>> Announcer: "theCUBE" presents HPE Discover 2022. Brought to you by HPE. >> Welcome back to HPE Discover 2022. You're watching "theCUBE's" coverage. This is Day 2, Dave Vellante with John Furrier. Sheila Rohra is here. She's the Senior Vice President and GM of the Data Infrastructure Business at Hewlett Packard Enterprise, and of course, the storage division. And Omer Asad. Welcome back to "theCUBE", Omer. Senior Vice President and General Manager for Cloud Data Services, Hewlett Packard Enterprise storage. Guys, thanks for coming on. Good to see you. >> Thank you. Always a pleasure, man. >> Thank you. >> So Sheila, I'll start with you. Explain the difference. The Data Infrastructure Business and then Omer's Cloud Data Services. You first. >> Okay. So Data Infrastructure Business. So I'm responsible for the primary secondary storage. Basically, what you physically store, the data in a box, I actually own that. So I'm going to have Omer explain his business because he can explain it better than me. (laughing) Go ahead. >> So 100% right. So first, data infrastructure platforms, primary secondary storage. And then what I do from a cloud perspective is wrap up those things into offerings, block storage offerings, data protection offerings, and then put them on top of the GreenLake platform, which is the platform that Antonio and Fidelma talked about on main Keynote stage yesterday. That includes multi-tenancy, customer subscription management, sign on management, and then on top of that we build services. Services are cloud-like services, storage services or block service, data protection service, disaster recovery services. Those services are then launched on top of the platform. Some services like data protection services are software only. Some services are software plus hardware. And the hardware on the platform comes along from the primary storage business and we run the control plane for that block service on the GreenLake platform and that's the cloud service. >> So, I just want to clarify. So what we maybe used to know as 3PAR and Nimble and StoreOnce. Those are the products that you're responsible for? >> That is the primary storage part, right? And just to kind of show that, he and I, we do indeed work together. Right. So if you think about the 3PAR, the primary... Sorry, the Primera, the Alletras, the Nimble, right? All that, right? That's the technology that, you know, my team builds. And what Omer does with his magic is that he turns it into HPE GreenLake for storage, right? And to deliver as a service, right? And basically to create a self-service agility for the customer and also to get a very Cloud operational experience for them. >> So if I'm a customer, just so I get this right, if I'm a customer and I want Hybrid, that's what you're delivering as a Cloud service? >> Yes. >> And I don't care where the data is on-premises, in storage, or on Cloud. >> 100%. >> Is that right? >> So the way that would work is, as a customer, you would come along with the partner, because we're 100% partner-led. You'll come to the GreenLake Console. On the GreenLake Console, you will pick one of our services. Could be a data protection service, could be the block storage service. All services are hybrid in nature. Public Cloud is 100% participant in the ecosystem. You'll choose a service. Once you choose a service, you like the rate card for that service. That rate card is just like a hyperscaler rate card. IOPS, Commitment, MINCOMMIT's, whatever. Once you procure that at the price that you like with a partner, you buy the subscription. Then you go to console.greenLake.com, activate your subscription. Once the subscription is activated, if it's a service like block storage, which we talked about yesterday, service will be activated, and our supply chain will send you our platform gear, and that will get activated in your site. Two things, network cable, power cable, dial into the cloud, service gets activated, and you have a cloud control plane. The key difference to remember is that it is cloud-consumption model and cloud-operation model built in together. It is not your traditional as a service, which is just like hardware leasing. >> Yeah, yeah, yeah. >> That's a thing of the past. >> But this answers a question that I had, is how do you transfer or transform from a company that is, you know, selling boxes, of course, most of you are engineers are software engineers, I get that, to one that is selling services. And it sounds like the answer is you've organized, I know it's inside baseball here, but you organize so that you still have, you can build best of breed products and then you can package them into services. >> Omer: 100%. 100%. >> It's separate but complementary organization. >> So the simplest way to look at it would be, we have a platform side at the house that builds the persistence layers, the innovation, the file systems, the speeds and feeds, and then building on top of that, really, really resilient storage services. Then how the customer consumes those storage services, we've got tremendous feedback from our customers, is that the cloud-operational model has won. It's just a very, very simple way to operate it, right? So from a customer's perspective, we have completely abstracted away out hardware, which is in the back. It could be at their own data center, it could be at an MSP, or they could be using a public cloud region. But from an operational perspective, the customer gets a single pane of glass through our service console, whether they're operating stuff on-prem, or they're operating stuff in the public cloud. >> So they get storage no matter what? They want it in the cloud, they got it that way, and if they want it as a service, it just gets shipped. >> 100%. >> They plug it in and it auto configures. >> Omer: It's ready to go. >> That's right. And the key thing is simplicity. We want to take the headache away from our customers, we want our customers to focus on their business outcomes, and their projects, and we're simplifying it through analytics and through this unified cloud platform, right? On like how their data is managed, how they're stored, how they're secured, that's all taken care of in this operational model. >> Okay, so I have a question. So just now the edge, like take me through this. Say I'm a customer, okay I got the data saved on-premise action, cloud, love that. Great, sir. That's a value proposition. Come to HPE because we provide this easily. Yeah. But now at the edge, I want to deploy it out to some edge node. Could be a tower with Telecom, 5G or whatever, I want to box this out there, I want storage. What happens there? Just ship it out there and connects up? Does it work the same way? >> 100%. So from our infrastructure team, you'll consume one or two platforms. You'll consume either the Hyperconverged form factor, SimpliVity, or you might convert, the Converged form factor, which is proliant servers powered by Alletras. Alletra 6Ks. Either of those... But it's very different the way you would procure it. What you would procure from us is an edge service. That edge service will come configured with certain amount of compute, certain amount of storage, and a certain amount of data protection. Once you buy that on a dollars per gig per month basis, whichever rate card you prefer, storage rate card or a VMware rate card, that's all you buy. From that point on, the platform team automatically configures the back-end hardware from that attribute-based ordering and that is shipped out to your edge. Dial in the network cable, dial in the power cable, GreenLake cloud discovers it, and then you start running the- >> Self-service, configure it, it just shows up, plug it in, done. >> Omer: Self-service but partner-led. >> Yeah. >> Because we have preferred pricing for our partners. Our partners would come in, they will configure the subscriptions, and then we activate those customers, and then send out the hardware. So it's like a hyperscaler on-prem at-scale kind of a model. >> Yeah, I like it a lot. >> So you guys are in the data business. You run the data portion of Hewlett Packard Enterprise. I used to call it storage, even if we still call it storage but really, it's evolving into data. So what's your vision for the data business and your customer's data vision, if you will? How are you supporting that? >> Well, I want to kick it off, and then I'm going to have my friend, Omer, chime in. But the key thing is that what the first step is is that we have to create a unified platform, and in this case we're creating a unified cloud platform, right? Where there's a single pane of glass to manage all that data, right? And also leveraging lots of analytics and telemetry data that actually comes from our infosite, right? We use all that, we make it easy for the customer, and all they have to say, and they're basically given the answers to the test. "Hey, you know, you may want to increase your capacity. You may want to tweak your performance here." And all the customers are like, "Yes. No. Yes, no." Basically it, right? Accept and not accept, right? That's actually the easiest way. And again, as I said earlier, this frees up the bandwidth for the IT teams so then they actually focus more on the business side of the house, rather than figuring out how to actually manage every single step of the way of the data. >> Got it. >> So it's exactly what Sheila described, right? The way this strategy manifests itself across an operational roadmap for us is the ability to change from a storage vendor to a data services vendor, right? >> Sheila: Right. >> And then once we start monetizing these data services to our customers through the GreenLake platform, which gives us cloud consumption model and a cloud operational model, and then certain data services come with the platform layer, certain data services are software only. But all the services, all the data services that we provide are hybrid in nature, where we say, when you provision storage, you could provision it on-prem, or you can provision it in a hyperscaler environment. The challenge that most of our customers have come back and told us, is like, data center control planes are getting fragmented. On-premises, I mean there's no secrecy about it, right? VMware is the predominant hypervisor, and as a result of that, vCenter is the predominant configuration layer. Then there is the public cloud side, which is through either Ajour, or GCP, or AWS, being one of the largest ones out there. But when the customer is dealing with data assets, the persistence layer could be anywhere, it could be in AWS region, it could be your own data center, or it could be your MSP. But what this does is it creates an immense amount of fragmentation in the context in which the customers understand the data. Essentially, John, the customers are just trying to answer three questions: What is it that I store? How much of it do I store? Should I even be storing it in the first place? And surprisingly, those three questions just haven't been answered. And we've gotten more and more fragmented. So what we are trying to produce for our customers, is a context to ware data view, which allows the customer to understand structured and unstructured data, and the lineage of how it is stored in the organization. And essentially, the vision is around simplification and context to ware data management. One of the key things that makes that possible, is again, the age old infosite capability that we have continued to hone and develop over time, which is now up to the stage of like 12 trillion data points that are coming into the system that are not corroborated to give that back. >> And of course cost-optimizing it as well. We're up against the clock, but take us through the announcements, what's new from when we sort of last talked? I guess it was in September. >> Omer: Right. >> Right. What's new that's being announced here and, or, you know, GA? >> Right. So three major announcements that came out, because to keep on establishing the context when we were with you last time. So last time we announced GreenLake backup and recovery service. >> John: Right. >> That was VMware backup and recovery as a complete cloud, sort of SaaS control plane. No backup target management, no BDS server management, no catalog management, it's completely a SaaS service. Provide your vCenter address, boom, off you go. We do the backups, agentless, 100% dedup enabled. We have extended that into the public cloud domain. So now, we can back up AWS, EC2, and EBS instances within the same constructs. So a single catalog, single backup policy, single protection framework that protects you both in the cloud and on-prem, no fragmentation, no multiple solutions to deploy. And the second one is we've extended our Hyperconverged service to now be what we call the Hybrid Cloud On-Demand. So basically, you go to GreenLake Console control plane, and from there, you basically just start configuring virtual machines. It supports VMware and AWS at the same time. So you can provision a virtual machine on-prem, or you can provision a virtual machine in the public cloud. >> Got it. >> And, it's the same framework, the same catalog, the same inventory management system across the board. And then, lastly, we extended our block storage service to also become hybrid in nature. >> Got it. >> So you can manage on-prem and AWS, EBS assets as well. >> And Sheila, do you still make product announcements, or does Antonio not allow that? (Omer laughing) >> Well, we make product announcements, and you're going to see our product announcements actually done through the HPE GreenLake for block storage. >> Dave: Oh, okay. >> So our announcements will be coming through that, because we do want to make it as a service. Again, we want to take all of that headache of "What configuration should I buy? How do I actually deploy it? How do I...?" We really want to take that headache away. So you're going to see more feature announcements that's going to come through this. >> So feature acceleration through GreenLake will be exposed? >> Absolutely. >> This is some cool stuff going on behind the scenes. >> Oh, there's a lot good stuff. >> Hardware still matters, you know. >> Hardware still matters. >> Does it still matter? Does hardware matter? >> Hardware still matters, but what matters more is the experience, and that's actually what we want to bring to the customer. (laughing) >> John: That's good. >> Good answer. >> Omer: 100%. (laughing) >> Guys, thanks so much- >> John: Hardware matters. >> For coming on "theCUBE". Good to see you again. >> John: We got it. >> Thanks. >> And hope the experience was good for you Sheila. >> I know, I know. Thank you. >> Omer: Pleasure as always. >> All right, keep it right there. Dave Vellante and John Furrier will be back from HPE Discover 2022. You're watching "theCUBE". (soft music)

