduce a debate topic and assign Corey and Stu each to a side. Remember, their assignments are what I decide and they might not actually match their true feelings about a topic, and it definitely does not represent the feelings of their employer or my employer, importantly. Each debater is going to have two minutes to state their opening arguments, then we'll have rebuttals. And each round you the audience gets to vote of who you think is winning. And at the end of the debate, I'll announce the winner. The prize is bragging rights of course, but then also we're having each debater play to win lunch for their local hospital, which is really exciting. So Stu, which hospital are you playing for? >> Yeah, so Rachel, I'm choosing Brigham Women's Hospital. I get a little bit of a home vote for the Boston audience here and was actually my wife's first job out of school. >> Great hospital. Very, very good. All right, Corey, what about you? >> My neighbor winds up being as specialist in infectious diseases as a doctor, and that was always one of those weird things you learn over a cocktail party until this year became incredibly relevant. So I will absolutely be sending the lunch to his department. >> Wonderful! All right. Well, is everyone ready? Any last words? This is your moment for smack talk. >> I think I'll say that for once we can apply it to a specific technology area. Otherwise, it was insulting his appearance and that's too easy. >> All right, let's get going. The first topic is multicloud. Corey, you'll be arguing that companies are better off standardizing on a single cloud. While Stu, you're going to argue the companies are better off with a multicloud strategy. Corey, you're up first, two minutes on the clock and go. >> All right. As a general rule, picking a single provider and going all in leads to the better outcome. Otherwise, you're trying to build every workload to run seamlessly on other providers on a moment's notice. You don't ever actually do it and all you're giving up in return is the ability to leverage whatever your primary cloud provider is letting you build. Now you're suddenly trying to make two differently behaving load balancers work together in the same way, you're using terraform or as I like to call it multicloud formation in the worst of all possible ways. Because now you're having to only really build on one provider, but all the work you're putting in to make that scale to other providers, you might theoretically want to go to at some point, it slows you down, you're never going to be able to move as quickly trying to build for everyone as you are for one particular provider. And I don't care which provider you pick, you probably care which one you pick, I don't care which one. The point is, you've got to pick what's right for your business. And in almost every case, that means start on a single platform. And if you need to migrate down the road years from now, great, that means A you've survived that long, and B you now have the longevity as a business to understand what migrating looks like. Otherwise you're not able to take care of any of the higher level offerings these providers offer that are even slightly differentiated from each other. And even managed database services behave differently. You've got to become a master of all the different ways these things can fail and unfortunate and displeasing ways. It just leaves you in a position where you're not able to specialize, and of course, makes hiring that much harder. Stu, fight me! >> Tough words there. All right, Stu, your turn. Why are companies better off if they go with a multicloud strategy? Got two minutes? >> Yeah, well first of all Corey, I'm really glad that I didn't have to whip out the AWS guidelines, you were not sticking strictly to it and saying that you could not use the words multicloud, cross-cloud, any cloud or every cloud so thank you for saving me that argument. But I want you to kind of come into the real world a little bit. We want access to innovation, we want flexibility, and well, we used to say I would have loved to have a single provider, in the real world we understand that people end up using multiple solutions. If you look at the AI world today, there's not a provider that is a clear leader in every environment that I have. So there's a reason why I might want to use a lot of clouds. Most companies I talked to, Corey, they still have some of their own servers. They're working in a data center, we've seen huge explosion in the service provider world connecting to multiple clouds. So well, a couple of years ago, multicloud was a complete mess. Now, it's only a little bit of a mess, Corey. So absolutely, there's work that we need to do as an industry to make these solutions better. I've been pining for a couple years to say that multicloud needs to be stronger than the sum of its pieces. And we might not yet be there but limiting yourself to a single cloud is reducing your access to innovation, it's reducing your flexibility. And when you start looking at things like edge computing and AI, I'm going to need to access services from multiple providers. So single cloud is a lovely ideal, but in the real world, we understand that teams come with certain skill sets. We end up in many industries, we have mergers and acquisitions. And it's not as easy to just rip out all of your cloud, like you would have 20 years ago, if you said, "Oh, well, they have a phone system or a router "that didn't match what our corporate guidelines is." Cloud is what we're doing. There's lots of solutions out there. And therefore, multicloud is the reality today, and will be the reality going forward for many years to come. >> Strong words from you, Stu. Corey, you've got 60 seconds for rebuttal. I mostly agree with what you just said. I think that having different workloads in different clouds makes an awful lot of sense. Data gravity becomes a bit of a bear. But if you acquire a company that's running on a different cloud than the one that you've picked, you'd be ridiculous to view migrating as anything approaching a strategic priority. Now, this also gets into the question of what is cloud? Our G Suite stuff counts as cloud, but no one really views it in that way. Similarly, when you have an AI specific workload, that's great. As long as it isn't you seriously expensive to move data between providers. That workload doesn't need to live in the same place as your marketing website does. I think that the idea of having a specific cloud provider that you go all in on for every use case, well, at some point that leads to ridiculous things like pretending that Amazon WorkDocs has customers, it does not. But for things that matter to your business and looking at specific workloads, I think that you're going to find a primary provider with secondary workloads here and they're scattered elsewhere to be the strategy that people are getting at when they use the word multicloud badly. >> Time's up for you Corey, Stu we've got time for rebuttal and remember, for those of you in the audience, you can vote at any time and who you think is winning this round. Stu, 60 seconds for a rebuttal. >> Yeah, absolutely Corey. Look, you just gave the Andy Jassy of what multicloud should be 70 to 80% goes to a single provider. And it does make sense we know nobody ever said multicloud equals the same amount in multiple environments but you made a clear case as to why multicloud leveraging multi providers is likely what most companies are going to do. So thank you so much for making a clear case as to why multicloud not equal cloud, across multiple providers is the way to go. So thank you for conceding the victory. >> Last Words, Corey. >> If that's what you took from it Stu, I can't get any closer to it than you have. >> All right, let's move on to the next topic then. The next topic is serverless versus containers which technology is going to be used in, let's say, five to 10 years time? And as a reminder, I'm going to assign each of the debaters these topics, their assignments may or may not match their true feelings about this topic, and they definitely don't represent the topics of my employer, CloudHealth by VMware. Stu, you're going to argue for containers. Corey you're going to argue for start serverless. Stu, you're up first. Two minutes on the clock and go. >> All right, so with all respect to my friends in the serverless community, We need to have a reality check as to how things work. We all know that serverless is a ridiculous name because underneath we do need to worry about all of the infrastructure underneath. So containers today are the de facto building block for cloud native architectures, just as the VM defined the ecosystem for an entire generation of solutions. Containers are the way we build things today. It is the way Google has architected their entire solution and underneath it is often something that's used with serverless. So yes, if you're, building an Alexa service, serverless make what's good for you. But for the vast majority of solutions, I need to have flexibility, I need to understand how things work underneath it. We know in IT that it's great when things work, but we need to understand how to fix them when they break. So containerization gets us to that atomic level, really close to having the same thing as the application. And therefore, we saw the millions of users that deploy Docker, we saw the huge wave of container orchestration led by Kubernetes. And the entire ecosystem and millions of customers are now on board with this way of designing and architecting and breaking down the silos between the infrastructure world and the application developer world. So containers, here to stay growing fast. >> All right, Corey, what do you think? Why is serverless the future? >> I think that you're right in that containers are the way you get from where you were to something that runs effectively in a cloud environment. That is why Google is so strongly behind Kubernetes it helps get the entire industry to write code the way that Google might write code. And that's great. But if you're looking at effectively rewriting something from scratch, or building something that new, the idea of not having to think about infrastructure in the traditional sense of being able to just here, take this code and run it in a given provider that takes whatever it is that you need to do and could loose all these other services together, saves an awful lot of time. As that continues to move up the stack towards the idea of no code or low code. And suddenly, you're now able to build these applications in ways that require just a little bit of code that tie together everything else. We're closer than ever to that old trope of the only code you write is business logic. Serverless gives a much clearer shot of getting there, if you can divorce yourself from the past of legacy workloads. Legacy, of course meaning older than 18 months and makes money. >> Stu, do you have a rebuttal, 60 seconds? >> Yeah. So Corey, we've been talking about this Nirvana in many ways. It's the discussion that we had for paths for over a decade now. I want to be able to write my code once not worry about where it lives, and do all this. But sometimes, there's a reason why we keep trying the same thing over and over again, but never reaching it. So serverless is great for some application If you talked about, okay, if you're some brand new webby thing there and I don't want to have to do this team, that's awesome. I've talked to some wonderful people that don't know anything about coding that have built some cool stuff with serverless. But cool stuff isn't what most business runs on, and therefore containerization is, as you said, it's a bridge to where I need to go, it lives in these cloud environments, and it is the present and it is the future. >> Corey, your response. >> I agree that it's the present, I doubt that it's the future in quite the same way. Right now Kubernetes is really scratching a major itch, which is how all of these companies who are moving to public cloud still I can have their infrastructure teams be able to cosplay as cloud providers themselves. And over time, that becomes simpler and I think on some level, you might even see a convergence of things that are container workloads begin to look a lot more like serverless workloads. Remember, we're aiming at something that is five years away in the context of this question. I think that the serverless and container landscape will look very different. The serverless landscape will be bright and exciting and new, whereas unfortunately the container landscape is going to be represented by people like you Stu. >> Hoarse words from Corey. Stu, any last words or rebuttals? >> Yeah, and look Corey absolutely just like we don't really think about the underlying server or VM, we won't think about the containers you won't think about Kubernetes in the future, but, the question is, which technology will be used in five to 10 years, it'll still be there. It will be the fabric of our lives underneath there for containerization. So, that is what we were talking about. Serverless I think will be useful in pockets of places but will not be the predominant technology, five years from now. >> All right, tough to say who won that one? I'm glad I don't have to decide. I hope everyone out there is voting, last chance to vote on this question before we move on to the next. Next topic is cloud wars. I'm going to give a statement and then I'm going to assign each of you a pro or a con, Google will never be an actual contender in the cloud wars always a far third, we're going to have Corey arguing that Google is never going to be an actual contender. And Stu, you're going to argue that Google is eventually going to overtake the top two AWS and Azure. As a constant reminder, I'm assigning these topics, it's my decision and also they don't match the opinions of me, my employer, or likely Stu or Corey. This is all just for fun and games. But I really want to hear what everyone has to say. So Corey, you're up first two minutes. Why is Google never going to be an actual contender and go. >> The biggest problem Google has in the time of cloud is their ability to forecast longer term on anything that isn't their advertising business, and their ability to talk to human beings long enough to meet people where they are. We're replacing their entire culture is what it's going to take to succeed in the time of cloud and with respect, Thomas Kurian is a spectacular leader internally but look at where he's come from. He spent 22 years at Oracle and now has been transplanted into Google. If we take a look at Satya Nadella's cloud transformation at Microsoft, he was able to pull that off as an insider, after having known intimately every aspect of that company, and he grew organically with it and was perfectly positioned to make that change. You can't instill that kind of culture change by dropping someone externally, on top of an organization and expecting anything to go with this magic one day wake up and everything's going to work out super well. Google has a tremendous amount of strengths, and I don't see that providing common denominator cloud computing services to a number of workloads that from a Google perspective are horrifying, is necessarily in their wheelhouse. It feels like their entire focus on this is well, there's money over there. We should go get some of that too. It comes down to the traditional Google lack of focus. >> Stu, rebuttal? Why do you think Google has a shaft? >> Yeah, so first of all, Corey, I think we'd agree Google is a powerhouse in the world today. My background is networking, when they first came out with with Google Cloud, I said, Google has the best network, second to none in the world. They are ubiquitous today. If you talk about the impact they have on the world, Android phones, you mentioned Kubernetes, everybody uses G Suite maps, YouTube, and the like. That does not mean that they are necessarily going to become the clear leader in cloud but, Corey, they've got really, really smart people. If you're not familiar with that talk to them. They'll tell you how smart they are. And they have built phenomenal solutions, who's going to be able to solve, the challenge every day of, true distributed systems, that a global database that can handle the clock down to the atomic level, Google's the one that does that we've all read the white papers on that. They've set the tone for Hadoop, and various solutions that are all over the place, and their secret weapon is not the advertising, of course, that is a big concern for them, but is that if you talk about, the consumer adoption, everyone uses Google. My kids have all had Chromebooks growing up. It isn't their favorite thing, but they get, indoctrinated with Google technology. And as they go out and leverage technologies in the world, Google is one that is known. Google has the strength of technology and a lot of positioning and partnerships to move them forward. Everybody wants a strong ecosystem in cloud, we don't want a single provider. We already discussed this before, but just from a competitive nature standpoint, if there is a clear counterbalance to AWS, I would say that it is Google, not Microsoft, that is positioned to be that clear and opportune. >> Interesting, very interesting Stu. So your argument is the Gen Zers will of ultimately when they come of age become the big Google proponents. Some strong words that as well but they're the better foil to AWS, Corey rebuttal? >> I think that Stu is one t-shirt change away from a pitch perfect reenactment of Charlie Brown. In this case with Google playing the part of Lucy yanking the football away every time. We've seen it with inbox, Google Reader, Google Maps, API pricing, GKE's pricing for control plane. And when your argument comes down to a suddenly Google is going to change their entire nature and become something that it is as proven as constitutionally incapable of being, namely supporting something that its customers want that it doesn't itself enjoy working on. And to the exclusion of being able to get distracted and focused on other things. Even their own conferences called Next because Google is more interested in what they're shipping than what they're building, than what they're currently shipping. I think that it is a fantasy to pretend that that is somehow going to change without a complete cultural transformation, which again, I don't see the seeds being planted for. >> Some sick burns in there Stu, rebuttal? >> Yeah. So the final word that I'll give you on this is, one of the most important pieces of what we need today. And we need to tomorrow is our data. Now, there are some concerns when we talk about Google and data, but Google also has strong strength in data, understanding data, helping customers leverage data. So while I agree to your points about the cultural shift, they have the opportunity to take the services that they have, and enable customers to be able to take their data to move forward to the wonderful world of AI, cloud, edge computing, and all of those pieces and solve the solution with data. >> Strong words there. All right, that's a tough one. Again, I hope you're all out there voting for who you think won that round. Let's move on to the last round before we start hitting the lightning questions. I put a call out on several channels and social media for people to have questions that they want you to debate. And this one comes from Og-AWS Slack member, Angelo. Angelo asks, "What about IBM Cloud?" Stu you're pro, Corey you're con. Let's have Stu you're up first. The question is, what about IBM Cloud? >> All right, so great question, Angelo. I think when you look at the cloud providers, first of all, you have to understand that they're not all playing the same game. We talked about AWS and they are the elephant in the room that moves nimbly as a cheetah. Every other provider plays a little bit of a different game. Google has strength in data. Microsoft, of course, has their, business productivity applications. IBM has a strong legacy. Now, Corey is going to say that they are just legacy and you need to think about them but IBM has strong innovation. They are a player in really what we call chapter two of the cloud. So when we start talking about multicloud, when we start talking about living in many environments, IBM was the first one to partner with VMware for VMware cloud before the mega VMware AWS announcement, there was IBM up on stage and if I remember right, they actually have more VMware customers on IBM Cloud than they do in the AWS cloud. So over my shoulder here, there's of course, the Red Hat $34 billion to bet on that multicloud solution. So as we talk about containerization, and Kubernetes, Red Hat is strongly positioned in open-source, and flexibility. So you really need a company that understands both the infrastructure side and the application side. IBM has database, IBM has infrastructure, IBM has long been the leader in middleware, and therefore IBM has a real chance to be a strong player in this next generation of platforms. Doesn't mean that they're necessarily going to go attack Amazon, they're partnering across the board. So I think you will see a kinder, gentler IBM and they are leveraging open source and Red Hat and I think we've let the dogs out on the IBM solution. >> Indeed. >> So before Corey goes, I feel the need to remind everyone that the views expressed here are not the views of my employer nor myself, nor necessarily of Corey or Stu. I have Corey. >> I haven't even said anything yet. And you're disclaiming what I'm about to say. >> I'm just warning the audience, 'cause I can't wait to hear what you're going to say next. >> Sounds like I have to go for the high score. All right. IBM's best days are behind it. And that is pretty clear. They like to get angry when people talk about how making the jokes about a homogenous looking group of guys in blue suits as being all IBM has to offer. They say that hasn't been true since the '80s. But that was the last time people cared about IBM in any meaningful sense and no one has bothered to update the relevance since then. Now, credit where due, I am seeing an awful lot of promoted tweets from IBM into my timeline, all talking about how amazing their IBM blockchain technology is. And yes, that is absolutely the phrasing of someone who's about to turn it all around and win the game. I don't see it happening. >> Stu, rebuttal? >> Look, Corey, IBM was the company that brought us the UPC code. They understand Mac manufacturing and blockchain actually shows strong presence in supply chain management. So maybe you're not quite aware of some of the industries that IBM is an expert in. So that is one of the big strengths of IBM, they really understand verticals quite well. And, at the IBM things show, I saw a lot in the healthcare world, had very large customers that were leveraging those solutions. So while you might dismiss things when they say, Oh, well, one of the largest telecom providers in India are leveraging OpenStack and you kind of go with them, well, they've got 300 million customers, and they're thrilled with the solution that they're doing with IBM, so it is easy to scoff at them, but IBM is a reliable, trusted provider out there and still very strong financially and by the way, really excited with the new leadership in place there, Arvind Krishna knows product, Jim Whitehurst came from the Red Hat side. So don't be sleeping on IBM. >> Corey, any last words? >> I think that they're subject to massive disruption as soon as they release the AWS 400 mainframe in the cloud. And I think that before we, it's easy to forget this, but before Google was turning off Reader, IBM stopped making the model M buckling spring keyboards. Those things were masterpieces and that was one of the original disappointments that we learned that we can't fall in love with companies, because companies in turn will not love us back. IBM has demonstrated that. Lastly, I think I'm thrilled to be working with IBM is exactly the kind of statement one makes only at gunpoint. >> Hey, Corey, by the way, I think you're spending too much time looking at all titles of AWS services, 'cause you don't know the difference between your mainframe Z series and the AS/400 which of course is heavily pending. >> Also the i series. Oh yes. >> The i series. So you're conflating your system, which still do billions of dollars a year, by the way. >> Oh, absolutely. But that's not we're not seeing new banks launching and then building on top of IBM mainframe technology. I'm not disputing that mainframes were phenomenal. They were, I just don't see them as the future and I don't see a cloud story. >> Only a cloud live your mainframe related smack talk. That's the important thing that we're getting to here. All right, we move-- >> I'm hoping there's an announcement from CloudHealth by VMware that they also will now support mainframe analytics as well as traditional cloud. >> I'll look into that. >> Excellent. >> We're moving on to the lightning rounds. Each debater in this round is only going to get 60 seconds for their opening argument and then 30 seconds for a rebuttal. We're going to hit some really, really big important questions here like this first one, which is who deserves to sit on the Iron Throne at the end of "Game of Thrones?" I've been told that Corey has never seen this TV show so I'm very interested to hear him argue for Sansa. But let's Sansa Stark, let's hear Stu go first with his argument for Jon Snow. Stu one minute on the clock, go. >> All right audience let's hear it from the king of the north first of all. Nothing better than Jon Snow. He made the ultimate sacrifice. He killed his love to save Westeros from clear destruction because Khaleesi had gone mad. So Corey is going to say something like it's time for the women to do this but it was a woman she went mad. She started burning the place down and Jon Snow saved it so it only makes sense that he should have done it. Everyone knows it was a travesty that he was sent back to the Wall, and to just wander the wild. So absolutely Jon Snow vote for King of the North. >> Compelling arguments. Corey, why should Sansa Stark sit on the throne? Never having seen the show I've just heard bits and pieces about it and all involves things like bloody slaughters, for example, the AWS partner Expo right before the keynote is best known as AWS red wedding. We take a look at that across the board and not having seen it, I don't know the answer to this question, but how many of the folks who are in positions of power we're in fact mediocre white dudes and here we have Stu advocating for yet another one. Sure, this is a lightning round of a fun event but yes, we should continue to wind up selecting this mediocre white person has many parallels in terms of power, et cetera, politics, current tech industry as a whole. I think she's right we absolutely should give someone with a look like this a potential opportunity to see what they can do instead. >> Ouch, Stu 30 seconds rebuttal. >> Look, I would just give a call out to the women in the audience and say, don't you want Jon Snow to be king? >> I also think it's quite bold of Corey to say that he looks like Kit Harington. Corey, any last words? >> I think that it sad you think Stu was running for office at this point because he's become everyone's least favorite animal, a panda bear. >> Fire. All right, so on to the next question. This one also very important near and dear to my heart personally, is a hot dog a sandwich. Corey you'll be arguing no, Stu will be arguing yes. I must also add this important disclaimer that these assignments are made by me and might not reflect the actual views of the debaters here so Corey, you're up first. Why is a hot dog not a sandwich? >> Because you'll get punched in the face if you go to a deli of any renown and order a hot dog. That is not what they serve there. They wind up having these famous delicatessen in New York they have different sandwiches named after different celebrities. I shudder to think of the deadly insult that naming a hot dog after a celebrity would be to that not only celebrity in some cases also the hot dog too. If you take a look and you want to get sandwiches for lunch? Sure. What are we having catered for this event? Sandwiches. You show up and you see a hot dog, you're looking around the hot dog to find the rest of the sandwich. Now while it may check all of the boxes for a technical definition of what a sandwich is, as I'm sure Stu will boringly get into, it's not what people expect, there's a matter of checking the actual boxes, and then delivering what customers actually want. It's why you can let your product roadmap be guided by cart by customers or by Gartner but rarely both. >> Wow, that one hurts. Stu, why is the hot dog a sandwich? >> Yeah so like Corey, I'm sorry that you must not have done some decent traveling 'cause I'm glad you brought up the definition because I'm not going to bore you with yes, there's bread and there's meat and there's toppings and everything else like that but there are some phenomenal hot dogs out there. I traveled to Iceland a few years ago, and there's a little hot dog stand out there that's been there for over 40 or 50 years. And it's one of the top 10 culinary experience I put in. And I've been to Michelin star restaurants. You go to Chicago and any local will be absolutely have to try our creation. There are regional hot dogs. There are lots of solutions there and so yeah, of course you don't go to a deli. Of course if you're going to the deli for takeout and you're buying meats, they do sell hot dogs, Corey, it's just not the first thing that you're going to order on the menu. So I think you're underselling the hot dog. Whether you are a child and grew up and like eating nothing more than the mustard or ketchup, wherever you ate on it, or if you're a world traveler, and have tried some of the worst options out there. There are a lot of options for hot dogs so hot dog, sandwich, culinary delight. >> Stu, don't think we didn't hear that pun. I'm not sure if that counts for or against you, but Corey 30 seconds rebuttal. >> In the last question, you were agitating for putting a white guy back in power. Now you're sitting here arguing that, "Oh some of my best friend slash meals or hot dogs." Yeah, I think we see what you're putting down Stu and it's not pretty, it's really not pretty and I think people are just going to start having to ask some very pointed, delicate questions. >> Tough words to hear Stu. Close this out or rebuttal. >> I'm going to take the high road, Rachel and leave that where it stands. >> I think that is smart. All right, next question. Tabs versus spaces. Stu, you're going to argue for tabs, Corey, you're going to argue for spaces just to make this fun. Stu, 60 seconds on the clock, you're up first. Why are tabs the correct approach? >> First of all, my competitor here really isn't into pop culture. So he's probably not familiar with the epic Silicon Valley argument over this discussion. So, Corey, if you could explain the middle of algorithm, we will be quite impressed but since you don't, we'll just have to go with some of the technology first. Looks, developers, we want to make things simple on you. Tabs, they're faster to do they take up less memory. Yes, they aren't quite as particular as using spaces but absolutely, they get the job done and it is important to just, focus on productivity, I believe that the conversation as always, the less code you can write, the better and therefore, if you don't have to focus on exactly how many spaces and you can just simplify with the tabs, you're gona get close enough for most of the job. And it is easier to move forward and focus on the real work rather than some pedantic discussion as to whether one thing is slightly more efficient than the other. >> Great points Stu. Corey, why is your pedantic approach better? >> No one is suggesting you sit there and whack the spacebar four times or eight times you hit the Tab key, but your editor should be reasonably intelligent enough to expand that. At that point, you have now set up a precedent where in other cases, other parts of your codebase you're using spaces because everyone always does. And that winds up in turn, causing a weird dissonance you'll see a bunch of linters throwing issues if you use tabs as a direct result. Now the wrong answer is, of course, and I think Steve will agree with me both in the same line. No one is ever in favor of that. But I also want to argue with Stu over his argument about "Oh, it saves a little bit of space "is the reason one should go with tabs instead." Sorry, that argument said bye bye a long time ago, and that time was the introduction of JavaScript, where it takes many hundreds of Meg's of data to wind up building hello world. Yeah, at that point optimization around small character changes are completely irrelevant. >> Stu, rebuttal? >> Yeah, I didn't know that Corey did not try to defend that he had any idea what Silicon Valley was, or any of the references in there. So Rachel, we might have to avoid any other pop culture references. We know Corey just looks at very specific cloud services and can't have fun with some of the broader themes there. >> You're right my mistake Stu. Corey, any last words? >> It's been suggested that whole middle out seen on the whiteboard was came from a number of conversations I used to have with my co-workers as in people who were sitting in the room with me watching that episode said, Oh my God, I've been in the room while you had this debate with your friend and I will not name here because they at least still strive to remain employable. Yeah, it's, I understand the value in the picking these fights, we could have gone just as easily with vi versus Emacs, AWS versus Azure, or anything else that you really care to pick a fight with. But yeah, this is exactly the kind of pedantic fight that everyone loves to get involved with, which is why I walked a different path and pick other ridiculous arguments. >> Speaking of those ridiculous arguments that brings us to our last debate topic of the day, Corey you are probably best known for your strong feelings about the pronunciation of the acronym for Amazon Machine Image. I will not be saying how I think it is pronounced. We're going to have you argue each. Stu, you're going to argue that the acronym Amazon Machine Image should be pronounced to rhyme with butterfly. Corey, you'll be arguing that it rhymes with mommy. Stu, rhymes with butterfly. Let's hear it, 60 seconds on the clock. >> All right, well, Rachel, first of all, I wish I could go to the videotape because I have clear video evidence from a certain Corey Quinn many times arguing why AMI is the proper way to pronounce this, but it is one of these pedantic arguments, is it GIF or GIF? Sometimes you go back and you say, Okay, well, there's the way that the community did it. And the way that oh wait, the founder said it was a certain way. So the only argument against AMI, Jeff Barr, when he wrote about the history of all of the blogging that he's done from AWS said, I wish when I had launched the service that I pointed out the correct pronunciation, which I won't even deem to talk it because the community has agreed by and large that AMI is the proper way to pronounce it. And boy, the tech industry is rific on this kind of thing. Is it SQL and no SQL and you there's various ways that we butcher these constantly. So AMI, almost everyone agrees and the lead champion for this argument, of course is none other than Corey Quinn. >> Well, unfortunately today Corey needs to argue the opposite. So Corey, why does Amazon Machine Image when pronounce as an acronym rhyme with mommy? >> Because the people who built it at Amazon say that it is and an appeal to authorities generally correct when the folks built this. AWS has said repeatedly that they're willing to be misunderstood for long periods of time. And this is one of those areas in which they have been misunderstood by virtually the entire industry, but they are sticking to their guns and continuing to wind up advocating for AMI as the correct pronunciation. But I'll take it a step further. Let's take a look at the ecosystem companies. Whenever Erica Brescia, who is now the COO and GitHub, but before she wound up there, she was the founder of Bitnami. And whenever I call it Bitn AMI she looks like she is barely successfully restraining herself from punching me right in the mouth for that pronunciation of the company. Clearly, it's Bitnami named after the original source AMI, which is what the proper term pronunciation of the three letter acronym becomes. Fight me Stu. >> Interesting. Interesting argument, Stu 30 seconds, rebuttal. >> Oh, the only thing he can come up with is that, you take the word Bitnami and because it has that we know that things sound very different if you put a prefix or a suffix, if you talk to the Kubernetes founders, Kubernetes should be coop con but the people that run the conference, say it cube con so there are lots of debates between the people that create it and the community. I in general, I'm going to vote with the community most of the time. Corey, last words on this topic 'cause I know you have very strong feelings about it. >> I'm sorry, did Stu just say Kubernetes and its community as bastions of truth when it comes to pronouncing anything correctly? Half of that entire conference is correcting people's pronunciation of Kubernetes, Kubernetes, Kubernetes, Kubernetes and 15 other mispronunciations that they will of course yell at you for but somehow they're right on this one. All right. >> All right, everyone, I hope you've been voting all along for who you think is winning each round, 'cause this has been a tough call. But I would like to say that's a wrap for today. big thank you to our debaters. You've been very good sports, even when I've made you argue for against things that clearly are hurting you deep down inside, we're going to take a quick break and tally all the votes. And we're going to announce a winner up on the Zoom Q and A. So go to the top of your screen, Click on Zoom Q and A to join us and hear the winner announced and also get a couple minutes to chat live with Corey and Stu. Thanks again for attending this session. And thank you again, Corey and Stu. It's been The Great Cloud Debate. All right, so each round I will announce the winner and then we're going to announce the overall winner. Remember that Corey and Stu are playing not just for bragging rights and ownership of all of the internet for the next 24 hours, but also for lunch to be donated to their local hospital. Corey is having lunch donated to the California Pacific Medical Centre. And Stu is having lunch donated to Boston Medical Centre. All right, first up round one multicloud versus monocloud. Stu, you were arguing for multicloud, Corey, you were arguing for one cloud. Stu won that one by 64% of the vote. >> The vendor fix was in. >> Yeah, well, look, CloudHealth started all in AWS by supporting customers across those environments. So and Corey you basically conceded it because we said multicloud does not mean we evenly split things up. So you got to work on those two skills, buddy, 'cause, absolutely you just handed the victory my way. So thank you so much and thank you to the audience for understanding multicloud is where we are today, and unfortunately, it's where we're gonnao be in the future. So as a whole, we're going to try to make it better 'cause it is, as Corey and I both agree, a bit of a mess right now. >> Don't get too cocky. >> One of those days the world is going to catch up with me and realize that ad hominem is not a logical fallacy so much as it is an excellent debating skill. >> Well, yeah, I was going to say, Stu, don't get too cocky because round two serverless versus containers. Stu you argued for containers, Corey you argued for serverless. Corey you won that one with 65, 66 or most percent of the vote. >> You can't fight the future. >> Yeah, and as you know Rachel I'm a big fan of serverless. I've been to the serverless comp, I actually just published an excellent interview with Liberty Mutual and what they're doing with serverless. So love the future, it's got a lot of maturity to deliver on the promise that it has today but containers isn't going anyway or either so. >> So, you're not sad that you lost that one. Got it, good concession speech. Next one up was cloud wars specifically Google. is Google a real contender in the clouds? Stu, you were arguing yes they are. Corey, you were arguing no they aren't. Corey also won this round was 72% of the votes. >> Yeah, it's one of those things where at some point, it's sort of embarrassing if you miss a six inch pot. So it's nice that that didn't happen in this case. >> Yeah, so Corey, is this the last week that we have any competitors to AWS? Is that what we're saying? And we all accept our new overlords. Thank you so much, Corey. >> Well I hope not, my God, I don't know what to be an Amazonian monoculture anymore than I do anyone else. Competition makes all of us better. But again, we're seeing a lot of anti competitive behaviour. For example, took until this year for Microsoft to finally make calculator uninstallable and I trust concerned took a long time to work its way of course. >> Yeah, and Corey, I think everyone is listening to what you've been saying about what Google's doing with Google Meet and forcing that us when we make our pieces there. So definitely there's some things that Google culture, we'd love them to clean up. And that's one of the things that's really held back Google's enterprise budget is that advertised advertising driven culture. So we will see. We are working hand-- >> That was already opted out of Hangouts, how do we fix it? We call it something else that they haven't opted out of yet. >> Hey, but Corey, I know you're looking forward to at least two months of weekly Google live stuff starting this summer. So we'll have a lot of time to talk about google. >> Let's not kid ourselves they're going to cancel it halfway through. (Stu laughs) >> Boys, I thought we didn't have any more smack talk left in you but clearly you do. So, all right, moving on. Next slide. This is the last question that we did in the main part of the debate. IBM Cloud. What about IBM Cloud was the question, Stu, you were pro, Corey you were con. Corey, you won this one again with 62% of the vote and for the main. >> It wasn't just me, IBM Cloud also won. The problem is that competition was oxymoron of the day. >> I don't know Rachel, I thought this one had a real shot as to putting where IBM fits. I thought we had a good discussion there. It seemed like some of the early voting was going my way but it just went otherwise. >> It did. We had some last minute swings in these polls. They were going one direction they rapidly swung another it's a fickle crowd today. So right now we've got Corey with three points Stu with one but really the lightning round anyone's game. They got very close here. The next question, lightning round question one, was "Game of Thrones" who deserves to sit on the Iron Throne? Stu was arguing for Jon Snow, Corey was arguing for Sansa Stark also Corey has never seen Game of Thrones. This was shockingly close with Stu at 51.5% of the vote took the crown on this King of the North Stu. >> Well, I'm thrilled and excited that King of the North pulled things out because it would have been just a complete embarrassment if I lost to Corey on this question. >> It would. >> It was the right answer, and as you said, he had no idea what he's talking about, which, unfortunately is how he is on most of the rest of it. You just don't realize that he doesn't know what he's talking about. 'Cause he uses all those fast words and discussion points. >> Well, thank you for saying the quiet part out loud. Now, I am completely crestfallen as to the results of this question about a thing I've never seen and could not possibly care less about not going in my favor. I will someday managed to get over this. >> I'm glad you can really pull yourself together and keep on going with life, Corey it's inspiring. All right, next question. Was the lightning round question two is a hot dog a sandwich? Stu, you were arguing yes. Corey, you were arguing no. Corey landslide, you won this 75% of the vote. >> It all comes down to customer expectations. >> Yeah. >> Just disappointment. Disappointment. >> All right, next question tabs versus spaces. Another very close one. Stu, what were you arguing for Stu? >> I was voting tabs. >> Tabs, yeah. And Corey, you were arguing spaces. This did not turn out the way I expected. So Stu you lost this by slim margin Corey 53% of the vote. You won with spaces. >> Yep. And I use spaces in my day to day life. So that's a position I can actually believe in. >> See, I thought I was giving you the opposite point of view there. I mistook you for the correct answer, in my opinion, which is tabs. >> Well, it is funnier to stalk me on Twitter and look what I have to there than on GitHub where I just completely commit different kinds of atrocities. So I don't blame you. >> Caught that pun there. All right, the last rounds. Speaking of atrocities, AMI, Amazon Machine Image is it pronounced AMI or AMI? >> I better not have won this one. >> So Stu you were arguing that this is pronounced AMI rhymes with butterfly. Corey, you were arguing that it's pronounced AMI like mommy. Any guesses under who won this? >> It better be Stu. >> It was a 50, 50 split complete tie. So no points to anyone. >> For your complete and utterly failed on this because I should have won in a landslide. My entire argument was based on every discussion you've had on this. So, Corey I think they're just voting for you. So I'm really surprised-- >> I think at this point it shows I'm such a skilled debater that I could have also probably brought you to a standstill taking the position that gravity doesn't exist. >> You're a master of few things, Corey. Usually it's when you were dressed up nicely and I think they like the t-shirt. It's a nice t-shirt but not how we're usually hiding behind the attire. >> Truly >> Well. >> Clothes don't always make a demand. >> Gentlemen, I would like to say overall our winner today with five points is Corey. Congratulations, Corey. >> Thank you very much. It's always a pleasure to mop the floor with you Stu. >> Actually I was going to ask Stu to give the acceptance speech for you, Corey and, Corey, if you could give a few words of concession, >> Oh, that's a different direction. Stu, we'll start with you, I suppose. >> Yeah, well, thank you to the audience. Obviously, you voted for me without really understanding that I don't know what I'm talking about. I'm a loudmouth on Twitter. I just create a bunch of arguments out there. I'm influential for reasons I don't really understand. But once again, thank you for your votes so much. >> Yeah, it's always unfortunate to wind up losing a discussion with someone and you wouldn't consider it losing 'cause most of the time, my entire shtick is that I sit around and talk to people who know what they're talking about. And I look smart just by osmosis sitting next to them. Video has been rough on me. So I was sort of hoping that I'd be able to parlay that into something approaching a victory. But sadly, that hasn't worked out quite so well. This is just yet another production brought to you by theCube which shut down my original idea of calling it a bunch of squares. (Rachael laughs) >> All right, well, on that note, I would like to say thank you both Stu and Corey. I think we can close out officially the debate, but we can all stick around for a couple more minutes in case any fans have questions for either of them or want to get them-- >> Find us a real life? Yeah. >> Yeah, have a quick Zoom fight. So thanks, everyone, for attending. And thank you Stu, thank you Corey. This has been The Great Cloud Debate.
SUMMARY :
Cloud Economist at the Duckbill Group and less of the pleasure to talk to Stu. to vote of who you think is winning. for the Boston audience All right, Corey, what about you? the lunch to his department. This is your moment for smack talk. to a specific technology area. minutes on the clock and go. is the ability to leverage whatever All right, Stu, your turn. and saying that you that leads to ridiculous of you in the audience, is the way to go. to it than you have. each of the debaters these topics, and breaking down the silos of the only code you and it is the future. I agree that it's the present, I doubt Stu, any last words or rebuttals? about Kubernetes in the future, to assign each of you a pro or a con, and their ability to talk but is that if you talk about, to AWS, Corey rebuttal? that that is somehow going to change and solve the solution with data. that they want you to debate. the Red Hat $34 billion to bet So before Corey goes, I feel the need And you're disclaiming what you're going to say next. and no one has bothered to update So that is one of the and that was one of the and the AS/400 which of course Also the i series. So you're conflating your system, I'm not disputing that That's the important thing that they also will now to sit on the Iron Throne at So Corey is going to say something like We take a look at that across the board to say that he looks like Kit Harington. you think Stu was running and might not reflect the actual views of checking the actual boxes, Wow, that one hurts. I'm not going to bore you I'm not sure if that just going to start having Close this out or rebuttal. I'm going to take the high road, Rachel Stu, 60 seconds on the I believe that the conversation as always, Corey, why is your and that time was the any of the references in there. Corey, any last words? that everyone loves to get involved with, We're going to have you argue each. and large that AMI is the to argue the opposite. that it is and an appeal to Stu 30 seconds, rebuttal. I in general, I'm going to vote that they will of course yell at you for So go to the top of your screen, So and Corey you basically realize that ad hominem or most percent of the vote. Yeah, and as you know Rachel is Google a real contender in the clouds? So it's nice that that that we have any competitors to AWS? to be an Amazonian monoculture anymore And that's one of the things that they haven't opted out of yet. to at least two months they're going to cancel and for the main. The problem is that competition a real shot as to putting where IBM fits. of the vote took the crown that King of the North is on most of the rest of it. to the results of this Was the lightning round question two It all comes down to Stu, what were you arguing for Stu? margin Corey 53% of the vote. And I use spaces in my day to day life. I mistook you for the correct answer, to stalk me on Twitter All right, the last rounds. So Stu you were arguing that this So no points to anyone. and utterly failed on this to a standstill taking the position Usually it's when you to say overall our winner It's always a pleasure to mop the floor Stu, we'll start with you, I suppose. Yeah, well, thank you to the audience. to you by theCube which officially the debate, Find us a real life? And thank you Stu, thank you Corey.
