(bouncy string music) >> TheCUBE presents KubeCon and CloudNativeCon Europe 2022, brought to you by Red Hat, the cloud native computing foundation, and its ecosystem partners. >> Welcome to Valencia, Spain in KubeCon and CloudNativeCon Europe 2022. I'm your host, Keith Townsend. And we're getting to the end of the day, but the energy level has not subsided on the show floors. Still plenty of activity, plenty of folks talking. I have, as a second time guest, this KubeCon, which is unusual, but not, I don't think, disappointing in any way, we're going to have plenty of content for you. Owen, you're the CPO, Owen Garrett, you're the CPO of... >> Of Deepfence. >> App Deepfence. >> Yeah. >> We're going to shift the conversation a little bit. Let's talk about open source availability, open source security availability for everybody. I drive a pretty nice SUV back home and it has all these cool safety features, that warns me when I'm dozing off, it lets me know when I'm steering into another lane, and I'm thinking, why isn't it just a standard thing on every vehicle? Isn't safety important? Think about that for open source security. Why isn't open source security just this thing available to every project and product? >> Keith, I love that analogy. And thanks for having me back! We had a lot of fun yesterday. >> Yeah, we did. >> Yeah. We, at Deepfence, we really believe security is something that everybody should benefit from. Because if applications aren't secure, if vulnerabilities find their way into production, then your mother, my aunt, uncle, using the internet, use an app, their identity is stolen, through no fault of their own, because the developer of that application didn't have access to the tools that he or she needed to secure the application. Security is built around public knowledge. When there are vulnerabilities, they're shared with the community. And we firmly believe that we should provide open source, accessible tools that takes that public knowledge and makes it easy for anybody to benefit from it. So at Deepfence, we've created a software platform, it's 100% open source, called ThreatMapper. And the job of this platform is to scan your applications as they're running and find, identify, are there security vulnerabilities that will find their way into production? So we'll look for these vulnerabilities, we'll use the wisdom of the community to inform that, and we'll help you find the vulnerabilities and identify which ones you've got to fix first. >> So when you say use the wisdom of the community, usually one of the hard things to crack is the definitions, what we called virus definitions in the past. >> Yes. How do we identify the latest threats? And that's usually something that's locked behind value. How do you do that >> You're right. when it comes to open source? >> You're right. And it's worrying, 'cause some organizations will take that and they'll hide that extra value and they'll only make it available to paying customers. Ethically, I think that's really wrong. That value is out there. It's just about getting it into hands of users, of developers. And what we will do is we'll take public feeds, like the CVEs from the NVD, National Vulnerability Database, we'll take feeds from operating system vendors, for language packs, and then we help organizations understand the context so they can unlock the value. The problem with security scanning is you find hundreds of thousands of false positives. Like in your SUV. As you drive down the street there are hundreds of things that you could hit. >> You're right. >> But you don't hit any of them. They're false positives, you don't need to worry about them. It's the one that walks across the road that you've got to avoid, you need to know about. We do the same with security vulnerabilities. We help you understand of these thousands of issues that might be present in your applications, which are the ones that really important? 'Cause developers, they're short of time. They can't fix everything. So we help them focus on the things that are going to give the biggest bang for their time. Not for the buck, because we're not charging them for it, but for their time. So when they invest time in improving the security of the applications, we, with our open source, accessible projects, will help guide them to invest that as best as possible. >> So I'm a small developer. I lead a smaller project, just a couple of developers. I don't have a dedicated security person. What's my experience in adopting this open source solution? Now I biting off more than I can chew and creating too much overhead? >> We try and make it as easy as possible to consume. So you're a developer, you're building applications, you're here at KubeCon, so you're probably deploying them onto Kubernetes, and you've probably used tools already to check them and make sure that there aren't vulnerabilities. But, nevertheless, you've got to let some of those vulnerable packages into production and there could be issues that were disclosed after you scanned. So with our tool, you place a little agent in your Kubernetes cluster, it's a DaemonSet, it's a one held command to push it out, and that talks back to the console that you own. So everything stays with you. Nothing comes to us, we respect your privacy. And you can use that to then scan and inventory your applications anytime you want and say, is this application still secure or are there new vulnerabilities disclosed recently that I didn't know about? And we make the user experience as easy as we can. We've had some fantastic chats on the demo booth here at KubeCon, and hey, if times were different, I'd love to have you across the booth, and we'll click and see. The user experience is as quick and as sweet and as joyable as we can make it. >> All right. We've had a nice casual chat up to this point, but we're going to flip the switch a little bit. I'm going to change personalities. >> All right. >> It's almost like, if you're an comic book fan, the Incredible Hulk. Keith, the mild-mannered guy with a button up shirt. Matter of fact, I'm going to unbutton my jacket. >> Okay. >> And we're going to get a little less formal. A little less formal, but a little bit more serious, and we're going to, in a second, start CUBE clock and you're going to give me the spiel. You're going to go from open source to commercial and you're going to try and convince me- >> Okay. >> In 60 seconds, or less, you can leave five seconds on the table and say you're done, why you should do- >> Here's the challenge. >> Why I should listen to you. >> Owen: Why you should listen to Deepfence. >> Why should you listen to app Deepfence? So I'm going to put the shot clock in my ear. Again, people never start on time. You need to use your whole 60 seconds. Start, CUBE clock. >> Keith, (dramatic horn music) you build and deploy applications, on Kubernetes or in the cloud. Your developers have ticked it off and signed off- >> Zero from zero is still zero. >> Saying they're secure, but do you know if they're still secure when they're running in production? With Deepfence ThreatMapper, it's an open source tool. >> You've got to call- >> You can scan them. >> Before you ball. You can find the issues >> Like you just thought out. >> In those applications running in your production environment and prioritize them so you know what to fix first. But, Keith, you can't always fix them straight away. >> Brands need to (indistinct). >> So deploy ThreatStryker, our enterprise platform, to then monitor those applications, see what's happening in real time. (dramatic horn music) Is someone attacking them? Are they gaining control? And if we see >> Success without, the exploits happening- success without passion- >> We will step in, >> Is nothing. >> Tell you what's going on. >> You got to have passion! >> And we can put the thumb on the attacker. We can stop them reaching the application by fire rolling just them. We can freeze the application (dramatic horn music) so it restarts, so you can go and investigate later. >> Keith: Five seconds. >> Be safe, shift left, (dramatic string music) but also, secure on the right hand side. >> That's it. I think you hit it out the park. Great job on- >> Cheers, Keith. >> Cheers. You did well under the pressure. TheCUBE, we bring the values. We're separating the signal from the noise. 60 seconds. That's a great explanation. From Valencia, Spain, I'm Keith Townsend, and you're watching theCUBE, the leader in high tech coverage. (bouncy percussive music)

>>The cube presents, Coon and cloud native con Europe, 2022, brought to you by red hat, the cloud native computing foundation and its ecosystem partners. >>Welcome to Valencia Spain in Coon and cloud native con Europe, 2022. I'm Keith Townsend, along with my host, Paul Gillon senior editor, enterprise architecture at Silicon angle. We are continuing the conversation here at KU con cloud native con around security app defense. Paul, were you aware it was this many security challenges and, and that were native to like cloud native >>Well there's security challenges with every new technology. And as we heard, uh, today from our, some of our earlier guests, uh, containers and Kubernetes naturally introduce new variables in the landscape and that creates the potential vulnerabilities. So there's a whole industry that's evolving around that. And what we've been looking at today, yesterday, we talked very much about managing Kubernetes today. We're talking about many of the nuances of building a, a Kubernetes based environment and security is clearly one of them. >>So welcome our guests on Garrett, head of products. >>Thank >>You and community at deep fence. You know what I'm going. I'm going to start out the question with a pretty interesting security at scale is one of your taglines. >>Absolutely. >>What does that mean? Exactly. >>So Kubernetes is all about scale securing applications and Kubernetes is a completely different game to securing your traditional monolithic legacy enterprise applications. Kubernetes grows it scales it's elastic, and the perimeter around a Kubernetes application is very, very porous. There are lots of entry points. So you can't think about securing a cloud native application. The way that you might have secured a monolith securing a monolith is like securing a castle. You build a wall around it. You put guards on the gate. You control, who comes in and out, and job is more or less done securing a cloud native application. It's like securing a city. People are roaming through the city without checks and balances. There are lots of services in the city that you've got to check and monitor. It's extremely porous. So sec, all of the security problems in Kubernetes with cloud native applications, they're amplified by scale, the size of the application, the number of nodes and the complexity of the application and the way that it's built and delivered. >>That's, uh, kind of a chilling phrase. The perimeter is porous. Uh, yeah, companies are adopting Kubernetes right now. Evidently bringing in all of these new, these new, uh, vulnerability points. Do they know what they're getting into >>Many don't, there's, there's a huge amount of work around trying to help organizations make the transition from thinking about applications as single components to thinking about them as microservices with multiple little, little components, it's a really essential step because that's what allows businesses to evolve, to digitize, to deliver services, using APIs, mobile, mobile apps. So it's a necessary technical change, but it brings with it. Lots of challenges and security is one of those biggest challenges. >>So as I'm thinking about that poorest nature, I can't help, but think, you know, if I have my, my traditional IPS does a really great job of blocking that centralized data center and access to that centralized data center. As I think about that city example that you gave me, I'm thinking, you know what? I have intruders or not even intruders. I have bad actors within my city. You >>Do you, how >>Do, how does deep defense help protect me from those bad actors that are inside or roaming the city? >>So this is the wonderful, unique technology we have within deep fence. So we install little sensors, little lightweight sensors on each host. That's running your application on Kubernetes nodes as a Damon set against Fargate instances on Docker hosts on bare metal. And those sensors install little taps into the network using E B P F and they monitor the workloads. So it's a little bit like having CCTV cameras throughout your city tracking what's happening. There are a lot of solutions which we'll look at what happens on a workload traditional XDR solutions that look for things like process changes or file system changes. And we gather those signals indicators of compromise, but those alone are too little too late. They tell you that a breach has probably already happened. What deep defense does is we also look at the network. We gather network signals. We can see someone using a, a reconnaissance tool roaming through your application, sending probe traffic to try and find weak points. >>We can see them then elevating the level of attack and trying to weaponize a particular exploit that they might have find, or vulnerability that they find. We can see everything that comes into each of the components, not just at the perimeter, but right inside your application. We see what happens in those components process file, integrity, changes. And we see what comes out, attempt exfiltrate, something that looks like a database file or et cetera password. And we put all of these little subtle signals, the indicators of attack, the network based signals and the indicators of compromise. We put those together and we build a picture of the threats against each of the workloads in your cloud, native application. There's lots and lots of background, recon traffic. We see that you generally don't need to worry about that. It's just noise. But as that elevates and you see evidence of exploits and later spread, we identify that we'll let you know, or we can step in and we can proactively block the behavior that's causing those problems. So we can stop someone from accessing a component, or if a component's compromised, we can, we can freeze it and restart it. And this is a key part of the technology within our threat striker security observability platform, >>Uh, false alerts are the bane of the security ministry's existence. What do you do to protect against those? >>So we use a range of heuristics and a degree, a small degree of machine learning to try and piece together. What's happening. It's a complicated picture. So some of your viewers will have heard of a might attack matrix. So a dictionary of techniques and tactics and, and protocols that attackers might use in order to attack an infrastructure. So we gather the signals, those TTPs, and we then build a model to try and understand how those little signals pieced together. So maybe there's, you know, there's a guy with a striped striped vest that is trying the doors in your city, you know, a low level criminal who isn't getting anywhere. We'll pick that up and that's low risk. But then if we see that person infiltrate a building, because they find an open door, then that raises the level of risk. So we monitor the growing level of risk against each workload. >>And once it hits a level of concern, then we let you know, but you can then forensically go back in time and look at all of the signals that surround that. So we don't just tell you, there was an alert and a file was compromised in your workload, do something about it. We tell you the file was compromised. And prior to that, there were these events, process failures. Those could have been caused by network events that are correlated to a vulnerability that we know. And those in, in turn could have been discovered by recon traffic. So we help you build that entire active picture up. Every application's different. You need to have the context to understand and interpret signals that a solution like threat striker gives you, and we give you that context. >>So I would push back. If I'm a platform team, say, you know what? I have a service mesh. I, I have trusted traffic going to trucked traffic going from trusted sources. I'm, I'm cutting off the problem even before it happens. Why should I use, uh, deep fix? >>So a service mesh won't cut off the problem. It'll just hide the problem because a service mesh will just encrypt the traffic between each of the components. It doesn't stop the bad traffic flowing. If a component is compromised, people can still talk to another component and the service mesh happily encrypts it and hides it. What we do. We love service meshes because we can decrypt the traffic or we can inspect the individual application components before they talk to the mesh side car. So we can pull out and see the plane, text traffic. We can identify things that other tools wouldn't have a hope of, of identifying. >>So, you know, you, you just, uh, triggered something. >>Yeah. >>A lot of companies do not like decrypting that traffic after it's been sent, they don't want anyone else, including security tools to see it. Yeah. How do you ensure, how do you serve those clients? >>So we serve those clients by having an architecture that sits entirely on premise in their infrastructure. Their sensitive data never leaves their network, their VPCs, their, their boundary. They install a threat striker console. So this is the tool that does all of the analysis and make the protection decisions. They run that themselves. They deploy the threat, striker sensors in their production environment. They talk over secure links, authenticated to the console. So everything sits within their power view, their level of their