[Music] in the 2010s organizations became keenly aware that data would become the key ingredient in driving competitive advantage differentiation and growth but to this day putting data to work remains a difficult challenge for many if not most organizations now as the cloud matures it has become a game changer for data practitioners by making cheap storage and massive processing power readily accessible we've also seen better tooling in the form of data workflows streaming machine intelligence ai developer tools security observability automation new databases and the like these innovations they accelerate data proficiency but at the same time they had complexity for practitioners data lakes data hubs data warehouses data marts data fabrics data meshes data catalogs data oceans are forming they're evolving and exploding onto the scene so in an effort to bring perspective to the sea of optionality we've brought together the brightest minds in the data analyst community to discuss how data management is morphing and what practitioners should expect in 2022 and beyond hello everyone my name is dave vellante with the cube and i'd like to welcome you to a special cube presentation analyst predictions 2022 the future of data management we've gathered six of the best analysts in data and data management who are going to present and discuss their top predictions and trends for 2022 in the first half of this decade let me introduce our six power panelists sanjeev mohan is former gartner analyst and principal at sanjamo tony bear is principal at db insight carl olufsen is well-known research vice president with idc dave meninger is senior vice president and research director at ventana research brad shimon chief analyst at ai platforms analytics and data management at omnia and doug henschen vice president and principal analyst at constellation research gentlemen welcome to the program and thanks for coming on thecube today great to be here thank you all right here's the format we're going to use i as moderator are going to call on each analyst separately who then will deliver their prediction or mega trend and then in the interest of time management and pace two analysts will have the opportunity to comment if we have more time we'll elongate it but let's get started right away sanjeev mohan please kick it off you want to talk about governance go ahead sir thank you dave i i believe that data governance which we've been talking about for many years is now not only going to be mainstream it's going to be table stakes and all the things that you mentioned you know with data oceans data lakes lake houses data fabric meshes the common glue is metadata if we don't understand what data we have and we are governing it there is no way we can manage it so we saw informatica when public last year after a hiatus of six years i've i'm predicting that this year we see some more companies go public uh my bet is on colibra most likely and maybe alation we'll see go public this year we we i'm also predicting that the scope of data governance is going to expand beyond just data it's not just data and reports we are going to see more transformations like spark jaws python even airflow we're going to see more of streaming data so from kafka schema registry for example we will see ai models become part of this whole governance suite so the governance suite is going to be very comprehensive very detailed lineage impact analysis and then even expand into data quality we already seen that happen with some of the tools where they are buying these smaller companies and bringing in data quality monitoring and integrating it with metadata management data catalogs also data access governance so these so what we are going to see is that once the data governance platforms become the key entry point into these modern architectures i'm predicting that the usage the number of users of a data catalog is going to exceed that of a bi tool that will take time and we already seen that that trajectory right now if you look at bi tools i would say there are 100 users to a bi tool to one data catalog and i i see that evening out over a period of time and at some point data catalogs will really become you know the main way for us to access data data catalog will help us visualize data but if we want to do more in-depth analysis it'll be the jumping-off point into the bi tool the data science tool and and that is that is the journey i see for the data governance products excellent thank you some comments maybe maybe doug a lot a lot of things to weigh in on there maybe you could comment yeah sanjeev i think you're spot on a lot of the trends uh the one disagreement i think it's it's really still far from mainstream as you say we've been talking about this for years it's like god motherhood apple pie everyone agrees it's important but too few organizations are really practicing good governance because it's hard and because the incentives have been lacking i think one thing that deserves uh mention in this context is uh esg mandates and guidelines these are environmental social and governance regs and guidelines we've seen the environmental rags and guidelines imposed in industries particularly the carbon intensive industries we've seen the social mandates particularly diversity imposed on suppliers by companies that are leading on this topic we've seen governance guidelines now being imposed by banks and investors so these esgs are presenting new carrots and sticks and it's going to demand more solid data it's going to demand more detailed reporting and solid reporting tighter governance but we're still far from mainstream adoption we have a lot of uh you know best of breed niche players in the space i think the signs that it's going to be more mainstream are starting with things like azure purview google dataplex the big cloud platform uh players seem to be uh upping the ante and and addressing starting to address governance excellent thank you doug brad i wonder if you could chime in as well yeah i would love to be a believer in data catalogs um but uh to doug's point i think that it's going to take some more pressure for for that to happen i recall metadata being something every enterprise thought they were going to get under control when we were working on service oriented architecture back in the 90s and that didn't happen quite the way we we anticipated and and uh to sanjeev's point it's because it is really complex and really difficult to do my hope is that you know we won't sort of uh how do we put this fade out into this nebulous nebula of uh domain catalogs that are specific to individual use cases like purview for getting data quality right or like data governance and cyber security and instead we have some tooling that can actually be adaptive to gather metadata to create something i know is important to you sanjeev and that is this idea of observability if you can get enough metadata without moving your data around but understanding the entirety of a system that's running on this data you can do a lot to help with with the governance that doug is talking about so so i just want to add that you know data governance like many other initiatives did not succeed even ai went into an ai window but that's a different topic but a lot of these things did not succeed because to your point the incentives were not there i i remember when starbucks oxley had come into the scene if if a bank did not do service obviously they were very happy to a million dollar fine that was like you know pocket change for them instead of doing the right thing but i think the stakes are much higher now with gdpr uh the floodgates open now you know california you know has ccpa but even ccpa is being outdated with cpra which is much more gdpr like so we are very rapidly entering a space where every pretty much every major country in the world is coming up with its own uh compliance regulatory requirements data residence is becoming really important and and i i think we are going to reach a stage where uh it won't be optional anymore so whether we like it or not and i think the reason data catalogs were not successful in the past is because we did not have the right focus on adoption we were focused on features and these features were disconnected very hard for business to stop these are built by it people for it departments to to take a look at technical metadata not business metadata today the tables have turned cdo's are driving this uh initiative uh regulatory compliances are beating down hard so i think the time might be right yeah so guys we have to move on here and uh but there's some some real meat on the bone here sanjeev i like the fact that you late you called out calibra and alation so we can look back a year from now and say okay he made the call he stuck it and then the ratio of bi tools the data catalogs that's another sort of measurement that we can we can take even though some skepticism there that's something that we can watch and i wonder if someday if we'll have more metadata than data but i want to move to tony baer you want to talk about data mesh and speaking you know coming off of governance i mean wow you know the whole concept of data mesh is decentralized data and then governance becomes you know a nightmare there but take it away tony we'll put it this way um data mesh you know the the idea at least is proposed by thoughtworks um you know basically was unleashed a couple years ago and the press has been almost uniformly almost uncritical um a good reason for that is for all the problems that basically that sanjeev and doug and brad were just you know we're just speaking about which is that we have all this data out there and we don't know what to do about it um now that's not a new problem that was a problem we had enterprise data warehouses it was a problem when we had our hadoop data clusters it's even more of a problem now the data's out in the cloud where the data is not only your data like is not only s3 it's all over the place and it's also including streaming which i know we'll be talking about later so the data mesh was a response to that the idea of that we need to debate you know who are the folks that really know best about governance is the domain experts so it was basically data mesh was an architectural pattern and a process my prediction for this year is that data mesh is going to hit cold hard reality because if you if you do a google search um basically the the published work the articles and databases have been largely you know pretty uncritical um so far you know that you know basically learning is basically being a very revolutionary new idea i don't think it's that revolutionary because we've talked about ideas like this brad and i you and i met years ago when we were talking about so and decentralizing all of us was at the application level now we're talking about at the data level and now we have microservices so there's this thought of oh if we manage if we're apps in cloud native through microservices why don't we think of data in the same way um my sense this year is that you know this and this has been a very active search if you look at google search trends is that now companies are going to you know enterprises are going to look at this seriously and as they look at seriously it's going to attract its first real hard scrutiny it's going to attract its first backlash that's not necessarily a bad thing it means that it's being taken seriously um the reason why i think that that uh that it will you'll start to see basically the cold hard light of day shine on data mesh is that it's still a work in progress you know this idea is basically a couple years old and there's still some pretty major gaps um the biggest gap is in is in the area of federated governance now federated governance itself is not a new issue uh federated governance position we're trying to figure out like how can we basically strike the balance between getting let's say you know between basically consistent enterprise policy consistent enterprise governance but yet the groups that understand the data know how to basically you know that you know how do we basically sort of balance the two there's a huge there's a huge gap there in practice and knowledge um also to a lesser extent there's a technology gap which is basically in the self-service technologies that will help teams essentially govern data you know basically through the full life cycle from developed from selecting the data from you know building the other pipelines from determining your access control determining looking at quality looking at basically whether data is fresh or whether or not it's trending of course so my predictions is that it will really receive the first harsh scrutiny this year you are going to see some organization enterprises declare premature victory when they've uh when they build some federated query implementations you're going to see vendors start to data mesh wash their products anybody in the data management space they're going to say that whether it's basically a pipelining tool whether it's basically elt whether it's a catalog um or confederated query tool they're all going to be like you know basically promoting the fact of how they support this hopefully nobody is going to call themselves a data mesh tool because data mesh is not a technology we're going to see one other thing come out of this and this harks back to the metadata that sanji was talking about and the catalogs that he was talking about which is that there's going to be a new focus on every renewed focus on metadata and i think that's going to spur interest in data fabrics now data fabrics are pretty vaguely defined but if we just take the most elemental definition which is a common metadata back plane i think that if anybody is going to get serious about data mesh they need to look at a data fabric because we all at the end of the day need to speak you know need to read from the same sheet of music so thank you tony dave dave meninger i mean one of the things that people like about data mesh is it pretty crisply articulates some of the flaws in today's organizational approaches to data what are your thoughts on this well i think we have to start by defining data mesh right the the term is already getting corrupted right tony said it's going to see the cold hard uh light of day and there's a problem right now that there are a number of overlapping terms that are similar but not identical so we've got data virtualization data fabric excuse me for a second sorry about that data virtualization data fabric uh uh data federation right uh so i i think that it's not really clear what each vendor means by these terms i see data mesh and data fabric becoming quite popular i've i've interpreted data mesh as referring primarily to the governance aspects as originally you know intended and specified but that's not the way i see vendors using i see vendors using it much more to mean data fabric and data virtualization so i'm going to comment on the group of those things i think the group of those things is going to happen they're going to happen they're going to become more robust our research suggests that a quarter of organizations are already using virtualized access to their data lakes and another half so a total of three quarters will eventually be accessing their data lakes using some sort of virtualized access again whether you define it as mesh or fabric or virtualization isn't really the point here but this notion that there are different elements of data metadata and governance within an organization that all need to be managed collectively the interesting thing is when you look at the satisfaction rates of those organizations using virtualization versus those that are not it's almost double 68 of organizations i'm i'm sorry um 79 of organizations that were using virtualized access express satisfaction with their access to the data lake only 39 expressed satisfaction if they weren't using virtualized access so thank you uh dave uh sanjeev we just got about a couple minutes on this topic but i know you're speaking or maybe you've spoken already on a panel with jamal dagani who sort of invented the concept governance obviously is a big sticking point but what are your thoughts on this you are mute so my message to your mark and uh and to the community is uh as opposed to what dave said let's not define it we spent the whole year defining it there are four principles domain product data infrastructure and governance let's take it to the next level i get a lot of questions on what is the difference between data fabric and data mesh and i'm like i can compare the two because data mesh is a business concept data fabric is a data integration pattern how do you define how do you compare the two you have to bring data mesh level down so to tony's point i'm on a warp path in 2022 to take it down to what does a data product look like how do we handle shared data across domains and govern it and i think we are going to see more of that in 2022 is operationalization of data mesh i think we could have a whole hour on this topic couldn't we uh maybe we should do that uh but let's go to let's move to carl said carl your database guy you've been around that that block for a while now you want to talk about graph databases bring it on oh yeah okay thanks so i regard graph database as basically the next truly revolutionary database management technology i'm looking forward to for the graph database market which of course we haven't defined yet so obviously i have a little wiggle room in what i'm about to say but that this market will grow by about 600 percent over the next 10 years now 10 years is a long time but over the next five years we expect to see gradual growth as people start to learn how to use it problem isn't that it's used the problem is not that it's not useful is that people don't know how to use it so let me explain before i go any further what a graph database is because some of the folks on the call may not may not know what it is a graph database organizes data according to a mathematical structure called a graph a graph has elements called nodes and edges so a data element drops into a node the nodes are connected by edges the edges connect one node to another node combinations of edges create structures that you can analyze to determine how things are related in some cases the nodes and edges can have properties attached to them which add additional informative material that makes it richer that's called a property graph okay there are two principal use cases for graph databases there's there's semantic proper graphs which are used to break down human language text uh into the semantic structures then you can search it organize it and and and answer complicated questions a lot of ai is aimed at semantic graphs another kind is the property graph that i just mentioned which has a dazzling number of use cases i want to just point out is as i talk about this people are probably wondering well we have relational databases isn't that good enough okay so a relational database defines it uses um it supports what i call definitional relationships that means you define the relationships in a fixed structure the database drops into that structure there's a value foreign key value that relates one table to another and that value is fixed you don't change it if you change it the database becomes unstable it's not clear what you're looking at in a graph database the system is designed to handle change so that it can reflect the true state of the things that it's being used to track so um let me just give you some examples of use cases for this um they include uh entity resolution data lineage uh um social media analysis customer 360 fraud prevention there's cyber security there's strong supply chain is a big one actually there's explainable ai and this is going to become important too because a lot of people are adopting ai but they want a system after the fact to say how did the ai system come to that conclusion how did it make that recommendation right now we don't have really good ways of tracking that okay machine machine learning in general um social network i already mentioned that and then we've got oh gosh we've got data governance data compliance risk management we've got recommendation we've got personalization anti-money money laundering that's another big one identity and access management network and i.t operations is already becoming a key one where you actually have mapped out your operation your your you know whatever it is your data center and you you can track what's going on as things happen there root cause analysis fraud detection is a huge one a number of major credit card companies use graph databases for fraud detection risk analysis tracking and tracing churn analysis next best action what-if analysis impact analysis entity resolution and i would add one other thing or just a few other things to this list metadata management so sanjay here you go this is your engine okay because i was in metadata management for quite a while in my past life and one of the things i found was that none of the data management technologies that were available to us could efficiently handle metadata because of the kinds of structures that result from it but grass can okay grafts can do things like say this term in this context means this but in that context it means that okay things like that and in fact uh logistics management supply chain it also because it handles recursive relationships by recursive relationships i mean objects that own other objects that are of the same type you can do things like bill materials you know so like parts explosion you can do an hr analysis who reports to whom how many levels up the chain and that kind of thing you can do that with relational databases but yes it takes a lot of programming in fact you can do almost any of these things with relational databases but the problem is you have to program it it's not it's not supported in the database and whenever you have to program something that means you can't trace it you can't define it you can't publish it in terms of its functionality and it's really really hard to maintain over time so carl thank you i wonder if we could bring brad in i mean brad i'm sitting there wondering okay is this incremental to the market is it disruptive and replaceable what are your thoughts on this space it's already disrupted the market i mean like carl said go to any bank and ask them are you using graph databases to do to get fraud detection under control and they'll say absolutely that's the only way to solve this problem and it is frankly um and it's the only way to solve a lot of the problems that carl mentioned and that is i think it's it's achilles heel in some ways because you know it's like finding the best way to cross the seven bridges of konigsberg you know it's always going to kind of be tied to those use cases because it's really special and it's really unique and because it's special and it's unique uh it it still unfortunately kind of stands apart from the rest of the community that's building let's say ai outcomes as the great great example here the graph databases and ai as carl mentioned are like chocolate and peanut butter but technologically they don't know how to talk to one another they're completely different um and you know it's you can't just stand up sql and query them you've got to to learn um yeah what is that carlos specter or uh special uh uh yeah thank you uh to actually get to the data in there and if you're gonna scale that data that graph database especially a property graph if you're gonna do something really complex like try to understand uh you know all of the metadata in your organization you might just end up with you know a graph database winter like we had the ai winter simply because you run out of performance to make the thing happen so i i think it's already disrupted but we we need to like treat it like a first-class citizen in in the data analytics and ai community we need to bring it into the fold we need to equip it with the tools it needs to do that the magic it does and to do it not just for specialized use cases but for everything because i i'm with carl i i think it's absolutely revolutionary so i had also identified the principal achilles heel of the technology which is scaling now when these when these things get large and complex enough that they spill over what a single server can handle you start to have difficulties because the relationships span things that have to be resolved over a network and then you get network latency and that slows the system down so that's still a problem to be solved sanjeev any quick thoughts on this i mean i think metadata on the on the on the word cloud is going to be the the largest font uh but what are your thoughts here i want to like step away so people don't you know associate me with only meta data so i want to talk about something a little bit slightly different uh dbengines.com has done an amazing job i think almost everyone knows that they chronicle all the major databases that are in use today in january of 2022 there are 381 databases on its list of ranked list of databases the largest category is rdbms the second largest category is actually divided into two property graphs and rdf graphs these two together make up the second largest number of data databases so talking about accolades here this is a problem the problem is that there's so many graph databases to choose from they come in different shapes and forms uh to bright's point there's so many query languages in rdbms is sql end of the story here we've got sci-fi we've got gremlin we've got gql and then your proprietary languages so i think there's a lot of disparity in this space but excellent all excellent points sanji i must say and that is a problem the languages need to be sorted and standardized and it needs people need to have a road map as to what they can do with it because as you say you can do so many things and so many of those things are unrelated that you sort of say well what do we use this for i'm reminded of the saying i learned a bunch of years ago when somebody said that the digital computer is the only tool man has ever devised that has no particular purpose all right guys we gotta we gotta move on to dave uh meninger uh we've heard about streaming uh your prediction is in that realm so please take it away sure so i like to say that historical databases are to become a thing of the past but i don't mean that they're going to go away that's not my point i mean we need historical databases but streaming data is going to become the default way in which we operate with data so in the next say three to five years i would expect the data platforms and and we're using the term data platforms to represent the evolution of databases and data lakes that the data platforms will incorporate these streaming capabilities we're going to process data as it streams into an organization and then it's going to roll off into historical databases so historical databases don't go away but they become a thing of the past they store the data that occurred previously and as data is occurring we're going to be processing it we're going to be analyzing we're going to be acting on it i mean we we only ever ended up with historical databases because we were limited by the technology that was available to us data doesn't occur in batches but we processed it in batches because that was the best we could do and it wasn't bad and we've continued to improve and we've improved and we've improved but streaming data today is still the exception it's not the rule right there's there are projects within organizations that deal with streaming data but it's not the default way in which we deal with data yet and so that that's my prediction is that this is going to change we're going to have um streaming data be the default way in which we deal with data and and how you label it what you call it you know maybe these databases and data platforms just evolve to be able to handle it but we're going to deal with data in a different way and our research shows that already about half of the participants in our analytics and data benchmark research are using streaming data you know another third are planning to use streaming technologies so that gets us to about eight out of ten organizations need to use this technology that doesn't mean they have to use it throughout the whole organization but but it's pretty widespread in its use today and has continued to grow if you think about the consumerization of i.t we've all been conditioned to expect immediate access to information immediate responsiveness you know we want to know if an uh item is on the shelf at our local retail store and we can go in and pick it up right now you know that's the world we live in and that's spilling over into the enterprise i.t world where we have to provide those same types of capabilities um so that's my prediction historical database has become a thing of the past streaming data becomes the default way in which we we operate with data all right thank you david well so what what say you uh carl a guy who's followed historical databases for a long time well one thing actually every database is historical because as soon as you put data in it it's now history it's no longer it no longer reflects the present state of things but even if that history is only a millisecond old it's still history but um i would say i mean i know you're trying to be a little bit provocative in saying this dave because you know as well as i do that people still need to do their taxes they still need to do accounting they still need to run general ledger programs and things like that that all involves historical data that's not going to go away unless you want to go to jail so you're going to have to deal with that but as far as the leading edge functionality i'm totally with you on that and i'm just you know i'm just kind of wondering um if this chain if this requires a change in the way that we perceive applications in order to truly be manifested and rethinking the way m applications work um saying that uh an application should respond instantly as soon as the state of things changes what do you say about that i i think that's true i think we do have to think about things differently that's you know it's not the way we design systems in the past uh we're seeing more and more systems designed that way but again it's not the default and and agree 100 with you that we do need historical databases you know that that's clear and even some of those historical databases will be used in conjunction with the streaming data right so absolutely i mean you know let's take the data warehouse example where you're using the data warehouse as context and the streaming data as the present you're saying here's a sequence of things that's happening right now have we seen that sequence before and where what what does that pattern look like in past situations and can we learn from that so tony bear i wonder if you could comment i mean if you when you think about you know real-time inferencing at the edge for instance which is something that a lot of people talk about um a lot of what we're discussing here in this segment looks like it's got great potential what are your thoughts yeah well i mean i think you nailed it right you know you hit it right on the head there which is that i think a key what i'm seeing is that essentially and basically i'm going to split this one down the middle is i don't see that basically streaming is the default what i see is streaming and basically and transaction databases um and analytics data you know data warehouses data lakes whatever are converging and what allows us technically to converge is cloud native architecture where you can basically distribute things so you could have you can have a note here that's doing the real-time processing that's also doing it and this is what your leads in we're maybe doing some of that real-time predictive analytics to take a look at well look we're looking at this customer journey what's happening with you know you know with with what the customer is doing right now and this is correlated with what other customers are doing so what i so the thing is that in the cloud you can basically partition this and because of basically you know the speed of the infrastructure um that you can basically bring these together and or and so and kind of orchestrate them sort of loosely coupled manner the other part is that the use cases are demanding and this is part that goes back to what dave is saying is that you know when you look at customer 360 when you look at let's say smart you know smart utility grids when you look at any type of operational problem it has a real-time component and it has a historical component and having predictives and so like you know you know my sense here is that there that technically we can bring this together through the cloud and i think the use case is that is that we we can apply some some real-time sort of you know predictive analytics on these streams and feed this into the transactions so that when we make a decision in terms of what to do as a result of a transaction we have this real time you know input sanjeev did you have a comment yeah i was just going to say that to this point you know we have to think of streaming very different because in the historical databases we used to bring the data and store the data and then we used to run rules on top uh aggregations and all but in case of streaming the mindset changes because the rules normally the inference all of that is fixed but the data is constantly changing so it's a completely reverse way of thinking of uh and building applications on top of that so dave menninger there seemed to be some disagreement about the default or now what kind of time frame are you are you thinking about is this end of decade it becomes the default what would you pin i i think around you know between between five to ten years i think this becomes the reality um i think you know it'll be more and more common between now and then but it becomes the default and i also want sanjeev at some point maybe in one of our subsequent conversations we need to talk about governing streaming data because that's a whole other set of challenges we've also talked about it rather in a two dimensions historical and streaming and there's lots of low latency micro batch sub second that's not quite streaming but in many cases it's fast enough and we're seeing a lot of adoption of near real time not quite real time as uh good enough for most for many applications because nobody's really taking the hardware dimension of this information like how do we that'll just happen carl so near real time maybe before you lose the customer however you define that right okay um let's move on to brad brad you want to talk about automation ai uh the the the pipeline people feel like hey we can just automate everything what's your prediction yeah uh i'm i'm an ai fiction auto so apologies in advance for that but uh you know um i i think that um we've been seeing automation at play within ai for some time now and it's helped us do do a lot of things for especially for practitioners that are building ai outcomes in the enterprise uh it's it's helped them to fill skills gaps it's helped them to speed development and it's helped them to to actually make ai better uh because it you know in some ways provides some swim lanes and and for example with technologies like ottawa milk and can auto document and create that sort of transparency that that we talked about a little bit earlier um but i i think it's there's an interesting kind of conversion happening with this idea of automation um and and that is that uh we've had the automation that started happening for practitioners it's it's trying to move outside of the traditional bounds of things like i'm just trying to get my features i'm just trying to pick the right algorithm i'm just trying to build the right model uh and it's expanding across that full life cycle of building an ai outcome to start at the very beginning of data and to then continue on to the end which is this continuous delivery and continuous uh automation of of that outcome to make sure it's right and it hasn't drifted and stuff like that and because of that because it's become kind of powerful we're starting to to actually see this weird thing happen where the practitioners are starting to converge with the users and that is to say that okay if i'm in tableau right now i can stand up salesforce einstein discovery and it will automatically create a nice predictive algorithm for me um given the data that i that i pull in um but what's starting to happen and we're seeing this from the the the companies that create business software so salesforce oracle sap and others is that they're starting to actually use these same ideals and a lot of deep learning to to basically stand up these out of the box flip a switch and you've got an ai outcome at the ready for business users and um i i'm very much you know i think that that's that's the way that it's going to go and what it means is that ai is is slowly disappearing uh and i don't think that's a bad thing i think if anything what we're going to see in 2022 and maybe into 2023 is this sort of rush to to put this idea of disappearing ai into practice and have as many of these solutions in the enterprise as possible you can see like for example sap is going to roll out this quarter this thing called adaptive recommendation services which which basically is a cold start ai outcome that can work across a whole bunch of different vertical markets and use cases it's just a recommendation engine for whatever you need it to do in the line of business so basically you're you're an sap user you look up to turn on your software one day and you're a sales professional let's say and suddenly you have a recommendation for customer churn it's going that's great well i i don't know i i think that's terrifying in some ways i think it is the future that ai is going to disappear like that but i am absolutely terrified of it because um i i think that what it what it really does is it calls attention to a lot of the issues that we already see around ai um specific to this idea of what what we like to call it omdia responsible ai which is you know how do you build an ai outcome that is free of bias that is inclusive that is fair that is safe that is secure that it's audible etc etc etc etc that takes some a lot of work to do and so if you imagine a customer that that's just a sales force customer let's say and they're turning on einstein discovery within their sales software you need some guidance to make sure that when you flip that switch that the outcome you're going to get is correct and that's that's going to take some work and so i think we're going to see this let's roll this out and suddenly there's going to be a lot of a lot of problems a lot of pushback uh that we're going to see and some of that's going to come from gdpr and others that sam jeeve was mentioning earlier a lot of it's going to come from internal csr requirements within companies that are saying hey hey whoa hold up we can't do this all at once let's take the slow route let's make ai automated in a smart way and that's going to take time yeah so a couple predictions there that i heard i mean ai essentially you disappear it becomes invisible maybe if i can restate that and then if if i understand it correctly brad you're saying there's a backlash in the near term people can say oh slow down let's automate what we can those attributes that you talked about are non trivial to achieve is that why you're a bit of a skeptic yeah i think that we don't have any sort of standards that companies can look to and understand and we certainly within these companies especially those that haven't already stood up in internal data science team they don't have the knowledge to understand what that when they flip that switch for an automated ai outcome that it's it's gonna do what they think it's gonna do and so we need some sort of standard standard methodology and practice best practices that every company that's going to consume this invisible ai can make use of and one of the things that you know is sort of started that google kicked off a few years back that's picking up some momentum and the companies i just mentioned are starting to use it is this idea of model cards where at least you have some transparency about what these things are doing you know so like for the sap example we know for example that it's convolutional neural network with a long short-term memory model that it's using we know that it only works on roman english uh and therefore me as a consumer can say oh well i know that i need to do this internationally so i should not just turn this on today great thank you carl can you add anything any context here yeah we've talked about some of the things brad mentioned here at idc in the our future of intelligence group regarding in particular the moral and legal implications of having a fully automated you know ai uh driven system uh because we already know and we've seen that ai systems are biased by the data that they get right so if if they get data that pushes them in a certain direction i think there was a story last week about an hr system that was uh that was recommending promotions for white people over black people because in the past um you know white people were promoted and and more productive than black people but not it had no context as to why which is you know because they were being historically discriminated black people being historically discriminated against but the system doesn't know that so you know you have to be aware of that and i think that at the very least there should be controls when a decision has either a moral or a legal implication when when you want when you really need a human judgment it could lay out the options for you but a person actually needs to authorize that that action and i also think that we always will have to be vigilant regarding the kind of data we use to train our systems to make sure that it doesn't introduce unintended biases and to some extent they always will so we'll always be chasing after them that's that's absolutely carl yeah i think that what you have to bear in mind as a as a consumer of ai is that it is a reflection of us and we are a very flawed species uh and so if you look at all the really fantastic magical looking supermodels we see like gpt three and four that's coming out z they're xenophobic and hateful uh because the people the data that's built upon them and the algorithms and the people that build them are us so ai is a reflection of us we need to keep that in mind yeah we're the ai's by us because humans are biased all right great okay let's move on doug henson you know a lot of people that said that data lake that term's not not going to not going to live on but it appears to be have some legs here uh you want to talk about lake house bring it on yes i do my prediction is that lake house and this idea of a combined data warehouse and data lake platform is going to emerge as the dominant data management offering i say offering that doesn't mean it's going to be the dominant thing that organizations have out there but it's going to be the predominant vendor offering in 2022. now heading into 2021 we already had cloudera data bricks microsoft snowflake as proponents in 2021 sap oracle and several of these fabric virtualization mesh vendors join the bandwagon the promise is that you have one platform that manages your structured unstructured and semi-structured information and it addresses both the beyond analytics needs and the data science needs the real promise there is simplicity and lower cost but i think end users have to answer a few questions the first is does your organization really have a center of data gravity or is it is the data highly distributed multiple data warehouses multiple data lakes on-premises cloud if it if it's very distributed and you you know you have difficulty consolidating and that's not really a goal for you then maybe that single platform is unrealistic and not likely to add value to you um you know also the fabric and virtualization vendors the the mesh idea that's where if you have this highly distributed situation that might be a better path forward the second question if you are looking at one of these lake house offerings you are looking at consolidating simplifying bringing together to a single platform you have to make sure that it meets both the warehouse need and the data lake need so you have vendors like data bricks microsoft with azure synapse new really to the data warehouse space and they're having to prove that these data warehouse capabilities on their platforms can meet the scaling requirements can meet the user and query concurrency requirements meet those tight slas and then on the other hand you have the or the oracle sap snowflake the data warehouse uh folks coming into the data science world and they have to prove that they can manage the unstructured information and meet the needs of the data scientists i'm seeing a lot of the lake house offerings from the warehouse crowd managing that unstructured information in columns and rows and some of these vendors snowflake in particular is really relying on partners for the data science needs so you really got to look at a lake house offering and make sure that it meets both the warehouse and the data lake requirement well thank you doug well tony if those two worlds are going to come together as doug was saying the analytics and the data science world does it need to be some kind of semantic layer in between i don't know weigh in on this topic if you would oh didn't we talk about data fabrics before common metadata layer um actually i'm almost tempted to say let's declare victory and go home in that this is actually been going on for a while i actually agree with uh you know much what doug is saying there which is that i mean we i remembered as far back as i think it was like 2014 i was doing a a study you know it was still at ovum predecessor omnia um looking at all these specialized databases that were coming up and seeing that you know there's overlap with the edges but yet there was still going to be a reason at the time that you would have let's say a document database for json you'd have a relational database for tran you know for transactions and for data warehouse and you had you know and you had basically something at that time that that resembles to do for what we're considering a day of life fast fo and the thing is what i was saying at the time is that you're seeing basically blur you know sort of blending at the edges that i was saying like about five or six years ago um that's all and the the lake house is essentially you know the amount of the the current manifestation of that idea there is a dichotomy in terms of you know it's the old argument do we centralize this all you know you know in in in in in a single place or do we or do we virtualize and i think it's always going to be a yin and yang there's never going to be a single single silver silver bullet i do see um that they're also going to be questions and these are things that points that doug raised they're you know what your what do you need of of of your of you know for your performance there or for your you know pre-performance characteristics do you need for instance hiking currency you need the ability to do some very sophisticated joins or is your requirement more to be able to distribute and you know distribute our processing is you know as far as possible to get you know to essentially do a kind of brute force approach all these approaches are valid based on you know based on the used case um i just see that essentially that the lake house is the culmination of it's nothing it's just it's a relatively new term introduced by databricks a couple years ago this is the culmination of basically what's been a long time trend and what we see in the cloud is that as we start seeing data warehouses as a checkbox item say hey we can basically source data in cloud and cloud storage and s3 azure blob store you know whatever um as long as it's in certain formats like you know like you know parquet or csv or something like that you know i see that as becoming kind of you know a check box item so to that extent i think that the lake house depending on how you define it is already reality um and in some in some cases maybe new terminology but not a whole heck of a lot new under the sun yeah and dave menger i mean a lot of this thank you tony but a lot of this is going to come down to you know vendor marketing right some people try to co-opt the term we talked about data mesh washing what are your thoughts on this yeah so um i used the term data platform earlier and and part of the reason i use that term is that it's more vendor neutral uh we've we've tried to uh sort of stay out of the the vendor uh terminology patenting world right whether whether the term lake house is what sticks or not the concept is certainly going to stick and we have some data to back it up about a quarter of organizations that are using data lakes today already incorporate data warehouse functionality into it so they consider their data lake house and data warehouse one in the same about a quarter of organizations a little less but about a quarter of organizations feed the data lake from the data warehouse and about a quarter of organizations feed the data warehouse from the data lake so it's pretty obvious that three quarters of organizations need to bring this stuff together right the need is there the need is apparent the technology is going to continue to verge converge i i like to talk about you know you've got data lakes over here at one end and i'm not going to talk about why people thought data lakes were a bad idea because they thought you just throw stuff in a in a server and you ignore it right that's not what a data lake is so you've got data lake people over here and you've got database people over here data warehouse people over here database vendors are adding data lake capabilities and data lake vendors are adding data warehouse capabilities so it's obvious that they're going to meet in the middle i mean i think it's like tony says i think we should there declare victory and go home and so so i it's just a follow-up on that so are you saying these the specialized lake and the specialized warehouse do they go away i mean johnny tony data mesh practitioners would say or or advocates would say well they could all live as just a node on the on the mesh but based on what dave just said are we going to see those all morph together well number one as i was saying before there's always going to be this sort of you know kind of you know centrifugal force or this tug of war between do we centralize the data do we do it virtualize and the fact is i don't think that work there's ever going to be any single answer i think in terms of data mesh data mesh has nothing to do with how you physically implement the data you could have a data mesh on a basically uh on a data warehouse it's just that you know the difference being is that if we use the same you know physical data store but everybody's logically manual basically governing it differently you know um a data mission is basically it's not a technology it's a process it's a governance process um so essentially um you know you know i basically see that you know as as i was saying before that this is basically the culmination of a long time trend we're essentially seeing a lot of blurring but there are going to be cases where for instance if i need let's say like observe i need like high concurrency or something like that there are certain things that i'm not going to be able to get efficiently get out of a data lake um and you know we're basically i'm doing a system where i'm just doing really brute forcing very fast file scanning and that type of thing so i think there always will be some delineations but i would agree with dave and with doug that we are seeing basically a a confluence of requirements that we need to essentially have basically the element you know the ability of a data lake and a data laid out their warehouse we these need to come together so i think what we're likely to see is organizations look for a converged platform that can handle both sides for their center of data gravity the mesh and the fabric vendors the the fabric virtualization vendors they're all on board with the idea of this converged platform and they're saying hey we'll handle all the edge cases of the stuff that isn't in that center of data gradient that is off distributed in a cloud or at a remote location so you can have that single platform for the center of of your your data and then bring in virtualization mesh what have you for reaching out to the distributed data bingo as they basically said people are happy when they virtualize data i i think yes at this point but to this uh dave meningas point you know they have convert they are converging snowflake has introduced support for unstructured data so now we are literally splitting here now what uh databricks is saying is that aha but it's easy to go from data lake to data warehouse than it is from data warehouse to data lake so i think we're getting into semantics but we've already seen these two converge so is that so it takes something like aws who's got what 15 data stores are they're going to have 15 converged data stores that's going to be interesting to watch all right guys i'm going to go down the list and do like a one i'm going to one word each and you guys each of the analysts if you wouldn't just add a very brief sort of course correction for me so sanjeev i mean governance is going to be the maybe it's the dog that wags the tail now i mean it's coming to the fore all this ransomware stuff which really didn't talk much about security but but but what's the one word in your prediction that you would leave us with on governance it's uh it's going to be mainstream mainstream okay tony bear mesh washing is what i wrote down that's that's what we're going to see in uh in in 2022 a little reality check you you want to add to that reality check is i hope that no vendor you know jumps the shark and calls their offering a data mesh project yeah yeah let's hope that doesn't happen if they do we're going to call them out uh carl i mean graph databases thank you for sharing some some you know high growth metrics i know it's early days but magic is what i took away from that it's the magic database yeah i would actually i've said this to people too i i kind of look at it as a swiss army knife of data because you can pretty much do anything you want with it it doesn't mean you should i mean that's definitely the case that if you're you know managing things that are in a fixed schematic relationship probably a relational database is a better choice there are you know times when the document database is a better choice it can handle those things but maybe not it may not be the best choice for that use case but for a great many especially the new emerging use cases i listed it's the best choice thank you and dave meninger thank you by the way for bringing the data in i like how you supported all your comments with with some some data points but streaming data becomes the sort of default uh paradigm if you will what would you add yeah um i would say think fast right that's the world we live in you got to think fast fast love it uh and brad shimon uh i love it i mean on the one hand i was saying okay great i'm afraid i might get disrupted by one of these internet giants who are ai experts so i'm gonna be able to buy instead of build ai but then again you know i've got some real issues there's a potential backlash there so give us the there's your bumper sticker yeah i i would say um going with dave think fast and also think slow uh to to talk about the book that everyone talks about i would say really that this is all about trust trust in the idea of automation and of a transparent invisible ai across the enterprise but verify verify before you do anything and then doug henson i mean i i look i think the the trend is your friend here on this prediction with lake house is uh really becoming dominant i liked the way you set up that notion of you know the the the data warehouse folks coming at it from the analytics perspective but then you got the data science worlds coming together i still feel as though there's this piece in the middle that we're missing but your your final thoughts we'll give you the last well i think the idea of consolidation and simplification uh always prevails that's why the appeal of a single platform is going to be there um we've already seen that with uh you know hadoop platforms moving toward cloud moving toward object storage and object storage becoming really the common storage point for whether it's a lake or a warehouse uh and that second point uh i think esg mandates are uh are gonna come in alongside uh gdpr and things like that to uh up the ante for uh good governance yeah thank you for calling that out okay folks hey that's all the time that that we have here your your experience and depth of understanding on these key issues and in data and data management really on point and they were on display today i want to thank you for your your contributions really appreciate your time enjoyed it thank you now in addition to this video we're going to be making available transcripts of the discussion we're going to do clips of this as well we're going to put them out on social media i'll write this up and publish the discussion on wikibon.com and siliconangle.com no doubt several of the analysts on the panel will take the opportunity to publish written content social commentary or both i want to thank the power panelist and thanks for watching this special cube presentation this is dave vellante be well and we'll see you next time [Music] you

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody welcome to this special cube in size powered by ET our enterprise Technology Research our partner who's got this database to solve the spending data and what we're gonna do is a braking analysis on the analytic database market we're seeing that cloud and cloud players are disrupting that marketplace and that marketplace really traditionally has been known as the enterprise data warehouse market so Alex if you wouldn't mind bringing up the first slide I want to talk about some of the trends in the traditional EDW market I almost don't like to use that term anymore because it's sort of a pejorative but let's look at it's a very large market it's about twenty billion dollars today growing it you know high single digits low double digits it's expected to be in the 30 to 35 billion dollar size by mid next decade now historically this is dominated by teradata who started this market really back in the 1980s with the first appliance the first converged appliance or coal with Exadata you know IBM I'll talk about IBM a little bit they bought a company called mateesah back in the day and they've basically this month just basically killed the t's and killed the brand Microsoft has entered the fray and so it's it's been a fairly large market but I say it's failed to really live up to the promises that we heard about in the late 90s early parts of the 2000 namely that you were going to be able to get a 360 degree view of your data and you're gonna have this flexible easy access to the data you know the reality is data warehouses were really expensive they were slow you had to go through a few experts to to get data it took a long time I'll tell you I've done a lot of research on this space and when you talked to the the data warehouse practitioners they would tell you we always had to chase the chips anytime Intel would come out with a new chip we forced it in there because we just didn't have the performance to really run the analytics as we need to it's took so long one practitioner described it as a snake swallowing a basketball so you've got all those data which is the sort of metaphor for the basketball just really practitioners had a hard time standing up infrastructure and what happened as a spate of new players came into the marketplace these these MPP players trying to disrupt the market you had Vertica who was eventually purchased by HP and then they sold them to Micro Focus greenplum was buy bought by EMC and really you know company is de-emphasized greenplum Netezza 1.7 billion dollar acquisition by IBM IBM just this month month killed the brand they're kind of you know refactoring everything par Excel was interesting was it was a company based on an open-source platform that Amazon AWS did a one-time license with and created a redshift it ever actually put a lot of innovation redshift this is really doing well well show you some data on that we've also at the time saw a major shift toward unstructured data and read much much greater emphasis on analytics it coincided with Hadoop which also disrupted the market economics I often joked it the ROI of a dupe was reduction on investment and so you saw all these data lakes being built and of course they turned into the data swamps and you had dozens of companies come into the database space which used to be rather boring but Mike Amazon with dynamodb s AP with HANA data stacks Redis Mongo you know snowflake is another one that I'm going to talk about in detail today so you're starting to see the blurring of lines between relational and non relational and what was was what once thought of is no sequel became not only sequel sequel became the killer app for Hadoop and so at any rate you saw this new class of data stores emerging and snowflake was one of the more interesting and and I want to share some of that data with you some of the spending intentions so over the last several weeks and months we've shared spending intentions from ETR enterprise technology research they're a company that that the manages of the spending data and has a panel of about 4,500 end-users they go out and do spending in tension surveys periodically so Alex if you bring up this survey data I want to show you this so this is spending intentions and and what it shows is that the public cloud vendors in snowflake who really is a database as a service offering so cloud like are really leading the pack here so the sector that I'm showing is the enterprise data warehouse and I've added in the the analytics business intelligence and Big Data section so what this chart shows is the vendor on the left-hand side and then this bar chart has colors the the red is we're leaving the platform the gray is our spending will be flat so this is from the July survey expect to expectations for the second half of 2019 so gray is flat the the dark green is increase and the lime green is we are a new customer coming on to the platform so if you take the the greens and subtract out the red and there's two Reds the dark red is leaving the lighter red is spending less so if you subtract the Reds from the greens you get what's called a net score so the higher the net score the better so you can see here the net score of snowflake is 81% so that very very high you can also see AWS in Microsoft a very high and Google so the cloud vendors of which I would consider a snowflake at cloud vendor like at the cloud model all kicking butt now look at Oracle look at the the incumbents Oracle IBM and Tara data Oracle and IBM are in the single digits for a net score and the Terra data is in a negative 10% so that's obviously not a good sign for those guys so you're seeing share gains from the cloud company snowflake AWS Microsoft and Google at the expense of certainly of teradata but likely IBM and Oracle Oracle's little for animal they got Exadata and they're putting a lot of investments in there maybe talk about that a little bit more now you see on the right hand side this black says shared accounts so the N in this survey this July survey that ETR did is a thousand sixty eight so of a thousand sixty eight customers each er is asking them okay what's your spending going to be on enterprise data warehouse and analytics big data platforms and you can see the number of accounts out of that thousand sixty eight that are being cited so snowflake only had 52 and I'll show you some other data from from past surveys AWS 319 Microsoft the big you know whale here trillion dollar valuation 851 going down the line you see Oracle a number you know very large number and in Tara data and IBM pretty large as well certainly enough to get statistically valid results so takeaway here is snowflake you know very very strong and the other cloud vendors the hyper scale is AWS Microsoft and Google and their data stores doing very well in the marketplace and challenging the incumbents now the next slide that I want to show you is a time series for selected suppliers that can only show five on this chart but it's the spending intentions again in that EDW and analytics bi big data segment and it shows the spending intentions from January 17 survey all the way through July 19 so you can see the the period the periods that ETR takes this the snapshots and again the latest July survey is over a thousand n the other ones are very very large too so you can see here at the very top snowflake is that yellow line and they just showed up in the January 19 a survey and so you're seeing now actually you go back one yeah January 19 survey and then you see them in July you see the net score is the July next net score that I'm showing that's 35 that's the number of accounts out of the corpus of data that snowflake had in the survey back in January and now it's up to 52 you can see they lead the packet just in terms of the spending intention in terms of mentions AWS and Microsoft also up there very strong you see big gap down to Oracle and Terra data I didn't show I BM didn't show Google Google actually would be quite high to just around where Microsoft is but you can see the pressure that the cloud is placing on the incumbents so what are the incumbents going to do about it well certainly you're gonna see you know in the case of Oracle spending a lot of money trying to maybe rethink the the architecture refactor the architecture Oracle open worlds coming up shortly I'm sure you're gonna see a lot of new announcements around Exadata they're putting a lot of wood behind the the exadata arrow so you know we'll keep in touch with that and stay tuned but you can see again the big takeaways here is that cloud guys are really disrupting the traditional edw marketplace alright let's talk a little bit about snowflakes so I'm gonna highlight those guys and maybe give a little bit of inside baseball here but what you need to know about snowflakes so I've put some some points here just some quick points on the slide Alex if you want to bring that up very fast-growing cloud and SAS based data warehousing player growing that couple hundred percent annually their annual recurring revenue very high these guys are getting ready to do an IPO talk about that a little bit they were founded in 2012 and it kind of came out of stealth and hiding in 2014 after bringing Bob Moog Leon from Microsoft as the CEO it was really the background on these guys is they're three engineers from Oracle will probably bored out of their mind like you know what we got this great idea why should we give it to Oracle let's go pop out and start a company and that NIN's and as such they started a snowflake they really are disrupting the incumbents they've raised over 900 million dollars in venture and they've got almost a four billion dollar valuation last May they brought on Frank salute Minh and this is really a pivot point I think for the company and they're getting ready to do an IPO so and so let's talk a little bit about that in a moment but before we do that I want to bring up just this really simple picture of Alex if you if you'd bring this this slide up this block diagram it's like a kindergarten so that you know people like you know I can even understand it but basically the innovation around the snowflake architecture was that they they separated their claim is that they separated the storage from the compute and they've got this other layer called cloud services so let me talk about that for a minute snowflake fundamentally rethought the architecture of the data warehouse to really try to take advantage of the cloud so traditionally enterprise data warehouses are static you've got infrastructure that kind of dictates what you can do with the data warehouse and you got to predict you know your peak needs and you bring in a bunch of storage and compute and you say okay here's the infrastructure and this is what I got it's static if your workload grows or some new compliance regulation comes out or some new data set has to be analyzed well this is what you got you you got your infrastructure and yeah you can add to it in chunks of compute and storage together or you can forklift out and put in new infrastructure or you can chase more chips as I said it's that snake swallowing a basketball was not pretty so very static situation and you have to over provision whereas the cloud is all about you know pay buy the drink and it's about elasticity and on demand resources you got cheap storage and cheap compute and you can just pay for it as you use it so the innovation from snowflake was to separate the compute from storage so that you could independently scale those and decoupling those in a way that allowed you to sort of tune the knobs oh I need more compute dial it up I need more storage dial it up or dial it down and pay for only what you need now another nuance here is traditionally the computing and data warehousing happens on one cluster so you got contention for the resources of that cluster what snowflake does is you can spin up a warehouse on the fly you can size it up you can size it down based on the needs of the workload so that workload is what dictates the infrastructure also in snowflakes architecture you can access the same data from many many different houses so you got again that three layers that I'm showing you the storage the compute and the cloud services so let me go through some examples so you can really better understand this so you've got storage data you got customer data you got you know order data you got log files you might have parts data you know what's an inventory kind of thing and you want to build warehouses based on that data you might have marketing a warehouse you might have a sales warehouse you might have a finance warehouse maybe there's a supply chain warehouse so again by separating the compute from that sort of virtualized compute from the from the storage layer you can access any data leave the data where it is and I'll talk about this in more and bring the compute to the data so this is what in part the cloud layer does they've got security and governance they got data warehouse management in that cloud layer and and resource optimization but the key in in my opinion is this metadata management I think that's part of snowflakes secret sauce is the ability to leave data where it is and have the smarts and the algorithms to really efficiently bring the compute to the data so that you're not moving data around if you think about how traditional data warehouses work you put all the data into a central location so you can you know operate on it well that data movement takes a long long time it's very very complicated so that's part of the secret sauce is knowing what data lives where and efficiently bringing that compute to the data this dramatically improves performance it's a game changer and it's much much less expensive now when I come back to Frank's Luqman this is somebody that I've is a career that I've followed I've known had him on the cube of a number of times I first met Frank Sloot when he was at data domain he took that company took it public and then sold it originally NetApp made a bid for the company EMC Joe Tucci in the defensive play said no we're not gonna let Ned afgan it there was a little auction he ended up selling the company for I think two and a half billion dollars sloop and came in he helped clean up the the data protection business of EMC and then left did a stint as a VC and then took over service now when snoop and took over ServiceNow and a lot of people know this the ServiceNow is the the shiny toy on Wall Street today service that was a mess when saluteth took it over it's about 100 120 million dollar company he and his team took it to 1.2 billion dramatically increased the the valuation and one of the ways they did that was by thinking about the Tam and expanding that Tim that's part of a CEOs job as Tam expansion Steuben is also a great operational guy and he brought in an amazing team to do that I'll talk a little bit about that team effect uh well he just brought in Mike Scarpelli he was the CFO was the CFO of ServiceNow brought him in to run finance for snowflake so you've seen that playbook emerge you know be interesting Beth white was the CMO at data domain she was the CMO at ServiceNow helped take that company she's an amazing resource she kind of you know and in retirement she's young but she's kind of in retirement doing some advisory roles wonder if slooping will bring her back I wonder if Dan Magee who was ServiceNow is operational you know guru wonder if he'll come out of retirement how about Dave Schneider who runs the sales team at at ServiceNow well he you know be be lord over we'll see the kinds of things that Sluman looks for just in my view of observing his playbook over the years he looks for great product he looks for a big market he looks for disruption and he looks for off-the-chart ROI so his sales teams can go in and really make a strong business case to disrupt the existing legacy players so I one of the things I said that snoopin looks for is a large market so let's look at this market and this is the thing that people missed around ServiceNow and to credit Pat myself and David for in the back you know we saw the Tam potential of ServiceNow is to be many many tens of billions you know Gartner when they when ServiceNow first came out said hey helpdesk it's a small market couple billion dollars we saw the potential to transform not only IT operations but go beyond helpdesk change management at cetera IT Service Management into lines of business and we wrote a piece on wiki Vaughn back then it's showing the potential Tam and we think something similar could happen here so the market today let's call 20 billion growing to 30 Billy big first of all but a lot of players in here what if so one of the things that we see snowflake potentially being able to do with its architecture and its vision is able to bring enterprise search you know to the marketplace 80% of the data that's out there today sits behind firewalls it's not searchable by Google what if you could unlock that data and access it in query at anytime anywhere put the power in the hands of the line of business users to do that maybe think Google search for enterprises but with provenance and security and governance and compliance and the ability to run analytics for a line of business users it's think of it as citizens data analytics we think that tam could be 70 plus billion dollars so just think about that in terms of how this company might this company snowflake might go to market you by the time they do their IPO you know it could be they could be you know three four five hundred billion dollar company so we'll see we'll keep an eye on that now because the markets so big this is not like the ITSM the the market that ServiceNow was going after they crushed BMC HP was there but really not paying attention to it IBM had a product it had all these products that were old legacy products they weren't designed for the cloud and so you know ServiceNow was able to really crush that market and caught everybody by surprise and just really blew it out there's a similar dynamic here in that these guys are disrupting the legacy players with a cloud like model but at the same time so the Amazon with redshift so is Microsoft with its analytics platform you know teradata is trying to figure it out they you know they've got an inertia of a large install base but it's a big on-prem install base I think they struggle a little bit but their their advantages they've got customers locked in or go with exudate is very interesting Oracle has burned the boats and in gone to cloud first in Oracle mark my words is is reacting everything for the cloud now you can say Oh Oracle they're old school they're old guard that's fine but one of the things about Oracle and Larry Ellison they spend money on R&D they're very very heavy investor in Rd and and I think that you know you can see the exadata as it's actually been a very successful product they will react attacked exadata believe you me to to bring compute to the data they understand you can't just move all this the InfiniBand is not gonna solve their problem in terms of moving data around their architecture so you know watch Oracle you've got other competitors like Google who shows up well in the ETR survey so they got bigquery and BigTable and you got a you know a lot of other players here you know guys like data stacks are in there and you've got you've got Amazon with dynamo DB you've got couch base you've got all kinds of database players that are sort of blurring the lines as I said between sequel no sequel but the real takeaway here from the ETR data is you've got cloud again is winning it's driving the discussion and the spending discussion with an IT watch this company snowflake they're gonna do an IPO I guarantee it hopefully they will see if they'll get in before the booth before the market turns down but we've seen this play by Frank Sluman before and his team and and and the spending data shows that this company is hot you see them all over Silicon Valley you're seeing them show up in the in the spending data so we'll keep an eye on this it's an exciting market database market used to be kind of boring now it's red-hot so there you have it folks thanks for listening is a Dave Volante cube insights we'll see you next time

