>>Hey guys and girls, welcome back to Motor City, Lisa Martin here with John Furrier on the Cube's third day of coverage of Coon Cloud Native Con North America. John, we've had some great conversations over the last two and a half days. We've been talking about identity and security management as a critical need for enterprises within the cloud native space. We're gonna have another quick conversation >>On that. Yeah, we got a great segment coming up from someone who's been in the industry, a long time expert, running a great company. Now it's gonna be one of those pieces that fits into what we call super cloud. Others are calling cloud operating system. Some are calling just Cloud 2.0, 3.0. But there's definitely a major trend happening around how cloud is going Next generation. We've been covering it. So this segment should be >>Great. Let's unpack those trends. One of our alumni is back with us, O Rika Zi, co-founder and CEO of Aerio. Omri. Great to have you back on the >>Cube. Thank you. Great to be here. >>So identity move to the cloud, Access authorization did not talk to us about why you found it assertive, what you guys are doing and how you're flipping that script. >>Yeah, so back 15 years ago, I helped start Azure at Microsoft. You know, one of the first few folks that you know, really focused on enterprise services within the Azure family. And at the time I was working for the guy who ran all of Windows server and you know, active directory. He called it the linchpin workload for the Windows Server franchise, like big words. But what he meant was we had 95% market share and all of these new SAS applications like ServiceNow and you know, Workday and salesforce.com, they had to invent login and they had to invent access control. And so we were like, well, we're gonna lose it unless we figure out how to replace active directory. And that's how Azure Active Directory was born. And the first thing that we had to do as an industry was fix identity, right? Yeah. So, you know, we worked on things like oof Two and Open, Id Connect and SAML and Jot as an industry and now 15 years later, no one has to go build login if you don't want to, right? You have companies like Odd Zero and Okta and one login Ping ID that solve that problem solve single sign-on, on the web. But access Control hasn't really moved forward at all in the last 15 years. And so my co-founder and I who were both involved in the early beginnings of Azure Active directory, wanted to go back to that problem. And that problem is even bigger than identity and it's far from >>Solved. Yeah, this is huge. I think, you know, self-service has been a developer thing that's, everyone knows developer productivity, we've all experienced click sign in with your LinkedIn or Twitter or Google or Apple handle. So that's single sign on check. Now the security conversation kicks in. If you look at with this no perimeter and cloud, now you've got multi-cloud or super cloud on the horizon. You've got all kinds of opportunities to innovate on the security paradigm. I think this is kind of where I'm hearing the most conversation around access control as well as operationally eliminating a lot of potential problems. So there's one clean up the siloed or fragmented access and two streamlined for security. What's your reaction to that? Do you agree? And if not, where, where am I missing that? >>Yeah, absolutely. If you look at the life of an IT pro, you know, back in the two thousands they had, you know, l d or active directory, they add in one place to configure groups and they'd map users to groups. And groups typically corresponded to roles and business applications. And it was clunky, but life was pretty simple. And now they live in dozens or hundreds of different admin consoles. So misconfigurations are rampant and over provisioning is a real problem. If you look at zero trust and the principle of lease privilege, you know, all these applications have these course grained permissions. And so when you have a breach, and it's not a matter of if, it's a matter of when you wanna limit the blast radius of you know what happened, and you can't do that unless you have fine grained access control. So all those, you know, all those reasons together are forcing us as an industry to come to terms with the fact that we really need to revisit access control and bring it to the age of cloud. >>You guys recently, just this week I saw the blog on Topaz. Congratulations. Thank you. Talk to us about what that is and some of the gaps that's gonna help sarto to fill for what's out there in the marketplace. >>Yeah, so right now there really isn't a way to go build fine grains policy based real time access control based on open source, right? We have the open policy agent, which is a great decision engine, but really optimized for infrastructure scenarios like Kubernetes admission control. And then on the other hand, you have this new, you know, generation of access control ideas. This model called relationship based access control that was popularized by Google Zanzibar system. So Zanzibar is how they do access control for Google Docs and Google Drive. If you've ever kind of looked at a Google Doc and you know you're a viewer or an owner or a commenter, Zanzibar is the system behind it. And so what we've done is we've married these two things together. We have a policy based system, OPPA based system, and at the same time we've brought together a directory, an embedded directory in Topaz that allows you to answer questions like, does this user have this permission on this object? And bringing it all together, making it open sources a real game changer from our perspective, real >>Game changer. That's good to hear. What are some of the key use cases that it's gonna help your customers address? >>So a lot of our customers really like the idea of policy based access management, but they don't know how to bring data to that decision engine. And so we basically have a, you know, a, a very opinionated way of how to model that data. So you import data out of your identity providers. So you connect us to Okta or oze or Azure, Azure Active directory. And so now you have the user data, you can define groups and then you can define, you know, your object hierarchy, your domain model. So let's say you have an applicant tracking system, you have nouns like job, you know, know job descriptions or candidates. And so you wanna model these things and you want to be able to say who has access to, you know, the candidates for this job, for example. Those are the kinds of rules that people can express really easily in Topaz and in assertive. >>What are some of the challenges that are happening right now that dissolve? What, what are you looking at to solve? Is it complexity, sprawl, logic problems? What's the main problem set you guys >>See? Yeah, so as organizations grow and they have more and more microservices, each one of these microservices does authorization differently. And so it's impossible to reason about the full surface area of, you know, permissions in your application. And more and more of these organizations are saying, You know what, we need a standard layer for this. So it's not just Google with Zanzibar, it's Intuit with Oddy, it's Carta with their own oddy system, it's Netflix, you know, it's Airbnb with heed. All of them are now talking about how they solve access control extracted into its own service to basically manage complexity and regain agility. The other thing is all about, you know, time to market and, and tco. >>So, so how do you work with those services? Do you replace them, you unify them? What is the approach that you're taking? >>So basically these organizations are saying, you know what? We want one access control service. We want all of our microservices to call that thing instead of having to roll out our own. And so we, you know, give you the guts for that service, right? Topaz is basically the way that you're gonna go implement an access control service without having to go build it the same way that you know, large companies like Airbnb or Google or, or a car to >>Have. What's the competition look like for you guys? I'm not really seeing a lot of competition out there. Are there competitors? Are there different approaches? What makes you different? >>Yeah, so I would say that, you know, the biggest competitor is roll your own. So a lot of these companies that find us, they say, We're sick and tired of investing 2, 3, 4 engineers, five engineers on this thing. You know, it's the gift that keeps on giving. We have to maintain this thing and so we can, we can use your solution at a fraction of the cost a, a fifth, a 10th of what it would cost us to maintain it locally. There are others like Sty for example, you know, they are in the space, but more in on the infrastructure side. So they solve the problem of Kubernetes submission control or things like that. So >>Rolling your own, there's a couple problems there. One is do they get all the corner cases who built a they still, it's a company. Exactly. It's heavy lifting, it's undifferentiated, you just gotta check the box. So probably will be not optimized. >>That's right. As Bezo says, only focus on the things that make your beer taste better. And access control is one of those things. It's part of your security, you know, posture, it's a critical thing to get right, but you know, I wanna work on access control, said no developer ever, right? So it's kind of like this boring, you know, like back office thing that you need to do. And so we give you the mechanisms to be able to build it securely and robustly. >>Do you have a, a customer story example that is one of your go-tos that really highlights how you're improving developer productivity? >>Yeah, so we have a couple of them actually. So there's the largest third party B2B marketplace in the us. Free retail. Instead of building their own, they actually brought in aer. And what they wanted to do with AER was be the authorization layer for both their externally facing applications as well as their internal apps. So basically every one of their applications now hooks up to AER to do authorization. They define users and groups and roles and permissions in one place and then every application can actually plug into that instead of having to roll out their own. >>I'd like to switch gears if you don't mind. I get first of all, great update on the company and progress. I'd like to get your thoughts on the cloud computing market. Obviously you were your legendary position, Azure, I mean look at the, look at the progress over the past few years. Just been spectacular from Microsoft and you set the table there. Amazon web service is still, you know, thundering away even though earnings came out, the market's kind of soft still. You know, you see the cloud hyperscalers just continuing to differentiate from software to chips. Yep. Across the board. So the hyperscalers kicking ass taking names, doing great Microsoft right up there. What's the future? Cuz you now have the conversation where, okay, we're calling it super cloud, somebody calling multi-cloud, somebody calling it distributed computing, whatever you wanna call it. The old is now new again, it just looks different as cloud becomes now the next computer industry, >>You got an operating system, you got applications, you got hardware, I mean it's all kind of playing out just on a massive global scale, but you got regions, you got all kinds of connected systems edge. What's your vision on how this plays out? Because things are starting to fall into place. Web assembly to me just points to, you know, app servers are coming back, middleware, Kubernetes containers, VMs are gonna still be there. So you got the progression. What's your, what's your take on this? How would you share, share your thoughts to a friend or the industry, the audience? So what's going on? What's, what's happening right now? What's, what's going on? >>Yeah, it's funny because you know, I remember doing this quite a few years ago with you probably in, you know, 2015 and we were talking about, back then we called it hybrid cloud, right? And it was a vision, but it is actually what's going on. It just took longer for it to get here, right? So back then, you know, the big debate was public cloud or private cloud and you know, back when we were, you know, talking about these ideas, you know, we said, well you know, some applications will always stay on-prem and some applications will move to the cloud. I was just talking to a big bank and they basically said, look, our stated objective now is to move everything we can to the public cloud and we still have a large private cloud investment that will never go away. And so now we have essentially this big operating system that can, you know, abstract all of this stuff. So we have developer platforms that can, you know, sit on top of all these different pieces of infrastructure and you know, kind of based on policy decide where these applications are gonna be scheduled. So, you know, the >>Operating schedule shows like an operating system function. >>Exactly. I mean like we now, we used to have schedulers for one CPU or you know, one box, then we had schedulers for, you know, kind of like a whole cluster and now we have schedulers across the world. >>Yeah. My final question before we kind of get run outta time is what's your thoughts on web assembly? Cuz that's getting a lot of hype here again to kind of look at this next evolution again that's lighter weight kind of feels like an app server kind of direction. What's your, what's your, it's hyped up now, what's your take on that? >>Yeah, it's interesting. I mean back, you know, what's, what's old is new again, right? So, you know, I remember back in the late nineties we got really excited about, you know, JVMs and you know, this notion of right once run anywhere and yeah, you know, I would say that web assembly provides a pretty exciting, you know, window into that where you can take the, you know, sandboxing technology from the JavaScript world, from the browser essentially. And you can, you know, compile an application down to web assembly and have it real, really truly portable. So, you know, we see for example, policies in our world, you know, with opa, one of the hottest things is to take these policies and can compile them to web assemblies so you can actually execute them at the edge, you know, wherever it is that you have a web assembly runtime. >>And so, you know, I was just talking to Scott over at Docker and you know, they're excited about kind of bringing Docker packaging, OCI packaging to web assemblies. So we're gonna see a convergence of all these technologies right now. They're kind of each, each of our, each of them are in a silo, but you know, like we'll see a lot of the patterns, like for example, OCI is gonna become the packaging format for web assemblies as it is becoming the packaging format for policies. So we did the same thing. We basically said, you know what, we want these policies to be packaged as OCI assembly so that you can sign them with cosign and bring the entire ecosystem of tools to bear on OCI packages. So convergence is I think what >>We're, and love, I love your attitude too because it's the open source community and the developers who are actually voting on the quote defacto standard. Yes. You know, if it doesn't work, right, know people know about it. Exactly. It's actually a great new production system. >>So great momentum going on to the press released earlier this week, clearly filling the gaps there that, that you and your, your co-founder saw a long time ago. What's next for the assertive business? Are you hiring? What's going on there? >>Yeah, we are really excited about launching commercially at the end of this year. So one of the things that we were, we wanted to do that we had a promise around and we delivered on our promise was open sourcing our edge authorizer. That was a huge thing for us. And we've now completed, you know, pretty much all the big pieces for AER and now it's time to commercially launch launch. We already have customers in production, you know, design partners, and you know, next year is gonna be the year to really drive commercialization. >>All right. We will be watching this space ery. Thank you so much for joining John and me on the keep. Great to have you back on the program. >>Thank you so much. It was a pleasure. >>Our pleasure as well For our guest and John Furrier, I'm Lisa Martin, you're watching The Cube Live. Michelle floor of Con Cloud Native Con 22. This is day three of our coverage. We will be back with more coverage after a short break. See that.

(upbeat music) >> Welcome back everyone, theCUBE's three days of wall to wall coverage of Snowflake Summit '22 is coming to an end, but Dave Vellante and I, Lisa Martin are so pleased to have our final guest as none other than the co-founder and president of products at Snowflake, Benoit Dageville. Benoit, thank you so much for joining us on the program. Welcome. >> Thank you. Thank you, thank you. >> So this is day four, 'cause you guys started on Monday. This is Thursday. The amount of people that are still here speaks volumes. We've had close to 10,000 people here. >> Yeah. >> Could you ever have imagined back in the day, 10 years ago that it would come to something like this in such a short period of time? >> Absolutely not. And I always say if I had imagined that I might not have started Snowflake, right. This is somehow scary. I mean and yeah, it's huge. And you can feel the excitement of everyone. It is like mind boggling and the fact that so many people are still there after four days is great. >> Your keynote on Tuesday was fantastic. Your energy was off the charts. It was standing room only. There were overflow rooms. Like we just mentioned, a lot of people are still here. Talk about the evolution of Snowflake, this week's announcements and what it means for the future of the data cloud. >> Yeah, so evolution, I mean, I will start with the evolution. It's true that that's what we have announced. This week is not where we started necessarily. So we started really very quickly with big data combined with data warehouse as one thing. We saw that the world was moving into fragmented siloing data and we thought with Thierry, we are going to combine big data and data warehouse in one system for the cloud with this elasticity and this service simplicity. So simplicity, amazing elasticity, which is this multi workload architecture that I was explaining during the keynotes and really extreme simplicity with the service. Then we realized that there is one other attribute in the cloud, which is unique, which doesn't exist on-premise, which is collaboration. How you can connect different tenets of the platform together. And Google showed that with Google Docs. I always say to me, it was amazing that you could share document and have direct access to document that you didn't produce and you can collaborate on this document. So we wanted to do the same thing for data and this is where we created the data cloud and the marketplace where you can have all these data sets available and really the next evolution I would say is really about applications that are (indistinct) by that data, but are way simpler to use for all the tenets of the data cloud. And this is the way you can share expertise also, including, ML model, everyone talks about ML and the democratization of ML. How are you going to democratize ML? It's not by making necessary training super easy. Such that everyone can train their ML for themselves. It's by having very specialized application where data and ML is at the core, which are shared, through the marketplace and we shall leverage by many tenets of this marketplace that have no necessary knowledge about building this ML models. So that's where, yeah. >> When you and Thierry started the company, I go back to the improbable rise of Kubernetes and there were other more sophisticated container management systems back then, but they chose to focus on simplicity. And you've told me before, that was our main tenet. We are not going to worry about all the complex database stuff. You knew how to do that, but you chose not to. So my question is, did you envision solving those complex problems over time yourselves or through an ecosystem? Was this by design or did you... As you started to get into it, say let's not even try to go there let's partner to go there. >> Yeah, I mean, it's both. It's a combination of both. Snowflake, the simplicity of the platform is really important because if our partners are struggling to put their solution and build solution on top of Snowflake they will not build it. So it's very important that number one, our platform is really easy to use from day one. And that really has to be built inside the platform. You cannot build simplicity on top. You cannot have a complex solution and all of a sudden realize that, oh, this is complex. I need to build another layer on top of it to make it simpler, that will not work. So it had to be built from day one, but you're right. What is going to be Snowflake? I always say in 10 years from now, we just turn 10 years old or we are going to turn 10 years old in few months. Actually a few months, yes. >> Right. >> So for the next 10 years I really believe that most of Snowflake will not be built by Snowflake. And that's the power of the partners and these applications. When you are going to say I'm using Snowflake, actually, probably you are not going to use directly code developed by Snowflake. That code will leverage our platform, but you will use a solution that has been built on top of Snowflake. And this is the way we are going to decouple, the effort of Snowflake and multiply it. >> It's an interesting balance, isn't it? When I think of what you did with Apache Iceberg, if I use Iceberg and I'm not going to get as much functionality, but I may want that openness, but I'm going to get more functionality inside of the data cloud. And I don't know, but if you know the answer to what's going to happen. >> No, that's a super good question. So to explain what we did with Apache Iceberg, and the fact that now it's a native format for us. So everything that you can do with our internal formats, you can do it with Apache Iceberg, including security, defining masking, data masking all the governors that we have, fine grain security aspects, the replications you can define you can use (indistinct) on top of... >> But there's a but, right? But if I do that with native Snowflake tools, I'm going to get an even greater advantage, am I not? >> Yes. So that's what I'm saying. So that's why we embraced Iceberg, because I think we can bring all the benefit of Snowflake to people who have decided to use Iceberg, I mean open formats. Iceberg is a table format. So and why it was important because people had massive investments in open source in Hadoop. And we had a lot of companies saying, we love Snowflake. We want to be a Snowflake customer, but we cannot really migrate all our data. I mean, it will be really costly. And we have a lot of tools that need access, direct access. So this is why we created Iceberg because we can really... I mean, we really think that we can bring the benefit of Snowflake to this data. >> Gives customers optionality. Okay. I use this term super cloud. You don't use the term, but that's okay. And I get a lot of heat for it. But to me, what you're doing is quite a bit different than multicloud because you're creating that abstraction layer. You're bringing value above it. My question to you is, the most of the heat I get is, oh, that's just SaaS. Are you just SaaS? >> No. I mean, no, absolutely not. I mean, you're right we are a super cloud. I mean it's a much better word than saying we are multicloud. Multicloud is often viewed as oh, I have my system and now I can run this system in the different cloud providers. Snowflake is different. We have one single platform for the world, which happens to have some regions are AWS region, some regions are Azure, some regions are GCP, Google and we merge them together. We have this Snowgrid technology that connects all our regions together so that we have really one platform for the world. And that's very important because when you talk about connections of data and expertise applications you want to have global reach, right. It doesn't exist. We are not siloed by region of the world, right? You have a lot of companies which are multinational that have presence everywhere. And you want to have this global reach. The world is not a independent set of regions and countries, right. And that's the realization. So we had to create this global platform for our customers. >> And now you have people building clouds on top of your data cloud, well that to me is the next signal. In your keynote, you talked about seven pillars, all data, all workloads, global architecture, self-managed, programmable, marketplace, governance, which ones are the most important? >> All of them. It's like when you have kids, you don't want to pick and say, this one is my preferred one, so they are really important. All of them, as I said without data, there is no Snowflake, right? So all data is so important that we can reach every data, wherever it is. And Iceberg is a part of that, but all workload is really important because you don't want to put your data in one platform, if you cannot run all your workloads and workloads are much broader than just data warehousing, there is data engineering, data science, ML engineering, (indistinct) all these workloads applications. So that's critical. Programmable is where we are moving, right. We want to be the place where data applications are built. And we think we have a lot of advantages because data application needs to use many workloads at once, right? It's not that that application will do only data warehousing, they need to store their states, they need to use this new workload that we define, which is Unistore. They need to do data engineering because they need to get data, right. They have to save this data. So they need to combine many workload and if they have to stitch this workload, because the platform was not designed as one single product where everything is consistent and works together, that you have to stitch, it's complicated for this application to make it work. So Snowflake is we believe an ideal platform to run these data applications. So all workloads, programmable, obviously, so that you can program. And programmable has two aspects, which is big part of our announcement. Is both data programmability, which is running Python against petabyte, terabytes of data at scale and doing it scale out. So that's what we call data programmability. So both Java, Python and (indistinct), but also running applications like UI. And we had this acquisition of Streamlit. Streamlit now has been fully integrated in Snowflake. We announced that such that not only you can have this data programmability, but you can expose your data through this nice UIs, interactive UI to business users potentially. So it goes all the way there. Global is super important. As we say, we want to be one platform for the world. And of course, as I said, the last pillar, which is somehow critical for us, because we are cloud, we need to have governance. We need to have security of our data. And why it took us so long to do Python is not because it's out to run Python, right? Everyone can run Python it's because we had to secure it. And I talk about it creating this amazing sandboxing technology, such that when you include third party libraries and third party codes, you are guaranteed that this third party code will not reach to infiltrate your data, right. We control the environment that Snowflake provides. >> Can you share us some of the feedback from the customer? You probably had many customer conversations over the last four days. >> Look at that smile. (interviewer laughing) (Lisa laughing) >> Actually not because I was so busy everywhere. Unfortunately, I didn't speak to many customers. Saying that, I had everyone stopping me and talking about what they heard and yeah, there is a huge excitement about all of this. >> What's been the feedback around the theme of the event? The world of data collaboration. Data collaboration is so critical as every company these days must be a data company to compete, to win. What's been from just some of the feedback that you've had customers really embracing data collaboration, what Snowflake is enabling. >> Yeah. I mean, almost every company which is using Snowflake, is collaborating with data. You have heard, the number of stable edges that we have, and there is a real need for that because your data alone... You cannot make sense of your data if it is just alone. It needs to be connected with other data. You haven't not generated. So all data, when you say the first pillar of Snowflake is all data is not only about your data, but is about all the data that's created around you. That puts perspective on your own data. And that's critical and it's so painful to get. I mean, even your data is difficult to have access to your data, but imagine data that you didn't produce. And so yes, so the data collaboration is critical, and then now we expanded it to application and expertise, sharing models, for example, That's going to have a huge impact. >> All data includes now transaction data, right? >> Yes. >> That's a big part of the announcements that you guys made. >> Yeah. So and that's the motivation for that was really, if we want to run application, full application, we announced native applications, which are fully executed and run inside the (indistinct) data cloud, right. They need all the services that application need and in particular managing their states. And so we created Unistore, which is a new workload, which allows you to combine transactional data, which are generated by this application. And at the same time being able to do analytics directly on this data. So we call it Hybrid Table because it has this hybrid aspect. You can do both transactional access to this data and at the same time analytic here without having data pipeline and moving data and transforming it from the transactional system to the analytical system, right. Snowflake is one system. Again, in the spirit of simplifying everything, this is the Snowflake (indistinct). >> I can ask the same question I ask at first, (indistinct) when was the aha moment that you and Thierry had that said, this is not just a better data warehouse, it's actually more than that. You probably didn't call it a data cloud until later on, but did you know that from the beginning or was that something you kind of stumbled into? >> No. So as I said, we founded Snowflake in 2012 and Thierry and I, we locked in my apartment and we were doing the blueprint of Snowflake and trying to find what is the revolution with the cloud for this data warehouse system and analytical system, both big data and data warehouse. And the aha moment was but of course cloud, okay. What is cloud? It's elasticity, it's service and later collaboration. So in the elasticity aspect, when you ask database people, what is elasticity, they will tell you, oh, you have a cluster of nodes. Like if it is Oracle, it would be a (indistinct) cluster. And the elasticities that you can add one node, two node to this cluster without having too much impact on the existing workload, because you need to shuffle data, right. It's hard and doing it online, right, that's elasticity. If you can do that, you are elastic. We thought that that was not very interesting to do that. What is interesting with elasticity is to plug new workloads. You can plug a workload like that and that workload is running without having any impact on other workloads, which are running on the platform. So elasticity for us was having dedicated computer resources to workloads. And these computer resources could start and be part as soon as the workload starts and will shut down when the workload finishes and they will be sized exactly for the demand of that workload. And we thought the aha moment was, okay if we can do that, now we can run a workload with, let's say 10X more computer resources than what you would have used or 100X more. Okay, let's say 100X more because we paralyzed things. Now this workload can run 100X faster, right? That's assuming we do a good job in the scale, which is our IP. And if we can do that, now the computer resources that you have used, you have used them for 100 times less. So you have used 100 times more resources because you have more nodes, but because you go fast, you use them for less time, right? So if you multiply the two it's constant. So you can run and accelerate workload dramatically 10X, 100X for the same price. Even if we are not better in efficiency than competition, just having that was the magic, right? >> You know how Google founders originally had trouble raising money because who needs another search engine? Did you get from original, like when you started going to raise money, Amazon's got a database, so who needs another cloud database? Did you get that early on or was it just obvious Speiser and companies as well. >> Speiser is a little bit on the crazy side and ambitious and so Speiser is Speiser. And of course he had no doubt, but even him was saying Benoit, Thierry, Hadoop, right. Everyone is saying Hadoop is going to be the revolution. And you guys are betting actually against Hadoop because we told Speiser, Hadoop is a bad system, it's going to fail, but at the time everyone was so bullish about Hadoop, everyone was implementing Hadoop that it didn't look like it was going to fail and we were probably wrong. So there was a lot of skepticism about not leveraging Hadoop and not being an Hadoop. Okay, something being on top of Hadoop. That was number one. There was no cloud warehouse at the time we started. Redshift was not started. It was the pioneer somewhere when Snowflake was founded. So creating a data warehouse in the cloud sounded crazy to people. How am I going to move my data over there? And security and what about security, the cloud is not secure. So that was another... >> So you guys predated that Parexel move by... >> Yes. >> Okay, so that's interesting. And I thought when Redshift... I mean, Amazon announced Redshift, I was sure that Mike Speiser will come and say, guys it's too sad, but they beat you guys and they build something and actually it was the reverse. Mike Speiser was super excited and so it was interesting to me. >> Wow, that's amazing. 'Cause John Furrier and I, we were early with theCUBE. when theCUBE started it was like the beginning of Hadoop. And so we brought theCUBE to, I think it was the second Hadoop World and we was rubbing nickels together at the time. And I was so excited bring compute to storage and it made so much sense. But I remember and I won't say who it was, but an early Hadoop committer told me this is going to fail. And I'm like, what? And he started going age basis crap and all this stuff. And I was sad because I was so excited, but it turned out that you had the same (indistinct). >> Because of complexity. Okay, Hadoop failed for two reasons. One is because they decided that, oh, a lot of this database thing, you don't need transaction, you don't need SQL, you don't necessarily, you don't need to go fast. It'll be batch, normal real time interaction with data, no one needs that. >> Cheap storage. >> So a lot of compromise on the very important technology. And at the same time, extreme complexity and complexity for me was, where I was I knew that it was going to fail big time and we bet Snowflake on the failure of Hadoop indeed. >> And there was no cloud early on in Hadoop. >> And there was no cloud too. >> And that was what killed it. That was like... >> You're right. And the model that Hadoop had for data didn't work on block storage. Block storage is not as efficient as HGFS. So that was also another figure. >> Do you ever sit back and think about... So you think about how much money has poured in to separating compute from storage and cloud databases and you started it all. (interviewer laughing) >> Yeah. No, this is... >> Pretty amazing. >> Yeah. >> Right, so that's good. That means that you're onto a good idea, but a lot of people get confused that again, they think that you're a cloud data warehouse and you're not, I mean, you're much more than that. >> Yeah, I hate that. I have to say, because from day one we were not a cloud data warehouse. As I said, it was all about combining the big data, massive amount of unstructured data, petabytes stored as files. Okay, that's very important, store as files where it's very easy to drop data in the system without... Very low cost to combine with data warehouse, full multi statement transaction when people will tell you today, oh, now we are a data warehouse. They don't have multi statement transaction, right. So we had from day one multi statement transaction really efficient SQL. You could run your dashboard. So combining these two worlds was I think the crazy thing, that's the crazy innovation that Snowflake did initially. >> Yeah. >> And I know it's really easy to build data warehouse somewhere, because if you don't think about big data, petabytes, extremely structured data, you remove a lot of complexity. >> This is why Lisa, when you get excited about technology, but you always have to have a, somebody who really deeply understands technology to stink test it, all right so awesome. Thank you for sharing that story. >> Yeah. >> Fantastic. So over 5,900 customers now. I saw over 500 in the Forbes G2K, over almost 10,000 people here this year. If we think back to 2019, there was about what? Less than 2000 people. >> Yeah. >> What do you think is going to happen next year? >> I don't know. I don't like to think about next year. I mean, I always say, Snowflake is so exciting to me because it is like a TV show, right. Where you wait the next season and we have one season every year. So I'm really excited to know what is going to happen next year. And I don't want to project what I think will happen, but all these movements to the Snowflake being the platform for data application. I want to see what people are going to build on our platform. I mean, that's the excitement. >> Season 11 coming up. >> Yes. Season 11. Yes. >> No binge watching here. Benoit, it's been a pleasure to have you on the program. >> Thank you. >> Congratulations on incredible success, the momentum, the energy is contagious. We love it. (Benoit laughing) >> Thank you so much. >> Thank you. >> Bye bye. >> For Benoit Dageville and Dave Vellante, I'm Lisa Martin. You're watching theCUBE's coverage of Snowflake Summit '22. Dave and I will be right back with a wrap. (upbeat music)