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Nick Barcet, Red Hat | Red Hat Summit 2020
>> Announcer: From around the globe, it's theCUBE with digital coverage of Red Hat Summit 2020. brought to you by Red Hat. >> Welcome back. This is theCUBE's coverage of Red Hat Summit 2020. Of course this year instead of all gathering together in San Francisco, we're getting to talk to Red Hat executives, their partners and their customers where they are around the globe. I'm your host Stuart Miniman and happy to welcome to the program Nick Barcet, who is the Senior Director of Technology Strategy at Red Hat. He happens to be on a boat in the Bahamas. So Nick, thanks so much for joining us. >> Hey thank you for inviting me. It's a great pleasure to be here and it's a great pleasure to work for a company that has always dealt with remote people. So it's really easy for us to, kind of thing. >> Yeah Nick. You know it's interesting, I've been saying probably for the last 10 years that the challenge of our time is really distributed systems. You know from a software standpoint that's what we talk about and even more so today number one of course the current situation with the global pandemic but number two the topic we're going to talk to you about is edge and 5G. It's obviously gotten a lot of hype. So before we get into that my understanding Nick, you know you came into Red Hat through an acquisition. So give us a little bit about your background and what you work on for Red Hat. >> About five years ago company I was working for eNovance got acquired by Red Hat and I've been very lucky in that acquisition where I found a perfect home to express my talent. I've been free software advocate for the past 20 some years. Always been working in free software for the past 20 years and Red Hat is really wonderful for that. >> Yeah it's addressing me okay yeah. I remember back the early days we used to talk about free software. Now we don't talk free, open-source is what we talk about you know. Bream is a piece of what we're doing but let's talk about you know, You know, eNovanceI absolutely remember they were partner of Red Hat. I talked to them and a lot at some of the OpenStack shows. So I'm guessing when we're talking about edge, these are kind of the pieces coming together of what Red had done for years with OpenStack and with NFB. So what, what's the solution set you're talking about? Bring us inside, how you're helping your customers with these types of split. >> Well clearly the solution we are trying to put together as to combine what people already have with where they want to go. Our vision for the future is a vision where OpenShift is delivering a common service on any platform including hardware at the far edge on a model where both v-ends and containers can be hosted on the same machine. However there is a long road to get there and until we can fulfill all the needs, we are going to be using combination of OpenShift, OpenStack and many other product that we have in our portfolio to fulfill the needs of our customer. We've seen for example Verizon starting with OpenStack quite a few years ago now going with us with OpenShift that they're going to place on up of OpenStack or directly on bare metal. We've seen other big telcos use that in very successful to deploy their 5G networks. There is great capabilities in the existing portfolio. We are just expanding that simplifying it because when we are talking about the edge, we are talking about managing thousands if not millions of device and simplicity is key if you do not want to have your management parts in Crete. >> Excellent. So you talked a lot about the service providers. Obviously 5G as a big wave coming a lot of promise as what it will enable both for the service providers as well as the end-users. Help us understand where that is today and what we should expect to see in the coming years though. >> So in respect of 5G, there is two reason why 5G is important. One it is-- It is important in terms of edge strategy because any person deploying 5G will need to deploy computer resources much closer to the antenna if they want to be able to deliver the promise of 5G and the promise of very low latency. The second reason it is important is because it allows to build a network of things which do not need to be interconnected other than through a 5G connection. And this simplifies a lot some of the edge application that we are going to see where sensors need to provide data in a way where you're not necessarily always connected to a physical network and maintaining a WiFi connection is really complex and costly. >> Yeah Nick a lot of pieces that sometimes get confused or conflated, I want you to help us connect the dots between what you're talking about for edge and what's happening in the telcos and the the broader conversation about hybrid cloud or Red Hat calls at the open hybrid cloud because you know there were some articles that were like you know edge is going to kill the cloud. I think we all know an IP nothing ever dies, everything is all additive. So how do these pieces all go together? >> So for us at Red Hat, it's very important to build edge as an extension of our open hybrid cloud strategy. Clearly what we are trying to build is an environment where developers can develop workloads once and then can the administrator that needs to deploy a workload or the business mode that needs to deploy a workload can do it on any footprint. And the edge is just one of these footprint as is the cloud as is a private environment. So really having a single way to administer all these footprints, having a single way to define the workloads running on it, is really what we are achieving today and making better and better in the years to come. The reality of... to process the data as close as possible to where the data is being consumed or generated. So you have new footprints to let's say summarize or simplify or analyze the data where it is being used. And then you can limit the traffic to a more central site to only the essential of it. It is clear that with the current growth of data, there won't be enough capacity to have all the data going directly to the central path. And this is what the edge is about, making sure we have intermediary of points of processing. >> Yeah absolutely. So Nick you talked about OpenStack and OpenShift. Of course there's open source project with with OpenStack. OpenShift the big piece of that is is Kubernetes. When it comes to edge are there other open source project, the parts of the foundations out there that we should highlight when looking at these edge loop? >> Oh, there is a tremendous amount of projects that are pertaining to the edge. Red Hat carries many of these projects in its portfolio. The middleware components for example Quercus or AMQ mechanism, Carlcare are very important components. We've got storage solutions that are super important also when you're talking about storing or handling data. You've got in our management portfolio two very key tool one called Ansible that allows to configure remotely confidence that is super handy when you need to reconfigure firewall in mass. You've got another tool that is the central piece of our strategy which is called ACM, Red Hat's I forgot the name of the product now. We are using the acronym all the time which is our central management mechanism just delivered to us through IBM. So this is a portfolio wide we are making and I forgot the important one which is Red Hat Enterprise Linux which is delivering very soon a new version that is going to enable easier management at yet. >> Yeah. Well of course we know that realers you know the core foundational piece fit with most of the solution in a portfolio. That it's really interesting how you laid that out though. As you know some people on the outside look and say, " Okay, Red Hat's got a really big portfolio. How does it all fit together?" You just discussed that all of these pieces become really important when they come together for the edge. So maybe you know, one of the things when we get together summit of course, we get to hear a lot from your customers. So any customers you can talk about, that might be a good proof point for these solutions that you're talking about today? >> So right now most of the proof points are in the telco industry because these are the first one that have made the investment in depth. And when we are talking about various and we are talking about very large investment that is reinforced in their strategy. We've got customers in telco all over the world that are starting to use our products to deploy their 5G networks and we've got lots of customer starting to work with us on creating their strategy for in other vertical particularly in the industrial and manufacturing sector which is our next endeavour after telco yet. >> Yeah well absolutely. Verizon a customer, I'm well familiar with when it comes to what they've been used with Red Hat. I'd interviewed them, it opens back few years back when they talked about that those nav-pipe solutions. You brought a manufacturing so that brings up one of the concerns when you talk about edge or specifically about IOT environment. When we did some original research looking at the industrial internet, the boundaries between the IT group and the OT which heavily lives in manufacturing wouldn't, they don't necessarily talk or work together. So how's Red Hat helping to make sure that customers you know, go through these transitions, pass through those silos and can take advantage of these sorts of new technologies? >> Well obviously you have to look at a problem in the entirety. You've got to look at the change management aspect and for this, you need to understand how people interact together if you intend on modifying the way they work together. You also need to ensure that the requirements of one are not impeding the other on demand, on environment of a manufacturer. Is really important especially when we are talking about dealing with IOT sensors which have very limited security capability. So you need to add in the appropriate security layers to make what is not secure, secure and if you don't do that you're going to introduce a friction. And you also need to ensure that you can delegate administration of the component to the right people. You cannot say, Oh from now on all of what you used to be controlling on a manufacturing floor is now controlled centrally and you have to go through this form in order to have anything modified. So having the flexibility in our tooling to enable respect of the existing organization and handle a change management the appropriate way. These are way to answer this... >> Right Nick, last thing for you. Obviously this is a maturing space, lots of change happening. So give us a little bit of a look forward as to what users should be expecting and you know what pieces will be the industry and Red Hat be working on that bring full value out of the edge and 5G solution? >> So as always, any such changes are driven by the applications. And what we are seeing is in terms of application, a very large predominance of requirements for AI, ML and data processing capability. So reinforcing all the components around this environment is one of our key addition and that we are making as we speak. You can see Chris keynote which is going to demonstrate how we are enabling a manufacturer to process the signal sent from multiple sensors through an AI and during early failure detection. You can also expect us to enable more and more complex use case in terms of footprint. Right now, we can do very small data center that are residing on three machine. Tomorrow we'll be able to handle remote worker nodes that are on a single machine. Further along we'll be able to deal with disconnected node. A single machine acting as a cluster. All these are elements that are going to allow us to go further and further in the complication of the use cases. It's not the same thing when you have to connect a manufacturer that is on solid grounds with fiber access or when you have to connect the knowledge for example or a vote and talk about that to. >> Well, Nick thank you so much for all the updates. I know there's some really good breakouts. I'm sure there's lots on the Red Hat website to find out more about edge in five B's. Nick Barcet thanks so much for joining us. >> Thank you very much for having me. >> All right. Back with lots more covered from Red Hat Summit 2020. I'm Stuart Miniman and thanks for watching theCUBE. (bright upbeat music)
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Nick Barcet, Red Hat | Red Hat Summit 2020
from around the globe it's the cube with digital coverage of Red Hat summit 2020 brought to you by Red Hat welcome back this is the cubes coverage of Red Hat summit 2020 of course this year instead of all gathering together in San Francisco we're getting to talk to red hat executives their partners and their customers where they are around the globe I'm your host Stu minimun and happy to welcome to the program Nick Barr said who is the senior director of Technology Strategy at Red Hat he happens to be on a boat in the Bahamas so Nick thanks so much for joining us hey thank you for inviting me it's a great pleasure to be here and it's a great pleasure to work for a company that has always dealt with remote people so it's really easy for us to kind of thing yeah Nick you know it's interesting I've been saying probably for the last 10 years that the challenge of our time is really distributed systems you know from a software standpoint that's what we talked about and even more so today and number one of course the current situation with the global plan global pandemic but number two the topic we're gonna talk to you about is edge and 5g it's obviously gotten a lot of hype so before we get into that - training Nick you know you came into Red Hat through an acquisition so give us a little bit about your background and what you work on Baretta about five years ago company I was working for involves got acquired by read at and I've been very lucky in that acquisition where I found a perfect home to express my talent I've been free software advocate for the past 20-some years always been working in free software for the past 20 years and Red Hat is really wonderful for that yeah it's addressing me ok yeah I remember back the early days we used to talk about free software now we don't talk free open-source is what we talk about you know dream is a piece of what we're doing but yeah let's talk about you know Ino Vaughn's I absolutely remember the they were a partner of Red Hat talked to them a lot at some of the OpenStack goes so I I'm guessing when we're talking about edge these are kind of the pieces coming together of what red had done for years with OpenStack and with NFB so what what what's the solution set you're talking about Ferguson side how you're helping your customers with these blue well clearly the solution we are trying to put together as to combine what people already have with where they want to go our vision for the future is a vision where openshift is delivering a common service on any platform including hardware at the far edge on a model where both viens and containers can be hosted on the same machine however there is a long road to get there and until we can fulfill all the needs we are going to be using combination of openshift OpenStack and many other product that we have in our portfolio to fulfill the needs of our customer we've seen for example a Verizon starting with OpenStack quite a few years ago now going with us with openshift that they're going to place on up of OpenStack or directly on bare metal we've seen other big telcos use tag in very successful to deploy their party networks there is great capabilities in the existing portfolio we are just expanding that simplifying it because when we are talking about the edge we are talking about managing thousands if not millions of device and simplicity is key if you do not want to have your management box in Crete excellent so you talked a lot about the service providers obviously 5g as a big wave coming a lot of promise as what it will enable both for the service providers as well as the end-users help us understand where that is today and what we should expect to see in the coming years though so in respect of 5g there is two reason why 5g is important one it is B it is important in terms of ad strategy because any person deploying 5g will need to deploy computer resources much closer to the antenna if they want to be able to deliver the promise of 5g and the promise of very low latency the second reason it is important is because it allows to build a network of things which do not need to be interconnected other than through a 5g connection and this simplifies a lot some of the edge application that we are going to see where sensors needs to provide data in a way where you're not necessarily always connected to a physical network and maintaining a Wi-Fi connection is really complex and costly yeah Nick a lot of pieces that sometimes get confused or conflated I want you to help us connect the dots between what you're talking about for edge and what's happening the telcos and the the broader conversation about hybrid cloud or red hat calls at the O the open hybrid cloud because you know there were some articles that were like you know edge is going to kill the cloud I think we all know an IP nothing ever dies everything is all additive so how do these pieces all go together so for us at reddit it's very important to build edge as an extension of our open hybrid cloud strategy clearly what we are trying to build is an environment where developers can develop workloads once and then can the administrator that needs to deploy a workload or the business mode that means to deploy a workload can do it on any footprint and the edge is just one of these footprint as is the cloud as is a private environment so really having a single way to administer all these footprints having a single way to define the workloads running on it is really what we are achieving today and making better and better in the years to come um the the reality of [Music] who process the data as close as possible to where the data is being consumed or generated so you have new footprints - let's say summarize or simplify or analyze the data where it is being used and then you can limit the traffic to a more central site to only the essential of it is clear that we've the current growth of data there won't be enough capacity to have all the data going directly to the central part and this is what the edge is about making sure we have intermediary of points of processing yeah absolutely so Nikki you talked about OpenStack and OpenShift of course there's open source project with with OpenStack openshift the big piece of that is is kubernetes when it comes to edge are there other open source project the parts of the foundations out there that we should highlight when looking at these that's Luke oh there is a tremendous amount of projects that are pertaining to the edge read ad carry's many of these projects in its portfolio the middleware components for example Quercus or our amq mechanism caki are very important components we've got storage solutions that are super important also when you're talking about storing or handling data you've got in our management portfolio two very key tool one called ansible that allows to configure remotely confidence that that is super handy when you need to reconfigure firewall in Mass you've got another tool that he's a central piece of our strategy which is called a CM read at forgot the name of the product now we are using the acronym all the time which is our central management mechanism just delivered to us through IBM so this is a portfolio wide we are making and I forgot the important one which is real that Enterprise Linux which is delivering very soon a new version that is going to enable easier management at the edge yeah well of course we know that well is you know the core foundational piece with most of the solution in a portfolio that's really interesting how you laid that out though as you know some people on the outside look and say ok Red Hat's got a really big portfolio how does it all fit together you just discussed that all of these pieces become really important when when they come together for the edge so maybe uh you know one of the things when we get together summit of course we get to hear a lot from your your your customer so any customers you can talk about that might be a good proof point for these solutions that you're talking about today so right now most of the proof points are in the telco industry because these are the first one that have made the investment in it and when we are talking about their eyes and we are talking about a very large investment that is reinforced in their strategy we've got customers in telco all over the world that are starting to use our products to deploy their 5g networks and we've got lots of customer starting to work with us on creating their tragedy for in other vertical particularly in the industrial and manufacturing sector which is our necks and ever after telco yet yeah well absolutely Verizon a customer I'm well familiar with when it comes to what they've been used with Red Hat I'd interviewed them it opens back few years back when they talked about that those nmv type solutions you brought a manufacturing so that brings up one of the concerns when you talk about edge or specifically about IOT environment when we did some original research looking at the industrial Internet the boundaries between the IT group and the OT which heavily lives lives in manufacturing wouldn't they did they don't necessarily talk or work together so Houser had had to help to make sure that customers you know go through these transitions Plus through those silos and can take advantage of these sorts of new technologies well obviously you you have to look at a problem in entirety you've got to look at the change management aspect and for this you need to understand how people interact together if you intend on modifying the way they work together you also need to ensure that the requirements of one are not impeding the yeah other the man an environment of a manufacturer is really important especially when we are talking about dealing with IOT sensors which have very limited security capability so you need to add in the appropriate security layers to make what is not secure secure and if you don't do that you're going to introduce a friction and you also need to ensure that you can delegate administration of the component to the right people you cannot say Oh from now on all of what you used to be controlling on a manufacturing floor is now controlled centrally and you have to go through this form in order to have anything modified so having the flexibility in our tooling to enable respect of the existing organization and handle a change management the appropriate way is our way to answer this problem right Nick last thing for you obviously this is a maturing space lots of age happening so gives a little bit of a look forward as to what users should be affecting and you know what what what pieces will the industry and RedHat be working on that bring full value out of the edge and find a solution so as always any such changes are driven by the application and what we are seeing is in terms of application a very large predominance of requirements for AI ml and data processing capability so reinforcing all the components around this environment is one of our key addition and that we are making as we speak you can see Chris keynote which is going to demonstrate how we are enabling a manufacturer to process the signal sent from multiple sensors through an AI and during early failure detection you can also expect us to enable more and more complex use case in terms of footprint right now we can do very small data center that are residing on three machine tomorrow we'll be able to handle remote worker nodes that are on a single machine further along we'll be able to deal with disconnected node a single machine acting as a cluster all these are elements that are going to allow us to go further and further in the complication of the use cases it's not the same thing when you have to connect a manufacturer that is on solid grounds with fiber access or when you have to connect the Norway for example or a vote and talk about that too Nick thank you so much for all the updates no there's some really good breakouts I'm sure there's lots on the Red Hat website find out more about edge in five B's the Nick bark set thanks so much for joining us thank you very much for having me all right back with lots more covered from Red Hat summit 2020 I'm stoom in a man and thanks though we for watching the queue [Music]
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Cisco Live Barcelona 2020 | Thursday January 30, 2020
[Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] you [Music] [Applause] [Music] live from Barcelona Spain it's the cube covering Cisco live 2020 rot to you by Cisco and its ecosystem partners come back this is the cubes coverage of Cisco live 2020 here in Barcelona doing about three and a half days of wall-to-wall coverage here I'm Stu minim and my co-host for this segment is Dave Volante John furs also here scouring the floor and really happy to welcome to the program to first-time guests I believe so Ron Daris is the product manager of product marketing for cloud computing with Cisco and sitting to his left is Matt Ferguson who's director of product development also with the Cisco cloud group Dave and I are from Boston Matt is also from the Boston area yes and Costas is coming over from London so thanks so much for joining us thanks IBPS all right so obviously cloud computing something we've been talking about many years we've really found fascinating the relationship Cisco's had with its customers as well as through the partner ecosystem had many good discussions about some of the announcements this week maybe start a little bit you know Cisco's software journey and you know positioning in this cloud space right now yes oh so it's a it's a really interesting dynamic when we start transitioning to multi cloud and we actually deal with cloud and compute coming together and we've had whether you're looking at the infrastructure ops organization or whether you're looking at the apps operations or whether you're looking at you know your dev environment your security operations each organization has to deal with their angle at which they view you know multi cloud or they view how they actually operate within those the cloud computing context and so whether you're on the infrastructure side you're looking at compute you're looking at storage you're looking at resources if you're an app operator you're looking at performance you're looking at visibility assurance if you are in the security operations you're looking at maybe governance you're looking at policy and then when you're a developer you really sort of thinking about CI CD you're talking about agility and there's very few organizations like Cisco that actually is looking at from a product perspective all those various angles of multi-cloud yeah definitely a lot of piece of cost us maybe up level it for us a little bit there's there's so many pieces you know we talked for so long you know you don't talk to any company that doesn't have a cloud strategy doesn't mean that it's not going to change over time and it means every company's got at home positioning but talk about the relationship cisco has with its customer and really the advisory position that you want to have with them it's actually a very relevant question to what to what Matt is talking about because we talk a lot about multi cloud as a trend and hybrid clouds and this kind of relationship between the traditional view of looking at computing data centers and then expanding to different clouds you know public cloud providers have now amazing platform capabilities and if you think about it the the it goes back to what Matt said about IT ops and the development kind of efforts why is this happening really you know there's there's the study that we did with with an analyst and there was an amazing a shocking stat around how within the next three years organizations will have to support 50% more applications than they do now and we have been trying to test this stat our events that made customer meetings etc that is a lot of a lot of change for organizations so if you think about why are they use why do they need to basically what go and expand to those clouds is because they want to service IT Ops teams want ER servers with capabilities their developers faster right and this is where you have within the IT ops kind of theme organization you have the security kind of frame the compute frame the networking where you know Cisco has a traditional footprint how do you blend all this how do you bring all this together in a linear way to support individual unique application modernization efforts I think that's what are we hearing from customers in terms of the feedback and this is what influences our strategy to converts the different business units and engineering engineering efforts right couple years ago I have to admit I was kind of a multi cloud skeptic I always said I thought it was more of a symptom than actually a strategy a symptom of you know shadow IT and different workloads and so forth but now I'm kind of buying in because I think IT in particular has been brought in to clean up the crime scene I often say so I think it is becoming a strategy so if you could help us understand what you're hearing from customers in terms of their strategy toward the multi cloud and how Cisco that was mapping into that yeah so so when we talk to customers it comes back to the angle at which they're approaching the problem in like you said the shadow IT has been probably around for longer than anybody won't cares to admit because the people want to move faster organizations want to get their product out to market sooner and and so what what really is we're having conversations now about you know how do I get the visibility how do I get you know the policies and the governance so that I can actually understand either how much I'm spending in the cloud or whether I'm getting the actual performance that I'm looking for that I need the connectivity so I get the bandwidth and so these are the kinds of conversations that we have with customers is is is going I realize that this is going on now I actually have to now put some you know governance and controls around that is their products is their solutions is their you know they're looking to Cisco to help them through this journey because it is a journey because as much as we talk about cloud and you know companies that were born in the cloud cloud native there is a tremendous number of IT organizations that are just starting that journey that are just entering into this phase where they have to solve these problems yeah I agree and it's just starting the journey with a deliberate strategy as opposed to okay we got this this thing but if you think about the competitive landscape its kind of interesting and I want to try to understand where Cisco fits because again you you initially had companies that didn't know in a public cloud sort of pushing multi cloud and you'd say oh well okay so they have to do that but now you see anthos come out with Google you see Microsoft leaning in we think eventually AWS is going to lean in and then you say I'm kind of interested in working with someone whose cloud agnostic not trying to force now now Cisco a few years ago you didn't really think about Cisco as a player now so this goes right in the middle I have said often that Cisco's in a great position John Fourier as well to connect businesses and from a source of networking strength making a strong argument that we have the most cost-effective most secure highest performance network to connect clouds that seems to be a pretty fundamental strength of yours and does that essentially summarize your strategy and and how does that map into the actions that you're taking in terms of products and services that you're bringing to market I would say that I can I can I can take that ya know it's a chewy question for hours yeah so I I was thinking about a satellite in you mentioned this before and you're like okay that's you know the world is turning around completely because we we seem to talk about satellite e is something bad happening and now suddenly we completely forgot about it like let let free free up the developers gonna let them do whatever they want and basically that is what I think is happening out there in the market so all the solutions you mentioned in the go to market approaches and the architectures that the public cloud providers at least are offering out there certainly the big three have differences have their strengths and I think those strengths are closer to the developer environment basically you know if you're looking into something like a IML there's one provider that you go with if you're looking for a mobile development framework you're gonna go somewhere else if you're looking for a dr you're gonna go somewhere else maybe not a big cloud but your service provider that you've been dealing with all these all these times and you know that they have their accreditation that you're looking for so where does Cisco come in you know we're not a public cloud provider we offer products as a service from our data centers and our partners data centers but at the - at the way that the industry sees a cloud provider a public cloud like AWS a sure Google Oracle IBM etc we're not that we don't do that our mission is to enable organizations with software hardware products SAS products to be able to facilitate their connectivity security visibility observability and in doing business and in leveraging the best benefits from those clouds so we we kind of we kind of moved to a point where we flip around the question and the first question is who is your cloud provider what how many tell us the clouds you work with and we can give you the modular pieces you can put we can put together for you so there's so that you can make the best out of your plan it's been being able to do that across clouds we're in an environment that is consistent with policies that are consistent that represent the edicts of your organization no matter where your data lives that's sort of the the vision in the way this is translated into products into Cisco's product you naturally think about Cisco as the connectivity provider networking that's that's really sort of our you know go to in what we're also when we have a significant computing portfolio as well so connectivity is not only the connectivity of the actual wire between geographies point A to point B in the natural routing and switching world there's connectivity between applications between cute and so this week you know the announcements were significant in that space when you talk about the compute and the cloud coming together on a single platform that gives you not only the ability to look at your applications from a experience journey map so you can actually know where the problems might occur in the application domain you can actually then go that next level down into the infrastructure level and you can say okay maybe I'm running out of some sort of resource whether it's compute resource whether it's memory whether it's on your private cloud that you have enabled on Prem or whether it's in the public cloud that you have that application residing and then why candidly you have the actual hardware itself so inter-site it has an ability to control that entire stack so you can have that visibility all the way down to the hardware layer I'm glad you brought up some of the applications wonderful we can you know stay there for a moment and talk about some of the changing patterns for customers a lot of talk in the industry about cloud native often it gets conflated with you know microservices containerization and lots of the individual pieces there but you know one of our favorite things that been talked about this week is the software that really sits at the application layer and how that connects down through some of the infrastructure pieces so help us understand what you're hearing from customers and and where how you're helping them through this transition to constants as you were saying absolutely there's going to be lots of new applications more applications and they still have the the old stuff that they need to continue to manage because we know an IT nothing ever goes away that's that's definitely true I was I was thinking you know there's there's a vacuum at the moment and and there's things that Cisco is doing from from technology leadership perspective to fill that gap between the application what do you see when it comes to monitoring making sure your services are observable and how does that fit within the infrastructure stack you know everything upwards network the network layer base again that is changing dramatically some of the things that Matt touched upon with regards to you know being able to connect the the networking the security in the infrastructure the computer infrastructure that the developers basically are deploying on top so there's a lot of there's a lot of things on containerization there's a lot of in fact it's you know one part of the of the self-injure side of the stack that you mentioned and one of the big announcements you know that there's a lot of discussion in the industry around ok how does that abstract further the conversation on networking for example because that now what we're seeing is that you have huge monoliths enterprise applications that are being carved down into micro services ok they you know there's a big misunderstanding around what is cloud native is it related to containers different kind of things right but containers are naturally the infrastructure de facto currency for developers to deploy because of many many benefits but then what happens you know between the kubernetes layer which seems to be the standard and the application who's gonna be managing services talking to each other that are multiplying you know things like service mesh network service mess how is the network evolving to be able to create this immutable infrastructure for developers to deploy applications so there's so many things happening at the same time where cisco has actually a lot of taking a lot of the front seat this is where it gets really interesting you know it's sort of hard to squint through because you mentioned kubernetes is the de facto standard but it's a de-facto standard that's open everybody's playing with but historically this industry has been defined by you know a leader who comes out with a de facto standard kubernetes not a company right it's an open standard and so but there's so many other components than containers and so history would suggest that there's going to be another de facto standard or multiple standards that emerge and your point earlier is you you got to have the full stack you can't just do networking you can't just do certain few so you guys are attacking that whole pie so how do you think this thing will evolve I mean you guys are obviously intend to put out as Casta as wide a net as possible capture not only your existing install base but attractive attract others and you're going aggressively at it as are as are others how do you see it shaking out deep do you see you know four or five pockets do you see you know one leader emerging I mean customers would love all you guys to get together come up with standards that's not going to happen so we're it's jump ball right now well yeah and you think about you know to your point regarding kubernetes is not a company right it is it is a community driven I mean it was open source by a large company but it's but it's community driven now and that's the pace at which open source is sort of evolving there is so much coming at IT organizations from a new paradigm a new software something that's you know the new the shiny object that sort of everybody sort of has to jump on to and sort of say that is the way we're going to function so IT organizations have to struggle with this influx of just every coming at them and every angle and I think what's starting to happen is the management and the you know that stack who controls that or who is helping IT organizations to manage it for them so really what we're trying to say is there's elements that you have to put together that have to function and kubernetes is just one example docker the operating system that associated with it that runs all that stuff then you have the application that goes rides IDEs on top of it so now what we have to have is things like what we just announced this week HX ap the application platform for HX so you have the compute cluster but then you have the on top of that that's managed by an organization that's looking at the security that's looking at the the actual making opinions about what should go in the stock and managing that for you so you don't have to deal with that because you can just focus on the application development yeah I mean Cisco's in a strong position to do there's no question about it and to me it comes down to execution if you guys execute and deliver on the the products and services that you say you know your nouns for instance this week and previously and you continue on a roadmap you're gonna get a fair share of this marketplace I think there's no question so last topic before we let you go is love your viewpoint on customers what's separating kind of leaders from you know the followers in this space you know there's so much data out there you know I'm a big fan of the state of DevOps report yeah focus you know separate you know some but not the not here's the technology or the piece but the organizational and you know dynamics that you should do so it sounds like Matt you you like that that report also love them what are you hearing from customers how do you help guide them towards becoming leaders in the cloud space yeah the state of DevOps report was fascinating and I mean they've been doing that for what a number of years yeah exactly and really what it's sort of highlighting is two main factors that I think that are in this revolution or this this this paradigm shift or journey we're going through there's the technology side for sure and so that's getting more complex you have micro services you have application explosion you have a lot of things that are occurring just in technology that you're trying to keep up but then it's really about the human aspect that human elements the people about it and that's really I think what separates you know the the elites that are really sort of you know just charging forward in the head because they've been able to sort of break down the silos because really what you're talking about in cloud native DevOps is how you take the journey of that experience of the service from end to end from the development all the way to production and how do you actually sort of not have organizations that look at their domain their data set their operations and then have to translate that or have to sort of you know have another conversation with another organization that it doesn't look at that that has no experience of that so that is what we're talking about that end-to-end view is that in addition to all the things we've been talking about I think Security's a linchpin here now you guys are executing on security you got a big portfolio and you've seen a lot of M&A and a lot of companies now trying to get in and it's gonna be interesting to see how that plays out but that's going to be a key because organizations are going to start there from a strategy standpoint and then build out yeah absolutely if you follow the DevOps methodology its security gets baked in along the way so that you're not having to sit on after do anything Custis give you the final word I was just as follow-up with regard what what Mark was saying there's so many there's what's happening out there is this just democracy around standards which is driven by communities and we will love that in fact cisco is involved in many open-source community projects but you asked about customers and and just right before you were asking about you know who's gonna be the winner there's so many use cases there's so much depth in terms of you know what customers want to do with on top of kubernetes you know take AI ml for example something that we have we have some some offering the services around there's the customer that wants to do AML there their containers that their infrastructure will be so much different to someone else's doing something just hosting yeah and there's always gonna be a SAS provider that is niche servicing some oil and gas company you know which means that the company of that industry will go and follow that instead of just going to a public law provider that is more organized if there's a does that make sense yeah yeah this there's relationships that exist the archer is gonna get blown away that add value today and they're not gonna just throw them out so exactly right well thank you so much for helping us understand the updates where your customers are driving super exciting space look forward to keeping an eye on it thank you thank you so much all right there's still lots more coming here from Cisco live 20/20 in Barcelona people are standing watching all the developer events lots of going on the floor and we still have more so thank you for watching the cute [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] you [Music] live from Barcelona Spain it's the cube covering Cisco live 2020 rot to you by Cisco and its ecosystem partners welcome back over 17,000 in attendance here for Cisco live 2020 in Barcelona ops to Minh and my co-host is Dave Volante and to help us to dig into of course one of the most important topic of the day of course that security we're thrilled to have back a distinguished engineer Francisco one of our cube alumni TK Kia Nene TK thanks so much for joining us ideal man good good all right so TK it's 2020 it's a new decade we know the bad actors are still out there they're there the the question always is you know it used to be you know how do you keep ahead of them then I've here Dave say many times well you know it's not you know when it's it's not if it's when you know you probably already have been okay you know compromised before so it gives latest so you know what you're seeing out there what you're talking to customers about in this important space yeah it's uh it's kind of an innovation spiral you know we we innovate we make it harder for them and then they innovate they make it harder for us right and round and round we go that's been going on for for many years I think I think the most significant changes that have happened recently have to deal with not essentially their objectives but how they go about their objectives and Defenders topologies have changed greatly instead of just your standard enterprise you now have you know hybrid multi cloud and all these new technologies so while while all that innovation happens you know they get a little clever and they find weaknesses and round and round we go so we talked a lot about the sort of changing profile of the the threat actors going from hacktivists took criminals now is a huge business and nation-states even what's that profile look like today and how has that changed over the last decade or so you know that's pretty much stayed the same bad guys are bad guys at some point in time you know just how how they go about their business their techniques they're having to like I said innovate around you know we make it harder for them they you know on Monday we're safe on Tuesday we're not you know and then on Wednesday it switches again so so it talked about kind of this multi-cloud environment when we talk to customers it's like well I want the developer to be able to build their application and not really have to think too much underneath it that that has to have some unique challenges we know security we knew long ago well I just go to the cloud it doesn't mean they take care of it some things are there some things they're gonna remind you now you need to make sure you set certain things otherwise you could be there but how do we make sure that Security's baked in everywhere and is up as a practice that everybody's doing well I mean again some of the practices hold true no matter what the environment I think the big thing was cognitive is in back in the day when when you looked at an old legacy data center you were part sort of administrator in your part detective and most people don't even know what's running on there that's not true in cloud native environments some some llamó file some some declaration it's it's just exactly what productions should look like right and then the machines instantiate production so you're doing things that machine scale forces the human scale people to be explicit and and for me I mean that's that's a breath of fresh air because once you're explicit then you take the mystery out of what you're protecting how about in terms of how you detect threats right phishing for credentials has become a huge deal but not just you know kicking down the door or smashing a window using your your own credentials to get inside of your network so how is that affected the way in which you detect yeah it's it's a big deal you know a lot of a lot of great technology has a dual use and what I mean by that is network cryptology you know that that whole crypto on the network has made us safer for us to compute over insecure networks and unfortunately it works just as well for the bad guys so you know all of their malicious activity is now private to so it you know for us we just have to invent new ways of detecting direct inspection for instance I think it's a thing of the past I mean we just can't depend on it anymore we have to have tools of inference and not only that but it's it's gave rise in a lot of innovation on behavioral science and as you say you know it's it's not that the attacker is breaking into your network anymore they're logging in ok what do you do then right Alice Alice's account it's not gonna set off the triggers so you have to say you know when did Alice start to behave differently you know she's working in accounting why is she playing around with the source code repository that's that's a different thing right yes automation is such a big trend you know how do we make sure that automation doesn't leave us more vulnerable that's rarity because we need to be able automate we've gone beyond human scale for most of these configurations that's exactly right and and how do how do we I always say just with security automation in particular just because you can automate something doesn't mean you should and you really have to go back and have practices you know you could argue that that this thing is just a you know machine scale automation you could do math on a legal pad or you can use a computer to do it right what so apply that to production if you mechanized something like order entry or whatever you're you're you're automating part of your business use threat modeling you use the standard threaten modeling like you would your code the network is code now right and the storage is code and everything is code so you know just automate your testing do your threat modeling do all that stuff please do not automate for your attacker matrix is here I want to go back to the Alice problem because you're talking about before you have to use inference so Alice's is in the network and you're observing her moves every day and then okay something anomalous occurs maybe she's doing something that normally she wouldn't do so you've got to have her profile in her actions sort of observed documented stored the data has got to be there and at the same time you want to make sure it's always that balance of putting handcuffs on people you know versus allowing them to do their job and be productive at the same time as well you don't want to let the bad guys know that you know that alice is doing something that she didn't be doing is actually not Alice so all that complexity how are you dealing with it and what's the data model look like doing it machines help let's say that machines can help us you know you and I we have only so many sense organs and the cognitive brain can only store so many so much state machines really help us extend that and so you know looking at not three dimensions of change but 7000 dimensions have changed right something in the machine is going to say there's an outlier here that's interesting and you can get another machine to say that's that's interesting maybe I should focus on that and you build these analytical pipelines so that at the end of it you know they may argue with each other all the way to the end but at the end you have a very high fidelity indicator that might be at the protocol level it might be at the behavioral level it might be seven days back or thirty days back all these temporal and spatial dimensions it's really cheap to do it with a machine yeah and if we could stay on that for a second so it try to understand I know that's a high-level example but is it best practice to have the Machine take action or is it is it an augmentation and I know it depends on the use case but but how is that sort of playing out again you have to do all of this safely okay a lot of things that machines do don't return back to human scale stuff that returns back to human scale that humans understand that is as useful so for instance if machines you know find out all these types of in assertions even in medical you know right now if if you've got so much telemetry going into the medical field see the machine tells you you have three weeks to live I mean you better explain what the heck you know how you came about that assertion it's the same with security you know if I'm gonna say look we're gonna quarantine your machine or we're gonna readjust machine it's not I'm not like picking movies for you or the next song you might listen to this is high stakes and so when you do things like that your analytics needs to have what is called entailment you have to explain what it is how you got to that assertion that's become incredibly important in how we measure our effectiveness in in doing analytics that's interesting because because you're using a lot of machine intelligence to do this and in a lot of AI is blackbox you're saying you cannot endure that blackbox problem in security yeah that black boxes is is very dangerous you know I you know personally I feel that you know things that should be open sourced this type of technology it's so advanced that the developer needs to understand that the tester needs to understand that certainly the customer needs to understand it you need to publish papers and be very very transparent with this domain because if it is in fact you know black box and it's given the authority to automate something like you know shut down the power or do things like that that's when things really start to get dangerous so good TK what wondered you know give us the latest on stealthWatch there you know Cisco's positioning when it when it comes to everything we've been talking about here you know stealthWatch again is it's been in market for quite some time it's actually been in market since 2001 and when I when I look back and see how much has changed you know how we've had to keep up with the market and again it's not just the algorithms rewrite for detection it's the environments have changed right but when did when did multi-cloud happen so so operating again cusp it's not that stealthWatch wants to go their customers are going there and they want the stealthWatch function across their digital business and so you know we've had to make advancements on the changing topology we've had to make advancements because of things like dark data you know the the network's opaque now right we have to have a lot of inference so we've just you know kept up and stayed ahead of it you know we've been spending a lot of time talking to developer communities and there's a lot of open-source tooling out there that that's helping enable developers specifically in security space you were talking about open-source earlier how does what you've been doing the self watch intersect with that yeah that's always interesting too because there's been sort of a shift in let's call them the cool kids right the cool kids they want everything is code right so it's not about what's on glass or you know a single pane of glass anymore it's it's what stealth watches code right what's your router as code look at dev net right yeah yeah I mean definite is basically Cisco as code and it's beautiful because that is infrastructure as code I mean that is the future and so all the products not just stealthWatch have beautiful api's and that's that's really exciting I've been saying for a while now it's do you I think you agree is that that is a big differentiator for Cisco I think you you're one of the few if not the only large established player and the enterprise that has figured out that sort of infrastructure is code play others have tried and are sort of getting there but you know start/stop you use a term that really cool is like living off the land you know bear bear grylls like the guy who lives down so bad so and and and threat actors are doing that now they're using your own installed software and tooling to hack you and and steal from you how were you dealing with that problem yeah it's a tough one and like I said you know much respect the the adversary is talented and they're patient they're well funded okay that's that's where it starts and so you know why why bring why bring an interpreter to a host when there's already one there right why right all this complicated software distribution when I can just use yours and so that's that's where the the play the game starts and and the most advanced threats aren't leaving footprints because the footprints are already there you know they'll get on a machine and behaviorally they'll check the cache to see what's hot and what's hot in the cache means that behaviorally it's a path they can go they're not cutting a new trail most of the time right so living off the land is not only the tools that they're using the automation your automation they're using against you but it's also behavioral and so that that makes it you know it makes it harder it's it impossible no can we make it harder for them yes so yeah no I'm having fun and I've been doing this for over twenty five years every week it's something new well it's a hard problem you're attacking and you know Robert Herjavec who came on the cube sort of opened my eyes and you think about what are we securing we're securing everything I mean a critical infrastructure were essentially exerted securing the entire global economy and he said something that really struck me it's an 86 trillion dollar economy we spend point zero one four percent on securing that economy and it's nothing now of course he's an entrepreneur and he's pimping for his is his business but it's true we are barely scratching the surface of this problem yeah I'm and it's changing I mean it's changing it could it be better yes it is changing his board awareness you know twenty years ago then right me to a dinner party they you know what does your husband do I'd say you know cyber security or something they'd roll their eyes and change the subject now they asked me the same question so oh you know my computer's running really slow right these are not this is everyone I'm worried about a life hack yeah how do I protect myself or what about these coming off the bank I mean that's those guys a dinner table cover every party so now now you know I just make something up I don't do cybersecurity I just you know a tort or a jipner's you've been to this business forever I can't remember have I ever asked you the superhero question what is that your favorite superhero that's a tough one there's all the security guys I know they like it's always dreamed about saving the world [Laughter] you're my superhero man I love what you do I think you've a great asset for Cisco and Cisco's customers really thanks TK give us a final word if people want to you know find out more about about what Cisco's doing read more of what you're working on but what's some of the best resource I have to go do you know just drop by the web pages I mean everything's published out that like I said even even for the super nerdy you know we published all our our laurs security analytics papers I think we're over 50 papers published in the last 12 years TK thank you so much always a pleasure to catch alright yeah and a travels thank you so much for de Villante I'm Stu Mittleman John furrier is also in the house we will be back with lots more coverage here from Cisco live 20/20 in Barcelona thanks for watching the keys [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] live from Barcelona Spain it's the cube covering Cisco live 2020s brought to you by Cisco and its ecosystem partners hello and welcome back to the cubes live coverage it's our fourth day of four days of coverage here in Barcelona Spain for Cisco live 2020 I'm John Faria my co-host to many men to great guests here in the dev net studio where the cube is sitting all week long been packed with action mindy Whaley senior director developer experiences but dev net and partner a senior director welcome back to this cube good to see you guys glad to be here so we've had a lot of history with you guys what from day one yes watching def net from an idea of hey we should develop earthing you also have definite create yes separate more developer focused definite is Cisco's developer environment we've been here from the beginning what a progression congratulations on the success thank you thank you so much it's great to be here in Barcelona with everybody here you know learning in the workshops and we just love these times to connect with our community at Cisco live and it definitely ate what you mentioned which is coming up in March so it's right around the corner def net zone which we're in it's been really robust spins it's been the top of the show every year and it gets bigger and the sessions are packed because people are learning developers new developers as well as Cisco engineers who were certified coming in getting new skills as the modern cloud hybrid environments are new skills is a technology shift yeah exactly and what we have in the definite zone are different ways that the engineers and developers can engage with that technology shift so we have demos around IOT and security and showing how you know to prevent threats from attacking the Industrial routers and things like that we have coding workshops from you know beginning intro to Python intro to get all the way up through advanced like kubernetes topics and things like that so people can really dive in with what they're looking for and this year we're really excited because we have the new definite certifications with those exams coming out right around the corner in February so a lot of people are here saying I'm ready to skill up for those exams I'm starting to dive into this topic well Susie we was on she's the chief of deaf net among other things and she said there's gonna be a definite 500 the first 500 certifications of deaf net are gonna be kind of like the Hall of Fame or you know the inaugural or founder certifications so can you explain what this it means it's not a definite certification badge it's a series of write different sir can you deeper in then yeah just like we have our you know existing network certifications which are so respected and loved around the world people get CCIE tattoos and things just like there's an associate and professional and expert level on the networking truck there's now a definite associate a definite professional and coming soon definite expert and then there's also specialist badges which help you add specific skills like data center automation IOT WebEx so it's a whole new set of certifications that are more focused on the software so there are about 80 80 % software skills 20 percent knowledge of networking and then how you really connect up and down the stock so these are new certifications not replacing anything all the same stuff they're new they're part of the same program they have the same rigor the same kind of tests they actually have ways to enter weave with the existing networking certifications because we want people to do both skill paths right to build this new IT team of the future and so it's a completely new set of exams the exams are gonna be available to take February 24th and you can start signing up now so with the definite 500 you know that's gonna be a special recognition for the first 500 people who get dead note certifications it'll be a lifetime achievement they'll always be in the definite 500 right and I've had people coming up and telling me you know I'm signed up for the first day I'm taking my exams on the first day I'm trying to get into them you and I only always want to be on the lift so I think we might be on them and what's really great is with the certifications we've heard from people in the zone that they've been coming and taking classes and learning these skills but they didn't have a specific way to map that to their career path to get rewarded at work you know to have that sort of progression and so with the certifications they really will have that and it's also really important for our partners and par is doing a lot of work with certifications and partners yeah definitely that would love to hear a little bit we've interviewed on the cube over the years some of the definite partners from a technology standpoint of course the the channels ecosystem hugely important to Cisco's business gives the update as to you know definite partnering as well as what will these certifications mean to both the technology and go to market partners yeah the wonderful thing about this is it really demonstrates Cisco's embracement of software and making sure that we're providing that common language for software developers and networkers to bring the two together and what we've found is that our partners are at different levels of maturity along that progression of program ability and this new definite specialization which is anchored in the individuals that are now certified at that partner allow them to demonstrate from a go-to-market standpoint from a recognition standpoint that as a practice they have these skills and look at the end of the day it's all about delivering what our customers need and our customers are asking us for significant help in automation digital transformation they're trying to drive new business outcomes and this this will provide that recognition on on who to partner with in the market it's so important I remember when Cisco helped a lot of the partner ecosystem build data center practices went from the silos and now embracing you've got the hardware the software we're talking multi cloud it's the practice that is needed today going forward to help customers with where they're going it really is and and another benefit that we're finding and talking to our partners is we're packaging this up and rolling it out is not only will it help them from a recognition standpoint from a practice standpoint and from a competitive differentiation standpoint but it'll also help them attract challenge I mean it's no secret there is a talent shortage right now if you talk to any CEO that's top of mind and how these partners are able to attract these new skills and attract smart people smart people like working on smart things right and so this has really been a big traction point for them as well it's also giving ways to really specifically train for new job roles so some of the ways that you can combine the new definite certifications with the network engineering certifications we've looked at it and said you know there's there's a role of Network automation developer that's a new role everyone we ask in one of our sessions who needs that person on their team so many customers partners raise their hands like we want the network Automation developer on our team and you can combine you know your CCNP Enterprise with a definite certification and build up the skills to be that Network automation developer certainly has been great buzz I got to get your guys thoughts because certainly it's for careers and you guys are betting on the the people and the people are betting on Cisco mm-hmm yes this is what's going on submit surety of Devin it almost it's like a pinch me moment for you guys because you continue to grow I got to ask you what are some of the cool things that you're showing here as you mature you still have the start here session which is intro to Python and other things pretty elementary and then there's more advanced things what are some of the new things that's going on yeah that you could share so some of the new things we've got going on and one of my favorites is the IOT insecurity demonstration there's a an industrial robot arm that's picking and placing things and you can see how it's connected to the network and then something goes wrong with that robot alarm and then you can actually show how you can use the software and security tools to see was there code trying to access you know something that that robot was it was using it's getting in the way of it working so you could detect threats and move forward on that we also have a whole automation journey that starts from modeling your network to testing to how you would deploy automation to a deep dive on telemetry and then ends with multi domain automation so really helping engineers like look at that whole progression that's been that's been really popular Park talked about the specialization which ones are more popular or entry-level which ones are people coming into getting certified first network engineering automation first or what's the yeah so we're so the program is going to roll out with three different levels one is a specialized level the second is an advanced level and then we'll look to that third level again they're anchored in the in the individual certs and so as we look for that entry level it's really all about automation right I mean some things you take for granted but you still need these new skills to be able to automate and scale and have repeatable