so at the starting at the Google level we have data centers in four continents so we're in North America South America Asia and Europe of course we have a probably one of the world's largest global private networks with you know 13 undersea cables that are our own and hundreds of thousands of miles of dark fiber and and lit fiber that we you know we operate like I said probably one of the world's largest networks we have in in Europe were in five countries in Europe we're in two countries in Asia were in one country in South America and that's at the Google and in North America of course we have many many many sites across all of North America that's at the Google level now cloud has 19 regions that they operate in and 58 zones so each region of course has multiple zones in it you know we cover Google has presence in over 200 countries worldwide so really it is truly global operations so AccuWeather has been running an API service for the past ten years and we have lots of enterprise clients but we started to realize we are missing a whole business opportunity so we partnered with a eg and we created a new self-serve API developer portal that allows developers to go in there sign up on their own and get started and it's been great for us as far as like basically unlocking new revenue opportunities with api's because as you said everything is api's we also say everything is impacted by the weather so why not have everyone use a cue other api's to fulfill their weather needs I think if you look at what's going on and I talk to a lot of customers and developers and IT teams and clearly I think they are overwhelmed with the different things which are going on in this space so how do you make it simple how do you make it open how do you make it hybrid so you have flexibility of choices becoming top of the mind for many of the users now the lock in which many vendors currently provide it becomes very difficult for many of this users people moving around and meet the business requirements so I think having a solution and technology stack which is really understanding that complexity around that and making it simple in after dock I think is important so the focus well there's a theme in a couple different levels the broad theme is a cloud like no other because we've introduced a lot of new different features and products and programs we introduced anthos this morning which was really revolutionary way of using containers broadly Multi cloud hybrid cloud so it's from a product standpoint but it's also a cloud like no other because it's about the community that's here and it's truly a partnership with our customers and our partners about building this cloud together and we see the community as a really key part of that it's really core to Google's values around openness open-source technology and really embracing the broader community to build the cloud together well you know I think it continues to be continues to cooperate in the technical community very well and a couple of data points right one is around kubernetes that started what four or five years ago and that's going really strong but more importantly you know as the industry matures there are what I would call special interest groups that are starting to emerge in the kubernetes community one thing that we are playing very close attention to is the storage sake which is the ability to federated storage across multiple clouds and how do you do it seamlessly within the framework of googan IDs as opposed to trying to create a hack or a one-off that some vendors attempted to do so we try to take a very holistic view of it and make sure I mean the industry we are in it's time to drive volumes and volumes drive standards so I think we play very very close I think one of the biggest things that I'm seeing in this entire conference to date has been almost a mind shift change I mean this is conferences called Google Next and for a long time that's been one of their biggest problems they're focusing on what's next rather than what is today and they're inventing the future - almost at the expense of the present I think the big messaging today was both about reassuring enterprises that they're serious about this and also building a narrative where they're now talking about coming at this from a position of being able to embrace customers where they are and speak their language I think that that's transformative for Google and it's something I don't think that we've seen them do seriously at least not for very long I think that there's no question that this is a data game and we said early on John and the cube that big data war was going to be one in the cloud the data was going to reside in the cloud and having now machine intelligence applied to that data is what's giving companies competitive advantage and scale and economics I was struck by the stats that Google gave at the beginning of the keynote today Google in the last three years has spent 47 billion dollars on capital expenditures this year to date alone they've spent 13 billion dollars in capex and data centers 13 billion it would take IBM three and a half years to spend that much in capex it would take Oracle six years so from an economic standpoint in a scale standpoint Google Microsoft and Amazon are gonna win that game there's no question in my mind I am a student of AI I did my masters and PhD in that and I went through that change in my career because we had to collect the data match it and now analyze it and actually make a decision about it and we had a lot of false positives in some cases know something of which you don't want that either and what happened is our modeling capabilities became much better and we with this rich data and you actually tap into that data like you can go in there the data is there and disparate data we can pull in data from different sources and actually remove the outliers and make our decision real time right there we didn't have the processing capability we didn't have a place like pops up where global can scan and bring in data at hundreds of gigabytes of data that's messaging that you want to deal with at scale no matter where it is and process that that wasn't available for us now it's a real it's like a candy shop for technologists all the technologies in our hands and we want all these things so if you look at that category of that repetitive work AI can play a really amazing role in helping alleviate that mundane repetitive work and so you know great example of that as smart composed which hopefully you've used yep and so what we look at is things like say a salutation in an email where you have to think about who are you addressing how do you want to address them how do you spell their name we can alleviate that and make your composition much faster so the exciting announcement that we had today was that we are leveraging the Google assistant so the assistant that you're used to using at home via your home devices or on your phone and we're connecting that to your