(upbeat music) >> Hello, and welcome to "theCUBE" conversation here in Palo Alto, California. I'm John Furrier, host of "theCUBE," got a great security conversation, Ed Casper who's the founder and CEO of Cloud Storage Security, the great Cloud background, Cloud security, Cloud storage. Welcome to the "theCUBE Conversation," Ed. Thanks for coming on. >> Thank you very much for having me. >> I got Lafomo on that background. You got the nice look there. Let's get into the storage blind spot conversation around Cloud Security. Obviously, reinforced has came up a ton, you heard a lot about encryption, automated reasoning but still ransomware was still hot. All these things are continuing to be issues on security but they're all brought on data and storage, right? So this is a big part of it. Tell us a little bit about how you guys came about the origination story. What is the company all about? >> Sure, so, we're a pandemic story. We started in February right before the pandemic really hit and we've survived and thrived because it is such a critical thing. If you look at the growth that's happening in storage right now, we saw this at reinforced. We saw even a recent AWS Storage Day. Their S3, in particular, houses over 200 trillion objects. If you look just 10 years ago, in 2012, Amazon touted how they were housing one trillion objects, so in a 10 year period, it's grown to 200 trillion and really most of that has happened in the last three or four years, so the pandemic and the shift in the ability and the technologies to process data better has really driven the need and driven the Cloud growth. >> I want to get into some of the issues around storage. Obviously, the trend on S3, look at what they've done. I mean, I saw my land at storage today. We've interviewed her. She's amazing. Just the EC2 and S3 the core pistons of AWS, obviously, the silicons getting better, the IaaS layers just getting so much more innovation. You got more performance abstraction layers at the past is emerging Cloud operations on premise now with hybrid is becoming a steady state and if you look at all the action, it's all this hyper-converged kind of conversations but it's not hyper-converged in a box, it's Cloud Storage, so there's a lot of activity around storage in the Cloud. Why is that? >> Well, because it's that companies are defined by their data and, if a company's data is growing, the company itself is growing. If it's not growing, they are stagnant and in trouble, and so, what's been happening now and you see it with the move to Cloud especially over the on-prem storage sources is people are starting to put more data to work and they're figuring out how to get the value out of it. Recent analysts made a statement that if the Fortune 1000 could just share and expose 10% more of their data, they'd have net revenue increases of 65 million. So it's just the ability to put that data to work and it's so much more capable in the Cloud than it has been on-prem to this point. >> It's interesting data portability is being discussed, data access, who gets access, do you move compute to the data? Do you move data around? And all these conversations are kind of around access and security. It's one of the big vulnerabilities around data whether it's an S3 bucket that's an manual configuration error, or if it's a tool that needs credentials. I mean, how do you manage all this stuff? This is really where a rethink kind of comes around so, can you share how you guys are surviving and thriving in that kind of crazy world that we're in? >> Yeah, absolutely. So, data has been the critical piece and moving to the Cloud has really been this notion of how do I protect my access into the Cloud? How do I protect who's got it? How do I think about the networking aspects? My east west traffic after I've blocked them from coming in but no one's thinking about the data itself and ultimately, you want to make that data very safe for the consumers of the data. They have an expectation and almost a demand that the data that they consume is safe and so, companies are starting to have to think about that. They haven't thought about it. It has been a blind spot, you mentioned that before. In regards to, I am protecting my management plane, we use posture management tools. We use automated services. If you're not automating, then you're struggling in the Cloud. But when it comes to the data, everyone thinks, "Oh, I've blocked access. I've used firewalls. I've used policies on the data," but they don't think about the data itself. It is that packet that you talked about that moves around to all the different consumers and the workflows and if you're not ensuring that that data is safe, then, you're in big trouble and we've seen it over and over again. >> I mean, it's definitely a hot category and it's changing a lot, so I love this conversation because it's a primary one, primary and secondary cover data cotton storage. It's kind of good joke there, but all kidding aside, it's a hard, you got data lineage tracing is a big issue right now. We're seeing companies come out there and kind of superability tangent there. The focus on this is huge. I'm curious, what was the origination story? What got you into the business? Was it like, were you having a problem with this? Did you see an opportunity? What was the focus when the company was founded? >> It's definitely to solve the problems that customers are facing. What's been very interesting is that they're out there needing this. They're needing to ensure their data is safe. As the whole story goes, they're putting it to work more, we're seeing this. I thought it was a really interesting series, one of your last series about data as code and you saw all the different technologies that are processing and managing that data and companies are leveraging today but still, once that data is ready and it's consumed by someone, it's causing real havoc if it's not either protected from being exposed or safe to use and consume and so that's been the biggest thing. So we saw a niche. We started with this notion of Cloud Storage being object storage, and there was nothing there protecting that. Amazon has the notion of access and that is how they protect the data today but not the packets themselves, not the underlying data and so, we created the solution to say, "Okay, we're going to ensure that that data is clean. We're also going to ensure that you have awareness of what that data is, the types of files you have out in the Cloud, wherever they may be, especially as they drift outside of the normal platforms that you're used to seeing that data in. >> It's interesting that people were storing data lakes. Oh yeah, just store a womp we might need and then became a data swamp. That's kind of like go back 67 years ago. That was the conversation. Now, the conversation is I need data. It's got to be clean. It's got to feed the machine learning. This is going to be a critical aspect of the business model for the developers who are building the apps, hence, the data has code reference which we've focused on but then you say, "Okay, great. Does this increase our surface area for potential hackers?" So there's all kinds of things that kind of open up, we start doing cool, innovative, things like that so, what are some of the areas that you see that your tech solves around some of the blind spots or with object store, the things that people are overlooking? What are some of the core things that you guys are seeing that you're solving? >> So, it's a couple of things, right now, the still the biggest thing you see in the news is configuration issues where people are losing their data or accidentally opening up to rights. That's the worst case scenario. Reads are a bad thing too but if you open up rights and we saw this with a major API vendor in the last couple of years they accidentally opened rights to their buckets. Hackers found it immediately and put malicious code into their APIs that were then downloaded and consumed by many, many of their customers so, it is happening out there. So the notion of ensuring configuration is good and proper, ensuring that data has not been augmented inappropriately and that it is safe for consumption is where we started and, we created a lightweight, highly scalable solution. At this point, we've scanned billions of files for customers and petabytes of data and we're seeing that it's such a critical piece to that to make sure that that data's safe. The big thing and you brought this up as well is the big thing is they're getting data from so many different sources now. It's not just data that they generate. You see one centralized company taking in from numerous sources, consolidating it, creating new value on top of it, and then releasing that and the question is, do you trust those sources or not? And even if you do, they may not be safe. >> We had an event around super Clouds is a topic we brought up to get bring the attention to the complexity of hybrid which is on premise, which is essentially Cloud operations. And the successful people that are doing things in the software side are essentially abstracting up the benefits of the infrastructures of service from HN AWS, right, which is great. Then they innovate on top so they have to abstract that storage is a key component of where we see the innovations going. How do you see your tech that kind of connecting with that trend that's coming which is everyone wants infrastructures code. I mean, that's not new. I mean, that's the goal and it's getting better every day but DevOps, the developers are driving the operations and security teams to like stay pace, so policy seeing a lot of policy seeing some cool things going on that's abstracting up from say storage and compute but then those are being put to use as well, so you've got this new wave coming around the corner. What's your reaction to that? What's your vision on that? How do you see that evolving? >> I think it's great, actually. I think that the biggest problem that you have to do as someone who is helping them with that process is make sure you don't slow it down. So, just like Cloud at scale, you must automate, you must provide different mechanisms to fit into workflows that allow them to do it just how they want to do it and don't slow them down. Don't hold them back and so, we've come up with different measures to provide and pretty much a fit for any workflow that any customer has come so far with. We do data this way. I want you to plug in right here. Can you do that? And so it's really about being able to plug in where you need to be, and don't slow 'em down. That's what we found so far. >> Oh yeah, I mean that exactly, you don't want to solve complexity with more complexity. That's the killer problem right now so take me through the use case. Can you just walk me through how you guys engage with customers? How they consume your service? How they deploy it? You got some deployment scenarios. Can you talk about how you guys fit in and what's different about what you guys do? >> Sure, so, we're what we're seeing is and I'll go back to this data coming from numerous sources. We see different agencies, different enterprises taking data in and maybe their solution is intelligence on top of data, so they're taking these data sets in whether it's topographical information or whether it's in investing type information. Then they process that and they scan it and they distribute it out to others. So, we see that happening as a big common piece through data ingestion pipelines, that's where these folks are getting most of their data. The other is where is the data itself, the document or the document set, the actual critical piece that gets moved around and we see that in pharmaceutical studies, we see it in mortgage industry and FinTech and healthcare and so, anywhere that, let's just take a very simple example, I have to apply for insurance. I'm going to upload my Social Security information. I'm going to upload a driver's license, whatever it happens to be. I want to one know which of my information is personally identifiable, so I want to be able to classify that data but because you're trusting or because you're taking data from untrusted sources, then you have to consider whether or not it's safe for you to use as your own folks and then also for the downstream users as well. >> It's interesting, in the security world, we hear zero trust and then we hear supply chain, software supply chains. We get to trust everybody, so you got kind of two things going on. You got the hardware kind of like all the infrastructure guys saying, "Don't trust anything 'cause we have a zero trust model," but as you start getting into the software side, it's like trust is critical like containers and Cloud native services, trust is critical. You guys are kind of on that balance where you're saying, "Hey, I want data to come in. We're going to look at it. We're going to make sure it's clean." That's the value here. Is that what I'm hearing you, you're taking it and you're saying, "Okay, we'll ingest it and during the ingestion process, we'll classify it. We'll do some things to it with our tech and put it in a position to be used properly." Is that right? >> That's exactly right. That's a great summary, but ultimately, if you're taking data in, you want to ensure it's safe for everyone else to use and there are a few ways to do it. Safety doesn't just mean whether it's clean or not. Is there malicious content or not? It means that you have complete coverage and control and awareness over all of your data and so, I know where it came from. I know whether it's clean and I know what kind of data is inside of it and we don't see, we see that the interesting aspects are we see that the cleanliness factor is so critical in the workflow, but we see the classification expand outside of that because if your data drifts outside of what your standard workflow was, that's when you have concerns, why is PII information over here? And that's what you have to stay on top of, just like AWS is control plane. You have to manage it all. You have to make sure you know what services have all of a sudden been exposed publicly or not, or maybe something's been taken over or not and you control that. You have to do that with your data as well. >> So how do you guys fit into the security posture? Say it a large company that might want to implement this right away. Sounds like it's right in line with what developers want and what people want. It's easy to implement from what I see. It's about 10, 15, 20 minutes to get up and running. It's not hard. It's not a heavy lift to get in. How do you guys fit in once you get operationalized when you're successful? >> It's a lightweight, highly scalable serverless solution, it's built on Fargate containers and it goes in very easily and then, we offer either native integrations through S3 directly, or we offer APIs and the APIs are what a lot of our customers who want inline realtime scanning leverage and we also are looking at offering the actual proxy aspects. So those folks who use the S3 APIs that our native AWS, puts and gets. We can actually leverage our put and get as an endpoint and when they retrieve the file or place the file in, we'll scan it on access as well, so, it's not just a one time data arrest. It can be a data in motion as you're retrieving the information as well >> We were talking with our friends the other day and we're talking about companies like Datadog. This is the model people want, they want to come in and developers are driving a lot of the usage and operational practice so I have to ask you, this fits kind of right in there but also, you also have the corporate governance policy police that want to make sure that things are covered so, how do you balance that? Because that's an important part of this as well. >> Yeah, we're really flexible for the different ways they want to consume and and interact with it. But then also, that is such a critical piece. So many of our customers, we probably have a 50/50 breakdown of those inside the US versus those outside the US and so, you have those in California with their information protection act. You have GDPR in Europe and you have Asia having their own policies as well and the way we solve for that is we scan close to the data and we scan in the customer's account, so we don't require them to lose chain of custody and send data outside of the accoun. That is so critical to that aspect. And then we don't ask them to transfer it outside of the region, so, that's another critical piece is data residency has to be involved as part of that compliance conversation. >> How much does Cloud enable you to do this that you couldn't really do before? I mean, this really shows the advantage of natively being in the Cloud to kind of take advantage of the IaaS to SAS components to solve these problems. Share your thoughts on how this is possible. What if there was no problem, what would you do? >> It really makes it a piece of cake. As silly as that sounds, when we deploy our solution, we provide a management console for them that runs inside their own accounts. So again, no metadata or anything has to come out of it and it's all push button click and because the Cloud makes it scalable because Cloud offers infrastructure as code, we can take advantage of that and then, when they say go protect data in the Ireland region, they push a button, we stand up a stack right there in the Ireland region and scan and protect their data right there. If they say we need to be in GovCloud and operate in GovCloud East, there you go, push the button and you can behave in GovCloud East as well. >> And with server lists and the region support and all the goodness really makes a really good opportunity to really manage these Cloud native services with the data interaction so, really good prospects. Final question for you. I mean, we love the story. I think it is going to be a really changing market in this area in a big way. I think the data storage relationship relative to higher level services will be huge as Cloud native continues to drive everything. What's the future? I mean, you guys see yourself as a all encompassing, all singing and dancing storage platform or a set of services that you're going to enable developers and drive that value. Where do you see this going? >> I think that it's a mix of both. Ultimately, you saw even on Storage Day the announcement of file cash and file cash creates a new common name space across different storage platforms and so, the notion of being able to use one area to access your data and have it come from different spots is fantastic. That's been in the on-prem world for a couple of years and it's finally making it to the Cloud. I see us following that trend in helping support. We're super laser-focused on Cloud Storage itself so, EBS volumes, we keep having customers come to us and say, "I don't want to run agents in my EC2 instances. I want you to snap and scan and I don't want to, I've got all this EFS and FSX out there that we want to scan," and so, we see that all of the Cloud Storage platforms, Amazon work docs, EFS, FSX, EBS, S3, we'll all come together and we'll provide a solution that's super simple, highly scalable that can meet all the storage needs so, that's our goal right now and where we're working towards. >> Well, Cloud Storage Security, you couldn't get a more a descriptive name of what you guys are working on and again, I've had many contacts with Andy Jassy when he was running AWS and he always loves to quote "The Innovator's Dilemma," one of his teachers at Harvard Business School and we were riffing on that the other day and I want to get your thoughts. It's not so much "The Innovator's Dilemma" anymore relative to Cloud 'cause that's kind of a done deal. It's "The Integrator's Dilemma," and so, it's the integrations are so huge now. If you don't integrate the right way, that's the new dilemma. What's your reaction to that? >> A 100% agreed. It's been super interesting. Our customers have come to us for a security solution and they don't expect us to be 'cause we don't want to be either. Our own engine vendor, we're not the ones creating the engines. We are integrating other engines in and so we can provide a multi engine scan that gives you higher efficacy. So this notion of offering simple integrations without slowing down the process, that's the key factor here is what we've been after so, we are about simplifying the Cloud experience to protecting your storage and it's been so funny because I thought customers might complain that we're not a name brand engine vendor, but they love the fact that we have multiple engines in place and we're bringing that to them this higher efficacy, multi engine scan. >> I mean the developer trends can change on a dime. You make it faster, smarter, higher velocity and more protected, that's a winning formula in the Cloud so Ed, congratulations and thanks for spending the time to riff on and talk about Cloud Storage Security and congratulations on the company's success. Thanks for coming on "theCUBE." >> My pleasure, thanks a lot, John. >> Okay. This conversation here in Palo Alto, California I'm John Furrier, host of "theCUBE." Thanks for watching.

