>> Announcer: theCUBE presents "Kubecon and Cloudnativecon Europe 2022" brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to theCUBE coverage of Kubecon 2022, E.U. I'm here with my cohost, Paul Gillin. >> Pleased to work with you, Keith. >> Nice to work with you, Paul. And we have our first two guests. "theCUBE" is hot. I'm telling you we are having interviews before the start of even the show floor. I have with me, we got to start with the customers first. Enterprise Architect Adnan Khan, welcome to the show. >> Thank you so much. >> Keith: CUBE time first, now you're at CUBE-alumni. >> Yup. >> And Haseeb Budhani, CEO Arathi, welcome back. >> Nice to talk to you again today. >> So, we're talking all things Kubernetes and we're super excited to talk to MoneyGram about their journey to Kubernetes. First question I have for Adnan. Talk to us about what your pre-Kubernetes landscape looked like? >> Yeah. Certainly, Keith. So, we had a traditional mix of legacy applications and modern applications. A few years ago we made the decision to move to a microservices architecture, and this was all happening while we were still on-prem. So, your traditional VMs. And we started 20, 30 microservices but with the microservices packing. You quickly expand to hundreds of microservices. And we started getting to that stage where managing them without sort of an orchestration platform, and just as traditional VMs, was getting to be really challenging, especially from a day two operational. You can manage 10, 15 microservices, but when you start having 50, and so forth, all those concerns around high availability, operational performance. So, we started looking at some open-source projects. Spring cloud, we are predominantly a Java shop. So, we looked at the spring cloud projects. They give you a number of initiatives for doing some of those management. And what we realized again, to manage those components without sort of a platform, was really challenging. So, that kind of led us to sort of Kubernetes where along with our journey new cloud, it was the platform that could help us with a lot of those management operational concerns. >> So, as you talk about some of those challenges, pre-Kubernetes, what were some of the operational issues that you folks experienced? >> Yeah, certain things like auto scaling is number one. I mean, that's a fundamental concept of cloud native, right? Is how do you auto scale VMs, right? You can put in some old methods and stuff, but it was really hard to do that automatically. So, Kubernetes with like HPA gives you those out of the box. Provided you set the right policies, you can have auto scaling where it can scale up and scale back, so we were doing that manually. So, before, you know, MoneyGram, obviously, holiday season, people are sending more money, Mother's Day. Our Ops team would go and basically manually scale VMs. So, we'd go from four instances to maybe eight instances, but that entailed outages. And just to plan around doing that manually, and then sort of scale them back was a lot of overhead, a lot of administration overhead. So, we wanted something that could help us do that automatically in an efficient and intrusive way. That was one of the things, monitoring and and management operations, just kind of visibility into how those applications were during what were the status of your workloads, was also a challenge to do that. >> So, Haseeb, I got to ask the question. If someone would've came to me with that problem, I'd just say, "You know what? Go to the plug to cloud." How does your group help solve some of these challenges? What do you guys do? >> Yeah. What do we do? Here's my perspective on the market as it's playing out. So, I see a bifurcation happening in the Kubernetes space. But there's the Kubernetes run time, so Amazon has EKS, Azure as AKS. There's enough of these available, they're not managed services, they're actually really good, frankly. In fact, retail customers, if you're an Amazon why would you spin up your own? Just use EKS, it's awesome. But then, there's an operational layer that is needed to run Kubernetes. My perspective is that, 50,000 enterprises are adopting Kubernetes over the next 5 to 10 years. And they're all going to go through the same exact journey, and they're all going to end up potentially making the same mistake, which is, they're going to assume that Kubernetes is easy. They're going to say, "Well, this is not hard. I got this up and running on my laptop. This is so easy, no worries. I can do EKS." But then, okay, can you consistently spin up these things? Can you scale them consistently? Do you have the right blueprints in place? Do you have the right access management in place? Do you have the right policies in place? Can you deploy applications consistently? Do you have monitoring and visibility into those things? Do your developers have access when they need it? Do you have the right networking layer in place? Do you have the right chargebacks in place? Remember you have multiple teams. And by the way, nobody has a single cluster, so you got to do this across multiple clusters. And some of them have multiple clouds. Not because they want to be multiple clouds, because, but sometimes you buy a company, and they happen to be in Azure. How many dashboards do you have now across all the open-source technologies that you have identified to solve these problems? This is where pain lies. So, I think that Kubernetes is fundamentally a solve problem. Like our friends at AWS and Azure, they've solved this problem. It's like a AKS, EKS, et cetera, EGK for that matter. They're great, and you should use them, and don't even think about spinning up QB best clusters. Don't do it, use the platforms that exist. And commensurately on-premises, OpenShift is pretty awesome. If you like it, use it. But then when it comes to the operations layer, that's where today, we end up investing in a DevOps team, and then an SRE organization that need to become experts in Kubernetes, and that is not tenable. Can you, let's say unlimited capital, unlimited budgets. Can you hire 20 people to do Kubernetes today? >> If you could find them. >> If you can find 'em, right? So, even if you could, the point is that, see five years ago when your competitors were not doing Kubernetes, it was a competitive advantage to go build a team to do Kubernetes so you could move faster. Today, you know, there's a high chance that your competitors are already buying from a Rafay or somebody like Rafay. So, now, it's better to take these really, really sharp engineers and have them work on things that make the company money. Writing operations for Kubernetes, this is a commodity now. >> How confident are you that the cloud providers won't get in and do what you do and put you out of business? >> Yeah, I mean, absolutely. In fact, I had a conversation with somebody from HBS this morning and I was telling them, I don't think you have a choice, you have to do this. Competition is not a bad thing. If we are the only company in a space, this is not a space, right? The bet we are making is that every enterprise, they have an on-prem strategy, they have at least a handful of, everybody's got at least two clouds that they're thinking about. Everybody starts with one cloud, and then they have some other cloud that they're also thinking about. For them to only rely on one cloud's tools to solve for on-prem, plus that second cloud, they potentially they may have, that's a tough thing to do. And at the same time, we as a vendor, I mean, the only real reason why startups survive, is because you have technology that is truly differentiator. Otherwise, I mean, you got to build something that is materially interesting, right? We seem to have- >> Keith: Now. Sorry, go ahead. >> No, I was going to, you actually have me thinking about something. Adnan? >> Yes. >> MoneyGram, big, well known company. a startup, adding, working in a space with Google, VMware, all the biggest names. What brought you to Rafay to solve this operational challenge? >> Yeah. A good question. So, when we started out sort of in our Kubernetes, we had heard about EKS and we are an AWS shop, so that was the most natural path. And we looked at EKS and used that to create our clusters. But then we realized very quickly, that, yes, to Haseeb's point, AWS manages the control plane for you, it gives you the high availability. So, you're not managing those components which is some really heavy lifting. But then what about all the other things like centralized dashboard? What about, we need to provision Kubernetes clusters on multicloud, right? We have other clouds that we use, or also on-prem, right? How do you do some of that stuff? We also, at that time were looking at other tools also. And I had, I remember come up with an MVP list that we needed to have in place for day one or day two operations before we even launch any single applications into production. And my Ops team looked at that list and literally, there was only one or two items that they could check off with EKS. They've got the control plane, they've got the cluster provision, but what about all those other components? And some of that kind of led us down the path of, you know, looking at, "Hey, what's out there in this space?" And we realized pretty quickly that there weren't too many. There were some large providers and capabilities like Antos, but we felt that it was a little too much for what we were trying to do at that point in time. We wanted to scale slowly. We wanted to minimize our footprint, and Rafay seemed to sort of, was a nice mix from all those different angles. >> How was the situation affecting your developer experience? >> So, that's a really good question also. So, operations was one aspect to it. The other part is the application development. We've got MoneyGram is when a lot of organizations have a plethora of technologies from Java, to .net, to node.js, what have you, right? Now, as you start saying, okay, now we're going cloud native and we're going to start deploying to Kubernetes. There's a fair amount of overhead because a tech stack, all of a sudden goes from, just being Java or just being .net, to things like Docker. All these container orchestration and deployment concerns, Kubernetes deployment artifacts, (chuckles) I got to write all this YAML as my developer say, "YAML hell." (panel laughing) I got to learn Docker files. I need to figure out a package manager like HELM on top of learning all the Kubernetes artifacts. So, initially, we went with sort of, okay, you know, we can just train our developers. And that was wrong. I mean, you can't assume that everyone is going to sort of learn all these deployment concerns and we'll adopt them. There's a lot of stuff that's outside of their sort of core dev domain, that you're putting all this burden on them. So, we could not rely on them in to be sort of CUBE cuddle experts, right? That's a fair amount overhead learning curve there. So, Rafay again, from their dashboard perspective, saw the managed CUBE cuddle, gives you that easy access for devs, where they can go and monitor the status of their workloads. They don't have to figure out, configuring all these tools locally, just to get it to work. We did some things from a DevOps perspective to basically streamline and automate that process. But then, also Rafay came in and helped us out on kind of that providing that dashboard. They don't have to break, they can basically get on through single sign on and have visibility into the status of their deployment. They can do troubleshooting diagnostics all through a single pane of glass, which was a key key item. Initially, before Rafay, we were doing that command line. And again, just getting some of the tools configured was huge, it took us days just to get that. And then the learning curve for development teams "Oh, now you got the tools, now you got to figure out how to use it." >> So, Haseeb talk to me about the cloud native infrastructure. When I look at that entire landscape number, I'm just overwhelmed by it. As a customer, I look at it, I'm like, "I don't know where to start." I'm sure, Adnan, you folks looked at it and said, "Wow, there's so many solutions." How do you engage with the ecosystem? You have to be at some level opinionated but flexible enough to meet every customer's needs. How do you approach that? >> So, it's a really tough problem to solve because... So, the thing about abstraction layers, we all know how that plays out, right? So, abstraction layers are fundamentally never the right answer because they will never catch up, because you're trying to write a layer on top. So, then we had to solve the problem, which was, well, we can't be an abstraction layer, but then at the same time, we need to provide some, sort of like centralization standardization. So, we sort of have this the following dissonance in our platform, which is actually really important to solve the problem. So, we think of a stack as floor things. There's the Kubernetes layer, infrastructure layer, and EKS is different from AKS, and it's okay. If we try to now bring them all together and make them behave as one, our customers are going to suffer. Because there are features in EKS that I really want, but then if you write an abstraction then I'm not going to get 'em so not okay. So, treat them as individual things that we logic that we now curate. So, every time EKS, for example, goes from 1.22 to 1.23, we write a new product, just so my customer can press a button and upgrade these clusters. Similarly, we do this for AKS, we do this for GK. It's a really, really hard job, but that's the job, we got to do it. On top of that, you have these things called add-ons, like my network policy, my access management policy, my et cetera. These things are all actually the same. So, whether I'm EKS or AKS, I want the same access for Keith versus Adnan, right? So, then those components are sort of the same across, doesn't matter how many clusters, doesn't matter how many clouds. On top of that, you have applications. And when it comes to the developer, in fact I do the following demo a lot of times. Because people ask the question. People say things like, "I want to run the same Kubernetes distribution everywhere because this is like Linux." Actually, it's not. So, I do a demo where I spin up access to an OpenShift cluster, and an EKS cluster, and then AKS cluster. And I say, "Log in, show me which one is which?" They're all the same. >> So, Adnan, make that real for me. I'm sure after this amount of time, developers groups have come to you with things that are snowflakes. And as a enterprise architect, you have to make it work within your framework. How has working with Rafay made that possible? >> Yeah, so I think one of the very common concerns is the whole deployment to Haseeb's point, is you are from a deployment perspective, it's still using HELM, it's still using some of the same tooling. How do you? Rafay gives us some tools. You know, they have a command line Add Cuddle API that essentially we use. We wanted parity across all our different environments, different clusters, it doesn't matter where you're running. So, that gives us basically a consistent API for deployment. We've also had challenges with just some of the tooling in general that we worked with Rafay actually, to actually extend their, Add Cuddle API for us so that we have a better deployment experience for our developers. >> Haseeb, how long does this opportunity exist for you? At some point, do the cloud providers figure this out, or does the open-source community figure out how to do what you've done and this opportunity is gone? >> So, I think back to a platform that I think very highly of, which has been around a long time and continues to live, vCenter. I think vCenter is awesome. And it's beautiful, VMware did an incredible job. What is the job? It's job is to manage VMs, right? But then it's for access, it's also storage. It's also networking in a sec, right? All these things got done because to solve a real problem, you have to think about all the things that come together to help you solve that problem from an operations perspective. My view is that this market needs essentially a vCenter, but for Kubernetes, right? And that is a very broad problem. And it's going to spend, it's not about a cloud. I mean, every cloud should build this. I mean, why would they not? It makes sense. Anto exist, right? Everybody should have