Google Calendar and so you'll be able to ask your assistant what you have on your schedule you know know what's ahead of you during your day and be able to do that on the go so you know I think in general one of the unique opportunities that we have with G suite is not only AI for taking these products that consumers know in love and bringing them into the enterprise and so we see that that helps people adopt and understand the products if it also just brings that like consumer grade simplicity and elegance in the design into the enterprise which brings joy to the workplace yeah so we've been working we've been hard at work over the last eight months since our last next can you believe that it's only been eight months and we last last year we were here announcing gk on prem this year we've rebranded CSP to anthos and enlarged it and we've moved it to GA so that's the big announcements in our spotlight we actually walk through all the pieces and gave three live demos as well as had two customers on stage and really the big difference in the eight months is while we're moving to GA now we've been working throughout this time with a set of customers we saw unprecedented demand for what we announced last year and we've had that privilege of working with customers to build a product which is what's unique really yeah and so we had two of those folks up on stage talking about the transformation that anthos is creating in their companies yeah absolutely I think particularly most of the larger enterprise accounts tend to have a multi vendor strategy for almost every category right including cloud which typically is one of the largest pens and you know it's it's typically what we see is people looking at certain classes or workloads running on particular clouds so it may be transactional systems running on AWS you know a lot of their more traditional enterprise workloads that were running on Windows servers potentially running on this year we see a lot of interest in data intensive sorts of analytics workloads potentially running on GCP and so I think larger companies tend to kind of look at it in terms of what's the best platform for the use case that they have in mind but in general you know I they are looking at multiple cloud vendors [Music] you

>>Live from Las Vegas. That's the Q covering splunk.com 19 brought to you by Splunk. >>Hey, welcome back. Every once the Q's live coverage here in Las Vegas for Splunk's dot com 2019 it's Splunk's 10th year having the events, the cubes coverage seven years, the cube independent media company breaking down, extracting the signal from the noise dot on the top people, top experts, tell them the stories that matter. We're here with Mike EG, director of applied research for coming red Canary. Mike, thanks for coming on. I appreciate it. Thank you. So red Canary is a company doing here. What's the focus? What does it company do? Take a minute to explain red County area and why you're here at.com. Sure, thank you. So we are a managed endpoint detection and response organization. We partner with organizations of all sizes to help them eradicate evil, for instance. So we help them with monitoring their environment. We investigate, respond and act on threats or so on the notes here, you guys have a topic session finding titled finding evil is never an accident, how to hunt in bots. >>So using bots, hunting down evil, you guys are out there doing this as a business. What does it mean? What does he, what if, first of all, what is evil and how do you hunt it down? Take us through that Sarah. So the talk is based around the boss of the SOC data set that was released by Splunk. They have version two, version one and version three will be coming out soon and they just released version four here. And so the talks all focused on how to find evil within bots. The three are actually V forum, sorry, the one that just came out. And so what we do as an organization is we help businesses get through their data, kind of like your guys' mission as well. Like get through them all the haystack, find the bad things and present that to our customers in a really fast way. >>So that's kind of where we are today. Archives to find the good content. Great experts like yourself tell about your role. You're like a researcher, but it's not like you're sitting back there applied research we applied means it's not like just making it up, you know the next moonshot, you guys are applied specifically to hunting down evil. That's your role. What does that entail? You guys have to sit back, zoom back, look at the data that the Splunk's providing some benefits with their, they're exposing their data. What does it mean to hunt down? What's, what's the requirements? How do you set that up? What are you looking at you going through day? Those are the dashboards. What are the what? What, what do you deal with and your job? >> Yeah, so like a day to day or like kind of what our team does is we focus on like what's going on previously, what are we seeing in the wild? >>Like what campaigns are happening and then my role within my team is focused on what's coming. So what are, what are red team's working on? What are pen testers looking into? Take that information, begin testing and begin building proof of concepts. Put that back into our products so that whether it's two weeks, six months, two years, we have coverage for it, no matter what. So a of us, a lot of our time is generating proof of concepts on what may be coming. So there's a lot of very unique things that may be in the wild today. And then there's some things that we may never see that are just very novel and kind of once, once, once a time kind of thing. Right? >> So you know, we love talking about data that we've been covering data since 2010 the thing that's interesting and I want to get your thoughts on this because you know, eval has arbitrage built into it. >>They know where to hide. And so the question is, is that what are you looking at matters, right? So the so, so, so there's a lot of exposure. But the question I have for you is, what is the problem that you're solving? Why do you guys exist? Was it because evil was better to adversaries? Were better at hiding? Is it automation can solve patterns they haven't seen yet? Because if you automate something you haven't seen yet, so is it new things? So why, what's the problem statement that you guys are attacking? Yeah. So hit it. It's a lot. There's a lot, there's a lot to inbox. Um, so like in particular in this instance, seeing something that happened yesterday and then what's happening today is actors are working to break process lineage within what's happening on the employee. Because actors know that everything's happening on an employment. >>Yes, there's traffic coming in, but there's execution going on in a single place on that box. So their whole tactic now is to try to break that lineage. So it's not Microsoft word spawning something. It's now Microsoft word opens and as spawns over there off