>> From the theCUBE studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Welcome to this week's Wikibon, theCUBE's insights powered by ETR. As we exited the isolation economy last year, supercloud is a term that we introduced to describe something new that was happening in the world of cloud. In this Breaking Analysis, we address the 10 most frequently asked questions we get around supercloud. Okay, let's review these frequently asked questions on supercloud that we're going to try to answer today. Look at an industry that's full of hype and buzzwords. Why the hell does anyone need a new term? Aren't hyperscalers building out superclouds? We'll try to answer why the term supercloud connotes something different from hyperscale clouds. And we'll talk about the problems that superclouds solve specifically. And we'll further define the critical aspects of a supercloud architecture. We often get asked, isn't this just multi-cloud? Well, we don't think so, and we'll explain why in this Breaking Analysis. Now in an earlier episode, we introduced the notion of super PaaS. Well, isn't a plain vanilla PaaS already a super PaaS? Again, we don't think so, and we'll explain why. Who will actually build and who are the players currently building superclouds? What workloads and services will run on superclouds? And 8-A or number nine, what are some examples that we can share of supercloud? And finally, we'll answer what you can expect next from us on supercloud? Okay, let's get started. Why do we need another buzzword? Well, late last year, ahead of re:Invent, we were inspired by a post from Jerry Chen called "Castles in the Cloud." Now in that blog post, he introduced the idea that there were sub-markets emerging in cloud that presented opportunities for investors and entrepreneurs that the cloud wasn't going to suck the hyperscalers. Weren't going to suck all the value out of the industry. And so we introduced this notion of supercloud to describe what we saw as a value layer emerging above the hyperscalers CAPEX gift, we sometimes call it. Now it turns out, that we weren't the only ones using the term as both Cornell and MIT have used the phrase in somewhat similar, but different contexts. The point is something new was happening in the AWS and other ecosystems. It was more than IaaS and PaaS, and wasn't just SaaS running in the cloud. It was a new architecture that integrates infrastructure, platform and software as services to solve new problems that the cloud vendors in our view, weren't addressing by themselves. It seemed to us that the ecosystem was pursuing opportunities across clouds that went beyond conventional implementations of multi-cloud. And we felt there was a structural change going on at the industry level, the supercloud, metaphorically was highlighting. So that's the background on why we felt a new catch phrase was warranted, love it or hate it. It's memorable and it's what we chose. Now to that last point about structural industry transformation. Andy Rappaport is sometimes and often credited with identifying the shift from the vertically integrated IBM mainframe era to the fragmented PC microprocesor-based era in his HBR article in 1991. In fact, it was David Moschella, who at the time was an IDC Analyst who first introduced the concept in 1987, four years before Rappaport's article was published. Moschella saw that it was clear that Intel, Microsoft, Seagate and others would replace the system vendors, and put that forth in a graphic that looked similar to the first two on this chart. We don't have to review the shift from IBM as the center of the industry to Wintel, that's well understood. What isn't as well known or accepted is what Moschella put out in his 2018 book called "Seeing Digital" which introduced the idea of "The Matrix" that's shown on the right hand side of this chart. Moschella posited that new services were emerging built on top of the internet and hyperscale clouds that would integrate other innovations and would define the next era of computing. He used the term Matrix because the conceptual depiction included not only horizontal technology rose like the cloud and the internet, but for the first time included connected industry verticals, the columns in this chart. Moschella pointed out that whereas historically, industry verticals had a closed value chain or stack and ecosystem of R&D, and production, and manufacturing, and distribution. And if you were in that industry, the expertise within that vertical generally stayed within that vertical and was critical to success. But because of digital and data, for the first time, companies were able to traverse industries, jump across industries and compete because data enabled them to do that. Examples, Amazon and content, payments, groceries, Apple, and payments, and content, and so forth. There are many examples. Data was now this unifying enabler and this marked a change in the structure of the technology landscape. And supercloud is meant to imply more than running in hyperscale clouds, rather it's the combination of multiple technologies enabled by CloudScale with new industry participants from those verticals, financial services and healthcare, manufacturing, energy, media, and virtually all in any industry. Kind of an extension of every company is a software company. Basically, every company now has the opportunity to build their own cloud or supercloud. And we'll come back to that. Let's first address what's different about superclouds relative to hyperscale clouds? You know, this one's pretty straightforward and obvious, I think. Hyperscale clouds, they're walled gardens where they want your data in their cloud and they want to keep you there. Sure, every cloud player realizes that not all data will go to their particular cloud so they're meeting customers where their data lives with initiatives like Amazon Outposts and Azure Arc, and Google Anthos. But at the end of the day, the more homogeneous they can make their environments, the better control, security, cost, and performance they can deliver. The more complex the environment, the more difficult it is to deliver on their brand promises. And of course, the lesser margin that's left for them to capture. Will the hyperscalers get more serious about cross-cloud services? Maybe, but they have plenty of work to do within their own clouds and within enabling their own ecosystems. They had a long way to go a lot of runway. So let's talk about specifically, what problems superclouds solve? We've all seen the stats from IDC or Gartner, or whomever the customers on average use more than one cloud. You know, two clouds, three clouds, five clouds, 20 clouds. And we know these clouds operate in disconnected silos for the most part. And that's a problem because each cloud requires different skills because the development environment is different as is the operating environment. They have different APIs, different primitives, and different management tools that are optimized for each respective hyperscale cloud. Their functions and value props don't extend to their competitors' clouds for the most part. Why would they? As a result, there's friction when moving between different clouds. It's hard to share data, it's hard to move work. It's hard to secure and govern data. It's hard to enforce organizational edicts and policies across these clouds, and on-prem. Supercloud is an architecture designed to create a single environment that enables management of workloads and data across clouds in an effort to take out complexity, accelerate application development, streamline operations and share data safely, irrespective of location. It's pretty straightforward, but non-trivial, which is why I always ask a company's CEO and executives if stock buybacks and dividends will yield as much return as building out superclouds that solve really specific and hard problems, and create differential value. Okay, let's dig a bit more into the architectural aspects of supercloud. In other words, what are the salient attributes of supercloud? So first and foremost, a supercloud runs a set of specific services designed to solve a unique problem and it can do so in more than one cloud. Superclouds leverage the underlying cloud native tooling of a hyperscale cloud, but they're optimized for a specific objective that aligns with the problem that they're trying to solve. For example, supercloud might be optimized for lowest cost or lowest latency, or sharing data, or governing, or securing that data, or higher performance for networking, for example. But the point is, the collection of services that is being delivered is focused on a unique value proposition that is not being delivered by the hyperscalers across clouds. A supercloud abstracts the underlying and siloed primitives of the native PaaS layer from the hyperscale cloud and then using its own specific platform as a service tooling, creates a common experience across clouds for developers and users. And it does so in a most efficient manner, meaning it has the metadata knowledge and management capabilities that can optimize for latency, bandwidth, or recovery, or data sovereignty, or whatever unique value that supercloud is delivering for the specific use case in their domain. And a supercloud comprises a super PaaS capability that allows ecosystem partners through APIs to add incremental value on top of the supercloud platform to fill gaps, accelerate features, and of course innovate. The services can be infrastructure-related, they could be application services, they could be data services, security services, user services, et cetera, designed and packaged to bring unique value to customers. Again, that hyperscalers are not delivering across clouds or on-premises. Okay, so another common question we get is, isn't that just multi-cloud? And what we'd say to that is yes, but no. You can call it multi-cloud 2.0, if you want, if you want to use it, it's kind of a commonly used rubric. But as Dell's Chuck Whitten proclaimed at Dell Technologies World this year, multi-cloud by design, is different than multi-cloud by default. Meaning to date, multi-cloud has largely been a symptom of what we've called multi-vendor or of M&A, you buy a company and they happen to use Google Cloud, and so you bring it in. And when you look at most so-called, multi-cloud implementations, you see things like an on-prem stack, which is wrapped in a container and hosted on a specific cloud or increasingly a technology vendor has done the work of building a cloud native version of their stack and running it on a specific cloud. But historically, it's been a unique experience within each cloud with virtually no connection between the cloud silos. Supercloud sets out to build incremental value across clouds and above hyperscale CAPEX that goes beyond cloud compatibility within each cloud. So if you want to call it multi-cloud 2.0, that's fine, but we chose to call it supercloud. Okay, so at this point you may be asking, well isn't PaaS already a version of supercloud? And again, we would say no, that supercloud and its corresponding superPaaS layer which is a prerequisite, gives the freedom to store, process and manage, and secure, and connect islands of data across a continuum with a common experience across clouds. And the services offered are specific to that supercloud and will vary by each offering. Your OpenShift, for example, can be used to construct a superPaaS, but in and of itself, isn't a superPaaS, it's generic. A superPaaS might be developed to support, for instance, ultra low latency database work. It would unlikely again, taking the OpenShift example, it's unlikely that off-the-shelf OpenShift would be used to develop such a low latency superPaaS layer for ultra low latency database work. The point is supercloud and its inherent superPaaS will be optimized to solve specific problems like that low latency example for distributed databases or fast backup and recovery for data protection, and ransomware, or data sharing, or data governance. Highly specific use cases that the supercloud is designed to solve for. Okay, another question we often get is who has a supercloud today and who's building a supercloud, and who are the contenders? Well, most companies that consider themselves cloud players will, we believe, be building or are building superclouds. Here's a common ETR graphic that we like to show with Net Score or spending momentum on the Y axis and overlap or pervasiveness in the ETR surveys on the X axis. And we've randomly chosen a number of players that we think are in the supercloud mix, and we've included the hyperscalers because they are enablers. Now remember, this is a spectrum of maturity it's a maturity model and we've added some of those industry players that we see building superclouds like CapitalOne, Goldman Sachs, Walmart. This is in deference to Moschella's observation around The Matrix and the industry structural changes that are going on. This goes back to every company, being a software company and rather than pattern match an outdated SaaS model, we see new industry structures emerging where software and data, and tools, specific to an industry will lead the next wave of innovation and bring in new value that traditional technology companies aren't going to solve, and the hyperscalers aren't going to solve. You know, we've talked a lot about Snowflake's data cloud as an example of supercloud. After being at Snowflake Summit, we're more convinced than ever that they're headed in this direction. VMware is clearly going after cross-cloud services you know, perhaps creating a new category. Basically, every large company we see either pursuing supercloud initiatives or thinking about it. Dell showed project Alpine at Dell Tech World, that's a supercloud. Snowflake introducing a new application development capability based on their superPaaS, our term of course, they don't use the phrase. Mongo, Couchbase, Nutanix, Pure Storage, Veeam, CrowdStrike, Okta, Zscaler. Yeah, all of those guys. Yes, Cisco and HPE. Even though on theCUBE at HPE Discover, Fidelma Russo said on theCUBE, she wasn't a fan of cloaking mechanisms, but then we talked to HPE's Head of Storage Services, Omer Asad is clearly headed in the direction that we would consider supercloud. Again, those cross-cloud services, of course, their emphasis is connecting as well on-prem. That single experience, which traditionally has not existed with multi-cloud or hybrid. And we're seeing the emergence of companies, smaller companies like Aviatrix and Starburst, and Clumio and others that are building versions of superclouds that solve for a specific problem for their customers. Even ISVs like Adobe, ADP, we've talked to UiPath. They seem to be looking at new ways to go beyond the SaaS model and add value within their cloud ecosystem specifically, around data as part of their and their customers digital transformations. So yeah, pretty much every tech vendor with any size or momentum and new industry players are coming out of hiding, and competing. Building superclouds that look a lot like Moschella's Matrix, with machine intelligence and blockchains, and virtual realities, and gaming, all enabled by the internet and hyperscale cloud CAPEX. So it's moving fast and it's the future in our opinion. So don't get too caught up in the past or you'll be left behind. Okay, what about examples? We've given a number in the past, but let's try to be a little bit more specific. Here are a few we've selected and we're going to answer the two questions in one section here. What workloads and services will run in superclouds and what are some examples? Let's start with analytics. Our favorite example is Snowflake, it's one of the furthest along with its data cloud, in our view. It's a supercloud optimized for data sharing and governance, query performance, and security, and ecosystem enablement. When you do things inside of that data cloud, what we call a super data cloud. Again, our term, not theirs. You can do things that you could not do in a single cloud. You can't do this with Redshift, You can't do this with SQL server and they're bringing new data types now with merging analytics or at least accommodate analytics and transaction type data, and bringing open source tooling with things like Apache Iceberg. And so it ticks the boxes we laid out earlier. I would say that a company like Databricks is also in that mix doing it, coming at it from a data science perspective, trying to create that consistent experience for data scientists and data engineering across clouds. Converge databases, running transaction and analytic workloads is another example. Take a look at what Couchbase is doing with Capella and how it's enabling stretching the cloud to the edge with ARM-based platforms and optimizing for low latency across clouds, and even out to the edge. Document database workloads, look at MongoDB, a very developer-friendly platform that with the Atlas is moving toward a supercloud model running document databases very, very efficiently. How about general purpose workloads? This is where VMware comes into to play. Very clearly, there's a need to create a common operating environment across clouds and on-prem, and out to the edge. And I say VMware is hard at work on that. Managing and moving workloads, and balancing workloads, and being able to recover very quickly across clouds for everyday applications. Network routing, take a look at what Aviatrix is doing across clouds, industry workloads. We see CapitalOne, it announced its cost optimization platform for Snowflake, piggybacking on Snowflake supercloud or super data cloud. And in our view, it's very clearly going to go after other markets is going to test it out with Snowflake, running, optimizing on AWS and it's going to expand to other clouds as Snowflake's business and those other clouds grows. Walmart working with Microsoft to create an on-premed Azure experience that's seamless. Yes, that counts, on-prem counts. If you can create that seamless and continuous experience, identical experience from on-prem to a hyperscale cloud, we would include that as a supercloud. You know, we've written about what Goldman is doing. Again, connecting its on-prem data and software tooling, and other capabilities to AWS for scale. And we can bet dollars to donuts that Oracle will be building a supercloud in healthcare with its Cerner acquisition. Supercloud is everywhere you look. So I'm sorry, naysayers it's happening all around us. So what's next? Well, with all the industry buzz and debate about the future, John Furrier and I, have decided to host an event in Palo Alto, we're motivated and inspired to further this conversation. And we welcome all points of view, positive, negative, multi-cloud, supercloud, hypercloud, all welcome. So theCUBE on Supercloud is coming on August 9th, out of our Palo Alto studios, we'll be running a live program on the topic. We've reached out to a number of industry participants, VMware, Snowflake, Confluent, Sky High Security, Gee Rittenhouse's new company, HashiCorp, CloudFlare. We've hit up Red Hat and we expect many of these folks will be in our studios on August 9th. And we've invited a number of industry participants as well that we're excited to have on. From industry, from financial services, from healthcare, from retail, we're inviting analysts, thought leaders, investors. We're going to have more detail in the coming weeks, but for now, if you're interested, please reach out to me or John with how you think you can advance the discussion and we'll see if we can fit you in. So mark your calendars, stay tuned for more information. Okay, that's it for today. Thanks to Alex Myerson who handles production and manages the podcast for Breaking Analysis. And I want to thank Kristen Martin and Cheryl Knight, they help get the word out on social and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does a lot of editing and appreciate you posting on SiliconANGLE, Rob. Thanks to all of you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcast. It publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me @DVellante, or comment on my LinkedIn post. And please do check out ETR.ai for the best survey data. And the enterprise tech business will be at AWS NYC Summit next Tuesday, July 12th. So if you're there, please do stop by and say hello to theCUBE, it's at the Javits Center. This is Dave Vellante for theCUBE insights powered by ETR. Thanks for watching. And we'll see you next time on "Breaking Analysis." (bright music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vallante. >> Welcome to this week's Wikibon CUBE Insights powered by ETR. As we exited the isolation economy last year, Supercloud is a term that we introduced to describe something new that was happening in the world of cloud. In this "Breaking Analysis," we address the 10 most frequently asked questions we get around Supercloud. Okay, let's review these frequently asked questions on Supercloud that we're going to try to answer today. Look at an industry that's full of hype and buzzwords. Why the hell does anyone need a new term? Aren't hyperscalers building out Superclouds? We'll try to answer why the term Supercloud connotes something different from hyperscale clouds. And we'll talk about the problems that Superclouds solve specifically, and we'll further define the critical aspects of a Supercloud architecture. We often get asked, "Isn't this just multi-cloud?" Well, we don't think so, and we'll explain why in this "Breaking Analysis." Now, in an earlier episode, we introduced the notion of super PaaS. Well, isn't a plain vanilla PaaS already a super PaaS? Again, we don't think so, and we'll explain why. Who will actually build and who are the players currently building Superclouds? What workloads and services will run on Superclouds? And eight A or number nine, what are some examples that we can share of Supercloud? And finally, we'll answer what you can expect next from us on Supercloud. Okay, let's get started. Why do we need another buzzword? Well, late last year ahead of re:Invent, we were inspired by a post from Jerry Chen called castles in the cloud. Now, in that blog post, he introduced the idea that there were submarkets emerging in cloud that presented opportunities for investors and entrepreneurs. That the cloud wasn't going to suck the hyperscalers, weren't going to suck all the value out of the industry. And so we introduced this notion of Supercloud to describe what we saw as a value layer emerging above the hyperscalers CAPEX gift, we sometimes call it. Now, it turns out that we weren't the only ones using the term, as both Cornell and MIT, have used the phrase in somewhat similar, but different contexts. The point is, something new was happening in the AWS and other ecosystems. It was more than IS and PaaS, and wasn't just SaaS running in the cloud. It was a new architecture that integrates infrastructure, platform and software as services, to solve new problems that the cloud vendors, in our view, weren't addressing by themselves. It seemed to us that the ecosystem was pursuing opportunities across clouds that went beyond conventional implementations of multi-cloud. And we felt there was a structural change going on at the industry level. The Supercloud metaphorically was highlighting. So that's the background on why we felt a new catch phrase was warranted. Love it or hate it, it's memorable and it's what we chose. Now, to that last point about structural industry transformation. Andy Rapaport is sometimes and often credited with identifying the shift from the vertically integrated IBM mainframe era to the fragmented PC microprocesor based era in his HBR article in 1991. In fact, it was David Moschella, who at the time was an IDC analyst who first introduced the concept in 1987, four years before Rapaport's article was published. Moschella saw that it was clear that Intel, Microsoft, Seagate and others would replace the system vendors and put that forth in a graphic that looked similar to the first two on this chart. We don't have to review the shift from IBM as the center of the industry to Wintel. That's well understood. What isn't as well known or accepted is what Moschella put out in his 2018 book called "Seeing Digital" which introduced the idea of the matrix that's shown on the right hand side of this chart. Moschella posited that new services were emerging, built on top of the internet and hyperscale clouds that would integrate other innovations and would define the next era of computing. He used the term matrix, because the conceptual depiction included, not only horizontal technology rows, like the cloud and the internet, but for the first time included connected industry verticals, the columns in this chart. Moschella pointed out that, whereas historically, industry verticals had a closed value chain or stack and ecosystem of R&D and production and manufacturing and distribution. And if you were in that industry, the expertise within that vertical generally stayed within that vertical and was critical to success. But because of digital and data, for the first time, companies were able to traverse industries jump across industries and compete because data enabled them to do that. Examples, Amazon and content, payments, groceries, Apple and payments, and content and so forth. There are many examples. Data was now this unifying enabler and this marked a change in the structure of the technology landscape. And Supercloud is meant to imply more than running in hyperscale clouds. Rather, it's the combination of multiple technologies, enabled by cloud scale with new industry participants from those verticals; financial services, and healthcare, and manufacturing, energy, media, and virtually all and any industry. Kind of an extension of every company is a software company. Basically, every company now has the opportunity to build their own cloud or Supercloud. And we'll come back to that. Let's first address what's different about Superclouds relative to hyperscale clouds. Now, this one's pretty straightforward and obvious, I think. Hyperscale clouds, they're walled gardens where they want your data in their cloud and they want to keep you there. Sure, every cloud player realizes that not all data will go to their particular cloud. So they're meeting customers where their data lives with initiatives like Amazon Outposts and Azure Arc and Google Antos. But at the end of the day, the more homogeneous they can make their environments, the better control, security, costs, and performance they can deliver. The more complex the environment, the more difficult it is to deliver on their brand promises. And, of course, the less margin that's left for them to capture. Will the hyperscalers get more serious about cross cloud services? Maybe, but they have plenty of work to do within their own clouds and within enabling their own ecosystems. They have a long way to go, a lot of runway. So let's talk about specifically, what problems Superclouds solve. We've all seen the stats from IDC or Gartner or whomever, that customers on average use more than one cloud, two clouds, three clouds, five clouds, 20 clouds. And we know these clouds operate in disconnected silos for the most part. And that's a problem, because each cloud requires different skills, because the development environment is different as is the operating environment. They have different APIs, different primitives, and different management tools that are optimized for each respective hyperscale cloud. Their functions and value props don't extend to their competitors' clouds for the most part. Why would they? As a result, there's friction when moving between different clouds. It's hard to share data. It's hard to move work. It's hard to secure and govern data. It's hard to enforce organizational edicts and policies across these clouds and on-prem. Supercloud is an architecture designed to create a single environment that enables management of workloads and data across clouds in an effort to take out complexity, accelerate application development, streamline operations, and share data safely, irrespective of location. It's pretty straightforward, but non-trivial, which is why I always ask a company's CEO and executives if stock buybacks and dividends will yield as much return as building out Superclouds that solve really specific and hard problems and create differential value. Okay, let's dig a bit more into the architectural aspects of Supercloud. In other words, what are the salient attributes of Supercloud? So, first and foremost, a Supercloud runs a set of specific services designed to solve a unique problem, and it can do so in more than one cloud. Superclouds leverage the underlying cloud native tooling of a hyperscale cloud, but they're optimized for a specific objective that