(upbeat music) >> We're back at AWS re:Invent 2021. You're watching theCUBE and we're really excited to have Adam Williams on, he's a senior director of engineering at Iron Mountain. Som Shahapurkar, who's the product engineering of vertical solutions at Iron Mountain. Guys, great to see you. Thanks for coming on. >> Thank you >> Thank you. All right Adam, we know Iron Mountain trucks, tapes, what's new? >> What's new. So we've developed a SaaS platform for digitizing, classifying and bringing out and unlocking the value of our customer's data and putting their data to work. The content services platform that we've developed, goes together with an IDP that we call an intelligent document processing capability to do basic content management, but also to do data extraction and to increase workflow capabilities for our customers. >> Yeah, so I was kind of joking before Iron Mountain, the legacy business of course, everybody's seeing the trucks, but $4 billion company, $13 billion market cap, the stock's been on fire. The pandemic obviously has been a tailwind for you guys, but Som, if you had to describe it to like my mother, what's the sound bite that you'd give. >> Well the sound bite, as everyone knows data is gold today, right? And we are sitting figuratively and literally on a mountain of data. And now we have the technology to take that data partner with AWS, the heavy machinery to convert that into value, into value that people can use to complete the human story of healthcare, of mortgage, finance. A lot of this sits in systems, but it also sits in paper. And we are bridging that paper to digital divide, the physical and digital divide to create one story. >> This has been a journey for you guys. I mean, I recall that when you kind of laid this vision out a number of years ago, I think he made some acquisitions. And so maybe take us through that amazing transformation that Iron Mountain has made, but help the audience understand that. >> Transformations really been going from the physical records management that we've built our business around to evolving with our customers, to be able to work with all of the digital documents and not just be a transportation and records management storage company, but to actually work with them, to put their data to work, allowing them to be able to digitize a lot of their content, but also to bring in already digitized content and rich media. >> One of the problems that always existed, especially if you go back to back of my brain, 2006, the federal rules of civil procedure, which said that emails could now be evidence in a case and everyone like, oh, I don't like, how do I find email. So one of the real problems was classifying the information for retention policies. The lawyers wanted to throw everything out after whatever six or seven years, the business people wanted to keep everything forever. Neither of those strategies work, so classification and you couldn't do it manually. So have you guys solved that problem? How do you solve that problem? Does the machine intelligence help? It used to be, I'll use support vector machines or math or probabilistic, latent, semantic, indexing, all kinds of funky stuff. And now we enter this cloud world, have you guys been able to solve that problem and how? >> So our customers already have 20 plus years of retention rules and guidelines that are built within our systems. And we've helped them define those over the years. So we're able to take those records, retention schedules that they have, and then apply them to the documents. But instead of doing that manually, we're able to do that using our classification capabilities with AI ML and that Som's expertise. >> Awesome, so lay it on me. How do you guys do that? It's a lot of math. >> Yeah, so it can get complicated real fast, but at a simple level, what's changed really from support beta machines of 2006 to today is the scale at which we can do it, right? The scale at which we are bringing those technologies. Plus the latest technologies of deep learning, your conventional neural networks going from a bag of characters and words to really the way humans look at it. You look at a document and you know this is an invoice or this is a prescription, you don't have to even know to read to know that, machines are now capable of having that vision, the computer vision to say prescription, invoice. So we train those models and have them do it at industrial scale. >> Yeah, because humans are actually pretty bad at classifying at scale. >> At scale like their back. >> You remember, we used to try to do, oh, it was just tag it, oh, what a nightmare. And then when something changes and so now machines and the cloud and Jane said, how about, I mean, I presume highly regulated industries are the target, but maybe you could talk about the industry solutions a little bit. >> Right. Regulated industries are a challenge, right. Especially when you talk about black box methodologies like AI, where we don't know, okay, why does it classify this as this and that is that? But that's where I think a combined approach of what we are trying to say, composite AI. So the human knowledge, plus AI knowledge combined together to say, okay, we know about these regulations and hey, AI, be cognizant of this regulations while you do our stuff, don't go blindly. So we keep the AI in the guardrails and guided to be within those lines. >> And other part of that is we know our customers really well. We spent a lot of time with them. And so now we're able to take a lot of the challenges they have and go meet those needs with the document classification. But we also go beyond that, allowing them to implement their own workflows within the system, allowing them to be able to define their own capabilities and to be able to take those records into the future and to use our content management system as a true content services platform. >> Okay, take me through the before and the after. So the workflow used to be, I'd ring you up, or maybe you come in and every week grab a box of records, put them in the truck and then stick them in the Iron Mountain. And that was the workflow. And you wanted them back, you'd go get it back and it take awhile. So you've digitized that whole and when you say I'm inferring that the customer can define their own workflow because it's now software defined, right. So that's what you guys have engineered. Some serious engineering work. So what's the tech behind that. Can you paint a picture? >> So the tech behind it is we've run all of our cloud systems and Kubernetes. So using Kubernetes, we can scale really, really large. All of our capabilities are obviously cloud-based, which allows us to be able to scale rapidly. With that we run elastic search is our search engine and MongoDB is our no SQL database. And that allows us to be able to run millions of documents per minute through our system. We have customers that we're doing eight million documents a day for the reel over the process. And they're able to do that with a known level of accuracy. And they can go look at the documents that have had any exceptions. And we can go back to what Som was talking about to go through and retrain models and relabel documents so that we can catch that extra percentage and get it as close to 100% accuracy as we would like, or they would like. >> So what happens? So take me through the customer experience. What is that like? I mean, do they still... we you know the joke, the paperless bathroom will occur before the paperless office, right? So there's still paper in the office, but so what's the workload? I presume a lot of this is digitized at the office, but there's still paper, so help us understand that. >> Customers can take a couple of different paths. One is that we already have the physical documents that they'd like us to scan. We call that backfile scanning. So we already have the documents, they're in a box they're in a record center. We can move them between different records centers and get them imaged in our high volume scanning operation centers. From there-- >> Sorry to interrupt. And at that point, you're auto classifying, right? It's not already classified, I mean, it kind of is manually, but you're going to reclassify it on creation. >> Correct. >> Is that electronic document? >> For some of our customers, we have base metadata that gives us some clues as to what documents may be. But for other documents, we're able to train the models to know if their invoices or if their contracts commonly formatted documents, but customers can also bring in their already digitized content. They can bring in basic PDFs or Word documents or Google Docs for instance, but they can also bring in rich media, such as video and audio. And from there, we also do a speech to text for video and audio, in addition to just basic OCR for documents. >> Public sector, financial services, health care, insurance, I got to imagine that those have got to be the sweet spots. >> Another sweet spot for us is the federal space in public sector. We achieved FedRAMP, which is a major certification to be able to work with, with the federal government. >> Now, how would he work with AWS? What's your relationship with them? How do you use the cloud? Maybe you could describe that a little bit. >> Well, yeah, at multiple levels, right? So of course we use their cloud infrastructure to run our computing because with the AI and machine learning, you need a lot of computing power, right. And AWS is the one who can reliably provide it, space to store the digital data, computing the processes, extract all the information, train our models, and then process these, like he's talking about, we are talking about eight, 12, 16 million documents a day. So now you need seconds and sub second processing times, right? So at different levels, at the company infrastructure level, also the AI and machine learning algorithms levels, AWS has great, like Tesseract is one the ones that everyone knows but there is others purpose-built model APIs that we utilize. And then we'll put our secret sauce on top of that to build that pathway up and make it really compelling. >> And the secret sauce is obviously there's a workflow and the flexibility of the workflow, there's the classification and the machine learning and intelligence and all the engineering that makes the cloud work you manage. What else is there? >> Knowledge graphs, like he was saying, right, the domain. So mortgage is not that a document that looks very similar in mortgage versus a bank stated mortgage and bank statement in healthcare have different meanings. You're looking at different things. So you have something called a knowledge graph that maintains the knowledge of a person working in that field. And then we have those created for different fields and within those fields, different applications and use cases. So that's unique and that's powerful. >> That provides the ability to prior to hierarchy for our customers, so they can trace a document back to the original box that was given to us some many years ago. >> You got that providence and that lineage, I know you're not go to market guys, but conceptually, how do you price? Is it that, it's SaaS? Is it licensed? Is it term? Is it is a consumption based, based on how much I ingest? >> We have varying different pricing models. So we first off we're in six major markets from EU, Latin America, North America and others that we serve. So within those markets, we offer different capabilities. We have an essentials offering on AWS that we've launched in the last two weeks that allows you to be able to bring in base content. And that has a per object pricing. And then from there, we go into our standard edition that has ability to bring in additional workflows and have some custom pricing. And then we have what we call the enterprise. And for enterprise, we look at the customer's problem. We look at custom AI and ML models who might be developing and the solution that we're having to build for them and we provide a custom price and capability for what they need. >> And then the nativists this week announced a new glacier tier. So you guys are all over that. That's where you use it, right? The cheapest and the deepest, right? >> Yeah, one of the major things that AWS provides us as well is the compliance capabilities for our customers. So our customers really require us to have highly secure, highly trusted environments in the cloud. And then the ability to do that with data sovereignty is really important. And so we're able to meet that with AWS as well. >> What do you do in situations where AWS might not have a region? Do you have to find your own data center to do that stuff or? >> Well, so data privacy laws can be really complex. When you work with the customer, we can often find that the nearest data center in their region works, but we also do, we've explored the ability to run cloud capabilities within data centers, within the region that allows us to be able to bridge that. We also do have offerings where we can run on-premise, but obviously our focus here is on the cloud. >> Awesome business. Does Iron Mountain have any competitors? I mean like... >> Yeah. >> You don't have to name them, but I mean, this is awesome business. You've been around for a long time. >> And we found that we have new competitors now that we're in a new business. >> They are trying to disrupt and okay. So you guys are transforming as an incumbent. You're the incumbent disruptor. >> Yes. >> Yes, it's self disruption to some extent, right. Saying, hey, let's broaden our horizon perspective offering value. But I think the key thing is, I want to focus more on the competitive advantage rather than the competitors is that we have the end to end flow, right? From the high volume scanning operations, trucking, the physical world, then up and about into the digital world, right? So you extract it, it's not just PDFs. And then you go into database, machine learnings, unstructured to structured extraction. And then about that value added models. It's not just about classification. Well, now that you have classified and you have all this documents and you have all this data, what can you glean from it? What can you learn about your customers, the customers, customers, and provide them better services. So we are adding value all throughout this chain. And think we are the only ones that can do that full stack. >> That's the real competitive advantage. Guys, really super exciting. Congratulations on getting there. I know it's been a lot of hard work and engineering and way to go. >> Thank you. >> It's fun. >> Dave: It's good, suppose to have you back. >> Thanks. >> All right and thank you for watching. This is Dave Vellante for theCUBE, the leader in live tech coverage. (upbeat music)