another process, right? So we're here to monitor those types of behaviors. And that's pretty much like the core of red Canary. We've always focused on the end points. We only do emblem implant based products. We don't like monitor networks. We don't monitor firewalls or anything like that. We're very focused, uh, hyper focus on employee behaviors. And so, and that, that's the cool part about our job is we get to see all the really new things that are happening. And if you look at it, these breaches in the past, it's happening on the endpoint and that's probably where we are. >>And actually day the Canary in the coal mines all expression, everyone knows that or if older might know that. But you know, identifying and being that early warning detection system really kind of was the whole purpose of the Canary in the coal mine, red Canary red teams. I'm kind of putting it together. What are some of the things that you've seen that, that as an example of why you exist? Because it, is it new things, is it that, you know, Hey, our known thing or balls, what are some of the examples that you can point to that, that point of why you guys exist? Yeah, sure. Um, a good example is kind of like the looking forward stuff where red team's going, where actor's going. So a lot of them are moving to C sharp and.net Tradecraft, which is very native to the operating system. >>And windows. Um, so if they're doing that, they're moving away from what they're always, what they've been used to the last few years, which is PowerShell. So our sales kind of dead then now we're going to C sharp and.net. So a lot of our focus today is how can we better detect those? And vendors are moving that way too. They're, they're starting to see that they have to evolve their products to the next level order to detect these behaviors. Cause I mean that's, that's the whole reason why a lot of these EDR vendors are here. Right? And, and it's all data like you said. And so feeding it into a Sam or with a Splunk in particular, you're able to correlate those behaviors and look at very specific things and find it real well know. One of the things that a lot of security practitioners and experts and advisors have been looking at over years is data. >>So it's not, it's no secret data and critical. But one of the things that's interesting is that data availability has always been an issue. Sharing data. And then the message here@splunk.com for the 19 is interesting. You've got data diversity now exposure to the fabric search concept there they got accelerated and realtime times too. We've always had that. But as it kind of comes together, they're looking to get more diverse aperture to data. Yup. Is that still an ongoing challenge and what are, cause if you have a blind spot, you only, this is where the potential danger. How do you guys talk about that? What's the narrative around diverse data sets? How to deal with them effectively and then if blind spots exist, what do they look like or how do you figure that out? Yeah, we, so I, I've been with red Canary for over three years, about three years now. >>And one of the things I started at was a technical account manager incident handler. And so I helped a lot of our customers go from, we bought you red Canary to monitor points, but what should we do next? And so we, our incident handling team will come in and assist a customer with, you guys should start going down this road. Like, how are you bringing everything together? How are you analyzing your data down to just operationalizing like some use cases and playbooks within their data. Like you got EDR. Now let's look at your firewalls. How, how rich of that data can be helped enrich what the EDR information like here's the IP address and carbon black response. Where's it going this way on your firewall or your appliance is going out and you know, and things like that. So we have a whole team dedicated to it and that's like the focus of the. >>We took a poll in our, we have a, you know, this acumen operate for 10 years. It's our seventh year squad, Dave and I took a poll of our cube community, um, but 5,000 alumni and we asked them about cloud security, which vendors are the best and Splunk is clearly number one in third party data management. I got him out, he's got a category but cloud security. How should the cloud vendors provide security, Google, AWS and Azure. But outside of the core cloud providers, Splunk's number one, clearly across the board. How is Splunk doing in your mind? How do you guys work with Splunk? What's the dynamic? What's your relationship with Splunk and where Splunk position in your mind? Because as cloud becomes more prevalent with cloud native, born in the cloud and with hybrid there's a unification, not just with data. They have infrastructure operations. >>Yup. So Splunk role and then their future prospects share. Um, so red Canary uses Splunk too. So we, we process I think like 30 terabytes plus of data a day coming to our engine that we built. And that's the kind of like proprietary piece of red Canary. 30 terabytes of data flows through. We use a like a DSL, like a language that sits on top of it, that queries they're looking for those behaviors. We send those tip offs as we call to Splunk and we actually track a lot of the efficiencies of our detectors that way. So we look for how low detectors doing, is it triggering, is that false positives? How many false positives over time. And then also how much time our analysts are spending on those detectors. You know, they get a detector or a in event and they review that event and they're spending 2030 minutes on it and well what's wrong with it? >>Is there something going on here? Do we need to cut something back and fix it? So we use Splunk a lot of, for like the analytics piece of just how our operation works. It's awesome. It's really neat to see >> him for, one of the things that I've been proud of with covering Splunk is we showed them early when they were just started, then they went public. Yeah. Just watching how they've grown. That did a lot of great things. But now the theme is applications on top of Splunk. They're an enabling platform. They had a couple of key pillars. I want you to talk about where you guys fit and where you see the upside. So swamp has the developer area, which is, they have all these deck, new developers, security and compliance and fraud, um, foundations and platform stuff. And then the it ops does this analytics, AI ops, they've got signal FX, cloud native. >>So those are the kind of the four key areas around their apps, their app strategy. Do you guys cut across all those? You are you guys developing? Are you doing all, what's the, what's the red Canary fit into that? Yeah, it seems like you've probably our cross section. Yeah, probably most likely fitting into a few areas within Ed's. My team has developed a couple apps for Splunk, so we've published those. We have like a app that we pushed out. We have a carbon black response app, which we co-developed