>>Good morning from Los Angeles, Lisa Martin here at Qube con cloud native con north America, 2021. This is the cubes third day, a wall-to-wall coverage. So great to be back at an event in person I'm excited to be joined by Vince Wang, senior director of products at 49. We're going to talk security and Kubernetes then welcome to the program. >>Thank you for having me. >>So I always love talking to 40 minutes. Cybersecurity is something that is such an impersonal interest of mine. The fording that talks about the importance of integrating security and compliance and the dev sec ops workflow across the container life cycle. Why is this important and how do you help companies achieve it? >>Well, as companies are making digital innovations, they're trying to move faster and as to move faster, or many companies are shifting towards a cloud native approach, uh, rapid integrations, rapid development, and rapid deployment, uh, but sometimes speed, you know, there's a benefit to that, but there's also the downside of that, where, you know, you can lose track of issues and you can, uh, introduce a human error in a problem. So as part of the, as part of the, the, the means to deliver fast while maintaining his six year approach, where both the company and the organizations delivering it and their end customers, it's important to integrate security throughout the entire life cycle. From the moment you start planning and development, and people's in process to when you're developing it and then deploying and running in production, um, the entire process needs to be secured, monitored, and, um, and vetted regularly with good quality, um, processes, deep visibility, and an integrated approach to the problem. Um, and I think the other thing to also consider is in this day and age with the current situation with COVID, there's a lot of, uh, development of employment in terms of what I call NASA dental Baltic cloud, where you're deploying applications in random places, in places that are unplanned because you need speed and that, uh, diversity of infrastructure and diversity of, uh, of clouds and development and things to consider then, uh, produces a lot of, uh, you know, uh, opportunities for security and, and challenges to come about. >>And we've seen so much change from a security perspective, um, the threat landscape over the last 18 months. So it's absolutely critical that the integration happens shifting left. Talk to us about now let's switch topics. Application teams are adopting CIC D uh, CICB workflows. Why does security need to be at the center of that adoption? >>Well, it goes back to my earlier point where when you're moving fast, your organizations are doing, um, you're building, deploying, running continuously and monitoring, and then improving, right? So the idea is you're, you're creating smaller, incremental changes, throwing it to the cloud, running it, adjusting it. So then you're, you're rapidly integrating and you're rapidly developing and delivery. And again, it comes down to that, that rapid nature, uh, things can happen. There's, there's more, uh, more points of touching and there's more points of interactions. And, you know, and again, when you're moving that fast, it's really easy to, um, miss things along the way. So as you have security as a core fundamental element of that DNA, as you're building it, uh, that that's in parallel with everything you're doing, you just make sure that, um, when you do deliver something that is the most secure application possible, you're not exposing your customers or your organizations to unforeseen risks that just kind of sits there. >>Uh, and I think part of that is if you think about cloud infrastructure, misconfiguration is still number one, uh, biggest problem with, uh, with security on the, in the cloud space, there's, uh, tasks and vulnerabilities those, we all know, and there's there's means to control that, but the configurations, when you're storing the data, the registries, all these different considerations that go into a cloud environment, those are the things that organizations need visibility on. And, um, the ability to, to adopt their processes, to be proactive in those things and know what they, uh, do. They just need to know what, what then, where are they're operating in, um, to kind of make these informed decisions. >>That visibility is key. When you're talking with customers in any industry, what are the top three, let's say recommendations to say, here's how you can reduce your exposure to security vulnerabilities in the CIS CD pipeline. What are some of the things that you recommend there to reduce the risk? >>There's a couple, oh, obviously security as a fundamental practice. We've been talking about that. So that's number one, key number. The second thing that I would say would be, uh, when you're adopting solutions, you need to consider the fact that there is a very much of a heterogeneous environment in today's, uh, ecosystem, lots of different clouds, lots of different tools. So integration is key. The ability to, um, have choices of deployment, uh, in terms of where you wanted to play. You don't want to deploy based upon the technology limitations. You want to deploy and operate your business to meet your business needs and having the right of integrations and toolings to, uh, have that flexibility. Now, option is key. And I think the third thing is once you have security, the choices, then you can treat, you create a situation where there's a lot of, uh, you know, process overhead and operational overhead, and you need a platform, a singular cybersecurity platform to kind of bring it all in that can work across multiple technologies and environments, and still be able to control at the visibility and consolidate, uh, policies and nationally consistent across all closet points. >>So we're to the DevOps folks, what are some of the key considerations that they need to take into >>Account to ensure that their container strategy isn't compromising security? Well, I think it comes down to having to think outside of just dev ops, right? You have to, we talk about CIC D you have to think beyond just the build process beyond just where things live. You have to think continuous life cycles and using a cyber security platform that brings it together, such as we have the Fortinet security fabric that does that tying a lot of different integration solutions. We work well within their core, but theirs have the ability to integrate well into various environments that provide that consistent policies. And I think that's the other thing is it's not just about integration. It's about creating that consistency across class. And the reality is also for, I think today's dev ops, many organizations are in transition it's, you know, as, as much as we all think and want to kind of get to that cloud native point in time, the reality is there's a lot of legacy things. >>And so dev ops set ups, the DevSecOps, all these different kind of operational functions need to consider the fact that everything is in transition. There are legacy applications, they are new cloud native top first type of application delivery is using containers of various technologies. And there needs to be a, again, that singular tool, the ability to tie this all together as a single pane of glass, to be able to then navigate emerge between legacy deployments and applications with the new way of doing things and the future of doing things with cloud native, uh, and it comes down again to, to something like the Fortinet security fabric, where we're tying things together, having solutions that can deploy on any cloud, securing any application on any cloud while bringing together that consistency, that visibility and the single point management, um, and to kind of lower that operational overhead and introduce security as part of the entire life cycle. >>Do you have a Vincent example of a customer that 49 has worked with that has done this, that you think really shows the value of what you're able to enable them to achieve? >>We do. We do. We have lots of customers, so can name any one specific customer for various reasons, you know, it's security after all. Um, but the, the most common use cases when customers look at it, that when you, we talked to a CIO, CSO CTO is I think that's a one enter they ask us is, well, how do we, how do we manage in this day and age making these cloud migrations? Everyone? I think the biggest challenge is everyone is in a different point in time in their cloud journey. Um, there's if you talk to a handful of customers or a rueful customers, you're not going to find one single organization that's going to be at the same point in time that matches them yet another person, another organization, in terms of how they're going about their cloud strategies, where they're deploying it at what stage of evolution there are in their organizational transformations. >>Um, and so what they're looking for is that, that that's the ability to deploy and security any application on any topic throughout their entire application life cycle. Um, and so, so the most common things that, that our customers are looking for, um, and, you know, they're doing is they're looking to secure things on the network and then interconnected to the cloud with, uh, to deliver that superior, uh, application experience. So they were deploying something like the security fabric. Uh, again, you know, Fordanet has a cybersecurity approach to that point and securing the native environments. They're looking at dev ops, they're deploying tooling to provide, uh, you know, security posture management, plus a few posture management to look at the things that are doing that, the registries, their environment, the dev environment, to then securing their cloud, uh, networks, uh, like what we do with our FortiGate solutions, where we're deploying things from the dev ops. >>I feel secure in the cloud environment with our FortiGate environments across all the various multitudes of cloud providers, uh, like, uh, AWS Azure, Google cloud, and that time that together with, with some secure, um, interconnections with SD LAN, and then tying that into the liver and productions, um, on the web application side. So it's a very much a continuous life cycle, and we're looking at various things. And again, the other example we have is because of the different places in different, uh, in terms of Tod journeys, that the number one key is the ability to then have that flexibility deployment to integrate well into existing infrastructure and build a roadmap out for, uh, cloud as they evolve. Because when you talk to customers today, um, they're not gonna know where they're going to be tomorrow. They know they need to get there. Uh, they're not sure how they're going to get there. And so what they're doing now is they're getting to cloud as quickly as they can. And then they're looking for flexibility to then kind of adjust and they need a partner like Fordanet to kind of bring that partnership and advisorship to, uh, to those organizations as they make their, their, their strategies clearer and, uh, adjust to new business demands. >>Yeah. That partnership is key there. So afforded it advocates, the importance of taking a platform approach to the application life cycle. Talk to me about what that means, and then give me like the top three considerations that customers need to be considering for this approach. >>Sure. Number one is how flexible is that deployment in terms of, do you, do customers have the option to secure and deploy any application, any cloud, do they have the flexibility of, um, integrating security into their existing toolings and then, uh, changing that out as they need, and then having a partner and a customer solution that kind of grows with that? I think that's the number one. Number two is how well are these, uh, integrations or these flexible options tied together? Um, like what we do with the security fabric, where everything kind of starts with, uh, the idea of a central management console that's, you know, uh, and consistent policies and security, um, from the get-go. And I think the third is, is looking at making sure that the, the, the security integrations, the secure intelligence is done in real time, uh, with a quality source of information, uh, and, and points of, uh, of responsiveness, um, what we do with four guard labs. >>For example, we have swell of large, um, machine learning infrastructure where have supported by all the various customer inputs and great intelligence organizations, but real time intelligence and percussion as part of that deployment life cycle. Again, this kind of really brings it all together, where organizations looking for application security and, and trying to develop in a CSED fashion. And you have the ability to then have security from the get, go hide ident to the existing toolings for flexibility, visibility, and then benefits from security all along the way with real time, you know, uh, you know, leading edge security, that then kind of brings that, that sense of confidence and reassurance as they're developing, they don't need to worry about security. Security should just be part of that. And they just need to worry about solving the customer problems and, uh, and, you know, delivering business outcomes and results. >>That's it, right? It's all about those business outcomes, but delivering that competence is key. Vince, thank you for joining me on the program today, talking through what 49 is doing, how you're helping customers to integrate security and compliance into the dev dev sec ops workflow. We appreciate your insights. >>Thank you so much for your time. I really appreciate it. My >>Pleasure for vents Wang. I'm Lisa Martin. You're watching the cube live from Los Angeles, uh, cube con and cloud native con 21 stick around at Dave Nicholson will join me next with my next guest.

(lively music) >> Narrator: From San Francisco, it's theCUBE. Covering GitLab Commit 2020. Brought to you by GitLab. >> Hi, I'm Stu Miniman. And this is the theCUBE's exclusive coverage of GitLab Commit 2020, here in San Francisco. You might notice it's a little chilly in San Francisco today. Welcome to the program, first time against Vince Stammegna who is the senior director of engineering at Axway and you can tell by the GitLab Commit jacket that he's a speaker at the show and good thing to wear that one today, yes, Vince? >> Yes, it's very very chilly here. But we're all having a great time. >> Yeah, absolutely. It's the warmth of the community that that's keeping everyone going. First of all, I believe it's first time we have Axway on our program, so people that don't know, tell us a little bit about Axway. >> Sure, Axway is in the business of helping save your company, basically, and help them through the digital transformation. So if you've ever deposited a check electronically on your phone, you've probably, there's a 90% chance you've crossed one of our API gateways or Managed File Transfer systems. So we've helped banks, we've helped hospitals, healthcare, lots of verticals and assisting them through their digital transformation. >> Awesome, so yeah, we love talking about digital transformation. Your presentation here at Commit is actually about journey to cloud. So tell us a little bit about what that means, gets a little bit of you inside what you're going to be sharing with the community here. >> Sure, journey to the cloud is a program that we conceived a couple years ago. And it's all about bringing our company into the cloud native space as well as bringing our existing product line into the cloud, so it can run, it can scale, easy to deploy day to operations. So what we're going to talk about today is basically Axway's journey from, as an ISV going from quarterly and semi-annual deliveries to daily deployments, low change failure rates, fast lead time for changes, so. >> Yeah, it's wonderful things if you hear about DevOps it's all about how we can shorten those release cycles and have those continuous feedback loops. So how long have you been with Axway? >> I've been with Axway for four years now. >> Okay, so yeah, bring us inside a little bit that journey is, what are the ripple effects as you try to tighten things down and not get on the train but just ship and ship and ship. (chuckling) >> Yeah, absolutely. I can say that it's a journey that really requires vigilance. It's constant practice, continuous learning to be lean. So if I were to describe the journey, it's about contributing together, working as one team to build one platform. And that's across DevOps and security. We'll go into a bit about how we really shift, shift in security-left this year by working closely with them. We really took the time to seek to understand their needs as well as the security team understanding our needs in terms of continuous deployment. And we work together on a solution called the Continuous Security Review, allows us to get to the deployment frequency of multiple times per day versus the deployment frequency before that we still followed the traditional initial security review, final security review. We could only release once a sprint, two weeks. >> Yeah, a mantra we've heard at many of the shows we go to is, "security is everyone's responsibility." Was there a lot of training that needed to be done? Did you have to, did the security people kind of lock everybody in the room and make them watch films? Or how did you work through some of these changes? >> That's a great question. So there are a lot of things that our product security group does along with our cloud security team. They do have training globally for Axway not only for the development team, operations team as well. They also, we also have built cross-functional teams within our scrum teams. So our scrum teams contain what's called a SPOC, a security point of contact, DevOps point of contact, the quality point of contact. And those members of the team help that scrum team have full ownership of that service. So when you say security is everybody's job, it's really security, quality, reliability, scalability, and stability is everybody's job. And when you build those cross-functional teams, you're able to provide the team the capability to have the ownership to take those services into the cloud on a daily basis. >> All right, Vince, help us connect the dots. Axway and GitLab, what's the connection there? >> Another great question. So we became a GitLab customer back in 2015. We were on SVN primarily and through lots of acquisitions, either CVS or SVN, and we were looking at the next generation source control management tool. We actually invested and purchased GitLab for Axway in 2015 because it had non-premise offering and we needed to store all of our source code on-premise. We have contracts with the governments around the world and so that's how our journey started. But what we couldn't have imagine was how it was going to evolve. And that's why we're so happy with GitLab. They really take our feedback seriously. A lot of things that we've asked them to go ahead and implement, they've gone and iterated and implemented those things. Allowed us to test features, get faster feedback. One of the things we were looking for was EKS recently as a native way to, basically, plug an EKS as a GitLab runner and run your workloads there. That was implemented, I think, within the last release or two releases ago. So we really appreciate GitLab's responsiveness with their product. >> Okay, yes, you're talking about Amazon's Kubernetes. >> Yes. >> Of course they're so, you talked about on-premises, what is your cloud deployment? Are you multicloud now or, what's and where does Kubernetes fit in that overall discussion? >> Another great question. So our journey to cloud native started with a product called AMPLIFY Central. And what we did was, we start out with docker swarm. We evolved to cops. At the time when we had first gotten our production deployment running on cops, EKS was just in its initial phases of rolling out. We're an Amazon Premier Technology partner. And we actually help them with their evaluation of the initial bit of EKS, give them feed back. A year later, we're looking at it as a way to consolidate platform and allow our teams to focus on building a better product rather than having infrastructure overhead of upgrading infrastructure to, and going through those cycles we can just test the infrastructure before we roll it out. >> All right, so Vince, you're talking a lot about your journey to cloud, what advice do you give to your peers as they're heading down their own journey. >> The advice I give to my peers is to keep calm (chuckles) and we'll go over that in our presentation. But really, it's about behavior change. So it's not just a words that are on some paper that you walk into and you look at. You really have to embody those behaviors and have those feelings about what you're doing. And that's going to change your values and attitudes about how you act and work and help each other out. And that's how you break down silos, and ultimately that's what changes culture. It's your values, attitudes, beliefs, and behaviors that culminate to build a one team, operating as one team to deliver one platform. >> Okay, so you're speaking at the show, obviously you've used GitLab quite a bit. What else, what brings you to this show? What are you hoping to get out of it? >> Just to see what our peers and fellow practitioners are doing in a cloud. See how GitLab's evolving. It was really great keynote this morning from Todd and Sid. So it's great to keep abreast as to what, even some of our customers are here today and to hear their story about how they're moving to the cloud and how might parallel and some things that we can learn from them. That's one of the key behaviors when you move towards cloud native is creating a culture of learning and that's how you grow. >> All right, well, Vince, thanks so much sharing your journey. >> Appreciate it. >> Great to meet you. >> Thanks so much too. >> Best luck with your presentation. And I'm Stu Miniman. This is GitLab Commit 2020. Thanks so much for watching theCUBE. (lively music)

>> Narrator: Live from Las Vegas, it's the Cube! Covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> Welcome back here on the Cube as we continue our coverage of Dell Technologies World 2018. We are live and we are in Las Vegas. Along with Stu Miniman, I'm John Walls, we're now joined by Vince Affatati, whose the the global VP of sale and pre-sales at Dell EMC. It's good to see you sir. >> Thanks for having me. >> John: And Dan Serpico who's the CEO of FusionStorm. Dan, good to see you as well. >> Nice to see you. >> Thanks for joining us here we appreciate it, especially late in the day. >> Dan: Yeah absolutely, glad to be here >> First off Dan, tell us a little about FusionStorm and we'll get into the channel partnership a little bit later, but first off a little bit more about what you do. >> Great, well FusionStorm is a global solution provider, we're rapidly approaching a billion dollars in sales, probably hit a billion dollars in sales this year, and Dell Technologies is our principal partner. >> Alright and then the partnership program, if you would get, a little bit of great success, you know, it's just an absolute home run, but, again, how does working with Dan's company kind of personify what you do in the broader scheme? >> Yeah I mean, FusionStorm's a great partner, you know, part of what we want to talk about today is Ready Stack and how, kind of, this partnership and this program evolved based on, kind of cross-engineering and marketing that we do together and how, you know, Dan's team is so much closer, they're very close to the business of our customers and they have a great understanding of what's needed in the marketplace, so they're able to design and engineer and support the service solutions that are really unique, they hit an industry vertical and they really leverage, kind of, the best of our technologies, so, it's a great partnership. >> Dan: Yes it is. >> Yeah, Dan maybe you could expand a little, you said that, you know, Dell's your primary partner, why is that, you know, what kind of things do they do to enable you from a channel partner to meet what your customers need and, you know, make the money you need to run your business? >> Boy-oh-boy, we probably don't have enough time in this interview to talk about why Dell's our best partner. Look, all kidding aside, they are our largest partner, they have the broadest portfolio of technology solutions bar-none compared to any of our other partners, they're number one in most of the technology stacks, which is really important, our customers want leading edge technology. Our customers are Google, Facebook, Apple, Square, Pandora, they want leading edge technology as part of their play and Dell has really a incredible portfolio, then frankly, from the business side, the tremendous partnership with the great channel program, which gives us a terrific opportunity to partner from a marketing perspective, back-end rebates and incentives are a critical part of our value add and profitability model, so they touch all of the important points that make us a viable business. >> Vince, we talked to Marius Haas a little bit this morning about how the Dell and the EMC pieces came together and of course, you know, long history of channel with both sides, but bring us inside some of those, you know, incentives and rebates and things that Dan was talking to, you know, how does Dell set up those programs and, you know, bring us inside a little bit. >> Yeah, so, there's front-end rebates and there's back-end rebates, we're actually in our second year of rebate design, so we've done some things to kind of change it, but ultimately, there's rebates paid on dollar one across our full, a full stack, so, and then as the metal, as you go in the metal tiers, the rebates kind of increase, right, so our top tier partners get a higher rebate amount and then today, we announced a richer rebate for taking our competitive gear, so that's on the back-end and those are the traditional design. Now on the front-end we have storage rebates, we announced about five months ago or so, which incent you to basically sell our modern infrastructure or the storage side, include DPS into those designs and then take out competitive gear. We also have some incentives for proposal writing and demand generation as well, so a pretty rich program. >> Alright, so Dan here's the question I have for ya. Dell, they've got a lot of offerings out there and change is something that, you know, at the keynote this morning they said, you know, today compared to the past, you know, is the busiest we've ever been, but tomorrow there's even going to be more change. So, do they make it simple, I mean, you know, that's something, you know, we're all looking for, you got to run your business, you got to listen to your customers, you know, how is it easier when, you know, working with Dell? >> Well, I think it's easier because they are leading the pack, really, if you think about the world of technology and how it evolves constantly, everybody is leap-frogging everybody else every six months, so what you want is, you want a partner who's going to be leading the technology play for the future, honestly. Our business 15 years ago sold, 99% of what we sold 15 years ago, we do not sell a nickel today, not a nickel because that partner couldn't keep up with the evolution that takes place in technology today. So really, while I appreciate the question, it's really not about what's easy, it's what is most advanced so that you can stay competitive. >> You know, Vince was talking about incentives, he was talking about rebates, right. And so, from your side of that fence, if you will, how critical is it that you have those kinds of opportunities or you have that kind of incentive, I would think in a competitive environment, it's fairly crucial, right, I mean, you've got to be able to offer to each other and then down the line, that kind of value, right? >> It's tremendously important, we pride ourselves on our ability to help influence customers in their buy-decisions around technology, okay. And so, look we're not going to sell, regardless of what the incentives are, we aren't going to sell bad products and bad technologies 'cause that's a good way to lose customers, but certainly the financial rewards for our sellers, for our SEs, and for us as a company so we can continue to stay viable is critically important and we absolutely take advantage of the programs that are in place with Dell and others too, by the way, but certainly with Dell and direct our customers to those things that make the most sense for them. >> Yeah, right, I mean really, simple, predictable and profitable, we talk about it a lot, but that's ultimately where we're trying to go. We're not perfect, we've learned a lot, but, you know, strong partnerships like this make it clear that that's the right way to go about it and it is more than just incentives, it's staffing, it's dedicating people to help, help make the business easier, doing boot camps and joint seminars and, you know, selling together. And that works. >> Vince, the other thing, can you put into context for us, you know, Ready Stack, we've got everything from, you know, Full Stack, everything bake to, you know, some of the software platforms, you know. What's in here and, you know, how does this fit in the overall? >> So, Ready Stack is a way to address a market that we haven't gone after directly, which is the build systems, when you look at converge infrastructure, it's about a six billion dollar market. We own about 49% of that and with the VxBlock 1000, is a good example of those, kind of, integrated systems, right? But what we haven't really done a lot of and we're really going into feet-first, head-first is the idea that we want to help with customers who aren't ready to buy the Full Stack, but they want to do something that's engineered special right? So, providing, Ready Stack is a way to, it's so we're close with our, it's a partner exclusive program we work with the partners to make it easier for them to sell our tech, right, into converged environments to help solve problems. I mean, it's something that you guys do everyday, already, but it's a program to help with the engineering and provide incentives, to make that easier to do. >> Well, I think that's right, the converged infrastructure which is, you know, what we call this, is probably, outside of maybe cloud computing and that world, the single fastest growing part of the tech space today, right? It's what our customers need, it's what our customers want. I think that what's unique about the Ready Stack play here, the architecture, is that it's flexible, okay? It's flexible and leads with Dell and leads with certified architecture, as opposed to others who are just taking piece parts from different vendors, cobbling it together and calling it a certified converged play, this is a truly converged play that has flexibility. Flexibility could mean that someone's, a customer's storage needs grow faster than compute needs or vice versa, alright? So you're not locked in a solution, but you still, you're locked in on a framework that allows you to expand based on your unique needs, then when you take their architecture and their engineering capabilities in combination with ours, the blueprints, you get, you have a really robust solution that we can align ourselves with and be consistent in terms of our delivery to the customers. >> So, you tell us about flexibility, I mean that, that's kind of a buzzword, right? I mean, you want to give people the ability to customize, right? Do people, I mean, are your customers now, you know, Dan, do they really, I mean, do people know what they want or because they have new capabilities, they have new, there are new avenues they can go down, new choices. I mean, how do you get 'em there? >> Well, our customers are very smart, again, if you heard the partial list of customers that we have, they are very smart and they're looking at this. >> Stu: You mentioned a couple of big names there. >> We've recognized a few of those. >> But they are very smart and access to Dell, lot of them are here at Dell Technologies World, they read information on the internet, these are very smart people, of course, but let's not undermine our role, or underestimate our role in helping them, whether it's through our labs, to do bake-offs, we can take, we can run some of their workloads on our architecture or the Dell architecture versus others and they can see how this technology works or how their workloads work, what performs better for them for their unique specs. There is constantly discussion around white boarding, okay? The technology is moving all the time and I don't think that can be underestimated either, right? If you look at a data center, if you picked up a thousand customers and looked at their data center, probably no three of them would be exactly alike because of the nature of technology, so what you need, is you need an OEM, like Dell Technologies get a robust portfolio of products and a good partner, like FusionStorm who can offer that robust portfolio and help it be fully integrable with all these other technologies, right? Look, the truth of the matter is that we would love to rip out somebody else, but that has a depreciation life and CIOs have to live with something they bought last year, for three years. So, how is that compatibility going to exist? That's very important; so all those things are part of the education of our customers. >> Vince, I know there's a huge push at this show, working with the channel partners, bringing them all together; but give us a little view past Dell Technologies World, you know, for this program, some of the roadmaps; what should we, that are watching the industry, look for throughout the rest of the year and in the channel partners? >> So, you mean what's coming forward or what? >> Stu: Just walking away from here. >> John: The road ahead! >> Stu: Your program, the road ahead, yeah. >> The road ahead, absolutely, so I'll tell you, particularly, let me focus for a minute on, on Ready Stack and where we're going there. So, as I said, we're, the idea here is maximum flexibility, but we also want to provide guidance and compatibility and sizing. So, what you'll see from us over the next year, is a lot, a lot of engineering around this program and working on building different scenarios, common scenarios and scenarios that we're learning about, you know, working with FusionStorm and our other partners, around the world. So, you'll see a lot of engineering going on around creating these design guides to deployment guides and help with sizing and we think that's really important. You'll also notice that, this is going to be hypervisor agnostic and so they'll be support for other hypervisors in this, we realize that other people do use other hypervisors besides VMware, which is kind of odd, but we know it exists, right, so a KVM we're work, they'll be, you'll see solutions that support KVM, we'll have solutions for Docker, we'll see, you'll see Hyper-V in here as well. Again, it's a realization that there's more to this do-it-yourself kind of options and we want to be there to support that, but we do think great integration, great support, sizing, is what you'll see more of as we kind of go through the year. >> Which brings us right back to flexibility, right? Give the people what they want, when they need it, right? >> Now we also say, our engineer systems, right? VxRail, our hyper conversion converge systems, we're not saying we're de emphasizing that, we're not at all, but we're realizing that, you know, more and more working with our partners there's, we're addressing a very large and growing part of the market space. >> Dan, Vince, thanks for being with us. >> Yeah. >> Thank you very much. >> We appreciate the time, enjoy the rest of the show, but I'm sure it's going well for ya. >> It's wonderful. >> And we hope to see you down the road. >> Terrific. >> Thank you for having us. >> Thank you for joining us. Back with more here on the Cube; we're live in Las Vegas at Dell Technologies World 2018. (electronic music)

>>from around the >>globe. It's the >>cube with coverage of Kublai >>Khan and Cloud Native Con Europe 2021 >>virtual brought to >>you by red hat, the cloud native computing foundation and ecosystem partners. Hello, welcome back to the cubes coverage of coupon 21 Cloud Native Con 21 Virtual, I'm John Ferrier Host of the Cube. We're here with a great gas to break down one of the hottest trends going on in the industry and certainly around cloud native as this new modern architecture is evolving so fast. Richard Hartman, director of community at Griffon, a lab's involved with Prometheus as well um, expert and fun to have on and also is going to share a lot here. Richard, thanks for coming. I appreciate it. >>Thank you >>know, we were chatting before we came on camera about the human's ability to to handle all this new shift uh and the and the future of observe ability is what everyone has been talking about. But you know, some say the reserve abilities, just network management was just different, you know, scale Okay, I can buy that, but it's got a lot more than that. It involves data involves a new architecture, new levels of scale that cloud native has brought to the table that everyone is agreeing on. It scales their new capabilities, thus setting up new architectures, new expectations and new experiences are all happening. Take us through the future of observe ability. >>Mhm. Yes, so um 11 of the things which many people find when they onboard themselves onto the cloud native space is um you can scale along different and new axis, which you couldn't scale along before, uh which is great. Of course, it enables growth, it enables different operating models, it enables you to choose different or more modern engineering trade offs, like the underlying problems are still the same, but you just slice and dice your problems and compartmentalize your services differently. But the problem is um it becomes more spread out and the more classic tooling tends to be built for those more classic um setups and architectures as your architecture becomes more malleable and as you can can choose and pick how to grow it along with which access a lot more directly and you have to um that limits the ability of the humans actually operating that system to understand what is truly going on. Um Obviously everyone is is fully fully all in on A. I. M. L. And all those things. But one of the dirty secrets is you will keep needing domain specific experts who know what they're doing and what that thing should look like, what should be working hard to be working. But enable those people to actually to actually understand the current state of the system and compare this to the desired state of the system. Is highly nontrivial in particular, once you have not machine lifetimes of month or years which he had before, which came down to two sometimes hours and when you go to Microsoft to surveillance and such sometimes even into sub seconds. So a lot of this is about enabling this, this this higher volume of data, this higher scale of data, this higher cardinality of what what you actually attach as metadata on your data and then still be able to carry all this and makes sense of it at scale and at speed because if you just toss it into a data lake and do better analysis like half a day later no one cares about it anymore. It needs to be life it needs or at least the largest part of it needs to be life. You need to be able to alert right now if something is imminently customer facing. >>Well, that's awesome. I love totally agree this new observe ability horizontally scalable, more surface area, more axes, as you point out, changes the data equation on the automation plays a big role in mention machine learning and ai great, great grounds for that. I gotta ask you just well before we move on to the next topic around this is that the most people that come from the old world with the tooling and come from that old school vendor mentality or old soup architecture, old school architecture tend to kind of throw stones at the future and say, well the economics are all wrong and the performance metrics. So I want to ask you so I assume that we believe we do believe because assume that's going to happen. What is the economic picture? What's the impact that people are missing? When you look at the benefits of what this system is going to enable the impact? Specifically whether it's economics, productivity, efficient code, what are some of the things that maybe the VCS or other people in the naysayers side? Old school will, will throw stones at what's the, what's the big upside here? >>Mhm. So this will not be true for everyone and there will still be certain situations where it makes sense to choose different sets of of trade offs, but most everyone will be moving into the cloud for for convenience and speed reasons. And I'm deliberately not saying cost reasons. Um the reason being um usually or in the past you had simply different standard service delineations and all of the proserve, the consulting your hiring pool was all aligned with this old type of service delineation, which used to be a physical machine or a service or maybe even a service and you had a hot standby or something. If we, if we got like really a hugely respect from the same things still need to operate under laying what you do. But as we grow as an industry, more of more of this is commoditized and same as we commoditize service and storage network. We commoditized actually running off that machine and with service and such go even further. Um so it's not so much about about this fundamentally changing how it's built. It's just that a larger or a previously thing which was part of your value at and of what you did in your core is now just off the shelf infrastructure which you just by as much as you need again at certain scales and for certain specific use cases, this will not be true for the foreseeable future, but most everyone um will be moving there simply because where they actually add value and the people they can hire for and who are interested in that type of problem. I just mean that it's a lot more more sensical to to choose this different delineation but it's not cheaper >>and the commoditization and disintermediation is definitely happening, totally agree. And the complexity that's gonna be abstracted away with software is novell and it's also systematic. There's just it's new and there's some systems involved, so great insight there. I totally agree with you. The disruption is happening majority of almost all areas, so in all verticals and all industries, so so great point. I think this is where I think everyone's so excited and some people are paranoid actually frankly, but we cover that in depth on the Cuban other segments. But great point. We'll get back to what you're where you're spending your time right now. Um You're spending a lot of time on open metrics. What is that enabling take us through that? >>So um the super quick history of Prometheus, of course, we need that for open metrics. Promises was actually created in 2012. Um and the wire format which he used to in the exposition format, which he used to transport metrics into Prometheus is stable since 2014. Um But there is a large problem here. Um It carries the promise his name and a lot of competing projects