>> Announcer: Live from San Diego, California, it's theCUBE covering Cisco Live U.S. 2019. Brought to you by Cisco and its ecosystem partners. >> Welcome back to Cisco Live 2019 in San Diego everybody. You're watching theCUBE, the leader in live tech coverage and my name is Dave Vellante and I'm with my co-host Stu Miniman and Lisa Martin is also in the house. This is day three of our coverage, Danny Allan is here. He's the Vice President of Product Strategy at Veeam and one of the key thought leaders at the company, one of the main figures at VeeamON, which we were just doing three weeks ago. Danny, great to see you again. >> Wonderful to be here with you. >> That was a really fun show VeeamON, it always is. You guys got a cool vibe. >> You chose the Fontainebleau Hotel this year in Miami, in Miami Beach which is just a great location. Many thousands of customers and you guys hit some milestones recently. You talked about a billion dollars in revenue, it's been something you're going after for a while, you've seen that happen. Of course things change, right? All the subscription stuff started to happen. That slowed you down a little bit but that's awesome that you guys finally hit that, so congratulations. Raised a big pile of dough and you just keep moving that ball forward. Give us the update on Veeam. >> So as you said, Veeam has a great culture, right? There's a passionate green army out there that loves us and we're thankful for that. We hit one billion in bookings for the trailing 12 months, we have 350,000 customers and the business is going well. One of the interesting things about Veeam is because we're private, we actually have the opportunity to decide when and how we do things like switch from perpetual to subscription type bookings. But business is doing great, we love it, we're glad to be here. >> One of the things that you talked about at VeeamON was kind of getting back to the basics. You talked a lot about look, it starts with backup. There's a lot of noise in the market today. You hear a lot about, you know, data management. We talk a lot about date assurance but at the end of the day, it starts with backup. That's something that you gave a lot of thought to. I mentioned that you were one of the thought leaders at Veeam. Double click on that, add some color. What were you thinking in terms of that being the starting point and that really driving a lot of your messaging at VeeamON? >> Yeah, I always say it's three things, right? This is a journey that we're on and I get excited about the end stages of that journey. But how many people actually have a budget for machine learning or blockchain or artificial intelligence? No one has a budget for that. What they have a budget for is backup and so we believe A, it's a journey, B, it does start with backup. There's a budget for that and the key thing is choose a partner for this journey and we believe Veeam is the right partner obviously to choose for that but we really wanted to go back to who is spending money to buy the products and for that, it's the technical decision maker who has the budget for backup today. >> Yeah, all right. So Danny, we talk about the Cisco relationship and budgets like you were talking about there. Cisco UCS was from day one a heavily virtualized environment and therefore had strong affinity with Veeam there. But you've got some great visibility into where UCS is going, what CI and HCI solutions are really starting to gain traction. So talk a little bit about that partnership and which ones of those Cisco solutions are really starting to, you know, kick in the market. >> We have a great partnership with Cisco, first of all and really in two areas, if you're talking infrastructure. So on the HyperFlex, the Converged Infrastructure but also on just the S3260 for example, a storage dense system and we have a target this year, this is public information, we have a target, a joint target of $100 million. We're actually at 80% of that right now. Business has been doing really well. In fact, we've been on the Global Price List now for 18 months and in 18 months, we've actually closed over 350 transactions. Like it's been going really, really well and here's what's exciting about that. Those customers that are spending money on Cisco gear with Veeam software, they might start in the drag, these are quantifiable numbers, it's about five to one. So every dollar they spend on Veeam, it's about $5 on Cisco. But over 35% of those customers within twelve months come back and buy more Cisco gear and actually if you look at the actual drag, quantifiable drag that we're bring for Cisco, it's 11 to one. So for every dollar they spend with Veeam, they're spending $11 in Cisco HyperFlex or S3260. So it's been a great partnership both for us obviously because we're on their resell list but also for them. >> And you said you're 80% of the way there. We're talking a calendar year or is that a fiscal year? >> That is their fiscal year, so that's ending in August or July. I should know the date but I know we're 80%. We're on track to hit that $100 million. >> What do you think is driving that? I mean obviously this is a partnership, which takes time. >> Yes. >> This is not just a press release partnership. What else have you done to really facilitate this? >> Well I would say two things. One is their infrastructure is great. In fact we have one of our Veeam cloud service providers that is protecting over a million VMs right now. So these are massive scale, are using S3260s in the backend as a repository, so their hardware actually works. But I would say the other thing that really resonates is, so they have this Hyper FEX Solution and on top of that they have Intersite and that concept of a cloud management plain that can roll out the hardware, can update it not only at the infrastructure but also the Veeam software is really critical and that resonates with customers. It's again, good for them but it's also good for us. >> Let's see. The last couple years you guys have had a big emphasis on the enterprise and then again we're hearing this theme of kind of back to basics. I mean you heard at VeeamON, it starts with backup. You talk to people at VeeamON, the customers. It's the, you know, a lot of medium sized customers, a lot of smaller customers. Do you feel like you over-rotated to the enterprise or do you feel like hey, we could get there just by slow and steady and still putting the accelerator on our core business? Can you just add some color to that and explain? >> Yeah, so if you back three years, our focus was very much on the small and medium enterprise where we said we wanted to capture the major enterprise and that by the way has worked. If you look, since January of 2017 we've done over a billion just in enterprise, enterprise being 1,000 employees or above. So focusing on the enterprise for a few years was the right thing to do. However, that was all on the messaging side and we had this core constituent that has been with us for over decade now and we didn't want to pivot away from them. So in the last six months, nine months, what you've seen is pivoting back towards the center. So we do a third of our business with SMB, a third with commercial and a third with enterprise. So we believe we're right there on the fairway now and it's a perfect alignment of that messaging. >> Well I mean history would show that the disruptors oftentimes come from, you know, down below and move up. I mean you certainly saw that with Microsoft in the 80s and there are many other examples. Is that part of the philosophy, that you guys just can keep adding value that will appeal to the enterprise customers? It sounds like with a 30 year business, you're actually already there in terms of functionality. Is there a functionality gap though still that you need to close in your opinion? >> I don't think so. We announced as you know probably v10 a few years ago and what we've done is we've introduced that over the years and so the final check box if you will for v10 is coming in our next release later this year. But that really covers off the gambit of everything that needs to be done and that's been resonating really strongly. We believe we have a portfolio that addresses everything from the smallest customer to the largest customer. >> Yeah and you don't live and die, we heard this from Radmere, you don't live and die by your long term product development roadmap. You tend to be very tactical and listen to customers and-- >> We're very agile, so we keep a backlog of all the things that we want to do but we will pivot on a dime if we believe hey, this is really strategic for our customer base. We'll change something that, you know, we had planned for year out and do something else in the interim. >> Dave: Pretty judicious about how you decide there. >> Yeah so Danny, bring us inside some of the customer conversations you're having here to show, you know, when I watch the keynotes, many of the messages about multi-cloud sound like the same kind of things that I've been hearing at VeeamON for the last couple of years. What are you hearing from the customers at this? >> Well, definitely cloud date management is top of mind. I ate dinner last night with an enterprise customer. They're rolling this out across about 100 different locations around the world and they very much wanted a local repository of data but they also wanted to tier that data into the HyperScale public cloud, so that is clearly an enterprise-centric message. But that same capability goes down to the SMB. But if you asked me what is the conversation on everyone's, on the tip of their tongue, it is cloud. How are you addressing cloud? And we've done that a number of ways. One is we take the backup data, we'll tier it into cloud. We'll recover workloads in cloud. It's not so much a lift and shift. You know what's interesting is the cloud is not a charity. If you just take what you had on premises and move it into the cloud, there's merge-in layered in there, right? But for some use cases, disaster recovery, business continuity, you want to be able to turn it on in cloud and then after it's in cloud of course, then you need to protect it. And so we've been addressing all of those capabilities within the Veeam portfolio. >> Do you think there's going to be a backlash? I mean you don't see it in the numbers. You see, you know, AWS's growth and I'm not talking about repatriation but the cloud as a target is just another piece of infrastructure, even though it's kind of virtual, that I have to manage. I mean it does add complexity in that sense. So do you think there'll be, there's maybe somewhat over-enthusiasm now or do you see this as an unstoppable trend? >> I believe that cloud is a tool in the toolbox and it's both the smallest, most precise tool and also the largest tool and everything in between. What I mean by that is this isn't just a lift and shift and move it over to the cloud. It's how do I leverage the cloud to extend my data center? I actually, a lot of people talk about multi-cloud, I actually think that the era is really hybrid cloud. It's how do I extend what I have on premises into the cloud? And we're only now really being pragmatic about how to leverage it. The people that jumped in, all in and said, "I'm going all to cloud," those are the ones that you're seeing a bit of buyers remorse but those that are a lot more pragmatic, they're now saying, "How do I deliver business outcomes?" Because it's not about cloud, it's actually about business outcomes, right? Focus on the services. How do I deliver business outcomes that are improved by leveraging aspects of the cloud? >> Yes. So Danny, I know you've talked to our team. You know, we look at the environment and customers today, they have multi-cloud. But the strategy has been well, I've got some stuff here and I use that service here and wait, I need to spin that stuff over here. We've almost remade multi-vendor into multi-cloud. >> Yes. >> So the goal we've been looking for is the solution should be more than just the sum of the parts. Veeam sits in an interesting layer to help customers leverage that and get value out of their data across all of those environments. So you know, do we see that as a viable future that is not just the state that we're in but be able to get more value out of those pieces in the near future? >> Yeah, so I'm obviously biased 'cause I work for Veeam but I think we sit at the intersection of all of this because what we do is we take services, we take workloads and we make them portable. I can take something from on premises, I can put it in cloud A, I can put it in cloud B, I can take it back on premises, I can move it to a private cloud provider. So we have the ability to be completely flexible and agnostic as to where it lands and the reason why that's important, people don't go out and say "I'm going to put 50% "of my workload in this cloud or this cloud." They say, "I need a data center in this geography" or "I need a data center that has this kind of service." So the reason they end up in multi-cloud is not because of a multi-cloud strategy but because they have a business need that is met by that infrastructure and we allow the portability, the flexibility to move the workloads as the business needs. >> So we have some data here. I want to dig into it a little bit. Can you share with us some of the fun facts? Like when, maybe the timeline of your relationship with Cisco, some of the things you've done. Walk us through that, Danny. >> So, we partnered with, we've had a longstanding relationship with Cisco. Officially we went on their Global Price List like I said, 18 months ago. Since then, 300 and, earlier this week, 359 transactions. But almost a transact, two transactions every three days and we have a great go-to-market program with them right now, so we do a lot of joint activities, both in the channel as well as between. We fund heads with them and vice versa. >> Who's your favorite partner? No, you don't have to answer that. >> We have, we have a lot of partners. They're all of my favorite children. >> So we're hearing kind of this land and expand strategy. We've heard that from many other companies. But it's actually happening inside of or within the Veeam ecosystem and what I heard here was you're selling with Cisco and then people are coming back and buying more Cisco. So that's part of land and expand but another dimension of land and expand is you sell it to an organization. Not only do they buy more but other parts of the organization, you sort of fan out horizontally. How much of that is happening? >> It's happening quite a bit. I would say the most significant expansion right now is actually at a line of business level and so you'll have multiple lines of business and then they will begin to coalesce together and say "Okay, let's supply a central policy to that." So that's what we're seeing. What we do know is that 35% of Cisco customers that are joint Veeam and Cisco customers, they'll come back within the next 12 months and they'll buy more Veeam and more Cisco gear. >> Okay last question, why Veeam? You got a lot of competitors obviously in this market. You and I have talked about that a lot. You got, Cisco has made an investment in one of them. Why Veeam? >> So, simple, reliable, flexible and the flexible is probably the key to all of this because we don't lock people in. We don't lock them into our hardware, we don't lock them into a specific cloud, we don't lock them into any one of our children if you will, we love them all equally and that flexibility, future proofing the organization is a huge deciding point for the organizations. Because they don't know what the landscape's going to look like two, three years from now. Is this still going to be your partner or is it not? So having an organization that will partner with you, that will be flexible in, and this isn't just flexibility at a technology level, it's also at a business level. Licensing, for example. Flexibility to move licenses from physical systems to virtual systems to cloud systems to back again. They want to partner with someone that has that flexibility. >> Danny, great to see you again. Thanks so much for coming to theCUBE, always a pleasure. >> Yes, likewise. >> Okay, Stu Miniman, Dave Vellante, Lisa Martin from Cisco Live in San Diego 2019. You're watching theCUBE, we'll be right back. (upbeat electronic tones)

>> Live from Los Vegas. It's theCUBE covering Dell Technologies World 2019. Brought to you by Dell Technologies and it's ecosystem partners. >> Welcome back to Los Vegas everybody. You're watching theCUBE, the leader in live tech coverage. This is our wall-to-wall coverage. We're wrapping up day one. I'm Dave Alonte, my cohost here at this segment is Stu Miniman. Jon Siegal is here as the vice president of product marketing, cubulum from Dehli MC. Good to see you again Jon. >> Great to be back as always guys! >> And I love that you brought a customer, Suzan Pickett is here. >> That's what I do, by the way. You realize that, that's my new thing. >> Suzan is the VP and director of Converged Infrastructure at US Bank. >> Thank you for having me. >> Welcome, one of my banks. I got a lease with US Bank. You guys are great. >> Thank you. >> Great to have you guys. >> Let's start with a customer, if that's okay? >> Absolutely. >> Tell us about your role, you got CI in your title that's interesting. >> I do. >> That's a relatively new trend, explain that. >> Yeah absolutely, so I've been at the bank a couple years now and my teams focus on Converged and Hyperconverged Infrastructure, delivering solutions and infrastructure as a service for our business. >> You guys have been working together for a while if I understand it Jon, right? Talk a little bit about what's happening here at the show maybe give us a quick overview of what's happening in CI and HCI in your world. >> Absolutely, so a lot going on as you saw today in Dell Tech cloud announcement. HCI was a key pillar there. Really VxRail, in particular, was featured as the simple and fast foundation for the Dell Tech cloud both as the on-prem manage version as well as, as you heard, the Data Center as a service. So really exciting to see how HCI continues to evolve and it's use cases around cloud and infrastructure as a service, as well as platform as a service as well. So a lot of exciting announcements there. In addition to that, just this past week, by the way, we also, since you mentioned CI, Converged Infrastructure, we just announced that we re-upped our agreement with Cisco, a new multiyear agreement extension to continue to innovate with Cisco on the VxBlock, which, as you know, was the pioneer in this, Converged Infrastructure space and with all the recent integrations we've done now with VMware, VxBlock as well as HCI, is really built to be a on-prem foundation for the cloud. >> Yeah so, this goes back to 2009, when Cisco and VMware and EMC got together and created this concept of Converged Infrastructure. There were other competitors in the market, but you guys kind of lead that trend, and so when you go back to that years ago, that's our storage and networking and compute, they were different parts of the organization. I presume you guys went through a similar journey. You had to put all that together. Herd some calves. And what did that do for your business? What was your journey like to CI? >> I think we're still on that journey, but I think it's also evolving as we go more Agile and more DevOps, more software-defined, we're seeing a lot more blending of the teams as well so we're creating a lot of virtual teams that encompass not just infrastructure but security, developers, networking as well and really being able to deliver that infrastructure's service, platform as a service, end-to-end provisioning for our business lines. >> Suzan, I love that story because I remember talking to, when this started, you talk to the storage group and they'd say, "Oh my gosh, you're going to take away my job." I'm like, "You know that security thing that they've been yelling at you to fix for a while? You talk about the new business apps that we need to do. These are the types of jobs that we want you to do." I heard you talk about Agile and DevOps and all these things. Talk a little bit about, what are the pressures you're facing from the business and the relationship between your group that help you to meet those now. >> Sure, well the first thing we did was we created an infrastructure automation services team and people looked at us like we're a little crazy to do that and we pull those highly, highly motivated potentials from within the organization that we already had to focus on automation and get the foundation for infrastructure as a service and get that part right. Something as basic as provisioning a virtual machine would take 12 weeks or longer and through our journey with Kubernetes today, containers, vRealize Automation Suite, on both Converge and Hyperconverge, VxFlex. We're now reducing that down to about three days and we anticipate, with a lot of our sprints and iterations, that we're going to be getting that down to less than a day within the next quarter. >> So John Furry says that automation is the killer app for infrastructure, so are you guys, are you building essentially out on infrastructure as a service platform, where people used to call it private cloud. I don't know if you use that term still. I think it's still valid. >> We do, yeah. >> How's that going? What's been the business impact of that so-called private cloud? >> We had a Business Critical Application that would often take year release cycles, more than 12 weeks to get a server, primarily focusing on physical servers, and now what we're doing is we're partnering with them with not only the business, the application folks, the developers, the middleware teams, networks, security, but also all of the infrastructure teams to deliver that faster speed to market, and so now they're down to days now to provision. They actually gave us a stat the other day that said, "By using our automation with Kubernetes on Hyperconverge VxFlex, that they were able to have cost avoidance of hiring a bunch of people to build physical servers. So that in and of itself was a huge win, but the fact that we can repurpose and releverage that automation, those workflows, the orchestration models, means that we can continue this conversation with the next business line and the next business line and keep telling that story and it's a good one. >> Jon I'd live to hear from what Suzan was saying and there's so many of the modern things that they're doing. When you look at your customer base, how are they doing on that journey? We used to always ask, in the earlier days, it was like, alright how much was I just eliminating sub-silos but pretty much doing the same apps and same processes before or have I really gone through some transformation? >> I tell you what, we've seen quite a bit of transformation in our customer base because they had to. You look at now, as you see with US Banks, they're now transforming their organization to support DevOps, right? That's an entirely new realm for them to focus on. That means they need to make infrastructure easier and simpler so we're finding that is really, I think, that's the catalyst and that they're realizing that the way to do this is let's make infrastructure as simple as possible. Infrastructure service. Make that platform as a service available so our customers can spend less, wait, our IT department can spend less time on the speeds and fees, if you will, of maintaining infrastructure, more time innovating up the stack versus down the stack, right? >> Alright Suzan, I got to ask a question Jon probably doesn't want me to ask you. You're trying to simplify, 'cause you're doing all this stuff that's not really adding value to your business, you want to do stuff that's going to make you more competitive. Well why don't you just throw all this stuff in the cloud? >> Good question and I think that eventually we will have a multicloud strategy, but it is a bank and we don't want to be in the news for a data breach and that's the real answer but also because we want to, again, lay that foundation for an on-premise, solid infrastructure as a service with service catalogs at the business. We can then drive that product taxonomy and they know that they get a good, solid product from IT and then we extend that into the cloud so as much as we can do that, and maybe there will be some cloud native apps down the road that go 100% in the public cloud. I don't have a crystal ball. I suspect there will be, but again we want to do it right and we think this is the right foundation to lay for that. >> You want to have total control over, certainly, your mission critical apps, I'm presuming, right? Maybe put some stuff up. I'm sure you have plenty of stuff in the cloud. Well why Dell EMC? >> I think it goes back to our strategic partnership. It's always been that strong partnership, that enablement, and that continuous feedback loop. We need something, we go talk to our product teams. We get that back, we get it back from our product teams, so it's not always perfect, and there are competitors out there, but at the end of the day, when we look at the Dell Technologies family and that ecosystem and our ability to integrate, iterate, automate within that family, it just helps us stream like that and standardize. >> We've heard this morning from a lot of folks. Michael Dell talked about it. Jeff Clark talked about it. Companies want to consolidate the number of suppliers, certainly infrastructure suppliers, throwing sass forget it, so many apps now. Are you seeing that? Is there pressure to consolidate the number of suppliers, or do you still have, in certain cases, where you really want to go best of breed, so-called best of breed, for some niche app, or do you want to consolidate suppliers? >> So I always want to standardize because that's going to help our automation story, but I still want best of breed, and so that's one of the primary reasons that we're standardized on Dell Technologies today. VxFlex being one of them and Converged Infrastructure being another. There are use cases for multi-vendor strategy, but again, you would look at the right solution for the right job at the right time. >> Okay Jon, that was a totally loaded question, so can you be both a portfolio company like yours and still be best of breed and if so, how so? >> Well I think what we are, we certainly are a portfolio company in the way that, but I think we have leading infrastructure, leading solutions in each case. You take things like Hyperconverge and Converge, great example of that, and I think what we see at the US Bank is that that porfolio of solutions is what's actually enabling US Bank to essentially address all other challenges, right? Whether it's the IS, whether it's the crown jewel applications that Suzan's trying to support, whether it's the DevOps that they're trying to actually build out right now. We've got best of breed solutions for each of those as well within our portfolio. And also, I would say that we're really focused on, ultimately, a portfolio with a purpose meaning that we're taking our networking, for example, portfolio, you just talk to Drew Shulkin. Together with out HCI portfolio, and we're ensuring that they work really seamlessly together so that in the case of, for example, working with, say VxRail or VxRack, we're able to automate all the networking for a HCI environment or at least 98% of it. That's really, again, taking but that's because we're best of breed and porfolio at the same time. >> Yeah so, I'm throwing all kinds of loaded questions out here, and I want to understand this because as independent observers you get Company A says this, Company B says that, but the customer's ultimately the arbiter. How do you, maybe not define, but how do you look at best of breed, what is best of breed to you? >> I look at the technology that's going to make me look good and that's going to make my teams look good and that's not just day one, that's day two and I think that's where the differentiator is as well. We've always found that Dell Technologies is there to support us. Stuff breaks, right? Your car needs oil, your tires need rotating, and it's the same with equipment in the Data Center. How those companies react and they support and they have your back when that happens, I think is the key differentiator and we always found Dell Technologies to be there for us. >> So I'm hearing the breadth, the porfolio. We haven't talked about services but I know that's a key part of it. >> Well, Suzan I hear you talking about day two. CI helped simplify that day one and then, as it matured, it worked more on the day two, and HCI even more. When you talk about the cloud solutions from Dell EMC, that cloud operating model. When you think about public cloud, I don't think about what version I'm on, it takes care of that. When I hear some of the solutions from Dell, it's getting to that model. How are they doing along that that spectrum, I guess, from the, "Okay I need to do the RCM and manage when I do the updates" to "I don't even think about it anymore." >> Sure, I think it is still something that we all care about as much as we're told we shouldn't care about it, I care. I want to make sure that we're doing the right things at the right time. I think it's a journey. I think we've come a long way in the last few years and I think that every year it gets better and as we start extending to that multicloud, obviously that's going to drive some of that solutioning as well. I think we'll continue to see improvement in that area. >> What is something that you'd like to see Jon do to make your life better? (laughs) Besides cut prices, you can't say cut prices. >> Alright, cut prices. >> Every year you cut prices. >> Let's talk about that deal. I think just continuing to be there, continuing to represent, bringing forth the products, the products team, helping us be strategic and also be very tactical. While I have this one last opportunity 'cause I don't know where we are timewise. I just want to shout out to my team. Right, so it's not just the Dell Technologies team that's bringing all this to the table, it's my team and the organization and my peer teams as well. We just keep sharing, we keep collaborating, and we keep iterating. >> Yeah Jon, one of the things, talk about collaboration, my understanding is Suzan's part of one of the user groups here. You know, big community. >> Yes. >> We always talk about at these shows. Maybe you can share that. >> Yeah so Suzan is actually a new board member for our Converge user group which has been around for several years now and she just joined a few months ago. >> I did. >> And I think that we talk about collaboration and feedback. Suzan is representing not just her own team, she's representing teams around IT around the world. And I think she's a great example of providing feedback, not just at Dell EMC directly, but to other users as well, and best practices and tips and tricks. We have a user group tomorrow at three o'clock. I think couple big executives might be there as well, so it's going to be a lot of fun. So tomorrow at three o'clock. I think it's, at least, our sixth annual that we've had here. But the user group itself, I think exemplifies as much as you've been talking about 'cause that's evolved from being what used to just be about a user group just about blocks, VxBlocks, now it's about CI, it's about HCI, it's about VxBlock, it's about Dell Tech cloud. We have VMware on the panel as well as Dell EMC so I think you see the user group has evolved with our customers and with our portfolio. >> It's a community, it's a mechanism for people to say, "How did you do that" or "How should I do this" or "How do I get my team motivated" or "How do I collaborate with security?" These are tough questions and so I think just having that network of people that can come together and ask those questions and be transparent and be authentic, that's what it's about. >> Appearance, problem-solving, sharing ideas. >> Yeah. >> You've been a Converged Infrastructure client, customer for a number of years. >> I have. >> So you've seen pre-acquisition, how has the Dell EMC merger affected your perception of the company and your relationship with them? >> I think in the last year, or the previous year, we were all waiting to see where things fell and what was going to happen, and I think now it's found it's feet, right? We're starting to see some announcements in both the Converged and the VxFlex space, and it's really starting to come together and I think that story, the Dell Technologies family story is really starting to come together where maybe in the last 12, 18 months, there was a little bit of unknown there and so, we just kind of sitting back and waiting and curious but keep doing what we're doing using that best of breed, the best practices that we have on the floor. >> Alright awesome. Suzan, Jon, thanks so much for coming on theCUBE. It was a great segment. >> Thank you. >> I appreciate it. Alright, that's a wrap for day one. Dave Alonte, Stu Miniman, John Furry's over there. Lisa Martin, Rebecca Knight is here. This is day one, we got wall-to-wall coverage. Tomorrow, day two and day three. Check out siliconangle.com for all the news. Michael Dell's coming on tomorrow. We got Pat Kelsey going to be on tomorrow. Tom Sweet's coming on later on in the week. Awesome coverage, check out thecube.net. This is Dave Alonte, Stu Miniman. We'll see you tomorrow, thanks for watching.

