>>Okay, we're back with the hybrid Cloud power panel. I'm Dave Ante and with me our Eric Lockhart, who's the corporate vice president of Microsoft Azure, Specialized Thomas Corny, the senior vice president of products at Nutanix, and Indu Care, who's the Senior Vice President of engineering, NCI and nnc two at Nutanix. Gentlemen, welcome to the cube. Thanks for coming on. >>It's to >>Be here. Have us, >>Eric, let's, let's start with you. We hear so much about cloud first. What's driving the need for hybrid cloud for organizations today? I mean, I wanna just ev put everything in the public cloud. >>Yeah, well, I mean, the public cloud has a bunch of inherent advantages, right? I mean, it's, it has effectively infinite capacity, the ability to, you know, innovate without a lot of upfront costs, you know, regions all over the world. So there is a, a trend towards public cloud, but you know, not everything can go to the cloud, especially right away. There's lots of reasons. Customers want to have assets on premise, you know, data gravity, sovereignty and so on. And so really hybrid is the way to achieve the best of both worlds, really to kind of leverage the assets and investments that customers have on premise, but also take advantage of, of the cloud for bursting or regionality or expansion, especially coming outta the pandemic. We saw a lot of this from work from home and, and video conferencing and so on, driving a lot of cloud adoption. So hybrid is really the way that we see customers achieving the best of both worlds. >>Yeah, makes sense. I wanna, Thomas, if you could talk a little bit, I don't wanna inundate people with the acronyms, but, but the Nutanix Cloud clusters on Azure, what is that? What problems does it solve? Give us some color there, please. >>That is, so, you know, cloud clusters on Azure, which we actually call NC two to make it simple. And so NC two on Azure is really our solutions for hybrid cloud, right? And you think about the hybrid cloud, highly desirable customers want it. They, they know this is the right way to do for them, given that they wanna have workloads on premises at the edge, any public clouds. But it's complicated. It's hard to do, right? And the first thing that you deal with is just silos, right? You have different infrastructure that you have to go and deal with. You have different teams, different technologies, different areas of expertise and dealing with different portals. Networkings get complicated, security gets complicated. And so you heard me say this already, you know, hybrid can be complex. And so what we've done, we then c to Azure is we make that simple, right? We allow teams to go and basically have a solution that allows you to go and take any application running on premises and move it as is to any Azure region where ncq is available. Once it's running there, you keep the same operating model, right? And that's something actually super valuable to actually go and do this in a simple fashion, do it faster, and basically do, do hybrid in a more cost effective fashion, know for all your applications. And that's really what's really special about NC Azure today. >>So Thomas, just a quick follow up on that. So you're, you're, if I understand you correctly, it's an identical experience. Did I get that right? >>This is, this is the key for us, right? Is when you think you're sending on premises, you are used to way of doing things of how you run your applications, how you operate, how you protect them. And what we do here is we extend the Nutanix operating model two workloads running in Azure using the same core stack that you're running on premises, right? So once you have a cluster deploying C to an Azure, it's gonna look like the same cluster that you might be running at the edge or in your own data center, using the same tools, using, using the same admin constructs to go protect the workloads, make them highly available with disaster recovery or secure them. All of that becomes the same, but now you are in Azure, and this is what we've spent a lot of time working with Americanist teams on, is you actually have access now to all of those suites of Azure services in from those workloads. So now you get the best of both world, you know, and we bridge them together and you get seamless access of those services between what you get from Nutanix, what you get from Azure. >>Yeah. And as you alluded to, this is traditionally been non-trivial and people have been looking forward to this for, for quite some time. So Indu, I want to understand from an engineering perspective, your team had to work with the Microsoft team, and I'm sure there was this, this is not just a press releases or a PowerPoint, you had to do some some engineering work. So what specific engineering work did you guys do and what's unique about this relative to other solutions in the marketplace? >>So let me start with what's unique about this, and I think Thomas and Eric both did a really good job of describing that the best way to think about what we are delivering jointly with Microsoft is that it speeds up the journey to the public cloud. You know, one way to think about this is moving to the public cloud is sort of like remodeling your house. And when you start remodeling your house, you know, you find that you start with something and before you know it, you're trying to remodel the entire house. And that's a little bit like what journey to the public cloud sort of starts to look like when you start to refactor applications. Because it wasn't, most of the applications out there today weren't designed for the public cloud to begin with. NC two allows you to flip that on its head and say that take your application as is and then lift and shift it to the public cloud, at which point you start the refactor journey. >>And one of the things that you have done really well with the NC two on Azure is that NC two is not something that sits by Azure side. It's fully integrated into the Azure fabric, especially the software defined network and SDN piece. What that means is that, you know, you don't have to worry about connecting your NC two cluster to Azure to some sort of a net worth pipe. You have direct access to the Azure services from the same application that's now running on an C2 cluster. And that makes your refactoring journey so much easier. Your management claim looks the same, your high performance notes let the NVMe notes, they look the same. And really, I mean, other than the facts that you're doing something in the public cloud, all the Nutanix goodness that you're used to continue to receive that, there is a lot of secret sauce that we have had to develop as part of this journey. >>But if we had to pick one that really stands out, it is how do we take the complexity, the network complexity, offer public cloud, in this case Azure, and make it as familiar to Nutanix's customers as the VPC construc, the virtual private cloud construct that allows them to really think of their on-prem networking and the public cloud networking in very similar terms. There's a lot more that's gone on behind the scenes. And by the way, I'll tell you a funny sort of anecdote. My dad used to say when I drew up that, you know, if you really want to grow up, you have to do two things. You have to like build a house and you have to marry your kid off to someone. And I would say our dad a third do a code development with the public cloud provider of the partner. This has been just an absolute amazing journey with Eric and the Microsoft team, and you're very grateful for their support. >>I need NC two for my house. I live in a house that was built and it's 1687 and we connect old to new and it's, it is a bolt on, but, but, but, and so, but the secret sauce, I mean there's, there's a lot there, but is it a PAs layer? You didn't just wrap it in a container and shove it into the public cloud, You've done more than that. I'm inferring, >>You know, the, it's actually an infrastructure layer offering on top of fid. You can obviously run various types of platform services. So for example, down the road, if you have a containerized application, you'll actually be able to tat it from OnPrem and run it on C two. But the NC two offer itself, the NCAA often itself is an infrastructure level offering. And the trick is that the storage that you're used to the high performance storage that you know, define Nutanix to begin with, the hypervisor that you're used to, the network constructs that you're used to light MI segmentation for security purposes, all of them are available to you on NC two in Azure, the same way that we're used to do on-prem. And furthermore, managing all of that through Prism, which is our management interface and management console also remains the same. That makes your security model easier, that makes your management challenge easier, that makes it much easier for an accusation person or the IT office to be able to report back to the board that they have started to execute on the cloud mandate and they have done that much faster than they'll be able to otherwise. >>Great. Thank you for helping us understand the plumbing. So now Thomas, maybe we can get to like the customers. What, what are you seeing, what are the use cases that are, that are gonna emerge for this solution? >>Yeah, I mean we've, you know, we've had a solution for a while and you know, this is now new on Azure is gonna extend the reach of the solution and get us closer to the type of use cases that are unique to Azure in terms of those solutions for analytics and so forth. But the kind of key use cases for us, the first one you know, talks about it is a migration. You know, we see customers on the cloud journey, they're looking to go and move applications wholesale from on premises to public cloud. You know, we make this very easy because in the end they take the same culture that are around the application and make them, we make them available Now in the Azure region, you can do this for any applications. There's no change to the application, no networking change. The same IP will work the same whether you're running on premises or in Azure. >>The app stays exactly the same, manage the same way, protected the same way. So that's a big one. And you know, the type of drivers point to politically or maybe I wanna go do something different or I wanna go and shut down education on premises, I need to do that with a given timeline. I can now move first and then take care of optimizing the application to take advantage of all that Azure has to offer. So migration and doing that in a simple fashion, in a very fast manner is, is a key use case. Another one, and this is classic for leveraging public cloud force, which are doing on premises IT disaster recovery and something that we refer to as elastic disaster recovery, being able to go and actually configure a secondary site to protect your on premises workloads, but I that site sitting in Azure as a small site, just enough to hold the data that you're replicating and then use the fact that you cannot get access to resources on demand in Azure to scale out the environment, feed over workloads, run them with performance, potentially feed them back to on premises and then shrink back the environment in Azure to again, optimize cost and take advantage of elasticity that you get from public cloud models. >>Then the last one, building on top of that is just the fact that you cannot get boosting use cases and maybe running a large environment, typically desktop, you know, VDI environments that we see running on premises and I have, you know, a seasonal requirement to go and actually enable more workers to go get access the same solution. You could do this by sizing for the large burst capacity on premises wasting resources during the rest of the year. What we see customers do is optimize what they're running on premises and get access to resources on demand in Azure and basically move the workload and now basically get combined desktops running on premises desktops running on NC two on Azure, same desktop images, same management, same services, and do that as a burst use case during, say you're a retailer that has to go and take care of your holiday season. You know, great use case that we see over and over again for our customers, right? And pretty much complimenting the notion of, look, I wanna go to desktop as a service, but right now I don't want to refactor the entire application stack. I just wanna be able to get access to resources on demand in the right place at the right time. >>Makes sense. I mean this is really all about supporting customers', digital transformations. We all talk about how that was accelerated during the pandemic and, but the cloud is a fundamental component of the digital transformation generic. You, you guys have obviously made a commitment between Microsoft and and Nutanix to simplify hybrid cloud and that journey to the cloud. How should customers, you know, measure that? What does success look like? What's the ultimate vision here? >>Well, the ultimate vision is really twofold. I think the one is to, you know, first is really to ease a customer's journey to the cloud to allow them to take advantage of all the benefits to the cloud, but to do so without having to rewrite their applications or retrain their, their administrators and or or to obviate their investment that they already have and platforms like, like Nutanix. And so the, the work that companies have done together here, you know, first and foremost is really to allow folks to come to the cloud in the way that they want to come to the cloud and take really the best of both worlds, right? Leverage, leverage their investment in the capabilities of the Nutanix platform, but do so in conjunction with the advantages and and capabilities of, of Azure. You know, Second is really to extend some of the cloud capabilities down onto the on-premise infrastructure. And so with investments that we've done together with Azure arc for example, we're really extending the Azure control plane down onto on premise Nutanix clusters and bringing the capabilities that that provides to the, the Nutanix customer as well as various Azure services like our data services and Azure SQL server. So it's really kind of coming at the problem from, from two directions. One is from kind of traditional on-premise up into the cloud and then the second is kind of from the cloud leveraging the investment customers have in in on-premise hci. >>Got it. Thank you. Okay, last question. Maybe each of you can just give us one key takeaway for our audience today. Maybe we start with with with with Thomas and then Indu and then Eric you can bring us home. >>Sure. So the key takeaway is, you know, Nutanix Cloud clusters on Azure is now ga you know, this is something that we've had tremendous demand from our customers, both from the Microsoft side and the Nutanix side going, going back years literally, right? People have been wanting to go and see this, this is now live GA open for business and you know, we're ready to go and engage and ready to scale, right? This is our first step in a long journey in a very key partnership for us at Nutanix. >>Great Indu >>In our Dave. In a prior life about seven or eight, eight years ago, I was a part of a team that took a popular cat's preparation software and moved it to the public cloud. And that was a journey that took us four years and probably several hundred million. And if we had had NC two then it would've saved us half the money, but more importantly would've gotten there in one third the time. And that's really the value of this. >>Okay. Eric, bring us home please. >>Yeah, I'll just point out like this is not something that's just both on or something. We, we, we started yesterday. This is something the teams, both companies have been working on together for, for years, really. And it's, it's a way of, of deeply integrating Nutanix into the Azure Cloud and with the ultimate goal of, of again, providing cloud capabilities to the Nutanix customer in a way that they can, you know, take advantage of the cloud and then compliment those applications over time with additional Azure services like storage, for example. So it really is a great on-ramp to the cloud for, for customers who have significant investments in, in Nutanix clusters on premise, >>Love the co-engineering and the ability to take advantage of those cloud native tools and capabilities, real customer value. Thanks gentlemen. Really appreciate your time. >>Thank >>You. Thank you. >>Okay. Keep it right there. You're watching Accelerate Hybrid Cloud, that journey with Nutanix and Microsoft technology on the cube. You're a leader in enterprise and emerging tech coverage.

(upbeat music) >> Hello, everyone. Welcome back to theCUBE's extended coverage. I'm John Furrier, host of theCUBE. We are here in Monaco at the Yacht Club, part of the VIP Gala with Prince Albert, DigitalBits, theCUBE. theCUBE and Prince Albert celebrating Monaco leaning into crypto. I'm here with Natasha Mahfar, who's our guest. She just came on theCUBE. Great story. Great to see you. Thanks for coming on. >> Thank you so much for having me. >> Tell the folks what you do real quick. >> Sure. So I actually started my career in Silicon Valley, like you have. And I had the idea of creating a startup in mental health that was voice based only. So it was peer to peer support groups via voice. So I created this startup, pretended to be a student at Stanford and built out a whole team, and unfortunately, at that time, no one was in the space of mental health and voice. Now, as you know, it's a $30 billion industry that's one of the biggest in Silicon Valley. So my career really started from there. And due to that startup, I got involved in the World XR Forum. Now, the World XR Forum is kind of like a mini Davos, but a little bit more exclusive, where we host entrepreneurs, people in blockchain, crypto, and we have a five day event covering all sorts of topics. So- >> When you host them, you mean like host them and they hang out and sleep over? It's a hotel? Is it an event? A workshop? >> There's workshops. We arrange hotels. We pretty much arrange everything that there is. >> It's a group get together. >> It's a group get together. Pretty much like Davos. >> And so Natasha, I wanted to talk to you about what we're passionate about which is theCUBE is bringing people up to have a voice and give them a voice. Give people a platform. You don't have to be famous. If you have something to say and share, we found that right now in this environment with media, we go out to an event, we stream as many stories, but we also have the virtual version of our studio. And I could tell you, I've found that internationally now as we bring people together, there are so many great stories. >> Absolutely. >> Out there that need to be told. And the bottleneck isn't the media, it's the fact that it's open now. >> Yes. >> So why aren't the stories coming out? So our mission is to get the stories. >> Wow. >> Scale stories. The more stories that are scaled, the more people can feel it. More people are impacted by it, and it changes the world. It gets people serendipity with data 'cause we're, you know, you shared some data about what you're working on. >> Yeah, of course. It's all about data these days. And the fact that you're doing it so openly is great because there is a need for that today, so. >> What do you see right now in the market for media? I mean, we got emerging markets, a lot of misinformation. Trust is a big problem. >> Right. >> Bullying, harassing. Smear campaigns. What's news, what's not news. I mean, how do you get your news? I mean, how do people figure out what's going on? >> No, absolutely. And this is such a pure format and a way of doing it. How did you come up with the idea, and how did you start? >> Well, I started... I realized after the Web 2.0, when social media started taking over and ruining the democratization . Blogging, podcasting, which I started in 2004, one of the first podcasts in Silicon Valley. >> Wow. >> I saw the network of that. I saw the value that people had when normal people, they call it user generated content, shared information. And I discovered something amazing that a nobody like me can have a really top podcast. >> Well, you're definitely not a nobody, but... >> Well, I was back then. And nobody knew me back then. But what it is is that even... If you put your voice out there, people will connect to it. And if you have the ability to bring other people in, you start to see a social dynamic. And what social media ruined, Facebook, Twitter, not so much Twitter 'cause Twitter's more smeary, but it's still got to open the API, LinkedIn, they're all terrible. They're all gardens. They don't really bring people together, so I think that stalled for about almost eight years or nine years. Now, with crypto and decentralization, you start to see the same thing come back. Democratization, level the playing field, remove the middle man and person, intermediate the middle bottlenecks. So with media, we found that live streaming and going to events was what the community wants. And then interviewing people, and getting their ideas out there. Not promotional, not getting paid to say stuff. Yeah, they get the plug in for the company that they're working on, that's good for everybody. But more share something that you're passionate about, data. And it works. And people like it. And we've been doing it for 12 years, and it creates a great brand of openness, community, and network effect. So we scaled up the brand to be- >> And it seems like you're international now. I mean, we're sitting in Monte Carlo, so I don't think it gets better than that. >> Well, in 2016, we started going international. 2017, we started doing stuff in Europe. 2018, we did the crypto, Middle East. And we also did London, a lot of different events. We had B2B Enterprise and Crypto Blooming. 2019, we were like, "Let's go global with staff and whatnot." >> Wow. >> And the pandemic hits. >> I know. >> And that really kind of allowed us to pivot and turn us into a virtual hybrid. And that's why we're into the metaverse, as we see the value of a physical face to face event where intimacy's there, but why aren't my friends connected first party? >> Right. How much would you say the company has grown from the time that you kind of pivoted? >> Well, we've grown in a different direction with new capabilities because the old way is over. >> Right. >> Every event right now, this event here, is in person. People are talking. They get connections. But every person that's connecting has a social graph behind them that's online too, and immediately available. And with Instagram, direct messaging, Telegram, Signal, all there. >> It's brilliant. Honestly, it was brilliant idea and a brilliant pivot. >> Thank you for interviewing me. >> Yeah, of course. (Natasha and John laugh) >> Any other questions? >> That should do it. >> Okay. Are you going to have fun tonight? >> Absolutely. >> What is your take of the Monaco scene here? What's it like? >> You know, I think it's a really interesting scene. I think there's a lot of potential because this is such an international place so it draws a very eclectic crowd, and I think there's a lot that could be done here. And you have a lot of people from Europe that are starting to get into this whole crypto, leaving kind of the traditional banks and finance behind. So I think the potential is very strong. >> Very progressive. Well, Natasha, thank you for sharing. >> Thank you so much. >> Here on theCUBE. We're the extended edition CUBE here in Monaco with Prince Albert, theCUBE, and Prince Albert, DigitalBits Al Burgio, a great market here for them. And just an amazing time. And thanks for watching. Natasha, thanks for coming on. Thanks for watching theCUBE. We'll be back with more after this break. (upbeat music)

(upbeat music) >> Hello, and welcome to theCUBE's presentation of the a AWS startup showcase, data as code is the theme. This is season two episode two of the ongoing series covering the exciting startups from the AWS ecosystem and we talk about data analytics. I'm your old John Furrier with the cube, and we have Javier De La Torre. who's the founder and chief strategy officer of Carto, which is doing some amazing innovation around geographic information systems or GIS. Javier welcome to the cube for this showcase. >> Thank you. Thank you for having me. >> So, you know, one of the things that you guys are bringing to the table is spatial analytic data that now moves into spatial relations, which is, you know, we know about geofencing. You're seeing more data coming from satellites, ground stations, you name it. Things are coming into the market from a data perspective, that's across the board and geo's one of them GIS systems. This is what you guys are doing in the rise of SQL in particular with spatial. This is a huge new benefit to the world. Can you take a minute to explain what Carto's doing and what spatial SQL is? >> Sure. Yeah. So like you said, like data, obviously we know is growing very fast and as you know now, being leveraged by many organizations in many different ways. There's one part of data, one dimension that is location. We like to say that everything happens somewhere. So therefore everything can be analyzed and understood based on the location. So we like to put an example, if all your neighbors get an alarm in their homes, the likelihood that you will get an alarm increases, right? So that's obvious we are all affected by our surroundings. What is spatial analytics, this type of analytics does is try to uncover those spacial relations so that you can model, you can predict where something is going to happen, or, you know, like, or optimize it, you know, like where else you want it to happen, right? So that's at the core of it. Now, this is something that as an industry has been done for many years, like the GIS or geographic information systems have existed for a long time. But now, and this is what Carto really brings to the table. We're looking at really the marketizing it, so that it's in the hands of any analyst, our vision is that you need to go five years, to a geography school to be able to do this type of spatial analysis. And the way that we want to make that happen is what we call with the rise of a spatial SQL. We add these capabilities around spatial analytics based on the language that is very, very popular for a analysts, which is SQL. So what we do is enables you to do this spatial analysis on top of the well known and well used SQL methods. >> It's interesting the cloud native and the cloud scale wave and now data as code has shown that the old school, the old guard, the old way of doing things, you mentioned data warehousing, okay, as one. BI tools in particular have always been limited. And the scope of the limitation was the environment was different. You have to have domain expertise, rich knowledge of the syntax. Usually it's for an application developer, not for like real time and building it into the CICD pipeline, or just from a workflow standpoint, making it available. The so-called democratization, this is where this connects. And so I got to ask you, what are you most excited about in the innovations at Carto? Can you share some of the things that people might know about or might not know about that's happening at Carto, that takes advantage of this cloud native wave because companies are now on this bandwagon. >> Yeah, no, it is. And cloud native analytics is probably the most disruptive kind of like trend that we've seen over the few years, in our particular space on the spatial it has tremendous effects on the way that we provide our service. So I'd like to kind of highlight four main reasons why cloud analytics, cloud native is super important to us. So the first one is obviously is a scalability, the working with the sizes of data that we work now in terms of location was just not possible or before. So for someone that is performing now analysis on autonomous car, or you're like that has any sensorized GPS on a device and is collecting hundreds of billions of points. If you want to do analysis on that type of data, cloud native allows you to do that in a scalable way, but it also is very cost effective. That is something that you'll see very quickly when your data grows a lot, which is that this computing storage separation, the idea that is store your data at cloud prices, but then use them with these data warehouses that we work in this private, makes for a very, very cost effective solution. But then, you know, there is other two, obviously one of them being SQL and spatial SQL that like means we like to say that SQL is becoming the lingua franca for analytics. So it's used by many products that you can connect through the usage of SQL, but I think like you coming towards why I think it's even more interesting it's like, in the cloud the concept like we all are serving, we are all living in the same infrastructure enables us that we can distribute a spatial data sets to a customer that they can join it on their database on SQL without having to move the data from one another, like in the case of Redshift or Amazon Redshift car connects and you using something called a spectrum, we can connect live to data that is stored on S3. And I think that is going to disrupt a lot the way that we think about data distributions and how cost effective it is. I think, it has a lot of your like potential on it. And in that sense what Carto is providing on top of it in the format of formats like parquet, which is a very popular with big data format. We adding geo parquet, we are specializing this big data technology for doing the spatial analysis. And that to me it is very exciting because it's putting some of the best tools at the hands of doing the space analytics for something that we're not able to do before. So to me, this is one area that I'm very, very excited. >> Well, I want to back up for a second. So you mentioned parquet and the standards around that format. And also you mentioned Redshift, so let me get this right. So you just saying that you can connect into Redshift. So I'm a customer and I have Redshift I'm using, I got my S3, I'm using Redshift for analysis. You're saying you can plug right into Redshift. >> Yes. And this is a very, very, very important part because what Carto does is leverage Redshift computing infrastructure to essentially kind of like do all the analysis. So what we do is we bring a spatial analysis where the data is, where Redshift is versus in the past, what we will do is take the data where the analysis was and that sense, it's at the core of cloud native. >> Okay. This is really where I see the exciting shift where data as code now becomes a reality is that you bring the... It redefines architecture, the script is flipped. The architecture has been redefined. You're making the data move to the environments that needs to move when it has to, if it doesn't have to move you bring compute to it. So you're seeing new kinds of use cases. So I have to ask you on the use cases and examples for Carto AWS customers with spatial analytics, what are some of the examples on how your clients are using cloud native spatial analytics or Carto? >> Yeah. So one, for example, that we've seen a lot, on the AWS ecosystem, obviously because of its suites and its position. We work together with another service in the AWS ecosystem called Amazon Location. So that actually provides you access to maps and SDKs for navigation. So it means that you are like a company that is delivering food or any other goods in the city. We have like hundreds or thousands of drivers around the city moving, doing all these deliveries. And each of these drivers they have an app and they're collecting actively their location, their position, right? So you get all the data and then it gets stored on something like a Redshift data cluster on S3 as well. There's different architectures in there, but now you essentially have like a full log of the activity that is happening on the ground from your business. So what Carto does on top of that data is you connect your data into Carto. And now you can do analysis, for example, for finding out where you user may be placed, another distribution center, you know, for optimizing your delivering routes, or like if you're in the restaurant business where you might want to have a new dark kitchen, right? So all this type of analysis based on, since I know where you're doing your operations, I can post analyze the data and then provide you a different way that you can think about solving your operation. So that's an example of a great use case that we're seeing right now. >> Talk to me about about the traditional BI tools out there, because you mentioned earlier, they lack the specific capabilities. You guys bring that to the table. What about the scalability limitations? Can you talk about where that is? Is there limitations there, obviously, if they don't have the capabilities, you can't scale that's one, but you know, as you start plugging into Redshift, scale and performance matters, what's the issue there? Can you unpack that a little bit real quick? >> Yeah. It goes back to the particulars of the spacial data, location data, like in the use case, like I was describing you very quickly are going to end up with really a lot of your like terabytes, if not petabytes of data very quickly, if you're start aggregating all this data, because it gets created by sensors. So volumes in our world kind of tends to grow a lot now. So when you work with BI tools, there's two things that you have to take in consideration. BI tools are great for seeing things like for example, if all you want to see is where your customers are, a BI tool is great. Seeing, creating a map and seeing your customers. That's totally in the world of BI. But if you want to understand why your customers are there, or where else could they be, you're going to need to perform what we call a spatial analysis. You're going to have to create a spatial model. You're going to have to, and for that BI tools will not give you that that's one side, the other it talks about the volumes that I was describing. Most of these BI tools can handle certain aggregations. Like, for example, if you are reading, if you're connecting your, let's say 10 billion data set to a BI tool, the BI tool will do some aggregations because you cannot display 10,000 rows on a BI tool and that's okay, you get aggregations and that works. But when it comes to a map, you cannot aggregate the data on the map. You actually want to see all the data on the map, and that's what Carto provides you. It allows you to make maps that sees all the data, not just aggregated by county or aggregated by other kind of like area, you see all your data on the map. >> You know, what's interesting is that location based service has been around for a long time. You know, when mobile started even hitting the scene, you saw it get better mashups, Google Maps, all this Google API mashups, things like that. You know, developers are used to it, but they could never get to the promised land on the big data side, because they just didn't have the compute. But now you add in geofencing, geo information, you now have access to this new edge like data, right? So I have to ask you on the mobile side, are you guys working with any 5G or edge providers? Because I can almost imagine that the spatial equation gets more complicated and more data full when you start blowing out edge data, like with 5G, you got more, more things happening at the edge. It's only going to fill in more data points. Can you share that's how that use case is going with mobile, mobile carriers or 5G? >> Yeah, that's totally, yeah. It's totally the case. Well, first, even before, you know, like we are there, we actually helping a lot of telcos on actually planning the 5G deployment. Where do you place your antennas is a very, very important topic when you're like talking about 5G. Because you know, like 5G networks require a lot of density. So it's a lot about like, okay, where do I start deploying my infrastructure to ensure the customers like meet, like have the best service and the places where I want to kind of like go first So like... >> You mean like the RF maps, like understanding how RF propagates. >> Well, that's one signal, but the other is like, imagine that your telco is more interested on, you know, let's say on a certain kind of like consumer profile, like young people that are using the one type of service. Well, we know where these demographics kind of