>>Okay, welcome back everyone to the Cube's live coverage here in Monaco for the MoCo crypto summit. I'm John fur. You're host of the cube. We got a great guest Dustin plant Boltz who is a crypto advisor, but also the crypto editor for Forbes Monaco here. Seeing the official event, the AAL event of the Monaco crypto summit in Monaco, your coverage area for Forbes, your MCing. Welcome to the >>Cube. Thank you for having me. And it's, it's always fun when I get to have an event in our backyard, cuz I get to hear what others know. And to me I'm very curious. Yeah. Always >>Learning. So you're on the MC on the stage here, you know, queue in the program online great program. So it's innovative event, inaugural event, great name by the way. Crypto summit and mono crypto >>Summit. Yeah, the MoCo crypto summit. >>That sounds like I want to attend every year. >>You're you're more than welcome to attend next year. >>Well, I hope so. Either way. I'm at the Al event with you. So gimme the take on what's on stage. What's been the program, like what's your observations going on here at the event today? >>So what we're starting to see globally is this digitization of things and the people that are part of the innovation side. And so that's what we've been able to see this morning. We're we're now at the break is what sort of companies are out there, the good ones and what are they building? Is this innovation? Is it even innovative and figuring out how they're gonna do it and the roadmaps to getting there from the metaverses to NFTs and even to decentralized finance. >>Yeah, it's the number one question I get is what's legit. What's not legit. And then you're starting to see the, the, the wheat and the shaft separating here and you know, something called crypto winter. But I don't see it. I mean, I see correction for some of the bad things going on in terms of not having the right underpinning infrastructure, the creative ideas are amazing. We're also seeing like digital bits and other platforms kind of coming together to enable the creators and, and the NFT side for instance has been huge. What has been your observation on that enablement? Because you have two schools of thoughts. You have the total nerds we're up and down building everything. Then you have artists and creators, whether it's music, tech apps building, they don't necessarily want to get 'em to the covers. They don't want to deal with all that. Yeah. Have you seen, what's your, what's your take on that? >>So I I'm seeing that a lot of these major brands, you know, they they're striving for excellence. You know, they're being more careful of who they partner with and the types of companies and you know, they, they look at it from reality and a little tough love to figure out should they align their brand. So what we're seeing here is is that there is so much inertia moving forward. That we're just at the beginning of this thing. Yeah. McKinsey recently said that the ecosystem will be over $30 trillion. So when you recognize that we are so early and it's those right now, or some might say are the risk takers. But to me there, aren't taking risk. They're being a part of making history. >>Yeah. You get the pioneers and you get the financial. So as they come together, how do you see the market? Cause what I've noticed with crypto and here in, in this, this market is international. One lot of international finance us is kind of lag behind. You got all kinds of rules, but you got the, the combination of the, the future billionaires. Sure. Okay. The pioneers and then the financeers yeah. Coming the money, the money and the power coming together. What's your reporting show you that's going on right now? What should people know about on how this is evolving? What they shouldn't >>Expect? Well, so you have a group that wants to become cryers they're seeing these individuals globally. They're making lots and lots of money, but what they don't realize is that not everybody is gonna have that outcome, but looking at the technology aspect of it and how it's going to improve a system that many can agree is collectively broken legacy just can't move beyond. It was never designed to you'll see people take shots at certain card companies and I go, but you recognize they developed the assembly line. And so I'm seeing that the smart money they got in long ago, believe it or not. And those now they're looking out for their errors are the ones that saying, I will not have an excuse when my, my grandkids or my, my nieces or my nephews, when they come and ask, where were you when the greatest transformational shift in human history, from both education to jobs, to careers and even wealth was being shifted to a digital world, why were you on the sideline waiting? And so I think what we're gonna see is this tsunami coming, and it's gonna start with one big player and then two and five, you go, go alone. You go far, go together. You go further. And that's what we're seeing is that this collective is moving forward >>And the community, we just had Beth Kaiser on, I've known Beth for many, many years. And she's what she's her journey has done. She's had a great mission and then gets she's a data scientist and came to Analytica. Now she's doing work with Ukraine and the rallying support around it has been impressive. And it's a community vibe, but the community's not just like sympathetic they're hands on together to your point. >>Yeah. It, but it also takes courage. I mean, you look at Britney Kaiser and what she had, and to me, courage is not, not having fear. Courage is not allowing the fear to stop. You, you know, recently asked my executive coach, who's 85 and I'm turning 39. This question of, do you let fear stop you? How do you decide? And he said, you know, you can either let, you can either ride the dragon. And I said, or let the dragon chase you. And Brittany has been one of these that made a decision to do what was right. And it came down to integrity. Yeah. >>So what are you have to these days what's going on in your world? >>What is going on in my world? So I moderate events all over and I connect and I like to ask people questions. So I'm gonna ask you, I'm gonna turn at the interviewer on the >>Interview. It's good. Natural. >>What are you learning? >>I mean, I'm learning, I mean today or this week or this month or this year. Well, I was just talking with Brittany about this. The security world is converging cloud technology, cloud computing. That revolution has just been amazing. Amazon posted their earnings yesterday. They blew it away as far as I'm concerned. So they kind of show there's no tech recession. I've learned that this recession, that we're so called in is the first downturn in tech where there's been cloud players as hyperscalers as an economic engine. Okay. So from a, from a business perspective, Amazon web services, Microsoft Azure now Google cloud, Alibaba's now in, in international version. This is the first time at downturns ever happened with cloud computing as an economic engine. And so therefore what I'm seeing is the digital transformation that's happening across the world for enterprises and entrepreneurs is not stopping. >>It's actually accelerating. So although the GDPs down in inflation is down, you're seeing a massive shift continuing to accelerate, spending and transformation with cloud technologies and decentralized. So you can almost see it kind of in the, this event and other events, even some of the bigger events, the best smartest people are working on it. The applications in all the categories are transforming. If cloud is step one, decentralized gonna be step two. So I see that kind of bridge going from cloud computing, cloud native to decentralized native. And I think a D DAPP market's gonna just explode. I think NFTs are just scratched on the surface. I think that's kind of, I won't say gimmicky, but I think no, but you're right, much more of a much more of a, an illustration that there's more coming. >>There is a lot more coming because people are seeing that there's more to an NFT than an ugly luck and J you know, ugly and JP image that there's, that there's data in there. And that your avatar will be stored as just that as an NFT. And I learned today from go of sing, that decentralization is, is the key to innovation. And I agree with that statement. Holy. >>Yeah. I mean, I think access to stuff is gonna be multidimensional. Like you think about the NFT as, as an ID, whether it's him or UN unstoppable domains is that company just got financing another round where the billion dollars, their concept is like, Hey, one NFT is your access for all of your potential identities in context. >>And isn't that exciting that we're now gonna be at this stage where you travel with you. Yeah. Instead of someone else traveling with you, you get to decide who you will be. And to me, everything you're doing in this world, this reality is now becoming part of your digital asset as a whole. >>I remember when I started my podcasting company in 20 2004, early pioneers, Evan Williams was there with Odo and you had, you know, the blogging revolution going on that whole democratization wave actually didn't happen right then. But all the people that were involved in that web two oh, kind of CRAs was all about democratization. It's kind of happening now. I mean, 15, 20 years later at web services is transformed cloud the democratization for own your own data, putting users in control. And I think in the middle of that, the Facebook's the world, the world garden data, you know, manipulation kind of took it off track a little bit. So I think now I'm, I psych to see that it's back on track to where it was. I mean, Facebook made billions of dollars. Now you got LinkedIn. I mean, LinkedIn's great for your resume, but it's also become a wall's garden with no data export. >>Yeah. And then >>No APIs keep >>Changing. Think about this. That if you wanna apply for a job, just change something quickly. Yeah. Ah, now you're the senior VP. Yeah. Before you were, you're an office manager >>Like to see the immutable block change, >>You don't get to see when did the record change. Yeah. >>Reputation data. You're a digital exhaust people gonna wanna reign that in. And I think the user in charge message that Brit Kaiser was talks about is hugely a mess under, under, under amplified concept. Digital assets are key, but the data ownership is something that I think is, is >>Powerful. So I'm gonna be launching a brand new company in and around September called cryptos. And it's a crypto career center. Think of it like the, the crypto for LinkedIn, that it's an aggregator becoming the industry standard for education, becoming the industry standard for crypto ships, with partners like ledger and moon pay and Casper labs. >>Look at this, we got an exclusive scoop on the cube. This >>Is the first time I will tell you this the first time in, in an environment like this. Yeah. That I'm excited to, I'm excited to talk about, right. Because it's time to be part of the change. Yeah, exactly. You know, as a father, I look at, I know where it's headed in the world of business. I know in the world of this, that we're gonna call the internet of connected things. Yeah. That it's gonna require you to have a certain talent skill or a certain certification. And to me, it's important to have an industry that supports one >>Staff and also, and also history on misinformation, smear campaigns can happen and ruin a career >>Overnight. Can you imagine that one little thing and because the internet never forgets. Yeah. It stays around indefinitely. >>The truth has to come out. Dustin. Great to have you on the queue. Thank you so much. Final question. What have you learned in there is MC what's your takeaway real quick? >>What I've learned is I never tire of learning. Thank you again, to learn more. Dustin plan.com. >>All right. Thanks for coming. Thank you. Cube coverage here at Monaco. I'm Shawn furry. We'll back with more coverage after this short break.