from San Mateo its the cube covering scaler innovation day brought to you by scaler Livan welcome to the special innovation day with the cube here in San Mateo California heart of Silicon Valley John for the cube our next guest as Steve Newman the co-founder scaler congratulations thanks for having us you guys got a great company here Thanks yeah go ahead glad to have you here so tell the story what's the backstory you guys found it interesting pedigree of founders all tech entrepreneurs tech tech savvy tech athletes as we say tell the backstory how'd it all start and had it all come together so I also traced the story back to I was part of the team that built the original Google Docs and a lot of the early people here at scaler either were part of that Google Docs team or you know they're people we met while we were at Google and really scaler is an outgrowth of the it's a solution to problems we were having trying to run that system at Google you know Google Docs of course became part of a whole ecosystem with Google Drive and Google sheets and there's that you know all these applications working together it's a very complicated system and keeping that humming behind the scenes became a very complicated problem well congratulate ago Google Docs is used by a lot of people so been great success scale is different though you guys are taking a different approach than the competition what's unique about it can you share kind of like the history of where it's going and where it came from and where it's going yeah so you know maybe it'd be helpful like just to kind of set the context a little bit to the blackboard yeah so you know I you know I talked about it's kind of probably put a little flesh on what I was saying about you know there's a very complicated system that we're trying to run in the whole Google Drive ecosystem too there are all these trends in the industry nowadays you know the move to the cloud and micro services and kubernetes and serverless and can use deployment is all everything like these are all great innovations makes you know people are building more complex applications they're evolving faster but it's making things a lot more complicated and to make that concrete imagine that you're running an e-commerce site back in the calm web 1.0 era so you're gonna have a web server maybe a patchy you've got a MySQL database behind that with your inventory and your shopping carts you may be an email gateway and some kind of payment gateway and that's about it that's your that's your system each one of these pieces involved you know going to Fry's buying a computer driving it over the data center slotting it into a rack you know a lot of sweat went into every one of those boxes but there's only about four boxes it's your whole system if you wanted to go faster you threw more hardware at it more ram exactly and like and you know not literally through but literally carried you literally brought in more hardware and so you know took a lot of work just to do the you know that simple system fast forward a couple of decades if you're running uh running an e-commerce site today well you know you're certainly not seeing the inside of a data center you know stripe will run the payments for you you know somebody's on will run the database server and say you know like this is much much you know you know one guy can get this going in an afternoon literally but nobody's running this today this is not a competitive operation today if you're an e-commerce today you also have personalization and advertising based on the surf service history or purchase history and you know there's a separate flow for gifts and you know then printing the you know interfacing to your delivery service and and you know you've got 150 blocks on this diagram and maybe your engineering team doesn't have to be so much larger because each one of those box is so much easier to run but it's still a complicated system and trying to actually understand what's working what's not working why isn't it working and and tracking that down and fixing it this is the challenge day and this and this is where we come in and that's the main focus for today is that you can figure it out but the complexity of the moving parts is the problem exactly so you know and so you see oh you know 10% of the time that somebody comes in to open their shopping cart it fails well you know the problem pops out here but the the root cause turns out to be a problem with your database system back here and and figuring that out you know that's that's the challenge okay so with cloud technology economics has changed how is cloud changing the game so it's interesting you know changes changes the game for our customers and it changes the game for us so for a customer you know kind of we touched on this a little bit like things are a lot easier people run stuff for you you know you're not running your own hardware you're not you know you're often you're not even running your own software you're just consuming a service it's a lot easier to scale up and down so you can do much more ambitious things and you can move a lot faster but you have these complexity problems for us what it presents an an economy of scale opportunity so to you know we step in to help you on the telemetry side what's happening in my system why is it happening when did it start happening what's causing it to happen that all takes a lot of data log data other kinds of data so every one of those components is generating data and by the way for our customers know that they're running a hundred and 50 services instead of four they are generating a lot more data and so traditionally if you're trying to manage that yourself running your own log management cluster or whatever solution you know it's a real challenge to you as you scale up as your system gets more complex you've got so much data to manage we've taken an approach where we're able to service all of our customers out of a single centralized cluster meaning we get an economy of scale each one of our customers gets to work with a basically log management engine that's to scale to our scale rather than the individual customers scale so the older versions of log management had the same kind of complexity challenges you just drew a lot ecommerce as the data types increase so does their complexity is that so the complexity increases and but you also get into just a data scale problem you know suddenly you're generating terabytes of data but you don't you know the you only want to devote a certain budget to the computing resources that are gonna process that data because we can share our processing across all of our customers we we fundamentally changed economics it's a little bit like when you go and run a search and Google thousands literally thousands of servers in that tenth of a second that Google is processing the query 3,000 servers on the Google site may have been involved those aren't your 3,000 servers you know you're sharing those with you know 50 million other people in your data center region but but for a millisecond there those 3,000 servers are all for you and that's that's a big part of how Google is able to give such amazing results so quickly but in still economically yeah economically for them and that's basically on a smaller scale that's what we're doing is you know taking the same hardware and making it all of it available to all of the customers people talk about metrics as the solution to scaling problems is that correct so this is a really interesting question so you know metrics are great you know basically the you know if you look up the definition of a metric it's basically just a measurement on number and you know and it's a great way to boil down you know so I've had 83 million people visit my website today and they did 163 million things in this add mirror and that's you can't make sense of that you can boil it down to you know this is the amount of traffic on the site this was the error rate this was the average response time so these you know these are great it's a great summarization to give you an overall flavor of what's going on the challenge with metrics is that they tend to measure they can be a great way to measure your problems your symptoms sites up it's down it's fast its slow when you want to get to then to the cause of that problem all right exactly why is the site now and I know something's wrong with the database but what's the error message and what you know what's the exact detail here and a metric isn't going to give that to you and in particular when people talk about metrics they tend to have in mind a specific approach to metrics where this flood of events and data very early is distilled down let's count the number of requests measure the average time and then throw away the data and keep the metric that's efficient you know throwing away data means you don't have to pay to manage the data and it gives you this summary but then as soon as you want to drill down you don't have any more data so if you want to look at a different metric one that you didn't set up in advance you can't do it and if you need to go into the the details you can't do an interesting story about that you know when you were at Google you mentioned you the problem statements came from Google but one of things I love about Google is they really kind of nailed the sre model and they clearly decoupled roles you know developers and site reliability engineers who are essentially one-to-many relationship with all the massive hardware and that's a nice operating model it's had a lot of efficiencies was tied together but you guys are kind of saying in a way that does developers use the cloud they become their own sres in a way because this cloud can give them that kind of Google like scale and in smaller ways not like Google size but but that's similar dynamic where there's a lot of compute and a lot of things happening on behalf of the application or the engineers developer as developers become the operator through their role what challenges do they have and what do you see that happening because that's interesting trim because as applications become larger cloud can service them at scale they then become their own sres what yeah well how does that roll out most how do you see that yes I mean and so this is something we see happening at more and more of our customers and one of the implications of that is you have all these people these developers who are now responsible for operations but but they're not special you know they're not that specialist SRE team they're specialists in developing code not in operations they're you know they they minor in operations and and they don't think of it as their real job you know that's the distraction something goes wrong all right they're they're called upon to help fix it they want to get it done as quickly as possible so they can get back to their real job so they're not gonna make the same mental investment in becoming an expert at operations and an expert at the operations tools and the telemetry tools you know they're not gonna be a log management expert on metrics expert um and so they need they need tools that have a gentle learning Kurt have a gentle learning curve and are gonna make it easy for them to get Ian's not really know what they're doing on this side of things but find an answer solve the problem and get back out and that's kind of a concept you guys have of speed to truth exactly so and we mean a couple of things by that sort of most literally we our tool is it's a high performance solution you you hand us your terabytes of log data you ask some question you know what's the trend on this error in this service over the last day and we you know we give you a quick answer Big Data scan through a give you a quick answer but really it's you know that's just part of the overall chain of events which goes from the you know the developer with a problem until they have a solution so they they have to figure out even how to approach the problem what question to ask us you know they have to pose the query and in our interface and so we've done a lot of work to to simplify that learning curve where instead of a complicated query language you can click a button get a graph and then start breaking down that just visually break that down which okay here's the error rate but how does that break down by server or user or whatever dimension and be able to drill down and explore in a you know very kind of straightforward way how would you describe the culture at scaler I mean you guys been around for a while you still growing fast growing startup you haven't done the B round yet got any you guys self-funded it got customers early they pushed you again now 300 plus customers what's the culture like here so you know it's been this has been a fun company to build in part because you know we're into you know the the heart of this company is the engineering team our customers our engineers so you know we're kind of the kind of the same group and that keeps the you know it kind of keeps the inside in the outside very close together and I think that's been a part of the culture we've built is you know we all know why we're building this what it's for you know we use scalar extensively internally but you but even you know even if we weren't we're it's the kind of thing we've used in the past and we're gonna use in the future and so you know I think people are really excited here because you know we understand why and you have an opinion of the future on how it should roll out what's the big problem statement you guys are solving as a company what's it how would you boil that down if asked so by a customer and engineer out there what real problem are you solving that's core problem big problem that's gonna be helping me you know at the end of the day it's giving people the confidence to keep you know building these kind of complicated systems and move quickly because because and this is the business pressure everyone is under you know whatever business you're in it has a digital element and your competitors are in the same you know doing the same thing and they are building these sophisticated systems and they're adding functionality and they're moving quickly you need to be able to do the same thing but it's easy then to get tangled up in this complexity so at the end of the day you know we're giving people the ability to understand those systems and and and the functionality and the software's getting stronger and stronger more complicated with service meshes and micro services as applications start to have these the ability to stand up and tear down services on the fly that's so annoying and they'll even wield more data exact you get more data it gets more complicated actually if you don't mind there's a little story I'd like to tell so hold on just will I clear this out this is going back back to Google and again you know kind of part of the inspiration of you know how he came to build scalar and this doesn't be a story of frustration of you know probably get ourselves into that operation and motivation yep so we were we were working on this project it was building a file system that could tie together Google Docs Google sheets Google Drive Google photos and the black diagram looks kind of like the thing I just erased but there was one particular problem we had that took us months and literally months and months and months to track down you know you'd like to solve a problem in a few minutes or a few hours but this one took months and it had to do with the the indexing system so you have all these files in Google Drive you wanna be able to search and so we had modeled out how we were gonna build this or this search engine you'd think you know Google searches a solve problem but actually so Google web search is four things the whole world can see there's also like Gmail search which is four things that only one person can see so it's lots of separate little indexes those are both solve problems at Google Google Drive is for things a few people can see you share it with your coworker or your whoever and it's actually a very different problem and but we looked at the statistics and we found that the average document our average file was shared with about 1.1 people in other words things were mostly private or maybe you share with one or two people so we said we're just gonna make if something's shared to three people we're just gonna make three copies of it and then now we have just the Gmail problem each copy is for one person and we did the math on how how much work is this going to be to build these indexes and in round numbers we were looking at something like at the time this would be so much larger now but at the time we had maybe one billion documents and files in the system each one was shared to about 1.1 people maybe it was a thousand words long on average and maybe it would change be edited once per day on average so we had about a trillion word updates per day if you multiply all that together and so we allocate it we put in a request and purchase machines to handle that much traffic and we started bringing up the system and immediately collapsed it was completely overloaded and we checked our numbers and we check them again yeah 1.1 about a billion whatever and but then work into the system with just way beyond them and we looked at our metrics so you know measuring the number documents measuring each of these things all the metrics looked right to make a month's long story short these metrics and averages were hiding some funny business there turned out there was this type of use case read of occasional documents that were shared to thousands of people and one of there was a specific example it was the signup sheet for the Google company picnic this is a spreadsheet it was shared to about 5,000 people so it wasn't the whole company but you know a big chunk of Mountain View which meant it was I don't know let's say 20 thousand words long because it had you know the name and a couple other things for each person this is one document but shared to 5,000 people and you know during the period people were signing up maybe it was changing a couple thousand times per day so you multiply out just this document and you get 200 billion word updates for that one document in a day where we're estimating a trillion for the whole earth and so there was something like a hundred documents in this kid Google was hamstringing your own thing we were hamstrung our own thing there were about a hundred examples like this so now we're up to 20 trillion and like that was the whole problem these hundred files and we would have never found that until we got way down into the details of the the logs which in this two months just took month so because we didn't have the tools because we didn't have scaler yeah and I think this is the kind of anomaly you might see with Web Services evolving with micro services which someone has an API interface with some other SAS as apps start to rely on each other this is a new dynamic we're seeing as SLA s are also tied together so the question is whose fault is it exactly you have to whose fault is it and also things get so much more varied now you know again web 1.0 e-commerce you buy a thing you buy a thing that's all the same now you're building a social media site or whatever you've got 8 followers you've got 8 million followers this person has three movies rented on Netflix this person has three thousand movies everything's different and so then you get these funny things hiding yeah you're flying blind if you don't get all the data exposed it's like it's like you know blind person trying to read Braille as we heard earlier see if thanks so much for sharing the insight great story I'm John furry you're here for the q4 innovation day at scalers headquarters thanks for watching

>> Announcer: Live, from Anaheim, California, it's theCUBE, covering Nutanix .NEXT 2019, brought to you by Nutanix. >> Welcome back, everyone to theCUBE's live coverage of Nutanix .NEXT here in Anaheim, California. I'm your host, Rebecca Knight, along with my co-host, John Furrier. We are so excited to welcome back to the program, Dheeraj Pandey, the co-founder/CEO and Chairman of Nutanix. Thank you so much for coming back on theCUBE. >> Thank you for pronouncing my name diligently. >> You are welcome. >> John: Gotta work on that. >> So, Dheeraj, it was a poignant moment in the keynote when you got up there with many of the people who were sort of employee number one, two, and three, four at Nutanix. They are the builders, the dreamers, the visionaries, the innovators, the disruptors of this company, a company that you started. So I'd love you to just start out by reflecting a little bit on your journey and sort of how Nutanix has evolved. >> Yeah, I mean it's a poignant 10 years, you know. The moment itself is poignant and it brought a lot of nostalgia, you know, for just looking at the early folks and how we had to huddle together in the smallest of technical blips that you'd find in our thesis, because our thesis was very bold. It was, like, hey, we can put a lot of hardware into your software. It's, like, the way Apple would say, we'll get rid of the camera and make it into an app. Like, what? There's no need for a camera anymore. So that's what we had to do with data center infrastructure. So, those moments are memorable, they're etched in history and my memory, and every time you get a tough moment now, we actually invoke a lot of those tough moments from the past and say, look, the more things change, the more they remain the same. >> The beautiful thing about theCUBE, is our 10th year as well, we've been following your journey as well. We actually have soundbites of the early interviews, and one of the things I was always impressed with you guys was you stayed the course, you didn't waver on what was fashionable at the time. HCI was an early category. You were misunderstood at the beginning and then the numbers started to show and you guys built a great business. But now, you're 10 years old, you're public. All the numbers are out there. You gotta go the next level. This is your challenge with the team. What's the focus? What's the strategy? What's the marching orders for the team now, as you go past 10 years old? You got competitive pressure. There's marketplace. The numbers are there. It's a big piece of the pie there. >> Yeah. You know, I go back to everything I just said in my last answer as well. The more things change, the more they remain the same. The friction hasn't changed. Five years ago we were a much smaller brand. We didn't have a customer base. We didn't have money in the bank and we still had to keep raising money to fund ourselves. Today, we are running this business, spending, you know, a billion dollars every year now. But it's a free cash flow neutral business, and we have told the Street that we gonna keep running it like that, but just go back to the basics. The basics of this company are what made it come to here. The same basics will need to take it from here to the next 10 years. 10 years is the new zero. I mean, I said, look, we've reset the clock and it's a very metaphorical thing to say, but it's the new zero for us, you know. So going back to the basics are the three Ds I talked about. Data, we are greater data. And we continue to be amazing at data. Reliable, highly available, high performance data management. A greater design. You know, just making things simple, and we're really really really good at delivery and when we suck at it, we go and improve and are very resilient in delivering things, you know, so whenever some things falter within our customer success, customer service, the way we delivering things with your software and subscription, I think nobody can touch us in these three Ds. >> As you guys have proven a great loyalty, customer basis, very loyal on the product. As you have to go multi-cloud, as the Enterprise gets modernized, this is a big part of your current business. What are some of the things that you're looking at, in terms of these new products? Because you don't want to open the door up for either a competitor or a misfire on you guys. You gotta continue to provide product leadership. >> Well, the most important thing is honesty and vulnerability. The fact that these things are not awesome big products yet, but they are awesome nonetheless. So how do you really have the small wins? You know, I go back in time to, Look, it took 10 years for Amazon Prime to become Primetime. It took six years for YouTube to even start to figure out who YouTube is really gonna be, and you know, Google bought Writely, which was the company that became Google Docs. Five years, they didn't know what they were doing with those things, so what's really important for the new products is this long-term greed. You know, the fact that you really have this 10 year view of a multi-product portfolio, but the most important thing is how they gell well together, how they really integrate well together, because if we don't integrate these products, and we just throw it out as things, as opposed to an experience. Customers are, like, I can buy things from Best of Breed. So how do you really make these multi-product look like an experience is where the real Nutanix design value is actually shown. >> One of the things that you guys have a good customer reaction to is the simplicity and how you can integrate well and reduce all these manual tasks, which is, people talk about automation and everything, but you guys have customers saying, "I went from 24 racks to six. "I now run everything with the push of a button. "Not there yet with the one-click but pretty close." That sounds like the multi-cloud game right now, where it is kinda hodge-podge. No one's actually figured out how to bring it all together and orchestrate it. >> That's the money statement, John. That's where the money is. Complexities where we go in and really figure out how to really save money for our customers, make money for our partners and make money for ourselves. >> And the partner-side, HPE, a big announcement that you guys have been part of. They're gonna be coming on today. How's that going? Give us the update on the HPE. >> You know, the energy levels are high, but there's a bell curve of people, you know. You can't have everybody really be an innovator, an early adopter. We're looking for innovators and early adopters. Some great discussions happening with HP account managers. They're our account managers of very large accounts, and the word-of-mouth has to basically play its powerful game actually. >> I wanna ask you about innovation. Earlier, on a CUBE conversation, you talked with our own John Furrier, and you said, we disrupt ourselves, but you also just talked about these products being these sort of long-term play and really thinking about what the, more of a holistic view of what the customers need. I wanna hear about the Nutanix innovation process and sort of how you have kept that culture of a tech start-up now that you are a company with a market cap in the multiple billions. >> You know, as I said before, we are like a billion dollar start-up, you know. And it's not easy, because everybody wants you to grow up, like, behave and grow up, and I saw one of my slides in there taking real potshots of the sand and we haven't changed much, you know. So in many ways, we're reminding everybody that it's still Day Zero and Day One. Is the great cultural gravitas that we need to keep, retained in the business, actually, in the company? You know, having the kind of humor that we had, and you know, keeping it personal and personable with everybody, as opposed to, you know, stiff upper lip, and suits and mahogany tables and corner offices. Those are things that are the antithesis of what Nutanix is. And just keeping it humble, you know. Like, the fact that even though we have layers of management in the middle, how do you go six levels deep and really have a conversation as technical as you wanted it to be and as business incisively as we want it to be? And you know, there's a lot of things you can do by going six levels deep that otherwise were not possible if you just said, look, I just talked to my next level action team, and to us, that's the engine of innovation. >> And how is your leadership changed? >> I have a new customer called Wall Street. >> That's true. >> 'Cause you know, they buy my product. It just happens to be a retail product that you folks can buy, too. It's called NTNX, the ticker. So I have Main Street customers and then I have Wall Street as a customer, and I need to figure out where to really keep them balanced, because I sell products to both of them, and it's a journey. You know, it's never easy, because there's a customer that actually wants instant success. There's another customer that says we are with you for the long haul, and what I need to find in this Wall Street customer is the ones who are actually for the long haul. My leadership, actually, is about balancing the two together. >> So let's talk about the Wall Street thing for a second, because I think that's interesting. You've always said to me, you're gonna play the long game and you do. We've kinda proved that, but Wall Street, they're very short sighted right? So the earnings come out, you gotta deal with the shot clock, as a public company. As you go to Wall Street, how are they looking at the long game? Because there's major examples. Microsoft stock's at an all-time high. They were in the 20s a few years ago. Cloud obviously is validated, so you got a cloud vision, this cloud marketplace. You're in the core enterprise, which has been revitalized with private cloud. Again, proves your thesis originally. So you're in good position and you got the cloud game right there. What are they missing? What's Wall Street missing? >> I think the biggest thing is that in any transformation is actually messy. Look at all the transformations in the last 20 years. The good thing is that those that took the tough call of transforming themselves, they really have done well, you know. And this is not just Microsoft alone, but Adobe, where I sit on the board. There is Autodesk and there is Parametric PTC and Cadence and many many other companies that have gone through this transition of getting out of the box to being software and subscription actually, and that's the journey that we said we couldn't punt and postpone 'cause we wanna be a hybrid cloud company. How can we not have subscription on prem? If subscription is gonna be the off prem, it has to have on prem subscription as well. And I think it requires communication, constant communication, watch, don't be stupid, with Wall Street as well. >> Well, Wall Street likes those valuations. If you look at the SaaS companies, or subscription-based companies, their valuations are really on a multiple, much higher than, >> I mean, look, valuation, to me, is not an end in itself. If you do it right by Main Street, I think this Wall Street thing will take care of itself. >> Awesome. On the long game with your innovation, I gotta ask you about how you're gonna look at the partnerships and integrating in, because the competitor out there in the middle of the room there is VMware and Dell Technologies. They want to go end-to-end and they want to own everything end-to-end. You guys are taking a different approach. Could you share your competitive strategy in terms of how you guys are different than that, because you're partnering? You're competing in a different way. >> Yeah, as we go into becoming a bigger company and yet, having a real child-like brain, I think it's important, really, that we are in this cooperative world and every competitor is also a company we cooperate with. Look, I mean, we run on top of VMware and more than half our customers still use VMware underneath us. We are an app on their platform. So we are a platform company. We are also an app company and our platform should run all apps and our apps should run on all platforms and that's the way we look at it. That's the reason why Microsoft is relevant again, 'cause they're still looking at, rather than a single stack strategy, how do you really look at yourselves as living two lives actually, you know? And to compete, you just have to go back to the three Ds I talked about. If you just keep doing a really good job of data, disrupting the biggest hardware players out there in data, and be really really good with design and elegance and friction-less delivery, I think we'll be in good shape. >> One of the compliments that the analysts on theCUBE always pay to you, Dheeraj, is that you have a really good sense of the wave. You really know which way the technological and economic winds are blowing. I wanna know, what do you read? Who do you talk to? What signals are you paying attention to? Or is it just this innate sense you have that the rest of us can't hope to ever achieve? >> Well, thank for that compliment, first of all. I'm honored. But I just have this simple mantra which is, the more things change, the more they remain the same. So I bring a lot of things from my consumer life because I read a lot about consumer life and I have a little bit of an artist in me and even though I am supposed to be a geek, I was telling somebody I was trying to recruit the other day that, look, I'm really, at heart, an artist, more so than an engineer, and I think a lot of what you see in this conference and this company and the product portfolio, it's really the empathy for the other side. You know, that really brings out a lot of the innovation, and obviously, I don't innovate alone, but the people that are with us in this company, I just try to tell them about the empathy that I invoke for everybody else and I read a lot of history, I'm a big history buff, and not just the last 30 years of IT, which I invoke a lot, but I'm deep into, like, the history of humans, you know. Like, last two weeks, I spent a lot of time reading about Neanderthals and the hybrid Neanderthals with humans, modern humans, and there's another ones that they found in these caves of Denisova. They call Denisovans, you know. So I read a lot of history and that gives me a lot of perspective and a lot of courage and I bring a lot of those things into this new life, that's again, as I said, it's the same as the old one, with some new color. >> You're an entrepreneur. That's what entrepreneurship is all about. What entrepreneurial thing are you working on right now? 'Cause I've known, You've gotta have your hands in some new things. What's the new entrepreneurial thinking or project that you're taking on? >> Well, the one that is very interesting one for operating a business is Capital Allocation, and it's a difficult one because you have to, basically, be somebody who really balances content and delivery, you know, and content is products and delivery is go to market, and when you go to market, it's marketing and sales. So as a company, we were tested in the last nine months to really understand Capital Allocation. I'm a big fan of the book, The Outsiders. I just read this probably a year ago, and you could see that there was some themes in The Outsiders about running the business on free cash flow, which is nothing new. It's not like Amazon invented it. They've been doing it for those 40, 50 years. Second one is Decentralized Decision Making. The third one is a really good capital allocation. So as an entrepreneur, I'm learning to actually understand what it means to decentralize decision making, and do a really good job of capital allocation, and finally, go and tell the Street about why free cash is the way to run a business as opposed to profitability and a gap way, because a lot of our dollars are sitting in the balance sheet, and they aren't in the P&L. So I think really running the business where growth matters, which is about free cash flow, about making sure that we can really create more CEOs in the company, independent decision making, and finally, this idea that you want to run this business as if it was a bunch of businesses, actually. >> Great. >> Awesome. >> One of the things you keep talking about in this interview is balance. You're balancing the needs of Main Street and Wall Street, the needs of your cloud customers, the needs of your employees, while also growing this business. How do you balance at all? As the CEO of this fast-growing company? You said you're an artist. And you read a lot of history. >> Honestly, I'm not a very balanced person. If you ask me, like, work and life, family and work, is because of my wife that I find a balance there. >> So you owe it all to her? >> Yeah, I think you can say that again, and the same thing is true for, like, one of my team members, our COO, David Sangster. He says, "Look, our health, family, and work, "in that order," and honestly, mine is in the reverse right now. So I need to really go and, These kind of conversations remind myself that it's important to actually have some balance. >> Great, well, Dheeraj, always a pleasure having you on theCUBE. >> Pleasure. >> I'm Rebecca Knight, for John Furrier. We'll have so much more from Nutanix next coming up on theCUBE just after this. (techno music)