lives. So you might want to start kind of like deploying your 5G in those areas, right. Versus if you go to more commercial and more kind of like residential areas, there might be other demographics. So that's one part around market analysis. Then the second part is once these 5G networks are in place, you're right. I mean, one of the premises that kind of like these news technologies give us is because the network is much smarter. You can have all these edge cases, there's much more location data that can be collected. So what we see now is a rise on the amount of what we call telemetry. That for example, the IOT space can make around location. And that's now enabled because of 5G. So I think 5G is going to be one of those trends that are going to make like more and more data coming into, I mean, more location, data available for analysis. >> So how does that, I mean, this is a great conversation because everyone can realize they're at a stadium and they see multiple bars but they can't get bandwidth. So they got a back haul problem or not enough signal. Everyone knows when they're driving their car, they know they can relate to the consumer side of it. So I get how the spatial data grows. What's the impact to Carto and specifically the cloud, because if you have more data coming in, you need the actionable insight. So I can see the use case, oh, put the antenna here. That's an actionable business decision, more content, more revenue, more happy customers, but where else is the impact to you guys and the spatial piece of it? >> Yeah. Well, I mean like there's many, many factors, right? So one of them, for example, on the telco, one of the things where we realize impact is that it gives the visibility to the operator, for example, around the quality of service. Like, okay, are my customers getting the quality of services where I want? Or like you said, like if there sitting outside a concert the quality of service in one particular area is dropping very fast. So the idea of like being able to now in real time, kind of like detect location issues, like I'm having an issue in this place. That means that then now I can act, I can drive up bandwidth, put more capacity et cetera right. So I think the biggest impact that we are seeing we are going to see on the upcoming years is that like more and more use cases going towards real time. So where, like before it was like, well, now that it has happened, I'm going to analyze it. I'm going to look at, you know, like how I could do better next time towards a more of like an industry where Carto ourselves, we are embedded in more real time type of, you know, like analytics where it's okay, if this happens, then do that, right. So it's going to be more personalized at the level that like in the code environment, it has to be art of a full kind of like pipeline kind of like type of analysis. That's already programmatically prepared to act on real time. >> That's great and it's a good segue. My next question, as more and more companies adopt cloud native analytics, what trends are you seeing out of the key to watch? Obviously you're seeing more developers coming on site, on the scene, open sources growing, what's the big cloud native analytics trends for Carto and geographic information. >> Yeah. So I think you know like the, we were talking before the cloud native now is unstoppable, but one of the things that we are seeing that is still needs to be developed and we are seeing progress is around a standardization, for example, around like data sets that are provided by different providers. What I mean with that is like, you as an organization, you're going to be responsible for your data like that you create on your cloud, right. On S3, or, you know and then you going to have a competing engine, like Redshift and you're going to have all that set up, but then you also going to have to think about like, okay, how do I ingest data from third party providers that are important for my analysis? So for example, Carto provides a lot of demographics, human mobility. we aggregate and clean up and prepare lot of spacial data so that we can then enrich your business. So for us, how we deliver that into your cloud native solution is a very important factor. And we haven't seen yet enough standardization around that. And that's one of the things, what we are pushing, you know, with the concept of geo Parquet of standardizing that body. That's one, then there is another, this is more what I like to say that you know, we are helping companies figure out their own geographies. What we mean by that is like most companies, when they start thinking about like how they interact, on the space, on the location, some of them will work like by zip codes and other by cities, they organize their operations based on a geography in a way, or technically what we call a geographic support system. Well, nowadays, like the most advance companies are defining their geographies in a continuous spectrum in what we call global grid system or spatial indexes that allows them to understand the business, not just as a set of regions, but as a continuous space. And that is now possible because of the technologies that we are introducing around spatial indexes at the cloud native infrastructure. And it provides a great a way to match data with resources and operate at scale. To me those two trends are going to be like very, very important because of the capabilities that cloud native brings to our spatial industry. >> So it changes the operation. So it's data as ops, data as code, is data ops, like infrastructures code means cloud DevOps. So I got to ask you because that's cool. Spatial index is a whole another way to think of it, rather than you go hyper local, super local, you get local zones for AWS and regions. Things are getting down to the granular levels I see that. So I have to ask you, what does data as code mean to you and what does it mean to Carto? Because you're kind of teasing at this new way because it's redefining the operation, the data operations, data engineering. So data as code is real. What does that mean to you? >> No, I think we already seeing it happening to me and to Carto what I will describe data as code is when an organization has moved from doing an analysis after the fact, like where they're like post kind of like analysis in a way to where they're actually kind of like putting analytics on their operational cycle. So then they need to really code it. They need to make these analysis, put them and insert them into the architecture bus, if you want to say of the organization. So if I get a customer, happens to be in this location, I'm going to trigger that and then this is going to do that. Or if this happens, I'm need to open up. And this is where if an organization is going to react in more real time, and we know that organizations need to drive in that direction, the only way that they can make that happen is if they operationalize analytics on their daily operations. And that can only happen with data as code. >> Yeah. And that's interesting. Look at ML ops, AI ops, people talk about that. This is data, so developers meets operations, that's the cloud, data meets code that's operations, that's data business. >> You got it. And add to that, the spacial with Carto and we go it. >> Yeah, because every piece of data now is important. And the spatial's key real quick before we close out, what is the index thing? Explain the benefit real quick of a spatial index. >> Yes. So the spatial index is well everybody can understand how we organize societies politically, right? Our countries, you have like states and then you have like counties and you have all these different kind, what we call administrative boundaries, right? That's a way that we organize information too, right? A spatial index is when you divide the world, not in administrative boundaries, but you actually make a grid. Imagine that you just essentially make a grid of the world. right? And you make that grid so that in every cell you can then split it into, let's say for example, four more cells. So you now have like an organization. You split the world in a grid that you can have multiple resolutions think like Google maps when you see the entire world, but you can zoom in and you end up seeing, you know, like one particular place, so that's one thing. So what a spatial indexes allows you is to technically put, you know like your location, not based coordinate, but actually on one grid place on an index. And we use that then later to correlate, let's say your data with someone else data, as we can use what we call this spatial indexes to do joints very, very fast and we can do a lot of operations with it. So it is a new way to do spatial computing based on this type of indexes, but for more than anything for an organization, what spatial index allows is that you don't need to work on zip codes or in boundaries on artificial boundaries. I mean, your customer doesn't change because he goes from this place to the road, to the other side of the road, this is the same place. It's an arbitrary in location. It's a spatial index break out all of that. You're like you break with your zip codes, you break. And you essentially have a continuous geography, that actually is a much closer look up to the reality. >> It's like the forest and the trees and the bark of the tree. (Javier laughing) You can see everything. >> That's it, you can get a look at everything. >> Javi, great to have you on. In real quick closing give a quick plug for the company, summarize what you do, what you're looking into, how many people you got, when you're hiring, what's the key goals for the company? >> Yeah, sure. So Carto is a company, now we are around 200 people. Our vision is that spatial analytics is something that every organization should do. So we really try to enable organizations with the best data and analysis around spatial. And we do all that cloud native on top of your data warehouse. So what we are really in enabling these organizations is to take that cloud native approach that they're already embracing it also to spatial analysis. >> Javi, founder, chief strategy officer for Carto. Great to have you on data as code, all data's real, all data has impact, operational impact with data is the new big trend. Thanks for coming on and sharing the company story and all your key innovations. Thank you. >> Thanks to you. >> Okay. This is the startup showcase. Data as code, season two episode two of the ongoing series. Every episode will explore new topics and new exciting companies pioneering this next cloud native wave of innovation. I'm John Furrier, your host of theCUBE. Thanks for watching. (upbeat music)

>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Every CEO is figuring out the right balance for new hybrid business models. Now, regardless of the chosen approach, which is going to vary, technology executives, they understand they have to accelerate their digital and build resilience as well as optionality into their platforms. Now, this is driving a dramatic shift in IT investments. And at the macro level, we expect total spending to increase at as much as 8% or even more in 2021, compared to last year's contraction. Investments in cybersecurity, cloud collaboration that are enabling hybrid work as well as data, including analytics, AI, and automation are at the top of the spending priorities for CXOs. Hello everyone. And welcome to this week's Wiki Bond Cube insights, powered by ETR. In this Breaking Analysis, we're pleased to welcome back Erik Bradley, who is the chief engagement strategist at our partner, ETR. Now in this segment, we're going to share some of the latest findings from ETR's surveys and provide our commentary on what it means for the markets, for sellers, and for buyers. Erik, great to see you, my friend. Welcome back to Breaking Analysis. >> Thank you for having me, always enjoy it. We've got some fresh data to talk about on this beautiful summer Friday, so I'm ready to go. >> All right. I'm excited too. Okay, last year we saw a contraction in IT spending by at least 5%. And now we're seeing a snapback to, as I said, at least 8% growth relative to last year. You got to go back to 2007 just before the financial crisis to see this type of top line growth. The shift to hybrid work, it's exposed us to new insidious security threats. And we're going to discuss that in a lot more detail. Cloud migration of course picked up dramatically last year, and based on the recent earnings results of the big cloud players, for now we got two quarters of data, that trend continues as organizations are accelerating their digital platform build-outs, and this is bringing a lot of complexity and a greater need for so-called observability solutions, which Erik is going to talk about extensively later on in this segment. Data, we think is entering a new era of de-centralization. We see organizations not only focused on analytics and insights, but actually creating data products. Leading technology organizations like JP Morgan, they're heavily leaning into this trend toward packaging and monetizing data products. And finally, as part of the digital transformation trend, we see no slow down in spending momentum for AI and automation, generally in RPA specifically. Erik, anything you want to add to that top level narrative? >> Yeah, there's a lot to take on the macro takeaways. The first thing I want to state is that that 8, 8.5% number that started off at just 3 to 4% beginning of the year. So as the year has continued, we are just seeing this trend in budgets continue to accelerate, and we don't have any reason to believe that's going to stop. So I think we're going to just keep moving on heading into 2021. And we're going to see a banner year of spend this year and probably next as well. >> All right, now we're going to bring up a chart that shows kind of that progression here of spending momentum. So Erik, I'm going to let you comment on this chart that tracks those projections over time. >> Erik: Yeah. Great. So thank you very much for pulling this up. As you can see in the beginning part of the year, when we asked people, "What do you plan to spend throughout 2021?" They were saying it would be about a 4% increase. Which we were happy with because as you said last year, it was all negative. That continues to accelerate and is only hyper accelerating now as we head into the back half of the year. In addition, after we do this data, I always host a panel of IT end users to kind of get their feedback on what we collected, to a man, every one of them expects continued increase throughout next year. There are some concerns and uncertainty about what we're seeing right now with COVID, but even with that, they're planning their budgets now for 2022 and they're planning for even further increases going forward. >> Dave: Great, thank you. So we circled that 8%. That's really kind of where we thought it was going to land. And so we're happy with that number, but let's take a look at where the action is by technology sector. This chart that we're showing you here, it tracks spending priorities back to last September. When I believe that was the point, Erik, that cyber became the top priority in the survey, ahead of cloud collaboration, analytics, and data, and the other sectors that you see there. Now, Erik, we should explain. These areas, they're the top seven, and they outrank all the other sectors. ETR tracks many, many other sectors, but please weigh in here and share your thoughts on this data. >> Erik: Yeah. Security, security, security. It hasn't changed. It had really hasn't. The hybrid work. The fact that you're behind the firewall one day and then you're outside working from home the next, switching in and out of networks. This is just a field day for bad actors. And we have no choice right now, but to continue to spend, because as you're going to talk about in a minute, hybrid's here to stay. So we have to figure out a way to secure behind the firewall on-prem. We also have to secure our employees and our assets that are not in the office. So it is a main priority. One of the things that point out on this chart, I had a couple of ITN users talk to me about customer experience and automation really need to move from the right part of that chart to the left. So they're seeing more in what you were talking about in RPA and automation, starting to creep up heading into next year. As cloud migration matures, as you know, cybersecurity spending has been ramping up. People are going to see a little bit more on the analytics and a little bit more on the automation side going forward. >> Dave: Great. Now, this next data view- well, first of all, one of the great things about the ETR dataset is that you can ask key questions and get a time series. And I will tell you again, I go back to last March, ETR hit it. They were the first on the work from home trend. And so if you were on that trend, you were able to anticipate it. And a lot of investors I think took advantage of that. Now, but we've shown this before, but there's new data points that we want to introduce. So the data tracks how CIOs and IT buyers have responded to the pandemic since last March. Still 70% of the organizations have employees working remotely, but 39% now have employees fully returning to the office and Erik, the rest of the metrics all point toward positives for IT spending, although accelerating IT deployments there at the right peaked last year, as people realized they had to invest in the future. Your thoughts? >> Erik: Yeah, this is the slide for optimism, without a doubt. Of the entire macro survey we did, this is the most optimistic slide. It's great for overall business. It's great for business travel. This is well beyond just IT. Hiring is up. I've had some people tell me that they possibly can't hire enough people right now. They had to furlough employees, they had to stop projects, and they want to re accelerate those now. But talent is very hard to find. Another point to you about your automation and RPA, another underlying trend for there. The one thing I did want to talk about here is the hybrid workplace, but I believe there's another slide on it. So just to recap on this extremely optimistic, we're seeing a lot of hiring. We're seeing increased spending, and I do believe that that's going to continue. >> Yeah I'm glad you brought that up because a session that you and I did a while ago, we pointed out, it was earlier this year, that the skill shortage is one potential risk to our positive scenario. We'll keep an eye on that, but so I want to show another set of data that we've showed previously, but ETR again, has added some new questions in here. So note here that 60% of employees still work remotely with 33% in a hybrid model currently, and the CIO's expect that to land on about 42% hybrid workforce with around 30% working remotely, which is around, it's been consistent by the way on your surveys, but that's about double the historic norm, Eric. >> Erik: Yeah, and even further to your point Dave, recently I did a panel asking people to give me some feedback on this. And three of those four experts basically said to me, if we had greed run this survey right now, that even more people would be saying remote. That they believe that that number, that's saying they're expecting that number of people to be back in office, is actually too optimistic. They're actually saying that maybe if we had- cause as a survey launched about six, seven weeks ago before this little blip on the radar, before the little COVID hiccup we're seeing now, and they're telling me that they believe if we reran this now that it would be even more remote work, even more hybrid and less returned to the office. So that's just an update I wanted to offer on this slide. >> Dave: Yeah. Thank you for that. I mean, we're still in this kind of day to day, week to week, month to month mode, but I want to do a little double click on this. We're not going to share this data, but there was so much ETR data. We got to be selective. But if you double click on the hybrid models, you'll see that 50% of organizations plan to have time roughly equally split between onsite and remote with again around 30 or 31% mostly remote, with onsite space available if they need it. And Erik, very few don't plan to have some type of hybrid model, at least. >> Yeah, I think it was less than 10% that said it was going to be exclusively onsite. And again, that was a more optimistic scenario six, seven weeks ago than we're seeing right now throughout the country. So I agree with you, hybrid is here to stay. There really is no doubt about it. from everyone I speak to when, you know, I basically make a living talking to IT end users. Hybrid is here to stay. They're planning for it. And that's really the drive behind the spending because you have to support both. You have to give people the option. You have to, from an IT perspective, you also have to support both, right? So if somebody is in office, I need the support staff to be in office. Plus I need them to be able to remote in and fix something from home. So they're spending on both fronts right now. >> Okay. Let's get into some of the vendor performance data. And I want to start with the cloud hyperscalers. It's something that we followed pretty closely. I got some Wiki bond data, that we just had earnings released. So here's data that shows the Q2 revenue shares on the left-hand side in the pie and the growth rates for the big four cloud players on the right hand side. It goes back to Q1 2019. Now the first thing I want to say is these players generated just under $39 billion in the quarter with AWS capturing 50% of that number. I said 39, it was 29 billion, sorry, with AWS capturing 50% of that in the quarter. As you're still tracking around a third in Alibaba and GCP in the, you know, eight or 9% range. But what's most interesting to me, Erik, is that AWS, which generated almost 15 billion in the quarter, was the only player to grow its revenue, both sequentially and year over year. And Erik, I think the street is missing the real story here on Amazon. Amazon announced earnings on Thursday night. The company had a 2% miss on the top line revenues and a meaningful 22% beat on earnings per share. So the retail side of the business missed its revenue targets, so that's why everybody's freaked out. But AWS, the cloud side, saw a 4% revenue beat. So the stock was off more than 70% after hours and into Friday. Now to me, a mix shift toward AWS, that's great news for investors. Now, tepid guidance is a negative, but the shift to a more profitable cloud business is a huge positive. >> Yeah, there's a lot that goes into stock price, right? I remember I was a director of research back in the day. One of my analysts said to me, "Am I crazy for putting a $1,000 target on Amazon?" And I laughed and I said, "No, you're crazy if you don't make it $2,000." (both chuckling) So, you know, at that time it was basically the mix shift towards AWS. You're a thousand percent right. I think the tough year over year comps had something to do with that reaction. That, you know, it's just getting really hard. What's that? The law of large numbers, right? It's really hard to grow at that percentage rate when you're getting this big. But from our data perspective, we're seeing no slowdown in AWS, in cloud, none whatsoever. The only slowdown we're seeing in cloud is GCP. But to, you know, to focus on AWS, extremely strong across the board and not only just in cloud, but in all their data products as well, data and analytics. >> Yeah and I think that the AWS, don't forget folks, that funds Amazon's TAM expansion into so many different places. Okay. As we said at the top, the world of digital and hybrid work, and multi-cloud, it's more complicated than it used to be. And that means if you need to resolve issues, which everybody does, like poor application performance, et cetera, what's happening at the user level, you have to have a better way to sort of see what's going on. And that's what the emergence of the observability space is all about. So Erik, let me set this up and you have a lot of comments here because you've recently had some, and you always have had a lot of round table discussions with CXOs on this topic. So this chart plots net score or spending momentum on the vertical axis, and market share or pervasiveness in the dataset on the horizontal axis. And we inserted a table that shows the data points in detail. Now that red dotted line is just sort of Dave Vellante's subjective mark in the sand for elevated spending levels. And there are three other points here. One is Splunk as well off is two-year peak, as highlighted in the red, but Signal FX, which Splunk acquired, has made a big move northward this last quarter. As has Datadog. So Erik, what can you share with us on this hot, but increasingly crowded space? >> Yeah. I could talk about the space for a long time. As you know, I've gotten some flack over the last year and a half about, you know, kind of pointing out this trend, this negative trend in Splunk. So I do want to be the first one to say that this data set is rebounding. Splunk has been horrific in our data for going back almost two years now, straight downward trend. This is the first time we're seeing any increase, any positivity there. So I do want to be fair and state that because I've been accused of being a little too negative on Splunk in the past. But I would basically say for observability right now, it's a rising tide lifts all boats, if I can use a New England phrase. The data across the board in analytics for these observability players is up, is accelerating. None more so than Datadog. And it's exactly your point, David. The complexity, the increased cloud migration is a perfect setup for Datadog, which is a cloud native. It focuses on microservices. It focuses on cloud observability. Old Splunk was just application monitoring. Don't get me wrong, they're changing, but they were on-prem application monitoring, first and foremost. Datadog came out as cloud native. They, you know, do microservices. This is just a perfect setup for them. And not only is Datadog leading the observability, it's leading the entire analytics sector, all of it. Not just the observability niche. So without a doubt, that is the strongest that we're seeing. It's leading Dynatrace new Relic. The only one that really isn't rebounding is Cisco App Dynamics. That's getting the dreaded legacy word really attached to it. But this space is really on fire, elastic as well, really doing well in this space. New Relic has shown a little bit of improvement as well. And what I heard when I asked my panelists about this, is that because of the maturity of cloud migration, that this observability has to grow. Spending on this has to happen. So they all say the chart looks right. And it's really just about the digital transformation maturity. So that's largely what they think is happening here. And they don't really see it getting, you know, changing anytime soon. >> Yeah, and I would add, and you see that it's getting crowded. You saw a service now acquired LightStep, and they want to get into the game. You mentioned, you know, last deck of the elk stack is, you know, the open source alternative, but then we see a company who's raised a fair amount of money, startup, chaos search, coming in, going after kind of the complexity of the elk stack. You've got honeycomb, which has got a really innovative approach, Jeremy Burton's company observes. So you have venture capital coming in. So we'll see if those guys could be disruptive enough or are they, you know, candidates to get acquired? We'll see how that all- you know that well. The M and A space. You think this space is ripe for M and A? >> I think it's ripe for consolidation, M and A. Something has to shake out. There's no doubt. I do believe that all of these can be standalone. So we shall see what's happened to, you mentioned the Splunk acquisition of Signal FX, just a house cleaning point. That was really nice acceleration by Signal FX, but it was only 20 citations. We'd looked into this a little bit deeper. Our data scientists did. It appears as if the majority of people are just signaling spunk and not FX separately. So moving forward for our data set, we're going to combine those two, so we don't have those anomalies going forward. But that type of acquisition does show what we should expect to see more of in this group going forward. >> Well that's I want to mention. That's one of the challenges that any data company has, and you guys do a great job of it. You're constantly having to reevaluate. There's so much M and A going on in the industry. You've got to pick the right spots in terms of when to consolidate. There's some big, you know, Dell and EMC, for example. You know, you've beautifully worked through that transition. You're seeing, you know, open shift and red hat with IBM. You just got to be flexible. And that's where it's valuable to be able to have a pipeline to guys like Erik, to sort of squint through that. So thank you for that clarification. >> Thank you too, because having a resource like you with industry knowledge really helps us navigate some of those as well for everyone out there. So that's a lot to do with you do Dave, >> Thank you. It's going to be interesting to watch Splunk. Doug Merritt's made some, you know, management changes, not the least of which is bringing in Teresa Carlson to run go to market. So if you know, I'd be interested if they are hitting, bouncing off the bottom and rising up again. They have a great customer base. Okay. Let's look at some of the same dimensions. Go ahead. You got a comment? >> A few of ETR's clients looked at our data and then put a billion dollar investment into it too. So obviously I agree. (Dave laughing) Splunk is looking like it's set for a rebound, and it's definitely something to watch, I agree. >> Not to rat hole in this, but I got to say. When I look back, cause theCUBE gives us kind of early visibility. So companies with momentum and you talk to the customers that all these shows that we go to. I will tell you that three companies stood out last decade. It was Splunk. It was Service Now and Tableau. And you could tell just from just discussions with their customers, the enthusiasm in that customer base. And so that's a real asset, and that helps them build them a moat. So we'll see. All right, let's take a look at the same dimensions now for cyber. This is cybersecurity net score in the vertical, and market share in the horizontal. And I filtered by in greater than a hundred shared in because just gets so crowded. Erik, the only things I would point out here is CrowdStrike and Zscaler continue to shine, CyberArk also showing momentum over that 40% line. Very impressively, Palo Alto networks, which has a big presence in the market. They've bounced back. We predicted that a while back. Your round table suggested people like working with Palo Alto. They're a gold standard. You know, we had reported earlier on that divergence with four to net in terms of valuation and some of the challenges they had in cloud, clearly, you know, back with the momentum. And of course, Microsoft in the upper, right. It's just, they're literally off the charts and obviously a major player here, but your thoughts on cyber? >> Erik: Yeah. Going back to the backdrop. Security, security, security. It has been the number one priority going back to last September. No one sees it changing. It has to happen. The threat vectors are actually expanding and we have no choice but to spend here. So it is not surprising to see. You did name our three favorite names. So as you know, we look at the dataset, we see which ones have the most positive inflections, and we put outlooks on those. And you did mention Zscaler, Okta and CrowdStrike, by far the three standouts that we're seeing. I just recently did a huge panel on Okta talking about their acquisition of Auth Zero. They're pushed into Sale Point space, trying to move just from single sign on and MFA to going to really privileged account management. There is some hurdles there. Really Okta's ability to do this on-prem is something that a little bit of the IT end users are concerned about. But what we're seeing right now, both Okta and Auth Zero are two of the main adopted names in security. They look incredibly well set up. Zscaler as well. With the ZTNA push more towards zero trust, Zscaler came out so hot in their IPO. And everyone was wondering if it was going to trail off just like Snowflake. It's not trailing off. This thing just keeps going up into the right, up into the right. The data supports a lot of tremendous growth for the three names that you just mentioned. >> Yeah. Yeah. I'm glad you brought up Auth Zero. We had reported on that earlier. I just feel like that was a great acquisition. You had Okta doing the belly to belly enterprise, you know, selling. And the one thing that they really lacked was that developer momentum. And that's what Auth Zero brings. Just a smart move by Todd McKinnon and company. And I mean, so this, you know, I want to, I want to pull up another chart show a quick snapshot of some of the players in the survey who show momentum and have you comment on this. We haven't mentioned Snowflake so far, but they remain again with like this gold standard of net score, they've consistently had those high marks with regard to spending velocity. But here's some other data. Erik, how should we interpret this? >> Erik: Yeah, just to harp on Snowflake for a second. Right, I mean the rich get richer. They came out- IPO was so hyped, so it was hard for us as a research company to say, "Oh, you know, well, you know, we agree." But we did. The data is incredible. You can't beat the management team. You can't beat what they're doing. They've got so much cash. I can't wait to see what they do with it. And meanwhile, you would expect something that debuted with that high of a net score, that high of spending velocity to trail off. It would be natural. It's not Dave, it's still accelerating. It's gone even higher. It's at all time highs. And we just don't see it stopping anytime soon. It's a really interesting space right now. Maybe another name to look at on here that I think is pretty interesting, kind of a play on return to business is Kupa. It's a great project expense management tool that got hit really hard. Listen, traveling stopped, business expense stopped, and I did a panel on it. And a lot of our guys basically said, "Yeah, it was the first thing I cut." But we're seeing a huge rebound in spending there in that space. So that's a name that I think might be worth being called out on a positive side. Negative, If you look down to the bottom right of that chart, unfortunately we're seeing some issues in RingCentral and Zoom. Anything that's sort of playing in this next, you know, video conferencing, IP telephony space, they seem to be having really decelerating spending. Also now with Zoom's acquisition of five nine. I'm not really sure how RingCentral's going to compete on that. But yeah, that's one where we debuted for the first time with a negative outlook on that name. And looking and asking to some of the people in our community, a lot of them say externally, you still need IP telepany, but internally you don't. Because the You Cast communication systems are getting so sophisticated, that if I have Teams, if I have Slack, I don't need phones anymore. (chuckling) That you and I can just do a Slack call. We can do a Teams call. And many of them are saying I'm truly ripping out my IP Telepany internally as soon as possible because we just don't need it. So this whole collaboration, productivity space is here to stay. And it's got wide ranging implications to some of these more legacy type of tools. >> You know, one of the other things I'd call out on this chart is Accenture. You and I had a session earlier this year, and we had predicted that that skill shortage was going to lead to an uptick in traditional services. We've certainly seen that. I mean, IBM beat its quarter on the strength of services largely. And seeing Accenture on that is I think confirmation. >> Yeah that was our New Year prediction show, right Dave? When we made top 10 predictions? >> That's right. That was part of our predictions show. Exactly, good memory. >> The data is really showing that continue. People want the projects, they need to do the projects, but hiring is very difficult. So obviously the number one beneficiary there are going to be the Accentures of the world. >> All right. So let's do a quick wrap. I'm going to make a few comments and then have you bring us home, Erik. So we laid out our scenario for the tech spending rebound. We definitely believe last year tracked downward, along with GDP contraction. It was interesting. Gardner doesn't believe, at least factions of Gardner don't believe there's a correlation between GDP and tech spending. But, you know, I personally think there generally is some kind of relatively proportional pattern there. And I think we saw contraction last year. People are concerned about inflation. Of course, that adds some uncertainty. And as well, as you mentioned around the Delta variant. But I feel as though that the boards of directors and CEOs, they've mandated that tech execs have to build out digital platforms for the future. They're data centric. They're highly automated, to your earlier points. They're intelligent with AI infused, and that's going to take investment. I feel like the tech community has said, "Look, we know what to do here. We're dealing with hybrid work. We can't just stop doing what we're doing. Let's move forward." You know, and as you say, we're flying again and so forth. You know, getting hybrid right is a major priority that directly impacts strategies. Technology strategies, particularly around security, cloud, the productivity of remote workers with collaboration. And as we've said many times, we are entering a new era of data that's going to focus on decentralized data, building data products, and Erik let's keep an eye on this observability space. Lot of interest there, and buyers have a number of choices. You know, do they go with a specialist, as we saw recently, we've seen in the past, or did they go with the generalist like Service Now with the acquisition of LightStep? You know, it's going to be interesting. A lot of people are going to get into this space, start bundling into larger platforms. And so as you said, there's probably not enough room for all the players. We're going to see some consolidation there. But anyway, let me give you the final word here. >> Yeah, no, I completely agree with all of it. And I think your earlier points are spot on, that analytics and automation are certainly going to be moving more and more to that left of that chart we had of priorities. I think as we continue that survey heading into 2022, we'll have some fresh data for you again in a few months, that's going to start looking at 2022 priorities and overall spend. And the one other area that I keep hearing about over and over and over again is customer experience. There's a transition from good old CRM to CXM. Right now, everything is digital. It is not going away. So you need an omni-channel support to not only track your customer experience, but improve it. Make sure there's a two way communication. And it's a really interesting space. Salesforce is going to migrate into it. We've got Qualtrics out there. You've got Medallia. You've got FreshWorks, you've got Sprinkler. You got some names out there. And everyone I keep talking to on the IT end user side keeps bringing up customer experience. So let's keep an eye on that as well. >> That's a great point. And again, it brings me back to Service Now. We wrote a piece last week that's sort of, Service Now and Salesforce are on a collision course. We've said that for many, many years. And you've got this platform of platforms. They're just kind of sucking in different functions saying, "Hey, we're friends with everybody." But as you know Erik, software companies, they want to own it all. (both chuckling) All right. Hey Erik, thank you so much. I want to thank you for coming back on. It's always a pleasure to have you on Breaking Analysis. Great to see you. >> Love the partnership. Love the collaboration. Let's go enjoy this summer Friday. >> All right. Let's do. Okay, remember everybody, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast, click subscribe to the series. Check out ETR's website at etr.plus. They've just launched a new website. They've got a whole new pricing model. It's great to see that innovation going on. Now remember we also publish a full report every week on WikiBond.com and SiliconAngle.com. You can always email me, appreciate the back channel comments, the metadata insights. David.Vellante@SiliconAngle.com. DM me on Twitter @DVellante or comment on the LinkedIn posts. This is Dave Vellante for Erik Bradley and theCUBE insights powered by ETR. Have a great week, a good rest of summer, be well. And we'll see you next time. (inspiring music)