and a lot of competing vendors of course there are vendors which compete with just the project. Um It's simply refused to to to take anything in which carried the promise his name. Of course, this doesn't align with their food um strategy, which they ran back then. So um together with scenes, the f we decided to just have a new different name for just that wire format for the underlying data model for everything which you need to make one complete exposition or a bunch of expositions towards towards permissions. So that's it at the corn, that's been ongoing since 2000 and 15 16 something. Um But there's also changes on the one hand, there is a super careful, a super super careful um Clean up and backwards compatible cleanup of a few things which the permit this exposition former serious here for didn't get right. But also we enable two features within this and as permitted chose open metrics as its official format. We also uplift committees and varying both heads. Obviously it's easier to get the synchronization. Um Ex employers stand out which is a completely new, at least outside of certain large search companies google. Um Who who used who use ex employers to do something different with with their traces. Um it was in 2017 when they told me that for them searching for traces didn't scale by labels. Uh and at that point I wanted to have both. I wanted to have traces and logs also with the same label set as permitting system. But when they tell you searching doesn't scale like they tell you you better listen. So uh the thing is this you have your index where you store all your data or your where you have the reference to enter your database and you have these label sets and they are super efficient and and quite powerful when compared to more traditional systems but they still carry a cost and that cost becomes non trivial at scale. So instead of storing the same labels for your metrics and your logs and your traces, the idea is to just store an I. D. For your trace which is super lightweight and it's literally just one idea. So your index is super tiny. Um And then you touch this information to your logs to your metrics and in the meantime also two year to year logs. Um So you know already that trace has certain properties because historically you have this needle estate problem. You have endless amounts of traces and you need to figure out what are the useful are they are the judicial and interesting aero state highlight and see some error occurring whatever if that information is already attached to your other signals. That's a lot easier. Of course. You see you're highlighting see bucket and you see a trace ID which is for that high latency bucket. So going into that trace, I already know it is a highlight and see trace for for a service which has a high latency, it has visited that labor. It was running this in that context, blah blah blah blah blah. Same for logs. There is an error. There is an exception, maybe a security breach, what have you and I can jump directly into a trace and I have all this mental context and the most expensive part is the humans. So enabling that human to not need to break mental uh train of thought to just jump directly from all the established state which they already have here in debugging just right into the trace, went back and just see why that thing behave that way. It's super powerful and it's also a lot cheaper to store this on the back and a four year traces which in our case internally we just run at 100% something. We do not throw data way, which means you don't have the super interesting thing. And by the way the trace just doesn't exist for us a good job. And that's the one thing to to from day one this intent to to marry those three pillars more closely. The other thing is by having a true lingua franca. It gave that concept of of of promises compatibility on the wire, its own name and it's its own distinct concept. And that is something which a lot of people simply attached to. So just by having that name, allow the completely different conversation over the last half decade or so and to close >>them close it >>up and to close that point because I come from the network, from the networking space and, and basically I T f r f C s are the currency within the networking space and how you force your vendors to support something, which is why I brought open metrics into the I. D. F. To to give it an official stamp of approval in Rfc number which is currently hopefully successful. Um So all of a sudden you can slip this into your tender and just tell your vendor, ex wife said okay, you need to support this. But I've seen all of a sudden by contract they're bound to to support communities native. So >>I support that Rfc yet or no, is that still coming? >>I, so at the last uh TF meeting, which was virtual, obviously I presented everything to the L. A W G. Um there was very good feedback. Um they want to adopt it as an informational uh I. D. Reason being it is most or it is a documentation of an already widely existed standard. So it gets different bits and pieces in the heather. Um Currently I'm waiting for a few rounds of feedback on specific wording how to make it more clear and such. Um looking >>good. It's looking good. >>Oh yes while presenting it. They actually told me that I have a conference with promises and performance. Well >>that's how you get things done in the old school internet. That's the way it was talking to Vince serving all of my friends and that generation we grew up, I mean I was telling a story on the clubhouse, just random that I grew up in the era. We used to pirate software used to deal software back in the old days. Pre open source. This is how things get done. So I gotta ask you the impact question. The, the deal with open metrics potentially could disrupt all those startups. So what, how does this impact all these stars because everyone is jockeying for land grabbing the observe ability space? Is that just because it's just too many people competing for one spot or do they all have differentiation? What happens to all those observe ability startups that got minted and funded? >>So I have, I think we have to split this into two answers, the first one open metrics and also Prometheus we're trying really hard to standardize what we're doing and to make this reusable as much as we possibly can um simply because premises itself does not have any any profit motivation or anything, it is just a project run by people. Um so we gain by, by users using our stuff and working in the way, which we think is a good way to operate. So anyone who just supports all those open standards, just on boards themselves onto a huge ecosystem of already installed base. And we're talking millions and millions and millions of installations, we don't have hard numbers, but the millions and millions I am certain of and thats installations, not users, so that's several orders of magnitude more. Um, so that that actually enables an ecosystem within which to move as to the second question. It is a super hot topic. So obviously that we see money starts coming in from all right. Um, I don't think that everyone will survive, but that is just how it usually is. There is a lot of of not very differentiated offerings, be the software, be they as a service, be their distributions? Well, you don't really see much much value and not not a lot of, not a lot of much anything in ways of innovation. So this is more about about making it easier to run or or taking that pain away, which obviously makes you open to attack by by all the hyper scale. Of course, they can just do this at a higher scale than you. Um, so unless you actually really in a way in that space and actually shape and lead in that space, at least to some extent, it will probably be relatively hard. That being said. >>Yeah, when you ride, when you ride the big waves like this, I mean, you you got to be on the right side of this. Uh, Pat Gelsinger's when he was that VM Where now is that intel told me on the cube one time. If you're not, you don't get it right on these waves, your driftwood, Right? So, so, you know, and we've seen this movie before, when you start to see the standards bodies like the I E T. F. Start to look at standards. You start to think there's a broader market opportunities, a need for some standards, which is good. It enables more value, right value creation, whether it's out in the open or if it's innovative from a commercialization standpoint, you know, these are good things and then you have everyone who's jockeying around from the land grab incomes, a standard momentum, you gotta be on the right side of these things. We know what we know it's gonna look like. If you're not on the right side of the standard, then your proprietary, >>precisely. >>And so that's the endgame. Okay, well, I really appreciate the impact. Final question. Um, as the world evolved post Covid as cloud Native goes mainstream, the enterprises in the cloud scale are demanding more things. Enterprises are are, you know, they want more stuff than just straight up in the cloud startups, for instance. So you start to see, you know, faster, more agility obviously, uh, with deploying modern apps, when you start getting into enterprise grade scale, you gotta start thinking, you know, this is an engineering and computer science discipline. Coming together, you've got to look at the architecture. What's your future vision of how the next gen programmable infrastructure looks like? >>You mean, as in actually manage those services or limited to observe ability to >>observe ability, role, observe ability. Just you're in the urine. The survivability speaks to the operating system of what's going on, distributed computing you're looking at, you gotta have a good observe ability if you want to deploy services. So, you know, as it evolves and this is not a fringe thing anymore. This is real deal. This observe abilities a key linchpin in the architecture. >>So, um, maybe to approach us from two sides. One of the things which, which, I mean I come from very much non cloud native background. One of the things which tends to be overlooked in cloud native is that not everything is green field. Matter of fact, legacy is the code word for makes actual money. Um, so a lot of brownfield installations, which still make money, which we keep making money and all of those existence, they will not go away anytime soon. And as soon as you go to actually industry trying to uplift themselves to industry that foreign, all those passwords you get a lot more complexity in, in just the availability of systems than just the cloud native scheme. So being able to to actually put all of those data types together and not just have you. Okay, nice. I have my micro service events fully instrumented and if anything happens on the layer below, I'm simply unable to make any any effort on debugging um things like for example, Prometheus course they are so widely adopted enable you to literally, and I did this myself um from the Diesel Genset of your data center over the network down to down to the office. If if someone is in there, if if if your station and your pager is is uh stepped in such to the database to the extra service which is facing your end customers, all of those use the same labels that use the same metadata to actually talk about this. So all of a sudden I can really drill down into my data, not only from you. Okay. I have my microservices, my database. Big deal. No, I can actually go down as deep in my infrastructure as my infrastructure is. And this is especially important for anyone who's from the more traditional enterprise because most of them will for the foreseeable future have tons and tons and tons of those installations and the ability to just marry all this data together no matter where it's coming from. Of course you have this lingual franklin, you have these widely adopted open standards. I think that is one of the main drivers in >>jail. I think you just nailed the hybrid and surprised use case, you know, operation at scale and integrating the systems. So great job Richard, thank you so much for coming on. Richard Hartman, Director of community Griffon A labs. I'm talking, observe ability here on the cube. I'm john for your host covering cube con 21 cognitive content. One virtual. Thanks for watching. Mhm Yeah. Mhm.

>>From around the globe. It's the queue with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Welcome back to the cubes. Live coverage for ADFS reinvent 2020 I'm John Ford with the cube, your host. We are the cube virtual. We're not there in person this year. We're remote with the pandemic and we're here for the keynote analysis for Verner Vogels, and we've got some great analysts on and friends of the cube cube alumni is Rob Hirschfeld is the founder and CEO of Rakin a pioneer in the dev ops space, as well as early on on the bare metal, getting on the whole on-premise he's seen the vision and I can tell you, I've talked to him many times over the years. He's been on the same track. He's on the right wave frog. Great to have you on. I'm going to have to start Veatch, come on. Y'all come on as well, but great to see you. Thanks, pleasure to be here. Um, so the keynote with Verna was, you know, he's like takes you on a journey, you know, and, and virtual is actually a little bit different vibe, but I thought he did an exceptional job of stage layout and some of the virtual stage craft. Um, but what I really enjoyed the most was really this next level, thinking around systems thinking, right, which is my favorite topic, because, you know, we've been saying, going back 10 years, the cloud is just, here's a computer, right. It's operating system. And so, um, this is the big thing. This is, what's your reaction to the keynote. >>Wow. So I think you're right. This is one of the challenges with what Amazon has been building is it's, you know, it is a lock box, it's a service. So you don't, you don't get to see behind the scenes. You don't really get to know how they run these services. And what, what I see happening out of all of those pieces is they've really come back and said, we need to help people operate this platform. And, and that shouldn't be surprising to anyone. Right? Last couple of years, they've been rolling out service, service service, all these new things. This talk was really different for Verner's con normal ones, because he wasn't talking about whizzbang new technologies. Um, he was really talking about operations, um, you know, died in the wool. How do we make the system easier to use? How do we expose things? What assistance can we have in, in building applications? Uh, in some cases it felt like, uh, an application performance monitoring or management APM talk from five or even 10 years ago, um, canaries, um, you know, Canary deployments, chaos engineering, observability, uh, sort of bread and butter, operational things. >>We have Savi Joel, who's a influencer cloud computing Xtrordinair dev ops guru. Uh, we don't need dev ops guru from Amazon. We got Sarpy and prop here. So it'd be great to see you. Um, you guys had a watch party. Um, tell me what the reaction was, um, with, of the influencers in the cloud or ADI out there that were looking at Vernon's announcement, because it does attract a tech crowd. What was your take and what was the conversation like? >>Yeah, we kinda geeked out. Um, we had a watch party and we were commenting back and forth, like when we were watching it. I think that the general consensus is that the complexity of AWS stack itself is, is increasing. Right. And they have been focused on developers a lot, I think a lot longer than they needed to be a little bit. I think, uh, now they need to focus on the operations. Like we, we are, we all love dev ops talks and it's very fancy and it's very modern way of building software. But if you think deep down that, like once we developed software traditionally and, and also going forward, I think we need to have that separation. Once you develop something in production, it's, it's, it's operating right. Once you build a car, you're operating car, you're not building car all the time. Right? >>So same with the software. Once you build a system, it should have some stability where you're running it, operating it for, for a while, at least before you touch it or refactoring all that stuff. So I think like building and operating at the same time, it's very good for companies like Amazon, AWS, especially, uh, and, and Google and, and, and Facebook and all those folks who are building technology because they are purely high-tech companies, but not for GM Ford Chrysler or Kaiser Permanente, which is healthcare or a school district. The, they, they need, need to operate that stuff once it's built. So I think, uh, the operationalization of cloud, uh, well, I think take focus going forward a lot more than it has and absorbable Deanna, on a funny note, I said, observability is one of those things. I, now these days, like, like, you know, and the beauty pageants that every contestant say is like, whatever question you asked, is it Dora and the answer and say at the end world peace, right? >>And that's a world peace term, which is the absorbability. Like you can talk about all the tech stuff and all that stuff. And at the end you say observability and you'll be fine. So, um, what I'm making is like observability is, and was very important. And when I was talking today about like how we can enable the building of absorbability into this new paradigm, which is a microservices, like where you pass a service ID, uh, all across all the functions from beginning to the end. Right. And so, so you can trace stuff. So I think he was talking, uh, at that level. Yeah. >>Let me, let's take an observer Billy real quick. I have a couple of other points. I want to get your opinions on. He said, quote, this three, enabling major enabling technologies, powering observability metrics, logging and tracing here. We know that it would, that is of course, but he didn't take a position. If you look at all the startups out there that are sitting there, the next observability, there's at least six that I know of. I mean, that are saying, and then you got ones that are kind of come in. I think signal effects was one. I liked, like I got bought by Splunk and then is observability, um, a feature, um, or is it a company? I mean, this is something that kind of gets talked about, right? I mean, it's, I mean, is it really something you can build a business on or is it a white space? That's a feature that gets pulled in what'd you guys react to that? >>So this is a platform conversation and, and, you know, one of the things that we've been having conversations around recently is this idea of platforms. And, and, you know, I've been doing a lot of work on infrastructure as code and distributed infrastructure and how people want infrastructure to be more code, like, which is very much what, what Verna was, was saying, right? How do we bring development process capabilities into our infrastructure operations? Um, and these are platform challenges. W what you're asking about from, uh, observability is perspective is if I'm running my code in a platform, if I'm running my infrastructure as a platform, I actually need to understand what that platform is doing and how it's making actions. Um, but today we haven't really built the platforms to be very transparent to the users. And observability becomes this necessary component to fix all the platforms that we have, whether they're Kubernetes or AWS, or, you know, even going back to VMware or bare metal, if you can't see what's going on, then you're operating in the blind. And that is an increasingly big problem. As we get more and more sophisticated infrastructure, right? Amazon's outage was based on systems can being very connected together, and we keep connecting systems together. And so we have to be able to diagnose and troubleshoot when those connections break or for using containers or Lambdas. The code that's running is ephemeral. It's only around for short periods of time. And if something's going wrong in it, it's incredibly hard to fix it, >>You know? And, and also he, you know, he reiterated his whole notion of log everything, right? He kept on banging on the drum on that one, like log everything, which is actually a good practice. You got to log everything. Why wouldn't you, >>I mean, how you do, but they don't make it easy. Right? Amazon has not made it easy to cross, cross, and, uh, connect all the data across all of those platforms. Right? People think of Amazon as one thing, but you know, the people who are using it understand it's actually a collection of services. And some of those are not particularly that tied together. So figuring out something that's going on across, across all of your service bundles, and this isn't an Amazon problem, this is an industry challenge. Especially as we go towards microservices, I have to be able to figure out what happened, even if I used 10 services, >>Horizontal, scalability argument. Sorry. Do you want to get your thoughts on this? So the observability, uh, he also mentioned theory kind of couched it before he went into the talk about systems theory. I'm like, okay. Let's, I mean, I love systems, and I think that's going to be the big wake up call here for the next 10 years. That's a systems mindset. And I think, you know, um, Rob's right. It's a platform conversation. When you're thinking about an operating system or a system, it has consequences when things change, but he talked about controllability versus, uh, observability and kinda T that teed up the, well, you can control systems controls, or you can have observability, uh, what's he getting at in all of this? What's he trying to say, keep, you know, is it a cover story? Is it this, is it a feature? What was the, what was the burner getting at with all this? >>Uh, I, I, I believe they, they understand that, that, uh, that all these services are very sort of micro in nature from Amazon itself. Right. And then they are not tied together as Rob said earlier. And they, he addressed that. He, uh, he, uh, announced that service. I don't know the name of that right now of problem ahead that we will gather all the data from all the different places. And then you can take a look at all the data coming from different services at this at one place where you have the service ID passed on to all the servers services. You have to do that. It's a discipline as a software developer, you have to sort of adhere to even in traditional world, like, like, you know, like how you do logging and monitoring and tracing, um, it's, it's your creativity at play, right? >>So that's what software is like, if you can pass on, I was treating what they gave an example of Citrix, uh, when, when, when you are using like tons of applications with George stream to your desktop, through Citrix, they had app ID concept, right? So you can trace what you're using and all that stuff, and you can trace the usage and all that stuff, and they can, they can map that log to that application, to that user. So you need that. So I think he w he was talking about, I think that's what he's getting too. Like we have to, we have to sort of rethink how we write software in this new Microsoft, uh, sort of a paradigm, which I believe it, it's a beautiful thing. Uh, as long as we can manage it, because Microsoft is, are spread across like, um, small and a smaller piece of software is everywhere, right? So the state, how do we keep the state intact? How do we, um, sort of trace things? Uh, it becomes a huge problem if we don't do it right? So it it's, um, it's a little, this is some learning curve for most of the developers out there. So 60 dash 70% >>Rob was bringing this up, get into this whole crash. And what is it kind of breakdown? Because, you know, there's a point where you don't have the Nirvana of true horizontal scalability, where you might have microservices that need to traverse boundaries or systems, boundaries, where, or silos. So to Rob's point earlier, if you don't see it, you can't measure it or you can't get through it. How do you wire services across boundaries? Is that containers, is that, I mean, how does this all work? How do you guys see that working? I just see a train wreck there. >>It's, it's a really hard problem. And I don't think we should underestimate it because everything we toast talked about sounds great. If you're in a single AWS region, we're talking about distributed infrastructure, right? If you think about what we've been seeing, even more generally about, you know, edge sites, uh, colo on prem, you know, in cloud multi-region cloud, all these things are actually taking this one concept and you're like, Oh, I just want to store all the log data. Now, you're not going to store all your log data in one central location anymore. That in itself, as a distributed infrastructure problem, where I have to be able to troubleshoot what's going on, you know, and know that the logs are going to the right place and capture the data, that's really important. Um, and one of the innovations in this that I think is going to impact the industry over the next couple of years is the addition of more artificial intelligence and machine learning, into understanding operations patterns and practices. >>And I think that that's a really significant industry trend where Amazon has a distinct advantage because it's their systems and it's captive. They can analyze and collect a lot of data across very many customers and learn from those things and program systems that learn from those things. Um, and so the way you're going to keep up with this is not by logging more and more data, but by doing exactly what we're talking through, which was how do I analyze the patterns with machine learning so that I can get predictive analysis so that I can understand something that looks wrong and then put people on checking it before it goes wrong. >>All right, I gotta, I gotta bring up something controversial. I can't hold back any longer. Um, you know, Mark Zuckerberg said many, many years ago, all the old people, they can do startups, they're too old and you gotta be young and hungry. You gotta do that stuff. If we're talking systems theory, uh, automated meta reasoning, evolvable systems, resilience, distributed computing, isn't that us old guys that have actually have systems experience. I mean, if you're under the age of 30, you probably don't even know what a system is. Um, and, or co coded to the level of systems that we use to code. And I'm putting my quote old man kind of theory, only kidding, by the way on the 30. But my point is there is a generation of us that had done computer science in the, in the eighties and seventies, late seventies, maybe eighties and nineties, it's all it was, was systems. It was a systems world. Now, when you have a software world, the aperture is increasing in terms of software, are the younger generation of developers system thinkers, or have we lost that art, uh, or is it doesn't matter? What do you guys think? >>I, I think systems thinking comes with age. I mean, that's, that's sort of how I think, I mean, like I take the systems thinking a greater sort of, >>Um, world, like state as a system country, as a system and everything is a system, your body's a system family system, so it's the same way. And then what impacts the system when you operated internal things, which happened within the system and external, right. And we usually don't talk about the economics and geopolitics. There's a lot of the technology. Sometimes we do, like we have, I think we need to talk more about that, the data sovereignty and all that stuff. But, but even within the system, I think the younger people appreciate it less because they don't have the, they don't see, um, software taught like that in the universities. And, and, and, and by these micro micro universities now online trainings and stuff like sweaty, like, okay, you learn this thing and you're good at it saying, no, no, it's not like that. So you've got to understand the basics and how the systems operate. >>Uh, I'll give you an example. So like we were doing the, the, the client server in early nineties, and then gradually we moved more towards like having ESB enterprise services, bus where you pass a state, uh, from one object to another, and we can bring in the heterogeneous, uh, languages. This thing is written in Java. This is in.net. This is in Python. And then you can pass it through that. Uh, you're gonna make a state for, right. And that, that was contained environment. Like ESBs were contained environment. We were, I, I wrote software for ESPs myself at commerce one. And so like, we, what we need today is the ESP equallant in the cloud. We don't have that. >>Rob, is there a reverse ageism developers? I mean, if you're young, you might not have systems. What do you think? I, I don't agree with that. I actually think that the nature of the systems that we're programming forces people into more distributed infrastructure thinking the platforms we have today are much better than they were, you know, 20 years ago, 30 years ago, um, in the sense that I can do distributed infrastructure programming without thinking about it very much anymore, but you know, people know, they know how to use cloud. They know how to use a big platform. They know how to break things into microservices. I, I think that these are inherent skills that people need to think about that you're you're right. There is a challenge in that, you know, you get very used to the platform doing the work for you, and that you need to break through it, but that's an experiential thing, right? >>The more experienced developers are going to have to understand what the platforms do. Just like, you know, we used to have to understand how registers worked inside of a CPU, something I haven't worried about for a long, long time. So I, I don't think it's that big of a problem. Um, from, from that perspective, I do think that the thing that's really hard is collaboration. And so, you know, it's, it's hard people to people it's hard inside of a platform. It's hard when you're an Amazon size and you've been rolling out services all over the place and now have to figure out how to fit them all together. Um, and that to me is, is a design problem. And it's more about being patient and letting things, uh, mature. If anything might take away from this keynote is, you know, everybody asked Amazon to take a breath and work on usability and, and cross cross services synchronizations rather than, than adding more services into the mix. And that's, >>That's a good point. I mean, again, I bring up the conversation because it's kind of the elephant in the room and I make it being controversial to make a point there. So our view, because, you know, I interviewed Judy Estrin who helped found the internet with Vince Cerf. She's well-known for her contributions for the TCP IP protocol. Andy Besta Stein. Who's the, who's the Rembrandt of motherboards. But as Pat Gelsinger, CEO of VMware, I would say both said to me on the cube that without systems thinking, you don't understand consequences of when things change. And we start thinking about this microservices conversation, you start to hear a little bit of that pattern emerging, where those systems, uh, designs matter. And then you have, on the other hand, you have this modern application framework where serverless takes over. So, you know, Rob back to your infrastructure as code, it really isn't an either, or they're not mutually exclusive. You're going to have a set of nerds and geeks engineering systems to make them better and easier and scalable. And then you're going to have application developers that need to just make it work. So you start to see the formation of kind of the, I won't say swim lanes, but I mean, what do you guys think about that? Because you know, Judy and, um, Andy better sign up. They're kind of right. Uh, >>Th th the enemy here, and we're seeing this over and over again is complexity. And, and the challenge has been, and serverless is like, those people like, Oh, I don't have to worry about servers anymore because I'm dealing with serverless, which is not true. What you're doing is you're not worrying about infrastructure as much, but you, the complexity, especially in a serverless infrastructure where you're pulling, you know, events from all sorts of things, and you have one, one action, one piece of code, you know, triggering a whole bunch of other pieces of code in a decoupled way. We are, we are bringing so much complexity into these systems, um, that they're very hard to conceive of. Um, and AIML is not gonna not gonna address that. Um, I think one of the things that was wonderful about the setting, uh, in the sugar factory and at all of that, you know, sort of very mechanical viewpoint, you know, when you're actually connecting all things together, you can see it. A lot of what we've been building today is almost impossible to observe. And so the complexity price that we're paying in infrastructure is going up exponentially and we can't sustain infrastructures like that. We have to start leveling that in, right? >>Your point on the keynote, by the way, great call out on, on the, on the setting. I thought that was very clever. So what do you think about this? Because as enterprises go through this transformation, one of the big conversations is the solution architecture, the architecture of, um, how you lay all this out. It's complexity involved. Now you've got on premise system, you've got cloud, you've got edge, which you're hearing more and more local processing, disconnected systems, managing it at the edge with visualization. We're going to hear more about that, uh, with Dirk, when he comes on the queue, but you know, just in general as a practitioner out there, what, what's, what's your, what do you see people getting their arms around, around this, this keynote? What do they, what's your thoughts? >>Yeah, I, I think, uh, the, the pattern I see emerging is like, or in the whole industry, regardless, like if you put, when does your sign is that like, we will write less and less software in-house I believe that SAS will emerge. Uh, and it has to, I mean, that is the solution to kill the complexity. I believe, like we always talk about software all the time and we, we try to put this in the one band, like it's, everybody's dining, same kind of software, and they have, I'm going to complexity and they have the end years and all that stuff. That's not true. Right. If you are Facebook, you're writing totally different kind of software that needs to scale differently. You needs a lot of cash and all that stuff, right. Gash like this and cash. Well, I ain't both gases, but when you are a mid size enterprise out there in the middle, like fly over America, what, uh, my friend Wayne says, like, we need to think about those people too. >>Like, how do they drive software? What kind of software do they write? Like how many components they have in there? Like they have three tiers of four tiers. So I think they're a little more simpler software for internal use. We have to distinguish these applications. I always talk about this, like the systems of record systems of differentiation, the system of innovation. And I think cloud will do great. And the newer breed of applications, because you're doing a lot of, a lot of experimentation. You're doing a lot of DevOps. You have two pizza teams and all that stuff, which is good stuff we talk about, well, when you go to systems of record, you need stability. You need, you need some things which is operational. You don't want to touch it again, once it's in production. Right? And so the, in between that, that thing is, I think that's, that's where the complexity lies the systems are, which are in between those systems of record and system or innovation, which are very new Greenfield. That, that's what I think that's where we need to focus, uh, our, um, platform development, um, platform as a service development sort of, uh, dollars, if you will, as an industry, I think Amazon is doing that right. And, and Azura is doing that right to a certain extent too. I, I, I, I worry a little bit about, uh, uh, Google because they're more tilted towards the data science, uh, sort of side of things right now. >>Well, Microsoft has the most visibility into kind of the legacy world, but Rob, you're shaking your head there. Um, on his comment, >>You know, I, I, you know, I, I watched the complexity of all these systems and, and, you know, I'm not sure that sass suffocation of everything that we're doing is leading to less is pushing the complexity behind a curtain so that you, you, you can ignore the man behind the curtain. Um, but at the end of the day, you know what we're really driving towards. And I think Amazon is accelerating this. The cloud is accelerating. This is a new set of standard operating processes and procedures based on automation, based on API APIs, based on platforms, uh, that ultimately, I think people could own and could come back to how we want to operate it. When I look at what we w we were just shown with the keynote, you know, it was an, is things that application performance management and monitoring do. It's, it's not really Amazon specific stuff. There's no magic beans that Amazon is growing operational knowledge, you know, in Amazon, greenhouses that only they know how to consume. This is actually pretty block and tackle stuff. Yeah. And most people don't need to operate it at that type of scale to be successful. >>It's a great point. I mean, let's, let's pick up on that for the last couple of minutes we have left. Cause I think that's a great, great double-down because you're thinking about the mantra, Hey, everything is a service, you know, that's great for business model. You know, you hand it over to the techies. They go, wait a minute. What does that actually mean? It's harder. But when I talk to people out there and you hear people talking about everything is a service or sanctification, I do agree. I think you're putting complexity behind the curtain, but it's kind of the depends answer. So if you're going to have everything as a service, the common thesis is it has to have support automation everywhere. You got to automate things to make things sassiphy specified, which means you need five nines, like factory type environments. They're not true factories, but Rob, to your point, if you're going to make something a SAS, it better be Bulletproof. Because if you're, if you're automating something, it better be automated, right? You can measure things all you want, but if it's not automated, like a, like a, >>And you have no idea what's going on behind the curtains with some of these, these things, right. Especially, you know, I know our business and you know, our customers' businesses, they're, they're reliant on more and more services and you have no idea, you know, the persistence that service, if they're going to break an API, if they're going to change things, a lot of the stuff that Amazon is adding here defensively is because they're constantly changing the wheels on the bus. Um, and that is not bad operational practice. You should be resilient to that. You should have processes that are able to be constantly updated and CICB pipelines and, you know, continuous deployments, you shouldn't expect to, to, you know, fossilize your it environment in Amber, and then hope it doesn't have to change for 10 years. But at the same time, we'll work control your house. >>That's angle about better dev ops hypothetical, like a factory, almost metaphor. Do you care if the cars are being shipped down the assembly line and the output works and the output, if you have self-healing and you have these kinds of mechanisms, you know, you could have do care. The services are being terminated and stood up and reformed as long as the factory works. Right? So again, it's a complexity level of how much it, or you want to bite off and chew or make work. So to me, if it's automated, it's simple, did it work or not? And then the cost of work to be, what's your, what's your angle on this? Yeah. >>I believe if you believe in systems thinking, right. You have to believe in, um, um, the concept of, um, um, Oh gosh, I'm losing over minor. Um, abstraction. Right? So abstraction is your friend in software. Abstraction is your friend anyways, right? That's how we, humans pieces actually make a lot more progress than any other sort of living things here in this world. So that's why we are smart. We can abstract complexity behind the curtains, right? We, we can, we can keep improving, like from the, the, you know, wooden cart to the car, to the, to the plane, to the other, like, we, we, we have this, like when, when we see we are flying these airplanes, like 90% of the time they're on autopilot, like that's >>Hi, hiding my attractions is, is about evolution. Evolvable software term. He said, it's true. All right, guys, we have one minute left. Um, let's close this out real quick. Each of you give a closing statement on what you thought of the keynote and Verner's talk prop, we'll start with you. >>Uh, you know, as always, it's a perf keynote, uh, very different this year because it was so operationally focused and using the platform and, and helping people run their, their, off their applications and software better. And I think it's an interesting turn that we've been waiting for for Amazon, uh, to look at, you know, helping people use their own platform more. Um, so, uh, refreshing change and I think really powerful and well delivered. I really did like the setting >>Great shopping. And when we found, I found out today, that's Teresa Carlson is now running training and certification. So I'm expecting that to be highly awesomely accelerated a success there. Sorry, what's your take real quick on burners talk, walk away. Keynote thoughts. >>I, I, I think it was what I expected it to be like, he focused on the more like a software architecture kind of discussion. And he focused this time a little more on the ops side and the dev side, which I think they, they are pivoting a little bit, um, because they, they want to sell more AWS stuff to us, uh, to the existing enterprises. So I think, um, that was, um, good. Uh, I wish at the end, he said, not only like, go, go build, but also go build and operate. So can, you know, they all say, go build, build, build, but like, who's going to operate this stuff. Right. So I think, um, uh, I will see a little shift, I think, going forward, but we were talking earlier, uh, during or watch party that I think, uh, going forward, uh, AWS will open start open sourcing the commoditized version of their cloud, which have been commoditized by other vendors and gradually they will open source it so they can keep the hold onto the enterprises. I think that's what my take is. That's my prediction is >>Awesome and want, I'll make sure I'm at your watch party next time. Sorry. I missed it. Nobody's taking notes. Try and prepare. Sorry, Rob. Thanks for coming on and sharing awesome insight and expertise to experts in cloud and dev ops. I know them. And can firstly vouch for their awesomeness? Thanks for coming on. I think Verner can verify what I thought already was reporting Amazon everywhere. And if you connect the dots, this idea of reasoning, are we going to have smarter cloud? That's the next conversation? I'm John for your host of the cube here, trying to get smarter with Aus coverage. Thanks to Robin. Sarvi becoming on. Thanks for watching.