many years ago. Those things are all out there. We've helped other people with their apps and, but yeah, it's, it's a little mix of everything. And I think the big core thing that we're all looking to today is like how can we use more of the machine learning toolkit with Splunk, um, for our customers and for us internally. >>Like how can we predict things better with it? So there's, there's a lot of little bit of focus of that same thing. In your opinion, B2B out in the field, you mean the front lines, now you're in research, you got that holistic view, you're looking down at the, on the field, the battlefield, if you will, the adversaries will evil out there. What do you look for? I mean, what's the, what's the triggering event for you? How do you know when you need to jump in and get full ready, alert and really kind of sound off that, you know, that Canary alarm saying, Hey, you know, let's take action here or let's kind of like look at that and take us through some of those priorities. What's the, some of the workflow you go through? Yeah, so um, we'll end up either sending a detection to a customer and either they'll trigger like, Hey, can you give us more context around this event that happened? >>Or it will be, we had a pen test, red team, bad thing happen. Can someone else investigate further? And so I'll come in might from my perspective, I'll come in kind of like a, almost like a tier three in a way. We'll come in, we'll do the additional research beyond what our detectors already caught looking for. Many things, you know, did, was there something we missed that we can do better at detecting next time? Is there any new behaviors involved with something drop that you know, that the actor had left within the environment that may have gone by antivirus prevention controls, anything like that. Um, and then also just understanding their trade craft. Right? So we track a lot of teams and disturbed behaviors and we're able to kind of explore and you know, build those you gotta you gotta be on everything. Basically you gotta survey the entire landscape. >>Yep. You come in post event. Yeah. Do the collateral damage analysis and the dead map. That's a really cool thing about like the Splunk boss's a sock data set. Right. And that's where my talks a lot about is it's a very like, basic talk, but it focuses on how to go from beginning to end investigating this big incident that happened. You know, cause when you get an a detection from like in organization you might just find that it was delivered to a word doc, a couple of things executed. But was there something else that happened? Right? And there's like your Canadian Nicole mind piece, right. You know, finding other things that occurred within the organization and helping ideally your data essentially is the foundation for essentially preventative side. So it's, yes, it's kind of a closed loop kind of life cycle of yep. Leverage operating leverage data standpoint. >>Yeah, it's a solid point. We, I coined the term like three years ago called driving, driving prevention with detection. So take all your detection logic and understanding and things you see with products, even EDR Avi, and use that to drive your prevention. So it's just a way that if you're just alerting on everything, take that data and put it into your preventative preventative controls. So Michael got asked you, how is cloud, how is cloud changing the security formulas? Because obviously scale and data are big themes we hear all the time. I mean has been around is not a new thing. But the constant theme that I see in all my cube interviews we've done over the years and this year is the Nord scale comes up, is unprecedented scale, both in data volume, surface area needs for things like red Canary teams to be in there. What do you see with the impact the cloud is it really should change the game in any way? >>He has it's speed as new cloud. It's the speed of new cloud technology that seems to constantly be coming out. Like one day it's Docker, next day it's Coobernetti's and then there's going to be something tomorrow. Right? Like it just constantly changes. So how can vendors keep up with logging, making sure it's the right type of logging and being able to write detection on it or even detect anything out of it. Right. One, the diversity too is a great point. I want to know. Firstly, blogs are great. Yeah, you got tracing. So you have, so there's now different signaling. Yeah. So this app now a new thing that you got to stay on top. Oh, totally. Like look at any, any MSSP, they have thousands of data sources coming in. And now I want you to monitor my Coubernetties cluster that scales horizontally from 100 to 5,000 all day, every day like Netflix or something. >>Right? And I want you to find the bad things in that. It's a lot going on. And this is where machine learning and automation come into play because the observability you need the machine learning. They've got to categorize this. Okay. Again, humans do all this. No, yeah, it takes a machine. I'm using machines with human intelligence in a way, right? So have a human driving the machine to pull out those indicators, those notables. Michael, thanks for coming on. Great insight. Great signal from the noise. You're still distracting there. Great stuff. Final question for that to end the segment. In your opinion, what's the top story in the security industry that needs to be continually told and covered and reported on? >> Ooh, that's, that's a good one. Um, you hear any threats, platform development, new stacks developing. Is there like a one area that you think deep that's the high order bit in terms of like impact? Yeah. I think focus on, I'm going to say point cause that's where everything's executing and everything's happening. Um, and that's the biggest thing that it's only gonna get more challenging with IOT edge and industrial IOT. Yes. The edge is the end point. End points are changing. The definition is changing at exact right stuff coming on from red Canary here in the queue, the Canary in the coal mine. That's the cube. Brand-new. The signal here from.com 19. I'm John furrier back with more after this short break.