one. But then, the clarity in thinking that the Rafay team seems to have exhibited, till date, seems to merit an independent company, in my opinion, I think like, I mean, from a technical perspective, this product's awesome, right? I mean, we seem to have no real competition when it comes to this broad breadth of capabilities. Will it last? We'll see, right? I mean, I keep doing "CUBE" shows, right? So, every year you can ask me that question again, and we'll see. >> You make a good point though. I mean, you're up against VMware, You're up against Google. They're both trying to do sort of the same thing you're doing. Why are you succeeding? >> Maybe it's focused. Maybe it's because of the right experience. I think startups, only in hindsight, can one tell why a startup was successful. In all honesty, I've been in a one or two startups in the past, and there's a lot of luck to this, there's a lot of timing to this. I think this timing for a product like this is perfect. Like three, four years ago, nobody would've cared. Like honesty, nobody would've cared. This is the right time to have a product like this in the market because so many enterprises are now thinking of modernization. And because everybody's doing this, this is like the boots strong problem in HCI. Everybody's doing it, but there's only so many people in the industry who actually understand this problem, so they can't even hire the people. And the CTO said, "I got to go. I don't have the people, I can't fill the seats." And then they look for solutions, and via that solution, that we're going to get embedded. And when you have infrastructure software like this embedded in your solution, we're going to be around with the... Assuming, obviously, we don't score up, right? We're going to be around with these companies for some time. We're going to have strong partners for the long term. >> Well, vCenter for Kubernetes I love to end on that note. Intriguing conversation, we could go on forever on this topic, 'cause there's a lot of work to do. I don't think this will over be a solved problem for the Kubernetes as cloud native solutions, so I think there's a lot of opportunities in that space. Haseeb Budhani, thank you for rejoining "theCUBE." Adnan Khan, welcome becoming a CUBE-alum. >> (laughs) Awesome. Thank you so much. >> Check your own profile on the sound's website, it's really cool. From Valencia, Spain, I'm Keith Townsend, along with my Host Paul Gillin . And you're watching "theCUBE," the leader in high tech coverage. (bright upbeat music)

[Music] welcome to thecube's coverage of vmworld 2021 i'm lisa martin pleased to welcome back to the program the cto of vmware kit kohlberg welcome back to the program and congrats on your new role thank you yeah i'm really excited to be here so you've been at vmware for a long time you started as an intern i read yeah yeah it's been uh 18 years as a full-timer but i guess 19 if you count my internship so quite a while it's many lifetimes in silicon valley right many lifetimes in silicon valley well we've seen a lot of innovation from vmware in its 23 years you've been there the vast majority of that we've seen a lot of successful big tech waves ridden by vmware in april vmware pulled tanzu and vmware cloud foundation together vmware cloud you've got some exciting news with respect to that what are you announcing today well we got a lot of exciting announcements happening at vmworld this week but one of the ones i'm really excited about is vmware cloud with tons of services so let me talk about what these things are so we have vmware cloud which is really us taking our vmware cloud foundation technology and delivering that as a service in partnership with our public cloud providers but in particular this one with aws vmware cloud on aws we're combining that with our tanzu portfolio of technologies and these are really technologies focused at developers at folks driving devops building and operating modern applications and what we're doing is really bringing them together to simplify customers moving from their data centers into the cloud and then modernizing their applications it's a pattern that we see very very often this notion of migrate and then modernize right once you're on a modern cloud infrastructure makes it much easier to modernize your applications talk to me about some of the catalysts for this change and this offering of services was it you know catalyzed by some of the events we've seen in the world in the last 18 months and this acceleration of digital adoption yeah absolutely and we saw this across our customer base across many many different industries although as you can imagine those industries that that were really considered essential uh were the ones where we saw the biggest sorts of accelerations we saw a tremendous amount of people needing to support remote workers overnight right and cloud is a perfect use case for that but the challenge a lot of customers had was that they couldn't take the time to retool that they had to use what they already had and so something like vmware cloud was perfect for that because it allowed them to take what they were doing on-prem and seamlessly extend it into the cloud without any changes able to do that you know almost overnight right but at the same time what we also saw was the acceleration of their digital transformation people are now online they're needing to interact with an app over their phone to get something you know remotely delivered or to schedule maybe um an appointment for their pet because you know a lot of people got pets during the pandemic and so you just saw this rush toward digitization and these new applications need to be created and so as customers move their application estate into the cloud with vmware cloud and aws they then had this need to modernize those applications to be able to deliver them faster to respond fast to the very dynamic nature of what was happening during the pandemic so let's talk about uh some of the opportunities and the advantages that vmware cloud with tanzania service is going to deliver to those it admins who have to deliver things even faster yep so let me talk a bit about the tech and then talk about how that fits into uh what the users will experience so vmware cloud with tons of services is really two key components uh the first of which is the tanzu kubernetes grid service the tkg service as we call it so what this is is actually a deep integration of tonsil kubernetes grid with vmware cloud and and the kubernetes we've actually integrated into vmware cloud foundation folks who are familiar with vmware may remember that a couple of years ago we announced project pacific which was a deep integration of kubernetes into vsphere essentially enabling vsphere to have a kubernetes interface to be natively kubernetes and what that did was it enabled the i.t admins to have direct insight inside of kubernetes clusters to understand what was happening in terms of the containers and pods that that their developers were running it also allowed them to leverage uh their existing vsphere and vmware cloud foundation tooling on those workloads so fast forward today we we have this built in now and what we're doing is actually offering that as a service so that the customer doesn't need to deal with managing it installing it updating any of that stuff instead they can just leverage it they can start creating kubernetes clusters and upstream conformant kubernetes clusters to allow their developers to take advantage of those capabilities but also be able to use their native tooling on it so i think that's really really important is that the it admin really can enable their developers to seamlessly start to build and operate modern applications on top of vmware cloud got it and talk to me about how this is going to empower those it admins to become kubernetes operators yeah well i think that's exactly it you know we talk to a lot of these admins and and they're seeing the desire for kubernetes uh from their lines of business from you know from the app teams and the idea is that when you look start looking at the kubernetes ecosystem there's a whole bunch of new tooling and technology out there we find that people have to spend a lot of time figuring out what the right thing to use is and for a lot of these folks they say hey i've already figured out how to operate applications in production i've got the tooling i've got the standardization i got things like security figured out right super important and so the real benefit of this approach and this deep integration is it allows them to take those those tools those operational best practices that they already have and now apply them to these new workloads fairly seamlessly and so this is really about the power of leveraging all the investments they've made to take those forward with modern applications and the total adjustable market here is pretty big i heard your cto referring to that in an interview in september and i was looking at some recent vmware survey numbers where 80 of customers say they're deploying applications in highly distributed environments that include their own data center multiple clouds uh edge and also customers said hey 90 of our application initiatives are focused on modernization so vmware clearly sees the big tam here yeah it's absolutely massive um you know we see uh many customers the vast majority something like 75 percent are using multiple clouds or on-prem in the cloud we have some customers using even more than that and you see this very large application estate that's spread out across this and so you know i think what we're really looking at is how do we enable uh the right sorts of consistency both from an infrastructure perspective enabling things like security but also management across all these environments and by the way it's another exciting thing neglected to mention about this announcement vmware cloud with tonsil services not only includes the tonsil kubernetes grid service giving you that sort of kubernetes uh cluster as a service if you will but it also includes tons of mission control essentials and this is really the next generation of management when you start looking at modern applications and what tons of mission control focuses on is enabling managing kubernetes consistently across clouds and so this is the other really important point is that yes we want to make vmware cloud vmware cloud infrastructure the best place to build and operate applications especially modern ones but we also realize that you know customers are doing all sorts of things right they're in the native cloud whether that's aws or azure or google and they want ways of managing more consistently across all these environments in addition to their vmware environments both in the cloud and on-prem and so tons of mission control really enables that as well and that's another really powerful aspect of this is that it's built in to enable that next level of administration and management that consistency is critical right i mean that's probably one of the biggest benefits that customers are getting is that familiarity with the console the consistency of being able to manage so that they can deploy apps faster um that as businesses are still pivoting and changing direction in light of the pandemics i imagine that that is a huge uh from a business outcomes perspective the workforce productivity there is probably pretty pretty big yeah and i think it's also about managing risk as well you know one of the the biggest worries that we hear from many of the cios uh ctos executives that we talk to at our customers is this uh software supply chain risk like what is it exactly like what are the exact bits that they're running out there right in their applications because the reality is that um those apps are composed of many open source technologies and you know as we saw with solarwinds it's very possible for someone to get in and you know plant malicious code into their source repository such that as it gets built and flows out it'll you know just go out and customers will start using it and it's a huge huge security vulnerability and one thing on that note that customers are particularly worried about is the lack of consistency across their cloud environments that because things are done different ways and the different teams have different processes across different clouds it's easy for small mistakes to creep in there for little openings right that a hacker might be able to go and exploit and so i think this gets back to that notion of consistency and that you're right it's great for productivity but the one i think that's almost in some ways you might say uh for many of these folks more important for is from a security standpoint that they can validate and ensure they're in compliance with their security standards and by the way you know this is uh for most companies a board level discussion right the board is saying hey like do we have the right controls in place because it is um such an important thing and such a critical risk factor it is a critical risk factor we saw you mentioned solar winds but just in the last 18 months the the massive changes to the threat landscape the huge rise in ransomware and ddos attacks you know we had this scatterer everybody went home and you've got you know the edge is booming and you've got folks using uh you know not using their vpns and things when they should be so that the fact that that's a board level discussion and that this is going to help from a risk mitigation perspective that consistency that you talked about is huge i think for a customer in any industry yep yeah and it's pretty interesting as well like you mentioned ransomware so we're doing some work on that one as well actually not specifically with this announcement but it's another vmware cloud service that plugs into this uh seamlessly vmware cloud disaster recovery and one of the really cool features that we're announcing at vmworld this week is the ability to actually support and and maybe uh handle ransomware attacks and so the idea there is that if you do get compromised and what typically happens is that the hackers come in and they encrypt you know some of your data and they say hey if you want to get access to it you got to pay us and we'll decrypt it for you but if you have the right dr solution um that's backing up on a fairly continuous basis it means that whatever data might be encrypted you know would only be a small delta like the last let's say hour or two of data right and so what we're looking at is leveraging that dr solution to be able to very rapidly restore specific individual files uh that may have been compromised and so this is like one way that we're helping customers deal with that like obviously we want to put a whole bunch of other security protections in place and we do when we enable them to do that but one thing when you think about security is that it's very much defense in depth that you have multiple layers of the fail-safes there and so this one being kind of like the end result that hackers do get in they do manage to compromise it they do manage to get a hold of it and encrypt it well you still got unencrypted backups that you control and that you have um a very clean delineation and separation from just like kind of an architectural standpoint that the hackers won't be able to get at right so that you can control that and restore it so again you know this is something very top of mind for us and it's funny because we don't always lead with the security angle maybe we should as i'm saying it here but uh but it's something that's very very top of mind for a lot of our customers it's something that's also top of mind for us and that we're focused on it is because it's no longer if we get attacked it's one and they've got to be able to have the right recovery strategy so that they don't have to pay those ransoms and of course we only hear about the big ones like the solar winds and the colonial pipelines and there's many more going on when i get back to vmware cloud with tanzania services talk to me about how this fits into vmware's bigger picture yeah yeah yeah great question thanks for bringing me back i'd love to geek out on some of these things so um but when you take a step back so what we're really doing uh with vmware cloud is trying to provide this really powerful infrastructure layer uh that is available anywhere customers want to run applications and that could be in the