(upbeat music) >> Narrator: From the CUBE studios in Palo Alto, in Boston connecting with thought leaders all around the world, this is theCUBE Conversation. >> Well, there's no question these days that in the world of business, it's all about data. Data is the king. How you harvest data, how you organize your data, how you distribute your data, how you secure your data, all very important questions. And certainly a leader in the data replication business is HVR. We're joined now by their CEO, Anthony Brooks-Williams, and by Diwakar Goel, who is the Global Chief Data Officer at GE. We're going to talk about, you guessed it, data. Gentlemen, thanks for being with us. Good to have you here on theCUBE Conversation. >> Thank you. Thanks, John. >> Yeah, well, listen, >> Thanks, John. >> first off, let's just characterize the relationship between the two companies, between GE and HVR. Maybe Diwakar, let's take us back to how you got to HVR, if you will and maybe a little bit about the evolution of that relationship, where it's gone from day one. >> No, absolutely. It's now actually a long time back. It's almost five and a half years back, that we started working with Anthony. And honestly it was our early days of big data. We all had big, different kind of data warehousing platforms, but we were transitioning into the big data ecosystem and we needed a partner that could help us to get more of the real-time data. And that's when we started working with Anthony. And I would say, John, over the years, you know we have learned a lot and our partnership has grown a lot. And it's grown based on the needs. When we started, honestly just being able to replicate a lot sources and to give you context like GBG, we have the fifth largest Oracle ERP. We have the seventh largest SAP ERP. They just, just by the nature of just getting those systems in was a challenge. And we had to work through different, different solutions because some of the normal ones wouldn't work. As we got matured, and we started using data over the last two, three years, specifically, we had different challenges. The challenges was like, you know is the data completely accurate? Are we losing and dropping some data? When you're bringing three billion, five billion rows of data, every five to six hours, even if you've dropped 1% you've lost like a huge set of insights, right? So that's when you started working with Anthony more around like the nuances as to, you know what could be causing us to lose some data, or duplicate some datasets, right? And I think our partnership's been very good, because some of our use cases have been unique and we've continuously pushed Anthony and the team to deliver that. With the light of, you know these use cases are not unique, in some cases we were just ahead, just by the nature of what we were handling. >> Okay. Anthony, about then the HVR approach, Diwakar, just took us through somewhat higher level of how this relationship has evolved. It's started with big data, now, it's gone (mumbles) in terms of even fine tuning the accuracy, that's so important. Latency is obviously a huge topic too from your side of the fence. But how do you address it then? Let's take GE for example, in terms of understanding their business, learning their business, their capabilities, maybe where their holes are, you know where their weaknesses were, and showing that up. How did you approach that from the HVR side? >> Yeah. Do you mean wanting back a few years? I mean, obviously it starts, you get in there, you find an initial use case and that was moving data into a certain data warehouse platform, whether it be around analytics or reporting such as Diwakar mentioned. And that's, I mean, most commonly what we see from a lot of customers. It's, the typical use case is real-time analytics, and moving the data to an area for consolidated reporting. It's either most (indistinct) in these times, it's in the cloud. But GE you know, where that's evolved and GE are a top customer for us. We work across many of their business units of their different BUS. GE had another arm Predix, which is the industrial IOT platform that actually OEM must as well for a solution they sell to other companies in the space. But where we've worked with GE is, you know the ability one, just to support the scale, the complexity, the volume of data, many different sources systems, many different BUS, whether it be, you know, their aviation division or our divisions, or those types, to sending that data across. And the difference being as well where we've really pushed us and Diwakar and team pushed us is around the accuracy to the exact point that Diwakar mentions. This study is typically financial data. This is data that they run their business off. This is data that the executing CEOs get dashboards on a daily basis. It can't be wrong. You may not only do businesses these days, you want to make decisions on the freshest data that they can, and specifically over the last year, because that's a matter about survival. Not only is it about winning, it's about survival and doing business in the most cost-effective way. But then that type of data, that we're moving, the financial data, the financial data lags we built for GE that is capturing this out of SAP systems, where we have some other features benefits, you know that's where that really pushed us around the accuracy. And that's whereby you mean, you can't really, these, you can't ever, but especially these days, have a typical just customer tab vendor approach. It has to be a partnership. And that was one other thing Diwakar and I spoke a while ago. It was about, how do we really push and develop a partnership between the two companies, between the two organizations? And that's key. And that's where we've been pushed. And there's much new things we're working on for them based on where they are going as a business, whether it be different sources, different targets. And so that's where it's worked out well for both companies. >> So Diwakar, about the margin of error then, in terms of accuracy, 'cause I'm hearing from Anthony that this is something you really pushed them on, right? You know, and 96, 97%, doesn't cut it, right? I mean, you can't be that close. It's got to be spot on. At what point in your data journey, if you will, did it come to roost that the accuracy, you know had to improve or, you know you needed a solution that would get you where you needed to operate your various businesses? >> I think John, it basically stems down to a broader question. You know, what are you using the data for? You know, a lot of us, when we're starting this journey we want to use the data for a lot of analytical use cases. And that basically means you want to look at a broad pattern and say, okay, you know what, do I have a significant amount of inventory sitting on one plant? Or, you know, is there a bigger problem with how I'm negotiating with a vendor, and I want to change that? And for those use cases, you know getting good enough data gives you an indicator as to how do you want to work with them, right? But when you want to take your data to a far more fidelity and more critical processes, whether, you know you're trying to capture from an airplane, the latest signal, and if you had five more signal, perhaps you solve the mystery of the Malaysian Med Sync plan, or when you're trying to solve and report on your financials, right? Then the fidelity and the accuracy of data has to be spot on. And what you realize is, you know you unlock a certain set of value with analytical use cases. But if you truly want to unlock what can be done with big data, you have to go at the operational level, you have to run your business using the data real-time. It's not about like, you know, in hindsight, how can I do things better? If I want to make real-time decisions on, you know, how, what I need to make right now, what's my healthcare indicator suggesting, how do I change the dosage for a customer or a patient, right? It has to be very operational. It has to be very accurate. And that margin of error then almost becomes zero, because you are dealing with things. If you go wrong you can cost lives, right? So that's where we are. And I think honestly being able to solve that problem has now opened up a massive door of what all we can do with data. >> Yeah. Yeah, man. I think I would just build on that as well. I mean, one, it's about us as a company. We are in the data business, obviously. Sources and targets. I mean that's the table stakes stuff. What do we support? It's our ability to bridge these modern environments and the legacy environments, that we do. And you see that across all organizations. A lot of their data source sits in these legacy top environments, but that will transition to other either target systems or the new world ones that we see, more modern bleeding edge environments. So we have to support those but they're not the same time. It's building on the performance, the accuracy of the total product, versus just being able to connect the data. And that's where we get driven down the path with companies like GE, with Diwakar. And they've pushed us. But it's really bridging those environments. >> You know, it also seems like with regard to data that you look at this almost like a verb tense, what happened, what is happening, what will happen, right? So in looking at it to that person, Diwakar, if you will, in terms of the kind of information that you can glean from this vast repository of data as opposed to, you know, what did happen, what's going on right now, and then what can we make happen down the road? Where does HVR factor into that for you in terms of not only, you know, making those, having those kinds of insights, but also making sure that the right people within your organization have access to the information that they need. And maybe just, they only need. >> No, you're right, John. It's funny, you're using a different analogy but I keep referring to as taillights versus headlights, right? Gone are the days you can refer back as to what's happening. You need to just be able to look forward, right? And I think real-time data too is no longer a question or believe, it's a necessity. And I think one of the things we often miss out is real-time data is actually a very collaborative piece of how it brings the various operators together. Because in the past, if you think, if you just go a little bit old school, people will go and do their job. And then they will come back and submit what they did, right? And then you will accumulate what everybody did and make sense out of it. Now, as people are doing things live, you are hearing about it. So for example, if I am issuing payments across different, different places I need to know how much balance I need to keep in the bank, it's the simplest example, right? Now I can keep the math, I can always stack my bank with a ton of money, then I'm losing money because now I'm blocking my money. And especially now, if you think about GE which has 6,000 bank account. If I keep stacking it, I will practically go bankrupt, right? So if I have an inference of what's happening every time a payment card issued by anybody, I am knowing it real-time. It allows me to adjust for optimal liquidity. As simple as it sounds, it saves you a hundred billion dollars if you do it right, in a year, right? So I think it is just fundamentally changes. We need to think about real-time data is no longer, it's just how you need to operate. It's no longer an option. >> Yeah. You may, we see, what we've seen as posture, we were fortunate. We had a great 2020. Just under a hundred percent year-over-year growth. Why? It's about the immediacy of data, so that they can act accordingly. You mean these days, it's table stakes. You mean, it's about winning and, or just surviving compared to, you know, years ago when day old data, week old data, that was okay. You mean, then largely these legacy type (mumbles) technologies, well it was fine. It's not anymore. You mean exactly what Diwakar was saying. It's table stakes. It's just what, that's what it is. >> And I think John, in fact, I see actually it's getting further pushed out, right? Because what happens is I get real-time data from HVR but then I'm actually doing some stuff to get real-time insights after that. And there is a lag from that time to when I'm actually generating insights on which I'm acting on. Now, there is more and more of a need that how do I even shorten that cycle time, right? I actually, from it, we are getting, not only data when it's getting refresh, I actually get signals when I need to add something. So I think in fact, the need of the future is going to be also far more event-driven, where every time something happens that I need to act on, how can technologies like HVR even help you with understanding those? >> Anthony: Yes. >> Anthony, what does scale do to all this? Diwakar touched on it briefly about accuracy and all of a sudden, if you know, if you have a, if you've got a, you know a small discrepancy on a small dataset, no big deal, right? But all of a sudden, if there are issues down the road and you're talking about, you know, millions and millions and millions of inputs, now we've got a problem. So just in terms of scale and with an operation the size of GE, what kind of impacts does that have? >> Yeah. Massive. You mean, it's part of the reason why we went, why we've been successful. We have the ability to scale very well from this highly distributed architecture that we have. And so that's what's been, you know, fortunate for us over the last year, as we know. What does the stat mean? 90% of the world's data was generated over the last two years or something like that. And that just feeds into more, human scale is key. Not only complexity at scale is a key thing, and that's where we've been fortunate to set ourselves apart on that space. I mean we, GE push us and challenge us on a daily basis. The same we do with another company, the biggest online e-commerce platform, massive scale, massive scale. Then that's, we get pushed the whole time and get pushed to improve all the time. But fortunately we have a very good solution that fits into that, but it's just, and I think it just doesn't get, worse is the wrong word. It's just, it's going to continue to grow. The problem is not going away. You know, the volumes are going to increase massively. >> So Diwakar, if I could, before we wrap up here, I'm just curious from your, if you put on your forward-thinking glasses right now, in terms of the data capabilities that HVR has provided you, are they driving you to different kinds of horizons in terms of your business strategy or are your business strategies driving the data solutions that you need? I mean, which way is it right now in terms of how you are going to expand your services down the road? >> It's an interesting question. I think, and Anthony keep correcting me on this one, but today, you know because if you think about big data solutions, right? They were largely designed for a different world historically. They were designed for our IOT parametric set of data sets in different kind of world. So there was a big catch up that a lot of these companies had to do to make it relevant even for the other relational data sets, transactional data sets and everything else, right? So a big part of what I feel like Anthony and other companies have been focusing on is really making this relevant for that world. And I feel like companies like HVR are now absolutely there. And as they are there they are now starting to think about solving or I would say focusing on people who are early in their stage, and how can they get them up and quick, you know, efficient early, because that's a lot of the challenges, right? So I would say, I don't know if Anthony's focuses me in, right? So it should not be me, but it's, I think like where they're going, for example like how do they connect with all the different cloud vendors? So when a company wants to come live and if they're using data from, you know the HR Workday solution or Concord Travel solution, they can just come pitch. We are plug and play. And say, okay, enable me data from all of these and it's there. Today what took us six months to get there, right? So I think rightly so, I think Anthony and the team are focusing on that. And I think we have been partnering on with Anthony more, I would say, perhaps pushing a little more on you know, getting not only accurate data but also now on the paradigm of compliant data. Because I think what you're going to also start seeing is as companies, especially in like different kind of industries, like financial, healthcare and others, they would need data certification also of various kinds. And that would require each of these tool to meet compliance standards that were very, they were not designed for again, right? So I think that's a different paradigm, that again Anthony and the team are really doing great in helping us get there. >> Yeah. I think there's, that was good Diwakar. There's quite a bit to unpack there, you know. With companies such as GE, we've been on a journey for many years. And so that's why we deployed across the enterprise. And let's start off with, I have this source system, I'll move my data into their target system. These targets systems you know, become more frequently either data lakes or environments that were on-premise to running in the cloud, to newer platforms that are built for the cloud, like we've seen the uptake in companies like Snowflake and those types. And you mean, we see this from you know big query from Google and those type of environments. So we see those. And that's things we've got to support along the way as well. But then at the same time, more and more data starts getting generated in your non-traditional trial platforms. I mean, cloud-based applications and those things which we then support and build into this whole framework. But at the same time to what Diwakar was saying, the eyes, you know, the legal requirements, the regulator requirements on the type of data that is now being used. Before you would never typically have years ago companies moving their most valuable or their financial data into these cloud-based type environments. Well, they are today. It happens. And so with that comes a whole bunch of regulation in security. And we've certainly seen particularly this last year the uptake in when these transactions have another level of scrutiny when you're bringing in new products into these environments. So they go through, you know, basically the security and the legal requirements are a lot longer and more depth than they used to be. And that's just the typical of the areas that they're deploying these technologies in as well, and where you're taking some technologies that weren't necessarily built for the modern world that they are now adopt in the modern world. So it's quite complex and a lot to unpack there, but it's, you've got to be on top of all of that. But that's where you then work with your top customers, like at GE, that future roadmap, that feeds where one, you obviously make a decision and you go, this is where we believe the market's going, and these are the things we need to go, we know we need to go support, no matter that no customer has asked us for it yet. But the majority of it is still where customers that are pushing, bleeding edge, that are pushing you as well, and that feeds the roadmap. And, you know, there's a number of new profile platforms GE even pushed us to go support and features that Diwakar and the team have pushed us around accuracy and security and those types of things. So it's an all encompassing approach to it. >> John, we could like-- >> Actually, I think we've set up an entirely new CUBE Conversation we're going to have down the road, I think. >> Yeah. (laughing) >> Hey, gentlemen, thank you for the time. I certainly appreciate it. Really enjoyed it. And I wish you both a very happy and importantly, a healthy 2021. >> Great. >> Thank you both. Appreciate your time. >> Thank you. >> Thanks, John. >> Thank you. >> Thanks, Anthony. Bye bye. >> Bye bye. (upbeat music)

>> Narrator: From around the globe it's theCUBE with digital coverage of DockerCon Live 2020. Brought to you by Docker and its ecosystem partners. >> Hi, I'm Stu Miniman and welcome to theCUBE's coverage of DockerCon Live 2020. Really excited to be part of this online event. We've been involved with DockerCon for a long time, of course one of my favorite things is always to be able to talk to the practitioners. Of course we remember for years, Docker exploded onto the marketplace, millions of people downloaded it, using it. So joining me is Hui Xue, who is a Principal Deputy Director of Medical Signal Processing at the National Heart, Lung, and Blood Institute, which is part of the National Institute of Health. Hui, thank you so much for joining us. >> Thank you for inviting me. >> So let's start. Of course, the name of your institute, very specific. I think anyone in the United States knows the NIH. Tell us a little bit about your role there and kind of the scope of what your team covers. >> So I'm basically a researcher and developer of the medical imaging technology. We are the heart, lung and the blood, so we work and focus on imaging the heart. So what we exactly do is to develop the new and novel imaging technology and deploy them to the front of our clinical library, which Docker played an essential role in the process. So, yeah, that's what we do at NHLBI. >> Okay, excellent. So research, you know, of course in the medical field with the global pandemic gets a lot of attention. So you keyed it up there. Let's understand, where does containerization and Docker specifically play into the work that your team is doing? >> So, maybe I'd like to give an example which will suffice. So for example, we're working on the magnetic resonance imaging, MRI. Many of us may may already have been scanned. So we're using MRI to image the heart. What Docker plays, is Docker allow us to deploy our imaging technology to the clinical hospital. So we have a global deployment around 40 hospitals, a bit more, around the world. If we are for example develop a new AI-based image analysis for the heart image, what we do with Docker is we can put our model and software into the Docker so that our collaboration sites, they will pull the software that contains the latest technology, then use them for the patients, of course under the research agreement at NIH. Because Docker is so efficient, available globally, we can actually implement a continuous integration and testing, update the framework based on Docker. Then our collaborators would have the latest technology instead of, you know, in the traditional medical imaging in general, the iteration of technology is pretty slow. But with all this latest technology, and such like container Docker come into the field. It's actually relatively new. In the past two to three years, all these paradigm is, it's changing, certainly very exciting to us. It give us the flexibility we never had before to reach our customers, to reach other people in the world to help them. They also help us so that's a very good experience to have. >> Yeah that's pretty powerful what you're talking about there rather than you know, we install some equipment, who knows how often things get updated, how do you make sure to synchronize between different locations. Obviously the medical field highly regulated and being a government agency, talk a little bit about how you make sure you have the right version control, security is in place, how do all of those things sort out? >> Yes, that's an essential question. So firstly I want to clarify one thing. So it's not NIH who endorse Docker, it's us as researchers. We practiced Docker too and we trust its performance. This container technology is efficient, it's globally available and it's very secure. So all the communication between the container and the imaging equipment is encrypted. We also have all the paperwork it saved to set up to allow us to provide technology to our clinician. When they post the latest software, every version they put up into the Docker went through an automated integration test system. So every time they make a change, the newer version of software runs through a rigorous test, something like 200 gigabytes of data runs through and checked everything is still working. So the basic principle is we don't allow any version of the software to be delivered to customer without testing Docker. Let's say this container technology in general actually is 100% automating all this process, which actually give us a lot of freedom so we have a rather very small team here at NIH. Many people are actually very impressed by how many customer we support within this so small team. So the key reason is because we have a strongly utilized container technology, so its automation is unparalleled, certainly much better than anything I had before using this container technology. So that's actually the key to maintain the quality and the continuous service to our customers. >> Yeah, absolutely. Automation is something we've been talking about in the industry for a long time but if we implement it properly it can have a huge impact. Can you bring us inside a little bit, you know, what tools are you doing? How is that automation set up and managed? And how that fits into the Docker environment. >> So I kind of describe to be more specific. So we are using a continuous testing framework. There are several apps to be using a specific one to build on, which is an open source Python tool, rather small actually. What it can do is, this tool will set up at the service, then this service will watch for example our GitHub repo. Whenever I make a change or someone in the team makes a change for example, fix a bug, add a new feature, or maybe update a new AI model, we push the edge of the GitHub then there's a continuous building system that will notice, it will trigger the integration test run all inside Docker environment. So this is the key. What container technology offers is that we can have 100% reproducible runtime environment for our customers as the software provider, because in our particular use case we don't set up customer with the uniform hardware so they bought their own server around the world, so everyone may have slightly different hardware. We don't want that to get into our software experience. So Docker actually offers us the 100% control of the runtime environment which is very essential if we want to deliver a consistent medical imaging experience because most applications actually it's rather computational intensive, so they don't want something to run for like one minute in one site and maybe three minutes at another site. So what Docker place is that Docker will run all the integration tests. If everything pass then they pack the Docker image then send to the Docker Hub. Then all our collaborators around the world have new image then they will coordinate with them so they will find a proper time to update then they have the newer technology in time. So that's why Docker is such a useful tool for us. >> Yeah, absolutely. Okay, containerization in Docker really transformed the way a lot of those computational solutions happen. I'm wondering if you can explain a little bit more the stack that you're using if people that might not have looked at solutions for a couple of years think oh it's containers, it's dateless architectures, I'm not sure how it fits into my other network environment. Can you tell us what are you doing for the storage in the network? >> So we actually have a rather vertical integration in this medical imaging application, so we build our own service as the software, its backbone is C++ for the higher computational efficiency. There's lots of Python because these days AI model essential. What Docker provides, as I mentioned, uniform always this runtime environment so we have a fixed GCC version then if we want to go into that detail. Specific version of numerical library, certain versions of Python, will be using PyTorch a lot. So that's our AI backbone. Another way of using Docker is actually we deploy the same container into the Microsoft Azure cloud. That's another ability I found out about Docker, so we never need to change anything in our software development process, but the same container I give you must work everywhere on the cloud, on site, for our customers. This actually reduces the development cost, also improve our efficiency a lot. Another important aspect is this actually will improve customers', how do they say it, customer acceptance a lot because they go to one customer, tell them the software you are running is actually running on 30 other sites exactly the same up to the let's say heights there, so it's bit by bit consistent. This actually help us convince many people. Every time when I describe this process I think most people accept the idea. They actually appreciate the way how we deliver software to them because we always can falling back. So yes, here is another aspect. So we have many Docker images that's in the Docker Hub, so if one deployment fails, they can easily falling back. That's actually very important for medical imaging applications that fail because hospitals need to maintain their continuous level of service. So even we want to avoid this completely but yes occasionally, very occasionally, there will be some function not working or some new test case never covered before, then we give them an magnet then, falling back, that's actually also our policy and offered by the container technology. >> Yeah, absolutely. You brought up, many have said that the container is that atomic unit of building block and that portability around any platform environment. What about container orchestration? How are you managing these environments you talked about in the public cloud or in different environments? What are you doing for container orchestration? >> Actually our set-up might be the simplest case. So we basically have a private Docker repo which we paid, actually the Institute has paid. We have something like 50 or 100 private repos, then for every repo we have one specific Docker setup with different software versions of different, for example some image is for PyTorch another for TensorFlow depending on our application. Maybe some customer has the requirement to have rather small Docker image size then they have some trimmed down version of image. In this process, because it's still in a small number like 20, 30 active repo, we are actually managing it semi-automatically so we have the service running to push and pull, and loading back images but we actually configured this process here at the Institute whenever we feel we have something new to offer to the customer. Regarding managing this Docker image, it's actually another aspect for the medical image. So at the customer side, we had a lot of discussion with them for whether we want to set up a continuous automated app, but in the end they decided, they said they'd better have customers involved. Better have some people. So we were finally stopped there by, we noticed customer, there are something new to update then they will decide when to update, how to test. So this is another aspect. Even we have a very high level of confirmation using the container technology, we found it's not 100%. In some site, it's still better have human supervision to help because if the goal is to maintain 100% continuous service then in the end they need some experts on the field to test and verify. So that's how they are in the current stage of deployment of this Docker image. We found it's rather light-weight so even with a few people at NIH in our team, they can manage a rather large network globally, so it's really exciting for us. >> Excellent. Great. I guess final question, give us a little bit of a road map as to, you've already talked about leveraging AI in there, the various pieces, what are you looking for from Docker in the ecosystem, and your solution for the rest of the year? >> I would say the future definitely is on the cloud. One major direction we are trying to push is to go the clinical hospital, linking and use the cloud in building as a routine. So in current status, some of sites, hospital may be very conservative, they are afraid of the security, the connection, all kinds of issues related to cloud. But this scenario is changing rapidly, especially container technology contributes a lot on the cloud. So it makes the whole thing so easy, so reliable. So our next push is to move in lots of the application into the cloud only. So the model will be, for example, we have new AI applications. It may be only available on the cloud. If some customer is waiting to use them they will have to be willing to connect to the cloud and maybe sending data there and receive, for example, the AI apps from our running Docker image in the cloud, but what we need to do is to make the Docker building even more efficiency. Make the computation 100% stable so we can utilize the huge computational power in the cloud. Also the price, so the key here is the price. So if we have one setup in the cloud, a data center for example, we currently maintain two data centers one across Europe, another is in United States. So if we have one data center and 50 hospitals using it every day, then we need the numbers. The average price for one patient comes to a few dollars per patient. So if we consider this medical health care system the costs, the ideal costs of using cloud computing can be truly trivial, but what we can offer to patients and doctor has never happened. The computation you can bring to us is something they never saw before and they never experienced. So I believe that's the future, it's not, the old model is everyone has his own computational server, then maintaining that, it costs a lot of work. Even doctor make the software aspects much easier, but the hardware, someone still need to set-up them. But using cloud will change all of. So I think the next future is definitely to wholly utilize the cloud with the container technology. >> Excellent. Well, we thank you so much. I know everyone appreciates the work your team's doing and absolutely if things can be done to allow scalability and lower cost per patient that would be a huge benefit. Thank you so much for joining us. >> Thank you. >> All right, stay tuned for lots more coverage from theCUBE at DockerCon Live 2020. I'm Stu Miniman and thank you for watching theCUBE. (gentle music)