>> Narrator: Live from Madrid, Spain. It's theCUBE. Covering HPE Discover Madrid 2017. Brought to you by Hewlett Packard Enterprise. >> Hi everybody. Welcome to Madrid, Spain. This is theCUBE, the leader in live tech coverage and we're here at the conference center in Madrid covering HPE Discover 2017. This is HPE's European conference for years. We've been covering not only the US version of this show but also the European version. Frankfurt, Barcelona, London and now move to southern Europe and central Spain. I'm here with Peter Burris. My co-host for the next two days. >> Peter. >> Hi, Dave. >> Good to see you. Good to be here in Spain and we're going to be covering the, we've been covering the transformation of HPE under the guise of, the guidance of Meg Whitman for the last six years, of course it was announced recently that Meg is stepping down and Antonio Neri's going to take over so we're going to be reviewing that, we're going to be covering all the innovations that these guys are announcing, talking to customers and very importantly, something that you've been talking about is juxtaposing HPE as a long time enterprise company with a lot of customers. Juxtaposing that strategy with the other end of the spectrum this week at AWS reinvent Amazon obviously, growing very fast. Many of the decisions that Meg and her team made they are a direct result of the cloud effect and other things that we will be talking about. So, welcome. >> You bet. >> Thanks for coming on. >> No, I, Madrid's a wonderful city and this is a great place to be running the conference like this. It's one of the transformational cities in the world. >> So, let's start by looking at Meg's tenure. When she came on and she inherited a mess, everybody knew about the acquisition issues that they had with autonomy. So, she inherited that from Leo Apotheker and really kind of took one for the Silicon Valley team, really and set the time, look it's going to take us five years to transform this company. So, it started with an organizational, sort of, look and you know, took some time to get that right. To understand who her team leaders were going to be and they made some missteps and sort of had to shuffle the deckchairs a little bit. So, they did that. They had a public cloud misstep but eventually they got that right. And they decided that they would split the company in two, HP INC and HPE. At the time it was believed that HPE would be the growth engine, HP INC would be the cash flow engine, it hasn't totally worked out that way but one of the things that came out of that was a much better balance sheet. HPE's got about $5.8 billion in cash now. It's started to make those, some acquisitions. That we'll talk about but essentially Peter, it emerged from that split as a much more focused company. As I say, a better balance sheet, much smaller company, with a focus on essentially a lower margin business to be able to compete with the cloud and with essentially China. Your take on the last five or six years under Meg Whitman? >> Well, I think you summarized it pretty nicely. I guess I'd say a couple of things. The first thing is that I think it philosophically, HPE was one of those companies that believed it's size was its own virtue in the technology industry. >> Dave: Mhm. >> And while that's certainly true in certain domains, it's not necessarily true in all. The complexity and the interplay of technology, solutions, software, hardware is such that one of the places where you get the most leverage out of something like that is at the customer interface. Are you capable of pulling together all that's possible in the tech industry and present it to the customer in a form that the customer then can turn into value. So HP for a long time, just presumed its size was its own virtue. Focused on acquiring as much stuff as it possibly could to feed that and probably left the customer a little bit on the sideline and didn't really focus on the customer. I think that was probably Meg's first good move is to step back and say, let's not act as though size is its own virtue. Let's stop the acquisition, let's focus on what we have which is mainly this large portfolio of customers and refocus on the company on that. That's a good thing. So, I think the first thing that they was they went back to the simple observation that HP's always had, that we don't exist if we don't have, if we don't take care of our customers. Second thing I think that they did as you said, they, the Leo era was about, oh we're going to be a software company and I think they strongly pulled away from that. Where the idea was to just get as many software assets as possible and try to figure out how to weave them together. They pulled away from that although we agree that it's a misnomer that HP got out of the software business. Clearly, they got rid of a bunch of assets that they couldn't use. They've reinvested in other assets that are more true to their heritage. We're going to see some big announcements this week about that. >> And that's really focused on, you know, making infrastructure better, right? >> Exactly, and ultimately the, it's interesting that there's no question that AWS is crafting the new look of the computing industry but it's not a complete picture and it's not going to be a complete picture. There's going to be plenty of room for companies to move and some of those companies are easily going to be tens of billions of dollars in size and so, the vision that HP has, the direction HP seems to be going has the potential to be very complimentary to that other vision. As we like to say, the goal is for customers, is the COD experience where the data demands. And that we know that the data's going to be at the edge and we know that the data's going to be, a lot of it's going to be on premise. And so as a consequence of that, there will be a play for a strong; multiple strong companies who are focusing on delivering at the edge, great technology, great management capabilities, and delivering true private cloud into a company where they got to put their proprietary data assets. >> Okay, so what that really says is HPE and its competitors who sell on prem actually need to mimic to the extent that they can, that cloud experience. >> Yeah. >> So we're going to be unpacking that. I mean, HPE talks a lot about flexible capacity. We're going to try to unpack that to see how cloud like it really is. I mean it's not identical but it certainly gets to be much more of an opex versus a capex model. >> Peter: It's moving in that direction. >> As well as the ability to deploy quickly and let's cut to the chase, reduce non differentiated IT labor costs and that's something that we're going to unpack with some of the customers here who you know, maybe used to be in the business of provisioning infrastructure and tuning infrastructure. You know likely moving toward a role in digital business. >> Peter: Mhmm. >> So, you know just some of the financials, HPE, the new HPE is roughly a $30 billion company. You know, the stock's done okay since the split but it's still trading at less than $1 from evaluation standpoint, a revenue dollar. So, you know trading, it's evaluation is well under that $30 billion, probably in the low 20's. So there's a lot of upside, you know certainly a company like HPE, if it can show some growth which it eeked out, ya know, a constant currency about a 1% growth last quarter. If you take out the Tier 1 sever business that it's exiting, the growth is actually a little bit better and there are some bright spots. Certainly, Aruba has been growing like crazy and it's interesting Peter. HPE is going to put forth a new financial reporting structure, next quarter. So, they're going to eliminate the whole, 'member it was EG and it was networking, et cetera. They're going to bundle