public cloud it could be in the data center it could be at the edge it could be at all those locations and you know you mentioned edge earlier and i think we're seeing explosive growth there as well and so what we're really doing is driving uh broad optionality in terms of how customers want to adopt these technologies and then as i said we're sort of you know we're kind of going broad many locations we're also building up in each of those locations this notion of ponzu services being seamlessly integrated in doing that uh you know starting now with vmware cloud aws but expanding that to every every location that we have in addition you know we're also really excited another thing we're announcing this week called project arctic now the idea with arctic is really to start driving more choice and flexibility into how customers consume vmware cloud do they consume it as software or as a service and where do they do that so traditionally the only way to get it delivered as a service would be in the public cloud right vmware cloud aws you can click a few buttons and you get a software defined data center set up for you automatically now traditionally on-prem we haven't had that we we did do something pretty powerful uh a year or two back with the release of vmware cloud on dell emc we can deliver a service there but that often required new hardware you know new setup for customers and customers are coming back to us and saying hey like we've got these really large vsphere deployments how do we enable them to take advantage of all this great vmware cloud functionality from where they are today right they say hey we can't rebuild all these overnight but we want to take advantage of vmware cloud today so that's what really what project arctic is focused on it's focused on connecting into these brownfield existing vsphere environments and delivering some of the vmware cloud benefits there things like being able to easily well first of all be able to manage those environments through the vmware cloud console so now you have one place where you can see your on-prem deployments your cloud deployments everything being able to really easily move uh applications between on-prem and the cloud leveraging some of the vmware cloud disaster recovery capabilities i just mentioned like the ransomware example you can now do that even on prem as well because keep in mind it's people aren't attacking you know the hackers aren't attacking just the public cloud they're attacking data centers or anywhere else where these applications might be running and so arctic's a great example of where we're saying hey there's a bunch of cool stuff happening here but let's really meet customers where they're at and many of our customers still have a very large data center footprint still want to maintain that that's really strategic for them or as i said may even want to be extending to the edge so it's really about giving them more of that flexibility so in terms of meeting customers where they are i know vmware has been focused on that for probably its entire history we talk about that on the cube in every vmworld where can customers go like what's the right starting point is this targeted for vmware cloud on aws current customers what's kind of the next steps for customers to learn more about this yeah absolutely so there's a bunch of different ways so first of all there's a tremendous amount of activity happening here at vmworld um just all sorts of breakout sessions like you know detailed demos like all sorts of really cool stuff just a ton of content i'm actually kind of i'm in this new role i'm super excited about it but one thing i'm kind of bummed out about is i don't have as much time to go look at all these cool sessions so i highly recommend going and checking those out um you know we have hands-on labs as well which is another great way to test out and try vmware products so hold.vmware.com uh you can go and spin those things up and just kind of take them for a test drive see what they're all about and then if you go to vmc.vmware.com that is vmware cloud right we want to make it very easy to get started whether you're in just a vsphere on-prem customer or whether you already have vmware cloud and aws what you can see is that it's really easy to get started in that there's a ton of value-add services on top of our core infrastructure so it's all about making it accessible making it easy and simple to consume and get started with so there's a ton of options out there and i highly recommend folks go and check out all the things i just mentioned excellent kit thank you for joining me today talking about vmware cloud with tons of services what's new what's exciting the opportunities in it for customers from the i.t admin folks to be empowered to be kubernetes operators to those businesses being able to do essential services in a changing environment and again congratulations on your promotion that's very exciting awesome thank you lisa thank you for having me our pleasure for kit colbert i'm lisa martin you're watching thecube's coverage of vmworld 2021 [Music] you

>> Joy: Welcome to the Virtual Big Data Conference. Vertica is so excited to host this event. I'm Joy King, and I'll be your host for today's Big Data Conference Keynote Session. It's my honor and my genuine pleasure to lead Vertica's product and go-to-market strategy. And I'm so lucky to have a passionate and committed team who turned our Vertica BDC event, into a virtual event in a very short amount of time. I want to thank the thousands of people, and yes, that's our true number who have registered to attend this virtual event. We were determined to balance your health, safety and your peace of mind with the excitement of the Vertica BDC. This is a very unique event. Because as I hope you all know, we focus on engineering and architecture, best practice sharing and customer stories that will educate and inspire everyone. I also want to thank our top sponsors for the virtual BDC, Arrow, and Pure Storage. Our partnerships are so important to us and to everyone in the audience. Because together, we get things done faster and better. Now for today's keynote, you'll hear from three very important and energizing speakers. First, Colin Mahony, our SVP and General Manager for Vertica, will talk about the market trends that Vertica is betting on to win for our customers. And he'll share the exciting news about our Vertica 10 announcement and how this will benefit our customers. Then you'll hear from Amy Fowler, VP of strategy and solutions for FlashBlade at Pure Storage. Our partnership with Pure Storage is truly unique in the industry, because together modern infrastructure from Pure powers modern analytics from Vertica. And then you'll hear from John Yovanovich, Director of IT at AT&T, who will tell you about the Pure Vertica Symphony that plays live every day at AT&T. Here we go, Colin, over to you. >> Colin: Well, thanks a lot joy. And, I want to echo Joy's thanks to our sponsors, and so many of you who have helped make this happen. This is not an easy time for anyone. We were certainly looking forward to getting together in person in Boston during the Vertica Big Data Conference and Winning with Data. But I think all of you and our team have done a great job, scrambling and putting together a terrific virtual event. So really appreciate your time. I also want to remind people that we will make both the slides and the full recording available after this. So for any of those who weren't able to join live, that is still going to be available. Well, things have been pretty exciting here. And in the analytic space in general, certainly for Vertica, there's a lot happening. There are a lot of problems to solve, a lot of opportunities to make things better, and a lot of data that can really make every business stronger, more efficient, and frankly, more differentiated. For Vertica, though, we know that focusing on the challenges that we can directly address with our platform, and our people, and where we can actually make the biggest difference is where we ought to be putting our energy and our resources. I think one of the things that has made Vertica so strong over the years is our ability to focus on those areas where we can make a great difference. So for us as we look at the market, and we look at where we play, there are really three recent and some not so recent, but certainly picking up a lot of the market trends that have become critical for every industry that wants to Win Big With Data. We've heard this loud and clear from our customers and from the analysts that cover the market. If I were to summarize these three areas, this really is the core focus for us right now. We know that there's massive data growth. And if we can unify the data silos so that people can really take advantage of that data, we can make a huge difference. We know that public clouds offer tremendous advantages, but we also know that balance and flexibility is critical. And we all need the benefit that machine learning for all the types up to the end data science. We all need the benefits that they can bring to every single use case, but only if it can really be operationalized at scale, accurate and in real time. And the power of Vertica is, of course, how we're able to bring so many of these things together. Let me talk a little bit more about some of these trends. So one of the first industry trends that we've all been following probably now for over the last decade, is Hadoop and specifically HDFS. So many companies have invested, time, money, more importantly, people in leveraging the opportunity that HDFS brought to the market. HDFS is really part of a much broader storage disruption that we'll talk a little bit more about, more broadly than HDFS. But HDFS itself was really designed for petabytes of data, leveraging low cost commodity hardware and the ability to capture a wide variety of data formats, from a wide variety of data sources and applications. And I think what people really wanted, was to store that data before having to define exactly what structures they should go into. So over the last decade or so, the focus for most organizations is figuring out how to capture, store and frankly manage that data. And as a platform to do that, I think, Hadoop was pretty good. It certainly changed the way that a lot of enterprises think about their data and where it's locked up. In parallel with Hadoop, particularly over the last five years, Cloud Object Storage has also given every organization another option for collecting, storing and managing even more data. That has led to a huge growth in data storage, obviously, up on public clouds like Amazon and their S3, Google Cloud Storage and Azure Blob Storage just to name a few. And then when you consider regional and local object storage offered by cloud vendors all over the world, the explosion of that data, in leveraging this type of object storage is very real. And I think, as I mentioned, it's just part of this broader storage disruption that's been going on. But with all this growth in the data, in all these new places to put this data, every organization we talk to is facing even more challenges now around the data silo. Sure the data silos certainly getting bigger. And hopefully they're getting cheaper per bit. But as I said, the focus has really been on collecting, storing and managing the data. But between the new data lakes and many different cloud object storage combined with all sorts of data types from the complexity of managing all this, getting that business value has been very limited. This actually takes me to big bet number one for Team Vertica, which is to unify the data. Our goal, and some of the announcements we have made today plus roadmap announcements I'll share with you throughout this presentation. Our goal is to ensure that all the time, money and effort that has gone into storing that data, all the data turns into business value. So how are we going to do that? With a unified analytics platform that analyzes the data wherever it is HDFS, Cloud Object Storage, External tables in an any format ORC, Parquet, JSON, and of course, our own Native Roth Vertica format. Analyze the data in the right place in the right format, using a single unified tool. This is something that Vertica has always been committed to, and you'll see in some of our announcements today, we're just doubling down on that commitment. Let's talk a little bit more about the public cloud. This is certainly the second trend. It's the second wave maybe of data disruption with object storage. And there's a lot of advantages when it comes to public cloud. There's no question that the public clouds give rapid access to compute storage with the added benefit of eliminating data center maintenance that so many companies, want to get out of themselves. But maybe the biggest advantage that I see is the architectural innovation. The public clouds have introduced so many methodologies around how to provision quickly, separating compute and storage and really dialing-in the exact needs on demand, as you change workloads. When public clouds began, it made a lot of sense for the cloud providers and their customers to charge and pay for compute and storage in the ratio that each use case demanded. And I think you're seeing that trend, proliferate all over the place, not just up in public cloud. That architecture itself is really becoming the next generation architecture for on-premise data centers, as well. But there are a lot of concerns. I think we're all aware of them. They're out there many times for different workloads, there are higher costs. Especially if some of the workloads that are being run through analytics, which tend to run all the time. Just like some of the silo challenges that companies are facing with HDFS, data lakes and cloud storage, the public clouds have similar types of siloed challenges as well. Initially, there was a belief that they were cheaper than data centers, and when you added in all the costs, it looked that way. And again, for certain elastic workloads, that is the case. I don't think that's true across the board overall. Even to the point where a lot of the cloud vendors aren't just charging lower costs anymore. We hear from a lot of customers that they don't really want to tether themselves to any one cloud because of some of those uncertainties. Of course, security and privacy are a concern. We hear a lot of concerns with regards to cloud and even some SaaS vendors around shared data catalogs, across all the customers and not enough separation. But security concerns are out there, you can read about them. I'm not going to jump into that bandwagon. But we hear about them. And then, of course, I think one of the things we hear the most from our customers, is that each cloud stack is starting to feel even a lot more locked in than the traditional data warehouse appliance. And as everybody knows, the industry has been running away from appliances as fast as it can. And so they're not eager to get locked into another, quote, unquote, virtual appliance, if you will, up in the cloud. They really want to make sure they have flexibility in which clouds, they're going to today, tomorrow and in the future. And frankly, we hear from a lot of our customers that they're very interested in eventually mixing and matching, compute from one cloud with, say storage from another cloud, which I think is something that we'll hear a lot more about. And so for us, that's why we've got our big bet number two. we love the cloud. We love the public cloud. We love the private clouds on-premise, and other hosting providers. But our passion and commitment is for Vertica to be able to run in any of the clouds that our customers choose, and make it portable across those clouds. We have supported on-premises and all public clouds for years. And today, we have announced even more support for Vertica in Eon Mode, the deployment option that leverages the separation of compute from storage, with even more deployment choices, which I'm going to also touch more on as we go. So super excited about our big bet number two. And finally as I mentioned, for all the hype that there is around machine learning, I actually think that most importantly, this third trend that team Vertica is determined to address is the need to bring business critical, analytics, machine learning, data science projects into production. For so many years, there just wasn't enough