>> Announcer: Live from San Francisco, it's theCUBE. Covering Google Cloud Next '19. Brought to you by Google Cloud and its ecosystem partners. >> Hey, welcome back everyone, and we're here at theCUBE coverage in San Francisco for Google Next 2019, I'm John Furrier, Dave Vellante, our next guest is Menaka Shroff global marketing head for emerging business at Google. Welcome to theCUBE, thanks for joining us. >> Thank you. Thank you for having me. >> So define emerging business, what is it within the Google Cloud? Just take a minute to explain what the business is. >> Yeah. Emerging business team is a group of marketers basically focused on products that help build a better Google story, so products like Chrome Browser, Chromebooks, Drive and especially Cloud Identity. All of these form the team of portfolio products that my team manages. >> And so they go to market, is it product development, both, or just? >> It's predominately marketing and go to market, yeah. >> What are some of the things that you're talking about here at the event? What's some news that you have, you guys got some news? >> Yeah, so one of the patterns we're seeing is this trend of cloud workers, where these are employees that spend almost four hours a day using SaaS applications using the browser as you just mentioned, that you do as well. And we're seeing-- >> Eight hours a day, 15 hours a day, yeah! >> Yes, excellent. And so, we're seeing this pattern actually, not only with digital natives but also with frontline, you know, back of the office front of the office where they're sort of skipping the traditional PC era and moving straight to a clouds based model. And so today we're actually announcing our Chrome Browser Cloud Management. So it's one central place to manage your browser deployments across, you know, a segmented workforce that's using Windows or Mac or Linux, and Chromebooks. and what you can do is have them obviously manage the Chrome Browser extensions and all of the deployment, but also have this IT collaborating and delegation within the same console. So of course if you're using G Suite, it's all in the same console, it's very easily available. >> And so this kind of brings back to conscious, we've been hearing the themes here, besides this is customer focused, it is end to end developer. So, life cycle from coding to deploying and running. So you run it on a Chromebook, or a Chrome Browser, you can have software at the endpoint for security, and integration, right? >> Exactly. So, what's great about being here is you see that full stack approach in how we want to make it available for our customers starting all the way from infrastructure to end user computing apps that people are using, all with that security layer and mindset. Obviously Chromebooks are known to be cloud based devices, historically popular with students, as you had just mentioned, as well. But we're seeing really good trends happening even with personal computing and in enterprise, because of the security model that runs through how cloud is architected, especially at Google. >> What're some of the conversations you're having here at the show, with customers and partners? What's the main driver? >> Yeah, it's really phenomenal because Chromebooks are actually 100% partner driven so we're already very partner-centric from that point of view, but, some of the customer conversations we're hearing, I'll mention three customers that I just talked to. SoulCycle, they have 94 locations with 500 endpoints deployed, and they're using this as their retail experience. That customer UX mindset with their Chromebooks, again, they're very cloud native. We have Starbucks that is using the Chrome Browser management capabilities across all of their stores, again thinking about extension management, but centralizing it all in one panel for all their locations. And then, very interesting, we have one medical hospital. They're using Chromebooks for their paramedics. Obviously we want paramedics to have the best technology available while they're doing their important job, saving lives. But they're doing this in a way where we want to enable them to do the right outcome which is, good patient experience. These are all things we're seeing in the variety of SMBs to IT, to, small businesses in variety of verticals, across geographies. Japan, India, all of that, in one place at Next, which is exciting. >> So very specific vertical use cases that you just mentioned, it's also this sort of general business usage, it's the old thin client story, right? Now, mobile becomes somewhat of a challenge for folks, but, I mean, I've written blog posts on my mobile. Yeah, we live, like I said, on Google Docs, and Google Sheets but, >> Absolutely. >> so, what are some of the things you're hearing, first of all, is that a tailwind for you? Is that a trend that you guys are leaning in to? And what are some of the things that your clients are asking for there? >> Yeah, so, phenomenal example. I think what we're seeing is the seamless application usage across different locations but also across different form factors. So what I do on my mobile, I want to be able to do on my tablet, on my phone, in a way that I interact in the same way, with the right context in mind. And we want to make that available. We definitely see that at Google because we are, after all, the biggest cloud native company if you think about that, and we operate in that model. But we're seeing this trend, actually with legacy companies which is, a new thing that is a good discovery for us and we obviously want to offer the best technology for our customers, we are definitely seeing a little bit of that happen as well. >> And Drive is part of your swim lane as well? >> Yes. >> I suppose, so, I mean one of the things I see a lot of people do is they'll take every document on their desktop, or their laptop, and put it up into the cloud. So they always have access to it. >> Yeah, I think Drive is phenomenal because not only does it serve the traditional ECM or the content management solution space, I mean, Drive has over a billion users now, so it's very worldwide known. But also it has the editors and the, you know, Google Docs, Google Sheets, as part of the solution mix too, so. Really when you offer that up along with the Chromebook it becomes a very powerful solution in combination for any cloud native employee. >> Well you've created, you got a tiger by the tail, 'cause it's so easy to create a Doc now, it's easier than spitting up a VM. >> Menaka: Well, I mean students are growing up with this as well, right? So we're seeing that. >> So what do you, are you getting a lot of requests to simplify the management of all those Docs, and what is Google doing in that regard? >> Yeah, I think ease of management, ease of deployment, ease of end user computing is always on our mind and we're always striving to do a great job, trying to make sure it doesn't take very long for anyone in IT to set up, whether it's their Drive instance or whether it's their Chromebooks we want to make it incredibly easy. And we are seeing this happen today, actually we have grab and go devices here, where you could take a Chromebook, log in and all your personalization kicks in within two minutes of you logging in, and then you shift a user, or give it to him and it doesn't require any reconfiguration. It sort of cleans out on its own, and has all of the other personalization set up. So we're thinking constantly about how do we do this for IT? So a five person team, actually I had a customer that has a five person team managing 4000 endpoints with just a small IT staff. And they want to be able to do interesting creative things not just manage end user devices, so we really are thinking hard about how do we do this in a way that's easy. >> Take the heavy lifting off the customer. >> Yeah exactly. We absolutely want to do that, even for end user, it should feel seamless. >> Menaka, great to to hear all the traction, love the end to end Chrome Browser, final question for you, what's new for you guys? What's going on under your business? What's your marketing plan? What are some of the exciting things that you're doing? >> Yeah we're just following the success we're seeing with our customers as you had mentioned earlier, we're seeing that with frontline, we're seeing that with healthcare, retail, those are all opportunities that we see, leaning in and supporting our customers in their journey to the cloud. And we see ours as a starting spot for that. >> Awesome, well congratulations. >> We'll have to look at getting some Chromebooks for theCUBE with a CUBE sticker. >> Yes! >> Can you make some custom Chromebooks for us? >> Custom, I don't, custom stickers. >> How about a custom browser? >> Custom stickers, browser is your personal, you can customize your browser as much as you like. >> John: We got stickers for you here. >> Oh, thank you! >> John: Love Chrome Browser, love the extensions, >> We'll take them. >> Programmability end to end, congratulations. Thanks for coming on. >> Thank you very much. >> Appreciate it. CUBE coverage here at San Francisco live, it's theCUBE covering Google Next 2019, stay with us for more after this short break. (electronic music)

>> Live from San Francisco, it's theCUBE, covering IBM Think 2019. Brought to you by IBM. >> Hey, welcome back everyone this is theCUBE's live coverage in San Francisco, California Moscone Center for IBM Think 2019. It's the wrap up of our four days of wall-to-wall live coverage. All the publishing on Siliconangle.com. I've got the journalism team cranking it out. Dave Vellante just put up a post on Forbes, check that out. And Stu's got the team cranking on the videos. Stu and Dave, four days, team's done a great job. Tons of video, tons of content, tons of data coming through theCUBE. We're sharing that live, we're sharing it on Twitter, we're sharing it everywhere on LinkedIn. What's going on with the data? Let's synthesize, let's extract the signal from the noise, let's assess IBM's prospects in this chapter two, as Ginni says. A lot of A.I., lot of data, I mean IBM is an old company that has so much business, so many moving parts and they've been working years to kind of pivot themselves into a position to run the table on the Modern Era of computing and software. So, what do you think, Dave? >> Well, I mean, this has been a long time coming and we're here, you pointed out John, to me privately that IBM's taking a playbook similar to Microsoft in that they're cloudifying everything. But there's differences, right? There's a bigger emphasis on A.I. than when, not that Microsoft's not in A.I. they of course are, but when Microsoft cloudified itself there wasn't as much of an emphasis on A.I. Ginni Rometty said, "Well, the first chapter was only about 20%, the remaining 80% is going to be chapter two. We're going hard after that." I wrote in that post today that, in 2013, IBM had a wake-up call. They lost that deal to Amazon at the C.I.A. They had to go out and buy Softlayer because their product was deficient, their cloud product was deficient. >> And by the way it looks like they're going to lose the JEDI Contract by the D.O.D., another agency that's a 10 billion dollar contract. >> So we can talk about they're going to lose that one too. >> We can talk about is Amazon's lead extending in Cloud? And so, IBM cannot take on Amazon head-to-head in infrastructures of service period, the end. It doesn't have the volume, >> And they know that, I think. >> It doesn't have the margins, and they know that. They got to rely on it's, as a service business it's SaaS, it's data, it's data platforms, obviously A.I. and now Red Hat. The fact that IBM had to spend, or spent, 34 billion dollars on Red Hat, to me underscores the fact that it's Cloud and it's 10-year attempt to commercialize Watson, isn't enough. It needs more to be a leader in hybrid. >> And let's talk about the Red Hat acquisition because Ray Wang on theCUBE yesterday and said, "Oh, P.E., private equity prices are driving up 34 billion dollars, pretty much market in today's world." He thinks they overpaid and could have used those services. You debated that, you've heard me say that, hey I could have used that 34 billion dollars of cobbled-together stuff, but you made a comment around speed. They don't have the gestation period there to do it. So, if you take market price for Red Hat, Stu, with open shifts accelerated success since Kubernetes really accelerated its adoption. You got IBM now with a mechanism to address the legacy on premise into Cloud Modern, and you got with this Cloud Private, Stu, this really is a secret weapon for IBM and to me, what I'm pulling out of all the data is that Rob Thomas at Interpol, the CDO have a great data A.I. strategy as a group. They have a team that's one team and this Cloud Private is a secret weapon for them. I think it's going to be a very key product and not a lot of people are talking about it. >> Well John, it shouldn't be a secret weapon for IBM because of course IBM has a strong legacy in the data center. We've talked about Z this week, you talk about power, talk about all the various pieces. Red Hat absolutely can help that a lot. What we noticed is there wasn't a lot of talk about Red Hat here just because it's going through the final pieces. We expect later this year to come out, but it's about the developers. That is where Red Hat is going to be successful, where they are successful and where they should be able to help IBM leverage that going forward. The concern we have is culture. IBM says that Red Hat will be separate. There will be no layoffs, they'll keep that alone but when I wrote about the acquisition I said, we should be able to see, for this to really be a successful acquisition, we should be able to see the Red Hat culture actually influence what's happening at IBM. And to be honest when I talk to people around this show, they're like, "That's never going to happen, Stu." >> I just want to make a point about the price. Ray was saying how they overpaid and made the private equity thing. IBM's paying a hundred and ninety dollars a share. If you dial back to June of '18, Stu you and I talked about this in our offices, Red Hat was trading at one seventy five a share. So they're paying an 8 1/2% premium over that price. Yes, when they made the deal in the fall you're talking about a 60% premium. So, the premium is really single digits over what it was just a few months earlier. >> And Cisco, Google, >> It was competitive, right. >> Microsoft all could have gone after that. I think it's a great buy for IBM. >> That's what they had to pay to get it. >> And definitely it helped there. So from my stand-point, looking at the show this week, first of all I was impressed to see really that data strategy and how that's pervasive through the company and A.I. is something that everyone's talking about how it fits in. John you commented a bunch of times Ginni mentioned Kubernetes two times in her Keynote. So, they're in these communities, they're working on all these environments. The concern I have is if this is chapter two and if A.I. is one of the battlefields, Amazon's all deep into A.I. I think heavily about Google when I talk about that. When I talk to Microsoft people they're like, "Satya Nadella is Mr. A.I.", that's all they care about. >> I don't think Microsoft has a lot of meat on the A.I. bone either. >> Really? >> No look it, here's the bottom line. A.I. is a moonshot it is an aspirational marketplace. It's about machine learning and using data. A.I.'s been around for a while and whoever can take advantage of that is going to be about this low-hanging use cases of deterministic processes that you throw machine learning at no problem. Doing cognition and reasoning a whole 'nother ballgame. You got state, this is where the Cloud Native piece is important as a lynch-pin to future growth because that wave is coming. And I think it's not going to impact IBM so much now, as it is in the future, because you got developers with Red Hat and you got the enablement for Cloud growth, Modern Cloud, stuff in any Cloud. But IBM has a zillion customers Dave, they have a business, they have mission critical workloads. And you pointed out in the Forbes post that we posted and on the Silicon Angle, that I.T. Economics are changing. And that the cloud services market is growing, so IBM has pre existing, big mission critical companies that they're serving. So, you can't just throw Kubernetes at that and say lift and shift. Z's there, you got other things happening. So, to me, that is IBM's focus, they nail their bread and butter, they bring multi-cloud from the table. Throw hybrid at it with Private Cloud and they're stable. Everything else I think is window dressing in my mind, because I think you're going to see that adoption more downstream. >> Well, the other thing you gave me for the piece actually, you helped me understand that IBM with Red Hat can use Cloud Native techniques and apply them to its customer base and to really create a new breed of business developers, right? Probably not the hoodie crowd necessarily, but business developers that are driving value apps based on mission critical apps and using Cloud Native techniques. Your thoughts on that? >> The difference between Oracle and IBM is the following, Oracle has no traction in developers in Cloud Native, IBM now with Red Hat can take the Cloud Native growth and use containers and Kubernetes and these new technologies to essentially containerize legacy workloads and make them compatible with modern technologies. Which means, if you're in business or in I.T. or running a lot of big shops, you don't have to kill the old to bring in the new. That's one factor. The other factor is the model's flipped. Applications are dictating architecture. It used to be infrastructure dictates what applications can do, it's completely reversed. We've heard this time and time again from the leading platforms, the ones that are looking at the applications with data as a fabric in there will dictate resource, Whether it's one Cloud or multiple Clouds or whatever architecture that's the fundamental shift. The people who get that will win and the people who don't won't. >> And the other thing I've pointed out in that article is that Ginny kept saying it's not backend loaded, The Red Hat deal, it's not back end loaded. IBM has about a 20 billion dollar business, captive business, in outsourcing, application management, application modernization and they can just point Red Hat right at that base, bring it's services business, Stu you've made this point, it's about scaling Red Hat. Red Hat's what, about a three and a half billion dollar company? >> Yeah >> And so that really is, she was explaining the business case for the acquisition. >> Yeah absolutely, I mean we've watched IBM for years, Bluemix had a little bit of traction but really faltered after a while, that application modernization. You hear from IBM, similar to what we've heard from Cisco a few weeks ago, meet customers where they are and help them move forward. We did a nice interview this week with a UK financial services company talking about how they've modernized what they're doing. Things like I.T. ops, new ops, these environments that are helping people with that app development. 'Cause IBM does have a good application work flow. There's lots of the infrastructure companies don't have apps and that's a big strength. >> When was the last, I got a direct message from the crowd, I want to get to Stu, but I want to ask you guys a question. When was the last time you saw a real innovation and disruption in a positive way around business applications. We're talking about business applications, not a software app, that's in a created category. We're talking about blocking and tackling business applications. When have you seen any kind of large scale transition innovation. Transition and innovation at the business application level? >> Google Docs? I mean >> I mean think about it. >> Right? >> So I think this is where IBM has an opportunity. I think the data science piece is going to transform into a business app marketplace and I think that's where their value is. >> Workday? >> Service Now. >> It's a sass ification of everything. >> Salesforce? >> Service Now, features become products. Products become companies. I mean this a big debate. I mean you can win on >> But that's not, Service Now really not a business, I mean it is a business app but it's more of an I.T. app. Alright Workday I'd say is an example. Salesforce I guess. >> And look here's one of the flaws in that multi-cloud picture, is it's I'm going to take all this heterogeneous environment and I'm going to give you a multi-Cloud manager. We've seen that single pane of glass discussion my entire career and it never works. So I'm a little concerned about that. >> So Andy Jassy makes the case that multi-cloud is less secure, more complex, more expensive. It's a strong case that he makes. Now of course my argument is that it's multi-vendor. It's not really multi-cloud. >> Well here's the Silicon Valley >> So he didn't have any control over that. It's not a procurement thing, it's just the way that people go by. >> The world has changed with cloud and I'll give you a Silicon Valley example anecdote. It used to be an expression in Silicon Valley, in venture capital community if you were a start-up or entrepreneur you'd build a platform. And there was an old expression, that's a feature, not a company. Kind of a joke within the VC community and that's how they would vet deals. Oh, that's a good feature" >> "Oh it's a feature company." >> "That's a great idea." Now with Cloud as a platform and now with all the stuff that's coming to bear, horizontally scalable, all the things that IBM's rolling out, sets the table for a feature to be a company. Where you have an innovation at the business model level, you don't really need tech anymore other than to scale up build it out and that's all done for you by other people. So people who are innovating on say an idea, well let's change this little feature in HR app or, that could meet up to Workday. Or let's change this feature. Features can become companies now so I think that's my observation. >> I think it's really interesting >> It could live in the cloud marketplaces too. It's so easy to get that scale if I could plug into all those marketplaces. IBM for years has had thousands of partners in their ecosystem. Of course Amazon's Marketplace, growing like gangbusters. >> But this is what Jerry Chen said when we were at Reinvent last year and we were asking him about Amazon, will it go up the stack, will it develop applications? He said, well, look but then what we got to do is give people a platform for application developers to build those features to disrupt, to your point, the core enterprise apps. Now, can IBM get there before Amazon, who knows? I mean its. >> Alright guys let's look at the big picture, zoom out. Your thoughts on Think 2019 IBM Think, Stu what's your final thoughts? >> Yeah, final thoughts is, I think IBM first of all is coming together. Just as this show was six shows and last year it was in two locations, there's cohesion. I heard the four days of interviews, we saw a lot of different pieces. Everything from talking about augmented reality through storage and we talked about the Z, and those pervasive themes of data, A.I., Dave what do you call it, It's the innovation cocktail now in Cloud. Data A.I. in cloud, put those three together. >> Innovation sandwich, innovation cocktail. Got to have a cocktail with a sandwich. That's your big take away? Okay, my take away Dave is that the, you nailed it in your post I thought, you should go to Forbes and check out, search on IBM Think you'll find the post by me and Dave Vellante but it's really written by Dave. I think to me IBM can change the game on two fronts. I learned and I walked away with a learning this week about these business apps. To me, my walk away is there's going to be innovation at a new genre of developers. I think you're going to see IBM target, they should target these business app ties as well as with the Could Native in Red Hat. I really think highly of that acquisition. From a speed stand point, I think the culture of Red Hat, although different, will be a nice check against IBM's naturally ability to blue-wash it. Which means you don't want to lose the innovation. I think Ginni saying Kubernetes twice on stage, is a sign that she sees this path, I think the Cloud Private opportunity could be a nice lever to bring open shifts and Kubernetes into that growth. And I think A.I. is going to be one of those things where they're either going to go big or go home. I think it's going to be one of those things. >> My take, love the venue, way better than last year in terms of the logistics. I like the new Moscone, easy to get around. May next year, May 2020 is going to be better than February here. I would've liked to see Ginni sell harder. She laid out a vision, she talked about a lot of sort of of high level things. I would have liked to seen her sell the new IBM and Red Hat harder. I guess they couldn't do that because they're worried about compliance. >> Quiet Period? >> Yeah right, you know monopolistic behavior I guess. But that I'm really excited to hear that story and a harder sell on the new IBM. >> I think if they can take the Microsoft playbook of cloudifying everything going with the open source with Red Hat and then just getting the great Sass if app revenue up, they're going to, can do well. >> Alright guys, great job. Thanks for hosting this week. Lisa Martin's not here today. Want to thank Lisa Martin if you're out there watching, great time. Guys, thanks to the crew. Thanks to IBM. Thanks to all of our sponsors that make theCUBE do what we do and thanks for all of your support to the community. I'm John Furrier along with Stu Miniman. Thanks for watching. See you next time. (pulsing electronic music)