degree of control. >>So if, if they're building a, a, a cloud application though, or, or a hybrid cloud application, how do you connect? How do you deal with the cloud side? >>So whether their production environments are next to the threat striker console, whether they're running on remote clouds, our sensors will run in all of those environments and the console will manage a complex hybrid environment. It will show you traffic running in your Kubernetes cluster and AWS traffic Mon running on your VMs on Google traffic, running in your 4g instances on again, on AWS and on your on-prem instances, it gathers that data securely from each of those remote places, sends it to the console that you own and operate securely. So you have full control over what is captured. It's encrypted, it's authenticated, it's streamed back. So it never leaves your level of control. >>Talk to me about the overhead. How is this deployed and managed with MI environment? >>So there are two components, as we've learned, we have the console. All of the work is done on the console, the any necessary decryption, all the calculation that runs on a Kubernetes cluster, that, that you would deploy, that you would scale. So that's fully in your control. Then you need to install little sensors on each of your production environments to bring the data back to the console. >>Now those on pots, or are those in running inside of, uh, containers themselves. >>So they are container based. They're typically deployed as a demon set. So one instance per node in your Kubernetes cluster, they are, we have put a lot of engineering work into making those as lightweight as possible. They do very little analysis themselves. They do a little bit of pre-filtering of network traffic to reduce the bandwidth, and then they pass the packets back to the management console. So our goal is to have the minimal impact on customers, production environments, so that they can scale and operate without an impact on the performance or availability of their applications. And we have customers who are monitoring services running on literally thousands of Kubernetes nodes and streaming the data back to their management console and using that to analyze from a single point of control what's going on in their applications. >>So we hear time and again, CIOs complaining that they have too many point security products. Yes, I think average of 87 in, in, in the enterprise, according to, to one survey, aren't you just another, >>And that is the big challenge with security. There is no silver bullet product that will secure everything that you have. You have your, the what, you're the, what you're securing scales over space from your infrastructure to the containers and the workloads and the application code. It scales over time. Are you secure? Are you putting security measures in, at shift left development when you deploy or are you securing production? And it scales over the environments. There is no silver bullet that will provide best to breed security across that entire set of dimensions. There are large organizations that will present you with holistic solutions, which are a bunch of different solutions with the same logo on them, bundle together under the same umbrella. Those don't necessarily solve the problem. You need to understand the risks that your organization is faced. And then what are the best to breed solutions for each of those risks and for the life cycle of your application at deep fence, we are about securing your production environment. >>Your developers have built applications. They've secured those applications using tools like SNCC, and they've ticked and signed off saying with this list of documented vulnerabilities, my application is secure. It's now ready to go into production. But when I talk to, to application security people to ops people, and I say, are the applications in your Kubernetes environment? Are they secure? They say, look, honestly, I don't know, the developers have signed off something, but that's not what I'm running. I've had to inject things into the application. So it's different. There could have been issues that were, that were discovered after the developers signed it off. The developers made exceptions, but also 60, 80% of the code I'm running in production. Didn't come from my development team. It's infrastructure, it's third party modules. So when you look at security as a whole, you realize there are so many ax axis that you have to consider. There are so many points along these, a axis, and you need to figure out in a kind of a van diagram fashion, how are you going to address security issues at each of those points? So when it comes to production security, if you want a best breed solution for finding vulnerabilities in your production environment, threat map, open source, we'll do that. And then for monitoring attack behavior threat striker enterprise will do that. Then deep defense is a great set of solutions to look at. >>So on. Thanks for stopping by security at layers is a repetitive thing that we hear security experts talk about. Not one solution will solve every problem when it comes to security from Valencia Spain, I'm Keith Townson, along with Paul Gillon and you're watching the Q the leader in high tech coverage.

>>Hey guys, welcome back to the cubes. Continuous coverage day, one of AWS and re-invent live that's right live in Las Vegas. I'm Lisa Martin. Pleased to be here. We are running actually one of the industry's most important hybrid tech events with AWS this year, and it's huge ecosystem of partners. We have two lives dots, two remote studios over 100 guests on the program. We'll be talking about the next decade in cloud innovation. I'm pleased to welcome back one of our alumni and a new guest to the program. Savina Joyce Sabina, Joseph GM of technology partners at AWS joins me as well as Scott Owen, the VP of business development and global channels at air slate, guys. Welcome to the program. Thank you for having us. It's a great to be here. Live happy. Fantastic. Let's go ahead and give the audience an overview of your roles. Sabina. We'll start with you. And then Scott will go to you. >>Great to see you again, Lisa general manager for technology partnerships globally out of the Americas, and we also help partners out of EMEA and APAC grow their business in the Americas. >>Awesome. Scott goes, I'd give, give us an overview of air slate and then your role. You will. >>You bet. Uh, so, uh, air slate, we have two offerings on the AWS marketplace or e-signature offering, which is sign now and then our no-code workflow automation, which we're really excited to bring on the marketplace. I lead our business development, uh, in channels organization for the company global partnership with AWS. Uh, we're very excited about it. >>Talk to me about some of the challenges that the tools that you just mentioned, what challenges are those solving for customers in any industry? So, >>Oh, the biggest challenges right now, obviously we are in a COVID environment and, and companies are trying to drive automation optimization, especially for remote workers to today. And so part of our solutions is obviously solving that in a very, very big way on a global basis as well. >>What are some of the key trends that you're seeing? We've seen so much flux on change in the last 20 months, but what are some of the key trends, especially as it relates to workforce productivity with those work from anywhere environments still persisting, >>It's still persisting. And I'd say the challenge is we're in a hybrid mode where you have both, you know, coming to the office, not coming to the office, but still very remote, just a last week's announcement of a new variant, for example, forcing everybody back out of the office, back into a remote environment. So flexibility, uh, around supporting that hybrid workforce is key. >>And of course here we are at a hybrid event. There are people here at a lot of them in person, but there's also a lot of content that's going on virtually for those folks that weren't quite comfortable coming back to an in-person event. But let's talk about savings about how AWS has been helping joint customers with air slate through the pandemic over the last 20 months as we saw this scatter. And now this work from this hybrid kind of work environment. Yeah. So, >>So I, Scott mentioned, right, that customers are really looking for business solutions. I did have some rapidly increased the last 20 months. We are really, we've been really working together to help both workers and businesses adapt to this remote environment. And customers are looking for simple and cost effective solutions anywhere from, you know, improving and automating their business workflows with e-signature solutions, all the way to complex processes with no code capabilities and air slate does a great job of providing these solutions for our customers. >>Some of the things from a business automation perspective that are critical these days is anything contactless talking about. E-signatures for example, it's, that's really became table stakes in the last 20 months. It's not talk to me about how you would from a biz-dev lens. Describe the partnership that air slate has with AWS. >>Yeah. For our company, it is the most strategic partnership that we have and it's all the way from our board level to our executive leadership team all the way through, throughout our organization end to end it's our most strategic partnership. >>And the things that we know and love about AWS that we've talked about with Sabina is their customer first focus, their customer obsession from a cultural perspective, is there alignment there with air Slate's culture, >>A hundred percent. And one of the cool things about the AWS partner program, which we're in a high echelon period, is the focus on the customer. The customer can reduce their EDP commit by buying solutions like ourselves on the AWS marketplace, as well as the AWS account executives are also paid and incented to sell our solution as well. So it's a one plus one equals three scenario. >>That's a good scenario. One plus one plus three. So be it, talk to me about the evolution. How long have you guys been partnering with air slate? And talk to me about the evolution of the partnership. >>Yeah. We've been working together for a few years now, but I would say the last 15 months, we've really accelerated that partnership again because of customer need and really built out high velocity Cosell motions. We made available to our slate, our partnership resources, both from commercial and public sector to scale the sales motion. As Scott mentioned, they're available in marketplace and they're also part of our ISV accelerate program, which means that our sales teams are incented to work with air slate, to close opportunities. And the key is all of this has led to 250% increase in customer wins year to date as compared to 2020. So that really speaks volumes with the partnership and the need that we are solving for our customers. >>Amazing, amazing growth, 250% in, in a year's period during a pandemic, that's massive, but we saw the acceleration of cloud adoption of digital transformation and this dependence on SAS and cloud for our business lives, our daily lives, our consumer lives. That was really absolutely critical. So Scott, from your perspective, what are some of the key aspects of the AWS relationship that you think really contribute to that success and that big metric that we just met? >>Yeah, absolutely. Well, the metric is driven by the partner programs. When you have a customer that can buy on the marketplace, reduce their EDP commit. You've got account executives that are incented to resell us, but for us, we have really great leadership support around the globe. We've created joint KPIs of which we all have stacked hands on and said, here's the KPIs we want to deliver as a joint partnership. And we're delivering those, which is creating these results as well. Can you share >>Some of those KPIs even at a high level? >>Yes. A lot of them are what, uh, opportunities in our renewal base can we bring into the ado, uh, UWS, uh, ecosystem, if you will. Um, as well as in nearly every deal that we're in, we're asking, is this an AWS customer? Is it a Greenfield opportunity for AWS and bring in the associated teams together to close that opportunity, >>Scott, about some of the business outcomes, the benefits that your joint customers are achieving, leveraging the power of this partnership? >>Absolutely well there's enormous cost savings in the solutions that we bring to the table creates the optimization that we talked about, that they need. It's also driving that digital transformation, any company, any size in order to survive has to move digitally into this new space. And we believe that the two offerings we bring to the marketplace can solve that for them. >>That's one of the things that we saw, there's definitely some silver linings that have come out of the last 20 I'm losing count 22 months, something like that. And nothing like that, right. A time to value is absolutely critical. Let's talk about now go to market Sydney and going back over to you, how does AWS support partners like air slate, um, and taking the solutions to market? You talked about the marketplace, but talk to me about that from a strategic perspective. Yes. >>So one of the things we are very focused on is creating business automation solutions, especially for industry verticals across automotive, telecommunications, healthcare, life sciences, and air slate really has solutions that help address all of the horizontal use cases and the vertical use cases, which means then we can focus our demand generation activities and actually help both our direct sales team and also our channel partners really, really scale. So again, it's kudos to Scott and the air slate team in order to be able to really scale this partnership, but most importantly help our customers through these really tough times in the past 20 months. >>And it's, uh, uh, you mentioned that with the Omicron Darion variant being announced just in the last week, of course, these challenging times persist in this uncertainty persists to it's important to have partnerships, but I also imagine Scott from your, from your perspective, being able to show transparency to the customers that you're really one team, you know, with AWS, with your channel partners. Talk to me a little bit about that. What does customers actually see and feel >>While we're excited, especially around the ecosystem piece is for example, in the last few months, we've been able to activate 35 of AWS's largest channel partners, uh, due to the fact that we are in this hand, stacked KPI go to market together. And so the ecosystem of AWS, it's the trusted partner of almost every customer. And we are trying to advantage ourselves with that trusted relationship, bringing a set of solutions that helps drive the customer's outcome. >>You mentioned an important word there, Scott, that trust that is critical for every company that is becoming a data company. If they haven't become a data company by now, they're probably not going to be around much longer. Talk to me about from a trust perspective, what that means for your customers to be able to adopt these solutions, automate their businesses, allow their folks to work from anywhere and have that trust and this solid partnership and technology. >>Well, and that's the benefit of the AWS partnership. When you think of security, reliability, our entire offering basis completely on the AWS infrastructure. So we bring that trust of you can trust that the technology that it's sitting on, you can trust that it's secure, that's reliable, and we're bringing a set of solutions that drives those customer outcomes, which is cost savings, optimizations, et cetera. That combination is a win-win out there. >>And that outcome spaced focus is critical. What are some of the things Scott that folks can learn at air Slate's booth this week at reinvent for those folks that are here in person and those folks that are attending virtually >>Great question. I love that question first and foremost, both offerings are on the AWS marketplace, but we're the only e-signature offering on the marketplace. And we're the only end to end workflow automation offering on the marketplace as well. So again, uh, important to note we're on that AWS marketplace, AEs from AWS can take advantage of that end. Customers can take advantage of that. Uh, and we take advantage of it just to the, our great go to market partnership. >>We're going to mark great, good to market partnership, but also I'm hearing a pretty significant differentiator being the only ones in the marketplace with those. Talk to me about how that, I mean, one, one more question. How does that facilitate like customer conversations? I imagine that's a huge differential >>Here's is a significant different traitor to us obviously, but again, it's the power of one. Plus one equals three in the partnership, we brought a set of solutions that the customer needs. We do it on the AWS marketplace and AWS infrastructure that we sit on that creates that trust factor that you mentioned. >>I have to add, right? That air slate and team, when they saw that they were the first right, they embraced that and they broke ground and they listed on marketplace and that's paying off for them. >>Very smart. Well guys, congratulations on your joint success. Your go to market strategy seems brilliant, and we look forward to hearing many more successful years from airside and AWS together. Thank you for your insights. Thank you. Thank you. Thank you. Pleasure. You were great for my guests. I'm Lisa Martin. You're watching the cube live from AWS. Reinvent the leader in global alive tech coverage.