scalable benefits from that this the second tier will be more cross-domain and that's where we're really thinking that an additional skill set is needed to deliver dashboard experience compliance experiences and then that next level again we'll anchor towards the expert level that's coming out but one thing I want to point out is in addition to just having the certified people on staff they also have to demonstrate that they have a practice around it so it's not just enough to say I've passed an exam as we work with them to roll out the practice and they earn the badge they're demonstrating that they have the full methodology in place so that it really there's a lot behind it that means we can't be in the 500 list then even if a 500 list I don't know that the cube would end up being specialized its advertising no seriously all fun it's all fun it's Cisco live in Europe is there a difference between European and USD seeing any differences in geographic talent you know in the first couple years we did it I think there was a bigger difference it felt like there were different topics that were very popular in the US slightly different in Europe last year and this year I feel like they have converged it's it's the same focus on DevOps automation security as a huge focus in both places and it also feels like the the interest and level of the people attending has also converged it's really similar congratulations been fun to watch the rise and success of Devon it continues to be strong how see in the hub here and the definite zone behind us pact sessions yes what's the biggest surprise for you guys in terms of things that you didn't expect or some of the success what's what's jumped out yeah I think you know one of the points that I want to make sure we also cover and it has been an added benefit we're hoping it would happen we just didn't realize it would happen this soon we're attracting new companies new partners so the specialization won't just be available for our traditional bars this is also available for our non resale and we are finding different companies accessing definite resources and learning these skills so that's been a really great benefit of Deb net overall definitely my favorite surprises are when I show up at the community events and I hear from someone I met last year what the what they went back and did and the change that they drove and they come in their company and I think we're seeing those across the board of people who start a grassroots movement take back some new ideas really create change and then they come back and we get to hear about that from them those are my favorite surprises and I tell you we've known for years how important the developer is but I think the timing on this has been perfect because it is no longer just oh the developer has some tools that they like in the corner the developer connected to the business and driving things forward exactly so perfect timing congratulations on this certification their thing that's been great is that our at Cisco itself we now have API is across the whole portfolio and up and down the stock so that's been a wonderful thing to see come together because it opens up possibilities for all these developers so Cisco's API first company we are building it guys everywhere we can and and that the community is is taking them and finding creative things to build it's been fun to watch you guys change Cisco but also impact customers has been great to watch far many thanks for coming up yeah games live coverage here in Barcelona for Cisco live 20/20 I'm John Ford Dave Dave Alon face to many men we right back with more after this short break [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] you live from Barcelona Spain it's the cube covering Cisco live 2020 brought to you by Cisco and its ecosystem partners hello and welcome back to the cubes live coverage here at Cisco live 20/20 and partial into Spain I'm John first evening men cube coverage we've got a lot of stuff going on with Cisco multi-cloud and cloud technologies of clarification of Cisco's happening in real time is happening right now cloud is here here to stay we got two great guests to unpack what's going on in cloud native and networking and applications as the modern infrastructure and software evolves we got eugene kim global product marketing and compute storage at cisco global part of marketing manager and fabio corey senior director cloud solutions marketing guys great comeback great thanks for coming back appreciate it thanks very much great to see a lot of guys so probably we've had multiple conversations and usually even out from the sales force given kind of the that the discussion and the motivation cloud is big it's here it's here to stay it's changing Cisco API first we hear and all the products it's changing everything what's the story now what's going on I would say you know the reason why we're so excited about the launch here in Barcelona it's because this time it's all about the application experience I mean the last two years we've been announcing some really exciting stuff in the cloud space right think about all the announcements with the AWS the Google's the Azure so the world but this time it really boils down to making sure that is incredibly hyper distributed world well there is an application explosion ultimately we will help for the right operations tools and infrastructure management tools to ensure that the right application experience will be guaranteed for the end customer and that's incredibly important because at the end what really really matters is that you will ensure the best possible digital experience to your customer otherwise ultimately nothing is gonna work and of course you're going to lose your brand and your customers one of the main stories that we're covering is the transformation of the industry also Cisco and one of the highlights to me was the opening keynote you had app dynamics first not networking normally it's like what's under the hood the routers and the gear no it was about the applications this is the story we're seeing it's kind of a quiet unveiling it's not yet a launch but it's evolving very quickly can you share what's going on behind this all this absolutely it's exactly along the lines of what I was saying a second ago in the end that the reason why we're driving the announcement if you want from the application experience side of the house is because without dynamics we already have a very very powerful application performance measurement tool which it's evolving extremely rapidly first of all after Amex can correlate not just the application performance to some technology kpi's but to true actual business KPIs so AB dynamics can give you for instance the real-time visibility of say a marketing funnel conversion rates transactions that you're having in your in your business operation now we're introducing an incredibly powerful new capability that takes the bar to a whole new level and that's the dynamics experience journey Maps what are those it's actually the ability of focusing not so much on front-ends and backends and databases performances but really focusing on what the user is seeing in front of his or her screen and so what really matters is capturing the journey that a given user of your application is is being and understanding whether the experience is the one that you want to deliver oh you have like a sudden drop of somewhere and you know why that is important because in the end we've been talking about is it a problem of the application performance user performance well it could be a badly designed page how do you know and so this is a very precious information is that were giving to application developers not just to the IT ops guys that is incredibly precious to get this in so you just brought up that journey so that's part of the news so just break down real quick one minute yeah what the news is yeah so we have three components the first one as you as you correctly pointed out is really introduction the application journey Maps right the experience journey Maps that's very very important the second is we are actually integrating after am it's with the inter-site action inter-site optimization manager the workload team is a workload promisor and so because there is a change of data between the two now you are in a position to immediately understand whether you have an application problem we have a workload problem or infrastructure problem which is ultimate what you really need to do as quickly as you can and thirdly we have introduced a new version of our hyper flex platform which is hyper-converged flat G flat for Cisco with a fully containerized version we tax free if you want as well there is a great platform for containerized application of parameter so you teen when I've been talking to customers last few years when they go through their transformational journey there's the modernization they need to do the patterns I've seen most successful is first you modernize the platform often HCI is you know and often for that it really simplifies the environment you know reduces the silos and has more of that operational model that looks closer to what the cloud experience is and then if I've got a good platform then I can modernize the applications on top of it but often those two have been a little bit disconnected it feels like the announcements now that they are coming together what are you seeing what are you hearing how is your solution set solving this issue yeah exactly I mean as we've been talking to our customers love them are going through different application modernisations and kubernetes and containers is extremely important to them and to build a container cloud on Prem is extremely one of their needs and so there's three distinctive requirements that they've kind of talked to us about a lot of it has to be able to it's got to be very simple very turnkey and a fully integrated ready to turn on the other one is something that's very agile right very DevOps friendly and the third being a very economic container cloud on Prem as far we mentioned high flex application platform takes our hyper-converged system and builds on top of it a integrated kubernetes platform to deliver a container as a service type capability and it provides a full stack fully supported element platform for our customers and the one of the best great aspects of is that's all managed from inside from the physical infrastructure to the hyper-converged layer to all the way to the container management so it's very exciting to have that full stack management and insight as well yeah it's great to you know John and I have been following this kubernetes wave you know since the early early days Fabio mentioned integrations with the Amazons and Google's the world because you know a few years ago you talked to customers and they're like oh well I'm just gonna build my own urbanity right back nobody ever said that is easy now just delivering at his service seems to be the way most people wanted so if I'm doing it on Amazon or Google they've got their manage service that I could do that or that they're through partners they're working with so explain what you're doing to make it simpler in the data center environment because I'm tram absolutely is a piece of that hybrid equation the customers need yes so essentially from the customer experience perspective as I mentioned it's very fairly turnkey right from the hyper flicks application platform we're taking our hyper grew software we're integrating a application virtualization layer on top of it Linux KVM based and then on top of that we're integrating the kubernetes stack on top as well and so in essence right it's a fully curated kubernetes stack right it has all the different elements from the networking from the storage elements and and providing that in a very turnkey way and as I mentioned the inner site management is really providing that simplicity that customers need for that management ok Fabio this the previous announcement you've made with the public clouds yeah this just ties into those hybrid environments that's exactly you know a few years ago people like oh is there gonna be a distribution that wins in kubernetes we don't think that's the answer but still I can't just move between kubernetes you know seamlessly yet but this is moving towards that direction so a lot of customers want to have a very simple implementation at the same time they want of course a multi cloud approach and I really care about you know marking the difference between you know multi-cloud hybrid cloud there's been a lot of confusion but if you think about it multi cloud is really rooted into the business need of harnessing innovation from whatever it comes from you know the different clouds PV different things and you know what they do today tomorrow it could even change so people want option maladie so they want a very simple implementation that's integrated with public cloud providers that simplifies their life in terms of networking security and application of workload management and we've been executing towards that goal to fundamentally simplify the operations of these pretty complex kind of hybrid environments I want you to nail that operations on ibrid that's where multi cloud comes in absolutely just a connection point absolutely you're not a shitty mice no isn't a shit so in order to fulfill your business like your I know business needs you then you have a hybrid problem and you want to really kind of have a consistent production rate environment between fins on Prem that you own and control versus things that you use and you want to control better now of course there are different school of thoughts but most of the customers who are speaking with really want to expand their governance and technology model right to the cloud as opposed to absorb in different ways of doing things from each and every clock I want to unpack a little bit of what you said earlier about the knowing where the problem is because a lot of times it's a point the finger at the other first and where's it's the application problem isn't a problem so I want to get into that but first I want to understand the hyper flex application platform Eugene if you could just share the main problem that you guys saw what did some of the pain points that customers had what problems does the AP solve yeah as I mentioned it's really the platform for our customers to modernize their applications on right and it addresses those things that they're looking for as far as the economics right really the ability to provide a full stack container experience without having to you know but you know bringing any third party hypervisor licenses as well as support cost so that's fully integrated there you have your integrated hyper-converged storage capability you have the cloud-based management and that's really developing you providing that developer DevOps simplicity from the data Julie that they're looking for internally as well as for their product production environments and then the other aspect is its simplicity to be able to manage all this right in the entire lifecycle management as well so it's the operational side of the whole yeah uncovers Papio on the application side where the problem is because this is where I'm a little bit skeptical you know normally rightfully so but I can see in a problem where it's like whose fault is it gasification is problem or the network I mean it runs into more serious workloads the banking app that's having trouble how do you know where it what the problem is and how do you solve that problem what what's going on for that specific issue absolutely and you know the name of the game here is breaking down this operational side right and I love what our app dynamics VP GM Danny winoker said you know it has this terminology beast DevOps which you know may sound like an interesting acrobatics but it's absolutely true the business has to be part of this operational kind of innovation because as you said you know developer edges you know drops their containers and their code to the IET ops team but you don't really know whether the problem a certain point is gonna be in the code or in how the application is actually deployed or maybe a server that doesn't have enough CPU so in the end it boils down to one very important thing you have to have visibility inside and take action and every layer of the stack I mean instrumentation absolutely there are players that only do it in their software overlay domain the problem is very often these kind of players assume that underneath links are fine and very often they're not so in the end this visibility inside inaction is the loop that everybody is going after these days to really get to the next if you want generational operation where you gotta have a constant feedback loop and making it more faster and faster because in the end you can only win in the marketplace right regardless of your IT ops if you're faster than your competitor well still still was questioning the GM of AppDynamics running observability and he's like no it's not to feature it's everywhere so he his comment was yeah but serve abilities don't really talk about it because it's big din do you agree with that absolutely it has to be at every layer of the stack and only if you have visibility inside an action through the entire stack from the software all the way to the infrastructure level that you can solve the problem otherwise the finger-pointing quote-unquote will continue and you will not be able to gain the speed that you need okay so the question on my mind I want to get both of you guys can weigh in on this is that you look at Cisco as a company you got a lot going on I mean a guy's huge customer base core routers - no applications there's a lot going on a lot of a lot of complexity you got IOT security Ramirez talked about that you got the WebEx rooms got totally popular it's kind of got a lot of glam to it having the WebEx kind of you know I guess what virtual presence was yeah telepresence kind of model and then you get cloud is there a mind share within the company around how cloud is baked into everything because you can't do IOT edge without having some sort of cloud operational things so there's stuff you're talking about is not just a division it's kind of gonna it's kind of threads everywhere across Cisco what's the what's the mind share right now within the Cisco teams and also customers around clarification well I would say it's it's a couple of dimension the first one is the cloud is one of the critical domains of this multi domain architecture that of course is the cornerstone of Cisco's technology strategy right if you think about it it's all about connecting users to applications wherever they are and not just the user the applications themselves like if you look at the latest stats from IDC 58% of workloads is heading to the public cloud and to the edge it's like the data center is literally exploding in many different directions so you have this highly distributed kind of fabric guess what sits in between all these applications and microservices is a secure network and that's exactly what we're executing upon now that's the first kind of consideration the second is if you look at the other silver line most of the Cisco technology innovation is also going a direction of absorbing cloud as a simplified way of managing all the components or the infrastructure you look at the IP flex ap is actually managed by inter site which is a SAS kind of component this journey started a long time ago with Cisco Meraki and then of course we have SAS properties like WebEx everything else is kind of absolutely migrants reporter we've been reporting eugen that from years ago we saw the movement where api's are starting to come in when you go back five years ago not a lot of the gear and stuff at Cisco had api's now you got api's building into all the new products that's right you see the software shift with you know you know intent-based networking to AppDynamics it's interesting it's you're seeing kind of this agile mindset this is some of you and I talk about all the time but agile now is the new model is it ready for customers I mean the normal Enterprise is still got the infrastructure and application it's separated okay how do I bring it together what are you guys seeing the customer base what's going on with with not that not the early adopters heavy-duty hardcore pioneers out there but you know the the general mainstream enterprise are they there yet have they had that moment of awakening yeah I mean I think they they are there because fundamentally it's all about that ensuring that application experience and you can only ensure that application experience right by having your application teams and your structure teams work together and that's what's exciting you mentioned the API is and what we've done there with AppDynamics integrating with inter-site workload optimizer as Fabio mentioned it's all about visibility inside action and what app dynamics is provides providing that business and end-user application performance experience visibility inner sites giving you know visibility on the underlining workload and the resources whether it's on Prem in your you know drive data center environment or in different type of cloud providers so you get that full stack visibility right from the application all the way down to the bottom and then inner side local optimizer is then also optimizing the resources to proactively ensure that application experience so before you know if we talk about someone at a checkout and they're about to have abandonment because the functions not working we're able to proactively prevent that and take a look at all that so you know in the end I think it's all about ensuring that application experience and what we're providing with app dynamics is for the application team is kind of that horizontal visibility of how that application is performing and at the same time if there's an issue the infrastructure team could see exactly within the workload topology where the issue is and insert' aeneas lee whether it be manual intervention or even automatically there's or a ops capability go ahead and provide that action so the action could be you know scaling out the VMS it's on-prem or looking at a new different type of ec2 template in the cloud that's what's very exciting about this it's really the application experience is now driving and optimizing infrastructure in real time and let me flip your question like do you even have a choice John when you think about in the next two years 50% more applications if you're a large enterprise you have 5 to 7,000 apps you have another to 3,000 applications just coming into into the the frame and then 50% of the existing ones that are gonna be refactor lifted and shifted or replace or retired by SAS application it's just like it's tsunami that's that's coming on you and oh by the way because of again the micro service is kind of affect the number of dependencies between all these applications is growing incredibly rapidly like last year we were eight average interdependencies for applications now we are 20 so imaging imaging what happens as as you are literally flooded with the way the scanner really you have to ensure that your application infrastructure fundamentally will get tied up as quickly as you can still and I have been toilet for at least five years now if not longer the networking has been the key kind of last changeover - clarification and I would agree with you guys I think I've asked the question because I wanted to get your perspective but think about it it's 13 years since the iPhone so mobile has shown people that a mobile app can change business but now if you look at the pressure the network's bringing the pressure on the network or the pressure for the network to be better than programmable is the rise of video and data I mean so you got mobile check now you've got video I mean more people doing video now than ever before videos of consumer oil as streaming you got data these two things absolutely forced yeah the customers to deal with it but what really tipped the the balance John is is actually the SAS effect is the cloud effect because as you know it's in IT sort of inflection points nothing is linear right so once you reach a certain critical mass of cloud apps and we're absolutely there already all of a sudden you're traffic pattern on your network changes dramatically so why in the world are you continuing kind of you know concentrating all of your traffic in your data center and then going to the internet you have to absolutely open the floodgates at the branch level as close to the users as possible and that implies a radical change I would even add to that and I think you guys are right on where you guys are going it may be hard to kind of tease out with all the complexity with Cisco but in the keynote the business model shifts come from SAS so you got all this technical stuff going on now you have this Asif ocation or cloud that's changes the business models so new entrants can come in and existing players can get better so I think that whole business model conversation yeah never was discussed at Cisco live before yeah in depth as well hey run your business connect your hubs campus move packets around that was applications in business model yeah but also the fact that there is increasing number of software capabilities and so fundamental you want to simplify the life of your customers through subscription models that help the customer by now using what they really need right at any given point in time all the way to having enterprise agreements I also think that's about delivering these application experiences for your business small different type experience that's really what's differentiating you from your different competitors right and so I think that's a different type of shift as well well you guys are good got some good angle on this cloud I love it I got to ask you the question what can we expect next from Cisco more progression along clarification what's next well I would say we've been incredibly consistent I believe in the last few years in executing on our cloud strategy which again is centered around helping customers really gluon this mix set of data centers and clouds to make it work as one write as much as possible and so what we really deliver is networking security and application of performance management and we're integrating there's more and more on the two sides of the equation right the the designer side and the powerful outside and more more integrating in between all of these layers again to fundamentally give you this operational capability to get faster and faster we'll continue doing so and you set up before we came on camera that you were talking to the sales teams what are they what's their vibe with the sales team they get excited by this what's that oh yeah feedback oh yeah absolutely from the inner side were claw optimizer and they have dynamics that's very exciting for them especially the conversations they're having with their customers really from that application experience and proactively insuring it and on the hyper flex application platform side this is extremely exciting with providing a container cloud to our customers and you know what's coming down is more and more capabilities for our customers to modernize their applications on hyper flex you guys are riding some pretty big waves here at Cisco I get a cloud way to get the IOT Security wave it's pretty exciting pretty big stuff thanks for coming in thanks for sharing the insights Fabio I appreciate it thank you for having us your coverage here in Barcelona I'm John Force dude Minutemen be back with more coverage fourth day of four days of cube coverage we right back after this short break [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] why Trump Barcelona Spain it's the cube covering Cisco live 2020 rot to you by Cisco and its ecosystem partners welcome back to Barcelona everybody we're here at Cisco live and you're watching the cube the leader in live tech coverage we got to the events and extract the signal from the noise this is day one really we started a zero yesterday Eric Hertzog is here he's the CMO and vice president of storage channels probably been on the cube more than [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] live from Barcelona Spain it's the cube covering Cisco live 2020 rot to you by Cisco and its ecosystem partners welcome back everyone's two cubes live coverage day four of four days of wall-to-wall action here in Barcelona Spain Francisco live 2020 I'm John Ferrier with mykos Dave Volante with a very special guest here to wrap up Cisco live the president of Europe Middle East Africa and Russia Francisco Wendy Mars cube alumni great to see you thanks for coming on to kind of put a bookend to the show here thanks for joining us right there it's absolutely great to be here thank you so what a transformation as Cisco's business model of continues to evolve we've been saying brick by brick we still think is a big move coming I think there's more action I can sense the walls talking to us like let's just go live in the US and more technical announcements in the next 24 months you can see you can see where it's going it's cloud its apps yeah its policy based program ability it's really a whole nother business model shift for you and your customers the technology shift and the business model shift so I want to get your perspective of this year opening key no you let it off talking about the philosophy of the business model but also the first presenter was not a networking guy it was an application person yeah app dynamics yep this is a shift what's going on with Cisco what's happening what's the story well you know if you look for all of the work that we're doing is but is really driven by what we see from requirements from our customers the change that's happening in the market and it is all around you know if you think digital transformation is the driver organizations now are incredibly interested in how do they capture that opportunity how do they use technology to help them but you know if you look at it really there's the three items that are so important it's the business model evolution it's actually the business operations for for organisations plus their people there are people in the communities within that those three things working together and if you look at it with you know it's so exciting with application dynamics there because if you look for us within Cisco that linkage of the application layer through into the infrastructure into the network and bringing that linkage together is the most powerful thing because that's the insight and the value our customers are looking for you know we've been talking about the in the innovation sandwich you know you got you know date in the middle and you got technology and applications underneath that's kind of what's going on here but you I'm glad you brought up the year the part about business model business operations and people in communities because during your keno you had a slide that laid out three kind of pillars yes people in communities business model and business operations there was no 800 series in there there was no product discussions this is fundamentally the big shift that business models are changing I tweeted provocatively the killer app and digital the business model because you think about it the applications are the business and what's running under the covers is the technology but it's all shifting and changing so every single vertical every single business is impacted by this it's not like a certain secular thing in the industry this is a real change can you describe how those three things are operating with that constitute think if you look from you know so thinking through those three areas if you look at the actual business model itself our business models as organizations are fundamentally changing and they're changing towards as consumers we are all much more specific about what we want we have incredible choice in the market we are more informed than ever before but also we are interested in the values of the organizations that were getting the capability from as well as the products and the services that naturally we're looking to gain so if you look in that business model itself this is about you know organizations making sure they stay ahead from a competitive standpoint about the innovation of portfolio that they're able to bring but also that they have a strong strong focus around the experience that their customer gains from an application a touch standpoint that all comes through those different channels which is at the end of the day the application then if you look as to how do you deliver that capability through the systems the tools and the processes as we all evolve our businesses you have to change the dynamic within your organization to cope with that and then of course in driving any transformation the critical success factor is your people and your culture you need your teams with you the way teams operate now is incredibly different it's no longer command and control its agile capability coming together you need that to deliver on any transformation never never mind let it be smooth you know in the execution there so it's all three together what I like about that model and I have to say we this is you know ten years to do in the cube you you see that marketing in the vendor community often leads what actually happens not surprising as we entered the last decade it was a lot of talk about cloud well it kind of was a good predictor we heard a lot about digital transformations a lot of people roll their eyes and think it's a buzzword but we really are I feel like an exiting this cloud era into the digital era it feels real and there are companies that you know get it and are leaning in there are others that maybe you're complacent I'm wondering what you're seeing in in Europe just in terms of everybody talks digital yeah be CEO wants to get it right but there is complacency there when it's a services say well I'm doing pretty well not on my watch others say hey we want to be the disruptors and not get disrupted what are you seeing in the region in terms of that sentiment I would say across the region you know there will always be verticals and industries that are slightly more advanced than others but I would say that then the bulk of conversations that I'm engaged in independence of the industry or the country in which we're having that conversation in there is a acceptance of transfer digital transformation is here it is affecting my business i if I don't disrupt I myself will be disrupted and be challenged help me so I you know I'm not disputing the end state I need guidance and support to drive the transition and a risk mythic mitigated manner and they're looking for help in that and there's actually pressure in the boardroom now around a what are we doing within within organizations within that enterprise the service right of the public said to any type of style of company there's that pressure point in the boardroom of come on we need to move it speed now the other thing about your model is technology plays a role in contribute it's not the be-all end-all but plays a role in each of those the business model of business operations and developing and nurturing communities can you add more specifics what role do you see technology in terms of advancing those three spheres so I think you know if you look at it technology is fundamental to all of those spheres in regard to the innovation the differentiation technology can bring then the key challenges one of being able to reply us in a manner where you can really see differentiation of value within the business so in then the customers organization otherwise it's just technology for the sake of technology so we see very much a movement now to this conversation of talk about the use case the use cases the way by which that innovation can be used to deliver the value to the organization and also different ways by which a company will work look at the collaboration capability that we announced earlier this week of helping to bring to life that agility look at the app D discussion of helping to link the layer of the application into the infrastructure the network's to get to root cause identification quickly and to understand where you may have a problem before you thought it actually arises and causes downtime many many ways I think the agility message has always been a technical conversation a gel methodology technology software development no problem check that's ten years ago but business agility mmm it's moving from a buzzword to reality exactly that's what you're kind of getting in here and teams how teams operate how they work you know and being able to be quick efficient stand up stand down and operate in that way you know we were kind of thinking out loud on the cube and just riffing with Fabio gory on your team on Cisco's team about clarification with Eugene Kim around just just kind of real-time what was interesting is we're like okay it's been 13 years since the iPhone and so 13 years of mobile in your territory in Europe Middle East Africa mobilities been around before the iPhone so with in more advanced data privacy much more advanced in your region so you got you out you have a region that's pretty much I think the tell signs for what's going on in North America and around the world and so you think about that you say okay how is value created how the economics changing this is really the conversation about the business model is okay if the value activities are shifting and be more agile and the economics are changing with sass if someone's not on this bandwagon it's not an in-state discussion where it's done deal yeah it's but I think also there were some other conversation which which are very prevalent here is in in the region so around trust around privacy law understanding compliance you look at data where data resides portability of that data GDP are came from Europe you know and as ban is pushed out and those conversations will continue as we go over time and if I also look at you know the dialogue that you saw so you know within World Economic Forum around sustainability that is becoming a key discussion now within government here in Spain you know from a climate standpoint and many other areas as well Dave and I've been riffing around this whole where the innovation is coming from it's coming from Europe region not so much the u.s. I mean us discuss some crazy innovations but look at blockchain us is like don't touch it pretty progressive outside United States little bit dangerous to but that's where innovation is coming from and this is really the key that we're focused on I want to get your thoughts on how do you see it going next level the next level next-gen business model what's your what's your vision so I think there'll be lots of things if we look at things like with the introduction of artificial intelligence robotics capability 5g of course you know on the horizon we have Mobile World Congress here in Barcelona in a few weeks time and if you talked about with the iPhone the smartphone of course when 4G was introduced no one knew what the use case would that would be it was the smartphone which wasn't around at that time so with 5g in the capability there that will bring again yet more change to the business model for different organizations and the capability and what we can bring to market when we think about AI privacy data ownership becomes more important some of the things you were talking about before it's interesting what you're saying John and when the the GDP are set the standard and and you see in the u.s. there are stovepipes for that standard California is going to do one every state is going to have a different center that's going to slow things down that's going to slow down progress do you see sort of an extension of a GDP are like framework of being adopted across the region and that potentially you know accelerating some of these you know sticky issues and public policy issues that can actually move the market forward I think I think the will because I think there'll be more and more you know if you look at there's this terminology of data is the new oil what do you do with data how do you actually get value from that data and make intelligent business decisions around that so you know that's critical but yet if you look for all of ours we are extremely passionate about you know where is our data used again back to trust and privacy you need compliance you need regulation you know I think this is just the beginning of how we will see that evolve you know when do I get your thoughts does Dave and I have been riffing for 10 years around the death of storage long live storage and but data needs to be stored somewhere networking is the same kind of conversation just doesn't go away in fact there's more pressure now forget the smartphone that was 13 years ago before that mobility data and video now super important driver that's putting more pressure on you guys and so hey we're networking so it's kind of like Moore's law it's like more networking more networking so video and data are now big your thoughts on video and data video but if you look at the Internet of the future you know what so if you look for all of us now we are also demanding as individuals around capability and access to that and inter vetted the future the next phase we want even more so there'll be more and more - you know requirement for speed availability that reliability of service the way by which we engage and we communicate there's some fundamentals there so continuing to to grow which is which is so so exciting for us so you talk about digital transformation that's obviously in the mind of c-level executives I got to believe security is up there as a topic what other what's the conversation like in the corner office when you go visit your customers so I think that there's a huge excitement around the opportunity realizing the value of the of the opportunity you know if you look at top of mind conversations are around security around making sure that you can make tank maintain that fantastic customer experience because if you don't the custom will go elsewhere how do you do that how do you enrich at all times and also looking at markets adjacencies you know as you go in and you talk at senior levels within within organizations independent of the industry in which they're in there are a huge amount of commonalities that we see across those of consistent problems by which organizations are trying to solve and actually one of the big questions is what's the pace of change that I should operate at and when is it too fast and when is what am I too slow and trying to balance that is exciting but also a challenge for companies so you feel like sentiment is still strong even though we're 10 years into this this bull market you know you got Briggs it you get you know China tensions with the US u.s. elections but but generally you see Tennessee sentiment still pretty strong and demand so I would say that the the excitement around technology the opportunity that is there around technology in its broadest sense is greater than ever before and I think it's on all of us to be able to help organizations to understand how they can consume I see value from us but it's you know it's fantastic science it tastes trying to get some economic indicators but really the real thing I'm trying to get you is Minh set of the CEO the corner office right now is it is it we're gonna we're gonna grow short-term by cutting or do we do are we gonna be aggressive and go after this incremental opportunity and it's probably both you're seeing a lot of automation yeah and I think if you look fundamentally for organizations it's it's that the three things helped me to make money how me to save money keep me out of trouble you know so those are the pivots they all operate with and you know depending on where an organization is in its journey whether a start-up there you know in in the in the mid or the more mature and some of the different dynamics and the markets in which they operate in as well there's all different variables you know so it's it's it's mix Wendy thanks so much for spending the time to come on the cube really appreciate great keynote folks watching if you haven't seen the keynote opening sections that's a good section the business model I think it's really right on I think that's going to be a conversation it's going to continue thanks for sharing that before we look before we leave I want to just ask you a question around what you what's going on for you here at Barcelona as the show winds down you had all your activities take us in the day of the life of what you do customer meetings what were some of those conversations take us inside inside what what goes on for you here well I'd say it's been an amazing it's been an amazing few days so it's a combination of customer conversations around some of the themes we just talked about conversations with partners and there's investor companies that we invest in a Cisco that I've been spending some time with and also you know spending time with the teams as well the DEF net zone you know is amazing we have this afternoon the closing session where we've got a fantastic external guest who's coming in it's going to be really exciting as well and then of course the party tonight and we'll be announcing the next location which I'm not gonna reveal now later on today we kind of figured it out already because that's our job and there's the break news but we're not gonna break it for you you can have that hey thank you so much for coming on really appreciate Wendy Martin expecting the Europe Middle East Africa and Russia for Cisco she's got our hand on the pulse and the future is the business model that's what's going on fundamental radical change across the board in all areas this the cue bringing you all the action here in Barcelona thanks for watching [Music] [Music] [Music] [Applause] [Music] [Music] [Music] [Music] [Applause] [Music] [Applause] [Music] [Music]
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Renaud Gaubert, NVIDIA & Diane Mueller, Red Hat | KubeCon + CloudNativeCon NA 2019
>>Live from San Diego, California It's the Q covering Koopa and Cloud Native Cot brought to you by Red Cloud, Native Computing Pounding and its ecosystem March. >>Welcome back to the Cube here at Q. Khan Club native Khan, 2019 in San Diego, California Instrumental in my co host is Jon Cryer and first of all, happy to welcome back to the program. Diane Mueller, who is the technical of the tech lead of cloud native technology. I'm sorry. I'm getting the wrong That's director of community development Red Hat, because renew. Goodbye is the technical lead of cognitive technologies at in video game to the end of day one. I've got three days. I gotta make sure >>you get a little more Red Bull in the conversation. >>All right, well, there's definitely a lot of energy. Most people we don't even need Red Bull here because we're a day one. But Diane, we're going to start a day zero. So, you know, you know, you've got a good group of community of geeks when they're like Oh, yeah, let me fly in a day early and do like 1/2 day or full day of deep dives. There So the Red Hat team decided to bring everybody on a boat, I guess. >>Yeah. So, um, open ships Commons gathering for this coup con we hosted at on the inspiration Hornblower. We had about 560 people on a boat. I promised them that it wouldn't leave the dock, but we deal still have a little bit of that weight going on every time one of the big military boats came by. And so people were like a little, you know, by the end of the day, but from 8 a.m. in the morning till 8 p.m. In the evening, we just gathered had some amazing deep dives. There was unbelievable conversations onstage offstage on we had, ah, wonderful conversation with some of the new Dev ops folks that have just come on board. That's a metaphor for navigation and Coop gone. And and for events, you know, Andrew Cliche for John Willis, the inevitable Crispin Ella, who runs Open Innovation Labs, and J Bloom have all just formed the global Transformation Office. I love that title on dhe. They're gonna be helping Thio preach the gospel of Cultural Dev ops and agile transformation from a red hat office From now going on, there was a wonderful conversation. I felt privileged to actually get to moderate it and then just amazing people coming forward and sharing their stories. It was a great session. Steve Dake, who's with IBM doing all the SDO stuff? Did you know I've never seen SDO done so well, Deployment explains so well and all of the contents gonna be recorded and up on Aaron. We streamed it live on Facebook. But I'm still, like reeling from the amount of information overload. And I think that's the nice thing about doing a day zero event is that it's a smaller group of people. So we had 600 people register, but I think was 560 something. People show up and we got that facial recognition so that now when they're traveling through the hallways here with 12,000 other people, that go Oh, you were in the room. I met you there. And that's really the whole purpose for comments. Events? >>Yeah, I tell you, this is definitely one of those shows that it doesn't take long where I say, Hey, my brain is full. Can I go home. Now. You know I love your first impressions of Q Khan. Did you get to go to the day zero event And, uh, what sort of things have you been seeing? So >>I've been mostly I went to the lightning talks, which were amazing. Anything? Definitely. There. A number of shout outs to the GPU one, of course. Uh, friend in video. But I definitely enjoyed, for example, of the amazing D. M s one, the one about operators. And generally all of them were very high quality. >>Is this your first Q? Khan, >>I've been there. I've been a year. This is my third con. I've been accused in Europe in the past. Send you an >>old hat old hand at this. Well, before we get into the operator framework and I wanna love to dig into this, I just wanted to ask one more thought. Thought about open shift, Commons, The Commons in general, the relationship between open shift, the the offering. And then Okay, the comments and okay, D and then maybe the announcement about about Okay. Dee da da i o >>s. Oh, a couple of things happened yesterday. Yesterday we dropped. Okay, D for the Alfa release. So anyone who wants to test that out and try it out it's an all operators based a deployment of open shift, which is what open ship for is. It's all a slightly new architectural deployment methodology based on the operator framework, and we've been working very diligently. Thio populate operator hub dot io, which is where all of the upstream projects that have operators like the one that Reynolds has created for in the videos GP use are being hosted so that anyone could deploy them, whether on open shift or any kubernetes so that that dropped. And yesterday we dropped um, and announced Open Sourcing Quay as project quay dot io. So there's a lot of Io is going on here, but project dia dot io is, um, it's a fulfillment, really, of a commitment by Red Hat that whenever we do an acquisition and the poor folks have been their acquired by Cora West's and Cora Weston acquired by Red Hat in an IBM there. And so in the interim, they've been diligently working away to make the code available as open source. And that hit last week and, um, to some really interesting and users that are coming up and now looking forward to having them to contribute to that project as well. But I think the operator framework really has been a big thing that we've been really hearing, getting a lot of uptake on. It's been the new pattern for deploying applications or service is on getting things beyond just a basic install of a service on open shift or any kubernetes. And that's really where one of the exciting things yesterday on we were talking, you know, and I were talking about this earlier was that Exxon Mobil sent a data scientist to the open ship Commons, Audrey Resnick, who gave this amazing presentation about Jupiter Hub, deeper notebooks, deploying them and how like open shift and the advent of operators for things like GP use is really helping them enable data scientists to do their work. Because a lot of the stuff that data signs it's do is almost disposable. They'll run an experiment. Maybe they don't get the result they want, and then it just goes away, which is perfect for a kubernetes workload. But there are other things you need, like a Jeep use and work that video has been doing to enable that on open shift has been just really very helpful. And it was It was a great talk, but we were talking about it from the first day. Signs don't want to know anything about what's under the hood. They just want to run their experiments. So, >>you know, let's like to understand how you got involved in the creation of the operator. >>So generally, if we take a step back and look a bit at what we're trying to do is with a I am l and generally like EJ infrastructure and five G. We're seeing a lot of people. They're trying to build and run applications. Whether it's in data Center at the and we're trying to do here with this operator is to bring GPS to enterprise communities. And this is what we're working with. Red Hat. And this is where, for example, things like the op Agrestic A helps us a lot. So what we've built is this video Gee, few operator that space on the upper air sdk where it wants us to multiple phases to in the first space, for example, install all the components that a data scientist were generally a GPU cluster of might want to need. Whether it's the NVIDIA driver, the container runtime, the community's device again feast do is as you go on and build an infrastructure. You want to be able to have the automation that is here and, more importantly, the update part. So being able to update your different components, face three is generally being able to have a life cycle. So as you manage multiple machines, these are going to get into different states. Some of them are gonna fail, being able to get from these bad states to good states. How do you recover from them? It's super helpful. And then last one is monitoring, which is being able to actually given sites dr users. So the upper here is decay has helped us a lot here, just laying out these different state slips. And in a way, it's done the same thing as what we're trying to do for our customers. The different data scientists, which is basically get out of our way and allow us to focus on core business value. So the operator, who basically takes care of things that are pretty cool as an engineer I lost due to your election. But it doesn't really help me to focus on like my core business value. How do I do with the updates, >>you know? Can I step back one second, maybe go up a level? The problem here is that each physical machine has only ah limited number of NVIDIA. GPU is there and you've got a bunch of containers that maybe spawning on different machines. And so they have to figure out, Do I have a GPU? Can I grab one? And if I'm using it, I assume I have to reserve it and other people can't use and then I have to give it up. Is that is that the problem we're solving here? So this is >>a problem that we've worked with communities community so that like the whole resource management, it's something that is integrated almost first class, citizen in communities, being able to advertise the number of deep, use their your cluster and used and then being able to actually run or schedule these containers. The interesting components that were also recently added are, for example, the monitoring being able to see that a specific Jupiter notebook is using this much of GP utilization. So these air supercool like features that have been coming in the past two years in communities and which red hat has been super helpful, at least in these discussions pushing these different features forward so that we see better enterprise support. Yeah, >>I think the thing with with operators and the operator lifecycle management part of it is really trying to get to Day two. So lots of different methodologies, whether it's danceable or python or job or or UH, that's helm or anything else that can get you an insult of a service or an application or something. And in Stan, she ate it. But and the operator and we support all of that with SD case to help people. But what we're trying to do is bridge the to this day to stuff So Thea, you know, to get people to auto pilot, you know, and there's a whole capacity maturity model that if you go to operator hab dot io, you can see different operators are a different stages of the game. So it's been it's been interesting to work with people to see Theo ah ha moment when they realize Oh, I could do this and then I can walk away. And then if that pod that cluster dies, it'll just you know, I love the word automatically, but they, you know, it's really the goal is to help alleviate the hands on part of Day two and get more automation into the service's and applications we deploy >>right and when they when they this is created. Of course it works well with open shift, but it also works for any kubernetes >>correct operator. HAB Daddio. Everything in there runs on any kubernetes, and that's really the goal is to be ableto take stuff in a hybrid cloud model. You want to be able to run it anywhere you want, so we want people to be unable to do it anywhere. >>So if this really should be an enabler for everything that it's Vinny has been doing to be fully cloud native, Yes, >>I think completely arable here is this is a new attack. Of course, this is a bit there's a lot of complexity, and this is where we're working towards is reducing the complexity and making true that people there. Dan did that a scientist air machine learning engineers are able to focus on their core business. >>You watch all of the different service is in the different things that the data scientists are using. They don't I really want to know what's under under the hood. They would like to just open up a Jupiter Hub notebook, have everything there. They need, train their models, have them run. And then after they're done, they're done and it goes away. And hopefully they remember to turn off the Jeep, use in the woods or wherever it is, and they don't keep getting billed for it. But that's the real beauty of it is that they don't have to worry so much anymore about that. And we've got a whole nice life cycle with source to image or us to I. And they could just quickly build on deploy its been, you know, it's near and dear to my heart, the machine learning the eyesight of stuff. It is one of the more interesting, you know, it's the catchy thing, but the work was, but people are really doing it today, and it's been we had 23 weeks ago in San Francisco, we had a whole open ship comments gathering just on a I and ML and you know, it was amazing to hear. I think that's the most redeeming thing or most rewarding thing rather for people who are working on Kubernetes is to have the folks who are doing workloads come and say, Wow, you know, this is what we're doing because we don't get to see that all the time. And it was pretty amazing. And it's been, you know, makes it all worthwhile. So >>Diane Renaud, thank you so much for the update. Congratulations on the launch of the operators and look forward to hearing more in the future. >>All right >>to >>be here >>for John Troy runs to minimum. More coverage here from Q. Khan Club native Khan, 2019. Thanks for watching. Thank you.
SUMMARY :
Koopa and Cloud Native Cot brought to you by Red Cloud, California Instrumental in my co host is Jon Cryer and first of all, happy to welcome back to the program. There So the Red Hat team decided to bring everybody on a boat, And that's really the whole purpose for comments. Did you get to go to the day zero event And, uh, what sort of things have you been seeing? But I definitely enjoyed, for example, of the amazing D. I've been accused in Europe in the past. The Commons in general, the relationship between open shift, And so in the interim, you know, let's like to understand how you got involved in the creation of the So the operator, who basically takes care of things that Is that is that the problem we're solving here? added are, for example, the monitoring being able to see that a specific Jupiter notebook is using this the operator and we support all of that with SD case to help people. Of course it works well with open shift, and that's really the goal is to be ableto take stuff in a hybrid lot of complexity, and this is where we're working towards is reducing the complexity and It is one of the more interesting, you know, it's the catchy thing, but the work was, Congratulations on the launch of the operators and look forward for John Troy runs to minimum.
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Keynote | Red Hat Summit 2019 | DAY 2 Morning