>>law from Las Vegas. It's the Q covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners. >>Welcome back to Las Vegas. Lisa Martin with John Ferrier, The Cube at AWS Reinvent 19 Lots of buzz. You can probably hear a little bit of it behind us here. There's about 65,000 people projected to be at a W s reinvent this week. Wow, we're very excited to welcome a distinguished guest and a distinguished architect from Splunk. Back to the Q r didn't murder, do you? Welcome back. >>Thank you very much. Thanks for having me back. >>Great to have you here. So let's kind of talk about here. We are re invent lots of news, lots of stuff. Lots of buzz going on. What kind of the latest with Splunk and a del us. >>All right, so the latest Splunk is obviously acquired us significance. The deal closed in trouble, So we're very excited about that. Um on we really feel that it's a it's a manager off complementary technologies, which is what I want some of the things we probably we can discuss later We're also very excited because we got acquired. Then we were able to go to dot com where we, you know, introduce the combined companies together. But then, at a cubicle on recently, we made a couple of very interesting product announcement that we're excited about, which is way discussing lots of reinvent conference. The 1st 1 is we have a brand new kubernetes experience called the community's Navigator, which we feel is a far, far better way Thio understand and make sense of the community environment. As you know, it's taking getting a lot of traction as a technology. So we're very excited about that because it not only gives you the infrastructure of you, but it also gives it the operators view, which I think operas. We really appreciate it. Three other thing that we're also focusing on. Obviously, if Splunk acquired US logs is an important part of this equation way are doubling down on the ability to ingest logs and make metrics out of them. You know, one of the things we've always discussed is how metrics every lightweight and actionable think that you can put on dashboard. You could put a lot son on the ability. Doing just logs and make them into metrics gives you that capability on the log data. We had a very interesting announcement around AWS. Fire lands on so on where you would be able to take love data from Splunk or other sources, and they bring them in as metrics to the system. The 13 has to do with the growing traction off open source standards. So we were actually very excited to make some contributions in the open telemetry project that we can discuss also later. But the idea is we want to promote open standards on open source, especially in instrumentation in the monitoring. Really? So that's kind of what's new >>question that's here at Amazon this week in this points to your success is observe ability, jazz he's laying out. This is distributed cloud Senator Gravity public Cloud Edge Outpost, Native AWS, Outpost five G with Verizon Wavelength All points to a lot of things. Move around, move compute to the edge where the data is so it speaks of large scale people having a hard time of doing it themselves on observe abilities. Harder and harder to roll your own are managed multiple tools. What are you guys doing to solve that problem? And how do you shape that going forward? >>That's a great question. Like the thing that blows my mind every time I come to reinvent is just the sheer variety of new things that comes across on. People are adopting them. All of these, he mentioned a bunch of different service is that I've got a lot of traction, got a lot of users, so that's happening across the user base. And then the question on D A. Y is because it's no longer about just building a database or, you know, things that you can sort some data and make some credit. It's about building the solution. A good solution. Need to support all the system. The service is that the customer the engineers are using right, so just keeping up with the sheer pace of innovation. Keeping that system up today is extremely, extremely hard. And so I feel that in generous making, less and less sense for most companies to try to roll their own observe ability, they would rather choose good tools that can sort of empower them that can able to move faster and invest in the people and process is part of it, which is also very, very key because >>the downside of rolling your own doing it yourself sure, what are some of the consequences that might happen? >>So in general, the people, the reason people want to build a couple of reasons, right? So one is they might undervalue, like the capabilities that good of the ruling might provide you, they might be afraid of the cost, like observe ability was cheap or free. Most people probably wouldn't build it. Some of them still vote because they might be afraid of vendor locking. Vendor lock in is a problem, and you don't want to be locked into vendors. Right? And what I feel in the terms of the risks is like if you consider observe ability as a cost center and not as an enabler, then you probably gonna try to do D i Y. But I think the view to the right view to have is think of it is something that accelerates your innovation and some of the risks of the advice. If you don't build something that's really capable that can that can do all the border or something that a system. Should you're gonna get slowed down, your innovation is gonna get slowed down. Another very thing, common pattern that we see a lot is maintaining, maintaining that it is a lot of resource is and people to build and maintain such a system. It's easy to prototype something and get it going, But are you going to be able to maintain the head count higher and grow the team on a long term basis? Because it's not something you can suddenly decide? Oops. I made a mistake. Time for a change. >>But change is difficult in any aspect of life. Changed management is something that we talk about office. It's way easier said than done. One of the things Andy Jassy talked about this morning and alluded to this and John's exclusive interview with him the other day was that the transformation needs to start at the top. It needs to be an executive level, a senior level and an aggressive tops down push in your experience in the last couple of years, what are some of the things that you're seeing companies in terms of the senior leadership embracing a understanding where D I y is useful where it's not, but also pushing that I want Oh my God, guys pushing it down from the top. So folks understand why this type of change is fundamental to a business to be competitive, >>right? So in general lighting, the focus is all on, like innovating, faster moving faster, keeping customers happy. Fundamentally, that's what we're doing. You know, our CMO Tom Bueller likes to say that you know the business. The Internet moves at the speed of life, a speed of life, Israel time, right? And so outages, Any kind of issues. They really affect your brand. And that's something that we need to avoid, like the plague, right? And that's gonna wear again. Observe. Ability comes in because this is the thing that's gonna allow you to find out renting There are. But more importantly, even when you don't have outages, the confidence that teams get in making changes, whether it be configuration changes or coat, which is a setup because they have a good system backing them up, is very, very critical. Right now. You can go D i y. You can go with a vendor solution, potentially terrifying, especially you can build one, but I think from top down. The important thing is like you have to be very clear about what you want out of it. And what are those things that you want to accelerate or make better in your organization? If your goal is, I want faster innovation, more code pushes, more changes, less deception like I feel that message needs to be done so that engineers understand that from management perspective, there's full support for this on their empowering you again. Where the two comes from is less important. But I think having those goals very clear and having that culture set from the top is very critical. >>A lot of open source discussions were hearing it here, laying out multiple databases you got pie towards you got tensorflow in machine, learning side on more and more kubernetes again, that's all speaks to where the service measures air going in. Micro Service's There's a lot of talk around open instrumentation open telemetry. What's your take on this? What is what's going on there? Can you share your commentary on those two things? >>Yes, so injured, as you know, like from the beginning, where since in Olympics started, we always believed that instrumentation should be open standards based. There should not be propriety instrumentation. They should be vendor lock in. It was a little bit perhaps ahead of the time, and we started off, but you can see that trend really accelerating now. But at this point, because of the sheer variety of service is and so on, it's very, very hard to build proprietary everything that supports all the all the things out there. What we're seeing is more bottoms up, open source, open standards efforts. Right, And that is great because A for the guys who are doing d i y. Because they don't want vendor lock in open standards is great because you're not really locked into a vendor in your environment. What you're doing is using a different back end, whether it be you know, your own or would it be a vendor's? Some of the things that we're doing is we're actually very happy to see this acceleration, and we're actually helping make that more so. Way just contributed pretty significant open telemetry project, which, as you know, is a way to instrument your environment for traces and metrics and logs eventually and so we actually donated the signal if Ickes smart Asian, which is pretty wonderful because it's a survey that's an agent that's running on your instances on your host, discovers as nuisances pop up. So, you know, speaking of community is the perfect fit for that, and it will start monitoring them and sending you did up on by making it by donating it to open telemetry. Were hoping to sort of accelerate out of the goodness and so that you know, all customers all use it. Whether they're significant customers or not should be able to benefit from that. >>Is an open source the source code? Or is it open as >>it's open source? There's two aspects to it is open standards as well as open. Both of them are happening because through the Amish in acquisition, we're now actually a pretty cool part of the open telemetry effort. So we're not really helping find finalize the standards, but also donating actual source code and components. >>Take a minute to explain. Signal FX is evolution now that you're in Splunk, right? What's changed? What's still the same? What's how is it? Evolve, how a signal effects evolved because you guys were really early ahead of it. A lot of people, but a lot of market power, great customer base and tech. What's the impact of Splunk and signal FX? >>Yes. So you know there's this cliche which is one plus one equals three. It kinda almost feels true here because, like I really, every time I think about this acquisition, it just feels how complimentary these two companies were because we have metrics and traces. Blanc has the best loss platform. But one of the things that we lot of times don't understand is he also a bunch of other technology which is highly relevant to the observe ability, space. For example, the acquired A company called Phantom, which is into automation, which is right up our alley because I feel like after all this mess has died down a little bit on communities, automation is gonna be the next frontier. They're fantastic. Automation platform built the security automation tool called Mission Control based on that, and now we're looking at how we can bring that into observe ability. Another example is incident management, Broncos Victor Ups, which is again exactly right up our alley. So we feel that we can really build a portfolio of solutions that work really, really well, that's one aspect. The other aspect, as you mentioned, is just the market power. And the resource is that's behind us, which is wonderful. For example. They're quite our mission, which is a fantastic complimentary technology to us, and we're working very quickly to sort of integrate the two together. Similarly, is getting the introductions. Having the financial benefit of a Splunk behind us is wonderful to have. So I think it'll only accelerate our >>congratulations on a great venture. I know you guys stayed the course and rightfully so great payday. But great outcome with Splunk Win is a win win. Yes, I gotta ask you the entrepreneurial question because a lot of people are saying, Oh my God, Amazon sucking up all the auction out of the room, Large scale. Got red shifts taking over this. That's taking over that someone's eating someone. Okay, I don't believe that. I believe that there's still a lot of opportunity for entrepreneurs because of this Born in the cloud and reborn in the cloud a new next gen architectures are developing with EJ. What's your opinion on this? As a cloud of alls What's the dynamics? And entrepreneurs and people thinking about innovating and either pivoting or reimagine their business? How should they be thinking about how to win in the new model? What are some of the architectural things that could bet on? What's your expert opinion on that? >>That's a good question. So I have some thoughts on it. Everybody might area once, right? So I feel like move to cloud is just happening. It's happened. Everything is going to move to the cloud. So I think the fundamental technologies like the databases, etcetera, that cloud provided they're always gonna have an advantage because they're going to be able to run it in a more performance way. But the thing that they're doing us a great favour are entrepreneurs is they're making a lot of different service is available to us now. They're not always necessarily all working well together to solve a specific use case. So I feel that they're giving us a tool set, among other things, to combined together to provide solutions for the problems that users organizations are facing. Not necessarily the platform but but the solution, the vertical on top of it. I think there's a lot of opportunity there, as well as sort of just new types of technology you can. As an entrepreneur, you can still build technology that the cloud provider might find as valuable, and they might want to buy you there right when I use you. So there's always opportunity there. But I think they're so busy building that the substrate, this enormous amount of opportunities for further up north. That's kind of my opinion. >>That's great opinion. >>Last question for you on the parlay of opportunity and the career that you've had as cloud is evolving the next gen of the cloud to Toto that John's calling it, and data becomes the critical element that can fine business differentiation and competitive advantages. What are some of the next industries you really think our prime to completely transform? If they get it right, >>I think we're still stop. It is a whole lot of talk of machine learning. I think we're just scratching the surface. I think what's happened is at this point it has become accessible enough on viable enough to be applied to different places. So every day we see a new headline where basically similar techniques were applied to this use case or that this case, and it's amazing being health care, transportation, you name it like digital business. It's happening all the way on our side, on our side of the fence. I feel a Splunk or a signal effects. We want to see a lot of that happening on our side of the fence, because again, because of the complexity, wonder thing that we have discussed with John earlier is how we feel machine learning and artificial intelligence gonna help us operate more efficiently because humans are going to be able to not really rock the entire complexity of what's out there. So I feel there's a lot of assistance that it can provide. That's one area which I think is interesting, And I feel also that one of the things we discussed within Signal FX is his move towards automation automated everything because complex systems, they just need to run themselves At some point. Humans cannot really go and make all the decisions like my my mainframe, itjust kind offer it to tell you we're not really in the middle of it, right to some extent. Similarly, I feel there's not a lot of action gonna happen on Automated Cloud and automated opposite really automated everything. So I think that's another sort of big area that I see happening on one thing that I also like to say that I don't want to make predictions because, like the world is so different from 10 years ago to now, it just blows my mind. I don't know whether I would have been able to sort of think what's gonna happen. So I only wonder what the next five years they're gonna >>bring. Love that opponent. You're >>right. Even a few years ago today, mine are just thank you for joining John A B on today. We appreciate your time. >>Thank you very much >>for John Ferrier. I'm Lisa Martin. You're watching the Cube from Reinvent 19 and Vegas will be right back.

>>live from Las Vegas. It's the Cube covering Splunk dot com. 19. Brought to You by spunk. >>Hey, welcome back. Everyone's live Cube coverage in Las Vegas. That's plunks dot com. 2019 thistles their annual customer conference, where they unleash all the new technologies, announce all the new things. Everyone's here. It's the 10th anniversary of Splunk dot com cubes. Seventh year we've been covering slung been quite the journey from scrappy, startup going public growth phase. Now market leader on Outside has to come to success from the products and the engineering. And, of course, the people in the field that that served customers. And we're here with Susan St Leger, who's the president of worldwide field operations. Thanks for coming back to see you. >>Thank you, John. It's exciting to be here. >>So in the keynote, bringing data to every outcome is really the theme. Um, you seem to got a spring to your step here. You excited this year? What an amazing successful show because you got a platform. But the proof is out there. You got that ecosystem. You got people building APS on top of it. It's kind of all coming together this year, >>It sure is experience. It's it's it's just it's a huge leap forward, and I think so. Much of it is a vision of data to everything. And if you think about it, we talk about. We want to bring data to every question, every problem in every action. And the biggest thing you're going to see that you did see in the show is it's no longer just about the Splunk index. We're going to help you get you get value out of data wherever it lives. >>You had some big news on acquisition front Signal FX. Big chunk of change for that company. Private hot category. Observe ability, which really taste is out. That next 20 mile stare in the marketplace, which is cloud native. >>That's a >>cloud Service is, which comes together in the platform with logging coming together. >>Yeah, so exciting Way looked hard at that entire market, and signal FX was definitely the right answer. They operated a scale similar to us. They know how to how to operate it that scale, and so they're gonna be able to serve our customers well. And our view of the world is it's going to be hybrid for a very long time. But they serve that new cloud native world better than anybody else. It's It's when you do monitoring the cloud native world. It's really interesting to think about it. It's all made up of Micro service is right. So thousands of Micro Service's hundreds, thousands of Micro Service's and so in traditional monitoring, it's always you're tryingto monitor things you know could go wrong. In a microt service landscape, you don't know everything that could possibly go wrong. And so it's a level of complexity that's just very different. And so it's all about instrument ing, so that when something does go wrong, you can solve it. >>You guys have a very loyal based customer base, and that's again testament success. But the product has changed, and the value problems is emerging even further with data. That's a big theme. Data to everywhere, everything and security has come up on the radar a few years ago, here, the show. But this almost is a full blown security show at this point, because security center of everything you can't ignore it's become a centerpiece of everything data, the access to the diversity, How is that impacting the field because you're not. I mean, I guess you're a security company enabler and solve security problems. Date is a big part of it. Sure, I was at shaping your operations, >>So I think the thing to understand is correct. We're not just a security company, but we are number one in the security Magic quadrant. We're number one in both I. D. C and Gardner, and so that's important. But what happens is all the data the equal act for security can also be used for all these other use cases. So, generally speaking, whatever you're collecting for security is also valuable for I t operations, and it's also valuable for many other use cases. So I'll give you an example. Dominoes, which is a great customer of ours. They're gone 65% of their orders now come in digitally, okay? And so they monitor the entire intend customer experience. But they monitor it not only from a nightie operations perspective. That same data that they used righty operations also tells them you know what's being ordered, what special orders are being made and they use that data for promotions based upon volume and traffic and timing. they actually create promotion. So now you're talking about the same data that he collected for security night operations you can actually use for promotions, which is marketing is >>not a lot of operating leverage in data. You're getting out this. The old model was is a database. Make a queer. You get a report. Little time problem there. But now you have. Well, that other date is over there in another database. Who runs that data? So the world has certainly changes now, data needs to be addressable. This seems to be a big theme here on undercurrent. I know data to everywhere is kind of global theme, but don't diverse data feeds a I cracked and address ability allows for application access. >>Correct. So we look at the entire data landscape and say, we want to help you get data value out of your data wherever it lives. And it's right now, we've changed to the point where we are operating on data in motion, which is with data stream processor, which is hugely beneficial. You mentioned you know, a I m l way actually do something so unique from an ML perspective because we're actually doing the ml on the live streaming so, so much more valuable than doing it in batch mode. And so the ability to create those ML models by working on live data is super powerful. >>Good announcement. So you guys had the data processor. You have the search fabric, >>data fabric search, >>real time and acceleration our themes there. I want to get your thoughts on your new pricing options. Yes. Why now? What's that mean for customers? >>So if we want to bring data to everything, we have to allow them to actually get all the data right? So we needed to give them more flexible models and more alternative models. So for some people and just motto is very comfortable. But what they want it was more flexibility. So if you look at our new traunch pricing are predictable pricing, there's a couple of things that we've done with it. Number one is from 125 gig all the way up to unlimited. We'll show your predictable pricing so you don't have to guess. Well, if I move from 20 terabytes 2 50 what's that gonna cost me? We're gonna tell you, and you're gonna know and so That's one. The second thing is you don't have to land on the exact ingest. So before, if you bought a terabyte, you got a terabyte. Right now there's a traunch from 1 to 2 terabytes. There's a trunk from 2 to 5 terabytes. And so it gives the customers flexibility so that they don't have to worry about it coming back to buy more right away. >>So that's kind of cloud by as you go variable pricing. Exactly. I want your thoughts on some of the sales motions and position and you guys have out in the field. Visa VI. The industry has seen a lot of success and say Observe ability. For instance, Southern to Rick and Kartik About this. Yes, you guys are an enterprise software cloud and on premises provider you Enterprise sales motion. >>Yes, >>there's a lot of other competition up there that sells for the SNB. They're like tools. What's the difference between an offering that might look like Splunk but may be targeting the SNB? Small means business and one that needs to be full blown enterprise. >>Yeah, so I think the first and foremost most of the offerings that we see land in S and B. They have scale issues over time, I and so what we look at it and say is and they're mostly point products, right? So you can you can clutter up your environment with a bunch of point products, doing all these different things and try and stitch them together. Or you can go with this fun clock for him. So which allows you thio perform all of the same operations, whether B I t Security or Data Analytics in general. But it really isn't. It's about having the platform. >>You guys, what reduced the steps it takes to implement our What's the value? I guess. Here's Here's the thing. What's the pitch? So I'm on Enterprise. I'm like, Okay, I kept Dad. I got a lot of potential things going on platform. I need to make my data work for me any day to be everywhere. I au g Enterprise Cloud. What's the Splunk pitch? >>So our pitches were bringing dated everything, and first and foremost it's important. Understand why? Because we believe at the heart of every problem is a data problem. And we're not just talking t and security. As you know, you saw so many examples. I think you talk to his own haven earlier this week. Right? Wildfires is a data problem New York Presbyterian is using using us for opioid crisis. Right? That's a data problem. So everything's a data problem. What you want is a platform that can operate against that data and remove the barriers between data and action. And that's really what we're focused on. >>He mentions own haven that was part of Splunk Ventures Fund. You have a social impact fund? Yes, what's the motivation line that is just for social good? Is there a business reason behind it or both? >>What's this? So we actually have to social focuses. One is long for good, and that is non profit. What we announced this, what we announced a couple weeks ago that we reiterated yesterday was the spunk, social impact funds, a splint venture social impact fund, and this is to invest in for profit companies using data for social good. And the whole reason is that we look at it and so we say we're a platform. If you're a platform, you want to build out the ecosystem, right? And so the Splunk Innovation Fund splint Ventures Innovation Fund is to invest in new technology focused on that that brings value out of data. And on the other side, it's the spunk. Social impact. Thio get data companies that are taking data and creating such a >>Splunk for good as Splunk employees or a separate nonprofit. And >>it's not a separate nonprofit entity, but it is what we what we invest in. Okay. >>Oh, investing in >>investing in non for profit. Exactly like when we talked about the Global Emancipation Network right, which uses Splunk to fight human trafficking. That's on the nonprofit side. >>So take me through. This is a really hot area we've been covering for good because all roads I want now is for bad. Mark Zuckerberg's testifying from the Congress this morning kind of weird to watch that, actually, but there's a lot of good use cases. Tech tech can be shaped for good. A lot of companies are starting and getting off the ground for good things, but they're kind of like SMB, but they want the Splunk benefit. How do they engage with spunk if I'm gonna do ah social impact thing say cube for good? I got all this Tech. How do I engage punk? I wanted, but I don't know what to do. Have access to tools? How do I buy or engage with Splunk? >>Yes, start parties. Fund managers is making sure it's not just money, right? It's money, its access to talent. It's access to our product. And it's, you know, help with actually thinking through what they're trying to achieve, so it really is the entire focus. It's not just about the tech, Thea. Other thing I would say is you saw that we put out a Splunk investigate, and you also saw us talking about spunk, business slow and mission control. Those air now all built on a native SAS platform. And so the ability for our ecosystem now to go build on a native son platform is going to be incredibly powerful. >>So you expect more accelerated opportunities that all right, what's your favorite customer success stories? I know it's hard to pick your favorites, like picking a favorite child may be filled with the categories. Most ambitious class clown class favorite me. What's the ones you would call a really strong, >>so hit on a couple of my lover Domino story and the other one that I love, that I touched on. But I want to expand on because I think it's an amazing story. Is New York Presbyterian on using the Yes See you sprung for traditional security for private patient privacy. They also use it for medical devices. But here's the thing they use it for to help the opioid crisis. And you're like, How is opioid crisis a data problem? What they do is they actually correlate all the data that so doctors are prescribing the opioids who they're prescribing them to a number of prescriptions being building their pharmacy and then the inventory of opioids. Because they actually have sensors on all the cabinets where they get the opioids, they correlate all the data, and they make sure that if they understand if opioids being stolen from the hospital, because what people don't understand is that the opioid a lot of big part of the opioid crisis starts with hospitals to say of such a big volume of opioids. And so that, to me, is just I guess I love it because it's a great customer success story. But it's also again, it's so much fun doing good problem. >>A lot of deaths. I gotta ask you around your favorite moments here dot com, and you're a lot of conversations in your customer conversations this year. Let's do a little Splunk of the Cube right now can take the patterns, all the data, your meetings. What's the top patterns that are emerging? What are some of the top conversation themes that just keep popping up with customer? Specifically, >>I think the biggest thing is that they have seen more innovation unleash this year than they have ever seen in one year from Splunk. The other thing is that we've gone far outside of our traditional spunk index right and that the portfolio has grown so much and that we're allowing them to operate and get value out of the data wherever it lives. So data in motion and then you saw in data fabric search. We'll let you query not only the Splunk indices, but also H D. F s and s three buckets and more buckets to come. So more sinks if you will. So, really, what we're trying to do is say, we're just going to be your date a platform to help you get value >>Susan, you're a great leader and slung. Congratulations on your success again. They continue to grow every year. Splunk defies the critics. Now you're a market leader. Culture is a big part of this. What is your plans this year To take it to the next level? You're president of field worldwide, field operations, global business landscape. What are some of your goals and objectives on culture >>and the culture? So thank you, Jon. First of all, for your comments and were so committed to our culture, I think you know, as you grow so quickly, it takes a real effort to stay focused on culture way, have an incredible diversity and inclusion program. Onda We do way. It's a business imperative for us. Every single leader has diversity, diversity, inclusion, focuses and targets. And so I think that's a huge part of our culture. And the reason I say that, John, I don't know if you've ever heard about a 1,000,000 data points. Did anybody ever way Always talk about, you know in different different settings will share a couple of our 1,000,000 data points. What we want to make sure is a culture is that way. >>We >>have our employees showing up with their authentic self and because you do your best work when you can show up is your authentic self. And so we have people share a handful of their 1,000,000 data points at all different times throughout the year to get to know each other as individuals, as human beings and really understand what matters to each other. And I love that 1,000,000 data points culture, and I got that. We truly live it. And again it's It's about authenticity. And so I think that's what makes us incredibly special. >>And inclusion helps that trust >>fund elaboration, yes, and also just add to that. We're very proud of the fact that we made the fortune list this year for best places to work for women. So it shows that our focus, you know, we started. We started revealing our metrics just about two years ago, and we've had significant improvement way. Believe that what you focus on what you measure is what you improve. So we started measuring and improving it, and this year we made the list for a fortune that's called walking. It is Congratulations. Thank you. We're very excited about >>awesome on global expansion. I'm assuming is on the radar. Well, >>always, especially at this point. We're ready to double down and some of the tier one mark. It's a lovely for sure >>wasn't saying. Legend. President of worldwide field operations here inside the Cube. Where day to slung dot com 10th anniversary of their customer conference Our seventh year covering Splunk Amazing Ride They continue to ride the big wave. Thats a Q bring you all the data on insights here. I'm John Ferrier. Thanks for watching.