data available to justify the investment in machine learning. Also, processing power was expensive, and storage was prohibitively expensive. But to train and score and evaluate all the different models to unlock the full power of predictive analytics was tough. Today you have those massive data volumes. You have the relatively cheap processing power and storage to make that dream a reality. And if you think about this, I mean with all the data that's available to every company, the real need is to operationalize the speed and the scale of machine learning so that these organizations can actually take advantage of it where they need to. I mean, we've seen this for years with Vertica, going back to some of the most advanced gaming companies in the early days, they were incorporating this with live data directly into their gaming experiences. Well, every organization wants to do that now. And the accuracy for clickability and real time actions are all key to separating the leaders from the rest of the pack in every industry when it comes to machine learning. But if you look at a lot of these projects, the reality is that there's a ton of buzz, there's a ton of hype spanning every acronym that you can imagine. But most companies are struggling, do the separate teams, different tools, silos and the limitation that many platforms are facing, driving, down sampling to get a small subset of the data, to try to create a model that then doesn't apply, or compromising accuracy and making it virtually impossible to replicate models, and understand decisions. And if there's one thing that we've learned when it comes to data, prescriptive data at the atomic level, being able to show end of one as we refer to it, meaning individually tailored data. No matter what it is healthcare, entertainment experiences, like gaming or other, being able to get at the granular data and make these decisions, make that scoring applies to machine learning just as much as it applies to giving somebody a next-best-offer. But the opportunity has never been greater. The need to integrate this end-to-end workflow and support the right tools without compromising on that accuracy. Think about it as no downsampling, using all the data, it really is key to machine learning success. Which should be no surprise then why the third big bet from Vertica is one that we've actually been working on for years. And we're so proud to be where we are today, helping the data disruptors across the world operationalize machine learning. This big bet has the potential to truly unlock, really the potential of machine learning. And today, we're announcing some very important new capabilities specifically focused on unifying the work being done by the data science community, with their preferred tools and platforms, and the volume of data and performance at scale, available in Vertica. Our strategy has been very consistent over the last several years. As I said in the beginning, we haven't deviated from our strategy. Of course, there's always things that we add. Most of the time, it's customer driven, it's based on what our customers are asking us to do. But I think we've also done a great job, not trying to be all things to all people. Especially as these hype cycles flare up around us, we absolutely love participating in these different areas without getting completely distracted. I mean, there's a variety of query tools and data warehouses and analytics platforms in the market. We all know that. There are tools and platforms that are offered by the public cloud vendors, by other vendors that support one or two specific clouds. There are appliance vendors, who I was referring to earlier who can deliver package data warehouse offerings for private data centers. And there's a ton of popular machine learning tools, languages and other kits. But Vertica is the only advanced analytic platform that can do all this, that can bring it together. We can analyze the data wherever it is, in HDFS, S3 Object Storage, or Vertica itself. Natively we support multiple clouds on-premise deployments, And maybe most importantly, we offer that choice of deployment modes to allow our customers to choose the architecture that works for them right now. It still also gives them the option to change move, evolve over time. And Vertica is the only analytics database with end-to-end machine learning that can truly operationalize ML at scale. And I know it's a mouthful. But it is not easy to do all these things. It is one of the things that highly differentiates Vertica from the rest of the pack. It is also why our customers, all of you continue to bet on us and see the value that we are delivering and we will continue to deliver. Here's a couple of examples of some of our customers who are powered by Vertica. It's the scale of data. It's the millisecond response times. Performance and scale have always been a huge part of what we have been about, not the only thing. I think the functionality all the capabilities that we add to the platform, the ease of use, the flexibility, obviously with the deployment. But if you look at some of the numbers they are under these customers on this slide. And I've shared a lot of different stories about these customers. Which, by the way, it still amaze me every time I talk to one and I get the updates, you can see the power and the difference that Vertica is making. Equally important, if you look at a lot of these customers, they are the epitome of being able to deploy Vertica in a lot of different environments. Many of the customers on this slide are not using Vertica just on-premise or just in the cloud. They're using it in a hybrid way. They're using it in multiple different clouds. And again, we've been with them on that journey throughout, which is what has made this product and frankly, our roadmap and our vision exactly what it is. It's been quite a journey. And that journey continues now with the Vertica 10 release. The Vertica 10 release is obviously a massive release for us. But if you look back, you can see that building on that native columnar architecture that started a long time ago, obviously, with the C-Store paper. We built it to leverage that commodity hardware, because it was an architecture that was never tightly integrated with any specific underlying infrastructure. I still remember hearing the initial pitch from Mike Stonebreaker, about the vision of Vertica as a software only solution and the importance of separating the company from hardware innovation. And at the time, Mike basically said to me, "there's so much R&D in innovation that's going to happen in hardware, we shouldn't bake hardware into our solution. We should do it in software, and we'll be able to take advantage of that hardware." And that is exactly what has happened. But one of the most recent innovations that we embraced with hardware is certainly that separation of compute and storage. As I said previously, the public cloud providers offered this next generation architecture, really to ensure that they can provide the customers exactly what they needed, more compute or more storage and charge for each, respectively. The separation of compute and storage, compute from storage is a major milestone in data center architectures. If you think about it, it's really not only a public cloud innovation, though. It fundamentally redefines the next generation data architecture for on-premise and for pretty much every way people are thinking about computing today. And that goes for software too. Object storage is an example of the cost effective means for storing data. And even more importantly, separating compute from storage for analytic workloads has a lot of advantages. Including the opportunity to manage much more dynamic, flexible workloads. And more importantly, truly isolate those workloads from others. And by the way, once you start having something that can truly isolate workloads, then you can have the conversations around autonomic computing, around setting up some nodes, some compute resources on the data that won't affect any of the other data to do some things on their own, maybe some self analytics, by the system, etc. A lot of things that many of you know we've already been exploring in terms of our own system data in the product. But it was May 2018, believe it or not, it seems like a long time ago where we first announced Eon Mode and I want to make something very clear, actually about Eon mode. It's a mode, it's a deployment option for Vertica customers. And I think this is another huge benefit that we don't talk about enough. But unlike a lot of vendors in the market who will dig you and charge you for every single add-on like hit-buy, you name it. You get this with the Vertica product. If you continue to pay support and maintenance, this comes with the upgrade. This comes as part of the new release. So any customer who owns or buys Vertica has the ability to set up either an Enterprise Mode or Eon Mode, which is a question I know that comes up sometimes. Our first announcement of Eon was obviously AWS customers, including the trade desk, AT&T. Most of whom will be speaking here later at the Virtual Big Data Conference. They saw a huge opportunity. Eon Mode, not only allowed Vertica to scale elastically with that specific compute and storage that was needed, but it really dramatically simplified database operations including things like workload balancing, node recovery, compute provisioning, etc. So one of the most popular functions is that ability to isolate the workloads and really allocate those resources without negatively affecting others. And even though traditional data warehouses, including Vertica Enterprise Mode have been able to do lots of different workload isolation, it's never been as strong as Eon Mode. Well, it certainly didn't take long for our customers to see that value across the board with Eon Mode. Not just up in the cloud, in partnership with one of our most valued partners and a platinum sponsor here. Joy mentioned at the beginning. We announced Vertica Eon Mode for Pure Storage FlashBlade in September 2019. And again, just to be clear, this is not a new product, it's one Vertica with yet more deployment options. With Pure Storage, Vertica in Eon mode is not limited in any way by variable cloud, network latency. The performance is actually amazing when you take the benefits of separate and compute from storage and you run it with a Pure environment on-premise. Vertica in Eon Mode has a super smart cache layer that we call the depot. It's a big part of our secret sauce around Eon mode. And combined with the power and performance of Pure's FlashBlade, Vertica became the industry's first advanced analytics platform that actually separates compute and storage for on-premises data centers. Something that a lot of our customers are already benefiting from, and we're super excited about it. But as I said, this is a journey. We don't stop, we're not going to stop. Our customers need the flexibility of multiple public clouds. So today with Vertica 10, we're super proud and excited to announce support for Vertica in Eon Mode on Google Cloud. This gives our customers the ability to use their Vertica licenses on Amazon AWS, on-premise with Pure Storage and on Google Cloud. Now, we were talking about HDFS and a lot of our customers who have invested quite a bit in HDFS as a place, especially to store data have been pushing us to support Eon Mode with HDFS. So as part of Vertica 10, we are also announcing support for Vertica in Eon Mode using HDFS as the communal storage. Vertica's own Roth format data can be stored in HDFS, and actually the full functionality of Vertica is complete analytics, geospatial pattern matching, time series, machine learning, everything that we have in there can be applied to this data. And on the same HDFS nodes, Vertica can actually also analyze data in ORC or Parquet format, using External tables. We can also execute joins between the Roth data the External table holds, which powers a much more comprehensive view. So again, it's that flexibility to be able to support our customers, wherever they need us to support them on whatever platform, they have. Vertica 10 gives us a lot more ways that we can deploy Eon Mode in various environments for our customers. It allows them to take advantage of Vertica in Eon Mode and the power that it brings with that separation, with that workload isolation, to whichever platform they are most comfortable with. Now, there's a lot that has come in Vertica 10. I'm definitely not going to be able to cover everything. But we also introduced complex types as an example. And complex data types fit very well into Eon as well in this separation. They significantly reduce the data pipeline, the cost of moving data between those, a much better support for unstructured data, which a lot of our customers have mixed with structured data, of course, and they leverage a lot of columnar execution that Vertica provides. So you get complex data types in Vertica now, a lot more data, stronger performance. It goes great with the announcement that we made with the broader Eon Mode. Let's talk a little bit more about machine learning. We've been actually doing work in and around machine learning with various extra regressions and a whole bunch of other algorithms for several years. We saw the huge advantage that MPP offered, not just as a sequel engine as a database, but for ML as well. Didn't take as long to realize that there's a lot more to operationalizing machine learning than just those algorithms. It's data preparation, it's that model trade training. It's the scoring, the shaping, the evaluation. That is so much of what machine learning and frankly, data science is about. You do know, everybody always wants to jump to the sexy algorithm and we handle those tasks very, very well. It makes Vertica a terrific platform to do that. A lot of work in data science and machine learning is done in other tools. I had mentioned that there's just so many tools out there. We want people to be able to take advantage of all that. We never believed we were going to be the best algorithm company or come up with the best models for people to use. So with Vertica 10, we support PMML. We can import now and export PMML models. It's a huge step for us around that operationalizing machine learning projects for our customers. Allowing the models to get built outside of Vertica yet be imported in and then applying to that full scale of data with all the performance that you would expect from Vertica. We also are more tightly integrating with Python. As many of you know, we've been doing a lot of open source projects with the community driven by many of our customers, like Uber. And so now with Python we've integrated with TensorFlow, allowing data scientists to build models in their preferred language, to take advantage of TensorFlow. But again, to store and deploy those models at scale with Vertica. I think both these announcements are proof of our big bet number three, and really our commitment to supporting innovation throughout the community by operationalizing ML with that accuracy, performance and scale of Vertica for our customers. Again, there's a lot of steps when it comes to the workflow of machine learning. These are some of them that you can see on the slide, and it's definitely not linear either. We see this as a circle. And companies that do it, well just continue to learn, they continue to rescore, they continue to redeploy and they want to operationalize all that within a single platform that can take advantage of all those capabilities. And that is the platform, with a very robust ecosystem that Vertica has always been committed to as an organization and will continue to be. This graphic, many of you have seen it evolve over the years. Frankly, if we put everything and everyone on here wouldn't fit on a slide. But it will absolutely continue to evolve and grow as we support our customers, where they need the support most. So, again, being able to deploy everywhere, being able to take advantage of Vertica, not just as a business analyst or a business user, but as a data scientists or as an operational or BI person. We want Vertica to be leveraged and used by the broader organization. So I think it's fair to say and I encourage everybody to learn more about Vertica 10, because I'm just highlighting some of the bigger aspects of it. But we talked about those three market trends. The need to