>>on the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Hello and welcome back to the Cubes Live coverage Cube live here in Palo Alto, California, with the Virtual Cube this year because we can't be there in person. I'm your host, John Fairy year. We're kicking off Day two of the three weeks of reinvent a lot of great leadership sessions to review, obviously still buzzing from the Andy Jassy three. Our keynote, which had so many storylines, is really hard to impact. We're gonna dig that into into into that today with Jerry Chan, who has been a Cube alumni since the beginning of our AWS coverage. Going back to 2013, Jerry was wandering the hallways as a um, in between. You were in between vm ware and V C. And then we saw you there. You've been on the Cube every year at reinvent with us. So special commentary from you. Thanks for coming on. >>Hey, John, Thanks for having me and a belated happy birthday as well. If everyone out there John's birthday was yesterday. So and hardest. Howard's working man in technology he spent his entire birthday doing live coverage of Amazon re events. Happy birthday, buddy. >>Well, I love my work. I love doing this. And reinvent is the biggest event of the year because it really is. It's become a bellwether and eso super excited to have you on. We've had great conversations by looking back at our conversations over the Thanksgiving weekend. Jerry, the stuff we were talking about it was very proposed that Jassy is leaning in with this whole messaging around change and horizontal scalability. He didn't really say that, but he was saying you could disrupt in these industries and still use machine learning. This was some of the early conversations we were having on the Cube. Now fast forward, more mainstream than ever before. So big, big part of the theme there. >>Yeah, it z you Amazon reinvent Amazon evolution to your point, right, because it's both reinventing what countries are using with the cloud. But also what Amazon's done is is they're evolving year after year with their services. So they start a simple infrastructure, you know, s three and e c. Two. And now they're building basically a lot of what Andy said you actually deconstructed crm? Ah, lot of stuff they're doing around the call centers, almost going after Salesforce with kind of a deconstructed CRM services, which is super interesting. But the day you know, Amazon announces all those technologies, not to mention the AI stuff, the seminar stuff you have slack and inquired by Salesforce for $27.7 billion. So ah, lot of stuff going on in the cloud world these days, and it's funny part of it, >>you know, it really is interesting. You look up the slack acquisition by, um, by Salesforce. It's interesting, you know, That kind of takes slack out of the play here. I mean, they were doing really well again. Message board service turns into, um, or collaboration software. They hit the mainstream. They have great revenue. Is that going to really change the landscape of the industry for Salesforce? They've got to acquire it. It opens the door up from, or innovation. And it's funny you mention the contact Center because I was pressing Jassy on my exclusive one on one with him. Like they said, Andy, my my daughter and my sons, they don't use the phone. They're not gonna call. What's this? Is it a call center deal? And he goes, No, it's the It's about the contact. So think about that notion of the contact. It's not about the call center. It's the point of contact. Okay, Linked in is with Microsoft. You got slack and Salesforce Contact driven collaboration. Interesting kind of play for Microsoft to use voice and their data. What's your take on that? >>I think it's, um you know, I have this framework. As you know, I talked my friend systems of engagement over systems intelligence and systems record. Right? And so you could argue voice email slack because we're all different systems of engagement, and they sit on top of system of record like CRM customer support ticketing HR. Something like that. Now what sells first did by buying slack is they now own a system engagement, right? Not on Lee is slack. A system engagement for CRM, but also system engagement for E. R. P Service. Now is how you interact with a bunch of applications. And so if you think about sales for strategy in the space, compete against Marcus Soft or serves now or other large AARP's now they own slack of system engagement, that super powerful way to actually compete against rival SAS companies. Because if you own the layer engagement layer, you can now just intermediate what's in the background. Likewise, the context center its own voice. Email, chat messaging, right? You can just inter mediate this stuff in the back, and so they're trying to own the system engagement. And then, likewise, Facebook just bought that company customer a week ago for a billion dollars, which also Omni Channel support because it is chat messaging voice. It's again the system engagement between End User, which could be a customer or could be employees. >>You know, this really gonna make Cit's enterprise has been so much fun over the past 10 years, I gotta say, in the past five, you know, it's been even more fun, has become or the new fun area, you know, And the impact to enterprise has been interesting because and we're talking about just engaging system of record. This is now the new challenge for the enterprise. So I wanna get your thoughts, Jerry, because how you see the Sea, X O's and CSOs and the architects out there trying to reinvent the enterprise. Jassy saying Look and find the truth. Be on the right side of history here. Certainly he's got himself service interest there, but there is a true band eight with Cove it and with digital acceleration for the enterprise to change. Um, given all these new opportunities Thio, revolutionize or disrupt or radically improve, what's the C. C X's do? What's your take on? How do you see that? >>It's increasingly messy for the CXS, and I don't I don't envy them, right? Because back in the day they kind of controlled all the I t spend and kind of they had a standard of what technologies they use in the company. And then along came Amazon in cloud all of sudden, like your developers and Dio Hey, let me swipe my credit card and I'm gonna access to a bunch of a P I s around computing stories. Likewise. Now they could swipe the credit card and you strike for billing, right? There's a whole bunch of services now, so it becomes incumbent upon CSOs. They need Thio new set of management tools, right? So not only just like, um, security tools they need, they need also observe ability, tools, understanding what services are being used by the customers, when and how. And I would say the following John like CSOs is both a challenge for them. But I think if I was a C X, so I'll be pretty excited because now I have a bunch of other weapons and other bunch of services I could offer. My end users, my developers, my employees, my customers and, you know it's exciting for them is not only could they do different things, but they also changed how their business being done. And so I think both interact with their end users. Be a chat like slack or be a phone like a contact center or instagram for your for your for your kids. It's actually a new challenge if I were sick. So it's it's time to build again, you know, I think Cove it has said it is time to build again. You can build >>to kind of take that phrase from the movie Shawshank Redemption. Get busy building or get busy dying. Kinda rephrase it there. And that's kind of the theme I'm seeing here because covert kind of forced people saying, Look, this things like work at home. Who would have thought 100% people would be working at home? Who would have thought that now the workloads gonna change differently? So it's an opportunity to deconstruct or distant intermediate these services. And I think, you know, in all the trends that I've seen over my career, it's been those inflection points where breaking the monolith or breaking the proprietary piece of it has always been an opportunity for for entrepreneur. So you know, and and for companies, whether you're CEO or startup by decomposing and you can come in and create value E I think to me, snowflake going public on the back of Amazon. Basically, this is interesting. I mean, so you don't have to be. You could kill one feature and nail it and go big. >>I think we talked to the past like it's Amazon or Google or Microsoft Gonna win. Everything is winner take all winner take most, and you could argue that it's hard to find oxygen as a start up in a broad platform play. But we think Snowflake and other companies have done and comes like mongo DB, for example, elastic have shown that if you can pick a service or a problem space and either developed like I p. That's super deep or own developer audience. You can actually fight the big guys. The Big Three cloud vendors be Amazon, Google or or market soft in different markets. And I think if you're a startup founder, you should not be afraid of competing with the big cloud vendors because there there are success patterns and how you can win and you know and create a lot of value. So I have found Investor. I'm super excited by that because, you know, I don't think you're gonna find a company takedown Amazon completely because they're just the scale and the network effects is too large. But you can create a lot of value and build Valuable comes like snowflake in and around the Amazon. Google Microsoft Ecosystem. >>Yeah, I want to get your thoughts. You have one portfolio we've covered rock rock set, which does a lot of sequel. Um, one of your investments. Interesting part of the Kino yesterday was Andy Jassy kind of going after Microsoft saying Windows sequel server um, they're targeting that with this new, uh, tool, but, you know, sucks in the database of it is called the Babel Fish for Aurora for post Chris sequel. Um, well, how was your take on that? I mean, obviously Microsoft big. Their enterprise sales tactics are looking like more like Oracle, which he was kind of hinting at and commenting on. But sequel is Lingua Franca for data >>correct. I think we went to, like, kind of a no sequel phase, which was kind of a trendy thing for a while and that no sequel still around, not only sequel like mongo DB Document TV. Kind of that interface still holds true, but your point. The world speaks sequel. All your applications be sequel, right? So if you want backwards, compatibility to your applications speaks equal. If you want your tire installed base of employees that no sequel, we gotta speak sequel. So, Rock said, when the first public conversations about what they're building was on on the key with you and Me and vent hat, the founder. And what Rock said is doing their building real time. Snowflake Thio, Lack of better term. It's a real time sequel database in the cloud that's super elastic, just like Snowflake is. But unlike snowflake, which is a data warehouse mostly for dashboards and analytics. Rock set is like millisecond queries for real time applications, and so think of them is the evolution of where cloud databases air going is not only elastic like snowflake in the cloud like Snowflake. We're talking 10 15 millisecond queries versus one or two second queries, and I think what any Jassy did and Amazon with bowel officials say, Hey, Sequels, Legal frank of the cloud. There's a large installed base of sequel server developers out there and applications, and we're gonna use Babel fish to kind of move those applications from on premise the cloud or from old workload to the new workloads. And, I think, the name of the game. For for cloud vendors across the board, big and small startups thio Google markets, often Amazon is how do you reduce friction like, How do you reduce friction to try a new service to get your data in the cloud to move your data from one place to the next? And so you know, Amazon is trying to reduce friction by using Babel fish, and I think it is a great move by them. >>Yeah, by the way. Not only is it for Aurora Post Chris equal, they're also open sourcing it. So that's gonna be something that is gonna be interesting to play out. Because once they open source it essentially, that's an escape valve for locking. I mean, if you're a Microsoft customer, I mean, it ultimately is. Could be that Gateway drug. It's like it is ultimately like, Hey, if you don't like the licensing, come here. Now there's gonna be some questions on the translations. Um, Vince, um, scuttlebutt about that. But we'll see it's open source. We'll see what goes on. Um great stuff on on rocks that great. Great. Start up next. Next, uh, talk track I wanna get with you is You know, over the years, you know, we've talked about your history. We're gonna vm Where, uh, now being a venture capitalist. Successful, wanted Greylock. You've seen the waves, and I would call it the two ways pre cloud Early days of cloud. And now, with co vid, we're kind of in the, you know, not just born in the cloud Total cloud scale cloud operations. This is kind of what jazz he was going after. E think I tweeted Cloud is eating the world and on premise and the edges. What it's hungry for. It kind of goof on mark injuries since quote a software eating the world. This is where it's going. So it's a whole another chapter coming. You saw the pre cloud you saw Cloud. Now we've got basically global I t everything else >>It's cloud only I would say, You know, we saw pre cloud right the VM ware days and before that he called like, you know, data centers. I would say Amazon lawns of what, 6 4007, the Web services. So the past 14 15 years have been what I've been calling cloud transition, right? And so you had cos technologies that were either doing on migration from on premise and cloud or hybrid on premise off premise. And now you're seeing a generation of technologies and companies. Their cloud only John to your point. And so you could argue that this 15 year transitions were like, you know, Thio use a bad metaphor like amphibians. You're half in the water, half on land, you know, And like, you know, you're not You're not purely cloud. You're not purely on premise, but you can do both ways, and that's great. That's great, because that's a that's a dominant architecture today. But come just like rock set and snowflake, your cloud only right? They're born in the cloud, they're built on the cloud And now we're seeing a generation Startups and technology companies that are cloud only. And so, you know, unlike you have this transitionary evolution of like amphibians, land and sea. Now we have ah, no mammals, whatever that are Onley in the cloud Onley on land. And because of that, you can take advantage of a whole different set of constraints that are their cloud. Only that could build different services that you can't have going backwards. And so I think for 2021 forward, we're going to see a bunch of companies or cloud only, and they're gonna look very, very different than the previous set of companies the past 15 years. And as an investor, as you covering as analysts, is gonna be super interesting to see the difference. And if anything, the cloud only companies will accelerate the move of I t spending the move of mawr developers to the cloud because the cloud only technologies are gonna be so much more compelling than than the amphibians, if you will. >>Yeah, insisting to see your point. And you saw the news announcement had a ton of news, a ton of stage making right calls, kind of the democratization layer. We'll look at some of the insights that Amazon's getting just as the monster that they are in terms of size. The scope of what? Their observation spaces. They're seeing all these workloads. They have the Dev Ops guru. They launched that Dev Ops Guru thing I found interesting. They got data acquisition, right? So when you think about these new the new data paradigm with cloud on Lee, it opens up new things. Um, new patterns. Um, S o. I think I think to me. I think that's to me. I see where this notion of agility moves to a whole nother level, where it's it's not just moving fast, it's new capabilities. So how do you How do you see that happening? Because this is where I think the new generation is gonna come in and be like servers. Lambs. I like you guys actually provisioned E c. Two instances before I was servers on data centers. Now you got ec2. What? Lambda. So you're starting to see smaller compute? Um, new learnings, All these historical data insights feeding into the development process and to the application. >>I think it's interesting. So I think if you really want to take the next evolution, how do you make the cloud programmable for everybody? Right. And I think you mentioned stage maker machine learning data scientists, the sage maker user. The data scientists, for example, does not on provisioned containers and, you know, kodama files and understand communities, right? Like just like the developed today. Don't wanna rack servers like Oh, my God, Jerry, you had Iraq servers and data center and install VM ware. The generation beyond us doesn't want to think about the underlying infrastructure. You wanna think about it? How do you just program my app and program? The cloud writ large. And so I think where you can see going forward is two things. One people who call themselves developers. That definition has expanded the past 10, 15 years. It's on Lee growing, so everyone is gonna be developed right now from your white collar knowledge worker to your hard core infrastructure developer. But the populist developers expanding especially around machine learning and kind of the sage maker audience, for sure. And then what's gonna happen is, ah, law. This audience doesn't want to care about the stuff you just mentioned, John in terms of the online plumbing. So what Amazon Google on Azure will do is make that stuff easy, right? Or a starved could make it easy. And I think that the move towards land and services that moved specifically that don't think about the underlying plumbing. We're gonna make it easy for you. Just program your app and then either a startup, well, abstract away, all the all the underlying, um, infrastructure bits or the big three cloud vendors to say, you know, all this stuff would do in a serverless fashion. So I think serverless as, ah paradigm and have, quite frankly, a battlefront for the Big Three clouds and for startups is probably one in the front lines of the next generation. Whoever owns this kind of program will cloud model programming the Internet program. The cloud will be maybe the next platform the next 10 or 15 years. I still have two up for grabs. >>Yeah, I think that is so insightful. I think that's worth calling out. I think that's gonna be a multi year, um, effort. I mean, look at just how containers now, with ks anywhere and you've got the container Service of control plane built in, you got, you know, real time analytics coming in from rock set. And Amazon. You have pinned Pandora Panorama appliance that does machine learning and computer vision with sensors. I mean, this is just a whole new level of purpose built stuff software powered software operated. So you have this notion of Dev ops going to hand in the glove software and operations? Kind of. How do you operate this stuff? So I think the whole new next question was Okay, this is all great. But Amazon's always had this problem. It's just so hard. Like there's so much good stuff. Like, who do you hired operate it? It is not yet programmable. This has been a big problem for them. Your thoughts on that, >>um e think that the data illusion around Dev ops etcetera is the solution. So also that you're gonna have information from Amazon from startups. They're gonna automate a bunch of the operations. And so, you know, I'm involved to come to Kronos Fear that we talked about the past team kind of uber the Bilson called m three. That's basically next generation data dog. Next generation of visibility platform. They're gonna collect all the data from the applications. And once they have their your data, they're gonna know how to operate and automate scaling up, scaling down and the basic remediation for you. So you're going to see a bunch of tools, take the information from running your application infrastructure and automate exactly how to scale and manager your app. And so AI and machine learning where large John is gonna be, say, make a lot of plumbing go away or maybe not completely, but lets you scale better. So you, as a single system admin are used. A single SRE site reliability engineer can scale and manage a bigger application, and it's all gonna be around automation and and to your point, you said earlier, if you have the data, that's a powerful situations. Once have the data can build models on it and can start building solutions on the data. And so I think What happens is when Bill this program of cloud for for your, you know, broad development population automating all this stuff becomes important. So that's why I say service or this, You know, automation of infrastructure is the next battleground for the cloud because whoever does that for you is gonna be your virtualized back and virtualized data center virtualized SRE. And if whoever owns that, it's gonna be a very, very strategic position. >>Yeah, it's great stuff. This is back to the theme of this notion of virtualization is now gone beyond server virtualization. It's, you know, media virtualization with the Cube. My big joke here with the Q virtual. But it's to your point. It's everything can now be replicated in software and scale the cloud scale. So it's super big opportunity for entrepreneurs and companies. Thio, pivot and differentiate. Uh, the question I have for you next is on that thread Huge edge discussion going on, right. So, you know, I think I said it two years ago or three years ago. The data center is just a edges just a big fat edge. Jassy kind of said that in his keynote Hey, looks at that is just a Nedum point with his from his standpoint. But you have data center. You have re alleges you've got five G with wavelength. This local zone concept, which is, you know, Amazon in these metro areas reminds me the old wireless point of presence kind of vibe. And then you've got just purpose built devices like cameras and factory. So huge industrial innovation, robotics, meet software. I mean, whole huge edge development exploding, Which what's your view of this? And how do you look at that from? Is an investor in industry, >>I think edges both the opportunity for start ups and companies as well as a threat to Amazon, right to the reason why they have outposts and all the stuff the edges if you think about, you know, decentralizing your application and moving into the eggs from my wearable to my home to my car to my my city block edges access Super interesting. And so a couple things. One companies like Cloudflare Fastly company I'm involved with called Kato Networks that does. SAS is secure access service edge write their names and the edges In the category definition sassy is about How do you like get compute to the edge securely for your developers, for your customers, for your workers, for end users and what you know comes like Cloudflare and Kate have done is they built out a network of pops across the world, their their own infrastructure So they're not dependent upon. You know, the big cloud providers, the telco providers, you know, they're partnering with Big Cloud, their parting with the telcos. But they have their own kind of system, our own kind of platform to get to the edge. And so companies like Kato Networks in Cloud Player that have, ah, presence on the edge and their own infrastructure more or less, I think, are gonna be in a strategic position. And so Kate was seen benefits in the past year of Of of Cove it and locked down because more remote access more developers, Um, I think edge is gonna be a super great area development going forward. I think if you're Amazon, you're pushing to the edge aggressively without post. I think you're a developer startup. You know, creating your own infrastructure and riding this edge wave could be a great way to build a moat against a big cloud guy. So I'm super excited. You think edge in this whole idea of your own infrastructure. Like what Kato has done, it is gonna be super useful going forward. And you're going to see more and more companies. Um, spend the money to try to copy kind of, ah, Cloudflare Kato presence around the world. Because once you own your own kind of, um, infrastructure instead of pops and you're less depend upon them a cloud provider, you're you're in a good position because there's the Amazon outage last week and I think like twilio and a bunch of services went down for for a few hours. If you own your own set of pops, your independent that it is actually really, really secure >>if you and if they go down to the it's on you. But that was the kinesis outage that they had, uh, they before Thanksgiving. Um, yeah, that that's a problem. So on this on. So I guess the question for you on that is that Is it better to partner with Amazon or try to get a position on the edge? Have them either by you or computer, create value or coexist? How do you see that that strategy move. Do you coexist? Do you play with them? >>E think you have to co exist? I think that the partner coexist, right? I think like all things you compete with Amazon. Amazon is so broad that will be part of Amazon and you're gonna compete with and that's that's fair game, you know, like so Snowflake competes against red shift, but they also part of Amazon's. They're running Amazon. So I think if you're a startup trying to find the edge, you have to coexist in Amazon because they're so big. Big cloud, right, The Big three cloud Amazon, Google, Azure. They're not going anywhere. So if you're a startup founder, you definitely coexist. Leverage the good things of cloud. But then you gotta invest in your own edge. Both both figure early what? Your edge and literally the edge. Right. And I think you know you complement your edge presence be it the home, the car, the city block, the zip code with, you know, using Amazon strategically because Amazon is gonna help you get two different countries, different regions. You know you can't build a company without touching Amazon in some form of fashion these days. But if you're a star found or doing strategically, how use Amazon and picking how you differentiate is gonna be key. And if the differentiation might be small, John. But it could be super valuable, right? So maybe only 10 or 15%. But that could be ah Holton of value that you're building on top of it. >>Yeah, and there's a little bit of growth hack to with Amazon if you you know how it works. If you compete directly against the core building blocks like a C two has three, you're gonna get killed, right? They're gonna kill you if the the white space is interest. In the old days in Microsoft, you had a white space. They give it to you or they would roll you over and level you out. Amazon. If you're a customer and you're in a white space and do better than them, they're cool with that. They're like, basically like, Hey, if you could innovate on behalf of the customer, they let you do that as long as you have a big bill. Yeah. Snowflakes paying a lot of money to Amazon. Sure, but they also are doing a good job. So again, Amazon has been very clear on that. If you do a better job than us for, the customer will do it. But if they want Amazon Red Shift, they want Amazon Onley. They can choose that eso kind of the playbook. >>I think it is absolutely right, John is it sets from any jassy and that the Amazon culture of the customer comes first, right? And so whatever is best for the customer that's like their their mission statement. So whatever they do, they do for the customer. And if you build value for the customer and you're on top of Amazon, they'll be happy. You might compete with some Amazon services, which, no, the GM of that business may not be happy, but overall. Net Net. Amazon's getting a share of those dollars that you're that you're charging the customer getting a share of the value you're creating. They're happy, right? Because you know what? The line rising tide floats all the boats. So the Mork cloud usage is gonna only benefit the Big Three cloud providers Amazon, particularly because they're the biggest of the three. But more and more dollars go the cloud. If you're helping move more. Absolute cloud helping build more solutions in the cloud. Amazon is gonna be happy because they know that regardless of what you're doing, you will get a fraction of those dollars. Now, the key for a startup founder and what I'm looking for is how do we get mawr than you know? A sliver of the dollars. How to get a bigger slice of the pie, if you will. So I think edge and surveillance or two areas I'm thinking about because I think there are two areas where you can actually invest, own some I p owned some surface area and capture more of the value, um, to use a startup founder and, you know, are built last t to Amazon. >>Yeah. Great. Great thesis. Jerry has always been great. You've been with the Cube since the beginning on our first reinvented 2013. Um, and so we're now on our eighth year. Great to see your success. Great investment. You make your world class investor to great firm Greylock. Um great to have you on from your perspective. Final take on this year. What's your view of Jackie's keynote? Just in general, What's the vibe. What's the quick, um, soundbite >>from you? First, I'm so impressed and you can do you feel like a three Archy? No more or less by himself. Right then, that is, that is, um, that's a one man show, and I'm All of that is I don't think I could pull that off. Number one. Number two It's, um, the ability to for for Amazon to execute at so many different levels of stack from semiconductors. Right there, there there ai chips to high level services around healthcare solutions and legit solutions. It's amazing. So I would say both. I'm impressed by Amazon's ability. Thio go so broad up and down the stack. But also, I think the theme from From From Andy Jassy is like It's just acceleration. It's, you know now that we will have things unique to the cloud, and that could be just a I chips unique to the cloud or the services that are cloud only you're going to see a tipping point. We saw acceleration in the past 15 years, John. He called like this cloud transition. But you know, I think you know, we're talking about 2021 beyond you'll see a tipping point where now you can only get certain things in the cloud. Right? And that could be the underlying inference. Instances are training instances, the Amazons giving. So all of a sudden you as a founder or developer, says, Look, I guess so much more in the cloud there's there's no reason for me to do this hybrid thing. You know, Khyber is not gonna go away on Prem is not going away. But for sure. We're going to see, uh, increasing celebration off cloud only services. Um, our edge only services or things. They're only on functions that serve like serverless. That'll be defined the next 10 years of compute. And so that for you and I was gonna be a space and watch >>Jerry Chen always pleasure. Great insight. Great to have you on the Cube again. Great to see you. Thanks for coming on. >>Congrats to you guys in the Cube. Seven years growing. It's amazing to see all the content put on. So you think it isn't? Just Last point is you see the growth of the curve growth curves of the cloud. I'd be curious Johnson, The growth curve of the cube content You know, I would say you guys are also going exponential as well. So super impressed with what you guys have dealt. Congratulations. >>Thank you so much. Cute. Virtual. We've been virtualized. Virtualization is coming here, or Cubans were not in person this year because of the pandemic. But we'll be hybrid soon as events come back. I'm John for a year. Host for AWS reinvent coverage with the Cube. Thanks for watching. Stay tuned for more coverage all day. Next three weeks. Stay with us from around the globe. It's the Cube with digital coverage of aws reinvent 2020 sponsored by Intel >>and AWS. Welcome back here to our coverage here on the Cube of AWS.