>> Live, from Barcelona, Spain it's theCUBE covering Cisco Live! Europe. Brought to you by Cisco and it's ecosystem partners. >> Welcome back to Barcelona everybody, this is theCUBE, the leader in live tech coverage. I'm Dave Vellante with my co-hosts. Stu Miniman, John Furrier has been here all week. Day three coverage of Cisco Live!, Barcelona. Cisco Live EMEA, and R. We learned the other day, add R for Russia. Kaustubh Das is back. KD is the vice president of product management for data center at Cisco and he's joined by Kevin Egan who is the director of the computer systems group for data center. Also from Cisco, gents, good to see you, welcome to theCUBE. >> Thank you. >> Great to be here. >> Thanks for having us. >> KD, Data center was a real focus of the announcements this week. The data center is exploding to a lot of different places. What's going on in the group? >> It's been a terrific weekend, you're right. Data center was a core of a lot of the announcements this week, and as we kicked off the key note with this concept that the data center is no longer centered. It's really, the data moves to the edges, the data center is moving to the edges. We had a lot of announcements around Hyperflex, Hyperflex anywhere, this product that we've been innovating on like monsters. Within a very short time, gone from a brand-new product on the market to a magic quarter liter with Gartner, and really kind of doing a lot of industry firsts with that. That's been a big focus. We had a lot of announcements with our technology partners, because we not only innovate within Cisco, but we work with Pure and NetApp and Citrix and Intel Optane and Nvidia to bring products to the market that get the richness of their innovation and our innovation together. The other big focus has been all about programmability. As the world becomes much more programmable, focus devops automation, it's been around Intersight and programmability and taking that to the next level. >> Interesting. So of course we always talk about shipping five megabytes of code as opposed to shipping petabytes through a straw into the god box. But so Kevin, programmability's a key theme here, of course we're in the devnet zone. We had Susie Wee on yesterday and she was just talking about the evolution of Cisco infrastructure and how early on you guys made the decision. Let's make all this stuff programmable. And that was sort of a game changer, your thoughts. >> Yeah, no it's been amazing. The growth of just Cisco devnet right? We've got half a million developers now developing against our SDKs, our devops, our opportunities all across our Cisco platforms. We've got thousands of Cisco resources doing work on that, producing those libraries, producing that, those sample sets of code and contributing to the communities. And today our customers are using it in a way that they've never really done. Previously it was a sort of a fix because vendor tools weren't getting it done. And now they're using these automation tools to really do every day tasks out to the mass, to reduce the complexity for their teams and reduce the burden. And then of course to have that repeatability and that security and that compliance aspect and it's been amazing the explosion. >> Yeah. The simplicity reminds me back you know the earliest days of UCS, you know UCS was built for that wave of virtualization and as KD has talked with us this week already about some of the partnerships that you've built. The wave of converged infrastructure, UCS really dominated in that marketplace, but here now we talk about AI with some of your partners, you talk about programmability, it's like that's not the Cisco UCS that I remember launching. So maybe give us the updates specifically that was announced this week. Where the platform has gone in more recent days. >> So I can start maybe, >> Yeah, absolutely. >> UCS came up with this concept of everything needs to be programmable, everything needs to be an API. And maybe we were a little ahead of our time, we conceived of this in 2007, got the product out in 09 and really from the very genesis of the program, of the UCS program, it's been a programmable platform, it's been everything's an API. The UI makes calls to the API, our SDKs make calls to the APIs. So that's been the core platform and in some ways it feels like the industry is coming to where we thought it would come to a little bit earlier. So they, this whole concept of infrastructure's code, softly defined what do we want to call it, this was core and germane to the product itself. What we've done lately is, it's taken that policy that we're encapsulated and taken out all of the silver into the fabric for scalability, we've taken that now into the cloud. And what that does is it leads to that velocity of innovation becoming even higher, the ability to create new and unique use cases becomes higher, the ability to conceive it becomes higher. And all of that coupled with where IT is going, which is becoming much more devops, much more around automation. I think those forces are coupling together to create some really unique use cases. >> You said, you gestured take it into the cloud, which is interesting, pointing. What does that mean? Taking it into the cloud? >> So let's speed back a little bit. So what we start off with was listen, a silver's a box, we need to abstract the silver, the personality of the silver out of that box into policy, put it in the fabric. And that allows us to really scale that and give the box different personalities depending upon the workload. What we've done is, we've launched a product called Intersight. Intersight takes that policy and makes it a SAS service, management of the service we want to call it. So now as data moves everywhere, as data centers move everywhere, as our applications no longer become monolithic but become these combinations of little applications communicating across data centers, it allows us to have a centralized dashboard for our infrastructure that we can access, because it's in the cloud, from anywhere. And because it's in the cloud it can kind of get, get that innovation wheel turning much faster. It's just been game changing, and obviously there's other things that can happen once you do that. You can have proactive guidance coming down from the cloud, you can have golden images come down from the cloud, you can do workload specific settings. So there's a lot of new areas that it opens up once you, >> Analytics, right? >> Analytics. >> Machine intelligence. >> So we've got the takeover happening in the devnet zone right now, so focus on the data center, everybody's got t shirts and I think it says Hyperflex on them, big announcement this week about Hyperflex anywhere. Kevin you know I think that when people heard HCI, they often picture a box, or it's a group of boxes it's in a rack, it's all that and everything, and the thing is as an analyst I was poking at it, it's like "well we virtualized a lot of the stuff "and we put it in a new form factor." That's great to modernize the platform but how do we make it cloud native, how does it fit into a hybrid and multi cloud world, and it feels like we're reaching that point now. So help us connect the dots as to how, what HCI was fits into this hybrid and multi cloud world today. >> Absolutely. I mean, HCI when it came out was an alternative to SAN, I mean it was an alternative and it was touting simplicity, touting you know grow with your applications. But really now, with the multi cloud instances that our customers are looking at, they have to have a way to deploy those, a way to connect to those remotely, manage those, monitor those, actually connect that back to the core so that you can take advantage of the analytics that are running at the core and make real time recommendations, make real time adjustments for services and those type of, you know that connectivity is really what we mean by Hyperflex anywhere. It's the evolution of how you deploy, how you manage, and then of course that day two, day five, day one hundred where you're actually making that experience simple for the customers. >> Help us understand exactly, is this, do I just have the backup image in a public cloud, do I actually have similar software stacks, what's the expanse? >> Let me try to unpack that a little bit. I think it's three different vectors that we're doing. So we want as we modernize, and as our customers modernize, they're looking for a much more cloud-like limber, elastic platform. That's the first vector, that's what HCI has done, that's what we've done. And we've actually done it on steroids because we've taken that code-designed hardware and software much like the public cloud guys are doing, but we control that and we can give that to our enterprise customers and our enterprise grade resilient infrastructure. The first thing is that, the second piece of it is what our customers and really our developers and the customers are wanting to do, is to create in one place and deploy in another. So create on the private cloud, deploy in the public cloud, or create in the public cloud, deploy in the private cloud, or actually have an application that bridges the two. So having a homogenous development environment whether it's, and a lot of this is around the container frameworks, whether it's on the public cloud, private cloud. That's key, and what we've done with Hyperflex, and the integrations we've got with our container platform, with open shift, with cloud center, which was again a big announcement this week. That's that second vector, is being able to port applications, develop one place, deploy any place. And the third piece is what we've been talking about all through this segment, which is the ability to now have the cloud drive your infrastructure. Everything's connected, everything's analyzed in the cloud, there's telemetry, there's proactive guidance, there's a common dashboard there's centralized monitoring, there's the ability to deploy, like we did in the key note demonstrating in the key note, multiple different sides spread out across the world, from a cental location. I think that's game changing. >> I'd like to get your take on differentiation. Obviously you guys are biased. Cisco's different, it's better. But I want to hear why. So relative to other infrastructure players, are you, in your words, however you want to describe it more cloud like more programmable, where's the differentiation? >> Go ahead and I'll later on. >> Yeah sure. So basically we started with a foundation of UCS and that foundation, virtualize compute bare metal compute, and of course now hyper-converge, and the reason that it allows us to do things, allows us to Hyperflex anywhere, allows us to have that cloud-based model is because we built that infrastructure around the API from day one. When we started this, that programmatic infrastructure, we were talking to customers, it was stateless it was desired state config, they didn't know what we were talking about. I mean, they had no idea when this came out. But that's the foundation that really allows us to drive the API integrations to our app layers, which is what KD was talking about, and then of course from there to our multi cloud integrations and that's really the foundation that laid, that we laid early on. And that's why all of our UCS platform really enables this cloud integration. >> Yeah, I mean the way I look at it is nobody else has a fully API driven infrastructure. Everything's an API for us, we don't expose APIs after the fact, it is built around, it's an API first infrastructure. And everything is built around them. Whether it's our STKs, our integrations with you know Pop and then Ansible, and those kind of tool sets, our integration with other tool sets that people use. It's all driven through that. The second thing that is different is, we have an emulator, so we can allow our customers to really time travel through the whole process of deployment. I mean, our customers can deploy the infrastructure before the infrastructure hits the loading dock because they can download the UCS emulator. They can actually configure, deploy, build the whole policy on our management platform, test it out, do the what ifs on the emulator. When the equipment shows up, we're ready to go, we are in business, nobody else can do that. And the final thing which is, aside from all of the cloud connected pieces I've talked about, the breadth of Cisco's portfolio spanning from all of our networking assets, our SD WAN assets, our security assets, our collaboration assets, our cloud assets, that breadth gets us to implement use cases for our customers that are just, it's just impossible for anybody else to do. >> We've heard lots of proof points here in the devnote zone specifically from programmability and the automation. I've talked to some service providers here at the show, we've also heard about the journey that enterprise customers are going through to kind of understand that space and learn places here like this. Kevin, I'm sure you're talking to a lot of customers here, maybe if you have examples as to you know the exemplars of who're doing this well, and what people can learn from customers like that. >> Yeah, I mean it's amazing right. In just devnet alone we've got sessions on UCS with Python, STKs, UCS with Powertool, how to integrate with Ansible, these are just becoming common terms, common household terms for our customers. As you go up to enterprise customers, service provider customers, they're using these tools in a day to day manner to do the automation on top of, to really deploy and manage their apps, right, and the way that, I mean, it's exciting, we have customers from all segments of all industry, and they really they use these programmatic, KD's simple example of platform emulator, you don't realize how powerful that is, where you can set that same exact state machine that's in your UCS, you can put it on your laptop, set up all your policies, and then when that gear hits the dock, you are up in hours. Literally we have very large e-commerce sites, they do this, thousands of servers hit it, and in a matter of hours, they've applied those policies and they're up and running. Python, we've got Python, Ruby, Powertool, software developer kits, we've got devops that sit on those, and Ansible, Puppet, Chef, and these are just the automation so if you want to do it yourself, we've got the world class API, nobody else gives you that programmatic API. That's how we built our foundation. If you want Cisco to call those APIs, we have Intersight and we'll make those calls for you. If you just want to do some simple scripting, Powertool. You can automate certain processes, it doesn't have to be the whole end to end. You know you can use all these, it's basically choice to really, what your applications are demanding and what your customers are demanding. >> That's a strong story, one of breadth and depth. We're out of time, but KD I wonder if you could sort of put a bow on Cisco Live! Europe this year, big takeaways from your point of view. >> Listen, we've been innovating like monsters and it's such a terrific week for us to come here, to really touch and feel and listen to our customers and see the delight on their faces as we show them what we've been doing. And this part of the show, day three the devnet takeover, this is where it gets really really real, because now we get to go down to the depths of looking at those APIs, looking at those use cases, getting people to play around with them. So it's just been terrific, I love it. >> I love it too, we're the interview monsters this week. So guys thanks very much for coming on theCUBE. >> Thanks for having us. >> You're welcome. Alright keep it right there everybody, we'll be back with our next guest right after this short break. You're watching theCUBE from Cicso Live! In Barcelona. Be right back. (upbeat electronic outro)

>> Live from Orlando, Florida, it's theCUBE covering Cisco Live 2018. Brought to you by Cisco, NetApp, and theCUBE's ecosystem partners. >> Hey, welcome back, everyone. We're here live at theCUBE in Orlando, Florida for Cisco Live 2018. I'm John Furrier, the co-host of theCUBE with Stu Miniman. It's our third day of three days of wall-to-wall coverage. Our next two guests are from NetApp. Russell Fishman, Director of Product Management, and Keith Barto, Director of Product Management, both directors of product management. One was the former CEO of Immersive, now with NetApp for a few years. Guys, great to see you, thanks for coming on theCUBE. >> Thanks for having us. >> Thanks for having us, John. Thank you. >> We saw you guys in Barcelona, obviously. The NetApp story just keeps on getting better. Also, you have core customer base. Cisco's going under transformation. You guys have been transforming ever since I started seeing NetApp arrive on the scene in the 90s. Every year there's always a new innovation. But now, more than ever, you're hearing even Cisco Bellwether in the routing networking business putting up old way network, hey there's a firewall. There's some devices in there. To a completely new, obviously, cloud made in the modern era really things are changing. So what's your reaction to that? Obviously, you guys are a part of that story. You have a relationship with Cisco. What's your reaction to that? And talk about your relationship with Cisco. >> So we obviously have a huge relationship with Cisco. And most folks will know about our FlexPods, I think that's probably the most famous way that we collaborate with these guys. We just came off the back of an amazing year, five straight quarters of double-digit, year-on-year growth, killing in the market. Obviously, we have to brag a little bit, right, come on. >> It's theCUBE, come on! >> It's theCUBE, we gotta be a little bit excited about it. So we're really excited about that, it just really talks to the strength of the relationship, right? So there's a very strong relationship there, and it's been there with FlexPod for eight years, and there's been a lot of transformation, exactly to your point John, a lot of transformation during that time, a lot of focus on the clouds. So one of the questions I always get asked, is why is converged infrastructure still relevant in a cloud-first world? And it is not obvious answer, now clearly our customers think that it is, and so do our partners. But it is not obvious why that is. NetApp has gone through, you talked about transformation, NetApp has gone through this massive transformation, huge focus on clouds, I mean, we have these cloud-first, cloud-native, focus around our data management platforms. We talk about a concept called the data fabric, I don't know if you've heard of the data fabric before. >> Yeah. >> And the data fabric really talks to how, our vision for how enterprises want to manage that new digital currency that is data across all the silos that they want to leverage, right? We've been able to bring some of that goodness into FlexPod, and that's why we're still relevant now. >> Yeah, so Keith, I think back to when converging infrastructure was built as about simplification, we were gonna take all these boxes and put it down to a box and that was the new unit of measurement. Well, Russell was just talking about we've got multi-cloud, when I think of NetApp now, it's always been a software company, but now software in that multi-cloud world, help connect the dots for us, as to management of converged infrastructure into that whole multi-cloud story. >> Yeah, we were very privileged to be acquired by NetApp last March, and my company Immersive, a lot of us came actually out of Cisco. So I was one of the original FlexPod architects from Cisco and had the privilege of helping to build the network, the storage that we brought into FlexPod, and a lot of our customers and our retailers kept on saying, "How do we know we put it together properly? "How are we following the best practices from the CVDs, "from the NVAs, from the TRs?" And so we took those rules and those analytics and we put them into platform, into a SaaS-based platform, and we were able to analyze that, coming from our customers' FlexPods, from within their deployments, from within their multi-data centers, and bring that into our service, run those analytics, prove those best practices, show the deficiencies, get our resellers out there to help our customers, 'cause FlexPod is a meet in the channel play, and we relied heavily on our resellers to make it a success. >> What was the driver for that product? When you started that company and that happened, what was the main motivation behind that? Was it analytics, was it insight, what was some of the things that you guys were building in, was it operational data? >> The real reason was people kept on asking, "How do I know?" Because it's a reference architecture, not a product, "How do I know I did it right?" Because it's really important, we're gonna run our key business applications on this platform, right? My SAP, my Oracle, my Sequel, my SharePoint, my Outlook. I gotta make sure this stuff is really gonna work properly, and it's going to grow in scale with the business. So I need to make sure that those redundant links are there. I need to make sure that when I do VMWare upgrade, or a Microsoft upgrade, that the firmware is alignment with the best practices in the interoperability matrix, so we wanted to make that as easy as possible, so that from a single dashboard, you can see all of those things, you can diagnose it quickly, you can get those email alerts and notifications, and because you end up with disparate operation teams, the server team, the network team, the storage team, the hypervisor team, sometimes they don't always talk effectively with each other, and from one single dashboard, we're now able to show everybody where things are today, and then, one of my favorites, when there is a problem, you call either Services or Support, and you say, "Hey it's not working," and they say, "What did you change?" And you say, "I didn't change anything." We have that historical-- >> Finger pointing kicks in, it was his fault! >> Yeah we have the historical snapshot and trending, so we can go back and look at where things were and do a comparison to where they are today, and it allows us to have a much faster mean time to resolution. >> And what do you guys call that product now within Cisco? What's it... >> It's now called Converged Systems Advisor in NetApp. >> Awesome, so what's next for convergers. Obviously, people, both cloud growth, we're seeing the on-premise, Wikibon has reported, the true private cloud numbers, which basically say there's a lot of on-premise activity going on, that's gonna look like cloud, it's gonna operate like cloud, so they need to have that. There's migration going on, but it's not a lift and shift, to cloud, there's gonna be, obviously, the hybrid cloud and multi-cloud. So, cloud folks still buy hardware, too. You gotta still run stuff, networks aren't going away, storage isn't going away, so what's next for the converged infrastructure play with FlexPod? How do you guys manage that roadmap? >> So, we just announced some things coming into, jointly with Cisco, coming into Cisco Live. One of those things we announced was something called Managed Private Cloud on FlexPods, or actually no, FlexPod Managed Private Cloud, sorry, I switch it around. And FlexPod Managed Private Cloud, it really talks to exactly what you're talking about, John, which is... What we find, cloud has fundamentally changed customers' expectations of what they want on-prem. They recognize the need on-prem, we live in a hybrid world. Those of us that've been in the industry long enough, and have a couple of gray hairs, know that there are very few transitions that are really absolute in the business. A lot of people pronounce that it's gonna be this way or that way, and the reality is, it's something in between. And that's fine because cloud is just another tool in the toolbox, and you don't want to hit every nail with the same hammer, you want to find the right tool for the right job. So what we've done is we've taken some of that cloud goodness, which really means not having to worry about the underlying infrastructure, all right. Worrying about the applications, being more application-focused, more business-value-focused, more line-of-business-focused. And being able to deliver that in a way that people can consume it on-premise. So it really feels like a FlexPod delivered like a cloud, but from a management day-to-day perspective, you don't have to do it-- >> So, it's flexible. >> It's flexible-- >> FlexPod. >> But it's done for you, so it's your little piece of cloud, sitting on-prem, and you don't have to manage it or run it day-to-day. >> Let's talk about what you just said about the whole transformation, people say a certain way, basically you're kind of saying, a lot of press, and a lot of analysts say, "Oh, you've got to do this digital transformation." Customers will take a pragmatic approach, but you guys at NetApp have been talking for a long time, I've been following it, non-disruptive operations. >> Yes. >> So what you see in the cloud if people wanna take those first three steps, but they don't want to have to overhaul anything, containers have proved to be great resource there, Kubernetes is showing a great way to have life cycle management on the app side of infrastructure. How does your customers, and Cisco customers, maintain that non-disruptive operational playbook, because Cisco guys are gonna start changing, moving up the stack too-- >> Absolutely. >> Doesn't mean storage is gonna go away, but they don't want to disrupt anything, your thoughts? >> And it doesn't mean any of it goes away, that's the funny thing, we talk about where we want to focus, but it's as much about not having to worry about the things that we had to worry about that are just there in the future, right? So it's kind of like if you went back 200 years, going to get fresh water was a big hassle, now it isn't, it's delivered to you, right? I know it sounds like a crazy analogy, but the reality is is that we shouldn't have to worry about the basics of on-premise, private cloud, it should just be automatic, it should be simple to execute, simple to manage, simple to order, simple to deploy, and then you focus on the value, so that's what we've been really focused on. >> Keith, when I listen to my friends in the networking space management's still a challenge. The punchline is usually, they hear single pane of glass, and they said that's spelled P-A-I-N. >> I've heard that one too. >> Talk a little bit about how your solutions tie into some of the broader tools out there. >> Well, we first looked at the compute layer and said, because of the extensibility of USC Manager and the API integration, we're able to take advantage of that, and be able to pull that data out, and XOS, right? We're able to do that exact same thing, and the background that we had at Cisco, and knowing those products really well, we were able to gather all the specific data we need to look at those best practices. And it's a complex architecture, but it's a very elegant architecture, because of the high availability, it can provide the performance, the non-disruptive operations that you were bringing up, John. We want to make sure that we're able to keep those things in line, so as we bring our next release of CSA out, we're going to be adding Enterprise Fibre Channel, so the new MDS switches, we're gonna be bringing our relationship with VMWare in our engine to be able to ingest the configuration of VMWare in. We're also bringing back our partner-centric reseller portal so when customer is running Converged Systems Advisor, they can share it to their reseller, and the reseller's going to be able to provide managed services, support services, and professional services to expand, to repair, to augment those existing FlexPods in their customers' environments. So we're really excited to be able to bring that solution back to our resellers-- >> What's that going to do, what's the impact of that, because I almost imagine that's going to enable them to want to be tightly integrated but also get data from their customers. What do you guys see as the value for the partners to take advantage of that? >> Well, I just met with a partner at our booth, just a few moments ago, and walked them through the solution they had never seen it before. It takes a reseller a week, or even multiple weeks, depending on the size of the FlexPod, to actually go through the configuration of the servers, the network, the storage, the hypervisors, and correlate that into a deliverable to their customer. We can do that in sub-10 minutes, sub-15 minutes. >> So faster time to the customer value. >> Faster time to customer value, faster time to resolution if there is a problem, and then again, they're running in their key business applications on this platform, we've been doing it for eight years, we want to continue to expand upon the value the FlexPod can offer. >> But I wanted to add just a couple of things to what you were saying. We talked about FlexPod really being a channel play. That's important to us in product management, not so important to our customers. What it really means to our customers is they tend to have a very close relationship with their partners. Their partners are the ones that are really enabling FlexPod for them. What we're doing with Converged Systems Advisor, is we are creating such a close relationship at a technical level, technology level, between the customer and the partner, that the partner's there to help them on a daily basis. Where there is a problem, it's almost like the telematics in your car, right? All the cars now, they're phoning back home, they're telling where there's something wrong, you get this letter or an email, you need a service, you need... This is exactly what we're achieving with the Converged System Advisor-- >> When you call support, what don't you want to hear? What's your model number, what's your serial number, what's your contract ID? Wouldn't it be great if everybody's singing off the same sheet of music? >> Well, you bring a great point there. There was so much discussion, well, converged infrastructure a public lot, those are gonna be really simple, and they're gonna be homogenous, and they're all gonna be great, but yeah, you're smiling and laughing because the reality is you're never gonna find two customers that have the same environment, no matter what you're talking about. >> No. >> So I need the tooling, I need the data and the analytics, to help get through that. I shouldn't have to spend half an hour on level one support. >> And that's all-- >> I shouldn't have to go through multiple forms the same time. >> Yes, and you're right Stu, that's always been, that's always been the mantra for FlexPod since the word dot. We don't get to an 11 billion dollar install base unless you're doing something right, and the word, the reason the word flex is in there, it's a dichotomy, whenever you go into these sorts of discussions, do you make it really fixed, right? Which is almost like, I call it like straight jacket, right. But you know what you get, right? Or do you make it flexible, right? And the flexibility really addresses the business need as opposed to the technology need. So the product guys love it when it's fixed, the customers love it when it's flexible. >> Yeah, you're talking about basically, changes... You want changes to be rolling with the... Technology rolling with the changes. >> Yes. >> Not be stuck in the straight jacket, or we'll also say tailor-made suit, but things change, you wanna... Fashion changes, so this is a real big issue, and talk about support, I think the ideal outcome is not to even call support, with analytics and push notifications and AI, you can almost see what DevNet's doing here, around how developer are getting involved with DevOps and network DevOps. Coders can come in and use the analytics, if tightly integrated in, so that you get the notifications, or they know exactly your environment. Is that, how far along are you guys on that path, because analytics play a big role, you've got the command center there, the Converged Systems Advisor, implies advising, resolution, prescription, what's the vision? >> So Immersive was a Cisco solution partner at the very beginning, so we were a part of this group right behind us, and it was exciting to be a part of that, to attend Cisco Live and be a part of DevNet, and we expanded upon, as you mentioned, the API, integrations of all these platforms, and when cluster data ONTAP came out for NetApp, we did the exact same thing, right? So we get integrated with NetApp, and very easily able to bring all that data in. Now, massaging that data is the hard part, right? Understanding what is noise and what is the real goodness, so you have to find those best practices, look at the hard work that our teams have done around validated designs between Cisco and NetApp, and look at the best practices that come from those particular pieces of hardware. And then once that intelligence is built, correlating that in the cloud service is really where the magic happens. So our teams are back there talking with the network experts the storage experts, the compute networks, the virtualization experts, and so when we have that data, and now you can decision-eer, right? You can start advising your resellers. So we bring up the rules dashboard, and then we do have alerting that we can send to ticketing systems to the remedies, the ServiceNows-- >> It's interesting, I'd love to get the product perspective on this, and across the bigger picture, because the trend we're seeing, certainly on theCUBE, over the past few years, and most recently this year, is the move from device, hardware, to system. So the systems approach really becomes more of a holistic view where, you're looking at the holistic view of multiple things happening. >> Yes. >> It's not just, this is the box, here's where the rack is, command line interface, you guys taking that same approach, can you just add some color on NetApp's vision on looking at holistically, 'cause that's really where software shines. >> No, no, and that's absolutely, so we have a way of seeing FlexPod as a, we call it a converged system, and for that exact reason. So what CSA is able to do is look at anything that happens within that converged system and the context of the overall system, and that really is the key, right? When you understand things in context it means so much more. Just think about when you listen to someone talk, a word taken out of context means nothing, right? So when we listen to that infrastructure, what it tells us is understood in context. And what it will ultimately do, and I think you were kind of hinting at this, John, the vision here is that there will be self-healing infrastructures, self-healing converged systems, just like the cloud, right? So we are continuously monitoring the configuration, the availability, and other aspects of your converged system and we are able to take action to make sure it stays on the rails. >> We saw you guys at the RSA event, you guys had a small little party we went to, and we were riffing, having fun with some of the NetApp folks, and the big trend in cloud is server-less. So the joke was, is this storage-less solution coming? To your point about this, if you think about it, it's just storage somewhere. This is kind of a joke, but it's also kind of nuanced. This is elastic-- >> No, no! It's absolutely true, if you look at NetApp's strategy, if you look at our cloud strategy, we're the first third-party branded services part of the AGI core services, we're not in the marketplace, we're actually part of AGI core. It's NetApp cloud volumes for AGI, and a customer doesn't know what's going on behind the scenes but let's be clear, we're talking about software-defined storage here, right? >> And cloud-ified, too, as well, talk about cloud operations. >> Yeah, still at the end of the day, for us, our intellectual property is not really tied to hardware, we obviously use that as a way to get our intellectual property in the hands of our customers. But we're not tied to a-- >> You guys made a good bet on cloud, I remember talking before Kurian took over, you guys were kicking the tires on Amazon years ago. >> Yes, yes, yes, that's right. >> So it's not like a Johnny-come-lately to the cloud, you guys have been deep in the core. >> Absolutely. >> To end this segment, I wanted to get your thoughts, because you guys are here at Cisco Live, what should the audience understand that couldn't make it out here as the top story at Cisco Live, and what is your role with Cisco here, what's the big story, top line, high-order bit, NetApp, Cisco story. >> So I'll go first, and I'll let my friend here go second. We were really excited coming into Cisco Live, right. We had this pretty big announcement last week, there were a few different aspects to it, but I'll talk about two of them. A new focus between Cisco and NetApp on verticals around FlexPod, and what that really means is that we're focused on very specific verticals, including healthcare, but there'll be others that come down the line. We announced a new solution base on Epic PHR. We announced some lead customers, including the Mercy Technology Services, which is part of the Mercy Hospital group. So that was super exciting, I think what it does is it just demonstrates that our focus is on the outcomes, as opposed to the actual infrastructure, the infrastructure is the way to deliver that. So we're very excited about that at Cisco. The second thing that we announced was, I said, mentioned this Managed Private Cloud, we actually announced it with four of our major joint partners, Dimension Data, ProAct, Microland, and oh my Lord, ePlus, yes of course. That was super exciting as well, and what it does is it captures the imagination, and it's always very fun when you're standing at a booth, and people say, "Oh, I've known FlexPod, "I've seen you guys around." But there's always something new to talk about. >> The relevance is more than ever. >> Absolutely. >> Keith, what wave is NetApp riding right now, if you look at the Cisco action going on, what they're going through, what should people know about the big wave that you guys are taking advantage of right now? >> I think the big wave is absolutely gotta be what we're doing with the hyperscalers. We by far have taken the industry by storm, when you think about what we've done with Microsoft, what we're doing with Google, you know, sorry? >> And Amazon. >> And Amazon, thank you. >> Small companies. >> Yeah, just small hyperscalers, right? It's amazing what we can do with cloud ONTAP, across those vendors, and when we look at what our customers have done with FlexPod, and their relationship with Cisco and NetApp, and our ability to work together to help customers get their data from their core data centers to cloud, back, to their customers, and for us to be able to use analytics the way we do on FlexPod, I think there's a real opportunity-- >> And riding the scale wave too, scaling is huge. Everyone's talking about large-scale, talking about hyperscale as that is the largest scale you can see. >> Well, and our ability to control where the data lives, right? Because you want to be able to hold control of your data, and being able to use familiar tools like what you're already using in your own data center and in your own converged infrastructures, being able to use that ONTAP operating system to be able to control that experience is gonna be very important. >> Guys, thanks for coming in for the NetApp update, great news, great alignment with Cisco. It's a large-scale world, and certainly, the world is changing, storage is gonna be a critical part of it, server, storage, infrastructure, cloud operations on-premise, and in the cloud. TheCUBE, bringing you live coverage. I'm John Furrier, Stu Miniman, stay with us for more day three of three days of coverage here in Orlando, Florida, for Cisco Live, we'll be right back. (electronic music)