aligns with the problem that they're trying to solve. For example, Supercloud might be optimized for lowest cost or lowest latency or sharing data or governing or securing that data or higher performance for networking, for example. But the point is, the collection of services that is being delivered is focused on a unique value proposition that is not being delivered by the hyperscalers across clouds. A Supercloud abstracts the underlying and siloed primitives of the native PaaS layer from the hyperscale cloud, and then using its own specific platform as a service tooling, creates a common experience across clouds for developers and users. And it does so in the most efficient manner, meaning it has the metadata knowledge and management capabilities that can optimize for latency, bandwidth, or recovery or data sovereignty, or whatever unique value that Supercloud is delivering for the specific use case in their domain. And a Supercloud comprises a super PaaS capability that allows ecosystem partners through APIs to add incremental value on top of the Supercloud platform to fill gaps, accelerate features, and of course, innovate. The services can be infrastructure related, they could be application services, they could be data services, security services, user services, et cetera, designed and packaged to bring unique value to customers. Again, that hyperscalers are not delivering across clouds or on premises. Okay, so another common question we get is, "Isn't that just multi-cloud?" And what we'd say to that is yeah, "Yes, but no." You can call it multi-cloud 2.0, if you want. If you want to use, it's kind of a commonly used rubric. But as Dell's Chuck Whitten proclaimed at Dell Technologies World this year, multi-cloud, by design, is different than multi-cloud by default. Meaning, to date, multi-cloud has largely been a symptom of what we've called multi-vendor or of M&A. You buy a company and they happen to use Google cloud. And so you bring it in. And when you look at most so-called multi-cloud implementations, you see things like an on-prem stack, which is wrapped in a container and hosted on a specific cloud. Or increasingly, a technology vendor has done the work of building a cloud native version of their stack and running it on a specific cloud. But historically, it's been a unique experience within each cloud, with virtually no connection between the cloud silos. Supercloud sets out to build incremental value across clouds and above hyperscale CAPEX that goes beyond cloud compatibility within each cloud. So, if you want to call it multi-cloud 2.0, that's fine, but we chose to call it Supercloud. Okay, so at this point you may be asking, "Well isn't PaaS already a version of Supercloud?" And again, we would say, "No." That Supercloud and its corresponding super PaaS layer, which is a prerequisite, gives the freedom to store, process, and manage and secure and connect islands of data across a continuum with a common experience across clouds. And the services offered are specific to that Supercloud and will vary by each offering. OpenShift, for example, can be used to construct a super PaaS, but in and of itself, isn't a super PaaS, it's generic. A super PaaS might be developed to support, for instance, ultra low latency database work. It would unlikely, again, taking the OpenShift example, it's unlikely that off the shelf OpenShift would be used to develop such a low latency, super PaaS layer for ultra low latency database work. The point is, Supercloud and its inherent super PaaS will be optimized to solve specific problems like that low latency example for distributed databases or fast backup in recovery for data protection and ransomware, or data sharing or data governance. Highly specific use cases that the Supercloud is designed to solve for. Okay, another question we often get is, "Who has a Supercloud today and who's building a Supercloud and who are the contenders?" Well, most companies that consider themselves cloud players will, we believe, be building or are building Superclouds. Here's a common ETR graphic that we like to show with net score or spending momentum on the Y axis, and overlap or pervasiveness in the ETR surveys on the X axis. And we've randomly chosen a number of players that we think are in the Supercloud mix. And we've included the hyperscalers because they are enablers. Now, remember, this is a spectrum of maturity. It's a maturity model. And we've added some of those industry players that we see building Superclouds like Capital One, Goldman Sachs, Walmart. This is in deference to Moschella's observation around the matrix and the industry structural changes that are going on. This goes back to every company being a software company. And rather than pattern match and outdated SaaS model, we see new industry structures emerging where software and data and tools specific to an industry will lead the next wave of innovation and bring in new value that traditional technology companies aren't going to solve. And the hyperscalers aren't going to solve. We've talked a lot about Snowflake's data cloud as an example of Supercloud. After being at Snowflake Summit, we're more convinced than ever that they're headed in this direction. VMware is clearly going after cross cloud services, perhaps creating a new category. Basically, every large company we see either pursuing Supercloud initiatives or thinking about it. Dell showed Project Alpine at Dell Tech World. That's a Supercloud. Snowflake introducing a new application development capability based on their super PaaS, our term, of course. They don't use the phrase. Mongo, Couchbase, Nutanix, Pure Storage, Veeam, CrowdStrike, Okta, Zscaler. Yeah, all of those guys. Yes, Cisco and HPE. Even though on theCUBE at HPE Discover, Fidelma Russo said on theCUBE, she wasn't a fan of cloaking mechanisms. (Dave laughing) But then we talked to HPE's head of storage services, Omer Asad, and he's clearly headed in the direction that we would consider Supercloud. Again, those cross cloud services, of course, their emphasis is connecting as well on-prem. That single experience, which traditionally has not existed with multi-cloud or hybrid. And we're seeing the emergence of smaller companies like Aviatrix and Starburst and Clumio and others that are building versions of Superclouds that solve for a specific problem for their customers. Even ISVs like Adobe, ADP, we've talked to UiPath. They seem to be looking at new ways to go beyond the SaaS model and add value within their cloud ecosystem, specifically around data as part of their and their customer's digital transformations. So yeah, pretty much every tech vendor with any size or momentum, and new industry players are coming out of hiding and competing, building Superclouds that look a lot like Moschella's matrix, with machine intelligence and blockchains and virtual realities and gaming, all enabled by the internet and hyperscale cloud CAPEX. So it's moving fast and it's the future in our opinion. So don't get too caught up in the past or you'll be left behind. Okay, what about examples? We've given a number in the past but let's try to be a little bit more specific. Here are a few we've selected and we're going to answer the two questions in one section here. What workloads and services will run in Superclouds and what are some examples? Let's start with analytics. Our favorite example of Snowflake. It's one of the furthest along with its data cloud, in our view. It's a Supercloud optimized for data sharing and governance, and query performance, and security, and ecosystem enablement. When you do things inside of that data cloud, what we call a super data cloud. Again, our term, not theirs. You can do things that you could not do in a single cloud. You can't do this with Redshift. You can't do this with SQL server. And they're bringing new data types now with merging analytics or at least accommodate analytics and transaction type data and bringing open source tooling with things like Apache Iceberg. And so, it ticks the boxes we laid out earlier. I would say that a company like Databricks is also in that mix, doing it, coming at it from a data science perspective trying to create that consistent experience for data scientists and data engineering across clouds. Converge databases, running transaction and analytic workloads is another example. Take a look at what Couchbase is doing with Capella and how it's enabling stretching the cloud to the edge with arm based platforms and optimizing for low latency across clouds, and even out to the edge. Document database workloads, look at Mongo DB. A very developer friendly platform that where the Atlas is moving toward a Supercloud model, running document databases very, very efficiently. How about general purpose workloads? This is where VMware comes into play. Very clearly, there's a need to create a common operating environment across clouds and on-prem and out to the edge. And I say, VMware is hard at work on that, managing and moving workloads and balancing workloads, and being able to recover very quickly across clouds for everyday applications. Network routing, take a look at what Aviatrix is doing across clouds. Industry workloads, we see Capital One. It announced its cost optimization platform for Snowflake, piggybacking on Snowflake's Supercloud or super data cloud. And in our view, it's very clearly going to go after other markets. It's going to test it out with Snowflake, optimizing on AWS, and it's going to expand to other clouds as Snowflake's business and those other clouds grows. Walmart working with Microsoft to create an on-premed Azure experience that's seamless. Yes, that counts, on-prem counts. If you can create that seamless and continuous experience, identical experience from on-prem to a hyperscale cloud, we would include that as a Supercloud. We've written about what Goldman is doing. Again, connecting its on-prem data and software tooling, and other capabilities to AWS for scale. And you can bet dollars to donuts that Oracle will be building a Supercloud in healthcare with its Cerner acquisition. Supercloud is everywhere you look. So I'm sorry, naysayers, it's happening all around us. So what's next? Well, with all the industry buzz and debate about the future, John Furrier and I have decided to host an event in Palo Alto. We're motivated and inspired to further this conversation. And we welcome all points of view, positive, negative, multi-cloud, Supercloud, HyperCloud, all welcome. So theCUBE on Supercloud is coming on August 9th out of our Palo Alto studios. We'll be running a live program on the topic. We've reached out to a number of industry participants; VMware, Snowflake, Confluent, Skyhigh Security, G. Written House's new company, HashiCorp, CloudFlare. We've hit up Red Hat and we expect many of these folks will be in our studios on August 9th. And we've invited a number of industry participants as well that we're excited to have on. From industry, from financial services, from healthcare, from retail, we're inviting analysts, thought leaders, investors. We're going to have more detail in the coming weeks, but for now, if you're interested, please reach out to me or John with how you think you can advance the discussion, and we'll see if we can fit you in. So mark your calendars, stay tuned for more information. Okay, that's it for today. Thanks to Alex Myerson who handles production and manages the podcast for "Breaking Analysis." And I want to thank Kristen Martin and Cheryl Knight. They help get the word out on social and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does a lot of editing and appreciate you posting on SiliconANGLE, Rob. Thanks to all of you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search, breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me directly at david.vellante@siliconangle.com. Or DM me @DVallante, or comment on my LinkedIn post. And please, do check out etr.ai for the best survey data in the enterprise tech business. We'll be at AWS NYC summit next Tuesday, July 12th. So if you're there, please do stop by and say hello to theCUBE. It's at the Javits Center. This is Dave Vallante for theCUBE Insights, powered by ETR. Thanks for watching. And we'll see you next time on "Breaking Analysis." (slow music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> After a two-year epic run in tech, 2022 has been an epically bad year. Through yesterday, The NASDAQ composite is down 30%. The S$P 500 is off 21%. And the Dow Jones Industrial average 16% down. And the poor holders at Bitcoin have had to endure a nearly 60% decline year to date. But judging by the attendance and enthusiasm, in major in-person tech events this spring. You'd never know that tech was in the tank. Moreover, walking around the streets of Las Vegas, where most tech conferences are held these days. One can't help but notice that the good folks of Main Street, don't seem the least bit concerned that the economy is headed for a recession. Hello, and welcome to this weeks Wiki Bond Cube Insights powered by ETR. In this Breaking Analysis we'll share our main takeaways from the first half of 2022. And talk about the outlook for tech going forward, and why despite some pretty concerning headwinds we remain sanguine about tech generally, but especially enterprise tech. Look, here's the bumper sticker on why many folks are really bearish at the moment. Of course, inflation is high, other than last year, the previous inflation high this century was in July of 2008, it was 5.6%. Inflation has proven to be very, very hard to tame. You got gas at $7 dollars a gallon. Energy prices they're not going to suddenly drop. Interest rates are climbing, which will eventually damage housing. Going to have that ripple effect, no doubt. We're seeing layoffs at companies like Tesla and the crypto names are also trimming staff. Workers, however are still in short supply. So wages are going up. Companies in retail are really struggling with the right inventory, and they can't even accurately guide on their earnings. We've seen a version of this movie before. Now, as it pertains to tech, Crawford Del Prete, who's the CEO of IDC explained this on theCUBE this very week. And I thought he did a really good job. He said the following, >> Matt, you have a great statistic that 80% of companies used COVID as their point to pivot into digital transformation. And to invest in a different way. And so what we saw now is that tech is now where I think companies need to focus. They need to invest in tech. They need to make people more productive with tech and it played out in the numbers. Now so this year what's fascinating is we're looking at two vastly different markets. We got gasoline at $7 a gallon. We've got that affecting food prices. Interesting fun fact recently it now costs over $1,000 to fill an 18 wheeler. All right, based on, I mean, this just kind of can't continue. So you think about it. >> Don't put the boat in the water. >> Yeah, yeah, yeah. Good luck if ya, yeah exactly. So a family has kind of this bag of money, and that bag of money goes up by maybe three, 4% every year, depending upon earnings. So that is sort of sloshing around. So if food and fuel and rent is taking up more, gadgets and consumer tech are not, you're going to use that iPhone a little longer. You're going to use that Android phone a little longer. You're going to use that TV a little longer. So consumer tech is getting crushed, really it's very, very, and you saw it immediately in ad spending. You've seen it in Meta, you've seen it in Facebook. Consumer tech is doing very, very, it is tough. Enterprise tech, we haven't been in the office for two and a half years. We haven't upgraded whether that be campus wifi, whether that be servers, whether that be commercial PCs as much as we would have. So enterprise tech, we're seeing double digit order rates. We're seeing strong, strong demand. We have combined that with a component shortage, and you're seeing some enterprise companies with a quarter of backlog, I mean that's really unheard of. >> And higher prices, which also profit. >> And therefore that drives up the prices. >> And this is a theme that we've heard this year at major tech events, they've really come roaring back. Last year, theCUBE had a huge presence at AWS Reinvent. The first Reinvent since 2019, it was really well attended. Now this was before the effects of the omicron variant, before they were really well understood. And in the first quarter of 2022, things were pretty quiet as far as tech events go But theCUBE'a been really busy this spring and early into the summer. We did 12 physical events as we're showing here in the slide. Coupa, did Women in Data Science at Stanford, Coupa Inspire was in Las Vegas. Now these are both smaller events, but they were well attended and beat expectations. San Francisco Summit, the AWS San Francisco Summit was a bit off, frankly 'cause of the COVID concerns. They were on the rise, then we hit Dell Tech World which was packed, it had probably around 7,000 attendees. Now Dockercon was virtual, but we decided to include it here because it was a huge global event with watch parties and many, many tens of thousands of people attending. Now the Red Hat Summit was really interesting. The choice that Red Hat made this year. It was purposefully scaled down and turned into a smaller VIP event in Boston at the Western, a couple thousand people only. It was very intimate with a much larger virtual presence. VeeamON was very well attended, not as large as previous VeeamON events, but again beat expectations. KubeCon and Cloud Native Con was really successful in Spain, Valencia, Spain. PagerDuty Summit was again a smaller intimate event in San Francisco. And then MongoDB World was at the new Javits Center and really well attended over the three day period. There were lots of developers there, lots of business people, lots of ecosystem partners. And then the Snowflake summit in Las Vegas, it was the most vibrant from the standpoint of the ecosystem with nearly 10,000 attendees. And I'll come back to that in a moment. Amazon re:Mars is the Amazon AI robotic event, it's smaller but very, very cool, a lot of innovation. And just last week we were at HPE Discover. They had around 8,000 people attending which was really good. Now I've been to over a dozen HPE or HPE Discover events, within Europe and the United States over the past decade. And this was by far the most vibrant, lot of action. HPE had a little spring in its step because the company's much more focused now but people was really well attended and people were excited to be there, not only to be back at physical events, but also to hear about some of the new innovations that are coming and HPE has a long way to go in terms of building out that ecosystem, but it's starting to form. So we saw that last week. So tech events are back, but they are smaller. And of course now a virtual overlay, they're hybrid. And just to give you some context, theCUBE did, as I said 12 physical events in the first half of 2022. Just to compare that in 2019, through June of that year we had done 35 physical events. Yeah, 35. And what's perhaps more interesting is we had our largest first half ever in our 12 year history because we're doing so much hybrid and virtual to compliment the physical. So that's the new format is CUBE plus digital or sometimes just digital but that's really what's happening in our business. So I think it's a reflection of what's happening in the broader tech community. So everyone's still trying to figure that out but it's clear that events are back and there's no replacing face to face. Or as I like to say, belly to belly, because deals are done at physical events. All these events we've been to, the sales people are so excited. They're saying we're closing business. Pipelines coming out of these events are much stronger, than they are out of the virtual events but the post virtual event continues to deliver that long tail effect. So that's not going to go away. The bottom line is hybrid is the new model. Okay let's look at some of the big themes that we've taken away from the first half of 2022. Now of course, this is all happening under the umbrella of digital transformation. I'm not going to talk about that too much, you've had plenty of DX Kool-Aid injected into your veins over the last 27 months. But one of the first observations I'll share is that the so-called big data ecosystem that was forming during the hoop and around, the hadoop infrastructure days and years. then remember it dispersed, right when the cloud came in and kind of you know, not wiped out but definitely dampened the hadoop enthusiasm for on-prem, the ecosystem dispersed, but now it's reforming. There are large pockets that are obviously seen in the various clouds. And we definitely see a ecosystem forming around MongoDB and the open source community gathering in the data bricks ecosystem. But the most notable momentum is within the Snowflake ecosystem. Snowflake is moving fast to win the day in the data ecosystem. They're providing a single platform that's bringing different data types together. Live data from systems of record, systems of engagement together with so-called systems of insight. These are converging and while others notably, Oracle are architecting for this new reality, Snowflake is leading with the ecosystem momentum and a new stack is emerging that comprises cloud infrastructure at the bottom layer. Data PaaS layer for app dev and is enabling an ecosystem of partners to build data products and data services that can be monetized. That's the key, that's the top of the stack. So let's dig into that further in a moment but you're seeing machine intelligence and data being driven into applications and the data and application stacks they're coming together to support the acceleration of physical into digital. It's happening right before our eyes in every industry. We're also seeing the evolution of cloud. It started with the SaaS-ification of the enterprise where organizations realized that they didn't have to run their own software on-prem and it made sense to move to SaaS for CRM or HR, certainly email and collaboration and certain parts of ERP and early IS was really about getting out of the data center infrastructure management business called that cloud 1.0, and then 2.0 was really about changing the operating model. And now we're seeing that operating model spill into on-prem workloads finally. We're talking about here about initiatives like HPE's Green Lake, which we heard a lot about last week at Discover and Dell's Apex, which we heard about in May, in Las Vegas. John Furrier had a really interesting observation that basically this is HPE's and Dell's version of outposts. And I found that interesting because outpost was kind of a wake up call in 2018 and a shot across the bow at the legacy enterprise infrastructure players. And they initially responded with these flexible financial schemes, but finally we're seeing real platforms emerge. Again, we saw this at Discover and at Dell Tech World, early implementations of the cloud operating model on-prem. I mean, honestly, you're seeing things like consoles and billing, similar to AWS circa 2014, but players like Dell and HPE they have a distinct advantage with respect to their customer bases, their service organizations, their very large portfolios, especially in the case of Dell and the fact that they have more mature stacks and knowhow to run mission critical enterprise applications on-prem. So John's comment was quite interesting that these firms are basically building their own version of outposts. Outposts obviously came into their wheelhouse and now they've finally responded. And this is setting up cloud 3.0 or Supercloud, as we like to call it, an abstraction layer, that sits above the clouds that serves as a unifying experience across a continuum of on-prem across clouds, whether it's AWS, Azure, or Google. And out to both the near and far edge, near edge being a Lowes or a Home Depot, but far edge could be space. And that edge again is fragmented. You've got the examples like the retail stores at the near edge. Outer space maybe is the far edge and IOT devices is perhaps the tiny edge. No one really knows how the tiny edge is going to play out but it's pretty clear that it's not going to comprise traditional X86 systems with a cool name tossed out to the edge. Rather, it's likely going to require a new low cost, low power, high performance architecture, most likely RM based that will enable things like realtime AI inferencing at that edge. Now we've talked about this a lot on Breaking Analysis, so I'm not going to double click on it. But suffice to say that it's very possible that new innovations are going to emerge from the tiny edge that could really disrupt the enterprise in terms of price performance. Okay, two other quick observations. One is that data protection is becoming a much closer cohort to the security stack where data immutability and air gaps and fast recovery are increasingly becoming a fundamental component of the security strategy to combat ransomware and recover from other potential hacks or disasters. And I got to say from our observation, Veeam is leading the pack here. It's now claiming the number one revenue spot in a statistical dead heat with the Dell's data protection business. That's according to Veeam, according to IDC. And so that space continues to be of interest. And finally, Broadcom's acquisition of Dell. It's going to have ripple effects throughout the enterprise technology business. And there of course, there are a lot of questions that remain, but the one other thing that John Furrier and I were discussing last night John looked at me and said, "Dave imagine if VMware runs better on Broadcom components and OEMs that use Broadcom run VMware better, maybe Broadcom doesn't even have to raise prices on on VMware licenses. Maybe they'll just raise prices on the OEMs and let them raise prices to the end customer." Interesting thought, I think because Broadcom is so P&L focused that it's probably not going to be the prevailing model but we'll see what happens to some of the strategic projects rather like Monterey and Capitola and Thunder. We've talked a lot about project Monterey, the others we'll see if they can make the cut. That's one of the big concerns because it's how OEMs like the ones that are building their versions of outposts are going to compete with the cloud vendors, namely AWS in the future. I want to come back to the comment on the data stack for a moment that we were talking about earlier, we talked about how the big data ecosystem that was once coalescing around hadoop dispersed. Well, the data value chain is reforming and we think it looks something like this picture, where cloud infrastructure lives at the bottom. We've said many times the cloud is expanding and evolving. And if companies like Dell and HPE can truly build a super cloud infrastructure experience then they will be in a position to capture more of the data value. If not, then it's going to go to the cloud players. And there's a live data layer that is increasingly being converged into platforms that not only simplify the movement in ELTing of data but also allow organizations to compress the time to value. Now there's a layer above that, we sometimes call it the super PaaS layer if you will, that must comprise open source tooling, partners are going to write applications and leverage platform APIs and build data products and services that can be monetized at the top of the stack. So when you observe the battle for the data future it's unlikely that any one company is going to be able to do this all on their own, which is why I often joke that the 2020s version of a sweaty Steve Bomber running around the stage, screaming, developers, developers developers, and getting the whole audience into it is now about ecosystem ecosystem ecosystem. Because when you need to fill gaps and accelerate features and provide optionality a list of capabilities on the left hand side of this chart, that's going to come from a variety of different companies and places, we're talking about catalogs and AI tools and data science capabilities, data quality, governance tools and it should be of no surprise to followers of Breaking Analysis that on the right hand side of this chart we're including the four principles of data mesh, which of course were popularized by Zhamak Dehghani. So decentralized data ownership, data as products, self-serve platform and automated or computational governance. Now whether this vision becomes a reality via a proprietary platform like Snowflake or somehow is replicated by an open source remains to be seen but history generally shows that a defacto standard for more complex problems like this is often going to emerge prior to an open source alternative. And that would be where I would place my bets. Although even that proprietary platform has to include open source optionality. But it's not a winner take all market. It's plenty of room for multiple players and ecosystem innovators, but winner will definitely take more in my opinion. Okay, let's close with some ETR data that looks at some of those major platform plays who talk a lot about digital transformation and world changing impactful missions. And they have the resources really to compete. This is an XY graphic. It's a view that we often show, it's got net score on the vertical access. That's a measure of spending momentum, and overlap or presence in the ETR survey. That red, that's the horizontal access. The red dotted line at 40% indicates that the platform is among the highest in terms of spending velocity. Which is why I always point out how impressive that makes AWS and Azure because not only are they large on the horizontal axis, the spending momentum on those two platforms rivals even that of Snowflake which continues to lead all on the vertical access. Now, while Google has momentum, given its goals and resources, it's well behind the two leaders. We've added Service Now and Salesforce, two platform names that have become the next great software companies. Joining likes of Oracle, which we show here and SAP not shown along with IBM, you can see them on this chart. We've also plotted MongoDB, which we think has real momentum as a company generally but also with Atlas, it's managed cloud database as a service specifically and Red Hat with trying to become the standard for app dev in Kubernetes environments, which is the hottest trend right now in application development and application modernization. Everybody's doing something with Kubernetes and of course, Red Hat with OpenShift wants to make that a better experience than do it yourself. The DYI brings a lot more complexity. And finally, we've got HPE and Dell both of which we've talked about pretty extensively here and VMware and Cisco. Now Cisco is executing on its portfolio strategy. It's got a lot of diverse components to its company. And it's coming at the cloud of course from a networking and security perspective. And that's their position of strength. And VMware is a staple of the enterprise. Yes, there's some uncertainty with regards to the Broadcom acquisition, but one thing is clear vSphere isn't going anywhere. It's entrenched and will continue to run lots of IT for years to come because it's the best platform on the planet. Now, of course, these are just some of the players in the mix. We expect that numerous non-traditional technology companies this is important to emerge as new cloud players. We've put a lot of emphasis on the data ecosystem because to us that's really going to be the main spring of digital, i.e., a digital company is a data company and that means an ecosystem of data partners that can advance outcomes like better healthcare, faster drug discovery, less fraud, cleaner energy, autonomous vehicles that are safer, smarter, more efficient grids and factories, better government and virtually endless litany of societal improvements that can be addressed. And these companies will be building innovations on top of cloud platforms creating their own super clouds, if you will. And they'll come from non-traditional places, industries, finance that take their data, their software, their tooling bring them to their customers and run them on various clouds. Okay, that's it for today. Thanks to Alex Myerson, who is on production and does the podcast for Breaking Analysis, Kristin Martin and Cheryl Knight, they help get the word out. And Rob Hoofe is our editor and chief over at Silicon Angle who helps edit our posts. Remember all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me at dvellante, or comment on my LinkedIn posts. And please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE's Insights powered by ETR. Thanks for watching be well. And we'll see you next time on Breaking Analysis. (upbeat music)