>>covering the space and cybersecurity symposium 2020 hosted by Cal poly. Hold on. Welcome to this special presentation with Cal poly hosting the space and cybersecurity symposium, 2020 virtual, um, John for your host with the cube and Silicon angle here in our Palo Alto studios with our remote guests, we couldn't be there in person, but we're going to be here remotely. Got a great session and a panel for one hour topic preparing students for the jobs of today and tomorrow, but a great lineup. Bill Britain, Lieutenant Colonel from the us air force, retired vice president for information technology and CIO and the director of the California cyber security Institute for Cal poly bill. Thanks for joining us, dr. Amy Fisher, who's the Dean of the college of engineering at Cal poly and trunk fam professor and researcher at the U S air force Academy. Folks, thanks for joining me today. >>Our pleasure got a great, great panel. This is one of my favorite topics preparing students for the next generation, the jobs for today and tomorrow. We've got an hour. I'd love you guys to start with an opening statement, to kick things off a bill. We'll start with you. Well, I'm really pleased to be, to start on this. Um, as the director for the cybersecurity Institute and the CIO at Cal poly, it's really a fun, exciting job because as a Polytechnic technology, as such a forefront in what we're doing, and we've had a, a wonderful opportunity being 40 miles from Vandenberg air force base to really look at the nexus of space and cyber security. And if you add into that, uh, both commercial government and civil space and cybersecurity, this is an expanding wide open time for cyber and space. In that role that we have with the cyber security Institute, we partner with elements of the state and the university. >>And we try to really add value above our academic level, which is some of the highest in the nation and to really merge down and go a little lower and start younger. So we actually are running the week prior to this showing a cybersecurity competition for high schools or middle schools in the state of California, that competition this year is based on a scenario around hacking of a commercial satellite and the forensics of the payload that was hacked and the networks associated with it. This is going to be done using products like Wireshark autopsy and other tools that will give those high school students. What we hope is a huge desire to follow up and go into cyber and cyber space and space and follow that career path. And either come to Cal poly or some other institution that's going to let them really expand their horizons in cybersecurity and space for the future >>Of our nation. >>Bill, thanks for that intro, by the way, it's gonna give you props for an amazing team and job you guys are doing at Cal poly, that Dex hub and the efforts you guys are having with your challenge. Congratulations on that great work. Thank you >>Star team. It's absolutely amazing. You find that much talent in one location. And I think Amy is going to tell you she's got the same amount of talent in her staff. So it's, it's a great place to be. >>Amy flasher. You guys have a great organization down there, amazing curriculum, grazing people, great community, your opening statement. >>Hello everybody. It's really great to be a part of this panel on behalf of the Cal poly college of engineering here at Cal poly, we really take preparing students for the jobs of today and tomorrow completely seriously. And we claim that our students really graduate. So they're ready day one for their first real job, but that means that in getting them to that point, we have to help them get valuable and meaningful job experience before they graduate, but through our curriculum and through multiple internship or summer research opportunities. So we focus our curriculum on what we call a learn by doing philosophy. And this means that we have a combination of practical experience and learn by doing both in and out of the classroom. And we find that to be really critical for preparing students for the workforce here at Cal poly, we have more than 6,000 engineering students. >>We're one of the largest undergraduate engineering schools in the country. Um, and us news ranks us the eighth best undergraduate engineering program in the, in the country and the top ranked state school. We're really, really proud that we offer this impactful hands on engineering education that really exceeds that of virtually all private universities while reaching a wider audience of students. We offer 14 degree programs and really we're talking today about cyber and space. And I think most of those degree programs can really make an impact in the space and cybersecurity economy. And this includes not only things like Aero and cyber directly, but also electrical engineering, mechanical engineering, computer engineering, materials, engineering, even manufacturing, civil and biomedical engineering. As there's a lot of infrastructure needs that go into supporting launch capabilities. Our aerospace program graduates hundreds of aerospace engineers, and most of them are working right here in California. >>I'm with many of our corporate partners, including Northrop Grumman, Lockheed, Boeing, Raytheon space, X, Virgin, galactic JPL, and so many other places where we have Cal poly engineer's impacting the space economy. Our cybersecurity focus is found mainly in our computer science and software engineering programs. And it's really a rapidly growing interest among our students. Computer science is our most popular major and industry interest and partnerships are integrated into our curriculum. And we do that oftentimes through support from industry. So we have partnerships with Northrop Grumman for professorship and a cyber lab and from PG and E for critical infrastructure, cybersecurity lab, and professorship. And we think that industry partnerships like these are really critical to preparing students for the future as the field's evolving so quickly and making sure we adapt our facilities and our curriculum to stay in line with what we're seeing in industry is incredibly important. >>In our aerospace program, we have an educational partnership with the air force research labs. That's allowing us to install new high performance computing capabilities and a space environments lab. That's going to enhance our satellite design capabilities. And if we talk about satellite design, Cal poly is the founding home of the cube sat program, which pioneered small satellite capabilities. And we remain the worldwide leader in maintaining the cube set standard. And our student program has launched more cube sets than any other program. So here again, we have this learn by doing experience every year for dozens of aerospace, electrical, computer science, mechanical engineering students, and other student activities that we think are just as important include ethical hacking through our white hat club, Cal poly space systems, which does really, really big rocket launches and our support program for women in both of these fields like wish, which is women in software and hardware. >>Now, you know, really trying to bring in a wide variety of people into these fields is incredibly important and outreach and support to those demographics. Traditionally underrepresented in these fields is going to be really critical to future success. So by drawing on the lived experiences by people with different types of backgrounds, while we develop the type of culture and environment where all of us can get to the best solution. So in terms of bringing people into the field, we see that research shows, we need to reach kids when they're in late elementary and middle schools to really overcome that cultural bias that works against diversity in our fields. And you heard bill talking about the cyber cybersec, the California cybersecurity institutes a year late cyber challenge. There's a lot of other people who are working to bring in a wider variety of, uh, of people into the field, like girl Scouts, which has introduced dozens of new badges over the past few years, including a whole cybersecurity series of badges and a concert with Palo Alto networks. So we have our work cut out for us, but we know what we need to do. And if we're really committed to prep properly preparing the workforce for today and tomorrow, I think our future is going to be bright. I'm looking forward to our discussion today. >>Yeah, you got a flashy for great, great comment, opening statement and congratulations. You got the right formula down there, the right mindset, and you got a lot of talent and community as well. Thank thank you for that opening statement. Next step from Colorado Springs, trunk fam, who's a professor and researcher. The us air force Academy is doing a lot of research around the areas that are most important for the intersection of space and technology trunk. >>Good afternoon, first electric and Cal poli for the opportunity. And today I want to go briefly about cyber security in S application. Whenever we talk about cyber security, the impression is got yes, a new phew that is really highly complex involving a lot of technical area. But in reality, in my personal opinion, it is in be complex because involve many disciplines. The first thing we think about is computer engineering and computer networking, but it's also involving communication sociology, law practice. And this practice of cyber security goes in on the info computer expert, but it's also info everybody else who has a computing device that is connected to the internet. And this participation is obviously every body in today's environment. When we think about the internet, we know that is a good source of information, but come with the convenience of information that we can access. >>We are constantly faced in being from the internet. Some of them, we might be aware of some of them we might not be aware of. For example, when we search on the internet, a lot of time, our browser will be saved and gotten this site is not trusted. So we will be more careful. What about the sites that we trusted? We know getting those salad chicken sites, but they're not a hundred percent good at proof. What happened? It was all side, uh, attack by hacker. And then they will be a silent source that we might not be aware of. So in the reality, we need to be more practicing the, um, cyber security from our SIBO point of view and not from a technical point of view. When we talk about space application, we should know that all the hardware, a computer based tool by computer system and therefore the hardware and the software must go through some certification process so that they can be record that air with the flight. >>What the, when we know that in the certification process is focusing on the functionality of the hardware and software, but one aspect that is explicitly and implicitly required is the security of those components. And we know that those components have to be connected with the ground control station and be communication is through the air, through the layby or signal. So anybody who has access to those communication regular signal will be able to control the space system that we put up there. And we certainly do not want our system to be hijacked by a third party. >>I'm not going to aspect of cybersecurity is we try to design the space system in a very strong manner. So it's almost impossible to hack in, but what about some August week system that might be connected to so strong system? For example, the spare system will be connected to the ground control station and on the ground control station, we have the human controller in those people have cell phone. They are allowed to use cell phones for communication, but at the same time, they are connected to the internet, to the cell phone and their cell phone might be connected to the computer that control the flight software and hardware. So what I want to say is that we try to build strong system and we protected them, but there will be some weaker system that we could not intended, but exists to be connected to our strong system. And those are the points that hacker will be trying to attack. If we know how to control the access to those points, we will be having a much better system for the space system. And when we see the cybersecurity that is requiring the participation everywhere, it's important to Merck that there is a source of opportunity for students to engage the workforce. To concede the obviously student in engineering can focus their knowledge and expertise to provide technological solution, to protect the system that we view. But we also >>Have students in business who can focus to write a business plan to reach the market. We also have student in law who can focus policy governing the cyber security. And we also have student in education who can focus the expert. She should be saying how to teach cyber security practice and students can focus the effort to implement security measures and it implies job opportunity. >>Thank you trunk for those great comments, great technology opportunities, but interesting as well as the theme that we're seeing across the entire symposium and in the virtual hallways that we're hearing conversations and you pointed out some of them, dr. Fleischer did as well. And bill, you mentioned it. It's not one thing. It's not just technology, it's different skills. And, um, Amy, you mentioned that computer science is the hottest degree, but you have the hottest aerospace program in the world. I mean, so all of this is kind of balancing it's interdisciplinary. It's a structural change before we get into some of the, um, how they prepare the students. Can you guys talk about some of the structural changes that are modern now in preparing, um, in these opportunities because societal impact is a law potentially impact it's, it's how we educate there's no cross-discipline skillsets. It's not just get the degree, see out in the field bill, you want to start. >>Well, what's really fun about this job is, is that in the air force, uh, I worked in the space and missile business and what we saw was a heavy reliance on checklist format, security procedures, analog systems, and what we're seeing now in our world, both in the government and the commercial side, uh, is a move to a digital environment. And the digital environment is a very quick and adaptive environment. And it's going to require a digital understanding. Matter of fact, um, the, uh, under secretary of the air force for acquisition, uh, rev recently referenced the need to understand the digital environment and how that's affecting acquisition. So as, as both Amy, um, and trunk said, even business students are now in the >>Cybersecurity business. And, and so, again, what we're seeing is, is the change. Now, another phenomenon that we're seeing in the space world is there's just so much data. Uh, one of the ways that we addressed that in the past was to look at high performance computing. It was a lot stricter control over how that worked, but now what we're seeing these adaptation of cloud cloud technologies in space support, space, data, command, and control. Uh, and so what we see is a modern space engineer who asked to understand digital, has to understand cloud and has to understand the context of all those with a cyber environment. That's really changing the forefront of what is a space engineer, what is a digital engineer and what does a future engineer, both commercial or government? So I think the opportunity for all of these things is really good, particularly for a Polytechnic air force Academy and others that are focusing on a more, uh, widened experiential level of cloud and engineering and other capabilities. >>And I'll tell you the part that as the CIO, I have to remind everybody, all this stuff works for the it stuff. So you've got to understand how your it infrastructures are tied and working together. Um, as we noted earlier, one of the things is, is that these are all relays from point the point, and that architecture is part of your cybersecurity architecture. So again, every component has now become a cyber aware cyber knowledgeable, and in what we'd like to call as a cyber cognizant citizen, where they have to understand the context, patients chip software, that the Fleischer talk about your perspective, because you mentioned some of the things that computer science. Remember when I'm in the eighties, when I got my computer science degree, they call the software engineers, and then you became software developers. And then, so again, engineering is the theme. If you're engineering a system, there's now software involved, um, and there's also business engineering business models. So talk about some of your comments was, you mentioned, computer science is hot. You got the aerospace, you've got these multidisciplines you got definitely diversity as well. It brings more perspectives in as well. Your thoughts on these structural interdisciplinary things. >>I think this is, this is really key to making sure that students are prepared to work in the workforce is looking at the, the blurring between fields no longer are you just a computer scientist, no longer are you just an aerospace engineer? You really have to have an expertise where you can work with people across disciplines. All of these, all of these fields are just working with each other in ways we haven't seen before. And bill brought up data, you know, data science is something that's cross cutting across all of our fields. So we want engineers that have the disciplinary expertise so that they can go deep into these fields, but we want them to be able to communicate with each and to be able to communicate across disciplines and to be able to work in teams that are across disciplines. You can no longer just work with other computer scientists or just work with other aerospace engineers. >>There's no part of engineering that is siloed anymore. So that's how we're changing. You have to be able to work across those, those disciplines. And as you, as Tron pointed out, you know, ethics has to come into this. So you can no longer try to fully separate what we would traditionally have called the, the liberal arts and say, well, that's over there in general education. No ethics is an important part of what we're doing and how we integrate that into our curriculum. So it was communication. So is working on public policy and seeing where all of these different aspects tied together to make the impact that we want to have in the world. So it, you no longer can work solo in these fields. >>Great point. And bill also mentioned the cloud. One thing about the cloud that showed us as horizontal scalability has created a lot of value and certainly data is now horizontal Trung. You mentioned some of the things about cryptography for the kids out there. I mean, you can look at the pathway for career. You can do a lot of tech and, but you don't have to go deep. Sometimes you can go, you can go as deep as you want, but there's so much more there. Um, what technology do you see, how it's going to help students in your opinion? >>Well, I'm a professor in computer science, so I'd like to talk out a little bit about computer programming. Now we, uh, working in complex project. So most of the time we design a system from scratch. We view it from different components and the components that we have either we get it from or some time we get it from the internet in the open source environment, it's fun to get the source code and then work to our own application. So now when we are looking at a Logie, when we talk about encryption, for example, we can easily get the source code from the internet. And the question is, is safe to use those source code. And my, my, my question is maybe not. So I always encourage my students to learn how to write source score distribution, where that I learned a long time ago before I allow them to use the open source environment. And one of the things that they have to be careful, especially with encryption is be quote that might be hidden in the, in the source, get the download here, some of the source. >>So open source, it's a wonderful place to be, but it's also that we have to be aware of >>Great point before we get into some of the common one quick thing for each of you like to get your comments on, you know, the there's been a big movement on growth mindset, which has been a great, I'm a big believer in having a growth mindset and learning and all that good stuff. But now that when you talk about some of these things that we're mentioning about systems, there's, there's an, there's a new trend around a systems mindset, because if everything's now a system distributed systems, now you have space in cyber security, you have to understand the consequences of changes. And you mentioned some of that Trung in changes in the source code. Could you guys share your quick opinions on the, the idea of systems thinking, is that a mindset that people should be looking at? Because it used to be just one thing, Oh, you're a systems guy or galley. There you go. You're done. Now. It seems to be in social media and data. Everything seems to be systems. What's your take dr. Fleischer, we'll start with you. >>Uh, I'd say it's a, it's another way of looking at, um, not being just so deep in your discipline. You have to understand what the impact of the decisions that you're making have on a much broader, uh, system. And so I think it's important for all of our students to get some exposure to that systems level thinking and looking at the greater impact of the decision that they're making. Now, the issue is where do you set the systems boundary, right? And you can set the systems boundary very close in and concentrate on an aspect of a design, or you can continually move that system boundary out and see, where do you hit the intersections of engineering and science along with ethics and public policy and the greater society. And I think that's where some of the interesting work is going to be. And I think at least exposing students and letting them know that they're going to have to make some of these considerations as they move throughout their career is going to be vital as we move into the future. Bill. What's your thoughts? >>Um, I absolutely agree with Amy and I think there's a context here that reverse engineering, um, and forensics analysis and forensics engineering are becoming more critical than ever, uh, the ability to look at what you have designed in a system and then tear it apart and look at it for gaps and holes and problem sets, or when you're given some software that's already been pre developed, checking it to make sure it is, is really going to do what it says it's going to do. That forensics ability becomes more and more a skillset that also you need the verbal skills to explain what it is you're doing and what you found. So the communication side, the systems analysis, >>The forensics analysis side, >>These are all things that are part of that system >>Approach that I think you could spend hours on. And we still haven't really done great job on it. So it's a, it's. One of my fortes is the really the whole analysis side of forensics and it reverse engineering >>Try and real quick systems thinking. >>Well, I'd like to share with you my experience. When I worked in the space patient program at NASA, we had two different approaches. One is a down approach where we design it from the system general point of view, where we put components to complex system. But at the same time, we have the bottom up approach where we have Ken Chile who spent time and effort the individual component. And they have to be expert in those Chinese component. That might be general component the gallery. And in the space station program, we bring together the welcome up engineer, who designed everything in detail in the system manager who manage the system design from the top down. And we meet in the middle and took the idea with compromise a lot of differences. Then we can leave a display station that we are operating to be okay, >>Great insight. And that's the whole teamwork collaboration that, that was mentioning. Thanks so much for that insight. I wanted to get that out there because I know myself as a, as a parent, I'm always trying to think about what's best for my kids in their friends, as they grow up into the workforce. I know educators and leaders in industry would love to know some of the best practices around some of the structural changes. So thanks for that insight, but this topics about students and helping them prepare. Uh, so we heard, you know, be, be multiple discipline, broaden your horizons, think like systems top down, bottom up, work together as a team and follow the data. So I got to ask you guys, there's a huge amount of job openings in cybersecurity. It's well documented and certainly at the intersection of space and cyber, it's only gonna get bigger, right? You're going to see more and more demand for new types of jobs. How do we get high school and college students interested in security as a career at the flagship? We'll start with you in this one. >>I would say really one of the best ways to get students interested in the career is to show them the impact that it's going to have. There's definitely always going to be students who are going to want to do the technology for the technology sake, but that will limit you to a narrow set of students. And by showing that the greater impact that these types of careers are going to have on the types of problems that you're going to be able to solve and the impact you're going to be able to have on the world, around you, that's the word that we really need to get out. And a wide variety of students really respond to these messages. So I think it's really kind of reaching out at the, uh, the elementary, the middle school level, and really kind of getting this idea that you can make a big difference, a big positive difference in the field with some of these careers is going to be really critical. >>Real question, follow up. What do you think is the best entry point? You mentioned middle squad in here, elementary school. This comes, there's a lot of discussions around pipelining and we're going to get into women in tech and under-represented matters later, but you know, is it too early or what's the, what's your feeling on this? >>My feeling is the earlier we can normalize it the better the, uh, if you can normalize an interest in, in computers and technology and building an elementary school, that's absolutely critical. But the dropoff point that we're seeing is between what I would call like late elementary and early middle school. Um, and just kind of as an anecdote, I, for years ran an outreach program for girl Scouts in grades four and five and grade six, seven, and eight. And we had a hundred slots in each program. And every year the program would sell out for girls in grades four and five, and every year we'd have spots remaining in grades six, seven, and eight. And that's literally where the drop-off is occurring between that late elementary and that middle school range. So that's the area that we need to target to make sure we keep those young women involved and interested as we move forward. >>Bill, how are we going to get these kids interested in security? You mentioned a few programs you got. Yeah. I mean, who wants to, who wouldn't want to be a white hat hacker? I mean, yeah, that sounds exciting. Yeah. Great questions. Let's start with some basic principles though. Is let me ask you a question, John, a name for me, one white hat, good person hacker. The name who works in the space industry and is an exemplar for students to look up to, um, you, um, Oh man. I'm hearing really. I can't, I can't, I can't, I can't imagine because the answer we normally get is the cricket sound. So we don't have individuals we've identified in those areas for them to look up to. I was going to be snarky and say, most white hackers won't even use their real name, but, um, there's a, there's an aura around their anonymity here. >>So, so again, the real question is, is how do we get them engaged and keep them engaged? And that's what Amy was pointing out too. Exactly the engagement and sticking with it. So one of the things that we're trying to do through our competition on the state level and other elements is providing connections. We call them ambassadors. These are people in the business who can contact the students that are in the game or in that, uh, challenge environment and let them interact and let them talk about what they do and what they're doing in life would give them a challenging game format. Um, a lot of computer based training, um, capture the flag stuff is great, but if you can make it hands on, if you can make it a learn by doing experiment, if you can make it am personally involved and see the benefit as a result of doing that challenge and then talk to the people who do that on a daily basis, that's how you get them involved. >>The second part is as part of what we're doing is, is we're involving partnership companies in the development of the teams. So this year's competition that we're running has 82 teams from across the state of California, uh, of those 82 teams at six students team, middle school, high school, and many of those have company partners. And these are practitioners in cybersecurity who are working with those students to participate. It's it's that adult connectivity, it's that visualization. Um, so at the competition this year, um, we have the founder of Def con red flag is a participant to talk to the students. We have Vince surf as who is of course, very well known for something called the internet to participate. It's really getting the students to understand who's in this. Who can I look up to and how do I stay engaged with them? >>There's definitely a celebrity aspect of it. I will agree. I mean, the influencer aspect here with knowledge is key. Can you talk about, um, these ambassadors and, and, and how far along are you on that program? First of all, the challenge stuff is anything gamification wise. We've seen that with hackathons is just really works well. Grades, bonding, people who create together kinda get sticky and get very high community aspect to it. Talking about this ambassador thing. What does that industry is that academic >>Absolutely partners that we've identified? Um, some of which, and I won't hit all of them. So I'm sure I'll short changes, but, uh, Palo Alto, Cisco, um, Splunk, um, many of the companies in California and what we've done is identified, uh, schools, uh, to participate in the challenge that may not have a strong STEM program or have any cyber program. And the idea of the company is they look for their employees who are in those school districts to partner with the schools to help provide outreach. It could be as simple as a couple hours a week, or it's a team support captain or it's providing computers and other devices to use. Uh, and so again, it's really about a constant connectivity and, uh, trying to help where some schools may not have the staff or support units in an area to really provide them what they need for connectivity. What that does gives us an opportunity to not just focus on it once a year, but throughout the year. So for the competition, all the teams that are participating have been receiving, um, training and educational opportunities in the game of education side, since they signed up to participate. So there's a website, there's learning materials, there's materials provided by certain vendor companies like Wireshark and others. So it's a continuum of opportunity for the, >>You know, I've seen just the re randomly, just going to random thought, you know, robotics clubs are moving den closer into that middle school area, in fact Fleischer. And certainly in high schools, it's almost like a varsity sport. E-sports is another one. My son just combined made the JV at the college Dean, you know, it's big and it's up and serious. Right. And, um, it's fun. This is the aspect of fun. It's hands on. This is part of the culture down there you learn by doing, is there like a group? Is it like, um, is it like a club? I mean, how do you guys organize these bottoms up organically interest topics? >>So, so here in the college of engineering, uh, when we talk about learning by doing, we have learned by doing both in the classroom and out of the classroom. And if we look at the, these types of, out of the classroom activities, we have over 80 clubs working on all different aspects of many of these are bottom up. The students have decided what they want to work on and have organized themselves around that. And then they get the leadership opportunities. The more experienced students train in the less experienced students. And it continues to build from year after year after year with them even doing aspects of strategic planning from year to year for some of these competitions. So, yeah, it's an absolutely great experience. And we don't define for them how their learned by doing experiences should be, we want them to define it. And I think the really cool thing about that is they have the ownership and they have the interest and they can come up with new clubs year after year to see which direction they want to take it. And, you know, we will help support those clubs as old clubs fade out and new clubs come in >>Trunk real quick. Before we go on the next, uh, talk track, what, what do you recommend for, um, middle school, high school or even elementary? Um, a little bit of coding Minecraft. I mean, what, how do you get them hooked on the fun and the dopamine of, uh, technology and cybersecurity? What's your, what's your take on that? >>On, on this aspect, I like to share with you my experience as a junior high and high school student in Texas, the university of Texas in Austin organized a competition for every high school in Texas. If we phew from poetry to mathematics, to science, computer engineering, but it's not about with university of Texas. The university of Texas is on the serving SSN for the final competition that we divide the competition to be strict and then regional, and then spit at each level, we have local university and colleges volunteering to host it competition and make it fun. >>Also students with private enterprises to raise funding for scholarship. So students who see the competition they get exposed to so they can see different option. They also get a scholarship when they attend university in college. So I've seen the combination in competition aspect would be a good thing to be >>Got the engagement, the aspiration scholarship, you know, and you mentioned a volunteer. I think one of the things I'll observe is you guys are kind of hitting this as community. I mean, the story of Steve jobs and was, was building the Mac, they call it bill Hewlett up in Palo Alto. It was in the phone book and they scoured some parts from them. That's community. This is kind of what you're getting at. So this is kind of the formula we're seeing. So the next question I really want to get into is the women in technology, STEM, underrepresented minorities, how do we get them on cybersecurity career path? Is there a best practices there, bill, we'll start with you? >>Well, I think it's really interesting. First thing I want to add is if I could have just a clarification, what's really cool that the competition that we have and we're running, it's run by student from Cal poly. Uh, so, you know, Amy referenced the clubs and other activities. So many of the, uh, organizers and developers of the competition that we're running are the students, but not just from engineering. So we actually have theater and liberal arts majors and technology for liberal arts majors who are part of the competition. And we use their areas of expertise, set design, and other things, uh, visualization of virtualization. Those are all part of how we then teach and educate cyber in our game effication and other areas. So they're all involved in their learning as well. So we have our students teaching other students. So we're really excited about that. And I think that's part of what leads to a mentoring aspect of what we're providing, where our students are mentoring the other students. And I think it's also something that's really important in the game. Um, the first year we held the game, we had several all girl teams and it was really interesting because a, they, they didn't really know if they could compete. I mean, this is their, their reference point. We don't know if they did better than anybody. I mean, they, they knocked the ball out >>Of the park. The second part then is building that confidence level that they can going back and telling their cohorts that, Hey, it's not this thing you can't do. It's something real that you can compete and win. And so again, it's building that comradery, that spirit, that knowledge that they can succeed. And I think that goes a long way and an Amy's programs and the reach out and the reach out that Cal poly does to schools to develop. Uh, I think that's what it really is going to take. It. It is going to take that village approach to really increase diversity and inclusivity for the community. >>That's the flusher. I'd love to get your thoughts. You mentioned, um, your, your outreach program and the dropoff, some of those data, uh, you're deeply involved in this. You're passionate about it. What's your thoughts on this career path opportunity for STEM? >>Yeah, I think STEM is an incredible career path opportunity for so many people. There's so many interesting problems that we can solve, particularly in cyber and in space systems. And I think we have to meet the kids where they are and kind of show them, you know, what the exciting part is about it, right. But, you know, bill was, was alluding to this. And when he was talking about, you know, trying to name somebody that you can can point to. And I think having those visible people where you can see yourself in that is, is absolutely critical and those mentors and that mentorship program. So we use a lot of our students going out into California, middle schools and elementary schools. And you want to see somebody that's like you, somebody that came from your background and was able to do this. So a lot of times we have students from our national society of black engineers or a society of Hispanic professional engineers or our society of women engineers. >>We have over a thousand members, a thousand student members in our society of women engineers who were doing these outreach programs. But like I also said, it's hitting them at the lower levels too. And girl Scouts is actually distinguishing themselves as one of the leading STEM advocates in the country. And like I said, they developed all these cybersecurity badges, starting in kindergarten. There's a cybersecurity badge for kindergarten and first graders. And it goes all the way up through late high school, the same thing with space systems. And they did the space systems in partnership with NASA. They did the cybersecurity and partnership with Palo Alto networks. And what you do is you want to build these, these skills that the girls are developing. And like bill said, work in and girl led teams where they can do it. And if they're doing it from kindergarten on, it just becomes normal. And they never think, well, this is not for me. And they see the older girls who are doing it and they see a very clear path leading them into these careers. >>Yeah. It's interesting. You used the word normalization earlier. That's exactly what it is. It's life, you get life skills and a new kind of badge. Why wouldn't learn how to be a white, white hat hacker, or have fun or learn new skills just in, in the, in the grind of your fun day. Super exciting. Okay. Trung your thoughts on this. I mean, you have a diverse diversity. It brings perspective to the table in cybersecurity because you have to think like the other, the adversary, you got to be the white headed hippie, a white hat, unless you know how black hat thinks. So there's a lot of needs here for more, more, more points of view. How are we going to get people trained on this from under represented minorities and women? What's your thoughts? >>Well, as a member of, I took a professional society of directed pool in the electronic engineer. You have the, uh, we participate in the engineering week. We'll be ploy our members to local junior high school and high school to talk about our project, to promote the discovery of engineering. But at the same time, we also participate in the science fair that we scaled up flex. As the squad organizing our engineer will be mentoring students, number one, to help them with the part check, but number two, to help us identify talents so that we can recruit them further into the field of STEM. One of the participation that week was the competition of the, what they call future CV. We're still going, we'll be doing a CT on a computer simulation. And in recent year we promote ops smart CV where CT will be connected the individual houses to be added in through the internet. >>And we want to bring awareness of cybersecurity into competition. So we deploy engineer to supervise the people, the students who participate in the competition, we bring awareness, not in the technical be challenged level, but in what we've called the compound level. So speargun will be able to know what is, why to provide cyber security for the smart city that they are building. And at the same time, we were able to identify talent, especially talent in the minority and in the room. And so that we can recruit them more actively. And we also raise money for scholarship. We believe that scholarship is the best way to get students to continue education in Epic college level. So with scholarship, it's very easy to recruit them, to give you and then push them to go further into the cyber security Eylea. >>Yeah. I mean, you know, I see a lot of the parents like, Oh, my kid's going to go join the soccer team, >>Private lessons, and maybe look at a scholarship >>Someday. Well, they only do have scholarships anyway. I mean, this is if they spent that time doing other things, it's just, again, this is a new lifestyle, like the girl Scouts. And this is where I want to get into this whole silo breaking down because Amy, you brought this up and bill, you were talking about as well, you've got multiple stakeholders here with this event. You got, you know, public, you got private and you've got educators. It's the intersection of all of them. It's again, that those, if those silos break down the confluence of those three stakeholders have to work together. So let's, let's talk about that. Educators. You guys are educating young minds, you're interfacing with private institutions and now the public. What about educators? What can they do to make cyber better? Cause there's no real manual. I mean, it's not like this court is a body of work of how to educate cybersecurity is maybe it's more recent, it's cutting edge, best practices, but still it's an, it's an evolving playbook. What's your thoughts for educators, bill? We'll start with you. >>Well, I don't really, I'm going to turn it off. >>I would say, I would say as, as educators, it's really important for us to stay on top of how the field is evolving, right? So what we want to do is we want to promote these tight connections between educators and our faculty and, um, applied research in industry and with industry partnerships. And I think that's how we're going to make sure that we're educating students in the best way. And you're talking about that inner, that confluence of the three different areas. And I think you have to keep those communication lines open to make sure that the information on where the field is going and what we need to concentrate on is flowing down into our educational process. And that, that works in both ways that, you know, we can talk as educators and we can be telling industry what we're working on and what are types of skills our students have and working with them to get the opportunities for our students to work in industry and develop those skills along the way as well. >>And I think it's just all part of this is really looking at, at what's going to be happening and how do we get people talking to each other and the same thing with looking at public policy and bringing that into our education and into these real hands on experiences. And that's how you really cement this type of knowledge with students, not by not by talking to them and not by showing them, but letting them do it. It's this learn by doing and building the resiliency that it takes when you learn by doing. And sometimes you learn by failing, but you just up and you keep going. >>And these are important skills that you develop along the way >>You mentioned, um, um, sharing too. That's the key collaborating and sharing knowledge. It's an open, open world and everyone's collaborating feel private public partnerships. I mean, there's a real private companies. You mentioned Palo Alto networks and others. There's a real intersection there there's, they're motivated. They could, the scholarship opportunities, trunk points to that. What is the public private educator view there? How do companies get involved? What's the benefit for them? >>Well, that's what a lot of the universities are doing is to bring in as part of either their cyber centers or institutes, people who are really focused on developing and furthering those public private partnerships. That's really what my role is in all these things is to take us to a different level in those areas, uh, not to take away from the academic side, but to add additional opportunities for both sides. Remember in a public private partnership, all entities have to have some gain in the process. Now, what I think is really interesting is the timing on particularly this subject space and cyber security. This has been an absolute banner year for space. The Stanhope of space force, the launch of commercial partnership, leaving commercial platforms, delivering astronauts to the space station, recovering them and bringing back the ability of a commercial satellite platform to be launched a commercial platforms that not only launch, but return back to where they're launched from. >>These are things that are stirring the hearts of the American citizens, the kids, again, they're getting interested, they're seeing this and getting enthused. So we have to seize upon that and we have to find a way to connect that public private partnerships is the answer for that. It's not one segment that can handle it all. It's all of them combined together. If you look at space, space is going to be about commercial. It's going to be about civil moving from one side of the earth, to the other via space. And it's about government. And what's really cool for us. All those things are in our backyard. Yeah. That's where that public private comes together. The government's involved, the private sector is involved. The educators are involved and we're all looking at the same things and trying to figure out like this forum, what works best to go to the future. >>You know, if people are bored and they want to look for an exciting challenge, he couldn't have laid it out any clearer. It's the most exciting discipline. It hits everything. I mean, we just talk about space. GPS is everything we do is well tested. Do with satellites. >>I have to tell you a story on that, right? We have a very unique GPS story right in our backyard. So our sheriff is the son of the father of GPS for the air force. So you can't get better than that when it comes to being connected to all those platforms. So we, we really want to say, you know, this is so exciting for all of us because >>It gives everybody a job for a long time. >>You know, the kids that don't think tick toxic, exciting, wait til they see what's going on here with you guys, this program, trunk final word on this from the public side, you're at the air force. You're doing research. Are you guys opening it up? Are you integrating into the private and educational sectors? How do you see that formula playing out? And what's the best practice for students and preparing them? >>I think it's the same in athlete university CP in the engineering program will require our students to be final project before graduation. And in this kind of project, we send them out to work in the private industry. The private company got sponsor. Then they get the benefit of having an intern working for them and they get the benefit of reviewing the students as the prospective employee in the future. So it's good for the student to gain practical experience working in this program. Some, some kind of, we call that a core program, some kind, we call that a capstone program and the company will accept the students on a trial PRCS, giving them some assignment and then pay them a little bit of money. So it's good for the student to earn some extra money, to have some experience that they can put on their resume when they apply for the final of the job. >>So the collaboration between university and private sector is really important. We, when I joined a faculty, normally they already exist that connection. It came from. Normally it came from the Dean of engineering who would whine and dine with companies. We work relationship and sign up women, but it's approach to do a good performance so that we can be credibility to continue the relationship with those company and the students that we selected to send to those company. We have to make sure that they will represent the university. Well, they will go a good job and they will make a good impression. >>Thank you very much for great insight, trunk, bill, Amy, amazing topic. I'd like to end this session with each of you to make a statement on the importance of cybersecurity to space. We'll go Trung bill and Amy Truong, the importance of cybersecurity space statement. >>We know that it's affecting components that we are using and we are connecting to. And normally we use them for personal purpose. But when we connect to the important system that the government public company put into space, so it's really important to practice cyber security and a lot of time, it's very easy to know concept. We have to be careful, but in reality, we tend to forget to partnership the way we forget how to ride safely. And with driving a car, we have a program called defensive driving that requires every two or three years to get. We can get discount. >>We are providing the cyber security practice, not to tell people about the technology, but to remind them not practicing cybersecurity. And it's a requirement for every one of us, bill, the importance of cyber security to space. It's not just about young people. It's about all of us as we grow and we change as I referenced it, you know, we're changing from an analog world to a digital world. Those of us who have been in the business and have hair that looks like mine. We need to be just as cognizant about cybersecurity practice as the young people, we need to understand how it affects our lives and particularly in space, because we're going to be talking about people, moving people to space, moving payloads, data, transfer all of those things. And so there's a whole workforce that needs to be retrained or upskilled in cyber that's out there. So the opportunity is ever expensive for all of us, Amy, the importance of cybersecurity space, >>Uh, and the, the emphasis of cybersecurity is space. Just simply, can't be over emphasized. There are so many aspects that are going to have to be considered as systems get ever more complex. And as we pointed out, we're putting people's lives at stake here. This is incredibly, incredibly complicated and incredibly impactful, and actually really exciting the opportunities that are here for students and the workforce of the future to really make an enormous impact on the world around us. And I hope we're able to get that message out to students, to children >>Today. But these are my really interesting fields that you need to consider. >>Thank you very much. I'm John foray with the cube and the importance of cybersecurity and space is the future of the world's all going to happen in and around space with technology, people and society. Thank you to Cal poly. And thank you for watching the Cypress of computer security and space symposium 2020.