>> Ladies and gentlemen, please welcome Red Hat President Products and Technologies. Paul Cormier. Boring. >> Welcome back to Boston. Welcome back. And welcome back after a great night last night of our opening with with Jim and talking to certainly saw ten Jenny and and especially our customers. It was so great last night to hear our customers in how they set their their goals and how they met their goals. All possible because certainly with a little help from red hat, but all possible because of because of open source. And, you know, sometimes we have to all due that has set goals. And I'm going to talk this morning about what we as a company and with community, have set for our goals along the way. And sometimes you have to do that. You know, audacious goals. It can really change the perception of what's even possible. And, you know, if I look back, I can't think of anything, at least in my lifetime, that's more important. Or such a big golden John F. Kennedy setting the gold to the American people to go to the moon. I believe it or not, I was really, really only three years old when he said that, honestly. But as I grew up, I remember the passion around the whole country and the energy to make that goal a reality. So let's sort of talk about in compare and contrast, a little bit of where we are technically at that time, you know, tto win and to beat and winning the space race and even get into the space race. There was some really big technical challenges along the way. I mean, believe it or not. Not that long ago. But even But back then, math Malik mathematical calculations were being shifted from from brilliant people who we trusted, and you could look in the eye to A to a computer that was programmed with the results that were mostly printed out. This this is a time where the potential of computers was just really coming on the scene and, at the time, the space race at the time of space race it. It revolved around an IBM seventy ninety, which was one of the first transistor based computers. It could perform mathematical calculations faster than even the most brilliant mathematicians. But just like today, this also came with many, many challenges And while we had the goal of in the beginning of the technique and the technology to accomplish it, we needed people so dedicated to that goal that they would risk everything. And while it may seem commonplace to us today to trust, put our trust in machines, that wasn't the case. Back in nineteen sixty nine, the seven individuals that made up the Mercury Space crew were putting their their lives in the hands of those first computers. But on Sunday, July twentieth, nineteen sixty nine, these things all came together. The goal, the technology in the team and a human being walked on the moon. You know, if this was possible fifty years ago, just think about what Khun B. Accomplished today, where technology is part of our everyday lives. And with technology advances at an ever increasing rate, it's hard to comprehend the potential that sitting right at our fingertips every single day, everything you know about computing is continuing to change. Today, let's look a bit it back. A computing In nineteen sixty nine, the IBM seventy ninety could process one hundred thousand floating point operations per second, today's Xbox one that sitting in most of your living rooms probably can process six trillion flops. That's sixty million times more powerful than the original seventy ninety that helped put a human being on the moon. And at the same time that computing was, that was drastically changed. That this computing has drastically changed. So have the boundaries of where that computing sits and where it's been where it lives. At the time of the Apollo launch, the computing power was often a single machine. Then it moved to a single data center, and over time that grew to multiple data centers. Then with cloud, it extended all the way out to data centers that you didn't even own or have control of. But but computing now reaches far beyond any data center. This is also referred to as the edge. You hear a lot about that. The Apollo's, the Apollo's version of the Edge was the guidance system, a two megahertz computer that weighed seventy pounds embedded in the capsule. Today, today the edge is right here on my wrist. This apple watch weighs just a couple of ounces, and it's ten ten thousand times more powerful than that seventy ninety back in nineteen sixty nine But even more impactful than computing advances, combined with the pervasive availability of it, are the changes and who in what controls those that similar to social changes that have happened along the way. Shifting from mathematicians to computers, we're now facing the same type of changes with regards to operational control of our computing power. In its first forms. Operational control was your team, your team within your control? In some cases, a single person managed everything. But as complexity grows, our team's expanded, just like in the just like in the computing boundaries, system integrators and public cloud providers have become an extension of our team. But at the end of the day, it's still people that are still making all the decisions going forward with the progress of things like a I and software defined everything. It's quite likely that machines will be managing machines, and in many cases that's already happening today. But while the technology at our finger tips today is so impressive, the pace of changing complexity of the problems we aspire to solve our equally hard to comprehend and they are all intertwined with one another learning from each other, growing together faster and faster. We are tackling problems today on a global scale with unsinkable complexity beyond anyone beyond what any one single company or even one single country Khun solve alone. This is why open source is so important. This is why open source is so needed today in software. This is why open sources so needed today, even in the world, to solve other types of complex problems. And this is why open source has become the dominant development model which is driving the technology direction. Today is to bring two brother to bring together the best innovation from every corner of the planet. Toe fundamentally change how we solve problems. This approach and access the innovation is what has enabled open source To tackle The challenge is big challenges, like creating the hybrid cloud like building a truly open hybrid cloud. But even today it's really difficult to bridge the gap of the innovation. It's available in all in all of our fingertips by open source development, while providing the production level capabilities that are needed to really dip, ploy this in the enterprise and solve RIA world business problems. Red Hat has been committed to open source from the very, very beginning and bringing it to solve enterprise class problems for the last seventeen plus years. But when we built that model to bring open source to the enterprise, we absolutely knew we couldn't do it halfway tow harness the innovation. We had to fully embrace the model. We made a decision very early on. Give everything back and we live by that every single day. We didn't do crazy crazy things like you hear so many do out there. All this is open corps or everything below. The line is open and everything above the line is closed. We didn't do that, and we gave everything back Everything we learned in the process of becoming an enterprise class technology company. We gave it all of that back to the community to make better and better software. This is how it works. And we've seen the results of that. We've all seen the results of that and it could only have been possible within open source development model we've been building on the foundation of open source is most successful Project Lennox in the architecture of the future hybrid and bringing them to the Enterprise. This is what made Red Hat, the company that we are today and red hats journey. But we also had the set goals, and and many of them seemed insert insurmountable at the time, the first of which was making Lennox the Enterprise standard. And while this is so accepted today, let's take a look at what it took to get there. Our first launch into the Enterprise was rail two dot one. Yes, I know we two dot one, but we knew we couldn't release a one dato product. We knew that and and we didn't. But >> we didn't want to >> allow any reason why anyone of any customer anyone shouldn't should look past rail to solve their problems as an option. Back then, we had to fight every single flavor of Unix in every single account. But we were lucky to have a few initial partners and Big Eyes v partners that supported Rehl out of the gate. But while we had the determination, we knew we also had gaps in order to deliver on our on our priorities. In the early days of rail, I remember going to ask one of our engineers for a past rehl build because we were having a customer issue on it on an older release. And then I watched in horror as he rifled through his desk through a mess of CDs and magically came up and said, I found it here It is told me not to worry that the build this was he thinks this was the bill. This was the right one, and at that point I knew that despite the promise of Lennox, we had a lot of work ahead of us. The not only convinced the world that Lennox was secure, stable, an enterprise ready, but also to make that a reality. But we did. And today this is our reality. It's all of our reality. From the Enterprise Data Center standard to the fastest computers on the planet, Red Hat Enterprise, Lennox has continually risen to the challenge and has become the core foundation that many mission critical customers run and bet their business on. And an even bigger today Lennox is the foundation of which practically every single technology initiative is built upon. Lennox is not only standard toe build on today, it's the standard for innovation that builds around it. That's the innovation that's driving the future as well. We started our story with rail two dot one, and here we are today, seventeen years later, announcing rally as we did as we did last night. It's specifically designed for applications to run across the open hybrid. Clyde Cloud. Railed has become the best operating simp system for on premise all the way out to the cloud, providing that common operating model and workload foundation on which to build hybrid applications. Let's take it. Let's take a look at how far we've come and see this in action. >> Please welcome Red Hat Global director of developer experience, burst Sutter with Josh Boyer, Timothy Kramer, Lars Carl, it's Key and Brent Midwood. All right, we have some amazing things to show you. In just a few short moments, we actually have a lot of things to show you. And actually, Tim and Brandt will be with us momentarily. They're working out a few things in the back because we have a lot of this is gonna be a live demonstration, some incredible capabilities. Now you're going to see clear innovation inside the operating system where we worked incredibly hard to make it vast cities. You're free to manage many, many machines. I want you thinking about that as we go to this process. Now, also, keep in mind that this is the basis our core platform for everything we do here. Red hat. So it is an honor for me to be able to show it to you live on stage today. And so I recognize the many of you in the audience right now. Her hand's on systems administrators, systems, architect, citizens, engineers. And we know that you're under ever growing pressure to deliver needed infrastructure. Resource is ever faster, and that is a key element to what you're thinking about every day. Well, this has been a core theme, and our design decisions find red Odd Enterprise Lennox eight and intelligent operating system, which is making it fundamentally easier for you manage machines that scale. So hold what you're about to see next. Feels like a new superpower and and that redhead azure force multiplier. So first, let me introduce you to a large. He's totally my limits guru. >> I wouldn't call myself a girl, but I I guess you could say that I want to bring Lennox and light meant to more people. >> Okay, Well, let's let's dive in. And we're not about the clinic's eight. >> Sure. Let me go. And Morgan, >> wait a >> second. There's windows. >> Yeah, way Build the weft Consul into Really? That means that for the first time, you can log in from any device including your phone or this standard windows laptop. So you just go ahead and and to my Saturday lance credentials here. >> Okay, so now >> you're putting >> your limits password and over the web. >> Yeah, that might sound a bit scary at first, but of course, we're using the latest security tech by T. L s on dh csp on. Because that's the standard Lennox off site. You can use everything that you used to like a stage keys, OTP, tokens and stuff like this. >> Okay, so now I see the council right here. I love the dashboard overview of the system, but what else can you tell us about this council? >> Right? Like right here. You see the load of the system, some some of its properties. But you can also dive into logs everything that you're used to from the command line, right? Or lookit, services. This's all the services I've running, can start and stuff them and enable >> OK, I love that feature right there. So what about if I have to add a whole new application to this environment? >> Good that you're bringing that up. We build a new future into hell called application streams. Which the way for you to install different versions of your half stack that are supported I'LL show you with Youngmin a command line. But since Windows doesn't have a proper terminal, I'll just do it in the terminal that we built into the Web console Since the browser, I can even make this a bit bigger. Go to, for example, to see the application streams that we have for Poskus. Ijust do module list and I see you know we have ten and nine dot six Both supported tennis a default on defy enable ninety six Now the next time that I installed prescribes it will pull all their lady towards from them at six. >> Ok, so this is very cool. I see two verses of post Chris right here What tennis to default. That is fantastic and the application streams making that happen. But I'm really kind of curious, right? I loved using know js and Java. So what about multiple versions of those? >> Yeah, that's exactly the idea way. Want to keep up with the fast moving ecosystems off programming language? Isn't it a business? >> Okay, now, But I have another key question. I know some people were thinking it right now. What about Python? >> Yeah. In fact, in a minimum and still like this, python gives you command. Not fact. Just have to type it correctly. You can't just install which everyone you want two or three or whichever your application needs. >> Okay, Well, that is I've been burned on that one before. Okay, so no actual. Have a confession for all you guys. Right here. You guys keep this amongst yourselves. Don't let Paul No, I'm actually not a linnet systems administrator. I'm an application developer, an application architect, And I recently had to go figure out how to extend the file system. This is for real. And I'm going to the rat knowledge base and looking up things like, you know, PV create VD, extend resized to f s. And I have to admit, that's hard, >> right? I've opened the storage space for you right here, where you see an overview of your storage. And the council has made for people like you as well not only for people that I knew that when you two lunatics, right? It's if you're running, you're running some of the commands only, you know, some of the time you don't remember them. So, for example, I haven't felt twosome here. That's a little bit too small. Let me just throw it. It's like, you know, dragging this lighter. It calls all the command in the background for you. >> Oh, that is incredible. Is that simple? Just drag and drop. That is fantastic. Well, so I actually, you know, we'll have another question for you. It looks like now this linen systems administration is no longer a dark heart involving arcane commands typed into a black terminal. Like using when those funky ergonomic keyboards you know I'm talking about right? Do >> you know a lot of people, including me and people in the audience like that dark out right? And this is not taking any of that away. It's on additional tool to bring limits to more people. >> Okay, well, that is absolute fantastic. Thank you so much for that Large. And I really love him installing everything is so much easier, including a post gra seeker and, of course, the python that we saw right there. So now I want to change gears for a second because I actually have another situation that I'm always dealing with. And that is every time I want to build a new Lenox system, not only I don't want to have to install those commands again and again, it feels like I'm doing it over and over. So, Josh, how would I create a golden image? One VM image that can use and we have everything pre baked in? >> Yeah, absolutely. But >> we get that question all the time. So really includes image builder technology. Image builder technology is actually all of our hybrid cloud operating system image tools that we use to build our own images and rolled up in a nice, easy to integrate new system. So if I come here in the web console and I go to our image builder tab, it brings us to blueprints, right? Blueprints or what we used to actually control it goes into our golden image. Uh, and I heard you and Lars talking about post present python. So I went and started typing here. So it brings us to this page, but you could go to the selected components, and you can see here I've created a blueprint that has all the python and post press packages in it. Ah, and the interesting thing about this is it build on our existing kickstart technology. But you can use it to deploy that whatever cloud you want. And it's saved so that you don't actually have to know all the various incantations from Amazon toe azure to Google, whatever it's all baked in on. When you do this, you can actually see the dependencies that get brought in as well. Okay. Should we create one life? Yes, please. All right, cool. So if we go back to the blueprints page and we click create blueprint Let's, uh let's make a developer brute blueprint here. So we click great, and you can see here on the left hand side. I've got all of my content served up by Red Hat satellite. We have a lot of great stuff, and really, But we can go ahead and search. So we'LL look for post grows and you know, it's a developer image at the client for some local testing. Um, well, come in here and at the python bits. Probably the development package. We need a compiler if we're going to actually build anything. So look for GCC here and hey, what's your favorite editor? >> A Max, Of course, >> Max. All right. Hey, Lars, about you. I'm more of a person. You Maxim v I All right, Well, if you want to prevent a holy war in your system, you can actually use satellite to filter that out. But we're going to go ahead and Adam Ball, sweetie, I'm a fight on stage. So wait, just point and click. Let the graphical one. And then when we're all done, we just commit our changes, and our image is ready to build. >> Okay, So this VM image we just created right now from that blueprint this is now I can actually go out there and easily deploys of deploy this across multiple cloud providers. And as well as this on stage are where we have right now. >> Yeah, absolutely. We can to play on Amazon as your google any any infrastructure you're looking for so you can really hit your Clyburn hybrid cloud operating system images. >> Okay. All right, listen, we >> just go on, click, create image. Uh, we can select our different types here. I'm gonna go ahead and create a local VM because it's available image, and maybe they want to pass it around or whatever, and I just need a few moments for it to build. >> Okay? So while that's taking a few moments, I know there's another key question in the minds of the audience right now, and you're probably thinking I love what I see. What Right eye right hand Priceline say. But >> what does it >> take to upgrade from seven to eight? So large can you show us and walk us through an upgrade? >> Sure, this's my little Thomas Block that I set up. It's powered by what Chris and secrets over, but it's still running on seven six. So let's upgrade that jump over to my house fee on satellite on. You see all my relate machines here, including the one I showed you what Consul on before. And there is that one with my sun block and there's a couple others. Let me select those as well. This one on that one. Just go up here. Schedule remote job. And she was really great. And hit Submit. I made it so that it makes the booms national before. So if anything was wrong Kans throwback! >> Okay, okay, so now it's progressing. Here, >> it's progressing. Looks like it's running. Doing >> live upgrade on stage. Uh, >> seems like one is failing. What's going on here? Okay, we checked the tree of great Chuck. Oh, yeah, that's the one I was playing around with Butter fest backstage. What? Detective that and you know, it doesn't run the Afghan cause we don't support operating that. >> Okay, so what I'm hearing now? So the good news is, we were protected from possible failed upgrade there, So it sounds like these upgrades are perfectly safe. Aiken, basically, you know, schedule this during a maintenance window and still get some sleep. >> Totally. That's the idea. >> Okay, fantastic. All right. So it looks like upgrades are easy and perfectly safe. And I really love what you showed us there. It's good point. Click operation right from satellite. Ok, so Well, you know, we were checking out upgrades. I want to know Josh. How those v ems coming along. >> They went really well. So you were away for so long. I got a little bored and I took some liberties. >> What do you mean? >> Well, the image Bill And, you know, I decided I'm going to go ahead and deploy here to this Intel machine on stage Esso. I have that up and running in the web. Counsel. I built another one on the arm box, which is actually pretty fast, and that's up and running on this. Our machine on that went so well that I decided to spend up some an Amazon. So I've got a few instances here running an Amazon with the web console accessible there as well. On even more of our pre bill image is up and running an azure with the web console there. So the really cool thing about this bird is that all of these images were built with image builder in a single location, controlling all the content that you want in your golden images deployed across the hybrid cloud. >> Wow, that is fantastic. And you might think that so we actually have more to show you. So thank you so much for that large. And Josh, that is fantastic. Looks like provisioning bread. Enterprise Clinic Systems ate a redhead. Enterprise Enterprise. Rhetta Enterprise Lennox. Eight Systems is Asian ever before, but >> we have >> more to talk to you about. And there's one thing that many of the operations professionals in this room right now no, that provisioning of'em is easy, but it's really day two day three, it's down the road that those viens required day to day maintenance. As a matter of fact, several you folks right now in this audience to have to manage hundreds, if not thousands, of virtual machines I recently spoke to. Gentleman has to manage thirteen hundred servers. So how do you manage those machines? A great scale. So great that they have now joined us is that it looks like they worked things out. So now I'm curious, Tim. How will we manage hundreds, if not thousands, of computers? >> Welbourne, one human managing hundreds or even thousands of'em says, No problem, because we have Ansel automation. And by leveraging Ansel's integration into satellite, not only can we spin up those V em's really quickly, like Josh was just doing, but we can also make ongoing maintenance of them really simple. Come on up here. I'm going to show you here a satellite inventory and his red hat is publishing patches. Weaken with that danceable integration easily apply those patches across our entire fleet of machines. Okay, >> that is fantastic. So he's all the machines can get updated in one fell swoop. >> He sure can. And there's one thing that I want to bring your attention to today because it's brand new. And that's cloud that red hat dot com And here, a cloud that redhead dot com You can view and manage your entire inventory no matter where it sits. Of Redhead Enterprise Lennox like on Prem on stage. Private Cloud or Public Cloud. It's true Hybrid cloud management. >> OK, but one thing. One thing. I know that in the minds of the audience right now. And if you have to manage a large number servers this it comes up again and again. What happens when you have those critical vulnerabilities that next zero day CV could be tomorrow? >> Exactly. I've actually been waiting for a while patiently for you >> to get to the really good stuff. So >> there's one more thing that I wanted to let folks know about. Red Hat Enterprise. The >> next eight and some features that we have there. Oh, >> yeah? What is that? >> So, actually, one of the key design principles of relate is working with our customers over the last twenty years to integrate all the knowledge that we've gained and turn that into insights that we can use to keep our red hat Enterprise Lennox servers running securely, inefficiently. And so what we actually have here is a few things that we could take a look at show folks what that is. >> OK, so we basically have this new feature. We're going to show people right now. And so one thing I want to make sure it's absolutely included within the redhead enterprise in that state. >> Yes. Oh, that's Ah, that's an announcement that we're making this week is that this is a brand new feature that's integrated with Red Hat Enterprise clinics, and it's available to everybody that has a red hat enterprise like subscription. So >> I believe everyone in this room right now has a rail subscriptions, so it's available to all of them. >> Absolutely, absolutely. So let's take a quick look and try this out. So we actually have. Here is a list of about six hundred rules. They're configuration security and performance rules. And this is this list is growing every single day, so customers can actually opt in to the rules that are most that are most applicable to their enterprises. So what we're actually doing here is combining the experience and knowledge that we have with the data that our customers opt into sending us. So customers have opted in and are sending us more data every single night. Then they actually have in total over the last twenty years via any other mechanism. >> Now there's I see now there's some critical findings. That's what I was talking about. But it comes to CVS and things that nature. >> Yeah, I'm betting that those air probably some of the rail seven boxes that we haven't actually upgraded quite yet. So we get back to that. What? I'd really like to show everybody here because everybody has access to this is how easy it is to opt in and enable this feature for real. Okay, let's do that real quick, so I gotta hop back over to satellite here. This is the satellite that we saw before, and I'll grab one of the hosts and we can use the new Web console feature that's part of Railly, and via single sign on I could jump right from satellite over to the Web console. So it's really, really easy. And I'LL grab a terminal here and registering with insights is really, really easy. Is one command troops, and what's happening right now is the box is going to gather some data. It's going to send it up to the cloud, and within just a minute or two, we're gonna have some results that we can look at back on the Web interface. >> I love it so it's just a single command and you're ready to register this box right now. That is super easy. Well, that's fantastic, >> Brent. We started this whole series of demonstrations by telling the audience that Red Hat Enterprise Lennox eight was the easiest, most economical and smartest operating system on the planet, period. And well, I think it's cute how you can go ahead and captain on a single machine. I'm going to show you one more thing. This is Answerable Tower. You can use as a bell tower to managing govern your answerable playbook, usage across your entire organization and with this. What I could do is on every single VM that was spun up here today. Opt in and register insights with a single click of a button. >> Okay, I want to see that right now. I know everyone's waiting for it as well, But hey, you're VM is ready. Josh. Lars? >> Yeah. My clock is running a little late now. Yeah, insights is a really cool feature >> of rail. And I've got it in all my images already. All >> right, I'm doing it all right. And so as this playbook runs across the inventory, I can see the machines registering on cloud that redhead dot com ready to be managed. >> OK, so all those onstage PM's as well as the hybrid cloud VM should be popping in IRC Post Chris equals Well, fantastic. >> That's awesome. Thanks to him. Nothing better than a Red Hat Summit speaker in the first live demo going off script deal. Uh, let's go back and take a look at some of those critical issues affecting a few of our systems here. So you can see this is a particular deanna's mask issue. It's going to affect a couple of machines. We saw that in the overview, and I can actually go and get some more details about what this particular issue is. So if you take a look at the right side of the screen there, there's actually a critical likelihood an impact that's associated with this particular issue. And what that really translates to is that there's a high level of risk to our organization from this particular issue. But also there's a low risk of change. And so what that means is that it's really, really safe for us to go ahead and use answerable to mediate this so I can grab the machines will select those two and we're mediate with answerable. I can create a new playbook. It's our maintenance window, but we'LL do something along the lines of like stuff Tim broke and that'LL be our cause. We name it whatever we want. So we'Ll create that playbook and take a look at it, and it's actually going to give us some details about the machines. You know what, what type of reboots Efendi you're going to be needed and what we need here. So we'LL go ahead and execute the playbook and what you're going to see is the outputs goingto happen in real time. So this is happening from the cloud were affecting machines. No matter where they are, they could be on Prem. They could be in a hybrid cloud, a public cloud or in a private cloud. And these things are gonna be remediated very, very easily with answerable. So it's really, really awesome. Everybody here with a red hat. Enterprise licks Lennox subscription has access to this now, so I >> kind of want >> everybody to go try this like, we really need to get this thing going and try it out right now. But >> don't know, sent about the room just yet. You get stay here >> for okay, Mr. Excitability, I think after this keynote, come back to the red hat booth and there's an optimization section. You can come talk to our insights engineers. And even though it's really easy to get going on your own, they can help you out. Answer any questions you might have. So >> this is really the start of a new era with an intelligent operating system and beauty with intelligence you just saw right now what insights that troubles you. Fantastic. So we're enabling systems administrators to manage more red in private clinics, a greater scale than ever before. I know there's a lot more we could show you, but we're totally out of time at this point, and we kind of, you know, when a little bit sideways here moments. But we need to get off the stage. But there's one thing I want you guys to think about it. All right? Do come check out the in the booth. Like Tim just said also in our debs, Get hands on red and a prize winning state as well. But really, I want you to think about this one human and a multitude of servers. And if you remember that one thing asked you upfront. Do you feel like you get a new superpower and redhead? Is your force multiplier? All right, well, thank you so much. Josh and Lars, Tim and Brent. Thank you. And let's get Paul back on stage. >> I went brilliant. No, it's just as always, >> amazing. I mean, as you can tell from last night were really, really proud of relate in that coming out here at the summit. And what a great way to showcase it. Thanks so much to you. Birth. Thanks, Brent. Tim, Lars and Josh. Just thanks again. So you've just seen this team demonstrate how impactful rail Khun b on your data center. So hopefully hopefully many of you. If not all of you have experienced that as well. But it was super computers. We hear about that all the time, as I just told you a few minutes ago, Lennox isn't just the foundation for enterprise and cloud computing. It's also the foundation for the fastest super computers in the world. In our next guest is here to tell us a lot more about that. >> Please welcome Lawrence Livermore National Laboratory. HPC solution Architect Robin Goldstone. >> Thank you so much, Robin. >> So welcome. Welcome to the summit. Welcome to Boston. And thank thank you so much for coming for joining us. Can you tell us a bit about the goals of Lawrence Livermore National Lab and how high high performance computing really works at this level? >> Sure. So Lawrence Livermore National >> Lab was established during the Cold War to address urgent national security needs by advancing the state of nuclear weapons, science and technology and high performance computing has always been one of our core capabilities. In fact, our very first supercomputer, ah Univac one was ordered by Edward Teller before our lab even opened back in nineteen fifty two. Our mission has evolved since then to cover a broad range of national security challenges. But first and foremost, our job is to ensure the safety, security and reliability of the nation's nuclear weapons stockpile. Oh, since the US no longer performs underground nuclear testing, our ability to certify the stockpile depends heavily on science based science space methods. We rely on H P C to simulate the behavior of complex weapons systems to ensure that they can function as expected, well beyond their intended life spans. That's actually great. >> So are you really are still running on that on that Univac? >> No, Actually, we we've moved on since then. So Sierra is Lawrence Livermore. Its latest and greatest supercomputer is currently the Seconds spastic supercomputer in the world and for the geeks in the audience, I think there's a few of them out there. We put up some of the specs of Syrah on the screen behind me, a couple of things worth highlighting our Sierra's peak performance and its power utilisation. So one hundred twenty five Pata flops of performance is equivalent to about twenty thousand of those Xbox one excess that you mentioned earlier and eleven point six megawatts of power required Operate Sierra is enough to power around eleven thousand homes. Syria is a very large and complex system, but underneath it all, it starts out as a collection of servers running Lin IX and more specifically, rail. >> So did Lawrence. Did Lawrence Livermore National Lab National Lab used Yisrael before >> Sierra? Oh, yeah, most definitely. So we've been running rail for a very long time on what I'll call our mid range HPC systems. So these clusters, built from commodity components, are sort of the bread and butter of our computer center. And running rail on these systems provides us with a continuity of operations and a common user environment across multiple generations of hardware. Also between Lawrence Livermore in our sister labs, Los Alamos and Sandia. Alongside these commodity clusters, though, we've always had one sort of world class supercomputer like Sierra. Historically, these systems have been built for a sort of exotic proprietary hardware running entirely closed source operating systems. Anytime something broke, which was often the Vander would be on the hook to fix it. And you know, >> that sounds >> like a good model, except that what we found overtime is most the issues that we have on these systems were either due to the extreme scale or the complexity of our workloads. Vendors seldom had a system anywhere near the size of ours, and we couldn't give them our classified codes. So their ability to reproduce our problem was was pretty limited. In some cases, they've even sent an engineer on site to try to reproduce our problems. But even then, sometimes we wouldn't get a fix for months or else they would just tell us they weren't going to fix the problem because we were the only ones having it. >> So for many of us, for many of us, the challenges is one of driving reasons for open source, you know, for even open source existing. How has how did Sierra change? Things are on open source for >> you. Sure. So when we developed our technical requirements for Sierra, we had an explicit requirement that we want to run an open source operating system and a strong preference for rail. At the time, IBM was working with red hat toe add support Terrell for their new little Indian power architecture. So it was really just natural for them to bid a red. A rail bay system for Sierra running Raylan Cyril allows us to leverage the model that's worked so well for us for all this time on our commodity clusters any packages that we build for X eighty six, we can now build those packages for power as well as our market texture using our internal build infrastructure. And while we have a formal support relationship with IBM, we can also tap our in house colonel developers to help debug complex problems are sys. Admin is Khun now work on any of our systems, including Sierra, without having toe pull out their cheat sheet of obscure proprietary commands. Our users get a consistent software environment across all our systems. And if the security vulnerability comes out, we don't have to chase around getting fixes from Multan slo es fenders. >> You know, you've been able, you've been able to extend your foundation from all the way from X eighty six all all the way to the extract excess Excuse scale supercomputing. We talk about giving customers all we talked about it all the time. A standard operational foundation to build upon. This isn't This isn't exactly what we've envisioned. So So what's next for you >> guys? Right. So what's next? So Sierra's just now going into production. But even so, we're already working on the contract for our next supercomputer called El Capitan. That's scheduled to be delivered the Lawrence Livermore in the twenty twenty two twenty timeframe. El Capitan is expected to be about ten times the performance of Sierra. I can't share any more details about that system right now, but we are hoping that we're going to be able to continue to build on a solid foundation. That relish provided us for well over a decade. >> Well, thank you so much for your support of realm over the years, Robin. And And thank you so much for coming and tell us about it today. And we can't wait to hear more about El Capitan. Thank you. Thank you very much. So now you know why we're so proud of realm. And while you saw confetti cannons and T shirt cannons last night, um, so you know, as as burned the team talked about the demo rail is the force multiplier for servers. We've made Lennox one of the most powerful platforms in the history of platforms. But just as Lennox has become a viable platform with access for everyone, and rail has become viable, more viable every day in the enterprise open source projects began to flourish around the operating system. And we needed to bring those projects to our enterprise customers in the form of products with the same trust models as we did with Ralph seeing the incredible progress of software development occurring around Lennox. Let's let's lead us to the next goal that we said tow, tow ourselves. That goal was to make hybrid cloud the default enterprise for the architecture. How many? How many of you out here in the audience or are Cesar are? HC sees how many out there a lot. A lot. You are the people that our building the next generation of computing the hybrid cloud, you know, again with like just like our goals around Lennox. This goals might seem a little daunting in the beginning, but as a community we've proved it time and time again. We are unstoppable. Let's talk a bit about what got us to the point we're at right right now and in the work that, as always, we still have in front of us. We've been on a decade long mission on this. Believe it or not, this mission was to build the capabilities needed around the Lenox operating system to really build and make the hybrid cloud. When we saw well, first taking hold in the enterprise, we knew that was just taking the first step. Because for a platform to really succeed, you need applications running on it. And to get those applications on your platform, you have to enable developers with the tools and run times for them to build, to build upon. Over the years, we've closed a few, if not a lot of those gaps, starting with the acquisition of J. Boss many years ago, all the way to the new Cuban Eddie's native code ready workspaces we launched just a few months back. We realized very early on that building a developer friendly platform was critical to the success of Lennox and open source in the enterprise. Shortly after this, the public cloud stormed onto the scene while our first focus as a company was done on premise in customer data centers, the public cloud was really beginning to take hold. Rehl very quickly became the standard across public clouds, just as it was in the enterprise, giving customers that common operating platform to build their applications upon ensuring that those applications could move between locations without ever having to change their code or operating model. With this new model of the data center spread across so many multiple environments, management had to be completely re sought and re architected. And given the fact that environments spanned multiple locations, management, real solid management became even more important. Customers deploying in hybrid architectures had to understand where their applications were running in how they were running, regardless of which infrastructure provider they they were running on. We invested over the years with management right alongside the platform, from satellite in the early days to cloud forms to cloud forms, insights and now answerable. We focused on having management to support the platform wherever it lives. Next came data, which is very tightly linked toe applications. Enterprise class applications tend to create tons of data and to have a common operating platform foyer applications. You need a storage solutions. That's Justus, flexible as that platform able to run on premise. Just a CZ. Well, as in the cloud, even across multiple clouds. This let us tow acquisitions like bluster, SEF perma bitch in Nubia, complimenting our Pratt platform with red hat storage for us, even though this sounds very condensed, this was a decade's worth of investment, all in preparation for building the hybrid cloud. Expanding the portfolio to cover the areas that a customer would depend on to deploy riel hybrid cloud architectures, finding any finding an amplifying the right open source project and technologies, or filling the gaps with some of these acquisitions. When that necessarily wasn't available by twenty fourteen, our foundation had expanded, but one big challenge remained workload portability. Virtual machine formats were fragmented across the various deployments and higher level framework such as Java e still very much depended on a significant amount of operating system configuration and then containers happened containers, despite having a very long being in existence for a very long time. As a technology exploded on the scene in twenty fourteen, Cooper Netease followed shortly after in twenty fifteen, allowing containers to span multiple locations and in one fell swoop containers became the killer technology to really enable the hybrid cloud. And here we are. Hybrid is really the on ly practical reality in way for customers and a red hat. We've been investing in all aspects of this over the last eight plus years to make our customers and partners successful in this model. We've worked with you both our customers and our partners building critical realm in open shift deployments. We've been constantly learning about what has caused problems and what has worked well in many cases. And while we've and while we've amassed a pretty big amount of expertise to solve most any challenge in in any area that stack, it takes more than just our own learning's to build the next generation platform. Today we're also introducing open shit for which is the culmination of those learnings. This is the next generation of the application platform. This is truly a platform that has been built with our customers and not simply just with our customers in mind. This is something that could only be possible in an open source development model and just like relish the force multiplier for servers. Open shift is the force multiplier for data centers across the hybrid cloud, allowing customers to build thousands of containers and operate them its scale. And we've also announced open shift, and we've also announced azure open shift. Last night. Satya on this stage talked about that in depth. This is all about extending our goals of a common operating platform enabling applications across the hybrid cloud, regardless of whether you run it yourself or just consume it as a service. And with this flagship release, we are also introducing operators, which is the central, which is the central feature here. We talked about this work last year with the operator framework, and today we're not going to just show you today. We're not going to just show you open shift for we're going to show you operators running at scale operators that will do updates and patches for you, letting you focus more of your time and running your infrastructure and running running your business. We want to make all this easier and intuitive. So let's have a quick look at how we're doing. Just that >> painting. I know all of you have heard we're talking to pretend to new >> customers about the travel out. So new plan. Just open it up as a service been launched by this summer. Look, I know this is a big quest for not very big team. I'm open to any and all ideas. >> Please welcome back to the stage. Red Hat Global director of developer Experience burst Sutter with Jessica Forrester and Daniel McPherson. All right, we're ready to do some more now. Now. Earlier we showed you read Enterprise Clinic St running on lots of different hardware like this hardware you see right now And we're also running across multiple cloud providers. But now we're going to move to another world of Lennox Containers. This is where you see open shift four on how you can manage large clusters of applications from eggs limits containers across the hybrid cloud. We're going to see this is where suffer operators fundamentally empower human operators and especially make ups and Deb work efficiently, more efficiently and effectively there together than ever before. Rights. We have to focus on the stage right now. They're represent ops in death, and we're gonna go see how they reeled in application together. Okay, so let me introduce you to Dan. Dan is totally representing all our ops folks in the audience here today, and he's telling my ops, comfort person Let's go to call him Mr Ops. So Dan, >> thanks for with open before, we had a much easier time setting up in maintaining our clusters. In large part, that's because open shit for has extended management of the clusters down to the infrastructure, the diversity kinds of parent. When you take >> a look at the open ship console, >> you can now see the machines that make up the cluster where machine represents the infrastructure. Underneath that Cooper, Eddie's node open shit for now handles provisioning Andy provisioning of those machines. From there, you could dig into it open ship node and see how it's configured and monitor how it's behaving. So >> I'm curious, >> though it does this work on bare metal infrastructure as well as virtualized infrastructure. >> Yeah, that's right. Burn So Pa Journal nodes, no eternal machines and open shit for can now manage it all. Something else we found extremely useful about open ship for is that it now has the ability to update itself. We can see this cluster hasn't update available and at the press of a button. Upgrades are responsible for updating. The entire platform includes the nodes, the control plane and even the operating system and real core arrests. All of this is possible because the infrastructure components and their configuration is now controlled by technology called operators. Thes software operators are responsible for aligning the cluster to a desired state. And all of this makes operational management of unopened ship cluster much simpler than ever before. All right, I >> love the fact that all that's been on one console Now you can see the full stack right all way down to the bare metal right there in that one console. Fantastic. So I wanted to scare us for a moment, though. And now let's talk to Deva, right? So Jessica here represents our all our developers in the room as my facts. He manages a large team of developers here Red hat. But more importantly, she represents our vice president development and has a large team that she has to worry about on a regular basis of Jessica. What can you show us? We'LL burn My team has hundreds of developers and were constantly under pressure to deliver value to our business. And frankly, we can't really wait for Dan and his ops team to provisioned the infrastructure and the services that we need to do our job. So we've chosen open shift as our platform to run our applications on. But until recently, we really struggled to find a reliable source of Cooper Netease Technologies that have the operational characteristics that Dan's going to actually let us install through the cluster. But now, with operator, How bio, we're really seeing the V ecosystem be unlocked. And the technology's there. Things that my team needs, its databases and message cues tracing and monitoring. And these operators are actually responsible for complex applications like Prometheus here. Okay, they're written in a variety of languages, danceable, but that is awesome. So I do see a number of options there already, and preaches is a great example. But >> how do you >> know that one? These operators really is mature enough and robust enough for Dan and the outside of the house. Wilbert, Here we have the operator maturity model, and this is going to tell me and my team whether this particular operator is going to do a basic install if it's going to upgrade that application over time through different versions or all the way out to full auto pilot, where it's automatically scaling and tuning the application based on the current environment. And it's very cool. So coming over toothy open shift Consul, now we can actually see Dan has made the sequel server operator available to me and my team. That's the database that we're using. A sequel server. That's a great example. So cynics over running here in the cluster? But this is a great example for a developer. What if I want to create a new secret server instance? Sure, we're so it's as easy as provisioning any other service from the developer catalog. We come in and I can type for sequel server on what this is actually creating is, ah, native resource called Sequel Server, and you can think of that like a promise that a sequel server will get created. The operator is going to see that resource, install the application and then manage it over its life cycle, KAL, and from this install it operators view, I can see the operators running in my project and which resource is its managing Okay, but I'm >> kind of missing >> something here. I see this custom resource here, the sequel server. But where the community's resource is like pods. Yeah, I think it's cool that we get this native resource now called Sequel Server. But if I need to, I can still come in and see the native communities. Resource is like your staple set in service here. Okay, that is fantastic. Now, we did say earlier on, though, like many of our customers in the audience right now, you have a large team of engineers. Lost a large team of developers you gotta handle. You gotta have more than one secret server, right? We do one for every team as we're developing, and we use a lot of other technologies running on open shift as well, including Tomcat and our Jenkins pipelines and our dough js app that is gonna actually talk to that sequel server database. Okay, so this point we can kind of provisions, Some of these? Yes. Oh, since all of this is self service for me and my team's, I'm actually gonna go and create one of all of those things I just said on all of our projects, right Now, if you just give me a minute, Okay? Well, right. So basically, you're going to knock down No Jazz Jenkins sequel server. All right, now, that's like hundreds of bits of application level infrastructure right now. Live. So, Dan, are you not terrified? Well, I >> guess I should have done a little bit better >> job of managing guests this quota and historically just can. I might have had some conflict here because creating all these new applications would admit my team now had a massive back like tickets to work on. But now, because of software operators, my human operators were able to run our infrastructure at scale. So since I'm long into the cluster here as the cluster admin, I get this view of pods across all projects. And so I get an idea of what's happening across the entire cluster. And so I could see now we have four hundred ninety four pods already running, and there's a few more still starting up. And if I scroll to the list, we can see the different workloads Jessica just mentioned of Tomcats. And no Gs is And Jenkins is and and Siegel servers down here too, you know, I see continues >> creating and you have, like, close to five hundred pods running >> there. So, yeah, filters list down by secret server, so we could just see. Okay, But >> aren't you not >> running going around a cluster capacity at some point? >> Actually, yeah, we we definitely have a limited capacity in this cluster. And so, luckily, though, we already set up auto scale er's And so because the additional workload was launching, we see now those outer scholars have kicked in and some new machines are being created that don't yet have noticed. I'm because they're still starting up. And so there's another good view of this as well, so you can see machine sets. We have one machine set per availability zone, and you could see the each one is now scaling from ten to twelve machines. And the way they all those killers working is for each availability zone, they will. If capacities needed, they will add additional machines to that availability zone and then later effect fast. He's no longer needed. It will automatically take those machines away. >> That is incredible. So right now we're auto scaling across multiple available zones based on load. Okay, so looks like capacity planning and automation is fully, you know, handle this point. But I >> do have >> another question for year logged in. Is the cluster admin right now into the console? Can you show us your view of >> operator suffer operators? Actually, there's a couple of unique views here for operators, for Cluster admits. The first of those is operator Hub. This is where a cluster admin gets the ability to curate the experience of what operators are available to users of the cluster. And so obviously we already have the secret server operator installed, which which we've been using. The other unique view is operator management. This gives a cluster I've been the ability to maintain the operators they've already installed. And so if we dig in and see the secret server operator, well, see, we haven't set up for manual approval. And what that means is if a new update comes in for a single server, then a cluster and we would have the ability to approve or disapprove with that update before installs into the cluster, we'LL actually and there isn't upgrade that's available. Uh, I should probably wait to install this, though we're in the middle of scaling out this cluster. And I really don't want to disturb Jessica's application. Workflow. >> Yeah, so, actually, Dan, it's fine. My app is already up. It's running. Let me show it to you over here. So this is our products application that's talking to that sequel server instance. And for debugging purposes, we can see which version of sequel server we're currently talking to. Its two point two right now. And then which pod? Since this is a cluster, there's more than one secret server pod we could be connected to. Okay, I could see right there the bounder screeners they know to point to. That's the version we have right now. But, you know, >> this is kind of >> point of software operators at this point. So, you know, everyone in this room, you know, wants to see you hit that upgrade button. Let's do it. Live here on stage. Right, then. All >> right. All right. I could see where this is going. So whenever you updated operator, it's just like any other resource on communities. And so the first thing that happens is the operator pot itself gets updated so we actually see a new version of the operator is currently being created now, and what's that gets created, the overseer will be terminated. And that point, the new, softer operator will notice. It's now responsible for managing lots of existing Siegel servers already in the environment. And so it's then going Teo update each of those sickle servers to match to the new version of the single server operator and so we could see it's running. And so if we switch now to the all projects view and we filter that list down by sequel server, then we should be able to see us. So lots of these sickle servers are now being created and the old ones are being terminated. So is the rolling update across the cluster? Exactly a So the secret server operator Deploy single server and an H A configuration. And it's on ly updates a single instance of secret server at a time, which means single server always left in nature configuration, and Jessica doesn't really have to worry about downtime with their applications. >> Yeah, that's awesome dance. So glad the team doesn't have to worry about >> that anymore and just got I think enough of these might have run by Now, if you try your app again might be updated. >> Let's see Jessica's application up here. All right. On laptop three. >> Here we go. >> Fantastic. And yet look, we're We're into two before we're onto three. Now we're on to victory. Excellent on. >> You know, I actually works so well. I don't even see a reason for us to leave this on manual approval. So I'm going to switch this automatic approval. And then in the future, if a new single server comes in, then we don't have to do anything, and it'll be all automatically updated on the cluster. >> That is absolutely fantastic. And so I was glad you guys got a chance to see that rolling update across the cluster. That is so cool. The Secret Service database being automated and fully updated. That is fantastic. Alright, so I can see how a software operator doesn't able. You don't manage hundreds if not thousands of applications. I know a lot of folks or interest in the back in infrastructure. Could you give us an example of the infrastructure >> behind this console? Yeah, absolutely. So we all know that open shift is designed that run in lots of different environments. But our teams think that as your redhead over, Schiff provides one of the best experiences by deeply integrating the open chief Resource is into the azure console, and it's even integrated into the azure command line toll and the easy open ship man. And, as was announced yesterday, it's now available for everyone to try out. And there's actually one more thing we wanted to show Everyone related to open shit, for this is all so new with a penchant for which is we now have multi cluster management. This gives you the ability to keep track of all your open shift environments, regardless of where they're running as well as you can create new clusters from here. And I'll dig into the azure cluster that we were just taking a look at. >> Okay, but is this user and face something have to install them one of my existing clusters? >> No, actually, this is the host of service that's provided by Red hat is part of cloud that redhead that calm and so all you have to do is log in with your red hair credentials to get access. >> That is incredible. So one console, one user experience to see across the entire hybrid cloud we saw earlier with Red update. Right and red embers. Thank Satan. Now we see it for multi cluster management. But home shift so you can fundamentally see. Now the suffer operators do finally change the game when it comes to making human operators vastly more productive and, more importantly, making Devon ops work more efficiently together than ever before. So we saw the rich ice vehicle system of those software operators. We can manage them across the Khyber Cloud with any, um, shift instance. And more importantly, I want to say Dan and Jessica for helping us with this demonstration. Okay, fantastic stuff, guys. Thank you so much. Let's get Paul back out here >> once again. Thanks >> so much to burn his team. Jessica and Dan. So you've just seen how open shift operators can help you manage hundreds, even thousands of applications. Install, upgrade, remove nodes, control everything about your application environment, virtual physical, all the way out to the cloud making, making things happen when the business demands it even at scale, because that's where it's going to get. Our next guest has lots of experience with demand at scale. and they're using open source container management to do it. Their work, their their their work building a successful cloud, First platform and there, the twenty nineteen Innovation Award winner. >> Please welcome twenty nineteen Innovation Award winner. Cole's senior vice president of technology, Rich Hodak. >> How you doing? Thanks. >> Thanks so much for coming out. We really appreciate it. So I guess you guys set some big goals, too. So can you baby tell us about the bold goal? Helped you personally help set for Cole's. And what inspired you to take that on? Yes. So it was twenty seventeen and life was pretty good. I had no gray hair and our business was, well, our tech was working well, and but we knew we'd have to do better into the future if we wanted to compete. Retails being disrupted. Our customers are asking for new experiences, So we set out on a goal to become an open hybrid cloud platform, and we chose Red had to partner with us on a lot of that. We set off on a three year journey. We're currently in Year two, and so far all KP eyes are on track, so it's been a great journey thus far. That's awesome. That's awesome. So So you Obviously, Obviously you think open source is the way to do cloud computing. So way absolutely agree with you on that point. So So what? What is it that's convinced you even more along? Yeah, So I think first and foremost wait, do we have a lot of traditional IAS fees? But we found that the open source partners actually are outpacing them with innovation. So I think that's where it starts for us. Um, secondly, we think there's maybe some financial upside to going more open source. We think we can maybe take some cost out unwind from these big fellas were in and thirdly, a CZ. We go to universities. We started hearing. Is we interviewed? Hey, what is Cole's doing with open source and way? Wanted to use that as a lever to help recruit talent. So I'm kind of excited, you know, we partner with Red Hat on open shift in in Rail and Gloucester and active M Q and answerable and lots of things. But we've also now launched our first open source projects. So it's really great to see this journey. We've been on. That's awesome, Rich. So you're in. You're in a high touch beta with with open shift for So what? What features and components or capabilities are you most excited about and looking forward to what? The launch and you know, and what? You know what? What are the something maybe some new goals that you might be able to accomplish with with the new features. And yeah, So I will tell you we're off to a great start with open shift. We've been on the platform for over a year now. We want an innovation award. We have this great team of engineers out here that have done some outstanding work. But certainly there's room to continue to mature that platform. It calls, and we're excited about open shift, for I think there's probably three things that were really looking forward to. One is we're looking forward to, ah, better upgrade process. And I think we saw, you know, some of that in the last demo. So upgrades have been kind of painful up until now. So we think that that that will help us. Um, number two, A lot of our open shift workloads today or the workloads. We run an open shifts are the stateless apse. Right? And we're really looking forward to moving more of our state full lapse into the platform. And then thirdly, I think that we've done a great job of automating a lot of the day. One stuff, you know, the provisioning of, of things. There's great opportunity o out there to do mohr automation for day two things. So to integrate mohr with our messaging systems in our database systems and so forth. So we, uh we're excited. Teo, get on board with the version for wear too. So, you know, I hope you, Khun, we can help you get to the next goals and we're going to continue to do that. Thank you. Thank you so much rich, you know, all the way from from rail toe open shift. It's really exciting for us, frankly, to see our products helping you solve World War were problems. What's you know what? Which is. Really? Why way do this and and getting into both of our goals. So thank you. Thank you very much. And thanks for your support. We really appreciate it. Thanks. It has all been amazing so far and we're not done. A critical part of being successful in the hybrid cloud is being successful in your data center with your own infrastructure. We've been helping our customers do that in these environments. For almost twenty years now, we've been running the most complex work loads in the world. But you know, while the public cloud has opened up tremendous possibilities, it also brings in another type of another layer of infrastructure complexity. So what's our next goal? Extend your extend your data center all the way to the edge while being as effective as you have been over the last twenty twenty years, when it's all at your own fingertips. First from a practical sense, Enterprises air going to have to have their own data centers in their own environment for a very long time. But there are advantages of being able to manage your own infrastructure that expand even beyond the public cloud all the way out to the edge. In fact, we talked about that very early on how technology advances in computer networking is storage are changing the physical boundaries of the data center every single day. The need, the need to process data at the source is becoming more and more critical. New use cases Air coming up every day. Self driving cars need to make the decisions on the fly. In the car factory processes are using a I need to adapt in real time. The factory floor has become the new edge of the data center, working with things like video analysis of a of A car's paint job as it comes off the line, where a massive amount of data is on ly needed for seconds in order to make critical decisions in real time. If we had to wait for the video to go up to the cloud and back, it would be too late. The damage would have already been done. The enterprise is being stretched to be able to process on site, whether it's in a car, a factory, a store or in eight or nine PM, usually involving massive amounts of data that just can't easily be moved. Just like these use cases couldn't be solved in private cloud alone because of things like blatant see on data movement, toe address, real time and requirements. They also can't be solved in public cloud alone. This is why open hybrid is really the model that's needed in the only model forward. So how do you address this class of workload that requires all of the above running at the edge? With the latest technology all its scale, let me give you a bit of a preview of what we're working on. We are taking our open hybrid cloud technologies to the edge, Integrated with integrated with Aro AM Hardware Partners. This is a preview of a solution that will contain red had open shift self storage in K V M virtual ization with Red Hat Enterprise Lennox at the core, all running on pre configured hardware. The first hardware out of the out of the gate will be with our long time. Oh, am partner Del Technologies. So let's bring back burn the team to see what's right around the corner. >> Please welcome back to the stage. Red Hat. Global director of developer Experience burst Sutter with Kareema Sharma. Okay, We just how was your Foreign operators have redefined the capabilities and usability of the open hybrid cloud, and now we're going to show you a few more things. Okay, so just be ready for that. But I know many of our customers in this audience right now, as well as the customers who aren't even here today. You're running tens of thousands of applications on open chef clusters. We know that disappearing right now, but we also know that >> you're not >> actually in the business of running terminators clusters. You're in the business of oil and gas from the business retail. You're in a business transportation, you're in some other business and you don't really want to manage those things at all. We also know though you have lo latest requirements like Polish is talking about. And you also dated gravity concerns where you >> need to keep >> that on your premises. So what you're about to see right now in this demonstration is where we've taken open ship for and made a bare metal cluster right here on this stage. This is a fully automated platform. There is no underlying hyper visor below this platform. It's open ship running on bare metal. And this is your crew vanities. Native infrastructure, where we brought together via mes containers networking and storage with me right now is green mush arma. She's one of her engineering leaders responsible for infrastructure technologies. Please welcome to the stage, Karima. >> Thank you. My pleasure to be here, whether it had summit. So let's start a cloud. Rid her dot com and here we can see the classroom Dannon Jessica working on just a few moments ago From here we have a bird's eye view ofthe all of our open ship plasters across the hybrid cloud from multiple cloud providers to on premises and noticed the spare medal last year. Well, that's the one that my team built right here on this stage. So let's go ahead and open the admin console for that last year. Now, in this demo, we'LL take a look at three things. A multi plaster inventory for the open Harbor cloud at cloud redhead dot com. Second open shift container storage, providing convert storage for virtual machines and containers and the same functionality for cloud vert and bare metal. And third, everything we see here is scuba unit is native, so by plugging directly into communities, orchestration begin common storage. Let working on monitoring facilities now. Last year, we saw how continue native actualization and Q Bert allow you to run virtual machines on Cabinet is an open shift, allowing for a single converge platform to manage both containers and virtual machines. So here I have this dark net project now from last year behead of induced virtual machine running it S P darknet application, and we had started to modernize and continue. Arise it by moving. Parts of the application from the windows began to the next containers. So let's take a look at it here. I have it again. >> Oh, large shirt, you windows. Earlier on, I was playing this game back stage, so it's just playing a little solitaire. Sorry about that. >> So we don't really have time for that right now. Birds. But as I was saying, Over here, I have Visions Studio Now the window's virtual machine is just another container and open shift and the i d be service for the virtual machine. It's just another service in open shift open shifts. Running both containers and virtual machines together opens a whole new world of possibilities. But why stop there? So this here be broadened to come in. It is native infrastructure as our vision to redefine the operation's off on premises infrastructure, and this applies to all matters of workloads. Using open shift on metal running all the way from the data center to the edge. No by your desk, right to main benefits. Want to help reduce the operation casts And second, to help bring advance good when it is orchestration concept to your infrastructure. So next, let's take a look at storage. So open shift container storage is software defined storage, providing the same functionality for both the public and the private lads. By leveraging the operator framework, open shift container storage automatically detects the available hardware configuration to utilize the discs in the most optimal vein. So then adding my note, you don't have to think about how to balance the storage. Storage is just another service running an open shift. >> And I really love this dashboard quite honestly, because I love seeing all the storage right here. So I'm kind of curious, though. Karima. What kind of storage would you What, What kind of applications would you use with the storage? >> Yeah, so this is the persistent storage. To be used by a database is your files and any data from applications such as a Magic Africa. Now the A Patrick after operator uses school, been at this for scheduling and high availability, and it uses open shift containers. Shortest. Restore the messages now Here are on premises. System is running a caf co workload streaming sensor data on DH. We want toe sort it and act on it locally, right In a minute. A place where maybe we need low latency or maybe in a data lake like situation. So we don't want to send the starter to the cloud. Instead, we want to act on it locally, right? Let's look at the griffon a dashboard and see how our system is doing so with the incoming message rate of about four hundred messages for second, the system seems to be performing well, right? I want to emphasize this is a fully integrated system. We're doing the testing An optimization sze so that the system can Artoo tune itself based on the applications. >> Okay, I love the automated operations. Now I am a curious because I know other folks in the audience want to know this too. What? Can you tell us more about how there's truly integrated communities can give us an example of that? >> Yes. Again, You know, I want to emphasize everything here is managed poorly by communities on open shift. Right. So you can really use the latest coolest to manage them. All right. Next, let's take a look at how easy it is to use K native with azure functions to script alive Reaction to a live migration event. >> Okay, Native is a great example. If actually were part of my breakout session yesterday, you saw me demonstrate came native. And actually, if you want to get hands on with it tonight, you can come to our guru night at five PM and actually get hands on like a native. So I really have enjoyed using K. Dated myself as a software developer. And but I am curious about the azure functions component. >> Yeah, so as your functions is a function is a service engine developed by Microsoft fully open source, and it runs on top of communities. So it works really well with our on premises open shift here. Right now, I have a simple azure function that I already have here and this azure function, you know, Let's see if this will send out a tweet every time we live My greater Windows virtual machine. Right. So I have it integrated with open shift on DH. Let's move a note to maintenance to see what happens. So >> basically has that via moves. We're going to see the event triggered. They trigger the function. >> Yeah, important point I want to make again here. Windows virtue in machines are equal citizens inside of open shift. We're investing heavily in automation through the use of the operator framework and also providing integration with the hardware. Right, So next, Now let's move that note to maintain it. >> But let's be very clear here. I wanna make sure you understand one thing, and that is there is no underlying virtual ization software here. This is open ship running on bear. Meddle with these bare metal host. >> That is absolutely right. The system can automatically discover the bare metal hosts. All right, so here, let's move this note to maintenance. So I start them Internets now. But what will happen at this point is storage will heal itself, and communities will bring back the same level of service for the CAFTA application by launching a part on another note and the virtual machine belive my great right and this will create communities events. So we can see. You know, the events in the event stream changes have started to happen. And as a result of this migration, the key native function will send out a tweet to confirm that could win. It is native infrastructure has indeed done the migration for the live Ian. Right? >> See the events rolling through right there? >> Yeah. All right. And if we go to Twitter? >> All right, we got tweets. Fantastic. >> And here we can see the source Nord report. Migration has succeeded. It's a pretty cool stuff right here. No. So we want to bring you a cloud like experience, but this means is we're making operational ease a fuse as a top goal. We're investing heavily in encapsulating management knowledge and working to pre certify hardware configuration in working with their partners such as Dell, and they're dead already. Note program so that we can provide you guidance on specific benchmarks for specific work loads on our auto tuning system. >> All right, well, this is tow. I know right now, you're right thing, and I want to jump on the stage and check out the spare metal cluster. But you should not right. Wait After the keynote didn't. Come on, check it out. But also, I want you to go out there and think about visiting our partner Del and their booth where they have one. These clusters also. Okay, So this is where vmc networking and containers the storage all come together And a Kurban in his native infrastructure. You've seen right here on this stage, but an agreement. You have a bit more. >> Yes. So this is literally the cloud coming down from the heavens to us. >> Okay? Right here, Right now. >> Right here, right now. So, to close the loop, you can have your plaster connected to cloud redhead dot com for our insights inside reliability engineering services so that we can proactively provide you with the guidance through automated analyses of telemetry in logs and help flag a problem even before you notice you have it Beat software, hardware, performance, our security. And one more thing. I want to congratulate the engineers behind the school technology. >> Absolutely. There's a lot of engineers here that worked on this cluster and worked on the stack. Absolutely. Thank you. Really awesome stuff. And again do go check out our partner Dale. They're just out that door I can see them from here. They have one. These clusters get a chance to talk to them about how to run your open shift for on a bare metal cluster as well. Right, Kareema, Thank you so much. That was totally awesome. We're at a time, and we got to turn this back over to Paul. >> Thank