(upbeat music) >> Narrator: Live from Las Vegas, it's theCUBE, covering Splunk .Conf19. Brought to you by Splunk. >> Welcome to theCUBE everybody, we're here in Las Vegas for Splunk's .Conf, I'm John Furrier, host of theCUBE, here with Lisa Martin for the next three days. Lisa will be here tomorrow and the next day. I'm going to be carrying it solo, this is our seventh year .Conf, Splunk's conference celebrating their 10th year. Our first guest is Melissa Zicopula, vice president of managed services of Herjavec Group. Robert's been on before, welcome to theCUBE. >> Thank you. >> I always get that, Herjavec? >> Herjavec Group. >> Herjavec Group. >> Happy to be here. >> Well known for the Shark Tank, but what's really interesting about Robert and your company is that we had multiple conversations and the Shark Tanks is what he's known for in the celebrity world. >> Melissa: Yes. >> But he's a nerd, he's a geek, he's one of us! (laughing) >> He's absolutely a cyber-security expert in the field, yes. >> So tell us what's going on this year at .Conf obviously security continues to be focus you guys have a booth here, what's the message you guys are sharing, what's the story from your standpoint? >> Yeah, so we do, Herjavec we're focusing on managed security services, where information security is all we do, focusing on 24/7 threat detection, security operations and also threat management. So, we want to be able to demo a lot of our capabilities, we're powered by Splunk, our HG analytics platform uses, heavily uses Splunk on the back end. So we want to be able to showcase for our customers, our clients, our prospects different types of use cases, different types of ways to detect malicious activity, while leveraging the tool itself. >> And data we're been covering since 2013, Splunk's .Conf, it's always been a data problem, but the data problem gets bigger and bigger, there's more volume than ever before which shifts the terms to the adversaries because ransomware is at an all time high. >> Melissa: Sure. >> Data is where the value is, but that's also where the attack vectors are coming from. This isn't going away. >> Absolutely, yeah, we want to focus on not just what type of data you're ingesting into your instance but to also understand what types of log sources you're feeding into your sim today. So we have experts actually focus on evaluating the type of log sources we're bringing in. Everything from IPS, to AV, to firewall you know, solutions into the sim so that way we can build use cases those, to be able to detect different types of activity. We leverage different types of methodologies, one of them is Mitre framework, CIS top 20. And being able to couple those two together it's able to give you a better detection mechanism in place. >> I want to some kind of, clarification questions because we talked to a lot of CSOs and CIOs and and CXOs in general. >> Melissa: Sure. >> The roles are changing, but the acronyms of the providers out in the market place are specializing, some have unique focuses, some have breadth, some have depth, you guys are an MSSPP. So, MSSPP, not to be confused with an MSP. Or ISV, there's different acronyms, what is the difference between an MSSPP versus an MSP? >> Melissa: Correct, so it's, we are a MSSP, which is a Managed Security Service Provider. And what we do is just, we're focused on we're very security-centric. So information, security is all we do everything from threat detection, we even have a consulting advisory role where we're actually doing penetration exams. We're PCI compliant, obviously SOC operations are the bread and butter of our service. Whereas, other MSPs, Managed Services Providers, they can do anything from architecture, network operations in that purview. So, we're focused on more of SIM solutions, endpoint, being able to manage any of your security technologies. And also, monitor them to take a fact into the SOC. >> So you guys are very focused? >> Melissa: Very focused on security. >> Then what's the key decision point for a customer to go with you guys, and what's the supplier relationship to the buyer because they're buying everything these days! >> Melissa: Sure. >> But they want to try and get it narrowed down so the right people are in the right place. >> Melissa: Yeah, so one of the great things about Herjavec Group is we are, you know, we're vendor agnostic, we have tons of experts in, you know, expertise resources that monitor, manage different types of technologies. Whether it's Splunk and other technologies out there, we have a team of people, that are very, very, you know, centric to actually monitor and manage them. >> How big is Splunk, in relative with your services? How involved are they with the scope? >> Melissa: Over 60% of our managed clients today, utilize Splunk, they're heavy Splunk users, they also utilize Splunk ES, Splunk Core, and from a management side, they're implementing them into their service. All of the CSOs and CROs or CIOs are leveraging and using it, not just for monitoring and security but they're also using it in development environments, as well as their network operations. >> So, one of the things I've been, I won't say preaching, because I do tend to preach a lot, but I've been saying and amplifying, is that tools that have come a long in the business and there's platforms and Splunk has always kind of been that, a platform provider, but also a good tool for folks. But, they've been enabling value, you guys have built an app on Splunk, the proprietary solutions. >> Absolutely. >> Could you tell me about that because this is really where the value starts to shift, where domain expertise focused practices and services, like you guys are doing, are building on someone else's platform with data, talk about your proprietary app. >> Absolutely, so we discovered, a few years ago, was that customers needed help getting to the data faster. So we were able to build in built-in queries, you know literally one click, say if you wanted to get to a statistical side of how many data sources are logging your SIM, is the data, you know, modeling complete, you know, is there anything missing in the environment or are there any gaps that we need to fill? You're able to do it by just clicking on a couple of different, you know, buttons within the tool itself. It gives you a holistic view of not just the alerts that are firing in your environment but all the data log sources that are coming into your SIM instance. It's a one stop shop. And also, what's great about it, is that it also powers Splunk ES, so Splunk ES also has similar tools and they are, literally, I mean that tool is so great you can go in, you can look at all the alerts, you can do an audit trail, you can actually do drill-down analysis, you can actually see the type of data like PCAP analysis, to get to the, you know, the type of activity you want to get to on a granular level. So, both tools do it really well. >> So you have hooks into ES, Splunk ES? >> Yes, we can actually see, depending on the instance that it's deployed on, 'cause our app is deployed on top of Splunk for every customer's instance. They're ale to leverage and correlate the two together. >> What are some of the trends in the marketplace that you're seeing with your customers? Obviously, again, volumes are increasing, the surface area of attacks is coming in it's more than log files now, it's, you got traces, you got other metrics >> Melissa: Sure. >> Other things to measure, it's almost It's almost too many alerts, what do you-- >> Yeah, a lot of KPI's. The most important thing that any company, any entity wants to measure is the MTTD, the Mean Time To Detection, and also mean time to resolve, right? You want to be able to ensure that your teams are have everything at their fingertips to get to the answer fast. And even if there's an attack or some type of breach in their environment, to at least detect it and understand where it is so they can quarantine it from spreading. >> What's the biggest surprise that you've seen in the past two years? I mean, 'cause I look back at our interviews with you guys in 2013, no 2015. I mean, the narrative really hasn't changed global security, I mean, all the core, top line stories are there, but it just seems to be bigger. What's the big surprise for you in terms of the marketplace? >> The big surprise for me is that companies are now focusing more on cyber-hygiene. Really ensuring that their infrastructure is you know, up to par, right? Because you can apply the best tools in-house but if you're not cleaning up you know, your backyard (laughing) it's going to get tough. So now we have a lot of entities really focusing and using tools like Splunk you know, to actually analyze what's happening in their environment, to clean up their back of house, I would say and to put those tools in place so they could be effective. >> You know, that's a classic story clean up your own house before you can go clean up others, right? >> Right. >> And what a trend we've been seeing in the marketplace on theCUBE and talking to a lot of practitioners is, and channel partners and suppliers is that, they tend to serve their customers, but they don't clean up their own house and data's moving around so now with the diversity of data, they've got the fabric search, they got all kind of new tools within Splunk's portfolio. >> It's a challenge, and it could be you know, lack of resources, it just means that we have you know, they don't have the right expertise in-house so they used managed security providers to help them get there. For example, if a network, if we identify the network being flat, we can identify you know, how to help them how to be able to kind of, look at the actual security landscape and what we need to do to have good visibility in their environment from places they didn't know existed. >> What's the one, one or two things that you see customers that need to do that, they aren't doing yet? You mentioned hygiene is a trend, what are some other things that that need to be addressed, that are almost, well that could be critical and bad, but are super important and valuable? >> I think now a lot of, actually to be quite honest a lot of our clients today or anyone who's building programs, security programs are getting you know, very mature. They're adopting methodologies, like Mitre Framework, CIS Top 20, and they're actually deploying and they're actually using specific use cases to identify the attacks happening in their environment. Not just from a security-centric standpoint but also from an operations side you know, you could identify misconfigurations in your environment, you can identify things that are you know, just cleaning up the environment as well. >> So, Splunk has this thing called SOAR, Security-- >> Automation. >> Orchestration Automation Recovery, resilience whatever R, I think R stands for that. How does that fit in to your market, your app and what you guys are doing? >> So it definitely fits in basically, being able to automate the redundant, mundane types of tasks that anyone can do, right? So if you think about it, if you have a security operations center with five or 10 analysts, it might take one analyst to do a task, it might take them two or three hours, where you can leverage a tool like Phantom, any type of SOAR platform to actually create a playbook to do that task within 30 seconds. So, not only are you minimizing the amount of you know, head count to do that, you're also you know, using your consistent tool to make that function make that function you know, more, I want to say enhanced. So you can build play books around it, you can basically use that on a daily basis whether it's for security monitoring or network operations, reporting, all that becomes more streamlined. >> And the impact to the organization is those mundane tasks can be demotivating. Or, there's a lot more problems to solve so for productivity, creativity, can you give some examples of where you've seen that shift into the personnel, HR side the human resource side of it? >> Yeah, absolutely so you know, you want to be able to have something consistent in your environment, right? So you don't want others to get kind of, get bored or you know, when you're looking at a platform day in and day out and you're doing the same task everyday, you might miss something. Whereas, if you build an automation tool that takes care of the low hanging fruit, so to speak, you're able to use a human component to put your muscles somewhere else, to find some you know, the human element to actually look for any types of malicious anomalies in the environment. >> How much has teamwork become a big part of how successful companies manage a security threat landscape? >> Very, very important. I mean, you're talking about leveraging different teams on the engineering side, on the operations side, even you know, coupling that with business stakeholders. You absolutely need to get the business involved so they have an understanding of what's critical to their environment, what's critical to their business, and making sure that we're taking security, obviously seriously, which a lot of companies know already, but not impeding on the operation. So doing it safely without having to minimize impact. >> Well let's just, I got to ask you this question around kind of, doing the cutting edge but not getting bled out, bleeding edge, bleeding out and failing. Companies are trying to balance you know, being cutting edge and balancing hardcore security Signal FX is a company that Splunk bought, we've been following them from the beginning. Strong tracing, great in that cloud native environment. So cloud native with micro services is super hot in areas you know, people see with Kubernetes and so on happening, kind of cutting edge though! >> Melissa: Right. >> You don't want to be bleeding edge 'cause there's some risks there too so, how do you guys advise your clients to think about cloud native with Splunk and some of the things that they're there but as the expression goes "there's a pony in there somewhere" but it's risky still, but certainly it's got a lot of promise. >> Yeah, you know, it's all about you know, everyone's different, every environment's different. It's really about explaining those options to them what they have available, whether they go on the cloud, whether they stay on-prem, explaining them from a cost perspective, how they can implement that solution, and what the risks are involved if they had and how long that will take for them to implement it in their environment. >> Do you see a lot of clients kicking the tires in cloud native? >> A lot of customers are migrating to cloud. One, because they don't have to keep it in a data warehouse, they don't have to have somebody manage it, they don't have to worry about hardware or licenses, renewals, all that. So, it's really easy to spin up a you know, a cloud instance where they can just keep a copy of it somewhere and then configure it and manage it and monitor it. >> Melissa, great insight, and love to have you on theCUBE, I got to ask you one final question >> Melissa: Sure. >> As a, on a personal note well, personal being you're in the industry you know, I hear a lot of patterns out there, see a lot of conversations on theCUBE. One consistent theme is the word scale. Cloud brings scale to the table, data scaling, so data at scale, cloud at scale, is becoming a reality for customers, and they got to deal with it. And this also impacts the security piece of it. What are some of the things that you guys and customers are doing to kind of one, take advantage of that wave but not get buried into it? >> Absolutely, so you just want to incorporate into the management life cycle, you know you don't want to just configure then it's one and done, it's over. You want to be able to continually monitor what's happening quarter over quarter you know, making sure that you're doing some asset inventory, you're managing your log sources, you have a full team that's monitoring, keeping up with the processes and procedures, and making sure that you know, you're also partnering with a company that can can follow you you know, year over year and build that road map to actually see what you're building your program, you know. >> So here's the personal question now, so, you're on this wave, security wave. >> Melissa: Sure. >> It's pretty exciting, can be intoxicating but at the same time, it's pretty dynamic. What are you excited about these days in the industry? What's really cool that you're getting jazzed about? What's exciting you in the industry these days? >> Automation, absolutely. Automation, being able to build as many playbooks and coupling that with different types of technologies, and you know, like Splunk, right? You can ingest and you can actually, automate your tier one and maybe even a half of a tier two, right, a level two. And that to me is exciting because a lot of what we're seeing in the industry now is automating as much as possible. >> And compare that to like, five years ago in terms of-- >> Oh absolutely, you know, SOAR wasn't a big thing five years ago, right? So, you had to literally sit there and train individuals to do a certain task, their certain function. And then you had to rely on them to be consistent across the board where now, automation is just taken that to the next level. >> Yeah it's super exciting, I agree with you. I think automation, I think machine learning and AI data feeds, machine learning. >> Michelle: Right. >> Machine learning is AI, AI is business value. >> Being able to get to the data faster, right? >> Awesome, speed, productivity, creativity, scale. This is the new formula inside the security practice I'm John Furrier with theCUBE. More live coverage here for the 10th anniversary of Splunk .Conf, our seventh year covering Splunk from a start-up, to going public, to now. One of the leaders in the industry. I'm John Furrier, we'll be right back. (techno music)

>> Narrator: From Sand Hill Road, in the heart of Silicon Valley, it's theCUBE, presenting the People First Network, insights from entrepreneurs and tech leaders. >> Hello and welcome to a special Cube conversation, I'm John Furrier with theCUBE. We're here at Mayfield Fund on Sand Hill Road, Venture Cap for investing here for the People First co-created production by theCube and Mayfield. Next to us, Phil Finucane who's the former CTO of Express Scripts as well as a variety of other roles. Went to Stanford, Stanford alum. >> Mm hmm. >> Good to see you, thanks for joining me for this interview. >> Thank you, thank you for having me. >> So, before we get into some of the specifics, talk about your career, you're a former CTO of Express Scripts >> Yep. >> What are some of the other journeys that you've had? Talk about your roles. >> Yeah, I've had sort of a varied career. I started off as just a computer coder for a contract coder in the mid-90s. I sort of stumbled into it, not because I had a computer science background, but because when you start coding, sort of for fun in Silicon Valley in the mid-90s, there are just lots of jobs and I was lucky to have great mentors along the way. In 2003, I joined Yahoo and came in as the lead engineer, sort of the ops guy and the build and release guy for the log in and registration team at Yahoo, so I learned how to, went from being just a coder to being somebody who know how to run and build big systems and manage them all around the world. That was in the day when everything was bare metal and I could go to a data center and actually look at my machine and say, "Wow, that one's mine," right? And you know, sort of progressed from there to being the architect by the time that I left for some of the big social initiatives at Yahoo. On my way out, the YOS, the initiative to try to build Facebook in I think 2007, 2008 to try to take them on. That didn't work out too well, but it was definitely a formative experience in my career. From there I went to Zynga, where I was the CTO for Farmville. Was really, really good at getting middle-aged women in the Midwest to come play our game, and you know, was there for >> And it was highly, >> About three years >> high growth, Farmville >> Huge growth >> Took off like a rocket ship. >> Yeah, you know, over the 10 quarters I worked on the game we had over a billion dollars in revenue and that was, you know, the Zynga IPO'd on the back of that, right? And we weren't the only game, but we were certainly >> That was one of the big games >> The big whale, us and poker were the two that really drove the value in Zynga at that point. After that, I went to American Express, where I worked in a division that sort of sat off on the side of American Express focusing on stored value products. I was the chief architect for that division. Stored value products and international currency exchange. So, you know, at one point, I was in charge of both a pre-paid platform and American Express's traveler's checks platform, believe it or not, a thing that still exists. Although it's not heavily used any more. And you know, finally, I went to Express Scripts, where I spent the last three years as the CTO for that org. >> It's interesting, you've got a very unique background, because you know, you've seen the web scale, talk about bare metal Yahoo days, I mean, I remember those days vividly, you know, dealing with database schemas, I mean certainly the scale of Yahoo front page, never mind the different services that they had, which by the way, silo-like, they had databases >> Very, oh totally >> So building a registration and identity system must've been like, really stitching together a core part of Yahoo, I mean, what a Herculean task that must've been. >> Yeah, it was a lot of fun. I learned a lot, you know, we, it was my first experience in figuring out how to deal with security around the web. You know, we had, at the beginning, some vulnerabilities here and there, as time went on, our standards around interacting around the web got better and better. Obviously, Yahoo has run into trouble around that in subsequent years, but it was definitely a big learning experience, being involved in you know, the development of the OAuth 2.0 spec and all of that, I was sort of sitting there advising the folks who were, you know, in the middle of that, doing all the work. >> And that became such a standard as we know, tokens, dealing with tokens and SAS. Really drove a lot of the SAS mobile generation that did cloud, which becomes kind of that next generation so you had, you know Web 1.0, Web 2.0, then you had the cloud era, cloud 2.0, now they're goin' DevOps and apps. I want to get your thought, and you throw crypto in there just for fun, of dealing with blockchain and then token economics and new kinds of paradigms are coming online >> It's amazing how far we've come in those years, right? I mean I look at the database that was built inside of Yahoo and this predated me, you know, this was back to circa 1996, I think, but you know, big massively scalable databases that were needed just because the traditional relational database just wouldn't work at that scale, and Yahoo was one of the first to sort of discover that. And now you look at the database technologies that are out there today that take some of those core concepts and just extend them so much further and they're so much easier to access, to use, to run, operate, all of those things than back in the days of Yahoozle, UDB, and it's amazing just to see how far we've come. >> Phil, I want to get your thoughts, because you know, talking about Yahoo and just your experiences and even today, at that time it was like changing the airplane's engine at 35,000 feet, it's really difficult. A lot of corporate enterprises right nhow are having that same kind of feeling with digital, and digital transformation, I'd say it's a cliche, but it is true this impact, the role of data that's playing and the just for value creation but also cybersecurity could put a company out of business, so there's all kinds of looming things that are opportunities and challenges, that are sizable, huge tasks that was once regulated to the full stack developers and the full web scalers, now the lonely CIO with the anemic enterprise staff has to turn around on a dime. Staff up, build a stack, build commodity, scale out, this is pretty massive, and not a lot of people are talking about this. What's your view on this? Because this is super important. >> Yeah it is, and you know, so I had kind of a shock, moving from working my whole career here on Silicon Valley and then going to American Express, which you know, is very similar in a lot of ways to Express Scripts, and the sort of corporate mindset around, "What is technology?" There is this notion that everything is IT and here in the valley, IT is you know, internal networks and laptops and those sorts of things, the stuff that's required to make your enterprise run internally. Their IT is all of your infrastructure, right? And IT is a service organization, it's not the competitive advantage in your industry, right? And so both of the places that I've gone have had really forward-thinking leaders that have wanted to change the way that their enterprise operates around technology, and move away from IT but, to technology, to thinking about engineering as a core competency. And that's a huge change, not only for the CIO >> You're saying they did have that vision >> They had the vision, but they didn't know how to get there, so my charter coming in and you know, others who were on the teams around me, our charter was to come in and help build a real engineering organization as opposed to an IT org that's very vendor-oriented, you know, that's dependent on third parties to tell you the right thing or the wrong thing, you know that hires consultants to come in and help set up architecture standards, because we couldn't do that on our own, we're not the experts on this side. You know, that's sort of the mindset in many old school companies, right? That needs, that I think needs to change. This notion that software is eating the world is still not something that people have gotten their heads around in many companies, right? >> And data's washing out old business models, so if software's eating the world, data's the tsunami that's coming in and going to take out the beach and the people there. >> Right. And so it's like, all of these things, it's one thing for, you know, a forward-thinking CEO like Tim Wentworth at Express Scripts, who was responsible for bringing me and the group in, you know, those kinds of folks, it's one thing to know that you have to make that transition it's another thing to have a sense of what that means for an engineering team, and all the more for the rest of the organization to be able to get behind it. I mean, people you know, I don't know any number of business partners who've been used to, just sort of taking a spec, throwing it over the wall, and saying, "Come back to me in two years when you're done." That's not how effective organizations work around technology. >> Let's drill into that, because one of the things that's cultural, I mean I do some of the interviews of theCUBE, I talk to leaders all the time like yourself, the theme keeps coming back, it's culture, it's process, technology, all those things you talk about, but culture is the number one issue people point to, saying, "That's the reason why "something did or didn't happen." >> Correct. >> So, you talk about throwing it over the fence, that's waterfall, so you think about the old waterfall methodology, agile, well documented, but the mindset of product thinking is a really novel concept to corporate America Not to Silicon Valley, and entrepreneurs, they got to launch a product, not roll out SAP over two years, right, or something they used to be doing. So that's a cultural mindset shift. >> It's difficult for folks, even if they want to get on board to come along some of the time. One of the real big successes we had early on at Express Scripts was, you know, transitioning our teams to Agile wasn't difficult, what was difficult was getting business partners to sort of come along and be actively engaged in that product development mindset and lifecycle and all those sorts of things. And you know, we had one partner in particular, we were migrating from a really old, really clunky customer care application that you know had taken years and years to build, took on average, a new agent took six weeks to get trained on it because it was so complex and it's Oracle Forms and you know, every field in the database was a field on this thing, and there were green screens to do the stuff that you couldn't do in Oracle Forms, so and we wanted to rebuild the application. We tried to get them to come along and say, "Okay, we're going to do it in really small chunks," but business partners were like, "No, we can't afford "to have our agents swiveling between two applications." And so finally after we got our first sort of full-feature complete, we begged to go into a call center, you know with our business partners, and sit down with a few agents and just have them use it and see if it looked like it worked, if it did the right thing, and it was amazing seeing the business partner go, over the course of an hour, from "I can't be engaged in this, "I don't want an agent swiveling, "I don't want to be, you know, delivering partial applications "I want the whole thing." to, "Oh my god, it works way better, "the design is much nicer, the agents seem to like it," you know, "Here are the next things we should work on, "These are the things we got wrong." They immediately pivoted, and it wasn't, it was because they're the experts, they know how to run their business, they know what's important in their call centers, they know what their agents need, and they had just never seen the movie before, they just had no concept you could work that way. >> So this is actually interesting, 'cause what you're saying is, a new thing, foreign to the business partners, the tech team's on board, being Agile, building product, they have to, they can't just hear the feature benefits, they got to feel it. >> Yeah, they have to see it >> This seems to be the experience of success before they can move. Is that a success you think culturally, something that people have to be mindful of? >> It's absolutely something you have to be mindful of. And that was just the first step down the path. I mean, that team made a number of mistakes that folks here I think in the valley wouldn't normally make, you know. Over-committing and getting themselves into deep water by trying to get too much done and actually getting less accomplished in the process because of it and you know, the engagement around using data to actually figure out what's the next feature that we build. When you've got this enormous application to migrate, you should probably have some insight as to you know, feature by feature, what are you going to work on next? And that was a real challenge, 'cause there's a culture of expertise-driven, you know being subject-matter driven, expertise driven as opposed to being data driven about how do you >> Let's talk about data-driven. We had an interview earlier this morning with another luminary here at the Mayfield 50th conference celebration that they're having, and he said, "Data is the new feedback mechanism." and his point was, is that if you treat the Agile as an R&D exercise from a data standpoint. Not from a product but get it out there, get the data circulating in, it's critical in formulation of the next >> It is, yeah, it's absolutely critical. That was the eye opener for me going to Zynga. Zynga had an incredible, probably still does have, an incredible product culture that every single thing gets rolled out behind an experiment. And so you know, that's great from an operational perspective, because it allows you to, you know, move quickly and roll things out in small increments and when it doesn't work, you can just shut it off but it's not some huge catastrophe. But it's also critical because it allows you to see what's working and what's not and the flip side of that is, some humility of the people developing the products that their ideas are not going to work sometimes just because you know this domain well doesn't mean that you're necessarily going to be the expert on exactly how everything is going to play out. And so you have to have this ability to go out, try stuff, let it fail, use that, hopefully you fail quickly, you learn what's not working and use that to inform what's the next step down the path that you take, right? And Agile plays into it, but that's for me, that's the big transition that corporations really have to struggle with, and it's hard. >> You know you're, been there done that, seen multiple waves of innovation, want to bring up something to kind of get you going here. You see this classically in the old school 90s, 80s day. Product management, product people and sales people. They're always buttin' heads, you know? Product marketing, marketing people want this sales and marketing want this, product people buttin' heads, but now with Agile, the engineering focus has been the front lines. People are building engineering teams in house. They're building custom stacks for whatever reasons, the apps are getting smarter. The engineers are getting closer to the edge, the customer if you will. How do you help companies, or how do you advise companies to think about the relationship between a product-centric culture and a sales-centric culture? Because sometimes you have companies that are all about the customer-centric, customer-centric customer-centric, product-centric and sometimes if you try to put 'em together there's always going to be an alpha-beta kind of thing there and that's the balance in this. What's your take on this? Seems to be a cutting edge topic >> Yeah, well, so you know, one of the last big initiatives that I worked on at Express Scripts. Express Scripts has the, to my knowledge, the largest automated home delivery pharmacy in the world. It's amazing if you walk into one of our pharmacies where automation is packaging and filling prescriptions and packaging and shipping and doing all of that stuff. And we've built so much efficiency into the process that we've started getting slack in the system. Every year, you're trying to figure out how to make something work better and you know, have better automation around it. And so, you know, what do you do with all of that slack? The sales team can't sign up enough new customers for Express Scripts to actually fill that capacity. And so they create a division of commoditizing this, basically white labeling your pharmacy. We called it Pharmacy as a Platform, exposing APIs to third parties who might want to come along and hey, Phil's pharmacy can now fill branded prescriptions to get sent to you in your home, right? And so that's a fantastic vision, but there's a real struggle between engineering who had all these legacy stacks that we needed to figure out how to move to be able to really live up to this, you know the core of Express Scripts was our members and not somebody else's members. And so there's a lot of rewiring at the core that needs to be done. An operations team, a product team that's, you know, running these home delivery pharmacies, and a sales team that wants to go off and sell all over the place, right? And so, you know, early on, we started off and the sales team tried to sell, like six different deals that all required different parts of the vision, but you know, they weren't really, there was no real roadmap to figure out how do you get from where we're at to the end, and