>> Live from Orlando, Florida it's theCUBE covering Cisco Live 2018. Brought to you by Cisco, NetApp and theCUBE's ecosystem partners. >> Hey, welcome back everyone. This is theCUBE's coverage here in Orlando, Florida at Cisco Live 2018. Our first year here at Cisco Live. We were in Barcelona this past year. Again, Cisco transforming to a next generation set of networking capabilities while maintaining all the existing networks and all the security. I'm John Furrier your host with Stu Miniman my co-host for the next three days. Our next guest is Arun Garg. Welcome to theCUBE. You are the Director of Product Management Converged Infrastructure Group at NetApp. >> Correct, thank you very much for having me on your show and it's a pleasure to meet with you. >> One of the things that we've been covering a lot lately is the NetApp's really rise in the cloud. I mean NetApp's been doing a lot of work on the cloud. I mean I've wrote stories back when Tom Georges was the CEO when Amazon just came on the scene. NetApp has been really into the cloud and from the customer's standpoint but now with storage and elastic resources and server lists, the customers are now startin' to be mindful. >> Absolutely. >> Of how to maximize the scale and with All Flash kind of a perfect storm. What are you guys up to? What's your core thing that you guys are talking about here at Cisco Live? >> So absolutely, thank you. So George Kurian, our CEO at NetApp, is very much in taking us to the next generation and the cloud. Within that I take care of some of the expansion plans we have on FlexPod with Cisco and in that we have got two new things that we are announcing right now. One is the FlexPod for Healthcare which is in FlexPod we've been doing horizontal application so far which are like the data bases, tier one database, as well as applications from Microsoft and virtual desktops. Now we are going vertical. Within the vertical our application, the first one we're looking in the vertical is healthcare. And so it's FlexPod for Healthcare. That's the first piece that we are addressing. >> What's the big thing with update on FlexPod? Obviously FlexPod's been very successful. What's the modernization aspect of it because Cisco's CEO was onstage today talking about Cisco's value proposition, about the old ways now transitioning to a new network architecture in the modern era. What's the update on FlexPod? Take a minute to explain what are the cool, new things going on with FlexPod. >> Correct, so the All Flash FAS, which is the underlying technology, which is driving the FlexPod, has really picked up over the last year as customers keep wanting to improve their infrastructure with better latencies and better performance the All Flash FAS has driven even the FlexPod into the next generation. So that's the place where we are seeing double-digit growth over the last five quarters consistently in FlexPod. So that's a very important development for us. We've also done more of the standard CVDs that we do on SAP and a few other are coming out. So those are all out there. Now we are going to make sure that all these assets can be consumed by the vertical industry in healthcare. And there's another solution we'll talk about, the managed private cloud on FlexPod. >> Yeah, Arun, I'd love to talk about the private cloud. So I think back to when Cisco launched UCS it was the storage partners that really helped drive that modernization for virtualization. NetApp with FlexPod, very successful over the years doing that. As we know, virtualization isn't enough to really be a private cloud. All the things that Chuck Robbins is talking about onstage, how do I modernize, how do I get you know, automation in there? So help us connect the dots as to how we got from you know, a good virtualized platform to this is, I think you said managed private cloud, FlexPod in Cisco. >> Absolutely. So everybody likes to consume a cloud. It's easy to consume a cloud. You go and you click on I need a VM, small, medium, large, and I just want to see a dashboard with how my VMs are doing. But in reality it's more difficult to just build your own cloud. There's complexity associated with it. You need a service platform where you can give a ticket, then you need an orchestration platform where you can set up the infrastructure, then you need a monitoring platform which will show you all of the ways your infrastructure's working. You need a capacity planning tool. There's tens of tools that need to be integrated. So what we have done is we have partnered with some of the premium partners and some DSIs who have already built this. So the risk of a customer using their private cloud infrastructure is minimized and therefore these partners also have a managed service. So when you combine the fact that you have a private cloud infrastructure in the software domain as well as a managed service and you put it on the on-prem FlexPod that are already sold then the customer benefits from having the best of both worlds, a cloud-like experience on their own premise. And that is what we are delivering with this FlexPod managed private cloud solution. >> Talk about the relationship with Cisco. So we're here at Cisco Live you guys have a good relationship with Cisco. What should customers understand about the relationship? What are the top bullet points and value opportunities and what does it mean to the impact for the customer? >> So we, all these solutions we work very closely with the Cisco business unit and we jointly develop these solutions. So within that what we do is there's the BU to BU interaction where the solution is developed and defined. There is a marketing to marketing interaction where the collateral gets created and reviewed by both parties. So you will not put a FlexPod brand unless the two companies agree. >> So it's tightly integrated. >> It's tightly integrated. The sales teams are aligned, the marketing, the communications team, the channel partner team. That's the whole value that the end customer gets because when a partner goes to a high-end enterprise customer he knows that both Cisco and NetApp teams can be brought to the table for the customer to showcase the value as well as help them through it all. >> Yeah, over in one of the other areas that's been talked about this show we talk about modernization. You talk about things like microservices. >> Yes. >> Containers are pretty important. How does that story of containerization fit into FlexPod? >> Absolutely. So containerization helps you get workloads, the cloud-native workloads or the type two native. Type two workloads as Gartner calls them. So our mode two. What we do is we work with the Cisco teams and we already had a CVD design with a hybrid cloud with a Cisco cloud center platform, which is the quicker acquisition. And we showed a design with that. What we are now bringing to the table is the ability for our customers to benefit with a managed service on top of it. So that's the piece we are dealing with the cloud teams. With the Cisco team the ACI fabric is very important to them. So that ACI fabric is visible and shown in our designs whether you do SAP, you do Oracle, you do VDI and you do basic infrastructure or you do the managed private cloud or FlexPod on Healthcare. All of these have the core networking technologies from Cisco, as well as the cloud technologies from Cisco in a form factor or in a manner that easily consumable by our customers. >> Arun, talk about the customer use cases. So say you've got a customer, obviously you guys have a lot of customers together with Cisco, they're doing some complex things with the technology, but for the customer out there that has not yet kinda went down the NetApp Cisco route, what do they do? 'Cause a lot of storage guys are lookin' at All Flash, so check, you guys have that. They want great performance, check. But then they gotta integrate. So what do you say to the folks watching that aren't yet customers about what they should look at and evaluate vis-a-vis your opportunity with them and say the competition? >> So yes, there are customers who are doing all this as separate silos, but the advantage of taking a converged infrastructure approach is that you benefit from the years of man experience or person experience that we have put behind in our labs to architect this, make sure that everything is working correctly and therefore is reduces their deployment time and reduces the risk. And if you want to be agile and faster even in the traditional infrastructure, while you're being asked to go to the cloud you can do it with our FlexPod design guides. If you want the cloud-like experience then you can do it with a managed private cloud solution on your premise. >> So they got options and they got flexibility on migrating to the cloud or architecting that. >> Yes. >> Okay, great, now I'm gonna ask you another question. This comes up a lot on theCUBE and certainly we see it in the industry. One of the trends is verticalization. >> Yes. >> So verticalization is not a new thing. Vertical industry, people go to market that way, they build products that are custom to verticals. But with cloud one of the benefits of cloud and kind of a cloud operations is you have a horizontally scalable capability. So how do you guys look at that, because these verticals, they gotta get closer to the front lines and have apps that are customized. I mean data that's fastly delivered to the app. How should verticals think about architecting storage to maintain the scale of horizontally scalable but yet provide customization into the applications that might be unique to the vertical? >> Okay, so let me give a trend first and then I'll get to the specific. So in the vertical industry, the next trend is industry clouds. For example, you have healthcare clouds and you'll have clouds to specific industries. And the reason is because these industries have to keep their data on-prem. So the data gravity plays a lot of impact in all of these decisions. And the security of their data. So that is getting into industry-specific clouds. The second pieces are analytics. So customers now are finding that data is valuable and the insight you can get from the data are actually more valuable. So what they want is the data on their premise, they want the ability all in their control so to say, they want the ability to not only run their production applications but also the ability to run analytics on top of that. In the specific example for health care what it does is when you have All Flash FAS it provides you a faster response for the patient because the physician is able to get the diagnostics done better if he has some kind of analytics helping him. [Interviewer] - Yeah. >> Plus the first piece I talked about, the rapid deployment is very important because you want to get your infrastructure set up so I can give an example on that too. >> Well before we get to the example, this is an important point because I think this is really the big megatrend. It's not really kinda talked much about but it's pretty happening is that what you just pointed out was it's not just about speeds and feeds and IOPs, the performance criteria to the industry cloud has other new things like data, the role of data, what they're using for the application. >> Correct. >> So it's just you've gotta have table stakes of great, fast storage. >> Yes. >> But it's gotta be integrated into what is becoming a use case for the verticals. Did I get that right? >> Yes, absolutely. So I'll give two examples. One I can name the customer. So they'll come at our booth tomorrow, in a minute here. So LCMC Health, part of UMC, and they have the UMC Medical Center. So when New Orleans had this Katrina disaster in Louisiana, so they came up with they need a hospital, fast. And they decided on FlexPod because within three months with the wire one's architecture and application they could scale their whole IT data center for health care. So that has helped them tremendously to get it up and running. Second is with the All Flash FAS they're able to provide faster response to their customer. So that's a typical example that we see in these kind of industries. >> Arun, thanks for coming on theCUBE. We really appreciate it. You guys are doing a great job. In following NetApps recent success lately, as always, NetApp's always goin' the next level. Quick question for you to end the segment. What's your take of Cisco Live this year? What's some of the vibe of the show? So I know it's day one, there's a lot more to come and you're just getting a sense of it. What's the vibe? What's coming out of the show this year? What's the big ah-ha? >> So I attended the keynote today and it was very interesting because Cisco has taken networking to the next level within 10 base networking, its data and analytics where you can put on a subscription mode on all the pieces of the infrastructure networking. And that's exactly the same thing which NetApp is doing, where we are going up in the cloud with this subscription base. And when you add the two subscription base then for us, at least in the managed private cloud solution we can provide the subscription base through the managed private cloud through our managed service provider. So knowing where the industry was going, knowing where Cisco was going and knowing where we want to go, we have come up with this solution which matches both these trends of Cisco as well as NetApp. >> And the number of connected devices going up every day. >> Yes. >> More network connections, more geo domains, it's complicated. >> It is complicated, but if you do it correctly we can help you find a way through it. >> Arun, thank you for coming on theCUBE. I'm John Furrier here on theCUBE with Stu Miniman here with NetApp at Cisco Live 2018. Back with more live coverage after this short break. (upbeat music)

>> Announcer: Live from Chicago, Illinois it's the CUBE, covering Veeamon 2018. Brought to you by Veeam. >> We're back in Chicago, Veeamon 2018, you're watching the CUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise. My name is Dave Vellante and I'm here with my co-host Stu Miniman. Day one of our two day coverage of Veeamon, On our second year. Vaughn Stewart is here who is the vice president of Technology at Pure Storage, Cube alum, good friend. Great to see you man. >> Good to see you Dave, Stu. >> Dave: Thanks so much for coming on. >> Vaughn: Great to be back. >> So Pure, you know, I remember when you joined Pure and you were like, "Dave, this is going to be the rocket ship of a lifetime." it's turned out to be the case. First company since NetApp to hit a billion dollars in the storage business. It's like independent storage companies are back. >> Yeah. (laughs) >> So give us the update, what's happening at Pure? >> So fantastic year. Wrapped up end of January, right. So first independent storage company to hit a billion dollars. Actually, we're kind of on the cusp of maybe being the the fastest infrastructure company, if not the fastest tied with being the fastest to hit a billion dollars. So the growth rates been great, the products, obviously, have been off the charts. Whether you're looking at it from an analyst's perspective, you know, the gardener reports, the IDC market scape, so if you look at from the customers perspective with the NPS scores, right. Just crushing in terms of the products, the customers stating that we're not overstating the capabilities, and we make some pretty bold statements. But when you kind of boil it back to where we're at now, I think our focus is helping customers adopt a data centric architecture as a part of their IT or data center modernization plans, right. This is, we've kind of gone through this phase of like virtualizing everything, now everything's in the cloud and now we're starting to mature a little bit and we're always looking at this tsunami of data that's being created and it's more around, where's your data going to reside? Because there's going to be some gravity around it and bring the compute to where the data should reside. And so our products and our strategy is to help customers again, this data-centric architecture, adopt new technologies that are going to help them radically shift how they operate, changing the cost of operations, changing the complexity to either let an existing storage team scale to a larger capacity per full-time, you know, FTE or to allow actually the application teams or the private cloud teams to just manage their infrastructure stack, right. We're seeing we're seeing kind of growth in both areas. I think beyond that, our technology with our evergreen storage as a subscription model has also been able to be transformative for Enterprise about how do they acquire, refresh, and introduce new technologies within the storage space. And so it's been pretty exciting. >> So let's talk about some of that. I remember, I've I've been around a long time Stu, as you know, so Al Shughart, the legend, once told me when I was just a pup trying to understand the business. He said, "Dave, the storage business is simple. The customers want it to be dirt cheap, rock solid, and lightning fast." >> Vaughn: Yeah. >> This is the days of spinning discs, which we're kind of dirt cheap, but they really weren't that rock solid and they really weren't that lightning fast. So you guys actually delivered on that promise but you added some other things. Simplicity, the business model of reduced friction. You mentioned Evergreen, so it's not, obviously, not just about flash, where we say, "oh, flash, Pure storage flash, we have flash too." It's so much more than that. The way you positioned it just now the company in terms of data centricity. And, as they say, the business model innovations have really worked well for you. You've been able to stay ahead of the competition. I wonder if you could comment. >> Sure. So I, for your audience, I think it's important to maybe back up a bit. Pure was born in in the the wave of a number of all flash arrays. >> Dave: Yeah. Right? And a fair amount of them were acquired by large existing storage vendors. And I think now that the dust has settled a bit, you know, we were kind of the phoenixes that rose through those ashes, if you will, within the storage space and I think, really, the key driver there was, it wasn't about performance. Flash makes everything faster. >> Dave: Right. It was about a combination of the business model, the operational simplicity, but also, what I would call, the Tier One Feature Sets, right. You had to deliver on six nines of greater availability. You had to have all the data management capabilities to plug into a large partner ecosystem like veeam, which, you know, we're at Veeam live and that was kind of what I would call Act one of Pure, which was, you know, flash ray based, you know, storage for your traditional enterprise apps. Last year we introduced flash blade, right. This was a radically different architecture. It was to scale out a scale out blade-based storage platform that scaled capacity and performance linearly. And the adoption in that space has been this next-generation apps, which... Are just..the sets are growing, you know, out of control and beyond what we would have ever expected with an Enterprise app. So whether it's AI, machine learning, deep learning, analytics, or this new use case we're seeing, which is rapid data recovery. The flash blade, because of the combination of its low latency and massive parallel throughput, has really been a big growth vector for us and it's kind of act two, if you will, of Pure Storage. >> Dave: Go ahead Stu. >> Yeah, Vaughn I'd love to hear more your thoughts on, kind of, an application proliferation. so I think back, you know, you and I lived through that wave of virtualization. While I love virtualization, one of the challenges I had with it was I could take my old application that was probably already too long in the tooth and stick it in a VM and then keep it for another five to ten years because it didn't care about the hardware, their OS, and all that standpoint. Today, talk about cloud native apps, talk about IOT and analytics and all of these micro services and everything like that. It's a huge impact on infrastructure and how we build things. It brings up to speed how we bridge from, kind of, the old world and the new world. >> Yeah, I'm glad that you asked this question. I wish you would be coming to our conference next week - >> Stu: Well, Dave will be there. >> because we'll have a session discussing this and it'll include an internal case study. And so that's all the details I can give right now. For a long time I think a lot of IT vendors, particularly, those who made hardware products, try to position this on-prem versus the cloud, right. and it was really the wrong mindset. Cloud is just one more deployment model for an organization to look at. The question that I think organizations have is, what fits where? And I think, to your point, if you're looking to build a new application or re-platform an existing, what you have today versus in the past was, you had a contained set of APIs and interfaces to work with, right. If you were building on, say, you know, a database vendor's enterprise business suite that was the tools that you got to use. Today you look at what's available, an open source or in the public cloud space, and you get to build a massively disaggregated application that's comprised of functions and and microservices, right. And it gets to leverage these notions of scaling on demand and being being very elastic. What I would share with you and what we discussed with customers is, your development team will want to go as fast as they can and leverage all these new tools and they're iterating very quickly, and the cloud is an ideal platform for that. But you need to plan and look forward to, around what's the the volume of data that you may be dealing with? What's the access requirements of that data over time? And where's it going to be a better position? Should it sit in the cloud? Should it sit on Prem? Should it sit in a private to public cloud hybrid type of architecture model and leverage, say, the compute and all the software agility within the cloud and yet still have stewardship over your data and not have to deal with with maybe unforeseen things like charges per, you know, API call or egress charges things of that nature. >> And Edge as the whole, >> And so I'm grossly simplifying a lot this. but these are the conversations that you get within the enterprise, which is where the sweet spot is. These are real considerations that that they have right there past the is cloud secure or, you know? They're past the data sovereignty type of concerns. They're more around how is this going to scale long-term because, for example, I'll give you an example. So we rolled out meta, which is our AI as part of our support for our products. This all getting ahead of the customers and predicting faults, getting them... This is what helps us achieve greater than six nines availability across the entire fleet for the last two and a half years, right. It's, it's getting ahead of the problems. When we work on looking at some of the AI that we create around meta and we want to test it, we have to download a year's worth of phone home data from the cloud. That takes 45 days to download today and it's not going to get any faster as the install base gets larger, right. And so those are challenges that you have to look at and say, maybe I started in the cloud but maybe I need to look at something in a hybrid model because it's going to impact my business agility. And so these are conversations that we can have and our architects have with customers based on whatever their criteria or forecast look like. >> So just about a year ago Scott Dietzen stepped down as CEO, brought in Charlie - >> Vaughn: Yeah >> new leader. It was kind of, kind of interesting, it was right on the heels of Frank Slootman doing something similar. Frank Slootman just stepped down as chairman and so how's the new leadership going? What, what has Charlie brought? I can't wait to interview him next week on the CUBE but give us your take as somebody who's been an industry observer and, obviously, a long-time Pure employee. >> So ,so a great question. So just for the audience to know, so Dietzen is still with us, right. He stepped down from being the CEO and is now the chairman of the board. and I owe a large gratitude of debt to Scott. Scott brought me into Pure and I'm always encouraged when, you know, every now and then you get that that direct email from him, you know, you know, keep, you know, keep being a thorn in someone's side and push this forward. That was a little self-serving, so I apologize. But what I like about Charlie is, and, and understand I was, I was with Ned F for 13 years, right. And so we did this large growth cycle, not as early as with Pure, but going through a lot of the same growth pains and and whatnot that we have today. But we did all that growth under Worman Joven before they changed over. What was nice about Scott is, he told me on day one that he didn't know how far he would take Pure but it was apparent to him that he had taken it as far as he could, he would find his, his, his heir and obviously Charlie was the choice. And what Charlie's brought in has been a lot of structure, right. The formation of business units, a lot of accountability, a lot of, what I would say, that maturation phase from startup, right. That's kind of grown to the, to the the maximum output of your current organizational structures, to looking forward into a structure that that is going to allow us to scale better over time, right. Continue to grow as well as.. I think Charlie be the first to tell ya, you know, Pure's on a trajectory to hit two billion dollars and can do that on inertia in the current products, right. Charlie's focus or one of Charlie's focuses over the last handful of months is, is, what are we going to become two years from now and what investments do we need to start making in the near term to get prepared for two years from now? >> So I, I brought up Frank Slootman who's in the service now because I know, I know Frank and Scott were close, right? There's some board action going on there over the years, they're part of the Silicon Valley mafia with the Mai Bucherii. But but I, and we can joke about that but there's a there's a culture of succession that has really taken hold in in certain parts of the valley and, and again, very similar to what we saw as service now, where was the new guy was brought in to take them to the next level. And the existing CEO, you know, mature enough, you know, maybe, maybe worked so hard for all these years too, maybe felt like they need a little break. but still mature enough to say, okay, I know my limitations and I want to bring somebody else in. So it's been sort of this new thing and I want to tie it back to something we were talking to before on the CUBE. I mean, you guys hit escape velocity. When you look back at the sort of the virtualization craze with Three Par and Isilon, Data Domain, Compelling. Yeah, they kind of hit a billion-dollar status you know, they hit unicorn, but they never hit billion dollar revenue. And, and so now, and then the other thing you talked about was some of the bigger players decided to buy up flash companies. >> Vaughn: Yeah. >> And they said, you know, rather than pay 2.5 billion dollars for a data domain or Three Par, we'll spend a billion dollars or, in some cases, hundreds of millions of dollars and then we'll organically grow that internally. Did it work? Yeah, maybe yeah, you know. Maybe some of it, maybe not. But, but you guys stayed the course and are now on track to do two billion. >> Vaughn: Yeah >> So here's my question, long-winded sort of narrative babble, sorry about that. I used to question Worman Joven all the time Tucci, even. Can you stay independent? Right? That was the big question. You know, because Converged is coming. But now it looks like being an independent is actually in vogue. Best-of-breed is actually still a viable business model. >> So obviously I'm not in on the inside of whatever the board decisions may be. >> Yeah, but you're an observer who know this business. We're kind of talking about Vaughn the prognosticator, analyst, if you will. >> What I think is different today, and Stu and I were talking about this because we ran into each other over in the corner with Duncan. You know, the emergence of all the flash vendors and them getting acquired and really what's happened by and large is just the same old products just got flash injected into them and, you know, got, you know, the the vendors hope to get another decade out of them. But okay, they're faster, but it doesn't fundamentally change your business model or your operations and sometimes that's a good thing, right. For some customers, right, their change averse. >> Right, they don't want that disruption. >> Yeah. For us, right, we're trying to usher in now this this next wave of shared accelerated storage and it's a disaggregated model, right. Start to look up it at what, you know, in a commercial sense, if you will. What are the enter.. what are the the hyper scalars, you know, delivering, you know? They're not running data direct attached storage. They're not doing HCI, right? They've got pools of compute and pools of storage and it's either disk and cold or it's flash flash and hot and, you know, they've got network and it's all over Ethernet, so it's greatly simplified. We're trying to help our customers with, with that type of architecture. Whether they're looking at simplifying their private cloud or extending the private cloud to the public cloud, or what's even more interesting, as they look at like their data pipelines, you know, a lot of, you know.. There's, there's AI and analytics in every organization of every size. They may or may not sit inside the IT department but they tend to follow that model of eighths and software. So I'm just going to do it on DAS and I'm going to build this siloed cluster. And, you know, it must be cheap regardless of whatever the efficiency I get out of it. And what we're trying to help large organizations look at is data pipelines and flow and the flexibility that you gain by separating compute from storage and not having to worry about the performance issues or constraints of disk-based systems from a decade ago because technologies like flash and now with non-volatile memory Express and non-volatile memory expressed over fabrics, right. You're getting direct memory to memory communications from the servers to the storage. So you're getting all the benefits of pooling and sharing your storage with all the benefits of it without a local bus in terms of speed and performance. And so it can change, particularly, a large volume of data. You can change your agility. >> So that that is certainly a tailwind for you but it was a tailwind for a lot of companies and you have the product. Let's assume best product just for sake of argument. I'm sure you would agree. But best product doesn't always win, right? So what I'm hearing is there was business model innovation. >> Vaughn: Yeah. >> Obviously very strong go to market. You guys knew where all the skeletons were buried with all the reps that you guys hired. But there were other factors involved in your ascendancy, which maybe is independent of the structure of the industry because the industry structure is changing. It's going from, you know, now remote cloud services into these digital, this digital matrix and somehow you have to fit into that digital matrix and participate in that. >> Yeah, it's.. I think you brought up two points,\. So I think if you if you're going to be a start-up, to be successful, it's not just technology. You've hit the head on the nail there. Pure had.. the technology had to deliver, Pure had that. The business model was innovative, the marketing was off the hook, right? For a start-up, you know, we were punching above our weight but you also have sales, have sales force execution and, you know, you never know what you get when you walk into a start-up. But you've got to.. If you don't hit on all four of those dimensions then you don't achieve escape velocity. In terms of shifting from startup to, you know, becoming mainstream. Not only did we achieve a billion dollars last year, we were cashflow positive for the year and we were profitable for Q4, right? So that puts a lot of wind in ourselves as we go forward. You know, with, at the end of last year, a half a billion dollars in the bank and now a billion dollars in the bank. You know, for us to go you know figure out what we're going to grow and go into. I think moving forward and being independent, I think we'll see, right? I think there's always a tick-tock in our industry, right? Things are distributed, they're centralized, their distributed, I want one throat to choke, I want best-of-breed. I think with all the distributed apps and all the analytics platforms that are going to start to become more important than what we're used to in the X83 space. I think best-of-breed is starting to rise up right now and so I think the runway for Pure to stay independent is there. Don't get me wrong, we're going to have to do our works with plugging into clouds, right? And all those those ecosystems because customers want a transparent experience. But we'll be sharing some news on that, I think next week. >> Well and excited to here that. The cartel will continue to suck up startups, no question about it. But, you know, we love companies like Pure, put Nutanix in that mix and it was sad to us to see all their run of the virtualization comers, they just disappeared. Because if it's just the cartel building new products, you're not going to have the level of innovation that you get with VC funded startups in the valley. you just, you're just not. >> Well, in the US you're seeing, I mean, you're, in the US you're seeing VC investment starting to diversify a bit, right? >> Dave: Yeah >> Colorado's getting hot, the Boston area is, it has been there for a while but it's getting hot. >> IOT and security. >> And, you know, that's been the great thing about, you know, about IT in the US, right, is we've been an innovative landscape. I think the barrier has probably forced some innovators out based on just the cost of living. So, you know, who knows what the mix will look like a decade from now, but yeah, we're still going to be Silicon Valley centric for the near-term. >> So I love talking you because we can have these conversations. We were joking off-camera, we could go for 90 minutes, which we easily could. We got to, we got to go soon but let's talk about Veeam, relationship with Veeam. You guys are kind of birds of a feather in a lot of ways but, but take us through that. >> Yeah, so the opportunity to partner with Veeam was a no-brainer. There were synergies there, right? Pure and Veeam both trying to just disrupt legacy markets, doing it through simplicity, right? Riding the wave of, you know, virtualization as a primary business focus but not exclusive. our Net Promoter scores with both companies are off the charts, right. Customers love it and, you know, we're multiples higher than any of our competitors. And so bringing the technologies together were real simple. So last month we announced, four or five weeks ago we announced and released a new set of solutions and integrations. It was comprised around three areas of benefit, right? Accelerating backups, increasing the speed at which you could recover data, and adding a new level of agility within your ecosystem. So delivering those three value props were based on us supporting their Universal API adapters. So now that they can offload some of the backup process to array-based snapshots and that preserves the performance, makes the window collapse faster. That's where when production data sits on the flash array. We've also certified putting the flash blade behind the Veeam servers as a backup data repository and the benefits of that from a backup window are faster data ingestion times across your real estate. Obviously, smaller footprint, lower cost within the data center. The bigger impact on both of these is on rapid data recovery. So with Veeam, through their explorer integrations, you can pull files, disks, VMs, applications, right out of the array snapshots. If the array is still online but someone's just munched the data, if the array is no longer there and you need to pull from the flash blade, flash blade gives them a capability that they never had with disk, which is they can start because, you know, how Veeam recovers, right? They actually start the data services and recover them from the backup repository and then live migrate it back to the production environment. With the live, with the back and the data repository being all flash, now they can bring up a significant, if not all of your data back online and then trickle restore it back to the production data sets. We had a customer with a large distributed database that was on a more traditional disk backup system that was really focused on ingest, right? Make the backup window not so much focused on the restore times. It took them in excess of 36 hours to put back their database and this was the mission critical database to the organization. We've come in and replaced that. 36 hours is now 30 minutes. So is all flashes as repository for your backup for everyone? Maybe not for every organization but we're seeing a big growth ramp on that in the enterprise. The last piece that we've brought to market together in integrations is, integrating with their data labs. That's their environment to be able to on-demand create, test, and DEV infrastructures for you and that pairs really well with all flash arrays and snapshots because it's instantaneous, consumes no new storage, and our automatic QOS preserves that, preserves the resources for the production environment from the lab. And so those are our three areas: accelerate backups, rapid restores, and give you some agility with your test DEV. >> Okay and the agility in the ecosystem is oftentimes underappreciated, right? >> I'm amazed at the customers that I.. Large enterprise customers, right? Revenues in the tens of billions of dollars that you still meet with today, where they've half staffs that their job is to restore, you know, an Oracle database to an Oracle developer and that's all the guy does 40, guy or gal, does 40 hours a week, it's amazing. >> Right, Vaughn, great to see you again. >> Dave, awesome. >> Thanks so much for coming to the CUBE. We'll see you next week Pure Accelerate at San Francisco. We're there Wednesday, I believe, we're broadcasting. So look for all the things that Vaughn teased. He showed a little leg on some stuff, so we'll be covering that next week. We're back here tomorrow. Stu and I will be kicking off at 9:30 with Peter MacKay, so don't miss that. We're out for today, Veeamon 2018 the CUBE. See you tomorrow (electronic music)