>> Announcer: Live from Nassau. (electronic music) Live from Nassau in The Bahamas, it's The Cube, covering Polygon '18, brought to you by Polymath. >> Welcome back, everyone. It's The Cube's exclusive coverage live in The Bahamas for Polycon '18. This is where all the action is, cryptocurrency, Bitcoin, blockchain, you name it, token economics, a paradigm shift of epic proportions. This is a decentralized internet. It's impacting the world. Missions, technology, applications, and all sectors. Our next guest, Shawn Owen, CEO of SALT Lending, serial entrepreneur, killer idea, so simple, so stupid simple. No one's doing it, he's doing it, lending cash for Bitcoin and currency. Welcome to The Cube. >> Thank you, it's good to be here. >> You know, there's two things that I love, the crazy ideas that everyone says is the dumbest idea on the planet that becomes billion-dollar opportunities, then something that's so simple and obvious that no one does because either a bag at your dogma or other interests. You're in kind of both. You got the simple idea, lending. Take a minute to talk about SALT Lending and your innovation that you guys do on the business side. >> Yeah, you got it. Everybody here at these conferences, or hopefully, people that are watching, have some interest in cryptocurrencies or blockchain, and probably accumulate some value in that currency, or the asset class. Once you do, then you have options, that you can either continue to hold that, or you can sell it. We're opening up a new market for the ability to see that as property and borrow against it. In fact, the technology makes a perfect form of collateral. We have all this ability to program in smart contracts. You can write in the rules. You can make it highly secure, yet nobody is doing it, so it's one of these simple things that, as this market emerges, became kind of obvious as a pain point, which is, I go to the bank, and I show them my personal financial statement, and they look at Bitcoin, and scratch their head. Somebody's got to bridge that gap, so we're building technology that ultimately should be used by banks or financial institutions to bring this together to where you have that ability like you would with any other type of property. If you look at any other type of property, you can lend against it, somebody's figured out how to, whether it's minerals, whether it's land, whether it's cars. Really now, we're doing that for cryptocurrency. SALT Lending stands for secured automated lending technology, so it's very much a technology-driven company, yet it's foundational in lending. It's just very simple to understand because it's the oldest business known to man. >> We covered cloud computing from day one. It's interesting, automation wins the day. We're seeing a lot of things where automating M&A process, we talked to those guys at LEXIT. You're doing something here with lending. You're just so simple. Here's the question, if I have Bitcoin, and there's a lot of whales walking around here, people, billionaires, millionaires, a lot of people have made money over the past couple of years. Certainly, if you were in it 2011 after, you're a whale. They got value. I put it up, and I get cash? Is that how it works? >> That's right. Everybody has assets that they want to hold onto, that are precious to them, whether it be gold, heirlooms, art, Bitcoin. Then they have currencies that are things that they want to spend quickly and/or just don't even think twice about it, I'll pay for a cup of coffee, a bottle of water, whatever. As the world moves into the blockchain era, as all value can be recorded on distributed ledgers in blockchains, you have this new way of thinking about everything. You can imagine a wallet where you have all the things you really care about, and you can dynamically decide what your currency is based off where you're traveling, where you want to spend, what you think is happening with inflation, depending on what your interest is. Maybe it's video game points you want to spend in the future. However, having that scale, and saying, at any point in time, I want to hold onto this, and I want to spend more of that, there's a partnership, right? A really easy way to think about that is, how can I leverage what I have, which is portfolio lending, or any type of lending, into more of the currencies I need, whether it's, I need to go buy a house, I need to buy a car, I want to buy more investments? We see it as a very powerful tool, and almost a necessity, but then, on top of that, just extremely cool in how you could imagine the future of finance in this world. >> Yeah, it's a total game-changer. I love what you're doing. I think, getting the fiat conversion really gets immediate liquidity in a currency that people can spend. If someone says, "Hey, I don't want Bitcoin," great, I want to buy a boat, or start a business, I need to get some fiat, I pledge up my coin. >> That's right. >> Now, you go valuation issues, so I'm assuming you have math behind this that says, "Hmm, but if Bitcoin drops..." >> Yep, that's the thing. We really solve a couple fundamental pieces of the blockchain that, at its core, are difficult for people to do well. One is security, and the other is user interface. When you wrap that into a product, and you build out the user interface and the security, suddenly, it becomes a lot easier. When it comes to the risk mitigation, it's simply over-collatoralized. We're going to pitch you as a borrower, and say, "You're already probably storing all this "somewhere anyway, in a wallet. "Why not put it in a secure wallet, "drive the loan to value ratio way down "so you're only borrowing what you need "when you need it, you don't bring out "these giant loans for no good reason, "you just borrow what you need, "the interest rate becomes a lot lower, "and then you have extra collateral for the volatility?" Ideally, that's the scenario. If, in a world where it's very volatile, and you're at a higher loan value rate, then that's where we give you options. We say, "Hey, would you like to sell some of this, "or would you like to add more? "Would you like to prepay your loan if not?" There's always the option for somebody to correct the loan instrument, but that's the other really cool part about a smart contract, or a smart written language around the instrument itself, is that you can get a little more creative. Instead of just having legal paperwork, you can say, "Let's put this into the code." It becomes very dynamic in the ability for it to cure, the instrument itself, to stay course. >> Software money, I love this. Let's go down, talk about the token that you have, SALT Token, and that's for the borrower, or the lender? >> It's, right now, the borrower, although it will expand into all uses. It's effectively, as people say, it's powering the network, or it's the gasoline behind it. It's our internal currency. It acts as a store value in the regards of how you would think about a serial number. If I have Microsoft Office, and you buy a serial number, that's the key that lets you in, and it tells you how much of the product you have. If you have 20 or 30 of them, you can give them to your employees, or you could redeem it for some other value. We just think that tokens actually do a better job of that recording 'cause it's now put on a permanent ledger. You have the permanent auditability of it, than just a serial number in a private database. >> I think you got a great solution because the alternative to not having it is essentially, get a liquid on an exchange, which some people might not want to do. Then also, where do you do it, right? There's all kinds of dynamics on the exchange side. Here, I'm saying, I'm long on Bitcoin, but I need to get some working capital for whatever the project is, so you're there. Is there any competition? Is anyone else doing this? >> There's no competition yet. There's definitely some people that are out there saying that they are, and I would be careful. Some of them may be legitimate. We've seen a few that are scams, so always be protected, and be wary. >> John: Give an example of what a scam would look like for the people. >> A scam would be somebody who says, "Hey, we're doing an ICO," and you start looking at it, and it looks exactly like what we've built, except for they're, maybe, in Russia, and you can't actually contact the people, and they don't have any banks behind them, or any kind of regulatory framework. >> They're spoofing your brand. >> Yeah, we've seen a lot of that. We've had a lot of phishing attempts, and people trying to spoof the idea or the site, and that's a little worrisome, but there probably will be competitors. It's a big market. >> Yeah, that's going to happen more and more, more of those spear phishing attacks too. Great, and outlook for you guys. Where are you guys at with the company? Talk about what your needs are. You hiring? What's going on with the operation? >> Yeah, we're constantly hiring, looking for anybody who's got great financial background and wants to be in the blockchain space, and/or developers, constantly looking for blockchain-focused developers, people that either want to learn the space, or already know the space, either way is fine. We'd love to talk to you. We've issued $30 million in loans in the states we're approved. We're rapidly expanding that genre of where we can lend. We're working to partner with banks, so if you're a bank, or you're a financial institution, there's a lot of capital money at this conference, we'd love to talk to all you guys because there's an opportunity for us to give you an indirect exposure into the market. >> It's good for the big whales who have a lot of currency, a lot of value, to pay it forward in the mission, in the community. They could be lenders too, right? >> Very much so, yes. >> Wow, so what states aren't you in? 30 million, that's a good number. What's your top list? >> The next on the list that we're working towards, we're really close to Texas, we're really close to California, really close to New York, really close to Utah. Those are some big ones. Lots of interest in Puerto Rico, so we're heavily focused on getting there, and it's just a road map, a heat map. There's a lot of interest in Europe, so we're going over into Europe, lots in Canada. >> Shawn, thanks for coming on, sharing the project, your success. Love your idea, again. Disruption continues. The stampede is coming behind us at Polycon. That's their logo. Polymath is the company behind this event. Of course, we're The Cube, we're independent, we're bringing you all the action here at Polycon '18. More live coverage after this short break. (electronic music)

>>from our studios in the heart of Silicon Valley. Palo ALTO, California It is a cute conversation. >>Hi, and welcome to the Cube studios for another cube conversation where we go in depth with thought leaders driving innovation across the technology industry. I'm your host, Peter Boris. Digital businesses affecting every enterprise of every size, small and large, and the types of solutions that required the types of outcomes that are being pursued are extremely complex and require an enormous amount of work from some of the best and brightest people on the business side as well as the technology side. And that means not just from a large company. It means from an entire ecosystem of potential sources of genius and insight and good hard work. So the consequence for every enterprises, how do they cobble together that collection of experts and capabilities that are gonna help them transform their business more successfully, Maur completely and more certainly than they would otherwise? And that's we're gonna talk about today. Today we're here with Kelly Ireland, who's the founder and C E o. C. B Technologies. Kelly. Welcome to the >>Cube. Thank you, Peter. Happy to be here, >>so let's start by finding a little bit about CV Technologies to also about what you do. >>Um, I have a IittIe background, so I have been in it for 40 years. In 2001 I decided I had a better idea of how to both support clients as well as my employees. So I opened CB Technologies were value added reseller, um, and then say about five years ago, I decided to do some transforming of the company itself. I saw what was going on in the industry, and I thought this was the time for us to get going. Turned out we were a little early, but we wanted to transform from what you would call it the value added reseller two systems integrator. Because that was the only words what they had for. You know what that end result would be? Now I've heard it's the, um, domain expert integrator, which we like a lot better. And what we've done is gone from this value add, which we've all seen over the last couple of decades, into actually engineering solutions, and mostly with consortiums, which will talk about of the O. T. I t. Convergence and what's going to be needed for that to make our customers successful. >>Well, you just described. In many respects, the vision that businesses have had and how it's changed over years were first. The asset was the hardware. Hence the var. Today, the asset really is the date of the application and how you're going to apply that to change the way your business operates the customer experiences, you provide the profitability that you're able to return back to shareholders. So let's dig into this because that notion of data that notion of digital transformation is especially important in a number of different names, perhaps no more important than in the whole industrial and end of things domain. That intersection of I t know Tia's, you said, Tell us a little bit about what you're experiencing with your customers as they try to think about new ways of applying technology technology rich data to their business challenges. >>We'll use the perfect word you said dig, because this is all about layers. It's all about it was technology and software. Now it's about technology, software and integration. In fact, the conversations were having with our clients. Right now we don't even talk about a no Yim's name. Where before you would. But we haven't our head. What? We know what would be best. What we look at now is the first thing you do is go in and sit down with the client. And not only with the client, the you know, the executives or the C I or the C T. O's et cetera, but the employees themselves. Because what we've seen with I I I o t o t i t Convergence, it's You have to take into account what the worker needs and the people that are addressing it that way. Um, this project that we started with Hewlett Packard Enterprise, they started up what we call the refinery of the future. It could be acts of the future. It doesn't really matter. But it was getting at least up to five use cases with a consortium of partner companies that could go address five different things within the refinery. And the reason that