we could've done any of those things, but trying to do them all at once was going to be a trainwreck. And so, you know, we stubbed our toes a couple of times along the way, but I think it just came down to having a conversation and trying to be as transparent as possible on all sides, in all sides. To you know, try to get to a place where we could be effective in delivering on the vision. The vision was right. Everybody was doing all of the right things. But if you haven't actually, with so much of this stuff, if you haven't seen the movie, if you haven't worked this way before, there's nothing I can tell you that's going to make it work magically for you tomorrow. You have to just get this together and work in small increments to figure out how to get there. >> You got to go through spring training, you got to do the reps. >> Yep, absolutely. >> All right, so on your career, as you look at what you've done in your career, and what people outside are looking at right now, you got startups trying to compete and get a market position. You have other existing suppliers who could be the old guard, retooling and replatforming, refactoring, whatever the buzz word you want to use. And then the ultimate customer who wants to consume and have the ability of having custom personalization, data analytics, unlimited elastic capability with resources for their solution. How, what advice would you give to the startup, to the supplier, and to the customer to survive this next transition of cloud 2.0, you know and data tsunami, and all the opportunities that are coming? Because if they don't, they'll be challenged a startup goes out of business, a supplier gets displaced. >> Right, I mean, well, so the startup, I don't know if I have good advice for the startup. Startups in general have to find a market that actually works for them. And so, you know, I don't know that I've got some secret key that allows startups to be effective other than don't run out of money, try to figure out how to build effectively to get you to the point where you're, you know, where you're going to win. One of my earliest, one of the earliest jobs I had in my career, I came into a startup, and I tried, one of the founders had written the initial version of the code base. I, as a headstrong engineer, was convinced that he had done horrible work, and so I sort of holed up for like, six to eight weeks doing a hundred hours a week trying to rewrite the entire code base while getting nothing done for the startup. You know, in the end, that was the one job I've ever been fired from, and I should've been fired, because, you know, honestly as a startup, you shouldn't worry about perfection from an engineering perspective. You should figure out how to try to find your marketplace. Everybody has tech debt, you can fix that as time goes on, the startup needs to figure out how to be viable more than anything else. As far as suppliers go, you know, I don't know it's interesting the, you know, I sort of look at corporate America and there are many many companies that really rely heavily on their vendors to tell them how to do things. They don't trust in their own internal engineering ability. And then there are the ones, like the teams I have built at AmEx and Express Scripts that really do want to learn it all and be independent. I would say, identify when you walk into somebody's shop which they are and sell to them appropriately. You know, I've been a Splunk customer for a long time, I love Splunk. But the Splunk sales team early on at Express Scripts tried to come in and sell me on a whole bunch of stuff that Splunk was just not good at, right? >> And you knew that. >> And I knew that, because I've been a hands-on customer every since Zynga, right? I know what it's good at, and I love it as a tool, but you know, it's not the Swiss Army knife. It can't do everything. >> Well now you got Signal FX, so now you can get the observability you need. >> Exactly, right? So yeah, I, you know, I would say, you know, for those kinds of companies, it's important to go in and understand what your customer is, you know, what your customer is asking for and respond to them appropriately. And in some cases, they're going to need your expertise, either because they're building towards it or they haven't gotten there yet, and some cases, one of the things that I have done with teams of mine in the past, was it with AppDynamics at Express Scripts, excuse me at AmEx, five or six years ago, they were sold on, you know, bringing in AppDynamics as a monitoring tool, I actually made them not bring it in, because they didn't know what they didn't know. I made them go build some basic monitoring, you know, using some open source tools, just to get some background, and then, you know, once they did, we ended up bringing AppDynamics in, but doing it in a way that they were accretive to what we were trying to accomplish and not just this thing that was going to solve all of our problems. >> And so that brings up the whole off-the-shelf general purpose software model that you were referring to. The old model was lean on your vendors. They're supplying you, and because you don't have the staff to do it yourself. That's changing, do you think that's changing? >> It is, it's changing, but again, I think there's a lot of places where people nominally want to go there, but don't know how to get there, and so, you know, people are stubbing their toes left and right. If you're doing it with this mindset of, we're constantly getting better and we're learning and it's okay to make mistakes as long as we move forward, >> It's okay to stub your toe as long as you don't cut an artery open. >> Yeah, that's true, yeah exactly >> You don't want to bleed out, that's a cybersecurity hack >> That's true, that's true. But for me a lot of the time that just comes down to how long are you waiting before you stub your toe? If you're, you know, if you wait two years before you actually try to launch something, the odds of you cutting your leg off are much higher than >> Well I want to get into the failure thing, so I think stubbing your toe brings up this notion of risk management, learning what to try, what not to do, take experiments to try to your, which is a great example. Before you get there, you mentioned suppliers. One of the things we hear and I want to get your thoughts on, is that, a lot of CIOs and C-sos, and CBOs, or whatever title is the acronym, they're trying to reduce the number of suppliers. They don't want more tools, right? They don't necessarily want another tool for the tool's sake or they might want to replatform, what does that even mean? So, we're hearing in our interviews and our discussions with partitioners, "Hey, I want to get my suppliers down, "and by the way, I want to be API driven, "so I want to start getting to a mode "where I'm dictating the relationship to suppliers." How do you respond to that? Do you see that as aspirational, real dynamic, or fiction? >> It's a good goal to give motivation, I believe it. For me, I approach the problem a little differently. I'm a big believer, well, so, because I've seen this pattern of this next tool is going to be the one that consolidates three things and it's going to be the right answer and instead of eliminating three and getting down to one, you have four, because you're, you need to unwire this new thing, there's a lot of time and effort required to get rid of, you know, your old technology stack, and move to the new one, right? I've seen that especially coming from the C-Sec for Express Scripts is an amazing guy, and you know, was definitely trying to head down that path but we stubbed our toes, we ran into problems in trying to figure out, you know, how do you move from one set of networking gear to the next set? How do you deal with, you know, all of the virus protection and all the other, there's a huge variety of tools. >> So it's not just technical debt, it's disruption >> It's disruption to the existing stack, and you've got to move from old to new, so my philosophy has always been, with technical debt, when you're in debt, and I think technical debt really does operate in a lot of ways like real debt, right? Probably good to have some of it. If you're completely debt-free, that's I've never been in that place before. >> You're comfortable. You might not be moving, >> Exactly, right? But with that technical debt, you know, there's two ways to pay down your debt. You can scrimp and save and put more money into debt principal payments as opposed to spending on other new things, or, well and/or, build productive capacity. So a huge focus for me for the engineering teams that we've built, and this is not anything new to the folks in this area, but, you know, always think about an arms race, where you're getting 1% better every day. The aggregation of marginal gains and investing in internal improvements so that your team is doubling productivity every year, which is something that's really possible for, you know, some of these engineering organizations, is the way that you deal with that, right? If you get to the point where your team is really, really productive, they can go through and eliminate all the old legacy technology. >> That's actually great advice, and it's interesting, because a lot of people just get hung up on one thing. Operating something, and then growing something, and you can have different management styles and different techniques for both, the growth team, the operating team. You're kind of bringing in and saying, we can do both. Operate with growth in mind, to 1% better approach. >> Right, you know, and for me, it's been an interesting journey, you know. I started off as the engineer and then the architect, who was always focused on just the technology, the design of the system in production. Sort of learned from there that you had to be good at the you know, all the systems that get code from a developer's desktop into production, that's a whole interrelated system that's not isolated from your production system. And then from there, it has to be the engineering team that you build has to be effective as well. And so, I've moved from being very technology-centric to somebody who says, "Okay, I have to start "with getting the team right "and getting the culture right if we're ever going to "be able to get the technology to a good place." Mind you, I still love the technology. I'm still an architect at my core, but I've come to this realization that good technology and bad teams will get crushed by bad technologies and good teams. Because now I've seen that a couple of places, where you have old but evolving technology stacks that have gone from low availability and poor performance and low ability to get new features into production to a place where you're fixing all of that at a high rate. It starts with the team. >> You're bringing us some core Silicon Valley ethos to the IT conversation, because what you're talking about is "I'll fund an A team with a B plan any day "over a B team with an A plan." >> Right. >> And where this makes sense, I think is true, is that to your point about debt, A teams know how to manage it. >> Yeah. >> So this is kind of what you're getting at here. >> Right. >> You can take that same ethos, so it's the Agile enterprise. >> Yeah, it is >> That's what we're talking about. Okay, so hypothetical final point I want to chat with you about. Let's just say you and I were startin' a company. We're chief architects, you're the chief architect, I'm a coder, what are we doing? Do I code from horizontally scalable cloud, certainly cloud native, how would you think about building, we have an app in mind, all of our requirements defined, it's going to be data-centric, it's going to be game change and have community, it might have some crypto in there, who knows, but it's going to be fun. How do we scale this out to be really fast? How would you architect this? >> Yeah, well, you know, I do start in the cloud. I go to AWS or Azure or any of the offerings that are out there, and you know, leverage everything that they have that's already wired up already for you. I mean the thing that we've seen in the evolution of software and production systems over the last, well, forever, is you get more and more leverage every day, every year, right? And so, if you and I are startin' a new company, let's go use the tools that are there to do the things that we shouldn't be wasting our time on. Let's focus on the value for our company as much as we can. Don't over-architect. I think premature optimization is a thing that you know, I learned early on is a real problem. You should, you know >> Give an example, what that would look like. >> I've seen >> Database scale decisions done with no scale >> Correct, yeah, you know? You go off >> Let's pick this! It's the most scalable database, well we have no users yet. >> Right, you know you build the super complicated caching architecture or you know, you go design the most critical part of the system out of the gate, you know, using Assembly. You use C++ or, you use a low level language when a high level language with your three users would be just fine, right? You can get the work done in a fraction of the time. >> And get the business logic down, the IP, >> Solve the problem when it becomes a problem. Like, it's, you know, I've, any number of times, I've run into systems, I've built systems where you have some issue that you run into, and you have to go back and redesign some chunk of the system. In my experience, I'm really bad at predicting, and I think engineers are really bad at predicting what are going to be the problem areas until you run into them, so just go as simple as you can out of the gate, you know. Use as many tools as you can to solve problems that, you know, maybe as an engineer, I want to go rebuild every thing from scratch every time. I get the inclination. But it's >> It's a knee-jerk reaction to do that but you stay your course. Don't over-provision, overthink it, thus start taking steps toward the destination, the vision you want to go to, and get better, operate >> Solve the problem you have when it shows up. >> So growth mindset, execute, solve the problems when they're there. >> Right, and initially the problem that you have is finding a market, you know, not building the greatest platform in the world, right? >> Find a market, exactly. >> Right? >> Phil, thanks for taking the time >> Thank you very much, appreciate it. >> Appreciate the insights. Hey, we're here for the People First, Mayfield's 50th celebration, 50 years in business. It's a CUBE co-production, I'm John Furrier, thanks for watching >> Thanks John. (outro music)

>> Announcer: Live from San Francisco, celebrating 10 years of high tech coverage, it's theCUBE. Covering VMworld 2019. Brought to you by VMware and its ecosystem partners. >> Welcome back to bright and sunny San Francisco. Gorgeous day here in the City on the Bay. Dave Vellante, John Walls. We continue our coverage here on theCUBE VMworld 2019 with Doc D'Errico from Infodant, CMO. Doc, good to see you again, sir! >> Infinidat. >> Oh Infinidat! Sorry, sorry, sorry. (Doc laughs) But, good to see you! >> I missed my opportunity but thanks, Dave, yeah, it's good to be back. >> John: You bet. Marc Creviere, who is principle systems engineer at US Signal. Good to see you again, Marc here. You were here just last year, right? >> Yeah, I'm an alumni now. >> We'll touch base on that in just a little bit. Doc, first off, let's just talk about the show from your perspective. What you're doing here, explain to our viewers at home what it's all about and what you find the vibe that's going on this year. What kind of sense do you get? >> The vibe is fantastic The sense is great. Coming back to San Francisco, I'm not sure what we were really expecting but it's a really good tempo, a lot of great people, lot of great feedback on our recent launch. A lot of people looking at what're we doing, especially with VMware and availability. Lots of new use cases for snapshot technologies which is fantastic. The 100% availability, it's great getting people come up to you who say "Hey, this is incredible. "You guys actually put some teeth behind your guarantees," "you know, you're not just promising "some future discounts or something. "In the VMworld environment where I've got my VMs, "I need that kind of guarantee, I need that support. "I need to know that my systems "are going to be there when I need them, "because that's my business," right? It's just an incredible vibe. >> And had your party last night? >> We had our party last night. And guess who was there? (laughs) >> I did stop by, it was a very cool venue. The San Francisco Mint, which is, it was kind of awesome. >> Yeah, it was a great, great environment. It was great having people like Dave there, and some of the other industry luminaries talk to our customers. >> I didn't get the tour of the Vault. >> Doc: I'll get you a picture. (laughing) >> So, Marc, I mentioned in the intro, we had you on last year. So, let's look back at the last 12 months for you. US Signal, and what's been going on with you, and what are you seeing here and kind of feeling here in terms of business? >> Yeah, thanks for having me back. It's been another great year at US Signal. We are planning on opening a new data center in the Detroit Metro area, coming up online Q1 of 2020, so that's exciting for us. Purpose built, wholly owned and operated by us, so that's great. It's going to add to our capabilities in that region. We've had a heavy focus on DR technologies, DR as a Service technologies in the past year. Seeing a lot of success, a lot of really good conversations with customers and developing their plans, and bringing our new capabilities to be able to service those needs. >> So, tell us more about the DR as a Service. I mean, that's obviously one of the early sort of cloud-use cases? >> Marc: Yeah. >> Add some color, what is it all about, how does it relate to some of the other DR solutions that are out there and what role do these guys play? >> Yeah, well we conducted a survey of a little over 100 of companies in our region, a little over 100 respondents, and three out of four respondents told us that their biggest concerns were either distributed denial of service or ransomware. Obviously, we've got these bad actors out there. And it doesn't necessarily have to be a bad actor, it could be something force of nature making data unavailable, right? It doesn't matter how great the equipment is if either a bad actor or nature takes it out for you. So, having that protection, we're able to have replication technology. We actually have three separate technologies that we use now. We enhanced our Zerto-based offering to include multi-cloud so we can now have customers replicate to either multiple cloud destinations, us being one of them, or they can replicate to one of their sites and us as a tertiary site, so that's new. They're able to bring their existing licensing. One thing that's exciting to me, near and dear to my heart, is drafts for VMware based on the vCloud availability platform. So, we're a big VM, vCloud shop, big consumer of VMware technologies, that's why we're out here, and that's really exciting to me because it uses built in VMware replication technologies. There's not a lot of learning curve, there's not a lot of extra components. Super simple to get up and running and get RPOs as low as 5 minutes, and it's easy, and it's relatively cheap on an OPX-type platform, where you're paying for storage and per VM and that's it. And then we've also spun up a replication for Veeam, Cloud replication for Veeam based on that ecosystem. So, we've got a lot of entry points, a lot of different ways that we can protect that data and bring it in and get a copy in our data center, so in the event that it becomes unavailable at the source, it's either managed or customer managed. We can get it up and running in a short time frame on our infrastructure. >> And Infinidat is the primary storage underneath all this? >> Marc: Yeah. >> So, explain more about... So, Doc, you and I have had these conversations. The state of the art, whatever, 15 years ago, was three-site data centers, very complex, extremely expensive. I'm interested in how we're attacking that problem today. You obviously, with multi cloud, it's multi-site, but how are we attacking the cost problem, the complexity problem, the "I can't test because I can fail over "but I'm afraid to fail back" problem? >> Well, you know, there's so many different ways to cover all of these. We're talking just about ransomware, you know, ransomware are immutable snaps, become an important play and we have Snap Rotator which will allow you to build a certain number of snaps and have them just rotate through so you're not just creating an infinite number, you're not wasting time and space. And, by the way, time and space, our snapshots are zero-overhead. There's zero performance penalty, unless you want to crash consistent copy, and there's really zero data overhead because it's only the incremental data that you write. So, by creating this, you can do it every couple seconds, and then create some immutable copies of that. You know, make them time out, so they can't be modified, 30 days, 60 days, whatever you decide administratively. So that's great. If you're looking for the DRaaS, the DR as a Service-type capabilities, whether it's single site or multi site, going to cloud service providers makes a lot of sense. 'Cause now, even if it's on premises to a cloud service provider, now you're not having to worry about that second set of infrastructure, you're not having to worry about the management of it, you're not having to worry about the systems integration of it, or even go CSP to CSP, right? Go from one data center within your favorite cloud service provider, hopefully US Signal, to another or any one of our great partners would be super, too. And then, of course, InfiniSync, where if you really want that longer distance capability, why bother with a bunker site? Why bother with all that complexity and that cost and overhead? Put in an InfiniSync appliance in with a VM, and you've got the recoverability. You can go asynchronous distances, and have a zero RPO. >> For way, way less. >> Oh, a fraction of the cost. It'll cost you less for the InfiniSync appliance than it'll cost you for the telecoms equipment that you need for a bunker site. >> If I don't want to build another data center... Go ahead. >> What I'm curious about; I heard a number yesterday in one of the interviews we had, about ransomware. The number kind of blew me away, and I thought about one out of every three companies will be a victim of, or at least a ransomware attack within the next two years, which means everyone, over the next six, if you extrapolate that out. Does that sound about right from what you're seeing? That the intrusions are reaching that kind of frequency? >> I'm surprised it's that low, but I'll let Marc try and answer that. >> We've done some events where we actually demo how easy it is, like, through a phishing attack, to get that in there. So, it's not just about having those protections in place, it's your user training; that's a huge area, training those users what to look for in those emails to avoid that sort of thing, but it's not perfect. People are imperfect. >> Dave: And yeah, you got to have both the protection on the front end, the training for the people, and those recovery options in the event it does get in. In our survey, the average monetary damage was over $150,000 per incident. And that means that some people got off a little lighter and some people paid a lot more, if that was the average. >> Should you pay the ransom? >> Uh, not if you've got a good plan in place that can test it. (laughs) >> But it is, it's a reasonable question. >> Huge quandary. Some are, some aren't, right? Atlanta says "no, we're going to pay a boatload "to protect against it, but we're not going to pay that," what was it, 55,000 or whatever it was? >> Let's negotiate. >> Yeah, I think I said last time I was here that until you've tested your plan, you don't really have one. You know, it rings just as true today. >> What's your business worth? I mean, it's a great question, really. What is your business worth to you? Your business is probably worth a lot more, and they probably throw these numbers out there, thinking "Well...", then becomes a no-brainer for you to pay, and that's the whole point. Because what is ransomware? It's malware that's recoverable, maybe. You're not even sure of that. >> Is it usually, is it operator error? Is it human error that allows that to work more often than not? Or, is it a mixture of technical chops, or just...? >> It's a mixture; you've got to know what vulnerabilities are out there on your infrastructure, you got to make sure you're staying up to date on patching those vulnerabilities, paying attention to any compliance practices, if you're a compliant organization. You know, HIPAA, PCI, our entire infrastructure footprint is actually HIPAA and PCI compliant at the levels that we control. So, it's a heavy lift. You got to stick with it. >> But just to kind of bring it full circle to the comment about the ransom and paying it, you know Marc said something really important, "Have a good plan." I would argue, have a good partner. If you don't have a CISO who's got the chops to be dealing with these types of problems, that's when you need a partner like US Signal to really step in and take you through what's involved in a realistic plan, something that's not going to break the bank, something that's really going to protect your business going forward, because these things are very real. >> One of the concerns I have in this topic is that things happen really fast these days. So, if there are problems, they replicate very, very quickly. How do you address that problem? Is it architecture, analytics, I'm sure process, maybe you could add some color to that. >> All of the above. Having those controls in place, those segregations, we've got, obviously, clear segregation between our management and customer data plans. And each of our customer data plans are separate from each other. It's secure multi-tenancy, not just multi-tenancy. So yeah, it's important to keep those delineations, user access, making sure that people only have access to what they need, and a lot of that, again, is covered by those compliance practices and paying close attention to what they have. There are reasons they have these guidelines and these rules and these audits. It's to help, in large part to protect against that. >> You mentioned before, Marc, you're a heavy VMware user, Infinidat, it's kind of the new kid on the block. People said "Oh, they'll never be--" >> Marc: Not for us. >> What's that? >> Not for us. >> Not for you, right, but for the storage industry. Doc and I have been in the storage industry a while. But, I'm curious as to what you want from a supplier like Infinidat, why you chose Infinidat? How're they doing with regard to VMware affinity, all those things people tend to talk about as important. >> Marc: All right, well-- >> What do you think is important? >> Well, in the Infinidat experience, the company experience, the support experience, it is the benchmark by which we judge all other vendors now. It's that good. The working with us whenever we need equipment, obviously they've got, the price per terabyte is hard to beat with the way they're able to leverage that technology. The responsiveness, if we've needed something in a hurry they've been able to get it to us in a hurry, It ties in extremely well with our infrastructure because we scale so quickly, right? Trends are very hard with us, because there's all these hockey sticks. It's going, going, going, we get a big order and it goes up really fast. I think the theme right now is scale to win? >> Yep. >> So that resonates with us because by having that in place and having that scale ready to go, we don't even need to anticipate those hockey sticks because it's already there. >> Great. Well, gentlemen, thanks for the time. We appreciate that. Doc, Infinidat. (laughs) >> Thank you very much it's great to see you both again. >> John: Look forward to see you in 2020, right? >> I'll be back. >> Yeah, it's become an annual thing. >> Michael said we'll be celebrating our 20th year, so I'm looking forward to seeing-- >> And this is our 10th year here, so anniversaries all across the board. >> Congratulations. >> Congratulations. >> Have a good rest of the show, we appreciate the time. >> Thank you very much. >> Thank you. >> Back with more VMworld 2019, we continue our coverage live here on theCUBE. We're at Moscone Center North in San Francisco. (upbeat electronic music)

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation. >> Hello and welcome to the Special Cube conversation with remote gas. Steve, harried managing director of General Catalyst, is he's a venture capitalist. >> Former >> CTO of the M. Where? Cube alumni. Steve, welcome to this special cube conversation coming in remote from Palo Alto. You're right across town, but still grab you big news happening. And also get your thoughts on the emerald 2019. Welcome to our remote conversation. >> Yeah, we were close. And yet this makes it even more convenient. We >> love the new format. Bring people into no matter where they are, no matter. Whatever it takes to get the stories we want to do that. And two important ones having. We know the emeralds coming next week. But congratulations. In order to you and your portfolio companies signal FX, another cube alumni from we've been covering since the beginning of their funding acquisition. Bye, Splunk today for over a billion dollars. 60% in cash and 40%. And stop. Congratulations. You've been on the board. You've known these guys from VM. We're quite a team. Quite an exit It's a win win for those guys. Congratulations. >> Yeah, Great group of guys. Several, which were at being where, as you as you mentioned, and as you've had on your show, that's great. They were doing a really good job of monitoring and getting metrics about applications and how they're doing it. And they're marrying it with spunk, stability to ingest logs and really understand operational >> data. And I think that combination will be very powerful. >> It brings kind of what we've been monitored. Calling Cloud 2.0, Suzie, monitoring 2.0, is really observe ability As the world starts moving into the kinds of service is we're seeing with Cloud on premises operations more than ever, that game has changed much more dynamic, and the security impact is significant. And certainly as as applications connect with its coyote or any I p device having that day, that scales really critical part of that. And I know signal left fax was one of those companies where you invested early, and I remember interviewing a couple of years ago in saying, Damn, these guys might be too early. I mean, they're so smart, they're so on it. But this is an example of skating to where the puck is As we increase, Key would say, These guys were just hitting their stride. Steve, can you Can you share any color commentary on on the deal and or you know why this is so important? >> Well, they've been at this for a long time, and they're a great team. I've been involved. Is investor less time? Obviously. But it was the really original team out of Facebook monitoring really at scale applications and then trying to take that technology that Facebook could use and applied it to our world. And, you know, as you discovered, we're in a world of micro service's and containers, and that is definitely hitting its stride right now. And so they were in the right place knowing how >> to monitor this very fast moving >> information and make some sense out of it. So you're a really good job on their part, and it was a pleasure to be >> along for part of the ride with him. >> It's great to me, great founders that have a vision and stay the course because, you know it's always it's always tricky when you're early to see the future especially around their top micro surfaces and containers way back before became the rage and now more relevant operationally for enterprises, it's easy to get distracted and man that fashion. We'll just jump on this trend of this way. They stayed the course. They stayed the nose to the grindstone and now observe ability. Which, to me is code word for monitoring. 