unify the silos, the need for hybrid multiple cloud deployment options, the need to operationalize business critical machine learning projects. Vertica 10 has absolutely delivered on those. But again, we are not going to stop. It is our job not to, and this is how Team Vertica thrives. I always joke that the next release is the best release. And, of course, even after Vertica 10, that is also true, although Vertica 10 is pretty awesome. But, you know, from the first line of code, we've always been focused on performance and scale, right. And like any really strong data platform, the execution engine, the optimizer and the execution engine are the two core pieces of that. Beyond Vertica 10, some of the big things that we're already working on, next generation execution engine. We're already actually seeing incredible early performance from this. And this is just one example, of how important it is for an organization like Vertica to constantly go back and re-innovate. Every single release, we do the sit ups and crunches, our performance and scale. How do we improve? And there's so many parts of the core server, there's so many parts of our broader ecosystem. We are constantly looking at coverages of how we can go back to all the code lines that we have, and make them better in the current environment. And it's not an easy thing to do when you're doing that, and you're also expanding in the environment that we are expanding into to take advantage of the different deployments, which is a great segue to this slide. Because if you think about today, we're obviously already available with Eon Mode and Amazon, AWS and Pure and actually MinIO as well. As I talked about in Vertica 10 we're adding Google and HDFS. And coming next, obviously, Microsoft Azure, Alibaba cloud. So being able to expand into more of these environments is really important for the Vertica team and how we go forward. And it's not just running in these clouds, for us, we want it to be a SaaS like experience in all these clouds. We want you to be able to deploy Vertica in 15 minutes or less on these clouds. You can also consume Vertica, in a lot of different ways, on these clouds. As an example, in Amazon Vertica by the Hour. So for us, it's not just about running, it's about taking advantage of the ecosystems that all these cloud providers offer, and really optimizing the Vertica experience as part of them. Optimization, around automation, around self service capabilities, extending our management console, we now have products that like the Vertica Advisor Tool that our Customer Success Team has created to actually use our own smarts in Vertica. To take data from customers that give it to us and help them tune automatically their environment. You can imagine that we're taking that to the next level, in a lot of different endeavors that we're doing around how Vertica as a product can actually be smarter because we all know that simplicity is key. There just aren't enough people in the world who are good at managing data and taking it to the next level. And of course, other things that we all hear about, whether it's Kubernetes and containerization. You can imagine that that probably works very well with the Eon Mode and separating compute and storage. But innovation happens everywhere. We innovate around our community documentation. Many of you have taken advantage of the Vertica Academy. The numbers there are through the roof in terms of the number of people coming in and certifying on it. So there's a lot of things that are within the core products. There's a lot of activity and action beyond the core products that we're taking advantage of. And let's not forget why we're here, right? It's easy to talk about a platform, a data platform, it's easy to jump into all the functionality, the analytics, the flexibility, how we can offer it. But at the end of the day, somebody, a person, she's got to take advantage of this data, she's got to be able to take this data and use this information to make a critical business decision. And that doesn't happen unless we explore lots of different and frankly, new ways to get that predictive analytics UI and interface beyond just the standard BI tools in front of her at the right time. And so there's a lot of activity, I'll tease you with that going on in this organization right now about how we can do that and deliver that for our customers. We're in a great position to be able to see exactly how this data is consumed and used and start with this core platform that we have to go out. Look, I know, the plan wasn't to do this as a virtual BDC. But I really appreciate you tuning in. Really appreciate your support. I think if there's any silver lining to us, maybe not being able to do this in person, it's the fact that the reach has actually gone significantly higher than what we would have been able to do in person in Boston. We're certainly looking forward to doing a Big Data Conference in the future. But if I could leave you with anything, know this, since that first release for Vertica, and our very first customers, we have been very consistent. We respect all the innovation around us, whether it's open source or not. We understand the market trends. We embrace those new ideas and technologies and for us true north, and the most important thing is what does our customer need to do? What problem are they trying to solve? And how do we use the advantages that we have without disrupting our customers? But knowing that you depend on us to deliver that unified analytics strategy, it will deliver that performance of scale, not only today, but tomorrow and for years to come. We've added a lot of great features to Vertica. I think we've said no to a lot of things, frankly, that we just knew we wouldn't be the best company to deliver. When we say we're going to do things we do them. Vertica 10 is a perfect example of so many of those things that we from you, our customers have heard loud and clear, and we have delivered. I am incredibly proud of this team across the board. I think the culture of Vertica, a customer first culture, jumping in to help our customers win no matter what is also something that sets us massively apart. I hear horror stories about support experiences with other organizations. And people always seem to be amazed at Team Vertica's willingness to jump in or their aptitude for certain technical capabilities or understanding the business. And I think sometimes we take that for granted. But that is the team that we have as Team Vertica. We are incredibly excited about Vertica 10. I think you're going to love the Virtual Big Data Conference this year. I encourage you to tune in. Maybe one other benefit is I know some people were worried about not being able to see different sessions because they were going to overlap with each other well now, even if you can't do it live, you'll be able to do those sessions on demand. Please enjoy the Vertica Big Data Conference here in 2020. Please you and your families and your co-workers be safe during these times. I know we will get through it. And analytics is probably going to help with a lot of that and we already know it is helping in many different ways. So believe in the data, believe in data's ability to change the world for the better. And thank you for your time. And with that, I am delighted to now introduce Micro Focus CEO Stephen Murdoch to the Vertica Big Data Virtual Conference. Thank you Stephen. >> Stephen: Hi, everyone, my name is Stephen Murdoch. I have the pleasure and privilege of being the Chief Executive Officer here at Micro Focus. Please let me add my welcome to the Big Data Conference. And also my thanks for your support, as we've had to pivot to this being virtual rather than a physical conference. Its amazing how quickly we all reset to a new normal. I certainly didn't expect to be addressing you from my study. Vertica is an incredibly important part of Micro Focus family. Is key to our goal of trying to enable and help customers become much more data driven across all of their IT operations. Vertica 10 is a huge step forward, we believe. It allows for multi-cloud innovation, genuinely hybrid deployments, begin to leverage machine learning properly in the enterprise, and also allows the opportunity to unify currently siloed lakes of information. We operate in a very noisy, very competitive market, and there are people, who are in that market who can do some of those things. The reason we are so excited about Vertica is we genuinely believe that we are the best at doing all of those things. And that's why we've announced publicly, you're under executing internally, incremental investment into Vertica. That investments targeted at accelerating the roadmaps that already exist. And getting that innovation into your hands faster. This idea is speed is key. It's not a question of if companies have to become data driven organizations, it's a question of when. So that speed now is really important. And that's why we believe that the Big Data Conference gives a great opportunity for you to accelerate your own plans. You will have the opportunity to talk to some of our best architects, some of the best development brains that we have. But more importantly, you'll also get to hear from some of our phenomenal Roth Data customers. You'll hear from Uber, from the Trade Desk, from Philips, and from AT&T, as well as many many others. And just hearing how those customers are using the power of Vertica to accelerate their own, I think is the highlight. And I encourage you to use this opportunity to its full. Let me close by, again saying thank you, we genuinely hope that you get as much from this virtual conference as you could have from a physical conference. And we look forward to your engagement, and we look forward to hearing your feedback. With that, thank you very much. >> Joy: Thank you so much, Stephen, for joining us for the Vertica Big Data Conference. Your support and enthusiasm for Vertica is so clear, and it makes a big difference. Now, I'm delighted to introduce Amy Fowler, the VP of Strategy and Solutions for FlashBlade at Pure Storage, who was one of our BDC Platinum Sponsors, and one of our most valued partners. It was a proud moment for me, when we announced Vertica in Eon mode for Pure Storage FlashBlade and we became the first analytics data warehouse that separates compute from storage for on-premise data centers. Thank you so much, Amy, for joining us. Let's get started. >> Amy: Well, thank you, Joy so much for having us. And thank you all for joining us today, virtually, as we may all be. So, as we just heard from Colin Mahony, there are some really interesting trends that are happening right now in the big data analytics market. From the end of the Hadoop hype cycle, to the new cloud reality, and even the opportunity to help the many data science and machine learning projects move from labs to production. So let's talk about these trends in the context of infrastructure. And in particular, look at why a modern storage platform is relevant as organizations take on the challenges and opportunities associated with these trends. The answer is the Hadoop hype cycles left a lot of data in HDFS data lakes, or reservoirs or swamps depending upon the level of the data hygiene. But without the ability to get the value that was promised from Hadoop as a platform rather than a distributed file store. And when we combine that data with the massive volume of data in Cloud Object Storage, we find ourselves with a lot of data and a lot of silos, but without a way to unify that data and find value in it. Now when you look at the infrastructure data lakes are traditionally built on, it is often direct attached storage or data. The approach that Hadoop took when it entered the market was primarily bound by the limits of networking and storage technologies. One gig ethernet and slower spinning disk. But today, those barriers do not exist. And all FlashStorage has fundamentally transformed how data is accessed, managed and leveraged. The need for local data storage for significant volumes of data has been largely mitigated by the performance increases afforded by all Flash. At the same time, organizations can achieve superior economies of scale with that segregation of compute and storage. With compute and storage, you don't always scale in lockstep. Would you want to add an engine to the train every time you add another boxcar? Probably not. But from a Pure Storage perspective, FlashBlade is uniquely architected to allow customers to achieve better resource utilization for compute and storage, while at the same time, reducing complexity that has arisen from the siloed nature of the original big data solutions. The second and equally important recent trend we see is something I'll call cloud reality. The public clouds made a lot of promises and some of those promises were delivered. But cloud economics, especially usage based and elastic scaling, without the control that many companies need to manage the financial impact is causing a lot of issues. In addition, the risk of vendor lock-in from data egress, charges, to integrated software stacks that can't be moved or deployed on-premise is causing a lot of organizations to back off the all the way non-cloud strategy, and move toward hybrid deployments. Which is kind of funny in a way because it wasn't that long ago that there was a lot of talk about no more data centers. And for example, one large retailer, I won't name them, but I'll admit they are my favorites. They several years ago told us they were completely done with on-prem storage infrastructure, because they were going 100% to the cloud. But they just deployed FlashBlade for their data pipelines, because they need predictable performance at scale. And the all cloud TCO just didn't add up. Now, that being said, well, there are certainly challenges with the public cloud. It has also brought some things to the table that we see most organizations wanting. First of all, in a lot of cases applications have been built to leverage object storage platforms like S3. So they need that object protocol, but they may also need it to be fast. And the said object may be oxymoron only a few years ago, and this is an area of the market where Pure and FlashBlade have really taken a leadership position. Second, regardless of where the data is physically stored, organizations want the best elements of a cloud experience. And for us, that means two main things. Number one is simplicity and ease of use. If you need a bunch of storage experts to run the system, that should be considered a bug. The other big one is the consumption model. The ability to pay for what you need when you need it, and seamlessly grow your environment over time totally nondestructively. This is actually pretty huge and something that a lot of vendors try to solve for with finance programs. But no finance program can address the pain of a forklift upgrade, when you need to move to next gen hardware. To scale nondestructively over long periods of time, five to 10 years plus is a crucial architectural decisions need to be made at the outset. Plus, you need the ability to pay as you use it. And we offer something for FlashBlade called Pure as a Service, which delivers exactly that. The third cloud characteristic that many organizations want is the option for hybrid. Even if that is just a DR site in the cloud. In our case, that means supporting appplication of S3, at the AWS. And the final trend, which to me represents the biggest opportunity for all of us, is the need to help the many data science and machine learning projects move from labs to production. This means bringing all the machine learning functions and model training to the data, rather than moving samples or segments of data to separate platforms. As we all know, machine learning needs a ton of data for accuracy. And there is just too much data to retrieve from the cloud for every training job. At the same time, predictive analytics without accuracy is not going to deliver the business advantage that everyone is seeking. You can kind of visualize data analytics as it is traditionally deployed as being on a continuum. With that thing, we've been doing the longest, data warehousing on one end, and AI on the other end. But the way this manifests in most environments is a series of silos that get built up. So data is duplicated across all kinds of bespoke analytics and AI, environments and infrastructure. This