I think it's been so successful is that the owner, the CEO Doug Smith and the VP of ops Linda Salinas, immediately wrap their arms around bringing employees. They're a small company there, maybe 50. They brought half of them to HPD Lab to show them what a smart pump laws for their chemical plant text. More chemical in Galina Park in Texas. Starting from that, it was like they put him on a party bus, took them down, put them in the lab, told them, showed them what a smart pump was and all of a sudden the lights turned on for the workers. These are people that have been, you know, manual valves and turning knobs and, you know, looking at computer screens they'd never seen what a smart, censored pump waas all of it sudden on the drive back to the company, ideas started turning. And then HP took it from there, brought in partners, sat everybody in the room, and we started feathering out. Okay, what's needed. But let's start with what the client needs. What do those different business users within the chemical plant need, and then build use cases from that? So we ended up building five use cases. >>Well, so what? Get another five years cases in a second? But you just described something very interesting, and I think it's something that partners have historically been able to do somewhat uniquely on that is that the customer journey is not taken by just an individual within the business. What really happens is someone has an idea. They find someone, often a partner, that can help them develop that idea. And then they go off and they recruit others within their business and a local partner that has good domain expertise at the time. And energy and customer commitment could be an absolutely essential feature of building the consensus within the organization to really accelerate that customer journey. If I got that right? >>Absolutely, absolutely. And what we saw with Refinery of the Future was getting those partnerships HP East started. It created the project kind of through information out to many of their ecosystem partners trying to gain interest because the thing was is this was kind of our bet was a very educated bet, but it's our bet to say, Yeah, we think this makes sense. So, you know, like I said, I think there's about 14 partners that all joined in both on the I t om side the ot oh am side and then both Deloitte and CB Technologies for the S. I and like expert domain expert integration where you really get into How do you tie OT and I t together? >>All right, so we've got this situation where this is not As you said, It's not just in the refining process, manufacturing businesses. It's in a lot of business. But in this particular one, you guys have actually fashioned what you call the refinery of of the future has got five clear use cases. Just give us an example of what those look like and how you've been RCB technology has been participated in the process of putting those together. >>Um, the 1st 1 was pretty wrapped around Predictive Analytics, and that was led by Deloitte and has a whole host of OT and I t integration on it >>again, not limited to process manufacturing at all >>at all, but and a good group, you know, you have national instruments, Intel flow. Serve. Oh, it's ice off Snyder Electric, PTC riel, where they're such a host >>of the >>consortium and I I think what was most important to start this whole thing was H P E. Came in and said, Here's an MOU. Here's a contract. You all will be contract ID to the overall resorts results. Not just your use case. Not just one or two use cases you're in, but all five because they all can integrate in some sense so >>that all can help. Each of you can help the others think. Problems. Truce. That's the 1st 1 about the 2nd 1 >>The 2nd 1 is video is a sensor that was Intel CB Technologies. I think we have as you're in there as well, doing some of the analytics, some P T. C. And what that was all about was taking video. And, you know, taking a use case from Linda and saying, Where where do you need some sort of video analytics Taking that processing it and what we ended up doing with that one was being able to identify, you know, animals or aggressive animals within the train yard. A downed worker transients that shouldn't be there because we can't decipher between you know, someone that's in text marks p p ease versus somebody that's in street clothes. So taking all that analyzing the information, the pictures, training it to understand when it needs to throw and alert >>lot of data required for that. And that's one of the major major drivers of some of the new storage technologies out there. New fabrics that are out there. How did that play? A role? >>As you can imagine, H p E is the under underlying infrastructure across the entire refinery. The future from compute with the, uh, EJ data center into the Reuben network into nimble storage for storing on site. Um, what we're finding, no matter who we talked to in the industry, it is. Most of them still want to keep it on Prem. In some sense, security. They're still all extremely cautious. So they want to keep it on Prem. So having the nimble storage right in the date, having the edge data center having everything in the middle of this chemical plant was absolutely a necessity. And having all of that set up having my team, which was the C B Tech team that actually did all the integration of setting up the wireless network, because guess what? When you're in a different kind of environment, not inside a building, you're out where there's metal pumps. There's restrictions because ah, flash could cause an explosion so intrinsically safe we had to set up all that and determined how? How could we get the best coverage? Especially? We want that video signal to move quite fast over the WiFi. How do we get all that set up? So it takes the most advantage of, you know, the facility and the capabilities of the Aruban network. >>So that's 12345 quickly were >>three worker safety, which hasn't started yet. We're still waiting for one of the manufacturers to get the certification they need. Um, four we have is connected worker, which is on fire, having a work >>of connected worker on fire and worker >>safety. >>Yeah, they don't sound, but just think of all the data and having the worker have it right at his fingertips. And, oh, by the way, hands free. So they're being ableto to take in all this data and transmit data, whether it's by voice or on screen back >>from a worker central perspective, from one that sustains the context of where the worker is, what stress there under what else? They've got to do it said. >>And and what are they trying to complete and how quickly? And that's where right now we have r A y that's in the 90% which is off the chart. But it's and and what's great about being at Text Mark is we actually can prove this. I can have somebody walk with me, a client that wants to look at it. They can go walk the process with me, and they will immediately see that we reduce the time by 90%. >>So I've given your four. What's the 5th 1? >>Acid intelligence, which is all about three D Point Cloud three D visualization. Actually being able to pull up a smart pump. You know it really? Any pump, you scan the facility you converted into three D and then in the program that we're using, you can actually pull up a pump. You can rotate it 360 degrees. It's got a database behind it that has every single bit of asset information connected videos, cad cams, P and I. D s. For the oil and gas industry. Everything's in their e mails could be attached to it, and then you can also put compliance reports. So there you might need to look a corrosion. One of those tests that they do on a you know, annual or every five year basis. That's point and click. You pull it up and it tells you where it sits, and then it also shows you green, yellow, red. Anything in red is immediate, attest that tension yellow is you need to address it greens. Everything's 100% running. >>So the complexity that we're talking about, the kind of specificity of these solutions, even though they can be generalized. And you know, you talked about analytics all the way out to asset optimization Intel intelligence. There are We can generalize and structure, but there's always going to be, it seems to us there's going to be a degree of specificity that's required, and that means we're not gonna talk about package software that does this kind of stuff. We're talking about sitting down with a customer with a team of experts from a lot of different places and working together and applying that to achieve customer outcome. So I got that right >>absolutely, and what we did with the consortium looking at everything. How they first addressed it was right along that line, and if you look at software development, agile following agile process, it's exactly what we're doing in four I I o T o R O T I t Convergence, because if you don't include all of those people, it's never going to be successful. I heard it a conference the other day that said, POC is goto I ot to die, and it's because a lot of people aren't addressing it the right way. We do something called Innovation Delivery as a service, which is basically a four day, 3 to 4 day boot camp. You get all the right people in, in in the room. You pull in everything from them. You boot out the executive team partway through, and you really get in depth with workers and you have them say what they wouldn't say in front of their bosses that this happened with Doug and Linda and Linda said it was mind blowing. She goes. I didn't realize we had so many problems because she came back in the room and there was a 1,000,000 stickies. And then she said, the more she read it and the more you know, we refined it down, she said it was absolutely delivered, you know, the use case that she would have eventually ended up with, but loved having all the insights from, >>well, work. Too often, tech companies failed to recognize that there's a difference between inventing something and innovation. Inventing is that engineering act of taking what you know about physics or social circumstance Secreting hardware software innovation is a set of social acts that get the customer to adopt it, get a marketplace to adopt it, change their behaviors. And partners historically have been absolutely essential to driving that innovation, to getting customers to actually change the way to do things and embed solutions in their operations. And increasingly, because of that deep knowledge with customers are trying to doing, they're participating. Maurine, the actual invention process, especially on the softer side of you said, >>Yeah, yeah, I think what's really interesting in this, especially with Coyote. When I look back a few years, I look at cloud and you know everything was cloud and everybody ran to it and everybody jumped in with both feet, and then they got burned. And what we're seeing with this whole thing with I o t you would think we're showing these are lies, return on. Investments were showing all this greatness that can come out of it and and they're very slow at sticking their toe in. But what we've found is no one arrives should say the majority of corporations anymore don't want to jump in and say, Let's do it two or five or $10 million project. We see your power point. No, let's let's depart Owen with with what we're doing, it's, you know, a really small amount of money to go in and really direct our attention at exactly what their problem is. It's not off the shelf. It's but it's off the shelf with customization. It's like we've already delivered on connected worker for oil and gas. But now we're are so starting to deliver multiple other industries because they actually walk through text mark. We could do tours, that text mark. That was kind of the trade off. All these partners brought technology and, you know, brought their intelligence and spent. We were now on two years of proving all this out. Well, they said, Fine, open the kimono will let your customers walk through and see it >>makes text mark look like a better suppliers. >>Well, it's enhanced their business greatly. I can tell you they're just starting a new process in another week. And it was all based on people going through, you know, a client that went through and went. Wait >>a minute. I >>really like this. There are also being able to recruit technologists within the use in industry, which you would think text marks 50 employees. It's a small little plant. It's very specialized. It's very small. They pulled one of the top. Uh, sorry. Lost not. I'm trying to think of what the name >>they're. They're a small number of employees, but the process manufacturing typically has huge assets. And any way you look at it, we're talking about major investments, major monies that require deep expertise. And my guess is the text Mark is able to use that to bring an even smarter and better >>people smarter and better. People that are looking at it going they're ahead of the curve, for they're so far ahead of the curve that they want to be on board were that they're bringing in millennials on they're connected. Worker Carlos is there trainload lead. And he dropped an intrinsically safe camera and it broke and he tried to glue it together, tried to super glue it together. And then he ran back to Linda and he said I broke the case and this case is like £10. They call it the Brick. They gotta lug it up. They got to climb up the train car, leg it up, take a picture that they have sealed the valves on all the cars before they leave. Well, he had used the real where had, you know, device. And he went into Linda and he said, I know there's a camera in there. There's camera capabilities. Can I use that until we get another case? And she's like, Yeah, go ahead. Well, he went through, started using that toe like lean over, say, Take photo. We engineered that it could go directly back to the audit file so that everybody knew the minute that picture was taken, it went back into the audio file. This is where we found the process was reduced by 90% of time. But he turned around and trained his entire team. He wasn't asked to, but he thought, this is the greatest thing. He went in trainable. And now, about every two weeks, Carlos walks in to my team that sits a text mark and comes up with another use case for connected worker. It's amazing. It's amazing what you know were developed right out of the customer by using their workers and then, you know, proactively coming to us going. Hey, I got another idea. Let's add this where I think at version 7.0, for connected worker. Because of that feedback because of that live feed back in production. >>Great story, Kelly. So, once again, Callie Ireland is a co founder and CEO of CB Technologies. Thanks for being on the tube. >>Thank you for having me >>on once again. I wanna thank all of you for joining us for another cute conversation. I'm Peter burgers. See you next time.