>> Announcer: Live from Chicago, Illinois, it's theCUBE. Covering VeeamOn 2018 brought to you by Veeam. >> We're back at VeeamOn 2018, you're watching theCUBE, the leader in live tech coverage. I'm Dave Vellante with my cohost Stu Miniman. Stu, always great working with you. Bruce Shaw is here, he's the Senior Director of Global Alliances and Industry Solutions at NetApp. Great to see you, thanks for coming on theCUBE. >> Thanks for having me. >> So, I got to start out with NetApp, I mean, we've followed NetApp for decades, ya know, from the very beginning back when I was at IDC, Stu, you were probably still in your mother's womb. (laughing) But you guys are back in a big way, I mean, for a while there it looked vulnerable. You took advantage of the Dell EMC merger. You're gaining share again, you're growing, stock price is up, there's a spring in your step, what's going on? >> Well, a lot of things are going on. I think we've had a lot of leadership additions to the company, Henri Richard joined and took over as the CSO with the company. We've got a new CMO in Jean English. But more importantly, a lot of the areas that we were late to the market, and candidly we've admitted we were late. We didn't have a good Flash story a couple years ago. We've been very aggressive with Flash over the last 24 to 18 months. We're now the fastest growing Flash storage provider out in the market, and we think we'll exit this year as number one. In fact, we think that's the current course and trajectory. We're very happy with where that's going. The FlexPod partnership with Cisco was great this past year. We had a record year in Converged infrastructure, which was a down market, we picked up about 13 points a share according to IDC, so a lot of the cylinders are starting to fire, but the one that is probably the biggest and the most shocking for folks is three, four years ago, the belief was that cloud was going to kill on-prem storage for companies like NetApp. I think the one thing that they did right ahead of the curve was they embraced the cloud. They've got great partnerships with Google, Amazon, the hyperscalers, and cloud strategy and the business that drives the company there is the fastest part of the company, and Anthony Lye runs that team, and it's doing an amazing job. >> Explain how, and you're absolutely right, many, most, frankly myself at times, felt that way. Explain how cloud is a tailwind and not just a one-way street into the roach motel. >> Oh well, there isn't an enterprise today that isn't thinking about cloud in some way, shape, or form, right? Now, ya have prognosticators on either side saying it's all going to the cloud or something less than that, but the truth is when you look at a strategy like ONTAP and the ability to move your data, whether it's on-prem or to the cloud and manage it through our data fabric story, that's where NetApp really starts coming into their own. I think, again, that's where we've been able to take advantage, and it's not just having it one way or the other or being good just with the hyperscalers or good with the guys that want to be secure because most companies do a hybrid story, and they want to bit of both. >> Well, I think the one thing that I would observe about NetApp, having followed the company for many, many years, which I think gives you an advantage, is NetApp really has always had storage services in software that were largely decoupled from the hardware, and that allowed you to get into cloud early, don't ya think, Stu? >> Yeah, absolutely, and Bruce, we're here at VeeamOn, and their message sounds a lot like that to me, so maybe help explain, we were just talking to Veeam's CMO, when you hear some of the descriptions of storage services, software, multicloud, and everything, NetApp and Veeam sound alike. How are they complementary in, ya know, maybe where do they bump up against each other, yeah? >> Yeah, well, we both compete in the same market, which is storage, so of course, there's areas where we're going to compete with each other, but we are very complementary in terms of the story and the markets that we serve, right? NetApp is incredible strong in the enterprise. Veeam has great commercial channel presence, so from a route to market there's a lot of complementary stuff we do with each other. Price point, in terms of where we hit the market and the things that we go after, we have a lot of opportunity where there's not overlap to help each out to the point they're now, the relationship's evolved over the last four years where we're actually doing OEM of each other's products. We've got our E-Series we just announced yesterday that we're OEMing with these guys, which again is targeted at exactly those markets. The story between the two that we're both at our core not hardware companies, not storage companies, but data management companies really is where this starts to come together and play well. The fact that they're mutually supportive of each other makes for a really strong value proposition for the customer and the channel, especially the guys like the service providers or ya know, hybrid cloud providers, it's a big time story for them. >> So you're growing with, the partnership with Veeam is growing. >> Right. >> Ya got a combination of trends that become tailwinds, but then you've got execution. Can you explain what are those tailwinds, and what's the execution ethos with the partnership? >> We are a channel-only company for all intents and purposes. >> Dave: Oh yeah, I don't know what the number is now, but you've always been very, very high performing. >> Yeah, I know, so we look at businesses that we drive, and channel is at the core of what we do, so when you have a tailwind like, ya know, where we are with Flash and the growth there, the channel partners are making more money, the programs that are coming for them, we're not taking business that they're doing today and pushing it towards the cloud. Again, we're talking about the story that's transitory between the two, so for a lot of the channel providers that are out there getting in the market, that's a very powerful story for them. That it's not a competitive business, we're not going to try to create our own cloud service to take away from them. We want to help them as they migrate between the two. >> All right, Bruce, one of the other areas we're hearing a lot about at this show that I think lines up with NetApp is the analytics and AI, can you maybe talk about how that ties into the products? >> Yeah, I mean, you look at a lot of these markets like AI, like analytics in terms of what companies are doing, it sheds off a tremendous amount of data, right? And that data is at the heart of what they want to analyze and go through, and when they bring those things to market, the goal is how I quickly move it from where I'm capturing it to where I need it, and ONTAP does a really good job of doing that in terms of being able to take the data to where they need it, whether it's at the edge or whether it's back at the core of the company, so that you can actually do the real work with it and gain the insights that drive the business. >> Bruce, what's the resale agreement that you have with Veeam, can you explain that? >> We have Veeam on our price list. Our sales reps can sell Veeam, can be compensated for it, vice versa, they can absolutely hook in and drive away with NetApp, and now that we're getting products like E-Series where their product is embedded in ours, that only strengthens that kind of motion. So for a NetApp sales rep today, if they have an opportunity where Veeam is needed on it as part of the offering, it's absolutely in their wheelhouse to go sell it, and they get the sale level of love and attention from quote and comp standpoint that they would if it was NetApp only products. >> So this is kind of interesting innovation that Veeam, I think, has been out in front of, they, and I dunno how they do it, Stu, but I think Veeam understands the lifetime value of a customer and is willing to make, put sweat equity into a deal as part of a partnership to make it transparent to a partner sales force. >> Yeah absolutely. >> That's innovation in business model. >> Absolutely, we're very proud of our sales force and the work that they're able to do. We view ourselves as kind of the last big enterprise standalone storage company that's out there doing this, and I run strategic alliances, and some partners integrate really well with our sales guys. Others, it's more of a, ya know, it requires more work. To your point, Veeam has done a superb job at identifying how and where they play with our folks and getting together where we go to market together. >> It's interesting, we used to, ya know, several years ago now, ask the question can NetApp remain independent. We've seen all these independent storage companies kind of go away. Used to have this conversation with David Scott at 3PAR all the time, EMC itself wasn't able to maintain it, and then NetApp got to the point where it was almost too big for an acquisition, and although stock price was down, everybody, NetApp was the rumor of MNA more than any company I can think of in the storage business, but now you're seeing sort of antithetical to what most people expected, it's kind of like the cloud we were talking about before, storage companies emerged. Pure was the first one over a billion since NetApp. What are your thoughts, and what's that, I wonder what, you guys must talk in the hallways about that whole, the dynamics of the industry. It seems like it's still a viable business model to be best of breed. >> It's very viable, so I took over running the strategic alliances at the beginning of January, and my dance card's full. I can't believe the number of folks that are calling up wanting to partner. I think we've gotten much more mature in terms of how we view the market and our ability to get strategically with other companies to be successful, and there absolutely is always going to be a place out there for a best of breed story. Customers want the best technology that they can get to handle their business needs, and if we partner with great partners, whether it's Veeam or others to provide that for them, I think the viability of NetApp only gets stronger not weaker. >> It's interesting because now ya got NetApp, Pure, Nutanix, soon to be Veeam, as billion dollar independent pure play companies in the storage business. Isilon couldn't get there, Data Domain couldn't get there, Compellent couldn't get there, 3PAR couldn't get there, Lefthand couldn't get, EqualLogic, I can go down the list. They were never able to reach that escape velocity, and maybe it is cloud, maybe cloud is that weird tailwind for people who can figure out how to take advantage of cloud and hybrid cloud, your thoughts? >> Yeah, I think it is, number one. I think also the companies that you mentioned at various times, and I'm a hardware industry dinosaur, I've been around forever. A lot of those companies you talk about the difficult moment from them was hey, we're a storage company, now we want to add compute or now we want to go into this part of the market that put them at odds with the guys they were partnering with. George, our CEO, has been absolutely maniacal with his vision of our path forward is managing data, period. Whatever that form takes, we don't need to be a compute company, we don't need to be a networking company, we want to be a data company. I think how that then drives the decisions, whether it's partnering with cloud, whether it's going into new markets with HCI, even if it's things about transforming the legacy data center from traditional data center and how it's managed on-prem to something that's all Flash driven and much more efficient and much more programmable than it was in the past, so it's easier to administer, those are the areas that we can go innovate, and as long as we're partnering with the right partners out in the industry, that makes us a very good viable destination for the customer without worrying about well, do we have a compute node, are we in the server business now, are we suddenly in the switch business? Those are things that are not even on our radar. >> Yeah, I mean, you guys are in a unique position from that standpoint. You're very large now, you're the largest independent storage company, so everybody wants to work with you. You don't bump up into these adjacencies, and you can make bets, you can place your chips in areas whereas some of the startups, there's tons of innovation, but it's really hard to hit that escape. The amount of resources that you need, the money you need for promotion, the talent war that's going on out there, the go-to-market challenges, the partner challenges, so you guys are in a pretty good position right now. >> We really are, and I think we've actually done a lot of the restructuring internally to continue that and capitalize on it. Probably the biggest change, which outside the company, most folks wouldn't notice immediately, is that we moved at the beginning of this year to a three distinct business unit structure where we're focusing on three parts of the business to go forward. We've got our cloud business unit, which is driving into, as I said, the hyperscalers under Anthony Lye. We've got cloud data center, which is more of the new technologies like HCI and Converge and object storage technology like StorageGRID, and that's, right now that's an incredibly fast growing business for us. Then, of course, we've got our traditional storage software infrastructure business where we have products like E-Series and modernizing the data center, which is primarily driven with this transition to Flash. You've got three BUs now that are maniacally focused on the different areas of the market where we see here's an immediate opportunity in Flash. Here's a slightly longer opportunity in things like hybrid cloud and HCI and Converge infrastructure and a much longer term bet was how does the cloud really become a piece where we're managing between all of those. It lets us be a lot nimble between it. It's almost like three subbusinesses where we're going to market. >> Yeah, Dave, and actually that aligns perfectly with the research we've been doing for over five years from server stand and true private cloud, you've got the hyperscale, you've got the transformation locally in spanning those two, and then you've got that transition from the traditional. >> Oh, I think it's a sound strategy, and it'll serve us well in the years to come. >> There's obviously a lot of noise about artificial intelligence in the marketplace. You've got some companies trying to position to be the platform for machine intelligence or artificial intelligence, what's NetApp's point of view on that? >> Well certainly, we share some of that, but again, I think at the end of the day for us, it's much more important about fine, wherever I'm capturing that artificial intelligence is not likely the place where I'm going to do a lot of the analytics and work on it, so it really does come down to, ya know, am I moving it up to the cloud to do that work, where am I making my big insights, where am I mining through it, and then how am I relating that back, whether it's at the edge or whether it's at the core data center, and again, we think with ONTAP, with the partners that we're going to market with for AI, for ML, IoT, that's the difference maker for us at the end of the day. It's not that we're just another storage company storing the telemetry data off of a car for AI, we're putting it into a format and a form that's usable quickly, efficiently, real time, where Tesla can go make a decision on the car right now, not days, weeks, months from now. >> All right, Bruce, well hey, thanks for coming on theCUBE. Really appreciate your time and good luck. >> Enjoyed having me, thank you. >> All right, great. >> Good to see you guys. >> All right, keep it right there everybody. We'll be back with our next guest. You're watching VeeamOn 2018, this is theCUBE.

>> Announcer: Live, from Las Vegas, it's theCUBE, covering Dell Technologies World 2018, brought to you by Dell EMC and its ecosystem partners. >> And welcome to our live coverage here. Day three at Dell Technologies World 2018. We are live in Las Vegas. Hope you've been with us for the first two days. We have a great lineup here for you on day three. I'm John Wallace, along with Stu Miniman. Glad to have you along, Stu, it's always great to work with you. >> Thanks, John. Same for you. >> Good week so far for you? >> It's been excellent, my voice is holding up, it's been a long week. >> You're a busy man. >> Excited to get all of this, and heck, I'll be seeing Dan again next week at the big show. >> Dan McConnell's becoming like, he's like not even an annual visitor, you're like a bimonthly visitor here on theCUBE, right? VP of Converged Platforms. >> Stu: Fifth time, you get a free sandwich. >> Yeah, that's right, I got to punch card, I got to sign and get it punched each time. >> Yeah, nice to have you, Dan. Nice to have you back, good to see you again. Alright, let's just talk about the show, first off. Here we are, day three, we talked a little bit yesterday about customer discussions, conversations, so now you've had a little bit of time to soak this in and what you've heard from folks, and what would be your takeaway here? >> Sure, may spin this one a little bit, may have an angle here. Tremendous interest in HCI, and I'm not saying that just because I'm in HCI. No, but it's a lot of good, solid feedback from customers. It's starting to shift more in the mainstream, right? So as we see customers deploy it, more workloads get deployed on top of it. There's a tremendous amount of interest in HCI. When we look at all the graphs of customer interviews we're doing and analyst discussions we're doing, HCI is right there at the top of the list, in terms of subjects that we're talking about. >> Can you quantify that? Are numbers at all out there floating around, in terms of growth, in terms of what... >> Oh, from the HCI side, yeah. Most analysts will agree, it's about 70 to 80 percent in growth year over year. I'd say, from a Dell perspective, we're doing 138 percent, so we're actually growing faster than market. A lot of that's due to, we've got a, one, we've been in the HCI business for a while, two, we take a portfolio approach. There's never any one size fits all, so we actually take a portfolio approach to HCI. We've got what are multiple different consumption models, one that is an appliance, this is the server, the hardware, the software, lifecycle managed in an appliance. And then the next layer is what we call rack scale. Obviously, HCI puts some pressure on the network, right? High network dependency. Rack scale, what rack scale does is include the networking components in that engineered system attribute. Pretested, pre-designed, inclusion of both the physical, as well as the virtual network, and across both of those consumption models, we have a stack that is very VMware-centric, right? VxRail, VxRack SDDC, and we have a stack that is what we call Open HCI. Supports multiple hypervisors, that is XC series on the appliance and VxRack Flex on the rack-scale solution, so portfolio approach, cover the whole market, and we're really seeing it blow up, it's great. >> Dan, it's interesting. I think back to when people were first trying to wrap their brains around this whole HCI thing, it was like, oh, okay, I took server and storage, kind of smashed it together, some software maybe in there, but it was, oh, this is small-end thing, it's maybe four nodes, maybe getting to eight nodes, but you talked about the VxRack Flex, which we've been watching ScaleIO since before the acquisition, and all that solutions. Much larger configuration, some people said, oh, it's not even HCI, because I've talked to some customers, well, I can do a storage-only configuration or I can do a full hyperconverged configuration. We've seen maturation and some segmentation in the marketplace, so you know, bring us inside that, from, you know, the Flex business, just what you're seeing, what differentiates it from some of the other options. >> Absolutely, I'd say it's flexible. (dog barking) Dog barking next door. >> John: On cue. >> On cue. >> There he is again. It's one of the philanthropic Dell outreach programs, it's comfort pets. >> Therapy dogs. >> Therapy dogs, thank you. So we're right next door, no reflection at all on the guests or the program or whatever. >> They're in day three, too. It's been a long conference for them. >> We're getting punchy, alright, back to Flex. >> Back to Flex. >> Just explaining, yeah. >> So, back to your point. Flex... is flexible. We've got customers from four nodes, all the way up to over, large enterprise customers over a thousand nodes. Matter of fact, about 45 percent of our business comes from Fortune 500, so when you think HCI, like you said, HCI started in what was VDI. We're going to pick a workload, VDI's kind of linearly scalable, HCI was a good fit. Nowadays, it's multiple workloads, right? That flexibility, agility, ease-of-scale, people are putting more and more workloads on top of it. VxRack Flex, we've got, when you talk about scalable, up to a thousand nodes, literally 30 million IOPS, right? So, performance, I think we've got it covered. So it's definitely maturing, some of those larger customers are running anywhere from database, all the way to mission-critical applications. >> Dan, I actually did a case-study of one of your larger global financial companies a few years ago. Want you to talk about what they saw this solution at. This was a foundation for their private cloud. They use, in certain regions, public cloud makes sense, but in a lot of areas, this is the foundational layer of private cloud. A lot of times, people, oh, HCI, it is what it is, it's some boxes and some software, but talk about the private cloud angle. >> This customer, it's actually a very interesting storyline. They started off doing what we would call do-it-yourself, build-your-own, and loved the technology, as is predominant with HCI, continued to scale. Bought a lot, added on, added on, and as they continued to add, continued having discussions with them, and they actually love the technology, would love to be able to automate more, would love to spend less time setting it up as it comes in. So they actually moved up that consumption pyramid into VxRack Flex, which comes, as opposed to do-it-yourself, comes shrink-wrapped, roll it in. So they actually designed their infrastructure, their data center around what they call pods. Fairly large pods, but they've changed the consumption units on how they consume IT. They'll actually wheel in Flex pods, that's their new unit of consumption. Now, a Flex pod is... >> Not to be confused with another product called FlexPod. >> Oh, gosh, yes, VxRack Flex pods. Yes, absolutely. >> We unfortunately have run out of words in our industry here, so yeah. >> I'm sure you'll find something in the vernacular that will apply here. >> I'll try and burn that one from my memory, but good catch. >> So that's one use case. Just in general now, so what is the value prop for a customer today, as opposed to what kind of flexibility you're giving them, we've heard about performance, but how are people actually putting it to use for them, and what are they doing better, do you think, because of that? >> I'll start off, one, which is an architectural discussion, and I'll crunch this down pretty small. In the beginning, there was DAS, direct-attached storage, and it was fast, and it was easy to manage, as long as you had to manage one. You get a hundred units, and it was siloed storage, and it was hard, so the world came up with SAN. It's consolidated storage, it's great. I can carve it up, I can manage it from one place, and then we came up with flash, SSD, blindingly fast, and that storage controller started to be a choking point, so we moved the storage back into the server, a la HCI. >> Actually, we called it Server SAN for that specific reason. >> Exactly right, exactly right. Initial ventures into some of HCI, you could only scale the storage or only scale the HCI clusters as big as one given cluster. So you started building somewhat of silos of HCI. One of the beauties of Flex and VxFlex OS storage software is it can scale across multiple clusters. Those clusters can be VMware, they can be BareMetal, they can be Linux, so you start to gain all the advantages of HCI, flexibility, agility, kind of incremental scaling, pay as you grow, with all of the advantages of storage consolidation. I no longer have pools of siloed storage, I can carve up ones as needed, when needed, I can manage it all as one combined storage pool. From a Flex perspective, it's got some pretty nice architectural attributes, which give you the best of HCI and agility and scale, as well as storage consolidation. So we're seeing a lot of success there. >> Dan, I hear things like open, flexible, some of those environments, and I think about the service providers and requirements that they have for how they need to simplify their environments, super conscious on cost, how's this been doing in the service provider market recently? >> Absolutely, funny you bring that up. We actually talk internally, we've got a service provider team inside Dell, they focus on servicing the large telcos and other service providers, and we've noticed that their underlying infrastructure is very very similar with Flex, so we're in discussions to see how we land what they do on top of what we do as a standardized offering. Even right now, a lot of our customers are in the service provider space. That large growth, flexibility, and some of the underlying storage stack has multi-tenancy capabilities, where you can carve up and isolate, that lend itself very very well to service providers. >> Oh, go ahead, Stu. >> For people that know ScaleIO, anything new that they should be understanding? I understand it's this packaging as like a hardware model. Organizationally, it lives under the server team now, I believe it is. >> Absolutely, so two things there. One, organizationally, all the HCI stuff came in up under Ashley Gorakhpurwalla so it came in up under the server side, and then, so, ScaleIO is up under Jeff Boudreau, under Dan Embar, it's storage stack, it's in under the storage division. We work very very closely together. Second thing that's happening, there's a, one, we've been in the HCI world for a while, in the CI world for a while. We've quickly determined we can drive much better customer experience, much better customer outcomes, as we lean more towards an appliance or an engineered system versus a do-it-yourself kind of model. With ScaleIO, what we're trying to do is push it more into an appliance model, push it more into rack scale model, VxRack Flex. There's a outbound shift away from, kind of, what was ScaleIO as a software only and into more of an engineered system appliance offering, so with that shift, you'll see a rebrand from ScaleIO to VxFlex OS. It's just a rebrand of the software. >> So I'm glad Stu talked about organization, because you had to kind of reorg not too long ago, and so we had Ashley on yesterday, we talked to Jeff yesterday, as well. So from your perspective, now that you've had a few months to settle in, find your groove, how much of a difference do you think, as far as customer-facing, is this making in terms of responding to those kinds of needs and those desires. >> Sticking HCI with the server team has an awful lot of synergy. Obvious, compute-centric, scale, from a business scale perspective. So there's an awful lot of goodness in living in that same organization. Ashley's done it pretty well to make sure there's a lot of alignment, but we're also keeping a lot of the engineered system special sauce focus on the HCI side. So we're able to, one, better leverage a lot of the, what I would call, supply chain scale, the processes and go-to-market capabilities of an engine that is built around hundreds and thousands of units, right? That stretches across services, that stretches across factory and supply chain. Obviously, we want to drive HCI, we want to drive HCI in the mainstream and scale. Sitting right there in the server organization, they do scale, right? So lot of good learnings, lot of good synergy and leverage across teams. >> It's coming together for you. Nicely done. Thanks for joining us again, good to see you. You going to see each other next week, you said? >> That's right. >> We down in New Orleans, is that... yeah. >> Yeah. >> Alright, enjoy, and stay out of trouble, both of you. >> Absolutely, you know, one week in Vegas... >> Vegas one week, New Orleans the next, that's a recipe for an interesting time. >> Yes, that it is. >> Dan McConnell, thanks for being with us here on theCUBE. >> Thank you, thanks for having me. >> Back with more from Las Vegas right after this. You're watching theCUBE from Dell Technologies World 2018. (upbeat techno music)