everything into much of the core business into hybrid IT, that's going to be their biggest business, server storage and core networking and services and they're going to have, essentially, The Edge is going to be it's second category. Which is going to comprise Aruba and edge services and all the wireless stuff and the third category interestingly is, financial services which has been growing like crazy. It grew about over 20% last quarter. So, HPE is now saying, okay this is the face that we're going to present to the street and they're going to try to present it as a growth company and certainly the largest business is going to be hybrid IT and then you got two growth businesses, The Edge and financial services which is really about creating that cloud experiences to a great degree through some financial engineering. >> Yeah and look that's smart because as we were talking about that the whole concept of where the scale is going to be in the future, is where Amazon is at putting all this stuff together and putting all these assets behind the wall so you get a service out of it or in the customer engagement side of things and the only way that HP is going to be successful at replicating or putting forward this notion of, what we call true private cloud that, where you do get the cloud experience but you get it on premise where your data requires, is by looking at things just in that way. Sources at the edge, finance that allows you to buy as you go and then great server technology that can run the workloads where they need to be run based on the availability of the data. >> So last thing I'll say. So, I asked the question five years ago. Can HPE, can HP get back to its roots? Remember the old logo, invent. I sort of tweeted out, I didn't think HP's strategy was to get there. I thought at the time that was sort of an imperative and I had a little discussion with somebody from HP on twitter where they suggested, hey there's a lot of innovation here and we've talked about the difference between innovation and invention and if you look at some of the acquisitions that HPE has made, SGI, SimpliVity, Nimble, some of the smaller acquisitions around, cloud technology partners. >> These are really focused acquisitions. >> Yeah, very focused tuck-ins and a lot of innovation there is I guess what I'd say and we're going to again, unpack that innovation, we had HP-- >> Peter: Lot of invention. >> Folks from labs coming on as well and we're going to talk about invention, innovation, we're going to talk about that all week. So, keep it right there everybody. This is theCUBE. We're live from HPE Discover Madrid. We'll be back right after this short break.

>> Announcer: You are CUBE Alumni. Live from Munich, Germany, it's theCUBE. Covering, DataWorks Summit Europe 2017. Brought to you by Hortonworks. >> Hello, everyone, welcome back to live coverage at DataWorks 2017, I'm John Furrier with my cohost, Dave Vellante. Two days of coverage here in Munich, Germany, covering Hortonworks and Yahoo, presenting Hadoop Summit, now called DataWorks 2017. Our next guest is Carlo Vaiti, who's the HPE chief technology strategist, EMEA Digital Solutions, Europe, Middle East, and Africa. Welcome to theCUBE. >> Thank you, John. >> So we were just chatting before we came on, of your historic background at IBM, Oracle, and now HPE, and now back into the saddle there. >> Don't forget Sun Microsystems. >> Sun Microsystems, sorry, Sun, yeah. I mean, great, great run. >> It was a long run. >> You've seen the computer revolution happen. I worked at HP for nine years, from '88 to '97. Again, Dave was a premier analyst during that run of client-server. We've seen the computer revolution happen. Now we're seeing the digital revolution where the iPhone is now 10 years old, Cloud is booming, data's at the center of the value proposition, so a completely new disruptive capability. >> Carlo: Sure, yes. >> So what are you doing as the CTO, chief technologist for HPE, how are you guys bringing this story together? 'Cause there's so much going on at HPE. You got the services spit, you got the software split, and HP's focusing on the new style of IT, as Meg Whitman calls it. >> So, yeah. My role in EMEA is actually all about having basically a visionary kind of strategy role for what's going to be HP in the future, in terms of IT. And one of the things that we are looking at is, is specifically to have, we split our strategy in three different aspects, so three transformation areas. The first one which we usually talk is what I call hybrid IT, right, which is basically making services around either On-Premise or on Cloud for our customer base. The second one is actually power the Intelligent Edge, so is actually looking after our collaboration and when we acquire Aruba components. And the third one, which is in the middle, and that's why I'm here at the DataWorks Summit, is actually the data-analytics aspects. And we have a couple of solution in there. One is the Enterprise great Hadoop, which is part of this. This is actually how we generalize all the figure and the strategy for HP. >> It's interesting, Dave and I were talking yesterday, being in Europe, it's obviously a different sideshow, it's smaller than the DataWorks or Hadoop Summit in North America in San Jose, but there's a ton of Internet of things, IoT or IIoT, 'cause here in Germany, obviously, a lot of industrial nations, but in Europe in general, a lot of smart cities initiatives, a lot of mobility, a ton of Internet of things opportunity, more than in the US. >> Absolutely. >> Can you comment on how you guys are tackling the IoT? Because it's an Intelligent Edge, certainly, but it's also data, it's in your wheelhouse. >> Yes, sure. So I'm actually working, it's a good question, because I'm actually working a couple of projects in Eastern Europe, where it's all about Industrial IoT Analytics, IIoTA. That's the new terminology we use. So what we do is actually, we analyze from a business perspective, what are the business pain points, in an oil and gas company for example. And we understand for example, what kind of things that they need and must have. And what I'm saying here is, one of the aspects for example, is the drilling opportunity. So how much oil you can extract from a specific rig in the middle of the North Sea, for example. This is one of the key question, because the customer want to understand, in the future, how much oil they can extract. The other one is for example, the upstream business. So doing on the retail side and having, say, when my customer is stopping in a gas station, I want go in the shop, immediately giving, I dunno, my daughter, a kind of campaign for the Barbie, because they like the Barbie. So IoT, Industrial IoT help us in actually making a much better customer experience, and that's the case of the upstream business, but is also helping us in actually much faster business outcomes. And that's what the customer wants, right? 