2.0 is probably one of the hottest segments you saw Cummings going public companies filing the pager Duty dynatrace. Now you guys with your acquisition with Signal FX, This is an important sector this would normally be viewed in. I t. Rule is kind of list of white space, but it seems to be a much bigger landscape. Can you comment on your view on this and why it's so important? Why is observe ability so hot? Steve? >> Well, it's been this actually had a great market to be in for quite a while. They've been a large number of companies, continue to be both built up, and it's pretty simple. That amount of e commerce, or the amount of customer interactions you're having over applications and over the Web has gone up, and so anything that's not performing well or as downtime literally cost you a lot of money as a company. And so as these applications get more complex and they're being relied on >> Maur for revenue and for custom directions, >> you simply have to have better tools. And that's gonna be something that continues to evolve, that we got more complex, absent, more commerce is going >> to go through them. >> Complexity is actually something that people, a lot of people are talking about. I want to ask you something around today's marketplace, but I want you to compare and contrast it, similar to what your experience wasn't v m Where were you? The CTO virtual ization of all very, very quickly on ended up becoming a really critical component of the infrastructure, and a lot of people were pooh poohing that initially at first, then all sudden became. We've got to kill the M where you know so the resiliency of the M, where was such that they continue to innovate on virtualization, and so that's been a part of the legacy of V M wear, and the embers will cover next next week. But when you look at what's happening now with cloud computing and now some of the hybrid cloud up opportunities with Micro Service's and other other cool things. The role of the application is being is important part of the equation. It used to be the standup infrastructure, and that would enable the application to do things virtualization kind of change that game. Now you don't need to stand up. Any infrastructure could just deploy an application, and the infrastructure can be code and be self form, so you can have unique requirements. As infrastructure driven by the application, the whole world seemed to have flipped around. Do you see it that way? Is that accurate assessment? What's your thoughts on that? >> I think you're right on a bunch of fronts. People have been calling a different things, but the beauty of the, um where and you know this is a while ago now, but the reason it was successful is that you didn't have to change any of your software to use. It sort of slid him underneath an added value. But at the same time applications evolved. And so the that path of looking like hardware was something that was great for not changing applications. You have to think about a little differently when people are taking advantage of new application patterns or new service. Is that air in the cloud? And as you build up these as they're called cloud Native applications, it really is about the infrastructure. You know. It's job in life is to run applications. It sort of felt like the other way around. It used to be you wrote an application for what your infrastructure was. It shouldn't be like that anymore. It's about what you need to do to get the job done. And so we see the evolution of the clouds and their service. Is that air there? Certainly the notion of containers and a lot of the stuff that being where is now doing has been focused on those new applications and making sure Veum, where adds value to them, whatever type >> of application they are. >> It's interesting one of the exciting things in this way that we're on this year around multi cloud hybrid cloud in Public Cloud Now that we've kind of crossed over to the reality that public cloud has been there, done that succeeded I call that cloud 1.0, you saw the emergence of hybrid cloud. Even early on, around 2012 2013 we were talking about that of'em world instantly pad Kelsey here, but now you're seeing hybrid cloud validated. You got Outpost, you've got Azure stack, among other things. The reality is, if you are cloud native, you might not need to have anything on premise. Like companies like ours with 50 plus people. We don't have an I T department, but most enterprises have stuff on premise, so the nuance these days is around. You know, what's the architecture of of I T. These days, we add security into It's complicated. So these debates can there be a soul cloud for a workload? Certainly that's been something that we've been covering with the Amazon Jet I contract, where it's not necessarily a soul cloud for the entire Department of Defense. It's a soul cloud for the workload, the military application workload or app. The military. It's $10 million application, and it's okay to have one cloud, as we would say, But yet they're going to use Microsoft's cloud for other things. So the ODS having a multiple cloud approach, multiple environments, multiple vendors, if you will, but you don't have to split the cloud up. Her say This is kind of one of those conversations really evolving quickly because there's no real school of thought around this other than the old way, which was have a multi vendor environment split the things. What's your thoughts on the the workload relationship to the cloud? Is it okay to have a workload, have a single cloud for that workload and coexist with other clouds? >> It's funny. I've been thinking about this more lately. Where if you went back earlier in time, forgetting cloud, there used to be a lot of different type of servers that you >> can run on, whether it >> be a mainframe or a mini mainframe or Unix system or Olynyk system. And to some extent, people are choosing what would run where, based on the demands of the application, sometimes on price, sometimes on certifications or even what's been poured into the right one. So this is a beating myself, you know, that's that's a while ago. It's not too different to kind of think about the different kind of cloud service is there out there, whether you're running your own on your own data center or whether you're leveraging one from the other partners. I really do think in the ideal world you get your choice of the best possible platform for the application across a variety of characteristics. And it's kind of up to the vendors of management software and monitoring software at security software to give you more flexibility to choose where to run. And so for getting D'Amore exactly. But think of a virtualization layer that really tries to abstract out and let you more fluidly run things on different clouds. Do you think that's where a lot of the the core software is head of these days really >> enable that toe work better >> as a >> 1,000,000 other use cases, but with storage being moved around >> for disaster recovery or for whatever it else might >> be? But that quarter flexibility reminds me a lot of choosing what application >> would want. Run would run where within your own company >> and the kubernetes trend in containers certainly really makes that so much more flexible because you can still run VM. Where's viens beams under the covers over Put stuff on bare metal a lot of great opportunities that's exciting >> and you slap in a P I in front of them and micro service is sort of works in tandem with that so that you could really have your application composed >> across multiple environments. >> And I think the ob surveilling observe ability is so hot because it takes what network management was doing in the old way, which is monitoring. Make sure things are operating effectively and combining with data. And so when I heard about the acquisition of signal effects into Splunk, I'm like, There it is. We're back to data. So observe ability is really a data challenge and opportunity for using what would be a white space monitoring. But it's more than monitoring because it's about the data and the efficacy of that data and how it's being used, whether it's for security or whatever your thoughts >> s. So there's more data than ever, for sure, and so being able to stream that in being able to capture it at cost, all that is a big part of our environment still working. The key thing is turning that into some actionable insight, and whether you're using no interesting calculations for that or different forms of machine learning like that's where this really has to go is with all this data coming in. How do >> I avoid false false >> positives? How do I only alert people when needed, then that allows you to do what everyone's talked about for 30 years, which is automatic remediation. But for now, let's talk about it. Is how do I process all of this rich data and give me the right information to take action? >> Do you want to thank you for coming on this promote cube conversation? You've been with us at the Cube since 2010. I think our first cube event was A M C. World 2010. That show doesn't existing longer because that folded into Del Technologies world. So VM world next week is the last show standing that has been around since the Cube. You've been around? Of course, you guys had VM worlds had their 10th anniversary was 2013 as a show. But this is our 10th year. Well, thank you for being part of our community and being a contributor with your commentary and your friendship and referral. Appreciate all that. So I gotta ask you looking back over the 10 years since you been with Doug, you've vm world. What's the most exciting moments? What are moments that you can say? Hey, that was an amazing time. That was a grind, but we got through it. Funny moments. Your thoughts. >> Boy, that's a tough question. I've enjoyed working with you, John and the Cube. There's been somebody really interesting things for me. The sum of the big acquisitions that we went through a V Um, where? Where? I think the NSX exposition. When we get a syrah, I think that really pushed us an interesting spots. But we have gone through, uh, I pose an acquisition ourself by the emcee begun Theo. It's a pretty vicious competition from Be Citrix Airs in or Microsoft. Yeah, that's just the joy of being a These companies is lots of ups and downs along the way that they almost kind of fit together to make an exciting life. >> What was some moments for you? I know you had left was the 2015 or 26 boys with your last day of >> the world. You go now, you know about six years. >> What do you miss about the end? Where >> the team is what everyone kind of cliche says. But it's totally true. The chance to kind of work with all those people at the executive staff all the way down to like these awesome engineers with Koi is so I definitely missed that Miss Shipping products. You don't get to do that as much directly as a venture capitalist. But on the flip side, this is a great world to be, and I get to see enthusiastic. You're very optimistic founders all day long, pushing the envelope. And while that was existing at the end where, uh, it's it's what I see every single day here. >> You've been on The Cube 10 times at the M World. That's the all time spot you're tied for. First congratulates on the leaderboard. It's been a great 10 years. Going forward. We've seen are so good. Looking back, I would say that you know Palmer, it's taking over from Diane Greene. Really set the table. He actually laid out. Essentially, what I think now is a clearly a cloud SAS architecture. I think he got that pretty much right again. Or maybe early in certain spots of what he proposed at that time. There's some things that didn't materialize is fast, but ultimately from core perspective. You guys got that right, Um, and then went in Try to do the cloud. But then and this year it comes in for suffered to find, you know, line with Amazon. And since that time, the stock has been really kind of it on the right. So, you know, some key moments there for Of'em. Where from Self >> Somali. More stuff. It's fun to see Pivotal now possibly coming back into after after getting started there. But I think you know, there's there's a hugely talented team of execs there. Pat L Singers come >> in and done a great job. I think, Greg, >> you and all these folks that Aaron, >> there are good thinkers. And so I >> think you'll consider just continue to see it evolved. Quite event and probably some cool announcements next week. >> Talk aboutthe roll Ragu and the team play because he doesn't really get a lot of the spotlight. He avoids it. I know he did talk to him privately that he won't come on the Q. I don't know what the other guys go on other guys in jail, so he's been instrumental. He was really critical in multiple deals. Could you share some insight into his role at bm bm were and why it's been so important. >> I'll push him to get on, especially now that you have remote. You can probably grab him now. He and Rajiv and Rayo Funeral Just all the guys air. I think he and Reggie basically split up half and half of the products. But Roger is very, very seminal in the whole cloud strategy that has clearly been working Well, he's a good friend in a very smart guy. >> Well, I want you to give me a personal word that you're gonna get me in a headlock and tell him to come on the Cube this year. We want him on. He's a great, great great guest. He's certainly knowledgeable going forward. Steve, 10 years out, we still got 10 more years of great change coming. If you look at the wee that's coming, you're out investing in companies again. You had one big exit today with the $1,000,000,000 acquisition that was happen by Splunk and signal effects. Ah, lot more action. You've been investing in security. What's your outlook? As you look at the next 10 years is a lot more action to happen. We seem to be early days in this new modern era. Historic time in the computer industry as applications without dictating infrastructure capabilities is still a lot more to do. What do you excited about? >> There's a million things I get to see every day, which are clearly where the world is headed. But I think at the end of the day there's there's infrastructure, which the job in life of infrastructure is to run applications. And so then you look at applications. How are they changing and what is the underlying fabric gonna need to do to support them? And if you look at the future of applications, it's clearly some amazing things around artificial intelligence and machine learning to actually make them smarter. It's all different factors form factors that they're running on and being displayed on. I think we clearly have a world where with the next generation of networking, you could do even more at the edge and communicate in a very different way with the back end. I kind of look at all these application patterns and really trying to think about what is the change to the underlying clouds and fabrics and compute that's gonna be needed to run them. I think we have plenty of head room of interesting ideas ahead. >> Stew, Dave and I were talks to Dave. Stupid Valenti student and I were talking about, you know, as infrastructure and cloud get automate as automation comes in, new waves are gonna be formed from it. What new waves do you see? Is it like R P ay, ay, ay, ay. Because as those things get sucked in and the ships and two new waves What? Oh, that's some of the key ways people should pay attention to. I'm not saying the industries is going away, but as it becomes automated, and as the shift happens, the value still is there. Where is those new waves? >> Well, then, today it looks like most applications they're gonna be composed of a lot of service is, um and I think they're gonna be able. They're going to need to be displaying on everything from big screens to small screens to purely as a headless 80. I front ends, and so again, I think at the end of the day, this this infrastructure is gonna have to have a lot of computation capability after crunch do tons of data but also have to stitch together these connections between components and provide really good experiences and predictability in the network and all those air very hard problems that we've been working on for a while. I think we'll keep working on them and new forms for the next 10 years at least. >> Awesome. Steve. Thanks for being a friend with us in the queue, but you're funny. Favorite moment of the Q. Can you share any observations about the cube and your experiences? Your observations over the 10 years we've come a long way, >> you go ugly, actually enjoyed it. I mean, it's a microcosm of all the other stuff going on, but I saw your first little box that you built and used for the Cube like that was that was really cool. But now the fact that I'm on my laptop, you doing this over the network and it's showing up is pretty awesome. So think you're following the same patterns of the other, have the other applications moving the cloud and having good user experiences. >> Cube native here software native Steve. Thank you so much for stating the time commenting on the acquisition. I know it's fresh on the press. Ah, lot more analysis and cut to come next week. It's certainly I'll be co hosting at Splunk dot com later in the year. So I'm looking forward to connect with a team there and again. Thanks for all your contribution into the cube community. We really appreciate one. Thank you for your time. >> Thanks. You guys are awesome. Thanks for chatting. >> Okay. Steve Herod, managing director at general counsel, Top tier VC From here in Silicon Valley and offices around the world, I'm John for breaking down the news as well as a V Emerald preview with the former CTO of'em. Were Steve hair now a big time venture capitalists. I'm John Ferrier. Thanks for watching.

our Studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hello everyone welcome to the special cube conversation with a remote guest Steve Herod managing director of general kennel s he's a venture capitalist former CTO of VMware cube alumni Steve welcome to this special cube conversation coming in remote from Palo Alto you're right across town but still we're gonna grab you big news happening and also get your thoughts on the Emerald 2019 welcome to our remote conversation yeah hey Jon yeah we're close and yet this makes it even more convenient go we'd love the new format of bring people into no matter where they are no matter what whatever it takes to get the stories we want to do that and and two important ones to having we we know vm world's coming next week but congratulations in order to you and your portfolio companies signal FX another cube alumni firm we've been covering since the beginning of their funding acquisition by Splunk today for over a billion dollars sixty percent in cash and forty percent in stop congratulations you've been on the board you've known these guys from VMware quite a team quite an exit it's a win-win for those guys congratulations yeah great group of guys several of which were at VMware has you as you mentioned and as you've had on your show that's great they were doing a really good job of monitoring and getting metrics about applications and how they're doing it and they're marrying it with spunks ability to ingest logs and really understand operational data and I think the combination will be very powerful it brings kind of what we've been monitoring cloud 2.0 essentially monitoring 2.0 is really observability as the world starts moving into the the kinds of services we're seeing with cloud and on-premises operations more than ever that game has changes much more dynamic and the security impact is significant and certainly as applications connect whether it's IOT or any IP device having that data at scale is really a critical part of that and I know signal FX was one of those companies where you invested early and I remember interview them a couple years ago and saying damn these guys might be too early I mean they're so smart they're so on it but this is an example of skating to where the as Wayne Gretzky would say these guys were just hitting their stride Steve can you can you share any color commentary on on the deal and or you know why this is so important well they've been at this for a long time and they're a great team I've been involved as an investor less time obviously but yeah it was the really original team out of Facebook monitoring really at scale applications and then trying to take that technology that Facebook could use and applied it to our world and you know as you discovered we're in a world of micro services and containers and that is definitely hitting its stride right now and so they were in the right place knowing how to monitor this very fast moving information and and make some sense out of it so yeah really good job on their part and it was a pleasure to be along for part of the ride with them it's great to meet great founders that have a vision and stay the course because you know it's always tricky when you're early to see the future especially around ok we're talking micro services and containers way back before it became the rage and now more relevant operationally for enterprises it's easy to get distracted and it's fashion well just jump on this trend or this wave they stayed the course they stayed the nose to the grindstone and now observability which to me is code word for monitoring 2.0 is probably one of the hottest segments you saw companies going public companies filing the pager Duty dynaTrace now the you guys with your acquisition with signal FX this is an important sector this would normally be viewed in the IT world as kind of lists of white space but it seems to be a much bigger landscape can you comment on your view on this and why it's so important why is observability so hot Steve well it's been this actually been a great market to be in for quite a while they've been a large number of companies continuing to be both built up and it's pretty simple the amount of e-commerce or the amount of customer interactions you're having over applications and over the web has gone up and so anything is not performing well or house downtime literally cost you a lot of money as a company and so as these applications get more complex and they're being relied on more for revenue and for customer interactions you know simply you have to have better tools and that's gonna be something that continues to evolve we have more complex apps and more commerce is going to go through them complexity is obviously something that people a lot of people are talking about I want to ask you something around today's marketplace but I want you to compare and contrast it similarly to what your experience was at VMware when you the CTO you know virtualization evolved very very quickly and ended up becoming a really critical component of the infrastructure and a lot of people were pooh-poohing that initially at first and then all the sudden became we got to kill VMware and you know so the resiliency of VMware was such that they continued to innovate on virtualization and so that's been you know part of the legacy of VMware and VM roads will cover next next week but when you look at what's happening now with cloud computing and now some of the hybrid cloud opportunities with micro services and other other cool things the the role of the application is being is important part of the equation it used to be the stand up infrastructure and that would enable the application to do things virtualization kind of changed that game now you don't need to stand up any infrastructure you can just deploy an application then the infrastructure can be code and be self formed so you can have unique requirements as infrastructure driven by the application the whole world seems to have flipped around do you see it that way is that accurate assessment and what's your thoughts on that I think you're right on a bunch of fronts people have been calling it different things but the beauty of VMware and you know this is a while ago now but the reason it was successful is that you didn't have to change any of your software to use it sort of slid in underneath and added value but at the same time applications evolved and so the path of looking like hardware was something that was great for not changing applications you have to think about a little differently when people are taking advantage of new application patterns or new services that are in the cloud and as you build up these as they're called cloud native applications it really is about the infrastructure you know it's job and life as to run applications and it's it sort of felt like the other way around it needs to be you wrote an application for what your infrastructure was it shouldn't be like that anymore it's about what what you need to do to get the job done and so we see the evolution of the clouds and their services that are there certainly the notion of containers and a lot the stuff that VMware is now doing has been focused on those new applications and making sure VMware adds value to them whatever type of application they are it's interesting one of the exciting things in this wave that we're on this year around multi cloud hybrid cloud and public cloud now that we've kind of crossed over to the reality that public cloud has been there done that succeeded I call that cloud 1.0 you saw the emergence of hybrid cloud even early on around 2012-2013 we were talking about that at VMworld you know certainly Pat Kelson here but now you're seeing hybrid cloud validated you got outpost you got Azure stack among other things the reality is if you are cloud native you might not need to have anything on premise like companies like ours with 50 plus people we don't have an IT department but most enterprises have stuff on premise so the the nuance these days is around you know what's the architecture of IT these days when you add security into it's complicated so there's debates can there be a sole cloud for a workload certainly that's been something that we've been covering with the Amazon Jedi contract where it's not necessarily a sole cloud for the entire department of defense it's a sole cloud for the workload the military application workload or app the military it's 10 billion dollar application and it's okay to have one cloud as we would say but yet they're gonna use Microsoft's cloud for other things so the DoD's having a multiple cloud approach multiple environments multiple vendors if you will but you don't have to split the cloud up or say this is kind of one of those conversations really evolving quickly because there's no real school of thought around this other than the old way which was have a multi-vendor environment split two things what's your thoughts on the the workload relationship to the cloud is it okay to have a workload have a single clap for that workload and coexist with other clouds it's funny I've been thinking about this more lately where if you went back earlier in time forgetting cloud there used to be a lot of different type of servers that you could run on whether it be a mainframe or a mini mainframe or UNIX system or a Linux system and to some extent people are choosing what would run where based on the demands of the application sometimes on price sometimes on certifications or even what's been ported to the right one so this is I'm beating myself but you know that's that's a while ago it's not too different to kind of think about the different kind of cloud services are out there whether you're running your own on your own data center or whether you're leveraging one from the other partners I really do think in the ideal world you get your choice of the best possible platform for the application across a variety of characteristics and it's kind of up to the vendors of management software and monitoring software at security software to give you more flexibility to choose where to run and so forgetting VMware exactly but think of a virtualization layer that that really tries to abstract out and let you more fluidly run things on different clouds I do think that's where a lot of the you know the core software is head of these days to really enable that to work better and so a million other use cases with with you know storage being moved around for disaster recovery or for whatever it else might be but that core of flexibility reminds me a lot of you know choosing what application would one run would run where within your own company and the kubernetes trend in container certainly really makes that so much more flexible because you can still run VMware's on the ends beams under the covers or put stuff on bare metal a lot of great opportunities so it's exciting and you slap an API in front of them and and micro-services sort of works in tandem with that so that you you could really have your application composed across multiple environments and I think the observable observability is so hot because it takes what network management was doing in the old way which is monitoring making sure things are operating effectively and combining with data and so when I heard about the acquisition of signal FX into Splunk I'm like there it is we're back to data so observability is really a data challenge and opportunity for using what would be a white space monitoring but it's more than monitoring because it's about the data and the efficacy of that data and how it's being used whether it's for security or whatever your thoughts so there's more data than ever for sure and so being able to stream that in being able to capture it at cost all that is a big part of our you know the environments we all work and the key thing is turning that into some actionable insight and whether you're using you know interesting calculations for that or different forms of machine learning like that's where this really has to go is with all this data coming in do I avoid false false positives how do i only alert people when needed and then that allows you to do what everyone has talked about for 30 years which is automatic remediation but for now let's talk about it is how do i process all of this rich data and give me the right information to take action see we want to thank you for coming on this promote cube conversation you've been with us at the cube since 2010 I think our first cube event was EMC world 2010 that show doesn't exist any longer because that folded into Dell technologies world so VM world next week is the last show standing that has been around since the cube cubes been around of course you guys had the VM worlds had their 10th anniversary I think was 2013 as a show but this is our 10th year I want to thank you for being part of our community and being a contributor with your commentary and your friendship and referral appreciate all that so I gotta ask you looking back over the 10 years since you've been with the cube VMworld what's the most exciting moments what are moments that you can say hey that was an amazing time that was a grind but we got through it funny moments your thoughts yeah boy that's a tough question I've enjoyed you know working with you John and the cube there have been so many really interesting things for me the some of the big acquisitions that we went through at VMware where I think the nsx acquisition when we get nasarah I think that really pushed us in an interesting spot but we had gone through IPOs and acquisition ourselves by EMC and we've gone through some pretty vicious competition from whether it be Citrix or Zin or Microsoft yeah that's just the joy of being at these companies it's lots of ups and downs along the way but they all kind of fit together to make an exciting life what were some moments for you I know you had left was a twenty fifteen or twenty six point eight vs world you go down there yeah about six years what do you miss about VMware the team is what everyone kind of cliche says but it's totally true the chance to kind of work with all those people at the executive staff all the way down to like these awesome engineers with Co ideas so I definitely missed that miss shipping products you don't get to do that as much as a venture capitalist but but on the flip side this is a great world to be and I get to see enthusiastic you know very optimistic founders all day long pushing the envelope and while that was existing at the EM where it's it's what I see every single day here you've been on the cube ten times at vmworld that's the all time spot you're tied but first congratulations on the leaderboard well it's been a great ten years going forward we've seen more so go looking back I would say that you know Palmer it's taking over from Diane Greene really set the table he actually laid out essentially what I think now as a clearly a cloud SAS architecture I think he got that pretty much right again or maybe early in certain spots of what he proposed at that time though some things that didn't materialize as fast but ultimately from a core perspective you guys got that right and then went in try to do the cloud but then and this year it comes in for a software-defined you know line with Amazon and since that time the stock has been really kind of up to the right so you know some key moments there for VMware from small somalia more stuff it's fun to see pivotal now possibly coming back into after after getting started there but I think you know there's there's a hugely talented team of executives there Pat Yeltsin jurors come in and done a great job I think Raghu and all these folks that are in there are good thinkers and so I think you'll consider to continue to see it evolve quite a bit and probably some cool announcements next week talk about the role Raghu and the team played because he doesn't really get a lot of the spotlight he avoids it I know he'd I've talked to him privately he won't come on the qoi let the other guys go on other guys and gals so he's been instrumental he was really critical in multiple deals could you share some insight into his role at VMware VMware and why it's been so important well I'll push them to get on especially now that you have remote you can probably grab him no he and Rajiv and andraia Ferrell just all the guys are I think he and regime basically split up half and half of the products but I know Raghu is very very similar in the whole cloud strategy that has clearly been working well he's good friend in a very smart guy well I want you to give me a personal word that you're gonna give him in a headlock and tell him to come on the cube this year we want him on he's a great great great guest he's certainly knowledgeable going forward Steve 10 years out we still got 10 more years of great change coming if you look at the wave that's coming you're out investing in companies again you had one big exit today with the billion dollar acquisition that was happening by Splunk and signal affects a lot more action you've been investing in security what's your outlook as you look at the next ten years there's a lot more action to happen we seem to be early days in this new modern era historic time in the computer industry has applications of now dictating infrastructure capabilities is still a lot more to do what are you excited about there's there's a million things I get to see everyday which are clearly where the world is headed but I think at the end of the day there's there's infrastructure which the job and life of infrastructure is to run applications and so then you look at applications how are they changing and and what is the underlying fabric gonna need to do to support them and if you look at the future of applications it's clearly some amazing things around artificial intelligence and machine learning to actually make them smarter it's all different factors form factors that they're running on and being displayed on I think we clearly have a world where with the next generation of networking you can do even more at the edge and communicate in a very different way with the backend so I kind of look at all these application patterns and really try to think about what is the change to the underlying clouds and fabrics and compute that's going to be needed to run them I think we have plenty of headroom of interesting ideas ahead stew Dave and I were talks to Dave Stuben they want this too many man died we're talking about you know as infrastructure and cloud get automated as automation comes in new waves are gonna be formed from it what new waves do you see is it's like RPAs a I I mean because as those things get sucked in and they ships in to new waves what are the some of the key ways people should pay attention to I'm not saying the inverse tress is going away but as it becomes automated and as the shift happens the value still is there where is those new waves well I think today it looks like most applications are going to be composed of a lot of services and I think they're gonna be able they're gonna need to be displaying on everything from big screens to small screens to purely as headless api friends and so again I think at the end of the day this this infrastructure is gonna have to have a lot of computation capability have to crunch through tons of data but also have to stitch together these connections between components and provide really good experiences and ability in the network and all those are very hard problems that we've been working on for a while I think we're gonna keep working on them and new forms for the next ten years at least awesome see thanks for being a friend with us in the cube what's your funny favorite moment of the Q can you share any observations about the cube and your experiences your observations over the 10 years we've come a long way you've come a long way actually I've enjoyed it I mean it's a microcosm of all the other stuff going on but I saw your first little box that you built and used for the cube like that was that was really cool but now the fact that I'm on my laptop you know doing this over the network and it's showing up is pretty awesome so I think you're following the same patterns of the other of the other applications moving to the cloud and having good user experience because cube native here software if the male native Steve thank you so much for staying the time commenting on the acquisition I know it's fresh on the press a lot more analysis and cut to come next week it's certainly I'll be co-hosting ATS plunks Kampf later in the year so I'm looking forward to connecting with the team there and again thanks for all your contribution into the cube community we really appreciate it one thank you for your time thanks John you guys are awesome thanks for chatting okay Steve Herod managing director at General Counsel top tier VC from here in Silicon Valley and they have offices around the world I'm Jean ferré breaking down the news as well as a VM real preview with the former CTO of VMware Steve hare now a big-time venture capitalist I'm John Ferrier thanks for watching [Music] you [Music]