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation >> lover on Welcome to this cube conversation here in Palo Alto, California. The Cube Studio. I'm John for the co host of the Cube Weird Sylvan shop. Who's the head of solution Architecture and open systems securing Esti win of right of other cloud to point out like capabilities. Very successful. 20 plus years. Operation Civil was the one of the first folks are coming over to the US to expand their operation from Europe into New York. Now here in Silicon Valley. Welcome to the Cube conversation. Thank you. So instituting trivia. You were part of the original team of three to move to the U. S. From Switzerland. You guys had phenomenal success in Europe. You've come to the U. S. Having phenomenal success in the US Now you moving west out here to California on that team, you're opening things up at the market. >> It's been a chance, Mikey. Things can presented themselves step by step, and I jumped on the trains and it's been a good right. >> Awesome. You guys have had great success. We interviewed your CEO a variety of your top people. One of the things that's interesting story is that you guys have been around for a long time. Been there, done that, riding this next next wave of digital transformation. What we call a cloud two point. Oh, but really is about enterprise. Full cloud scale, securing it. You have a lot of organic growth with customers, great word of mouth. So that's not a lot of big marketing budgets, riel. Real success there. You guys now are in the US doing the same thing here. What's been the key to success for open systems wide such good customers? Why the success formula is it you guys are on the right wave. What is it? The product? All the above. What's the What's the secret formula? >> So multiple things I say. And we started as a privately owned company like broad banks to, um, to the Internet email into one back in the nineties. And, um, yeah, we started to grow organically, as he said were by mouth, and Indiana is we put heavy focus on operations, so we wanted to make our customers happy and successful, and, um, yeah, that's how we got there like it was slow organic growth. But we always kind of kept the core and we tried to be unconventional, tried to do things differently than others do. And that's what brought us to where we are today and now capabilities Being here in the Valley, um, opens up a lot of more doors. >> It's got a nice office and we would see I saw the video so props for that. Congratulations. But the real to me, the meat on the bone and story is, is that and I've been really ranting on this whole SD win is changing. SD Win used to be around for a long, long time. It's been known industries known market. It's got a total addressable market, but really, what has really talks to is the the cloud. The cloud is a wide area network. Why do we never used to be locked down? He had the old way permitted based security. Now everything is a wide area. That multi cloud in hybrid club. This is essentially networking. It's a networking paradigms. It's not lately rocket science technically, but the cloud 2.0 shift is about, you know, data. It's about applications, different architectures you have everything kind of coming together, which creates a security problem, an opportunity for new people to come in. That's what you guys? One of them. This is the big wave. What? It explain the new s t win with, you know, the old way and the new way. What is the what? What should people know about the new S D win marketplace? >> Yeah. So let me start. Where do Owen has come from and how digital transformation has impacted that. So typically corporate wider networks were centered around the Clear Data Center where all applications were hosted, storage and everything and all traffic was back holding to the data center. Typically, one single provider that Broady, Mpls links on dhe. It was all good. You had a central location where you could manage it. You had always ability security stack was there. So you had full control. Now new requirements from natural transformation broad as users are on the road, they're on their phones ipads on the in, restaurants in ah, hotels, Starbucks. Wherever we have applications moved to the cloud. So their access directly You wanna have or be as close as possible Unify Communications. I OT It's all things deposed. Different requirements now in the network and the traditional architecture didn't were wasn't able to respond to that. It's just that the links they were filled up. You couldn't invest enough thio blow up your Nampula slings to handle the band with You lost visibility because users were under road. You lost control, and that's where new architectures had to be found. That's where Ston step them and say, Hey, look now we're not centered around the headquarter anymore were sent around where the applications are, your scent around, where the data is, and we need to find means to connected a data as quickly as possible. And so you can use the Internet. Internet has become a commodity. It's become more performance more stable, so we can leverage that we can route traffic according to our policies. We can include the cloud, and that's where Ston actually benefits from the clown. As much as the club benefits from SD went because they go hand in hand and that's also what we really drive to say, Hey, look, now the cloud can be directly brought into your network, no matter where, where data and where applications. >> Yeah, and this is the thing. You know, Although you've been critical of S t when I still see it as the path of the future because it's networking. And the end of the day networking is networking. You moving packets from point A to point B and you're moving somebody story you moving from point A to store the point C. It's hard. And you brought this up about Mpls. It's hard to, like rip and replace You can't just do a wholesale change on the network has the networks are running businesses. So this is where the trick is, in my opinion. So I want to get your thoughts on how companies were dealing with this because, I mean, if you want to move, change something in the network, it takes a huge task. How did you guys discover this new opportunity? How did you implement it? What was the and how should customers think about not disrupting their operations at the same time bringing in the new capabilities of this SD win two point? Oh, >> yeah, that's it's a perfect sweet spot, because in the end is, um, nobody starts at a green field. If you could start with a green field. It's easy. You just take on the new technology and you're happy. But, um, customers that we look up large enterprises, they have a brownfield. They haven't existing that work. They have business critical applications running 24 7 And if you look at what options large enterprises have to implement and manage a nasty when is typically three approaches, they either do it themselves, meaning they need a major investment in on boarding people having the talent validating technology and making the project work already. Look at a conventional managers provider. In the end, that is just the same as doing yourself. It's just done by somebody else, and you have the the challenge that those providers typically, um, have a lot of portfolio that they manage. And they do not have enough expertise in Nasty Wen. And so you just end up with the same problems and a lot of service, Janey. So even then you do not get the expertise that you need. >> I think what's interesting about what you guys have done? I want to get your reaction to this is that the manage service piece of it makes it easier to get in without a lot of tinkering with existing infrastructure. Exact. And that's been one of that tail winds for you guys and success wise. Talk about that dynamic of why they managed service is a good approach because you put your toe in the water, so to speak, and you can kind of get involved, get as much as you need to go and go further. Talk about that dynamic and why that's important. >> Yeah, technology Jane is very quickly. So you need people that are able to manage that and open systems as a pure play provider. We build purposely build our platform for us, he went. So we integrated feature sets. We we know how to monitor it, how to configure it, how to manage it. Lifecycle management, technology, risk technology management. All this is purposely purposely built into it, so we strongly believe that to be successful, you need people that are experts in what they do to help you so that you and your I t people can focus in enabling the business. And that's kind of our sweet spot where we don't say we have experts. Our experts operating the network for you as a customer and therefore our experts are your experts. And that's kind of where we believe that a manage service on the right way ends up in Yeah, the best customer. >> And I think the human capital pieces interesting people can level up faster when you when you're not just deploying here. Here's the software load. It is the collaborations important. They're good. They're all right. While you're on this topic, I want to get your thoughts. Since you're an expert, we've been really evaluating this cloud 2.0, for lack of a better description. Cloud 2.0, implying that the cloud 1.0 was Amazon miss on The success of Amazon Web service is really shows Dev Ops in Action Agility The Lean startup Although all that stuff we read reading about for the past 10 plus years great compute storage at scale, amazing use of data like you, said Greenfield. Why not use the cloud? Great. Now all the talk about hybrid cloud even going back to 2013 We were of'em world at that time start 10th year their hybrid cloud was just introduced. Now it's mainstream now multi cloud is around the corner. This teases out cloud 2.0, Enterprise Cloud Enterprise Scale Enterprise Security Cloud Security monitoring 2.0, is observe ability. Got Cooper All these new things air coming on. This is the new clout to point out what is your definition of cloud two point? Oh, if you had to describe it to a customer or a friend, >> it is really ah, some of hybrid cloud or multi cloud, as you want to name it, because in the end, probably nobody can say I just select one cloud, and that's going to make me successful because in the end, cloud is it's not everywhere, as we kind of used to believe in the beginning, but in the end, it's somebody else's computer in a somebody else's data center. So the cloud is you selectively pick the location where you want to for your cloud instances and asked if Cloud Service providers opened up more locations that are closer to your users in the or data you actually can leverage more possibilities. So what we see emerging now is that while for a long time everything has moved to the cloud, the cloud is again coming back to us at the sietch. So a lot of compute stuff is done close to where data is generated. Um, it's where the users are. I mean, Data's generated with with us. Yeah, phones and touch and feel and vision and everything. So we can leverage these technologies to really compute closer to the data. But everything controlled out of central cloud instances. >> So this brings up a good point. You essentially kind of agreeing with cloud one detto being moved to the cloud. But now you mentioned something that's really interesting around cloud to point out, which is moving having cloud, certainly public clouds. Great. But now moving technology to the edge edge being a data center edge being, you know, industrial I ot other things wind farms, whatever users running around remotely you mentioned. So the edges now becomes a critical component of this cloud. Two point. Oh, okay. So I gotta ask the question, How does the networking and what's the complexity? And I'm just imagining massive complexity from this. What are some of the complexities and challenges and opportunities will arise out of this new dynamic of club two point. Oh, >> So the traditional approaches does just don't work anymore. So we need new ways to not only on the networking side, but obviously also the security side. So we need to make sure that not on Lee the network follows in the footsteps of the business of what it needs. But actually, the network can drive business innovation and that the network is ready to handle those new leaps and technologies. And that's what we see is kind of being able to tightly integrate whatever pops up, being able to quickly connect to a sass provider, quickly integrate a new cloud location into your network and have the strong security posture there. Directly integrated is what you need because if you always have to think about weight, if I add this, it's gonna break something else, and I have to. To change is here. Then you lose all the speed that your business needs. >> I mean, the ripple effect of it's like throwing a stone in the lake and seeing the ripple effect with cloud to point. You mentioned a few of them. Network and Security won't get to that in a second, but doesn't change every aspect of computing categories. Backup monitoring. I mean all the sectors that were traditional siloed on premise that moves with the cloud are now being disrupted again for the third time. Yeah, you agree with that? >> It's true. And I mean your club 0.1 point. Oh, you say a lot of things will be seen his lift and shift and that still works like there is a lot of work loads where it's not worth it to re factor everything. But then, for your core applications, the business where the business makes money, you want a leverage, the latest instead of technologies to really drive, drive your business there. >> I got to get your take on this because you're the head of architecture solutions at Open Systems. Um, is a marketing tagline that I saw that you guys promote, which I live. I want to get your thoughts on. It says, Stop treating your network like a network little marketing. I love it, but it's kind of like stop trying your network like a network implying that the networks changing may be inadequate. Antiquated needs to modernize. I'm kind of feeling the vibe there on that. What do you mean by that? Slow Stop treating your network like a network. What's what's the purpose >> behind that? But yeah, in the end, it to be a little flaw provoking. But I mean, even est even in its pure forms, where you have a softer controller that steers your traffic along different path. Already. For me, as an engineer, I'm gonna lose my mind because I want to know where routing is going. I want deterministic. Lee defined my policy, so I always have things under control. But now it's a softer agent that takes care. Furred takes care of it for me so that already I lose control in favor off. Yeah, more capabilities. And I think that's cloud just kind of accelerate. >> So you guys really put security kind of in between the network and application? Is that the way you're thinking about it? It used to be Network was at the bottom. You built the application, had security. Now you're thinking differently. Explain that the the architectural thinking around this because this is a modern approach you guys were taking, and I want to get this on the record. Applications have serving users and machines network delivers packets, and then you're saying security's wrapping up between them explain. >> So when we go back again to the traditional model Central Data Center, you had a security stack full rack of appliances that the care of your security was easy to manage. Now, if you wanna go ask you when connect every brand side to the Internet, you cannot replicate such an infrastructure to every branch. Location just doesn't skill. So what do you do? Why do you say I cannot benefit of this where I use new methods? And that's where we say we integrate security directly into our networking stack. So to be able to not rely on the service training but have everything compiled into one platform and be able to leverage that data is passing through our network. You've eyes. But then why not apply the same security functions that we used to do in our headquarter directly at the edge and therefore every branch benefits of the same security posture that I typically were traditionally only had in my data center? >> You guys so but also weighing as a strategic infrastructure critical infrastructure opponent. I would agree with that. That's obvious, but as we get into hybrid cloud and multi cloud infrastructures of service support. Seamless integration is critical. This has become a topic, will certainly be talking about for the rest of the year Of'em world and reinvented other conferences like Marcel that night as well. This is the big challenge for customers. Do I invest in Azure A. W as Google in another cloud? Who knows how many clouds coming be another cloud potentially around the corner? I don't want to fork my development team. I want to do one of the great different code bases. This has become kind of like the challenge. How do you see this playing out? Because again, the applications want to run on the best cloud possible. I'm a big believer in that. I think that the cloud should dictate the AP should dictate which cloud runs. That's why I'm a believer in the single cloud for the workload, not a single cloud for all workloads. So your thoughts, >> I think, from an application point of view. As you say, the application guys have to determine more cloud is best for them, I think from a networking point of view, as a network architect, we need to we can't work against this but