you. Right. >> Okay. Okay. Thanks >> again. Burned, Kareema. Awesome. You know, So even with all the exciting capabilities that you're seeing, I want to take a moment to go back to the to the first platform tenant that we learned with rail, that the platform has to be developer friendly. Our next guest knows something about connecting a technology like open shift to their developers and part of their company. Wide transformation and their ability to shift the business that helped them helped them make take advantage of the innovation. Their Innovation award winner this year. Please, Let's welcome Ed to the stage. >> Please welcome. Twenty nineteen. Innovation Award winner. BP Vice President, Digital transformation. Ed Alford. >> Thanks, Ed. How your fake Good. So was full. Get right into it. What we go you guys trying to accomplish at BP and and How is the goal really important in mandatory within your organization? Support on everyone else were global energy >> business, with operations and over seventy countries. Andi. We've embraced what we call the jewel challenge, which is increasing the mind for energy that we have as individuals in the world. But we need to produce the energy with fuel emissions. It's part of that. One of our strategic priorities that we >> have is to modernize the whole group on. That means simplifying our processes and enhancing >> productivity through digital solutions. So we're using chlo based technologies >> on, more importantly, open source technologies to clear a community and say, the whole group that collaborates effectively and efficiently and uses our data and expertise to embrace the jewel challenge and actually try and help solve that problem. That's great. So So how did these heart of these new ways of working benefit your team and really the entire organ, maybe even the company as a whole? So we've been given the Innovation Award for Digital conveyor both in the way it was created and also in water is delivering a couple of guys in the audience poll costal and brewskies as he they they're in the team. Their teams developed that convey here, using our jail and Dev ops and some things. We talk about this stuff a lot, but actually the they did it in a truly our jail and develops we, um that enabled them to experiment and walking with different ways. And highlight in the skill set is that we, as a group required in order to transform using these approaches, we can no move things from ideation to scale and weeks and days sometimes rather than months. Andi, I think that if we can take what they've done on DH, use more open source technology, we contain that technology and apply across the whole group to tackle this Jill challenge. And I think that we use technologists and it's really cool. I think that we can no use technology and open source technology to solve some of these big challenges that we have and actually just preserve the planet in a better way. So So what's the next step for you guys at BP? So moving forward, we we are embracing ourselves, bracing a clothed, forced organization. We need to continue to live to deliver on our strategy, build >> over the technology across the entire group to address the jewel >> challenge and continue to make some of these bold changes and actually get into and really use. Our technology is, I said, too addresses you'LL challenge and make the future of our planet a better place for ourselves and our children and our children's children. That's that's a big goal. But thank you so much, Ed. Thanks for your support. And thanks for coming today. Thank you very much. Thank you. Now comes the part that, frankly, I think his best part of the best part of this presentation We're going to meet the type of person that makes all of these things a reality. This tip this type of person typically works for one of our customers or with one of with one of our customers as a partner to help them make the kinds of bold goals like you've heard about today and the ones you'll hear about Maura the way more in the >> week. I think the thing I like most about it is you feel that reward Just helping people I mean and helping people with stuff you enjoy right with computers. My dad was the math and science teacher at the local high school. And so in the early eighties, that kind of met here, the default person. So he's always bringing in a computer stuff, and I started a pretty young age. What Jason's been able to do here is Mohr evangelize a lot of the technologies between different teams. I think a lot of it comes from the training and his certifications that he's got. He's always concerned about their experience, how easy it is for them to get applications written, how easy it is for them to get them up and running at the end of the day. We're a loan company, you know. That's way we lean on accounting like red. That's where we get our support front. That's why we decided to go with a product like open shift. I really, really like to product. So I went down. The certification are out in the training ground to learn more about open shit itself. So my daughter's teacher, they were doing a day of coding, and so they asked me if I wanted to come and talk about what I do and then spend the day helping the kids do their coding class. The people that we have on our teams, like Jason, are what make us better than our competitors, right? Anybody could buy something off the shelf. It's people like him. They're able to take that and mold it into something that then it is a great offering for our partners and for >> customers. Please welcome Red Hat Certified Professional of the Year Jason Hyatt. >> Jason, Congratulations. Congratulations. What a what a big day, huh? What a really big day. You know, it's great. It's great to see such work, You know that you've done here. But you know what's really great and shows out in your video It's really especially rewarding. Tow us. And I'm sure to you as well to see how skills can open doors for for one for young women, like your daughters who already loves technology. So I'd liketo I'd like to present this to you right now. Take congratulations. Congratulations. Good. And we I know you're going to bring this passion. I know you bring this in, everything you do. So >> it's this Congratulations again. Thanks, Paul. It's been really exciting, and I was really excited to bring my family here to show the experience. It's it's >> really great. It's really great to see him all here as well going. Maybe we could you could You guys could stand up. So before we leave before we leave the stage, you know, I just wanted to ask, What's the most important skill that you'LL pass on from all your training to the future generations? >> So I think the most important thing is you have to be a continuous learner you can't really settle for. Ah, you can't be comfortable on learning, which I already know. You have to really drive a continuous Lerner. And of course, you got to use the I ninety. Maxwell. Quite. >> I don't even have to ask you the question. Of course. Right. Of course. That's awesome. That's awesome. And thank you. Thank you for everything, for everything that you're doing. So thanks again. Thank you. You know what makes open source work is passion and people that apply those considerable talents that passion like Jason here to making it worked and to contribute their idea there. There's back. And believe me, it's really an impressive group of people. You know you're family and especially Berkeley in the video. I hope you know that the redhead, the certified of the year is the best of the best. The cream of the crop and your dad is the best of the best of that. So you should be very, very happy for that. I also and I also can't wait. Teo, I also can't wait to come back here on this stage ten years from now and present that same award to you. Berkeley. So great. You should be proud. You know, everything you've heard about today is just a small representation of what's ahead of us. We've had us. We've had a set of goals and realize some bold goals over the last number of years that have gotten us to where we are today. Just to recap those bold goals First bait build a company based solely on open source software. It seems so logical now, but it had never been done before. Next building the operating system of the future that's going to run in power. The enterprise making the standard base platform in the op in the Enterprise Olympics based operating system. And after that making hybrid cloud the architecture of the future make hybrid the new data center, all leading to the largest software acquisition in history. Think about it around us around a company with one hundred percent open source DNA without. Throughout. Despite all the fun we encountered over those last seventeen years, I have to ask, Is there really any question that open source has won? Realizing our bold goals and changing the way software is developed in the commercial world was what we set out to do from the first day in the Red Hat was born. But we only got to that goal because of you. Many of you contributors, many of you knew toe open source software and willing to take the risk along side of us and many of partners on that journey, both inside and outside of Red Hat. Going forward with the reach of IBM, Red hat will accelerate. Even Mohr. This will bring open source general innovation to the next generation hybrid data center, continuing on our original mission and goal to bring open source technology toe every corner of the planet. What I what I just went through in the last hour Soul, while mind boggling to many of us in the room who have had a front row seat to this overto last seventeen plus years has only been red hats. First step. Think about it. We have brought open source development from a niche player to the dominant development model in software and beyond. Open Source is now the cornerstone of the multi billion dollar enterprise software world and even the next generation hybrid act. Architecture would not even be possible without Lennox at the core in the open innovation that it feeds to build around it. This is not just a step forward for software. It's a huge leap in the technology world beyond even what the original pioneers of open source ever could have imagined. We have. We have witnessed open source accomplished in the last seventeen years more than what most people will see in their career. Or maybe even a lifetime open source has forever changed the boundaries of what will be possible in technology in the future. And in the one last thing to say, it's everybody in this room and beyond. Everyone outside continue the mission. Thanks have a great sum. It's great to see it
SUMMARY :
Ladies and gentlemen, please welcome Red Hat President Products and Technologies. Kennedy setting the gold to the American people to go to the moon. that point I knew that despite the promise of Lennox, we had a lot of work ahead of us. So it is an honor for me to be able to show it to you live on stage today. And we're not about the clinic's eight. And Morgan, There's windows. That means that for the first time, you can log in from any device Because that's the standard Lennox off site. I love the dashboard overview of the system, You see the load of the system, some some of its properties. So what about if I have to add a whole new application to this environment? Which the way for you to install different versions of your half stack that That is fantastic and the application streams Want to keep up with the fast moving ecosystems off programming I know some people were thinking it right now. everyone you want two or three or whichever your application needs. And I'm going to the rat knowledge base and looking up things like, you know, PV create VD, I've opened the storage space for you right here, where you see an overview of your storage. you know, we'll have another question for you. you know a lot of people, including me and people in the audience like that dark out right? much easier, including a post gra seeker and, of course, the python that we saw right there. Yeah, absolutely. And it's saved so that you don't actually have to know all the various incantations from Amazon I All right, Well, if you want to prevent a holy war in your system, you can actually use satellite to filter that out. Okay, So this VM image we just created right now from that blueprint this is now I can actually go out there and easily so you can really hit your Clyburn hybrid cloud operating system images. and I just need a few moments for it to build. So while that's taking a few moments, I know there's another key question in the minds of the audience right now, You see all my relate machines here, including the one I showed you what Consul on before. Okay, okay, so now it's progressing. it's progressing. live upgrade on stage. Detective that and you know, it doesn't run the Afghan cause we don't support operating that. So the good news is, we were protected from possible failed upgrade there, That's the idea. And I really love what you showed us there. So you were away for so long. So the really cool thing about this bird is that all of these images were built So thank you so much for that large. more to talk to you about. I'm going to show you here a satellite inventory and his So he's all the machines can get updated in one fell swoop. And there's one thing that I want to bring your attention to today because it's brand new. I know that in the minds of the audience right now. I've actually been waiting for a while patiently for you to get to the really good stuff. there's one more thing that I wanted to let folks know about. next eight and some features that we have there. So, actually, one of the key design principles of relate is working with our customers over the last twenty years to integrate OK, so we basically have this new feature. So And this is this list is growing every single day, so customers can actually opt in to the rules that are most But it comes to CVS and things that nature. This is the satellite that we saw before, and I'll grab one of the hosts and I love it so it's just a single command and you're ready to register this box right now. I'm going to show you one more thing. I know everyone's waiting for it as well, But hey, you're VM is ready. Yeah, insights is a really cool feature And I've got it in all my images already. the machines registering on cloud that redhead dot com ready to be managed. OK, so all those onstage PM's as well as the hybrid cloud VM should be popping in IRC Post Chris equals Well, We saw that in the overview, and I can actually go and get some more details about what this everybody to go try this like, we really need to get this thing going and try it out right now. don't know, sent about the room just yet. And even though it's really easy to get going on and we kind of, you know, when a little bit sideways here moments. I went brilliant. We hear about that all the time, as I just told Please welcome Lawrence Livermore National Laboratory. And thank thank you so much for coming for But first and foremost, our job is to ensure the safety, and for the geeks in the audience, I think there's a few of them out there. before And you know, Vendors seldom had a system anywhere near the size of ours, and we couldn't give them our classified open source, you know, for even open source existing. And if the security vulnerability comes out, we don't have to chase around getting fixes from Multan slo all the way to the extract excess Excuse scale supercomputing. share any more details about that system right now, but we are hoping that we're going to be able of the data center spread across so many multiple environments, management had to be I know all of you have heard we're talking to pretend to new customers about the travel out. Earlier we showed you read Enterprise Clinic St running on lots of In large part, that's because open shit for has extended management of the clusters down to the infrastructure, you can now see the machines that make up the cluster where machine represents the infrastructure. Thes software operators are responsible for aligning the cluster to a desired state. of Cooper Netease Technologies that have the operational characteristics that Dan's going to actually let us has made the sequel server operator available to me and my team. Okay, so this point we can kind of provisions, And if I scroll to the list, we can see the different workloads Jessica just mentioned Okay, But And the way they all those killers working is Okay, so looks like capacity planning and automation is fully, you know, handle this point. Is the cluster admin right now into the console? This gives a cluster I've been the ability to maintain the operators they've already installed. So this is our products application that's talking to that sequel server instance. So, you know, everyone in this room, you know, wants to see you hit that upgrade button. And that point, the new, softer operator will notice. So glad the team doesn't have to worry about that anymore and just got I think enough of these might have run by Now, if you try your app again Let's see Jessica's application up here. And yet look, we're We're into two before we're onto three. So I'm going to switch this automatic approval. And so I was glad you guys got a chance to see that rolling update across the cluster. And I'll dig into the azure cluster that we were just taking a look at. all you have to do is log in with your red hair credentials to get access. So one console, one user experience to see across the entire hybrid cloud we saw earlier with Red Thanks so much to burn his team. of technology, Rich Hodak. How you doing? center all the way to the edge while being as effective as you have been over of the open hybrid cloud, and now we're going to show you a few more things. You're in the business of oil and gas from the business retail. And this is your crew vanities. Well, that's the one that my team built right here on this stage. Oh, large shirt, you windows. open shift container storage automatically detects the available hardware configuration to What kind of storage would you What, What kind of applications would you use with the storage? four hundred messages for second, the system seems to be performing well, right? Now I am a curious because I know other folks in the audience want to know this too. So you can really use the latest coolest to manage And but I am curious about the azure functions component. and this azure function, you know, Let's see if this will We're going to see the event triggered. So next, Now let's move that note to maintain it. I wanna make sure you understand one thing, and that is there is no underlying virtual ization software here. You know, the events in the event stream changes have started to happen. And if we go to Twitter? All right, we got tweets. No. So we want to bring you a cloud like experience, but this means is I want you to go out there and think about visiting our partner Del and their booth where they have one. Right here, Right now. So, to close the loop, you can have your plaster connected to cloud redhead These clusters get a chance to talk to them about how to run your open shift for on a bare metal Thank you. rail, that the platform has to be developer friendly. Please welcome. What we go you guys trying to accomplish at BP and and How is the goal One of our strategic priorities that we have is to modernize the whole group on. So we're using chlo based technologies And highlight in the skill part of this presentation We're going to meet the type of person that makes And so in the early eighties, welcome Red Hat Certified Professional of the Year Jason Hyatt. So I'd liketo I'd like to present this to you right now. to bring my family here to show the experience. before we leave before we leave the stage, you know, I just wanted to ask, What's the most important So I think the most important thing is you have to be a continuous learner you can't really settle for. And in the one last thing to say, it's everybody in this room and
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Dave Russell, Veeam | IBM Think 2019
>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Welcome back. We're here in Moscow, named North for IBM. Think twenty nineteen. I'm stupid. I'm unhappy. Toe. Welcome back to the program. A cube alone. Dave Russell, who is the vice president of enterprise strategy with Team and IBM partner Dave. Thanks so much for joining us. >> Hey, thank you for having against two. >> All right, S o. You know, big thing we're talking about here of the show. It's hybrid cloud. It's multi cloud and IBM, you know, spent, you know, big money to make acquisitions in the space to be there. Multi club. Something I've been hearing from theme for a number of years. Talk to us about kind of the relevant. Why beams here at this show? And we'll get into it from there. >> Yeah, absolutely. You know, So I've been traveling the world. Really? You mentioned Barcelona just a moment ago. Been? You know, Barcelona, Vegas, a number of other cities really pitching beams, multi cloud capabilities and story. And the short version of it is we believe that all organizations are really multi cloud today. Whether they realize it or not, they're going to be more multi cloud in the future. And what I mean by that is if you think about availability, backup in recovery and replication, you know it's a Zurich zur stack. It's a ws. It's private cloud. It's obviously what you have on premise, and it's the stuff you haven't even thought about tomorrow. And you. If you want to make a little adjacent stretch, you can put software is a service. I think in there, too, So it's about really offering protection, but also portability. >> Yeah, absolutely. When you have that multi cloud world world, of course, data is one of the most important things and how to lie for you. No protect and secure my data and leverage that data is critically important. IBM has a lot of different pieces. Where's the intersection between vehement IBM? >> Yeah, it's actually pretty exhaustive. So I'm a former I B M for fifteen plus years still live in Tucson, where IBM storage has a big presence and, you know, so it's everything from tape. We still believe Tape has a role to play, by the way, actually just released some new tape capabilities. It's, of course, the servers that they offer, and as well as the GTS Global Services and IBM cloud, of course, were interact with but their storage raise their virtual ization solutions. All of that. We have hooks and integration into today. >> Yeah, IBM have a pretty broad and deep portfolio, so lots of places for for being too play Dave. If he had an announcement recently updated, you were just alluding to some of the function of what? Why do you walk us through what the latest is? >> Yeah, it's actually the largest in company's history, which is now eleven years shipping product as of today, which is three weeks ago today we released the product, but as of today, there's sixty four thousand downloads that's against the base of three hundred thirty thousand ish customers might be three hundred thirty two thousand, but sixty four thousand dollars in exactly three weeks. Couple of capabilities from a cloud perspective alone. We've got this kind of probability that we spoke about take any workload on premises or physical virtual that's running in your shop and to be able to move it somewhere else. Really, to click restores to be able to get Teo Zura zur Stak E. W s. From an IBM perspective, we can definitely support IBM cloud in that we've got beam availability suite for a W s, where we can take instances running in a Ws like Mongo to be Cassandra and bring that back. You may want to bring that back for safekeeping or even transformation on prime two of'em instance, we've got all kinds of interesting things to not least of which is called cloud Tear. It sounds like an archive solution. It's it's really not. We underneath the covers take what's on running on premises for you. Let's say you're a beam shop today, and we can take out those unused blocks, unbeknownst to you and stage als off objects storage. And we can optimize how we do that. Right? So we can make sure you avoid egress charges. We essentially short version of that is in active source side D duplication of optimizing the blocks in the cloud. And then we leave uninterrupted access to it on prime. You don't ever have to know what's in the cloud. Change your behaviour. Changed the application to update it. Those are just a couple of the many things that we introduced. >> Well, yeah, quite a few things there, Dave. You know, in a multi cloud world. Can you bring us inside the customers? You know, Who is it that teams working with there? You know, cloud architect. Seems like it would be different than kind of the traditional, you know, storage or system administrator there. You know, one of the things we worry about in a multi cloud worlds is I've got different skill sets I need for all of these and how their organizations manage that. And, you know, how is the organization shaping up? >> Well, today You're right. It can be dispersed people, you know, disparity, folks. You know, it could be the software as a service person. It could be someone that's used to thinking, say, a ws. And I know when we go as a company to ignite their conference when we go there because, Ah, company Ricard called and two ws that specializes in that the people that come up to that desk don't even know who I mean. So >> reinvent your saying for all it was on >> my bed yet. So, you know, they don't even know the on premise, right? They only know what their specific focuses. And so, you know, we interact with a multitude of different roles where they tend to unite is vice president of infrastructure. But it could be many different touch points. I think is an organization. If you're especially a C i. O, you're probably a little bit worried about how many different things are going on there. Can we have a common management plain? >> Yeah. One of the areas that's really interesting. We talk about the public clouds. IBM has a long tradition with kind of C. S, P. S and M s bees, the service providers ahs. You will where does seem interacted at that layer of the ecosystem. Yeah, >> well, we have really twenty one thousand different being cloud service providers today, some of which manage over one million different machine instances just themselves. So we did a number of actually updates for them as well. And that's actually one of the tape integration points we now offer tenant to tape ifyou're a cloud service provider to offer an additional capability. But we offered, you know, the engine, if you will, that people can build it back up as a service disaster, recovery as a service, a solution around. >> Okay. Excellent. And thiss new release. What was it called? Yeah. >> It's a long name. Its aversion nine dot five update for >> that That screams major release. Yeah, >> well, it's the importance of it belies the, you know, the Newman clincher. But, you know, the reality is it's the biggest in our history. >> Yeah. So, Dave, give us a little insight. You know, you're doing the presentation here at IBM. Think give us some of the the team present where we're going to be seeing the bright green throughout the show. >> Yeah. Yeah. So there's been a couple of different things taking place already. I'm really going to hit multi cloud. Very, very hard. Really? From a how you should think about. So I really intended to be so much a beam commercial we'll talk about, you know, unabashedly, what being capabilities are but really set up a thought process. You know, a framework I get to kind of play a little bit of my analyst role, but, well, how much you want, You know, approach this. >> Yeah. David, I'm glad you brought it up. I love when you get here. We put your analyst hat roll on. We can. You know, talk is analysts here when I look at multi cloud networking. Management and security have just been this challenge we've been looking at. We've made progress as a whole, but there's still a lot of concerns. And, you know, multi cod sure isn't simple for the enterprise today. Ah, where we doing well is an industry. I know there's some areas that Beam has specific expertise to help on DH solutions, but I won't give a critical eyes, too. You know, what we need to do is an industry as a whole to make things better for customers, You >> know, the number one thing I would say is have a design, have a plan, don't fall into this haphazard. And one of the reasons I assert that just about every organization is multi cloud is because no matter what size you are, somebody somewhere has deployed something in a cloud or two or more. And again, if you throw software is a service into that. Now, this's just geometrically expanded. But it hasn't been like a conscious design strategy. >> Yeah, in many ways that we used to talk about shadow it Teo and many thie old. It was we used to call it either silos or cylinders of excellent, depending on the organization that you lived into. The concern I have is we're kind of rebuilding these in the cloud. So how we've learned from the past, our customers, you know, the CEOs, the organization's getting a better handle around their environment today. Or are we failed to do what was done in the past? >> I think we're getting incrementally better. Obviously, some organizations are, you know, accelerating faster than others. I think initially, when people thought, well, I can lift and shift and life will be better. You know, I can just like I introduce server virtual ization. Now, everything's cheaper, and I'm going to spend a lot of money to do that, you know? Well, I'm going to go to the cloud. It's going to be cheaper. And I just doing the same exact capabilities, instances and deployment that I was doing before never really worked out. So I think if you're approaching us something fresh and new and trying to actually take advantage of those capabilities here in a better position. >> Yeah. So I had a really interesting discussion earlier today. Had had the heads of V M wears cloud a group in an IBM cloud on. Of course, one of them comes up is you know, are we just lifting and shifting or re transforming and how to developers fit into it? So I'd love to hear from a beam standpoint as that, you know, application, maturity and modernization happens. You know What? What does that mean to the VM portfolio? >> Well, I would be really exciting if we do see more of a development base because I think really then you can add on extensions to what? Today the team is a data capture retention engine. It's best known for backup in recovery, disaster, recovery. But it could be so much more than that. So just a quick commercial button integration. Answer your question of we can now stand up ad hoc, isolated instances of machines and you can run things on that like GDP are scrubbing. You know, you can also do what we call a secure restore you, Khun. Understand? Well or not, it has a virus associated with it before populated back into the environment. But as a application community, you may want to say tomorrow morning at ten AM I want thes ten servers stood up with fresh data so my team could go in there and now generate faster applications for the business. It's really a business transformation St That's why I think we need more developers. >> Yeah, I remember one of the demons I attended, the CTO of Microsoft came, and you handed out his book, which I read recently, and it was kind of that they called it. It's not like science fact. But, you know, you talked about about cyber security and the challenge we faced in, you know? Okay. The global terrorists are going to come, you know, wipe out, you know, the entire infrastructure, and it's a little bit close to home, you know, because you kind of understand the security threat. Where does seem fit into the security picture when it when it comes to multi cloud things like Ransomware and the like, >> Yeah, unfortunately, things are going to happen. And we know this because things are already happen to number of organizations. It doesn't, you know, really take too long to find somebody that's been affected by this already. And so when that happens, you need some first level step of remediation. You need to get back as fast as you can to known. Good copy of your data. You know, Certainly that's where beam comes in, but being ableto also have portability. What if we could go and take your Azzurri instance data? Do the bios conversion for you automatically and send that to Amazon or vice versa. So you can have another offline, baldheaded copy. Or, you know, in that ransom where notion I presented to you. You know what? If you have to go backto backups, put ransomware typically lies dormant before it actually deploys the payload. So you don't know exactly how far back you need to go. So with this capability, you could go back on ly so far as you need to me Because you could verify exactly when vulnerability was introduced. But do that in a way that's sandbox isolated off the network and not putting you at risk. All >> right, Dave gives little look forward. What would be it would be expecting to see from beam through twenty. Nineteen? >> Yeah, we're focused a lot on increasing scale way. Believe that were very easy to use. Solution. People say no. Simple, you know, flexible, reliable. We wantto keep enhancing that, but we're looking at additional work loads to protect all the time cloud capabilities to expand upon a new ways, though, to take what it has always been a data protection company and make it a data management company. Things we were just speaking about from a developer angle. You're going to see us go a lot harder on that. We have a significant amount of investment way Got the largest We believe storage software investment history of five hundred million ended last year with a rich cash reserves. So now, instead of busy trying to do stuff, we're also looking at busy. What else do we need to acquire? Potentially. All right, >> well, Dave, the Cube is really excited to be back here in the redone Mosconi. A little bit more glass, a little bit more light, a little bit more space. The theme is having its annual user conference at facility. We really like to the front of blue in Miami for people that are going or thinking about going to tell him what they should be expected if they attended. >> Yeah, well, you'll get to see live demonstrations of everything I've been speaking about and Mohr, you know, seeing is believing, right? It's one thing to have power point. It's another thing to actually see someone demo it. And some of our folks, they actually demo this live on stage mean they're not canned demos. They're actually going into real servers and doing things like having a virus infiltrate and then remediating from that. So you'll get to see that you get to Seymour of road map. You'll get to see more customers, success stories and our partner ecosystem. We have a huge number of partners, of course, IBM being one of them. But we'll have a whole legal system of people there as well that have built his business around. Wien. >> Alright, Dave, want to give you the final word takeaways as to the importance of what's happening here at IBM, think the partnership and beyond, Well, >> IBM like you mentioned. I mean, they're probably the last major portfolio vendor on the planet, right? And they do just about everything you can imagine. And so from a partnership perspective, there's there's no geography, There's no vertical. There's practically no cos. Size, and there's almost no technology that's untouched. So the opportunity to interact and partner is huge. We believe we can offer some advantages in terms of simplicity in terms of cloud mobility and exploitation of IBM infrastructure. And we're just happy to be here and view them as a very strong partner. >> All right, well, Dave Russell. Always a pleasure to catch up with you. Thanks so much for joining us. Thank you. All right. And we'll be back with more coverage here from IBM. Think twenty nineteen. Of course, the Cube will also be a giveem on May twentieth through twenty second at The Phantom. Blew in Miami, Florida on stew minimum. And thank you for watching the Cube.
SUMMARY :
IBM thing twenty nineteen brought to you by IBM. Welcome back to the program. It's multi cloud and IBM, you know, spent, you know, big money to make acquisitions It's obviously what you have on premise, and it's the stuff you haven't even thought When you have that multi cloud world world, of course, data is one of the most important live in Tucson, where IBM storage has a big presence and, you know, so it's everything from tape. Why do you walk us through what the latest is? So we can make sure you avoid egress charges. You know, one of the things we worry about in a multi cloud It can be dispersed people, you know, disparity, folks. And so, you know, We talk about the public clouds. you know, the engine, if you will, that people can build it back up as a service disaster, And thiss new release. It's a long name. that That screams major release. well, it's the importance of it belies the, you know, the Newman clincher. You know, you're doing the presentation here So I really intended to be so much a beam commercial we'll talk about, you know, unabashedly, And, you know, multi cod sure isn't simple And again, if you throw software is a service into that. So how we've learned from the past, our customers, you know, Obviously, some organizations are, you know, accelerating faster than others. Of course, one of them comes up is you know, You know, you can also do what we call a secure restore you, Khun. and the challenge we faced in, you know? You need to get back as fast as you can to known. What would be it would be expecting to see from beam through People say no. Simple, you know, flexible, reliable. We really like to the front of blue in Miami for you know, seeing is believing, right? And they do just about everything you can imagine. And thank you for watching the Cube.
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Rob Thomas, IBM | IBM Think 2019
>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Okay. Welcome back, everyone. He live in San Francisco. Here on Mosconi St for the cubes. Exclusive coverage of IBM. Think twenty nineteen. I'm Jeffrey David Long. Four days of coverage bringing on all the action talking. The top executives, entrepreneurs, ecosystem partners and everyone who can bring the signal from the noise here on the Q and excuses. Rob Thomas, general manager, IBM Data and a I with an IBM Cube Alumni. Great to see you again. >> Great. There you go. >> You read a >> book yet? This year we've written ten books on a data. Your general manager. There's >> too much work. Not enough time >> for that's. Good sign. It means you're working hard. Okay. Give us give us the data here because a I anywhere in the center of the announcements we have a story up on. Slick earnings have been reported on CNBC. John Ford was here earlier talking to Ginny. This is a course centerpiece of it. Aye, aye. On any cloud. This highlights the data conversation you've been part of. Now, I think what seven years seems like more. But this is now happening. Give us your thoughts. >> Go back to basics. I've shared this with you before. There's no AI without IA, meaning you need an information architecture to support what you want to do in AI. We started looking into that. Our thesis became so clients are buying into that idea. The problem is their data is everywhere onpremise, private cloud, multiple public clouds. So our thesis became very simple. If we can bring AI to the data, it will make Watson the leading AI platform. So what we announced wtih Watson Anywhere is you could now have it wherever your data is public, private, any public cloud, build the models, run them where you want. I think it's gonna be amazing >> data everywhere and anywhere. So containers are big role in This is a little bit of a deb ops. The world you've been living in convergence of data cloud. How does that set for clients up? What are they need to know about this announcement? Was the impact of them if any >> way that we enable Multi Cloud and Watson anywhere is through IBM cloud private for data? That's our data Micro services architectural writing on Cooper Netease that gives you the portability so that it can run anywhere because, in addition Teo, I'd say, Aye, aye, ambitions. The other big client ambition is around how we modernize to cloud native architectures. Mohr compose herbal services, so the combination gets delivered. Is part of this. >> So this notion of you can't have a eye without a it's It's obviously a great tagline. You use it a lot, but it's super important because there's a gap between those who sort of have a I chops and those who don't. And if I understand what you're doing is you're closing that gap by allowing you to bring you call that a eye to the data is it's sort of a silo buster in regard. Er yeah, >> the model we use. I called the eye ladder. So they give it as all the levels of sophistication an organization needs to think about. From how you collect data, how you organize data, analyze data and then infused data with a I. That's kind of the model that we used to talk about. Talk to clients about that. What we're able to do here is same. You don't have to move your data. The biggest problem Modi projects is the first task is OK move a bunch of data that takes a lot of time. That takes a lot of money. We say you don't need to do that. Leave your data wherever it is. With Cloud private for data, we can virtualized data from any source. That's kind of the ah ha moment people have when they see that. So we're making that piece really >> easy. What's the impact this year and IBM? Think to the part product portfolio. You You had data products in the past. Now you got a eye products. Any changes? How should people live in the latter schism? A kind of a rubric or a view of where they fit into it? But what's up with the products and he changes? People should know about? >> Well, we've brought together the analytics and I units and IBM into this new organization we call Dayton ay, ay, that's a reflection of us. Seen that as two sides of the same coin. I really couldn't really keep them separate. We've really simplified how we're going to market with the Watson products. It's about how you build run Manager II watching studio Watson Machine Learning Watson Open scale. That's for clients that want to build their own. Aye, aye. For clients that wants something out of the box. They want an application. We've got Watson assistant for customer service. Watson Discovery, Watson Health Outset. So we've made it really easy to consume Watson. Whether you want to build your own or you want an application designed for the line of business and then up and down the data, stack a bunch of different announcements. We're bringing out big sequel on Cloudera as part of our evolving partnership with the new Cloudera Horn Works entity. Virtual Data Pipeline is a partnership that we've built with active fio, so we're doing things at all layers of the last. >> You're simplifying the consumption from a client, your customer perspective. It's all data. It's all Watson's, the umbrella for brand for everything underneath that from a tizzy, right? >> Yeah, Watson is the Aye, aye, brand. It is a technology that's having an impact. We have amazing clients on stage with this this week talking about, Hey, Eyes No longer. I'd like to say I was not magic. It's no longer this mystical thing. We have clients that are getting real outcomes. Who they II today we've got Rollback of Scotland talking about how they've automated and augmented forty percent of their customer service with watching the system. So we've got great clients talking about other using >> I today. You seen any patterns, rob in terms of those customers you mentioned, some customers want to do their own. Aye, aye. Some customers wanted out of the box. What? The patterns that you're seeing in terms of who wants to do their own. Aye. Aye. Why do they want to do their own, eh? I do. They get some kind of competitive advantage. So they have additional skill sets that they need. >> It's a >> It's a maker's mark. It is how I would describe it. There's a lot of people that want to make their own and try their own. Ugh. I think most organizations, they're gonna end up with hundreds of different tools for building for running. This is why we introduced Watson Open Scale at the end of last year. That's How would you manage all of your A II environments? What did they come from? IBM or not? Because you got the and the organization has to have this manageable. Understandable, regardless of which tool they're using. I would say the biggest impact that we see is when we pick a customer problem. That is widespread, and the number one right now is customer service. Every organization, regardless of industry, wants to do a better job of serving clients. That's why Watson assistant is taking off >> this's. Where? Data The value of real time data. Historical data kind of horizontally. Scaleable data, not silo data. We've talked us in the past. How important is to date a quality piece of this? Because you have real time and you have a historical date and everything in between that you had to bring to bear at low ladened psi applications. Now we're gonna have data embedded in them as a feature. Right. How does this change? The workloads? The makeup of you? Major customer services? One piece, the low hanging fruit. I get that. But this is a key thing. The data architecture more than anything, isn't it? >> It is. Now remember, there's there's two rungs at the bottom of the ladder on data collection. We have to build a collect data in any form in any type. That's why you've seen us do relationships with Mongo. D B. Were they ship? Obviously with Claude Era? We've got her own data warehouse, so we integrate all of that through our sequel engine. That thing gets to your point around. Are you gonna organize the data? How are you going to curate it? We've got data catalogue. Every client will have a data catalogue for many dollar data across. Clouds were now doing automated metadata creation using a I and machine learning So the organization peace. Once you've collected it than the organization, peace become most important. Certainly, if you want to get to self service analytics, you want to make data available to data scientists around the organization. You have to have those governance pieces. >> Talk about the ecosystem. One of the things that's been impressive IBM of the years is your partnerships. You've done good partners. Partnership of relationships now in an ecosystem is a lot of building blocks. There's more complexity requires software to distract him away. We get that. What's opportunities for you to create new relationships? Where are the upper opportunities for someone a developer or accompanied to engage with you guys? Where's the white spaces? Where is someone? Take advantage of your momentum and you're you're a vision. >> I am dying for partners that air doing domain specific industry specific applications to come have them run on IBM cloud private for data, which unleashes all the data they need to be a valuable application. We've already got a few of those data mirrors. One sensing is another one that air running now as industry applications on top of IBM Club private for data. I'd like to have a thousand of these. So all comers there. We announced a partnership with Red Hat back in May. Eventually, that became more than just a partnership. But that was about enabling Cloud Private, for data on red had open shift, So we're partnered at all layers of the stack. But the greatest customer need is give me an industry solution, leveraging the best of my data. That's why I'm really looking for Eyes V. Partners to run on Ivan clubs. >> What's your pitch to those guys? Why, why I should be going. >> There is no other data platform that will connect to all your data sources, whether they're on eight of us as your Google Cloud on premise. So if you believe data is important to your application. There's simply no better place to run than IBM. Claude Private for data >> in terms of functionality, breath o r. Everything >> well, integrating with all your data. Normally they have to have the application in five different places. We integrate with all the data we build the data catalogue. So the data's organized. So the ingestion of the data becomes very easy for the Iast V. And by the way, thirdly, IBM has got a pretty good reach. Globally, one hundred seventy countries, business partners, resellers all over the world, sales people all over the world. We will help you get your product to market. That's a pretty good value >> today. We talk about this in the Cube all the time. When the cloud came, one of the best things about the cloud wasn't allowed. People to put applications go there really quickly. Stand them up. Startups did that. But now, in this domain world of of data with the clouds scale, I think you're right. I think domain X expertise is the top of the stack where you need specially special ism expertise and you don't build the bottom half out. What you're getting at is of Europe. If you know how to create innovation in the business model, you could come in and innovate quickly >> and vertical APS don't scale enough for me. So that's why focus on horizontal things like customer service. But if you go talk to a bank, sometimes customer service is not in office. I want to do something in loan origination or you're in insurance company. I want to use their own underwriting those air, the solutions that will get a lot of value out of running on an integrated data start >> a thousand flowers. Bloom is kind of ecosystem opportunity. Looking forward to checking in on that. Thoughts on on gaps. For that you guys want to make you want to do em in a on or areas that you think you want to double down on. That might need some help, either organic innovation or emanate what areas you looking at. Can you share a little bit of direction on that? >> We have, >> ah, a unique benefit. And IBM because we have IBM research. One of their big announcement this week is what we call Auto Way I, which is basically automating the process of feature engineering algorithm selection, bringing that into Watson Studio and Watson Machine learning. I am spending most of my time figure out howto I continue to bring great technology out of IBM research and put in the hand of clients through our products. You guys solve the debaters stuff yesterday. We're just getting started with that. We've got some pretty exciting organic innovation happen in IBM. >> It's awesome. Great news for startups. Final question for you. For the folks watching who aren't here in San Francisco, what's the big story here? And IBM think here in San Francisco. Big event closing down the streets here in Howard Street. It's huge. What's the big story? What's the most important things happening? >> The most important thing to me and the customer stories >> here >> are unbelievable. I think we've gotten past this point of a eyes, some idea for the future we have. Hundreds of clients were talking about how they did an A I project, and here's the outcome they got. It's really encouraging to see what I encourage. All clients, though, is so build your strategy off of one big guy. Project company should be doing hundreds of Aye, aye projects. So in twenty nineteen do one hundred projects. Half of them will probably fail. That's okay. The one's that work will more than make up for the ones that don't work. So we're really encouraging mass experimentation. And I think the clients that air here are, you know, creating an aspirational thing for things >> just anecdotally you mentioned earlier. Customer service is a low hanging fruit. Other use cases that are great low hanging fruit opportunities for a >> data discovery data curation these air really hard manual task. Today you can start to automate some of that. That has a really big impact. >> Rob Thomas, general manager of the data and a I groupie with an IBM now part of a bigger portfolio. Watson Rob. Great to see you conventionally on all your success. But following you from the beginning. Great momentum on the right way. Thanks. Gradually. More cute coverage here. Live in San Francisco from Mosconi North. I'm John for Dave A lot. They stay with us for more coverage after this short break
SUMMARY :
It's the cube covering Great to see you again. There you go. This year we've written ten books on a data. too much work. in the center of the announcements we have a story up on. build the models, run them where you want. Was the impact of them if any gives you the portability so that it can run anywhere because, in addition Teo, I'd say, So this notion of you can't have a eye without a it's It's obviously a great tagline. That's kind of the ah ha moment people have when they see that. What's the impact this year and IBM? Whether you want to build your own or you want an application designed for the line of business and then You're simplifying the consumption from a client, your customer perspective. Yeah, Watson is the Aye, aye, brand. You seen any patterns, rob in terms of those customers you mentioned, some customers want to do their own. That's How would you manage all of your A II environments? you had to bring to bear at low ladened psi applications. How are you going to curate it? One of the things that's been impressive IBM of the years is your partnerships. But the greatest customer need is give me an industry solution, What's your pitch to those guys? So if you believe data is important to your application. We will help you get your product to market. If you know how to create innovation in the business But if you go talk to a bank, sometimes customer service is not in office. For that you guys want to make you want to do em in a on or areas that you think you want to double You guys solve the debaters stuff yesterday. What's the most important things happening? and here's the outcome they got. just anecdotally you mentioned earlier. Today you can start to automate some of that. Rob Thomas, general manager of the data and a I groupie with an IBM now part of a bigger portfolio.
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Daniel Berg, IBM Cloud & Norman Hsieh, LogDNA | KubeCon 2018
>> Live from Seattle, Washington it's theCUBE, covering KubeCon and CloudNativeCon North America 2018. Brought to you by Red Hat, the Cloud Native Computing Foundation, and its ecosystem partners. >> Hey, welcome back everyone, it's theCUBE live here in Seattle for day three of three of wall-to-wall coverage. We've been analyzing here on theCUBE for three days, talking to all the experts, the CEOs, CTOs, developers, startups. I'm John Furrier, Stu Miniman, with theCUBE coverage of here at dock, not DockerCon, KubeCon and CloudNativeCon. Getting down to the last Con. >> So close, John, so close. >> Lot of Docker containers around here. We'll check it on the Kubernetes. Our next two guests got a startup, hot startup here. You got Norman Hsieh, head of business development, LogDNA. New compelling solution on Kubernetes give them a unique advantage, and of course, Daniel Berg who's distinguished engineer at IBM. They have a deal. We're going to talk about the startup and the deal with IBM. The highlights, kind of a new model, a new world's developing. Thanks for joining us. >> Yeah, no problem, thanks for having us. >> May get you on at DockerCon sometimes. (Daniel laughing) Get you DockerCon. The container certainly been great, talk about your product first. Let's get your company out there. What do you guys do? You got something new and different. Something needed. What's different about it? >> Yeah, so we started building this product. One thing we were trying to do is finding a login solution that was built for developers, especially around DevOps. We were running our own multi-tenant SaaS product at the time and we just couldn't find anything great. We tried open source Elastic and it turned out to be a lot to manage, there was a lot of configuration we had to do. We tried a bunch of the other products out there which were mostly built for log analysis, so you'd analyze logs, maybe a week or two after, and there was nothing just realtime that we wanted, and so we decided to build our own. We overcame a lot of challenges where we just felt that we could build something that was easier to use than what was out there today. Our philosophy is for developers in the terms of we want to make it as simple as possible. We don't want you to manage where you're going to think about how logs work today. And so, the whole idea, even you can go down to some of the integrations that we have, our Kubernetes integration's two lines. You essentially hit two QCTL lines, your entire cluster will get logged, directly logged in in seconds. That's something we show often times at demos as well. >> Norman, I wonder if you can drill in a little bit more for us. Always look at is a lot of times the new generation, they've got just new tools to play with and new things to do. What was different, what changes? Just the composability and what a small form factor. I would think that you could just change the order of magnitude in some of the pricing of some of these. Tell us why it's different. >> Yeah, I mean, I think there's, three major things was speed. So what we found was that there weren't a lot of solutions that were optimized really, really well for finding logs. There were a lot of log solutions out there, but we wanted to optimize that so we fine-tuned Elasticsearch. We do a lot of stuff around there to make that experience really pleasurable for our users. The other is scale. So we're noticing now is if you kind of expand on the world of back in the day we had single machines that people got logs off of, then you went to VMware where you're taking a single machine and splitting up to multiple different things, and now you have containers, and all of a sudden you have Kubernetes, you're talking about thousands and thousands of nodes running and large production service. How do you find logs in those things? And so we really wanted to build for that scale and that usability where, for Kubernetes, we'll automatically tag all your logs coming through. So you might get a single log line, but we'll tag it with all the meta-data you need to find exactly what you want. So if I want to, if my container dies and I no longer know that containers around, how am I going to get the logs off of that, well, you can go to LogDNA, find the container that you're looking for, know exactly where that error's coming from as well. >> So you're basically storing all this data, making it really easy for the integration piece. Where does the IBM relationship fit in? What's the partnership? What are you guys doing together? >> I don't know if Dan wants to-- >> Go ahead, go ahead. >> Yeah, so we're partnering with IBM. We are one of their major partners for login. So if you go into Observability tab under IMB Cloud and click on Login, login is there, you can start the login instance. What we've done is, IBM's brought us a great opportunity where we could take our product and help benefit their own customers and also IBM themselves with a lot of the login that we do. They saw that we are very simplistic way of thinking about logs and it was really geared towards when you think about IBM Cloud and the shift that they're moving towards, which is really developer-focused, it was a really, really good match for us. It brought us the visibility into the upmarket with larger customers and also gives us the ability to kind of deploy globally across IBM Cloud as well. >> I mean, IBMs got a great channel on the sales side too, and you guys got a great relationship. We've seen that playbook before where I think we've interviewed in all the other events with IBM. Startups can really, if they fit in with IBM, it's just massive, but what's the reason? Why the partnership? Explain. >> Well, I mean, first of all we were looking for a solution, a login solution, that fit really well with IKS, our Kubernetes service. And it's cloud-native, high scale, large number of cluster, that's what our customers are building. That's what we want to use internally as well. I mean, we were looking for a very robust cloud-native login service that we could use ourselves, and that's when we ran across these guys. What, about a year ago? >> Yeah, I mean, I think we kind of first got introduced at last year's KubeCon and then it went to Container World, and we just kept seeing each other. >> And we just kept on rolling with it so what we've done with that integration, what's nice about the integration, is it's directly in the catalog. So it's another service in the catalog, you go and select it, and provision it very easily. But what's really cool about it is we wanted to have that integration directly with the Kubernetes services as well, so there's the tab on the Integration tab on the Kubernetes, literally one button, two lines of code that you just have to execute, bam! All your logs are now streaming for the entire cluster with all the index and everything. It just makes it a really nice, rich experience to capture your logs. >> This is infrastructure as code, that's what the promise was. >> Absolutely, yes. >> You have very seamless integration and the backend just works. Now talk about the Kubernetes pieces. I think this is fascinating 'cause we've been pontificating and evaluating all the commentary here in theCUBE, and we've come to the conclusion that cloud's great, but there's other new platform-like things emerging. You got Edge and all these things, so there's a whole new set, new things are going to come up, and it's not going to be just called cloud, it's going to be something else. There's Edge, you got cameras, you got data, you got all kinds of stuff going on. Kubernetes seems to fit a lot of these emerging use cases. Where does the Kubernetes fit in? You say you built on Kubernetes, just why is that so important? Explain that one piece. >> Yeah, I mean, I think there's, Kubernetes obviously brought a lot of opportunities for us. The big differentiator for us was because we were built on Kubernetes from the get go, we made that decision a long time ago, we didn't realize we could actually deploy this package anywhere. It didn't have to be, we didn't have to just run as a multi-tenant SaaS product anymore and I think part of that is for IBM, their customers are actually running, when they're talking about an integrated login service, we're actually running on IBM Cloud, so their customers can be sure that the data doesn't actually move anywhere else. It's going to stay in IBM Cloud and-- >> This is really important and because they're on the Kubernetes service, it gives them the opportunity, running on Kubernetes, running automatic service, they're going to be able to put LogDNA in each of the major regions. So customer will be able to keep their logged data in the regions that they want it to stay. >> Great for compliance. >> Absolutely. >> I mean, compliance, dreams-- >> Got to have it. >> Especially with EU. >> How about search and discovery, that's fit in too? Just simple, what's your strategy on that? >> Yeah, so our strategy is if you look at a lot of the login solutions out there today, a lot of times they require you to learn complex query languages and things like that. And so the biggest thing we were hearing was like, man, onboarding is really hard because some of our developers don't look at logs on a daily basis. They look at it every two weeks. >> Jerry Chen from Greylock Ventures said machine learning is the new, ML is the new SQL. >> Yup. (Daniel laughing) >> To your point, this complex querying is going to be automated away. >> Yup. >> Yes. >> And you guys agree with that. >> Oh, yeah. >> You actually, >> Totally agree with that. >> you talked about it on our interview. >> Norman, wonder if you can bring us in a little bit of compliance and what discussions you're having with customers. Obviously GDPR, big discussion point we had. We've got new laws coming from California soon. So how important is this to your customers, and what's the reality kind of out there in your user base? >> Yeah, compliance was, our founders had run a lot of different businesses before. They had two major startups where they worked with eBay, compliance was the big thing, so we made a decision early on to say, hey, look, we're about 50 people right now, let's just do compliance now. I've been at startups where we go, let's just keep growing and growing and we'll worry about compliance later-- >> Yeah, bite you in the ass, big time. >> Yeah, we made a decision to say, hey, look, we're smaller, let's just implement all the processes and necessary needs, so. >> Well, the need's there too, that's two things, right? I mean, get it out early. Like security, build it up front and you got it in. >> Exactly. >> And remember earlier we were talking and I was telling you how within the Kubernetes service we like to use our own services to build expertise? It's the same thing here. Not only are they running on top of IKS, we're using LogDNA to manage the logs and everything, and cross the infrastructure for IKS as well. So we're heavily using it. >> This also highlights, Daniel, the ecosystem dynamic of having when you break down this monolithic type of environments and their sets of services, you benefit because you can tap into a startup, they can tap in to IBM's goodness. It's like somewhat simple Biz Dev deal other than the RevShare component of the sales, but technically, this is what customers want at the endgame is they want the right tool, the right job, the right product. If it comes from a startup, you guys don't have to build it. >> I mean, exactly. Let the experts do it, we'll integrate it. It's a great relationship. And the teams work really well together which is fantastic. >> What do you guys do with other startups? If a startup watches and says, hey, I want to be like LogDNA. I want to plug into IBM's Cloud. I want to be just like them and make all that cash. What do they got to do? What's the model? >> I mean, we're constantly looking at startups and new business opportunities obviously. We do this all the time. But it's got to be the right fit, alright? And that's important. It's got to be the right fit with the technology, it's got to be the right fit as far as culture, and team dynamics of not only my team but the startup's teams and how we're going to work together, and this is why it worked really great with LogDNA. I mean, everything, it just all fit, it all made sense, and it had a good business model behind that as well. So, yes, there's opportunities for others but we have to go through and explore all those. >> So, Norman, wonder if you can share, how's your experience been at the show here? We'd love to hear, you're going to have so many startups here. You got record-setting attendance for the show. What were your expectations coming in? What are the KPIs you're measuring with and how has it met what you thought you were going to get? >> No, it's great, I mean, previous to the last year's KubeCon we had not really done any events. We're a small company, we didn't want to spend the resources, but we came in last year and I think what was refreshing was people would talk to us and we're like, oh, yeah, we're not an open source technology, we're actually a log vendor and we can, and we'll-- (Stu laughing) So what we said was, hey, we'll brush that into an experience, and people were like, oh, wow, this is actually pretty refreshing. I'm not configuring my fluentd system, fluentd to tap into another Elasticsearch. There was just not a lot of that. I think this year expectation was we need the size doubled. We still wanted to get the message out there. We knew we were hot off the presses with the IMB public launch of our service on IBM Cloud. And I think we we're expecting a lot. I mean, we more than doubled what our lead count was and it's been an amazing conference. I mean, I think the energy that you get and the quality of folks that come by, it's like, yeah, everybody's running Kubernetes, they know what they're talking about, and it makes that conversation that much easier for us as well. >> Now you're CUBE alumni now too. It's the booth, look at that. (everyone laughing) Well, guys, thanks for coming on, sharing the insight. Good to see you again. Great commentary, again, having distinguished engineering, and these kinds of conversations really helps the community figure out kind of what's out there, so I appreciate that. And if everything's going to be on Kubernetes, then we should put theCUBE on Kubernetes. With these videos, we'll be on it, we'll be out there. >> Hey, yeah, absolutely, that'd be great. >> TheCUBE covers day three. Breaking it down here. I'm John Furrier, Stu Miniman. That's a wrap for us here in Seattle. Thanks for watching and look for us next year, 2019. That's a wrap for 2018, Stu, good job. Thanks for coming on, guys, really appreciate it. >> Thanks. >> Thank you. >> Thanks for watching, see you around. (futuristic instrumental music)
SUMMARY :
Brought to you by Red Hat, the CEOs, CTOs, developers, startups. We're going to talk about the startup and the deal with IBM. What do you guys do? And so, the whole idea, even you can go down and new things to do. and all of a sudden you have Kubernetes, What are you guys doing together? about IBM Cloud and the shift that they're moving towards, and you guys got a great relationship. Well, I mean, first of all we were looking for a solution, Yeah, I mean, I think we kind of first got introduced And we just kept on rolling with it so what we've done that's what the promise was. and it's not going to be just called cloud, It didn't have to be, we didn't have to just run in each of the major regions. And so the biggest thing we were hearing was like, machine learning is the new, ML is the new SQL. is going to be automated away. you talked about it So how important is this to your customers, so we made a decision early on to say, Yeah, we made a decision to say, and you got it in. And remember earlier we were talking and I was telling you of having when you break down this monolithic type And the teams work really well together which is What do you guys do It's got to be the right fit with the technology, and how has it met what you thought you were going to get? I mean, I think the energy that you get Good to see you again. Hey, yeah, absolutely, That's a wrap for us here in Seattle. see you around.