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBEConversation. >> Hello everyone, welcome to Palo Alto's CUBE studios. I'm John Furrier, host of theCUBE. We're here for a special CUBEConversation as part of our new brand of tech leader series as well as Extracting the Signal From the Noise. We're here with Gary Conway, the CMO of Automation Anywhere, a hot startup, heavily funded, attacking a whole new market segment, that's kind of changing the game of value in digital, obviously, RPA, robotic process automation, is the buzz word. It's actually real, it's happening, we're seeing a lot of success in companies there. It's changing the way business is operated, business is structured, and value is created. Gary, thanks for joining me. >> My pleasure. >> So we covered your event, Automation Anywhere. You guys are essentially doing very very well, heavily funded, growing like crazy. RPA is one of the fastest growing segments in this next generation digital culture. You're seeing a lot of companies coming out attacking this. What's your perspective, why is RPA so important, why is it so hot? >> It's a pretty simple reason, actually. You know, the truth of the matter is that companies are now, because of RPA, able to automate parts of their business processes, or entire processes that they were never able to automate before, and they can do it with RPA at a relatively little cost compared to a lot of other technologies out there, especially from the big ERP vendors. We say that, and we really believe this, and we're finding this to be true, that since the onset of automation about 30 years ago, from the big technology companies, only about 20% of the processes that businesses manage now are actually automated. The 80% of them that are not automated are pretty much done by human beings, you know. Millions of human beings employed to manage those back office processes. RPA is enabling companies to actually automate more of those processes than ever before. >> Before we get started, just quickly define, what is RPA for the folks that are learning for the first time, because we're now seeing the concept really penetrating mainstream right now. It's becoming, frankly, a topic that's being discussed across most of the largest enterprises and small business, what is RPA? >> So RPA means robotic process automation. So think of them as robots that are built as predesigned software bots that you can plug into any business process, and it'll automate a part of that process, or the entire process, by just plugging it in. It actually is capable of observing what human beings do, remembering what human beings do, and then repeating that again and again and again, only in a fraction of a second. That's the easiest way to think of it. >> So when I think of robots, I think of like a machine, you know, moving things around, from, like, manufacturing, whatnot. It's beyond that, it's not just robots, it's software as well, and this is the key in all this. >> It is software, I mean. >> It is software, it's not robots. >> RPA is only software. >> It's only software. >> I think most people, when they think of robotics, do think of, you know, mechanical robots used in manufacturing. That's not what RPA is. RPA is robotics that is only constructed with preconfigured software. >> I want to get your take on the impact to business and how leaders are adapting to this, but first I want to get to the mainstream topic that is trying to be figured out, and the classic one is technology's going to automate my jobs away, and the example that I use is retail. Most people go to retail, and they think, you know, whether it's a person out of college, or someone working in retail, that oh my god, a robot's going to show up and move stuff on the shelves, and eliminate those jobs. It's not so much robots, per se, it's Amazon that's going to impact in retail. We know what Amazon and Walmart has done to commerce. So that's already happening, retail's impacted. It's not so much that jobs are going away, they're just changing. That's our opinion. Can you share your opinion on the impact of software automation to jobs? >> We agree that jobs are not going away. They will change, but I always tell people when I'm asked this question that there's not been one technology that's ever been introduced that has actually done anything but create more jobs, and I always use the example of the PC. You know, I'm old enough to remember when the PC was introduced, the headlines were what will people do with all this additional time? You know, people were predicting a three day work week because of all the efficiencies that would be created by the PCs, and in fact the opposite has happened. Technology actually makes people more productive, and when they're more productive they're capable of doing more things. So with the automation of certain things that people happen to be doing now, those people are being upskilled, they are being redeployed to other jobs, as we've seen in the past, and actually, more jobs are being created. >> You know, we cover a lot of the Big Data space going back to 2010 when we first started theCUBE, at Hadoop World, which that kind of had its course, but ultimately Big Data, which became AI, you know the bank teller example, you know the ATM was going to kill the branches, when in reality there's been even more branch offices-- >> That's what we're seeing, yeah. >> than ever before. So again, I think the argument is pretty clear from the data and the trend, technology is actually helping create new jobs, but not the jobs maybe that there were once there. That seems to be the big debate, so we agree with you on that. Now we applied some of our, not RPA, but we had some technology that applied to all of our videos that we did with you at your event, and a couple things came out of the entity extraction. I want to share with you, I want to get your reaction. Business hubs, human versus machines, complex problems, digital colleagues, digital worker, new potential applications, digital native companies, supply chain, system integrators, labor platforms, AI assistance, inefficiencies, and machine learning. These are key words that really kind of point to the next generation. This is essentially the language of your company. What's your reaction to that? >> Well, I'm not sure it's the language of our company as much as it's the language that people are using to determine what role they will play in the future, and what role, how they will impact their businesses going into the future. So these are not our terms, these are terms that exist in the space right now as people try to determine for themselves the role they will play in defining the future and how they will use technology to make their businesses more efficient. >> And companies are using cloud, for instance, to kind of reshape. We had a big conversation yesterday around, you know, do I want to be in the business of managing data centers, or be in the business of managing my business with technology. These concepts are interesting from an industry standpoint. Business hubs. Good concept, I get that. Digital worker. This is the impact that you guys are enabling. What's the managerial leadership role as an executive or a worker in these new cultural shifts? Because, as this is being enabled, new value is being created. Digital is enabling that. How does someone manage all this? What do you guys see, how do you see that playing out? >> Look, I think that whenever things are changing, and things are changing dramatically in business today, the only way to manage it is a day at a time. You can't project yourself so far into the future that you trip over the things that are immediately facing you now. So my suggestion would always be to evaluate options every day, every week, and make decisions when it's the right time to make decisions for your business. But let's go back to one of the terms you described, digital worker. So a digital worker in our view is actually available in what we call our bot store, which is a bot that is actually preconfigured to have skillsets that you would require. So let's just say you need an order-to-cash person, person who understands that, and it's a part of an automated process. The idea is that you would be able to download a digital worker with similar skills, and plug that bot into your process, and it would begin to work with, I would say, the skillsets of somebody who understands the order-to-cash process. That's really what a digital worker is. Now imagine that, in the future, and that future is not that far away, where every human being will be working side by side with a digital worker, so that the human being can offload the repetitive things that a digital something could actually do for them, and that digital worker would take on the task-based stuff, freeing up the individual to use their creativity to create higher order value for the business. That's really what we mean by digital worker and the importance of a digital colleague, for example. >> I think that it's a profound statement, and I think this is one of the cultural shifts that I see that this next generation workforce and leaders have to get their arms around, and in watching folks in Washington, D.C., we've been covering a lot of the procurement changes going on in government and businesses. There's a leveling up going on in the IQ of organizations, because that is a profound statement. Now we saw that with DevOps in cloud. You know, you talk to tech people, if you're doing the repetitive task more than three times, automate it. You're getting at something a little bit different. You're not just automating, you're adding intelligence to it, so what I like about the process automation area, is it's not just an undifferentiated, heavy lifting, mundane task. Yes it is, but there's an era of machine learning, you're seeing intelligence being applied to it, so it's truly becoming an augmentation to a human. That's kind of what I hear you saying. Do you agree with that, and is that something that you guys see happening, and what does that actually mean for the enterprise? >> No, I do agree with it, and we are at various stages of that evolution. But like anything else in business, and in life, you don't just flip a switch and all of a sudden people migrate to that new model, that's not how life really works. We evolve to those things, and I think what we're seeing is a very fast evolution to exactly what you just described. >> I want to get your thoughts on operationalizing new technology. You know, obviously, being an entrepreneur, I've done a bunch of startups, and the startup ethos is come on a narrow entry, get a landing area, and then sequence to the broader market opportunity. There's a lot of entrepreneurial ethos involved in how to operationalize something new like RPA, because you can't just, you know, shut down the old and bring in the new, there's a method there. This is a challenge in any new technology. How do you guys see this playing out? Because you guys are on the front end, bringing real value to the table, but people might want to get more aspirational and then get the reality. How do you get into the point of going into someone and saying I love what you guys do, what's the playbook, what do I do next? This is the challenge, can you share your thoughts on how an executive or a business can operationalize these benefits? >> So we have a lot of customers, 1800 customers, unique customers, and 2800 entities around the world that are using the software now. And I think that each of them had one thing in common. They started in bite-sized chunks. They said we're going to try this, and what's happening with RPA, which is one of the reasons it's growing so fast, is that once you try it, once you implement a few bots to automate the things that you weren't able to automate before, it starts ramping like this, right? It has a very very fast ramp-up. So you realize some successes in the processes that you begin to automate that you've never automated before. And the more you do it, the more you learn from it. The more you learn from it, the more you want to do it, the more processes you identify that could be automated, and should be automated, and what starts happening in most companies is they start adopting much much faster once they understand the benefits of it. And the benefits to business is driving higher levels of efficiencies, and reducing costs dramatically. >> So the tie to value is fast. >> Right, the value is very fast, compared to-- >> And that's driving the ramp-up, to your point. >> And that's driving the map. >> The flywheel kicks in, you start with a process that's known, and you automate it, wow, that's good, do it again, do it again. >> Correct. Well, do it again, and do it with more processes, right? And the other unique thing about this technology is human beings, once they understand the advantages of automating things that other human beings may have to do manually, most of those people who have been doing them manually will say I want more of that. We should be automating this, we should be automating that, and it actually makes them much more productive, and it makes them feel as if they are delivering higher value to the business themselves, and what an amazing human dynamic that is. >> You know, I was talking to Dave Vellante about this, we were talking about the TAM, the total adjustment market, for RPA, we're like, I think it's just in the trillions because with digital, everything is connected, so you can measure everything. Everything is ultimately a supply chain, whether it's network effect for internet, whether it's, you know, some process with cryptocurrency, whether it's blockchain or a process with cybersecurity, digital is pretty much connected, it's pretty much a supply chain. Some of them are more formed than others. This seems to be the entry point that most people would go to. Do they go to the supply chains first, or, better yet, what's the use cases that you see as the low hanging fruit that people come in on and automate? Is it simple supply chain stuff that's known, or are they applying it as they grow to other areas? >> It's very broad, but the fastest adoption, especially beginning about two years ago, were from the companies in industries like banking, other financial services, insurance, healthcare, manufacturing, which is supply chain, as you rightly point out. Those businesses that tend to be earlier adopters of technology have also become earlier adopters of RPA. But what we're finding now is it's now, because of the results that these businesses have demonstrated, and because digital native competitors are actually coming into the space and threatening what are sometimes referred to as legacy businesses, businesses are not delaying the investments they're making so that they can actually become more competitive, and when you think about that, it's not just the efficiencies that these technologies like RPA drive, but it's the ability to make businesses acutely more competitive than they've ever been before. >> That's a great angle, competitive strategy has always been one of those things where, you know, the cloud native world or digital native world was like oh yeah, pick one feature, innovate, and you can go beat an incumbent. The incumbent now has leverage in the marketplace, whether it's physical presence or other assets. Using RPA gives them a way to level up, so to speak. >> Level up, for sure. So let's just take something we're all familiar with, right? You can now go on your phone, and you can have a car at your house to take you somewhere in about four minutes in most cities, right? If you have an issue, you can solve that issue on your phone as well. You don't have to call anybody, you just solve it on your phone. These ride share companies have made it so simple, it's almost as if there's no such thing anymore as a front office or a back office. Digital native companies have brought those things together, and now there's one office. So that immediacy is what legacy companies are actually competing against, and if those companies don't adopt this kind of automation to make more efficient those processes and narrow the gap between customer facing and back office, they won't be able to compete. >> Yeah, they can turn a liability into an advantage, with software. Big big bullish on the software, I think the competitive landscape also is interesting, I'd like your thoughts on. There seems to be a battlefield, at least from my perspective, my opinion is that, okay, RPA software is out there, it's going to grow really fast. The competitive battle will be around intelligence. How do you guys view the competitive levers? How do you guys compete, what's the advantage? Is it intelligence, is it being more intelligent, is it more operational, what's the advantage you guys see vis-a-vis the competition? >> Yeah, so we're actually seeing a sort of a bringing together of technology, what we have considered to be strictly technology, and what's being described broadly now as artificial intelligence. Artificial intelligence is still evolving. Everybody has his own definition of what it really is, but what we're seeing, and I think in other sectors we're seeing the same thing, is now the merging of things that have truly been technology with things that are perceived to be artificial intelligence, and they're beginning to come together. What that will look like five years from now, nobody knows. What it'll look like 10 years from now, no one can even conceive of, but we're seeing that dynamic in place now, and this is the beginning. >> It's a great wave, excited to have you on and share your insights, Gary. It's great stuff you guys are doing over there at Automation Anywhere, love the, we love this wave, I think it's going to be relevant. My final question for you, though, is little bit different. You know, you're at a cocktail party, you're at a friend's house, you're at a confab, and you see people that aren't in the business, and they're like Gary, I need to get, I need to be more competitive. What do I do, what is this RPA thing, how do I change my culture, how do I get my people and my process aligned with software, what's the playbook, what's your advice? >> So what I would say is, get started as quickly as possible, because if you delay too long, you will be left behind. So that's would be my first bit of advice. The other, it would be to start slowly. Learn as quickly as you can. Don't worry about automating things that are hard to automate, go to the things that are easy to automate. Companies find that when they address those things first, they're actually able to drive more success faster, and then they will look for more and more opportunities based on what they've learned and the success that they've derived, and that's what happens to create this ramp effect, where it becomes almost viral-like. Where you have one process that works great, you automate that, you automate another one, you automate five more, 10 more, and before you know it, believe it or not, we have customers that are implementing more than 3000 bots over the last year and a half, and that's how they started. >> Get rid of the mundane work, you've got happy people, HR is happy, you've got more revenue coming in, you're more competitive as a business, this is a good value proposition. It's an easy sale. >> Nothing's easy, but it has a huge appeal. >> Gary, thanks so much for coming on and sharing your insights around RPA, appreciate it and congratulations on your success. >> Thank you. >> This is CUBEConversation, and I'm John Furrier here in Palo Alto, thanks for watching. (upbeat music)

>> live from London, England. It's the queue covering a ws summat. London twenty nineteen Brought to you by Amazon Web services >> Welcome back to London Summit Everybody, this is David Lamont and you watching the Cube, the leader in live tech coverage. We loved to go out to the events. We extract the signal from the noise. This is our one day coverage of a WS summit London, and it's packed house twelve thousand people here. The twenty six thousand people registered, which is just outstanding. Chris Bunches. Here's the general manager of a MIA for cloud reach, and he's joined by Mark Randy, whose CEO of signal FX. Gentlemen, welcome to the Cube. >> Thank you. >> Okay, let's start with signal effects. What's going on at the show? What's the buzz like? >> Very busy. Dozens deep. A lot of demonstrations feature in our massively scalable metrics platform and distributed tracing platform. So we've had a very good show. Good showing in London. >> Good. We're going to get into some of that. Chris, tell us about cloud reach. What you guys do? >> Sure. So Cloud Reach was founded in two thousand and nine. So quite a long time ago in the history of cloud confusing, at least >> was right after the Cloud City with >> quite a pure vision around helping complex organizations to adults public cloud computing technologies to doom or faster and better. That's all we've ever done. It's all we ever intend to do way work these days with enterprise organizations across the cloud lifecycle starting with adoption, helping them to understand White Cloud. How am I going to do this? How am I going to move my data center's into the cloud? How am I gonna build new services moving on through the life cycle? We help them with that. At that migration, we helped them to shut down their data centers on rebuild them in a WS. We helped build New Cloud native Services. Using the latest offerings from from Amazon and other cloud providers, we worked with him on Data analytics, helping them to generate insights from their data. Data flows in an ever faster pace from across the across the world into their organization. On all of that is wraps with an MSP manage service twenty four hours a day, seven days a week. >> So, Mark, I gotta ask you so back back in the day, the narrative was that the public law was going to kill every man, his service provider out there. It's been nothing but a tailwind for your business. Business is booming. What's what actually happened to give you that? Left >> on the signal effects side I look, the big trends are the move to the cloud number one. The second piece is just a change in the architecture's you know, the move to communities, the introduction for elastic burst e type use cases of things like Lambda and and that even more importantly, just the process of developing software movement from, you know, waterfall, Dad, agile and the Whole Dev ops movement in introduction of micro services. So that's it's It's just a lot of a lot of these ways been going on for quite some time, but they're really starting to hit the shore to shore right now, and I think it's been a great great opportunity for companies like Cloud Reach Tio to take advantage of were very excited by the partnership. >> Well, it has. It has ripple effects on the rest of the business, doesn't it? I was saying earlier in a segment that it used to be the business of No, we can't do that because and now you look around this audience, it's all doers and builders, and, you know, it's it's actually great marketing because it works, doesn't it? So clouded has been a fundamental component of >> Yeah, I mean, our whole businesses around making t v enabler helping businesses to innovate. Once upon a time, the message was all around. Cost saving is the reason to move to the cloud, and there's still an element of that. Nobody wants to pay Mohr, but actually, increasingly, what we're seeing is organizations moving to Amazon because they want the agility, they want to move faster. And they don't want to be the the culture of no and have a process that takes six months to deliver a new service to the business. They want to be out of deliver things in hours or minutes in the some cases, and they want to do so quickly on they want to innovate, a pace that they've never been able to before, partly from a competitive threat perspective and partly from a market opportunity. There's so much, but we can deliver to customers if we put our minds to it and use the primitives, the Amazon providers, as building blocks to enable new >> services. You know where you live in the Bay Area. I spent a lot of time out there, were based in Palo Alto and use a vortex that unique that sometimes I think way think that that's where all the action is. You come to London and you see all these startups. Every business is becoming a software company. And you know, we don't in Silicon Valley in America have a monopoly on innovation anymore, >> not even close. So there's a lot of great innovation all over Europe. Uh, here in the U K. All the way to Northern Europe, Doc, uh, Paris Way we see it across the board. So >> So what are people doing? They building new cloud native APS in the public loud. Are they doing a lifted shift and trying to get more agility out of those traditional APs? What's the landscape? Looks like? >> It's ah, combination of the two. The startup organizations, of course, is starting with no legacy. There's nothing to my great and they are building cloud native and they're doing so far, >> we have no I d >> no. Yeah, technically, before nine years, four hundred on eBay test migrations. But that's the only hardware for the museum. Exactly the larger organizations. They have huge volumes of legacy infrastructure, some of it dating back to the seventies. In the case of financial institutions or public sector, then all of that is an opportunity to modernize, and not just for the agility and innovation but in some cases just to reduce risk. There is huge business risk in these old, untouched, dusty, cobweb ridden servers that nobody understands anymore. And there's a really opportunity to move that to the public cloud, reduce and remove that risk. And while you're there, take advantage of the new technologies and innovative deliver a better service to you or in consumer whoever that may be >> so prik uber, Netease and micro services, even though containers have been around for a while. But the modern doctors ascendancy. You know why? To K was the year of the decade of modernization. It was like four or five years leading up to y two K at some I T shop said, Okay, we're going to modernize, but but none of these micro services existed, so it really was. It was about dates, maybe some application portfolio rationalization. What's different today that I could take those apse that were written in the seventies with a lot of custom code? How am I able to modernize, though >> I think it's the maturity of the services. You look at something a platform like Amazon. There's one hundred twenty hundred thirty, or Mohr. It grows almost every week. Building blocks primitives, the Amazon are providing, and its a rating on it. At an incredible rate on DH, there's almost a service for everything. And when you think they've run out of services to introduce, a new services is created. And, you know, we talked about micro services. They introduced Lambda back in two thousand fourteen, which was there. Serve Elice environment driving event based micro services architectures, and it's ahead of the game. It's ahead of the curve. It's causing people to think very differently about what's even possible from a night perspective. And there's no way. In most organizations, you, Khun, build that kind of infrastructure on that kind of platform that is build and costs you on a Microsoft microsecond basis. I mean, it's it's >> incredible. It was amazing. I remember the first virtual machine. It would be anywhere that I saw spun up like, Wow, this is going to change the world. And then the cloud comes along like a while. This is going to change the world. And now survivalists. I don't even have to deploy servers anymore. It's side by Amazon >> way. See this? Even even in some of the more traditional organizations we we worked with in the UK and in Germany and France and elsewhere, you don't even need to be looking at service. Just the ability toe programmatically spin up a virtual machine without a human touching anything. That's incredible to some organizations, right? They're used to it, taking six months to provision of infrastructure to deploy an application. Now they can click a button, and by the time they've made a cup of coffee, it's it's up and running, and it's It changes the way people >> think So much Talk about Cloud Region signal effects. What's the partnership like between you two and what's your partnership like with eight of us? >> Um, on the cloud reach side, we went through an extensive evaluation by cloud reach, and over several months they evaluated all the alternatives on the market and ended up selecting us to be their standard for their many service provider business. It's We're super excited about that. On the go for it, we're rolling that out with them there. Current customer based on DH. We were hoping that, uh, using signal effects, that cloud reach that will help them be the point of spear on all cloud native. You know, in their marketplaces, they go pursue other customers, so it's pretty excited about. >> So it's not a pressure release deal, not a Barney deal. Like we like to say that >> they're up there, They're a paying customer. And, you know, I made a big bet on signal effects going forward. >> So why the choice to go with manage service provider? You have You could have built it yourself and take us through that. >> Yeah. I mean, the nature of the business we're in is very much predicated on the fact that you don't build it yourself. You know, you look at the market and if somebody is already doing it well and provides excellent service as a commodity, you use it. We've been in the MSP space since round about twenty ten very soon after the the company was was founded, and we know it pretty well. We have a large customer base. We are one of the top tier MSP for along the major cloud vendors in the world, lots of large organizations. However, as we look to refresh our tooling with a view on Maura, an application centric approach, which is what all of our customers want and expect a CZ we look to micro services and the very latest platforms and technologies he's being released by the hyper scale cloud vendors. We recognize the need for a newer, more modern tooling on DH. After a thorough evaluation, a CZ mark says signal effects came out on top. Why is that? Partly it's the cloud native element. You know, some of that sounds a little bit like a marketing buzzword, but in reality, what it means is the company was founded relatively recently and as a result, was geared towards modern technology. So out of the box they support doctor, they support containers, they understand, and they're orchestrated around micro services. It deals with scale on volume, and we we want to low test things in a big way. We only serve large scale and surprise customers. And they are going to throw tens of thousands of containers on micro services at their tooling, and it has to be able to track tto handle that massive volume of transactions. >> It's a complicated picture, actually. You know, sometimes micro services aren't so micro. Yes, and you've got to secure all these containers. Got spinning up of'Em is easy. >> Well, >> you see multiples. So how do you guys deal with that? I mean, you're obviously experts at it, but But give us the sales pitch >> on. Yeah. So I think you kind of you covered it earlier with, You know, all these great new technology with introduction of micro services. I mean, developers in our writing it the running it, they're pushing code directly into production environment. You know, you went from releasing code once or twice a year, a few years back now toe several releases and you know your people lifting shift. They're starting with a few micro services. Someone we're getting up into the hundreds, even thousands in our most advanced deployments. It it it ends up being worth a situation Where Alright, all this innovation is great, but it also introduces a ton of complexity. And based on the way we've architect of our system, really time streaming like within seconds, you're going to need to see it, to react to it, whatever the use cases. And that's what differentiates signal FX is this massively scalable streaming architect we built for from a Metrix platform standpoint and then from an Eastern West standpoint for your from your custom code are Micro Services, a PM solution on top of that to go help measure what those transactions air how they're performing across the entire complex environment. So we feel like we're just purpose built for today to help in the lift and shift crowd and or for the more advanced customers, they're intothe point dozens, if not hundreds of micro services. >> Tell me more about this metrics platform you mentioned a couple times. What is that all about? >> Well, we start with essentially, you know, the three big pillars are logs, metrics and eight p. M. And you know, our company was found it. We have deep roots. Back in the two thousand seven ranges, our founders were you know, they built the monitoring stack at Facebook and so had several years, you know, kind of earning and learning that secret. You know, in the early days, they didn't call it Dev Ops. Back then they called it move fast, break things, didn't call >> it. They didn't call it >> a micro services. I mean, and then twenty, twenty, thirteen, early, two thousand fourteen. That's when the founders got together and started. The company is also the same time frame. Doctor came out. Were just purpose built for this for this environment. >> Final thoughts. Yeah. Thie event where you guys were headed. Maybe little road map, if you could. >> The event has been incredible. Every year it gets a little bit bigger. It gets a little bit more exciting. There's, ah, bigger range of organizations, different industries. And it changes a little bit over time. This year, financial services has been particularly of interest for us, but this event is a lot of large large banks, investment houses, those kind of companies here on DH. That's been really exciting for us. I think trend I'm most excited about is really around machine learning. Amazon talked about it in the keynote this morning and democratization of very, very complex technology bring it to the masses is a as a manage service that can be provisioned in minutes and seconds. And to me that something that's that's really exciting and using the signal FX platform, we're now in a position to provide manage service wrappers around the machine learning based solutions that we build for our >> customers. Yeah, the financial services. Interesting. Back in two thousand nine when you started, a lot of the banks in New York thought they could scale and compete essentially with KWS >> world. The world changes very quickly. Absolutely >> final thoughts for you. >> Yeah, I think they think we're moving past that point. You know, even the later adopters. I think we're moving past that point and look at that name there getting pressure from the startup community, whether it's intact or or any industry's gonna have that type of pressure. You talked about that y two k moment. I think in any vertical out there, it's that you know those cloud native type companies the companies are becoming software companies were going toe transform yourself or you're going to have some pressure from the start up going forward. We're >> guys. I'm thrilled that you could make time to come in the queue. Thank you. Thank you. Thanks for having us. All right. Keep it right there. But it is. Dave Alonso will be back with our next guests right after this short break. You watching the Cube from London? Eight of US Summit right back.