(upbeat music) >> Hello everyone, welcome to this CUBE conversation. I'm John Furrier, your host of theCUBE here in Palo Alto, California in our studios. Got a great guest here, Rachel Obstler, Vice President, Head of Product at heap.io or Heap is the company name, heap.io is URL. Rachel, thanks for coming on. >> Thanks for having me, John. Great to be here. >> So you guys are as a company is heavily backed with some big time VCs and funders. The momentum is pretty significant. You see the accolades in the industry. It's a hot market for anyone who can collect data easily and make sense of it relative to everything being measured, which is the Nirvana. You can measure everything, but then what do you do with it? So you're at the center of it. You're heading up product for heap. This is what you guys do. And there's a lot of solutions, so let's get into it. Describe the company. What's your mission and what you guys do? >> Yeah, so let me start maybe with how Heap was even started and where the idea came from. So Heap was started by Matin Movassate, someone who was working at Facebook. And this is important 'cause it gets right at the problem that we are trying to solve, which is that he was a product manager at Facebook and he was spending a lot of money on pizza. The reason why he was spending a lot of money on pizza is because he wanted to be able to measure what the users were doing in the product that he was responsible for, and he couldn't get the data. And in order to get the data, he would have to go beg his engineers to put in all sorts of tracking code to collect data. And every time he did so, he had to bribe him with pizza because it's no one's favorite work, number one, and then people want to build new things. They don't want to just constantly be adding tracking code. And then the other thing he found is that even when he did that then it took a couple weeks to get it done. And then he had to wait to collect the data to see what data is. It takes a while to build up the data, and he just thought there must be a better way. And so he founded, he with a couple other co-founders, and the idea was that we could automatically collect data all the time. So it didn't matter if you launched something new, you didn't have to do anything. The data would be automatically collected. And so Heap's mission is really to make it easy to create amazing digital experiences. And we do that by firstly, just making sure you have all the data of what your users are doing because you would think you want to create a new digital experience. You could just do that and it would be perfect the first time, but that's not how it works and users are not predictable. >> Yeah, remember back in the day, big data, Hadoop and that kind of fell flap, but the idea of a data lake started there. You saw the rise of Databricks, the Snowflakes. So this idea that you can collect is there. It's here now, state of the art. Now I see that market. Now the business model comes in. Okay, I can collect everything. How fast can I turn around the insights becomes the next question. So what is the business model of the company? What does the product do? Is it SaaS? Is it a as a package software? How do you guys deploy? How do your customers consume and pay for the service? >> Yeah, so we are a SaaS company and we sell largely to, it could be a product manager. It could be someone in marketing, but it's someone who is responsible for a digital service or a digital product. So they're responsible for making sure that that they're hitting whatever targets they have. It could be revenue, it could be just usage, getting more users adopted, making sure they stay in the product. So that's who we sell to. And so basically our model is just around sessions. So how many sessions do you have? How much data are you collecting? How much traffic do you have? And that's how we charge. I think you were getting at something else though that was really interesting, which is this proliferation of data and then how do you get to an insight. And so one of the things that we've done is first of all, okay, collecting all the data and making sure that you have everything that you need, but then you have a lot of data. So that is indeed an issue. And so we've also built on top of Heap a data science layer that will automatically surface interesting points. So for instance, let's say that you have a very common user flow. Maybe it's your checkout flow. Maybe it's a signup flow and you know exactly what the major milestones are. Like you first fill out a form, you sign up, like maybe you get to do the first thing in the trial. You configure it, you get some value. So we're collecting not only those major milestones, we're collecting every single thing that happens in between. And then we'll automatically surface when there is an important drop off point, for instance, between two milestones so that you know exactly where things are going wrong. >> So you have these indicators. So it's a data driven business. I can see that clearly. And the value proposition in the pitch to the customer is ease of use. Is it accelerated time to value for insights? Is it eliminating IT? Is it the 10X marketer? Or all of those things? What is the core contract with the customer, the brand promise? >> That's exactly. So it's the ability to get to insight. First of all, that you may never have found on your own, or that would take you a long time to keep trialing an error of collecting data until you found something interesting. So getting to that insight faster and being able to understand very quickly, how you can drive impact with your business. And the other thing that we've done recently that adds a lot to this is we recently joined forces with a company named Auryc so we just announced this on Monday. So now on top of having all the data and automatically surfacing points of interest, like this is where you're having drop off, this is where you have an opportunity, we now allow you to watch it. So not only just see it analytically, see it in the numbers, but immediately click a show me button, and then just watch examples of users getting stuck in that place. And it really gives you a much better or clearer context for exactly what's happening. And it gives you a much better way to come up with ideas as to how to fix it as one of those digital builders or digital owners. >> You know, kind of dating myself when I mention this movie "Contact" where Jodie foster finds that one little nugget that opens up so much more insight. This is what you're getting at where if you can find that one piece that you didn't see before and bring it in and open it up and bring in that new data, it could change the landscape and lens of the entire data. >> Yeah. I can give you an example. So we have a customer, Casper. Most are familiar with that they sell mattresses online. So they're really a digital innovator for selling something online that previously you had to like go into a store to do. And they have a whole checkout flow. And what they discovered was that users that at the very end of the flow chose same day delivery were much more likely to convert and ultimately buy a mattress. They would not necessarily have looked at this. They wouldn't necessarily have looked at or decided to track like delivery mechanism. Like that's just not the most front and center thing, but because he collects all the data, they could look at it and say, oh, people who are choosing this converted a much higher rate. And so then they thought, well, okay, this is happening at the very end of the process. Like they've already gone through choosing what they want and putting it in their card and then it's like the very last thing they do. What if we made the fact that you could get same day delivery obvious at the beginning of the whole funnel. And so they tried that and it improved their conversion rate considerably. And so these are the types of things that you wouldn't necessarily anticipate. >> I got to have a mattress to sleep on. I want it today. Come on. >> Yeah, exactly. Like there's a whole market of people who are like, oh no, I need a mattress right now. >> This is exactly the point. I think this is why I love this opportunity that you guys are in. Every company now is digitalizing their business, aka digital transformation. But now they're going to have applications, they're going to have cloud native developers, they're going to be building modern applications. And they have to think like an eCommerce company, but it's not about brick and mortars anymore. It's just digital. So this is the new normal. This is an imperative. This is a fact. And so a lot of them don't know what to do. So like, wait a minute, who do we call? This is like a new problem for the mainstream. >> Yeah, and think about it too. Actually e-commerce has been doing this for quite a while, but think about all the B2B companies and B2B SaaS, like all the things that today, you do online. And that they're really having to start thinking more like e-commerce companies and really think about how do we drive conversion, even if conversion isn't the same thing or doesn't mean the same thing, but it means like a successful retained user. It's still important to understand what their journey is and where you going to help them. >> Recently, the pandemic has pulled forward this digital gap that every company's seeing, especially the B2B, which is virtual events, which is just an indicator of the convergence of physical and online. But it brings up billions of signals and I know we have an event software that people do as well. But when you're measuring everything, someone's in a chat, someone hit a web page, I mean there are billions of signals that need to get stored, and this is what you guys do. So I want to ask you, you run the product team. What's under the covers? What's the secret sauce for you guys at Heap? Because you got to store everything. That's one challenge. That's one problem you got to solve. Then you got to make it fast because most of the databases can't actually roll up data fast enough. So you're waiting for the graph forever when some people say. What's under the covers? What's the secret sauce? >> Well, it's a couple different things. So one is we designed the system from the very beginning for that purpose. For the purpose of bringing in all those different signals and then being able to cut the data lots of different ways. And then also to be able to apply data science to it in real time to be able to surface these important points that you should be looking at. So a lot of it is just about designing the system for the very beginning for that purpose. It was also designed to be easy for everyone to use. So what was a really important principle for us is a democratization of data. So in the past, you have these central data teams. You still have them today. Central data teams that are responsible for doing complex analysis. Well, we want to bring as much of that functionality to the digital builders, the product managers, the marketers, the ones that are making decisions about how to drive impact for their digital products and make it super easy for them to find these insights without having to go through a central team that could again take weeks and months to get an answer back from. >> Well, that's what brings up a good point. I want to dig into, if you don't mind, Rachel, this data engineering challenge. There's not enough talent out there. When I call data engineer, I'm talking about like the specialist person. She could be a unique engineer, but not a data scientist. We're talking about like hardcore data engineering, pipelining, streaming data, hardcore. There's not many people that fit that bill. So how do you scale that? Is that what you guys help do? >> We can help with that. Because, again, like if you put the power in the hands of the product people or the marketers or the people that are making those decisions, they can do their own analysis. Then you can really offload some of those central teams and they can do some of the much more complex work, but they don't have to spend their time constantly serving maybe the easier questions to answer. You have data that's self-service for everyone. >> Okay, before I get into the quick customer side of it, quickly while I have you on the product side. What are some of your priorities? You look at the roadmap, probably got tons of people calling. I can only imagine the customer base is diverse in its feature requests. Everyone has the same need, but they all have different businesses. So they want a feature here. They want a feature there. What's the priorities? How do you prioritize? What are some of your priorities for how you're going to build out and keep continuing the momentum? >> Yeah, so I mentioned earlier that we just joined forces with a company name Auryc that has session replay capabilities, as well as voice of customer. So one of our priorities is that we've noticed in this market, there's a real, it's very broken up in a strange way. I shouldn't say it's strange. It's probably because this is the way markets form, startups start, and they pick a technology and they build on top of it. So as a result, the way the market has formed is that you have analytics tools like Heap, and they look at very quantitative data, collecting all sorts of data and doing all sorts of quantitative cuts on it. And then you have tools that do things like session replay. So I just want to record sessions and watch and see exactly what the user's doing and follow their path through one at a time. And so one is aggregating data and the other one is looking at individual user journeys, but they're solving similar jobs and they're used by the same people. So a product manager, for example, wants to find a point of friction, wants to find an opportunity in their product that is significant, that is happening to a lot of people, that if they make a change will drive impact like a large impact for the business. So they'll identify that using the quant, but then to figure out how to fix it, they need the qual. They need to be able to watch it and really understand where people are getting stuck. They know where, but what does that really look like? Like, let me visualize this. And so our priority is really to bring these things together to have one platform where someone can just, in seconds, find this point of opportunity and then really understand it with a show me button so that they can watch examples of it and be like, I see exactly what's happening here and I have ideas of how to fix this. >> Yeah, something's happening at that intersection. Let's put some cameras on. Let's get some eyes on that. Let's look at it. >> Exactly. >> Oh, hey, let's put something. Let's fix that. So it makes a lot of sense. Now, customer attraction has been strong. I know it's been a lot of press and accolades online with when you guys are getting review wise. I mean, I can see DevOps and app people just using this easily, like signing up and I can collect all the data and seeing value, so I get that. What are some of the customer value propositions that are coming out of that, that you can share? And for the folks watching that don't know Heap, what's their problem that they're facing that you can solve, and what pain are they in or what problem do they solve? So example of some success that's coming out of the platform, enablement, the disruptive enablement, and then what's the problem, what's the customer's pain point, and when they know to call you guys or sign up. >> Yeah, so there's a couple different ways to look at it. When I was talking about is really for the user. There's this individual person who owns an outcome and this is where the market is going that the product managers, the marketers, they're not just there to build new features, they're there to drive outcomes for the business. And so in order to drive these outcomes, they need to figure out what are the most impactful things to do? Where are the investments that they need to make? And so Heap really helps them narrow down on those high impact areas and then be able to understand quickly as I was mentioning how to fix them. So that's one way to look at it. Another use case is coming from the other side. So talking in about session replay, you may have a singular problem. You may have a single support ticket. You may have someone complaining about something and you want to really understand, not only what is the problem, like what were they experiencing that caused them to file this ticket, but is this a singular problem, or is this something that is happening to many different people? And therefore, like we should prioritize fixing it very quickly. And so that's the other use case is let's start, not with the group, like the biggest impact and go to like exactly some examples, let's start with the singular and figure out if that gives you a path to the group. But the other use case that I think is really interesting is if you think about it from a macro point of view or from a product leader or a marketing leader's point of view, they're not just trying to drive impact. They're trying to make it easy for their team to drive that impact. So they're thinking about how do they make their whole organization a lot more data driven or insights driven? How do they change the culture, the process, not just the tool, but all of those things together so that they can have a bigger business impact and enable their team to be able to do this on their own? >> You guys are like a data department for developers and product managers. >> Essentially, like we are the complete dataset and the easy analysis that really helps you figure out, where do I invest? How do I justify my investments? And how do I measure how well my investments are doing? >> And this is where the iteration comes in. This is the model everyone's doing. You see a problem, you keep iterating. Got to look at the data, get some insight and keep looking back and making that product, get that flywheel going. Rachel, great stuff. Coming out here, real quick question for you to end the segment. What's the culture like over at Heap? If people are interested in joining the company or working with you guys. Every company has their own kind of DNA. What's the Heap culture like? >> That's a great question. So Heap is definitely a unique company that I've worked at and in a really good way. We find it really important to be respectful to each other. So one of our values is respectful candor. So you may be familiar with radical candor. We've kind of softened it a bit and said, look, it's good to be truthful and have candor, but let's do it in a respectful way. We really find important that everyone has a growth mindset. So we're always thinking about how do we improve? How do we get better? How do we grow faster? How do we learn? And then the other thing that I'll mention, another one of our values that I love, we call it, "taste the soup". Some people use to call it dogfooding, but we are in Heap all the time. We call it Heap on Heap. We really want to experience what our customers experience and constantly use our product to also get better and make our product better. >> A little more salt on the sauce, keep the soup, taste it a little bit. Good stuff. Rachel, thanks for coming on. Great insights and congratulations on a great product opportunity. Again, as world goes digital transformation, developers, product, all people want to instrument everything to then start figuring out how to improve their offering. So really hot market and hot company. Thanks for coming on. >> Thanks, John. Thanks for having me. >> This is theCUBE conversation. I'm John Furrier here in Palo Alto, California. Thanks for watching. (gentle music)