(upbeat music) >> Welcome back to the Javits in the big apple, New York City. This is theCUBE's coverage of MongoDB World 2022. We're here for a full day of coverage. We're talking to customers, partners, executives and analysts as well. Peder Ulander is here. He's the Chief Marketing Officer of MongoDB and he's joined by Radhika Krishnan, who's the Chief Product Officer at Hitachi Ventara. Folks, welcome back to theCUBE. Great to see you both again. >> Good to see you. >> Thank you David, it's good to be back again. >> Peder, first time since 2019, we've been doing a lot of these conferences and many of them, it's the first time people have been out in a physical event in three years. Amazing. >> I mean, after three years to come back here in our hometown of New York and get together with a few thousand of our favorite customers, partners, analysts, and such, to have real good discussions around where we're taking the world with regards to our developer data platform. It's been great. >> I think a big part of that story of course, is ecosystem and partnerships and Radhika, I remember I was at an event when Hitachi announced its strategy and it's name change, and really tried to understand why and the what's behind that. And of course, Hitachi's a company that looks out over the long term, and of course it has to perform tactically, but it thinks about the future. So give us the update on what's new at Hitachi Ventara, especially as it relates to data. >> Sure thing, Dave. As many, many folks might be aware, there's a very strong heritage that Hitachi has had in the data space, right. By virtue of our products and our presence in the data storage market, which dates back to many decades, right? And then on the industrial side, the parent company Hitachi has been heavily focused on the OT sector. And as you know, there is a pretty significant digital transformation underway in the OT arena, which is all being led by data. So if you look at our mission statement, for instance, it's actually engineering the data driven because we do believe that data is the fundamental platform that's going to drive that digital transformation, irrespective of what industry you're in. >> So one of the themes that you guys both talk about is modernization. I mean, you can take a cloud, I remember Alan Nance, who was at the time, he was a CIO at Philips, he said, look, you could take a cloud workload, or on-prem workload, stick it into the cloud and lift it and shift it. And in your case, you could just put it on, run it on an RDBMS, but you're not going to affect the operational models. >> Peder Ulander: It's just your mess for less, man. >> If you do that. >> It's your mess, for less. >> And so, he goes, you'll get a few, you know, you'll get a couple of zeros out of that. But if you want to have, in his case, billion dollar impact to the business, you have to modernize. So what does modernize mean to each of you? >> Maybe Peder, you can start. >> Yeah, no, I'm happy to start. I think it comes down to what's going on in the industry. I mean, we are truly moving from a world of data centers to centers of data, and these centers of data are happening further and further out along the network, all the way down to the edges. And if you look at the transformation of infrastructure or software that has enabled us to get there, we've seen apps go from monoliths to microservices. We've seen compute go from physical to serverless. We've seen networking go from old wireline copper to high powered 5G networks. They've all transformed. What's the one layer that hasn't completely transformed yet, data, right? So if we do see this world where things are getting further and further out, you've got to rethink your data architecture and how you basically support this move to modernization. And we feel that MongoDB with our partners, especially with Hitachi, we're best suited to really kind of help with this transition for our customers as they move from data centers to centers of data. >> So architecture. And at the failure, I will say this and you tell me if you agree or not. A lot of the failures of sort of the big data architectures of today are there's, everything's in this monolithic database, you've got to go through a series of hyper-specialized professionals to get to the data. If you're a business individual, you're so frustrated because the market's changing faster than you can get answers. So you guys, I know, use this concept of data fabric, people talk about data mesh. So how do you think, Radhika, about modernization in the future of data, which by its very nature is distributed? >> Yeah. So Dave, everybody talks about the hybrid cloud, right? And so the reality is, every one of our customers is having to deal with data that's straddled across on-prem as well as the public cloud and many other places as well. And so it becomes incredibly important that you have a fairly seamless framework, that's relatively low friction, that allows you to go from the capture of the data, which could be happening at the edge, could be happening at the core, any number of places, all the way to publish, right. Which is ultimately what you want to do with data because data exists to deliver insights, right? And therefore you dramatically want to minimize the friction in the process. And that is exactly what we're attempting to do with our data fabric construct, right. We're essentially saying, customers don't have to worry about, like you mentioned, they may have federated data structures, architectures, data lakes, fitting in multiple locations. How do you ensure that you're not having to double up custom code in order to drive the pipelines, in order to drive the data movement from one location to the other and so forth. And so essentially what we're providing is a mechanism whereby they can be confident about the quality of the data at the end of the day. And this is so paramount. Every customer that I talk to is most worried about ensuring that they have data that is trustworthy. >> So this is a really important point because I've always felt like, from a data quality standpoint, you know you get the data engineers who might not have any business context, trying to figure out the quality problem. If you can put the data responsibility in the hands of the business owner, who, he or she, has context, that maybe starts to solve this problem. There's some buts though. So infrastructure becomes an operational detail. Let's hide that. Don't worry about it. Figure it out, okay, so the business can run, but you need self-service infrastructure and you have to figure out how to have federated governance so that the right people can have access. So how do you guys think about that problem in the future? 'Cause it's almost like this vision creates those two challenges. Oh, by the way, you got to get your organization behind it. Right, 'cause there's an organizational construct as well. But those are, to me, wonderful opportunities but they create technology challenges. So how are you guys thinking about that and how are you working on it? >> Yeah, no, that's exactly right, Dave. As we talk to data practitioners, the recurring theme that we keep hearing is, there is just a lot of use cases that require you to have deep understanding of data and require you to have that background in data sciences and so on, such as data governance and vary for their use cases. But ultimately, the reason that data exists is to be able to drive those insights for the end customer, for the domain expert, for the end user. And therefore it becomes incredibly important that we be able to bridge that chasm that exists today between the data universe and the end customer. And that is what we essentially are focused on by virtue of leaning into capabilities like publishing, right? Like self, ad hoc reporting and things that allow citizen data scientists to be able to take advantage of the plethora of data that exists. >> Peder, I'm interested in this notion of IT and OT. Of course, Hitachi is a partner, established in both. Talk about Mongo's position in thinking. 'Cause you've got on-prem customers, you're running now across all clouds. I call it super cloud connecting all these things. But part of that is the edge. Is Mongo running there? Can Mongo run there, sort of a lightweight version? How do you see that evolve? Give us some details there. >> So I think first and foremost, we were born on-prem, obviously with the origins of MongoDB, a little over five years ago, we introduced Atlas and today we run across a hundred different availability zones around the globe, so we're pretty well covered there. The third bit that I think people miss is we also picked up a product called Realm. Realm is an embedded database for mobile devices. So if you think about car companies, Toyota, for example, building connected cars, they'll have Realm in the car for the telemetry, connects back into an Atlas system for the bigger operational side of things. So there's this seamless kind of, or consistency that runs between data center to cloud to edge to device, that MongoDB plays across all the way through. And then taking that to the next level. We talked about this before we sat down, we're also building in the security elements of that because obviously you not only have that data in rest and data in motion, but what happens when you have that data in use? And announced, I think today? We purchased a little company, Aroki, experts in encryption, some of the smartest security minds on the planet. And today we introduce query-able encryption, which basically enables developers, without any security background, to be able to build searchable capabilities into their applications to access data and do it in a way where the security rules and the privacy all remain constant, regardless of whether that developer or the end user actually knows how that works. >> This is a great example of people talk about shift left, designing security in, for the developer, right from the start, not as a bolt-on. It's a great example. >> And I'm actually going to ground that with a real life customer example, if that's okay, Dave. We actually have a utility company in North Carolina that's responsible for energy and water. And so you can imagine, I mean, you alluded to the IO to use case, the industrial use case and this particular customer has to contend with millions of sensors that are constantly streaming data back, right. And now think about the challenge that they were encountering. They had all this data streaming in and in large quantities and they were actually resident on numerous databases, right. And so they had this very real challenge of getting to that quality data that I, data quality that I talked about earlier, as well, they had this challenge of being able to consolidate all of it and make sense of it. And so that's where our partnership with MongoDB really paid off where we were able to leverage Pentaho to integrate all of the data, have that be resident on MongoDB. And now they're leveraging some of the data capabilities, the data fabric capabilities that we bring to the table to actually deliver meaningful insights to their customers. Now their customers are actually able to save on their electricity and water bills. So great success story right there. >> So I love the business impact there, and also you mentioned Pentaho, I remember that acquisition was transformative for Hitachi because it was the beginning of sort of your new vector, which became Hitachi Ventara. What is Lumada? That's, I presume the evolution of Pentaho? You brought in organic, and added capabilities on top of that, bringing in your knowledge of IOT and OT? Explain what Lumada is. >> Yeah, no, that's a great question, Dave. And I'll say this, I mentioned this early on, we fundamentally believe that data is the backbone for all digital transformation. And so to that end, Hitachi has actually been making a series of acquisitions as well as investing organically to build up these data capabilities. And so Pentaho, as you know, gives us some of that front-end capability in terms of integrations and so forth. And the Lumada platform, the umbrella brand name is really connoting everything that we do in the data space that allow customers to go through that, to derive those meaningful insights. Lumada literally stands for illuminating data. And so that's exactly what we do. Irrespective of what vertical, what use case we're talking about. As you know very well, Hitachi is very prominent in just about every vertical. We're in like 90% of the Fortune 500 customers across banking and financial, retail, telecom. And as you know very well, very, very strong in the industrial space as well. >> You know, it's interesting, Peder, you and Radhika were both talking about this sort of edge model. And so if I understand it correctly, and maybe you could bring in sort of the IOT requirements as well. You think about AI, most of the AI that's done today is modeling in the cloud. But in the future and as we're seeing this, it's real-time inferencing at the edge and it's massive amounts of data. But you're probably not, you're going to persist some, I'm hearing, probably not going to persist all of it, some of it's going to be throwaway. And then you're going to send some back to the cloud. I think of EVs or, a deer runs in front of the vehicle and they capture that, okay, send that back. The amounts of data is just massive. Is that the right way to think about this new model? Is that going to require new architectures and hearing that Mongo fits in. >> Yeah. >> Beautifully with that. >> So this is a little bit what we talked about earlier, where historically there have been three silos of data. Whether it's classic system of record, system of engagement or system of intelligence and they've each operated independently. But as applications are pushing in further and further to the edge and real time becomes more and more important, you need to be able to take all three types of workloads or models, data models and actually incorporate it into a single platform. That's the vision we have behind our developer data platform. And it enables us to handle those transactional, operational and analytical workloads in real time, right. One of the things that we announced here this week was our columnar indexing, which enables some of that step into the analytics so that we can actually do in-app analytics for those things that are not going back into the data warehouse or not going back into the cloud, real time happening with the application itself. >> As you add, this is interesting, as basically Mongo's becoming this all-in-one database, as you add those capabilities, are you able to preserve, it sounds like you've still focused on simplicity, developer product productivity. Are there trade off, as you add, does it detract from those things or are you able to architecturally preserve those? >> I think it comes down to how we're thinking through the use case and what's going to be important for the developers. So if you look at the model today, the legacy model was, let's put it all in one big monolith. We recognize that that doesn't work for everyone but the counter to that was this explosion of niche databases, right? You go to certain cloud providers, you get to choose between 15 different databases for whatever workload you want. Time series here, graph here, in-memory here. It becomes a big mess that is pushed back on the company to glue back together and figure out how to work within those systems. We're focused on really kind of embracing the document model. We obviously believe that's a great general purpose model for all types of workloads. And then focusing in on not taking a full search platform that's doing everything from log management all the way through in-app, we're optimizing for in-app experiences. We're optimizing analytics for in-app experiences. We're optimizing all of the different things we're doing for what the developer is trying to go accomplish. That helps us maintain consistency on the architectural design. It helps us maintain consistency in the model by which we're engaging with our customers. And I think it helps us innovate as quickly as we've been been able to innovate. >> Great, thank you. Radhika, we'll give you the last word. We're seeing this convergence of function in the data based, data models, but at the same time, we're seeing the distribution of data. We're not, you're clearly not fighting that, you're embracing that. What does the future look like from Hitachi Ventara's standpoint over the next half decade or even further out? >> So, we're trying to lean into what customers are trying to solve for, Dave. And so that fundamentally comes down to use cases and the approaches just may look dramatically different with every customer and every use case, right? And that's perfectly fine. We're leaning into those models, whether that is data refining on the edge or the core or the cloud. We're leaning into it. And our intent really is to ensure that we're providing that frictionless experience from end to end, right. And I'll give a couple of examples. We had this very large bank, one of the top 10 banks here in the US, that essentially had multiple data catalogs that they were using to essentially sort through their metadata and make sense of all of this data that was coming into their systems. And we were able to essentially, dramatically simplify it. Cut down on the amount of time that it takes to deliver insights to them, right. And it was like, the metric shared was 600% improvement. And so this is the kind of thing that we're manically focused on is, how do we deliver that quantifiable end-customer improvement, right? Whether it's in terms of shortening the amount to drive the insights, whether it's in terms of the number of data practitioners that they have to throw at a problem, the level of manual intervention that is required, so we're automating everything. We're trying to build in a lot of security as Peder talked about, that is a common goal for both sides. We're trying to address it through a combination of security solutions at varying ends of the spectrum. And then finally, as well, delivering that resiliency and scale that is required. Because again, the one thing we know for sure that we can take for granted is data is exploding, right? And so you need that scale, you need that resiliency. You need for customers to feel like there is high quality, it's not dirty, it's not dark and it's something that they can rely upon. >> Yeah, if it's not trusted, they're not going to use it. The interesting thing about the partnership, especially with Hitachi, is you're in so many different examples and use cases. You've got IT. You've got OT. You've got industrial and so many different examples. And if Mongo can truly fit into all those, it's just, the rocket ship's going to continue. Peder, Radhika, thank you so much for coming back in theCUBE, it's great to see you both. >> Thank you, appreciate it. >> Thank you, my pleasure. >> All right. Keep it right there. This is Dave Vellante from the Javits Center in New York City at MongoDB World 2022. We'll be right back. (upbeat music)

>> Narrator: Live from New York, it's theCube! Covering AWS Global Summit 2019, brought to you by Amazon Web Services. >> Welcome back, we're here at the Javits Center in New York City for AWS Summit, I'm Stu Miniman, my cohost is Corey Quinn and happy to welcome to the program Scott Mullins, who's the head of Worldwide Financial Services Business Development with Amazon Web Services based here in The Big Apple, thanks so much for joining us. >> Thanks for having me, Stu, thanks for having me, Corey. >> All right so we had obviously financial services big location here in New York City. We just had FINRA on our program, had a great conversation about how they're using AWS for their environments, but give us a thumbnail if you will about your business, your customers and what you're seeing there. >> Sure, we're working with financial institutions all the way from the newest FinTech startups, all the way to organizations like FINRA, the largest exchanges and brokers dealers like Nasdaq, as well as insurers and the largest banks. And I've been here for five years and in that time period I actually went from being a customer speaking at the AWS Summit here in the Javits Center on stage like Steve Randich was today to watching more and more financial institutions coming forward, talking about their use in the cloud. >> Yeah before we get into technology, one of the biggest trends of moving to cloud is I'm moving from CapEx more to OpEx and oh my gosh there's uncertainty because I'm not locking in some massive contract that I'm paying up front or depreciating over five years but I've got flexibility and things are going to change. I'm curious what you're seeing as the financial pieces of how people both acquire and keep on the books what they're doing. >> Yeah it can be a little bit different, right, then what most people are used to. They're used to kind of that muscle memory and that rhythm of how you procured technology in the past and there can be a stage of adjustment, but cost isn't really the thing that people I think look to the most when it comes to cloud today, it's all about agility and FINRA is a great example. Steve has talked about over and over again over the last several years how they were able to gain such business agility and actually to do more, the fact that they're now processing 155 billion market events every night and able to run all their surveillance routines. That's really indicative of the value that people are looking for. Being able to actually get products to market faster and reducing development cycles from 18 months to three months, like Allianz, one of our customers over in Europe has been able to do. Being able to go faster I think actually trumps cost from the standpoint of what that biggest value driver that we're seeing our customers going after in financial services. >> We're starting to see such a tremendous difference as far as the people speaking at these keynotes. Once upon a time you had Netflix and folks like that on stage telling a story about how they're using cloud to achieve all these amazing things, but when you take a step back and start blinking a little bit, they fundamentally stream movies and yes, produce some awesome original content. With banks and other financial institutions if the ATM starts spitting out the wrong number, that's a different point on the spectrum of are people going to riot in the street. I'm not saying it's further along, people really like their content but it's still a different use case with a different risk profile. Getting serious companies that have world shaking impact to trust public cloud took time and we're seeing it with places like FINRA, Capital One has been very active as far as evangelizing their use of cloud. It's just been transformative. What does that look like, from being a part of that? >> Well you know it's interesting, so you know you just said it, financial services is the business of risk management. And so to get more and when you see more and more of these financial institutions coming forward and talking about their use of cloud, what that really equates to is comfort, they've got that muscle memory now, they've probably been working with us in some way, shape or form for some great period of time and so if you look at last year, you had Dean Del Vecchio from Guardian Life Insurance come out on stage at Reinvent and say to the crowd "Hey we're a 158 year old insurance company but we've now closed our data center and we're fully on AWS and we've completed the transformation of our organization". The year before you saw Goldman Sachs walk out and say "Yeah we've been working with AWS for about four years now and we're actually using them for some very interesting use cases within Goldman Sachs". And so typically what you've seen is that over the course of about a two year to sometimes a four year time period, you've got institutions that are working deeply with us, but they're not talking about it. They're gaining that muscle memory, they're putting those first use cases to begin to scale that work up and then when they're ready man, they're ready to talk about it and they're excited to talk about it. What's interesting though is today we're having this same summit that we're having here in Cape Town in Africa and we had a customer, Old Mutual, who's one of the biggest insurers there, they just started working with us in earnest back in May and they were on stage today, so you're seeing that actually beginning to happen a lot quicker, where people are building that