>> Narrator: Live from Las Vegas, it's theCube. Covering Dell Technologies World 2018. Brought to you by Dell EMC, and it's ecosystem partners. (light music) >> Welcome back to Las Vegas, everybody, you're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with my co-host Keith Townsend. Craig Nunes is here, he's the CMO of Datrium. >> Yeah. >> Dave: Long time CUBE's alum, it's great to see you again. >> Great to be back, awesome. >> Dave: And James Stock is a Datrium customer, he's the Vice President of IT at Grow Financial. James, welcome, first time on theCUBE, looking good man. >> It is, yes, thank you very much. >> All right, Craig, Datrium-- >> Yeah. >> You guys are smoking hot, changing the storage world give us the quick update, we'll get into it. >> Look, we are filling a huge gap, bigger, I think, than we had imagined. Because, a lot of, it's no secret, the array market is in decline. And Hyper Converged has tried to reinvent that market. And it has to a degree on the low end, BDI, that kind of stuff. But data centers need an answer that scales. They need an answer that's got resilience. And it turns out, after all these years, back up is still a problem. Figuring out the cloud is still a problem. And so we put together a system that really takes a tier one approach to HCI, a full on scale out back up system and a cloud DR approach built into one convert system. And customers love it. From cloud to back up to performance in primaries, it's been awesome reception. >> Well, let's see if they really love it, I guess. So James, first of all, so let's start with Grow Financial, your role, you heard the pitch, and then we'll get into how it your applying it to new business. But, tell us about your company. >> So we started in 1955 in a broom closet in McDowell Air Force bases headquarters, there in Tampa. And over the years, we've grown. We're now a $2.4 billion in assets. We have over 200,000 members, and we do lending throughout the south eastern United States. Offices in Tampa, and in South Carolina. >> So in your role, head of IT-- >> Basically, what I tell people, is that if it plugs in, I'm responsible for it. >> (laughs) okay. All right, so, take us through the Datrium project of before and after, what was the motivation? >> So, really, the issue that we were running into is that our existing storage solution, which was the Dell SE, was our trays were running end of life, and if we only had a couple of them, it probably wouldn't have been a problem. We might not of even entertained it, but we had probably two dozen. So, we started looking around and said, "all right, "well, what does it cost to replace what we've got? "and what else is on the market?". And we started to find out that just replacing what we had with like, was going to cost almost 200 grand more than what our full Datrium replacement cost. So, it started making financial sense, right away. But, we met up with Datrium probably, might've been summer of 2016, when they were on version one. And it looked good, you could see the promise, the whole idea of having that back in storage, that was really intriguing, because none of the other players had anything like that at the time. And we said, "All right, we're not ready." And then when they came back out in May of last year, whoa, the difference in what they've done in such a short period of time is what really kind of blew us away. >> Okay, but, we're here at Dell Technologies World, where you guys are a partner of Dells, right? So you're using Dell servers and right? >> James: Yep. >> That's part of the deal here, so, they let you in. >> They let us in, in fact, our compute nodes, it's no secret, our Dell branded compute nodes, and in fact we have partnered with Dell in one of their data centers to set a world record IO mark on Dell here, just to prove a lot of the performance specs that we've shared in the market, proved it out. And we've proved it out on Dell here. >> Cool, so James, talk to me a little bit about your perception of Olby converge. Because I've talked to Craig about Olby convergence versus Hyper convergence versus Converge infrastructure, at the end of the day, you just want a reliable, fast system, however, what about the Olby convergence story drew you today? >> So, I didn't have to replace any of the nodes I had, if I really didn't have, if I wanted too. So I've got CISCO nodes around my call center, I've got Dell nodes, I've got Datrium nodes now. But at the time, it wouldn't have mattered. I could've just, like, in my CISCO environment, I actually had to add a raid controller to the UCS box and then I could throw any solid state drives that I wanted into the device. So that was where it really got compelling, and I'm like wait a minute, so you're telling me, I don't have to buy enterprise flash drives, and stick these into each of my servers. I could just go down to Best Buy, or wherever local, grab something off the shelf, and throw it in there, as long as the server supported it? And, okay, where do I sign up? >> So we've heard that story, and one of the things that some of the hyper converge infrastructure players say, you know what, we could do that, but it's almost impossible to support. Because of firmware issues, et cetera, et cetera. Did you guys run into any of those issues? >> Nope, that's been the greatest thing. When we first started to do our reference calls, it was like everybody I talked to, I said, well, where's the catch? >> Keith: Right. Because that really seemed too good to be true. And customer after customer that I called, they said, "we ran into it with our back ups." But they finished a third of the time faster. I said, "how is that even possible?" and, so we didn't believe it either. We actually had to go back and check because some of our backup jobs finished so fast, we thought it was an error or something like that. They were fine, it was just, you're backing up from flash now, instead of backing up from old spinning discs. >> Okay, so you put the system in, talk about the business impact. It sounds like there was some residual impacts from the initial motivation? >> Right, right, so from the business impact, that's a tough story to sell. Because, really, where we saw it, it was on the backend. And that was the way our systems were before, there really wasn't a huge deal of impact in the business with our old system, until it came back to back up times. Now, where I will say that we still have reductions is, if I have to reboot a server today, our call center application, buyers are putting it on Datrium, it took anywhere from 15 to 20 minutes for that to boot up. Well, 15 to 20 minutes while our call centers down, is like an eternity. Now, that time's down to about five to seven minutes. So, like overnight, you've more than halfed that time. And the same thing with web servers, or anything else that would be member facing, those times have been greatly reduced. So, if I do have to reboot something, because everybody knows it happens, it's sped up the process tremendously for us. >> And what's the secret sauce here? We're talking architecture, just sort of modern approach? Software design? >> So that the secret sauce, if you will, is this split design that runs your workloads. Especially read intensive workloads, on flash, on the host with powerful software, Datrium software. All of your durable data does not live on those hosts, those hosts are not stay full, they can fail at any time, and you still have data availability. So you've got that bullet proof availability, and on the back end, your data's kept secure, it is shared so we don't have any network traffic between hosts, your network doesn't blow up when you install, like it does with a hyper converged approach. And that split provisioning, that split architecture is the breakthrough, and that's why we talk about beyond HCI, we took a good step there. The scale line attributes, VIUM centric admin, but then we really built in tier one capabilities, full on backup, and of course, we haven't talked about it, but access to AWS re-offset backups. >> So, James, let's talk about day two operations. What are the advantages of hyper converged? There's this idea of like I'm one pane of glass. Like, firmware updates, I can free line my operations. Do you guys see similar advantages, day two, versus your previous infrastructures? >> Yeah, I mean, one of the things that saves us a lot of times now, is the fact that there's just one big pool of data out there, instead of having to provision lunds, we were setting up our exchange conversion, so we're building out four or five servers for that. Well, normally, that'd be about a two hour process, not that we were sitting there waiting the whole time, but, all right, we'll carve out some space in this one, twiddle your thumbs, go do something else. Come back, and maybe they'll be done. Well, now, that's like an instant process. So those sort of things are like, "wow, you know what, "I'm saving tons of time", just in admin experiences. In terms of pane of glass, it is a single pane of glass. One of the cool things that we've run into is every now and then, of course, we've got to do our disaster recovery testing, we're a financial institution. Well, Datrium's approach is really unique, and a problem that we used to have, is if I failed over to our DR facility, well, now I've got to bring that data back. Because if you fail in over, it's not a problem, you've already seated that data. Well, it doesn't work the other way around. It does with Datrium. So with Datrium, when I go to bring that data back, it's now doing a differential copy back, so I'm not sitting there for days and days and days, waiting to finish my DR testing anymore. So, there's just so many different benefits that have just been great for us. >> I mean, that's huge, because a lot of times, organizations, they can't test DR's, it's too risky, or they just don't have time, and even on the resources. >> James: Right. >> Did you have that problem beforehand? Or are you guys-- >> Well, yeah, because what you would run into is that it took so much to do it before, that I had to run my guys ragged for two or three weeks. I'm like, "All right, stay up overnight, make sure "it all copies" and then once it's copied, okay bring it back up. So, I mean, yeah, that was a challenge before that's not a problem anymore. >> Burning the team out, right. And or missing your window. >> Well, and because of the way that it's architected with the production groups, I no longer need to use a third party recovery tools to do the transitions back and forth. I can do that, natively, inside their application. >> I would also like to ask practitioners, if you had to mull it again, what would you do over. And it sounds like nothing, or what kind of advice would you give to your peers embarking on a similar journey? >> Do all of your reference calls. See it for yourself, I mean, I take quite a number of reference calls because people are in the same boat I was. Is it true, does it really work the way that you say it does? Yeah, it does. I'll screen share with them, if they want to see our numbers, I'll show them. >> All right, last word, what are we looking for? >> What are we looking for? >> Dave: Looking forward. >> So you're going to see us double down on the work we just went into market. Our DVX 4.0 software which comes with that cloud DVX, cloud based capability. And take that in to full on disaster recovery, orchestration. And not in the too distant future, you'll get the whole run down, so stay tuned. >> Awesome, Craig, thanks for coming on. James, pleasure meeting you. >> Likewise, thank you. >> Good luck with everything. Thanks for hanging out with me. >> Always. >> All right, Keith, good job, good questions. All right, keep it right there everybody, we will be back with our next guest, right after this short break. You're watching theCUBE live, from Dell Technologies World 2018. We'll be right back. (light music)

>> Announcer: Live from Las Vegas, it's theCUBE covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> And welcome back to theCUBE We continue our coverage here live. We are in the Sands at Dell Technologies World 2018. Big show, 14,000 plus they're expecting here. 4,000 just in the business partners summit alone. So a very impressive turnout here in day one, as I said, of three days of coverage on theCUBE. Along with Keith Townsend, I'm John Walls. We're now joined by Lee Caswell who's a VP of Products at VMWare. Lee, good to see you, sir. >> Great to be here, yes. >> John: Every year we get together like this, right? >> Well, you know, there's always something new to talk about, right? >> John: Absolutely, and we're also joined by Chris Stanley here, who's the IT Manager at the Celtic Manor Resorts in Newport, Wales. Chris, the first person from Wales I think I've ever met, as a matter of fact. >> Chris: (laughs) A privilege; thank you. >> For me it is, but thank you for being here. We appreciate the time. So we're talking about your migration, and, really, it wasn't a migration, it was like your head-first dive into the hyper-converged environment. You didn't tiptoe around it, you didn't wade into the water, You guys just dove right in. >> Chris: We're fearless, yes. >> What was the driver of that decision to be so fearless? >> Chris: As an organization, we've grown very quickly the last few years, and we've got significant growth in new hotels and a new conference center coming on board. And we're bursting at the seams in our existing environment, so we needed a platform that we could grow into this new environment very quickly and with predictive costs as best as we could. >> And so, Lee, walking them through this, >> Yeah, >> I mean, there's no convincing to be done here, but you do have to inspire some confidence, right? So somebody who's making a pretty bold move like this how did you approach that, and what did you do as far as assigning? >> Lee: You know, our partnership with Dell EMC is just a great testament here, right? I mean, you've taken the latest of 14G servers, for example, as part of VxRail. So you've got the best in hardware combined with VMWare underlying VCN software packaged up together, right, in a single point of support in a way that really makes us able to drop in and get started. Right, when you think about this, this is also interesting, in that here's a customer you know, in this case, you were using converged infrastructure in the past. >> It really is. Yeah. >> That's very common, right? So people who are looking for the advantage of like, how did I get the operational efficiencies? And now what you find is hyper-converge changes the operational model, and so it's around speed and agility, right? More than cost, right? And so, together, that's kind of the, our partnership is so powerful for customers looking to go and basically drive that kind of efficiency. >> Chris: Definitely, yeah. >> Keith: So, Chris, talk to us about that decision process. In typical organizations, this is Wired U, You're on theCUBE and it's so special. It's easy to talk about use cases on the edge VDI, specific, non-mission critical applications. But when it comes to stuff that runs the business, if it's down, the CIO, the CFO is at someone's desk asking when it's going to be back up. How did this discussion start? Was it from the bottom up, or was it from the top down? Exactly which teams said, "You know what? We need more agility, HCI, go!" >> Chris: Definitely from a bottom up perspective, but supported from top down when we came for it. We could see it in our environment, in our growing environment. We're a 24 hour business in a resort hotel, and we have little downtime Or, sorry, little time to do any upgrades, etc. So resilience within that environment was key to us for our uptime, so failing over with VMWare we use, with the VxWare we get now DRS and the Enterprise version which it comes with which we hadn't in our converged. So there is that automation of balancing your workloads, not having someone there watching it all the time so that has freed up a lot of time for my guys. Going forward there will be a lot more free time as well so we've got more time to concentrate on the guests and how we can make their experience better. >> So the story behind Converged systems, you know you have SAP, Oracle, BASSP, all these mission critical apps mission critical runs on CI and then everything else to run on, even from a vendor support, you know you talk to all the major software vendors, they say you all CI is the best opportunity. How did that conversation go with vendors when you said you know what, we're going to run mission critical on, I'm assuming vSAN? >> Lee: This is on vSAN in VxRail. >> vSAN, you know, we can't see your TR1 software providers and you know what, we're all vSAN, global size and scope, global? >> What, as an environment? >> Yes. >> It's a global environment really of over four hotels at the moment but growing into a bigger environment. We're going for an international conference center so kind of this sort of size, not quite as big as this but we're definitely not support from the hyper converged. And all our core systems are written on it, yes. Big Oracle databases, SQL, and our exchange service and there was a split between two clusters now in VxRail so we can, we can fail over to a node in VxRail, we can fail over to a cluster as well so as an SLE for up time we're business critical and the guys at the top of Celtic Manor have seen how that is for business you know. If we're not serving people or taking money then we're giving money back in a case for disruption. >> All right so you've been into this for a little bit less than a year now, correct? >> Correct, yes. >> I know Lee's sitting right next to you but let's just for a moment. I'm sure there has been at least a troubling moment of that transition or at least a hiccup somewhere that you had to settle, you had a problem, right? Something came up, if someone's watching this, thinking I wonder what they got hit with and how they handled it, how did you work around that, how did you adapt that, what would that be? What was the, maybe the one little hiccup right now that you've successfully- >> With deployment? >> Yeah. >> Nothing much but when we were migrating from a Converged infrastructure to a hyperconverged we added on the SANs to the hyperconverged so we could see them migrate over. A couple of servers didn't take too well to that one being motioned over. Nothing of the critical ones thankfully. But they, it was either a Windows update or once they restarted, it was only two of the servers but, we used the recover point then within VxRail and literally go back five, 10 minutes, which we did and up and running again, switched over, and we were you know, back up and running, but it was we had the decision there of, how long do we troubleshoot it for or do we just, that was our first instance of using recover point so we hadn't done it in a live environment so it was kind of, okay and pretty much out but it worked and it filled us with a lot of confidence now that we could do, we have that resilience going forward in an environment. >> Well let's talk about day two. >> I was just going to comment Ray, that this is part of the partnership that's so powerful for us right, is, you know I think VMWare learn that supporting storage systems, as we know, it's a little different than just computing. You know this, right, I mean, you know the idea of like, hey listen, a purple screen isn't the worst that can happen, 'cause you can reboot, right? It's really about, like, my data. And so when you start thinking about that, the ability for us to partner with Dell AMC who understands what it means to be supporting in a datacentric world, like that element, right is so powerful for us, right, because we've got a partner here who really understands the ability and that's part of the powerful concept of VxRail. >> So we had Tom Burns earlier and we were talking about VI and the importance of CI and there's still a great, I think, desire and temptation, and valid that CI gets you on the ground, running quickly, complex systems, easily deployed relative to traditional architectures. Talk to me about the practical of HCI, Day 2 Operations, CI, relatively easy to deploy but you still have some traditional operations concerns. What specifically did you guys see as the advantage Day two once you went to ACI? What's saving you all this time? >> Purely I think the time saver is the management of the system or the lack of management that we now need to do. There's, you've got one pane of glass to see everything which is very nice, you haven't got something separate for your SANs, your SX hosts, your networking and that support that you have, you know, there's one of them to call. You're not fighting between different entities saying it's your fault, it's your fault, there you go, sort it, so again that has freed up a lot of time, you know not knowing who to call or where to call but, you know, having one person who's going to sort it out and take ahold of that and fix it for you. And the remote support then, which is very good you know, you've got someone else monitoring your systems if you enable it, so you've got Dell support there and they can potentially see something before you do so I kind of gained another IT person for in this solution which is very nice. >> Yeah, we kind of joke you know, that a lot of people talk about hyperconvergence as if it's about us, but hyperconvergence is about you. When you think about it, right, it's about hyperconverging the IT staff. If you can hyperconverge the staff, right, that's when hyperconvergence does well, when we have one team, it's a converged team and people are like, hey listen, I'm going to go to a VMcentric management model. Now I can go and debug things right from a single console which is V center. That model works really fast, right? And where Converged still does a good job, right, is where I've got storage scaling at big scale but separate from compute separate. Hyperconvergence is about, it's about the organizational environment right? >> Very much so, bringing it all together, yeah. And it's simplistic in VMWare being so tightly integrated with VxRail was our main call against the other vendors, as a big call to, while they, you know, it's the best chef with the best ingredients, let's use that, not a dessert chef with the best ingredients >> Yeah, we have 500,000 customers who are familiar with V Center, right, and if you know V Center you know V SAN, you know VxRail, right? >> You can get simplistic again, so you already know it. >> Yeah, right. >> Well we could talk about this til we're blue in the face. I think we need to go see it in operation, don't you Keith? >> We'll set you up with some golf >> Now we're talking, be careful Chris, what you offer. Lee, Chris, good to see you guys. Thanks for being with us, we appreciate you sharing the story. Thank you very much. Back with more, here from Dell Technologies World we are live on theCUBE in Las Vegas.

>> We're back with Trey Layton, who's the senior vice president and CTO of Converged at Dell EMC. Trey, it's always a pleasure, good to see you. >> Dave, good to see you as well. >> We're at eight years into Vblock. Take us back to the converged infrastructure early days. What problems were you trying to solve with CI? >> Well, one of the problems with IT in general is it's been hard, and one of the reasons why it's been hard is all the variability that customers consume, and how do you integrate all that variability in a sustaining manner to maintain the assets so it can support the business? The thing that we've learned is, the original recipe that we had for Vblock was to go at and solve that very problem. We have referred to that as lifecycle. Manage the lifecycle services of the data center assets that you're deploying. We have created some great intellectual property, some great innovation around helping minimize the complexity associated with managing the lifecycle of a very complex integration by way of one of the largest data center assets that people operate in their environments. >> So, yeah, thousands and thousands of customers. They're telling you lifecycle management is critical, but what are they doing? They're shifting their labor resource to more strategic activities? Is that what's going on? >> Well, there's so much variation and complexity in just maintaining the different integration points that they're spending an inordinate amount of their time, a lot of nights and weekends, on understanding and figuring out which software combinations, which configuration combinations that need to operate. What we do as an organization and have done since inception is, we manage that complexity for them. We deliver them an outcome-based architecture that is pre-integrated, and we sustain that integration over its life, so they spend less time doing that and letting the experts who actually build the components focus on maintaining those integrations. >> As an analyst, I always looked at converged infrastructure as an evolutionary trend, bringing together storage servers, networking, bespoke components. My question is, where's the innovation underneath converged infrastructure? >> I would say innovation is in two areas. We're blessed with a lot of technology innovations that come from our partner and our own companies, Dell EMC and Cisco. Cisco produces wonderful innovations in the space of networking compute in the context of Vblock. Dell EMC, storage innovations, data protection, et cetera. We harmonize all of these very complex integration in a manner where an organization can put those advanced integrations into solving business problems immediately. There's two vectors of innovation. There are the technology components that we're acquiring to solve business problems, and there's the method in which we integrate them to get to the business of solving problems. >> Okay, let's get into the announcement. What are you announcing, what's new, why should we care? >> The announcement is, we are announcing the VxBlock 1000. The interesting thing about Vblocks over the years is they have been individual systems architectures. A compute technology integrated with a particular storage architecture would produce a model of Vblock. With VxBlock 1000, we're actually introducing an architecture that provides a full gamut of array optionality for customers. Both blade and rack server options for customers on the UCS compute side, and before, we would integrate data protection technologies as an extension or an add-on into the architecture. Data protection is native to the offer. In addition to that, unstructured data storage. So, being able to include unstructured data into the architecture as one singular architecture, as opposed to buying individualized systems. >> Okay, so you're just further simplifying the underlying infrastructure, which is going to save me even more time, is that right? >> Producing a standard which can adapt to virtually any use case that a customer has in a data center environment, giving them the ability to expand and grow that architecture as their workload dictates in their environment, as opposed to buying a system to accommodate one workload, buying another system to accommodate another workload. This is breaking the barriers of traditional CI and moving it forward so that we can create an adaptive architecture that can accommodate not only the technologies available today, but the technologies on the horizon tomorrow. >> Okay, so it's workload diversity, which means greater asset leverage from that underlying infrastructure. >> Trey: Absolutely. >> Can you give us some examples? How do you envision customers using this? >> I would talk specifically about customers that we have today, and when they deploy, have deployed Vblocks in the past. We've done wonderful by building architectures that accommodate, or they're tailor-made for certain types of workloads. A customer environment would end up acquiring a Vblock model 700 to accommodate an SAP workload, for example. They would acquire a Vblock 300 or 500 to accommodate a VI workload. And then, as those workloads would grow, they would grow those individualized systems. What it did was, it created islands of stranded resource and capacity. Vblock 1000 is about bringing all those capabilities into a singular architecture where you can grow the resources based on pools. As your workload shifts in your environment, you can reallocate resources to accommodate the needs of that workload, as opposed to worrying about stranded capacity in the architecture. >> Where do you go from here with the architecture? Can you share with us, to the extent that you can, a little roadmap? Give us a vision as to how you see this playing out over the next several years. >> Well, one of the reasons why we did this was to simplify and make it easier to operate these very complex architectures that everyone's consuming around the world. Vblock has always been about simplifying complex technologies in the data center. There are a lot of innovations on the horizon. NVMe, for example. Next-generation compute platforms. There are new-generation fabric services that are merging. VxBlock 1000 is the place at which you will see all of these technologies introduce, and our customers won't have to wait on new models of Vblock to consume those technologies. They will be resident in them upon their availability to the market. >> The buzzword from the vendor community is "Futureproof," but you're saying you'll be able to, if you buy today, you'll be able to bring in things like NVMe and these new technologies down the road? >> The architecture inherently supports the idea of adapting to new technologies as they emerge, and will consume those integrations as a part of the architectural standard footprint for the life of the architecture. >> All right, excellent. Trey, thanks very much for that overview. Cisco, obviously, a huge partner of yours, with this whole initiative, many, many years. A lot of people have questioned where that goes, so we have a segment from Cisco Live. Stu Miniman's out there. Let's break to Stu, and then we'll come back and pick it up from there. Thanks for watching.