enable them and be able to find ways that the network can seamlessly connect to whatever cloud the business wants to use. And there's plenty of opportunity to do that today and to integrate or partner with other providers that actually have partnered with dozens of cloud providers. And as we now can architect, we have solutions to directly bring you as a customer within milliseconds, to each cloud, premise is a huge advantage. It takes a few clicks in a portal. You have a new clouds instance up and running, and now you're connected. And the good thing is, we have different ways to do that. Either. We spin up our virtual instance virtual esti one appliance in cloud environments so we can leverage the Internet to go. They're still all secured, all encrypted, ordering me again. Use different cloud connect interconnections to access the clouds. Depending on the business requirements, >> you guys have been very successful. A lot of comfort from financial service is the U. N. With NGOs, variety of industries. So I want to get your thoughts on this. I've been we've been covering the Department of Defense is joining and Chet I joint and the presentation of defense initiative where the debate was soul single purpose Cloud. Now the reality is and we've covered this on silicon angle that D O D is going multi cloud as an organization because they're gonna have Microsoft Cloud for collaboration and other contracts. They're gonna win $8,000,000,000. So that a Friday cloud opportunities, but for the particular workload for the military, they have unique requirements. Their workload has chosen one cloud. That was the controversy. Want to get your thoughts on this? Should the workloads dictate the cloud? And is that okay? And certainly multi cloud is preferred Narada instances. But is it okay to have a single cloud for a workload? >> Yeah, again, from if the business is okay with that, that's fine from our side of you. We see a lot of lot of business that have global presence, so they're spread across the globe. So for them, it's beneficial to done distribute workloads again across different regions, and it could still be the same provider, but across different regions. And then already, question is How do you now we're out traffic between those workloads? Do we? Do you love right? Your esteem and infrastructure or do you actually use, for example, the backbone that the cloud provider provides you in case of Microsoft? They guarantee you the traffic between regions stay in their backbone. So gifts, asshole, new opportunities to leverage large providers. Backbone. >> And this is an interesting nuance point because multi cloud doesn't have to be. That's workload. Spreading the workload across three different clouds. It's this workload works on saving Amazon. This workload works on Azure. This workload works on another cloud that's multi cloud from a reality standpoint today, so that implies that most every country will be multi cloud for sure. But workloads might have a single cloud for either the routing and the transit security with the data stored. And that's okay, too. >> Yeah, yeah, and keep in mind, Cloud is not only infrastructure or platform is the service. It's also software as a service. So as soon as we have sales forests, work day office 3 65 dropbox or box, then we are multiplied. >> So basically the clouds are fighting it out by the applications that they support and the infrastructure behind. Exactly. All right, well, what's next for you? You're on the road. You guys doing a lot of customer activity. What's the coolest thing that you're seeing in the customer base from open system standpoint that you like to share with the audience? >> Um, so again, it's just cool to see that customers realized that there's plenty of opportunities. And just to see how we go through that evolution with our customers, were they initially or little concerned? But then eventually we see that actually, the network change drives new business project and customers air happy that they launched or collaborate with us. That's what that's what makes me happy and makes me and a continuing down that path >> and securing it is a key. Yeah, he wins in this market Having security? >> Absolutely. Yeah, Sylvia saying mind and not wake up at 2 a.m. Full sweat, because here >> we'll manage. Service is a preferred for my people like to consume and procure product in So congratulations and congressional on your Silicon Valley office looking for chatting more. I'm John for here in the keep studios for cute conversation. Thanks for watching

>> Live, from Barcelona, Spain, it's theCUBE, covering KubeCon and CloudNativeCon Europe, 2019. Brought to you by Red Hat, the Cloud Native Computing Foundation and ecosystem partners. >> Welcome back. This is theCUBE at KubeCon CloudNativeCon 2019 here in Barcelona, Spain. I'm Stu Miniman, my co-host is Corey Quinn and welcoming back to the program, friend of the program, Brian Gracely who is the Director of Product Strategy at Red Hat. Brian, great to see you again. >> I've been, I feel like I've been in the desert. It's three years, I'm finally back, it's good to be back on theCUBE. >> Yeah well, I feel like we've been traveling parallel paths a lot. TheCUBE goes to a lot of events. We do a lot of interviews but I think when you go to shows, you actually have more back-to-back meetings than we even do, so we feel you in the jet lag and a little bit of exhaustion. Thanks for making time. >> Yeah, it's great. I had dinner with you two weeks ago, I did a podcast with Corey a week ago, and now, due to the magic of the internet, we're all here together in one place. It's good. >> Absolutely. Well Brian, as we know at a show like this we all want to hold hands and sing Kubernetes Kumbaya. It's wonderful to see that all of the old fights of the past have all been solved by software in the cloud. >> They're all good, it's all good. Yeah, somebody said it's a cult. I think I heard Owen Rodgers said it's now officially a cult. Corey, you called it the Greek word for spending lots of money. >> Uh yeah, it was named after the Kubernetes, the Greek god of spending money on cloud services. >> So, Brian, you talk to a lot of customers here. As they look at this space, how do they look at it? There's still times that I hear them, "I'm using this technology and I'm using this technology, "and gosh darn it vendor, "you better get together and make this work." So, open-source, we'd love to say is the panacea, but maybe not yet. >> I don't think we hear that as much anymore because there is no more barrier to getting the technology. It's no longer I get this technology from vendor A and I wish somebody else would support the standard. It's like, I can get it if I want it. I think the conversations we typically have aren't about features anymore, they're simply, my business is driven by software, that's the way I interact with my customer, that's the way I collect data from my customers, whatever that is. I need to do that faster and I need to teach my people to do that stuff. So the technology becomes secondary. I have this saying and it frustrates people sometimes, but I'm like, there's not a CEO, a CIO, a CTO that you would talk to that wakes up and says, "I have a Kubernetes problem." They all go, "I have a, I have this business problem, "I have that problem, it happens to be software." Kubernetes is a detail. >> Yeah Brian, those are the same people 10 years ago had a convergent problem, I never ran across them. >> If you screw up a Kubernetes roll-out, then you have a Kubernetes problem. But it's entertaining though. I mean, you are the Director of Product Strategy, which is usually a very hard job with the notable exception of one very large cloud company, where that role is filled by a post-it note that says simply, yes. So as you talk to the community and you look at what's going on, how are you having these conversations inform what you're building in terms of Openshift? >> Yeah, I mean, strategy you can be one of two things. You can either be really good at listening, or you can have a great crystal ball. I think Red Hat has essentially said, we're not going to be in the crystal ball business. Our business model is there's a lot of options, we will go get actively involved with them, we will go scratch our knees and get scars and stuff. Our biggest thing is, I have to spend a lot of time talking to customers going, what do you want to do? Usually there's some menu that you can offer them right now and it's really a matter of, do you want it sort of half-baked? Are you willing to sort of go through the learning process? Do you need something that's a little more finalized? We can help you do that. And our big thing is, we want to put as many of those things kind of together in one stew, so that you're not having-- Not you Stu, but other stews, thinking about like, I don't want to really think about them, I just want it to be monitored, I want the network to just work, I want scalability built in. So for us it's not so much a matter of making big, strategic bets, it's a matter of going, are we listening enough and piecing things together so they go, yeah, it's pretty close and it's the right level of baked for what I want to do right now. >> Yeah, so Brian, an interesting thing there. There's still quite a bit of complexity in this ecosystem. Red Hat does a good job of giving adult supervision to the environment, but, you know, when I used to think when row came out, it was like, okay, great. Back in the day, I get a CD and I know I can run this. Today here, if I talk to every Kubernetes customer that I run across and say okay, tell me your stack and tell me what service measure you're using, tell me which one of these projects you're doing and how you put them together. There's a lot of variation, so how do you manage that, the scale and growth with the individual configurations that everybody still can do, even if they're starting to do public clouds and all those other things? >> So, it's always interesting to me. I watch the different Keynotes and people will talk about all the things in their stack and why they had problems and this, that, and the other, and I kind of look at it and I'm like, we've solved that problem for you. Our thing is always, and I don't mean that sort of boastfully, but like, we put things together in what we think are pretty good defaults. It's the one probably big difference between Openshift and a lot of these other ones that are here is that we've put all those things together as sort of what we think are pretty good defaults. We allow some flexibility. So, you don't like the monitoring, you don't like Prometheus plugin splunk, that's fine. But we don't make you stand on your head. So for us, a lot of these problems that, our customers don't go, well, we can't figure out the stack, we can't do these things, they're kind of built in. And then their problem becomes okay, can I highly automate that? Did I try and make too many choices where you let me plug things in? And for us, what we've done, is I think if we went back a few years, people could say you guys are too modular, you're too plugable. We had to do that to kind of adapt to the market. Now we've sort of learned over time, you want to be immutable, you want to give them a little less choice. You want to really, no, if you're going to deploy an AWS, you got to know AWS really well. And that's, you know, not to make this a commercial, but that's basically what Openshift four became, was much more opinions about what we think are best practices based on about a thousand customers having done this. So we don't run into as many of pick your stack things, we run into that next level thing. Are we automating it enough? Do we scale it? How do we do statefulness? Stuff like that. >> Yeah, I'm curious in the Keynote this morning they called, you know, Kubernetes is a platform of platforms. Did that messaging resonate with you and your customers? >> Yeah, I think so, I mean, Kubernetes by itself doesn't really do anything, you need all this other stuff. So when I hear people say we deployed Kubernetes, I'm like, no you don't. You know, it's the engine of what you do, but you do a bunch of other stuff. So yeah, we like to think of it as like, we're platform builders, you should be a platform consumer, just like you're a consumer of Salesforce. They're a platform, you consume that. >> Yeah, one of the points made in the Keynote was how one provider, I believe it was IBM, please yell at me if I got that one wrong, talks about using Kubernetes to deploy Kubernetes. Which on the one hand, is super cool and a testament to the flexibility of how this is really working. On the other, it's-- and thus the serpent devours itself, and it becomes a very strange question of, okay, then we're starting to see some weird things. Where do we start, where do we look? Indeed.com for a better job. And it's one of those problems that at some point you just can't manage a head around complexities inside of complexities, but we've been dealing with that for 40 years. >> Yeah, Kubernetes managing Kubernetes is kind of one of those weird words like serverless, you're like what does that mean? I don't, it doesn't seem to, I don't think you mean what you want it to mean. The simplest way we explain that stuff, so... A couple of years ago there was a guy named Brandon Philips who had started a company called CoreOS. He stood up at Kube-- >> I believe you'll find it's pronounce CoreOS, but please, continue. >> CoreOS, exactly. Um, he stood up in the Seattle one when there was a thousand people at this event or 700, and he said, "I've created this pattern, "or we think there's a pattern that's going to be useful." The simplest way to think of it is, there's stuff that you just want to run, and I want essentially something monitoring it and keep it in a loop, if you will. Kubernetes just has that built in. I mean, it's kind of built in to the concept because originally Google said, "I can't manage it all myself." So that thing that he originally came up with or codified became what's now called operators. Operators is that thing now that's like okay, I have a stateful application. It needs to do certain things all the time, that's the best practice. Why don't we just build that around it? And so I think you heard in a lot of the Keynotes, if you're going to run storage, run it as an operator. If you're going to run a database, run it as an operator. It sounds like inception, Kubernetes running-- It's really just, it's a health loop that's going on all the time with a little bit of smarts that say hey, if you fail, fail this way. I always use the example like if I go to Amazon and get RDS, I don't get a DVA, there's no guy that shows up and says, "Hey, I'm your DVA." You just get some software that runs it for you. That's all this stuff is, it just never existed in Kubernetes before. Kubernetes has now matured enough to where they go, oh, I can play in that world, I can make that part of what I do. So it's less scary, it sounds sort of weird, inception-y. It's really just kind of what you've already gotten out of the public cloud now brought to wherever you want it. >> Well, one of the concerns that I'm starting to see as well is there's a level of hype around this. We've had a lot of conversations around Kubernetes today and yesterday, to the point where you can almost call this Kubernetes and friends instead of CloudNativeCon. And everyone has described it slightly differently. You see people describing it as systemd, as a kernel, sometimes as the way and the light, and someone on stage yesterday said that we all are familiar with the value that Kubernetes has brought to our jobs and our lives, is I think was the follow-up to that, which is a little strange. And I got to thinking about that. I don't deny that it has brought value, but what's interesting to me about this is I don't think I've heard two people define its value in the same terminology at all, and we've had kind of a lot of these conversations. >> So obviously not a cult because they would all be on message if it was a cult. >> Yeah, yeah yeah yeah. >> It's a cult with very crappy brand control, maybe. We don't know. >> I always just explain it that like, you know, if I went back 10 years or something, people... Any enterprise said hey, I would love to run like Google or like Amazon. Apparently for every one admin, I can manage a thousand servers and in their own data centers it's like well, I have one guy and he manages five, so I have cloud envy. >> We tried to add a sixth and he was crushed to death. Turns out those racks have size and weight limits. >> That's right, that's right. And so, people, they wanted this thing, they would've paid an arm and a leg for it. You move forward five years from that and it's like oh, Google just gave you their software, it's now available for free. Now what are you going to do with it? I gave you a bunch of power. So yeah, depending on how much you want to drink the Kool-Aid you're like, this is awesome, but at the end of the day you're just like, I just want the stuff that is available to, that's freely, publicly available, but for whatever reason, I can't be all in on one cloud, or I can't be all in on a public cloud, which, you believe in that there's tons of economic value about it, there's just some companies that can't do that. >> And I fully accept that. My argument has always been that it is, I think it's a poor best practice. When you have a constraint that forces