>> [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.

>> 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.

>> 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. >> Hi everybody, welcome back to theCUBE's special presentation. We're here at the Western Hotel and the theater district covering IBM's announcements. They've got an analyst meeting today, partner event. They've got a big event tonight. IBM.com/winwithAI, go to that website, if you're in town register. You can watch the webcast online. You'll see this very cool play of Vince Lombardy, one of his famous plays. It's kind of a power sweep right which is a great way to talk about sort of winning and with X's and O's. So anyway, Daniel Hernandez is here the vice president of IBM analytics, long time Cube along. It's great to see you again, thanks for coming on. >> My pleasure Dave. >> So we've talked a number of times. We talked earlier this year. Give us the update on momentum in your business. You guys are doing really well, we see this in the quadrants and the waves, but your perspective. >> Data science and AI, so when we last talked we were just introducing something called IBM Club Private for data. The basic idea is anybody that wants to do data science, data engineering or building apps with data anywhere, we're going to give them a single integrated platform to get that done. It's going to be the most efficient, best way to do those jobs to be done. We introduced it, it's been a resounding success. Been rolling that out with clients, that's been a whole lot of fun. >> So we talked a little bit with Rob Thomas about some of the news that you guys have, but this is really your wheelhouse so I'm going to drill down into each of these. Let's say we had Rob Beerden on yesterday on our program and he talked a lot about the IBM Red Hat and Hortonworks relationship. Certainly they talked about it on their earnings call and there seems to be clear momentum in the marketplace. But give us your perspective on that announcement. What exactly is it all about? I mean it started kind of back in the ODPI days and it's really evolved into something that now customers are taking advantage of. >> You go back to June last year, we entered into a relationship with Hortonworks where the basic primacy, was customers care about data and any data driven initiative was going to require data science. We had to do a better job bringing these eco systems, one focused on kind of Hadoop, the other one on classic enterprise analytical and operational data together. We did that last year. The other element of that was we're going to bring our data science and machine learning tools and run times to where the data is including Hadoop. That's been a resounding success. The next step up is how do we proliferate that single integrated stack everywhere including private Cloud or preferred Clouds like Open Shift. So there was two elements of the announcement. We did the hybrid Cloud architecture initiative which is taking the Hadoop data stack and bringing it to containers and Kubernetes. That's a big deal for people that want to run the infrastructure with Cloud characteristics. And the other was we're going to bring that whole stack onto Open Shift. So on IBM's side, with IBM Cloud Private for data we are driving certification of that entire stack on OpenShift so any customer that's betting on OpenShift as their Cloud infrastructure can benefit from that and the single integrated data stack. It's a pretty big deal. >> So OpenShift is really interesting because OpenShift was kind of quiet for awhile. It was quiest if you will. And then containers come on the scene and OpenShift has just exploded. What are your perspectives on that and what's IBM's angle on OpenShift? >> Containers of Kubernetes basically allow you to get Cloud characteristics everywhere. It used to be locked in to kind of the public Cloud or SCP providers that were offering as a service whether PAS OR IAS and Docker and Kubernetes are making the same underline technology that enabled elasticity, pay as you go models available anywhere including your own data center. So I think it explains why OpenShift, why IBM Cloud Private, why IBM Club Private for data just got on there. >> I mean the Core OS move by Red Hat was genius. They picked that up for the song in our view anyway and it's really helped explode that. And in this world, everybody's talking about Kubernetes. I mean we're here at a big data conference all week. It used to be Hadoop world. Everybody's talking about containers, Kubernetes and Multi cloud. Those are kind of the hot trends. I presume you've seen the same thing. >> 100 percent. There's not a single client that I know, and I spend the majority of my time with clients that are running their workloads in a single stack. And so what do you do? If data is an imperative for you, you better run your data analytic stack wherever you need to and that means Multi cloud by definition. So you've got a choice. You can say, I can port that workload to every distinct programming model and data stack or you can have a data stack everywhere including Multi clouds and Open Shift in this case. >> So thinking about the three companies, so Hortonworks obviously had duped distro specialists, open source, brings that end to end sort of data management from you know Edge, or Clouds on Prim. Red Hat doing a lot of the sort of hardcore infrastructure layer. IBM bringing in the analytics and really empowering people to get insights out of data. Is that the right way to think about that triangle? >> 100 percent and you know with the Hortonworks and IBM data stacks, we've got our common services, particularly you're on open meta data which means wherever your data is, you're going to know about it and you're going to be able to control it. Privacy, security, data discovery reasons, that's a pretty big deal. >> Yeah and as the Cloud, well obviously the Cloud whether it's on Prim or in the public Cloud expands now to the Edge, you've also got this concept of data virtualization. We've talked about this in the past. You guys have made some announcements there. But let's put a double click on that a little bit. What's it all about? >> Data virtualization been going on for a long time. It's basic intent is to help you access data through whatever tools, no matter where the data is. Traditional approaches of data virtualization are pretty limiting. So they work relatively well when you've got small data sets but when you've got highly fragmented data, which is the case in virtually every enterprise that exists a lot of the undermined technology for data virtualization breaks down. Data coming through a single headnote. Ultimately that becomes the critical issue. So you can't take advantage of data virtualization technologies largely because of that when you've got wide scale deployments. We've been incubating technology under this project codename query plex, it was a code name that we used internally and that we were working with Beta clients on and testing it out, validating it technically and it was pretty clear that this is a game changing method for data virtualization that allows you to drive the benefits of accessing your data wherever it is, pushing down queries where the data is and getting benefits of that through highly fragmented data landscape. And so what we've done is take that extremely innovated next generation data virtualization technology include it in our data platform called IBM Club Private for Data, and made it a critical feature inside of that. >> I like that term, query plex, it reminds me of the global sisplex. I go back to the days when actually viewing sort of distributed global systems was very, very challenging and IBM sort of solved that problem. Okay, so what's the secret sauce though of query plex and data virtualization? How does it all work? What's the tech behind it? >> So technically, instead of data coming and getting funneled through one node. If you ever think of your data as kind of a graph of computational data nodes. What query plex does is take advantage of that computational mesh to do queries and analytics. So instead of bringing all the data and funneling it through one of the nodes, and depending on the computational horsepower of that node and all the data being able to get to it, this just federates it out. It distributes out that workload so it's some magic behind the scenes but relatively simple technique. Low computing aggregate, it's probably going to be higher than whatever you can put into that single node. >> And how do customers access these services? How long does it take? >> It would look like a standard query interface to them. So this is all magic behind the scenes. >> Okay and they get this capability as part of what? IBM's >> IBM's Club Private for Data. It's going to be a feature, so this project query plex, is introduced as next generation data virtualization technology which just becomes a part of IBM Club Private for Data. >> Okay and then the other announcement that we talked to Rob, I'd like to understand a little bit more behind it. Actually before we get there, can we talk about the business impact of query plex and data virtualization? Thinking about it, it dramatically simplifies the processes that I have to go through to get data. But more importantly, it helps me get a handle on my data so I can apply machine intelligence. It seems like the innovation sandwich if you will. Data plus AI and then Cloud models for scale and simplicity and that's what's going to drive innovation. So talk about the business impact that people are excited about with regard to query plex. >> Better economics, so in order for you to access your data, you don't have to do ETO in this particular case. So data at rest getting consumed because of this online technology. Two performance, so because of the way this works you're actually going to get faster response times. Three, you're going to be able to query more data simply because this technology allows you to access all your data in a fragmented way without having to consolidate it. >> Okay, so it eliminates steps, right, and gets you time to value and gives you a bigger corporate of data that you can the analyze and drive inside. >> 100 percent. >> Okay, let's talk about stack overflow. You know, Rob took us through a little bit about what that's, what's going on there but why stack overflow, you're targeting developers? Talk to me more about that. >> So stack overflow, 50 million active developers each month on that community. You're a developer and you want to know something, you have to go to stack overflow. You think about data science and AI as disciplines. The idea that that is only dermained to AI and data scientists is very limiting idea. In order for you to actually apply artificial intelligence for whatever your use case is instead of a business it's going to require multiple individuals working together to get that particular outcome done including developers. So instead of having a distinct community for AI that's focused on AI machine developers, why not bring the artificial intelligence community to where the developers already are, which is stack overflow. So, if you go to AI.stackexchange.com, it's going to be the place for you to go to get all your answers to any question around artificial intelligence and of course IBM is going to be there in the community helping out. >> So it's AI.stackexchange.com. You know, it's interesting Daniel that, I mean to talk about digital transformation talking about data. John Furrier said something awhile back about the dots. This is like five or six years ago. He said data is the new development kit and now you guys are essentially targeting developers around AI, obviously a data centric. People trying to put data at the core of the organization. You see that that's a winning strategy. What do you think about that? >> 100 percent, I mean we're the data company instead of IBM, so you're probably asking the wrong guy if you think >> You're biased. (laughing) >> Yeah possibly, but I'm acknowledged. The data over opinions. >> Alright, tell us about tonight what we can expect? I was referencing the Vince Lombardy play here. You know, what's behind that? What are we going to see tonight? >> We were joking a little bit about the old school power eye formation, but that obviously works for your, you're a New England fan aren't you? >> I am actually, if you saw the games this weekend Pat's were in the power eye for quite a bit of the game which I know upset a lot of people. But it works. >> Yeah, maybe we should of used it as a Dallas Cowboy team. But anyways, it's going to be an amazing night. So we're going to have a bunch of clients talking about what they're doing with AI. And so if you're interested in learning what's happening in the industry, kind of perfect event to get it. We're going to do some expert analysis. It will be a little bit of fun breaking down what those customers did to be successful and maybe some tips and tricks that will help you along your way. >> Great, it's right up the street on the west side highway, probably about a mile from the Javis Center people that are at Strata. We've been running programs all week. One of the themes that we talked about, we had an event Tuesday night. We had a bunch of people coming in. There was people from financial services, we had folks from New York State, the city of New York. It was a great meet up and we had a whole conversation got going and one of the things that we talked about and I'd love to get your thoughts and kind of know where you're headed here, but big data to do all that talk and people ask, is that, now at AI, the conversation has moved to AI, is it same wine, new bottle, or is there something substantive here? The consensus was, there's substantive innovation going on. Your thoughts about where that innovation is coming from and what the potential is for clients? >> So if you're going to implement AI for let's say customer care for instance, you're going to be three wrongs griefs. You need data, you need algorithms, you need compute. With a lot of different structure to relate down to capture data wasn't captured until the traditional data systems anchored by Hadoop and big data movement. We landed, we created a data and computational grid for that data today. With all the advancements going on in algorithms particularly in Open Source, you now have, you can build a neuro networks, you can do Cisco machine learning in any language that you want. And bringing those together are exactly the combination that you need to implement any AI system. You already have data and computational grids here. You've got algorithms bringing them together solving some problem that matters to a customer is like the natural next step. >> And despite the skills gap, the skill gaps that we talked about, you're seeing a lot of knowledge transfer from a lot of expertise getting out there into the wild when you follow people like Kirk Born on Twitter you'll see that he'll post like the 20 different models for deep learning and people are starting to share that information. And then that skills gap is closing. Maybe not as fast as some people like but it seems like the industry is paying attention to this and really driving hard to work toward it 'cause it's real. >> Yeah I agree. You're going to have Seth Dulpren, I think it's Niagara, one of our clients. What I like about them is the, in general there's two skill issues. There's one, where does data science and AI help us solve problems that matter in business? That's really a, trying to build a treasure map of potential problems you can solve with a stack. And Seth and Niagara are going to give you a really good basis for the kinds of problems that we can solve. I don't think there's enough of that going on. There's a lot of commentary communication actually work underway in the technical skill problem. You know, how do I actually build these models to do. But there's not enough in how do I, now that I solved that problem, how do we marry it to problems that matter? So the skills gap, you know, we're doing our part with our data science lead team which Seth opens which is telling a customer, pick a hard problem, give us some data, give us some domain experts. We're going to be in the AI and ML experts and we're going to see what happens. So the skill problem is very serious but I don't think it's most people are not having the right conversations about it necessarily. They understand intuitively there's a tech problem but that tech not linked to a business problem matters nothing. >> Yeah it's not insurmountable, I'm glad you mentioned that. We're going to be talking to Niagara Bottling and how they use the data science elite team as an accelerant, to kind of close that gap. And I'm really interested in the knowledge transfer that occurred and of course the one thing about IBM and companies like IBM is you get not only technical skills but you get deep industry expertise as well. Daniel, always great to see you. Love talking about the offerings and going deep. So good luck tonight. We'll see you there and thanks so much for coming on theCUBE. >> My pleasure. >> Alright, keep it right there everybody. This is Dave Vellanti. We'll be back right after this short break. You're watching theCUBE. (upbeat music)

>> PA Announcer: Off the plastic tab, and we'll turn on the colors. Welcome to New Orleans. ♪ This is it ♪ ♪ The part when I say I don't want ya ♪ ♪ I'm stronger than I've been before ♪ ♪ This is the part when I set your free ♪ (New Orleans jazz music) ("When the Saints Go Marching In") (rock music) >> PA Announcer: Ladies and gentleman, would you please welcome state of Louisiana chief design officer Matthew Vince and Choice Hotels director of infrastructure services Stacy Nigh. (rock music) >> Well good morning New Orleans, and welcome to my home state. My name is Matt Vince. I'm the chief design office for state of Louisiana. And it's my pleasure to welcome you all to .Next 2018. State of Louisiana is currently re-architecting our cloud infrastructure and Nutanix is the first domino to fall in our strategy to deliver better services to our citizens. >> And I'd like to second that warm welcome. I'm Stacy Nigh director of infrastructure services for Choice Hotels International. Now you may think you know Choice, but we don't own hotels. We're a technology company. And Nutanix is helping us innovate the way we operate to support our franchisees. This is my first visit to New Orleans and my first .Next. >> Well Stacy, you're in for a treat. New Orleans is known for its fabulous food and its marvelous music, but most importantly the free spirit. >> Well I can't wait, and speaking of free, it's my pleasure to introduce the Nutanix Freedom video, enjoy. ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ Ah, ah, ♪ ♪ Ah, ah, ♪ ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ I'm free, I'm free, I'm free, I'm free ♪ ♪ Gritting your teeth, you hold onto me ♪ ♪ It's never enough, I'm never complete ♪ ♪ Tell me to prove, expect me to lose ♪ ♪ I push it away, I'm trying to move ♪ ♪ I'm desperate to run, I'm desperate to leave ♪ ♪ If I lose it all, at least I'll be free ♪ ♪ Ah, ah ♪ ♪ Ah, ah ♪ ♪ Hallelujah, I'm free ♪ >> PA Announcer: Ladies and gentlemen, please welcome chief marketing officer Ben Gibson ♪ Ah, ah ♪ ♪ Ah, ah ♪ ♪ Hallelujah, I'm free ♪ >> Welcome, good morning. >> Audience: Good morning. >> And welcome to .Next 2018. There's no better way to open up a .Next conference than by hearing from two of our great customers. And Matthew, thank you for welcoming us to this beautiful, your beautiful state and city. And Stacy, this is your first .Next, and I know she's not alone because guess what It's my first .Next too. And I come properly attired. In the front row, you can see my Nutanix socks, and I think my Nutanix blue suit. And I know I'm not alone. I think over 5,000 people in attendance here today are also first timers at .Next. And if you are here for the first time, it's in the morning, let's get moving. I want you to stand up, so we can officially welcome you into the fold. Everyone stand up, first time. All right, welcome. (audience clapping) So you are all joining not just a conference here. This is truly a community. This is a community of the best and brightest in our industry I will humbly say that are coming together to share best ideas, to learn what's happening next, and in particular it's about forwarding not only your projects and your priorities but your careers. There's so much change happening in this industry. It's an opportunity to learn what's coming down the road and learn how you can best position yourself for this whole new world that's happening around cloud computing and modernizing data center environments. And this is not just a community, this is a movement. And it's a movement that started quite awhile ago, but the first .Next conference was in the quiet little town of Miami, and there was about 800 of you in attendance or so. So who in this hall here were at that first .Next conference in Miami? Let me hear from you. (audience members cheering) Yep, well to all of you grizzled veterans of the .Next experience, welcome back. You have started a movement that has grown and this year across many different .Next conferences all over the world, over 20,000 of your community members have come together. And we like to do it in distributed architecture fashion just like here in Nutanix. And so we've spread this movement all over the world with .Next conferences. And this is surging. We're also seeing just today the current count 61,000 certifications and climbing. Our Next community, close to 70,000 active members of our online community because .Next is about this big moment, and it's about every other day and every other week of the year, how we come together and explore. And my favorite stat of all. Here today in this hall amongst the record 5,500 registrations to .Next 2018 representing 71 countries in whole. So it's a global movement. Everyone, welcome. And you know when I got in Sunday night, I was looking at the tweets and the excitement was starting to build and started to see people like Adile coming from Casablanca. Adile wherever you are, welcome buddy. That's a long trip. Thank you so much for coming and being here with us today. I saw other folks coming from Geneva, from Denmark, from Japan, all over the world coming together for this moment. And we are accomplishing phenomenal things together. Because of your trust in us, and because of some early risk candidly that we have all taken together, we've created a movement in the market around modernizing data center environments, radically simplifying how we operate in the services we deliver to our businesses everyday. And this is a movement that we don't just know about this, but the industry is really taking notice. I love this chart. This is Gartner's inaugural hyperconvergence infrastructure magic quadrant chart. And I think if you see where Nutanix is positioned on there, I think you can agree that's a rout, that's a homerun, that's a mic drop so to speak. What do you guys think? (audience clapping) But here's the thing. It says Nutanix up there. We can honestly say this is a win for this hall here. Because, again, without your trust in us and what we've accomplished together and your partnership with us, we're not there. But we are there, and it is thanks to everyone in this hall. Together we have created, expanded, and truly made this market. Congratulations. And you know what, I think we're just getting started. The same innovation, the same catalyst that we drove into the market to converge storage network compute, the next horizon is around multi-cloud. The next horizon is around whether by accident or on purpose the strong move with different workloads moving into public cloud, some into private cloud moving back and forth, the promise of application mobility, the right workload on the right cloud platform with the right economics. Economics is key here. If any of you have a teenager out there, and they have a hold of your credit card, and they're doing something online or the like. You get some surprises at the end of the month. And that surprise comes in the form of spiraling public cloud costs. And this isn't to say we're not going to see a lot of workloads born and running in public cloud, but the opportunity is for us to take a path that regains control over infrastructure, regain control over workloads and where they're run. And the way I look at it for everyone in this hall, it's a journey we're on. It starts with modernizing those data center environments, continues with embracing the full cloud stack and the compelling opportunity to deliver that consumer experience to rapidly offer up enterprise compute services to your internal clients, lines of businesses and then out into the market. It's then about how you standardize across an enterprise cloud environment, that you're not just the infrastructure but the management, the automation, the control, and running any tier one application. I hear this everyday, and I've heard this a lot already this week about customers who are all in with this approach and running those tier one applications on Nutanix. And then it's the promise of not only hyperconverging infrastructure but hyperconverging multiple clouds. And if we do that, this journey the way we see it what we are doing is building your enterprise cloud. And your enterprise cloud is about the private cloud. It's about expanding and managing and taking back control of how you determine what workload to run where, and to make sure there's strong governance and control. And you're radically simplifying what could be an awfully complicated scenario if you don't reclaim and put your arms around that opportunity. Now how do we do this different than anyone else? And this is going to be a big theme that you're going to see from my good friend Sunil and his good friends on the product team. What are we doing together? We're taking all of that legacy complexity, that friction, that inability to be able to move fast because you're chained to old legacy environments. I'm talking to folks that have applications that are 40 years old, and they are concerned to touch them because they're not sure if they can react if their infrastructure can meet the demands of a new, modernized workload. We're making all that complexity invisible. And if all of that is invisible, it allows you to focus on what's next. And that indeed is the spirit of this conference. So if the what is enterprise cloud, and the how we do it different is by making infrastructure invisible, data centers, clouds, then why are we all here today? What is the binding principle that spiritually, that emotionally brings us all together? And we think it's a very simple, powerful word, and that word is freedom. And when we think about freedom, we think about as we work together the freedom to build the data center that you've always wanted to build. It's about freedom to run the applications where you choose based on the information and the context that wasn't available before. It's about the freedom of choice to choose the right cloud platform for the right application, and again to avoid a lot of these spiraling costs in unanticipated surprises whether it be around security, whether it be around economics or governance that come to the forefront. It's about the freedom to invent. It's why we got into this industry in the first place. We want to create. We want to build things not keep the lights on, not be chained to mundane tasks day by day. And it's about the freedom to play. And I hear this time and time again. My favorite tweet from a Nutanix customer to this day is just updated a lot of nodes at 38,000 feed on United Wifi, on my way to spend vacation with my family. Freedom to play. This to me is emotionally what brings us all together and what you saw with the Freedom video earlier, and what you see here is this new story because we want to go out and spread the word and not only talk about the enterprise cloud, not only talk about how we do it better, but talk about why it's so compelling to be a part of this hall here today. Now just one note of housekeeping for everyone out there in case I don't want anyone to take a wrong turn as they come to this beautiful convention center here today. A lot of freedom going on in this convention center. As luck may have it, there's another conference going on a little bit down that way based on another high growth, disruptive industry. Now MJBizCon Next, and by coincidence it's also called next. And I have to admire the creativity. I have to admire that we do share a, hey, high growth business model here. And in case you're not quite sure what this conference is about. I'm the head of marketing here. I have to show the tagline of this. And I read the tagline from license to launch and beyond, the future of the, now if I can replace that blank with our industry, I don't know, to me it sounds like a new, cool Sunil product launch. Maybe launching a new subscription service or the like. Stay tuned, you never know. I think they're going to have a good time over there. I know we're going to have a wonderful week here both to learn as well as have a lot of fun particularly in our customer appreciation event tonight. I want to spend a very few important moments on .Heart. .Heart is Nutanix's initiative to promote diversity in the technology arena. In particular, we have a focus on advancing the careers of women and young girls that we want to encourage to move into STEM and high tech careers. You have the opportunity to engage this week with this important initiative. Please role the video, and let's learn more about how you can do so. >> Video Plays (electronic music) >> So all of you have received these .Heart tokens. You have the freedom to go and choose which of the four deserving charities can receive donations to really advance our cause. So I thank you for your engagement there. And this community is behind .Heart. And it's a very important one. So thank you for that. .Next is not the community, the moment it is without our wonderful partners. These are our amazing sponsors. Yes, it's about sponsorship. It's also about how we integrate together, how we innovate together, and we're about an open community. And so I want to thank all of these names up here for your wonderful sponsorship of this event. I encourage everyone here in this room to spend time, get acquainted, get reacquainted, learn how we can make wonderful music happen together, wonderful music here in New Orleans happen together. .Next isn't .Next with a few cool surprises. Surprise number one, we have a contest. This is a still shot from the Freedom video you saw right before I came on. We have strategically placed a lucky seven Nutanix Easter eggs in this video. And if you go to Nutanix.com/freedom, watch the video. You may have to use the little scrubbing feature to slow down 'cause some of these happen quickly. You're going to find some fun, clever Easter eggs. List all seven, tweet that out, or as many as you can, tweet that out with hashtag nextconf, C, O, N, F, and we'll have a random drawing for an all expenses paid free trip to .Next 2019. And just to make sure everyone understands Easter egg concept. There's an eighth one here that's actually someone that's quite famous in our circles. If you see on this still shot, there's someone in the back there with a red jacket on. That's not just anyone. We're targeting in here. That is our very own Julie O'Brien, our senior vice president of corporate marketing. And you're going to hear from Julie later on here at .Next. But Julie and her team are the engine and the creativity behind not only our new Freedom campaign but more importantly everything that you experience here this week. Julie and her team are amazing, and we can't wait for you to experience what they've pulled together for you. Another surprise, if you go and visit our Freedom booths and share your stories. So they're like video booths, you share your success stories, your partnerships, your journey that I talked about, you will be entered to win a beautiful Nutanix brand compliant, look at those beautiful colors, bicycle. And it's not just any bicycle. It's a beautiful bicycle made by our beautiful customer Trek. I actually have a Trek bike. I love cycling. Unfortunately, I'm not eligible, but all of you are. So please share your stories in the Freedom Nutanix's booths and put yourself in the running, or in the cycling to get this prize. One more thing I wanted to share here. Yesterday we had a great time. We had our inaugural Nutanix hackathon. This hackathon brought together folks that were in devops practices, many of you that are in this room. We sold out. We thought maybe we'd get four or five teams. We had to shutdown at 14 teams that were paired together with a Nutanix mentor, and you coded. You used our REST APIs. You built new apps that integrated in with Prism and Clam. And it was wonderful to see this. Everyone I talked to had a great time on this. We had three winners. In third place, we had team Copper or team bronze, but team Copper. Silver, Not That Special, they're very humble kind of like one of our key mission statements. And the grand prize winner was We Did It All for the Cookies. And you saw them coming in on our Mardi Gras float here. We Did It All for Cookies, they did this very creative job. They leveraged an Apple Watch. They were lighting up VMs at a moments notice utilizing a lot of their coding skills. Congratulations to all three, first, second, and third all receive $2,500. And then each of them, then were able to choose a charity to deliver another $2,500 including Ronald McDonald House for the winner, we did it all for the McDonald Land cookies, I suppose, to move forward. So look for us to do more of these kinds of events because we want to bring together infrastructure and application development, and this is a great, I think, start for us in this community to be able to do so. With that, who's ready to hear form Dheeraj? You ready to hear from Dheeraj? (audience clapping) I'm ready to hear from Dheeraj, and not just 'cause I work for him. It is my distinct pleasure to welcome on the stage our CEO, cofounder and chairman Dheeraj Pandey. ("Free" by Broods) ♪ Hallelujah, I'm free ♪ >> Thank you Ben and good morning everyone. >> Audience: Good morning. >> Thank you so much for being here. It's just such an elation when I'm thinking about the Mardi Gras crowd that came here, the partners, the customers, the NTCs. I mean there's some great NTCs up there I could relate to because they're on Slack as well. How many of you are in Slack Nutanix internal Slack channel? Probably 5%, would love to actually see this community grow from here 'cause this is not the only even we would love to meet you. We would love to actually do this in a real time bite size communication on our own internal Slack channel itself. Now today, we're going to talk about a lot of things, but a lot of hard things, a lot of things that take time to build and have evolved as the industry itself has evolved. And one of the hard things that I want to talk about is multi-cloud. Multi-cloud is a really hard problem 'cause it's full of paradoxes. It's really about doing things that you believe are opposites of each other. It's about frictionless, but it's also about governance. It's about being simple, and it's also about being secure at the same time. It's about delight, it's about reducing waste, it's about owning, and renting, and finally it's also about core and edge. How do you really make this big at a core data center whether it's public or private? Or how do you really shrink it down to one or two nodes at the edge because that's where your machines are, that's where your people are? So this is a really hard problem. And as you hear from Sunil and the gang there, you'll realize how we've actually evolved our solutions to really cater to some of these. One of the approaches that we have used to really solve some of these hard problems is to have machines do more, and I said a lot of things in those four words, have machines do more. Because if you double-click on that sentence, it really means we're letting design be at the core of this. And how do you really design data centers, how do you really design products for the data center that hush all the escalations, the details, the complexities, use machine-learning and AI and you know figure our anomaly detection and correlations and patter matching? There's a ton of things that you need to do to really have machines do more. But along the way, the important lesson is to make machines invisible because when machines become invisible, it actually makes something else visible. It makes you visible. It makes governance visible. It makes applications visible, and it makes services visible. A lot of things, it makes teams visible, careers visible. So while we're really talking about invisibility of machines, we're talking about visibility of people. And that's how we really brought all of you together in this conference as well because it makes all of us shine including our products, and your careers, and your teams as well. And I try to define the word customer success. You know it's one of the favorite words that I'm actually using. We've just hired a great leader in customer success recently who's really going to focus on this relatively hard problem, yet another hard problem of customer success. We think that customer success, true customer success is possible when we have machines tend towards invisibility. But along the way when we do that, make humans tend towards freedom. So that's the real connection, the yin-yang of machines and humans that Nutanix is really all about. And that's why design is at the core of this company. And when I say design, I mean reducing friction. And it's really about reducing friction. And everything we do, the most mundane of things which could be about migrating applications, spinning up VMs, self-service portals, automatic upgrades, and automatic scale out, and all the things we do is about reducing friction which really makes machines become invisible and humans gain freedom. Now one of the other convictions we have is how all of us are really tied at the hip. You know our success is tied to your success. If we make you successful, and when I say you, I really mean Main Street. Main Street being customers, and partners, and employees. If we make all of you successful, then we automatically become successful. And very coincidentally, Main Street and Wall Street are also tied in that very same relation as well. If we do a great job at Main Street, I think the Wall Street customer, i.e. the investor, will take care of itself. You'll have you know taken care of their success if we took care of Main Street success itself. And that's the narrative that our CFO Dustin Williams actually went and painted to our Wall Street investors two months ago at our investor day conference. We talked about a $3 billion number. We said look as a company, as a software company, we can go and