muscle memory faster and they're much more eager to talk about it. You're going to see that trend I think continue in financial services over the next few years so I'm very excited for future summits as well as Reinvent because the stories that we're going to see are going to come faster. You're going to see more use cases that go a lot deeper in the industry and you're going to see it covering a lot more of the industry. >> It's very much not, IT is no longer what people think of in terms of Tech companies in San Francisco building products. It's banks, it's health care and these companies are transitioning to become technology companies but when your entire, as you mentioned, the entire industry becomes about risk management, it's challenging sometimes to articulate things when you're not both on the same page. I was working with a financial partner years ago at a company I worked for and okay they're a financial institution, they're ready to sign off on this but before that they'd like to tour US East one first and validate that things are as we say they are. The answer is yeah me too, sadly, you folks have never bothered to invite me to tour an active AZ, maybe next year. It's challenging to I guess meet people where they are and speak the right language, the right peace for a long time. >> And that's why you see us have a financial services team in the first place, right? Because your financial services or health care or any of the other industries, they're very unique and they have a very specific language and so we've been very focused on making sure that we speak that language that we have an understanding of what that industry entails and what's important to that industry because as you know Amazon's a very customer obsessed organization and we want to work backwards from our customers and so it's been very important for us to actually speak that language and be able to translate that to our service teams to say hey this is important to financial services and this is why, here's the context for that. I think as we've continued to see more and more financial institutions take on that technology company mindset, I'm a technology company that happens to run a bank or happens to run an exchange company or happens to run an insurance business, it's actually been easier to talk to them about the services that we offer because now they have that mindset, they're moving more towards DevOps and moving more towards agile. And so it's been really easy to actually communicate hey, here are the appropriate changes you have to make, here's how you evolve governance, here's how you address security and compliance and the different levels of resiliency that actually improve from the standpoint of using these services. >> All right so Scott, back before I did this, I worked for some large technology suppliers and there were some groups on Wall Street that have huge IT budgets and IT staffs and actually were very cutting edge in what they were building, in what they were doing and very proud of their IT knowledge, and they were like, they have some of the smartest people in the industry and they spend a ton of money because they need an edge. Talking about transactions on stock markets, if I can translate milliseconds into millions of dollars if I can act faster. So you know, those companies, how are they moving along to do the I need to build it myself and differentiate myself because of my IT versus hey I can now have access to all the services out there because you're offering them with new ones every day, but geez how do I differentiate myself if everybody can use some of these same tools. >> So that's my background as well and so you go back that and milliseconds matter, milliseconds are money, right? When it comes to trading and actually building really bespoke applications on bespoke infrastructure. So I think what we're seeing from a transitional perspective is that you still have that mindset where hey we're really good at technology, we're really good at building applications. But now it's a new toolkit, you have access to a completely new toolkit. It's almost like The Matrix, you know that scene where Neo steps into that white room and hey says "I need this" and then the shelves just show up, that's kind how it is in the cloud, you actually have the ability to leverage the latest and greatest technologies at your fingertips when you want to build and I think that's something that's been a really compelling thing for financial institutions where you don't have to wait to get infrastructure provisioned for you. Before I worked for AWS, I worked for large financial institutions as well and when we had major projects that we had to do that sometimes had a regulatory implication, we were told by our infrastructure team hey that's going to be six months before we can actually get your dev environment built so you can actually begin to develop what you need. And actually we had to respond within about thirty days and so you had a mismatch there. With the cloud you can provision infrastructure easily and you have an access to an array of services that you can use to build immediately. And that means value, that means time to market, that means time to answering questions from customers, that means really a much faster time to answering questions from regulatory agencies and so we're seeing the adoption and the embrace of those services be very large and very significant. >> It's important to make sure that the guardrails are set appropriately, especially for a risk managed firm but once you get that in place correctly, it's an incredible boost of productivity and capability, as opposed to the old crappy way of doing governance of oh it used to take six weeks to get a server in so we're going to open a ticket now whenever you want to provision an instance and it only takes four, yay we're moving faster. It feels like there's very much a right way and a wrong way to start embracing cloud technology. >> Yeah and you know human nature is to take the run book you have today and try to apply it to tomorrow and that doesn't always work because you can use that run book and you'll get down to line four and suddenly line four doesn't exist anymore because of what's happened from a technological change perspective. Yeah I think that's why things like AWS control tower and security hub, which are those guardrails, those services that we announced recently that have gone GA. We announced them a couple of weeks ago at Reinforce in Boston. Those are really interesting to financial services customers because it really begins to help automate a lot of those compliance controls and provisioning those through control tower and then monitoring those through security hub and so you've seen us focus on how do we actually make that easier for customers to do. We know that risk management, we know that governance and controls is very important in financial services. We actually offer our customers a way to look from a country specific angle, add the different countries and the rule sets and the requirements that exist in those countries and how you map those to our controls and how you map those into your own controls and all the considerations that you have, we've got them on our public website. If you went to atlas.aws right now, that's our compliance center, you could actually pick the countries you're interested in and we'll have that mapping for you. So you'll see us continue to invest in things like that to make that much easier for customers to actually deploy quickly and to evolve those governance frameworks. >> And things like with Artifact, where it's just grab whatever compliance report you need, submit it and it's done without having to go through a laborious process. It's click button, receive compliance in some cases. >> If you're not familiar with it you can go into the AWS console and you've got Artifact right there and if you need a SOC report or you need some other type of artifact, you can just download it right there through the console, yeah it's very convenient. >> Yeah so Scott you know we talked about some of the GRC pieces in place, what are you seeing trends out there kind of globally, you know GDRP was something that was on everybody's mind over the last year or so. California has new regulations that are coming in place, so anything specific in your world or just the trends that you're seeing that might impact our environments-- >> I think that the biggest trends I would point to are data analytics, data analytics, data analytics, data analytics. And on top of that obviously machine learning. You know, data is the lifeblood of financial services, it's what makes everything go. And you can look at what's happening in this space where you've got companies like Bloomberg and Refinitiv who are making their data products available on AWS so you can get B-Pipe on AWS today, you can also get the elektron platform from Refintiv and then what people are trying to do in relation to hey I want to organize my data, I want to make it much easier to actually find value in data, both either from the standpoint of regulatory reporting, as you heard Steve talk about on stage today. FINRA is building a very large data repository that they have to from the standpoint of a regulatory perspective with CAT. Broker dealers have to actually feed the CAT and so they are also worried about here in the US, how do I actually organize my data, get all the elements I have to report to CAT together and actually do that in a very efficient way. So that's a big data analytic project. Things that are helping to make that much easier are leg formations, so we came up with leg formation last year and so you've got many financial institutions that are looking at how do you make building a data leg that much easier and then how do you layer analytics on top of that, whether it's using Amazon elastic map reduce or EMR to actually run regulatory reporting jobs or how do I begin to leverage machine learning to actually make my data analytics from a standpoint of trade surveillance or fraud detection that much more enriched and actually looking for those anomalies rather than just looking for a whole bunch of false positives. So data analytics I think is what I would point to as the biggest trend and how to actually make data more useful and how to get to data insights faster. >> On the one end it seems like there's absolutely a lot of potential in this, on the other it feels in many cases with large scale data analytics, it's we have all these tools for machine learning and the rest that we can wind up passing out to you but you need to figure out what to do with them, how to make it work and it's unclear outside of a few specific use cases and I think you've alluded to a couple of those how to take in a typical business that maybe doesn't have an enormous pile of data and start applying machine learning to it in a way that makes intelligent sense. That feels right now like a storytelling failure to some extent industry wide. We're starting to see some stories emerge but it still feels a little "Gold Rush"-y to some extent. >> Yeah I would say, and my advice would be don't try to boil the ocean or don't try to boil the data leg, meaning you want to do machine learning, you've got a great amount of earnestness about that but picture use case, really hone in on what you're trying to accomplish and work backwards from that. And we offer tooling that can be really helpful in that, you know with stage maker you can train your models and you can actually make data science available to a much broader array of people than just your data scientists. And so where we see people focusing first, is where it matters to their business. So if you've got a regulatory obligation to do surveillance or fraud detection, those are great use cases to start with. How do I enhance my existing surveillance or fraud detection, so that I'm not just wading again through a sea of false positives. How do I actually reduce that workload for a human analyst using machine learning. That's a one step up and then you can go from there, you can actually continue to work deeper into the use cases and say okay how do I treat those parameters, how do I actually look for different things that I'm used to with the rules based systems. You can also look at offering more value to customers so with next best offer with Amazon Personalize, we now have encapsulated the service that we use on the amazon.com retail site as a service that we offer to customers so you don't have to build all that tooling yourself, you can actually just consume Personalize as a service to help with those personalized recommendations for customers. >> Scott, really appreciate all the updates on your customers in the financial services industry, thanks so much for joining us. >> Happy to be here guys, thanks for having me. >> All right for Corey Quinn, I'm Stu Miniman, back with more here at AWS Summit in New York City 2019, thanks as always for watching theCube.

>> Live from Atlanta, Georgia, It's theCUBE covering Citrix Synergy Atlanta 2019. Brought to you by Citrix. >> Hey, welcome back to theCUBE's coverage day two of our coverage of Citrix Synergy 2019. Lisa Martin with my cohost Keith Townsend, and we've got another CUBE alumni joining us, Dana Gardner, President and Principle Analyst at Interarbor Solutions. >> Sorry, my language skills are declining on day two. >> It's been a long day. >> It has been a long day. We've had, speaking of, had a lot of great conversations with Citrix Execs, customers, analysts over the last day and a half. People are very excited about what Citrix is doing with intelligence, experience, and really helping businesses to transform their workforces. But you have been following Citrix for a long time. >> Yes. >> So, talk to us about some of the early days back in the 90's. I'd love to get your perspectives on what you saw back then and what your thoughts are about some of the things that they're announcing at this event. >> Sure, well back in 1995-1996, the internet was still the new kid on the block, and browsers were kind of cool but, how would they ever help a business? And then, along comes this company that says, "Oh, we're not going to deliver things through a browser, we're going to deliver the whole app experience, apps that you're familiar with, your Windows-based apps over the wire. Over the internet protocol." Wow, so I remember at Internet Expo in New York at the Javits Center, Ed Iacobucci, The co-founder of Citrix got up there and explained how, yeah, we're going to deliver apps. And basically what they were describing is cloud computing as we know it today. Wow, it was very interesting, but we all kind of look at him like he was a little crazy. (host laughing) Yes. >> And, that's been a long time, man. Citrix has made a name for itself since then. You know, the day I was talking to David Hansel, yesterday and I said, "You know what, Citrix is a verb. I'm going to Citrix in an application. They established something for themselves." And, ironically, on stage yesterday he said, "85 percent of the IT budget goes to keeping the lights on." And I would firmly, as pre-kenote yesterday I'd say, you know what Citrix is firmly in that 85 percent of, they are rock, fast, hard technology partner, but they're in that 85 percent. But this intelligent experience I think kind of pushes them into that 15 percent of innovation. What did you think about yesterday's announcement? >> Well, based on my memory from 1996, I think it's consistent. That they're looking for something that's two or three years, maybe more out that will mature then. But they're not afraid of tackling it now. They had some really strong established businesses, but they're not resting on their laurels. They're looking at, I think a problem that almost everybody can identify with. In the past, their problems were people they could identify with in IT. The end user wasn't aware that anybody was Citrixing behind the scenes. Now, they're identifying issues that people have with work. The fact they were taking apps and services from multiple clouds, multiple data centers some of them our own company, some of our partners, some across an ecosystem or a supply chain, and it's becoming rather crowded. Disenfranchised. Fragmented. And people, I think are struggling to keep up with that amount of diversity. So, we're dealing with, yet again a heterogeneity problem, a reoccurring problem in technology. And Citrix is identifying with something that's a higher elevation than they had in the past. So, they're not addressing just IT although, that's where the actions going to take place to solve some of these problems. But they're focused on just about all of us. Whether we're working in a small, two or three person mom and pop shop or a 30,000 seat enterprise. >> And they've also done this pivot in the last, what we've heard in the last 24 hours, of really being positioned to the general user. Something that I didn't know until yesterday was that the majority of enterprise software has been designed for power users, which is one percent of the users. And so, they've really made that positioning pivot yesterday to, this is for the Marketing Managers, somebody in supply chain who has a day that is bombarded with seven to ten apps. They're losing hours and hours of productivity a week. You can look at that in terms of the amount of dollars that's being spent or wasted. But really making this, bringing those tasks to the user, those actions to the user. Rather than forcing the users to go out to all the different apps, put those pieces together. Oh, and then trying to get back to our actual day-to-day function. >> Right, we wouldn't have to talk about user experience if these things had been designed properly in the first place. It's a bit myopic on behalf of the IT power designer, that they often craft the product for themselves. That, this is still the dark arts behind the curtain thinking. It's very difficult for a highly efficient, productive IT group to create something for a non-IT audience. And I don't blame them, but it has to happen. It's going to happen one way or the other. So, we've seen companies that have taken extraordinary steps on usability, Apple computer is probably the poster child for this. Look at where it got them. There were lots of mobile phones around ten years ago, before the iPhone. Why did the iPhone become so popular, so dominant? Because of the usability. So, Citrix is I think, perhaps doing IT a favor by getting out in front of this. But still, if we're going to get IT in the hands of all people for productivity, what I look to is a fit-for-purpose mentality. No more, no less. You can't design it as if it's your own baby and your own special design, I don't know, once in a lifetime opportunity to strut your stuff. It has to be fit-for-purpose and it can't just be monolithic, where we're looking at little bits and pieces. So, the software's recent acquisition that Citrix made is going to be able to start picking out productivity units, for lack of a better term, from different applications, assimilate those in an environment, the workspace, where the productivity, the work flow, the goal of accomplishing business outcomes comes first and foremost. >> So Dana, let's talk a little bit about, you know the next level. Because it's broken. Even when you look at modern applications, one of the applications they showed on stage yesterday, was a cloud application. Salesforce. I mean, we know a people who make a good deal of money simplifying Salesforce, which is a born in the cloud application. This isn't just about cloud versus legacy, this is about end-user experiences, and end-users using applications in a way that makes them productive. One of the things that caught me as soon as Citrix said that they want to be the future of work, I tweeted out, "Well, you can't be the future of work unless you start to automate processes," and boom, intelligent experience. And the first thing that came to my mind was when we attended an event a couple weeks ago for RPA, Robotic Process Automation tool, that was very user-centric, but used the term "bots". Robots, sulfer robots that did the job. Citrix only used the term, "bots" once yesterday. What's your sense, is this a competitive solution to those partners? Or is this more of a complementary solution? >> I think Citrix is correctly trying to keep the horse in front of the cart and not the other way around. We have to look at work as flows of productivity first, and not conforming to the app second. But to get out in front and say, "Oh, it's all going to be animated and the robot will tell you what to do," I think does a disservice. So, let's take first things first. But let's not also lose track of the fact that by elevating work to a process and not just being locked into one platform, one cloud, one set of microservices on one framework, that we have the opportunity to integrate in analytics along the whole path. From beginning to end. And that we can even have the context of what you're doing feed back into how the analytics come at you. And reinforce one another. So, we need to get the process stuff set first. we need to recognize that people need to rethink getting off a desktop, getting out of email, looking at the full process. Looking at working across organizational boundaries. So, extra enterprise, supply-chain interactions, contingent workforce. Then, bring in analytics. So, first things first but it's going to be a very interesting mash-up when we can elevate process, get out of sort of silos, manage that heterogeneity and inject intelligence and context along the way. That changes the game. >> So, you've seen the workforce dramatically transform throughout your career. There are five generations of people in the workforce today. Madeleine Albright, there she was on stage this morning, 82 years old. I thought that was, what an inspiration? But companies have different generations, different experiences, different experiences with technology, differing expectations. What, in your opinion, did you hear yesterday from Citrix that is going to help businesses enable five different generations to be as productive as they want to be. >> Right, it's an extension of what Citrix has been doing for decades, and it's allowing more flexibility into where you are is accommodated. What device you're using can be accommodated. The fact that you want to be outside your home office but secure can be accommodated. So, what I heard was instead of locking in an application mentality, where everybody has to learn to use the same app, we need to have flexibility. And it's not just ages and generations. It's geographics, it's language, it's culture. People do business and they do work differently around the world. And they should be very well entitled to continue to do that. So, we need to create the systems that adjust to the people and read the people's work habits. And then reinforce them rather than force them into, let's say a monolithic ERP type of affair. And we've know that a large percentage of ERP projects over the years have failed. And it's not that the technology doesn't work, it's that sometimes, you can put a round peg in a square hole. >> Wow, speaking of round peg, square hole, IT, you know, they're preaching to the choir I think on this piece. You know, we want thing to be simpler. We want to get engaged. We want to solve this problem. But, is Citrix talking to the wrong audience when it comes to process automation? To your point, you have to have the large view of it, and a lot of timeS, especially folks at this conference, may not have the large view. How does Citrix get to the CMO's the COO's, the process people versus the technology folks. >> I think that's a significant challenge. Keith and I recorded a podcast with David Henchel earlier today and it'll be out in a few weeks on Briefings Direct, and I asked him that, I said, "You're well-known in the IT department. They use a verb, they're Citrixing. The end user, not so much. But if you're going to impact work as you intend to and as you've laid out here at Synergy, you do need to become more of a household word, and you need to brand and you need to impact." And we know one of the hardest things to do is to get people to change their behavior. You don't do that behind the scenes. In some ways, Citrix has been very modest. They haven't been the Citrix inside, they haven't branded and gone to market with. They've usually let their partners like Microsoft and now even Google Cloud be on the front page, even as they're behind the scenes. But I think they need to think a little bit differently. If they're going to impact people, people need to understand the value that Citrix is bringing. But identifying themselves as they have at this show with work and productivity issues, usability and intelligence will start that process. But I do think they can go further on their go-to-market and not just bring this message to their sales accounts, but to a larger work productivity, human capital management enterprise architect type of base. >> And they are making those impacts. Keith and I today have already spoken with their three innovation award nominees. There were over a thousand nominations. And we spoke with Schroders, which is a wealth management company based out of the UK and how they have been able, a 200 year old company, to really transform their culture with Citrix's workspace was, it was done so strategically, so methodically. But how they enabled that and a seamless integration in terms of their customer experience and engagement with their wealth managers was really compelling. Not only are they able to retain their probably longstanding wealth management clients, but they have the ability now, and the technology capabilities to allow their people to work remote three days a week if they want to or from wherever, and actually work on getting new clients. So, the business impact is really clear. We also spoke with Indiana University. They have gone from just enabling the students on the seven campuses to 130,000 plus across campuses online. They're enabling sight impaired people to also, by virtualization, have access to computer technology. So, you're talking about going from tens of thousands to a ten X at a minimum multiplier, and enabling professors to have conversations and hold classes with people in Budapest. Big impact. >> So Lisa, you're bringing up the point that user experience isn't just employing experience, it's end user and-- >> Absolutely >> Consumer experience. If you're going to do this and do it right, don't consider it just for your employees. It's for reaching out to the very edge of the markets, and that includes consumers and students and mom and pop shops and everything in-between. So when you do this right, and not only will you be delivering intelligence and context to your employees, you'll be able to start to better serve your customers. And that's what digital transformation is really about. >> It is, and the cultural transformation that Citrix is undergoing and that they're enabling their businesses to achieve, like the two we just talked about, are critical catalysts for digital transformation. But to me, employee experience and customer experiences are hand in hand because every employee, whatever function you're in, in some way you're a touchpoint to the customer. If you're in retail, you're presenting a shop-able moment as often as you can. But you also are dealing with customers who have choice to turn and go to another provider of that product or service. So, having those employees not only be satisfied, but have the tools that they need and the intelligence to deliver the content. >> So, I'd be happy to go to a brick and mortor shop. I'll walk in there physically if they can help me in the shopping experience be smarter, but if I can do it online in my bedroom on my browser, then I'll do it there. So it's no so much the interface or even the place anymore, it's who's going to give me the information to make the right decision and make me feel confident that I'm spending my money the most productively. Whether I'm a consumer or a business. So B-to-B. That's what's going to be the killer app, is the smart decision making, and the experience of bringing the right information, right place, right time. That's key. And that's what Citrix has repositioned itself for. I think it's really quite a dramatic shift for the company but they've done it before. >> Well, Dana it's been great having you back on theCUBE unpacking this. It's been an exciting day and a half for us and we look forward to having you back on theCUBE sometime soon. >> My pleasure. >> For Keith Townsend, I'm Lisa Martin. You're watching theCUBE Live from Citrix Synergy 2019. Thanks for watching.