(music) >> Everyone, welcome to a special CUBE Conversation. We're here in Palo Alto, theCUBE Studios, I'm John Furrier, the host of theCUBE video, we're here with a very special guest and the new CEO of a hot startup, Christine Heckart, CEO Scalyr. Welcome to theCUBE, great to see you. >> Thank you. >> Thanks for coming on. So, you're the new CEO of Scalyr, the CEO transitioned. >> Super great founder, great engineering team. >> Yes, yes. >> Hot startup, lot of finance and a lot of customers. Tell us about Scalyr. >> So, Scalyr was founded by a guy named Steve Newman. He is a serial entrepreneur. Scalyr is his 7th company. His 6th company was called Writely and it got bought by Google and is what we all know and love as Google Docs today. So, when he was inside Google, building out Google Docs he had the same problem that a lot of engineers do right now especially if they're on a modern stack. It's really hard to troubleshoot. It's hard to figure out what's running well and if there's a problem where it's at and fix it quickly. And so he left in 2011 and he founded Scalyr. >> And so, the company has how many employees? Just give us the quick numbers of employees, funding, venture involved, customers... Give us the quick numbers. >> The company has a little over 50 employees. It just took a Series A round about a year, a little under a year-and-a-half ago. Led by Shasta Ventures. There are 300 paying customers. We grew the core customer base last year by 170% revenue. So, it's growing very quickly. We more than doubled the employees in the last year. So, like you say, it's on fire and we're trying to scale up ourselves as we help our customers scale. >> So growth is obviously rocket ship growth is an attractive, enticing opportunity for you. You've been there, done that. So, what else attracted you to the opportunity? What made you make the move to take the leadership helm as the chief of Scalyr? >> The thing that attracted me most to Scalyr is that the world runs on code right now. And for companies for whom the code is the company downtime is money, it's critical. But, in these modern stacks, it's really hard to figure out where the problem is. Everything's been so abstracted. And if you're cloud-based, if you're moving to serverless, if you're on Kubernetes or some kind of container platform trying to do orchestration... Any of that makes it faster and easier to build a service but a lot harder to figure out if and where there's a problem within the service. And Scalyr's designed by engineers for engineers on modern stacks to help them figure out where that problem is and get it solved very quickly. >> So obviously the new wave is the cloud. Cloud natives search for big opportunities converging. What's the market opportunity? What are you guys going after in terms of, if you look at the marketplace, what's the segment you're going after? Lay that out, what segment are you in? Is it just cloud, is it a piece of cloud native, what's the market opportunity? >> We serve customers who have applications built on a new stack a cloud-based stack. And typically the people who use us most and who love us most are the site-reliability engineers, responsible for keeping it up and running. Dev Ops, true developers... One of our largest customers is a company called Zalando. They're an older company that did a digital transition, and so they do online e-commerce now, one of the largest in Europe. And for their engineers, 25% of their engineers use the product daily. 50% use it weekly. So, it's part of the workflow. It helps them do their jobs better. So, it's a utility. And the founder, you said, worked at Google, obviously he saw the scale there. They have a site reliability engineer concept that's obviously run a huge infrastructure. Is that kind-of the market you're going after? Dev Ops, SRE types? >> Yep, so we're an observability tool. There's kind-of two camps of observability. We've started in the logging space. So, what we're really known for is the fast logging tool. And the reason why we're known for being fast is unlike all the other architectures that were optimized for the more traditional stack, we've been written and optimized for the new stack and we're the only architecture that doesn't use keyword index in order to do that search. And that's what makes us fast. But it's also what makes us more affordable. And it contributes to, the architecture contributes to the simplicity of how you can use the tool and how the tool is written. >> So, the core tech is, under the hood would be, what, what's the core tech in that. Because speed obviously means you've got some technology there. What's the core technology that makes that speed work? >> So, we're a true multi-tenancy product, we run on Amazon ourself, it's a multi-tenancy system, it uses massive parallel processing. And basically we can ingest any data, in fact we're designed for machine data, for logs, for things that don't, they're not full documents, it's not like a video or something on the World Wide Web. These are little tiny events that come in and there's lots and lots and lots of them. Scalyr is the name of the company, we scale up and we scale out. And what we do is, when you go to run a query we throw every processor in our system at every query that comes in. And the reason why that becomes important in this multi-tenancy architecture is the more customers we have, the more data that we ingest, the more servers we have to throw at every query for every customer. So as we grow, the service gets better, it gets faster, it gets more affordable for all customers. >> That's the best thing about the cloud, you can bring that compute to bear so you have a little flywheel of acceleration. Talk about the role of data, because this is interesting, one of the core problems we hear a lot in the cloud native world is that so many, now, sets of services being deployed Kubernetes is becoming the de-facto sceme for orchestration around micro-services, containers obviously they're our standard as well. Which means there's more instrumentation, right? So, I could almost see how the founder saw this future because he lived it. >> Exactly. >> He lived the future, and now the real world's going "hey, we have that Google-like problem, we have tons of services playing around but it's not just logging and getting a query back in minutes. These services are talking to applications through each other. This is like mission critical. >> Very mission critical. >> Is this what you guys are doing? >> Right, if you are running in a traditional environment and you're running sort-of traditional applications there are really good logging solutions out there for that. That's what Splunk was founded on, they're amazing at doing that. But, nobody had built an optimized logging system and an observability system for the new stack. And that's what we're designed to do. And you use, you said, in minutes. And minutes is what it takes for most log queries in a traditional environment. 96% of all of our queries happen in less than a second. We're fast. >> So, this is really what the Agile teams need, Dev Ops teams need. >> Yes. When code is money, when it's the company, when every second of downtime, or even a service that's impaired, it might not be hard down but it's not running the way that it should, that impacts the customer experience, it impacts how many customers you can get if you're a real-time business, it impacts revenue. It's important to get that service up and running quickly. >> So, you guys are re-imagining logging, which is more mission critical rather than okay, where the breach is, what's going on in the basic logs, like Splunk used to do. So, talk about the product. Who's the target persona, how is it consumed, you mentioned on the cloud, is it SAS? How does someone get involved, do they just download it, do they get a consult, talk about the product and the target audiences. >> So, it is SAS, it's delivered by SAS. We don't have a non-prime service today or an offering. And, typically it's the site-reliability engineer, the architects, the developers themselves, Dev Ops for sure, Cloud Ops, they're the ones that are using the tool day-to-day. And it's a beautiful dashboard, a lot of it is just point and click. You can go in, if you want to add English-language query, you don't have to learn a special query language to use this, that's why people say it's so fast and easy to learn to use and I think that's why we get the kind of daily usage we have. You don't have to be an expert in the tool, it's very intuitive, you get a dashboard, you can just keep clicking down off of a chart and get all the way to the code. In fact, we can link you from where the problem is straight into the code that underlies that so you can then go and solve the problem. >> So, it's really easy to get into. >> Very. >> So I don't need do any kind of elaborate configurations? >> No. You don't need to do elaborate configurations and, as importantly, you don't need to learn a new specialized query language. Which, again, in the more traditional systems you find that there's only a few people that really know how to use the product because you have to learn the query language. It's kind-of like CLI or something in networking. And so there's a few specialists and they're very good, but if you're an engineer and there's a problem and you want to use the tool, you don't have time to become an expert. You've got to just use it. And so, even though it's designed to search machine language, you can use English, it's pretty easy to figure out how to write that query, and it comes back so quickly, if you didn't get it quite right you can just refine and do the search again and narrow down. >> I can see why the V.C.'s like this, the venture capitalists, because it markets good, big wave, cloud native lot of growth there. Certainly hyper-scalers, enterprisers are coming next, so I can imagine that's more head room. Product is consumable, SAS, in the cloud, technology that's fast, compelling, >> You're good, you can be on the pitch team. >> Final check box is customers. >> Yes. >> So, how many customers do you have? >> We have 300 paying customers. That doubled in the last year, and we have some big names and a lot of small companies. So, some of the fun ones are Giphy, my kids love that, my husband, right? Using them every day. NBC Universal, kind-of on the other side of that. Companies for whom the application is the business. And it can be a traditional company that's trying to launch new digital transformation initiatives, or it can be companies that were born in the cloud. >> And that's only going to get better, again, the markup. There's more companies going to the cloud. Talk about multi-cloud, because you know we had conversations in the past before you came on Scalyr around multi-cloud. That's only going to increase the sets of microservices and the role of data. Not just code, because code is data. Data is code. It's going to be a whole data ops movement coming soon, we see that tsunami coming. How does the multi-cloud fit into all of this in your mind? Is it too early, is that coming later? Or, is it available now? Could your customers have the multi-cloud now? >> For our customers, if they are in a multi-cloud environment today, we're an ideal tool for them 'cause we can run on any of their clouds. Most customers are not yet in multi-cloud, but they're trying to get there. Just like most customers are not yet fully containerized, but you want to pick a tool today that will grow with you and get you to tomorrow. And that's where Scalyr comes in, because we are designed and optimized for that environment. And, there's kind-of no scale too big for us. The company was named very deliberately. We can scale up, we can scale out, and we can continue to be simple and fast as your business scales. >> Christine, you've had a track record, you've had a great career, you've seen a lot of waves of innovation. You've been working for big companies, a dozen start-ups, now you're back at a start-up. So, I got to ask you a personal question, how does it feel? What's it like back into the trenches? And, you've got a hot start-up here. One month on the job, what's going on there? >> I love it. I really love it. You know, there's 50 people in the company every one of them is high-energy they're so committed to the cause. You know, when the world runs on code and you help that code run better, you're making an impact on the world every single day. These people know it, they feel it. They're very committed. And, unlike some of the much bigger companies I've been at, you can innovate so quickly. So, I just finished my first 30 days onboarding, I have talked to our big customers, a couple dozen of our really big customers. And, they all say a couple of things over and over again, there's just some consistent themes. Fast always comes up, it's usually the first word. Simple comes up. Affordable, which is nice. People pay a lot of money for these tools and they don't always feel good about all that money. We can come in and be much more affordable and they appreciate that. But, the thing that kept coming up over and over again was the customer service and the customer support. And nobody, I come from worlds where nobody ever raves about customer service and customer support. So, it was odd and I dug a little bit, and there were two pieces to that. One, because we're 50 people, when somebody has a problem, we're all-in. It gets solved quickly. A lot of times we can sort-of flag that problem for the customer because we're keeping track. But the other thing that was brought up is when they need something that maybe we don't deliver today they ask for it. And a lot of times we can give it to them pretty quickly. There's not some big, huge long roadmap process. We're a small company, we can't always do it quickly, but a lot of times we can turn stuff around and it's great. >> Well, you're hitting the ground running, got your running shoes on, sounds like a great opportunity. You've got a lot of work to do! What are some of the priorities? I'm sure hiring is big. Take a minute to give the plug on for any hirings you have. >> So, we're just moving to brand new facilities in downtown San Mateo a couple blocks from Caltrain. And that is because we doubled the company size last year, and we need to double it again this year. So, we are hiring, if you know of any great people, please send them to us. We announced some new things at Amazon Reinvent, late last year, one of which is new distributed tracing. We're on the very leading edge of this trend, and it's an important one. It's probably a conversation maybe with Steve himself. Yeah, he's very knowledgeable, and it's a fascinating area because the APM systems, again, kind-of the traditional if you can say that for APM, have all been built for the front-end, for the websites. But, once you move into these container environments you need that same kind of capability for the back end. And so you need something called distributed tracing. It turns out that if you're born in the logs like we are doing that distributed tracing which links them together and gives you a picture systemically of what's happening and how you link the events for a fuller picture. We're kind-of uniquely good at that. So, we've got that coming out later this quarter. >> That'll attract some engineers 'cause that's a hard problem. >> It's a hard, a lot of the problems we solve are hard, interesting problems, and they're problems for the new stack, and they're problems at scale. And smart engineers like to work on that. >> You know, state's a big one, stateless applications, state is a huge problem I'm sure you guys are on, this is where the tracing plays in. >> Yes, exactly. >> Final question for you before we end is competition. Certainly people who are in the new world, going cloud native, they get it, they get the complexity, they get the opportunity as well. So, there's a lot of investment there. But, the folks that are looking at Scalyr like "ooh, what's the competitive lens"? How do you answer that? What's your response to differentiate, being different from the competition? So, there's lots and lots of observability tools, and even logging tools in the market. And from that standpoint you could say there's tons of competition. They're all built on keyword indexing, so they're all optimized for looking back, for yesterday's world. We're the only ones that are built on this very new architecture, designed for the future stack, designed for the new stack. And, we're the only ones that don't use keyword indexing. And, what we have is this amazing, multi-tenancy, columnar-based approach that gives you these advantages of fast, simple, and affordable. >> So you're staking the ground in the marketplace of speed, sub-second response, 2 queries, 4 runtime applications that are mission critical to businesses. Is that right? >> Said very well, thank you. >> Well, that's what we do here at theCUBE, we figure it out, we get the data. >> Christine, thanks for coming out. Congratulations on the new role. We'll be following you guys. Love the name, Scalyr. Scaling is table stakes now in the cloud. If you don't compete at scale, or operate at scale, or develop at scale, you're probably going to be in trouble. So, theCUBE's covering it as always. Thanks for watching, I'm John Furrier.

>> Dave: Good morning everybody and welcome to Big Data SV. >> Come down, hang out with us today as we have continued conversations. >> Will this trend, this Big Data trend, solve the problems that decision support and business intelligence couldn't solve. We're going to talk about that today. Gentlemen, welcome to theCUBE. (energetic rock music) >> Dave: We're setting up for the digital business era. >> What do people really want to do? And it's big data analytics. I want to ingest a lot of information. I want to enrich it. I want to analyze it and I want to take actions and then I want to go park it. >> Leveraging everything that is open source to build models and put models in production. >> We talk a little bit like it's Google Docs for your data. >> So I no longer have to send daily data dumps to partners. They can simply query the data themselves. >> We've taken the two approaches of enterprise analytics and self-services and tried to create a scenario where you kind of get the best of both worlds. >> The epicenter of this whole data management has to move to cloud. >> It saves you a lot of time and effort. You can focus on more strategic projects. >> Do you agree it's kind of bifurcated. There's the Spotifys, and the Ubers, and the AirBnBs that are crushing it and then there's a lot of traditional enterprises that are still stovepipe and struggling. >> Marketing people, operational people, finance people, they need data to do their jobs. Their jobs are becoming more data-driven but they're not necessarily data people. >> They're depending on the vendor landscape to provide them with an entry level set of tools. >> Don't make me work harder and add new staff. Solve the problem. >> Yeah, it's all about solving problems. >> A lot more on machine learning now and artificial intelligence and frankly a lot of discussion around ethics. >> Data governance, it is in fact a business imperative. >> Marketers want all the customer data they can get, right? But there's social security numbers, PII-- Who should be able to see and use what because if this data is used inappropriately then it can cause a lot of problems. >> Creating that visibility is very important. >> The biggest casualty is going to be their customer relationship if they don't do this because most companies don't know their customers fully. >> The key that digital transformation is really a lauder on the concept of real time. >> If anybody deals with the data that's in motion, you lose because I'm analyzing as it's happening and then you would be analyzing after at rest. >> Speed is so important these days and the new companies that are grasping data aggressively, putting it somewhere where they can make decisions on it on a day-to-day basis, they're winning. >> Come on down, be part of our audience. We also have a great party tonight where you can network with some of our experts and analysts. (energetic rock music) >> Our expectation is that as the tooling gets better, we will see more people be able to present themselves truly as capable of doing this, and that will accelerate the process. >> To me, one of the first things a CDO has to do is understand how a company gets value out of its data. >> You can either run away from that data and say, look, I'm going to not, I'm going to bury my head in the sand, I'm going to be a business, I'm just going to forget about that data stuff and that's certainly a way to go. Right? It's a way to go away. >> It's easy to get overwhelmed for companies, you have to pick somewhere, right? >> You don't have to go sit in the basement for a year having something that is 'the thing', the unicorn in the business, it's small quick wins. >> We're not afraid of makin' mistakes. If we provision infrastructure and we don't get it right the first time, we just change it. >> That's something that we would just never be able to do previously in a data center. >> When companies get started with the right first project they can build on that success and invest more, whereas if you're not experimenting and trying things and moving, you're never going to get there. >> Dave: Thanks for watching, everybody. This is thCUBE. We're live from Big Data SV. >> And we're clear. Thank you. (audience applauds)

>> Announcer: Live from San Jose, it's theCUBE, presenting Big Data Silicon Valley. Brought to you by SiliconANGLE Media and it's ecosystem partners. >> Welcome back to Big Data SV in San Jose. This theCUBE, the leader in live tech coverage. My name is Dave Vellante and this is day two of our wall-to-wall coverage. We've been here most of the week, had a great event last night, about 50 or 60 of our CUBE community members were here. We had a breakfast this morning where the Wikibon research team laid out it's big data forecast, the eighth big data forecast and report that we've put out, so check out that online. Jacques Nadeau is here. He is the CTO and co-founder of Dremio. Jacque, welcome to theCUBE, thanks for coming on. >> Thanks for having me here. >> So we were talking a little bit about what you guys do. Three year old company. Well, let me start. Why did you co-found Dremio? >> So, it was a very simple thing I saw, so, over the last ten years or so, we saw a regression in the ability for people to get at data, so you see all these really cool technologies that came out to store data. Data lakes, you know, SQL systems, all these different things that make developers very agile with data. But what we were also seeing was a regression in the ability for analysts and data consumers to get at that data because the systems weren't designed for analysts, they were designed for data producers and developers. And we said, you know what, there needs to be a way to solve this. We need to be able to empower people to be self-sufficient again at the data consumption layer. >> Okay, so you solved that problem how, you said, called it a self-service of a data platform. >> Yeah, yeah, so self-service data platform and the idea is pretty simple. It's that, no matter where the data is physically, people should be able to interact with a logical view of it. And so, we talk a little bit like it's Google Docs for your data. So people can go into the system, they can see the different data sets that are available to them, collaborate around those, create changes to those that they can then share with other people in the organization, always dealing with the logical layer and then, behind the scenes, we have physical capabilities to interact with all the different system we interact with. But that's something that business users shouldn't have to think as much about and so, if you think about how people interact with data today, it's very much about copies. So every time you want to do something, typically you're going to make a copy. I want to reshape the data, I make a copy. I want to make it go faster, I make a copy. And those copies are very, very difficult for people to manage and they could have mixed the business meaning of data with the physical, I'm making copies to make them faster or whatever. And so our perspective is that, if you can separate away the physical concerns from the logical, then business users have a much more, much more likelihood to be able to do something self-service. >> So you're essentially virtualizing my corpus of data, independent of location, is that right, I mean-- >> It's part of what we do, yeah. No, it's part of what we do. So, the way we look at it is, is kind of several different components to try to make something self-service. It starts with, yeah, virtualize or abstract away the details of the physical, right? But then, on top of that, expose a very, sort of a very user-friendly interface that allows people to sort of catalog and understand the different things, you know, search for things that they want to interact with, and then curate things, even if they're non-technical users, right? So the goal is that, if you talk to sort of even large internet companies in the Valley, it's very hard to even hire the amount of data engineering that you need to satisfy all the requests of your end-users of data. And so the, and so the goal of Dremio is basically to figure out different tools that can provide a non-technical experience for getting at the data. So that's sort of the start of it but then the second step is, once you've got access to this thing and people can collaborate and sort of deal with the data, then you've got these huge volumes of data, right? It's big data and so how do you make that go faster? And then we have some components that we deal with, sort of, speed and acceleration. >> So maybe talk about how people are leveraging this capability, this platform, what the business impact is, what have you seen there? >> So a lot of people have this problem, which is, they have data all over the place and they're trying to figure out "How do I expose this "to my end-users?" And those end-users might be analysts, they might be data scientists, they might be product managers that are trying to figure out how their product is working. And so, what they're doing today is they're typically trying to build systems internally that, to provide these capabilities. And so, for example, working with a large auto manufacturer. And they've got a big initiative where they're trying to make the data that they have, they have huge amounts of data across all sort of different parts of the organization and they're trying to make that available to different data consumers. Now, of course, there's a bunch of security concerns that you need to have around that, but they just want to make the data more accessible. And so, what they're doing is they're using Dremio to figure out ways to, basically, catalog all the data below, expose that to the different users, applying lots of different security rules around that, and then create a bunch of reflections, which make the things go faster as people are interacting with the things. >> Well, what about the governance factor? I mean, you heard this in the hadoop world years ago. "Ah, we're going to make, we're going to harden hadoop, "we're going to" and really, there was no governance and it became more and more important. How do you guys handle that? Do you partner with people? Is it up to the customer to figure that out? Do you provide that? >> It's several different things, right? It's a complex ecosystem, right? So it's a combination of things. You start with partnering with different systems to make sure that you integrate well with those things. So the different things that control some parts of credentials inside the systems all the way down to "What's the file system permissions?", right? "What are the permissions inside of something like Hive and the metastore there?" And then other systems on top of that, like Sentry or Ranger are also exposing different credentialing, right? And so we work hard to sort of integrate with those things. On top of that, Dremio also provides a full security model inside of the sort of virtual space that we work. And so people can control the permissions, the ability to access or edit any object inside of Dremio based on user roles and LDAP and those kinds of things. So it's, it's kind of multiple layers that have to be working together. >> And tell me more about the company. So founded three years ago, I think a couple of raises, >> Yep >> who's backing you? >> Yeah, yeah, yeah, so we founded just under three years ago. We had great initial investors, in Red Point and Lightspeed, so two great initial investors and we raised about 15 million on that round. And then we actually just closed a B round in January of this year and we added Norwest to the portfolio there. >> Awesome, so you're now in the mode of, I mean, they always say, you know, software is such a capital-efficient business but you see software companies raising, you know, 900 million dollars and so, presumably, that's to compete, to go to market and, you know, differentiate with your messaging and branding. Is that sort of what the, the phase that you're in now? You kind of developed a product, it's technically sound, it's proven in the marketspace and now you're scaling the, the go-to-market, is that right? >> That's exactly right. So, so we've had a lot of early successes, a lot of Fortune 100 companies using Dremio today. For example, we're working with TransUnion. We're working with Intel. We actually have a great relationship with OVH, which is the third-largest hosting company in the world, so a lot of great, Daimler is another one. So working with a lot of great companies, seeing sort of great early success with the product with those companies, and really looking to say "Hey, we're out here." We've got a booth for the first time at Strata here and we're sort of letting people know about, sort of, a better way, or easier way, for people to deal with data >> Yeah. >> A happier way. >> I mean, it's a crowded space, right? There's a lot of tools out there, a lot of companies. I'm interested in how you sort of differentiate. Obviously simplification is a part of that, the breadth of your capabilities. But maybe, in your words, you could share with me how you differentiate from the competition and how you break out from the noise. >> Yeah, yeah, yeah, so it's, you're absolutely right, it's a very crowded space. Everybody's using the same words and that makes it very hard for people to understand what's going on. And so, what we've found is very simple is that typically we will actually, the first meeting we deal with a customer, within the first 10 minutes we'll demo the product. Because so many technologies are technologies, not, they're not products and so you have to figure out how to use the product. You've got to figure out how you would customize it for your certain use-case. And what we've found with our product is, by making it very, very simple, people start, the light goes on in a very short amount of time and so, we also do things on our website so that you can see, in a couple of minutes, or even less than that, little animations that sort of give you a sense of what it's about. But really, it's just "Hey, this is a product "which is about", there's this light bulb that goes on, it's great. And you figure this out over the course of working with different customers, right? But there's this light bulb that goes on for people that are so confused by all the things that are going on and if we can just sit down with them, show them the product for a few minutes, all of a sudden they're like "Wait a minute, "I can use this", right? So you're frequently talking to buyers that are not the most technical parts of the organization initially, and so most of the technologies they look at are technologies that are very difficult to understand and they have to look to others to try to even understand how it would fit into their architecture. With Dremio, we have customers that can, that have installed it and gotten up, and within an hour or two, started to see real value. And that sort of excitement happens even in the demo, with most people. >> So you kind of have this bifurcated market. Since the big data meme, everybody says they're data-driven and you've got a bifurcated market in that, you've got the companies that are data-driven and you've got companies who say they're data-driven but really aren't. Who are your customers? Are they in both? Are they predominantly in the data-driven side? Are they predominantly in the trying to be data-driven? >> Well, I would say that they all would say that they're data-driven. >> Yeah, everyone, who's going to say "Well, we're not data-driven." >> Yeah, yeah, yeah. So I would say >> We're dead. >> I would say that everybody has data and they've got some ways that they're using it well and other places where they feel like they're not using it as well as they should. And so, I mean, the reason that we exist is to make it so it's easier for people to get value out of data, and so, if they were getting all the value they think they could get out of data, then we probably wouldn't exist and they would be fully data-driven. So I think that everybody, it's a journey and people are responding well to us, in part, because we're helping them down that journey. >> Well, the reason I asked that question is that we go to a lot of shows and everybody likes to throw out the digital transformation buzzword and then use Uber and Airbnb as an example, but if you dig deeper, you see that data is at the core of those companies and they're now beginning to apply machine intelligence and they're leveraging all this data that they've built up, this data architecture that they built up over the last five or 10 years. And then you've got this set of companies where all the data lives in silos and I can see you guys being able to help them. At the same time, I can see you helping the disruptors, so how do you see that? I mean, in terms of your role, in terms of affecting either digital transformations or digital disruptions. >> Well, I'd say that in either case, so we believe in a very sort of simple thing, which is that, so going back to what I said at the beginning, which is just that I see this regression in terms of data access, right? And so what happens is that, if you have a tightly-coupled system between two layers, then it becomes very difficult for people to sort of accommodate two different sets of needs. And so, the change over the last 10 years was the rise of the developer as the primary person for controlling data and that brought a huge amount of great things to it but analysis was not one of them. And there's tools that try to make that better but that's really the problem. And so our belief is very simple, which is that a new tier needs to be introduced between the consumers and the, and the producers of data. And that, and so that tier may interact with different systems, it may be more complex or whatever, for certain organizations, but the tier is necessary in all organizations because the analysts shouldn't be shaken around every time the developers change how they're doing data. >> Great. John Furrier has a saying that "Data is the new development kit", you know. He said that, I don't know, eight years ago and it's really kind of turned out to be the case. Jacques Nadeau, thanks very much for coming on theCUBE. Really appreciate your time. >> Yeah. >> Great to meet you. Good luck and keep us informed, please. >> Yes, thanks so much for your time, I've enjoyed it. >> You're welcome. Alright, thanks for watching everybody. This is theCUBE. We're live from Big Data SV. We'll be right back. (bright music)