'Cause, and was talking with your colleague before, I'm talking to the business guy. I'm not talking to the IT anymore in these kind of place, and that's how IoT allow us a chance to change the conversation at the industry level. >> These are first-time conversations too. You're getting at the kinds of business conversations that weren't possible five years ago. >> Carlo: Yes, sure. >> I mean and 10 years ago, they would have seemed fantasy. Now they're reality. >> The role of analytics in my opinion, is becoming extremely key, and I said this morning, for me my best center is that the detail, is the stone foundation of the digital economy. I continue to repeat this terminology, because it's actually where everything is starting from. So what I mean is, let's take a look at the analytic aspect. So if I'm able to analyze the data close to the shop floor, okay, close to the shop manufacturing floor, if I'm able to analyze my data on the rig, in the oil and gas industry, if I'm able to analyze doing preprocessing analytics, with Kafka, Druid, these kind of open-source software, where close to the Intelligent Edge, then my customers going to be happy, because I give them very fast response, and the decision-maker can get to decision in a faster time. Today, it takes a long time to take these type of decision. So that's why we want to move into the power Intelligent Edge. >> So you're saying, data's foundational, but if you get to the Intelligent Edge, it's dynamic. So you have a dynamic reactive, realtime time series, or presences of data, but you need the foundational pre-data. >> Perfect. >> Is that kind of what you're getting at? >> Yes, that's the first step. Preprocessing analytics is what we do. In the next generation of, we think is going to be Industrial IoT Analytics, we're going to actually put massive amount of compute close to the shop manufacturing floor. We call internally or actually externally, convergent planned infrastructure. And that's the key point, right? >> John: Convergent plan? >> Convergent planned infrastructure, CPI. If you look at in Google, you will find. It's a solution we bring in the market a few months ago. We announce it in December last year. >> Yeah, Antonio's smart. He also had a converged systems as well. One of the first ones. >> Yeah, so that's converge compute at the edge basically. >> Correct, converge compute-- >> Very powerful. >> Very powerful, and we run analytics on the edge. That's the key point. >> Which we love, because that means you don't have to send everything back to the Cloud because it's too expensive, it's going to take too long, it's not going to work. >> Carlo: The bandwidth on the network is much less. >> There's no way that's going to be successful, unless you go to the edge and-- >> It takes time. >> With a cost. >> Now the other thing is, of course, you've got the Aruba asset, to be able to, I always say, joke, connect the windmill. But, Carlo, can we go back to the IoTA example? >> Carlo: Correct, yeah. >> I want to help, help our audience understand, sort of, the new HP, post these spin merges. So perviously you would say, okay, we have Vertica. You still have partnership, or you still own Vertica, but after September 1st-- >> Absolutely, absolutely. It's part of the columnar side-- >> Right, yes, absolutely, but, so. But the new strategy is to be more of a platform for a variety of technology. So how for instance would you solve, or did you solve, that problem that you described? What did you actually deliver? >> So again, as I said, we're, especially in the Industrial IoT, we are an ecosystem, okay? So we're one element of the ecosystem solution. For the oil and gas specifically, we're working with other system integrator. We're working with oil and the industry gas expertise, like DXC company, right, the company that we just split a few days ago, and we're working with them. They're providing the industry expertise. We are a infrastructure provided around that, and the services around that for the infrastructure element. But for the industry expertise, we try to have a kind of little bit of knowledge, to start the conversation with the customer. But again, my role in the strategy is actually to be a ecosystem digital integrator. That's the new terminology we like to bring in the market, because we really believe that's the way HP role is going to be. And the relevance of HP is totally depending if we are going to be successful in these type of things. >> Okay, now a couple other things you talked about in your keynote. I'm just going to list them, and then we can go wherever we want. There was Data Link 3.0, Storage Disaggregation, which is kind of interesting, 'cause it's been a problem. Hadoop as a service, Realtime Everywhere, and then Analytics at the Edge, which we kind of just talked about. Let's pick one. Let's start with Data Link 3.0. What is that? John doesn't like the term data link. He likes data ocean. >> I like data ocean. >> Is Data Link 3.0 becoming an ocean? >> It's becoming an ocean. So, Data Link 3.0 for us is actually following what is going to be the future for HDFS 3.0. So we have three elements. The erasure coding feature, which is coming on HDFS. The second element is around having HDFS data tier, multi-data tier. So we're going to have faster SSD drives. We're going to have big memory nodes. We're going to have GPU nodes. And the reason why I say disaggregation is because some of the workload will be only compute, and some of the workload will be only storage, okay? So we're going to bring, and the customer require this, because it's getting more data, and they need to have for example, YARN application running on compute nodes, and the same level, they want to have storage compute block, sorry, storage components, running on the storage model, like HBase for example, like HDFS 3.0 with the multi-tier option. So that's why the data disaggregation, or disaggregation between compute and storage, is the key point. We call this asymmetric, right? Hadoop is becoming asymmetric. That's what it mean. >> And the problem you're solving there, is when I add a node to a cluster, I don't have to add compute and storage together, I can disaggregate and choose whatever I need, >> Everyone that we did. >> based on the workload. >> They are all multitenancy kind of workload, and they are independent and they scale out. Of course, it's much more complex, but we have actually proved that this is the way to go, because that's what the customer is demanding. >> So, 3.0 is actually functional. It's erasure coding, you said. There's a data tier. You've got different memory levels. >> And I forgot to mention, the containerization of the application. Having dockerized the application for example. Using mesosphere for example, right? So having the containerization of the application is what all of that means, because what we do in Hadoop, we actually build the different clusters, they need to talk to each other, and change data in a faster way. And a solution like, a product like