achieve $3 billion in billings three years from now. And it was a telling moment for the company. It was really about talking about where we could be three years from now. But it was not based on a hunch. It was based on what we thought was customer success. Now realize that $3 billion in pure software. There's only 10 to 15 companies in the world that actually have that kind of software billings number itself. But at the core of this confidence was customer success, was the fact that we were doing a really good job of not over promising and under delivering but under promising starting with small systems and growing the trust of the customers over time. And this is one of the statistics we actually talk about is repeat business. The first dollar that a Global 2000 customer spends in Nutanix, and if we go and increase their trust 15 times by year six, and we hope to actually get 17 1/2 and 19 times more trust in the years seven and eight. It's very similar numbers for non Global 2000 as well. Again, we go and really hustle for customer success, start small, have you not worry about paying millions of dollars upfront. You know start with systems that pay as they grow, you pay as they grow, and that's the way we gain trust. We have the same non Global 2000 pay $6 1/2 for the first dollar they've actually spent on us. And with this, I think the most telling moment was when Dustin concluded. And this is key to this audience here as well. Is how the current cohorts which is this audience here and many of them were not here will actually carry the weight of $3 billion, more than 50% of it if we did a great job of customer success. If we were humble and honest and we really figured out what it meant to take care of you, and if we really understood what starting small was and having to gain the trust with you over time, we think that more than 50% of that billings will actually come from this audience here without even looking at new logos outside. So that's the trust of customer success for us, and it takes care of pretty much every customer not just the Main Street customer. It takes care of Wall Street customer. It takes care of employees. It takes care of partners as well. Now before I talk about technology and products, I want to take a step back 'cause many of you are new in this audience. And I think that it behooves us to really talk about the history of this company. Like we've done a lot of things that started out as science projects. In fact, I see some tweets out there and people actually laugh at Nutanix cloud. And this is where we were in 2012. So if you take a step back and think about where the company was almost seven, eight years ago, we were up against giants. There was a $30 billion industry around network attached storage, and storage area networks and blade servers, and hypervisors, and systems management software and so on. So what did we start out with? Very simple premise that we will collapse the architecture of the data center because three tier is wasteful and three tier is not delightful. It was a very simple hunch, we said we'll take rack mount servers, we'll put a layer of software on top of it, and that layer of software back then only did storage. It didn't do networks and security, and it ran on top of a well known hypervisor from VMware. And we said there's one non negotiable thing. The fact that the design must change. The control plane for this data center cannot be the old control plane. It has to be rethought through, and that's why Prism came about. Now we went and hustled hard to add more things to it. We said we need to make this diverse because it can't just be for one application. We need to make it CPU heavy, and memory heavy, and storage heavy, and flash heavy and so on. And we built a highly configurable HCI. Now all of them are actually configurable as you know of today. And this was not just innovation in technologies, it was innovation in business and sizing, capacity planning, quote to cash business processes. A lot of stuff that we had to do to make this highly configurable, so you can really scale capacity and performance independent of each other. Then in 2014, we did something that was very counterintuitive, but we've done this on, and on, and on again. People said why are you disrupting yourself? You know you've been doing a good job of shipping appliances, but we also had the conviction that HCI was not about hardware. It was about a form factor, but it was really about an operating system. And we started to compete with ourselves when we said you know what we'll do arm's length distribution, we'll do arm's length delivery of products when we give our software to our Dell partner, to Dell as a partner, a loyal partner. But at the same time, it was actually seen with a lot of skepticism. You know these guys are wondering how to really make themselves vanish because they're competing with themselves. But we also knew that if we didn't compete with ourselves someone else will. Now one of the most controversial decisions was really going and doing yet another hypervisor. In the year 2015, it was really preposterous to build yet another hypervisor. It was a very mature market. This was coming probably 15 years too late to the market, or at least 10 years too late to market. And most people said it shouldn't be done because hypervisor is a commodity. And that's the word we latched on to. That this commodity should not have to be paid for. It shouldn't have a team of people managing it. It should actually be part of your overall stack, but it should be invisible. Just like storage needs to be invisible, virtualization needs to be invisible. But it was a bold step, and I think you know at least when we look at our current numbers, 1/3rd of our customers are actually using AHV. At least every quarter that we look at it, our new deployments, at least 35% of it is actually being used on AHV itself. And again, a very preposterous thing to have said five years ago, four years ago to where we've actually come. Thank you so much for all of you who've believed in the fact that virtualization software must be invisible and therefore we should actually try out something that is called AHV today. Now we went and added Lenovo to our OEM mix, started to become even more of a software company in the year 2016. Went and added HP and Cisco in some of very large deals that we talk about in earnings call, our HP deals and Cisco deals. And some very large customers who have procured ELAs from us, enterprise license agreements from us where they want to mix and match hardware. They want to mix Dell hardware with HP hardware but have common standard Nutanix entitlements. And finally, I think this was another one of those moments where we say why should HCI be only limited to X86. You know this operating systems deserves to run on a non X86 architecture as well. And that gave birth to this idea of HCI and Power Systems from IBM. And we've done a great job of really innovating with them in the last three, four quarters. Some amazing innovation that has come out where you can now run AIX 7.x on Nutanix. And for the first time in the history of data center, you can actually have a single software not just a data plane but a control plane where you can manage an IBM farm, an Power farm, and open Power farm and an X86 farm from the same control plane and have you know the IBM farm feed storage to an Intel compute farm and vice versa. So really good things that we've actually done. Now along the way, something else was going on while we were really busy building the private cloud, we knew there was a new consumption model on computing itself. People were renting computing using credit cards. This is the era of the millennials. They were like really want to bypass people because at the end of the day, you know why can't computing be consumed the way like eCommerce is? And that devops movement made us realize that we need to add to our stack. That stack will now have other computing clouds that is AWS and Azure and GCP now. So similar to the way we did Prism. You know Prism was really about going and making hypervisors invisible. You know we went ahead and said we'll add Calm to our portfolio because Calm is now going to be what Prism was to us back when we were really dealing with multi hypervisor world. Now it's going to be multi-cloud world. You know it's one of those things we had a gut around, and we really come to expect a lot of feedback and real innovation. I mean yesterday when we had the hackathon. The center, the epicenter of the discussion was Calm, was how do you automate on multiple clouds without having to write a single line of code? So we've come a long way since the acquisition of Calm two years ago. I think it's going to be a strong pillar in our overall product portfolio itself. Now the word multi-cloud is going to be used and over used. In fact, it's going to be blurring its lines with the idea of hyperconvergence of clouds, you know what does it mean. We just hope that hyperconvergence, the way it's called today will morph to become hyperconverged clouds not just hyperconverged boxes which is a software defined infrastructure definition itself. But let's focus on the why of multi-cloud. Why do we think it can't all go into a public cloud itself? The one big reason is just laws of the land. There's data sovereignty and computing sovereignty, regulations and compliance because of which you need to be in where the government with the regulations where the compliance rules want you to be. And by the way, that's just one reason why the cloud will have to disperse itself. It can't just be 10, 20 large data centers around the world itself because you have 200 plus countries and half of computing actually gets done outside the US itself. So it's a really important, very relevant point about the why of multi-cloud. The second one is just simple laws of physics. You know if there're machines at the edge, and they're producing so much data, you can't bring all the data to the compute. You have to take the compute which is stateless, it's an app. You take the app to where the data is because the network is the enemy. The network has always been the enemy. And when we thought we've made fatter networks, you've just produced more data as well. So this just goes without saying that you take something that's stateless that's without gravity, that's lightweight which is compute and the application and push it close to where the data itself is. And the third one which is related is just latency reasons you know? And it's not just about machine latency and electrons transferring over the speed light, and you can't defy the speed of light. It's also about human latency. It's also about multiple teams saying we need to federate and delegate, and we need to push things down to where the teams are as opposed to having to expect everybody to come to a very large computing power itself. So all the ways, the way they are, there will be at least three different ways of looking at multi-cloud itself. There's a centralized core cloud. We all go and relate to this because we've seen large data centers and so on. And that's the back office workhorse. It will crunch numbers. It will do processing. It will do a ton of things that will go and produce results for you know how we run our businesses, but there's also the dispersal of the cloud, so ROBO cloud. And this is the front office server that's really serving. It's a cloud that's going to serve people. It's going to be closer to people, and that's what a ROBO cloud is. We have a ton of customers out here who actually use Nutanix and the ROBO environments themselves as one node, two node, three node, five node servers, and it just collapses the entire server closet room in these ROBOs into something really, really small and minuscule. And finally, there's going to be another dispersed edge cloud because that's where the machines are, that's where the data is. And there's going to be an IOT machine fog because we need to miniaturize computing to something even smaller, maybe something that can really land in the palm in a mini server which is a PC like server, but you need to run everything that's enterprise grade. You should be able to go and upgrade them and monitor them and analyze them. You know do enough computing up there, maybe event-based processing that can actually happen. In fact, there's some great innovation that we've done at the edge with IOTs that I'd love for all of you to actually attend some sessions around as well. So with that being said, we have a hole in the stack. And that hole is probably one of the hardest problems that we've been trying to solve for the last two years. And Sunil will talk a lot about that. This idea of hybrid. The hybrid of multi-cloud is one of the hardest problems. Why? Because we're talking about really blurring the lines with owning and renting where you have a single-tenant environment which is your data center, and a multi-tenant environment which is the service providers data center, and the two must look like the same. And the two must look like the same is that hard a problem not just for burst out capacity, not just for security, not just for identity but also for networks. Like how do you blur the lines between networks? How do you blur the lines for storage? How do you really blur the lines for a single pane of glass where you can think of availability zones that look highly symmetric even though they're not because one of 'em is owned by you, and it's single-tenant. The other one is not owned by you, that's multi-tenant itself. So there's some really hard problems in hybrid that you'll hear Sunil talk about and the team. And some great strides that we've actually made in the last 12 months of really working on Xi itself. And that completes the picture now in terms of how we believe the state of computing will be going forward. So what are the must haves of a multi-cloud operating system? We talked about marketplace which is catalogs and automation. There's a ton of orchestration that needs to be done for multi-cloud to come together because now you have a self-service portal which is providing an eCommerce view. It's really about you know getting to do a lot of requests and workflows without having people come in the way, without even having tickets. There's no need for tickets if you can really start to think like a self-service portal as if you're just transacting eCommerce with machines and portals themselves. Obviously the next one is networking security. You need to blur the lines between on-prem and off-prem itself. These two play a huge role. And there's going to be a ton of details that you'll see Sunil talk about. But finally, what I want to focus on the rest of the talk itself here is what governance and compliance. This is a hard problem, and it's a hard problem because things have evolved. So I'm going to take a step back. Last 30 years of computing, how have consumption models changed? So think about it. 30 years ago, we were making decisions for 10 plus years, you know? Mainframe, at least 10 years, probably 20 plus years worth of decisions. These were decisions that were extremely waterfall-ish. Make 10s of millions of dollars worth of investment for a device that we'd buy for at least 10 to 20 years. Now as we moved to client-server, that thing actually shrunk. Now you're talking about five years worth of decisions, and these things were smaller. So there's a little bit more velocity in our decisions. We were not making as waterfall-ish decision as we used to with mainframes. But still five years, talk about virtualized, three tier, maybe three to five year decisions. You know they're still relatively big decisions that we were making with computer and storage and SAN fabrics and virtualization software and systems management software and so on. And here comes Nutanix, and we said no, no. We need to make it smaller. It has to become smaller because you know we need to make more agile decisions. We need to add machines every week, every month as opposed to adding you know machines every three to five years. And we need to be able to upgrade them, you know any point in time. You can do the upgrades every month if you had to, every week if you had to and so on. So really about more agility. And yet, we were not complete because there's another evolution going on, off-prem in the public cloud where people are going and doing reserved instances. But more than that, they were doing on demand stuff which no the decision was days to weeks. Some of these things that unitive compute was being rented for days to weeks, not years. And if you needed something more, you'd shift a little to the left and use reserved instances. And then spot pricing, you could do spot pricing for hours and finally lambda functions. Now you could to function as a service where things could actually be running only for minutes not even hours. So as you can see, there's a wide spectrum where when you move to the right, you get more elasticity, and when you move to the left, you're talking about predictable decision making. And in fact, it goes from minutes on one side to 10s of years on the other itself. And we hope to actually go and blur the lines between where NTNX is today where you see Nutanix right now to where we really want to be with reserved instances and on demand. And that's the real ask of Nutanix. How do you take care of this discontinuity? Because when you're owning things, you actually end up here, and when you're renting things, you end up here. What does it mean to really blur the lines between these two because people do want to make decisions that are better than reserved instance in the public cloud. We'll talk about why reserved instances which looks like a proxy for Nutanix it's still very, very wasteful even though you might think it's delightful, it's very, very wasteful. So what does it mean for on-prem and off-prem? You know you talk about cost governance, there's security compliance. These high velocity decisions we're actually making you know where sometimes you could be right with cost but wrong on security, but sometimes you could be right in security but wrong on cost. We need to really figure out how machines make some of these decisions for us, how software helps us decide do we have the right balance between cost, governance, and security compliance itself? And to get it right, we have introduced our first SAS service called Beam. And to talk more about Beam, I want to introduce Vijay Rayapati who's the general manager of Beam engineering to come up on stage and talk about Beam itself. Thank you Vijay. (rock music) So you've been here a couple of months now? >> Yes. >> At the same time, you spent the last seven, eight years really handling AWS. Tell us more about it. >> Yeah so we spent a lot of time trying to understand the last five years at Minjar you know how customers are really consuming in this new world for their workloads. So essentially what we tried to do is understand the consumption models, workload patterns, and also build algorithms and apply intelligence to say how can we lower this cost and you know improve compliance of their workloads.? And now with Nutanix what we're trying to do is how can we converge this consumption, right? Because what happens here is most customers start with on demand kind of consumption thinking it's really easy, but the total cost of ownership is so high as the workload elasticity increases, people go towards spot or a scaling, but then you need a lot more automation that something like Calm can help them. But predictability of the workload increases, then you need to move towards reserved instances, right to lower costs. >> And those are some of the things that you go and advise with some of the software that you folks have actually written. >> But there's a lot of waste even in the reserved instances because what happens it while customers make these commitments for a year or three years, what we see across, like we track a billion dollars in public cloud consumption you know as a Beam, and customers use 20%, 25% of utilization of their commitments, right? So how can you really apply, take the data of consumption you know apply intelligence to essentially reduce their you know overall cost of ownership. >> You said something that's very telling. You said reserved instances even though they're supposed to save are still only 20%, 25% utilized. >> Yes, because the workloads are very dynamic. And the next thing is you can't do hot add CPU or hot add memory because you're buying them for peak capacity. There is no convergence of scaling that apart from the scaling as another node. >> So you actually sized it for peak, but then using 20%, 30%, you're still paying for the peak. >> That's right. >> Dheeraj: That can actually add up. >> That's what we're trying to say. How can we deliver visibility across clouds? You know how can we deliver optimization across clouds and consumption models and bring the control while retaining that agility and demand elasticity? >> That's great. So you want to show us something? >> Yeah absolutely. So this is Beam as just Dheeraj outlined, our first SAS service. And this is my first .Next. And you know glad to be here. So what you see here is a global consumption you know for a business across different clouds. Whether that's in a public cloud like Amazon, or Azure, or Nutanix. We kind of bring the consumption together for the month, the recent month across your accounts and services and apply intelligence to say you know what is your spent efficiency across these clouds? Essentially there's a lot of intelligence that goes in to detect your workloads and consumption model to say if you're spending $100, how efficiently are you spending? How can you increase that? >> So you have a centralized view where you're looking at multiple clouds, and you know you talk about maybe you can take an example of an account and start looking at it? >> Yes, let's go into a cloud provider like you know for this business, let's go and take a loot at what's happening inside an Amazon cloud. Here we get into the deeper details of what's happening with the consumption of a specific services as well as the utilization of both on demand and RI. You know what can you do to lower your cost and detect your spend efficiency of a dollar to see you know are there resources that are provisioned by teams for applications that are not being used, or are there resources that we should go and rightsize because you know we have all this monitoring data, configuration data that we crunch through to basically detect this? >> You think there's billions of events that you look at everyday. You're already looking at a billon dollars worth of AWS spend. >> Right, right. >> So billions of events, billing, metering events every year to really figure out and optimize for them. >> So what we have here is a very popular international government organization. >> Dheeraj: Wow, so it looks like Russians are everywhere, the cloud is everywhere actually. >> Yes, it's quite popular. So when you bring your master account into Beam, we kind of detect all the linked accounts you know under that. Then you can go and take a look at not just at the organization level within it an account level. >> So these are child objects, you know. >> That's right. >> You can think of them as ephemeral accounts that you create because you don't want to be on the record when you're doing spams on Facebook for example. >> Right, let's go and take a look at what's happening inside a Facebook ad spend account. So we have you know consumption of the services. Let's go deeper into compute consumption, and you kind of see a trendline. You can do a lot of computing. As you see, looks like one campaign has ended. They started another campaign. >> Dheeraj: It looks like they're not stopping yet, man. There's a lot of money being made in Facebook right now. (Vijay laughing) >> So not only just get visibility at you know compute as a service inside a cloud provider, you can go deeper inside compute and say you know what is a service that I'm really consuming inside compute along with the CPUs n'stuff, right? What is my data transfer? You know what is my network? What is my load blancers? So essentially you get a very deeper visibility you know as a service right. Because we have three goals for Beam. How can we deliver visibility across clouds? How can we deliver visibility across services? And how can we deliver, then optimization? >> Well I think one thing that I just want to point out is how this SAS application was an extremely teachable moment for me to learn about the different resources that people could use about the public cloud. So all of you who actually have not gone deep enough into the idea of public cloud. This could be a great app for you to learn about things, the resources, you know things that you could do to save and security and things of that nature. >> Yeah. And we really believe in creating the single pane view you know to mange your optimization of a public cloud. You know as Ben spoke about as a business, you need to have freedom to use any cloud. And that's what Beam delivers. How can you make the right decision for the right workload to use any of the cloud of your choice? >> Dheeraj: How 'about databases? You talked about compute as well but are there other things we could look at? >> Vijay: Yes, let's go and take a look at database consumption. What you see here is they're using inside Facebook ad spending, they're using all databases except Oracle. >> Dheeraj: Wow, looks like Oracle sales folks have been active in Russia as well. (Vijay laughing) >> So what we're seeing here is a global view of you know what is your spend efficiency and which is kind of a scorecard for your business for the dollars that you're spending. And the great thing is Beam kind of brings together you know through its intelligence and algorithms to detect you know how can you rightsize resources and how can you eliminate things that you're not using? And we deliver and one click fix, right? Let's go and take a look at resources that are maybe provisioned for storage and not being used. We deliver the seamless one-click philosophy that Nutanix has to eliminate it. >> So one click, you can actually just pick some of these wasteful things that might be looking delightful because using public cloud, using credit cards, you can go in and just say click fix, and it takes care of things. >> Yeah, and not only remove the resources that are unused, but it can go and rightsize resources across your compute databases, load balancers, even past services, right? And this is where the power of it kind of comes for a business whether you're using on-prem and off-prem. You know how can you really converge that consumption across both? >> Dheeraj: So do you have something for Nutanix too? >> Vijay: Yes, so we have basically been working on Nutanix with something that we're going to deliver you know later this year. As you can see here, we're bringing together the consumption for the Nutanix, you know the services that you're using, the licensing and capacity that is available. And how can you also go and optimize within Nutanix environments >> That's great. >> for the next workload. Now let me quickly show you what we have on the compliance side. This is an extremely powerful thing that we've been working on for many years. What we deliver here just like in cost governance, a global view of your compliance across cloud providers. And the most powerful thing is you can go into a cloud provider, get the next level of visibility across cloud regimes for hundreds of policies. Not just policies but those policies across different regulatory compliances like HIPA, PCI, CAS. And that's very powerful because-- >> So you're saying a lot of what you folks have done is codified these compliance checks in software to make sure that people can sleep better at night knowing that it's PCI, and HIPA, and all that compliance actually comes together? >> And you can build this not just by cloud accounts, you can build them across cloud accounts which is what we call security centers. Essentially you can go and take a deeper look at you know the things. We do a whole full body scan for your cloud infrastructure whether it's AWS Amazon or Azure, and you can go and now, again, click to fix things. You know that had been probably provisioned that are violating the security compliance rules that should be there. Again, we have the same one-click philosophy to say how can you really remove things. >> So again, similar to save, you're saying you can go and fix some of these security issues by just doing one click. >> Absolutely. So the idea is how can we give our people the freedom to get visibility and use the right cloud and take the decisions instantly through one click. That's what Beam delivers you know today. And you know get really excited, and it's available at beam.nutanix.com. >> Our first SAS service, ladies and gentleman. Thank you so much for doing this, Vijay. It looks like there's going to be a talk here at 10:30. You'll talk more about the midterm elections there probably? >> Yes, so you can go and write your own security compliances as well. You know within Beam, and a lot of powerful things you can do. >> Awesome, thank you so much, Vijay. I really appreciate it. (audience clapping) So as you see, there's a lot of work that we're doing to really make multi-cloud which is a hard problem. You know think about working the whole body of it and what about cost governance? What about security compliance? Obviously what about hybrid networks, and security, and storage, you know compute, many of the things that you've actually heard from us, but we're taking it to a level where the business users can now understand the implications. A CFO's office can understand the implications of waste and delight. So what does customer success mean to us? You know again, my favorite word in a long, long time is really go and figure out how do you make you, the customer, become operationally efficient. You know there's a lot of stuff that we deliver through software that's completely uncovered. It's so latent, you don't even know you have it, but you've paid for it. So you've got to figure out what does it mean for you to really become operationally efficient, organizationally proficient. And it's really important for training, education, stuff that you know you're people might think it's so awkward to do in Nutanix, but it could've been way simpler if you just told you a place where you can go and read about it. Of course, I can just use one click here as opposed to doing things the old way. But most importantly to make it financially accountable. So the end in all this is, again, one of the things that I think about all the time in building this company because obviously there's a lot of stuff that we want to do to create orphans, you know things above the line and top line and everything else. There's also a bottom line. Delight and waste are two sides of the same coin. You know when we're talking about developers who seek delight with public cloud at the same time you're looking at IT folks who're trying to figure out governance. They're like look you know the CFOs office, the CIOs office, they're trying to figure out how to curb waste. These two things have to go hand in hand in this era of multi-cloud where we're talking about frictionless consumption but also governance that looks invisible. So I think, at the end of the day, this company will do a lot of stuff around one-click delight but also go and figure out how do you reduce waste because there's so much waste including folks there who actually own Nutanix. There's so much software entitlement. There's so much waste in the public cloud itself that if we don't go and put our arms around, it will not lead to customer success. So to talk more about this, the idea of delight and the idea of waste, I'd like to bring on board a person who I think you know many of you actually have talked about it have delightful hair but probably wasted jokes. But I think has wasted hair and delightful jokes. So ladies and gentlemen, you make the call. You're the jury. Sunil R.M.J. Potti. ("Free" by Broods) >> So that was the first time I came out from the bottom of a screen on a stage. I actually now know what it feels to be like a gopher. Who's that laughing loudly at the back? Okay, do we have the... Let's see. Okay, great. We're about 15 minutes late, so that means we're running right on time. That's normally how we roll at this conference. And we have about three customers and four demos. Like I think there's about three plus six, about nine folks coming onstage. So we'll have our own version of the parade as well on the main stage for the next 70 minutes. So let's just jump right into it. I think we've been pretty consistent in terms of our longterm plans since we started the company. And it's become a lot more clearer over the last few years about our plans to essentially make computing invisible as Dheeraj mentioned. We're doing this across multiple acts. We started with HCI. We call it making infrastructure invisible. We extended that to making data centers invisible. And then now we're in this mode of essentially extending it to converging clouds so that you can actually converge your consumption models. And so today's conference and essentially the theme that you're going to be seeing throughout the breakout sessions is about a journey towards invisible clouds, but make sure that you internalize the fact that we're investing heavily in each of the three phases. It's just not about the hybrid cloud with Nutanix, it's about actually finishing the job about making infrastructure invisible, expanding that to kind of go after the full data center, and then of course embark on some real meaningful things around invisible clouds, okay? And to start the session, I think you know the part that I wanted to make sure that we are all on the same page because most of us in the room are still probably in this phase of the journey which is about invisible infrastructure. And there the three key products and especially two of them that most of you guys know are Acropolis and Prism. And they're sort of like the bedrock of our company. You know especially Acropolis which is about the web scale architecture. Prism is about consumer grade design. And with Acropolis now being really mature. It's in the seventh year of innovation. We still have more than half of our company in terms of R and D spend still on Acropolis and Prism. So our core product is still sort of where we think we have a significant differentiation on. We're not going to let our foot off the peddle there. You know every time somebody comes to me and says look there's a new HCI render popping out or an existing HCI render out there, I ask a simple question to our customers saying show me 100 customers with 100 node deployments, and it will be very hard to find any other render out there that does the same thing. And that's the power of Acropolis the code platform. And then it's you know the fact that the velocity associated with Acropolis continues to be on a fast pace. We came out with various new capabilities in 5.5 and 5.6, and one of the most complicated things to get right was the fact to shrink our three node cluster to a one node, two node deployment. Most of you actually had requirements on remote office, branch office, or the edge that actually allowed us to kind of give us you know sort of like the impetus to kind of go design some new capabilities into our core OS to get this out. And associated with Acropolis and expanding into Prism, as you will see, the first couple of years of Prism was all about refactoring the user interface, doing a good job with automation. But more and more of the investments around Prism is going to be based on machine learning. And you've seen some variants of that over the last 12 months, and I can tell you that in the next 12 to 24 months, most of our investments around infrastructure operations are going to be driven by AI techniques starting with most of our R and D spend also going into machine-learning algorithms. So when you talk about all the enhancements that have come on with Prism whether it be formed by you know the management console changing to become much more automated, whether now we give you automatic rightsizing, anomaly detection, or a series of functionality that have gone into it, the real core sort of capabilities that we're putting into Prism and Acropolis are probably best served by looking at the quality of the product. You probably have seen this slide before. We started showing the number of nodes shipped by Nutanix two years ago at this conference. It was about 35,000 plus nodes at that time. And since then, obviously we've you know continued to grow. And we would draw this line which was about enterprise class quality. That for the number of bugs found as a percentage of nodes shipped, there's a certain line that's drawn. World class companies do about probably 2% to 3%, number of CFDs per node shipped. And we were just broken that number two years ago. And to give you guys an idea of how that curve has shown up, it's now currently at .95%. And so along with velocity, you know this focus on being true to our roots of reliability and stability continues to be, you know it's an internal challenge, but it's also some of the things that we keep a real focus on. And so between Acropolis and Prism, that's sort of like our core focus areas to sort of give us the confidence that look we have this really high bar that we're sort of keeping ourselves accountable to which is about being the most advanced enterprise cloud OS on the planet. And we will keep it this way for the next 10 years. And to complement that, over a period of time of course, we've added a series of services. So these are services not just for VMs but also for files, blocks, containers, but all being delivered in that single one-click operations fashion. And to really talk more about it, and actually probably to show you the real deal there it's my great pleasure to call our own version of Moses inside the company, most of you guys know him as Steve Poitras. Come on up, Steve. (audience clapping) (rock music) >> Thanks Sunil. >> You barely fit in that door, man. Okay, so what are we going to talk about today, Steve? >> Absolutely. So when we think about when Nutanix first got started, it was really focused around VDI deployments, smaller workloads. However over time as we've evolved the product, added additional capabilities and features, that's grown from VDI to business critical applications as well as cloud native apps. So let's go ahead and take a look. >> Sunil: And we'll start with like Oracle? >> Yeah, that's one of the key ones. So here we can see our Prism central user interface, and we can see our Thor cluster obviously speaking to the Avengers theme here. We can see this is doing right around 400,000 IOPs at around 360 microseconds latency. Now obviously Prism central allows you to mange all of your Nutanix deployments, but this is just running on one single Nutanix cluster. So