>> Hey, welcome back everybody. Jeff Frigg here with theCUBE. We're at Data Privacy Day 2018 here at Linked-In's brand new, downtown San Francisco headquarters not in Sunny Vale. And we're excited to be here for the second time. And we've got Eve Maylar back she's a VP in innovation and emerging tech at Forge Rock, we caught up last year, so great to see you. >> Likewise. >> So what's different in 2018 than 2017? >> Well GDPR, the general data protection regulation Well, also we didn't talk about it much here today, but the payment services directive version two is on the lips of everybody in the EU who's in financial services, along with open banking, and all these regulations are actually as much about digital transformation, I've been starting to say hashtag digital transformation, as they are about regulating data protection and privacy, so that's big. >> So why aren't those other two being talked about here do you think? >> To a certain extent they are for the global banks and the multinational banks and they have as much impact on things like user consent as GDPR does, so that's a big thing. >> Jeff: Same penalties? >> They do have some penalties, but they are as much about, okay, I'm starting to say hashtag in front of all these cliches, but you know they are as much about trying to do the digital single market as GDPR is, so what they're trying to do is have a level playing field for all those players. So the way that GDPR is trying to make sure that all of the countries have the same kind of regulations to apply so that they can get to the business of doing business. >> Right, right, and so it's the same thing trying to have this kind of unified platform. >> Yup, absolutely, and so that affects companies here if they play in that market as well. >> So there's a lot of talk on this security site when you go to these security conferences about baking security in everywhere, right? It can't be OL guard anymore, there is no such thing as keeping the bad guys out, it's more all the places you need to bake in security, and so you're talking about that really needs to be on the privacy side as well, it needs to go hand-in-hand, not be counter to innovation. >> Yes, it is not a zero sum game, it should be a positive sum game in fact, GDPR would call it data protection by design and by default. And so, you have to bake it in, and I think the best way to bake it in is to see this as an opportunity to do better business with your customers, your consumers, your patients, your citizens, your students, and the way to do that is to actually go for a trust mark instead of, I shouldn't say a trust mark, but go for building trusted digital relationships with all those people instead of just saying "Well I'm going to go for compliance" and then say " Well I'm sorry if you didn't feel that action "on my part was correct" >> Well hopefully it's more successful than we've seen on the security side right? Because data breaches are happening constantly, no one is immune and I don't know, we're almost kind of getting immune to it. I mean Yahoo's it was their entire database of however many billions of people, and some will say it's not even when you get caught it's more about how you react, when you do get caught both from a PR perspective, as well as mending faith like the old Tylenol issue back in the day, so, on the privacy side do you expect that to be the same? Are these regulations in such a way where it's relatively easy to implement so we won't have kind of this never ending breach problem on the security side, or is it going to be kind of the same. >> I think I just made a face when you said easy, the word easy okay. >> Not easy but actually doable, 'cause sometimes it feels like some of the security stuff again on the breaches specifically, yeah it seems like it should be doable, but man oh man we just hear over and over again on the headlines that people are getting compromised. >> Yeah people are getting compromised and I think they are sort of getting immune to the stories when it's a security breach. We try to do at my company at Forge Rock we're identities so I have this identity lens that I see everything through, and I think especially in the internet of things which we've talked about in the past there's a recognition that digital identity is a way that you can start to attack security and privacy problems, because if you want to, for example, save off somebody's consent to let information about them flow, you need to have a persistent storage that they did consent, you need to have persistent storage of the information about them, and if they want to withdraw consent which is a thing like GDPR requires you to be able to do, and prove that they're able to do, you need to have a persistent storage of their digital identity. So identity is actually a solution to the problem, and what you want to do is have an identity and access management solution that actually reduces the friction to solving those problems so it's basically a way to have consent life cycle management if you will and have that solution be able to solve your problems of security and privacy. >> And to come at it from the identity point of view versus coming at it from the data point of view. >> That's right, and especially when it comes to internet of things, but not even just internet of things, you're starting to need to authenticate and identity everything; services, applications, piles of data, and smart devices, and people, and keep track of the relationships among them. >> We just like to say people are things too so you can always include the people in the IT conversation. But it is pretty interesting the identity task 'cause we see that more and more, security companies coming at the problem from an identity problem because now you can test the identity against applications, against data, against usage, change what's available, not available to them, versus trying to build that big wall. >> Yes, there's no perimeters anymore. >> Unless you go to China and walk the old great wall. >> Yes you're taking your burner devices with you aren't you? (laughs) >> Yes. >> Good, good to hear >> Yeah but it's a very different way to attack the problem from an identity point of view. >> Yeah, and one of the interesting things actually about PSD2 and this open banking mandate, and I was talking about they want to get digital business to be more attractive, is that they're demanding strong customer authentication, SCA they call it, and so I think we're going to see, I think we talked about passwords last time we met, less reliance. >> Jeff: And I still have them and I still can't remember them. >> Well you know, less reliance on passwords either is the only factor or sometimes a factor, and more sophisticated authentication that has less impact, well less negative impact on your life, and so I'm kind of hopeful that they're getting it, and these things are rolling up faster than GDPR, so I think those are kind of easier. They're aware of the API economy, they get it. They get all the standards that are needed. >> 'Cause the API especially when you get the thing to thing and you got multi steps and everything is depending on the connectivity upstream, you've got some significant issues if you throw a big wrench into there. But it's interesting to see how the two factor authentication is slowly working its way into more and more applications, and using a phone now without the old RSA key on the keychain, what a game changer that is. >> Yeah I think we're getting there. Nice to hear something's improving right? >> There you go. So as you look forward to 2018 what are some of your priorities, what are we going to be talking about a year from now do you think? >> Well I'm working on this really interesting project, this is in the UK, it has to do with Affintech, the UK has a mandate that it's calling the Pensions Dashboard Project, and I think that this has got a great analogy in the US, we have 401ks. They did a study there where they say the average person has 11 jobs over their lifetime and they leave behind some, what they call pension pots, so that would be like our 401ks, and this Pensions Dashboard Project is a way for people to find all of their left behind pension pots, and we talked last year about the technology that I've worked on called user managed access, UMA, which is a way where you can kind of have a standardized version of that Google Docs share button where you're in control of how much you share with somebody else, well they're using UMA to actually manage this pension finder service, so you give access first of all, to yourself, so you can get this aggregated dashboard view of all your pensions, and then you can share, one pension pot, you know one account, or more, with financial advisors selectively, and get advice on how to spend your newly found money. It's pretty awesome and it's an Affintech use case. >> How much unclaimed pension pot money, that must just be. >> In the country, in the UK, apparently it's billions upon billions, so imagine in the US, I mean it's probably a trillion dollars. I'm not sure, but it's a lot. We should do something here, I'm wondering how much money I have left behind. >> All right check your pension pot, that's the message from today's interview. All right Eve, well thanks for taking a few minutes, and again really interesting space and you guys are right at the forefront, so exciting times. >> It's a pleasure. >> All right she's Eve Maylar I'm Jeff Frigg you're watching theCUBE from Data Privacy Day 2018, thanks for watching, catch you next time. (upbeat music)

>> Hey, welcome back everybody. Jeff Frick here with the CUBE. We're in Palo Alto, California at the Chertoff's event, "Security in the Boardroom." And again, this is an event about elevating the security conversation beyond speeds and feeds and in-points and IOT and ever-increasing attack surfaces, and really, how do we elevate it into the boardroom discussion, because that's where it needs to be before they wake up on Monday morning and see their company's name in the newspaper, which is when you don't want to have your first conversation. So we're excited to have our next guest. He's Joe Gottlieb, the Senior Vice President of Corporate Development for Sailpoint. Joe, welcome. >> Thank you, good to be here, Jeff. >> Absolutely, so for people who aren't familiar with Sailpoint, why don't you give us a quick overview. >> Sure, so Sailpoint helps large enterprises control who has access to what. So at the end of the day, all the access that you need to do your job should fall into what your role is in the company, and what projects you're working on, and for many companies, that's not what is proactively being delivered. You're accumulating a set of things based upon who you ask, who you know, and a lot of inadvertent accumulation of things that you might need or you might not need. So we help companies put that under lock and key and under control, make sure that there's a process for who should approve your access. How can we empower you quickly when you start your job? How can we transfer you to a new role if you move jobs? And most importantly, oftentimes, how do we take away things very systematically when you leave the company? So that's what we do in a nutshell. >> So I would imagine, before you get there, it's a hodgepodge of spreadsheets and Google Docs and all types of assorted random things. >> You bet, for the average large company, this is a manual effort, and it is just not systematic, which it has to be. What you have when you don't have a systematic effort here that's filtered by business approvals and work flow processes is a cumulated surface area that need not be available to the attacker. We want to narrow that surface area by narrowing your access to only that's what's needed and keep it pruned as you evolve with your role in the company. >> It seems like there's so much low-hanging fruit, about just doing what you should be doing, just doing it and so many people don't apply patches, they don't systematically take people out of things when they leave the company. All these things that seem relatively simple on the surface from the outside, but in fact, in a large organization, are not simple by any stretch of the imagination. >> It's so true. In security in particular, it's a really hard job but consistency and patience and methodic progress is really, really key. I liken it to the quality movement that we experienced in manufacturing over two decades ago. We started measuring, we started being consistent, we started thinking about what is the root cause of this or that and how can we continually make ourselves a bit better every time period. And so that's what some of the basics are all about, and governance is a big part of that. >> Okay, so you just got off a panel. And the event here is really focused about the boardroom conversation, so let's just jump into that. You made an interesting conversation from the board about a portfolio approach, which is only natural since you're a corp dev guy, thinking of portfolio strategies. So how should they think about the portfolio? I haven't heard anyone discuss their tools in a portfolio strategy method. >> So, let's zoom out on the context here. Boards are trying to provide governance. They need wisdom to provide governance. If they don't understand security at all, how can they be wise about it? So there's definitely a really, really strong push to get the board being more proactive about demanding the right levels of security and being shown the data that they can have for how security is being applied. I look at security portfolio management as a great way to step out of the Fudd domain, where we have vendors selling us technologies that we don't understand and most of the people talking to us don't even understand, and into a domain where there is less of a bet on prevention, which we know isn't going to happen, and more of a bet on monitoring a response, governance, which is just going back to the source and making sure people have the right access, and education, helping end users understand what that phishing attack would look like, actually going through testing and really accumulating awareness of what to avoid. Because we know that's the easiest way to get started. Every attack starts with a phishing attack that compromises an end-user point in-station, and then moves laterally to the good stuff. That portfolio view allows the board to start understanding how we're not making a bunch of hopeful bets on prevention that is elusive, and we're actually making some balanced bets around the pieces of the puzzle that we know can give us immediate returns and we can measure against the returns. >> Now what about the scale of the bets? We've talked about this with a few of the other guests that came on, 'cause again I liken it to insurance. You'd add some, you could be probably over-insured. There's not infinite resources, so there's always a ying and yang on how much do we invest and then what came up in the kickoff this morning and then how do we measure success? Because obviously success would be no problems, but you probably need a much softer way to measure success. >> Very true. So this came up earlier in the discussion, and that is you've got to get the board thinking about a risk posture, where there are tradeoffs. You can't ask them, you can't use Fudd on the board. You're going to freak 'em out. You have to say, "This is what I have to do "to enable this business to operate at this velocity." And if they don't want that risk, here's the velocity that they ought to be operating within because we are less exposed at that velocity. And so translating it into these sorts of terms that the board understands in the world of business. They're well experienced in advising you on how to operate your business. They've thought about travel risks. They've thought about plant closure risks. And they've thought about employee lawsuit risks. Translate security into risks that they can also understand and then present your measurements and your investment trade-offs in that context. That's what the best practice appears to be. It's still really hard, and so here's the knock: you can have all that great thinking and still struggle because of the degree of difficulty here. You just have to keep at it. >> Now unfortunately, the CISO on the agenda at the board meeting was down toward the end of the day and just before him was the CMO and the Head of Sales and Operations and they're like, "We got to go, we got to go, it's digital transformation. "We got to go, we got to go, competitors are going like crazy. "Speed, speed, speed, digital transformation." That's what you beat us up about last quarter. So as people are trying to really evolve their companies, they're trying to move to a more digital platform, they're innovate faster, they're trying to enable more people in the company to have access to the data, and access to the tools so they can innovate faster. How does that then bang up when he sits down and the CISO stands up? >> So, digital transformation is an opportunity. For me, it's just code for reinventing business around customer engagement, for many companies that have direct relationships to their customers in a broad form, at least it's that for them. That means there's an investment elasticity opportunity. And so building security into that velocity we talked about, or the mode of digital transformation that you're going to deliver is really, really key. It's less about defending security as a horizontal utility that is generic and hard to place within the context of that digital transformation, that customer engagement, that velocity of business, it's that latter scenario. Actually, one of the folks of the panel that I was on, Debbie from PNC Bank, made a great point. She talks about security as part of the brand, part of the brand prompts. We want people to trust our brand. And so more and more, I would argue that the monetization and the maturation of the attack life cycle, and the ability to take customer records and sell them, has forced us to realize that's a distinct business risk. So losing all of our customer data is a huge business risk that business people now understand and you can equip them to reduce that risk with good security measures. While you're doing digital transformation, you have an opportunity to bake it in. So now, you can suddenly say, "Hey look! "We can fit that into the overall architecture." You want it to be a collaborative part of the new design, versus an overlay, which has typically been the approach, when we've automated business on top of IT and then wrapped security around that. >> It's funny, you're the first person that's ever really tied security to trust and trust to brand, because there's always an ongoing conversation about, "Do brands matter? "What is a brand? "How are brands defined "in an increasingly competitive world?" So, is security in that context, table stakes or is it a competitive advantage? >> Well, let me ask you a question. How's Yahoo's brand today? >> Not so good. >> After repeated losses, right, I could name plenty. The circumstance and the experience, and our ability to absorb that experience frankly through a lot of reporting, has helped us to know what we're up against. What are the downsides? That's just education. I think that's the good part of Fudd, when things are reported accurately and we understand that these things have happened, even if we learn a bit later, that's very necessary for us to say, "This is what needs to be done." Just like anything else. When transportation evolved and we reinvented business at the speed of our new transportation in the way we collaborate, that was an impact. We now have to continue to think about business as being more digital and has to be more secure. >> Well, Joe, this has been a great conversation and the other thing you nailed, you're the first person that has ever talked about digital transformation as redefining your business process around customer engagement. That is spectacular. >> Wow. >> Thanks for sharing that, we'll use that. >> Good stuff. >> Alright. Thanks for stopping by. >> You bet. >> He's Joe Gottlieb, I'm Jeff Frick, you're watching the CUBE. We'll catch you next time, thanks for watching.