>>LA Las Vegas. It's the cube hovering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Hey, welcome back to the cube. Our day one coverage of AWS reinvent 19 continues. Lisa Martin with Dave Volante. Dave and I have a couple of guests we'd like you to walk up. We've got Anthony Brooks billions, the CEO of HBR back on the cube. You're alumni. We should get you a pin and snowflake alumni. But Chris, your new Chris Dagon, chief revenue officer from snowflake. Chris, welcome to the program. Excited to be here. All right guys. So even though both companies have been on before, Anthony, let's start with you. Give our audience a refresher about HVR, who you guys are at, what you do. >>Sure. So we're in the data integration space, particularly a real time data integration. So we move data to the cloud in the in the most efficient way and we make sure it's secure and it's accurate and you're moving into environments such as snowflake. Um, and that's where we've got some really good customers that we happy to talk about joint custody that we're doing together. But Chris can tell us a little bit about snowflake. >>Sure. And snowflake is a cloud data warehousing company. We are cloud native, we are on AWS or on GCP and we're on Azure. And if you look at the competitive landscape, we compete with our friends at Amazon. We compete with our friends at Microsoft and our friends at Google. So it's super interesting place to be, but it very exciting at the same time and super excited to partner with Anthony and some others who aren't really a friends. That's correct. So I wonder if we could start by just talking about the data warehouse sort of trends that you guys see. When I talk to practitioners in the old days, they used to say to me things like, Oh, infrastructure management, it's such a nightmare. It's like a snake swallowing a basketball every time until it comes out with a new chips. We chase it because we just need more performance and we can't get our jobs done fast enough. And there's only three. There's three guys that we got to go through to get any answers and it was just never really lived up to the promise of 360 degree view of your business and realtime analytics. How has that changed? >>Well, there's that too. I mean obviously the cloud has had a big difference on that illustrious city. Um, what you would find is in, in, in yesterday, customers have these, a retail customer has these big events twice a year. And so to do an analysis on what's being sold and Casper's transactions, they bought this big data warehouse environment for two events a year typically. And so what's happening that's highly cost, highly costly as we know to maintain and then cause the advances in technology and trips and stuff. And then you move into this cloud world which gives you that Lester city of scale up, scale down as you need to. And then particular where we've got Tonies snowflake that is built for that environment and that elicited city. And so you get someone like us that can move this data at today's scale and volume through these techniques we have into an environment that then bleeds into helping them solve the challenge that you talk about of Yesi of >>these big clunky environments. That side, I think you, I think you kind of nailed it. I think like early days. So our founders are from Oracle and they were building Oracle AI nine nine, 10 G. and when I interviewed them I was the first sales rep showing up and day one I'm like, what the heck am I selling? And when I met them I said, tell me what the benefit of snowflake is. And they're like, well at Oracle, and we'd go talk to customers and they'd say, Oracles, you know, I have this problem with Oracle. They'd say, Hey, that's, you know, seven generations ago were Oracle. Do you have an upgraded to the latest code? So one of the things they talked about as being a service, Hey, we want to make it really easy. You never have to upgrade the service. And then to your point around, you have a fixed amount of resources on premise, so you can't all of a sudden if you have a new project, do you want to bring on the first question I asked when I started snowflake to customers was how long does it take you to kick off a net new workload onto your data, onto your Vertica and it take them nine to 12 months because they'd have to go procure the new hardware, install it, and guess what? >>With snowflake, you can make an instantaneous decision and because of our last test city, because the benefits of our partner from Amazon, you can really grow with your demand of your business. >>Many don't have the luxury of nine to 12 months anymore, Chris, because we all know if, if an enterprise legacy business isn't thinking, there's somebody not far behind me who has the elasticity, who has the appetite, who's who understands the opportunity that cloud provides. If you're not thinking that, as auntie Jessie will say, you're going to be on the wrong end of that equation. But for large enterprises, that's hard. The whole change culture is very hard to do. I'd love to get your perspective, Chris, what you're seeing in terms of industries shifting their mindsets to understand the value that they could unlock with this data, but how are big industries legacy industries changing? >>I'd say that, look, we were chasing Amad, we were chasing the cloud providers early days, so five years ago, we're selling to ad tech and online gaming companies today. What's happened in the industry is, and I'll give you a perfect example, is Ben wa and I, one of our founders went out to one of the largest investment banks on wall street five years ago, and they said, and they have more money than God, and they say, Hey, we love what you've built. We love, when are you going to run on premise? And Ben, Ben wa uttered this phrase of, Hey, you will run on the public cloud before we ever run in the private cloud. And guess what? He was a truth teller because five years later, they are one of our largest customers today. And they made the decision to move to the cloud and we're seeing financial services at a blistering face moved to the cloud. >>And that's where, you know, partnering with folks from HR is super important for us because we don't have the ability to just magically have this data appear in the cloud. And that's where we rely quite heavily on on instance. So Anthony, in the financial services world in particular, it used to be a cloud. Never that was an evil word. Automation. No, we have to have full control and in migration, never digital transformation to start to change those things. It's really become an imperative, but it's by in particular is really challenging. So I wonder if we could dig into that a little bit and help us understand how you solve that problem. >>Yes. A customer say they want to adopt some of these technologies. So there's the migration route. They may want to go adopt some of these, these cloud databases, the cloud data warehouses. And so we have some areas where we, you know, we can do that and keep the business up and running at the same time. So the techniques we use are we reading the transactional logs, other databases or something called CDC. And so there'll be an initial transfer of the bulk of the data initiative stantiating or refresh. At that same time we capturing data out of the transaction logs, wildlife systems live and doing a migration to the new environment or into snowflakes world, capturing data where it's happening, where the data is generated and moving that real time securely, accurately into this environment for somewhere like 1-800-FLOWERS where they can do this, make better decisions to say the cost is better at point of sale. >>So have all their business divisions pulling it in. So there's the migration aspects and then there's the, the use case around the realtime reporting as well. So you're essentially refueling the plane. Well while you're in mid air. Um, yeah, that's a good one. So what does the customer see? How disruptive is it? How do you minimize that disruption? Well, the good thing is, well we've all got these experienced teams like Chris said that have been around the block and a lot of us have done this. What we do, what ed days fail for the last 15 years, that companies like golden gate that we sold to Oracle and those things. And so there's a whole consultative approach to them versus just here's some software, good luck with it. So there's that aspect where there's a lot of planning that goes into that and then through that using our technologies that are well suited to this Appleton shows some good success and that's a key focus for us. And in our world, in this subscription by SAS top world, customer success is key. And so we have to build a lot of that into how we make this successful as well. >>I think it's a barrier to entry, like going, going from on premise to the cloud. That's the number one pushback that we get when we go out and say, Hey, we have a cloud native data warehouse. Like how the heck are we going to get the data to the cloud? And that's where, you know, a partnership with HR. Super important. Yeah. >>What are some of the things that you guys encountered? Because we many businesses live in the multi-cloud world most of the time, not by strategy, right? A lot of the CIO say, well we sort of inherited this, or it's M and a or it's developers that have preference. How do you help customers move data appropriately based on the value that the perceived value that it can give in what is really a multi world today? Chris, we'll start with you. >>Yeah, I think so. So as we go into customers, I think the biggest hurdle for them to move to the cloud is security because they think the cloud is not secure. So if we, if you look at our engagement with customers, we go in and we actually have to sell the value snowflake and then they say, well, okay great, go talk to the security team. And then we talked to security team and say, Hey, let me show you how we secure data. And then then they have to get comfortable around how they're going to actually move, get the data from on premise to the cloud. And that's again, when we engage with partners like her. So yeah, >>and then we go through a whole process with a customer. There's a taking some of that data in a, in a POC type environment and proving that after, as before it gets rolled out. And a lot of, you know, references and case studies around it as well. >>Depends on the customer that you have some customers who are bold and it doesn't matter the size. We have a fortune 100 customer who literally had an on premise Teradata system that they moved from on prem, from on premise 30 to choose snowflake in 111 days because they were all in. You have other customers that say, Hey, I'm going to take it easy. I'm going to workload by workload. And it just depends. And the mileage may vary is what can it give us an example of maybe a customer example or in what workloads they moved? Was it reporting? What other kinds? Yeah. >>Oh yeah. We got a couple of, you mean we could talk a little bit about 1-800-FLOWERS. We can talk about someone like Pitney Bowes where they were moving from Oracle to secret server. It's a bunch of SAP data sitting in SAP ECC. So there's some complexity around how you acquire, how you decode that data, which we ever built a unique ability to do where we can decode the cluster and pool tables coupled with our CDC technique and they had some stringent performance loads, um, that a bunch of the vendors couldn't meet the needs between both our companies. And so we were able to solve their challenge for them jointly and move this data at scale in the performance that they needed out with these articles, secret server enrollments into, into snowflake. >>I almost feel like when you have an SAP environment, it's almost stuck in SAP. So to get it out is like, it's scary, right? And this is where it's super awesome for us to do work like this. >>On that front, I wanted to understand your thoughts on transformation. It's a word, it's a theme of reinvent 2019. It's a word that we hear at every event, whether we're talking about digital transformation, workforce, it, et cetera. But one of the things that Andy Jassy said this morning was that got us start. It's this is more than technology, right? This, the next gen cloud is more than technology. It's about getting those senior leaders on board. Chris, your perspective, looking at financial services first, we were really surprised at how quickly they've been able to move. Understanding presumably that if they don't, there's going to be other businesses. But are you seeing that as the chief revenue officer or your conversations starting at that CEO level? >>It kinda has to like in the reason why if you do in bottoms up approach and say, Hey, I've got a great technology and you sell this great technology to, you know, a tech person. The reality is unless the C E O CIO or CTO has an initiative to do digital transformation and move to the cloud, you'll die. You'll die in security, you'll die in legal lawyers love to kill deals. And so those are the two areas that I see D deals, you know, slow down significantly. And that's where, you know, we, it's, it's getting through those processes and finding the champion at the CEO level, CIO level, CTO level. If you're, if you're a modern day CIO and you do not have a a cloud strategy, you're probably going to get replaced >>in 18 months. So you know, you better get on board and you'd better take, you know, taking advantage of what's happening in the industry. >>And I think that coupled with the fact that in today's world, you mean, you said there's a, it gets thrown around as a, as a theme and particularly the last couple of years, I think it's, it's now it is actually a strategy and, and reality because what Josephine is that there's as many it tech savvy people sit in the business side of organizations today that used to sit in legacy it. And I think it's that coupled with the leadership driving it that's, that's demanding it, that demanding to be able to access that certain type of data in a geo to make decisions that affect the business. Right now. >>I wonder if we could talk a little bit more about some of the innovations that are coming up. I mean I've been really hard on data. The data warehouse industry, you can tell I'm jaded. I've been around a long time. I mean I've always said that that Sarbanes Oxley saved the old school BI and data warehousing and because all the reporting requirements, and again that business never lived up to its promises, but it seems like there's this whole new set of workloads emerging in the cloud where you take a data warehouse like a snowflake, you may be bringing in some ML tools, maybe it's Databricks or whatever. You HVR helping you sort of virtualize the data and people are driving new workloads that are, that are bringing insights that they couldn't get before in near real time. What are you seeing in terms of some of those gestalt trends and how are companies taking advantage of these innovations? >>I think one is just the general proliferation of data. There's just more data and like you're saying from many different sources, so they're capturing data from CNC machines in factories, you know like like we do for someone like GE, that type of data is to data financial data that's sitting in a BU taking all of that and going there's just as boss some of data, how can we get a total view of our business and at a board level make better decisions and that's where they got put it in I snowflake in this an elastic environment that allows them to do this consolidated view of that whole organization, but I think it's largely been driven by things that digitize their sensors on everything and there's just a sheer volume of data. I think all of that coming together is what's, what's driven it >>is is data access. We talked about security a little bit, but who has rights to access the data? Is that a challenge? How are you guys solving that or is it, I mean I think it's like anything like once people start to understand how a date where we're an acid compliant date sequel database, so we whatever your security you use on your on premise, you can use the same on snowflake. It's just a misperception that the industry has that being on, on in a data center is more secure than being in the cloud and it's actually wrong. I guess my question is not so much security in the cloud, it's more what you were saying about the disparate data sources that coming in hard and fast now. And how do you keep track of who has access to the data? I mean is it another security tool or is it a partnership within owes? >>Yeah, absolutely man. So there's also, there's in financial data, there's certain geos, data leaves, certain geos, whether it be in the EU or certain companies, particularly this end, there's big banks now California, there's stuff that we can do from a security perspective in the data that we move that's secure, it's encrypted. If we capturing data from multiple different sources, items we have that we have the ability to take it all through one, one proxy in the firewall, which does, it helps him a lot in that aspect. Something unique in our technology. But then there's other tools that they have and largely you sit down with them and it's their sort of governance that they have in the, in the organization to go, how do they tackle that and the rules they set around it, you know? >>Well, last question I have is, so we're seeing, you know, I look at the spending data and my breaking analysis, go on my LinkedIn, you'll see it snowflakes off the charts. It's up there with, with robotic process automation and obviously Redshift. Very strong. Do you see those two? I think you addressed it before, but I'd love to get you on record sort of coexisting and thriving. Really, that's not the enemy, right? It's the, it's the Terra data's and the IBM's and the Oracles. The, >>I think, look, uh, you know, Amazon, our relationship with Amazon is like a, you know, a 20 year marriage, right? Sometimes there's good days, sometimes there's bad days. And I think, uh, you know, every year about this time, you know, we get a bat phone call from someone at Amazon saying, Hey, you know, the Redshift team's coming out with a snowflake killer. And I've heard that literally for six years now. Um, it turns out that there's an opportunity for us to coexist. Turns out there's an opportunity for us to compete. Um, and it's all about how they handle themselves as a business. Amazon has been tremendous in separation of that, of, okay, are going to partner here, we're going to compete here, and we're okay if you guys beat us. And, and so that's how they operate. But yes, it is complex and it's, it's, there are challenges. >>Well, the marketplace guys must love you though because you're selling a lot of computers. >>Well, yeah, yeah. This is three guys. They, when they left, we have a summer thing. You mean NWS have a technological DMS, their data migration service, they work with us. They refer opportunities to us when it's these big enterprises that are use cases, scale complexity, volume of data. That's what we do. We're not necessary into the the smaller mom and pop type shops that just want to adopt it, and I think that's where we all both able to go coexist together. There's more than enough. >>All right. You're right. It's like, it's like, Hey, we have champions in the Esri group, the EEC tuna group, that private link group, you know, across all the Amazon products. So there's a lot of friends of ours. Yeah, the red shift team doesn't like us, but that's okay. I can live in >>healthy coopertition, but it just goes to show that not only do customers and partners have toys, but they're exercising it. Gentlemen, thank you for joining David knee on the key of this afternoon. We appreciate your time. Thank you for having us. Pleasure our pleasure for Dave Volante. I'm Lisa Martin. You're watching the queue from day one of our coverage of AWS reinvent 19 thanks for watching.