creates an expensive and complex environment. So historically, there was no other way to do it because some level of performance is always table stakes. And each of these parts of the data pipeline has a different workload profile. A single platform to deliver on the multi dimensional performances, diverse set of applications required, that didn't exist three years ago. And that's why the application vendors pointed you towards bespoke things like DAS environments that we talked about earlier. And the fact that better options exists today is why we're seeing them move towards supporting this disaggregation of compute and storage. And when it comes to a platform that is a better option, one with a modern architecture that can address the diverse performance requirements of this continuum, and allow organizations to bring a model to the data instead of creating separate silos. That's exactly what FlashBlade is built for. Small files, large files, high throughput, low latency and scale to petabytes in a single namespace. And this is importantly a single rapid space is what we're focused on delivering for our customers. At Pure, we talk about it in the context of modern data experience because at the end of the day, that's what it's really all about. The experience for your teams in your organization. And together Pure Storage and Vertica have delivered that experience to a wide range of customers. From a SaaS analytics company, which uses Vertica on FlashBlade to authenticate the quality of digital media in real time, to a multinational car company, which uses Vertica on FlashBlade to make thousands of decisions per second for autonomous cars, or a healthcare organization, which uses Vertica on FlashBlade to enable healthcare providers to make real time decisions that impact lives. And I'm sure you're all looking forward to hearing from John Yavanovich from AT&T. To hear how he's been doing this with Vertica and FlashBlade as well. He's coming up soon. We have been really excited to build this partnership with Vertica. And we're proud to provide the only on-premise storage platform validated with Vertica Eon Mode. And deliver this modern data experience to our customers together. Thank you all so much for joining us today. >> Joy: Amy, thank you so much for your time and your insights. Modern infrastructure is key to modern analytics, especially as organizations leverage next generation data center architectures, and object storage for their on-premise data centers. Now, I'm delighted to introduce our last speaker in our Vertica Big Data Conference Keynote, John Yovanovich, Director of IT for AT&T. Vertica is so proud to serve AT&T, and especially proud of the harmonious impact we are having in partnership with Pure Storage. John, welcome to the Virtual Vertica BDC. >> John: Thank you joy. It's a pleasure to be here. And I'm excited to go through this presentation today. And in a unique fashion today 'cause as I was thinking through how I wanted to present the partnership that we have formed together between Pure Storage, Vertica and AT&T, I want to emphasize how well we all work together and how these three components have really driven home, my desire for a harmonious to use your word relationship. So, I'm going to move forward here and with. So here, what I'm going to do the theme of today's presentation is the Pure Vertica Symphony live at AT&T. And if anybody is a Westworld fan, you can appreciate the sheet music on the right hand side. What we're going to what I'm going to highlight here is in a musical fashion, is how we at AT&T leverage these technologies to save money to deliver a more efficient platform, and to actually just to make our customers happier overall. So as we look back, and back as early as just maybe a few years ago here at AT&T, I realized that we had many musicians to help the company. Or maybe you might want to call them data scientists, or data analysts. For the theme we'll stay with musicians. None of them were singing or playing from the same hymn book or sheet music. And so what we had was many organizations chasing a similar dream, but not exactly the same dream. And, best way to describe that is and I think with a lot of people this might resonate in your organizations. How many organizations are chasing a customer 360 view in your company? Well, I can tell you that I have at least four in my company. And I'm sure there are many that I don't know of. That is our problem because what we see is a repetitive sourcing of data. We see a repetitive copying of data. And there's just so much money to be spent. This is where I asked Pure Storage and Vertica to help me solve that problem with their technologies. What I also noticed was that there was no coordination between these departments. In fact, if you look here, nobody really wants to play with finance. Sales, marketing and care, sure that you all copied each other's data. But they actually didn't communicate with each other as they were copying the data. So the data became replicated and out of sync. This is a challenge throughout, not just my company, but all companies across the world. And that is, the more we replicate the data, the more problems we have at chasing or conquering the goal of single version of truth. In fact, I kid that I think that AT&T, we actually have adopted the multiple versions of truth, techno theory, which is not where we want to be, but this is where we are. But we are conquering that with the synergies between Pure Storage and Vertica. This is what it leaves us with. And this is where we are challenged and that if each one of our siloed business units had their own stories, their own dedicated stories, and some of them had more money than others so they bought more storage. Some of them anticipating storing more data, and then they really did. Others are running out of space, but can't put anymore because their bodies aren't been replenished. So if you look at it from this side view here, we have a limited amount of compute or fixed compute dedicated to each one of these silos. And that's because of the, wanting to own your own. And the other part is that you are limited or wasting space, depending on where you are in the organization. So there were the synergies aren't just about the data, but actually the compute and the storage. And I wanted to tackle that challenge as well. So I was tackling the data. I was tackling the storage, and I was tackling the compute all at the same time. So my ask across the company was can we just please play together okay. And to do that, I knew that I wasn't going to tackle this by getting everybody in the same room and getting them to agree that we needed one account table, because they will argue about whose account table is the best account table. But I knew that if I brought the account tables together, they would soon see that they had so much redundancy that I can now start retiring data sources. I also knew that if I brought all the compute together, that they would all be happy. But I didn't want them to tackle across tackle each other. And in fact that was one of the things that all business units really enjoy. Is they enjoy the silo of having their own compute, and more or less being able to control their own destiny. Well, Vertica's subclustering allows just that. And this is exactly what I was hoping for, and I'm glad they've brought through. And finally, how did I solve the problem of the single account table? Well when you don't have dedicated storage, and you can separate compute and storage as Vertica in Eon Mode does. And we store the data on FlashBlades, which you see on the left and right hand side, of our container, which I can describe in a moment. Okay, so what we have here, is we have a container full of compute with all the Vertica nodes sitting in the middle. Two loader, we'll call them loader subclusters, sitting on the sides, which are dedicated to just putting data onto the FlashBlades, which is sitting on both ends of the container. Now today, I have two dedicated storage or common dedicated might not be the right word, but two storage racks one on the left one on the right. And I treat them as separate storage racks. They could be one, but i created them separately for disaster recovery purposes, lashing work in case that rack were to go down. But that being said, there's no reason why I'm probably going to add a couple of them here in the future. So I can just have a, say five to 10, petabyte storage, setup, and I'll have my DR in another 'cause the DR shouldn't be in the same container. Okay, but I'll DR outside of this container. So I got them all together, I leveraged subclustering, I leveraged separate and compute. I was able to convince many of my clients that they didn't need their own account table, that they were better off having one. I eliminated, I reduced latency, I reduced our ticketing I reduce our data quality issues AKA ticketing okay. I was able to expand. What is this? As work. I was able to leverage elasticity within this cluster. As you can see, there are racks and racks of compute. We set up what we'll call the fixed capacity that each of the business units needed. And then I'm able to ramp up and release the compute that's necessary for each one of my clients based on their workloads throughout the day. And so while they compute to the right before you see that the instruments have already like, more or less, dedicated themselves towards all those are free for anybody to use. So in essence, what I have, is I have a concert hall with a lot of seats available. So if I want to run a 10 chair Symphony or 80, chairs, Symphony, I'm able to do that. And all the while, I can also do the same with my loader nodes. I can expand my loader nodes, to actually have their own Symphony or write all to themselves and not compete with any other workloads of the other clusters. What does that change for our organization? Well, it really changes the way our database administrators actually do their jobs. This has been a big transformation for them. They have actually become data conductors. Maybe you might even call them composers, which is interesting, because what I've asked them to do is morph into less technology and more workload analysis. And in doing so we're able to write auto-detect scripts, that watch the queues, watch the workloads so that we can help ramp up and trim down the cluster and subclusters as necessary. There has been an exciting transformation for our DBAs, who I need to now classify as something maybe like DCAs. I don't know, I have to work with HR on that. But I think it's an exciting future for their careers. And if we bring it all together, If we bring it all together, and then our clusters, start looking like this. Where everything is moving in harmonious, we have lots of seats open for extra musicians. And we are able to emulate a cloud experience on-prem. And so, I want you to sit back and enjoy the Pure Vertica Symphony live at AT&T. (soft music) >> Joy: Thank you so much, John, for an informative and very creative look at the benefits that AT&T is getting from its Pure Vertica symphony. I do really like the idea of engaging HR to change the title to Data Conductor. That's fantastic. I've always believed that music brings people together. And now it's clear that analytics at AT&T is part of that musical advantage. So, now it's time for a short break. And we'll be back for our breakout sessions, beginning at 12 pm Eastern Daylight Time. We have some really exciting sessions planned later today. And then again, as you can see on Wednesday. Now because all of you are already logged in and listening to this keynote, you already know the steps to continue to participate in the sessions that are listed here and on the previous slide. In addition, everyone received an email yesterday, today, and you'll get another one tomorrow, outlining the simple steps to register, login and choose your session. If you have any questions, check out the emails or go to www.vertica.com/bdc2020 for the logistics information. There are a lot of choices and that's always a good thing. Don't worry if you want to attend one or more or can't listen to these live sessions due to your timezone. All the sessions, including the Q&A sections will be available on demand and everyone will have access to the recordings as well as even more pre-recorded sessions that we'll post to the BDC website. Now I do want to leave you with two other important sites. First, our Vertica Academy. Vertica Academy is available to everyone. And there's a variety of very technical, self-paced, on-demand training, virtual instructor-led workshops, and Vertica Essentials Certification. And it's all free. Because we believe that Vertica expertise, helps everyone accelerate their Vertica projects and the advantage that those projects deliver. Now, if you have questions or want to engage with our Vertica engineering team now, we're waiting for you on the Vertica forum. We'll answer any questions or discuss any ideas that you might have. Thank you again for joining the Vertica Big Data Conference Keynote Session. Enjoy the rest of the BDC because there's a lot more to come

from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone live here in San Francisco California Moscone West is the cubes live coverage of Red Hat Summer 2018 I'm John furry and my co-host John Troyer our next guest is Denise Dumas vice president software engineering operating system group the Red Hat welcome back to the cube good to see you thank you so much great to be here with you so operating systems Linux the base base with everything yeah now you got all those other goodness going on you have some acquisitions permit bit we were just talking about before he came on a lot of action going on yeah what's new well you know you think that the world of operating systems would be boring but honest to god it is so not especially now right because there is a whole generation of change going on in the hardware and when the hardware changes the operating system has got to change to keep up right you look at the stuff that's going on with GPUs with FPGA right I mean and that's just like tip of the iceberg yeah and everything has to be programmable so you need software to keep track of it so it's not just the patches you gotta keep on top of the DevOps automations a big part of it and security models are changing with the cloud there's no perimeter so you have to have maybe chip level encryption os the way up this is challenging so what is it what's the impact to Red Hat as these new things come on because you know you got you know fishing out there sphere fishing is a big problem you got to handle it all how do you guys handle all the security challenges well you know it's it's actually interesting because rel is the base the core of Red Hat's product line which means that we provide the firm underpinning for everything else in the portfolio so we have the FIP certification we're doing the Common Criteria certification we provide the reliable crypto that everybody else can just expect to have in their world and we have to be the really firm basis for everything that layers on top and it's really great to have the additional products in the portfolio working very closely with us to make sure that we can be end-to-end secure end-to-end compliant and that we're looking at the bigger problems because it's not about the operating system it's about the infrastructure and what you're going to run on top of it right a lot of people have been saying security oh it's hard to do security open source is actually a problem for security and then the world shifts back and says wait a minute open source is better to attack security problem because it's out more people working on it versus the human problem of having proprietary so obviously open source is a good thing - security what's the modern approach that you see now that that that you guys are watching and building around that because that's the number one question that coot at kubernetes con we saw a great thing do some kubernetes we saw is do service meshes but Security's got to be thought of on the front end of all the application developers that means it's on you put it into the OS and it's a different world right because the application developers are not accustomed to having to deal with that because that was always the job of the IT guys right that was a problem for the infrastructure to deal with and so clearly we have to provide