>> [Announcer] Live from Times Square in New York City, it's theCUBE covering IBM's Change the Game: Winning with AI, brought to you by IBM. >> Hello everybody, welcome to theCUBE's special presentation. We're covering IBM's announcements today around AI. IBM, as theCUBE does, runs of sessions and programs in conjunction with Strata, which is down at the Javits, and we're Rob Thomas, who's the General Manager of IBM Analytics. Long time Cube alum, Rob, great to see you. >> Dave, great to see you. >> So you guys got a lot going on today. We're here at the Westin Hotel, you've got an analyst event, you've got a partner meeting, you've got an event tonight, Change the game: winning with AI at Terminal 5, check that out, ibm.com/WinWithAI, go register there. But Rob, let's start with what you guys have going on, give us the run down. >> Yeah, it's a big week for us, and like many others, it's great when you have Strata, a lot of people in town. So, we've structured a week where, today, we're going to spend a lot of time with analysts and our business partners, talking about where we're going with data and AI. This evening, we've got a broadcast, it's called Winning with AI. What's unique about that broadcast is it's all clients. We've got clients on stage doing demonstrations, how they're using IBM technology to get to unique outcomes in their business. So I think it's going to be a pretty unique event, which should be a lot of fun. >> So this place, it looks like a cool event, a venue, Terminal 5, it's just up the street on the west side highway, probably a mile from the Javits Center, so definitely check that out. Alright, let's talk about, Rob, we've known each other for a long time, we've seen the early Hadoop days, you guys were very careful about diving in, you kind of let things settle and watched very carefully, and then came in at the right time. But we saw the evolution of so-called Big Data go from a phase of really reducing investments, cheaper data warehousing, and what that did is allowed people to collect a lot more data, and kind of get ready for this era that we're in now. But maybe you can give us your perspective on the phases, the waves that we've seen of data, and where we are today and where we're going. >> I kind of think of it as a maturity curve. So when I go talk to clients, I say, look, you need to be on a journey towards AI. I think probably nobody disagrees that they need something there, the question is, how do you get there? So you think about the steps, it's about, a lot of people started with, we're going to reduce the cost of our operations, we're going to use data to take out cost, that was kind of the Hadoop thrust, I would say. Then they moved to, well, now we need to see more about our data, we need higher performance data, BI data warehousing. So, everybody, I would say, has dabbled in those two area. The next leap forward is self-service analytics, so how do you actually empower everybody in your organization to use and access data? And the next step beyond that is, can I use AI to drive new business models, new levers of growth, for my business? So, I ask clients, pin yourself on this journey, most are, depends on the division or the part of the company, they're at different areas, but as I tell everybody, if you don't know where you are and you don't know where you want to go, you're just going to wind around, so I try to get them to pin down, where are you versus where do you want to go? >> So four phases, basically, the sort of cheap data store, the BI data warehouse modernization, self-service analytics, a big part of that is data science and data science collaboration, you guys have a lot of investments there, and then new business models with AI automation running on top. Where are we today? Would you say we're kind of in-between BI/DW modernization and on our way to self-service analytics, or what's your sense? >> I'd say most are right in the middle between BI data warehousing and self-service analytics. Self-service analytics is hard, because it requires you, sometimes to take a couple steps back, and look at your data. It's hard to provide self-service if you don't have a data catalog, if you don't have data security, if you haven't gone through the processes around data governance. So, sometimes you have to take one step back to go two steps forward, that's why I see a lot of people, I'd say, stuck in the middle right now. And the examples that you're going to see tonight as part of the broadcast are clients that have figured out how to break through that wall, and I think that's pretty illustrative of what's possible. >> Okay, so you're saying that, got to maybe take a step back and get the infrastructure right with, let's say a catalog, to give some basic things that they have to do, some x's and o's, you've got the Vince Lombardi played out here, and also, skillsets, I imagine, is a key part of that. So, that's what they've got to do to get prepared, and then, what's next? They start creating new business models, imagining this is where the cheap data officer comes in and it's an executive level, what are you seeing clients as part of digital transformation, what's the conversation like with customers? >> The biggest change, the great thing about the times we live in, is technology's become so accessible, you can do things very quickly. We created a team last year called Data Science Elite, and we've hired what we think are some of the best data scientists in the world. Their only job is to go work with clients and help them get to a first success with data science. So, we put a team in. Normally, one month, two months, normally a team of two or three people, our investment, and we say, let's go build a model, let's get to an outcome, and you can do this incredibly quickly now. I tell clients, I see somebody that says, we're going to spend six months evaluating and thinking about this, I was like, why would you spend six months thinking about this when you could actually do it in one month? So you just need to get over the edge and go try it. >> So we're going to learn more about the Data Science Elite team. We've got John Thomas coming on today, who is a distinguished engineer at IBM, and he's very much involved in that team, and I think we have a customer who's actually gone through that, so we're going to talk about what their experience was with the Data Science Elite team. Alright, you've got some hard news coming up, you've actually made some news earlier with Hortonworks and Red Hat, I want to talk about that, but you've also got some hard news today. Take us through that. >> Yeah, let's talk about all three. First, Monday we announced the expanded relationship with both Hortonworks and Red Hat. This goes back to one of the core beliefs I talked about, every enterprise is modernizing their data and application of states, I don't think there's any debate about that. We are big believers in Kubernetes and containers as the architecture to drive that modernization. The announcement on Monday was, we're working closer with Red Hat to take all of our data services as part of Cloud Private for Data, which are basically microservice for data, and we're running those on OpenShift, and we're starting to see great customer traction with that. And where does Hortonworks come in? Hadoop has been the outlier on moving to microservices containers, we're working with Hortonworks to help them make that move as well. So, it's really about the three of us getting together and helping clients with this modernization journey. >> So, just to remind people, you remember ODPI, folks? It was all this kerfuffle about, why do we even need this? Well, what's interesting to me about this triumvirate is, well, first of all, Red Hat and Hortonworks are hardcore opensource, IBM's always been a big supporter of open source. You three got together and you're proving now the productivity for customers of this relationship. You guys don't talk about this, but Hortonworks had to, when it's public call, that the relationship with IBM drove many, many seven-figure deals, which, obviously means that customers are getting value out of this, so it's great to see that come to fruition, and it wasn't just a Barney announcement a couple years ago, so congratulations on that. Now, there's this other news that you guys announced this morning, talk about that. >> Yeah, two other things. One is, we announced a relationship with Stack Overflow. 50 million developers go to Stack Overflow a month, it's an amazing environment for developers that are looking to do new things, and we're sponsoring a community around AI. Back to your point before, you said, is there a skills gap in enterprises, there absolutely is, I don't think that's a surprise. Data science, AI developers, not every company has the skills they need, so we're sponsoring a community to help drive the growth of skills in and around data science and AI. So things like Python, R, Scala, these are the languages of data science, and it's a great relationship with us and Stack Overflow to build a community to get things going on skills. >> Okay, and then there was one more. >> Last one's a product announcement. This is one of the most interesting product annoucements we've had in quite a while. Imagine this, you write a sequel query, and traditional approach is, I've got a server, I point it as that server, I get the data, it's pretty limited. We're announcing technology where I write a query, and it can find data anywhere in the world. I think of it as wide-area sequel. So it can find data on an automotive device, a telematics device, an IoT device, it could be a mobile device, we think of it as sequel the whole world. You write a query, you can find the data anywhere it is, and we take advantage of the processing power on the edge. The biggest problem with IoT is, it's been the old mantra of, go find the data, bring it all back to a centralized warehouse, that makes it impossible to do it real time. We're enabling real time because we can write a query once, find data anywhere, this is technology we've had in preview for the last year. We've been working with a lot of clients to prove out used cases to do it, we're integrating as the capability inside of IBM Cloud Private for Data. So if you buy IBM Cloud for Data, it's there. >> Interesting, so when you've been around as long as I have, long enough to see some of the pendulums swings, and it's clearly a pendulum swing back toward decentralization in the edge, but the key is, from what you just described, is you're sort of redefining the boundary, so I presume it's the edge, any Cloud, or on premises, where you can find that data, is that correct? >> Yeah, so it's multi-Cloud. I mean, look, every organization is going to be multi-Cloud, like 100%, that's going to happen, and that could be private, it could be multiple public Cloud providers, but the key point is, data on the edge is not just limited to what's in those Clouds. It could be anywhere that you're collecting data. And, we're enabling an architecture which performs incredibly well, because you take advantage of processing power on the edge, where you can get data anywhere that it sits. >> Okay, so, then, I'm setting up a Cloud, I'll call it a Cloud architecture, that encompasses the edge, where essentially, there are no boundaries, and you're bringing security. We talked about containers before, we've been talking about Kubernetes all week here at a Big Data show. And then of course, Cloud, and what's interesting, I think many of the Hadoop distral vendors kind of missed Cloud early on, and then now are sort of saying, oh wow, it's a hybrid world and we've got a part, you guys obviously made some moves, a couple billion dollar moves, to do some acquisitions and get hardcore into Cloud, so that becomes a critical component. You're not just limiting your scope to the IBM Cloud. You're recognizing that it's a multi-Cloud world, that' what customers want to do. Your comments. >> It's multi-Cloud, and it's not just the IBM Cloud, I think the most predominant Cloud that's emerging is every client's private Cloud. Every client I talk to is building out a containerized architecture. They need their own Cloud, and they need seamless connectivity to any public Cloud that they may be using. This is why you see such a premium being put on things like data ingestion, data curation. It's not popular, it's not exciting, people don't want to talk about it, but we're the biggest inhibitors, to this AI point, comes back to data curation, data ingestion, because if you're dealing with multiple Clouds, suddenly your data's in a bunch of different spots. >> Well, so you're basically, and we talked about this a lot on theCUBE, you're bringing the Cloud model to the data, wherever the data lives. Is that the right way to think about it? >> I think organizations have spoken, set aside what they say, look at their actions. Their actions say, we don't want to move all of our data to any particular Cloud, we'll move some of our data. We need to give them seamless connectivity so that they can leave their data where they want, we can bring Cloud-Native Architecture to their data, we could also help move their data to a Cloud-Native architecture if that's what they prefer. >> Well, it makes sense, because you've got physics, latency, you've got economics, moving all the data into a public Cloud is expensive and just doesn't make economic sense, and then you've got things like GDPR, which says, well, you have to keep the data, certain laws of the land, if you will, that say, you've got to keep the data in whatever it is, in Germany, or whatever country. So those sort of edicts dictate how you approach managing workloads and what you put where, right? Okay, what's going on with Watson? Give us the update there. >> I get a lot of questions, people trying to peel back the onion of what exactly is it? So, I want to make that super clear here. Watson is a few things, start at the bottom. You need a runtime for models that you've built. So we have a product called Watson Machine Learning, runs anywhere you want, that is the runtime for how you execute models that you've built. Anytime you have a runtime, you need somewhere where you can build models, you need a development environment. That is called Watson Studio. So, we had a product called Data Science Experience, we've evolved that into Watson Studio, connecting in some of those features. So we have Watson Studio, that's the development environment, Watson Machine Learning, that's the runtime. Now you move further up the stack. We have a set of APIs that bring in human features, vision, natural language processing, audio analytics, those types of things. You can integrate those as part of a model that you build. And then on top of that, we've got things like Watson Applications, we've got Watson for call centers, doing customer service and chatbots, and then we've got a lot of clients who've taken pieces of that stack and built their own AI solutions. They've taken some of the APIs, they've taken some of the design time, the studio, they've taken some of the Watson Machine Learning. So, it is really a stack of capabilities, and where we're driving the greatest productivity, this is in a lot of the examples you'll see tonight for clients, is clients that have bought into this idea of, I need a development environment, I need a runtime, where I can deploy models anywhere. We're getting a lot of momentum on that, and then that raises the question of, well, do I have expandability, do I have trust in transparency, and that's another thing that we're working on. >> Okay, so there's API oriented architecture, exposing all these services make it very easy for people to consume. Okay, so we've been talking all week at Cube NYC, is Big Data is in AI, is this old wine, new bottle? I mean, it's clear, Rob, from the conversation here, there's a lot of substantive innovation, and early adoption, anyway, of some of these innovations, but a lot of potential going forward. Last thoughts? >> What people have to realize is AI is not magic, it's still computer science. So it actually requires some hard work. You need to roll up your sleeves, you need to understand how I get from point A to point B, you need a development environment, you need a runtime. I want people to really think about this, it's not magic. I think for a while, people have gotten the impression that there's some magic button. There's not, but if you put in the time, and it's not a lot of time, you'll see the examples tonight, most of them have been done in one or two months, there's great business value in starting to leverage AI in your business. >> Awesome, alright, so if you're in this city or you're at Strata, go to ibm.com/WinWithAI, register for the event tonight. Rob, we'll see you there, thanks so much for coming back. >> Yeah, it's going to be fun, thanks Dave, great to see you. >> Alright, keep it right there everybody, we'll be back with our next guest right after this short break, you're watching theCUBE.

>> Live from Times Square in New York City, it's The Cube covering IBM's Change the Game: Winning with AI, brought to you by IBM. >> Hello everybody, welcome to The Cube's special presentation. We're covering IBM's announcements today around AI. IBM, as The Cube does, runs of sessions and programs in conjunction with Strata, which is down at the Javits, and we're Rob Thomas, who's the General Manager of IBM Analytics. Long time Cube alum, Rob, great to see you. >> Dave, great to see you. >> So you guys got a lot going on today. We're here at the Westin Hotel, you've got an analyst event, you've got a partner meeting, you've got an event tonight, Change the game: winning with AI at Terminal 5, check that out, ibm.com/WinWithAI, go register there. But Rob, let's start with what you guys have going on, give us the run down. >> Yeah, it's a big week for us, and like many others, it's great when you have Strata, a lot of people in town. So, we've structured a week where, today, we're going to spend a lot of time with analysts and our business partners, talking about where we're going with data and AI. This evening, we've got a broadcast, it's called Winning with AI. What's unique about that broadcast is it's all clients. We've got clients on stage doing demonstrations, how they're using IBM technology to get to unique outcomes in their business. So I think it's going to be a pretty unique event, which should be a lot of fun. >> So this place, it looks like a cool event, a venue, Terminal 5, it's just up the street on the west side highway, probably a mile from the Javits Center, so definitely check that out. Alright, let's talk about, Rob, we've known each other for a long time, we've seen the early Hadoop days, you guys were very careful about diving in, you kind of let things settle and watched very carefully, and then came in at the right time. But we saw the evolution of so-called Big Data go from a phase of really reducing investments, cheaper data warehousing, and what that did is allowed people to collect a lot more data, and kind of get ready for this era that we're in now. But maybe you can give us your perspective on the phases, the waves that we've seen of data, and where we are today and where we're going. >> I kind of think of it as a maturity curve. So when I go talk to clients, I say, look, you need to be on a journey towards AI. I think probably nobody disagrees that they need something there, the question is, how do you get there? So you think about the steps, it's about, a lot of people started with, we're going to reduce the cost of our operations, we're going to use data to take out cost, that was kind of the Hadoop thrust, I would say. Then they moved to, well, now we need to see more about our data, we need higher performance data, BI data warehousing. So, everybody, I would say, has dabbled in those two area. The next leap forward is self-service analytics, so how do you actually empower everybody in your organization to use and access data? And the next step beyond that is, can I use AI to drive new business models, new levers of growth, for my business? So, I ask clients, pin yourself on this journey, most are, depends on the division or the part of the company, they're at different areas, but as I tell everybody, if you don't know where you are and you don't know where you want to go, you're just going to wind around, so I try to get them to pin down, where are you versus where do you want to go? >> So four phases, basically, the sort of cheap data store, the BI data warehouse modernization, self-service analytics, a big part of that is data science and data science collaboration, you guys have a lot of investments there, and then new business models with AI automation running on top. Where are we today? Would you say we're kind of in-between BI/DW modernization and on our way to self-service analytics, or what's your sense? >> I'd say most are right in the middle between BI data warehousing and self-service analytics. Self-service analytics is hard, because it requires you, sometimes to take a couple steps back, and look at your data. It's hard to provide self-service if you don't have a data catalog, if you don't have data security, if you haven't gone through the processes around data governance. So, sometimes you have to take one step back to go two steps forward, that's why I see a lot of people, I'd say, stuck in the middle right now. And the examples that you're going to see tonight as part of the broadcast are clients that have figured out how to break through that wall, and I think that's pretty illustrative of what's possible. >> Okay, so you're saying that, got to maybe take a step back and get the infrastructure right with, let's say a catalog, to give some basic things that they have to do, some x's and o's, you've got the Vince Lombardi played out here, and also, skillsets, I imagine, is a key part of that. So, that's what they've got to do to get prepared, and then, what's next? They start creating new business models, imagining this is where the cheap data officer comes in and it's an executive level, what are you seeing clients as part of digital transformation, what's the conversation like with customers? >> The biggest change, the great thing about the times we live in, is technology's become so accessible, you can do things very quickly. We created a team last year called Data Science Elite, and we've hired what we think are some of the best data scientists in the world. Their only job is to go work with clients and help them get to a first success with data science. So, we put a team in. Normally, one month, two months, normally a team of two or three people, our investment, and we say, let's go build a model, let's get to an outcome, and you can do this incredibly quickly now. I tell clients, I see somebody that says, we're going to spend six months evaluating and thinking about this, I was like, why would you spend six months thinking about this when you could actually do it in one month? So you just need to get over the edge and go try it. >> So we're going to learn more about the Data Science Elite team. We've got John Thomas coming on today, who is a distinguished engineer at IBM, and he's very much involved in that team, and I think we have a customer who's actually gone through that, so we're going to talk about what their experience was with the Data Science Elite team. Alright, you've got some hard news coming up, you've actually made some news earlier with Hortonworks and Red Hat, I want to talk about that, but you've also got some hard news today. Take us through that. >> Yeah, let's talk about all three. First, Monday we announced the expanded relationship with both Hortonworks and Red Hat. This goes back to one of the core beliefs I talked about, every enterprise is modernizing their data and application of states, I don't think there's any debate about that. We are big believers in Kubernetes and containers as the architecture to drive that modernization. The announcement on Monday was, we're working closer with Red Hat to take all of our data services as part of Cloud Private for Data, which are basically microservice for data, and we're running those on OpenShift, and we're starting to see great customer traction with that. And where does Hortonworks come in? Hadoop has been the outlier on moving to microservices containers, we're working with Hortonworks to help them make that move as well. So, it's really about the three of us getting together and helping clients with this modernization journey. >> So, just to remind people, you remember ODPI, folks? It was all this kerfuffle about, why do we even need this? Well, what's interesting to me about this triumvirate is, well, first of all, Red Hat and Hortonworks are hardcore opensource, IBM's always been a big supporter of open source. You three got together and you're proving now the productivity for customers of this relationship. You guys don't talk about this, but Hortonworks had to, when it's public call, that the relationship with IBM drove many, many seven-figure deals, which, obviously means that customers are getting value out of this, so it's great to see that come to fruition, and it wasn't just a Barney announcement a couple years ago, so congratulations on that. Now, there's this other news that you guys announced this morning, talk about that. >> Yeah, two other things. One is, we announced a relationship with Stack Overflow. 50 million developers go to Stack Overflow a month, it's an amazing environment for developers that are looking to do new things, and we're sponsoring a community around AI. Back to your point before, you said, is there a skills gap in enterprises, there absolutely is, I don't think that's a surprise. Data science, AI developers, not every company has the skills they need, so we're sponsoring a community to help drive the growth of skills in and around data science and AI. So things like Python, R, Scala, these are the languages of data science, and it's a great relationship with us and Stack Overflow to build a community to get things going on skills. >> Okay, and then there was one more. >> Last one's a product announcement. This is one of the most interesting product annoucements we've had in quite a while. Imagine this, you write a sequel query, and traditional approach is, I've got a server, I point it as that server, I get the data, it's pretty limited. We're announcing technology where I write a query, and it can find data anywhere in the world. I think of it as wide-area sequel. So it can find data on an automotive device, a telematics device, an IoT device, it could be a mobile device, we think of it as sequel the whole world. You write a query, you can find the data anywhere it is, and we take advantage of the processing power on the edge. The biggest problem with IoT is, it's been the old mantra of, go find the data, bring it all back to a centralized warehouse, that makes it impossible to do it real time. We're enabling real time because we can write a query once, find data anywhere, this is technology we've had in preview for the last year. We've been working with a lot of clients to prove out used cases to do it, we're integrating as the capability inside of IBM Cloud Private for Data. So if you buy IBM Cloud for Data, it's there. >> Interesting, so when you've been around as long as I have, long enough to see some of the pendulums swings, and it's clearly a pendulum swing back toward decentralization in the edge, but the key is, from what you just described, is you're sort of redefining the boundary, so I presume it's the edge, any Cloud, or on premises, where you can find that data, is that correct? >> Yeah, so it's multi-Cloud. I mean, look, every organization is going to be multi-Cloud, like 100%, that's going to happen, and that could be private, it could be multiple public Cloud providers, but the key point is, data on the edge is not just limited to what's in those Clouds. It could be anywhere that you're collecting data. And, we're enabling an architecture which performs incredibly well, because you take advantage of processing power on the edge, where you can get data anywhere that it sits. >> Okay, so, then, I'm setting up a Cloud, I'll call it a Cloud architecture, that encompasses the edge, where essentially, there are no boundaries, and you're bringing security. We talked about containers before, we've been talking about Kubernetes all week here at a Big Data show. And then of course, Cloud, and what's interesting, I think many of the Hadoop distral vendors kind of missed Cloud early on, and then now are sort of saying, oh wow, it's a hybrid world and we've got a part, you guys obviously made some moves, a couple billion dollar moves, to do some acquisitions and get hardcore into Cloud, so that becomes a critical component. You're not just limiting your scope to the IBM Cloud. You're recognizing that it's a multi-Cloud world, that' what customers want to do. Your comments. >> It's multi-Cloud, and it's not just the IBM Cloud, I think the most predominant Cloud that's emerging is every client's private Cloud. Every client I talk to is building out a containerized architecture. They need their own Cloud, and they need seamless connectivity to any public Cloud that they may be using. This is why you see such a premium being put on things like data ingestion, data curation. It's not popular, it's not exciting, people don't want to talk about it, but we're the biggest inhibitors, to this AI point, comes back to data curation, data ingestion, because if you're dealing with multiple Clouds, suddenly your data's in a bunch of different spots. >> Well, so you're basically, and we talked about this a lot on The Cube, you're bringing the Cloud model to the data, wherever the data lives. Is that the right way to think about it? >> I think organizations have spoken, set aside what they say, look at their actions. Their actions say, we don't want to move all of our data to any particular Cloud, we'll move some of our data. We need to give them seamless connectivity so that they can leave their data where they want, we can bring Cloud-Native Architecture to their data, we could also help move their data to a Cloud-Native architecture if that's what they prefer. >> Well, it makes sense, because you've got physics, latency, you've got economics, moving all the data into a public Cloud is expensive and just doesn't make economic sense, and then you've got things like GDPR, which says, well, you have to keep the data, certain laws of the land, if you will, that say, you've got to keep the data in whatever it is, in Germany, or whatever country. So those sort of edicts dictate how you approach managing workloads and what you put where, right? Okay, what's going on with Watson? Give us the update there. >> I get a lot of questions, people trying to peel back the onion of what exactly is it? So, I want to make that super clear here. Watson is a few things, start at the bottom. You need a runtime for models that you've built. So we have a product called Watson Machine Learning, runs anywhere you want, that is the runtime for how you execute models that you've built. Anytime you have a runtime, you need somewhere where you can build models, you need a development environment. That is called Watson Studio. So, we had a product called Data Science Experience, we've evolved that into Watson Studio, connecting in some of those features. So we have Watson Studio, that's the development environment, Watson Machine Learning, that's the runtime. Now you move further up the stack. We have a set of APIs that bring in human features, vision, natural language processing, audio analytics, those types of things. You can integrate those as part of a model that you build. And then on top of that, we've got things like Watson Applications, we've got Watson for call centers, doing customer service and chatbots, and then we've got a lot of clients who've taken pieces of that stack and built their own AI solutions. They've taken some of the APIs, they've taken some of the design time, the studio, they've taken some of the Watson Machine Learning. So, it is really a stack of capabilities, and where we're driving the greatest productivity, this is in a lot of the examples you'll see tonight for clients, is clients that have bought into this idea of, I need a development environment, I need a runtime, where I can deploy models anywhere. We're getting a lot of momentum on that, and then that raises the question of, well, do I have expandability, do I have trust in transparency, and that's another thing that we're working on. >> Okay, so there's API oriented architecture, exposing all these services make it very easy for people to consume. Okay, so we've been talking all week at Cube NYC, is Big Data is in AI, is this old wine, new bottle? I mean, it's clear, Rob, from the conversation here, there's a lot of substantive innovation, and early adoption, anyway, of some of these innovations, but a lot of potential going forward. Last thoughts? >> What people have to realize is AI is not magic, it's still computer science. So it actually requires some hard work. You need to roll up your sleeves, you need to understand how I get from point A to point B, you need a development environment, you need a runtime. I want people to really think about this, it's not magic. I think for a while, people have gotten the impression that there's some magic button. There's not, but if you put in the time, and it's not a lot of time, you'll see the examples tonight, most of them have been done in one or two months, there's great business value in starting to leverage AI in your business. >> Awesome, alright, so if you're in this city or you're at Strata, go to ibm.com/WinWithAI, register for the event tonight. Rob, we'll see you there, thanks so much for coming back. >> Yeah, it's going to be fun, thanks Dave, great to see you. >> Alright, keep it right there everybody, we'll be back with our next guest right after this short break, you're watching The Cube.