you to be in multiple cloud providers, yes, do it! That makes absolute perfect sense. >> Right, if it makes sense, do it. And that's kind of what we've always said look, we're agnostic to that. If you want to run it, if you want to run it in a disconnected mode on a cruise ship, great, if it makes sense for you. If you need to run, you know, like... The other thing that we see-- >> That cruise ship becomes a container ship. >> Becomes a container ship. I had an interesting conversation with the bank last night. I had dinner with the bank. We were talking, they said, look, I run some stuff locally where I'm at, 'cause I have to, and then, we put a ton of stuff in AWS. He told me this story about a batch processing job that cost him like $4 or $5 million today. He does a variant of it in Lambda, and it cost him like $50 a month. So we had this conversation and it's going like, I love AWS, I want to be all in at AWS. And he said, here's my problem. I wake up every morning worried that I'm going to open the newspaper and Amazon, not AWS, Amazon is going to have moved closer into the banking industry than they are today. And so I have to have this kind of backup plan if you will. Backup's the wrong word, but sort of contingency plan of if they stop being my technology partner and they start becoming my competitor, which, there's arguments-- >> And for most of us I'd say that's not a matter of if, but when. >> Right, right. And some people live with it great. Like, Netflix lives with it, right? Others struggle. That guy's not doing multi-cloud in the future, he's just going, I would like to have the technology that allows me if that comes along. I'm not doing it to do it, I'd like the bag built in. >> So Brian, just want to shift a little bit off of kind of the mutli-cloud discussion. The thing that's interest me a lot, especially I've talked to a number of the Openshift customers, it is historically, infrastructure was the thing that slowed me down. We understand, oh, I want to modernize that. No, no wait. The back in thing or you know, provisioning, these kind of things take forever. The lever of this platform has been, I can move faster, I can really modernize my environment, and, whether that's in my data center or in one public cloud and a couple of others, it is that you know, great lever to help me be able to do that. Is that the right way to think about this? You've talked to a lot of customers. Is that a commonality between them? >> I think we see, I hate to give you a vendor answer, but we tend to see different entry points. So for the infrastructure people, I mean the infrastructure people realize in some cases they're slow, and a lot of cases the ones that are still slow, it's 'cause of some compliance thing. I can give you a VM in an hour, but I got to go through a process. They're the ones that are saying, look, my developers are putting stuff in containers or we're downloading, I just need to be able to support that. The developers obviously are the ones who are saying, look, business need, business problem, have budget to do something, That's usually the more important lever. Just faster infrastructure doesn't do a whole lot. But we find more and more where those two people have to be in the room. They're not making choices independently. But the ones that are successful, the ones that you hear case studies about, none of them are like, we're great at building containers. They're great at building software. Development drives it, infrastructure still tends to have a lot of the budget so they play a role in it, but they're not dictating where it goes or what it does. >> Yeah, any patterns you're seeing or things that customers can do to kind of move further along that spectrum? >> I think, I mean there's a couple of things, and whether you fit in this or not, number one, nobody has a container problem. Start with a business problem. That's always good for technology in general, but this isn't a refresh thing, this is some business problem. That business problem typically should be, I have to build software faster. We always say... I've seen enough of these go well and I've seen enough go poorly. There's, these events are great. They're great in the sense of people see that there's progress, there's innovation. They're also terrible because if you walk into this new, you feel like, man, everybody understands this, it must be pretty simple. And what'll happen is they start working on it and they realize, I don't know what I'm doing. Even if they're using Openshift and we made it easy, they don't know what they're doing. And then they go, I'm embarrassed to ask for help. Which is crazy because if you get into open source the community's all there to help. So it's always like, business problem, ask for help early and often, even if it embarrasses you. Don't go after low-hanging fruit, especially if you're trying to get further investment. Spinning up a bunch of web clusters or hello worlds doesn't, nobody cares anymore. Go after something big. It basically forces your organization to be all in. And then the other thing, and this is the thing that's never intuitive to IT teams, is you, at the point where you actually made something work, you have to look more like my organization than yours, which is basically you have to look like a software marketing company, because internally, you're trying to convince developers to come use your platform or to build faster or whatever, you actually have to have internal evangelist and for a lot of them, they're like, dude, marketing, eh, I don't want anything to do with that. But it's like, that's the way you're going to get people to come to your new way of doing things. >> Great points, Brian. I remember 15 years ago, it was the first time I was like wait, the CIO has a marketing person under him to help with some of those transformations? Some of the software roles to do. >> Yeah, it's the reason they all want to come and speak at Keynotes and they get at the end and they go, we're hiring. It's like, I got to make what I'm doing sound cool and attract 8,000 people to it. >> Well absolutely it's cool here. We really appreciate Brian, you sharing all the updates here. >> Great to see you guys again. It's good to be back. >> Definitely don't be a stranger. So for Corey Quinn, I'm Stu Miniman. Getting towards the end. Two days live, wall-to-wall coverage here at KubeCon, CloudNativeCon 2019. Thanks for watching theCUBE. (rhythmic music)

(bright music) >> Hi, I'm Peter Burris, and welcome to another special digital community event, brought to you by theCUBE and Wikibon. We've got a great session planned for the next hour or so. Specifically, we're gonna talk about the journey to the data-driven multi-cloud. Sponsored by IBM, with a lot of great thought leadership content from IBM guests. Now, what we'll do is, we'll introduce some of these topics, we'll have these conversations, and at the end, this is gonna be an opportunity for you to participate, as a community, in a crowd chat, so that you can ask questions, voice your opinions, hear what others have to say about this crucial issue. Now why is this so important? Well Wikibon believes very strongly that one of the seminal features of the transition to digital business, driving new-type AI classes of applications, et cetera, is the ability of using flash-based storage systems and related software, to do a better job of delivering data to more complex, richer applications, faster, and that's catalyzing a lot of the transformation that we're talking about. So let me introduce our first guest. Eric Herzog is the CMO and VP Worldwide Storage Channels at IBM. Eric, thanks for coming on theCUBE. >> Great, well thank you Peter. We love coming to theCUBE, and most importantly, it's what you guys can do to help educate all the end-users and the resellers that sell to them, and that's very, very valuable and we've had good feedback from clients and partners, that, hey, we heard you guys on theCUBE, and very interesting, so I really appreciate all the work you guys do. >> Oh, thank you very much. We've got a lot of great things to talk about today. First, and I want to start it off, kick off the proceedings for the next hour or so by addressing the most important issue here. Data-driven. Now Wikibon believes that digital transformation means something, it's the process by which a business treats data as an asset, and re-institutionalizes its work and changes the way it engages with customers, et cetera. But this notion of data-driven is especially important because it elevates the role that storage is gonna play within an organization. Sometimes I think maybe we shouldn't even call it storage. Talk to us a little bit about data-driven and how that concept is driving some of the concepts in innovation that are represented in this and future IBM products. >> Sure. So I think the first thing, it is all about the data, and it doesn't matter whether you're a small company, like Herzog's Bar and Grill, or the largest Fortune 500 in the world. The bottom line is, your most valuable asset is you data, whether that's customer data, supply chain data, partner data that comes to you, that you use, services data, the data you guys sell, right? You're an analysis firm, so you've got data, and you use that data to create you analysis, and then you use that as a product. So, data is the most critical asset. At the same time, data always goes onto storage. So if that foundation of storage is not resilient, is not available, is not performant, then either A, it's totally unavailable, right, you can't get to the customer data. B, there's a problem with the data, okay, so you're doing supply chain and if the storage corrupts the data, then guess what? You can't send out the T-shirts to the right retail location, or have it available online if you're an online retailer. >> Or you sent 200,000 instead of 20, and you get stuck with the bill. >> Right, exactly. So data is that incredible asset and then underneath, think of storage as the foundation of a building. Data is your building, okay, and all the various aspects of that data, customer data, your data, internal data, everything you're doing, that's the building. If the foundation of the building isn't rock solid the building falls down. Whether your building is big or small, and that's what storage does, and then storage can also optimize the building above it. So think of it more than just the foundation but the foundation if you will, that almost has like a tree, and has got things that come up from the bottom and have that beautiful image, and storage can help you out. For example, metadata. Metadata which is data about data could be used by analytics, package them, well guess what? The metadata about data could be exposed by the storage company. So that's why data-driven is so important from an end-user perspective and why storage is that foundation underneath a data-driven enterprise. >> Now we've seen a lot of folks talk about how cloud is the centerpiece of thinking about infrastructure. You're suggesting that data is the centerpiece of infrastructure, and cloud is gonna be an implementation decision. Where do I put the workloads, costs, all the other elements associated with it. But it suggests ultimately that data is not gonna end up in one place. We have to think about data as being where it needs to be to perform the work. That suggests multi-cloud, multi-premise. Talk to us a little bit about the role that storage and multi-cloud play together. >> So let's take multi-cloud first and peel that away. So multi-cloud, we see a couple of different things. So first of all, certain companies don't want to use a public cloud. Whether it's a security issue, and actually some people have found out that public cloud providers, no matter who the vendor is, sort of is a razor in a razor blade. Very cheap to put the storage out there but we want certain SLAs, guess what? The cloud vendors charge more. If you move data around a lot, in and out as you were describing, it's really that valuable, guess what? On ingress and egress gets you charges for that. The cloud provider. So it's almost the razor and the razor blades. So A, there's a cost factor in public only. B, you've got people that have security issues. C, what we've seen is, in many cases, hybrid. So certain datasets go out to the cloud and other datasets stay on the premises. So you've got that aspect of multi, which is public, private or hybrid. The second aspect, which is very common in bigger companies that are either divisionalized or large geographically, is literally the usage, in a hybrid or a public cloud environment, of multiple cloud vendors. So for example, in several countries the data has to physically stay within the confines of that country. So if you're a big enterprise and you've got offices in 200 different, well not 200, but 100 different countries, and 20 of 'em you have to keep in that country by law. If your cloud provider doesn't have a data center there you need to use a different cloud provider. So you've got that. And you also have, I would argue that the cloud is not new anymore. The internet is the original cloud. So it's really old. >> Cloud in many respects is the programming model, or the mature programming model for the internet-based programming applications. >> I'd agree with that. So what that means is, as it gets more mature, from the mid-sized company up, all of a sudden procurement's involved. So think about the way networking, storage and servers, and sometimes even software was bought. The IT guy, the CIO, the line of business might specify, I want to use it but then it goes to procurement. In the mid to big company it's like, great, are we getting three bids on that? So we've also seen that happen, particularly with larger enterprise where, well you were using IBM cloud, that's great, but you are getting a quote from Microsoft or Amazon right? So those are the two aspects we see in multi-cloud, and by the way, that can be a very complex situation dealing with big companies. So the key thing that we do at IBM, is make sure that whichever model you take, public, private or hybrid, or multiple public clouds, or multiple public cloud providers, using a hybrid configuration, that we can support that. So things like our transparent cloud tiering, we've also recently created some solution blueprints for multi-clouds. So these things allow you to simply and easily deploy. Storage has to be viewed as transparent to a cloud. You've gotta be able to move the data back and forth, whether that be backing the data up, or archiving the data, or secondary data usage, or whatever that may be. And so storage really is, gotta be multi-cloud and we've been doing those solutions already and in fact, but honestly for the software side of the IBM portfolio for storage, we have hundreds of cloud providers mid, big and small, that use our storage software to offer backup as a service or storage as a service, and we're again the software foundation underneath what an end-user would buy as a service from those cloud providers. >> So I want to pick up on a word you used, simplicity. So, you and I are old infrastructure hacks and for many years I used to tell my management, infrastructure must do no harm. That's the best way to think about infrastructure. Simplicity is the new value proposition, complexity remains the killer. Talk to us a little bit about the role that simplicity in packaging and service delivery and everything else is again, shaping the way you guys, IBM, think about what products, what systems and when. >> So I think there's a couple of things. First of all, it's all about the right tool for the right job. So you don't want to over-sell and sell a big, giant piece of high-end all-flash array, for example, to a small company. They're not gonna buy that. So we have created a portfolio of which our FlashSystem 9100 is our newest product, but we've got a whole set of portfolios from the entry space to the mid range to the high end. We also have stuff that's tuned for applications, so for example, our lasting storage server which comes in an all-flash configuration is ideal for big data analytics workloads. Our DS8000 family of flash is ideal for mainframe attach, and in fact we have close to 65% of all mainframe attached storage, is from IBM. But you have the right tool for the right job, so that's item number one. The second thing you want to do is easier and easier to use. Whether that be configuring the physical entity itself, so how do you cable, how do you rack and stack it, make sure that it easily integrates into whatever else they're putting together in their data center, but it a cloud data center, a traditional on-premises data center, it doesn't matter. The third thing is all about the software. So how do you have software that makes the array easier and easier to use, and is heavily automated based on AI. So the old automation way, and we've both been in that era, was you set policies. Policy-based management, and when it came out 10 years ago, it was a transformational event. Now it's all about using AI in your infrastructure. Not only does your storage need to be right to enable AI at the server workload level, but we're saying, we've actually deployed AI inside of our storage, making it easier for the storage manager or the IT manager, and in some cases even the app owner to configure the storage 'cause it's automated. >> Going back to that notion that the storage knows something about the