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Ryan Welsh, Kyndi | CUBEConversation, October 2018
(dramatic music) >> Welcome back, everyone to theCUBE's headquarters in Palo Alto, I'm John Furrier, the host of theCUBE, founder of SiliconANGLE Media, we're here for Cube Conversation with Ryan Welsh, who's the founder of CEO of Kyndi. It's a hot startup, it's a growing startup, doing really well in a hot area, it's in AI, it's where cloud computing, AI, data, all intersect around IoT, RPA's been a hot trend everyone's on, they're in that as well, but really an interesting startup we want to profile here, Ryan, thanks for spending the time to come in and talk about the startup. >> Yeah, thanks for having me. >> So I love getting the startups in, because we get the real scoop, you know, what's real, what's not real, and also, practitioners also tell us the truth too, so we love to have especially founders in. So first, before we get started, tell 'em about the company, how old is your company, what's the core value proposition, what do you guys do? >> Yeah, we're four years old, we were founded in June 2014. The first two, three years were really fundamental research and developing some new AI algorithms. What we focus on is, we focused on building explainable AI products for government customers, pharmaceutical customers and financial services customers. So our-- >> Let's explain the AI, what does that mean, like how do you explain AI? AI works, especially machine learning, well AI doesn't really exist, 'cause it's really machine learning, and what is AI? So what is explainable AI? >> Yeah, for us, it's the ability of a machine to communicate with the user in natural language. So there's kind of two aspects to explainability. Some of the deep learning folks are grabbing onto it, and really what they're talking about with explainability is algorithmic transparency, but where they tell you how the algorithm works, they tell you the parameters that are being used. So I explain to you the algorithm, you can actually interrogate the system. For us, if our system's going to make a recommendation to you, you would want to know why it's making the recommendation, right? So for us, we're able to communicate with users in natural language, like it's another person, of why we make a recommendation, why we bring back a search result, why we do whatever it is as part of the business process. >> And you mentioned deep learning AI is obviously the buzzword everybody's talking about, I mean I'm a big fan of AI in the sense that hyping it up means my kids know what it is, and everybody say, hey Dad, love machine learning. They love AI 'cause it's got a futuristic sound to it, but deep learning is real, deep learning is about learning systems that learn, which means they need to know what's going on, right? So this learning loop, how does that work? Is that kind of where explainable AI needs to go? Is that where it's going, where if you can explain it and it's explainable, you can interrogate it, does it have a learning mechanism to it? >> I think there's two major aspects of intelligence. There's the learning aspect, then there's the reasoning aspect. So if you look back through the history of AI, current machine learning is phenomenal at learning from data, like you're saying, learning the patterns in the data, but its reasoning is actually pretty weak. It can do statistical inferencing, but in the field of symbolic AI, where there's inductive, deductive, abductive, analogical reasoning, kind of advanced reasoning, it's terrible at reasoning. Whereas the symbolic approaches are phenomenal at reasoning but can't learn from data. So what is AI? A sub-group of that is machine learning that can learn from data. Another sub-group of that, it's knowledge-based approaches, which can't learn from data, they are phenomenal at reasoning, and really the trend that we're seeing at the edge in AI, or kind of the cutting edge, is actually fusing those two paradigms together, which is effectively what we've done. You've seen DeepMind and Google Brain publish a paper on that earlier this year, you've seen Gary Marcus start to talk about that, so for us, explainability is kind of bringing together these two paradigms of AI, that can both learn from data, reason about data, and answer questions like, why are you giving me this recommendation. >> Great explanation. And I want to just ask you, what' the impact of that, because we've always talked in the old search world, meta-reasoning, you type in a misspelling on Google, and it says, there's the misspelling, okay, I get that, but what if is misspell the word all the time, can't Google figure out that I really want that word? So reasoning has been a hard nut to crack, big time. >> Well you have to acquire the knowledge first to combine bits of knowledge to then reason, right? But the challenge is acquiring the knowledge. So you have all these systems or knowledge-based approaches, and you have human beings on-site, professional services, building and managing your knowledge base. So that's been one of the hurdles for knowledge-based approaches. Now you have machine learning that can learn from data, one of the problems with that is, that you need a bunch of labeled data. So you're kind of trading off between handcrafted knowledge systems, handcrafted labeled systems which you can then learn from data. So the benefits of fusing the two together is you can use machine learning approaches to acquire the knowledge, as opposed to hand engineering it, and then you can put that in a form or a data model that you can then reason about. So the benefit is really it all comes down to customer. >> Awesome, great area, great concepts, we can go for an hour on this, I love this topic, I think it's super relevant, especially as cloud and automation become the key accelerant to a lot of new value. But let's get back to the company. So four years old, you've done some R and D, give me the stats, where are you guys in the product side, product shipping, what's the value proposition, how do people engage with you, just go down looking on the list. >> Yeah, yeah, shipping product to customers in pharmaceutical, and government use cases. How people engage with us-- >> It's a software product? >> It's a software product. Yeah, yeah. So we can deliver it, surprisingly a lot of customers still want it on-prem. (both laugh) But we can deploy in the cloud as well. Typically, how we work with customers is we'll have close engagements for specific use cases within pharma or government or financial services, because it's a very broad platform an can be applied to any text-based use case. So we work with them closely, develop a use case, they're able to sell that internally to champions >> And what problems are they solving, what specifically is the answer? >> So for pharmaceutical companies, a lot of their internal, historical clinical trial data, they'll develop memos, emails, notes as they bring a drug to market. How do you leverage that data now? Instead of just storing it, how do I find new and innovative ways to use existing drugs that someone in another part of the organization could have developed? How do I manage the risks within that historical clinical trial data? Are there people that are doing research incorrectly? Are they reporting things incorrectly? You know, this entire process of both getting drugs through the pipeline and managing drugs as they move through the pipeline, is a very manual process that revolves around text-based data sources. So how do you develop systems that amplify the productivity of the people that are developing the drugs, then also the people that are managing the process. >> And so what are you guys actually delivering as value? What's the value proposition for them? >> Yeah, so >> Is it time? >> It's saving time, but ultimately increasing their productivity of getting that work done. It's not replacing individuals, because there's so much work to do. >> So all the... The loose stuff like the paper, they can discover it faster, so they have more access to the data. >> That's right. >> Using your tools >> That's right >> and your software. >> You can classify things in certain ways, saying there's data integrity issues, you need to look at this closer, but ultimately managing that data. >> And that's where machine learning and some of these AI techniques matter, because you want to essentially throw software at that problem, accelerate that process of getting the data, bringing it in, assessing it. >> Yeah, I mean we spend most of our time looking for the information to then analyze. I mean we spend 80% of our time doing it, right? Where it's like are there ways to automate that process, so we can spend 80% of our time actually doing our job? >> So Ryan, who's the customer out there? So is it someone, someone's watching this video, and what's their pain point, when do they call you, why do they call you? What's some of the signals that might tell someone, hey I want to give these guys a call, I need this solution? >> Yeah, a lot of it comes down to the amount of manual labor that you're doing. So we see a lot of big expenses around people, because you haven't traditionally been able to automate that process, or to use software in that process. So if you actually look at your income statement and you say where am I spending my most money, on tons of people, and I'm just throwing people at the problem, that's typically where people engage with us and say, how do I amplify the productivity of these people so I can get more out of them, hopefully make them more efficient? >> And it's not just so much to reduce the head count issue, it's more of increasing the automation for saying value in top-line revenue, because if you have to reproduce people all the time, why not replicate that in software? So I think what I'm seeing is, get that right? >> That's exactly right. And the job consistently changes too, so it's not like this robotic process that you can just automate away. They're looking for certain things one day, then they're looking for certain things the next day, but you need a capability that kind of matches their expertise. >> You know, I was talking to a CIO the other day and we were talking about some of the things around reproducing things, replicating, and the notion of how things get scaled or moved along, growth, is, and the expression was "Throw a body at that". That's been IT. Outsource it. So throwing a body, or throw bodies at it, you know, throw that problem at me, that doesn't really end well. With software automation you can say, you don't just throw a body at it, you can say, if it can be automated, automate it. >> Yeah, here's what I think most people miss, is that we are the bottleneck in the modern production process because we can't read and understand information any faster than our parents or grandparents. And there's not enough people on the planet to increase our capacity, to push things through. So if we were to compare the modern knowledge economy, it's interesting, to the manufacturing process, you have raw materials, manufacture it, and end product. All these technologies that we have effectively stack information and raw materials at the front of it. We haven't actually automated that process. >> You nailed it, and in fact one of the things I would say that would support that is, in interviewed Dave Redskin, who's a site reliable engineer at Google, and we were talking about the history of how Google scaled, and they have this whole new program around how to operate large data centers. He said years and years ago at Google, they looked up the growth and said, we're going to need a thousand people per data center, at least, if not, per data center, so that means we need 15,000 people just to manage the servers. 'Cause what they did was they just did the operating cycle on provisioning servers, and essentially, they automated it all away, and they created a lot of the tools that became now Google Cloud. His point was, is that, they now have one person, site reliability engineer, who overlooks the entire automation piece. This is where the action is. That concept of not, to scale down the people focus, scale up the machine base model. Is that kind of the trend that you guys are riding? >> Absolutely. And I think that's why AI is hot right now. I mean, AI's been around since the late 40s, early 50s, but why this time I think it's different is, one, that it's starting to work, given the computational resources and the data that we have, but then also the economic need for it. Businesses are looking, and saying, how I historically address these problems, I can no longer address them that way, I can't hire 15,000 people to run my data center. I need to now automate-- >> You got to get out front on it. >> Yeah, I got to augment those people with better technologies to make them do the work better. >> All right, so how much does the product cost, how do people engage with you guys, what's the engagement cost, is it consulting you come in, POC you ship 'em software, to appliances in the cloud, you mention on-premise. >> Yeah, yeah. >> So what's, how's the product look, how much does it cost? >> Yeah, it costs a good chunk for folks, so typically north of 500K. We do provide a lot of ROI around that, hence the ability to charge such a high price. Typically how we push people through the cycle and how we actually engage with folks is, we do what we demonstration of value. So there's a lot of different, or typically there's about 15 use cases that any given Fortune 500 customer wants to address. We find the ones with the highest ROI, the ones with accessible data >> And they point at it, >> The ones with budget >> They think, that's my problem, they point to it, right? >> Yeah. >> It's not hard to find. >> We have to walk 'em through it a little bit. Hopefully they've engaged with other vendors in the market that have been pushing AI solutions for the last few years, and have had some problems. So they're coached up on that, but we engage with demonstration of value, we typically demonstrate that ROI, and then we transition that into a full operational deployment for them. If they have a private cloud, we can deploy on a private cloud. Typically we provide an appliance to government customers and other folk. >> So is that a pre-sale activity, and you throw bodies at it, on your team. What's the engagement required kind of like a... Then during that workshop if you will, call it workshop. You come in and you show some value. Kind of throw some people at it, right? >> Yeah, you got-- >> You have SE, and sales all that. >> Exactly right. Exactly right. So we'll have our sales person managing the relationship, an SE also interacting with the data, working with the system, working closely with a contact on the customer's side. >> And they typically go, this is amazing, let's get started. Do they break it up, or-- >> They break it up. It's an iterative process, 'cause a lot of times, people don't fully grasp the power of these capabilities, so they'll come through and say, hey can you just help us with this small aspect of it, and once you show 'em that I can manage all of your unstructured text data, I can turn it into this giant knowledge graph, on top of which I can build apps. Then the light kind of goes off and they go, they go, all right, I can see this being used in HR, marketing, I mean legal, everywhere. >> Yeah, I mean you open up a whole new insight engine basically for 'em. >> That's exactly right. >> So, okay, so competition. Who are you competing with? I mean, we've been covering UiPath, they just had an event in Miami. This is the hot area, who's competing with you, who are you up against, and how are you guys winning, why are you winning? >> Yeah, we don't compete with the RPA folks. You know there's interesting aspects there, and I think we'll chat about that. Mainly there are incumbents like IBM Watson that are out there, we think IBM has done phenomenal research over the last 60 years in the field of AI. But we do run into the IBMs, big consulting companies, a lot of the AI deployments that we see, candidly are from all the big consulting shops. >> And they're weak, or... They're weaker than yours. >> Yeah, I would argue yes. (both laugh) >> It's okay, get that out of your sleigh. >> I think one of the big challenges-- >> Is it because they just don't have the chops, or they're just recycling old tech into a-- >> We do have new novel algorithms. I mean, what's interesting is, and this has actually been quite hard for us, is coming out saying, we've taken a step beyond deep learning. We've take a step beyond existing approaches. And really it's fusing those two paradigms of AI together, 'cause what I want to do is to be able to acquire the knowledge from the data, build a giant knowledge graph, and use that knowledge graph for different applications. So yeah, we deploy our systems way faster than everyone else out there, and our system's fully explainable. >> Well I mean it's a good position to be in. At least from a marketing standpoint, you can have a leadership strategy, you don't need to differentiate in anyway 'cause you're different, right, so... >> Yeah, yeah >> Looks like you're in good shape. So easy marketing playbook there, just got to pound the pavement. RPA, you brought that up and I think that's certainly been an area. You mentioned you guys kind of dip into that. How do you, I mean that's not an area you would, you would fit well in there, so, I want to get you, well you're not positioning yourself as an RPA solution, but you can solve RPA challenges or those kinds of... Explain why you're not an RPA but you will play in it. >> Here's what's so fascinating about this market is, a lot of people in AI will knock the RPA guys as not being sophisticated approaches. Those guys are solving real business problems, providing real value to enterprises, and they are automating processes. Then you have sophisticated AI companies like ours, that are solving really really high-level white-collar worker tasks, and it's interesting, I feel like the AI community needs to kind of come down a step of sophistication, and the RPA companies are starting to come up a level of sophistication, and that's where you're starting to see that overlap. RPA companies moving from RPA to intelligence process automation, where AI companies can actually add value in the analysis of unstructured text data. So around natural language processing, natural language understanding. RPA companies no longer need to look at specific structured aspects and forms, but can actually move into more sophisticated extraction of things from text data and other-- >> Well I think it's not a mutually exclusive scenario anymore, as you mentioned earlier, there's a blending of the two machine learning and symbolics coming together in this new reasoning model. If you look at RPA, my view is it's kind of a dogmatic view of certain things. They're there to replace people, right (laughs) >> Yeah, totally. >> We got robotics, we don't need people on the manufacturing line, we just put some robotics on as an example. And AI's always been about getting the best out of the software and the data, so if you look at the new RPA that we see that's relevant is to your point, let's use machines to augment humans. A different, that's a cultural thing. So I think you're right, I think it's coming together in new ground where most people who are succeeding in data, if you will, data driven or AI, really have the philosophy that humans have to be getting the value. Like that SRE example, Google, so that's a fundamental thing. >> Absolutely. >> And okay, so what's next for you guys? Business is good? >> Business is good. >> Hiring, I'm imagining with your kind of community >> Always hiring phenomenal AI and ML expertise, if you have it, >> Good luck competing with Google >> Shoot us an email. >> And Google will think that you're hiring 'em all. How do you handle that, I mean... >> Yeah I mean they actually get to work on novel algorithms. I mean what's fascinating is a lot of the AI out there, I mean you can date it all the way back to Rumelhart and Hinton's paper from 1986. So I mean, we've had backprop for a while. If you want to come work on new, novel algorithms, that are really pushing the limit of what's possible, >> Yeah, if you're bored at Google or Facebook, check these guys out. >> Check us out. >> Okay, so funding, you got plenty of money in the bank, strategic partners, what's the vision, what's your goal for the next 12 months or so, what's your objective? >> Yeah, focusing big on the customers that we have now. I'm always big on having customers, get a viral factor within the B2B enterprise software space, get customers that are screaming from the mountaintop that this is the best stuff ever, then you can kind of take care of it. >> How about biz dev, partnerships, are you guys looking at an ecosystem? Obviously rising tide floats all boats, I mean I can almost imagine might salivate for some of the software you're talking about, like we have all this data, here inside theCUBE, we have all kinds of processes that are, we're trying to streamline, I mean, we need more software, I mean, can I buy your stuff? I mean we don't have half a million bucks, can I get a discount? I mean how do I >> We'll see. We'll see how we end up. >> I mean is there like a biz dev partner program? >> No, not... >> Forgetting about theCUBE, we'd love if that's so, but if it's to partner, do you guys partner? >> So not yet in exposing APIs to third parties. So I mean I would love if I had the balance sheet to go to market horizontally, but I don't. So it's go to market vertically, focus on specific solutions. >> Industries. >> Industries, pharma >> So you're sort of, you're industry-focused >> government, financial services. >> That's the ones you've got right now. >> They're the three. >> For now. >> Yep. >> Okay, so once you nail an industry, you move onto the next one. >> Yeah, then I would love expose APIs for tab partners to work on this stuff. I mean we see that every day someone wants to use certain engines that we have, or to embed them within applications. >> Well I mean you've got a nice vertical strategy. You've knocked down maybe one or two verticals. Then you kind of lay down a foundational... >> Yeah. >> Yeah, development platform. >> Yeah, that's right. >> That's your strategy. >> And we can be, I mean at Kyndi I think we can be embedded in every application out there that's looking at unstructured data >> Which is also the mark of maturity, you got to go where the customers are, and you know the vision of having this global platform could be a great vision, but you've got to meet the customers where they are, and where they are now is, solve my vertical problem. (laughs) >> Yeah, and for us, with new technologies, well, show me that they're better than other approaches. I can't go to market horizontally and just say, I have better AI than Google. Who's going to come beyond the Kyndi person? >> Well IBM's been trying to do it with Watson, and that's hard. >> It's very hard. >> And they end up specializing in industries. Well Ryan, thanks for coming on theCUBE, appreciate it. Kyndi, great company, check 'em out, they're hiring. We're going to keep an eye on these guys 'cause they're really hitting a part of the market that we think, here at theCUBE, is going to be super-powerful, it's really the intersection of a lot of major markets, cloud, AIs, soon to be blockchain, supply chain, data center of course, storage networking, this is IoT security and data at the center of all the action. New models can emerge, with you guys in the center, so thanks for coming and sharing your story, appreciate it. >> Thank you very much. >> I'm John Furrier, here in theCUBE studios in Palo Alto. Thanks for watching. (dramatic music)
SUMMARY :
Ryan, thanks for spending the time to come in because we get the real scoop, you know, What we focus on is, we focused on building So I explain to you the algorithm, Is that where it's going, where if you can explain it So if you look back through the history of AI, So reasoning has been a hard nut to crack, big time. So the benefit is really it all comes down to customer. give me the stats, where are you guys in the product side, How people engage with us-- So we work with them closely, develop a use case, So how do you develop systems that amplify so much work to do. so they have more access to the data. you need to look at this closer, of getting the data, bringing it in, assessing it. looking for the information to then analyze. So if you actually look at your income statement that you can just automate away. With software automation you can say, is that we are the bottleneck in the modern Is that kind of the trend that you guys are riding? given the computational resources and the data that we have, Yeah, I got to augment those people with does the product cost, how do people engage with you guys, hence the ability to charge such a high price. in the market that have been pushing AI solutions and you throw bodies at it, on your team. You have SE, and sales a contact on the customer's side. And they typically go, this is amazing, let's get started. and once you show 'em that I can manage all of Yeah, I mean you open up a whole new insight engine and how are you guys winning, why are you winning? a lot of the AI deployments that we see, And they're weak, or... Yeah, I would argue yes. acquire the knowledge from the data, you can have a leadership strategy, You mentioned you guys kind of dip into that. and the RPA companies are starting to come up If you look at RPA, my view is it's kind of a on the manufacturing line, we just put some robotics on How do you handle that, I mean... I mean you can date it all the way back to Yeah, if you're bored at Google or Facebook, Yeah, focusing big on the customers that we have now. We'll see how we end up. So it's go to market vertically, Okay, so once you nail an industry, I mean we see that every day someone wants to use Then you kind of lay down a foundational... and you know the vision of having this global platform Yeah, and for us, with new technologies, and that's hard. New models can emerge, with you guys in the center, I'm John Furrier, here in theCUBE studios in Palo Alto.
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Keynote Analysis | UiPath Forward 2018
(energetic music) >> Live from Miami Beach, Florida. It's theCUBE covering UiPathForward Americas. Brought to you by UiPath. >> Welcome to Miami everybody. This is theCUBE the leader in live tech coverage. We're here covering the UiPathForward Americas conference. UiPath is a company that has come out of nowhere, really. And, is a leader in robotic process automation, RPA. It really is about software robots. I am Dave Vellante and I am here with Stu Miniman. We have one day of coverage, Stu. We are all over the place this weekend. Aren't we? Stu and I were in Orlando earlier. Flew down. Quick flight to Miami and we're getting the Kool-Aid injection from the RPA crowd. We're at the Fontainebleau in Miami. Kind of cool hotel. Stu you might remember, I am sure, you do, several years ago we did the very first .NEXT tour. .NEXT from Nutanix at this event. About this same size, maybe a little smaller. This is a little bigger. >> Dave, this is probably twice the size, about 1,500 people here. I remember about a year ago you were, started buzzing about RPA. Big growth in the market, you know really enjoyed getting into the keynote here. You know, you said we were at splunk and data was at the center of everything, and the CEO here for (mumbles), it's automation first. We talked about mobile first, cloud first, automation first. I know we got a lot of things we want to talk about because you know, I think back through my career, and I know you do too, automation is something we've been talking about for years. We struggle with it. There's challenges there, but there's a lot of things coming together and that's why we have this new era that RPA is striking at to really explode this market. >> Yeah, so I made a little prediction that I put out on Twitter, I'll share with folks. I said there's a wide and a gap between the number of jobs available worldwide and the number for people to fill them. That's something that we know. And there's a productivity gap. And the numbers aren't showing up. We're not seeing bump-ups in productivity even though spending on technology is kind of through the roof. Robotic Process Automation is going to become a fundamental component of closing that gap because companies, as part of the digital process transformation, they want to automate. The market today is around a billion. We see it growing 10 x over the next five to seven years. We're going to have some analysts on today from Forester, we'll dig into that a little bit, they cover this market really, really closely. So, we're hearing a lot more about RPA. We heard it last week at Infor, Charles Phillips was a big proponent of this. UiPath has been in this business now for a few years. It came out of Romania. Daniel Dines, former Microsoft executive, very interesting fellow. First time I've seen him speak. We're going to meet him today. He is a techy. Comes on stage with a T-shirt, you know. He's very sort of thoughtful, he's talking about open, about culture, about having fun. Really dedicated to listening to customers and growing this business. He said, he gave us a data point that they went from nothing, just a couple of million dollars, two years ago. They'll do 140 million. They're doing 140 million now in annual reccurring revenue. On their way to 200. I would estimate, they'll probably get there. If not by the end of year, probably by the first quarter next year. So let's take look at some of the things that we heard in the keynote. We heard from customers. A lot of partners here. Seen a lot of the big SIs diving in. That's always a sign of big markets. What did you learn today at the keynotes? >> Yeah, Dave, first thing there is definitely, one of the push backs about automation is, "Oh wait what is that "going to do for jobs?" You touched on it. There's a lot of staff they threw out. They said that RPA can really bring, you know, 75% productivity improvement because we know productivity improvement kind of stalled out over all in the market. And, what we want to do is get rid of mundane tasks. Dave, I spent a long time of my career helping to get, you know, how to we get infrastructure simpler? How do we get rid of those routine things? The storage robe they said if you were configuring LUNs, you need to go find other jobs. If you were networking certain basic things, we're going to automate that with software. But there are things that the automation are going to be able to do, so that you can be more creative. You can spend more time doing some higher level functions. And that's where we have a skills gap. I'm excited we're going to have Tom Clancy, who you and I know. I've got his book on the shelf and not Tom Clancy the fiction author, but you know the Tom Clancy who has done certifications and education through storage and cloud and now how do we get people ready for this next wave of how you can do people and machines. One of my favorite events, Dave, that we ever did was the Second Machine Age with MIT in London. Talking about it's really people plus machines, is really where you're going to get that boom. You've interviewed Garry Kasparov on this topic and it's just fascinating and it really excites me as someone, I mean, I've lived with my computers all my life and just as a technologist, I'm optimistic at how, you know, the two sides together can be much more powerful than either alone. >> Well, it's an important topic Stu. A lot of the shows that we go to, the vendors don't want to talk about that. "Oh, we don't want to talk about displacing humans." UiPath's perspective on that, and we'll poke them a little on that is, "That's old news. "People are happy because they're replacing their 'mundane tasks.'" And while that's true, there's some action on Twitter. (mumbles name) just tweeted out, replying to some of the stuff that we were talking about here, in the hashtag, which is UiPathForward, #UiPathForward, "Automation displaces unskilled workers, "that's the crux of the problem. "We need best algorithms to automate re-training and "re-skilling of workers. "That's what we need the most for best socio-economic "outcomes, in parallel to automation through "algorithm driven machines," he's right. That gap, and we talked about this at 2MA, is it going to be a creativity gap? It's an education issue, it's an education challenge. 'Cause you just don't want to displace, unskilled workers, we want to re-train people. >> Right, absolutely. You could have this hollowing out of the market place otherwise, where you have really low paid workers on the one end, and you have really high-end creative workers but the middle, you know, the middle class workers could be displaced if they are not re-trained, they're not put forward. The World Economic Forum actually said that this automation is going to create 60-million net new jobs. Now, 60-million, it sounds like a big number, but it is a large global workforce. And, actually Dave, one of the things that really struck me is, not only do you have a Romanian founder but up on stage we had, a Japanese customer giving a video in Japanese with the subtitles in English. Not something that you typically see at a U.S. show. Very global, in their reach. You talked about the community and very open source focus of something we've seen. This is how software grows very fast as you get those people working. It's something I want to understand. They've got, the UiPath that's 2,000 customers but they've got 114,000 certified RPA developers. So, I'm like, okay, wait. Those numbers don't make sense to me yet, but I'm sure our guests are going to be able to explain them. >> And, so you're right about the need for education. I was impressed that UiPath is actually spending some of it the money that it's raised. This company, just did a monster raise, 225-million. We had Carl Ashenbach on in theCUBE studio to talk about that. Jeff Freck interviewed him last week. You can find that interview on our YouTube play list and I think on out website as well. But they invested, I think it was 10-million dollars with the goal of training a million students in the next three years. They've hired Tom Clancy, who we know from the old EMC education world. EMC training and education world. So they got a pro in here who knows to scale training. So that's huge. They've also started a 20-million investment fund investing in start ups and eco-system companies, so they're putting their money where their mouth is. The company has raised over 400-million dollars to date. They've got a 3-billion dollar evaluation. Some of the other things we've heard from the keynote today, um, they've got about 1,400 employees which is way up. They were just 270, I believe, last year. And they're claiming, and I think it's probably true, they're the fastest growing enterprise software company in history, which is kind of astounding. Like you said, given that they came out of Romania, this global company maybe that's part of the reason why. >> I mean, Dave, they said his goal is they're going to have 4,000 employees by 2019. Wait, there are a software company and they raised huge amounts of money. AS you said, they are a triple unicorn with a three billion dollar valuation. Why does a software company need so many employees? And 3,000, at least 3,000 of those are going to be technical because this is intricate. This is not push button simplicity. There's training that needs to happen. How much do they need to engage? How much of this is vertical knowledge that they need to get? I was at Microsoft Ignite two weeks ago. Microsoft is going really deep vertically because AI requires specialized knowledge in each verticals. How much of that is needed from RPA? You've got a little booklet that they have of some basic 101 of the RPA skills. >> I don't know if you can see this, but... Is that the right camera? So, it's this kind of robot pack. It's kind of fun. Kind of go through, it says, you got to reliable friend you can automate, you know, sending them a little birthday wish. They got QR codes in the back you can download it. You know, waiters so you can order online food. There's something called Tackle, for you fantasy football players who help you sort of automate your fantasy football picks. Which is kind of cool. So, that's fun. There's fun culture here, but really it's about digital transformation and driving it to the heart of process automation. Daniel Dines, talked about taking things from hours to minutes, from sort of accurate to perfectly accurate. You know, slow to fast. From very time consuming to automated. So, he puts forth this vision of automation first. He talked about the waves, main frames, you know the traditional waves client server, internet, etc. And then, you know I really want to poke at this and dig into it a little bit. He talked about a computer vision and that seemed to be a technical enabler. So, I'm envisioning this sort of computer vision, this visual, this ability to visualize a robot, to visualize what's happening on the screen, and then a studio to be able to program these things. I think those are a couple of the components I discerned. But, it's really about a cultural shift, a mind shift, is what Daniel talked about, towards an automation first opportunity. >> And Dave, one of the things you said right there... Three things, the convergence of computer vision, the Summer of AI, and what he meant by that is that we've lived through a bunch of winters. And we've been talking about this. And, then the business.. >> Ice age of a, uh... >> Business, process, automation together, those put together and we can create that automation first era. And, he talked about... We've been talking about automation since the creation of the first computer. So, it's not a new idea. Just like, you know we've been talking on theCUBE for years. You know, data science isn't a new thing. We sometimes give these things new terms like RPA. But, I love digging into why these are real, and just as we've seen these are real indicators, you know, intelligence with like, whether you call it AI or ML, are doing things in various environments that we could not do in the past. Just borders of magnitude, more processing, data is more important. We could do more there. You know, are we on the cusp of really automation. being able to deliver on the things that we've been trying to talk about a couple of generations? >> So a couple of other stats that I thought were interesting. Daniel put forth a vision of one robot for every person to use. A computer for every person. A chicken for every pot, kind of thing (laughs) So, that was kind of cool. >> "PC for every person," Bill Gates. >> Right, an open and free mind set, so he talked a about, Daniel talked about of an era of openness. And UiPath has a market place where all the automations. you can put automations in there, they're all free to use. So, they're making money on the software and not on the automation. So, they really have this... He said, "We're making our competitors better. "They're copying what we're doing, "and we think that's a good thing. "Because it's going to help change the world." It's about affecting society, so the rising tides lift all boats. >> Yeah Dave, it reminds me a lot of, you know, you look at GitHub, you look at Docker Hub. There's lots of places. This is where code lives in these open market places. You know, not quite like the AWS or IBM market places where you can you can just buy software, but the question is how many developers get in there. They say they got 250,000 community members already there. So, and already what do they have? I think hundreds of processes that are built in there, so that will be a good metric we can see to how fast that scales. >> We had heard from a couple of customers, and Wells Fargo was up there, and United Health. Mr. Yamomoto from SNBC, they have 1,000 robots. So, they are really completely transforming their organization. We heard from a partner, Data Robot, Jeremy Atchins, somebody who's been on theCUBE before, Data Robot. They showed an automated loan processing where you could go in, talk to a chat bot and within minutes get qualified for a loan. I don't know if you noticed the loan amount was $7,000 and the interest rate was 13.6% so the applicant, really, must not of had great credit history. Cause that's kind of loan shark rates, but anyway, it was kind of a cool demo with the back end data robot munging all the data, doing whatever they had to do, transferring through a CSV into the software robot and then making that decision. So, that was kind of cool, those integrations seemed to be pretty key. I want to learn more about that. >> I mean it reminds me of chat box have been hot in a lot of areas lately, as how we can improve customer support and automate things on infrastructure in the likes of, we'll see how those intersections meet. >> Yeah, so we're going to be covering this all day. We got technologists coming on, customers, partners. Stu and I will be jamming. He's @Stu and I'm @Dvellante. Shoot us any questions, comments. Thanks for the ones we've had so far. We're here at the Fontainebleau in Miami Beach. Pretty crazy hotel. A lot of history here. A lot of pictures of Frank Sinatra on the wall. Keep it right there, buddy. You're watching theCUBE. We'll be right back after this short break. (energetic music)
SUMMARY :
Brought to you by UiPath. We are all over the place this weekend. Big growth in the market, Seen a lot of the big SIs diving in. of my career helping to get, A lot of the shows that we but the middle, you know, Some of the other things 101 of the RPA skills. They got QR codes in the And Dave, one of the of the first computer. So a couple of other on the software and not on but the question is how many and the interest rate was in the likes of, we'll see Thanks for the ones we've had so far.
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Rob Thomas, IBM | Change the Game: Winning With AI 2018
>> [Announcer] Live from Times Square in New York City, it's theCUBE covering IBM's Change the Game: Winning with AI, brought to you by IBM. >> Hello everybody, welcome to theCUBE's special presentation. We're covering IBM's announcements today around AI. IBM, as theCUBE does, runs of sessions and programs in conjunction with Strata, which is down at the Javits, and we're Rob Thomas, who's the General Manager of IBM Analytics. Long time Cube alum, Rob, great to see you. >> Dave, great to see you. >> So you guys got a lot going on today. We're here at the Westin Hotel, you've got an analyst event, you've got a partner meeting, you've got an event tonight, Change the game: winning with AI at Terminal 5, check that out, ibm.com/WinWithAI, go register there. But Rob, let's start with what you guys have going on, give us the run down. >> Yeah, it's a big week for us, and like many others, it's great when you have Strata, a lot of people in town. So, we've structured a week where, today, we're going to spend a lot of time with analysts and our business partners, talking about where we're going with data and AI. This evening, we've got a broadcast, it's called Winning with AI. What's unique about that broadcast is it's all clients. We've got clients on stage doing demonstrations, how they're using IBM technology to get to unique outcomes in their business. So I think it's going to be a pretty unique event, which should be a lot of fun. >> So this place, it looks like a cool event, a venue, Terminal 5, it's just up the street on the west side highway, probably a mile from the Javits Center, so definitely check that out. Alright, let's talk about, Rob, we've known each other for a long time, we've seen the early Hadoop days, you guys were very careful about diving in, you kind of let things settle and watched very carefully, and then came in at the right time. But we saw the evolution of so-called Big Data go from a phase of really reducing investments, cheaper data warehousing, and what that did is allowed people to collect a lot more data, and kind of get ready for this era that we're in now. But maybe you can give us your perspective on the phases, the waves that we've seen of data, and where we are today and where we're going. >> I kind of think of it as a maturity curve. So when I go talk to clients, I say, look, you need to be on a journey towards AI. I think probably nobody disagrees that they need something there, the question is, how do you get there? So you think about the steps, it's about, a lot of people started with, we're going to reduce the cost of our operations, we're going to use data to take out cost, that was kind of the Hadoop thrust, I would say. Then they moved to, well, now we need to see more about our data, we need higher performance data, BI data warehousing. So, everybody, I would say, has dabbled in those two area. The next leap forward is self-service analytics, so how do you actually empower everybody in your organization to use and access data? And the next step beyond that is, can I use AI to drive new business models, new levers of growth, for my business? So, I ask clients, pin yourself on this journey, most are, depends on the division or the part of the company, they're at different areas, but as I tell everybody, if you don't know where you are and you don't know where you want to go, you're just going to wind around, so I try to get them to pin down, where are you versus where do you want to go? >> So four phases, basically, the sort of cheap data store, the BI data warehouse modernization, self-service analytics, a big part of that is data science and data science collaboration, you guys have a lot of investments there, and then new business models with AI automation running on top. Where are we today? Would you say we're kind of in-between BI/DW modernization and on our way to self-service analytics, or what's your sense? >> I'd say most are right in the middle between BI data warehousing and self-service analytics. Self-service analytics is hard, because it requires you, sometimes to take a couple steps back, and look at your data. It's hard to provide self-service if you don't have a data catalog, if you don't have data security, if you haven't gone through the processes around data governance. So, sometimes you have to take one step back to go two steps forward, that's why I see a lot of people, I'd say, stuck in the middle right now. And the examples that you're going to see tonight as part of the broadcast are clients that have figured out how to break through that wall, and I think that's pretty illustrative of what's possible. >> Okay, so you're saying that, got to maybe take a step back and get the infrastructure right with, let's say a catalog, to give some basic things that they have to do, some x's and o's, you've got the Vince Lombardi played out here, and also, skillsets, I imagine, is a key part of that. So, that's what they've got to do to get prepared, and then, what's next? They start creating new business models, imagining this is where the cheap data officer comes in and it's an executive level, what are you seeing clients as part of digital transformation, what's the conversation like with customers? >> The biggest change, the great thing about the times we live in, is technology's become so accessible, you can do things very quickly. We created a team last year called Data Science Elite, and we've hired what we think are some of the best data scientists in the world. Their only job is to go work with clients and help them get to a first success with data science. So, we put a team in. Normally, one month, two months, normally a team of two or three people, our investment, and we say, let's go build a model, let's get to an outcome, and you can do this incredibly quickly now. I tell clients, I see somebody that says, we're going to spend six months evaluating and thinking about this, I was like, why would you spend six months thinking about this when you could actually do it in one month? So you just need to get over the edge and go try it. >> So we're going to learn more about the Data Science Elite team. We've got John Thomas coming on today, who is a distinguished engineer at IBM, and he's very much involved in that team, and I think we have a customer who's actually gone through that, so we're going to talk about what their experience was with the Data Science Elite team. Alright, you've got some hard news coming up, you've actually made some news earlier with Hortonworks and Red Hat, I want to talk about that, but you've also got some hard news today. Take us through that. >> Yeah, let's talk about all three. First, Monday we announced the expanded relationship with both Hortonworks and Red Hat. This goes back to one of the core beliefs I talked about, every enterprise is modernizing their data and application of states, I don't think there's any debate about that. We are big believers in Kubernetes and containers as the architecture to drive that modernization. The announcement on Monday was, we're working closer with Red Hat to take all of our data services as part of Cloud Private for Data, which are basically microservice for data, and we're running those on OpenShift, and we're starting to see great customer traction with that. And where does Hortonworks come in? Hadoop has been the outlier on moving to microservices containers, we're working with Hortonworks to help them make that move as well. So, it's really about the three of us getting together and helping clients with this modernization journey. >> So, just to remind people, you remember ODPI, folks? It was all this kerfuffle about, why do we even need this? Well, what's interesting to me about this triumvirate is, well, first of all, Red Hat and Hortonworks are hardcore opensource, IBM's always been a big supporter of open source. You three got together and you're proving now the productivity for customers of this relationship. You guys don't talk about this, but Hortonworks had to, when it's public call, that the relationship with IBM drove many, many seven-figure deals, which, obviously means that customers are getting value out of this, so it's great to see that come to fruition, and it wasn't just a Barney announcement a couple years ago, so congratulations on that. Now, there's this other news that you guys announced this morning, talk about that. >> Yeah, two other things. One is, we announced a relationship with Stack Overflow. 50 million developers go to Stack Overflow a month, it's an amazing environment for developers that are looking to do new things, and we're sponsoring a community around AI. Back to your point before, you said, is there a skills gap in enterprises, there absolutely is, I don't think that's a surprise. Data science, AI developers, not every company has the skills they need, so we're sponsoring a community to help drive the growth of skills in and around data science and AI. So things like Python, R, Scala, these are the languages of data science, and it's a great relationship with us and Stack Overflow to build a community to get things going on skills. >> Okay, and then there was one more. >> Last one's a product announcement. This is one of the most interesting product annoucements we've had in quite a while. Imagine this, you write a sequel query, and traditional approach is, I've got a server, I point it as that server, I get the data, it's pretty limited. We're announcing technology where I write a query, and it can find data anywhere in the world. I think of it as wide-area sequel. So it can find data on an automotive device, a telematics device, an IoT device, it could be a mobile device, we think of it as sequel the whole world. You write a query, you can find the data anywhere it is, and we take advantage of the processing power on the edge. The biggest problem with IoT is, it's been the old mantra of, go find the data, bring it all back to a centralized warehouse, that makes it impossible to do it real time. We're enabling real time because we can write a query once, find data anywhere, this is technology we've had in preview for the last year. We've been working with a lot of clients to prove out used cases to do it, we're integrating as the capability inside of IBM Cloud Private for Data. So if you buy IBM Cloud for Data, it's there. >> Interesting, so when you've been around as long as I have, long enough to see some of the pendulums swings, and it's clearly a pendulum swing back toward decentralization in the edge, but the key is, from what you just described, is you're sort of redefining the boundary, so I presume it's the edge, any Cloud, or on premises, where you can find that data, is that correct? >> Yeah, so it's multi-Cloud. I mean, look, every organization is going to be multi-Cloud, like 100%, that's going to happen, and that could be private, it could be multiple public Cloud providers, but the key point is, data on the edge is not just limited to what's in those Clouds. It could be anywhere that you're collecting data. And, we're enabling an architecture which performs incredibly well, because you take advantage of processing power on the edge, where you can get data anywhere that it sits. >> Okay, so, then, I'm setting up a Cloud, I'll call it a Cloud architecture, that encompasses the edge, where essentially, there are no boundaries, and you're bringing security. We talked about containers before, we've been talking about Kubernetes all week here at a Big Data show. And then of course, Cloud, and what's interesting, I think many of the Hadoop distral vendors kind of missed Cloud early on, and then now are sort of saying, oh wow, it's a hybrid world and we've got a part, you guys obviously made some moves, a couple billion dollar moves, to do some acquisitions and get hardcore into Cloud, so that becomes a critical component. You're not just limiting your scope to the IBM Cloud. You're recognizing that it's a multi-Cloud world, that' what customers want to do. Your comments. >> It's multi-Cloud, and it's not just the IBM Cloud, I think the most predominant Cloud that's emerging is every client's private Cloud. Every client I talk to is building out a containerized architecture. They need their own Cloud, and they need seamless connectivity to any public Cloud that they may be using. This is why you see such a premium being put on things like data ingestion, data curation. It's not popular, it's not exciting, people don't want to talk about it, but we're the biggest inhibitors, to this AI point, comes back to data curation, data ingestion, because if you're dealing with multiple Clouds, suddenly your data's in a bunch of different spots. >> Well, so you're basically, and we talked about this a lot on theCUBE, you're bringing the Cloud model to the data, wherever the data lives. Is that the right way to think about it? >> I think organizations have spoken, set aside what they say, look at their actions. Their actions say, we don't want to move all of our data to any particular Cloud, we'll move some of our data. We need to give them seamless connectivity so that they can leave their data where they want, we can bring Cloud-Native Architecture to their data, we could also help move their data to a Cloud-Native architecture if that's what they prefer. >> Well, it makes sense, because you've got physics, latency, you've got economics, moving all the data into a public Cloud is expensive and just doesn't make economic sense, and then you've got things like GDPR, which says, well, you have to keep the data, certain laws of the land, if you will, that say, you've got to keep the data in whatever it is, in Germany, or whatever country. So those sort of edicts dictate how you approach managing workloads and what you put where, right? Okay, what's going on with Watson? Give us the update there. >> I get a lot of questions, people trying to peel back the onion of what exactly is it? So, I want to make that super clear here. Watson is a few things, start at the bottom. You need a runtime for models that you've built. So we have a product called Watson Machine Learning, runs anywhere you want, that is the runtime for how you execute models that you've built. Anytime you have a runtime, you need somewhere where you can build models, you need a development environment. That is called Watson Studio. So, we had a product called Data Science Experience, we've evolved that into Watson Studio, connecting in some of those features. So we have Watson Studio, that's the development environment, Watson Machine Learning, that's the runtime. Now you move further up the stack. We have a set of APIs that bring in human features, vision, natural language processing, audio analytics, those types of things. You can integrate those as part of a model that you build. And then on top of that, we've got things like Watson Applications, we've got Watson for call centers, doing customer service and chatbots, and then we've got a lot of clients who've taken pieces of that stack and built their own AI solutions. They've taken some of the APIs, they've taken some of the design time, the studio, they've taken some of the Watson Machine Learning. So, it is really a stack of capabilities, and where we're driving the greatest productivity, this is in a lot of the examples you'll see tonight for clients, is clients that have bought into this idea of, I need a development environment, I need a runtime, where I can deploy models anywhere. We're getting a lot of momentum on that, and then that raises the question of, well, do I have expandability, do I have trust in transparency, and that's another thing that we're working on. >> Okay, so there's API oriented architecture, exposing all these services make it very easy for people to consume. Okay, so we've been talking all week at Cube NYC, is Big Data is in AI, is this old wine, new bottle? I mean, it's clear, Rob, from the conversation here, there's a lot of substantive innovation, and early adoption, anyway, of some of these innovations, but a lot of potential going forward. Last thoughts? >> What people have to realize is AI is not magic, it's still computer science. So it actually requires some hard work. You need to roll up your sleeves, you need to understand how I get from point A to point B, you need a development environment, you need a runtime. I want people to really think about this, it's not magic. I think for a while, people have gotten the impression that there's some magic button. There's not, but if you put in the time, and it's not a lot of time, you'll see the examples tonight, most of them have been done in one or two months, there's great business value in starting to leverage AI in your business. >> Awesome, alright, so if you're in this city or you're at Strata, go to ibm.com/WinWithAI, register for the event tonight. Rob, we'll see you there, thanks so much for coming back. >> Yeah, it's going to be fun, thanks Dave, great to see you. >> Alright, keep it right there everybody, we'll be back with our next guest right after this short break, you're watching theCUBE.