>> Narrator: From Hell's Kitchen in New York City, it's theCUBE, on the ground at Serverlessconf brought to you by SiliconAngle Media >> Hi, I'm Stu Miniman, here with theCUBE at Serverless Conference in New York City, Hell's Kitchen. Happy to have with me, first time guest on the program Sam Kroonenburg, we had your brother on the program at the AWS Summit not far from here, at the Javits Center in New York City, but you're also one of the co-founders its the two brothers for A Cloud Guru. Thanks so much for joining me, and thank you for allowing us to come get some phenomenal content here. >> Yeah, no problem. Thank you for coming for the conference today. >> Alright, so Sam, take me back, you know, we talked to your brother a little bit about, well it was an interesting story, he said actually I got turned down for a job from Amazon and ended up creating a training company. But you built this and you built it on Serverless. >> I did yeah. >> So walk us through a little bit the thought process, the timing, you know, aren't you a little bit ahead of your time on that? >> Yeah, it was mid 2015, it was a strange time. We decided we wanted to build this school, this online learning platform, but the challenge we had was that we didn't have a lot of time, we both had families, kids, you know, mortgages, financial commitments. Basically I had four weeks. I had four weeks of leave owing to me, from my employer at the time. My wife and I had been planning this big family holiday with the kids for years and we were about to take it, and I remember having this phone call with Ryan and we were talking about how there were these people taking these online courses and they were really liking them. And we thought, what if we could build this school to teach people cloud computing. It was such a buzz and we just thought, there's something in this. But the challenge was the timing. I remember my wife turned to me and she said, "Look you've got to do it, we'll cancel the holiday, "take the four weeks and give it a try." So that's what we did, we actually flew down to live with Aaron, my in-laws and help look after the kids and I locked myself in a bedroom for four weeks and tried to build an online school. And that was there was no epiphany to go Serverless there was no grand plan. It was, we had a constraint, which was time. I had no time to build this thing. And so ended up using some of the latest technologies like AWS Lambda, API Gateway, a whole bunch of Serverless technologies because I saw that they would help me build this faster. And I could get something to market in the four weeks that I had. I actually spent the first couple of days trying to skin and configure Moodle, the learning management system and I tore my hair out and yeah, ended up putting this thing together with Serverless technologies. >> Ryan just walked by-- >> Oh, there he is. >> It's a llama unicorn with a cat or something like that. >> I'm going to put in the background. >> In the back of our video. Sam, what's your brother doing here? >> He's always trying to troll me. >> So talk to us, you know one of the things the maturation, kind of the speed of change in the industry for new technologies is just so fast these days. Take us through from those early days to you know Serverless today. What's your experience been? What would you say to people that look at this technology? >> I think it's a lot easier to get into now than it was two years ago. The ecosystem has grown around it, the core technologies are pretty much the same as they were two years ago, function as a service, execute functions in the cloud very similar, but the tooling around it, the ecosystem around it has grown. There's great deployment tools, orchestration systems that have come along. It's a lot easier to just get in now and early on, when we started we had to roll a lot of things ourselves, which took a lot of time, and that's what you're trying to stop, is losing time. Yeah, so there's that and the community has really grown, there's a lot of support in the community now. >> So if you had to do it all over, you could have done it in a weekend, rather than the four weeks. >> Yeah, instead of the four weeks. >> Yeah, I mean what's-- >> That's the interesting thing about what happened to us, we would not exist, our business would not exist if it wasn't for Serverless technologies. I literally couldn't, we could not have, built that school. It's not like it was the most amazing school when we launched it, but it was enough. It was just enough to get people using it, to get to market, to start to build a business around it. >> Alright, talk to me about this event. So, its the 5th Serverlessconf, not unheard of a company that does training to get involved with physical events, 'cause you bring them together, you know, what's the thought process, talk to us a little bit about that journey and this event itself. >> Yeah, I mean, a lot of this is organic for us. We built, it was early last year, you know we're part of the Serverless communities, a lot of pioneering going on here, a lot of people facing the same challenges. And we thought, well there's no event to bring all of these people together. And there's a lot of very fast pace of change here, a lot of rapid ideation and new technologies. Let's bring everyone together and see what we can do. That's what we did with Serverlessconf. We've never run a conference before, we just hired a warehouse in Brooklyn, a bunch of Australians and British guys coming over and we just invited a bunch of people on Twitter and 250 people turned out to the first one. It just got bigger and bigger from there. So this is actually the 5th Serverlessconf now. >> Well, its a hot week again, so we appreciate that the air conditioning works at this one. >> Yes, we have air conditioning at this one. >> 460 people here, you brought in some great speakers, we had a number of them on our program this week, speak to us, I mean you've got sponsors here, you've got good speakers, give us some of the highlights. >> We've got all of the main Cloud vendors are here, Google, IBM, Microsoft, Amazon and it's actually the product teams who build this stuff. That's what I love about this event, it's actually the people who build it. It's vendor neutral, it's really cool. You get great thought leaders from the community, Simon Wardley was a highlight this morning, his talk on Value Chain Mapping and Strategy was really interesting. Randall Hunt from AWS X Space X, talking about the continuous integration process when building rockets. Space X was absolutely fascinating and what bugs in production mean when you're building a rocket. It means the rocket blows up. Really interesting variety of talks from those tooling providers, companies like us who are just building on Serverless and then Serverless tooling companies and vendors. Really fascinating. >> Alright, Sam what should we be looking for in the future from Serverless and from A Cloud Guru? >> We're going to be doing a whole lot more Serverless content. You're going to see a lot of really interesting new content through our site, a lot of teaching on Serverless, we're going to be doing more Serverless Conferences. You'll see a lot from us, not just us, but from the wider community who come to the conference, who we know well, a lot of the experts, we're going to be doing a lot of work with those people. >> Well Sam Kroonenburg, really appreciate you joining us, appreciate the media sponsorship to allow theCube to come get some great content and share it with our communities, hope to see you at many more events in the future. >> Thank you for coming. >> Thank you so much. Sam Kroonenburg, I'm Stu Miniman. Thank you for watching theCUBE. (upbeat music)

>> Announcer: Live from midtown Manhattan, it's theCUBE covering BigData New York City 2017. Brought to you by SiliconANGLE Media, and its ecosystem sponsors. >> Hello everyone, welcome back to our day one, at Big Data NYC, of three days of wall to wall coverage. This is theCUBE. I'm John Furrier, with my co-hosts Jim Kobielus and Peter Burris. We do this event every year, this is theCUBE's BigData NYC. It's our event that we run in New York City. We have a lot of great content, we have theCUBE going live, we don't go to Strata anymore. We do our own event in conjunction, they have their own event. You can go pay over there and get the booth space, but we do our media event and attract all the influencers, the VIPs, the executives, the entrepreneurs, we've been doing it for five years, we're super excited, and thank our sponsors for allowing us to get here and really appreciate the community for continuing to support theCUBE. We're here to wrap up day one what's going on in New York, certainly we've had a chance to check out the Strata situations, Strata Data, which is Cloudera, and O'Reilly, mainly O'Reilly media, they run that, kind of old school event, guys. Let's kind of discuss the impact of the event in context to the massive growth that's going outside of their event. And their event is a walled garden, you got to pay to get in, they're very strict. They don't really let a lot of people in, but, okay. Outside of that the event it going global, the activity around big data is going global. It's more than Hadoop, we certainly thought about that's old news, but what's the big trend this year? As the horizontally scalable cloud enters the equation. >> I think the big trend, John, is the, and we've talked about in our research, is that we have finally moved away from big data, being associated with a new type of infrastructure. The emergence of AI, deep learning, machine learning, cognitive, all these different names for relatively common things, are an indications that we're starting to move up into people thinking about applications, people thinking about services they can use to get access, or they can get access to build their applications. There's not enough skills. So I think that's probably the biggest thing is that the days of failure being measured by whether or not you can scale your cluster up, are finally behind us. We're using the cloud, other resources, we have enough expertise, the technologies are becoming simpler and more straightforward to do that. And now we're thinking about how we're going to create value out of all of this, which is how we're going to use the data to learn something new about what we're doing in the organization, combine it with advanced software technologies that actually dramatically reduce the amount of work that's necessary to make a decision. >> And the other trend I would say, on top of that, just to kind of put a little cherry on top of that, kind of the business focus which is again, not the speeds and feeds, although under the hood, lot of great innovation going on from deep learning, and there's a ton of stuff. However, the conversation is the business value, how it's transforming work and, but the one thing that nobody's talking about is, this is why I'm not bullish on these one shows, one show meets all kind of thing like O'Reilly Media does, because there's multiple personas in a company now in the ecosystem. There are now a variety of buyers of some products. At least in the old days, you'd go talk to the IT CIO and you're in. Not anymore. You have an analytics person, a Chief Data Officer, you might have an IT person, you might have a cloud person. So you're seeing a completely broader set of potential buyers that are driving the change. We heard Paxata talk about that. And this is a dynamic. >> Yeah, definitely. We see a fair amount of, what I'm sensing about Strata, how it's evolving these big top shows around data, it's evolving around addressing a broader, what we call maker culture. It's more than software developers. It's business analysts, it's the people who build the hardware for the internet of things into which AI and machine learning models are being containerized and embedded. I've, you know, one of the takeaways from today so far, and the keynotes are tomorrow at Strata, but I've been walking the atrium at the Javits Center having some interesting conversations, in addition, of course, to the ones we've been having here at theCUBE. And what I'm notic-- >> John: What are those hallway conversations that you're having? >> Yeah. >> What's going on over there? >> Yeah, what I've, the conversations I've had today have been focused on, the chief trend that I'm starting to sense here is that the productionization of the machine learning development process or pipeline, is super hot. It spans multiple data platforms, of course. You've got a bit of Hadoop in the refinery layer, you've got a bit of in-memory columnar databases, like the Act In discussed at their own, but the more important, not more important, but just as important is that what users are looking at is how can we build these DevOps pipelines for continuous management of releases of machine learning models for productionization, but also for ongoing evaluation and scoring and iteration and redeployment into business applications. You know there's, I had conversations with Mapbar, I had conversations with IBM, I mean, these were atrium conversations about things that they are doing. IBM had an announcement today on the wires and so forth with some relevance to that. And so I'm seeing a fair, I'm hearing, I'm sensing a fair amount of It's The Apps, it's more than just Hadoop. But it's very much the flow of these, these are the core pieces, like AI, core pieces of intellectual property in the most disruptive applications that are being developed these days in all manner, in business and industry in the consumer space. >> So I did not go over to the show floor yet, I've not been over to the Atrium. But, I'll bet you dollars to donuts this is indicative of something that always happens in a complex technology environment. And again, this is something we've thought about particularly talked about here on theCUBE, in fact we talked to Paxata about it a little bit as well. And that is, as an organization gains experience, it starts to specialize. But there's always moments, there' always inflection points in the process of gaining that experience. And by that, or one of the indications of that is that you end up with some people starting to specialize, but not quite sure what they're specializing in yet. And I think that's one of the things that's happening right now is that the skills gap is significant. At the same time that the skills gap is being significant, we're seeing people start to declare their specializations that they don't have skills, necessarily, to perform yet. And the tools aren't catching up. So there's still this tension model, open source, not necessarily focusing on the core problem. Skills looking for tools, and explosion in the number of tools out there, not focused on how you simplify, streamline, and put into operation. How all these things work together. It's going to be an interesting couple of years, but the good news, ultimately, is that we are starting to see for the first time, even on theCUBE interviews today, the emergence of a common language about how we think about the characteristics of the problem. And I think that that heralds a new round of experience and a new round of thinking about what is all the business analysts, the data scientists, the developer, the infrastructure person, business person. >> You know, you bring up that comment, those comments, about the specialists and the skills. We talked, Jim and I talked on the segment this morning about tool shed. We're talking about there are so many tools out there, and everyone loves a good tool, a hammer. But the old expression is if you're a hammer, everything looks like a nail, that's cliche. But what's happened is there are a plethora of tools, right, and tools are good. Platforms are better. As people start to replatformize everything they could have too many tools. So we asked the C Chief Data Officer, he goes yeah, I try to manage the tool tsunami, but his biggest issue was he buys a hammer, and it turns into a lawnmower. That's a vendor mentality of-- >> What a truck. Well, but that's a classic example of what I'm talking about. >> Or someone's trying to use a hammer to mow the lawn right? Again, so this is what you're getting at. >> Yeah! >> The companies out there are groping for relevance, and that's how you can see the pretenders from the winners. >> Well, a tool, fundamentally, is pedagogical. A tool describes the way work is going to be performed, and that's been a lot of what's been happening over the course of the past few years. Now, businesses that get more experience, they're describing their own way of thinking throughout a problem. And they're still not clear on how to bring the tools together because the tools are being generated, put into the marketplace by an expanding array of folks and companies, and they're now starting to shuffle for position. But I think ultimately, what we're going to see happen over the next year and I think this is an inflection point, going back to this big tent notion, is the idea that ultimately we are going to see greater specialization over the next few years. My guess is that this year will probably, should get better, or should get bigger, I'm not certain it will because it's focused on the problems that we already solved and not moving into the problems that we need to focus on. >> Yeah, I mean, a lot of the problems I have with the O'Reilly show is that they try to throw default leadership out there, and there's some smart people that go to that, but the problem is is that it's too monetization, they try to make too much money from the event when this action's happening. And this is where the tool becomes, the hammer becomes a lawnmower, because what's happening is that the vendor's trying to stay alive. And you mentioned this earlier, to your point, the customers that are buyers of the technology don't want to have something that's not going to be a fit, that's going to be agile from us. They don't want the hammer that they bought to turn into something that they didn't buy it for. And sometimes, teams can't make that leap, skillset-wise, to literally pivot overnight. Especially as a startup. So this is where the selection of the companies makes a big difference. And a lot of the clients, a lot of customers that we're serving on the end user side are reaching the conclusion that the tools themselves, while important, are clearly not where the value is. The value is in how they put them together for their business. And that's something that's going to have to, again, that's a maturation process, roles, responsibilities, the chief data officer, they're going to have a role in that or not, but ultimately, they're going to have to start finding their pipelines, their process for ingestion out to analysis. >> Let me get your reaction, you guys, your reactions to this tape. Because one of the things that I heard today, and I think this validates a bigger trend as we talk about the landscape of the markup from the event to how people are behaving and promoting and building products and companies. The pattern that I'm hearing, we said it multiple times on theCUBE today and one from the guy who's basically reading the script, is, in his interview, explaining 'cause it's so factual, I asked him the straight-up question, how do you deal with suppliers? What's happening is the trend is don't show me sizzle. I want to see the steak. Don't sell me hype, I got too many business things to work on right now, I need to nail down some core things. I got application development, I got security to build out big time, and then I got all those data channels that I need, I don't have time for you to sell me a hammer that might not be a hammer in the future! So I need real results, I need real performance that's going to have a business impact. That is the theme, and that trumps the hype. I see that becoming a huge thing right now. Your thoughts, reactions, guys-- >> Well I'll start-- >> What's your reaction then? True or false on the trend? Be-- >> Peter: True! >> Get down to business. >> I'll say that much, true, but go ahead. >> I'll say true as well, but let me just add some context. I think a show like O'Reilly Strata is good up to a point, especially to catalyze an industry, a growing industry like big data's own understanding of it, of the value that all these piece parts, Hadoop and Spark and so forth, can add, can provide when deployed in a unit according to some emerging patterns, whatever. But at a certain point where a space like this becomes well-established, it just becomes a pure marketing event. And customers, at a certain point say, you know, I come here for ideas about things that I can do in my environ, my business, that could actually many ways help me to do new things. You know, you can't get that at a marketing-oriented, you can get that, as a user, more at a research-oriented show. When it's an emerging market, like let's say Spark has been, like the Spark Summit was in the beginning, those are kind of like, when industries go through the phase those are sort of in the beginning, sort of research-focused shows where industry, the people who are doing the development of this new architecture, they talk ideas. Now I think in 2017, where we're at now, is what the idea is everybody's trying to get their heads around, they're all around AI, what the heck that is. For a show like an O'Reilly Ready show to have relevance in a market that's in this much ferment of really innovation around AI and deep learning, there needs to be a core research focus that you don't get at this point in the lifecycle of Strata, for example. So that's my take on what's going on. >> So, my take is this. And first of all, I agree with everything you said, so it's not in opposition to anything. Many years ago I had this thought that I think still is very true. And that is the value of industry, the value of infrastructure is inversely correlated with the degree to which anybody knows anything about it. So if I know a lot about my infrastructure, it's not creating a lot of business value. In fact, more often than not, it's not working, which is why people end up knowing more about it. But the problem is, the way that technology has always been sold is as a differentiated, some sort of value-add thing. So you end up with this tension. And this is an application domain, a very, very complex application domain like big data. The tension is, my tool is so great that, and it's differentiating all those other stuff, yeah but it becomes valuable to me if and only if nobody knows it exists. So I think, and one of the reasons why I bring this up, John, is many of the companies that are in the big data space today that are most successful are companies that are positioning themselves as a service. There's a lot of interesting SaaS applications for big data analysis, pipeline management, all the other things you can talk about, that are actually being rendered as a service, and not as a product. So that all you need to know is what the tool does. You don't need to know the tool. And I don't know that that's necessarily going to last, but I think it's very, very interesting that a lot of the more successful companies that we're talking to are themselves mere infrastructure SaaS companies. >> Because-- >> AtScale is interesting, though. They came in as a service. But their service has an interesting value proposition. They can allow you to essentially virtualize the data to play with it, so people can actually sandbox data. And if it gets traction, they can then double-down on it. So to me that's a freebie. To me, I'm a customer, I got to love that kind of environment because you're essentially giving almost a developer-like environment-- >> Peter: Value without necessarily-- >> Yeah, the cost, and the guy gets the signal from the marketplace, his customer, of what data resolves. To me that's a very cool scene. I don't, you saying that's bad, or? >> No, no, I think it's interesting. I think it's-- >> So you're saying service is-- >> So what I'm saying is, what I'm saying is, that the value of infrastructure is inversely proportional to the degree to which anybody knows anything about it. But you've got a bunch of companies who are selling, effectively, infrastructure software, so it's a value-add thing, and that creates a problem. And a lot of other companies not only have the ability to sell something as a service as opposed to a product, they can put the service froward, and people are using the service and getting what they need out of it without knowing anything about the tool. >> I like that. Let me just maybe possibly restate what you just said. When a market goes toward a SaaS go-to-market delivery model for solutions, the user, the buyer's focus is shifted away from what the solution can do, I mean, how it works under the cover. >> Peter: Quote, value-add-- >> To what it can do potentially for you. >> The business, that's right. >> But you're not going to, don't get distracted by the implementation details. You have then as a user become laser-focused on, wow, there's a bunch of things that this can do for me. I don't care how it works, really. You SaaS provider, you worry about that stuff. I can worry now about somehow extracting the value. I'm not distracted. >> This show, or this domain, is one of the domains where SaaS has moved, just as we're thinking about moving up the stack, the SaaS business model is moving down the stack in the big data world. >> All right, so, in summary, the stack is changing. Predictions for the next few days. What are we going to see come out of Strata Data, and our BigData NYC? 