>> Hi I'm Peter Burris, welcome to Action Item. (electronic music) There's an enormous net new array of software technologies that are available to businesses and enterprises to tend to some new classes of problems and that means that there's an explosion in the number of problems that people perceive as could be applied, or could be solved, with software approaches. The whole world of how we're going to automate things differently in artificial intelligence and any number of other software technologies, are all being brought to bear on problems in ways that we never envisioned or never thought possible. That leads ultimately to a comparable explosion in the number of approaches to how we're going to solve some of these problems. That means new tooling, new models, new any number of other structures, conventions, and artifacts that are going to have to be factored by IT organizations and professionals in the technology industry as they conceive and put forward plans and approaches to solving some of these problems. Now, George that leads to a question. Are we going to see an ongoing ever-expanding array of approaches or are we going to see some new kind of steady-state that kind of starts to simplify what happens, or how enterprises conceive of the role of software and solving problems. >> Well, we've had... probably four decades of packaged applications being installed and defining really the systems of record, which first handled the ordered cash process and then layered around that. Once we had more CRM capabilities we had the sort of the opportunity to lead capability added in there. But systems of record fundamentally are backward looking, they're tracking about the performance of the business. The opportunity-- >> Peter: Recording what has happened? >> Yes, recording what has happened. The opportunity we have is now to combine what the big Internet companies pioneered, with systems of engagement. Where you had machine learning anticipating and influencing interactions. You can now combine those sorts of analytics with systems of record to inform and automate decisions in the form of transactions. And the question is now, how are we going to do this? Is there some way to simplify or, not completely standardized, but can we make it so that we have at least some conventions and design patterns for how to do that? >> And David, we've been working on this problem for quite some time but the notion of convergence has been extent in the hardware and the services, or in the systems business for quite some time. Take us through what convergence means and how it is going to set up new ways of thinking about software. >> So there's a hardware convergence and it's useful to define a few terms. There's converged systems, those are systems which have some management software that have been brought into it and then on top of that they have traditional SANs and networks. There's hyper-converged systems, which started off in the cloud systems and now have come to enterprise as well. And those bring software networking, software storage, software-- >> Software defined, so it's a virtualizing of those converged systems. >> David: Absolutely, and in the future is going to bring also automated operational stuff as well, AI in the operational side. And then there's full stack conversions. Where we start to put in the software, the application software, to begin with the database side of things and then the application itself on top of the database. And finally these, what you are talking about, the systems of intelligence. Where we can combine both the systems of record, the systems of engagement, and the real-time analytics as a complete stack. >> Peter: Let's talk about this for a second because ultimately what I think you're saying is, that we've got hardware convergence in the form of converged infrastructure, hyper-converged in the forms of virtualization of that, new ways of thinking about how the stack comes together, and new ways of thinking about application components. But what seems to be the common thread, through all of this, is data. >> David: Yes. >> So it's basically what we're seeing is a convergence or a rethinking of how software elements revolve around the data, is that kind of the centerpiece of this? >> David: That's the centerpiece of it and we had very serious constraints about accessing data. Those will improve with flash but there's still a lot of room for improvement. And the architecture that we are saying is going to come forward, which really helps this a lot, is the unit grid architecture. Where we offload the networking and the storage from the processor. This is already happening in the hyper scale clouds, they're putting a lot of effort into doing this. But we're at the same time allowing any processor to access any data in a much more fluid way and we can grow that to thousands of processes. Now that type of architecture gives us the ability to converge the traditional systems of record, and there are a lot of them obviously, and the systems of engagement and the the real-time analytics for the first time. >> But the focal point of that convergence is not the licensing of the software, the focal point is convergence around the data. >> The data. >> But that has some pretty significant implications when we think about how software has always been sold, how organizations to run software have been structured, the way that funding is set up within businesses. So George, what does it mean to talk about converging software around data from a practical standpoint over the next few years? >> Okay, so let me take that and interpret that as converging the software around data in the context of adding intelligence to our existing application portfolio and then the new applications that follow on. And basically, when we want to inject an intelligence enough to inform and anticipate and inform interactions or inform or automate transactions, we have a bunch of steps that need to get done. Where we're ingesting essentially contextual or ambient information. Often this is information about a user or the business process. And this data, it's got to go through a pipeline where there's both a Design Time and a Run Time. In addition to ingesting it, you have to sort of enrich it and make it ready for analysis. Then the analysis has essentially picking out of all that data and calculating the features that you plug into a machine learning model. And then that, produces essentially an inference based on all that data, that says well this is the probable value and it sounds like, sounds like it's in the weeds but the point is it's actually a standardized set of steps. Then the question is, do you put that all together in one product across that whole pipeline? Can one piece of infrastructure software manage that ? Or do you have a bunch of pieces each handing off to the next? And-- >> Peter: But let me stop you so because I want to make sure that we kind of follow this thread. So we've argued that hardware convergence and the ability to scale the role the data plays or how data is used, is happening and that opens up new opportunities to think about data. Now what we've got is we are centering a lot of the software convergence around the use of data through copies and other types of mechanisms for handling snapshots and whatnot and things like uni grid. What you're, let's start with this. It sounds like what you're saying is we need to think of new classes of investments in technologies that are specifically set up to handling the processing of data in a more distributed application way, right? If I got that right, that's kind of what we mean by pipelines? >> George: Yes. >> Okay, so once we do that, once we establish those conventions, once we establish organizationally institutionally how that's going to work. Now we take the next step of saying, are we going to default to a single set of products or are we going to do best to breed and what kind of convergence are we going to see there? >> And there's no-- >> First of all, have I got that right? >> Yes, but there's no right answer. And I think there's a bunch of variables that we have to play with that depend on who the customer is. For instance, the very largest and most sophisticated tech companies are more comfortable taking multiple pieces each that's very specialized and putting them together in a pipeline. >> Facebook, Yahoo, Google-- >> George: LinkedIn. >> Got it. >> George: Those guys. And the knobs that they're playing with, that everyone's playing with, are three, basically on the software side. There's your latency budget, which is how much time do you have to produce an answer. So that drives the transaction or the interaction. And it's not, that itself is not just a single answer because... It's not, the goal isn't to get it as short as possible. The goal is to get as much information into the analysis within the budgeted latency. >> Peter: So it's packing the latency budget with data? >> George: Yes, because the more data that goes into making the inference, the better the inference. >> Got it. >> The example that someone used actually on Fareed Zakaria GPS, one show about it was, if he had 300 attributes describing a person he could know more about that person then that person did (laughs) in terms of inferring other attributes. So the the point is, once you've got your latency budget, the other two knobs that you can play with are development complexity and admin complexity. And the idea is on development complexity, there's a bunch of abstractions that you have to deal with. If it's all one product you're going to have one data model, one address and namespace convention, one programming model, one way of persisting data, a whole bunch of things. That's simplicity. And that makes it more accessible to mainstream organizations. Similarly there's a bunch of, let me just add that, there's probably two or three times as many constructs that admins would have to deal with. So again, if you're dealing with one product, it's a huge burden off the admin and we know they struggled with Hadoop. >> So convergence, decisions about how to enact convergence is going to be partly or strongly influenced by those three issues. Latency budget, development complexity or simplicity, and administrative, David-- >> I'd like to add one more to that, and that is location of data. Because you want to be able to, you want to be able to look at the data that is most relevant to solving that particular problem. Now, today a lot of the data is inside the enterprise. There's a lot of data outside that but they're still, you will want to, in the best possible way, combine that data one way or another. >> But isn't that a variable on the latency budget? >> David: Well there's, I would think it's very useful to split the latency budget, which is to do with inference mainly, and development with the machine learning. So there is a development cycle with machine learning that is much longer. That is days, could be weeks, could be months. >> I would still done in Bash. >> It is or will be done, wait a second. It will be done in Bash, it is done in Bash, and it's. You need to test it and then deliver it as an inference engine to the applications that you're talking about. Now that's going to be very close together, that inference, then the rest of it has to be all physically very close together. But the data itself is spread out and you want to have mechanisms that can combine those datas, move application to those datas, bring those together in the best possible way. That is still a Bash process. That can run where the data is, in the cloud locally, wherever it is. >> George: And I think you brought up a great point, which I would tend to include in latency budget because... no matter what kind of answers you're looking for, some of the attributes are going to be pre computed and those could be-- >> David: Absolutely. >> External data. >> David: Yes. >> And you're not going to calculate everything in real time, there's just-- >> You can't. >> Yes you can't. >> But is the practical reality that the convergence of, so again, the argument. We've got all these new problems, all new kinds of new people that are claiming that they know how to solve the problems, each of them choosing different classes of tools to solve the problem, an explosion across the board in the approaches, which can lead to enormous downstream integration and complexity costs. You've used the example of Cloudera, for example. Some of the distro companies who claim that 50 plus percent of their development budget is dedicated to just integrating these pieces. That's a non-starter for a lot of enterprises. Are we fundamentally saying that the degree of complexity or the degree of simplicity and convergence, it's possible in software, is tied to the degree of convergence in the data? >> You're honing in on something really important, give me-- >> Peter: Thank you! (laughs) >> George: Give an example of the convergence of data that you're talking about. >> Peter: I'll let David do it because I think he's going to jump on it. >> David: Yes so let me take examples, for example. If you have a small business, there's no way that you want to invest yourself in any of the normal levels of machine learning and applications like that. You want to outsource that. So big software companies are going to do that for you and they're going to do it especially for the specific business processes which are unique to them, which give them digital differentiation of some sort or another. So for all of those type of things, software will come in from vendors, from SAP or son of SAP, which will help you solve those problems. And having data brokers which are collecting the data, putting them together, helping you with that. That seems to me the way things are going. In the same way that there's a lot of inference engines which will be out at the IOT level. Those will have very rapid analytics given to them. Again, not by yourself but by companies that specialize in facial recognition or specialize in making warehouse-- >> Wait a minute, are you saying that my customers aren't special, that require special facial recognition? (laughs) So I agree with David but I want to come back to this notion because-- >> David: The point I was getting at is, there's going to be lots and lots of room for software to be developed, to help in specific cases. >> Peter: And large markets to sell that software into. >> Very large markets. >> Whether it's a software, but increasingly also with services. But I want to come back to this notion of convergence because we talked about hardware convergence and we're starting to talk about the practical limits on software convergence. But somewhere in between I would argue, and I think you guys would agree, that really the catalyst for, or the thing that's going to determine the rate of change and the degree of convergence is going to be how we deal with data. Now you've done a lot of research on this, I'm going to put something out there and you tell me if I'm wrong. But at the end of the day, when we start thinking about uni grid, when we start thinking about some of these new technologies, and the ability to have single copies or single sources of data, multiple copies, in many respects what we're talking about is the virtualization of data without loss. >> David: Yes. >> Not loss of the characters, the fidelity of the data, or the state of the data. I got that right? >> Knowing the state of the data. >> Peter: Or knowing state of the data. >> If you take a snapshot, that's a point in time, you know what that point of time is, and you can do a lot of analytics for example on, and you want to do them on a certain time of day or whatever-- >> Peter: So is it wrong to say that we're seeing, we've moved through the virtualization of hardware and we're now in a hyper scale or hyper-converged, which is very powerful stuff. We're seeing this explosion in the amount of software that's being you know, the way we approach problems and whatnot. But that a forcing function, something that's going to both constrain how converged that can be, but also force or catalyze some convergence, is the idea that we're moving into an era where we can start to think about virtualized data through some of these distributed file systems-- >> David: That's right, and the metadata that goes with it. The most important thing about the data is, and it's increasing much more rapidly than data itself, is the metadata around it. But I want to just, make one point on this, all data isn't useful. There's a huge amount of data that we capture that we're just going to have to throw away. The idea that we can look at every piece of data for every decision is patently false. There's a lovely example of this in... fluid mechanics. >> Peter: Fluid dynamics. >> David: Fluid dynamics, if you're trying to, if you're trying to have simulation at a very very low level, the amount of-- >> Peter: High fidelity. >> High fidelity, you run out of capacity very very very quickly indeed. So you have to make trade-offs about everything and all of that data that you're doing in that simulation, you're not going to keep that. All the data from IOT, you can't keep that. >> Peter: And that's not just a statement about the performance or the power or the capabilities of the hardware, there's some physical realities-- >> David: Absolutely, yes. >> That are going to limit what you can do with the simulation. But, and we've talked. We've talked about this in other action items, There is this notion of options on data value, where the value of today's data is maybe-- >> David: Is much higher. >> Peter: Well it's higher from at a time standpoint for the problems that we understand and are trying to solve now but there may be future problems where we still want to ensure that we have some degree of data where we can be better at attending those future problems. But I want to come back to this point because in all honesty, I haven't heard anybody else talking about this and maybe's because I'm not listening. But this notion of again, your research that the notion of virtualized data inside these new architectures being a catalyst for a simplification of a lot of the sharing subsystem. >> David: It's essentially sharing of data. So instead of having the traditional way of doing it within a data center, which is I have my systems of record, I make a copy, it gets delivered to the data warehouse, for example. That's the way that's being done. That is too slow, moving data is incredibly slow. So another way of doing it is to share that data, make a virtual copy of it, and technologies allowing you to do that because the access density has gone up by thousands of times-- >> Peter: Because? >> Because. (laughs) Because of flash, because of new technologies at that level, >> Peter: High performance interfaces, high performance networks. >> David: All of that stuff is now allowing things, which just couldn't be even conceived. However, there is still a constraint there. It may be a thousand times bigger but there is still an absolute constraint to the amount of data that you can actually process. >> And that constraint is provided by latency. >> Latency. >> Peter: Speed of light. >> Speed of light and speed of the processes themselves. >> George: Let me add something that may help explain the sort of the virtualization of data and how it ties into the convergence or non convergence of the software around it. Which is, when we're building these analytic pipelines, essentially we've disassembled what used to be a DBMS. And so out of that we've got a storage engine, we've got query optimizers, we've got data manipulation languages which have grown into full-blown analytic languages, data definition language. Now the system catalog used to be just, a way to virtualize all the tables in the database and tell you where all the stuff was, and the indexes and things like that. Now, what we're seeing is since data is now spread out over so many places and products, we're seeing an emergence of a new of catalog. Whether that's from Elation or Dremio or on AWS, it's the Glue catalog, and I think there's something equivalent coming on Asure. But the point is, we're beginning, those are beginning to get useful enough to be the entry point for analytic products and maybe eventually even for transactional products to update, or at least to analyze the data in these pipelines that we're putting together out of these components of what was a disassembled database. Now, we could be-- >> I would make a difference there there between the development of analytics and again, the real-time use of those analytics within systems of intelligence. >> George: Yeah but when you're using them-- >> David: There's a different, problems they have to solve. >> George: But there's a Design Time and a Run Time, there's actually four pipelines for the sort of analytic pipeline itself. There's Design Time and Run Time, and then for the inference engine and the modeling that goes behind it, there's also a Design Time and Run Time. But I guess where. I'm not disagreeing that you could have one converged product to manage the Run Time analytic pipeline. I'm just saying that the pieces that you assemble could come from one vendor. >> Yeah but I think David's point, I think it's accurate and this has been since the beginning of time. (laughs) Certainly predated UNIVAC. That at the end of the day, read/write ratios and the characteristics of the data are going to have an enormous impact on the choices that you make. And high write to read ratios almost dictate the degree of convergence, and we used to call that SMP, or you know scale-up database managers. And for those types of applications, with those types of workloads, it's not necessarily obvious that that's going to change. Now we can still find ways to relax that but you're talking about, George, the new characteristics >> Injecting the analytics. >> Injecting the analytics where we're doing more reading as opposed to writing. We may still be writing into an application that has these characteristics-- >> That's a small amount of data. >> But a significant portion of the new function is associated with these new pipelines. >> Right. And it's actually... what data you create is generally derived data. So you're not stepping on something that's already there. >> All right, so let me get some action items here. David, I want to start with you. What's the action item? >> David: So for me, about conversions, there's two levels of conversions. First of all, converge as much as possible and give the work to the vendor, would be my action item. The more that you can go full stack, the more that you can get the software services from a single point, single throat to choke, single hand to shake, the more you have out source your problems to them. >> Peter: And that has a speed implication, time to value. >> Time to value, it has a, you don't have to do undifferentiated work. So that's the first level of convergence and then the second level of convergence is to look hard about how you can bring additional value to your existing systems of record by putting in automation or a real-time analytics. Which leads to automation, that is the second one, for me, where the money is. Automation, reduction in the number of things that people have to do. >> Peter: George, action item. >> So my action item is that you have to evaluate, you the customer have to evaluate sort of your skills as much as your existing application portfolio. And if more of your greenfield apps can start in the cloud and you're not religious about open source but you're more religious about the admin burden and development burden and your latency budget, then start focusing on the services that the cloud vendors originally created that were standalone, but they are increasingly integrating because the customers are leading them there. And then for those customers who you know, have decades and decades of infrastructure and applications on Prem and need a pathway to the cloud, some of the vendors formerly known as Hadoop vendors. But for that matter, any on Prem software vendor is providing customers a way to run workloads in a hybrid environment or to migrate data across platforms. >> All right, so let me give this a final action item here. Thank you David Foyer, George Gilbert. Neil Raiden and Jim Kobielus and the rest of the Wikibon team is with customers today. We talked today about convergence at the software level. What we've observed over the course of the last few years is an expanding array of software technologies, specifically AI, big data, machine learning, etc. That are allowing enterprises to think differently about the types of problems that they can solve with technology. That's leading to an explosion and a number of problems that folks are looking at, the number of individuals participating in making those decisions and thinking those issues through. And very importantly, an explosion of the number of vendors with piecemeal solutions about what they regard, their best approach to doing things. However, that is going to have a significant burden that could have enormous implications for years and so the question is, will we see a degree of convergence in the approach to doing software, in the form of pipelines and applications and whatnot, driven by a combination of: what the hardware is capable of doing, what the skills are or make possible, and very importantly, the natural attributes of the data. And we think that there will be. There will always be tension in the model if you try to invent new software but one of the factors that's going to bring it all back to a degree of simplicity, will be a combination of what the hardware can do, what people can do, and what the data can do. And so we believe, pretty strongly, that ultimately the issues surrounding data whether it be latency or location, as well as the development complexity and administrative complexity, are going to be a range of factors that are going to dictate ultimately of how some of these solutions start to converge and simplify within enterprises. As we look forward, our expectation is that we're going to see an enormous net new investment over the next few years in pipelines, because pipelines are a first-level set of investments on how we're going to handle data within the enterprise. And they'll look like, in certain respects, how DBMS used to look but just in a disaggregated way but conceptually and administratively and then from a product selection and service election standpoint, the expectation is that they themselves have to come together so the developers can have a consistent view of the data that's going to run inside the enterprise. Want to thank David Floyer, want to thank George Gilbert. Once again, this has been Wikibon Action Item and we look forward to seeing you on our next Action Item. (electronic music)

>> Announcer: From the SiliconANGLE Media Office, in Boston, Massachusetts, it's The Cube. Now, here's your host, Dave Vellante. >> Hello everyone welcome to this special presentation, The Future of Converged Infrastructure, my name is David Vellante, and I'll be your host, for this event where the focus is on Dell EMC's converged infrastructure announcement. Nearly a decade ago, modern converged infrastructure really came to the floor in the marketplace, and what you had is compute, storage, and network brought together in a single managed entity. And when you talk to IT people, the impact was roughly a 30 to 50% total cost of ownership reduction, really depending on a number of factors. How much virtualization they had achieved, how complex their existing processees were, how much they could save on database and other software licenses and maintenance, but roughly that 30 to 50% range. Fast forward to 2018 and you're looking at a multibillion dollar market for converged infrastructure. Jeff Boudreau is here, he's the President of the Dell EMC Storage Division, Jeff thanks for coming on. >> Thank you for having me. >> You're welcome. So we're going to set up this announcement let me go through the agenda. Jeff and I are going to give an overview of the announcement and then we're going to go to Trey Layton, who's the Chief Technology Officer of the converged infrastructure group at Dell EMC. He's going to focus on the architecture, and some of the announcement details. And then, we're going to go to Cisco Live to a pre-recorded session that we did in Barcelona, and get the Cisco perspective, and then Jeff and I will come back to wrap it up. We also, you might notice we have a crowd chat going on, so underneath this video stream you can ask questions, you got to log in with LinkedIn, Twitter, or Facebook, I prefer Twitter, kind of an ask me anything crowd chat. We have analysts on, Stu Miniman is hosting that call. We're going to talk about what this announcement is all about, what the customer issues are that are being addressed by this announcement. So Jeff, let's get into it. From your perspective, what's the state of converged infrastructure today? >> Great question. I'm really bullish on CI, in regards to what converged infrastructure and kind of the way the market's going. We see continued interest in the growth of the market of our customers. Driven by the need for simplicity, agility, elasticity of those on-prem resources. Dell EMC pioneered the CI market several years ago, with the simple premise of simplify IT, and our focus and commitment to our customers has not changed of simplifying IT. As our customers continue to seek for new ways to simplify and consolidate infrastructure, we expect more and more of our customers to embrace CI, as a fast and easy way to modernize their infrastructure, and transform IT. >> You talk about transformation, we do a lot of events, and everybody's talking about digital transformation, and IT transformation, what role does converged infrastructure play in those types of transformations, maybe you could give us an example? >> Sure, so first I'd say our results speak for themselves. As I said we pioneered the CI industry, as the market leader, we enabled thousands of customers worldwide to drive business transformation and digital transformation. And when I speak to customers specifically, converged infrastructure is not just about the infrastructure, it's about the operating model, and how they simplify IT. I'd say two of the biggest areas of impact that customers highlight to me, are really about the acceleration of application delivery, and then the other big one is around the increase in operational efficiencies allowing customers to free up resources, to reinvest however they see fit. >> Now since the early days of converged infrastructure Cisco has been a big partner of yours, you guys were kind of quasi-exclusive for awhile, they went out and sought other partners, you went out and sought other partners, a lot of people have questions about that relationship, what's your perspective on that relationship. >> So our partnership with Cisco is strong as ever. We're proud of this category we've created together. We've been on this journey for a long time we've been working together, and that partnership will continue as we go forward. In full transparency there are of course some topics where we disagree, just like any normal relationship we have disagreements, an example of that would be HCI, but in the CI space our partnership is as strong as ever. We'll have thousands of customers between the two of us, that we will continue to invest and innovate together on. And I think later in this broadcast you're going to hear directly from Cisco on that, so we're both doubling down on the partnership, and we're both committed to CI. >> I want to ask you about leadership generally, and then specifically as it relates to converged infrastructure and hyper converged. My question is this, hyper converged is booming, it's a high growth market. I sometimes joke that Dell EMC is now your leader in the Gartner Magic Quadrants, 101 Gartner Magic Quadrants out of the 99. They're just leading everything and I think both the CI and the HCI categories, what's your take, is CI still relevant? >> First I'd say it's great to come from a leadership position so I thank you for bringing that up, I think it's really important. As Micheal talks about being the essential infrastructure company, that's huge for us as Dell Technologies, so we're really proud of that and we want to lean into that strength. Now on HCI vs CI, to me it's an AND world. Everybody wants to get stock that's in either or, to me it's about the AND story. All our customers are going on a journey, in regards to how they transform their businesses. But at the end of the day, if I took my macro view, and took a step back, it's about the data. The data's the critical asset. The good news for me and for our team is data always continues to grow, and is growing at an amazing rate. And as that critical asset, customers are really kind of thinking about a modern data strategy as they drive foreword. And as part of that, they're looking at how to store, protect, secure, analyze, move that data, really unleashing that data to provide value back to their businesses. So with all of that, not all data is going to be created equal, as part of that, as they build out those strategies, it's going to be a journey, in regards to how they do it. And if that's software defined, vs purpose built arrays, vs converged, or hyper converged, or even cloud, those deployment models, we, Dell EMC, and Dell Technologies want to be that strategic partner, that trusted advisor to help them on that journey. >> Alright Jeff, thanks for helping me with the setup. I want to ask you to hang around a little bit. >> Jeff: Sure. >> We're going to go to a video, and then we're going to bring back Trey Layton, talk about the architecture so keep it right there, we'll be right back. >> Announcer: Dell EMC has long been number one in converged infrastructure, providing technology that simplifies all aspects of IT, and enables you to achieve better business outcomes, faster, and we continue to lead through constant innovation. Introducing, the VxBlock System 1000, the next generation of converged infrastructure from Dell EMC. Featuring enhanced life cycle management, and a broad choice of technologies, to support a vast array of applications and resources. From general purpose to mission critical, big data to specialized workloads, VxBlock 1000 is the industry's first converged infrastructure system, with the flexible data services, power, and capacity to handle all data center workloads, giving you the ultimate in business agility, data center efficiency, and operational simplicity. Including best-of-breed storage and data protection from Dell EMC, and computer networking from Cisco. (orchestral music) Converged in one system, these technologies enable you to flexibly adapt resources to your evolving application's needs, pool resources to maximize utilization and increase ROI, deliver a turnkey system in lifecycle assurance experience, that frees you to focus on innovation. Four times storage types, two times compute types, and six times faster updates, and VME ready, and future proof for extreme performance. VxBlock 1000, the number one in converged now all-in-one system. Learn more about Dell EMC VxBlock 1000, at DellEMC.com/VxBlock. >> We're back with Trey Layton who's the Senior Vice President and CTO of converged at Dell EMC. Trey it's always a pleasure, good to see you. >> Dave, good to see you as well. >> So we're eight years into Vblock, take us back to the converged infrastructure early days, what problems were you trying to solve with CI. >> Well one of the problems with IT in general is it's been hard, and one of the reasons why it's been hard is all the variability that customers consume. And how do you integrate all that variability in a sustaining manner, to maintain the assets so it can support the business. And, the thing that we've learned is, the original recipe that we had for Vblock, was to go at and solve that very problem. We have referred to that as life cycle. Manage the life cycle services of the biggest inner assets that you're deploying. And we have created some great intellectual property, some great innovation around helping minimize the complexity associated with managing the life cycle of a very complex integration, by way of, one of the largest data center assets that people operate in their environment. >> So you got thousands and thousands of customers telling you life cycle management is critical. They're shifting their labor resource to more strategic activities, is that what's going on? Well there's so much variation and complexity in just maintaining the different integration points, that they're spending an inordinate amount of their time, a lot of nights and weekends, on understanding and figuring out which software combinations, which configuration combinations you need to operate. What we do as an organization, and have done since inception is, we manage that complexity for them. We delivery them an outcome based architecture that is pre-integrated, and we sustain that integration over it's life, so they spend less time doing that, and letting the experts who actually build the components focus on maintaining those integrations. >> So as an analyst I always looked at converged infrastructure as an evolutionary trend, bringing together storage, servers, networking, bespoke components. So my question is, where's the innovation underneath converged infrastructure. >> So I would say the innovation is in two areas. We're blessed with a lot of technology innovations that come from our partner, and our own companies, Dell EMC and Cisco. Cisco produces wonderful innovations in the space of networking compute, in the context of Vblock. Dell EMC, storage innovations, data protection, et cetera. We harmonize all of these very complex integrations in a manner where an organization can put those advanced integrations into solving business problems immediately. So there's two vectors of innovation. There are the technology components that we are acquiring, to solve business problems, and there's the method at which we integrate them, to get to the business of solving problems. >> Okay, let's get into the announcement. What are you announcing, what's new, why should we care. >> We are announcing the VxBlock 1000, and the interesting thing about Vblocks over the years, is they have been individual system architectures. So a compute technology, integrated with a particular storage architecture, would produce a model of Vblock. With VxBlock 1000, we're actually introducing an architecture that provides a full gamut of array optionality for customers. Both blade and rack server options, for customers on the UCS compute side, and before we would integrate data protection technologies as an extension or an add-on into the architecture, data protection is native to the offer. In addition to that, unstructured data storage. So being able to include unstructured data into the architecture as one singular architecture, as opposed to buying individualized systems. >> Okay, so you're just further simplifying the underlying infrastructure which is going to save me even more time? >> Producing a standard which can adapt to virtually any use case that a customer has in a data center environment. Giving them the ability to expand and grow that architecture, as their workload dictates, in their environment, as opposed to buying a system to accommodate one workload, buying another system to accommodate another workload, this is kind of breaking the barriers of traditional CI, and moving it foreword so that we can create an adaptive architecture, that can accommodate not only the technologies available today, but the technologies on the horizon tomorrow. >> Okay so it's workload diversity, which means greater asset leverage from that underlying infrastructure. >> Trey: Absolutely. >> Can you give us some examples, how do you envision customers using this? >> So I would talk specifically about customers that we have today. And when they deploy, or have deployed Vblocks in the past. We've done wonderful by building architectures that accommodate, or they're tailor made for certain types of workloads. And so a customer environment would end up acquiring a Vblock model 700, to accommodate an SAP workload for example. They would acquire a Vblock 300, or 500 to accommodate a VDI workload. And then as those workloads would grow, they would grow those individualized systems. What it did was, it created islands of stranded resource capacities. Vblock 1000 is about bringing all those capabilities into a singular architecture, where you can grow the resources based on pools. And so as your work load shifts in your environment, you can reallocate resources to accommodate the needs of that workload, as opposed to worrying about stranded capacity in the architecture. >> Okay where do you go from here with the architecture, can you share with us, to the extent that you can, a little roadmap, give us a vision as to how you see this playing out over the next several years. >> Well, one of the reasons why we did this was to simplify, and make it easier to operate, these very complex architectures that everyone's consuming around the world. Vblock has always been about simplifying complex technologies in the data center. There are a lot of innovations on the horizon in VME, for example, next generation compute platforms. There are new generation fabric services, that are emerging. VxBlock 1000 is the place at which you will see all of these technologies introduced, and our customers won't have to wait on new models of Vblock to consume those technologies, they will be resident in them upon their availability to the market. >> The buzz word from the vendor community is future proof, but your saying, you'll be able to, if you buy today, you'll be able to bring in things like NVME and these new technologies down the road. >> The architecture inherently supports the idea of adapting to new technologies as they emerge, and will consume those integrations, as a part of the architectural standard footprint, for the life of the architecture. >> Alright excellent Trey, thanks very much for that overview. Cisco obviously a huge partner of yours, with this whole initiative, many many years. A lot of people have questioned where that goes, so we have a segment from Cisco Live, Stu Miniman is out there, let's break to Stu, then we'll come back and pick it up from there. Thanks for watching. >> Thanks Dave, I'm Stu Miniman, and we're here at Cisco Live 2018 in Barcelona, Spain. Happy to be joined on the program by Nigel Moulton the EMEA CTO of Dell EMC, and Siva Sivakumar, who's the Senior Director of Data Center Solutions at Cisco, gentlemen, thanks so much for joining me. >> Thanks Stu. >> Looking at the long partnership of Dell and Cisco, Siva, talk about the partnership first. >> Absolutely. If you look back in time, when we launched UCS, the very first major partnership we brought, and the converged infrastructure we brought to the market was Vblock, it really set the trend for how customers should consume compute, network, and storage together. And we continue to deliver world class technologies on both sides and the partnership continues to thrive as we see tremendous adoption from our customers. So we are here, several years down, still a very vibrant partnership in trying to get the best product for the customers. >> Nigel would love to get your perspective. >> Siva's right I think I'd add, it defined a market, if you think what true conversion infrastructure is, it's different, and we're going to discuss some more about that as we go through. The UCS fabric is unique, in the way that it ties a network fabric to a compute fabric, and when you bring those technologies together, and converge them, and you have a partnership like Cisco, you have a partnership with us, yeah it's going to be a fantastic result for the market because the market moves on, and I think, VxBlock actually helped us achieve that. >> Alright so Siva we understand there's billions of reasons why Cisco and Dell would want to keep this partnership going, but talk about from an innovation standpoint, there's the new VxBlock 1000, what's new, talk about what's the innovation here. >> Absolutely. If you look at the VxBlock perspective, the 1000 perspective, first of all it simplifies an extremely fast successful product to the next level. It simplifies the storage options, and it provides a seamless way to consume those technologies. From a Cisco perspective, as you know we are in our fifth generation of UCS platform, continues to be a world class platform, leading blade service in the industry. But we also bring the innovation of rack mount servers, as well as 40 gig fabric, larger scale, fiber channel technology as well. As we bring our compute, network, as well as a sound fabric technology together, with world class storage portfolio, and then simplify that for a single pane of glass consumption model. That's absolutely the highest level of innovation you're going to find. >> Nigel, I think back in the early days the joke was you could have a Vblock anyway you want, as long as it's black. Obviously a lot of diversity in product line, but what's new and different here, how does this impact new customers and existing customers. >> I think there's a couple of things to pick up on, what Trey said, what Siva said. So the simplification piece, the way in which we do release certification matrix, the way in which you combine a single software image to manage these multiple discreet components, that is greatly simplified in VxBlock 1000. Secondly you remove a model number, because historically you're right, you bought a three series, a five series, and a seven series, and that sort of defined the architecture. This is now a system wide architecture. So those technologies that you might of thought of as being discreet before, or integrated at an RCM level that was perhaps a little complex for some people, that's now dramatically simplified. So those are two things that I think we amplify, one is the simplification and two, you're removing a model number and moving to a system wide architecture. >> Want to give you both the opportunity, gives us a little bit, what's the future when you talk about the 1000 system, future innovations, new use cases. >> Sure, I think if you look at the way enterprise are consuming, the demand for more powerful systems that'll bring together more consolidation, and also address the extensive data center migration opportunities we see, is very critical, that means the customers are really looking at whether it is a in-memory database that scales to, much larger scale than before, or large scale cluster databases, or even newer workloads for that matter, the appetite for a larger system, and the need to have it in the market, continues to grow. We see a huge install base of our customers, as well as new customers looking at options in the market, truly realize, the strength of the portfolio that each one of us brings to the table, and bringing the best-of-breed, whether it is today, or in the future from an innovation standpoint, this is absolutely the way that we are approaching building our partnership and building new solutions here. >> Nigel, when you're talking to customers out there, are they coming saying, I'm going to need this for a couple of months, I mean this is an investment they're making for a couple years, why is this a partnership built to last. >> An enterprise class customer certainly is looking for a technology that's synonymous with reliability, availability, performance. And if you look at what VxBlock has traditionally done and what the 1000 offers, you see that. But Siva's right, these application architectures are going to change. So if you can make an investment in a technology set now that keeps the premise of reliability, availability, and performance to you today, but when you look at future application architectures around high capacity memory, adjacent to a high performance CPU, you're almost in a position where you are preparing the ground for what that application architecture will need, and the investments that people make in the VxBlock system with the UCS power underneath at the compute layer, it's significant, because it lays out a very clear path to how you will integrate future application architectures with existing application architectures. >> Nigel Moulton, Siva Sivakumar, thank you so much for joining, talking about the partnership and the future. >> Siva: Thank you. >> Nigel: Pleasure. >> Sending back to Dave in the US, thanks so much for watching The Cube from Cisco Live Barcelona. >> Thank you. >> Okay thanks Stu, we're back here with Jeff Boudreau. We talked a little bit earlier about the history of conversion infrastructure, some of the impacts that we've seen in IT transformations, Trey took us through the architecture with some of the announcement details, and of course we heard from Cisco, was a lot of fun in Barcelona. Jeff bring it home, what are the take aways. >> Some of the key take aways I have is just I want to make sure everybody knows Dell EMC's continued commitment to modernizing infrastructure for conversion infrastructure. In addition to that was have a strong partnership with Cisco as you heard from me and you also heard from Cisco, that we both continue to invest and innovate in these spaces. In addition to that we're going to continue our leadership in CI, this is critical, and it's extremely important to Dell, and EMC, and Dell EMC's Cisco relationship. And then lastly, that we're going to continue to deliver on our customer promise to simplify IT. >> Okay great, thank you very much for participating here. >> I appreciate it. >> Now we're going to go into the crowd chat, again, it's an ask me anything. What make Dell EMC so special, what about security, how are the organizations affected by converged infrastructure, there's still a lot of, roll your own going on. There's a price to pay for all this integration, how is that price justified, can you offset that with TCO. So let's get into that, what are the other business impacts, go auth in with Twitter, LinkedIn, or Facebook, Twitter is my preferred. Let's get into it thanks for watching everybody, we'll see you in the crowd chat. >> I want IT to be dial tone service, where it's always available for our providers to access. To me, that is why IT exists. So our strategy at the hardware and software level is to ruthlessly standardize leverage in a converged platform technology. We want to create IT almost like a vending machine, where a user steps up to our vending machine, they select the product they want, they put in their cost center, and within seconds that product is delivered to that end user. And we really need to start running IT like a business. Currently we have a VxBlock that we will run our University of Vermont Medical Center epic install on. Having good performance while the provider is within that epic system is key to our foundation of IT. Having the ability to combine the compute, network, and storage in one aspect in one upgrade, where each component is aligned and regression tested from a Dell Technology perspective, really makes it easy as an IT individual to do an upgrade once or twice a year versus continually trying to keep each component of that infrastructure footprint upgraded and aligned. I was very impressed with the VxBlock 1000 from Dell Technologies, specifically a few aspects of it that really intrigued me. With the VxBlock 1000, we now have the ability to mix and match technologies within that frame. We love the way the RCM process works, from a converged perspective, the ability to bring the compute, the storage, and network together, and trust that Dell Technologies is going to upgrade all those components in a seamless manner, really makes it easier from an IT professional to continue to focus on what's really important to our organization, provider and patient outcomes.