better security better better tooling available to them but the operations guys right they still they need help in this new world as well because suddenly there's this explosion of containers in their environment and who knows what's in those containers right we've got to have the ability to scan the containers and make sure that they get patched regularly right so it's just it's a whole different set of problems but it all starts with making sure it's secure underneath all the rest of it well so that's that brings up the console of this concept of layers right there's all the operational things there's the apps and the containers and then you know rail is running underneath that that's the hardware and the micro code and all the rest of the stuff so this year we the whole entire IT industry - the kind of a gasp with with the meltdown inspector problems that that surfaced or you know I guess it was in January I think yeah when they were Republican what that was that was how the colonel team spent their Christmas vacation oh my goodness yeah I the colonel team the performance team the security team the virtualization team all those guys so Red Hat shuts down for a week at Christmastime if they didn't yeah that was exciting I mean we've been trained security is one of these things but there's another one coming because cyber attacks are there what's that what's the viewpoint how do you keep on how do you how do you keep on top of it yeah well you know we have a fabulous security team so if you happen to get up to the second floor go talk with chrome Chris Robinson his guys they monitor what's going on in the upstreams they work with mitre they work with the organization's right and when they discover that something is in the wind they come to us and disclose people as needed and then we get to go and figure out how we're gonna get fixes in usually a lot of this stuff happens as you know under embargo so we really we can't talk about it that's a real problem if a lot of the upstream hasn't been read in right so like for instance with meltdown inspector a lot of that was going on not so much in the upstream so there were kind of divergent patches that we got to bring back together that was really we knew that well we had a really strong suspicion that the embargo was gonna break early there that's why my guys were over Christmas right they had to have something ready secure for when it broke and then we could worry about the performance afterwards yeah right and then you had to roll that out into the entire customer base there's some fairly standard mechanisms was there anything special with that because it was fairly high priority I suppose yeah well I mean anything like that we make available a synchronously cuz we want to have it available that the day that that embargo goes public right because that's when we're gonna be getting the phone calls that's when people say oh my god now what do I do but if but the hard part with this one was that you had to have the microcode as well right but we had to do a lot of Education because this was this the side channel attacks it's just a different way of thinking right it's not so much a flaw in the code as in the overall hardware architecture that we get to deal with that stuff what did you learn what's the learnings that were magnifying we have to be as transparent as we can possibly be because security researchers are going to keep on looking for this kind of flaw and we you know we just have to be able to work as much in the open as we can but we also have to have an education function right this is not an area of core expertise for a lot of people who are working in databases right or who are who are designing Java apps and yet we have to be able to explain to them why there's a performance impact on some of the stuff that they're doing and how we can work together to try to get back some of that performance over time no meltdown inspector that's kind of off my radar now but I don't think we're completely out of it right you people have had to patch and reboot and and update but it sounds like we're not I don't think we're at 100% for sure of all systems yeah well you know IT infrastructure right there's your window in which you can actually afford to reboot your systems and I think a lot of those are very tightly scheduled I mean we have customers who get you know ten minutes a year yeah up times of years and years I mean old rebooting is kind of old fashioned at this point yeah really right as it should be as it should be but but when it's the minor code you're kind of stuck yeah I mean that's a hardware thing getting back to the hardware still hardware's even though cloud is extracting away the complexities Hardware still is out there so you never gonna go away for you and as you said it's changing look at the GPU side and you got all kinds of new things coming on the horizon like blockchain and decentralized infrastructure that's encrypted amen right so you know this is you know systems level code mm-hmm with software guys who don't know micro code mm-hmm so you guys got to be on top of it so so I guess the big question is is that operating system that you guys have is very reliable and the support is phenomenal use of industries how do you take the support and the engineering in rel and operating systems and bring that operate system mindset to the next level up as you move up the stack kubernetes new OpenStack as well openshift yeah and apps they all want the same reliability you all want the same kind of robustness nature of an ecosystem at the same time more people are being certified yeah so you have a balance of growth and reliability how do you how do you guys see that and it's also speed and time to market right which is the other factor because there's so much pressure on any emerging technology to get the features out there that you end up carrying the technical debt right or you end up not being able to be as hardened as you might like to be the instant that you go out the door and so it's always gonna be a balancing act and a trade-off so you I know you guys were just talking with Mark Oh bill Peter and he was probably talking about how we're trying to focus on use cases right we need to understand the use cases that our customers have and now those are clearly across the entire product portfolio right but those are the test scenarios that I need to get in flight and those are also the the paths that I need to make sure we've optimized for right and so it's a partnership with the rest of the products in the portfolio and we really do a lot to work together as tightly as we can which is one of the benefits of being at the core right I'm working with everybody yeah and you got the instrumentation too so the other theme yeah the automation big time theme here is breaking down the two of real granular level sets of services which actually is a good thing because if you can instrument it then it's just easy to manage because then he can isolate things so I mean this is a good thing in the OS people love this because you can see couple and make things work well but the instrumentation if you have the API API and you need the instrumentation and looking in so how is that created a challenge because it's all those great for Red Hat's business and then you see in the the forecast and the analysts are seeing the growth you guys are seeing the successes but it makes your job harder a bit that one's a harder but I mean it's you know you get it right more code and make glue layers of abstraction layers yeah but I wouldn't want it to be boring well I do want it to I want it to be boring for our customers I want our customers to just be able to pick up and no drum and exciting homes not ringing with no spectra again it's working like a charm no problem yeah drama llama does not live here yeah yeah that's an interesting point though just a lot of talk about the whole Red Hat stack here right and you got as we've said you the base of it where does where does Linux where is this Linux and especially rail go from here what are you looking at that over the next few years some different technologies you're looking to pull it etc mm-hmm there's always I mean we have to keep up with the hardware advances clearly right but then there's let's oh look at our permaban what a great ad right so perma bit for people who don't know they do a video virtual data optimizer so they do D dupe and compression on the fly on the path to the disk and with rail 75 as part of your subscription you get so we buy we buy companies and we open-source their soft code side their software and we make it available to you as part of your subscription right how good is that so is when you deploy 75 in your environment now suddenly you're gonna need a whole lot less storage right depending on of course it depends upon your data footprint right but but you might find that you're able to shrink the amount of all that expensive storage and expensive cloud storage particularly that you need significantly and you get the compression right was avenge compression was very popular we know we followed in fallen permit bit question on permit bit for you was that open source was that they build their front open stores because now and are you guys open sourcing that that's okay so you have to go gain and and then open it up and do a review and clean it up and yeah yeah and we have to help them get it into an upstream right so they actually they were fabulous the perma because they have been so fabulous to work with best acquisition ever seems to be pretty good at acquiring companies and incorporating their tacit that seems to be part of the culture here yeah that's cuz we're not you know people think we're like big and scary right I'll tell you I have worked for companies that are big and scary Red Hat is not it we're really open and it's really in many ways in engineering culture which is wonderful it's a great fit if you happen to be from a startup culture because we don't overwhelm you with process right I mean we a lot of smart people again I can attest to my interactions over the years smart people very humble a lot of systems people to which is cooperating system hello the world's turning into an operating system good for that but humble and plays the long game you guys I've been you deserve credit for that and that's that's attracting and reason why you successful but you know the thing is we really believe in our core values right we really truly honest-to-god believe in open source and the power that it has to change the world that you know you say oh yeah sure right she's part of the management change she's gonna see him anyway yeah but you guys are growing so I mean over the years again since we started the cube nine years ago we've watched red add just in that time span grow significantly I'll see it's well documented an alternative to the other proprietary os's second-tier citizen now running the world the first tier great job so the youth success business model of open source is now mainstream but you got to onboard more people more ecosystem partners in a really dynamic big wave of innovation coming yeah how do you maintain the recruiting how do you get the great people how do you preserve the culture I'm sure these are questions how do you the more inclusion and diversity questions this is all happening right they're gonna have to catch him at nine years old and grown I mean although honest to god we do a lot of university outreach right if you look in the Czech Republic for instance we have a huge operation in Brno which is the second largest city there and we are so tied in to the university system we bring in lots and lots and lots of interns and it's wonderful right because we want to teach people about open-source we find people who have passion projects and we bring them in this is this is our world right we don't we want non-traditional people as well as traditional computer science majors open-source is a great leveler your CV is online I mean imagine right you're you want to change careers you want a new life you love to code you've been working on writing games in your in your spare time you are our people that's the code your code is who you are your code is it's your CV well this is what Oh doing your things on the open means and also it's been great for your business and we had gym writers on earlier there's no a/b testing they just go into the community and find out what's they want and they just that's the a B C's e testing it's just right there you guys do the due diligence sometimes make big time real fun decisions on features based upon what is in demand practically speaking not just focusing on the new tech that's a good business model we hope so cuz you know I mean as as one of our former CFO I said there are a lot of people a lot of Associates at Red Hat who are dependent on Red Hat for a paycheck and it's very important to us that we remain profitable stable and and really good for our people right we've got a lot of people that we need to take care of in the time it's a good place to be in the timing spray with kubernetes and containers we're taking it up a notch and bringing that extensibility you know just beyond stand-alone Linux so congratulations Denise thanks for coming on and sharing your perspective as always we love these conversations in the cube talk and everything from operating systems to core OS and kubernetes and culture as the cue here out in the open on the floor at Moscone West John Troy yer stay with us we'll be back with more day two of three days of live coverage on the cube net we'll be right back

>>The queue at Hadoop summit, 2014 is brought to you by anchor sponsor Hortonworks. We do, I do. And headline sponsor when disco we make Hadoop invincible >>Okay. Welcome back. Everyone live here in Silicon valley in San Jose. This is a dupe summit. This is Silicon angle and Wiki bonds. The cube is our flagship program. We go out to the events and extract the signal to noise. I'm John barrier, the founder SiliconANGLE joins my cohost, Jeff Kelly, top big data analyst in the, in the community. Our next guest, Jack Norris, COO of map R security enterprise. That's the buzz of the show and it was the buzz of OpenStack summit. Another open source show. And here this year, you're just seeing move after, move at the moon, talking about a couple of critical issues. Enterprise grade Hadoop, Hortonworks announced a big acquisition when all in, as they said, and now cloud era follows suit with their news. Today, I, you sitting back saying, they're catching up to you guys. I mean, how do you look at that? I mean, cause you guys have that's the security stuff nailed down. So what Dan, >>You feel about that now? I think I'm, if you look at the kind of Hadoop market, it's definitely moving from a test experimental phase into a production phase. We've got tremendous customers across verticals that are doing some really interesting production use cases. And we recognized very early on that to really meet the needs of customers required some architectural innovation. So combining the open source ecosystem packages with some innovations underneath to really deliver high availability, data protection, disaster recovery features, security is part of that. But if you can't predict the PR protect the data, if you can't have multitenancy and separate workflows across the cluster, then it doesn't matter how secure it is. You know, you need those. >>I got to ask you a direct question since we're here at Hadoop summit, because we get this question all the time. Silicon lucky bond is so successful, but I just don't understand your business model without plates were free content and they have some underwriters. So you guys have been very successful yet. People aren't looking at map are as good at the quiet leader, like you doing your business, you're making money. Jeff. He had some numbers with us that in the Hindu community, about 20% are paying subscriptions. That's unlike your business model. So explain to the folks out there, the business model and specifically the traction because you have >>Customers. Yeah. Oh no, we've got, we've got over 500 paying customers. We've got at least $1 million customer in seven different verticals. So we've got breadth and depth and our business model is simple. We're an enterprise software company. That's looking at how to provide the best of open source as well as innovations underneath >>The most open distribution of