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape all right buddy welcome to this cute conversation my name is Dave Ville on time or the co-host of the cube and we're gonna have a conversation to really try to explore does infrastructure matter you hear a lot today I've ever since I've been in this business I've heard Oh infrastructure is dead hardware is dead but we're gonna explore that premise and with me is Randy Arsenault and Steve Kenaston they're both global market development execs at IBM guys thanks for coming in and let's riff thanks for having us Dave so here's one do I want to start with the data we were just recently at the MIT chief data officer event 10 years ago that role didn't even exist now data is everything so I want to start off with you here this bro my data is the new oil and we've said you know what data actually is more valuable than oil oil I can put in my car I can put in my house but I can't put it in both data is it doesn't follow the laws of scarcity I can use the same data multiple times and I can copy it and I can find new value I can cut cost I can raise revenue so data in some respects is more valuable what do you think right yeah I would agree and I think it's also to your point kind of a renewable resource right so so data has the ability to be reused regularly to be repurposed so I would take it even further we've been talking a lot lately about this whole concept that data is really evolving into its own tier so if you think about a traditional infrastructure model where you've got sort of compute and network and applications and workloads and on the edge you've got various consumers and producers of that data the data itself has those pieces have evolved the data has been evolving as well it's becoming more complicated it's becoming certainly larger and more voluminous it's better instrumented it carries much more metadata it's typically more proximal with code and compute so the data itself is evolving into its own tier in a sense so we we believe that we want to treat data as a tier we want to manage it to wrap the services around it that enable it to reach its maximum potential in a sense so guys let's we want to make this interactive in a way and I'd love to give you my opinions as well as links are okay with that but but so I want to make an observation Steve if you take a look at the top five companies in terms of market cap in the US of Apple Google Facebook Amazon and of course Microsoft which is now over a trillion dollars they're all data companies they've surpassed the bank's the insurance companies the the Exxon Mobil's of the world as the most valuable companies in the world what are your thoughts on that why is that I think it's interesting but I think it goes back to your original statement about data being the new oil the and unlike oil Ray's said you can you can put it in house what you can't put it in your car you also when it's burnt it's gone right but with data you you have it around you generate more of it you keep using it and the more you use it and the more value you get out of it the more value the company gets out of it and so as those the reason why they continue to grow in value is because they continue to collect data they continue to leverage that data for intelligent purposes to make user experiences better their business better to be able to go faster to be able to new new things faster it's all part of part of this growth so data is one of the superpowers the other superpower of course is machine intelligence or what everybody talks about as AI you know it used to be that processing power doubling every 18 months was what drove innovation in the industry today it's a combination of data which we have a lot of it's AI and cloud for scaling we're going to talk about cloud but I want to spend a minute talking about AI when I first came into this business AI was all the rage but we didn't have the amount of data that we had today we don't we didn't have the processing power it was too expensive to store all this data that's all changed so now we have this emerging machine intelligence layer being used for a lot of different inks but it's sort of sitting on top of all these workloads that's being injected into databases and applications it's being used to detect fraud to sell us more stuff you know in real time to save lives and I'm going to talk about that but it's one of these superpowers that really needs new hardware architectures so I want to explore machine intelligence a little bit it really is a game changers it really is and and and tying back to the first point about sort of the the evolution of data and the importance of data things like machine learning and adaptive infrastructure and cognitive infrastructure have driven to your point are a hard requirement to adapt and improve the infrastructure upon which that lives and runs and operates and moves and breathes so we always had Hardware evolution or development or improvements and networks and the basic you know components of the infrastructure being driven again by advances in material science and silicon etc well now what's happening is the growth and importance and and Dynamis city of data is far outpacing the ability of the physical sciences to keep pace right that's a reality that we live in so therefore things like you know cognitive computing machine learning AI are kind of bridging the gap almost between the limitations we're bumping up against in physical infrastructure and the immense unlocked potential of data so that intermediary is really where this phenomenon of AI and machine learning and deep learning is happening and you're also correct in pointing out that it's it's everywhere I mean it's imbuing every single workload it's transforming every industry and a fairly blistering pace IBM's been front and center around artificial intelligence in cognitive computing since the beginning we have a really interesting perspective on it and I think we bring that to a lot of the solutions that we offer as well Ginni Rometty a couple years ago actually use the term incumbent disruptors and when I think of that I think about artificial intelligence and I think about companies like the ones I mentioned before that are very valuable they have data at their core most incumbents don't they have data all over the place you know they might have a bottling plant at the core of the manufacturing plant or some human process at the core so to close that gap artificial intelligence from the incumbents the appointees they're gonna buy that from companies like IBM they're gonna you know procure Watson or other AI tools and you know or maybe you know use open-source AI tools but they're gonna then figure out how to apply those to their business to do whatever fraud detection or recommendation engines or maybe even improve security and we're going to talk about this in detail but Steve this there's got to be new infrastructure behind that we can't run these new workloads on infrastructure that was designed 30 40 years ago exactly I mean I think I am truly fascinated by with this growth of data it's now getting more exponential and why we think about why is it getting more exponential it's getting more exponential because the ease at which you can actually now take advantage of that data it's going beyond the big financial services companies the big healthcare companies right we're moving further and further and further towards the edge where people like you and I and Randi and I have talked about the maker economy right I want to be able to go in and build something on my own and then deliver it to either as a service as a person a new application or as a service to my infrastructure team to go then turn it on and make something out of that that infrastructure it's got to come down in cost but all the things that you said before performance reliability speed to get there intelligence about data movement how do we get smarter about those things all of the underlying ways we used to think about how we managed protect secure that it all has evolved and it's continuing to evolve everybody talks about the journey the journey to cloud why does that matter it's not just the cloud it's also the the componentry underneath and it's gonna go much broader much bigger much faster well and I would just add just amplify what Steve said about this whole maker movement one of the other pressures that that's putting on corporate IT is it's driving essentially driving product development and innovation out to the end to the very edge to the end user level so you have all these very smart people who are developing these amazing new services and applications and workloads when it gets to the point where they believe it can add value to the business they then hand it off to IT who is tasked with figuring out how to implement it scale it protect it secured debt cetera that's really where I believe I um plays a key role or where we can play a key role add a lot of values we understand that process of taking that from inception to scale and implementation in a secure enterprise way and I want to come back to that so we talked about data as one of the superpowers an AI and the third one is cloud so again it used to be processor speed now it's data plus AI and cloud why is cloud important because cloud enables scale there's so much innovation going on in cloud but I want to talk about you know cloud one dot o versus cloud two dot o IBM talks about you know the new era of cloud so what was cloud one dot o it was largely lift and shift it was taking a lot of crap locations and putting him in the public cloud it was a lot of tests in dev a lot of startups who said hey I don't need to you know have IT I guess like the cube we have no ID so it's great for small companies a great way to experiment and fail fast and pay for you know buy the drink that was one dot o cloud to dot all to datos is emerging is different it's hybrid it's multi cloud it's massively distributed systems distributed data on Prem in many many clouds and it's a whole new way of looking at infrastructure and systems design so as Steve as you and I have talked about it's programmable so it's the API economy very low latency we're gonna talk more about what that means but that concept of shipping code to data wherever it lives and making that cloud experience across the entire infrastructure no matter whether it's on Prem or in cloud a B or C it's a complicated problem it really is and when you think about the fact that you know the big the big challenge we started to run into when we were talking about cloud one always shadow IT right so folks really wanted to be able to move faster and they were taking data and they were actually copying it to these different locations to be able to use it for them simply and easily well once you broke that mold you started getting away from the security and the corporate furnance that was required to make sure that the business was safe right it but it but it but following the rules slowed business down so this is why they continued to do it in cloud 2.0 I like the way you position this right is the fact that I no longer want to move data around moving data it within the infrastructure is the most expensive thing to do in the data center so if I can move code to where I need to be able to work on it to get my answers to do my AI to do my intelligent learning that all of a sudden brings a lot more value and a lot more speed and speed as time as money rate if I can get it done faster I get more valuable and then just you know people often talk about moving data but you're right on you the last thing you want to do is move data in just think about how long it takes to back up the first time you ever backed up your iPhone how long it took well and that's relatively small compared to all the data in a data center there's another subtext here from a standpoint of cloud 2.0 and it involves the edge the edge is a new thing and we have a belief inside of wiki bond and the cube that we talk about all the time that a lot of the inference is going to be done at the edge what does that mean it means you're going to have factory devices autonomous vehicles a medical device equipment that's going to have intelligence in there with new types of processors and we'll talk about that but a lot of the the inference is that conclusions were made real-time and and by the way these machines will be able to talk to each other so you'll have a machine to machine communication no humans need to be involved to actually make a decision as to where should I turn or you know what should be the next move on the factory floor so again a lot of the data is gonna stay in place now what does that mean for IBM you still have an opportunity to have data hubs that collect that data analyze it maybe push it up to the cloud develop models iterate and push it back down but the edge is a fundamentally new type of approach that we've really not seen before and it brings in a whole ton of new data yeah that's a great point and it's a market phenomenon that has moved and is very rapidly moving from smartphones to the enterprise right so right so your point is well-taken if you look in the fact is we talked earlier that compute is now proximal to the data as opposed to the other way around and the emergence of things like mesh networking and you know high bandwidth local communications peer-to-peer communications it's it's not only changing the physical infrastructure model and the and the best practices around how to implement that infrastructure it's also fundamentally changing the way you buy them the way you consume them the way you charge for them so it's it's that shift is changing and having a ripple effect across our industry in every sense whether it's from the financial perspective the operational perspective the time to market perspective it's also and we talked a lot about industry transformation and disruptors that show up you know in an industry who work being the most obvious example and just got an industry from the from the bare metal and recreate it they are able to do that because they've mastered this new environment where the data is king how you exploit that data cost-effectively repeatably efficiently is what differentiates you from the pack and allows you to create a brand new business model that that didn't exist prior so that's really where every other industry is going you talking about those those those big five companies in North America that are that are the top top companies now because of data I often think about rewind you know 25 years do you think Amazon when they built Amazon really thought they were going to be in the food service business that the video surveillance business the drone business all these other book business right maybe the book business right but but their architecture had to scale and change and evolve with where that's going all around the data because then they can use these data components and all these other places to get smarter bigger and grow faster and that's that's why they're one of the top five this is a really important point especially for the young people in the audience so it used to be that if you were in an industry if you were in health care or you were in financial services or you were in manufacturing you were in that business for life every industry had its own stack the sales the marketing the R&D everything was wired to that industry and that industry domain expertise was really not portable across businesses because of data and because of digital transformations companies like Amazon can get into content they can get into music they can get it to financial services they can get into healthcare they can get into grocery it's all about that data model being portable across those industries it's a very powerful concept that you and I mean IBM owns the weather company right so I mean there's a million examples of traditional businesses that have developed ways to either enter new markets or expand their footprint in existing markets by leveraging new sources of data so you think about a retailer or a wholesale distributor they have to very accurately or as accurately as possible forecast demand for goods and make sure logistically the goods are in the right place at the right time well there are million factors that go into that there's whether there's population density there's local cultural phenomena there's all sorts of things that have to be taken into consideration previously that would be near impossible to do now you can sit down again as an individual maker I can sit down at my desk and I can craft a model that consumes data from five readily available public api's or data sets to enhance my forecast and I can then create that model execute it and give it to two of my IT guy to go scale-out okay so I want to start getting into the infrastructure conversation again remember the premise of this conversation it doesn't read for structure matter we want