if we hop over here to our explore tab, we can see we have a few categories. We have some Kubernetes, some AFS, some Xen desktop as well as Oracle RAC. Now if we hope over to Oracle RAC, we're running a SLOB workload here. So obviously with Oracle enterprise applications performance, consistency, and extremely low latency are very critical. So with this SLOB workload, we're running right around 300 microseconds of latency. >> Sunil: So this is what, how many node Oracle RAC cluster is this? >> Steve: This is a six node Oracle RAC deployment. >> Sunil: Got it. And so what has gone into the product in recent releases to kind of make this happen? >> Yeah so obviously on the hardware front, there's been a lot of evolutions in storage mediums. So with the introduction of NVME, persistent memory technologies like 3D XPoint, that's meant storage media has become a lot faster. Now to allow you to full take advantage of that, that's where we've had to do a lot of optimizations within the storage stack. So with AHV, we have what we call AHV turbo mode which allows you to full take advantage of those faster storage mediums at that much lower latency. And then obviously on the networking front, technologies such as RDMA can be leveraged to optimize that network stack. >> Got it. So that was Oracle RAC running on a you know Nutanix cluster. It used to be a big deal a couple of years ago. Now we've got many customers doing that. On the same environment though, we're going to show you is the advent of actually putting file services in the same scale out environment. And you know many of you in the audience probably know about AFS. We released it about 12 to 14 months ago. It's been one of our most popular new products of all time within Nutanix's history. And we had SMB support was for user file shares, VDI deployments, and it took awhile to bake, to get to scale and reliability. And then in the last release, in the recent release that we just shipped, we now added NFS for support so that we can no go after the full scale file server consolidation. So let's take a look at some of that stuff. >> Yep, let's do it. So hopping back over to Prism, we can see our four cluster here. Overall cluster-wide latency right around 360 microseconds. Now we'll hop down to our file server section. So here we can see we have our Next A File Server hosting right about 16.2 million files. Now if you look at our shares and exports, we can see we have a mix of different shares. So one of the shares that you see there is home directories. This is an SMB share which is actually mapped and being leveraged by our VDI desktops for home folders, user profiles, things of that nature. We can also see this Oracle backup share here which is exposed to our rack host via NFS. So RMAN is actually leveraging this to provide native database backups. >> Got it. So Oracle VMs, backup using files, or for any other file share requirements with AFS. Do we have the cluster also showing, I know, so I saw some Kubernetes as well on it. Let's talk about what we're thinking of doing there. >> Yep, let's do it. So if we think about cloud, cloud's obviously a big buzz word, so is containers in Kubernetes. So with ACS 1.0 what we did is we introduced native support for Docker integration. >> And pause there. And we screwed up. (laughing) So just like the market took a left turn on Kubernetes, obviously we realized that, and now we're working on ACS 2.0 which is what we're going to talk about, right? >> Exactly. So with ACS 2.0, we've introduced native Kubernetes support. Now when I think about Kubernetes, there's really two core areas that come to mind. The first one is around native integration. So with that, we have our Kubernetes volume integration, we're obviously doing a lot of work on the networking front, and we'll continue to push there from an integration point of view. Now the other piece is around the actual deployment of Kubernetes. When we think about a lot of Nutanix administrators or IT admins, they may have never deployed Kubernetes before, so this could be a very daunting task. And true to the Nutanix nature, we not only want to make our platform simple and intuitive, we also want to do this for any ecosystem products. So with ACS 2.0, we've simplified the full Kubernetes deployment and switching over to our ACS two interface, we can see this create cluster button. Now this actually pops up a full wizard. This wizard will actually walk you through the full deployment process, gather the necessary inputs for you, and in a matter of a few clicks and a few minutes, we have a full Kubernetes deployment fully provisioned, the masters, the workers, all the networking fully done for you, very simple and intuitive. Now if we hop back over to Prism, we can see we have this ACS2 Kubernetes category. Clicking on that, we can see we have eight instances of virtual machines. And here are Kubernetes virtual machines which have actually been deployed as part of this ACS2 installer. Now one of the nice things is it makes the IT administrator's job very simple and easy to do. The deployment straightforward monitoring and management very straightforward and simple. Now for the developer, the application architect, or engineers, they interface and interact with Kubernetes just like they would traditionally on any platform. >> Got it. So the goal of ACS is to ensure that the developer ecosystem still uses whatever tools that they are you know preferring while at that same time allowing this consolidation of containers along with VMs all on that same, single runtime, right? So that's ACS. And then if you think about where the OS is going, there's still some open space at the end. And open space has always been look if you just look at a public cloud, you look at blocks, files, containers, the most obvious sort of storage function that's left is objects. And that's the last horizon for us in completing the storage stack. And we're going to show you for the first time a preview of an upcoming product called the Acropolis Object Storage Services Stack. So let's talk a little bit about it and then maybe show the demo. >> Yeah, so just like we provided file services with AFS, block services with ABS, with OSS or Object Storage Services, we provide native object storage, compatibility and capability within the Nutanix platform. Now this provides a very simply common S3 API. So any integrations you've done with S3 especially Kubernetes, you can actually leverage that out of the box when you've deployed this. Now if we hop back over to Prism, I'll go here to my object stores menu. And here we can see we have two existing object storage instances which are running. So you can deploy however many of these as you wanted to. Now just like the Kubernetes deployment, deploying a new object instance is very simple and easy to do. So here I'll actually name this instance Thor's Hammer. >> You do know he loses it, right? He hasn't seen the movies yet. >> Yeah, I don't want any spoilers yet. So once we specified the name, we can choose our capacity. So here we'll just specify a large instance or type. Obviously this could be any amount or storage. So if you have a 200 node Nutanix cluster with petabytes worth of data, you could do that as well. Once we've selected that, we'll select our expected performance. And this is going to be the number of concurrent gets and puts. So essentially how many operations per second we want this instance to be able to facilitate. Once we've done that, the platform will actually automatically determine how many virtual machines it needs to deploy as well as the resources and specs for those. And once we've done that, we'll go ahead and click save. Now here we can see it's actually going through doing the deployment of the virtual machines, applying any necessary configuration, and in the matter of a few clicks and a few seconds, we actually have this Thor's Hammer object storage instance which is up and running. Now if we hop over to one of our existing object storage instances, we can see this has three buckets. So one for Kafka-queue, I'm actually using this for my Kafka cluster where I have right around 62 million objects all storing ProtoBus. The second one there is Spark. So I actually have a Spark cluster running on our Kubernetes deployed instance via ACS 2.0. Now this is doing analytics on top of this data using S3 as a storage backend. Now for these objects, we support native versioning, native object encryption as well as worm compliancy. So if you want to have expiry periods, retention intervals, that sort of thing, we can do all that. >> Got it. So essentially what we've just shown you is with upcoming objects as well that the same OS can now support VMs, files, objects, containers, all on the same one click operational fabric. And so that's in some way the real power of Nutanix is to still keep that consistency, scalability in place as we're covering each and every workload inside the enterprise. So before Steve gets off stage though, I wanted to talk to you guys a little bit about something that you know how many of you been to our Nutanix headquarters in San Jose, California? A few. I know there's like, I don't know, 4,000 or 5,000 people here. If you do come to the office, you know when you land in San Jose Airport on the way to longterm parking, you'll pass our office. It's that close. And if you come to the fourth floor, you know one of the cubes that's where I sit. In the cube beside me is Steve. Steve sits in the cube beside me. And when I first joined the company, three or four years ago, and Steve's if you go to his cube, it no longer looks like this, but it used to have a lot of this stuff. It was like big containers of this. I remember the first time. Since I started joking about it, he started reducing it. And then Steve eventually got married much to our surprise. (audience laughing) Much to his wife's surprise. And then he also had a baby as a bigger surprise. And if you come over to our office, and we welcome you, and you come to the fourth floor, find my cube or you'll find Steve's Cube, it now looks like this. Okay, so thanks a lot, my man. >> Cool, thank you. >> Thanks so much. (audience clapping) >> So single OS, any workload. And like Steve who's been with us for awhile, it's my great pleasure to invite one of our favorite customers, CSC Karen who's also been with us for three to four years. And I'll share some fond memories about how she's been with the company for awhile, how as partners we've really done a lot together. So without any further ado, let me bring up Karen. Come on up, Karen. (rock music) >> Thank you for having me. >> Yeah, thank you. So I remember, so how many of you guys were with Nutanix first .Next in Miami? I know there was a question like that asked last time. Not too many. You missed it. We wished we could go back to that. We wouldn't fit 3/4s of this crowd. But Karen was our first customer in the keynote in 2015. And we had just talked about that story at that time where you're just become a customer. Do you want to give us some recap of that? >> Sure. So when we made the decision to move to hyperconverged infrastructure and chose Nutanix as our partner, we rapidly started to deploy. And what I mean by that is Sunil and some of the Nutanix executives had come out to visit with us and talk about their product on a Tuesday. And on a Wednesday after making the decision, I picked up the phone and said you know what I've got to deploy for my VDI cluster. So four nodes showed up on Thursday. And from the time it was plugged in to moving over 300 VDIs and 50 terabytes of storage and turning it over for the business for use was less than three days. So it was really excellent testament to how simple it is to start, and deploy, and utilize the Nutanix infrastructure. Now part of that was the delight that we experienced from our customers after that deployment. So we got phone calls where people were saying this report it used to take so long that I'd got out and get a cup of coffee and come back, and read an article, and do some email, and then finally it would finish. Those reports are running in milliseconds now. It's one click. It's very, very simple, and we've delighted our customers. Now across that journey, we have gone from the simple workloads like VDIs to the much more complex workloads around Splunk and Hadoop. And what's really interesting about our Splunk deployment is we're handling over a billion events being logged everyday. And the deployment is smaller than what we had with a three tiered infrastructure. So when you hear people talk about waste and getting that out and getting to an invisible environment where you're just able to run it, that's what we were able to achieve both with everything that we're running from our public facing websites to the back office operations that we're using which include Splunk and even most recently our Cloudera and Hadoop infrastructure. What it does is it's got 30 crawlers that go out on the internet and start bringing data back. So it comes back with over two terabytes of data everyday. And then that environment, ingests that data, does work against it, and responds to the business. And that again is something that's smaller than what we had on traditional infrastructure, and it's faster and more stable. >> Got it. And it covers a lot of use cases as well. You want to speak a few words on that? >> So the use cases, we're 90%, 95% deployed on Nutanix, and we're covering all of our use cases. So whether that's a customer facing app or a back office application. And what are business is doing is it's handling large portfolios of data for fortune 500 companies and law firms. And these applications are all running with improved stability, reliability, and performance on the Nutanix infrastructure. >> And the plan going forward? >> So the plan going forward, you actually asked me that in Miami, and it's go global. So when we started in Miami and that first deployment, we had four nodes. We now have 283 nodes around the world, and we started with about 50 terabytes of data. We've now got 3.8 petabytes of data. And we're deployed across four data centers and six remote offices. And people ask me often what is the value that we achieved? So simplification. It's all just easier, and it's all less expensive. Being able to scale with the business. So our Cloudera environment ended up with one day where it spiked to 1,000 times more load, 1,000 times, and it just responded. We had rally cries around improved productivity by six times. So 600% improved productivity, and we were able to actually achieve that. The numbers you just saw on the slide that was very, very fast was we calculated a 40% reduction in total cost of ownership. We've exceeded that. And when we talk about waste, that other number on the board there is when I saved the company one hour of maintenance activity or unplanned downtime in a month which we're now able to do the majority of our maintenance activities without disrupting any of our business solutions, I'm saving $750,000 each time I save that one hour. >> Wow. All right, Karen from CSE. Thank you so much. That was great. Thank you. I mean you know some of these data points frankly as I started talking to Karen as well as some other customers are pretty amazing in terms of the genuine value beyond financial value. Kind of like the emotional sort of benefits that good products deliver to some of our customers. And I think that's one of the core things that we take back into engineering is to keep ourselves honest on either velocity or quality even hiring people and so forth. Is to actually the more we touch customers lives, the more we touch our partner's lives, the more it allows us to ensure that we can put ourselves in their shoes to kind of make sure that we're doing the right thing in terms of the product. So that was the first part, invisible infrastructure. And our goal, as we've always talked about, our true North is to make sure that this single OS can be an exact replica, a truly modern, thoughtful but original design that brings the power of public cloud this AWS or GCP like architectures into your mainstream enterprises. And so when we take that to the next level which is about expanding the scope to go beyond invisible infrastructure to invisible data centers, it starts with a few things. Obviously, it starts with virtualization and a level of intelligent management, extends to automation, and then as we'll talk about, we have to embark on encompassing the network. And that's what we'll talk about with Flow. But to start this, let me again go back to one of our core products which is the bedrock of our you know opinionated design inside this company which is Prism and Acropolis. And Prism provides, I mentioned, comes with a ton of machine-learning based intelligence built into the product in 5.6 we've done a ton of work. In fact, a lot of features are coming out now because now that PC, Prism Central that you know has been decoupled from our mainstream release strain and will continue to release on its own cadence. And the same thing when you actually flip it to AHV on its own train. Now AHV, two years ago it was all about can I use AHV for VDI? Can I use AHV for ROBO? Now I'm pretty clear about where you cannot use AHV. If you need memory overcome it, stay with VMware or something. If you need, you know Metro, stay with another technology, else it's game on, right? And if you really look at the adoption of AHV in the mainstream enterprise, the customers now speak for themselves. These are all examples of large global enterprises with multimillion dollar ELAs in play that have now been switched over. Like I'll give you a simple example here, and there's lots of these that I'm sure many of you who are in the audience that are in this camp, but when you look at the breakout sessions in the pods, you'll get a sense of this. But I'll give you one simple example. If you look at the online payment company. I'm pretty sure everybody's used this at one time or the other. They had the world's largest private cloud on open stack, 21,000 nodes. And they were actually public about it three or four years ago. And in the last year and a half, they put us through a rigorous VOC testing scale, hardening, and it's a full blown AHV only stack. And they've started cutting over. Obviously they're not there yet completely, but they're now literally in hundreds of nodes of deployment of Nutanix with AHV as their primary operating system. So it is primetime from a deployment perspective. And with that as the base, no cloud is complete without actually having self-service provisioning that truly drives one-click automation, and can you do that in this consumer grade design? And Calm was acquired, as you guys know, in 2016. We had a choice of taking Calm. It was reasonably feature complete. It supported multiple clouds. It supported ESX, it supported Brownfield, It supported AHV. I mean they'd already done the integration with Nutanix even before the acquisition. And we had a choice. The choice was go down the path of dynamic ops or some other products where you took it for revenue or for acceleration, you plopped it into the ecosystem and sold it at this power sucking alien on top of our stack, right? Or we took a step back, re-engineered the product, kept some of the core essence like the workflow engine which was good, the automation, the object model and all, but refactored it to make it look like a natural extension of our operating system. And that's what we did with Calm. And we just launched it in December, and it's been one of our most popular new products now that's flying off the shelves. If you saw the number of registrants, I got a notification of this for the breakout sessions, the number one session that has been preregistered with over 500 people, the first two sessions are around Calm. And justifiably so because it just as it lives up to its promise, and it'll take its time to kind of get to all the bells and whistles, all the capabilities that have come through with AHV or Acropolis in the past. But the feature functionality, the product market fit associated with Calm is dead on from what the feedback that we can receive. And so Calm itself is on its own rapid cadence. We had AWS and AHV in the first release. Three or four months later, we now added ESX support. We added GCP support and a whole bunch of other capabilities, and I think the essence of Calm is if you can combine Calm and along with private cloud automation but also extend it to multi-cloud automation, it really sets Nutanix on its first genuine path towards multi-cloud. But then, as I said, if you really fixate on a software defined data center message, we're not complete as a full blown AWS or GCP like IA stack until we do the last horizon of networking. And you probably heard me say this before. You heard Dheeraj and others talk about it before is our problem in networking isn't the same in storage. Because the data plane in networking works. Good L2 switches from Cisco, Arista, and so forth, but the real problem networking is in the control plane. When something goes wrong at a VM level in Nutanix, you're able to identify whether it's a storage problem or a compute problem, but we don't know whether it's a VLAN that's mis-configured, or there've been some packets dropped at the top of the rack. Well that all ends now with Flow. And with Flow, essentially what we've now done is take the work that we've been working on to create built-in visibility, put some network automation so that you can actually provision VLANs when you provision VMs. And then augment it with micro segmentation policies all built in this easy to use, consume fashion. But we didn't stop there because we've been talking about Flow, at least the capabilities, over the last year. We spent significant resources building it. But we realized that we needed an additional thing to augment its value because the world of applications especially discovering application topologies is a heady problem. And if we didn't address that, we wouldn't be fulfilling on this ambition of providing one-click network segmentation. And so that's where Netsil comes in. Netsil might seem on the surface yet another next generation application performance management tool. But the innovations that came from Netsil started off at the research project at the University of Pennsylvania. And in fact, most of the team right now that's at Nutanix is from the U Penn research group. And they took a really original, fresh look at how do you sit in a network in a scale out fashion but still reverse engineer the packets, the flow through you, and then recreate this application topology. And recreate this not just on Nutanix, but do it seamlessly across multiple clouds. And to talk about the power of Flow augmented with Netsil, let's bring Rajiv back on stage, Rajiv. >> How you doing? >> Okay so we're going to start with some Netsil stuff, right? >> Yeah, let's talk about Netsil and some of the amazing capabilities this acquisition's bringing to Nutanix. First of all as you mentioned, Netsil's completely non invasive. So it installs on the network, it does all its magic from there. There're no host agents, non of the complexity and compatibility issues that entails. It's also monitoring the network at layer seven. So it's actually doing a deep packet inspection on all your application data, and can give you insights into services and APIs which is very important for modern applications and the way they behave. To do all this of course performance is key. So Netsil's built around a completely distributed architecture scaled to really large workloads. Very exciting technology. We're going to use it in many different ways at Nutanix. And to give you a flavor of that, let me show you how we're thinking of integrating Flow and Nestil together, so micro segmentation and Netsil. So to do that, we install Netsil in one of our Google accounts. And that's what's up here now. It went out there. It discovered all the VMs we're running on that account. It created a map essentially of all their interactions, and you can see it's like a Google Maps view. I can zoom into it. I can look at various things running. I can see lots of HTTP servers over here, some databases. >> Sunil: And it also has stats, right? You can go, it actually-- >> It does. We can take a look at that for a second. There are some stats you can look at right away here. Things like transactions per second and latencies and so on. But if I wanted to micro segment this application, it's not really clear how to do so. There's no real pattern over here. Taking the Google Maps analogy a little further, this kind of looks like the backstreets of Cairo or something. So let's do this step by step. Let me first filter down to one application. Right now I'm looking at about three or four different applications. And Netsil integrates with the metadata. So this is that the clouds provide. So I can search all the tags that I have. So by doing that, I can zoom in on just the financial application. And when I do this, the view gets a little bit simpler, but there's still no real pattern. It's not clear how to micro segment this, right? And this is where the power of Netsil comes in. This is a fairly naive view. This is what tool operating at layer four just looking at ports and TCP traffic would give you. But by doing deep packet inspection, Netsil can get into the services layer. So instead of grouping these interactions by hostname, let's group them by service. So you go service tier. And now you can see this is a much simpler picture. Now I have some patterns. I have a couple of load balancers, an HA proxy and an Nginx. I have a web application front end. I have some application servers running authentication services, search services, et cetera, a database, and a database replica. I could go ahead and micro segment at this point. It's quite possible to do it at this point. But this is almost too granular a view. We actually don't usually want to micro segment at individual service level. You think more in terms of application tiers, the tiers that different services belong to. So let me go ahead and group this differently. Let me group this by app tier. And when I do that, a really simple picture emerges. I have a load balancing tier talking to a web application front end tier, an API tier, and a database tier. Four tiers in my application. And this is something I can work with. This is something that I can micro segment fairly easily. So let's switch over to-- >> Before we dot that though, do you guys see how he gave himself the pseudonym called Dom Toretto? >> Focus Sunil, focus. >> Yeah, for those guys, you know that's not the Avengers theme, man, that's the Fast and Furious theme. >> Rajiv: I think a year ahead. This is next years theme. >> Got it, okay. So before we cut over from Netsil to Flow, do we want to talk a few words about the power of Flow, and what's available in 5.6? >> Sure so Flow's been around since the 5.6 release. Actually some of the functionality came in before that. So it's got invisibility into the network. It helps you debug problems with WLANs and so on. We had a lot of orchestration with other third party vendors with load balancers, with switches to make publishing much simpler. And then of course with our most recent release, we GA'ed our micro segmentation capabilities. And that of course is the most important feature we have in Flow right now. And if you look at how Flow policy is set up, it looks very similar to what we just saw with Netsil. So we have load blancer talking to a web app, API, database. It's almost identical to what we saw just a moment ago. So while this policy was created manually, it is something that we can automate. And it is something that we will do in future releases. Right now, it's of course not been integrated at that level yet. So this was created manually. So one thing you'll notice over here is that the database tier doesn't get any direct traffic from the internet. All internet traffic goes to the load balancer, only specific services then talk to the database. So this policy right now is in monitoring mode. It's not actually being enforced. So let's see what happens if I try to attack the database, I start a hack against the database. And I have my trusty brute force password script over here. It's trying the most common passwords against the database. And if I happen to choose a dictionary word or left the default passwords on, eventually it will log into the database. And when I go back over here in Flow what happens is it actually detects there's now an ongoing a flow, a flow that's outside of policy that's shown up. And it shows this in yellow. So right alongside the policy, I can visualize all the noncompliant flows. This makes it really easy for me now to make decisions, does this flow should it be part of the policy, should it not? In this particular case, obviously it should not be part of the policy. So let me just switch from monitoring mode to enforcement mode. I'll apply the policy, give it a second to propagate. The flow goes away. And if I go back to my script, you can see now the socket's timing out. I can no longer connect to the database. >> Sunil: Got it. So that's like one click segmentation and play right now? >> Absolutely. It's really, really simple. You can compare it to other products in the space. You can't get simpler than this. >> Got it. Why don't we got back and talk a little bit more about, so that's Flow. It's shipping now in 5.6 obviously. It'll come integrated with Netsil functionality as well as a variety of other enhancements in that next few releases. But Netsil does more than just simple topology discovery, right? >> Absolutely. So Netsil's actually gathering a lot of metrics from your network, from your host, all this goes through a data pipeline. It gets processed over there and then gets captured in a time series database. And then we can slice and dice that in various different ways. It can be used for all kinds of insights. So let's see how our application's behaving. So let me say I want to go into the API layer over here. And I instantly get a variety of metrics on how the application's behaving. I get the most requested endpoints. I get the average latency. It looks reasonably good. I get the average latency of the slowest endpoints. If I was having a performance problem, I would know exactly where to go focus on. Right now, things look very good, so we won't focus on that. But scrolling back up, I notice that we have a fairly high error rate happening. We have like 11.35% of our HTTP requests are generating errors, and that deserves some attention. And if I scroll down again, and I see the top five status codes I'm getting, almost 10% of my requests are generating 500 errors, HTTP 500 errors which are internal server errors. So there's something going on that's wrong with this application. So let's dig a little bit deeper into that. Let me go into my analytics workbench over here. And what I've plotted over here is how my HTTP requests are behaving over time. Let me filter down to just the 500 ones. That will make it easier. And I want the 500s. And I'll also group this by the service tier so that I can see which services are causing the problem. And the better view for this would be a bar graph. Yes, so once I do this, you can see that all the errors, all the 500 errors that we're seeing have been caused by the authentication service. So something's obviously wrong with that part of my application. I can go look at whether Active Directory is misbehaving and so on. So very quickly from a broad problem that I was getting a high HTTP error rate. In fact, usually you will discover there's this customer complaining about a lot of errors happening in your application. You can quickly narrow down to exactly what the cause was. >> Got it. This is what we mean by hyperconvergence of the network which is if you can truly isolate network related problems and associate them with the rest of the hyperconvergence infrastructure, then we've essentially started making real progress towards the next level of hyperconvergence. Anyway, thanks a lot, man. Great job. >> Thanks, man. (audience clapping) >> So to talk about this evolution from invisible infrastructure to invisible data centers is another customer of ours that has embarked on this journey. And you know it's not just using Nutanix but a variety of other tools to actually fulfill sort of like the ambition of a full blown cloud stack within a financial organization. And to talk more about that, let me call Vijay onstage. Come on up, Vijay. (rock music) >> Hey. >> Thank you, sir. So Vijay looks way better in real life than in a picture by the way. >> Except a little bit of gray. >> Unlike me. So tell me a little bit about this cloud initiative. >> Yeah. So we've won the best cloud initiative twice now hosted by Incisive media a large magazine. It's basically they host a bunch of you know various buy side, sell side, and you can submit projects in various categories. So we've won the best cloud twice now, 2015 and 2017. The 2017 award is when you know as part of our private cloud journey we were laying the foundation for our private cloud which is 100% based on hyperconverged infrastructure. So that was that award. And then 2017, we've kind of built on that foundation and built more developer-centric next gen app services like PAS, CAS, SDN, SDS, CICD, et cetera. So we've built a lot of those services on, and the second award was really related to that. >> Got it. And a lot of this was obviously based on an infrastructure strategy with some guiding principles that you guys had about three or four years ago if I remember. >> Yeah, this is a great slide. I use it very often. At the core of our infrastructure strategy is how do we run IT as a business? I talk about this with my teams, they were very familiar with this. That's the mindset that I instill within the teams. The mission, the challenge is the same which is how do we scale infrastructure while reducing total cost of ownership, improving time to market, improving client experience and while we're doing that not lose sight of reliability, stability, and security? That's the mission. Those are some of our guiding principles. Whenever we take on some large technology investments, we take 'em through those lenses. Obviously Nutanix went through those lenses when we invested in you guys many, many years ago. And you guys checked all the boxes. And you know initiatives change year on year, the mission remains the same. And more recently, the last few years, we've been focused on converged platforms, converged teams. We've actually reorganized our teams and aligned them closer to the platforms moving closer to an SRE like concept. >> And then you've built out a full stack now across computer storage, networking, all the way with various use cases in play? >> Yeah, and we're aggressively moving towards PAS, CAS as our method of either developing brand new cloud native applications or even containerizing existing applications. So the stack you know obviously built on Nutanix, SDS for software fine storage, compute and networking we've got SDN turned on. We've got, again, PAS and CAS built on this platform. And then finally, we've hooked our CICD tooling onto this. And again, the big picture was always frictionless infrastructure which we're very close to now. You know 100% of our code deployments into this environment are automated. >> Got it. And so what's the net, net in terms of obviously the business takeaway here? >> Yeah so at Northern we don't do tech for tech. It has to be some business benefits, client benefits. There has to be some outcomes that we measure ourselves against, and these are some great metrics or great ways to look at if we're getting the outcomes from the investments we're making. So for example, infrastructure scale while reducing total cost of ownership. We're very focused on total cost of ownership. We, for example, there was a build team that was very focus on building servers, deploying applications. That team's gone down from I think 40, 45 people to about 15 people as one example, one metric. Another metric for reducing TCO is we've been able to absorb additional capacity without increasing operating expenses. So you're actually building capacity in scale within your operating model. So that's another example. Another example, right here you see on the screen. Faster time to market. We've got various types of applications at any given point that we're deploying. There's a next gen cloud native which go directly on PAS. But then a majority of the applications still need the traditional IS components. The time to market to deploy a complex multi environment, multi data center application, we've taken that down by 60%. So we can deliver server same day, but we can deliver entire environments, you know add it to backup, add it to DNS, and fully compliant within a couple of weeks which is you know something we measure very closely. >> Great job, man. I mean that's a compelling I think results. And in the journey obviously you got promoted a few times. >> Yep. >> All right, congratulations again. >> Thank you. >> Thanks Vijay. >> Hey Vijay, come back here. Actually we forgot our joke. So razzled by his data points there. So you're supposed to wear some shoes, right? >> I know my inner glitch. I was going to wear those sneakers, but I forgot them at the office maybe for the right reasons. But the story behind those florescent sneakers, I see they're focused on my shoes. But I picked those up two years ago at a Next event, and not my style. I took 'em to my office. They've been sitting in my office for the last couple years. >> Who's received shoes like these by the way? I'm sure you guys have received shoes like these. There's some real fans there. >> So again, I'm sure many of you liked them. I had 'em in my office. I've offered it to so many of my engineers. Are you size 11? Do you want these? And they're unclaimed? >> So that's the only feature of Nutanix that you-- >> That's the only thing that hasn't worked, other than that things are going extremely well. >> Good job, man. Thanks a lot. >> Thanks. >> Thanks Vijay. So as we get to the final phase which is obviously as we embark on this multi-cloud journey and the complexity that comes with it which Dheeraj hinted towards in his session. You know we have to take a cautious, thoughtful approach here because we don't want to over set expectations because this will take us five, 10 years to really do a good job like we've done in the first act. And the good news is that the market is also really, really early here. It's just a fact. And so we've taken a tiered approach to it as we'll start the discussion with multi-cloud operations, and we've talked about the stack in the prior session which is about look across new clouds. So it's no longer Nutanix, Dell, Lenova, HP, Cisco as the new quote, unquote platforms. It's Nutanix, Xi, GCP, AWS, Azure as the new platforms. That's how we're designing the fabric going forward. On top of that, you obviously have the hybrid OS both on the data plane side and