Hadoop. But you add that value separately to that, right? So you're, it's not so much that you're proprietary at all. Right. Okay. >>You clarify that. Right. So if you look at, at this exciting ecosystem, Hadoop is fairly early in its life cycle. If it's a commoditization phase like Linux or, or relational database with my SQL open source, kind of equates the whole technology here at the beginning of this life cycle, early stages of the life cycle. There's some architectural innovations that are really required. If you look at Hadoop, it's an append only file system relying on Linux. And that really limits the types of operations. That types of use cases that you can do. What map ours done is provide some deep architectural innovations, provide complete read-write file systems to integrate data protection with snapshots and mirroring, et cetera. So there's a whole host of capabilities that make it easy to integrate enterprise secure and, and scale much better. Do you think, >>I feel like you were maybe a little early to the market in the sense that we heard Merv Adrian and his keynote this morning. Talk about, you know, it's about 10 years when you start to get these questions about security and governance and we're about nine years into Hadoop. Do you feel like maybe you guys were a little early and now you're at a tipping point, whereas these more, as more and more deployments get ready to go to production, this is going to be an area that's going to become increasingly important. >>I think, I think our timing has been spectacular because we, we kind of came out at a time when there was some customers that were really serious about Hadoop. We were able to work closely with them and prove our technology. And now as the market is just ramping, we're here with all of those features that they need. And what's a, what's an issue. Is that an incremental improvement to provide those kind of key features is not really possible if the underlying architecture isn't there and it's hard to provide, you know, online real-time capabilities in a underlying platform that's append only. So the, the HDFS layer written in Java, relying on the Linux file system is kind of the, the weak underbelly, if you will, of, of the ecosystem. There's a lot of, a lot of important developments happening yarn on top of it, a lot of really kind of exciting things. So we're actively participating in including Apache drill and on top of a complete read-write file system and integrated Hindu database. It just makes it all come to life. >>Yeah. I mean, those things on top are critical, but you know, it's, it's the underlying infrastructure that, you know, we asked, we keep on community about that. And what's the, what are the things that are really holding you back from Paducah and production and the, and the biggest challenge is they cited worth high availability, backup, and recovery and maintaining performance at scale. Those are the top three and that's kind of where Matt BARR has been focused, you know, since day one. >>So if you look at a major retailer, 2000 nodes and map bar 50 unique applications running on a single cluster on 10,000 jobs a day running on top of that, if you look at the Rubicon project, they recently went public a hundred million add actions, a hundred billion ad auctions a day. And on top of that platform, beats music that just got acquired for $3 billion. Basically it's the underlying map, our engine that allowed them to scale and personalize that music service. So there's a, there's a lot of proof points in terms of how quickly we scale the enterprise grade features that we provide and kind of the blending of deep predictive analytics in a batch environment with online capabilities. >>So I got to ask you about your go to market. I'll see Cloudera and Hortonworks have different business models. Just talk about that, but Cloudera got the massive funding. So you get this question all the time. What do you, how do you counter that army and the arms race? I think >>I just wrote an article in Forbes and he says cash is not a strategy. And I think that was, that was an excellent, excellent article. And he goes in and, you know, in this fast growing market, you know, an amount of money isn't necessarily translate to architectural innovations or speeding the development of that. This is a fairly fragmented ecosystem in terms of the stack that runs on top of it. There's no single application or single vendor that kind of drives value. So an acquisition strategy is >>So your field Salesforce has direct or indirect, both mixable. How do you handle the, because Cloudera has got feet on the street and every squirrel will find it, not if they're parked there, parking sales reps and SCS and all the enterprise accounts, you know, they're going to get the, squirrel's going to find a nut once in awhile. Yeah. And they're going to actually try to engage the clients. So, you know, I guess it is a strategy if they're deploying sales and marketing, right? So >>The beauty about that, and in fact, we're all in this together in terms of sharing an API and driving an ecosystem, it's not a fragmented market. You can start with one distribution and move to another, without recompiling or without doing any sort of changes. So it's a fairly open community. If this were a vendor lock-in or, you know, then spending money on brand, et cetera, would, would be important. Our focus is on the, so the sales execution of direct sales, yes, we have direct sales. We also have partners and it depends on the geographies as to what that percentage is. >>And John Schroeder on with the HP at fifth big data NYC has updated the HP relationship. >>Oh, excellent. In fact, we just launched our application gallery app gallery, make it very easy for administrators and developers and analysts to get access and understand what's available in the ecosystem. That's available directly on our website. And one of the featured applications there today is an integration with the map, our sandbox and HP Vertica. So you can get early access, try it and get the best of kind of enterprise grade SQL first, >>First Hadoop app store, basically. Yeah. If you want to call it that way. Right. So like >>Sure. Available, we launched with close to 30, 30 with, you know, a whole wave kind of following that. >>So talk a little bit about, you know, speaking of verdict and kind of the sequel on Hadoop. So, you know, there's a lot of talk about that. Some confusion about the different methods for applying SQL on predicts or map art takes an open approach. I know you'll support things like Impala from, from a competitor Cloudera, talk about that approach from a map arts perspective. >>So I guess our, our, our perspective is kind of unbiased open source. We don't try to pick and choose and dictate what's the right open source based on either our participation or some community involvement. And the reality is with multiple applications being run on the platform, there are different use cases that make difference, you know, make different sense. So whether it's a hive solution or, you know, drill drills available, or HP Vertica people have the choice. And it's part of, of a broad range of capabilities that you want to be able to run on the platform for your workflows, whether it's SQL access or a MapReduce or a spark framework shark, et cetera. >>So, yeah, I mean there is because there's so many different there's spark there's, you know, you can run HP Vertica, you've got Impala, you've got hive. And the stinger initiative is, is that whole kind of SQL on Hadoop ecosystem, still working itself out. Are we going to have this many options in a year or two years from now? Or are they complimentary and potentially, you know, each has its has its role. >>I think the major differences is kind of how it deals with the new data formats. Can it deal with self-describing data? Sources can leverage, Jason file does require a centralized metadata, and those are some of the perspectives and advantages say the Apache drill has to expand the data sets that are possible enabled data exploration without dependency on a, on an it administrator to define that, that metadata. >>So another, maybe not always as exciting, but taking workloads from existing systems, moving them to Hadoop is one of the ways that a lot of people get started with, to do whether associated transformation workloads or there's something in that vein. So I know you've announced a partnership with Syncsort and that's one of the things that they focus on is really making it as easy as possible to meet those. We'll talk a little bit about that partnership, why that makes sense for you and, and >>When your customer, I think it's a great proof point because we announced that partnership around mainframe offload, we have flipped comScore and experience in that, in that press release. And if you look at a workload on a mainframe going to duke, that that seems like that's a, that's really an oxymoron, but by having the capabilities that map R has and making that a system of record with that full high availability and that data protection, we're actually an option to offload from mainframe offload, from sand processing and provide a really cost effective, scalable alternative. And we've got customers that had, had tried to offload from the mainframe multiple times in the past, on successfully and have done it successfully with Mapbox. >>So talk a little bit more about kind of the broader partnership strategy. I mean, we're, we're here at Hadoop summit. Of course, Hortonworks talks a lot about their partnerships and kind of their reseller arrangements. Fedor. I seem to take a little bit more of a direct approach what's map R's approach to kind of partnering and, and as that relates to kind of resell arrangements and things like, >>I think the app gallery is probably a great proof point there. The strategy is, is an ecosystem approach. It's having a collection of tools and applications and management facilities as well as applications on top. So it's a very open strategy. We focus on making sure that we have open API APIs at that application layer, that it's very easy to get data in and out. And part of that architecture by presenting standard file system format, by allowing non Java applications to run directly on our platform to support standard database connections, ODBC, and JDBC, to provide database functionality. In addition to kind of this deep predictive analytics really it's about supporting the broadest set of applications on top of a single platform. What we're seeing in this kind of this, this modern architecture is data gravity matters. And the more processing you can do on a single platform, the better off you are, the more agile, the more competitive, right? >>So in terms of, so you're partnering with people like SAS, for example, to kind of bring some of the, some of the analytic capabilities into the platform. Can you kind of tell us a little bit about any >>Companies like SAS and revolution analytics and Skytree, and I mean, just a whole host of, of companies on the analytics side, as well as on the tools and visualization, et cetera. Yeah. >>Well, I mean, I, I bring up SAS because I think they, they get the fact that the, the whole data gravity situation is they've got it. They've got to go to where the data is and not have the data come to them. So, you know, I give them credit for kind of acknowledging that, that kind of big data truth ism, that it's >>All going to the data, not bringing the data >>To the computer. Jack talk about the success you had with the customers had some pretty impressive numbers talking about 500 customers, Merv agent. The garden was on with us earlier, essentially reiterating not mentioning that bar. He was just saying what you guys are doing is right where the puck is going. And some think the puck is not even there at the same rink, some other vendors. So I gotta give you props on that. So what I want you to talk about the success you have in specifically around where you're winning and where you're successful, you guys have struggled with, >>I need to improve on, yeah, there's a, there's a whole class of applications that I think Hadoop is enabling, which is about operations in analytics. It's taking this, this higher arrival rate machine generated data and doing analytics as it happens and then impacting the business. So whether it's fraud detection or recommendation engines, or, you know, supply chain applications using sensor data, it's happening very, very quickly. So a system that can tolerate and accept streaming data sources, it has real-time operations. That is 24 by seven and highly available is, is what really moves the needle. And that's the examples I used with, you know, add a Rubicon project and, you know, cable TV, >>The very outcome. What's the primary outcomes your clients want with your product? Is it stability? And the platform has enabled development. Is there a specific, is there an outcome that's consistent across all your wins? >>Well, the big picture, some of them are focused on revenues. Like how do we optimize revenue either? It's a new data source or it's a new application or it's existing application. We're exploding the dataset. Some of it's reducing costs. So they want to do things like a mainframe offload or data warehouse offload. And then there's some that are focused on risk mitigation. And if there's anything that they have in common it's, as they moved from kind of test and looked at production, it's the key capabilities that they have in enterprise systems today that they want to make sure they're in Hindu. So it's not, it's not anything new. It's just like, Hey, we've got SLS and I've got data protection policies, and I've got a disaster recovery procedure. And why can't I expect the same level of capabilities in Hindu that I have today in those other systems. >>It's a final question. Where are you guys heading this year? What's your key objectives. Obviously, you're getting these announcements as flurry of announcements, good success state of the company. How many employees were you guys at? Give us a quick update on the numbers. >>So, you know, we just reported this incredible momentum where we've tripled core growth year over year, we've added a tremendous amount of customers. We're over 500 now. So we're basically sticking to our knitting, focusing on the customers, elevating the proof points here. Some of the most significant customers we have in the telco and financial services and healthcare and, and retail area are, you know, view this as a strategic weapon view, this is a huge competitive advantage, and it's helping them impact their business. That's really spring our success. We've, you know, we're, we're growing at an incredible clip here and it's just, it's a great time to have made those calls and those investments early on and kind of reaping the benefits. >>It's. Now I've always said, when we, since the first Hadoop summit, when Hortonworks came out of Yahoo and this whole community kind of burst open, you had to duke world. Now Riley runs at it's a whole different vibe of itself. This was look at the developer vibe. So I got to ask you, and we would have been a big fan. I mean, everyone has enough beachhead to be successful, not about map arbors Hortonworks or cloud air. And this is why I always kind of smile when everyone goes, oh, Cloudera or Hortonworks. I mean, they're two different animals at this point. It would do different things. If you guys were over here, everyone has their quote, swim lanes or beachhead is not a lot of super competition. Do you think, or is it going to be this way for awhile? What's your fork at some? At what point do you see more competition? 10 years out? I mean, Merv was talking a 10 year horizon for innovation. >>I think that the more people learn and understand about Hadoop, the more they'll appreciate these kind of set of capabilities that matter in production and post-production, and it'll migrate earlier. And as we, you know, focus on more developer tools like our sandbox, so people can easily get experienced and understand kind of what map are, is. I think we'll start to see a lot more understanding and momentum. >>Awesome. Jack Norris here, inside the cube CMO, Matt BARR, a very successful enterprise grade, a duke player, a leader in the space. Thanks for coming on. We really appreciate it. Right back after the short break you're live in Silicon valley, I had dupe December, 2014, the right back.