to we want to explore that oh I start at the high level with with with cloud multi-cloud specifically we said cloud 2.0 is about hybrid multi cloud I'm gonna make a statements of you guys chime in my my assertion is that multi cloud has largely been a symptom of multi-vendor shadow IT different developers different workloads different lines of business saying hey we want to we want to do stuff in the cloud this happened so many times in the IT business all and then I was gonna govern it how is this gonna be secure who's got access control on and on and on what about compliance what about security then they throw it over to IT and they say hey help us fix this and so itea said look we need a strategy around multi cloud it's horses for courses maybe we go for cloud a for our collaboration software cloud B for the cognitive stuff cloud C for the you know cheap and deep storage different workloads for different clouds but there's got to be a strategy around that so I think that's kind of point number one and I T is being asked to kind of clean up this stuff but the future today the clouds are loosely coupled there may be a network that connects them but there's there's not a really good way to take data or rather to take code ship it to data wherever it lives and have it be a consistent well you were talking about an enterprise data plane that's emerging and that's kind of really where the opportunity is and then you maybe move into the control plane and the management piece of it and then bring in the edge but envision this mesh of clouds if you will whether it's on pram or in the public cloud or some kind of hybrid where you can take metadata and code ship it to wherever the data is leave it there much smaller you know ship five megabytes of code to a petabyte of data as opposed to waiting three months to try to ship you know petabytes to over the network it's not going to work so that's kind of the the spectrum of multi cloud loosely coupled today going to this you know tightly coupled mesh your guys thoughts on that yeah that's that's a great point and and I would add to it or expand that even further to say that it's also driving behavioral fundamental behavioral and organizational challenges within a lot of organizations and large enterprises cloud and this multi cloud proliferation that you spoke about one of the other things that's done that we talked about but probably not enough is it's almost created this inversion situation where in the past you'd have the business saying to IT I need this I need this supply chain application I need this vendor relationship database I need this order processing system now with the emergence of this cloud and and how easy it is to consume and how cost-effective it is now you've got the IT guys and the engineers and the designers and the architects and the data scientists pushing ideas to the business hey we can expand our footprint and our reach dramatically if we do this so you've get this much more bi-directional conversation happening now which frankly a lot of traditional companies are still working their way through which is why you don't see you know 100% cloud adoption but it drives those very productive full-duplex conversations at a level that we've never seen before I mean we encounter clients every day who are having these discussions are sitting down across the table and IT is not just doesn't just have a seat at the table they are often driving the go-to-market strategy so that's a really interesting transformation that we see as well in addition to the technology so there are some amazing things happening Steve underneath the covers and the plumbing and infrastructure and look at we think infrastructure matters that's kind of why we're here we're infrastructure guys but I want to make a point so for decades this industry is marked to the cadence of Moore's law the idea that you can double processing speeds every 18 months disk drive processors disk drives you know they followed that curve you could plot it out the last ten years that started to attenuate so what happened is chip companies would start putting more cores on to the real estate well they're running out of real estate now so now what's happening is we've seen this emergence of alternative processors largely came from mobile now you have arm doing a lot of offload processing a lot of the storage processing that's getting offloaded those are ARM processors in video with GPUs powering a lot of a lot of a is yours even seeing FPGAs they're simple they're easy them to spin up Asics you know making a big comeback so you've seen these alternative processes processors powering things underneath where the x86 is and and of course they're still running applications on x86 so that's one sort of big thing big change in infrastructure to support this distributed systems the other is flash we saw flash basically take out spinning disk for all high-speed applications we're seeing the elimination of scuzzy which is a protocol that sits in between the the the disk you know and the rest of the network that's that's going away you're hearing things like nvme and rocky and PCIe basically allowing stores to directly talk to the so now a vision envision this multi-cloud system where you want to ship metadata and code anywhere these high speed capabilities interconnects low latency protocols are what sets that up so there's technology underneath this and obviously IBM is you know an inventor of a lot of this stuff that is really gonna power this next generation of workloads your comments yeah I think I think all that 100% true and I think the one component that we're fading a little bit about it even in the infrastructure is the infrastructure software right there's hardware we talked a lot talked about a lot of hardware component that are definitely evolving to get us better stronger faster more secure more reliable and that sort of thing and then there's also infrastructure software so not just the application databases or that sort of thing but but software to manage all this and I think in a hybrid multi cloud world you know you've got these multiple clauses for all practical purposes there's no way around it right marketing gets more value out of the Google analytic tools and Google's cloud and developers get more value out of using the tools in AWS they're gonna continue to use that at the end of the day I as a business though need to be able to extract the value from all of those things in order to make different business decisions to be able to move faster and surface my clients better there's hardware that's gonna help me accomplish that and then there are software things about managing that whole consetta component tree so that I can maximize the value across that entire stack and that stack is multiple clouds plus the internal clouds external clouds everything yeah so it's great point and you're seeing clear examples of companies investing in custom hardware you see you know Google has its own ship Amazon its own ship IBM's got you know power 9 on and on but none of this stuff works if you can't manage it so we talked before about programmable infrastructure we talked about the data plane and the control plane that software that's going to allow us to actually manage these multiple clouds as at least a quasi single entity you know something like a logical entity certainly within workload classes and in Nirvana across the entire you know network well and and the principal or the principle drivers of that evolution of course is containerization right so the containerization phenomenon and and you know obviously with our acquisition of red hat we're now very keenly aware and acutely plugged into the whole containerization phenomenon which is great we're you're seeing that becoming almost the I can't think of us a good metaphor but you're seeing containerization become the vernacular that's being spoken in multiple different types of reference architectures and use case environments that are vastly different in their characteristics whether they're high throughput low latency whether they're large volume whether they're edge specific whether they're more you know consolidated or hub-and-spoke models containerization is becoming the standard by which those architectures are being developed and with which they're being deployed so we think we're very well-positioned working with that emerging trend and that rapidly developing trend to instrument it in a way that makes it easier to deploy easier to instrument easier to develop so that's key and I want to sort of focus now on the relevance of IBM one side one thing that we understand because that that whole container is Asian think back to your original point Dave about moving data being very expensive and the fact that the fact that you want to move code out to the data now with containers microservices all of that stuff gets a lot easier development becomes a lot faster and you're actually pushing the speed of business faster well and the other key point is we talked about moving code you know to the data as you move the code to the data and run applications anywhere wherever the data is using containers the kubernetes etc you don't have to test it it's gonna run you know assuming you have the standard infrastructure in place to do that and the software to manage it that's huge because that means business agility it means better quality and speed alright let's talk about IBM the world is complex this stuff is not trivial the the more clouds we have the more edge we have the more data we have the more complex against IBM happens to be very good at complex three components of the innovation cocktail data AI and cloud IBM your customers have a lot of data you guys are good with data it's very strong analytics business artificial intelligence machine intelligence you've invested a lot in Watson that's a key component business and cloud you have a cloud it's not designed to compete not knock heads and the race to zero with with the cheap and deep you know storage clouds it's designed to really run workloads and applications but you've got all three ingredients as well you're going hard after the multi cloud world for you guys you've got infrastructure underneath you got hardware and software to manage that infrastructure all the modern stuff that we've talked about that's what's going to power the customers digital transformations and we'll talk about that in a moment but maybe you could expand on that in terms of IBM's relevance sure so so again using the kind of maker the maker economy metaphor bridging from that you know individual level of innovation and creativity and development to a broadly distributed you know globally available work loader or information source of some kind the process of that bridge is about scale and reach how do you scale it so that it runs effectively optimally is easily managed Hall looks and feels the same falls under the common umbrella of services and then how do you get it to as many endpoints as possible whether it's individuals or entities or agencies or whatever scale and reach iBM is all about scale and reach I mean that's kind of our stock and trade we we are able to take solutions from small kind of departmental level or kind of skunkworks level and make them large secure repeatable easily managed services and and make them as turnkey as possible our services organizations been doing it for decades exceptionally well our product portfolio supports that you talk about Watson and kind of the cognitive computing story we've been a thought leader in this space for decades I mean we didn't just arrive on the scene two years ago when machine learning and deep learning and IO ste started to become prominent and say this sounds interesting we're gonna plant our flag here we've been there we've been there for a long time so you know I kind of from an infrastructure perspective I kind of like to use the analogy that you know we are technology ethos is built on AI it's built on cognitive computing and and sort of adaptive computing every one of our portfolio products is imbued with that same capability so we use it internally we're kind of built from AI for AI so maybe that's the answer to this question of it so what do you say that somebody says well you know I want to buy you know my flash storage from pure AI one of my bi database from Oracle I want to buy my you know Intel servers from Dell you know whatever I want to I want to I want control and and and I gotta go build it myself why should I work with IBM do you do you get that a lot and how do you respond to that Steve I think I think this whole new data economy has opened up a lot of places for data to be stored anywhere I think at the end of the day it really comes down to management and one of the things that I was thinking about as you guys were we're conversing is the enterprise class or Enterprise need for things like security and protection that sort of thing that rounds out the software stack in our portfolio one of the things we can bring to the table is sure you can go by piece parts and component reform from different people that you want right and in that whole notion around fail-fast sure you can get some new things that might be a little bit faster that might be might be here first but one of the things that IBM takes a lot of pride was a lot of qual a lot of pride into is is the quality of their their delivery of both hardware and software right so so to me even though the infrastructure does matter quite a bit the question is is is how much into what degree so when you look at our core clients the global 2,000 right they want to fail fast they want to fail fast securely they want to fail fast and make sure they're protected they want to fail fast and make sure they're not accidentally giving away the keys to the kingdom at the end of the day a lot of the large vendor a lot of the large clients that we have need to be able to protect their are their IP their brain trust there but also need the flexibility to be creative and create new applications that gain new customer bases so the way I the way I look at it and when I talk to clients and when I talk to folks is is we want to give you them that while also making sure they're they're protected you know that said I would just add that that and 100% accurate depiction the data economy is really changing the way not only infrastructure is deployed and designed but the way it can be I mean it's opening up possibilities that didn't exist and there's new ones cropping up every day to your point if you want to go kind of best to breed or you want to have a solution that includes multi vendor solutions that's okay I mean the whole idea of using again for instance containerization thinking about kubernetes and docker for instance as a as a protocol standard or a platform standard across heterogeneous hardware that's fine like like we will still support that environment we believe there are significant additive advantages to to looking at IBM as a full solution or a full stack solution provider and our largest you know most mission critical application clients are doing that so we think we can tell a pretty compelling story and I would just finally add that we also often see situations where in the journey from the kind of maker to the largely deployed enterprise class workload there's a lot of pitfalls along the way and there's companies that will occasionally you know bump into one of them and come back six months later and say ok we encountered some scalability issues some security issues let's talk about how we can develop a new architecture that solves those problems without sacrificing any of our advanced capabilities all right let's talk about what this means for customers so everybody talks about digital transformation and digital business so what's the difference in a business in the digital business it's how they use data in order to leverage data to become one of those incumbent disruptors using Ginny's term you've got to have a modern infrastructure if you want to build this multi cloud you know connection point enterprise data pipeline to use your term Randy you've got to have modern infrastructure to do that that's low latency that allows me to ship data to code that allows me to run applet anywhere leave the data in place including the edge and really close that gap between those top five data you know value companies and yourselves now the other piece of that is you don't want to waste a lot of time and money managing infrastructure you've got to have intelligence infrastructure you've got to use modern infrastructure and you've got to redeploy those labor assets toward a higher value more productive for the company activities so we all know IT labor is a chop point and we spend more on IT labor managing Leung's provisioning servers tuning databases all that stuff that's gotta change in order for you to fund digital transformations so that to me is the big takeaway as to what it means