SUMMARY :
brought to you by IBM. Long time Cube alum, Rob, great to see you. But Rob, let's start with what you guys have going on, it's great when you have Strata, a lot of people in town. and kind of get ready for this era that we're in now. where you want to go, you're just going to wind around, and data science collaboration, you guys have It's hard to provide self-service if you don't have and it's an executive level, what are you seeing let's get to an outcome, and you can do this and I think we have a customer who's actually as the architecture to drive that modernization. So, just to remind people, you remember ODPI, folks? has the skills they need, so we're sponsoring a community and it can find data anywhere in the world. of processing power on the edge, where you can get data a couple billion dollar moves, to do some acquisitions This is why you see such a premium being put on things Is that the right way to think about it? to a Cloud-Native architecture if that's what they prefer. certain laws of the land, if you will, that say, for how you execute models that you've built. I mean, it's clear, Rob, from the conversation here, and it's not a lot of time, you'll see the examples tonight, Rob, we'll see you there, thanks so much for coming back. we'll be back with our next guest
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Influencer Panel | theCUBE NYC 2018
- [Announcer] Live, from New York, it's theCUBE. Covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media, and its ecosystem partners. - Hello everyone, welcome back to CUBE NYC. This is a CUBE special presentation of something that we've done now for the past couple of years. IBM has sponsored an influencer panel on some of the hottest topics in the industry, and of course, there's no hotter topic right now than AI. So, we've got nine of the top influencers in the AI space, and we're in Hell's Kitchen, and it's going to get hot in here. (laughing) And these guys, we're going to cover the gamut. So, first of all, folks, thanks so much for joining us today, really, as John said earlier, we love the collaboration with you all, and we'll definitely see you on social after the fact. I'm Dave Vellante, with my cohost for this session, Peter Burris, and again, thank you to IBM for sponsoring this and organizing this. IBM has a big event down here, in conjunction with Strata, called Change the Game, Winning with AI. We run theCUBE NYC, we've been here all week. So, here's the format. I'm going to kick it off, and then we'll see where it goes. So, I'm going to introduce each of the panelists, and then ask you guys to answer a question, I'm sorry, first, tell us a little bit about yourself, briefly, and then answer one of the following questions. Two big themes that have come up this week. One has been, because this is our ninth year covering what used to be Hadoop World, which kind of morphed into big data. Question is, AI, big data, same wine, new bottle? Or is it really substantive, and driving business value? So, that's one question to ponder. The other one is, you've heard the term, the phrase, data is the new oil. Is data really the new oil? Wonder what you think about that? Okay, so, Chris Penn, let's start with you. Chris is cofounder of Trust Insight, long time CUBE alum, and friend. Thanks for coming on. Tell us a little bit about yourself, and then pick one of those questions. - Sure, we're a data science consulting firm. We're an IBM business partner. When it comes to "data is the new oil," I love that expression because it's completely accurate. Crude oil is useless, you have to extract it out of the ground, refine it, and then bring it to distribution. Data is the same way, where you have to have developers and data architects get the data out. You need data scientists and tools, like Watson Studio, to refine it, and then you need to put it into production, and that's where marketing technologists, technologists, business analytics folks, and tools like Watson Machine Learning help bring the data and make it useful. - Okay, great, thank you. Tony Flath is a tech and media consultant, focus on cloud and cyber security, welcome. - Thank you. - Tell us a little bit about yourself and your thoughts on one of those questions. - Sure thing, well, thanks so much for having us on this show, really appreciate it. My background is in cloud, cyber security, and certainly in emerging tech with artificial intelligence. Certainly touched it from a cyber security play, how you can use machine learning, machine control, for better controlling security across the gamut. But I'll touch on your question about wine, is it a new bottle, new wine? Where does this come from, from artificial intelligence? And I really see it as a whole new wine that is coming along. When you look at emerging technology, and you look at all the deep learning that's happening, it's going just beyond being able to machine learn and know what's happening, it's making some meaning to that data. And things are being done with that data, from robotics, from automation, from all kinds of different things, where we're at a point in society where data, our technology is getting beyond us. Prior to this, it's always been command and control. You control data from a keyboard. Well, this is passing us. So, my passion and perspective on this is, the humanization of it, of IT. How do you ensure that people are in that process, right? - Excellent, and we're going to come back and talk about that. - Thanks so much. - Carla Gentry, @DataNerd? Great to see you live, as opposed to just in the ether on Twitter. Data scientist, and owner of Analytical Solution. Welcome, your thoughts? - Thank you for having us. Mine is, is data the new oil? And I'd like to rephrase that is, data equals human lives. So, with all the other artificial intelligence and everything that's going on, and all the algorithms and models that's being created, we have to think about things being biased, being fair, and understand that this data has impacts on people's lives. - Great. Steve Ardire, my paisan. - Paisan. - AI startup adviser, welcome, thanks for coming to theCUBE. - Thanks Dave. So, uh, my first career was geology, and I view AI as the new oil, but data is the new oil, but AI is the refinery. I've used that many times before. In fact, really, I've moved from just AI to augmented intelligence. So, augmented intelligence is really the way forward. This was a presentation I gave at IBM Think last spring, has almost 100,000 impressions right now, and the fundamental reason why is machines can attend to vastly more information than humans, but you still need humans in the loop, and we can talk about what they're bringing in terms of common sense reasoning, because big data does the who, what, when, and where, but not the why, and why is really the Holy Grail for causal analysis and reasoning. - Excellent, Bob Hayes, Business Over Broadway, welcome, great to see you again. - Thanks for having me. So, my background is in psychology, industrial psychology, and I'm interested in things like customer experience, data science, machine learning, so forth. And I'll answer the question around big data versus AI. And I think there's other terms we could talk about, big data, data science, machine learning, AI. And to me, it's kind of all the same. It's always been about analytics, and getting value from your data, big, small, what have you. And there's subtle differences among those terms. Machine learning is just about making a prediction, and knowing if things are classified correctly. Data science is more about understanding why things work, and understanding maybe the ethics behind it, what variables are predicting that outcome. But still, it's all the same thing, it's all about using data in a way that we can get value from that, as a society, in residences. - Excellent, thank you. Theo Lau, founder of Unconventional Ventures. What's your story? - Yeah, so, my background is driving technology innovation. So, together with my partner, what our work does is we work with organizations to try to help them leverage technology to drive systematic financial wellness. We connect founders, startup founders, with funders, we help them get money in the ecosystem. We also work with them to look at, how do we leverage emerging technology to do something good for the society. So, very much on point to what Bob was saying about. So when I look at AI, it is not new, right, it's been around for quite a while. But what's different is the amount of technological power that we have allow us to do so much more than what we were able to do before. And so, what my mantra is, great ideas can come from anywhere in the society, but it's our job to be able to leverage technology to shine a spotlight on people who can use this to do something different, to help seniors in our country to do better in their financial planning. - Okay, so, in your mind, it's not just a same wine, new bottle, it's more substantive than that. - [Theo] It's more substantive, it's a much better bottle. - Karen Lopez, senior project manager for Architect InfoAdvisors, welcome. - Thank you. So, I'm DataChick on twitter, and so that kind of tells my focus is that I'm here, I also call myself a data evangelist, and that means I'm there at organizations helping stand up for the data, because to me, that's the proxy for standing up for the people, and the places and the events that that data describes. That means I have a focus on security, data privacy and protection as well. And I'm going to kind of combine your two questions about whether data is the new wine bottle, I think is the combination. Oh, see, now I'm talking about alcohol. (laughing) But anyway, you know, all analogies are imperfect, so whether we say it's the new wine, or, you know, same wine, or whether it's oil, is that the analogy's good for both of them, but unlike oil, the amount of data's just growing like crazy, and the oil, we know at some point, I kind of doubt that we're going to hit peak data where we have not enough data, like we're going to do with oil. But that says to me that, how did we get here with big data, with machine learning and AI? And from my point of view, as someone who's been focused on data for 35 years, we have hit this perfect storm of open source technologies, cloud architectures and cloud services, data innovation, that if we didn't have those, we wouldn't be talking about large machine learning and deep learning-type things. So, because we have all these things coming together at the same time, we're now at explosions of data, which means we also have to protect them, and protect the people from doing harm with data, we need to do data for good things, and all of that. - Great, definite differences, we're not running out of data, data's like the terrible tribbles. (laughing) - Yes, but it's very cuddly, data is. - Yeah, cuddly data. Mark Lynd, founder of Relevant Track? - That's right. - I like the name. What's your story? - Well, thank you, and it actually plays into what my interest is. It's mainly around AI in enterprise operations and cyber security. You know, these teams that are in enterprise operations both, it can be sales, marketing, all the way through the organization, as well as cyber security, they're often under-sourced. And they need, what Steve pointed out, they need augmented intelligence, they need to take AI, the big data, all the information they have, and make use of that in a way where they're able to, even though they're under-sourced, make some use and some value for the organization, you know, make better use of the resources they have to grow and support the strategic goals of the organization. And oftentimes, when you get to budgeting, it doesn't really align, you know, you're short people, you're short time, but the data continues to grow, as Karen pointed out. So, when you take those together, using AI to augment, provided augmented intelligence, to help them get through that data, make real tangible decisions based on information versus just raw data, especially around cyber security, which is a big hit right now, is really a great place to be, and there's a lot of stuff going on, and a lot of exciting stuff in that area. - Great, thank you. Kevin L. Jackson, author and founder of GovCloud. GovCloud, that's big. - Yeah, GovCloud Network. Thank you very much for having me on the show. Up and working on cloud computing, initially in the federal government, with the intelligence community, as they adopted cloud computing for a lot of the nation's major missions. And what has happened is now I'm working a lot with commercial organizations and with the security of that data. And I'm going to sort of, on your questions, piggyback on Karen. There was a time when you would get a couple of bottles of wine, and they would come in, and you would savor that wine, and sip it, and it would take a few days to get through it, and you would enjoy it. The problem now is that you don't get a couple of bottles of wine into your house, you get two or three tankers of data. So, it's not that it's a new wine, you're just getting a lot of it. And the infrastructures that you need, before you could have a couple of computers, and a couple of people, now you need cloud, you need automated infrastructures, you need huge capabilities, and artificial intelligence and AI, it's what we can use as the tool on top of these huge infrastructures to drink that, you know. - Fire hose of wine. - Fire hose of wine. (laughs) - Everybody's having a good time. - Everybody's having a great time. (laughs) - Yeah, things are booming right now. Excellent, well, thank you all for those intros. Peter, I want to ask you a question. So, I heard there's some similarities and some definite differences with regard to data being the new oil. You have a perspective on this, and I wonder if you could inject it into the conversation. - Sure, so, the perspective that we take in a lot of conversations, a lot of folks here in theCUBE, what we've learned, and I'll kind of answer both questions a little bit. First off, on the question of data as the new oil, we definitely think that data is the new asset that business is going to be built on, in fact, our perspective is that there really is a difference between business and digital business, and that difference is data as an asset. And if you want to understand data transformation, you understand the degree to which businesses reinstitutionalizing work, reorganizing its people, reestablishing its mission around what you can do with data as an asset. The difference between data and oil is that oil still follows the economics of scarcity. Data is one of those things, you can copy it, you can share it, you can easily corrupt it, you can mess it up, you can do all kinds of awful things with it if you're not careful. And it's that core fundamental proposition that as an asset, when we think about cyber security, we think, in many respects, that is the approach to how we can go about privatizing data so that we can predict who's actually going to be able to appropriate returns on it. So, it's a good analogy, but as you said, it's not entirely perfect, but it's not perfect in a really fundamental way. It's not following the laws of scarcity, and that has an enormous effect. - In other words, I could put oil in my car, or I could put oil in my house, but I can't put the same oil in both. - Can't put it in both places. And now, the issue of the wine, I think it's, we think that it is, in fact, it is a new wine, and very simple abstraction, or generalization we come up with is the issue of agency. That analytics has historically not taken on agency, it hasn't acted on behalf of the brand. AI is going to act on behalf of the brand. Now, you're going to need both of them, you can't separate them. - A lot of implications there in terms of bias. - Absolutely. - In terms of privacy. You have a thought, here, Chris? - Well, the scarcity is our compute power, and our ability for us to process it. I mean, it's the same as oil, there's a ton of oil under the ground, right, we can't get to it as efficiently, or without severe environmental consequences to use it. Yeah, when you use it, it's transformed, but our scarcity is compute power, and our ability to use it intelligently. - Or even when you find it. I have data, I can apply it to six different applications, I have oil, I can apply it to one, and that's going to matter in how we think about work. - But one thing I'd like to add, sort of, you're talking about data as an asset. The issue we're having right now is we're trying to learn how to manage that asset. Artificial intelligence is a way of managing that asset, and that's important if you're going to use and leverage big data. - Yeah, but see, everybody's talking about the quantity, the quantity, it's not always the quantity. You know, we can have just oodles and oodles of data, but if it's not clean data, if it's not alphanumeric data, which is what's needed for machine learning. So, having lots of data is great, but you have to think about the signal versus the noise. So, sometimes you get so much data, you're looking at over-fitting, sometimes you get so much data, you're looking at biases within the data. So, it's not the amount of data, it's the, now that we have all of this data, making sure that we look at relevant data, to make sure we look at clean data. - One more thought, and we have a lot to cover, I want to get inside your big brain. - I was just thinking about it from a cyber security perspective, one of my customers, they were looking at the data that just comes from the perimeter, your firewalls, routers, all of that, and then not even looking internally, just the perimeter alone, and the amount of data being pulled off of those. And then trying to correlate that data so it makes some type of business sense, or they can determine if there's incidents that may happen, and take a predictive action, or threats that might be there because they haven't taken a certain action prior, it's overwhelming to them. So, having AI now, to be able to go through the logs to look at, and there's so many different types of data that come to those logs, but being able to pull that information, as well as looking at end points, and all that, and people's houses, which are an extension of the network oftentimes, it's an amazing amount of data, and they're only looking at a small portion today because they know, there's not enough resources, there's not enough trained people to do all that work. So, AI is doing a wonderful way of doing that. And some of the tools now are starting to mature and be sophisticated enough where they provide that augmented intelligence that Steve talked about earlier. - So, it's complicated. There's infrastructure, there's security, there's a lot of software, there's skills, and on and on. At IBM Think this year, Ginni Rometty talked about, there were a couple of themes, one was augmented intelligence, that was something that was clear. She also talked a lot about privacy, and you own your data, etc. One of the things that struck me was her discussion about incumbent disruptors. So, if you look at the top five companies, roughly, Facebook with fake news has dropped down a little bit, but top five companies in terms of market cap in the US. They're data companies, all right. Apple just hit a trillion, Amazon, Google, etc. How do those incumbents close the gap? Is that concept of incumbent disruptors actually something that is being put into practice? I mean, you guys work with a lot of practitioners. How are they going to close that gap with the data haves, meaning data at their core of their business, versus the data have-nots, it's not that they don't have a lot of data, but it's in silos, it's hard to get to? - Yeah, I got one more thing, so, you know, these companies, and whoever's going to be big next is, you have a digital persona, whether you want it or not. So, if you live in a farm out in the middle of Oklahoma, you still have a digital persona, people are collecting data on you, they're putting profiles of you, and the big companies know about you, and people that first interact with you, they're going to know that you have this digital persona. Personal AI, when AI from these companies could be used simply and easily, from a personal deal, to fill in those gaps, and to have a digital persona that supports your family, your growth, both personal and professional growth, and those type of things, there's a lot of applications for AI on a personal, enterprise, even small business, that have not been done yet, but the data is being collected now. So, you talk about the oil, the oil is being built right now, lots, and lots, and lots of it. It's the applications to use that, and turn that into something personally, professionally, educationally, powerful, that's what's missing. But it's coming. - Thank you, so, I'll add to that, and in answer to your question you raised. So, one example we always used in banking is, if you look at the big banks, right, and then you look at from a consumer perspective, and there's a lot of talk about Amazon being a bank. But the thing is, Amazon doesn't need to be a bank, they provide banking services, from a consumer perspective they don't really care if you're a bank or you're not a bank, but what's different between Amazon and some of the banks is that Amazon, like you say, has a lot of data, and they know how to make use of the data to offer something as relevant that consumers want. Whereas banks, they have a lot of data, but they're all silos, right. So, it's not just a matter of whether or not you have the data, it's also, can you actually access it and make something useful out of it so that you can create something that consumers want? Because otherwise, you're just a pipe. - Totally agree, like, when you look at it from a perspective of, there's a lot of terms out there, digital transformation is thrown out so much, right, and go to cloud, and you migrate to cloud, and you're going to take everything over, but really, when you look at it, and you both touched on it, it's the economics. You have to look at the data from an economics perspective, and how do you make some kind of way to take this data meaningful to your customers, that's going to work effectively for them, that they're going to drive? So, when you look at the big, big cloud providers, I think the push in things that's going to happen in the next few years is there's just going to be a bigger migration to public cloud. So then, between those, they have to differentiate themselves. Obvious is artificial intelligence, in a way that makes it easy to aggregate data from across platforms, to aggregate data from multi-cloud, effectively. To use that data in a meaningful way that's going to drive, not only better decisions for your business, and better outcomes, but drives our opportunities for customers, drives opportunities for employees and how they work. We're at a really interesting point in technology where we get to tell technology what to do. It's going beyond us, it's no longer what we're telling it to do, it's going to go beyond us. So, how we effectively manage that is going to be where we see that data flow, and those big five or big four, really take that to the next level. - Now, one of the things that Ginni Rometty said was, I forget the exact step, but it was like, 80% of the data, is not searchable. Kind of implying that it's sitting somewhere behind a firewall, presumably on somebody's premises. So, it was kind of interesting. You're talking about, certainly, a lot of momentum for public cloud, but at the same time, a lot of data is going to stay where it is. - Yeah, we're assuming that a lot of this data is just sitting there, available and ready, and we look at the desperate, or disparate kind of database situation, where you have 29 databases, and two of them have unique quantifiers that tie together, and the rest of them don't. So, there's nothing that you can do with that data. So, artificial intelligence is just that, it's artificial intelligence, so, they know, that's machine learning, that's natural language, that's classification, there's a lot of different parts of that that are moving, but we also have to have IT, good data infrastructure, master data management, compliance, there's so many moving parts to this, that it's not just about the data anymore. - I want to ask Steve to chime in here, go ahead. - Yeah, so, we also have to change the mentality that it's not just enterprise data. There's data on the web, the biggest thing is Internet of Things, the amount of sensor data will make the current data look like chump change. So, data is moving faster, okay. And this is where the sophistication of machine learning needs to kick in, going from just mostly supervised-learning today, to unsupervised learning. And in order to really get into, as I said, big data, and credible AI does the who, what, where, when, and how, but not the why. And this is really the Holy Grail to crack, and it's actually under a new moniker, it's called explainable AI, because it moves beyond just correlation into root cause analysis. Once we have that, then you have the means to be able to tap into augmented intelligence, where humans are working with the machines. - Karen, please. - Yeah, so, one of the things, like what Carla was saying, and what a lot of us had said, I like to think of the advent of ML technologies and AI are going to help me as a data architect to love my data better, right? So, that includes protecting it, but also, when you say that 80% of the data is unsearchable, it's not just an access problem, it's that no one knows what it was, what the sovereignty was, what the metadata was, what the quality was, or why there's huge anomalies in it. So, my favorite story about this is, in the 1980s, about, I forget the exact number, but like, 8 million children disappeared out of the US in April, at April 15th. And that was when the IRS enacted a rule that, in order to have a dependent, a deduction for a dependent on your tax returns, they had to have a valid social security number, and people who had accidentally miscounted their children and over-claimed them, (laughter) over the years them, stopped doing that. Well, some days it does feel like you have eight children running around. (laughter) - Agreed. - When, when that rule came about, literally, and they're not all children, because they're dependents, but literally millions of children disappeared off the face of the earth in April, but if you were doing analytics, or AI and ML, and you don't know that this anomaly happened, I can imagine in a hundred years, someone is saying some catastrophic event happened in April, 1983. (laughter) And what caused that, was it healthcare? Was it a meteor? Was it the clown attacking them? - That's where I was going. - Right. So, those are really important things that I want to use AI and ML to help me, not only document and capture that stuff, but to provide that information to the people, the data scientists and the analysts that are using the data. - Great story, thank you. Bob, you got a thought? You got the mic, go, jump in here. - Well, yeah, I do have a thought, actually. I was talking about, what Karen was talking about. I think it's really important that, not only that we understand AI, and machine learning, and data science, but that the regular folks and companies understand that, at the basic level. Because those are the people who will ask the questions, or who know what questions to ask of the data. And if they don't have the tools, and the knowledge of how to get access to that data, or even how to pose a question, then that data is going to be less valuable, I think, to companies. And the more that everybody knows about data, even people in congress. Remember when Zuckerberg talked about? (laughter) - That was scary. - How do you make money? It's like, we all know this. But, we need to educate the masses on just basic data analytics. - We could have an hour-long panel on that. - Yeah, absolutely. - Peter, you and I were talking about, we had a couple of questions, sort of, how far can we take artificial intelligence? How far should we? You know, so that brings in to the conversation of ethics, and bias, why don't you pick it up? - Yeah, so, one of the crucial things that we all are implying is that, at some point in time, AI is going to become a feature of the operations of our homes, our businesses. And as these technologies get more powerful, and they diffuse, and know about how to use them, diffuses more broadly, and you put more options into the hands of more people, the question slowly starts to turn from can we do it, to should we do it? And, one of the issues that I introduce is that I think the difference between big data and AI, specifically, is this notion of agency. The AI will act on behalf of, perhaps you, or it will act on behalf of your business. And that conversation is not being had, today. It's being had in arguments between Elon Musk and Mark Zuckerberg, which pretty quickly get pretty boring. (laughing) At the end of the day, the real question is, should this machine, whether in concert with others, or not, be acting on behalf of me, on behalf of my business, or, and when I say on behalf of me, I'm also talking about privacy. Because Facebook is acting on behalf of me, it's not just what's going on in my home. So, the question of, can it be done? A lot of things can be done, and an increasing number of things will be able to be done. We got to start having a conversation about should it be done? - So, humans exhibit tribal behavior, they exhibit bias. Their machine's going to pick that up, go ahead, please. - Yeah, one thing that sort of tag onto agency of artificial intelligence. Every industry, every business is now about identifying information and data sources, and their appropriate sinks, and learning how to draw value out of connecting the sources with the sinks. Artificial intelligence enables you to identify those sources and sinks, and when it gets agency, it will be able to make decisions on your behalf about what data is good, what data means, and who it should be. - What actions are good. - Well, what actions are good. - And what data was used to make those actions. - Absolutely. - And was that the right data, and is there bias of data? And all the way down, all the turtles down. - So, all this, the data pedigree will be driven by the agency of artificial intelligence, and this is a big issue. - It's really fundamental to understand and educate people on, there are four fundamental types of bias, so there's, in machine learning, there's intentional bias, "Hey, we're going to make "the algorithm generate a certain outcome "regardless of what the data says." There's the source of the data itself, historical data that's trained on the models built on flawed data, the model will behave in a flawed way. There's target source, which is, for example, we know that if you pull data from a certain social network, that network itself has an inherent bias. No matter how representative you try to make the data, it's still going to have flaws in it. Or, if you pull healthcare data about, for example, African-Americans from the US healthcare system, because of societal biases, that data will always be flawed. And then there's tool bias, there's limitations to what the tools can do, and so we will intentionally exclude some kinds of data, or not use it because we don't know how to, our tools are not able to, and if we don't teach people what those biases are, they won't know to look for them, and I know. - Yeah, it's like, one of the things that we were talking about before, I mean, artificial intelligence is not going to just create itself, it's lines of code, it's input, and it spits out output. So, if it learns from these learning sets, we don't want AI to become another buzzword. We don't want everybody to be an "AR guru" that has no idea what AI is. It takes months, and months, and months for these machines to learn. These learning sets are so very important, because that input is how this machine, think of it as your child, and that's basically the way artificial intelligence is learning, like your child. You're feeding it these learning sets, and then eventually it will make its own decisions. So, we know from some of us having children that you teach them the best that you can, but then later on, when they're doing their own thing, they're really, it's like a little myna bird, they've heard everything that you've said. (laughing) Not only the things that you said to them directly, but the things that you said indirectly. - Well, there are some very good AI researchers that might disagree with that metaphor, exactly. (laughing) But, having said that, what I think is very interesting about this conversation is that this notion of bias, one of the things that fascinates me about where AI goes, are we going to find a situation where tribalism more deeply infects business? Because we know that human beings do not seek out the best information, they seek out information that reinforces their beliefs. And that happens in business today. My line of business versus your line of business, engineering versus sales, that happens today, but it happens at a planning level, and when we start talking about AI, we have to put the appropriate dampers, understand the biases, so that we don't end up with deep tribalism inside of business. Because AI could have the deleterious effect that it actually starts ripping apart organizations. - Well, input is data, and then the output is, could be a lot of things. - Could be a lot of things. - And that's where I said data equals human lives. So that we look at the case in New York where the penal system was using this artificial intelligence to make choices on people that were released from prison, and they saw that that was a miserable failure, because that people that release actually re-offended, some committed murder and other things. So, I mean, it's, it's more than what anybody really thinks. It's not just, oh, well, we'll just train the machines, and a couple of weeks later they're good, we never have to touch them again. These things have to be continuously tweaked. So, just because you built an algorithm or a model doesn't mean you're done. You got to go back later, and continue to tweak these models. - Mark, you got the mic. - Yeah, no, I think one thing we've talked a lot about the data that's collected, but what about the data that's not collected? Incomplete profiles, incomplete datasets, that's a form of bias, and sometimes that's the worst. Because they'll fill that in, right, and then you can get some bias, but there's also a real issue for that around cyber security. Logs are not always complete, things are not always done, and when things are doing that, people make assumptions based on what they've collected, not what they didn't collect. So, when they're looking at this, and they're using the AI on it, that's only on the data collected, not on that that wasn't collected. So, if something is down for a little while, and no data's collected off that, the assumption is, well, it was down, or it was impacted, or there was a breach, or whatever, it could be any of those. So, you got to, there's still this human need, there's still the need for humans to look at the data and realize that there is the bias in there, there is, we're just looking at what data was collected, and you're going to have to make your own thoughts around that, and assumptions on how to actually use that data before you go make those decisions that can impact lots of people, at a human level, enterprise's profitability, things like that. And too often, people think of AI, when it comes out of there, that's the word. Well, it's not the word. - Can I ask a question about this? - Please. - Does that mean that we shouldn't act? - It does not. - Okay. - So, where's the fine line? - Yeah, I think. - Going back to this notion of can we do it, or should we do it? Should we act? - Yeah, I think you should do it, but you should use it for what it is. It's augmenting, it's helping you, assisting you to make a valued or good decision. And hopefully it's a better decision than you would've made without it. - I think it's great, I think also, your answer's right too, that you have to iterate faster, and faster, and faster, and discover sources of information, or sources of data that you're not currently using, and, that's why this thing starts getting really important. - I think you touch on a really good point about, should you or shouldn't you? You look at Google, and you look at the data that they've been using, and some of that out there, from a digital twin perspective, is not being approved, or not authorized, and even once they've made changes, it's still floating around out there. Where do you know where it is? So, there's this dilemma of, how do you have a digital twin that you want to have, and is going to work for you, and is going to do things for you to make your life easier, to do these things, mundane tasks, whatever? But how do you also control it to do things you don't want it to do? - Ad-based business models are inherently evil. (laughing) - Well, there's incentives to appropriate our data, and so, are things like blockchain potentially going to give users the ability to control their data? We'll see. - No, I, I'm sorry, but that's actually a really important point. The idea of consensus algorithms, whether it's blockchain or not, blockchain includes games, and something along those lines, whether it's Byzantine fault tolerance, or whether it's Paxos, consensus-based algorithms are going to be really, really important. Parts of this conversation, because the data's going to be more distributed, and you're going to have more elements participating in it. And so, something that allows, especially in the machine-to-machine world, which is a lot of what we're talking about right here, you may not have blockchain, because there's no need for a sense of incentive, which is what blockchain can help provide. - And there's no middleman. - And, well, all right, but there's really, the thing that makes blockchain so powerful is it liberates new classes of applications. But for a lot of the stuff that we're talking about, you can use a very powerful consensus algorithm without having a game side, and do some really amazing things at scale. - So, looking at blockchain, that's a great thing to bring up, right. I think what's inherently wrong with the way we do things today, and the whole overall design of technology, whether it be on-prem, or off-prem, is both the lock and key is behind the same wall. Whether that wall is in a cloud, or behind a firewall. So, really, when there is an audit, or when there is a forensics, it always comes down to a sysadmin, or something else, and the system administrator will have the finger pointed at them, because it all resides, you can edit it, you can augment it, or you can do things with it that you can't really determine. Now, take, as an example, blockchain, where you've got really the source of truth. Now you can take and have the lock in one place, and the key in another place. So that's certainly going to be interesting to see how that unfolds. - So, one of the things, it's good that, we've hit a lot of buzzwords, right now, right? (laughing) AI, and ML, block. - Bingo. - We got the blockchain bingo, yeah, yeah. So, one of the things is, you also brought up, I mean, ethics and everything, and one of the things that I've noticed over the last year or so is that, as I attend briefings or demos, everyone is now claiming that their product is AI or ML-enabled, or blockchain-enabled. And when you try to get answers to the questions, what you really find out is that some things are being pushed as, because they have if-then statements somewhere in their code, and therefore that's artificial intelligence or machine learning. - [Peter] At least it's not "go-to." (laughing) - Yeah, you're that experienced as well. (laughing) So, I mean, this is part of the thing you try to do as a practitioner, as an analyst, as an influencer, is trying to, you know, the hype of it all. And recently, I attended one where they said they use blockchain, and I couldn't figure it out, and it turns out they use GUIDs to identify things, and that's not blockchain, it's an identifier. (laughing) So, one of the ethics things that I think we, as an enterprise community, have to deal with, is the over-promising of AI, and ML, and deep learning, and recognition. It's not, I don't really consider it visual recognition services if they just look for red pixels. I mean, that's not quite the same thing. Yet, this is also making things much harder for your average CIO, or worse, CFO, to understand whether they're getting any value from these technologies. - Old bottle. - Old bottle, right. - And I wonder if the data companies, like that you talked about, or the top five, I'm more concerned about their nearly, or actual $1 trillion valuations having an impact on their ability of other companies to disrupt or enter into the field more so than their data technologies. Again, we're coming to another perfect storm of the companies that have data as their asset, even though it's still not on their financial statements, which is another indicator whether it's really an asset, is that, do we need to think about the terms of AI, about whose hands it's in, and who's, like, once one large trillion-dollar company decides that you are not a profitable company, how many other companies are going to buy that data and make that decision about you? - Well, and for the first time in business history, I think, this is true, we're seeing, because of digital, because it's data, you're seeing tech companies traverse industries, get into, whether it's content, or music, or publishing, or groceries, and that's powerful, and that's awful scary. - If you're a manger, one of the things your ownership is asking you to do is to reduce asset specificities, so that their capital could be applied to more productive uses. Data reduces asset specificities. It brings into question the whole notion of vertical industry. You're absolutely right. But you know, one quick question I got for you, playing off of this is, again, it goes back to this notion of can we do it, and should we do it? I find it interesting, if you look at those top five, all data companies, but all of them are very different business models, or they can classify the two different business models. Apple is transactional, Microsoft is transactional, Google is ad-based, Facebook is ad-based, before the fake news stuff. Amazon's kind of playing it both sides. - Yeah, they're kind of all on a collision course though, aren't they? - But, well, that's what's going to be interesting. I think, at some point in time, the "can we do it, should we do it" question is, brands are going to be identified by whether or not they have gone through that process of thinking about, should we do it, and say no. Apple is clearly, for example, incorporating that into their brand. - Well, Silicon Valley, broadly defined, if I include Seattle, and maybe Armlock, not so much IBM. But they've got a dual disruption agenda, they've always disrupted horizontal tech. Now they're disrupting vertical industries. - I was actually just going to pick up on what she was talking about, we were talking about buzzword, right. So, one we haven't heard yet is voice. Voice is another big buzzword right now, when you couple that with IoT and AI, here you go, bingo, do I got three points? (laughing) Voice recognition, voice technology, so all of the smart speakers, if you think about that in the world, there are 7,000 languages being spoken, but yet if you look at Google Home, you look at Siri, you look at any of the devices, I would challenge you, it would have a lot of problem understanding my accent, and even when my British accent creeps out, or it would have trouble understanding seniors, because the way they talk, it's very different than a typical 25-year-old person living in Silicon Valley, right. So, how do we solve that, especially going forward? We're seeing voice technology is going to be so more prominent in our homes, we're going to have it in the cars, we have it in the kitchen, it does everything, it listens to everything that we are talking about, not talking about, and records it. And to your point, is it going to start making decisions on our behalf, but then my question is, how much does it actually understand us? - So, I just want one short story. Siri can't translate a word that I ask it to translate into French, because my phone's set to Canadian English, and that's not supported. So I live in a bilingual French English country, and it can't translate. - But what this is really bringing up is if you look at society, and culture, what's legal, what's ethical, changes across the years. What was right 200 years ago is not right now, and what was right 50 years ago is not right now. - It changes across countries. - It changes across countries, it changes across regions. So, what does this mean when our AI has agency? How do we make ethical AI if we don't even know how to manage the change of what's right and what's wrong in human society? - One of the most important questions we have to worry about, right? - Absolutely. - But it also says one more thing, just before we go on. It also says that the issue of economies of scale, in the cloud. - Yes. - Are going to be strongly impacted, not just by how big you can build your data centers, but some of those regulatory issues that are going to influence strongly what constitutes good experience, good law, good acting on my behalf, agency. - And one thing that's underappreciated in the marketplace right now is the impact of data sovereignty, if you get back to data, countries are now recognizing the importance of managing that data, and they're implementing data sovereignty rules. Everyone talks about California issuing a new law that's aligned with GDPR, and you know what that meant. There are 30 other states in the United States alone that are modifying their laws to address this issue. - Steve. - So, um, so, we got a number of years, no matter what Ray Kurzweil says, until we get to artificial general intelligence. - The singularity's not so near? (laughing) - You know that he's changed the date over the last 10 years. - I did know it. - Quite a bit. And I don't even prognosticate where it's going to be. But really, where we're at right now, I keep coming back to, is that's why augmented intelligence is really going to be the new rage, humans working with machines. One of the hot topics, and the reason I chose to speak about it is, is the future of work. I don't care if you're a millennial, mid-career, or a baby boomer, people are paranoid. As machines get smarter, if your job is routine cognitive, yes, you have a higher propensity to be automated. So, this really shifts a number of things. A, you have to be a lifelong learner, you've got to learn new skillsets. And the dynamics are changing fast. Now, this is also a great equalizer for emerging startups, and even in SMBs. As the AI improves, they can become more nimble. So back to your point regarding colossal trillion dollar, wait a second, there's going to be quite a sea change going on right now, and regarding demographics, in 2020, millennials take over as the majority of the workforce, by 2025 it's 75%. - Great news. (laughing) - As a baby boomer, I try my damnedest to stay relevant. - Yeah, surround yourself with millennials is the takeaway there. - Or retire. (laughs) - Not yet. - One thing I think, this goes back to what Karen was saying, if you want a basic standard to put around the stuff, look at the old ISO 38500 framework. Business strategy, technology strategy. You have risk, compliance, change management, operations, and most importantly, the balance sheet in the financials. AI and what Tony was saying, digital transformation, if it's of meaning, it belongs on a balance sheet, and should factor into how you value your company. All the cyber security, and all of the compliance, and all of the regulation, is all stuff, this framework exists, so look it up, and every time you start some kind of new machine learning project, or data sense project, say, have we checked the box on each of these standards that's within this machine? And if you haven't, maybe slow down and do your homework. - To see a day when data is going to be valued on the balance sheet. - It is. - It's already valued as part of the current, but it's good will. - Certainly market value, as we were just talking about. - Well, we're talking about all of the companies that have opted in, right. There's tens of thousands of small businesses just in this region alone that are opt-out. They're small family businesses, or businesses that really aren't even technology-aware. But data's being collected about them, it's being on Yelp, they're being rated, they're being reviewed, the success to their business is out of their hands. And I think what's really going to be interesting is, you look at the big data, you look at AI, you look at things like that, blockchain may even be a potential for some of that, because of mutability, but it's when all of those businesses, when the technology becomes a cost, it's cost-prohibitive now, for a lot of them, or they just don't want to do it, and they're proudly opt-out. In fact, we talked about that last night at dinner. But when they opt-in, the company that can do that, and can reach out to them in a way that is economically feasible, and bring them back in, where they control their data, where they control their information, and they do it in such a way where it helps them build their business, and it may be a generational business that's been passed on. Those kind of things are going to make a big impact, not only on the cloud, but the data being stored in the cloud, the AI, the applications that you talked about earlier, we talked about that. And that's where this bias, and some of these other things are going to have a tremendous impact if they're not dealt with now, at least ethically. - Well, I feel like we just got started, we're out of time. Time for a couple more comments, and then officially we have to wrap up. - Yeah, I had one thing to say, I mean, really, Henry Ford, and the creation of the automobile, back in the early 1900s, changed everything, because now we're no longer stuck in the country, we can get away from our parents, we can date without grandma and grandpa setting on the porch with us. (laughing) We can take long trips, so now we're looked at, we've sprawled out, we're not all living in the country anymore, and it changed America. So, AI has that same capabilities, it will automate mundane routine tasks that nobody wanted to do anyway. So, a lot of that will change things, but it's not going to be any different than the way things changed in the early 1900s. - It's like you were saying, constant reinvention. - I think that's a great point, let me make one observation on that. Every period of significant industrial change was preceded by the formation, a period of formation of new assets that nobody knew what to do with. Whether it was, what do we do, you know, industrial manufacturing, it was row houses with long shafts tied to an engine that was coal-fired, and drove a bunch of looms. Same thing, railroads, large factories for Henry Ford, before he figured out how to do an information-based notion of mass production. This is the period of asset formation for the next generation of social structures. - Those ship-makers are going to be all over these cars, I mean, you're going to have augmented reality right there, on your windshield. - Karen, bring it home. Give us the drop-the-mic moment. (laughing) - No pressure. - Your AV guys are not happy with that. So, I think the, it all comes down to, it's a people problem, a challenge, let's say that. The whole AI ML thing, people, it's a legal compliance thing. Enterprises are going to struggle with trying to meet five billion different types of compliance rules around data and its uses, about enforcement, because ROI is going to make risk of incarceration as well as return on investment, and we'll have to manage both of those. I think businesses are struggling with a lot of this complexity, and you just opened a whole bunch of questions that we didn't really have solid, "Oh, you can fix it by doing this." So, it's important that we think of this new world of data focus, data-driven, everything like that, is that the entire IT and business community needs to realize that focusing on data means we have to change how we do things and how we think about it, but we also have some of the same old challenges there. - Well, I have a feeling we're going to be talking about this for quite some time. What a great way to wrap up CUBE NYC here, our third day of activities down here at 37 Pillars, or Mercantile 37. Thank you all so much for joining us today. - Thank you. - Really, wonderful insights, really appreciate it, now, all this content is going to be available on theCUBE.net. We are exposing our video cloud, and our video search engine, so you'll be able to search our entire corpus of data. I can't wait to start searching and clipping up this session. Again, thank you so much, and thank you for watching. We'll see you next time.
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Rob Thomas, IBM | Change the Game: Winning With AI
>> Live from Times Square in New York City, it's The Cube covering IBM's Change the Game: Winning with AI, brought to you by IBM. >> Hello everybody, welcome to The Cube's special presentation. We're covering IBM's announcements today around AI. IBM, as The Cube does, runs of sessions and programs in conjunction with Strata, which is down at the Javits, and we're Rob Thomas, who's the General Manager of IBM Analytics. Long time Cube alum, Rob, great to see you. >> Dave, great to see you. >> So you guys got a lot going on today. We're here at the Westin Hotel, you've got an analyst event, you've got a partner meeting, you've got an event tonight, Change the game: winning with AI at Terminal 5, check that out, ibm.com/WinWithAI, go register there. But Rob, let's start with what you guys have going on, give us the run down. >> Yeah, it's a big week for us, and like many others, it's great when you have Strata, a lot of people in town. So, we've structured a week where, today, we're going to spend a lot of time with analysts and our business partners, talking about where we're going with data and AI. This evening, we've got a broadcast, it's called Winning with AI. What's unique about that broadcast is it's all clients. We've got clients on stage doing demonstrations, how they're using IBM technology to get to unique outcomes in their business. So I think it's going to be a pretty unique event, which should be a lot of fun. >> So this place, it looks like a cool event, a venue, Terminal 5, it's just up the street on the west side highway, probably a mile from the Javits Center, so definitely check that out. Alright, let's talk about, Rob, we've known each other for a long time, we've seen the early Hadoop days, you guys were very careful about diving in, you kind of let things settle and watched very carefully, and then came in at the right time. But we saw the evolution of so-called Big Data go from a phase of really reducing investments, cheaper data warehousing, and what that did is allowed people to collect a lot more data, and kind of get ready for this era that we're in now. But maybe you can give us your perspective on the phases, the waves that we've seen of data, and where we are today and where we're going. >> I kind of think of it as a maturity curve. So when I go talk to clients, I say, look, you need to be on a journey towards AI. I think probably nobody disagrees that they need something there, the question is, how do you get there? So you think about the steps, it's about, a lot of people started with, we're going to reduce the cost of our operations, we're going to use data to take out cost, that was kind of the Hadoop thrust, I would say. Then they moved to, well, now we need to see more about our data, we need higher performance data, BI data warehousing. So, everybody, I would say, has dabbled in those two area. The next leap forward is self-service analytics, so how do you actually empower everybody in your organization to use and access data? And the next step beyond that is, can I use AI to drive new business models, new levers of growth, for my business? So, I ask clients, pin yourself on this journey, most are, depends on the division or the part of the company, they're at different areas, but as I tell everybody, if you don't know where you are and you don't know where you want to go, you're just going to wind around, so I try to get them to pin down, where are you versus where do you want to go? >> So four phases, basically, the sort of cheap data store, the BI data warehouse modernization, self-service analytics, a big part of that is data science and data science collaboration, you guys have a lot of investments there, and then new business models with AI automation running on top. Where are we today? Would you say we're kind of in-between BI/DW modernization and on our way to self-service analytics, or what's your sense? >> I'd say most are right in the middle between BI data warehousing and self-service analytics. Self-service analytics is hard, because it requires you, sometimes to take a couple steps back, and look at your data. It's hard to provide self-service if you don't have a data catalog, if you don't have data security, if you haven't gone through the processes around data governance. So, sometimes you have to take one step back to go two steps forward, that's why I see a lot of people, I'd say, stuck in the middle right now. And the examples that you're going to see tonight as part of the broadcast are clients that have figured out how to break through that wall, and I think that's pretty illustrative of what's possible. >> Okay, so you're saying that, got to maybe take a step back and get the infrastructure right with, let's say a catalog, to give some basic things that they have to do, some x's and o's, you've got the Vince Lombardi played out here, and also, skillsets, I imagine, is a key part of that. So, that's what they've got to do to get prepared, and then, what's next? They start creating new business models, imagining this is where the cheap data officer comes in and it's an executive level, what are you seeing clients as part of digital transformation, what's the conversation like with customers? >> The biggest change, the great thing about the times we live in, is technology's become so accessible, you can do things very quickly. We created a team last year called Data Science Elite, and we've hired what we think are some of the best data scientists in the world. Their only job is to go work with clients and help them get to a first success with data science. So, we put a team in. Normally, one month, two months, normally a team of two or three people, our investment, and we say, let's go build a model, let's get to an outcome, and you can do this incredibly quickly now. I tell clients, I see somebody that says, we're going to spend six months evaluating and thinking about this, I was like, why would you spend six months thinking about this when you could actually do it in one month? So you just need to get over the edge and go try it. >> So we're going to learn more about the Data Science Elite team. We've got John Thomas coming on today, who is a distinguished engineer at IBM, and he's very much involved in that team, and I think we have a customer who's actually gone through that, so we're going to talk about what their experience was with the Data Science Elite team. Alright, you've got some hard news coming up, you've actually made some news earlier with Hortonworks and Red Hat, I want to talk about that, but you've also got some hard news today. Take us through that. >> Yeah, let's talk about all three. First, Monday we announced the expanded relationship with both Hortonworks and Red Hat. This goes back to one of the core beliefs I talked about, every enterprise is modernizing their data and application of states, I don't think there's any debate about that. We are big believers in Kubernetes and containers as the architecture to drive that modernization. The announcement on Monday was, we're working closer with Red Hat to take all of our data services as part of Cloud Private for Data, which are basically microservice for data, and we're running those on OpenShift, and we're starting to see great customer traction with that. And where does Hortonworks come in? Hadoop has been the outlier on moving to microservices containers, we're working with Hortonworks to help them make that move as well. So, it's really about the three of us getting together and helping clients with this modernization journey. >> So, just to remind people, you remember ODPI, folks? It was all this kerfuffle about, why do we even need this? Well, what's interesting to me about this triumvirate is, well, first of all, Red Hat and Hortonworks are hardcore opensource, IBM's always been a big supporter of open source. You three got together and you're proving now the productivity for customers of this relationship. You guys don't talk about this, but Hortonworks had to, when it's public call, that the relationship with IBM drove many, many seven-figure deals, which, obviously means that customers are getting value out of this, so it's great to see that come to fruition, and it wasn't just a Barney announcement a couple years ago, so congratulations on that. Now, there's this other news that you guys announced this morning, talk about that. >> Yeah, two other things. One is, we announced a relationship with Stack Overflow. 50 million developers go to Stack Overflow a month, it's an amazing environment for developers that are looking to do new things, and we're sponsoring a community around AI. Back to your point before, you said, is there a skills gap in enterprises, there absolutely is, I don't think that's a surprise. Data science, AI developers, not every company has the skills they need, so we're sponsoring a community to help drive the growth of skills in and around data science and AI. So things like Python, R, Scala, these are the languages of data science, and it's a great relationship with us and Stack Overflow to build a community to get things going on skills. >> Okay, and then there was one more. >> Last one's a product announcement. This is one of the most interesting product annoucements we've had in quite a while. Imagine this, you write a sequel query, and traditional approach is, I've got a server, I point it as that server, I get the data, it's pretty limited. We're announcing technology where I write a query, and it can find data anywhere in the world. I think of it as wide-area sequel. So it can find data on an automotive device, a telematics device, an IoT device, it could be a mobile device, we think of it as sequel the whole world. You write a query, you can find the data anywhere it is, and we take advantage of the processing power on the edge. The biggest problem with IoT is, it's been the old mantra of, go find the data, bring it all back to a centralized warehouse, that makes it impossible to do it real time. We're enabling real time because we can write a query once, find data anywhere, this is technology we've had in preview for the last year. We've been working with a lot of clients to prove out used cases to do it, we're integrating as the capability inside of IBM Cloud Private for Data. So if you buy IBM Cloud for Data, it's there. >> Interesting, so when you've been around as long as I have, long enough to see some of the pendulums swings, and it's clearly a pendulum swing back toward decentralization in the edge, but the key is, from what you just described, is you're sort of redefining the boundary, so I presume it's the edge, any Cloud, or on premises, where you can find that data, is that correct? >> Yeah, so it's multi-Cloud. I mean, look, every organization is going to be multi-Cloud, like 100%, that's going to happen, and that could be private, it could be multiple public Cloud providers, but the key point is, data on the edge is not just limited to what's in those Clouds. It could be anywhere that you're collecting data. And, we're enabling an architecture which performs incredibly well, because you take advantage of processing power on the edge, where you can get data anywhere that it sits. >> Okay, so, then, I'm setting up a Cloud, I'll call it a Cloud architecture, that encompasses the edge, where essentially, there are no boundaries, and you're bringing security. We talked about containers before, we've been talking about Kubernetes all week here at a Big Data show. And then of course, Cloud, and what's interesting, I think many of the Hadoop distral vendors kind of missed Cloud early on, and then now are sort of saying, oh wow, it's a hybrid world and we've got a part, you guys obviously made some moves, a couple billion dollar moves, to do some acquisitions and get hardcore into Cloud, so that becomes a critical component. You're not just limiting your scope to the IBM Cloud. You're recognizing that it's a multi-Cloud world, that' what customers want to do. Your comments. >> It's multi-Cloud, and it's not just the IBM Cloud, I think the most predominant Cloud that's emerging is every client's private Cloud. Every client I talk to is building out a containerized architecture. They need their own Cloud, and they need seamless connectivity to any public Cloud that they may be using. This is why you see such a premium being put on things like data ingestion, data curation. It's not popular, it's not exciting, people don't want to talk about it, but we're the biggest inhibitors, to this AI point, comes back to data curation, data ingestion, because if you're dealing with multiple Clouds, suddenly your data's in a bunch of different spots. >> Well, so you're basically, and we talked about this a lot on The Cube, you're bringing the Cloud model to the data, wherever the data lives. Is that the right way to think about it? >> I think organizations have spoken, set aside what they say, look at their actions. Their actions say, we don't want to move all of our data to any particular Cloud, we'll move some of our data. We need to give them seamless connectivity so that they can leave their data where they want, we can bring Cloud-Native Architecture to their data, we could also help move their data to a Cloud-Native architecture if that's what they prefer. >> Well, it makes sense, because you've got physics, latency, you've got economics, moving all the data into a public Cloud is expensive and just doesn't make economic sense, and then you've got things like GDPR, which says, well, you have to keep the data, certain laws of the land, if you will, that say, you've got to keep the data in whatever it is, in Germany, or whatever country. So those sort of edicts dictate how you approach managing workloads and what you put where, right? Okay, what's going on with Watson? Give us the update there. >> I get a lot of questions, people trying to peel back the onion of what exactly is it? So, I want to make that super clear here. Watson is a few things, start at the bottom. You need a runtime for models that you've built. So we have a product called Watson Machine Learning, runs anywhere you want, that is the runtime for how you execute models that you've built. Anytime you have a runtime, you need somewhere where you can build models, you need a development environment. That is called Watson Studio. So, we had a product called Data Science Experience, we've evolved that into Watson Studio, connecting in some of those features. So we have Watson Studio, that's the development environment, Watson Machine Learning, that's the runtime. Now you move further up the stack. We have a set of APIs that bring in human features, vision, natural language processing, audio analytics, those types of things. You can integrate those as part of a model that you build. And then on top of that, we've got things like Watson Applications, we've got Watson for call centers, doing customer service and chatbots, and then we've got a lot of clients who've taken pieces of that stack and built their own AI solutions. They've taken some of the APIs, they've taken some of the design time, the studio, they've taken some of the Watson Machine Learning. So, it is really a stack of capabilities, and where we're driving the greatest productivity, this is in a lot of the examples you'll see tonight for clients, is clients that have bought into this idea of, I need a development environment, I need a runtime, where I can deploy models anywhere. We're getting a lot of momentum on that, and then that raises the question of, well, do I have expandability, do I have trust in transparency, and that's another thing that we're working on. >> Okay, so there's API oriented architecture, exposing all these services make it very easy for people to consume. Okay, so we've been talking all week at Cube NYC, is Big Data is in AI, is this old wine, new bottle? I mean, it's clear, Rob, from the conversation here, there's a lot of substantive innovation, and early adoption, anyway, of some of these innovations, but a lot of potential going forward. Last thoughts? >> What people have to realize is AI is not magic, it's still computer science. So it actually requires some hard work. You need to roll up your sleeves, you need to understand how I get from point A to point B, you need a development environment, you need a runtime. I want people to really think about this, it's not magic. I think for a while, people have gotten the impression that there's some magic button. There's not, but if you put in the time, and it's not a lot of time, you'll see the examples tonight, most of them have been done in one or two months, there's great business value in starting to leverage AI in your business. >> Awesome, alright, so if you're in this city or you're at Strata, go to ibm.com/WinWithAI, register for the event tonight. Rob, we'll see you there, thanks so much for coming back. >> Yeah, it's going to be fun, thanks Dave, great to see you. >> Alright, keep it right there everybody, we'll be back with our next guest right after this short break, you're watching The Cube.