>> Man's Voice: Live from Orlando, Florida, it's theCUBE covering ServiceNow Knowledge17, brought to you by ServiceNow. >> Welcome back to Orlando, everybody. This is theCUBE, the leader in live tech coverage. We go out to the events, we extract a signal from the noise. My name is Dave Vellante, and I'm here with my co-host, Jeff Frick. This is theCUBE's fifth year covering Knowledge. We started in Las Vegas, a little small event, Jeff, at Aria Hotel, and it's exploded from 3,500 all the way up to 15,000 people here in Orlando at the Convention Center. This is day two of our three day coverage. And, we heard this morning, you know, day one was the introduction of the new CEO, John Donahoe, taking over the reins for Frank Slootman. And, actually it was interesting, Jeff. Last night, we went around to some of the parties and talked to some of the folks and some of the practitioners. It was interesting to hear how many people were saying how much they missed Fred. >> Right, right. >> And the culture of fun and kind of zaniness and quirkiness that they sort of have, and there's some of that that's maintained here. We saw that in the keynotes this morning, and we'll talk about that a little bit, but what are your impressions of sort of that transition from, you know, really the third phase now we're into of ServiceNow leadership? >> Right, well as was commented again last night at some of the events, you know, a relatively peaceful transition, right. So, the difference between an evolution and a revolution is people die in revolutions. This was more of an evolution. It was an organized handoff, and a lot of the product leaders are relatively new. We just saw CJ Desai. He said he's only 100 days ahead of where John is at 45 days. So, it is kind of a, I don't know if refresh is the right word, but all new leadership in a lot of the top positions to basically go from, as been discussed many times, from kind of the one billion dollar mark to the four billion dollar mark, and then, of course, onward to the 10. So, it sounds like everyone is very reverent to the past, and Fred has a huge following. He's one of our favorite guest. The guy's just a super individual. People love him. That said, you know, it's a very clear and focused move to the next stage in evolution of growth. >> Well, I think that, you know, Fred probably, I mean, he may have said something similar to this either in theCUBE or sort of in back channel conversations with us, is, you know, ServiceNow, when they brought in Frank Slootman, it needed adult supervision. And, Fred doesn't strike me as the kind of person that's going to be doing a lot of the, you know, HR functions and performance reviews and stuff. He wants to code, right. I mean, that was his thing. And, now, we're seeing sort of this next level of ascension for ServiceNow, and you seen the advancement of their product, their platform. So this morning, CJ Desai kicked off the keynotes. Now, CJ Desai was an executive in the security business. He was an executive at EMC, hardcore product guy. He's a hacker. You heard him this morning saying when he was at a previous company, he didn't mention EMC, but that's what he was talking about, I'm pretty sure. They use ServiceNow, and when ServiceNow started recruiting him, he said I opened up an instance and started playing around with it, and see if I could develop an app, and I was amazed at how easy it was. And, they started talking to some of the customers and seeing how passionate they were about this platform, and it became an easy decision for him to, you know, come and run. He's got a big job here. He run, he's basically, you know, manages all products, essentially taking over for Fred Luddy and, you know, Dan McGee as a chief operating officer even though he hasn't used that title 'cause he's a product guy. But, all the GMs report up into him, so he is the man, you know, on top of the platform. So, he talked this morning about Jakarta, the announcement, and the key thing about, you know, that I'm learning really in talking to ServiceNow over the years, is they put everything in the platform, and then the business units have to figure out how to leverage that new capability, you know, whether it's machine learning or AI or some kind of new service catalog or portal. The business units, whether it's, you know, the managers, whether it's Farrell Hough and her team, she does IT service management, Abhijit Mitra who does customer service management, the IT operations management people, the HR folks, they have to figure out how they can take the capabilities of this platform, and then apply it to their specific use cases and industry examples. And, that's what we saw a lot of today. >> But, it's still paper-based workflow, right? 'Cause back to Fred's original vision, which I love repeating about, the copy room with all the pigeonholes of colored paper that you would grab for I need a new laptop, I need a vacation request, I need whatever, which nobody remembers anymore. But, you know, at the end of the day, it's put in a request, get it approved, does it need to be worked, and then executed. So, whether that's asking for a new laptop for a new employee, whether that's getting a customer service ticket handled, whether it's we're swinging by doing name changes, it's relatively simple process under the covers, and then now, they're just wrapping it with this specific vocabulary and integration points to the different systems to support that execution. So, it's a pretty straightforward solution. What I really like about ServiceNow is they're applying, you know, technology to relatively straightforward problems that have huge impact and efficiency, and just getting away from email, getting away from so many notification systems that we have, getting away from phone calls, getting away from tech-- Trying to aggregate that into one spot, like we see it a lot of successful applications, sass applications. So, now you've got a single system of record for the execution of these relatively straightforward processes. >> Yeah, it really is all about a new way to work, and with the millennial work force becoming younger, obviously, they're going to work in a different way. I saw, when I tweeted out, was the best IT demo that I'd ever seen. Didn't involve a laptop, didn't involve a screen. What Chris Pope did, who's kind of an evangelist, he's in the CSO office, he was on... the chief strategy office, he was on yesterday. He came up with a soccer ball. Right, you saw it. And, he said >> Football. Make sure you say it right. He would correct you. (Jeff laughs) >> And, he said for those of you who are not from the colonies, this is a football. And then, he had somebody in a new employee's t-shirt, he had the HR t-shirt, the IT t-shirt, the facilities t-shirt, and they were passing the ball around, and he did a narrative on what it was like to onboard a new employee, and the back and forth and the touch points and, you know, underscoring the point of how complex it is, how many mistakes can be made, how frustrating it is, how inefficient it is, and then, obviously, setting up conveniently the morning of how the workflow would serve us now. But, it was a very powerful demo, I thought. >> Well, the thing that I want to get into, Dave, is how do you get people to change behavior? And, we talk about it all the time in theCUBE. People process in tech. The tech's the easy part. How do you change people's behavior? When I have to make that request to you, what gets me to take the step to do it inside of service now versus sending you that email? It seems to me that that's the biggest challenge, and you talk about it all the time, is we get kind of tool-creep in all these notification systems and, you know, there's Slack and there's Atlassian JIRA and there's Salesforce and there's Dropbox and there's Google Docs and, you know, the good news is we're getting all these kind of sass applications that, ultimately, we're seeing this growth of IPA's in between them and integration between them, but, on the bad side, we get so many notifications from so many different places. You know, how do you force really a compliance around a particular department to use a solution, as we say that, that's what's on your desk all the time, and not email? And, I think that's, I look forward to hearing kind of what are best practices to dictate that? I know that Atlassian, internally, they don't use email. Everything is on JIRA. I would presume in ServiceNow, it's probably very similar where, internally, everything is in the ServiceNow platform, but, unfortunately, there's those pesky people outside the organization who are still communicating with email. So, then you get, >> Exactly. >> Then, now, you're running kind of a parallel track as you're getting new information from a customer that's coming in maybe via email that you need to, then, populate into those tickets. That's the part I see as kind of a challenge. >> Well, I think it is a big challenge. And, of course, when you talk to ServiceNow people privately and you say to them, "Have you guys eliminated email?" Then, they roll their eyes and "I wish." (Jeff chuckles) But, I would presume their internal communications, as you say, are a lot more efficient and effective. But, you know, it's a Cloud app, and Cloud apps suffer from latency issues. And, it's like when you go into a Cloud app, you know, you log in. A lot of times, it logs you out just for security reasons, so you got to log back in and you get the spinning logo for awhile. You finally get in and then, you got to find what you want to do, and then you do it. And, it's a lot slower just from an elapse time standpoint than, actually not from an elapse time. So, from an initiation standpoint, getting something off your desk, it's slower. The elapse time is much more efficient. >> Jeff: Right, right. >> And so, what I think ends up happening is people default to the simple email system. It's a quick fix. And then, it starts the cycle of hell. But, I think you're making a great point about adoption. How do you improve that adoption? One of the things that ServiceNow announced this morning, is that roughly 30% improvement in performance, right. So, people complain about performance like any Cloud-based application, and it's hard. You know, when you even when you use, you know, look at LinkedIn. A lot of times, you get a LinkedIn request, and you go, "I'll check it later." You don't want to go through the process of logging in. Everybody's experienced that. It's one of those >> Right, right. >> Sort of heavy apps, and so, you just say, "Alright, I'll figure it out later." And, Facebook is the same thing. And, no doubt, that ServiceNow, certainly Salesforce, similar sort of dynamics 'cause it's a Cloud-based app. And so, hitting performance hard, as you say, the culture of leaving it on your desk. The folks at Nutanix, Dheeraj is telling me they essentially run their communications in Slack. (chuckles) and so, >> Right. >> You know, they'll hit limits there, I'm sure, as well, but everybody's trying to find a new way to work, and this is something that I know is a passion of yours, because the outcome is so much better if you can eliminate email trails and threads and lost work. >> Right. And, we're stuck now in this, in the middle phase which is just brutal 'cause you just get so many notifications from so many different applications. How do you prioritize? How do you keep track? Oh my God, did you ping me on Slack? Did you ping me on a text? Did you ping me on a email? I don't even know. The notification went away, went off my phone. I don't even know which one it came through its difficulty. The good news is that we see in sass applications and, again, it's interesting. Maybe just 'cause I was at AWS summit recently. I just keep thinking AWS, and in terms of the efficiency that they can bring to bear, that resources they can bring to bear around CP utilization, storage utilization, security execution, all those things that they can do as a multi-vendor, Cloud-based application, and apply to their Cloud in support of their customers on their application, will grow and grow and grow, and quickly surpass what most people would do on their own 'cause they just don't have the resources. So, that is a huge benefit of these Cloud-based applications and again, as the integration points get better, 'cause we keep hearin' it 'cause you got some stuff in Dropbox, you got some stuff in Google Docs, you got some stuff in Salesforce. That's going to be interesting, how that plays out, and will it boil back down to, again, how many actual windows do you have open that you work with on your computer. Is it two? Is it three? Is it four? Not many more than that, and it can't be. >> Yeah, so today here at Knowledge, it's a big announcement day. You're hearing from all the sort of heads of the businesses. Jakarta is the big announcement. That's the new release of the platform. Kingston's coming, you know, later on this year. ServiceNow generally does two a year, one in the spring summer, one in the fall, kind of early winter. And, Jakarta really comprises performance improvement, a new security capability where, I thought this was very interesting, where you have all these vendors that you're trying to interact with, and you tryin' to figure out, okay, "What do I integrate with "in terms of my third party vendors, and who's safe?" You know, and "Do they comply "to my corpoetics?" >> Right, right. >> And, ServiceNow introducing a module in Jakarta which going to automate that whole thing, and simplify it. And then, the one, the big one was software asset management. Every time you come to a conference like Knowledge, and you get this at Splunk too, the announcements that they make, they're not golf claps. You'd get hoots and woos and "Yes" and people standing up. >> Jeff: That was that and that was the one, right? >> Software SM Management was the one. >> Jeff: (chuckles) put a big star on that one. >> Now, let's talk about this a little bit because they mentioned in, they didn't mention Oracle, but this is a bit pain point of a lot of Oracle customers, is audits, software audits. >> Jeff: Right, right. >> And, certainly Oracle uses software audits as negotiating leverage, and clients customers don't really know what they have, what the utilization is, do they buy more licenses even though they could repurpose licenses. They just can't keep track of all that stuff, and so, ServiceNow is going to do it for ya. So, that's a pretty big deal and, obviously, people love that. As I said, 30% improvement in performance. And, yeah, this software asset management thing, we're going to talk to some people about that and see what their-- >> But, they got the big cheer. >> What their expectation is. >> The other thing that was interesting on the product announcement, is using AI. Again, I just love password reset as an example 'cause it's so simple and discrete, but still impactful about using AI on relatively, it sounds like, simple processes that are super high ROI, like auto-categorization. You know, let the machine do auto-categorization and a lot of these little things that make a huge difference in productivity to be able to find and discover and work with this data that you're now removing the people from it, and making the machine, the better for machine processes handled by the machine. And, we see that going all through the application, a lot of the announcements that were made. So, it's not just AI for AI, but it's actually, they call it Intelligent Automation, and applying it to very specific things that are very fungible and tangible and easy to see, and provide direct ROI, right out of the gate. >> Well, this auto-categorization is something that, I mean, it's been a vexing problem in the industry for years. I mentioned yesterday that in 2006 with the federal rules of civil procedure change that made electronic documents admissible, it meant that you had to be able to find and submit to a court of law all the electronic documents on a legal hold. And, there were tons of cases in the sort of mid to late part of the 2000's where companies were fined hundreds and millions of dollars. Morgan Stanley was the sort of poster child of that because they couldn't produce emails. And, as part of that, there was a categorization effort that went on to try to say, okay, let's put these emails in buckets, something as simple as email >> Right, right. >> So that when we have to go find something in a legal hold, we can find it or, more importantly, we can defensively delete it. But, the problem was, as I said yesterday, the math has been around forever. Things like support vector machines and probabilistic latent semantic index and all these crazy algorithms. But, the application of them was flawed, and the data quality >> Jeff: Right, right. >> Was poor. So, we'll see if now, you know, AI which is the big buzz word now, but it appears that it's got legs and is real with machine learning and it's kind of the new big data meme. We'll see if, in fact, it can really solve this problem. We certainly have the computing horse power. We know the math is there. And, I think the industry has learned enough that the application of those algorithms, is now going to allow us to have quality categorization, and really take the humans out of the equation. >> Yeah, I made some notes. It was Farrell, her part of the keynote this morning where she really talked about some of these things. And, again, categorization, prioritization, and assignment. Let the machine take the first swag at that, and let it learn and, based on what happens going forward, let it adjust its algorithms. But, again, really simple concepts, really painful to execute as a person, especially at scale. So, I think that's a really interesting application that ServiceNow is bringing AI to these relatively straightforward processes that are just painful for people. >> Yes, squinting through lists and trying to figure out, okay, which one's more important, and weighting them, and I'm sure, they have some kind of scoring system or weighting system that you can tell the machine, "Hey, prioritize, you know, these things," you know, security incidence >> Right, right. >> Or high value assets first. Give me a list. I can then eyeball them and say, okay, hm, now I'm going to do this third one first, and the first one second, whatever. And, you can make that decision, but it's like a first pass filter, like a vetting system. >> Like what Google mail does for you, right? >> Right. >> It takes a first pass. So, you know, these are the really specific applications of machine learning in AI that will start to have an impact in the very short-term, on the way that things happen. >> So, the other thing that we're really paying attention here, is the growth of the ecosystem. It's something that Jeff and I have been tracking since the early days of ServiceNow Knowledge, in terms of our early days of theCUBE. And, the ecosystem is really exploding. You know, you're seeing the big SIs. Last night, we were at the Exen Sure party. It was, you know, typical Exen Sure, very senior level, a bunch of CIOs there. It reminded me of when you go to the parties at Oracle, and the big SIs have these parties. I mean, they're just loaded with senior executives. And, that's what this was last night. You know, the VIP room and all the suits were in there, and they were schmoozing. These are things that are really going to expand the value of ServiceNow. It's a new channel for them. And, these big SIs, they have the relationships at the board room level. They have the deep industry expertise. I was talking to Josh Kahn, who's running the Industry Solutions now, another former EMCer, and he, obviously, is very excited to have these relationships with the SI. So, that to me, is a big windfall for ServiceNow. It's something that we're going to be tracking. >> And, especially, this whole concept of the SIs building dedicated industry solutions built on SI. I overheard some of the conversation at the party last night between an SI executive, it was an Exen Sure executive, and one of the ServiceNow people, and, they talked about the power of having the combination of the deep expertise in an industry, I can't remember which one they were going after, it was one big company, their first kind of pilot project, combined with the stability and roadmap of ServiceNow side to have this stable software platform. And, the combination of those two, so complementary to take to market to this particular customer that they were proposing this solution around. And then, to take that solution as they always do and then, you know, harden it and then, take it to the next customer, the next customer, the next customer. So, as you said, getting these big integrators that own the relationships with a lot of big companies, actively involved in now building industry solutions, is a huge step forward beyond just, you know, consultative services and best practices. >> Well, and they have such deep industry expertise. I mean, we talked yesterday about GDPR and some of the new compliance regulations that are coming to the banking industry, particularly in Europe, the fines are getting much more onerous. These SIs have deep expertise and understanding of how to apply something like ServiceNow. ServiceNow, I think of it as a generic platform, but it needs, you know, brain power to say, okay, we can solve this particular problem by doing A, B, C, and D or developing this application or creating this solution. That's really where the SIs are. It's no surprise that a lot of the senior ServiceNow sales reps were at that event last night, you know, hanging with the customers, hanging with their partners. And, that is just a positive sign of momentum in my opinion. Alright, Jeff, so big day today. CJ Desai is coming on. We're going to run through a lot of the business units. You know, tomorrow is sort of Pronic demo day. It's the day usually that Fred Luddy hosts, and Pat Casey, I think, is going to be the main host tomorrow. And, we'll be covering all of this from theCUBE. This is day two ServiceNow Knowledge #Know17. Check out siliconangle.com for all the news. You can watch us live, of course, at thecube.net. I'm Dave Vellante, he's Jeff Frick. We'll be right back after this short break. (easygoing music)

(exciting, upbeat music) >> (Announcer) Live from Orlando, Florida. It's theCUBE, covering ServiceNow Knowledge '17. Brought to you by ServiceNow. >> We're back. Dave Vellante with Jeff Frick. This is theCube and we're here at ServiceNow Knowledge '17. Stanley Toh is here, he's the Global IT Director at semiconductor manufacturer Broadcom. Stanley, thanks for coming to theCUBE. >> Nice to be here. >> So, semiconductor, hot space right now. Things are going crazy and it's a good market, booming. That's good, it's always good to be in a hot space. But we're here at Knowledge. Maybe talk a little bit about your role, and then we'll get into what you're doing with ServiceNow. >> Sure. You're right. Semiconductor is booming. But we don't do anything sexy. Everything is components that go into your iPhones and stuff like that. They do the sexy stuff. We do the thing that make it work. So, I'm the what we call the Enterprise and User Services Director, so basically anything that touches the end user, from the help desk to collaboration to your PC support desk, everything is under. Basically anything that touches the end user, even onboarding, and then, now with the latest, we actually moved our old customer support portal to even ServiceNow CSM. >> Okay, so what led you to ServiceNow? Maybe take us back, and take us through the before and the after. >> Okay. Broadcom Limited, before we changed our name to Broadcom, we were Avago Technologies. We are very cloud centric. Anything that we can move to the cloud, we moved to the cloud. So we were the first multi-billion dollar company to move to Google, back in 2007. That was 10 years ago. And then we never stopped since. We have Opta, we have Workday. And if you look at it, all this cloud technology works so well with ServiceNow. And ServiceNow is a platform that has all the API and connectors to all these other cloud platforms. So, when we were looking and evaluating, first as just the ITSM replacement, we selected ServiceNow because of the ease of integration. But as we get into ServiceNow, and as we learn ServiceNow, we found that it's not just an ITSM platform. You can use it for HR, for finance, for legal, for facilities. Recently, probably about six months ago, we launched the HR module. And then three weeks ago, we went live with a CSM portal for the external customer. >> When you say you go back to 2007 with Google, you're talking about what, Google Docs? >> Everything. >> Dave: Everything. >> Email, calendar, docs, sites, Drive, but it was unknown. >> Dave: All the productivity stuff. >> Everything. >> Dave: Outsourced stuff. >> They were unknown then, >> Jeff: Right, right, right. >> And it's a risk. >> So what was the conversation to take that risk? Because obviously there was a lot of concern at the enterprise level on some of these cloud services beyond test/dev in the early days. Obviously you made the right bet, it worked out pretty well. (Stanley laughing) But I'm curious, what were the conversations and why did you ultimately decide to make that bet? >> Okay. So 2007 was just after the downturn. >> Jeff: Right. >> So everyone was looking at cost, at supportability. But at the same time, the mobile phone, the smart phone is just exploding in the market. So we want something that is very flexible, very scalable, and very easy to integrate, plus also give you mobility. So that's why we went with Google as the first cloud platform, but then we started adding. So right now, we can basically do everything on your smart phone. We have Opta as our single sign-on. From one portal, I go everywhere. >> Dave: Okay, so that's good. So you talked about some of the criteria for the platform. How has that affected how you do business, how you do IT business? >> See, IT has always been looked upon as a cost center. And we are always slow, legacy system, hard to use, we don't listen to you. (Jeff laughing) >> Dave: What do those guys do? >> You know, why are we paying those guys, right? And then you look at all the consumer stuff. They are sexy, they are mobile, they have pretty pictures. Now all your internal users want the same experience. So, the experience has changed. The old UNIX command key doesn't work anymore. They want something touch, GUI, mobile. They want the feel, the color, you know. >> That might be the best description (Stanley laughing) of the consumerization of IT, Dave, that we've ever had on theCUBE. >> It's really honest. Coming from an IT person, it is, it is honest. And now you've driven ServiceNow into other areas beyond IT. >> Stanley: Yes. >> You mentioned HR. >> HR. We went live six months ago. >> Okay. And these other areas, are you thinking about it, looking at it, or? >> So we are also looking with legal, because they have a lot of legal documents and NDAs and stuff like that. And ServiceNow have a very nice integration to DocuSign and Vox. So we are looking at that. But the latest one, we went live three weeks ago, is the CSM, the customer support management portal. And that one actually replaced one of our legacy system that has a stack of sixteen application running. And we collapsed that, and went live on ServiceNow CSM three weeks ago. >> And what has been, two impacts - the business impact, and, I'm curious, is it the culture impact. You sort of set it up as the attitude. We had fun with it, but it's true. What's the business impact? And what has the cultural impact been? >> The last few years, we have been doing a lot of acquisition. So we have been bringing in a lot of new BU's. Business units. And they want things to move fast, and we want to integrate them into one brand. So speed and agility is key when you do acquisitions. So that's why we are moving into a platform where we can integrate all these new companies easily. We found that in ServiceNow and we can integrate them. So for example, when we acquired Broadcom Corporation, they have 18,000 employees. We onboarded them on day one, and usually when you do an acquisition, they don't give you the employee information until the last minute. Two days, all I need, is to bring them all on, onboarded into my collaboration suite. I only need two days of the information, and on day one, Turn it on, they are live. Their information is in, they have an email account. All their information is in ServiceNow. They call one help desk, they call our help desk, they get all the help and services. So it's fully integrated on day one itself. >> And you guys also own LSI now, right? >> Yes, LSI. >> Emulex? >> Emulex, PLX. >> PLX. >> The latest acquisition is Brocade, which we will close in the summer. And then, the rumored Toshiba NAND business. So, yeah, we are doing a lot of acquisitions. >> Yeah, quite a roll-up there. >> Correct. So as you can see, they are all very different companies. So when they come in, they have different culture. They have different workflow, they have different processes. But if you integrate them into a platform that we are very familiar right now, it's the consumerized look and feel, it's very easy to bring them in. >> And that is the cultural change that has occurred. >> Yes, it's a huge, >> So do people love IT now? >> They still hate IT. (Jeff and Dave laughing) They still say iT is a cost center. But right now, they are coming around. They see that we are bringing value to them. So right now, IT is just not to provide you the basic. IT is to enable the business to be better and more competitive. >> A true partner for the business. >> Yes, correct. >> Stanley, thanks very much for coming to theCUBE. It was great to hear your story, we appreciate it. >> Stanley: Thanks for having me. >> You're welcome. All right, keep it right there, buddy. We'll be back with our next guest. This is theCUBE, we're live from ServiceNow Knowledge '17. We'll be right back. (upbeat music)