for customer and we talked about that sorry what we talked about that all the time and specifically in the context of the enterprise data pipeline and within that pipeline kind of the newer generation machine learning deep learning cognitive workload phases the data scientists who are involved at various stages along the process are obviously kind of scarce resources they're very expensive so you can't afford for them to be burning cycles and managing environments you know spinning up VMs and moving data around and creating working sets and enriching metadata that they that's not the best use of their time so we've developed a portfolio of solutions specifically designed to optimize them as a resource as a very valuable resource so I would vehemently agree with your premise we talked about the rise of the infrastructure developer right so at the end of the day I'm glad you brought this topic up because it's not just customers it's personas Pete IBM talks to different personas within our client base or our prospect base about why is this infrastructure important to to them and one of the core components is skill if you have when we talk about this rise of the infrastructure developer what we mean is I need to be able to build composable intelligent programmatic infrastructure that I as IT can set up not have to worry about a lot of risk about it break have to do in a lot of troubleshooting but turn the keys over to the users now let them use the infrastructure in such a way that helps them get their job done better faster stronger but still keeps the business protected so don't make copies into production and screw stuff up there but if I want to make a copy of the data feel free go ahead and put it in a place that's safe and secure and it won't it won't get stolen and it also won't bring down the enterprise's is trying to do its business very key key components - we talked about I infused data protection and I infused storage at the end of the day it's what is an AI infused data center right it needs to be an intelligent data center and I don't have to spend a lot of time doing it the new IT person doesn't want to be troubleshooting all day long they want to be in looking at things like arm and vme what's that going to do for my business to make me more competitive that's where IT wants to be focused yeah and it's also we just to kind of again build on this this whole idea we haven't talked a lot about it but there's obviously a cost element to all this right I mean you know the enterprise's are still very cost-conscious and they're still trying to manage budgets and and they don't have an unlimited amount of capital resources so things like the ability to do fractional consumption so by you know pay paper drink right buy small bits of infrastructure and deploy them as you need and also to Steve's point and this is really Steve's kind of area of expertise and where he's a leader is kind of data efficiency you you also can't afford to have copy sprawl excessive data movement poor production schemes slow recovery times and recall times you've got a as especially as data volumes are ramping you know geometrically the efficiency piece and the cost piece is absolutely relevant and that's another one of the things that often gets lost in translation between kind of the maker level and the deployment level so I wanted to do a little thought exercise for those of you think that this is all you know bromide and des cloud 2.0 is also about we're moving from a world of cloud services to one where you have this mesh which is ubiquitous of of digital services you talked about intelligence Steve you know the intelligent data center so all these all these digital services what am I talking about AI blockchain 3d printing autonomous vehicles edge computing quantum RPA and all the other things on the Gartner hype cycle you'll be able to procure these as services they're part of this mesh so here's the thought exercise when do you think that owning and driving your own vehicle is no longer gonna be the norm right interesting thesis question like why do you ask the question well because these are some of the disruptions so the questions are designed to get you thinking about the potential disruptions you know is it possible that our children's children aren't gonna be driving their own car it's because it's a it's a cultural change when I was 16 year olds like I couldn't wait but you started to see a shifted quasi autonomous vehicles it's all sort of the rage personally I don't think they're quite ready yet but it's on the horizon okay I'll give you another one when will machines be able to make better diagnosis than doctors actually both of those are so so let's let's hit on autonomous and self-driving vehicles first I agree they're not there yet I will say that we have a pretty thriving business practice and competency around working with a das providers and and there's an interesting perception that a das autonomous driving projects are like there's okay there's ten of them around the world right maybe there's ten metal level hey das projects around the world what people often don't see is there is a gigantic ecosystem building around a das all the data sourcing all the telemetry all the hardware all the network support all the services I mean building around this is phenomenal it's growing at a had a ridiculous rate so we're very hooked into that we see tremendous growth opportunities there if I had to guess I would say within 10 to 12 years there will be functionally capable viable autonomous vehicles not everywhere but they will be you will be able as a consumer to purchase one yeah that's good okay and so that's good I agree that's a the time line is not you know within the next three to five years all right how about retail stores will well retail stores largely disappeared we're we're rainy I was just someplace the other day and I said there used to be a brick-and-mortar there and we were walking through the Cambridge Tseng Galleria and now the third floor there's no more stores right there's gonna be all offices they've shrunken down to just two floors of stores and I highly believe that it's because you know the brick you know the the retailers online are doing so well I mean think about it used to be tricky and how do you get in and and and I need the Walmart minute I go cuz I go get with Amazon and that became very difficult look at places like bombas or Casper or all the luggage plate all this little individual boutique selling online selling quickly never having to have to open up a store speed of deployment speed of product I mean it's it's it's phenomenal yeah and and frankly if if Amazon could and and they're investing billions of dollars and they're trying to solve the last mile problem if Amazon could figure out a way to deliver ninety five percent of their product catalog Prime within four to six hours brick-and-mortar stores would literally disappear within a month and I think that's a factual statement okay give me another one will banks lose control traditional banks lose control of the payment systems you can Moselle you see that banks are smart they're buying up you know fin tech companies but right these are entrenched yeah that's another one that's another one with an interesting philosophical element to it because people and some of its generational right like our parents generation would be horrified by the thought of taking a picture of a check or using blockchain or some kind of a FinTech coin or any kind of yeah exactly so Bitcoin might I do my dad ask you're not according I do I don't bit going to so we're gonna we're waiting it out though it's fine by the way I just wanted to mention that we don't hang out in the mall that's actually right across from our office I want to just add that to the previous comment so there is a philosophical piece of it they're like our generation we're fairly comfortable now because we've grown up in a sense with these technologies being adopted our children the concept of going to a bank for them will be foreign I mean it will make it all have no context for the content for the the the process of going to speak face to face to another human it just say it won't exist well will will automation whether its robotic process automation and other automation 3d printing will that begin to swing the pendulum back to onshore manufacturing maybe tariffs will help to but again the idea that machine intelligence increasingly will disrupt businesses there's no industry that's safe from disruption because of the data context that we talked about before Randy and I put together a you know IBM loves to use were big words of transformation agile and as a sales rep you're in the field and you're trying to think about okay what does that mean what does that mean for me to explain to my customer so he put together this whole thing about what his transformation mean to one of them was the taxi service right in the another one was retail so and not almost was fencers I mean you're hitting on on all the core things right but this transformation I mean it goes so deep and so wide when you think about exactly what Randy said before about uber just transforming just the taxi business retailers and taxis now and hotel chains and that's where the thing that know your customer they're getting all of that from data data that I'm putting it not that they're doing work to extract out of me that I'm putting in so that autonomous vehicle comes to pick up Steve Kenaston it knows that Steve likes iced coffee on his way to work gives me a coupon on a screen I hit the button it automatically stops at Starbucks for me and it pre-ordered it for me you're talking about that whole ecosystem wrapped around just autonomous vehicles and data now it's it's unbeliev we're not far off from the Minority Report era of like Anthem fuck advertising targeted at an individual in real time I mean that's gonna happen it's almost there now I mean you just use point you will get if I walk into Starbucks my phone says hey why don't you use some points while you're here Randy you know so so that's happening at facial recognition I mean that's all it's all coming together so and again underneath all this is infrastructure so infrastructure clearly matters if you don't have the infrastructure to power these new workloads you're drugged yeah and I would just add and I think we're all in agreement on that and and from from my perspective from an IBM perspective through my eyes I would say we're increasingly being viewed as kind of an arms dealer and that's a probably a horrible analogy but we're being used we're being viewed as a supplier to the providers of those services right so we provide the raw materials and the machinery and the tooling that enables those innovators to create those new services and do it quickly securely reliably repeatably at a at a reasonable cost right so it's it's a step back from direct engagement with consumer with with customers and clients and and architects but that's where our whole industry is going right we are increasingly more abstracted from the end consumer we're dealing with the sort of assembly we're dealing with the assemblers you know they take the pieces and assemble them and deliver the services so we're not as often doing the assembly as we are providing the raw materials guys great conversation I think we set a record tends to be like that so thank you very much for no problem yeah this is great thank you so much for watching everybody we'll see you next time you're watching the cube

from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation welcome everybody to this cube conversation my name is Dave Volante and we're here in our Palo Alto studios Medusa doc R is here he's an investor and entrepreneur and a friend we're do great to see you again thanks so much for coming in thank you it's a head too long it is you and I sat down and had a conversation on the cube so it's been well yeah yeah well you've been on the cube a bunch and you've a I've seen some great conversations that you had with with with Peter and John so thanks for making the time and coming back in thank you so I want to start with when I go around and talk to executives every CEO is trying to get digital right you know whatever that means you know they know it's important and they're trying to figure it out they know it relates to data they know they have to leverage data they know this buzzword of digital transformation what are you seeing when you talk to executives and companies how real is this digital transformation is it a fad or is it a substantive good question to look from my view point of view digital transformation is the word people use but at the end of the day CIOs have to disrupt their businesses every CEO has to figure out am i cutting the cost I'm a helping companies grow in revenue from a look at from a board perspective and what people are looking at the investor perspective most CEOs are CEOs are looking at somehow looking running their operations on a day-to-day basis to that point I think most CEOs are expecting see I was to do the new innovative things at you probably hearing that people are adding CDO as a title yeah so it's up to see I were to see will it be the innovate to CIO it's like you have two kids like in your case your four kids you have two how do you make sure that all four kids are given the equal responsibility so Ciara has to decide look I have budget X X by two goes to my existing business X by two goes to the new business that decision making is not happening with the see I was today and that's what the distal transformation has to be is going on in a what I call not in a disruptive manner but the CEOs who have figure out how to disrupt it I really taking the next stage the next thing that people are interested there is where do I start right you have all should I start with my CRM supply chain should I start with my IT you got to figure out what all the but start someplace you pick one the area but that has to be disruptive in the sense we are living in the age of where I call it autonomous everything right there's a data there is cloud and there's AI our mission like what are you these three are such a large disruption in our industry see us how to figure out and say what can I do in terms of cost saving in terms of revenue growth but that can't be incremental it has to be revolutionary so I often say we've decades we've marched to the cadence of Moore's law in this industry that's where innovation came from no longer it's as you said it's data now for the last 10 years and you were involved in this we were collecting all this data we lowered the cost of collecting data and and and in running data warehouses with Hadoop but now data's plentiful insights aren't so you have data you have to apply machine intelligence to that data and then cloud gives you scale so that's like the new innovation cocktail so you agree that digital I agree digital transformation is real and the other dynamic mudo is you see companies are because it's data are able to traverse industries used to be you're in an industry if you're in financial services that's it if you're in healthcare that's it now you see Amazon's and content apples into financial services so people are afraid of getting disrupted you've got this new innovation cocktail so your point was really get started so you've got a shift resources you don't have unlimited budget right so how do people do that how are they taking cost out of the business and how are they reapportioning that cost for innovation really good so I'll give you two examples from Megan again thinking of where I see it one is for CIOs has something called IT operations IT operation is a very big piece that people need to figure out how to get the cost out of it the IT operations cannot be developed we've been running IT for last 30 years I mean what are the word they used I know Gartner uses the word called AAA Hobbs I don't care what the word is but the key is you have to run your 18 autonomous manner we are living in the age of your trading is autonomous your my your four on game by four on K is being traded through hedge funds your add technologies autonomous with Facebook Google and Amazon with all data when I saw with with Casper and Splunk we made cybersecurity autonomous to whatever extent threat detection but when it came to IT operations and IT customer support today manual if I may see over right now I'll invest on customer service and support to start as a point of what can I do to make my service agents better or what can I do to make the end users or the users experience better without going to a human can I eliminate the human in the equation here the mileage may vary it's like the driverless consequence you have level 1 to level 5 they may like to have autopilot some people may have a fully autonomous car depending on the organization you got to have a right amount of autonomous City in your organization both for