'Cause remember, this show was always a big hit, but it's very clear from the data on our dashboards, we're seeing all the social data. Microsoft Ignite is going on, and Microsoft Azure, just in the past few years, has burst on the scene. Cloud is sucking the oxygen out of the big data event. Or is it? >> I doubt it was sucking it out of the event, but you know, theCUBE is in, theCUBE is not at Ignite. Where's theCUBE right now? >> John: BigData NYC. >> No, it's here, but it's also at the Splunk show. >> John: That's true. >> And isn't it interesting-- >> John: We're sucking the data out of two events. >> Did a lot of people coming in, exactly. A lot of people coming-- >> We're live streaming in a streaming data kind of-- >> John just said we suck, there's that record saying that. >> We're sucking all the data. >> So we are-- >> We're sharing data. These videos are data-driven. >> Yeah, absolutely, but the point is, ultimately, is that, is that Splunk is an example of a company that's putting forward a service about how you do this and not necessarily a product focus. And a lot of the folks that are coming on theCUBE here are also going on to theCUBE down in Washington D.C., which is where the Splunk show's at. And so I think one of the things, one of the predictions I'll make, is that we're going to hear over the next couple of days more companies talk about their SaaS trash. >> Yeah, I mean I just think, I agree with you, but I also agree with the comments about the technology coming together. And here's one thing I want to throw on the table. I've gotten the sense a few times about connecting the dots on it, we'll put it out publicly for comment right now. The role that communities will play outside of developer, is going to be astronomical. I think we're seeing signals, certainly open-source communities have been around for a long time. They continue to grow shoulders of giants before them. Even these events like O'Reilly, which are a small community that they rely on is now not the only game in town. We're seeing the notion of a community strategy in things like Blockchain, you're seeing it in business, you're seeing people rolling out their recruitment to say, data scientists. You're seeing a community model developing in business, yes or no? >> Yes, but I would say, I would put it this way, John. That it's always been there. The difference is that we're now getting enough experience with things that have occurred, for example, collaboration, communal, communal collaboration in open-source software that people are now saying, and they've developed a bunch of social networking techniques where they can actually analyze how those communities work together, but now they're saying, hmm, I've figured out how to do an assessment analysis understanding that community. I'm going to see if I can take that same concept and apply it over here to how sales works, or how B-to-B engagement works, or how marketing gets conducted, or how sales and marketing work together. And they're discovering that the same way of thinking is actually very fruitful over there. So I totally agree, 100%. >> So they don't rely on other people's version of a community, they can essentially construct their own. >> They are, they are-- >> John: Or enabling their own. >> That's right, they are bringing that approach to thinking about a community-driven business and they're applying it to a lot of new ways, and that's very exciting. >> As the world gets connected with mobile and internet of things as we're seeing, it's one big online community. We're seeing things, I'm writing a post right now, what you could, what B-to-B markets should learn from the fake news problem. And that is content and infrastructure are now contextually tied together. >> Peter: Totally. >> And related. The payload of the fake news is also related to the gamification of the network effect, hence the targeting, hence the weaponization. >> Hey, we wrote the three Cs, we wrote a piece on the three Cs of strategy a year and a half ago. Content, community, context. And at the end of the day, the most important thing to what you're saying about, is that there is, you know, right now people talk about social networking. Social media, you think Facebook. Facebook is a community with a single context, stay in touch with your friends. >> Connections. >> Connections. But what you're really saying is that for the first time we're now going to see an enormous amount of technology being applied to the fullness of all the communities. We're going to see a lot more communities being created with the software, each driven by what content does, creates value, against the context of how it works, where the community's defined in terms of what do we do? >> Let me focus on the fact that bringing, using community as a framework for understanding how the software world is evolving. The software world is evolving towards, I've said this many times in my work about a resurge, the data scientists or data people, data science skills are the core developers in this new era. Now, what is data science all about at its heart? Machine learning, building, and training machine learning models. And so training machine learning models is everything towards making sure that they are fit for their predicted purpose of classification. Training data, where you get all the training data from to feed all, to train all these models? Where do you get all the human resources to label, to do the labeling of the data sets, and so forth, that you need communities, crowdsourcing and whatnot, and you need sustainable communities that can supply the data and the labeling services, and so forth, to be able to sustain the AI and machine learning revolution. So content, creating data and so forth, really rules in this new era, like-- >> The interest in machine learning is at an all-time high, I guess. >> Jim: Yeah, oh yeah, very much so. >> Got it, I agree. I think the social grab, interest grab, value grab is emerging. I think communities, content, context, communities are relevant. I think a lot of things are going to change, and that the scuttlebutt that I'm hearing in this area now is it's not about the big event anymore. It's about the digital component. I think you're seeing people recognize that, but they still want to do the face-to-face. >> You know what, that's right. That's right, they still want, let's put it this way. That there are, that the whole point of community is we do things together. And there are some things that are still easier to do together if we get together. >> But B-to-B marketing, you just can't say, we're not going to do events when there's a whole machinery behind events. Legion batch marketing, we call it. There's a lot of stuff that goes on in that funnel. You can't just say hey, we're going to do a blog post. >> People still need to connect. >> So it's good, but there's some online tools that are happening, so of course. You wanted to say something? >> Yeah, I just want to say one thing. Face to face validates the source of expertise. I don't really fully trust an expert, I can't in my heart engage with them, 'til I actually meet them and figure out in person whether they really do have the goods, or whether they're repurposing some thinking that they got from elsewhere and they gussy it up. So face, there's no substitute for face-to-face to validate the expertise. The expertise that you value enough to want to engage in your solution, or whatever it might be. >> Awesome, I agree. Online activities, the content, we're streaming the data, theCUBE, this is our annual event in New York City. We've got three days of coverage, Tuesday, Wednesday, Thursday, here, theCUBE in Manhattan, right around the corner from Strata Hadoop, the Javits Center of influencers. We're here with the VIPs, with the entrepreneurs, with the CEOs and all the top analysts from WikiBon and around the community. Be there tomorrow all day, day one wrap up is done. Thanks for watching, see you tomorrow. (rippling music)

>> Narrator: Live from Manhattan, It's theCUBE. Covering AWS Summit, New York City, 2017. Brought to you by Amazon Web Services. >> Welcome back to Midtown. We're at the Javits Center here. (sound cuts out) 2017, along with Stu Miniman, I'm John Walls and you're watching The Cube as we continue with what's happening here. About five thousand people on the show floor and they said some twenty thousand registrants. Right Stew? That people came in and wanted to watch the keynotes live. >> It could be ten thousand that walked through before the days-- >> Right, it's hard to tell. >> Yeah. >> And right now half of them are outside looking for a cab I think. That's the way it works here. Ryan Kroonenburg is also here. He's the founder of a company called A Cloud Guru. >> Yes. >> I like Ryan already. I liked him as soon as we met him because he said, "like the beer, Kroonenburg." So you resonated with the two of us, Ryan. >> Ryan like the airline and Kroonenburg like the beer. >> We appreciate that. Alright, so you're a cloud education company. >> Yes. >> And you bill yourself or at least in the conversation as you want to be the Netflix of cloud education. That's what you're doing. Tell us a little bit about the founding of the company. It began with your brother? >> Yes, yeah. >> Just two years ago and now you've grown to some 40 employees. >> Yeah, so I used to be a solutions architect and I was desperate to get a job at AWS so I became obsessed with getting trained in AWS. And at the time, a company I worked for had a training freeze. So we couldn't go out and do in-classroom training. If I had to do that myself, I'd have to pay for it myself. And I found that there wasn't a lot of good on-line training companies two years ago. I didn't get the job with AWS and turned out to be the best thing that ever happened to me. And so I decided to create my own course on AWS. Launched that, started going viral and that was the birth of A Cloud Guru. >> Ryan, bring is in a little inside of building the company, so you're not only teaching cloud, but you're built on cloud and not just any cloud, but using the LAN to server list from pretty early on that. >> Exactly, so we practice what we preach. You know, we are real AWS engineers. We built the entire platform serverlessly. We think we're the world's first serverless start-up. We're certainly the world's first serverless learning management system. So we don't pay for any servers whatsoever. There's no virtual/physical servers. And we're basically, purely AWS native. We do use a bunch of third party services like Xero and PayPal and things like that. But most of our platforms are AWS. >> Yeah, in the keynote this morning, Adrian Cockroft talked about Bustle, A New York based start-up that uses a lot of serverless, but you built the company before you even had funding and now you've got a little bit of funding. Can you give any insight? Do the investors looks at that and say, wow, this is a great model? >> Yeah, so we raised a decent series A. One of the founders of Warby Parker is on our board now so that's really exciting. A guy called Andy and he's helping us scale. One of the reasons we took funding was helping to scale. So our infrastructure scales automatically with AWS because it's built on Lambda and API Gateway. But we as a company are struggling to scale in like finding the right employees and all of that sort of thing, so that's where we're getting some help. >> Alright, what are you hearing from people taking your courses? What new things are they asking for? How are you expanding the scope of your offerings? >> Everyone is obviously very interested in AWS, but they also want to learn other cloud-computing platforms now, especially Azure, so we are expanding the scope of our content to do Azure as well as Guru. The other problem people are having is, AWS innovates so quickly. You know, there's like a thousand updates last year. There's 19 new updates last week. So there having trouble keeping up so we run just a weekly TV show called, AWS This Week, and we basically just tell people what's new this week. And the great thing about New York Summit is there's been like five or six announcements here so I'm going to be busy on Friday, filming. >> Is there any one particular area of training that you see more people drifting toward or following toward? >> I think serverless and big data are the hot topics. Big data, by that I mean AI, machine learning. That's just exploding right now. And just serverless architectures because the future of cloud is serverless. Why pay for virtual, physical machines by the hour or by the minute and have system administrators, network administrators, database administrators when all you actually want to focus on is your code and your end customers and serverless allows you to do that. >> So what's your process then? In terms of you staying on top of it, right? Because now you have to. >> Ryan: Yeah. >> I mean, you, you're it, right? You're the point of expertise. So how do you ... I guess, remain in that kind of relationship with AWS that you're the cusp? >> So, I obviously read all the blogs. Our students, We've got 300,000 students right now and our discussion forums are very very active so if they have announced something that I've missed, the students tell me, like, we'll know within a few hours. So, that's it really. It's just forever learning, but I love learning anyway so it's fun to get paid to learn. >> John: Sure. You bet. >> Ryan, how many people have gone through the training so far? Do you know how many of them get certified after they do that? And how many are kind of repeat customers? >> We've got 300,00 have gone through the training so far. We do track our pass rates. Our pass rates vary from anywhere between, normally 80 to 90%. Not everyone will pass on the first go because the exams are tough and it's also quite stressful. Sitting these exams can be quite stressful. In terms of the number of students that actually go on to get certified, that's not something we track just yet, but we're looking to change that as well. But yeah, we have a very good pass rate. >> So how does it work? I want to learn, you know, whatever. I want to dive into AI, whatever it is. I come to you, you've got something for me there right? You've got, I don't know how many hours of work I have to do, but take us through how it really works. >> Yeah so, it's video training. Online video training. So say you want to learn DynamoDB. We have a 19 hour course on that. And we go right into the very depths of DynamoDB. So you watch the videos. we'll show you what we're doing in the labs. We'll give you all the sample code if we're using code and then you can go and do it yourself. We very much believe in, the only way to learn Cloud is by getting your hands dirty. To actually go and do it yourself. So people watch the labs, do the stuff themselves and then complete the course. If it's a certification course, then at the end what they'll do is go and book the exam and hopefully, they'll pass the exam as well. >> So Ryan, you're in there looking at all this stuff, especially things like server lists. What are you looking for, for kind of the maturation? Is there anything that do you give feedback to Amazon? The community give you feedback? I have to imagine that there's some good feedback loops there? >> Yeah, I'm lucky enough to be an AWS community hero. So we get get briefed by Amazon on things that are coming out. You know, under MDA of course. We give a lot of feedback on that. No, I think serverless is the next big revolution. I hate hype and buzz words and things like that, but the thing about serverless is that, now you don't have to worry about servers. You can just focus on your code and you don't need to worry about any of the normal administration behind it and it's like ridiculously cheap. You get a million lambda implications a month for free. That's just part of Free Tier. We actually only just came off of Lambda Free Tier a couple of months ago and we've got 300,000 students. So, it's very very very cheap so its amazing. It's driving new revolution. >> What advice would you give to someone if they were looking to start a business and using serverless as a platform? >> Yeah, definitely check out AWS of course, we build our entire business off AWS. Design, try if you can, architect everything in a serverless fashion because like I keep saying, you don't have to worry about management of operating systems, virus patching, security, any of that. AWS, they take all... They take care of all of the heavy lifting for you. >> So I know you are a big fan of Lambda, but have you looked at some of the other serverless options out there? Is there any concern around, there's open source options out there. >> Ryan: Yeah. >> How do we get compatibility and not be just locked into Amazon? >> Azure Functions looks really good. See, this thing about vendor lock-in, I mean, you've got the serverless framework as well. If you build your applications on the serverless framework, you can move between platforms quite easily. That is coming so you could build it out on AWS and then move over to Azure if you wanted. The founder of serverless frameworks is a good friend of mine. So I definitely recommended checking it out. And that would be my advice. If you are going to go serverless use the serverless framework so then you don't have to worry about vendor lock in. But at the same time, Amazon, they reduce their prices all the time. So it is a good vendor to be with. >> I just think your story is great. I think that the best "no" you ever got in your life was from AWS. And now you're giving them a big "yes". >> Yeah, absolutely, I love AWS. They're such amazing people as well. They've all become my-- through my business and people I used to work with have all become really good friends of mine as well. It's been a great journey in last two years. >> You've done well for them, they've done well for you. It's a good relationship. >> Exactly. >> Ryan, thanks for being with us. >> Thank you. >> And continued success. >> Right, thanks guys. >> Good for you. You bet, Ryan Kroonenburg. The founder of A Cloud Guru. Along with his brother, Sam, making a pretty good business out of things on the AWS platform right now. Back with more here from AWS Summit, right after this. You're watching The Cube. (fast music)

>> Announcer: Live from Manhattan, it's theCUBE covering AWS Summit New York City 2017. Brought to you by Amazon Web Services. >> Welcome back live to Midtown Manhattan, along with Stu Miniman, I am John Walls. We're here on theCUBE and we're wrapping up our coverage here at AWS Summit. Again, kind of tough to get a feeling for just how many folks were here. But some were in that seven, eight, $9,000 range and most of them are still here I think, out on the show floor here behind us. Good keynotes this morning. Good programming throughout the day as well and then really good buzz here on the show floor. So, good day I think, for AWS Stu, and we've talked about it, it is kind of remarkable to see the number of people who turned out for a regional show. >> Yeah John, you know I've been to some shows in the Javits Center where people wander in, they get some swag, they look for a free beer and a t-shirt and then that's kind of their... These people are, you know, kind of diggin' in. I know there's a bunch of sessions been going on. The pavilion here has had all these little breakout sessions. There was one on, you know, VMware and VMware and AWS and it was, you know, not only the seats, which usually it was like oh come on in, you know, come get a prize and things like that. >> John: Right, right. >> There was five rows of people standing pressed in and asking questions like, "How do I set up "the networking on this, how does this work?" Things like this, so it's like a mini AWS re:Invent, so their big show, one we've done theCUBE at a number of years, I've been there a number of years. I commented on our intro that this is larger than the first Amazon re:Invent that I went to like four years ago. >> How about that, in that short of period of time? >> Yeah and that's one of the things about Amazon and public Cloud in general and all of these technologies, the growth and the speed of change is just amazing. It used to be we talked from a software standpoint, it was like okay, I'm tied to that Intel release of every 18 months that I'm going to click out, then it was like okay, we kind of go to a yearly cycle. Now it was more like well not only is a lot of software released, you know, continuous integration and continuous deployment CICD, which sometimes it's every six weeks, sometimes it's daily, but Amazon's releasing new features every day. We talked in the intro, oh there were three major releases and we had the guy I'm talking about, the machine learning stuff and he's like oh you mean the three announcements that we had in machine learning? And we're like oh, we only heard about one of those. Wait, you had a couple others underneath there? Oh, let's talk about the F1 compute instance and the FPGAs. There's always so much in Amazon and when you go into any environment in the little boxes that they put in there and you start peeling the onion, it's impressive. >> It is. >> And there's just depth and customers are interested in it and people are using it. You know, I was used to so much in my career where something gets announced and a year later it's like hello, is anybody using this? As opposed to at this show, a bunch of the announcements, I already talked to a bunch of people that have been in private beta, they've been testing this out, they're excited about it and because it's just so easy to get on all of these new features. >> Right, and I mean, we've seen it here, we've heard from many people here from a lot of different walks of life. You mentioned some of the past shows, AWS Public Sector. I was at that not too long ago in Washington, D.C. and you see a company that has its units very focused and very driven and doing very well and the right relationships. Buzzword, serverless, right? We heard it a lot today. Serverless applications, serverless computing. From more than one source, we heard it from several folks and so obviously this is not just a popular piece of nomenclature for the day, this is a trend, a theme that's going to be evolving and maturing over the next year or two. >> Yeah I mean everybody for the last couple years they've kind of been looking at it with their head sideways. I'm not sure that I understand it. We talked to two companies today, it was IOPipe and A Cloud Guru that their company, their IT infrastructure was all built on serverless, and they both got funding recently, so this isn't just oh yeah, some developer does some cool stuff on the side, microservices, buzz buzz, things like that. We talked to FICO is using serverless for their admin functions, certain areas they're not ready to roll it out across the board, governance compliance, things like that, I need to understand it. It is still very early, but that being said, there's a lot of usage in it. Last year it was oh, if you want to develop for the Alexa platform, the Amazon Echo type thing, that uses serverless, so we're seeing lots and lots of cases. That really is a new way of architecting the way to roll out really microservices driven applications and when we talk about the big challenge of our time, it's distributed architectures and how do I have new applications? We talked to a number of companies moving from the old way of doing my application to building new application, that's the long hole in the 10. This is not something that happens overnight, but I can start playing with it in a much smaller form factor and do it for pennies not years and millions of dollars so there is really serverless has really in many ways eclipsed kind of the container's discussion for the hot buzz in the industry. Kubernetes fits into that whole picture, but not just serverless in general, but AWS Lambda is the leader of the pack out there and you know, yet another reason why Amazon just going strong, their revenue still doing well, keeps adding to what they're doing and you don't hear many people griping when you walk around the show floor as to what they wish they had. It's a very positive experience. >> And you hear criticisms saying, "They only had 42% growth year to year." It's not what it used to be. But 42 as you know, most people would gladly be in that position. What about your thoughts about the maturation of the Cloud? You mentioned transformative and things are evolving and growing, where do you put it now? Is this second phase, next phase, late phase? Where are we in terms of what's happening and what AWS is making happen? >> So a couple years ago we know that Cloud is here to stay. There's still the joke a friend of friend of mine in the keynote. 20,000 people registered for this event and it was like well, I guess this Cloud thing might have legs, so we are still early in the overall wave of this. I've been in a number of conferences this year that we've done theCUBE on. You talk about the infrastructure companies and companies that have built on virtualization. They said, "We went through a decade "of tremendous growth with virtualization." Virtualization is still very important. Amazon builds their infrastructure not on VMWare, but they leverage virtualization technologies, but the next 10 years will be this huge wave of really that going up the uptake of the S curve so we're past really the classic crossing the chasm. We're in the early majority going to mid majority of people using it and there's just no shortage of new use cases that people can use it for. We've talked to lots of companies that start up and say, "I'm just leveraging Cloud because it's easy." THere's VCs that look at that as how to get involved and as I've just mentioned before, there's companies now that are building themselves on serverless so this is even kind of the next piece that follows these waves we are early in Cloud if you look at kind of overall ham of IT, public Cloud is still a very small piece. At Wikiban we've been talking for the last I think two years about what we really the multi Cloud environment. There's true private Cloud and there's public Cloud and how do I get that operational model that I can scale, I can build really a distributed architecture? I shift more to an operational expense rather than a capital expense, so it's flexibility, it's agility, it's speed, and it's very interesting, exciting times. There's no more exciting time to be in tech than today, maybe tomorrow, because we know the only thing constant is that the pace of change keeps increasing. >> It does increase and two big drivers of that, we heard again today, artificial intelligence, machine learning. How would you rate or how would you characterize the impotence that they're providing in terms of pushing the envelope? >> Absolutely there was some good announcements today, I don't know that there's any today that you'd say, "I'm going to look back five years from now and be like, 'Wow, I was in New York City when that was announced.'" >> John: Right, but just in general? >> But in general, let me say one of the things that I didn't hear today, I was was little bit disappointed, I mentioned it in the open, we talked to a couple of the partners here, you know the Kubernetes option. Adrian Kovrov got up on stage. He had written a blog post there was an announcement last week, no mention of where Kubernetes is going to fit in here. Definitely they're committed to it, they're making developments, but maybe something will come out in beta soon. I would expect by the time we get to the re:Invent show in November that we will have more clarity here. I was hoping to hear that more and that was something that didn't come out of Amazon, but they're embracing it. Customers are asking for it, developers, there's a ground swell on that, so they're involved with it. Lambda and serverless absolutely. Amazon is at the vanguard, they're pushing things forward. Machine learning and IoT, Amazon is at the table. It is still very early, they're driving a lot of things forward. Yeah, you know, you get enough, it's like come on, there's no BitCoin discussed today, why is that? So some of the other vendors there, but Amazon is in all the appropriate conversations. There's not any wide gaps that you'd say customers like hate these. Amazon's not in this base and I expect them to and therefore I'm going to choose another platform provider. That being said, it's not a winner-take-all, it is a multi Cloud world, most of these environments, we talked about even if I do serverless, if I architect them a certain way I can move them and make changes, Kubernetes the same way. So Amazon, one of the things that they pride themselves on is they need to keep proving to their customers every month that they are the ones that they fuse on because otherwise it is relatively easy to make a change, but they're the big dog, they got the leadership position, and it's always impressive to watch them. >> It is and you speak of impressive. re:Invent, is just what, two and a half months away, three months away, we'll be out there as well. Huge show, probably one of the largest shows by far that we attend and looking forward to that and seeing you down the road. Always a pleasure to be with you. >> Thanks so much. >> And great job as always. Stu Miniman does an outstanding job providing analysis for Wikiban, so on behalf of Stu and all the crew here at theCUBE, we thank you for joining us here at the AWS Summit in Midtown. We've been live at the Javits Center. Have a good week and we'll see you down the road here on theCUBE. (light electronic music)