>> Announcer: Live from Las Vegas, it's the Cube! Covering NAB 2017, brought to you by HGST. >> Hey welcome back everybody Jeff Rick here with The Cube, We are getting towards the end of day three at NAB 2017, and we've talked to a ton of people from security, and storage, and applications, and now we get to talk to a creator. And really excited to have Victoria Nece on, she's a project manager for adobe After Effects, welcome. >> Thank you it's great to be here. >> Absolutely, been getting a little background on you, you were just really an animator and Adobe was smart enough to say "Hey this girl's got her shit together, we should bring her inside and have her help with the team at a bigger level." Instead of all the little things you were doing. >> Yeah so I was a motion designer mostly for documentary for a long time. And I got really into writing my own scrips and extensions and I used to say I like to make After Effects do stuff it wasn't supposed to do, and now it's my job to help make it do those things. >> Okay so what are some of the new things you said that you know, luckily we're past the official release date, you can actually talk about things >> Yes. >> So what are some of the new things? >> Uh, so we have a great new release, just came out last week, last Wednesday we're super proud of it, it's available to anyone who has creative cloud subscription. And a big thing, and this is across After Effects and Premier, is a new thing called the essential graphics panel. It allows you to make really elaborate- anything you want to do in After Effects you can go fully advanced motion graphics, and then choose the properties in editor you want to be able to change. So I can say, I'm designing something but it's on brand, I don't want you to change the color, but you can change the text, you can reposition something on the screen, we can change the background color, do all of those kind of things, and I can add those controls in After Effects and when I save those as a motion graphics template, it gets packed up and someone can use it in Premier and change those things live in the timeline with no rendering, so. >> It's really interesting just the whole collaboration, you know, kind of aspect. It used to be so much, you know, an individual sitting down on their hopefully very big machine with a lot of memory and compute, you know, working on Adobe. But now, it's really more of a collaborative effort. There's not a lot of people just working independantly all by themselves on the machine. >> True. >> Especially with Cloud and some of these really higher performance applications. >> Yeah it's actually been really interesting to watch what's happened. We have a beta service called Team Projects and I've been doing press demos where I'm in Seattle and one of my colleagues is in Germany and we're collaborating live on the same projects, I'm on After Effects, he's in Premier, I make a change, it shows up right in his timeline he doesn't even have to open After Effects, doesn't have to import anything, and it's all really seemless. And we've actually, we've all been collaborating the whole time but now you can do it without all those extra steps of rendering, and sending a file, and downloading the file, and importing it, and then adding it. Now that can all just happen in one click. >> It's like Google Docs versus Word. >> Yeah, right. >> Save and attach a file and send, hopefully you remember to save the file. >> Alright and the other thing you're really excited about is character animator. >> Yes. >> So what's going on there? >> So for people who don't know, character animator is a new application from the original creators of After Effects. It's a separate application that allows you to do real time live animation using your webcam and your microphone and also even use a touch screen, keyboard, mouse, basically hardware you already have, to power a character that starts off as a Photoshop or Illustrator file, and character animator brings it to life. We've seen some really amazing stuff people are doing with it. >> So real time live animation, so that seems like completely impossible, cause back in the day that's all we would hear about, is you know you have to render render render render render to get this animations stuff going. But now you're saying you've got it broken down so that we can do it live. >> There's this great line from The Simpsons that animation is rarely done live, it's a terrible strain on the animators wrists, and we're working to change that (laughs). It's a lot of fun and also you look at the screen and your character looks back at you, it's this really amazing experience working in it. And we've been working to make it easier to use, easier to get started, we've added workspaces so now it actually walks you through the process of getting characters set up and rigged and then a different space for performing. But it's, character animation's fun. >> And then now you're bolting that onto all these various live video distribution services. >> Mhm, we've added Mercury transmit support, which means you can go out to broadcast hardware, you can connect to absolute stream, to Facebook live, Youtube live, we're seeing things like Steven Colbert's The Late Show they use character animator to do cartoon Trump and he's improving live with a cartoon character and it's all happening in real time. >> (laughs) So as you look back and this is all fascinating and it's great, now you've got the power of the whole company to kind of make many of your visions come true. Where does it go next? It just seems like the creative opportunity, or the tools for the creator, are just exploding. >> I think there's a lot of cool stuff we can do, but for me one of the biggest things is anything we can do to save people time, and to save people doing the boring stuff, I want to give people more space to create. >> Right. >> So, don't have to think about verging, you don't have to think about all those outputs, but all the stuff about- get that out of the way, get the data entry out of the way so you can actually focus on the stuff you really want to be doing. >> And what about 360 and VR and all those crazy new technologies which are all over these halls. >> It's everywhere. Premier's got some really cool stuff this release, they've got Ambisonic audio so you can actually do VR, 360 footage and the sound comes from the right place in the shot as you turn your head. >> Ambisonic v- >> Ambisonic audio. >> Ambisonic audio. >> So there's some really cool stuff happening there. And then on the After Effects side we have some amazing partners who have been doing super cool stuff with VR, their tools are really evolving, and it's a really nice seemless workflow working with them. >> (laughs) So where does it go next? >> Oof. >> Anywhere, right? >> Anywhere really. >> No it's just amazing how again these tools that really put everything in the power of basically anybody's hands. It's kind of this whole democratization theme which we continue to hear over and over again. >> We've really focused a lot on trying to get just the tools you need right now to get you most of the way there, super simple, and then when you need to go deep, you can go deep. We're not limiting you to the simple tools, but everything's right in context, right in front of you, the stuff you change the most is right there. And then when you need to go in and tweak and get to the pro level it's another step down. And so we're trying to really build that kind of a workflow so that you have sound and graphics and color all right in edit and then you have the big pro apps for when you need to do the fancy stuff. >> The heavy lifting. And I wonder, Victoria, you talked about the community, cause Adobe's got a really active community, you guys have a huge show that brings everybody together, you obviously came out of that community into the mothership. How important is this, you know, kind of an active community around the creative process, tools you mentioned you even wrote your own scripts. >> Mhm it's, I love the After Effects community in particular they're my friends and a show like this, I see people I have really great friends that I only see once or twice a year at these kind of shows, but it's such a great strong global community that we stay in touch throughout the year, and our users really drive where we're going with things. A lot of the features in this release of After Effects, I could tell you by name who's been asking for them for years and who's super excited to see something in there. >> Okay, so if I see you again in 2018 can you give us a hint as to maybe what we'll see? Don't get in trouble. >> I might get in trouble. But we've got some really cool stuff under way. >> Alright, well we'll keep an eye, and you guys over on the table, you got to learn how to do this talking creative animator thing. I could think of some people that we might want to chin up not the real Donald Trump, but some other people. (laughs) >> Alright Victoria, well thanks for spending a few minutes with us and again, congrats on the new relase. >> Thank you, it's really great to be here. >> Alright Victoria Nece, I'm Jeff Rick you're watching the Cube from NAB 2017. Thanks for watching.

>> Narrator: Live from Las Vegas it's The Cube covering Interconnect 2017. Brought to you by IBM. >> Okay welcome back everyone. We are live at the Mandalay Bay for IBM Interconnect 2017, The Cube's exclusive coverage. I'm John Frower, Dave Vellante, my co-host. Our next guest is Jim Casey and Michael Gilfix. Michael's the VP of process transformation and Jim is offering manager at IBM. Guys, welcome back to The Cube. >> Both: Thank you. >> So you guys had a big announcement on Monday, the digital assistant, so I've been craving a digital assistant since the little Microsoft little, you know, icon would pop up. >> Michael: You're talking about Clip, aren't you? >> The clip man. >> Don't talk about that. >> We don't like that. >> To me that was once called the digital assistant. It was a help button, but this is now, digital assistant is real automation, and you guys got a whole other take on this. It's totally cloud, cloud first. What's the digital assistant product that you announced? Take us through that. >> So here was our vision. What we found was in the modern, digital workplace, everyone is struggling to just keep up pace. Too many sources of information, and the information is buried everywhere. It's buried in emails, in spreadsheets, in documents. Many corporations have undertaken a BI project. In fact, there's an explosion of all these different dashboards that has all kinds of business data that they could go and see, so no one has the time to read all these things. Meanwhile, everyone in the modern world is trying to do 50 things at once and it's hard to figure out what is the best time to progress something and make progress? Our vision, so what we thought is wouldn't it be great if I could program this assistant, programmable by everyday business users, to watch for the things that matter to me and figure out when I should take action or take automated action on my behalf to save me time. >> So it's an interface, so it's software interface, cloud-based SAS, and the back end, does the user have to, what's the persona of the user that's using your product? >> Well, we want them to be used by non-developers, non-technical users, and so we thought really carefully about how you can teach your assistant these notions of skills, really point to tasks that can really make your life easier on a daily basis and they can pick anything that they like working with, that they can connect to, get the information from, and effectively assemble into these point-to tasks. >> Host: And the data sources are whatever I want them to be, explain how that works? >> Yeah, it can connect to common SAS applications. Those could be things like productivity suites, like G-Suite, they can be things like CRM systems, like Sales Force, campaign management systems like Marketo, and that's just in the beta that we just launched. And of course in the future, they'll be able to connect into their on-premise systems as well. >> So is it to replace the dashboards and all the wrangling that goes on? Most business users will have either a department that does all the data science or data prep for them, wrangling data sets, and then they get reports or spreadsheets or some BI dashboard. >> Yeah, we wanted the assistant to push the work to the user instead of the user having to go and spend time watching all these dashboards that really, they just didn't have time to do. And so the assistant takes all the heavy lifting of watching the data for you, figures out when action is needed, and then taps you on the shoulder. >> So Ginny Ramete was talking about that your customers want to own the data. So that's a great purpose, we buy into that mission, but a lot of the data is spread all over the place, so one of the problems that we're seeing in the big data world, now IOT complicates even further, is that data's everywhere, scattered, and the tools might have stacks and data wrangling within tools so you have complexity out there just on the scaffolding of how the data's managed. Is that part of the problem that you guys help solve? Because that seems to be a pain point. >> Yeah, and I think the amount of time that people spend just searching and aggregating and gathering information so they can figure out what to do, it's staggering. And when you think about the, it takes about two the three hours often for people to gather all the information that they need in order to make a real significant decision, every day, daily, you know operations. You're spending time in your email, you're building spreadsheets. Think of all the time you spend building a spreadsheet, wrangling data, you know. It's a productivity killer, and so a lot of the use cases that we look for, we'll ask our clients show me the ugliest spreadsheet that you use on a day-to-day basis for business operations. That's usually a starting point, or show me how many dashboards are you looking at and what are the decision you make off that? That's the stuff that we want to collapse into what the assistant can provide. >> So I got a use case for you, I'm a walking, I'm like everybody, right, so I've got my email, I've got five or six spreadsheets, Google Docs that I'm in every day all day, maybe there's a base camp, maybe there's a slack. I'm in Sales Force, all right, and then I got my social. >> Tool overdose. >> You just described the typical modern environment. All fragmented tools. >> And I'm in there and I'm like which browser is it, oh is it in Firefox, I'll put my Safari stuff I'll put over here, and I'll put my email in Mozilla, okay. It is just awful, it's a bloody nightmare, I get lost. I got to back up, hit the escape key, and go, okay, where am I, how do I find it again? >> Jim: It's connecting the dots. >> Okay, explain now how you can help me. >> So think of the things that you're looking for in all those different data sources. We're seeing the trend now. It's not about how can I just connect with things, it's how can I connect the dots? It's the actual business data inside of there, and how do I put that in a context that's relevant to you, what you're trying to do? You know, and a great example, we're working with one client who, they're moving, and a lot of people are doing this, they're moving from a point in time sale to being as a service, and in that kind of scenario, relationships with your clients really matter. And preventing customer churn is really important. So they have people who are responsible for making sure that people are not going to churn. That's a lot of dots to connect, right? So with the Digital Business Assistant, what we do is we look for those patterns that are really common that predict churn, but those things are scattered across your sales systems, your marketing systems, the website traffic, social media even, and we're able to combine all those things into a really consumable component called a skill. And then that individual person that's responsible for this set of customers can tailor it to their needs. So it's kind of like how you would buy a suit. When you go in and buy a suit, you don't get just the fabric laid out on a table and they cut it, right? You, most people don't anyway. (they laugh) >> I buy what's on the rack. I say "I want that one." >> Yeah, you walk in and you say that. >> I want what that is. >> 42 long, right? And they make a couple adjustments and then it's yours. >> All right, I'll take that suit up there, what's on the mannequin. >> They make a few adjustments and it's yours. Software should be the same way. You should be able to configure software in a few clicks. >> That's the whole thing, I mean, I joke about the mannequin but that's really kind of what hangs the perfect use case so that would be an automated example of an assistant model for you guys. Sometimes you just want everything to hang together for you, and sometimes you might want to go in and go look at the data. >> Yeah, and we see this across a lot of different industries, so things like customer service and sales and marketing, but we also see it in, let's say I'm a field technician, right? And I got to go out to an oil field. How do I know all the different patterns of information that might predict whether or not I need to, what I need to do when I'm out there. >> So you monitor my patterns, my behavior, and then ultimately train the model, or? >> Well you program it. You tell it what to watch for for you. So to give you an example of the kind of use case, to pick a specific use case, and we shared this again in sort of our unveiling on Monday. We shared the idea of a sales rep who is pursuing a given opportunity, and thinking about all the factors that went into their success and, you know, that sales rep has several different things they need to use to really maximize their chance of closing that deal. So one is they need to be responsive do their customer, and you know, like many different corporations out there who sell many different products and services, while you're busy working on the new opportunity, you've got to service the old. So when some issue comes up, you have to be responsive to it. Well, it's really hard while you're busy working on all these opportunities, to make sure that the issue's being resolved, that you're being responsive to your customer. Meanwhile, everybody in the corporation is coming up with new opportunities, new marketing brochures, new values in the product. And so is your rep knowledgeable about the latest and greatest products? So we imagine that you could teach your assistant how to watch some of this stuff for you and really help you to close your opportunity. And a very pointed example of the kinds of things that it should watch for you, I should be able to say something like hey, if I can have an active opportunity and then my customer goes and opens a service support ticket and that service support ticket hasn't been resolved in a week and meanwhile, I got a bunch of email coming from that client, of tone angry, notice the cognitive part there, about this particular product, and meanwhile I'm on the road and I'm not checking my email. Well, I have a catastrophe waiting to happen. So I can program my assistant to watch for these kinds of things. >> Does it do push notifications? >> Exactly, so you can then have it push to you, look, here's all the information about the active service thing, here's how long it was sitting there waiting for resolution, this is what's happened since, and you can immediately take action. >> So you're orchestrating basically signals that the user connects, like a Google alert on search is a trivial example, right? Someone types, a result comes on Google, you get an email. Here, you're kind of doing that-- >> But it's proactive. You tell your assistant to proactively watch it for you, and that's a unique technology that we developed in-house. Because it's watching all these events happening in the enterprise and figuring out when that thing becomes actionable. >> And the user would know where to look, because like Dave's spreadsheet might say "hey, cash balance" or you know, sales trend, this rep and then something happens, and he can get that pushed to him from three different disparate side-load apps, that's pretty much what it is. >> That's right. >> Okay, so give us the status on the beta right now. It's a beta, so it's sign-up required. Okay, and the requirements to implement it, if you get through the beta, is just log in to a portal? It's a SAS model and then do the connectors? >> So the first thing you do, you go to IBM.com/assistant. You can sign up to. >> That, by the way, might be the easiest URL I think we ever came up with. I'm pretty sure that one's going to be memorable. >> Yeah, so you just go to that site, you sign up, you give us a little bit of information, your email, how to contact you and we'll put you on the waiting list, and what we're going to be doing is opening up more seats as we go through over the next couple weeks, and then we plan in the near term here to make it available as an open beta that you could see, and you'll see that inside of Bloomix as a tile inside of Bloomix. >> And here's the thing, we're doing something really different in the marketplace. This is a very different kind of offering, really targeting, again, non-technical people, this proactive situational awareness that your assistant can do, uses your data, built-in intelligence, intelligence that can customize to the way you work, guide you to the next best action. We have an incredible vision for this. The idea behind the beta is to start getting feedback. We worked very closely with early customers in the initial design and development. We want to open that up and get even more feedback and ideas on this kind of technology. >> So how is this different from Watson's discovery services that they have? I can imagine that you're building on Watson. Is it the cognitive piece within IBM, or is this kind of, I mean how would a customer figure that out, or just more of a-- >> Yeah, so I can give you an example. So we have one of our prototypes that we're actually taking some of the components of Watson discovery service and we package that up as a skill inside of your assistant, and it's a specific implementation, so what it allows you to do in this case is it'll look at your email and it'll look for specific entities, like a customer that matters to you, and if I get three emails of negative sentiment from a customer where I also have an open opportunity in the last week, that's a pattern I want to know about, right? Or we can start to correlate with all sorts of different things, so I think what you're going to see is these skills that we make available with the digital business assistant really up, take consumability of these really, really powerful technologies around cognitive and cloud. We take that to the next level. >> That's the key, how do we make Watson tailorable and put in the hands of every knowledge worker in every company? >> Host: So I presume you guys are dog fooding this personally, is that right? >> We have plans to do that, yes. >> Host: Oh, you haven't started yet? >> Sampling our own champagne. >> But we are, yes. >> He always gets called on that. >> We will be using it, yes. >> We created that champagne. >> We're beer drinkers, that's it, beer. >> We're going back to dog food, we eat beer, we should drink our own beer now. We created that with all our boost men, remember? (laughs) >> So get back to the status of the product. So it's got some Watson capability, but this is for the user to use. I don't have to get IT involved? >> Jim: That's right. >> This is where the user takes a personal productivity approach, and you bring in some Watson-- >> A user may not even know that they're using some of these Watson capabilities. To the end user, what do you want it to do for me? Well, I want it to tell me if, uh, if I think a customer might be upset with me. Well, that might be a combination of a lot of different things, but it just makes it really consumable and easy for people. >> So where do you guys sit within IBM? Because now there's like, because this is a really cool user tool, so is this part of Watson? >> Jim: We think so. >> Is it part of the Watson team? >> Well, honestly our organization doesn't really matter, I mean, we're working with teams across IBM as a whole. It's a great opportunity to take this technology and really reach a whole set of new use cases, I think, across the company, and we want to integrate Watson technology to, like we were saying, really make it easy for the end-user to go and access it. >> Any plans around developer outreach? >> Well, we will, I think, later this year, one of the things we envisioned really early on is that people are going to want to have pre-built skill sets, and that's a great opportunity to build an incredibly powerful ecosystem and we've been in discussion with a lot of our partners about how to do that. >> Well you guys are API based, so this is a beautiful thing, right? >> Well we're going to start to open up some SDKs to our partners, to others, and that's going to allow them to extend the assistant and really create even more powerful industry content. >> You know, the business model of reducing the steps it takes to do something and saving people time, making it easy to use is a magical formula of success. >> And not even just less steps, it's less time reading things, less time sifting through information so you can spend time on stuff that matters. >> Just email by itself, I mean, Dave, your example was the best, because I know, we live that. But we have a multitude of tools and sometimes it just organically goes, because the one guy like, you know, this tool set, or now I got-- >> So do you want to do the deal now or? >> Right, that's what I'm saying, they should be signing up. >> So do we get paid? (they laugh) >> We're already both signed up. We have a testimonial. >> If you can't get it, how can we get it? >> We'll kick the tires on it, and uh, but the thing that gets my excitement is potential for API integration. Because if I know I can the automation to a whole other level and the use cases start to patternize in the enterprise, then it can get interesting. All right guys, thanks so much. What's going on here with the show, what else is happening for you guys? Share some stories for the folks that aren't here, that are watching on IBM Go right now. What's the vibe at the show this week? >> Well, it's been a great vibe. We've had a chance to share some incredible success stories, so in addition to the unveiling of this particular product, on Monday we had a chance for one of our marquee clients to share their story, and I'll tell you a little bit about what they did. It was at the National Health Service of the UK. Part of their blood and transplant, and we were fortunate enough to have Aaron Powell, who's the chief digital officer there, share their story of using process technology to improve the speed at which they get organs in the hands of recipients, and they did it on the cloud. And the results they obtained were unbelievable. So the before and after, they had staff at 2am, writing lists of high-risk patients and how to map their donors and he kidded us not, that when someone's priority changes, they would wipe the board and reset things. And these are people's lives that are at stake in the matching process. >> And they're tired, human error is huge. >> Human error, absolutely, and by the way, when you look at the end-to-end process, there was something like 90 steps if I remember, 96 steps I think end-to-end. All of which were very manual and error-prone, and error-prone means risk. And they were able to improve organ allocation by 3x, so 3x faster, they automated something like 58% of the steps, reducing propensity for manual error, and what he shared in his story is, they successfully a few months ago did the first heart transplant on the cloud. >> Host: Wow, that's amazing. >> So it's an amazing, amazing story. >> That's a great story, yeah. Did he say that in the session? >> He did, actually, he said that. >> That's actually a good thing to chase down for a great blog post, that would be phenomenal. It would have been covered yet on the news? >> So we're going to post actually the video of it online so people can also see him live presenting his story, it was unbelievable. >> Make sure you send me the link. The other thing that they could apply there is two-block chain, I mean some of the block chain stuff coming out is going to be really interesting. >> Absolutely, and we're working very closely with that team to really leverage this kind of process technology, take people's business operations and connect that in to this feature network that's going to power businesses. >> CRM is the human supply chain, I mean, but now extend it out to the internet of things. I mean, it's interesting how this could play out. Guys, thanks so much for coming on The Cube. Thanks for sharing the insight, congratulations on the launch. I just signed up for the beta while we were talking. >> Dave: Me too, so let us cut the line. >> Done. >> We need it. Perfect use case, we need help. It's The Cube, of course, no help here, great guests here on The Cube. I'm John Frower, Dave Vellante, more great coverage, stay with us. Day three of Interconnect 2017, we'll be right back. (techno music)