IT operations and IT Service Management that hasn't happened and that will be happen in the next 4 5 years so let's talk about that you were at ServiceNow for a period of time they've obviously disrupted the old-line helpdesk and you know they really did a job on BMC and hewlett-packard etc are they in a position to take that next step in when you go to service now analogy here folks talk about AI and infusing AI obviously there's a lot of data being collected is that the right model I mean if they've automated forms but you think you're talking about something more I help us understand that sure looks abused know is in a great position they'll continue to do well it's a great company right I think what's going to happen next is how can companies like ServiceNow take her to the next stage right either become a partner with ServiceNow or service now itself we'll do it a little bit new companies will be for me one angle is forces enterprises is this game going to be for enterprises same playbook as a playbook for the cloud so imagine an apps that are born on the cloud their IT operations data their ticketing data where will that go to that means we think through enterprise data which is enterprise apps and so as they need to figure out so if I am a company today if I'm daring I need to decide what will I do for my enterprise applications and services what do I do it for my cloud Orion services so that is addition you have to make it at the top once it goes down the next level then able to decide is it for IT support customer support or IT operations what can I do in terms of augmenting there if I do is just to make my agents better you can take the cost out of the equation the cost should be is can I automate to the point I can eliminate 50% of my DevOps 50% of my SR ease my role of the come is in the next four five years this 70 80 % of devops I tell you when I study jobs will be gone that should be automated it should be a driverless IT autonomous IT people should have him that's not even a moonshot goal we all in America let's make great our great again this is our time it's IT if we don't do it some other country will do it Chile is going to eat us for lunch so he basically putting forth the scenario a DevOps was essentially a stepping stone and you see that largely going away it has to be it has been automated I'm not going to hide hundreds of tunas I called Manuel tuners right yes I'll need some DevOps people I need some IT admin things that system cannot do it algorithmically should go to humans at some point but there are enough things like if you want to install something in your laptop why should I talk to somebody else if I want to upgrade to Microsoft Office if I want to buy a CRM license if I want to get a zoom provisioning why do I need to talk to a human being in this equation can I oughta mater complete autonomous can I get to a level five autonomous in IT right that's what I'm looking towards robotic process automation play a role here can our PA we've done some some events with automation anywhere new iPad you're seeing huge valuations uipath as supposedly as another six billion dollar evaluation I mean you know amazing unicorn plus plus plus can those technologies be applied to solve this problem yes or no I think it depends on what the HRP are under star doing IP is a great topic right not be resolved very successful what I'm talking about is our IT operations and IT support and customer support automation can our PA guys take their technology their substrate a platter sure they can try it but these are all have to be grown organically doing this in nit going for customer service and support doing it for the cloud has its own its own skin its own platform like you and me were talking earlier if I'm doing this thing on Amazon why wait and launch a VM I won't even do it like if a new ticket comes in I should be doing through kinases I should be doing through my lambda functions I shouldn't be my cost of goods with so much that I want it should not cost me anything until the point Dave generates a ticket to me first all why should Dave generate a ticket right look at the very much extreme model of the test laws just like our today tells me when should I service my car why should you do the same thing like I should be coming and telling your SharePoint is going to go down they have today your Kube application you cannot do an interview with me too unless you fix it that is what the world wants to go so back to service management for minutes so in the old days our service manager was too cumbersome we really didn't have a single CMDB it just really didn't work that well it didn't change anything a lot of tickets that's what it did service now obviously solved that that that problem but what I'm inferring from what you're saying is it's still too expensive the entire infrastructure it needs to be more streamlined and automation is the answer absolutely so I think if you take it'll add layers and layers the first is in the support starting women from CMDB most organizers say my CMD that I still all are stale that's never accurate how can I get a dynamic view of Dave's ink right I should know when and that has to be done at the level of services and apps and at kubernetes level 2 container level once I have a blueprint of what my organization is then I need to know how do I handle the tickets against it then I can I do a health monitoring for all my CIS right I should be telling the outage put it at the another what business carries is my business running correctly you do have a downtime what is going to happen even though if I am false positives few times people are expecting saying that tell me proactively what services will impact and who will be impacted so I can take a corrective action and that will happen starting from CMDB automation I actually call it cloud CMDB our dynamic CMDB in the world of cloud and dynamic let's make a good cmdbs dynamic and accurate then take it to the ultimate outage prediction right if I can give your business up time and outage prediction that would be Nirvana are you telling me that IT cannot solve it you and me are saying in Palo Alto a driverless cars are going around we are going to see it in our lifetime IT can be so complex that the car can be autonomous but IT cannot be I don't buy them well I mean you hear about all the systems are down or my systems are slow today that's that's a form of outage that costs Fortune 2000 companies and money I mean it's you know 50 60 thousand dollars a minute in this in some cases so the and I think sometimes people aren't aware as to how much how much revenue is lost to downtime or lost productivity so there's huge huge gains to be made there and it seems that the cloud is the platform on which you're going to you're gonna build these these these natural choice it has to be yeah and it has we want a cloud to you can't say we are in the eight if you are a noose new cloud you're building it I tell people bill it is a multi cloud your same code should work on GCP Amazon and Azure right and on VMware if you want to be a private cloud but should be same the same codebase should be able to compile and run on all multiple processor kubernetes micro services that's really the enabler there right right at once run it anywhere interesting conversation multi-cloud you're hearing a lot of discussion you know certainly in DC the Jedi case Oracle is contesting that when you read the rulings from the General Accounting Office that basically the the DoD determined that multi-cloud is is less secure more expensive more complex now that's the DoD everybody's gonna have multi cloud because multi-cloud is multi vendor sure but it's interesting you don't hear Amazon talking about multi cloud other than you don't want to do it because it's too expensive but everybody else is talking about multi cloud is kubernetes somewhat of a threat to that Amazon posture I don't think I think if you look at Amazon is saying they call it hybrid cloud the word may be different multi cloud or hybrid cloud yeah say they've already partnered like the best public cloud partner with the best pressure of your house is awesome announcement right so vehement software ever talk to Pat gal singer and his team and look they got VMware working with AWS vice-versa so that's it great I mean maybe even call it a two ecosystem but they got that whole thing working there yeah anything with agile is going to do with their public cloud on Azure with as you understand I'll just tack on prom yeah right everybody has 70 mgcp will figure out so then after a while if you and me as a customer I should be able to move things many times it happen is I'm not going to move things dynamically for a nibble but if I want I don't want to vendor lock it I want a code such that if tomorrow something happens I should be able to have an option to move my code base to a different cloud and that's what multi-cloud will happen as a requirement as you build it how much you exercise are not people will design software going for a formal techno so a whole new vector of conversation I would love to get your opinion on that multi-cloud opportunity obviously Cisco's going after VMware's in the strong position there certainly Microsoft is is vying for that you have a ton of startups looking at this IBM with the Red Hat acquisition now is in a in a pretty strong position you know given its open source chops how do you see that whole multi-cloud you know vendor landscape shaking out I think I got really good I have a TD for this at the end when the dust settles you won't have 100 aircraft carriers you will have only four or five yeah so it's like what happened in 90s compact went away Dec went away so same thing is going to happen here there will be four or five vendors will survive there will be Amazon's as yours maybe GCPs VMware's maybe it's Cisco and IBM talks about a I mean there's like maybe alley cloud in China you won't have hundreds of cloud so the number is already decreasing it will let be 10 will it be 5 will it before that still you will see the tall rise but it's already been the whole council isn't happening so if I'm a customer if I'm a vendor if I'm a startup or a public company I'm going to build it only for a few these multi cloud vendors I'm not going to across hundred yeah because the marginal economics of those those hyper clouds we've been saying this for years if there's just so much more compelling and at the end of the day if the economics are 10x less expensive and more attractive that they're gonna win you know and and I think even though you have thousands and thousands of service providers who call themselves cloud we're talking about a different kind of cloud it's got one of those you know it when you see it types of things and I'm going to add something so if you take this back to your earlier question about where the disruption is happening we talked about all the customer service support an IT service management industry but imagine if an app is born on the cloud call it cloud native applications you have millions of new apps that are there on this cloud platforms what is that going to do where is the data going there they want another customer service and support applicant on their platform it currently it's like I'm in your house I'm drinking your wine but when it comes to managing my customers of an operation I will take your log data your even data or take indeed and put in somebody else's house even though John is your partner when you put it there it doesn't make sense it should run it inside yours so all these vendors would want a native application that is running on their platform solving their customer data which hasn't happened yet well this is interesting so obviously Oracle has its own cloud but you're seeing well see work day Salesforce service now all these SAS companies just used to build their own clouds they're building their own data centers Chuck Chuck Philips oven forces I don't friends don't let friends build data centers so maybe he's prescient maybe the trend is that these apps are going to largely predominantly run in the public cloud the Oracle IBM notwithstanding they've got the resources to maybe you know tough it out is that the scenario that you see I have take the consumer companies whether you take V work Airbnb uber all these guys you are already seeing them on to some opinion maybe they have their own datacenter but there are vastly learning and public clouds right and you have already seen that's even the big SAS vendors whether it's Adobe yeah it'll be solid partner with Microsoft Azure workday is partnering with Amazon you saw em Salesforce partnering with Google cloud and AW so you're only seeing these vendors the large SAS when there's already saying in order for me for economics wise it doesn't make sense whether it's for my marketing cloud my service cloud my ecommerce cloud I want this to run on this cloud platform to get scale cost of economics and also I need my services that are built there with a new substrate like we talked about that's lambda functions to kinases I'm not going to do it on my platform but and that trend is going on it's just accelerating so how are you spending your time these days you've had a very successful entrepreneur investor you've been CEO of multiple companies what do you do in these days I'm look I'm very happy with what I'm doing right now so I spend a lot of time with this company called I set up that's right I'm even we talked about it it's a startup company in Palo Alto their vision is to apply like what we got AI ops applying AI for digital transformation for AI customer service I trps oh I like the region look I want to spend time with companies which are taking a big bet right it's like in our IT industry nobody talks about moonshot goals let's take a bigger bet let's take a much vision of for five year ten years what can we disrupt right and I look at those companies I invest with those companies and spending time with them I'm learning a lot in the process I'm contributing back to the those companies well you know sitter I was on Twitter yesterday with with a little group we're having an interesting discussion about you know how things are changing the dynamics of where innovation comes over so we started this conversation with that sort of new innovation cocktail and there just seems to be a whole new fabric of services not only it's not just remote cloud services anymore it's these embedded services that are can think they can act they can sense and it's ubiquitous now even the edge autonomous vehicles we're entering a whole new era it's very exciting right and again one thing that we didn't talk to see Mike and son and my it again it's society has to have regulations and will come if you look at the what's happened in this whole call center customer service industry if autonomous city will happen of any level from level even if I automate 30 percent of your customer service and you don't touch a human being when you are at home for your Comcast to your nest imagine all those services inside your home from field service to if they get automated what's going to happen first of all if Sally's gonna improve your costs are going to reduce if I'm a business I can take that money and invest somewhere else but more importantly those most of those things it's it's a big disruption happening in the outsourced industry right these are your jobs in China India Philippines Vietnam my concern is dart saying that there will be a certain is going to happen people are not paying attention to that and this this strain has already left the station yeah it's going to come to a platform again some next platform but next for five years you'll see a tremendous disruption in this area of digital transformation well I remember a couple decades ago there was a lot of talk about well you people spending a lot of money on IT but that you don't see it in the productivity numbers and all of a sudden because of the PC revolution the productivity went through the roof you're hearing similar sort of discussions now we feel like productivity is about to explode because of what you're saying here absolutely and again the per back to the RP has already shown the value our peers no longer in each category it's what we talked about success renders from you iPad automation anywhere blue prism that just on the back end of the supply chain and RPF cell taking the two front office applying that to customer service facing to your crm facing that your IT hasn't happened yet can I automatically can I ought Americans right from an employee experience to customer experience that productivity if you employ it you'll get more customers doing that yeah it scares people but but it's the future so you better embrace it and lean in voodoo thanks so much oh let's go always measure to see you alright thanks for watching everybody this is David day from our studios in Palo Alto and we'll see you next time thank you [Music]