SQL Manager, from Hortonworks, is actually helping us to get this connection between the cluster faster and faster. And that's what the customer wants. >> And then Hadoop as a service, is that an on-premise solution, is that a hybrid solution, is it a Cloud solution, all three? >> I can offer all of them. Hadoop is a service could be run on-premise, could be run on a public Cloud, could be run on Azure, or could be mix of them, partially on-premise, and partially on public. >> And what are you seeing with regard to customer adoption of Cloud, and specifically around Hadoop and big data? >> I think the way I see that option is all the customer want to start very small. The maturity is actually better from a technology standpoint. If you're asking me the same question maybe a year ago, I would say, it's difficult. Now I think they've got the point. Every large customer, they want to build this big data ocean, note the delay, ocean, whatever you want to call it. >> John: Love that. (laughs) >> All right. They want to build this data ocean, and the point I want to make is, they want to start small, but they want to think very high. Very big, right, from their perspective. And the way they approach us is, we have a kind of methodology. We establish the maturity assessment. We do a kind of capability maturity assessment, where we find that if the customer is actually a pioneer, or is actually a very traditional one, so it's very slow-going. Once we determine where is the stage of the customer is, we propose some specific proof of concept. And in three months usually, we're putting this in place. >> You also talked about realtime everywhere. We in our research, we talk about the, historically, you had batchy of interactive, and now you have what we call continuous, or realtime streaming workloads. How prevalent is that? Where do you see it going in the future? >> So I think is another train for the future, as I mentioned this morning in my presentation. So and Spark is actually doing the open-source memory engine process, is actually the core of this stuff. We see 60 to 70 time faster analytics, compared to not to use Spark. So many customer implemented Spark because of this. The requirement are that the customer needs an immediate response time, okay, for a specific decision-making that they have to do, in order to improve their business, in order to improve their life. But this require a different architecture. >> I have a question, 'cause you, you've lived in the United States, you're obviously global, and spent a lot of time in Europe as well, and a lot of times, people want to discuss the differences between, let's make it specific here, the European continent and North America, and from a sophistication standpoint, same, we can agree on that, but there are still differences. Maybe, more greater privacy concerns. The whole thing with the Cloud and the NSA in the United States, created some concerns. What do you see as the differences today between North America and Europe? >> From my perspective, I think we are much more for example take IoT, Industrial IoT. I think in Europe we are much more advanced. I think in the manufacturing and the automotive space, the connected car kind of things, autonomous driving, this is something that we know already how to manage, how to do it. I mean, Tesla in the US is a good example that what I'm saying is not true, but if I look at for example, large German manufacturing car, they always implemented these type of things already today. >> Dave: For years, yeah. >> That's the difference, right? I think the second step is about the faster analytic approach. So what I mentioned before. The Power the Intelligent Edge, in my opinion at the moment, is much more advanced in the US compared to Europe. But I think Europe is starting to run back, and going on the same route. Because we believe that putting compute capacity on the edge is what actually the customer wants. But that's the two big differences I see. >> The other two big external factors that we like to look at, are Brexit and Trump. So (laughs) how 'about Brexit? Now that it's starting to sort of actually become, begin the process, how should we think about it? Is it overblown? It is critical? What's your take? >> Well, I think it's too early to say. UK just split a few days ago, right, officially. It's going to take another 18 months before it's going to be completed. From a commercial standpoint, we don't see any difference so far. We're actually working the same way. For me it's too early to say if there's going to be any implication on that. >> And we don't know about Trump. We don't have to talk about it, but the, but I saw some data recently that's, European sentiment, business sentiment is trending stronger than the US, which is different than it's been for the last many years. What do you see in terms of just sentiment, business conditions in Europe? Do you see a pick up? >> It's getting better, it is getting better. I mean, if I look at the major countries, the P&L is going positive, 1.5%. So I think from that perspective, we are getting better. Of course we are still suffering from the Chinese, and Japanese market sometimes. Especially in some of the big large deals. The inclusion of the Japanese market, I feel it, and the Chinese market, I feel that. But I think the economy is going to be okay, so it's going to be good. >> Carlo, I want to thank you for coming on and sharing your insight, final question for you. You're new to HPE, okay. We have a lot of history, obviously I was, spent a long part of my career there, early in my career. Dave and I have covered the transformation of HP for many, many years, with theCUBE certainly. What attracted you to HP and what would you say is going on at HP from your standpoint, that people should know about? >> So I think the number one thing is that for us the word is going to be hybrid. It means that some of the services that you can implement, either on-premise or on Cloud, could be done very well by the new Pointnext organization. I'm not part of Pointnext. I'm in the EG, Enterprise Group division. But I am fan for Pointnext because I believe this is the future of our company, is on the services side, that's where it's going. >> I would just point out, Dave and I, our commentary on the spin merge has been, create these highly cohesive entities, very focused. Antonio now running EG, big fans, of where it's actually an efficient business model. >> Carlo: Absolutely. >> And Chris Hsu is running the Micro Focus, CUBE Alumni. >> Carlo: It's a very efficient model, yes. >> Well, congratulations and thanks for coming on and sharing your insights here in Europe. And certainly it is an IoT world, IIoT. I love the analytics story, foundational services. It's going to be great, open source powering it, and this is theCUBE, opening up our content, and sharing that with you. I'm John Furrier, Dave Vellante. Stay with us for more great coverage, here from Munich after the short break.