SUMMARY :
brought to you by IBM. Rob, great to see you. what you guys have going on, it's great when you have on the phases, the waves that we've seen where you want to go, you're the BI data warehouse modernization, a data catalog, if you and get the infrastructure right with, and help them get to a first and I think we have a as the architecture to news that you guys announced that are looking to do new things, I point it as that server, I get the data, of processing power on the the edge, where essentially, it's not just the IBM Cloud, Is that the right way to think about it? We need to give them seamless connectivity certain laws of the land, that is the runtime for people to consume. and it's not a lot of time, register for the event tonight. Yeah, it's going to be fun, we'll be back with our next guest
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Craig Muzilla, Red Hat | Red Hat Summit 2018
from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone this is the cube live in San Francisco Moscone West for coverage of Red Hat summit 2018 I'm John for the co-host of the cube mykos this week as analyst John Schwarz the co-founder of tech reckoning advisory and Community Development firm our next guest is Craig pizzelles right senior vice president application platforms business and portfolio for Red Hat great to see you welcome back to the cube thank you very much John so big-time executive a company is doing well and you guys are growing adding more people every time being successful again an open source another generations upon us a standing on the shoulders of giants you guys have been a business model for Red Hat for many many years rel certainly successful container madness now mainstream kubernetes clear line of sight on what that's doing as an abstraction layer and standard de-facto standard around orchestration the really good tailwind for you guys and the industry absolutely absolutely congratulations and what's your take I mean obviously you got apps now you're good people gonna be building apps system working OpenStack what's what's going on right well there's a lot going on I mean we've we've been very consistent about our strategy and it's finally starting to pay off and come together and I think the mark is starting to realize that we have been talking about hybrid cloud before it was in vogue and you know well over five years ago and so all those pieces come together we've always talked about a story of there are multiple footprints whether it's physical vert traditional virtual private cloud and public cloud and then companies will want to and customers will want to do more than just the four footprints they want to do multi cloud as well so you know we've been very strong on the infrastructure side having Linux as the base and the operational consistency across those footprints in which to build on and then now containers and kubernetes with OpenShift gives us plus that that last leg together to give us that abstraction layer across these multiple footprints to allow hybrid to happen I wanna get your reaction this because we were talking on our intro package around the dynamic we're seeing in today's business landscape and technical landscape open source clearly the business model for software right check kubernetes provide some interoperability and cloud native growth for new applications cloud we're cloud native what are you gonna call it and then you've got legacy applications for the first time don't have to get thrown away to go to the new world you have the ability to containerize write pre-existing applications while bringing a new functionality new infrastructure new software methodologies development architectures modernizing software yeah while maintaining and preserving the life cycle of pre-existing applications great absolutely this is the dynamic that is really a wonderful thing because takes the pressure off absolutely and I think that's unique to Red Hat which is we've always had not only the hybrid cloud story the multi cloud story but the fact that containers allows you to advanced advanced a movement to you know do digital transformation start using micro services etc but you don't need to start over you can take existing applications you can containerize those applications get them into a cloud environment gain those efficiencies operational efficiencies and development efficiencies and then start to also build new applications based on microservices architectures and bring both together some of the other vendors out there may only have a story about well you have to rewrite everything it right or it's only going to be public cloud and you're tied to those public cloud api's I think you know using containers as a methodology and then using orchestration with kubernetes you can have the best of both worlds and we think that's important I wanted to drill down to the stack a little bit more right I think this year maybe even as opposed to last year the cube was that the OpenStack summit and there was a little bit of confused talk about you know containers you know what on what openshift on OpenStack or vice versa the message this this year very clear you know openshift on OpenStack here's the infrastructure don't get confused so we've got those two layers that you lay down but also there's a lot of application services in the Red Hat stack that you all have built out and I think if people were listening closely right there's a multi-year investment in there in things like you know that originated with an application server like JBoss that now actually in 2018 architectural II look very different now that's a set of services that developers can use so maybe I mean can you talk a little bit about I mean that's an example also I'm not throwing everything out but evolving can talk a little bit about the depth of the stack there and and servicing all those various requirements I mean if you look at the stack we're talking about infrastructure services some of those are in things like OpenStack so you know whether it's compute storage networking etc we demonstrated some ability in through kubernetes to provision and orchestrate VMs and so you saw some of that in the demos that we show today but then once you lay down that foundational layer with containers and kubernetes with openshift then we start to build services on top of that we have been building this portfolio of middleware services for some time and so we can provide messaging as a service we can provide integration and ipad services we have something now called Roar which is packaging together a runtime and frameworks to put together inside of OpenShift we have process management and orchestration technologies business process management so all those services are something that developers need and you start adding those now as cloud services and so the other one of the other things that we've also done beginning about two years ago we began a journey for automating the application lifecycle of building application the pipeline capability we did an acquisition of a company called codenvy which is the founders of eclipse CheY the cloud native ide and workspace environment and so now we've now begun shipping openshift i/o to give you that end-to-end capability from beginning your project to writing the code to doing CI CD and managing the full lifecycle so it's all starting to come together for us a big big talk here at the show about kubernetes being kind of dun dun gnu/linux right the new platform that's going to enable a huge amount of innovation but I love that openshift is more than kubernetes a and also that you know as part of this it's it's a it's you know the role of Linux was a bunch of device drivers right and you're and you're organizing on one machine the clap now that we're in cloud right kubernetes is is about operations like you just said about the code lifecycle about all this stuff and all of a sudden yes it yes it's a it's an analogy but but it's much broader than that it's much broader than that one analogy I mean you made the analogy about Linux I mean Linux basically abstracted a number of hardware architectures and gave you a common operating environment in which to run on x86 or even run on a mainframe or run on power now running on arm you know we have looked at and said well there's a similar analogy now having and taking place with containers in kubernetes where you can create an orchestration layer and an abstraction layer across multiple infrastructures and then building app dev services on top of that so that's what's coming together right now so you know we think it's important also to build out the ecosystem so we're providing application development services on top of this you know this abstraction layer we're building tooling and application lifecycle management but we're also bringing in partners so our announcements today with or yesterday with IBM and even Microsoft they're container izing sequel server they're putting it into our container catalog there will be a distribution of that the the the IBM products and the IBM middleware products and so we'd right now in our ecosystem development program we have about 60 is v's already certified already in a container catalog we grade them in terms of their security so you have some confidence we have another pipeline of another two hundred is BS coming in and then also our service broker so bringing in services we made announcements last year with with AWS to bring in some of their services like lambda and other services into the service broker so you see this hybrid world where you have a lot of different application development capabilities both from us and from our on the ecosystem and the service broker technology to help you bridge you know the best of breed services from all these multiple clouds okay I talked about the ecosystem evolution because you're creating an enabling technology capability and new new growth is coming we see that already kind of on the radar how is that gonna change the ecosystem makeup for you guys actually the the container catalog and ISPs what's it gonna look like is V is gonna be developer I mean what how do you guys envision the ecosystem evolving over the ecosystem it obviously is involved most of these you know most of the traditional the ISPs will begin to offer their own services you know they might be hosting them on AWS but they're gonna provide cloud services so they're gonna be exposing api's to use those services so I see that the evolution isn't there will be a lot of code that you still containerize and offer but there will be many services that are hosted somewhere else posted in a cloud hosting but you want to bring those services to bear I'm creating in an application maybe on Prem with openshift but I need to use a machine learning service from perhaps Google or from Watson and IBM so how do i and those are hosted services so how do I use those services even though my cloud native environment is inside inside the inside the firewall front I'm an integration or two critical pieces you guys got a layout across that right yeah yeah yes and so there's a distributed computer it sounds like an operating system out but it's spread all over the place it's spread all over the place your thoughts on your current portfolio how's it kind of all you talk about some of the services you're enabling within your own portfolio for your customers out there now rel very stable operationally everybody knows that how is the portfolio within Red Hat gonna continue to evolve at what's their vision there yeah so we are beginning to do more of you know integrating infrastructure services in from kubernetes so what you saw you know cnv containerized virtualization allows you to orchestrate VMS we've done the same thing with storage and storage virtualization you'll see more on the infrastructure side probably things like networking are next some of the API is within OpenStack but then up stack we're looking at other capabilities we do have a project going on right now with server list it's in tech preview it was demoed yesterday so you'll see a server list offering from us we have been experimenting with machine learning and AI and we're using it inside of our own capabilities like insights which is a management a hosted management tool but providing machine learning capabilities and offering those inside natively with inside of open ship these are all futures and part of the roadmap that we have going forward for application developers out there are potential partners of Red Hat what's the mandate in your mind to make kubernetes a first-class citizen so if I'm watching I want it I want a vector into this you know skate to where the puck is going kind of mindset what do I need to do what is an enterprise and a business or developer or startup right need to do two cunning connect into the growth is it a playbook do you see something involving that stick and maybe a clear line one of the things I mean from is just a technical basis if you if a partner has software well get a containerized figure out how that works in containers how many how do you structure that if a partner has a service then make that available through the service broker we will work with those partners to you know look at business models that might be appropriate in a cloud native environment that spans across cloud to help them market so those are some of the things I think you know a partner or an ecosystem provider would you should think about what's the feedback of the show here after the hallway conversations Dobbs a lot a lot of openshift conversations it's a centerpiece what are you hearing what are you seeing what's what's going on for you at the show here I think the breadth of what Red Hat has become I you know when we'd go to shows five six years ago we had you know started to build out the portfolio but you know people would still come to the show and you know it's the Linux show but it's no longer the Linux show it's it's a much bigger it's it's about computing open-source computing in the enterprise and cloud-based computing and so the breadth of the portfolio I think is a surprise for many people and how many things we do offer when you look at some of the customer testimonials and the demos we're showing everything from you know infrastructure and private cloud infrastructure out to very sophisticated application development use cases so I think that's a big difference than what you might have seen six broad you're broadening your portfolio from standalone Linux to include management applicate more applications this is a bigger market it's a much bigger market I think we you know we view our we we view our opportunity as becoming the computing platform both at an infrastructure level and helping the developers for the next you know for the next 50 years so hopefully right and it's a shift in the marketplace - and a shift in skill set of the people who are here right that's another thing that to be able to pull those two people into the future like yeah absolutely I mean the skill set used to be again you know a primary linux show a lot of linux systems administrators and and data center executives and data center managers and now you have a much more senior levels many c-suite people coming here to to understand how they transform their business how open-source can help how this broad hybrid cloud platform can help and then a large set of architects and developers so the mix is really interesting now it's not just the infrastructure and data center guys but it's the executives that make those decisions as well as the application develop you have more community members that are users inside the open source projects making things happen oh absolutely you guys now it helps everyone else oh I was just approached by a large bank this week and on openshift i/o which is this tool chain this pipeline capability now an open shift they want to participate they asked how do we get involved in the projects in the upstream projects we would like to build this out so that's just one example I think of and we get asked all the time about hey can you teach us how to be an open company how to be how does open source work how could we facilitate that in our culture to be a little bit more creative collaborative and move faster so I mean open source model is definitely real what are the customer feedback can you share because we're hearing the same thing the customers saying okay it's easier to recruit it's easier to just make everything open just from an operational standpoint right what are some of your top customers that have been with red head for a while what are they saying to you when they say wow this the benefits are are well well the benefits I think are are that they are much faster to market they can leverage skills and capabilities that may not be inherent in their own company beyond their walls they could you know get build ecosystems that have affinity to the to themselves all because they're just you know reaching out there they're participating in open source communities and trying to create a culture of open source and then you get better products out of a certain link wray thanks for coming on the cube and sharing your insights congratulations on all your success great to have you on we're here at the Red Hat summit 28 teens the cubes live covers stay with us for more work day two of three days of wall-to-wall coverage we'll be right back after this short break I'm John four with John Troy here stay with us
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Day One Morning Keynote | Red Hat Summit 2018
[Music] [Music] [Music] [Laughter] [Laughter] [Laughter] [Laughter] [Music] [Music] [Music] [Music] you you [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] wake up feeling blessed peace you warned that Russia ain't afraid to show it I'll expose it if I dressed up riding in that Chester roasted nigga catch you slippin on myself rocks on I messed up like yes sir [Music] [Music] [Music] [Music] our program [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] you are not welcome to Red Hat summit 2018 2018 [Music] [Music] [Music] [Laughter] [Music] Wow that is truly the coolest introduction I've ever had thank you Wow I don't think I feel cool enough to follow an interaction like that Wow well welcome to the Red Hat summit this is our 14th annual event and I have to say looking out over this audience Wow it's great to see so many people here joining us this is by far our largest summit to date not only did we blow through the numbers we've had in the past we blew through our own expectations this year so I know we have a pretty packed house and I know people are still coming in so it's great to see so many people here it's great to see so many familiar faces when I had a chance to walk around earlier it's great to see so many new people here joining us for the first time I think the record attendance is an indication that more and more enterprises around the world are seeing the power of open source to help them with their challenges that they're facing due to the digital transformation that all of enterprises around the world are going through the theme for the summit this year is ideas worth exploring and we intentionally chose that because as much as we are all going through this digital disruption and the challenges associated with it one thing I think is becoming clear no one person and certainly no one company has the answers to these challenges right this isn't a problem where you can go buy a solution this is a set of capabilities that we all need to build it's a set of cultural changes that we all need to go through and that's going to require the best ideas coming from so many different places so we're not here saying we have the answers we're trying to convene the conversation right we want to serve as a catalyst bringing great minds together to share ideas so we all walk out of here at the end of the week a little wiser than when we first came here we do have an amazing agenda for you we have over 7,000 attendees we may be pushing 8,000 by the time we got through this morning we have 36 keynote speakers and we have a hundred and twenty-five breakout sessions and have to throw in one plug scheduling 325 breakout sessions is actually pretty difficult and so we used the Red Hat business optimizer which is an AI constraint solver that's new in the Red Hat decision manager to help us plan the summit because we have individuals who have a clustered set of interests and we want to make sure that when we schedule two breakout sessions we do it in a way that we don't have overlapping sessions that are really important to the same individual so we tried to use this tool and what we understand about people's interest in history of what they wanted to do to try to make sure that we spaced out different times for things of similar interests for similar people as well as for people who stood in the back of breakouts before and I know I've done that too we've also used it to try to optimize room size so hopefully we will do our best to make sure that we've appropriately sized the spaces for those as well so it's really a phenomenal tool and I know it's helped us a lot this year in addition to the 325 breakouts we have a lot of our customers on stage during the main sessions and so you'll see demos you'll hear from partners you'll hear stories from so many of our customers not on our point of view of how to use these technologies but their point of views of how they actually are using these technologies to solve their problems and you'll hear over and over again from those keynotes that it's not just about the technology it's about how people are changing how people are working to innovate to solve those problems and while we're on the subject of people I'd like to take a moment to recognize the Red Hat certified professional of the year this is known award we do every year I love this award because it truly recognizes an individual for outstanding innovation for outstanding ideas for truly standing out in how they're able to help their organization with Red Hat technologies Red Hat certifications help system administrators application developers IT architects to further their careers and help their organizations by being able to advance their skills and knowledge of Red Hat products and this year's winner really truly is a great example about how their curiosity is helped push the limits of what's possible with technology let's hear a little more about this year's winner when I was studying at the University I had computer science as one of my subjects and that's what created the passion from the very beginning they were quite a few institutions around my University who were offering Red Hat Enterprise Linux as a course and a certification paths through to become an administrator Red Hat Learning subscription has offered me a lot more than any other trainings that have done so far that gave me exposure to so many products under red hair technologies that I wasn't even aware of I started to think about the better ways of how these learnings can be put into the real life use cases and we started off with a discussion with my manager saying I have to try this product and I really want to see how it really fits in our environment and that product was Red Hat virtualization we went from deploying rave and then OpenStack and then the open shift environment we wanted to overcome some of the things that we saw as challenges to the speed and rapidity of release and code etc so it made perfect sense and we were able to do it in a really short space of time so you know we truly did use it as an Innovation Lab I think idea is everything ideas can change the way you see things an Innovation Lab was such an idea that popped into my mind one fine day and it has transformed the way we think as a team and it's given that playpen to pretty much everyone to go and test their things investigate evaluate do whatever they like in a non-critical non production environment I recruited Neha almost 10 years ago now I could see there was a spark a potential with it and you know she had a real Drive a real passion and you know here we are nearly ten years later I'm Neha Sandow I am a Red Hat certified engineer all right well everyone please walk into the states to the stage Neha [Music] [Applause] congratulations thank you [Applause] I think that - well welcome to the red has some of this is your first summit yes it is thanks so much well fantastic sure well it's great to have you here I hope you have a chance to engage and share some of your ideas and enjoy the week thank you thank you congratulations [Applause] neha mentioned that she first got interest in open source at university and it made me think red hats recently started our Red Hat Academy program that looks to programmatically infuse Red Hat technologies in universities around the world it's exploded in a way we had no idea it's grown just incredibly rapidly which i think shows the interest that there really is an open source and working in an open way at university so it's really a phenomenal program I'm also excited to announce that we're launching our newest open source story this year at Summit it's called the science of collective discovery and it looks at what happens when communities use open hardware to monitor the environment around them and really how they can make impactful change based on that technologies the rural premier that will be at 5:15 on Wednesday at McMaster Oni West and so please join us for a drink and we'll also have a number of the experts featured in that and you can have a conversation with them as well so with that let's officially start the show please welcome red hat president of products and technology Paul Cormier [Music] Wow morning you know I say it every year I'm gonna say it again I know I repeat myself it's just amazing we are so proud here to be here today too while you all week on how far we've come with opens with open source and with the products that we that we provide at Red Hat so so welcome and I hope the pride shows through so you know I told you Seven Summits ago on this stage that the future would be open and here we are just seven years later this is the 14th summit but just seven years later after that and much has happened and I think you'll see today and this week that that prediction that the world would be open was a pretty safe predict prediction but I want to take you just back a little bit to see how we started here and it's not just how Red Hat started here this is an open source in Linux based computing is now in an industry norm and I think that's what you'll you'll see in here this week you know we talked back then seven years ago when we put on our prediction about the UNIX error and how Hardware innovation with x86 was it was really the first step in a new era of open innovation you know companies like Sun Deck IBM and HP they really changed the world the computing industry with their UNIX models it was that was really the rise of computing but I think what we we really saw then was that single company innovation could only scale so far could really get so far with that these companies were very very innovative but they coupled hardware innovation with software innovation and as one company they could only solve so many problems and even which comp which even complicated things more they could only hire so many people in each of their companies Intel came on the scene back then as the new independent hardware player and you know that was really the beginning of the drive for horizontal computing power and computing this opened up a brand new vehicle for hardware innovation a new hardware ecosystem was built around this around this common hardware base shortly after that Stallman and leanness they had a vision of his of an open model that was created and they created Linux but it was built around Intel this was really the beginning of having a software based platform that could also drive innovation this kind of was the beginning of the changing of the world here that system-level innovation now having a hardware platform that was ubiquitous and a software platform that was open and ubiquitous it really changed this system level innovation and that continues to thrive today it was only possible because it was open this could not have happened in a closed environment it allowed the best ideas from anywhere from all over to come in in win only because it was the best idea that's what drove the rate of innovation at the pace you're seeing today and it which has never been seen before we at Red Hat we saw the need to bring this innovation to solve real-world problems in the enterprise and I think that's going to be the theme of the show today you're going to see us with our customers and partners talking about and showing you some of those real-world problems that we are sought solving with this open innovation we created rel back then for this for the enterprise it started it's it it wasn't successful because it's scaled it was secure and it was enterprise ready it once again changed the industry but this time through open innovation this gave the hardware ecosystem a software platform this open software platform gave the hardware ecosystem a software platform to build around it Unleashed them the hardware side to compete and thrive it enabled innovation from the OEMs new players building cheaper faster servers even new architectures from armed to power sprung up with this change we have seen an incredible amount of hardware innovation over the last 15 years that same innovation happened on the software side we saw powerful implementations of bare metal Linux distributions out in the market in fact at one point there were 300 there are over 300 distributions out in the market on the foundation of Linux powerful open-source equivalents were even developed in every area of Technology databases middleware messaging containers anything you could imagine innovation just exploded around the Linux platform in innovation it's at the core also drove virtualization both Linux and virtualization led to another area of innovation which you're hearing a lot about now public cloud innovation this innovation started to proceed at a rate that we had never seen before we had never experienced this in the past in this unprecedented speed of innovation and software was now possible because you didn't need a chip foundry in order to innovate you just needed great ideas in the open platform that was out there customers seeing this innovation in the public cloud sparked it sparked their desire to build their own linux based cloud platforms and customers are now are now bringing that cloud efficiency on-premise in their own data centers public clouds demonstrated so much efficiency the data centers and architects wanted to take advantage of it off premise on premise I'm sorry within their own we don't within their own controlled environments this really allowed companies to make the most of existing investments from data centers to hardware they also gained many new advantages from data sovereignty to new flexible agile approaches I want to bring Burr and his team up here to take a look at what building out an on-premise cloud can look like today Bure take it away I am super excited to be with all of you here at Red Hat summit I know we have some amazing things to show you throughout the week but before we dive into this demonstration I want you to take just a few seconds just a quick moment to think about that really important event your life that moment you turned on your first computer maybe it was a trs-80 listen Claire and Atari I even had an 83 b2 at one point but in my specific case I was sitting in a classroom in Hawaii and I could see all the way from Diamond Head to Pearl Harbor so just keep that in mind and I turn on an IBM PC with dual floppies I don't remember issuing my first commands writing my first level of code and I was totally hooked it was like a magical moment and I've been hooked on computers for the last 30 years so I want you to hold that image in your mind for just a moment just a second while we show you the computers we have here on stage let me turn this over to Jay fair and Dini here's our worldwide DevOps manager and he was going to show us his hardware what do you got Jay thank you BER good morning everyone and welcome to Red Hat summit we have so many cool things to show you this week I am so happy to be here and you know my favorite thing about red hat summit is our allowed to kind of share all of our stories much like bird just did we also love to you know talk about the hardware and the technology that we brought with us in fact it's become a bit of a competition so this year we said you know let's win this thing and we actually I think we might have won we brought a cloud with us so right now this is a private cloud for throughout the course of the week we're going to turn this into a very very interesting open hybrid cloud right before your eyes so everything you see here will be real and happening right on this thing right behind me here so thanks for our four incredible partners IBM Dell HP and super micro we've built a very vendor heterogeneous cloud here extra special thanks to IBM because they loaned us a power nine machine so now we actually have multiple architectures in this cloud so as you know one of the greatest benefits to running Red Hat technology is that we run on just about everything and you know I can't stress enough how powerful that is how cost-effective that is and it just makes my life easier to be honest so if you're interested the people that built this actual rack right here gonna be hanging out in the customer success zone this whole week it's on the second floor the lobby there and they'd be glad to show you exactly how they built this thing so let me show you what we actually have in this rack so contained in this rack we have 1056 physical chorus right here we have five and a half terabytes of RAM and just in case we threw 50 terabytes of storage in this thing so burr that's about two million times more powerful than that first machine you boot it up thanks to a PC we're actually capable of putting all the power needs and cooling right in this rack so there's your data center right there you know it occurred to me last night that I can actually pull the power cord on this thing and kick it up a notch we could have the world's first mobile portable hybrid cloud so I'm gonna go ahead and unplug no no no no no seriously it's not unplug the thing we got it working now well Berg gets a little nervous but next year we're rolling this thing around okay okay so to recap multiple vendors check multiple architectures check multiple public clouds plug right into this thing check and everything everywhere is running the same software from Red Hat so that is a giant check so burn Angus why don't we get the demos rolling awesome so we have totally we have some amazing hardware amazing computers on this stage but now we need to light it up and we have Angus Thomas who represents our OpenStack engineering team and he's going to show us what we can do with this awesome hardware Angus thank you Beth so this was an impressive rack of hardware to Joe has bought a pocket stage what I want to talk about today is putting it to work with OpenStack platform director we're going to turn it from a lot of potential into a flexible scalable private cloud we've been using director for a while now to take care of managing hardware and orchestrating the deployment of OpenStack what's new is that we're bringing the same capabilities for on-premise manager the deployment of OpenShift director deploying OpenShift in this way is the best of both worlds it's bare-metal performance but with an underlying infrastructure as a service that can take care of deploying in new instances and scaling out and a lot of the things that we expect from a cloud provider director is running on a virtual machine on Red Hat virtualization at the top of the rack and it's going to bring everything else under control what you can see on the screen right now is the director UI and as you see some of the hardware in the rack is already being managed at the top level we have information about the number of cores in the amount of RAM and the disks that each machine have if we dig in a bit there's information about MAC addresses and IPs and the management interface the BIOS kernel version dig a little deeper and there is information about the hard disks all of this is important because we want to be able to make sure that we put in workloads exactly where we want them Jay could you please power on the two new machines at the top of the rack sure all right thank you so when those two machines come up on the network director is going to see them see that they're new and not already under management and is it immediately going to go into the hardware inspection that populates this database and gets them ready for use so we also have profiles as you can see here profiles are the way that we match the hardware in a machine to the kind of workload that it's suited to this is how we make sure that machines that have all the discs run Seth and machines that have all the RAM when our application workouts for example there's two ways these can be set when you're dealing with a rack like this you could go in an individually tag each machine but director scales up to data centers so we have a rules matching engine which will automatically take the hardware profile of a new machine and make sure it gets tagged in exactly the right way so we can automatically discover new machines on the network and we can automatically match them to a profile that's how we streamline and scale up operations now I want to talk about deploying the software we have a set of validations we've learned over time about the Miss configurations in the underlying infrastructure which can cause the deployment of a multi node distributed application like OpenStack or OpenShift to fail if you have the wrong VLAN tags on a switch port or DHCP isn't running where it should be for example you can get into a situation which is really hard to debug a lot of our validations actually run before the deployment they look at what you're intending to deploy and they check in the environment is the way that it should be and they'll preempts problems and obviously preemption is a lot better than debugging something new that you probably have not seen before is director managing multiple deployments of different things side by side before we came out on stage we also deployed OpenStack on this rack just to keep me honest let me jump over to OpenStack very quickly a lot of our opens that customers will be familiar with this UI and the bare metal deployment of OpenStack on our rack is actually running a set of virtual machines which is running Gluster you're going to see that put to work later on during the summit Jay's gone to an awful lot effort to get this Hardware up on the stage so we're going to use it as many different ways as we can okay let's deploy OpenShift if I switch over to the deployed a deployment plan view there's a few steps first thing you need to do is make sure we have the hardware I already talked about how director manages hardware it's smart enough to make sure that it's not going to attempt to deploy into machines they're already in use it's only going to deploy on machines that have the right profile but I think with the rack that we have here we've got enough next thing is the deployment configuration this is where you get to customize exactly what's going to be deployed to make sure that it really matches your environment if they're external IPs for additional services you can set them here whatever it takes to make sure that the deployment is going to work for you as you can see on the screen we have a set of options around enable TLS for encryption network traffic if I dig a little deeper there are options around enabling ipv6 and network isolation so that different classes of traffic there are over different physical NICs okay then then we have roles now roles this is essentially about the software that's going to be put on each machine director comes with a set of roles for a lot of the software that RedHat supports and you can just use those or you can modify them a little bit if you need to add a monitoring agent or whatever it might be or you can create your own custom roles director has quite a rich syntax for custom role definition and custom Network topologies whatever it is you need in order to make it work in your environment so the rawls that we have right now are going to give us a working instance of openshift if I go ahead and click through the validations are all looking green so right now I can click the button start to the deploy and you will see things lighting up on the rack directors going to use IPMI to reboot the machines provisioned and with a trail image was the containers on them and start up the application stack okay so one last thing once the deployment is done you're going to want to keep director around director has a lot of capabilities around what we call de to operational management bringing in new Hardware scaling out deployments dealing with updates and critically doing upgrades as well so having said all of that it is time for me to switch over to an instance of openshift deployed by a director running on bare metal on our rack and I need to hand this over to our developer team so they can show what they can do it thank you that is so awesome Angus so what you've seen now is going from bare metal to the ultimate private cloud with OpenStack director make an open shift ready for our developers to build their next generation applications thank you so much guys that was totally awesome I love what you guys showed there now I have the honor now I have the honor of introducing a very special guest one of our earliest OpenShift customers who understands the necessity of the private cloud inside their organization and more importantly they're fundamentally redefining their industry please extend a warm welcome to deep mar Foster from Amadeus well good morning everyone a big thank you for having armadillos here and myself so as it was just set I'm at Mario's well first of all we are a large IT provider in the travel industry so serving essentially Airlines hotel chains this distributors like Expedia and others we indeed we started very early what was OpenShift like a bit more than three years ago and we jumped on it when when Retta teamed with Google to bring in kubernetes into this so let me quickly share a few figures about our Mario's to give you like a sense of what we are doing and the scale of our operations so some of our key KPIs one of our key metrics is what what we call passenger borders so that's the number of customers that physically board a plane over the year so through our systems it's roughly 1.6 billion people checking in taking the aircrafts on under the Amarillo systems close to 600 million travel agency bookings virtually all airlines are on the system and one figure I want to stress out a little bit is this one trillion availability requests per day that's when I read this figure my mind boggles a little bit so this means in continuous throughput more than 10 million hits per second so of course these are not traditional database transactions it's it's it's highly cached in memory and these applications are running over like more than 100,000 course so it's it's it's really big stuff so today I want to give some concrete feedback what we are doing so I have chosen two applications products of our Mario's that are currently running on production in different in different hosting environments as the theme here is of this talk hybrid cloud and so I want to give some some concrete feedback of how we architect the applications and of course it stays relatively high level so here I have taken one of our applications that is used in the hospitality environment so it's we have built this for a very large US hotel chain and it's currently in in full swing brought into production so like 30 percent of the globe or 5,000 plus hotels are on this platform not so here you can see that we use as the path of course on openshift on that's that's the most central piece of our hybrid cloud strategy on the database side we use Oracle and Couchbase Couchbase is used for the heavy duty fast access more key value store but also to replicate data across two data centers in this case it's running over to US based data centers east and west coast topology that are fit so run by Mario's that are fit with VMware on for the virtualization OpenStack on top of it and then open shift to host and welcome the applications on the right hand side you you see the kind of tools if you want to call them tools that we use these are the principal ones of course the real picture is much more complex but in essence we use terraform to map to the api's of the underlying infrastructure so they are obviously there are differences when you run on OpenStack or the Google compute engine or AWS Azure so some some tweaking is needed we use right at ansible a lot we also use puppet so you can see these are really the big the big pieces of of this sense installation and if we look to the to the topology again very high high level so these two locations basically map the data centers of our customers so they are in close proximity because the response time and the SLA is of this application is are very tight so that's an example of an application that is architectures mostly was high ability and high availability in minds not necessarily full global worldwide scaling but of course it could be scaled but here the idea is that we can swing from one data center to the unit to the other in matters of of minutes both take traffic data is fully synchronized across those data centers and while the switch back and forth is very fast the second example I have taken is what we call the shopping box this is when people go to kayak or Expedia and they're getting inspired where they want to travel to this is really the piece that shoots most of transit of the transactions into our Mario's so we architect here more for high scalability of course availability is also a key but here scaling and geographical spread is very important so in short it runs partially on-premise in our Amarillo Stata Center again on OpenStack and we we deploy it mostly in the first step on the Google compute engine and currently as we speak on Amazon on AWS and we work also together with Retta to qualify the whole show on Microsoft Azure here in this application it's it's the same building blocks there is a large swimming aspect to it so we bring Kafka into this working with records and another partner to bring Kafka on their open shift because at the end we want to use open shift to administrate the whole show so over time also databases and the topology here when you look to the physical deployment topology while it's very classical we use the the regions and the availability zone concept so this application is spread over three principal continental regions and so it's again it's a high-level view with different availability zones and in each of those availability zones we take a hit of several 10,000 transactions so that was it really in very short just to give you a glimpse on how we implement hybrid clouds I think that's the way forward it gives us a lot of freedom and it allows us to to discuss in a much more educated way with our customers that sometimes have already deals in place with one cloud provider or another so for us it's a lot of value to set two to leave them the choice basically what up that was a very quick overview of what we are doing we were together with records are based on open shift essentially here and more and more OpenStack coming into the picture hope you found this interesting thanks a lot and have a nice summer [Applause] thank you so much deeper great great solution we've worked with deep Marv and his team for a long for a long time great solution so I want to take us back a little bit I want to circle back I sort of ended talking a little bit about the public cloud so let's circle back there you know even so even though some applications need to run in various footprints on premise there's still great gains to be had that for running certain applications in the public cloud a public cloud will be as impactful to to the industry as as UNIX era was of computing was but by itself it'll have some of the same limitations and challenges that that model had today there's tremendous cloud innovation happening in the public cloud it's being driven by a handful of massive companies and much like the innovation that sundeck HP and others drove in a you in the UNIX era of community of computing many customers want to take advantage of the best innovation no matter where it comes from buddy but as they even eventually saw in the UNIX era they can't afford the best innovation at the cost of a siloed operating environment with the open community we are building a hybrid application platform that can give you access to the best innovation no matter which vendor or which cloud that it comes from letting public cloud providers innovate and services beyond what customers or anyone can one provider can do on their own such as large scale learning machine learning or artificial intelligence built on the data that's unique probably to that to that one cloud but consumed in a common way for the end customer across all applications in any environment on any footprint in in their overall IT infrastructure this is exactly what rel brought brought to our customers in the UNIX era of computing that consistency across any of those footprints obviously enterprises will have applications for all different uses some will live on premise some in the cloud hybrid cloud is the only practical way forward I think you've been hearing that from us for a long time it is the only practical way forward and it'll be as impactful as anything we've ever seen before I want to bring Byrne his team back to see a hybrid cloud deployment in action burr [Music] all right earlier you saw what we did with taking bare metal and lighting it up with OpenStack director and making it openshift ready for developers to build their next generation applications now we want to show you when those next turn and generation applications and what we've done is we take an open shift and spread it out and installed it across Asia and Amazon a true hybrid cloud so with me on stage today as Ted who's gonna walk us through an application and Brent Midwood who's our DevOps engineer who's gonna be making sure he's monitoring on the backside that we do make sure we do a good job so at this point Ted what have you got for us Thank You BER and good morning everybody this morning we are running on the stage in our private cloud an application that's providing its providing fraud detection detect serves for financial transactions and our customer base is rather large and we occasionally take extended bursts of traffic of heavy traffic load so in order to keep our latency down and keep our customers happy we've deployed extra service capacity in the public cloud so we have capacity with Microsoft Azure in Texas and with Amazon Web Services in Ohio so we use open chip container platform on all three locations because openshift makes it easy for us to deploy our containerized services wherever we want to put them but the question still remains how do we establish seamless communication across our entire enterprise and more importantly how do we balance the workload across these three locations in such a way that we efficiently use our resources and that we give our customers the best possible experience so this is where Red Hat amq interconnect comes in as you can see we've deployed a MQ interconnect alongside our fraud detection applications in all three locations and if I switch to the MQ console we'll see the topology of the app of the network that we've created here so the router inside the on stage here has made connections outbound to the public routers and AWS and Azure these connections are secured using mutual TLS authentication and encrypt and once these connections are established amq figures out the best way auda matically to route traffic to where it needs to get to so what we have right now is a distributed reliable broker list message bus that expands our entire enterprise now if you want to learn more about this make sure that you catch the a MQ breakout tomorrow at 11:45 with Jack Britton and David Ingham let's have a look at the message flow and we'll dive in and isolate the fraud detection API that we're interested in and what we see is that all the traffic is being handled in the private cloud that's what we expect because our latencies are low and they're acceptable but now if we take a little bit of a burst of increased traffic we're gonna see that an EQ is going to push a little a bi traffic out onto the out to the public cloud so as you're picking up some of the load now to keep the Layton sees down now when that subsides as your finishes up what it's doing and goes back offline now if we take a much bigger load increase you'll see two things first of all asher is going to take a bigger proportion than it did before and Amazon Web Services is going to get thrown into the fray as well now AWS is actually doing less work than I expected it to do I expected a little bit of bigger a slice there but this is a interesting illustration of what's going on for load balancing mq load balancing is sending requests to the services that have the lowest backlog and in order to keep the Layton sees as steady as possible so AWS is probably running slowly for some reason and that's causing a and Q to push less traffic its way now the other thing you're going to notice if you look carefully this graph fluctuate slightly and those fluctuations are caused by all the variances in the network we have the cloud on stage and we have clouds in in the various places across the country there's a lot of equipment locked layers of virtualization and networking in between and we're reacting in real-time to the reality on the digital street so BER what's the story with a to be less I noticed there's a problem right here right now we seem to have a little bit performance issue so guys I noticed that as well and a little bit ago I actually got an alert from red ahead of insights letting us know that there might be some potential optimizations we could make to our environment so let's take a look at insights so here's the Red Hat insights interface you can see our three OpenShift deployments so we have the set up here on stage in San Francisco we have our Azure deployment in Texas and we also have our AWS deployment in Ohio and insights is highlighting that that deployment in Ohio may have some issues that need some attention so Red Hat insights collects anonymized data from manage systems across our customer environment and that gives us visibility into things like vulnerabilities compliance configuration assessment and of course Red Hat subscription consumption all of this is presented in a SAS offering so it's really really easy to use it requires minimal infrastructure upfront and it provides an immediate return on investment what insights is showing us here is that we have some potential issues on the configuration side that may need some attention from this view I actually get a look at all the systems in our inventory including instances and containers and you can see here on the left that insights is highlighting one of those instances as needing some potential attention it might be a candidate for optimization this might be related to the issues that you were seeing just a minute ago insights uses machine learning and AI techniques to analyze all collected data so we combine collected data from not only the system's configuration but also with other systems from across the Red Hat customer base this allows us to compare ourselves to how we're doing across the entire set of industries including our own vertical in this case the financial services industry and we can compare ourselves to other customers we also get access to tailored recommendations that let us know what we can do to optimize our systems so in this particular case we're actually detecting an issue here where we are an outlier so our configuration has been compared to other configurations across the customer base and in this particular instance in this security group were misconfigured and so insights actually gives us the steps that we need to use to remediate the situation and the really neat thing here is that we actually get access to a custom ansible playbook so if we want to automate that type of a remediation we can use this inside of Red Hat ansible tower Red Hat satellite Red Hat cloud forms it's really really powerful the other thing here is that we can actually apply these recommendations right from within the Red Hat insights interface so with just a few clicks I can select all the recommendations that insights is making and using that built-in ansible automation I can apply those recommendations really really quickly across a variety of systems this type of intelligent automation is really cool it's really fast and powerful so really quickly here we're going to see the impact of those changes and so we can tell that we're doing a little better than we were a few minutes ago when compared across the customer base as well as within the financial industry and if we go back and look at the map we should see that our AWS employment in Ohio is in a much better state than it was just a few minutes ago so I'm wondering Ted if this had any effect and might be helping with some of the issues that you were seeing let's take a look looks like went green now let's see what it looks like over here yeah doesn't look like the configuration is taking effect quite yet maybe there's some delay awesome fantastic the man yeah so now we're load balancing across the three clouds very much fantastic well I have two minute Ted I truly love how we can route requests and dynamically load transactions across these three clouds a truly hybrid cloud native application you guys saw here on on stage for the first time and it's a fully portable application if you build your applications with openshift you can mover from cloud to cloud to cloud on stage private all the way out to the public said it's totally awesome we also have the application being fully managed by Red Hat insights I love having that intelligence watching over us and ensuring that we're doing everything correctly that is fundamentally awesome thank you so much for that well we actually have more to show you but you're going to wait a few minutes longer right now we'd like to welcome Paul back to the stage and we have a very special early Red Hat customer an Innovation Award winner from 2010 who's been going boldly forward with their open hybrid cloud strategy please give a warm welcome to Monty Finkelstein from Citigroup [Music] [Music] hi Marty hey Paul nice to see you thank you very much for coming so thank you for having me Oh our pleasure if you if you wanted to we sort of wanted to pick your brain a little bit about your experiences and sort of leading leading the charge in computing here so we're all talking about hybrid cloud how has the hybrid cloud strategy influenced where you are today in your computing environment so you know when we see the variable the various types of workload that we had an hour on from cloud we see the peaks we see the valleys we see the demand on the environment that we have we really determined that we have to have a much more elastic more scalable capability so we can burst and stretch our environments to multiple cloud providers these capabilities have now been proven at City and of course we consider what the data risk is as well as any regulatory requirement so how do you how do you tackle the complexity of multiple cloud environments so every cloud provider has its own unique set of capabilities they have they're own api's distributions value-added services we wanted to make sure that we could arbitrate between the different cloud providers maintain all source code and orchestration capabilities on Prem to drive those capabilities from within our platforms this requires controlling the entitlements in a cohesive fashion across our on Prem and Wolfram both for security services automation telemetry as one seamless unit can you talk a bit about how you decide when you to use your own on-premise infrastructure versus cloud resources sure so there are multiple dimensions that we take into account right so the first dimension we talk about the risk so low risk - high risk and and really that's about the data classification of the environment we're talking about so whether it's public or internal which would be considered low - ooh confidential PII restricted sensitive and so on and above which is really what would be considered a high-risk the second dimension would be would focus on demand volatility and responsiveness sensitivity so this would range from low response sensitivity and low variability of the type of workload that we have to the high response sensitivity and high variability of the workload the first combination that we focused on is the low risk and high variability and high sensitivity for response type workload of course any of the workloads we ensure that we're regulatory compliant as well as we achieve customer benefits with within this environment so how can we give developers greater control of their their infrastructure environments and still help operations maintain that consistency in compliance so the main driver is really to use the public cloud is scale speed and increased developer efficiencies as well as reducing cost as well as risk this would mean providing develop workspaces and multiple environments for our developers to quickly create products for our customers all this is done of course in a DevOps model while maintaining the source and artifacts registry on-prem this would allow our developers to test and select various middleware products another product but also ensure all the compliance activities in a centrally controlled repository so we really really appreciate you coming by and sharing that with us today Monte thank you so much for coming to the red echo thanks a lot thanks again tamati I mean you know there's these real world insight into how our products and technologies are really running the businesses today that's that's just the most exciting part so thank thanks thanks again mati no even it with as much progress as you've seen demonstrated here and you're going to continue to see all week long we're far from done so I want to just take us a little bit into the path forward and where we we go today we've talked about this a lot innovation today is driven by open source development I don't think there's any question about that certainly not in this room and even across the industry as a whole that's a long way that we've come from when we started our first summit 14 years ago with over a million open source projects out there this unit this innovation aggregates into various community platforms and it finally culminates in commercial open source based open source developed products these products run many of the mission-critical applications in business today you've heard just a couple of those today here on stage but it's everywhere it's running the world today but to make customers successful with that interact innovation to run their real-world business applications these open source products have to be able to leverage increase increasingly complex infrastructure footprints we must also ensure a common base for the developer and ultimately the application no matter which footprint they choose as you heard mati say the developers want choice here no matter which no matter which footprint they are ultimately going to run their those applications on they want that flexibility from the data center to possibly any public cloud out there in regardless of whether that application was built yesterday or has been running the business for the last 10 years and was built on 10-year old technology this is the flexibility that developers require today but what does different infrastructure we may require different pieces of the technical stack in that deployment one example of this that Effects of many things as KVM which provides the foundation for many of those use cases that require virtualization KVM offers a level of consistency from a technical perspective but rel extends that consistency to add a level of commercial and ecosystem consistency for the application across all those footprints this is very important in the enterprise but while rel and KVM formed the foundation other technologies are needed to really satisfy the functions on these different footprints traditional virtualization has requirements that are satisfied by projects like overt and products like Rev traditional traditional private cloud implementations has requirements that are satisfied on projects like OpenStack and products like Red Hat OpenStack platform and as applications begin to become more container based we are seeing many requirements driven driven natively into containers the same Linux in different forms provides this common base across these four footprints this level of compatible compatibility is critical to operators who must best utilize the infinite must better utilize secure and deploy the infrastructure that they have and they're responsible for developers on the other hand they care most about having a platform that can creates that consistency for their applications they care about their services and the services that they need to consume within those applications and they don't want limitations on where they run they want service but they want it anywhere not necessarily just from Amazon they want integration between applications no matter where they run they still want to run their Java EE now named Jakarta EE apps and bring those applications forward into containers and micro services they need able to orchestrate these frameworks and many more across all these different footprints in a consistent secure fashion this creates natural tension between development and operations frankly customers amplify this tension with organizational boundaries that are holdover from the UNIX era of computing it's really the job of our platforms to seamlessly remove these boundaries and it's the it's the goal of RedHat to seamlessly get you from the old world to the new world we're gonna show you a really cool demo demonstration now we're gonna show you how you can automate this transition first we're gonna take a Windows virtual machine from a traditional VMware deployment we're gonna convert it into a KVM based virtual machine running in a container all under the kubernetes umbrella this makes virtual machines more access more accessible to the developer this will accelerate the transformation of those virtual machines into cloud native container based form well we will work this prot we will worked as capability over the product line in the coming releases so we can strike the balance of enabling our developers to move in this direction we want to be able to do this while enabling mission-critical operations to still do their job so let's bring Byrne his team back up to show you this in action for one more thanks all right what Red Hat we recognized that large organizations large enterprises have a substantial investment and legacy virtualization technology and this is holding you back you have thousands of virtual machines that need to be modernized so what you're about to see next okay it's something very special with me here on stage we have James Lebowski he's gonna be walking us through he's represents our operations folks and he's gonna be walking us through a mass migration but also is Itamar Hine who's our lead developer of a very special application and he's gonna be modernizing container izing and optimizing our application all right so let's get started James thanks burr yeah so as you can see I have a typical VMware environment here I'm in the vSphere client I've got a number of virtual machines a handful of them that make up my one of my applications for my development environment in this case and what I want to do is migrate those over to a KVM based right at virtualization environment so what I'm gonna do is I'm gonna go to cloud forms our cloud management platform that's our first step and you know cloud forms actually already has discovered both my rev environment and my vSphere environment and understands the compute network and storage there so you'll notice one of the capabilities we built is this new capability called migrations and underneath here I could begin to there's two steps and the first thing I need to do is start to create my infrastructure mappings what this will allow me to do is map my compute networking storage between vSphere and Rev so cloud forms understands how those relate let's go ahead and create an infrastructure mapping I'll call that summit infrastructure mapping and then I'm gonna begin to map my two environments first the compute so the clusters here next the data stores so those virtual machines happen to live on datastore - in vSphere and I'll target them a datastore data to inside of my revenue Arman and finally my networks those live on network 100 so I'll map those from vSphere to rover so once my infrastructure is map the next step I need to do is actually begin to create a plan to migrate those virtual machines so I'll continue to the plan wizard here I'll select the infrastructure mapping I just created and I'll select migrate my development environment from those virtual machines to Rev and then I need to import a CSV file the CSV file is going to contain a list of all the virtual machines that I want to migrate that were there and that's it once I hit create what's going to happen cloud forms is going to begin in an automated fashion shutting down those virtual machines begin converting them taking care of all the minutia that you'd have to do manually it's gonna do that all automatically for me so I don't have to worry about all those manual interactions and no longer do I have to go manually shut them down but it's going to take care of that all for me you can see the migrations kicked off here this is the I've got the my VMs are migrating here and if I go back to the screen here you can see that we're gonna start seeing those shutdown okay awesome but as people want to know more information about this how would they dive deeper into this technology later this week yeah it's a great question so we have a workload portability session in the hybrid cloud on Wednesday if you want to see a presentation that deep dives into this topic and how some of the methodologies to migrate and then on Thursday we actually have a hands-on lab it's the IT optimization VM migration lab that you can check out and as you can see those are shutting down here yeah we see a powering off right now that's fantastic absolutely so if I go back now that's gonna take a while you got to convert all the disks and move them over but we'll notice is previously I had already run one migration of a single application that was a Windows virtual machine running and if I browse over to Red Hat virtualization I can see on the dashboard here I could browse to virtual machines I have migrated that Windows virtual machine and if I open up a tab I can now browse to my Windows virtual machine which is running our wingtip toy store application our sample application here and now my VM has been moved over from Rev to Vita from VMware to Rev and is available for Itamar all right great available to our developers all right Itamar what are you gonna do for us here well James it's great that you can save cost by moving from VMware to reddit virtualization but I want to containerize our application and with container native virtualization I can run my virtual machine on OpenShift like any other container using Huebert a kubernetes operator to run and manage virtual machines let's look at the open ship service catalog you can see we have a new virtualization section here we can import KVM or VMware virtual machines or if there are already loaded we can create new instances of them for the developer to work with just need to give named CPU memory we can do other virtualization parameters and create our virtual machines now let's see how this looks like in the openshift console the cool thing about KVM is virtual machines are just Linux processes so they can act and behave like other open shipped applications we build in more than a decade of virtualization experience with KVM reddit virtualization and OpenStack and can now benefit from kubernetes and open shift to manage and orchestrate our virtual machines since we know this virtual machine this container is actually a virtual machine we can do virtual machine stuff with it like shutdown reboot or open a remote desktop session to it but we can also see this is just a container like any other container in openshift and even though the web application is running inside a Windows virtual machine the developer can still use open shift mechanisms like services and routes let's browse our web application using the OpenShift service it's the same wingtip toys application but this time the virtual machine is running on open shift but we're not done we want to containerize our application since it's a Windows virtual machine we can open a remote desktop session to it we see we have here Visual Studio and an asp.net application let's start container izing by moving the Microsoft sequel server database from running inside the Windows virtual machine to running on Red Hat Enterprise Linux as an open shipped container we'll go back to the open shipped Service Catalog this time we'll go to the database section and just as easily we'll create a sequel server container just need to accept the EULA provide password and choose the Edition we want and create a database and again we can see the sequel server is just another container running on OpenShift now let's take let's find the connection details for our database to keep this simple we'll take the IP address of our database service go back to the web application to visual studio update the IP address in the connection string publish our application and go back to browse it through OpenShift fortunately for us the user experience team heard we're modernizing our application so they pitched in and pushed new icons to use with our containerized database to also modernize the look and feel it's still the same wingtip toys application it's running in a virtual machine on openshift but it's now using a containerized database to recap we saw that we can run virtual machines natively on openshift like any other container based application modernize and mesh them together we containerize the database but we can use the same approach to containerize any part of our application so some items here to deserve repeating one thing you saw is Red Hat Enterprise Linux burning sequel server in a container on open shift and you also saw Windows VM where the dotnet native application also running inside of open ships so tell us what's special about that that seems pretty crazy what you did there exactly burr if we take a look under the hood we can use the kubernetes commands to see the list of our containers in this case the sequel server and the virtual machine containers but since Q Bert is a kubernetes operator we can actually use kubernetes commands like cube Cpl to list our virtual machines and manage our virtual machines like any other entity in kubernetes I love that so there's your crew meta gem oh we can see the kind says virtual machine that is totally awesome now people here are gonna be very excited about what they just saw we're gonna get more information and when will this be coming well you know what can they do to dive in this will be available as part of reddit Cloud suite in tech preview later this year but we are looking for early adopters now so give us a call also come check our deep dive session introducing container native virtualization Thursday 2:00 p.m. awesome that is so incredible so we went from the old to the new from the close to the open the Red Hat way you're gonna be seeing more from our demonstration team that's coming Thursday at 8 a.m. do not be late if you like what you saw this today you're gonna see a lot more of that going forward so we got some really special things in store for you so at this point thank you so much in tomorrow thank you so much you guys are awesome yeah now we have one more special guest a very early adopter of Red Hat Enterprise Linux we've had over a 12-year partnership and relationship with this organization they've been a steadfast Linux and middleware customer for many many years now please extend a warm welcome to Raj China from the Royal Bank of Canada thank you thank you it's great to be here RBC is a large global full-service is back we have the largest bank in Canada top 10 global operate in 30 countries and run five key business segments personal commercial banking investor in Treasury services capital markets wealth management and insurance but honestly unless you're in the banking segment those five business segments that I just mentioned may not mean a lot to you but what you might appreciate is the fact that we've been around in business for over 150 years we started our digital transformation journey about four years ago and we are focused on new and innovative technologies that will help deliver the capabilities and lifestyle our clients are looking for we have a very simple vision and we often refer to it as the digitally enabled bank of the future but as you can appreciate transforming a hundred fifty year old Bank is not easy it certainly does not happen overnight to that end we had a clear unwavering vision a very strong innovation agenda and most importantly a focus towards a flawless execution today in banking business strategy and IT strategy are one in the same they are not two separate things we believe that in order to be the number one bank we have to have the number one tactic there is no question that most of today's innovations happens in the open source community RBC relies on RedHat as a key partner to help us consume these open source innovations in a manner that it meets our enterprise needs RBC was an early adopter of Linux we operate one of the largest footprints of rel in Canada same with tables we had tremendous success in driving cost out of infrastructure by partnering with rahat while at the same time delivering a world-class hosting service to your business over our 12 year partnership Red Hat has proven that they have mastered the art of working closely with the upstream open source community understanding the needs of an enterprise like us in delivering these open source innovations in a manner that we can consume and build upon we are working with red hat to help increase our agility and better leverage public and private cloud offerings we adopted virtualization ansible and containers and are excited about continuing our partnership with Red Hat in this journey throughout this journey we simply cannot replace everything we've had from the past we have to bring forward these investments of the past and improve upon them with new and emerging technologies it is about utilizing emerging technologies but at the same time focusing on the business outcome the business outcome for us is serving our clients and delivering the information that they are looking for whenever they need it and in whatever form factor they're looking for but technology improvements alone are simply not sufficient to do a digital transformation creating the right culture of change and adopting new methodologies is key we introduced agile and DevOps which has boosted the number of adult projects at RBC and increase the frequency at which we do new releases to our mobile app as a matter of fact these methodologies have enabled us to deliver apps over 20x faster than before the other point about around culture that I wanted to mention was we wanted to build an engineering culture an engineering culture is one which rewards curiosity trying new things investing in new technologies and being a leader not necessarily a follower Red Hat has been a critical partner in our journey to date as we adopt elements of open source culture in engineering culture what you seen today about red hearts focus on new technology innovations while never losing sight of helping you bring forward the investments you've already made in the past is something that makes Red Hat unique we are excited to see red arts investment in leadership in open source technologies to help bring the potential of these amazing things together thank you that's great the thing you know seeing going from the old world to the new with automation so you know the things you've seen demonstrated today they're they're they're more sophisticated than any one company could ever have done on their own certainly not by using a proprietary development model because of this it's really easy to see why open source has become the center of gravity for enterprise computing today with all the progress open-source has made we're constantly looking for new ways of accelerating that into our products so we can take that into the enterprise with customers like these that you've met what you've met today now we recently made in addition to the Red Hat family we brought in core OS to the Red Hat family and you know adding core OS has really been our latest move to accelerate that innovation into our products this will help the adoption of open shift container platform even deeper into the enterprise and as we did with the Linux core platform in 2002 this is just exactly what we did with with Linux back then today we're announcing some exciting new technology directions first we'll integrate the benefits of automated operations so for example you'll see dramatic improvements in the automated intelligence about the state of your clusters in OpenShift with the core OS additions also as part of open shift will include a new variant of rel called Red Hat core OS maintaining the consistency of rel farhat for the operation side of the house while allowing for a consumption of over-the-air updates from the kernel to kubernetes later today you'll hear how we are extending automated operations beyond customers and even out to partners all of this starting with the next release of open shift in July now all of this of course will continue in an upstream open source innovation model that includes continuing container linux for the community users today while also evolving the commercial products to bring that innovation out to the enterprise this this combination is really defining the platform of the future everything we've done for the last 16 years since we first brought rel to the commercial market because get has been to get us just to this point hybrid cloud computing is now being deployed multiple times in enterprises every single day all powered by the open source model and powered by the open source model we will continue to redefine the software industry forever no in 2002 with all of you we made Linux the choice for enterprise computing this changed the innovation model forever and I started the session today talking about our prediction of seven years ago on the future being open we've all seen so much happen in those in those seven years we at Red Hat have celebrated our 25th anniversary including 16 years of rel and the enterprise it's now 2018 open hybrid cloud is not only a reality but it is the driving model in enterprise computing today and this hybrid cloud world would not even be possible without Linux as a platform in the open source development model a build around it and while we have think we may have accomplished a lot in that time and we may think we have changed the world a lot we have but I'm telling you the best is yet to come now that Linux and open source software is firmly driving that innovation in the enterprise what we've accomplished today and up till now has just set the stage for us together to change the world once again and just as we did with rel more than 15 years ago with our partners we will make hybrid cloud the default in the enterprise and I will take that bet every single day have a great show and have fun watching the future of computing unfold right in front of your eyes see you later [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] anytime [Music]
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