>> Announcer: Live, from Manhattan, it's the Cube, covering AWS Summit, New York City, 2017. Brought to you by Amazon Web Services. >> And you are watching the Cube. Along with Stu Miniman, I'm John Walls. We're at the Javits Center, here, Midtown Manhattan, for the AWS Summit. We're continuing our coverage here live on the Cube. We'll broadcast outlet of the silicon angle tv platform, and we're joined now by Anuj Dutia, who is Senior Manager of Product and New Business at Verizon. Anuj, it's good to see you today, sir. >> Thank you, thanks for having me. >> You bet, absolutely. Now, you have a partnership in the works with AWS. I know you had an announcement today, of sorts. Also, adding a little more flavor to that, I want you to tell us a little bit about that announcement, and the significance of that. >> Yeah, absolutely. We're really observing the industry's, our customers are the biggest, Fortune 500 customer's enterprises, they're moving their vote close to AWS. So, once they move their vote close to AWS, they want us to connect to their applications, our networks to connect to their applications in a seamless way. They want to make sure that the end user experience, the application experience, when the application's under AWS, is seamless. So, what we're trying to do is we're trying to make sure we instantiate the workshop appliances in AWS, so that we're able to give them internet connectivity. So, we have a service offer, which is across the platforms. You know, we have our private cloud, we have AWS, we have the end CPE devices. For our customers, they want to have hybrid environment. They want to make sure that they are able to connect with each of these business applications with the best user experience. So, that's what we are enabling them to do with this service. >> I'm wondering if you could help clarify for us, because those of us that have watched a while, I mean, I remember when Verizon bought Terremark recently, I know you're still working through some of the details, but people still come to me and say oh, you're talking to Verizon, I hear they're selling off all their data centers. So, of course, that's kind of the headlines when you dig in to what you were talking about, the hybrid solutions, lots of partners. What is the role of cloud in Verizon, and what are some of those important solutions you're putting together? >> Sure, so we have our own offering, you know, which is the hosted network services. It's an open stack, base back form that we have around the world, but we're not in the business of, we want the customers to be connected, so we're in the business of networks. So, if our customers are moving on to a public cloud, or a private cloud, or their own data centers, we want to enable them to have that internet connectivity, and make sure they're able to take advantage of the application that we're routing, as well as the transport diversity. You know, we have a product called Secure Cloud Interconnect, or Direct Connect in AWS terms, which is one of the transports that will be used their high priority applications, and internet for another one. So, basically, we want to make sure we are able to give them the advantage of the through transports, as well as enabling them to have the best experience. So, regardless of what deployment they have, to your question, we want to make sure we are their partners in enabling them to do that. >> Yeah, the open stack solution, I mean, that's really building NFV, so what you care about is delivering services to the end user, correct? >> Correct, correct. So, we do have a concept of white boxes, or genetic platforms on the CP side. So, if I'm an enterprise with 5000 stores, as an example. I want to deploy these lightweight white boxes around the country, and then haul all the traffic to my private data center, to AWS, to other cloud providers. We will be able to do that, and with this partnership, we will be able to get them closer to their applications within AWS, that's the whole plan of action. >> Yeah, all of the carriers, including Verizon, have lots of edge deployments, that's been one of the hottest topics. Does that fit in with what you're doing with Amazon? Maybe you can, you know, what does Edge mean to kind of your business unit, your customers? What's important there? >> Absolutely, absolutely. As far as Edge is concerned, right? There is a thick Edge, and there is a thin Edge. When you say a thick Edge, you want to have all the applications, network applications, routing, firewall, you name it, everything to be sitting in the Edge. If I'm a bank, I may need that, but if I'm a retailer, I may not. I may say, no, I want to have my security applications in the cloud. The cloud could be our private cloud, it could be customers' cloud, or it could be AWS. We will enable to connect those Edge devices, the thicker version, or thinner version, to each of these cloud locations, so that it's a seamless connectivity for the enterprises. So, our strength is in the virtualization, and in the network connectivity. But all focused on the network. That's our whole use case, and we want to make sure if a customer walks in to our door with these different hybrid deployments, we're able to support them without any exceptions. >> We talked a lot so far about what you do, or the goals or the mission that you have, put it on the other side of the fence, from a customer expectation, and from a customer demand. How has that changed? >> That's a good question. So, what we've seen is our customers have a lot of options. We are not in the business of telling them where their applications should reside, where their business applications should reside. Now, if, as an organization, if they've decided to move their critical applications to AWS, or have them in their private data centers, so they are coming to us, customers are coming to us and telling us, we want, what is our business goal? Our business goal is to have, when my employee tries to reach my HR application, it should be seamless. It should not matter whether I host it in my data center, yours, AWS, or on the Edge. They don't care, they want to have access to those four top applications, or 40 top applications all the time. So, we've seen customers coming in and saying, and telling us, we're not asking you where to host the business apps, we have already made a decision, we are going to host it in these four clouds. One of them definitely being AWS. And we're like, okay, we will enable you, you just tell us what kind of connectivity you guys need, where do you want to host it, and with AWS being their key data center for hosting their business applications, now we have an automated, orchestrated way. So, you have your 5000 devices, with a click of a button, we'll instantiate something on AWS for you. That way, you're able to connect to all of your business applications seamlessly. So, with the demand that, going back to your question, the demand that we're seeing is hey, we want to have a variety of deployment models, we don't want to be locked down, we don't want to spend a whole lot on our data centers, we like the AWS solution, so we're going to have our business apps hosted at AWS, but at the same time, we want to make sure everything is connected for our users, and there is no latency that they experience. Customers are still having a lot of challenges about kind of getting their arms around this whole multi cloud environment, and networking a lot of times is kind of networking security and management sit at kind of the top of the challenges there. How would you rate how we're doing as an industry, how have we moved the ball forward, and what do we still need to do, to be able to make this seamless, manageable, much easier going forward? >> It's a great question. We come across these customers all the time, right? They see a bunch of PowerPoint presentations and advertisements, in all the different forms, and they think that they think that they're able to do that all by themselves, and have the cost efficiency. The key challenge is the key know how, and connecting it with the whole end to end network, as well as applications. So, what we bring to the table is exactly that. We partner with AWS and other cloud providers, but AWS being the biggest one, we try to make sure we are, get them the fully orchestrated solution. So, our whole solution is we're enabling, in this service, right, we're enabling Cisco and Viptela solutions on AWS. So, our whole value prop with them is you place an order with Verizon, we take care of making sure you're connected to AWS, seamlessly, with the appliance of your choice, which in this case happens to be Cisco, Viptela solutions, and the reliable network from Verizon, but completely automated and orchestrated. What we've been observing is customers go down the DIY path, and that's absolutely fair, sometimes they succeed, but most often they come back and say I don't know how to make it work end to end. I'm able to do this little piece part, have done my dev opps here, so it works, but when I move my production load, I don't know what to do. And, that's the value of this partnership, that we're looking to provide that seamless experience to our customers. >> And also, we've been talking a lot about enterprise, but that market is mostly small and midsize. I mean, which one do you think sells the wind in it's sails right now? I mean, or is it apples and oranges, because they have different concerns, different levels and different options? >> That's an interesting question. They are apples and oranges, at least in my opinion, and I'll tell you why. Because the needs for the top Fortune 500, Fortune 1000 companies, is very different from a dentist's office or a lawyer's office. But, there is a middle line. The middle line is, what if I'm a coffee shop with 8000 stores? Am I on this side, or that side? Because, each of these 8000 stores are like small businesses, if you will, but as a company I'm a tier one, so I have my own needs from a corporate network standpoint. So, what we're trying to do is we're trying to make sure we take advantage of our partnership with AWS, where we are saying we're able to enable you if you are moving your production workloads anyway. But, if that's something you want to scale, then probably you've got to have a hybrid deployment and we make that happen for you. But, to your question, right? I do think they're apples and oranges, because their needs are very different. The need for the application availability for an enterprise, but a big tier one enterprise, is way higher than, say a dentist's office. If Outlook 365, Office 365 doesn't work for a dentist office for an hour, who cares? But, if it doesn't work for a big. >> Just don't let your dentist hear you say that. Be careful. >> All right. >> Everybody buy your dentist, right? >> Yeah, exactly. >> All right, Anuj, thanks for being with us. >> Thank you, thanks for having me. >> We appreciate the time. >> Thank you. >> Good luck down the road. >> Thanks >> Anuj Dutia from Verizon joining us here on the Cube. We continue live from New York City. AWS Summit. Back in a bit.

>> Announcer: Live from Manhattan, it's the CUBE. Covering AWS Summit, New York City, 2017. Brought to you by Amazon web services. >> And we are live here at AWS Summit here at the Javits Center, New York City, we're midtown, Manhattan, a lot of activity going on outside, you can imagine all the buzz inside as well. Somewhere between 6, 7, 8,000 attendees, kind of tough to tell right now, but everybody's jammed inside here on the show floor and they've been here all day and they're going to stay for a while I think too. As I said, a lot of buzz going on, and good buzz too. Along with Stu Miniman, I'm John Walls and we're now joined by Erica Windisch who is the Co-founder and the CTO of IOpipe. Erica, thanks for being with us here on the CUBE. >> Thank you, thank you for having me. >> You have had a big day. >> Yes we have, yeah. >> It's always fun to talk about money but you did have a fairly significant announcement this morning to make. Tell us about that. >> Yeah, so this morning we announced funding, $2.5 million from several investors including NEA, Madrona, and Underscore. >> So, yeah, you don't often get to high-five everybody for a day like that. I mean that kind of validation, obviously is something that not you just take to the bank, you take it to the marketplace too. >> Yeah, absolutely. And we actually started, our first check was from Techstars so we joined Techstars here in New York City and did that last year for their summer program and it was really great and that was the first foundation that we really had, and then having that further validation from major VCs like NEA and Madrona, Underscore, you know that really was really validating for us as well as just the fact that we're building, we're hiring and we're building and having what I think is an increasingly awesome product. >> Sure, well tell us about IOpipe, for folks at home who are watching might not be familiar with your space, what you do and how you do it. >> Yeah, so we provide tools for software developers to build and manage their applications on Amazon Lambda. So, basically, it's all serverless, we're actually built on serverless as well, we monitor with IOpipe, we dogfood everything. And we are providing deeper insights into those application workloads as well as correlating that information in more useful ways. Deeper knowledge of what exactly is happening in the run times, so we're able to see the data we ingest tells us information on the processes and the containers and the virtual machines that are running your Lambda workload, so we can see things like memory leaks and we can see file descriptor leaks and displaced utilization leaks, things like that that Amazon doesn't collect or at least doesn't give you that information. So, we're looking at ways we can provide more value to users of Lambda and also extending it with plugins so we have a plugin for tracing where you can time aspects of your application as well as profiler, so you can enable a profiling plugin and you get a full flame graph. So you can see, these are all the functions and this one ran and this one ran and the stack looks like this and so you can see the full flame graph of what happened and when and full timing information. This kind of insight that nothing else really gives you. >> Yeah, Erica, every time we have a new technology we go through this kind of diffusion of innovation that goes through. Remember back, I go back thinking about when virtualization came, people, what is it, how do I use it? We saw that in containers and each wave seems to be going faster and faster so there's still plenty of people I talked to that were like, "serverless what?" You know, some new as a service, I mean I thought I knew it with SAS and everything else like that. You're digging into these environments further. Can you give us, what are some of the kind of key use cases you're seeing, what are the challenges that customers are having? What works, what doesn't work, help us unpack that some? >> So, I think there's a number of challenges that users run into today. One is the fact that it is new so some of the tools are still evolving. Operations tools, development tools are still evolving. Just this week, Amazon announced SAM local so you can do editing and debugging locally on your machine or your laptop. That wasn't available before, right? So these tools, we're very much still in a learning phase for some of the tools, but some of the things like what we're doing with IOpipe, in some ways is more traditional because we're bringing in some of the basic monitoring tools and capabilities that you would expect from other platforms. But the other side, also innovating because we're bridging that development and operations into a single tool so it's not development and operations, it's, not even just different tools for those two things, but single tools for those. So I think that's part of the solution, part of the problem, in terms of workloads, I think there's a lot of ETLs, streaming applications, very infrequent things like chron jobs, web applications, you can take flask applications or express applications and just port them directly over to Lambda with almost a lift and shift for those, right? So there's a lot of power for bringing on the web 'cause you pay per the request. You don't scale your application and build your application for the number of servers that you need to handle the requests, it scales it per request and you pay per request and that's what's powerful in both scale of operations and team and like financially, but also, yeah, I lost train of thought there, but it all scales that way, right? Like just according to the request. >> Yeah, bring us into a typical customer, I know there are no typical customers, everyone's a little bit different, but you've got the developers, you've got the operators, finance has always had, you know, there's challenges with cloud in general but serverless at least promises that it's going to be less expensive. What are those dynamics from an organizational standpoint that you see inside? >> In terms of cost? >> Not just cost, but do the developers make something and the operators are like, wait, you know, there's challenges there? Or who drives this initiative in general? Does finance come and say, has finance heard about this and said hey, I heard I could save 60-70% on my cloud if you just re-architect this on Lambda. Or is it the developers coming through and saying, oh, wow, this is great, and can do it, or are operators, who's driving the initiatives and what are some of those dynamics? >> So I see a combination of these things. Some organizations, and I don't want to say names 'cause I don't want to like, you know, they did this and that's how it is. But I get the impression that certain organizations they have a top-down approach where they're going like, everything is going to be serverless and the cost really matters. So you're going to build serverless unless you can't, right? Serverless by default, anything else as an exception. Then there's organizations where developers are really pushing for it because it simplifies their requirements, right? It's a self-service aspect, right, even if they can spit out VMs, even if they have self-service VMs, they won't have to spit out VMs, they don't have to build docker images, they don't have to look at how the operating system is configured. They write code and they deploy code. There's no other steps, right? They're not like, oh, what version of Python is on here and how do I install all the libraries and how do I, right, like with serverless you just write the code and you ship the code. Which is really, really nice. So, in a way it's like having a golden image that you can't change, and you just know you're always going to build for in every application and every organization is going to the same golden image. Which simplifies a lot of things. >> Stu and I were talking about serverless, the whole concept, because it's really not truly serverless it's just different server, or it's a different flavor of it basically. So, first off, what gave birth to that and then where do you think, with serverless computering, serverless application, so on and so forth, where's that going? >> Yeah. >> What's going to be the real value at the end of the day of that? >> So, first of all the term "serverless," I look at it as, yes there are servers, serverless is servers are not my concern as a developer, right, I am not worrying about what the server looks like or operating the servers necessarily. I care about building my application which is why we're looking at building tools that are bridging development and operations so that operations is part of your development. But I see, the direction of serverless, really interesting in a few ways. One is that it's going to be available for more use cases. So right now there's certain use cases that make sense and one of the challenges is figuring out which use cases it doesn't work for. Eventually, you're not going to have that question, potentially, right? So maybe we get to a point where you don't have to ask, the challenge isn't, is serverless good for this use case? Maybe it's good for all use cases eventually down the road, maybe. Another thing is... >> If I could just follow up on that. Some of the announcements today like AWS Glue has serverless in the background there. Seems very promising, things like machine learning, artificial intelligence, serverless, IOT where you know, I need to balance the surface area of attack there but with serverless it won't be active as much and there will be links that are a little bit more dynamic. So, lots of those new use cases seem to be built really well for serverless. What are some of the cases today that you just say, hey, don't even go serverless there. >> Oh don't go serverless, where to do that? Well, so, Lambda has an execution time window which can be limiting for some things that you might want to do. So, like, Lambda in particular may not be the best case for all video encoding tasks. Some video encoding tasks if you can time limit it can be fine. But it's not good for all video encoded tasks because it's a batch process, potentially. Serverless processes that can let's say paralyze that and say, we're going to run Lambda but we're going to say split this up into segments, for instance, you can do that, or if you do it as a stream, right? Like you pipe a video and blocks into Kinesis, right, you can make that work. But it becomes a challenge to those kinds of use cases. >> Yeah, there was the example I think in the keynote was, this high process that would have taken five years, we can do 155 seconds. >> Right, but you have to paralyze it, right? >> Stu: Exactly. >> And if you can't paralyze a task and you can't do it within five or ten minutes, you can't use Lambda for it today. But it also depends on how you define serverless, right, because if serverless is Lambda, that's one thing. But if serverless is these other SAS products as well potentially, like AWS Transcode service, well is that serverless? If it is, then there you go. There's a solution potentially for you. So there's very blurry lines sometimes around what is serverless, and we're looking at IOpipe around serverless functions. I feel the same way around cloud in general was that there's cloud compute and it kind of evolved over time and the cloud is everything like all these things are in a cloud. But originally when we're talking cloud, five years ago, ten years ago, it was all compute. That's what we were talking about. So these terms change over time, so it's hard to say what serverless will be in five years or ten years because it'll mean something different. >> Or next week, for that matter. >> Yeah. >> Erica, last question I have. $2.5 million, what's that going to drive, what should we expect to see from your company and give us any final thoughts on what you'd like to see for the maturation of the serverless technology field? >> Yeah, so we've been hiring and building out a team, we're working on improving the user experience of the product, we are adding additional plugins and enhancements to the service. We feel that we have a really good base with our 1.0 announcement, 'cause we're not just the 2.5 million, we also announced our 1.0. And the 1.0 has a really good base of functionality and we're looking at adding additional plugins and additional features that can extend the service. So we're looking at doing that with that money. And with serverless in general, I think this is really compelling, what we're going to see in the next year, because we're going to see more large enterprises and more enterprise adoption, I think. I mean I was involved early in cloud. I was involved early in docker. And this point of serverless is very much at the early days of these technologies, and I definitely see a rocket ship taking off, and I think in the next year it's going to be really interesting to kind of see it starting to orbit a little bit. >> Well, new product, new funding, and a new day for IOpipe. >> Yes. >> So congratulations on a good day and thank you for being with us here on the CUBE. >> Thank you very much. >> You bet, we'll continue here at the Javits Center we're in midtown Manhattan continuing our coverage of the AWS Summit, here on the CUBE. (futuristic music)