control plane side. Then what you're seeing with the advent of Calm doing a marketplace and automation as well as Beam doing governance and compliance is the fact that you'll see more and more such capabilities of multi-cloud operations burnt into the platform. And example of that is Calm with the new 5.7 release that they had. Launch supports multiple clouds both inside and outside, but the fundamental premise of Calm in the multi-cloud use case is to enable you to choose the right cloud for the right workload. That's the automation part. On the governance part, and this we kind of went through in the last half an hour with Dheeraj and Vijay on stage is something that's even more, if I can call it, you know first order because you get the provisioning and operations second. The first order is to say look whatever my developers have consumed off public cloud, I just need to first get our arm around to make sure that you know what am I spending, am I secure, and then when I get comfortable, then I am able to actually expand on it. And that's the power of Beam. And both Beam and Calm will be the yin and yang for us in our multi-cloud portfolio. And we'll have new products to complement that down the road, right? But along the way, that's the whole private cloud, public cloud. They're the two ends of the barbell, and over time, and we've been working on Xi for awhile, is this conviction that we've built talking to many customers that there needs to be another type of cloud. And this type of a cloud has to feel like a public cloud. It has to be architected like a public cloud, be consumed like a public cloud, but it needs to be an extension of my data center. It should not require any changes to my tooling. It should not require and changes to my operational infrastructure, and it should not require lift and shift, and that's a super hard problem. And this problem is something that a chunk of our R and D team has been burning the midnight wick on for the last year and a half. Because look this is not about taking our current OS which does a good job of scaling and plopping it into a Equinix or a third party data center and calling it a hybrid cloud. This is about rebuilding things in the OS so that we can deliver a true hybrid cloud, but at the same time, give those functionality back on premises so that even if you don't have a hybrid cloud, if you just have your own data centers, you'll still need new services like DR. And if you think about it, what are we doing? We're building a full blown multi-tenant virtual network designed in a modern way. Think about this SDN 2.0 because we have 10 years worth of looking backwards on how GCP has done it, or how Amazon has done it, and now sort of embodying some of that so that we can actually give it as part of this cloud, but do it in a way that's a seamless extension of the data center, and then at the same time, provide new services that have never been delivered before. Everyone obviously does failover and failback in DR it just takes months to do it. Our goal is to do it in hours or minutes. But even things such as test. Imagine doing a DR test on demand for you business needs in the middle of the day. And that's the real bar that we've set for Xi that we are working towards in early access later this summer with GA later in the year. And to talk more about this, let me invite some of our core architects working on it, Melina and Rajiv. (rock music) Good to see you guys. >> You're messing up the names again. >> Oh Rajiv, Vinny, same thing, man. >> You need to back up your memory from Xi. >> Yeah, we should. Okay, so what are we going to talk about, Vinny? >> Yeah, exactly. So today we're going to talk about how Xi is pushing the envelope and beyond the state of the art as you were saying in the industry. As part of that, there's a whole bunch of things that we have done starting with taking a private cloud, seamlessly extending it to the public cloud, and then creating a hybrid cloud experience with one-click delight. We're going to show that. We've done a whole bunch of engineering work on making sure the operations and the tooling is identical on both sides. When you graduate from a private cloud to a hybrid cloud environment, you don't want the environments to be different. So we've copied the environment for you with zero manual intervention. And finally, building on top of that, we are delivering DR as a service with unprecedented simplicity with one-click failover, one-click failback. We're going to show you one click test today. So Melina, why don't we start with showing how you go from a private cloud, seamlessly extend it to consume Xi. >> Sounds good, thanks Vinny. Right now, you're looking at my Prism interface for my on premises cluster. In one-click, I'm going to be able to extend that to my Xi cloud services account. I'm doing this using my my Nutanix credential and a password manager. >> Vinny: So here as you notice all the Nutanix customers we have today, we have created an account for them in Xi by default. So you don't have to log in somewhere and create an account. It's there by default. >> Melina: And just like that we've gone ahead and extended my data center. But let's go take a look at the Xi side and log in again with my my Nutanix credentials. We'll see what we have over here. We're going to be able to see two availability zones, one for on premises and one for Xi right here. >> Vinny: Yeah as you see, using a log in account that you already knew mynutanix.com and 30 seconds in, you can see that you have a hybrid cloud view already. You have a private cloud availability zone that's your own Prism central data center view, and then a Xi availability zone. >> Sunil: Got it. >> Melina: Exactly. But of course we want to extend my network connection from on premises to my Xi networks as well. So let's take a look at our options there. We have two ways of doing this. Both are one-click experience. With direct connect, you can create a dedicated network connection between both environments, or VPN you can use a public internet and a VPN service. Let's go ahead and enable VPN in this environment. Here we have two options for how we want to enable our VPN. We can bring our own VPN and connect it, or we will deploy a VPN for you on premises. We'll do the option where we deploy the VPN in one-click. >> And this is another small sign or feature that we're building net new as part of Xi, but will be burned into our core Acropolis OS so that we can also be delivering this as a stand alone product for on premises deployment as well, right? So that's one of the other things to note as you guys look at the Xi functionality. The goal is to keep the OS capabilities the same on both sides. So even if I'm building a quote, unquote multi data center cloud, but it's just a private cloud, you'll still get all the benefits of Xi but in house. >> Exactly. And on this second step of the wizard, there's a few inputs around how you want the gateway configured, your VLAN information and routing and protocol configuration details. Let's go ahead and save it. >> Vinny: So right now, you know what's happening is we're taking the private network that our customers have on premises and extending it to a multi-tenant public cloud such that our customers can use their IP addresses, the subnets, and bring their own IP. And that is another step towards making sure the operation and tooling is kept consistent on both sides. >> Melina: Exactly. And just while you guys were talking, the VPN was successfully created on premises. And we can see the details right here. You can track details like the status of the connection, the gateway, as well as bandwidth information right in the same UI. >> Vinny: And networking is just tip of the iceberg of what we've had to work on to make sure that you get a consistent experience on both sides. So Melina, why don't we show some of the other things we've done? >> Melina: Sure, to talk about how we preserve entities from my on-premises to Xi, it's better to use my production environment. And first thing you might notice is the log in screen's a little bit different. But that's because I'm logging in using my ADFS credentials. The first thing we preserved was our users. In production, I'm running AD obviously on-prem. And now we can log in here with the same set of credentials. Let me just refresh this. >> And this is the Active Directory credential that our customers would have. They use it on-premises. And we allow the setting to be set on the Xi cloud services as well, so it's the same set of users that can access both sides. >> Got it. There's always going to be some networking problem onstage. It's meant to happen. >> There you go. >> Just launching it again here. I think it maybe timed out. This is a good sign that we're running on time with this presentation. >> Yeah, yeah, we're running ahead of time. >> Move the demos quicker, then we'll time out. So essentially when you log into Xi, you'll be able to see what are the environment capabilities that we have copied to the Xi environment. So for example, you just saw that the same user is being used to log in. But after the use logs in, you'll be able to see their images, for example, copied to the Xi side. You'll be able to see their policies and categories. You know when you define these policies on premises, you spend a lot of effort and create them. And now when you're extending to the public cloud, you don't want to do it again, right? So we've done a whole lot of syncing mechanisms making sure that the two sides are consistent. >> Got it. And on top of these policies, the next step is to also show capabilities to actually do failover and failback, but also do integrated testing as part of this compatibility. >> So one is you know just the basic job of making the environments consistent on two sides, but then it's also now talking about the data part, and that's what DR is about. So if you have a workload running on premises, we can take the data and replicate it using your policies that we've already synced. Once the data is available on the Xi side, at that point, you have to define a run book. And the run book essentially it's a recovery plan. And that says okay I already have the backups of my VMs in case of disaster. I can take my recovery plan and hit you know either failover or maybe a test. And then my application comes up. First of all, you'll talk about the boot order for your VMs to come up. You'll talk about networking mapping. Like when I'm running on-prem, you're using a particular subnet. You have an option of using the same subnet on the Xi side. >> Melina: There you go. >> What happened? >> Sunil: It's finally working.? >> Melina: Yeah. >> Vinny, you can stop talking. (audience clapping) By the way, this is logging into a live Xi data center. We have two regions West Coat, two data centers East Coast, two data centers. So everything that you're seeing is essentially coming off the mainstream Xi profile. >> Vinny: Melina, why don't we show the recovery plan. That's the most interesting piece here. >> Sure. The recovery plan is set up to help you specify how you want to recover your applications in the event of a failover or a test failover. And it specifies all sorts of details like the boot sequence for the VMs as well as network mappings. Some of the network mappings are things like the production network I have running on premises and how it maps to my production network on Xi or the test network to the test network. What's really cool here though is we're actually automatically creating your subnets on Xi from your on premises subnets. All that's part of the recovery plan. While we're on the screen, take a note of the .100 IP address. That's a floating IP address that I have set up to ensure that I'm going to be able to access my three tier web app that I have protected with this plan after a failover. So I'll be able to access it from the public internet really easily from my phone or check that it's all running. >> Right, so given how we make the environment consistent on both sides, now we're able to create a very simple DR experience including failover in one-click, failback. But we're going to show you test now. So Melina, let's talk about test because that's one of the most common operations you would do. Like some of our customers do it every month. But usually it's very hard. So let's see how the experience looks like in what we built. >> Sure. Test and failover are both one-click experiences as you know and come to expect from Nutanix. You can see it's failing over from my primary location to my recovery location. Now what we're doing right now is we're running a series of validation checks because we want to make sure that you have your network configured properly, and there's other configuration details in place for the test to be successful. Looks like the failover was initiated successfully. Now while that failover's happening though, let's make sure that I'm going to be able to access my three tier web app once it fails over. We'll do that by looking at my network policies that I've configured on my test network. Because I want to access the application from the public internet but only port 80. And if we look here under our policies, you can see I have port 80 open to permit. So that's good. And if I needed to create a new one, I could in one click. But it looks like we're good to go. Let's go back and check the status of my recovery plan. We click in, and what's really cool here is you can actually see the individual tasks as they're being completed from that initial validation test to individual VMs being powered on as part of the recovery plan. >> And to give you guys an idea behind the scenes, the entire recovery plan is actually a set of workflows that are built on Calm's automation engine. So this is an example of where we're taking some of power of workflow and automation that Clam has come to be really strong at and burning that into how we actually operationalize many of these workflows for Xi. >> And so great, while you were explaining that, my three tier web app has restarted here on Xi right in front of you. And you can see here there's a floating IP that I mentioned early that .100 IP address. But let's go ahead and launch the console and make sure the application started up correctly. >> Vinny: Yeah, so that .100 IP address is a floating IP that's a publicly visible IP. So it's listed here, 206.80.146.100. And that's essentially anybody in the audience here can go use your laptop or your cell phone and hit that and start to work. >> Yeah so by the way, just to give you guys an idea while you guys maybe use the IP to kind of hit it, is a real set of VMs that we've just failed over from Nutanix's corporate data center into our West region. >> And this is running live on the Xi cloud. >> Yeah, you guys should all go and vote. I'm a little biased towards Xi, so vote for Xi. But all of them are really good features. >> Scroll up a little bit. Let's see where Xi is. >> Oh Xi's here. I'll scroll down a little bit, but keep the... >> Vinny: Yes. >> Sunil: You guys written a block or something? >> Melina: Oh good, it looks like Xi's winning. >> Sunil: Okay, great job, Melina. Thank you so much. >> Thank you, Melina. >> Melina: Thanks. >> Thank you, great job. Cool and calm under pressure. That's good. So that was Xi. What's something that you know we've been doing around you know in addition to taking say our own extended enterprise public cloud with Xi. You know we do recognize that there are a ton of workloads that are going to be residing on AWS, GCP, Azure. And to sort of really assist in the try and call it transformation of enterprises to choose the right cloud for the right workload. If you guys remember, we actually invested in a tool over last year which became actually quite like one of those products that took off based on you know groundswell movement. Most of you guys started using it. It's essentially extract for VMs. And it was this product that's obviously free. It's a tool. But it enables customers to really save tons of time to actually migrate from legacy environments to Nutanix. So we took that same framework, obviously re-platformed it for the multi-cloud world to kind of solve the problem of migrating from AWS or GCP to Nutanix or vice versa. >> Right, so you know, Sunil as you said, moving from a private cloud to the public cloud is a lift and shift, and it's a hard you know operation. But moving back is not only expensive, it's a very hard problem. None of the cloud vendors provide change block tracking capability. And what that means is when you have to move back from the cloud, you have an extended period of downtime because there's now way of figuring out what's changing while you're moving. So you have to keep it down. So what we've done with our app mobility product is we have made sure that, one, it's extremely simple to move back. Two, that the downtime that you'll have is as small as possible. So let me show you what we've done. >> Got it. >> So here is our app mobility capability. As you can see, on the left hand side we have a source environment and target environment. So I'm calling my AWS environment Asgard. And I can add more environments. It's very simple. I can select AWS and then put in my credentials for AWS. It essentially goes and discovers all the VMs that are running and all the regions that they're running. Target environment, this is my Nutanix environment. I call it Earth. And I can add target environment similarly, IP address and credentials, and we do the rest. Right, okay. Now migration plans. I have Bifrost one as my migration plan, and this is how migration works. First you create a plan and then say start seeding. And what it does is takes a snapshot of what's running in the cloud and starts migrating it to on-prem. Once it is an on-prem and the difference between the two sides is minimal, it says I'm ready to cutover. At that time, you move it. But let me show you how you'd create a new migration plan. So let me name it, Bifrost 2. Okay so what I have to do is select a region, so US West 1, and target Earth as my cluster. This is my storage container there. And very quickly you can see these are the VMs that are running in US West 1 in AWS. I can select SQL server one and two, go to next. Right now it's looking at the target Nutanix environment and seeing it had enough space or not. Once that's good, it gives me an option. And this is the step where it enables the Nutanix service of change block tracking overlaid on top of the cloud. There are two options one is automatic where you'll give us the credentials for your VMs, and we'll inject our capability there. Or manually you could do. You could copy the command either in a windows VM or Linux VM and run it once on the VM. And change block tracking since then in enabled. Everything is seamless after that. Hit next. >> And while Vinny's setting it up, he said a few things there. I don't know if you guys caught it. One of the hardest problems in enabling seamless migration from public cloud to on-prem which makes it harder than the other way around is the fact that public cloud doesn't have things like change block tracking. You can't get delta copies. So one of the core innovations being built in this app mobility product is to provide that overlay capability across multiple clouds. >> Yeah, and the last step here was to select the target network where the VMs will come up on the Nutanix environment, and this is a summary of the migration plan. You can start it or just save it. I'm saving it because it takes time to do the seeding. I have the other plan which I'll actually show the cutover with. Okay so now this is Bifrost 1. It's ready to cutover. We started it four hours ago. And here you can see there's a SQL server 003. Okay, now I would like to show the AWS environment. As you can see, SQL server 003. This VM is actually running in AWS right now. And if you go to the Prism environment, and if my login works, right? So we can go into the virtual machine view, tables, and you see the VM is not there. Okay, so we go back to this, and we can hit cutover. So this is essentially telling our system, okay now it the time. Quiesce the VM running in AWS, take the last bit of changes that you have to the database, ship it to on-prem, and in on-prem now start you know configure the target VM and start bringing it up. So let's go and look at AWS and refresh that screen. And you should see, okay so the SQL server is now stopping. So that means it has quiesced and stopping the VM there. If you go back and look at the migration plan that we had, it says it's completed. So it has actually migrated all the data to the on-prem side. Go here on-prem, you see the production SQL server is running already. I can click launch console, and let's see. The Windows VM is already booting up. >> So essentially what Vinny just showed was a live cutover of an AWS VM to Nutanix on-premises. >> Yeah, and what we have done. (audience clapping) So essentially, this is about making two things possible, making it simple to migrate from cloud to on-prem, and making it painless so that the downtime you have is very minimal. >> Got it, great job, Vinny. I won't forget your name again. So last step. So to really talk about this, one of our favorite partners and customers has been in the cloud environment for a long time. And you know Jason who's the CTO of Cyxtera. And he'll introduce who Cyxtera is. Most of you guys are probably either using their assets or not without knowing their you know the new name. But is someone that was in the cloud before it was called cloud as one of the original founders and technologists behind Terremark, and then later as one of the chief architects of VMware's cloud. And then they started this new company about a year or so ago which I'll let Jason talk about. This journey that he's going to talk about is how a partner, slash customer is working with us to deliver net new transformations around the traditional industry of colo. Okay, to talk more about it, Jason, why don't you come up on stage, man? (rock music) Thank you, sir. All right so Cyxtera obviously a lot of people don't know the name. Maybe just give a 10 second summary of why you're so big already. >> Sure, so Cyxtera was formed, as you said, about a year ago through the acquisition of the CenturyLink data centers. >> Sunil: Which includes Savvis and a whole bunch of other assets. >> Yeah, there's a long history of those data centers, but we have all of them now as well as the software companies owned by Medina capital. So we're like the world's biggest startup now. So we have over 50 data centers around the world, about 3,500 customers, and a portfolio of security and analytics software. >> Sunil: Got it, and so you have this strategy of what we're calling revolutionizing colo deliver a cloud based-- >> Yeah so, colo hasn't really changed a lot in the last 20 years. And to be fair, a lot of what happens in data centers has to have a person physically go and do it. But there are some things that we can simplify and automate. So we want to make things more software driven, so that's what we're doing with the Cyxtera extensible data center or CXD. And to do that, we're deploying software defined networks in our facilities and developing automations so customers can go and provision data center services and the network connectivity through a portal or through REST APIs. >> Got it, and what's different now? I know there's a whole bunch of benefits with the integrated platform that one would not get in the traditional kind of on demand data center environment. >> Sure. So one of the first services we're launching on CXD is compute on demand, and it's powered by Nutanix. And we had to pick an HCI partner to launch with. And we looked at players in the space. And as you mentioned, there's actually a lot of them, more than I thought. And we had a lot of conversations, did a lot of testing in the lab, and Nutanix really stood out as the best choice. You know Nutanix has a lot of focus on things like ease of deployment. So it's very simple for us to automate deploying compute for customers. So we can use foundation APIs to go configure the servers, and then we turn those over to the customer which they can then manage through Prism. And something important to keep in mind here is that you know this isn't a manged service. This isn't infrastructure as a service. The customer has complete control over the Nutanix platform. So we're turning that over to them. It's connected to their network. They're using their IP addresses, you know their tools and processes to operate this. So it was really important for the platform we picked to have a really good self-service story for things like you know lifecycle management. So with one-click upgrade, customers have total control over patches and upgrades. They don't have to call us to do it. You know they can drive that themselves. >> Got it. Any other final words around like what do you see of the partnership going forward? >> Well you know I think this would be a great platform for Xi, so I think we should probably talk about that. >> Yeah, yeah, we should talk about that separately. Thanks a lot, Jason. >> Thanks. >> All right, man. (audience clapping) So as we look at the full journey now between obviously from invisible infrastructure to invisible clouds, you know there is one thing though to take away beyond many updates that we've had so far. And the fact is that everything that I've talked about so far is about completing a full blown true IA stack from all the way from compute to storage, to vitualization, containers to network services, and so forth. But every public cloud, a true cloud in that sense, has a full blown layer of services that's set on top either for traditional workloads or for new workloads, whether it be machine-learning, whether it be big data, you know name it, right? And in the enterprise, if you think about it, many of these services are being provisioned or provided through a bunch of our partners. Like we have partnerships with Cloudera for big data and so forth. But then based on some customer feedback and a lot of attention from what we've seen in the industry go out, just like AWS, and GCP, and Azure, it's time for Nutanix to have an opinionated view of the past stack. It's time for us to kind of move up the stack with our own offering that obviously adds value but provides some of our core competencies in data and takes it to the next level. And it's in that sense that we're actually launching Nutanix Era to simplify one of the hardest problems in enterprise IT and short of saving you from true Oracle licensing, it solves various other Oracle problems which is about truly simplifying databases much like what RDS did on AWS, imagine enterprise RDS on demand where you can provision, lifecycle manage your database with one-click. And to talk about this powerful new functionality, let me invite Bala and John on stage to give you one final demo. (rock music) Good to see you guys. >> Yep, thank you. >> All right, so we've got lots of folks here. They're all anxious to get to the next level. So this demo, really rock it. So what are we going to talk about? We're going to start with say maybe some database provisioning? Do you want to set it up? >> We have one dream, Sunil, one single dream to pass you off, that is what Nutanix is today for IT apps, we want to recreate that magic for devops and get back those weekends and freedom to DBAs. >> Got it. Let's start with, what, provisioning? >> Bala: Yep, John. >> Yeah, we're going to get in provisioning. So provisioning databases inside the enterprise is a significant undertaking that usually involves a myriad of resources and could take days. It doesn't get any easier after that for the longterm maintence with things like upgrades and environment refreshes and so on. Bala and team have been working on this challenge for quite awhile now. So we've architected Nutanix Era to cater to these enterprise use cases and make it one-click like you said. And Bala and I are so excited to finally show this to the world. We think it's actually Nutanix's best kept secrets. >> Got it, all right man, let's take a look at it. >> So we're going to be provisioning a sales database today. It's a four-step workflow. The first part is choosing our database engine. And since it's our sales database, we want it to be highly available. So we'll do a two node rack configuration. From there, it asks us where we want to land this service. We can either land it on an existing service that's already been provisioned, or if we're starting net new or for whatever reason, we can create a new service for it. The key thing here is we're not asking anybody how to do the work, we're asking what work you want done. And the other key thing here is we've architected this concept called profiles. So you tell us how much resources you need as well as what network type you want and what software revision you want. This is actually controlled by the DBAs. So DBAs, and compute administrators, and network administrators, so they can set their standards without having a DBA. >> Sunil: Got it, okay, let's take a look. >> John: So if we go to the next piece here, it's going to personalize their database. The key thing here, again, is that we're not asking you how many data files you want or anything in that regard. So we're going to be provisioning this to Nutanix's best practices. And the key thing there is just like these past services you don't have to read dozens of pages of best practice guides, it just does what's best for the platform. >> Sunil: Got it. And so these are a multitude of provisioning steps that normally one would take I guess hours if not days to provision and Oracle RAC data. >> John: Yeah, across multiple teams too. So if you think about the lifecycle especially if you have onshore and offshore resources, I mean this might even be longer than days. >> Sunil: Got it. And then there are a few steps here, and we'll lead into potentially the Time Machine construct too? >> John: Yeah, so since this is a critical database, we want data protection. So we're going to be delivering that through a feature called Time Machines. We'll leave this at the defaults for now, but the key thing to not here is we've got SLAs that deliver both continuous data protection as well as telescoping checkpoints for historical recovery. >> Sunil: Got it. So that's provisioning. We've kicked off Oracle, what, two node database and so forth? >> John: Yep, two node database. So we've got a handful of tasks that this is going to automate. We'll check back in in a few minutes. >> Got it. Why don't we talk about the other aspects then, Bala, maybe around, one of the things that, you know and I know many of you guys have seen this, is the fact that if you look at database especially Oracle but in general even SQL and so forth is the fact that look if you really simplified it to a developer, it should be as simple as I copy my production database, and I paste it to create my own dev instance. And whenever I need it, I need to obviously do it the opposite way, right? So that was the goal that we set ahead for us to actually deliver this new past service around Era for our customers. So you want to talk a little bit more about it? >> Sure Sunil. If you look at most of the data management functionality, they're pretty much like flavors of copy paste operations on database entities. But the trouble is the seemingly simple, innocuous operations of our daily lives becomes the most dreaded, complex, long running, error prone operations in data center. So we actually planned to tame this complexity and bring consumer grade simplicity to these operations, also make these clones extremely efficient without compromising the quality of service. And the best part is, the customers can enjoy these services not only for databases running on Nutanix, but also for databases running on third party systems. >> Got it. So let's take a look at this functionality of I guess snapshoting, clone and recovery that you've now built into the product. >> Right. So now if you see the core feature of this whole product is something we call Time Machine. Time Machine lets the database administrators actually capture the database tape to the granularity of seconds and also lets them create clones, refresh them to any point in time, and also recover the databases if the databases are running on the same Nutanix platform. Let's take a look at the demo with the Time Machine. So here is our customer relationship database management database which is about 2.3 terabytes. If you see, the Time Machine has been active about four months, and SLA has been set for continuously code revision of 30 days and then slowly tapers off 30 days of daily backup and weekly backups and so on, so forth. On the right hand side, you will see different colors. The green color is pretty much your continuously code revision, what we call them. That lets you to go back to any point in time to the granularity of seconds within those 30 days. And then the discreet code revision lets you go back to any snapshot of the backup that is maintained there kind of stuff. In a way, you see this Time Machine is pretty much like your modern day car with self driving ability. All you need to do is set the goals, and the Time Machine will do whatever is needed to reach up to the goal kind of stuff. >> Sunil: So why don't we quickly do a snapshot? >> Bala: Yeah, some of these times you need to create a snapshot for backup purposes, Time Machine has manual controls. All you need to do is give it a snapshot name. And then you have the ability to actually persist this snapshot data into a third party or object store so that your durability and that global data access requirements are met kind of stuff. So we kick off a snapshot operation. Let's look at what it is doing. If you see what is the snapshot operation that this is going through, there is a step called quiescing the databases. Basically, we're using application-centric APIs, and here it's actually RMAN of Oracle. We are using the RMan of Oracle to quiesce the database and performing application consistent storage snapshots with Nutanix technology. Basically we are fusing application-centric and then Nutanix platform and quiescing it. Just for a data point, if you have to use traditional technology and create a backup for this kind of size, it takes over four to six hours, whereas on Nutanix it's going to be a matter of seconds. So it almost looks like snapshot is done. This is full sensitive backup. You can pretty much use it for database restore kind of stuff. Maybe we'll do a clone demo and see how it goes. >> John: Yeah, let's go check it out. >> Bala: So for clone, again through the simplicity of command Z command, all you need to do is pick the time of your choice maybe around three o'clock in the morning today. >> John: Yeah, let's go with 3:02. >> Bala: 3:02, okay. >> John: Yeah, why not? >> Bala: You select the time, all you need to do is click on the clone. And most of the inputs that are needed for the clone process will be defaulted intelligently by us, right? And you have to make two choices that is where do you want this clone to be created with a brand new VM database server, or do you want to place that in your existing server? So we'll go with a brand new server, and then all you need to do is just give the password for you new clone database, and then clone it kind of stuff. >> Sunil: And this is an example of personalizing the database so a developer can do that. >> Bala: Right. So here is the clone kicking in. And what this is trying to do is actually it's creating a database VM and then registering the database, restoring the snapshot, and then recoding the logs up to three o'clock in the morning like what we just saw that, and then actually giving back the database to the requester kind of stuff. >> Maybe one finally thing, John. Do you want to show us the provision database that we kicked off? >> Yeah, it looks like it just finished a few seconds ago. So you can see all the tasks that we were talking about here before from creating the virtual infrastructure, and provisioning the database infrastructure, and configuring data protection. So I can go access this database now. >> Again, just to highlight this, guys. What we just showed you is an Oracle two node instance provisioned live in a few minutes on Nutanix. And this is something that even in a public cloud when you go to RDS on AWS or anything like that, you still can't provision Oracle RAC by the way, right? But that's what you've seen now, and that's what the power of Nutanix Era is. Okay, all right? >> Thank you. >> Thanks. (audience clapping) >> And one final thing around, obviously when we're building this, it's built as a past service. It's not meant just for operational benefits. And so one of the core design principles has been around being API first. You want to show that a little bit? >> Absolutely, Sunil, this whole product is built on API fist architecture. Pretty much what we have seen today and all the functionality that we've been able to show today, everything is built on Rest APIs, and you can pretty much integrate with service now architecture and give you your devops experience for your customers. We do have a plan for full fledged self-service portal eventually, and then make it as a proper service. >> Got it, great job, Bala. >> Thank you. >> Thanks, John. Good stuff, man. >> Thanks. >> All right. (audience clapping) So with Nutanix Era being this one-click provisioning, lifecycle management powered by APIs, I think what we're going to see is the fact that a lot of the products that we've talked about so far while you know I've talked about things like Calm, Flow, AHV functionality that have all been released in 5.5, 5.6, a bunch of the other stuff are also coming shortly. So I would strongly encourage you guys to kind of space 'em, you know most of these products that we've talked about, in fact, all of the products that we've talked about are going to be in the breakout sessions. We're going to go deep into them in the demos as well as in the pods. So spend some quality time not just on the stuff that's been shipping but also stuff that's coming out. And so one thing to keep in mind to sort of takeaway is that we're doing this all obviously with freedom as the goal. But from the products side, it has to be driven by choice whether the choice is based on platforms, it's based on hypervisors, whether it's based on consumption models and eventually even though we're starting with the management plane, eventually we'll go with the data plane of how do I actually provide a multi-cloud choice as well. And so when we wrap things up, and we look at the five freedoms that Ben talked about. Don't forget the sixth freedom especially after six to seven p.m. where the whole goal as a Nutanix family and extended family make sure we mix it up. Okay, thank you so much, and we'll see you around. (audience clapping) >> PA Announcer: Ladies and gentlemen, this concludes our morning keynote session. Breakouts will begin in 15 minutes. ♪ To do what I want ♪