metadata, too. >> Right, exactly, exactly. So the last thing is our multi-cloud blueprint. So in those cases, what we've done is create these multi-cloud blueprints. For example, disaster recovery and business continuity using a public cloud. Or secondary data use in a public cloud. How do you go ahead and take a snapshot, a replica or a backup, and use it for dev-ops or test or analytics? And by the way, our Spectrum copy data management software allows you, but you need a blueprint so that it's easy for the end user, or for those end users who buy through our partners, our partners then have this recipe book, these blueprints, you put them together, use the software that happens to come embedded in our new FlashSystem 9100 and then they use that and create all these various different recipes. Almost, I hate to say it, like a baker would do. They use some base ingredients in baking but you can make cookies, candies, all kinds of stuff, like a donut is essentially a baked good that's fried. So all these things use the same base ingredients and that software that comes with the FlashSystem 9100, are those base ingredients, reformulated in different models to give all these multi-cloud blueprints. >> And we've gotta learn more about vegetables so we can talk about salad in that metaphor, (Eric laughing) you and I. Eric once again. >> Great, thank you. >> Thank you so much for joining us here on the CUBE. >> Great, thank you. >> Alright, so let's hear this come to life in the form of a product video from IBM on the FlashSystem 9100. >> Some things change so quickly, it's impossible to track with the naked eye. The speed of change in your business can be just as sudden and requires the ability to rapidly analyze the details of your data. The new, IBM FlashSystem 9100, accelerates your ability to obtain real-time value from that information, and rapidly evolve to a multi-cloud infrastructure, fueled by NVMe technology. In one powerful platform. IBM FlashSystem 9100, combines the performance, of IBM FlashCore technology. The efficiency of IBM Spectrum Virtualize. The IBM software solutions, to speed your multi-cloud deployments, reduce overall costs, plan for performance and capacity, and simplify support using cloud-based IBM storage insights to provide AI-powered predictive analytics, and simplify data protection with a storage solution that's flexible, modern, and agile. It's time to re-think your data infrastructure. (upbeat music) >> Great to hear about the IBM FlashSystem 9100 but let's get some more details. To help us with that, we've got Bina Hallman who's the Vice President Offering Management at IBM Storage. Bina, welcome to theCUBE. >> Well, thanks for having me. It's an exciting even, we're looking forward to it. >> So Bina, I want to build on some of the stuff that we talked to Eric about. Eric did a good job of articulating the overall customer challenge. As IBM conceives how it's going to approach customers and help them solve these challenges, let's talk about some of the core values that IBM brings to bear. What would you say would be one of the, say three, what are the three things that IBM really focuses on, as it thinks about its core values to approach these challenges? >> Sure, sure. It's really around helping the client, providing a simple one-stop shopping approach, ensuring that we're doing all the right things to bring the capabilities together so that clients don't have to take different component technologies and put them together themselves. They can focus on providing business value. And it's really around, delivering the economic benefits around CapEx and OpEx, delivering a set of capabilities that help them move on their journey to a data-driven, multi-cloud. Make it easier and make it simpler. >> So, making sure that it's one place they can go where they can get the solution. But IBM has a long history of engineering. Are you doing anything special in terms of pre-testing, pre-packaging some of these things to make it easier? >> Yeah, we over the years have worked with many of our clients around the world and helping them achieve their vision and their strategy around multi-cloud, and in that journey and those set of experiences, we've identified some key solutions that really do make it easier. And so we're leveraging the breadth of IBM, the power of IBM, making those investment to deliver a set of solutions that are pre-tested, they are supported at the solutions level. Really focusing on delivering and underpinning the solutions with blueprints. Step-by-step documentation, and as clients deploy these solutions, they run into challenges, having IBM support to assist. Really bringing it all together. This notion of a multi-cloud architecture, around delivering modern infrastructure capabilities, NVMe acceleration, but also some of our really core differentiation that we deliver through FlashCore data reduction capabilities, along with things like modern data protection. That segment is changing and we really want to enable clients, their IT, and their line of business to really free them up and focus on a business value, versus putting these components together. So it's really around taking those complex things and make them easier for clients. Get improved RPO, RTO, get improved performance, get improved costs, but also flexibility and agility are very critical. >> That sounds like therefore, I mean the history of storage has been trade-offs that you, this can only go that fast, and that tape can only go that fast but now when we start thinking about flash, NVMe, the trade-offs are not as acute as they used to be. Is IBM's engineering chops capable of pointing how you can in fact have almost all of this at one time? >> Oh absolutely. The breadth and the capabilities in our R and D and the research capabilities, also our experiences that I talked about, engagements, putting all of that together to deliver some key solutions and capabilities. Like, look, everybody needs backup and archive. Backup to recover your data in case of a disaster occurs, archive for long-term retention. That data management, the data protection segment, it's going through a transformation. New emerging capabilities, new ways to do backup. And what we're doing is, pulling all of that together, with things that we introduced, for example, our Protect Plus in the fourth quarter, along with this FS 9100 and the cloud capabilities, to deliver a solution around data protection, data reuse, so that you have a modern backup approach for both virtual and physical environments that is really based on things like snapshots and mountable copies, So you're not using that traditional approach to recovering your copy from a backup by bringing it back. Instead, all you're doing is mounting one of those copies and instantly getting your application back and running for operational recovery. >> So to summarize some of those value, once stop, pre-tested, advanced technologies, smartly engineered. You guys did something interesting on July 10th. Why don't you talk about how those values, and the understanding of the problem, manifested so fast. Kind of an exciting set of new products that you guys introduced on July 10th. >> Absolutely. On July 10th we not only introduced our flagship FlashSystem, the FS 9100, which delivers some amazing client value around the economic benefits of CapEx, OpEx reduction, but also seamless data mobility, data reuse, security. All the things that are important for a client on their cloud journey. In addition to that, we infused that offering with AI-based predictive analytics and of course that performance and NVMe acceleration is really key, but in addition to doing that, we've also introduced some very exciting solutions. Really three key solutions. One around data protection, data reuse, to enable clients to get that agility, and second is around business continuity and data reuse. To be able to really reduce the expense of having business continuity in today's environment. It's a high-risk environment, it's inevitable to have disruptions but really being prepared to mitigate some of those risks and having operational continuity is important and by doing things like leveraging the public cloud for your DR capabilities. That's very important, so we introduced a solution around that. And the third is around private cloud. Taking your IBM storage, your FS 9100, along with the heterogeneous environment you have, and making it cloud-ready. Getting the cloud efficiencies. Making it to where you can use it for environments to create things like native cloud applications that are portable, from on-prem and into the cloud. So those are some of the key ways that we brought this together to really deliver on client value. >> So could you give us just one quick use case of your clients that are applying these technologies to solve their problems? >> Yeah, so let me use the first one that I talked about, the data protection and data reuse. So to be able to take your on-premise environment, really apply an abstraction layer, set up catalogs, set up SLAs and access control, but then be able to step away and manage that storage all through API bays. We have a lot of clients that are doing that and then taking that, making the snapshots, using those copies for things like, whether it's the disaster recovery or secondary use cases like analytics, dev-ops. You know, dev-ops is a really important use case and our clients are really leveraging some of these capabilities for it because you want to make sure that, as application developers are developing their applications, they're working with the latest data and making sure that the testing they're doing is meaningful in finding the maximum number of defects so you get the highest quality of code coming out of them and being able to do that, in a self-service driven way so that they're not having to slow down their innovation. We have clients leveraging our capabilities for those kinds of use cases. >> It's great to hear about the FlashSystem 9100 but let's hear what customers have to say about it. Not too long ago, IBM convened a customer panel to discuss many aspects of this announcement. So let's hear what some of the customers had to say about the FlashSystem 9100. >> Now Owen, you've used just about every flash system that IBM has made. Tell us, what excites you about this announcement of our new FlashSystem 9100. >> Well, let's start with the hardware. The fact that they took the big modules from the older systems, and collapsed that down to a two-and-a-half inch form-factor NVMe drive is mind-blowing. And to do it with the full speed compression as well. When the compression was first announced, for the last FlashSystem 900, I didn't think it was possible. We tested it, I was proven wrong. (laughing) It's entirely possible. And to do that on a small form-factor NVMe drive is just astounding. Now to layer on the full software stack, get all those features, and the possibilities for your business, and what we can do, and leverage those systems and technologies, and take the snapshots in the replication and the insights into what our system's doing, it is really mind-blowing what's coming out today and I cannot wait to just kick those tires. There's more. So with that real-world compression ratio, that we can validate on the new 900, and it's the same in this new system, which is astounding, but we can get more, and just the amount of storage you get in this really small footprint. Like, two rack units is nothing. Half our services are two rack units, which is absolutely astounding, to get that much data in such a very small package, like, 460 terabytes is phenomenal, with all these features. The full solution is amazing, but what else can we do with it? And especially as they've said, if it's for a comparable price as what we've bought before, and we're getting the full solution with the software, the hardware, the extremely small form-factor, what else can you do? What workloads can you pull forward? So where our backup systems weren't on the super fast storage like our production systems are, now we can pull those forward and they can give the same performance as production to run the back-end of the company, which I can't wait to test. >> It's great to hear from customers. The centerpiece of the Wikibon community. But let's also get the analyst's perspective. Let's hear from Eric Burgener, who's the Research Vice President for Storage at IDC. >> Thanks very much Peter, good to be back. >> So we've heard a lot from a number of folks today about some of the changes that are happening in the industry and I want to amplify some things and get the analyst's perspective. So Wikibon, as a fellow analyst, Wikibon believes pretty strongly that the emergence of flash-based storage systems is one of the catalyst technologies that's driving a lot of the changes. If only because, old storage technologies are focused on persisting data. Disc, slow, but at least it was there. Flash systems allow a bit flip, they allow you to think about delivering data to anywhere in your organization. Different applications, without a lot of complexity, but it's gotta be more than that. What else is crucial, to making sure that these systems in fact are enabling the types of applications that customers are trying to deliver today. >> Yeah, so actually there's an emerging technology that provides the perfect answer to that, which is NVMe. If you look at most of the all-flash systems that have shipped so far, they've been based around SCSI. SCSI was a protocol designed for hard disk drives, not flash, even though you can use it with flash. NVMe is specifically designed for flash and that's really gonna open up the ability to get the full value of the performance, the capacity utilization, and the efficiencies, that all-flash arrays can bring to the market. And in this era of big data, more than ever, we need to unlock that performance capability. >> So as we think about the big data, AI, that's gonna have a significant impact overall in the market and how a lot of different vendors are jockeying for position. When IDC looks at the impact of flash, NVMe, and the reemergence of some traditional big vendors, how do you think the market landscape's gonna be changing over the next few years? >> Yeah, how this market has developed, really the NVMe-based all-flash arrays are gonna be a carve-out from the primary storage market which are SCSI-based AFAs today. So we're gonna see that start to grow over time, it's just emerging. We had startups begin to ship NVMe-based arrays back in 2016. This year we've actually got several of the majors who've got products based around their flagship platforms that are optimized for NVMe. So very quickly we're gonna move to a situation where we've got a number of options from both startups and major players available, with the NVMe technology as the core. >> And as you think about NVMe, at the core, it also means that we can do more with software, closer to the data. So that's gotta be another feature of how the market's gonna evolve over the next couple of years, wouldn't you say? >> Yeah, absolutely. A lot of the data services that generate latencies, like in-line data reduction, encryption and that type of thing, we can run those with less impact on the application side when we have much more performant storage on the back-end. But I have to mention one other thing. To really get all that NVMe performance all the way to the application side, you've gotta have an NVMe Over Fabric connection. So it's not enough to just have NVMe in the back-end array but you need that RDMA connection to the hosts and that's what NVMe Over Fabric provides for you. >> Great, so that's what's happening on the technology-product-vendor side, but ultimately the goal here is to enable enterprises to do something different. So what's gonna be the impact on the enterprise over the next few years? >> Yeah, so we believe that SCSI clearly will get replaced in the primary storage space, by NVMe over time. In fact, we've predicted that by 2021, we think that over 50% of all the external, primary storage revenue, will be generated by these end-to-end NVMe-based systems. So we see that transition happening over the course of the next two to three years. Probably by the end of this year, we'll have NVMe-based offerings, with NVMe Over Fabric front ends, available from six of the established storage providers, as well as a number of smaller startups. >> We've come a long way from the brown, spinning stuff, haven't we? >> (laughing) Absolutely. >> Alright, Eric Burgener, thank you very much. IDC Research Vice President, great once again to have you in theCUBE. >> Thanks Peter. >> Always great to get the analyst's perspective, but let's get back to the customer perspective. Again, from that same panel that we saw before, here's some highlights of what customers had to say about IBM's Spectrum family of software. (upbeat music) We love hearing those customer highlights but let's get into some of the overall storage trends and to do that we've asked Eric Herzog and Bina Hallman back to theCUBE. Eric, Bina, thanks again for coming back. So, what I want to do now is, I want to talk a little bit about some trends within the storage world and what the next few years are gonna mean, but Eric, I want to start with you. I was recently at IBM Think, and Ginni Rometty talked about the idea of putting smart to work. Now, I can tell you, that means something to me because the whole notion of how data gets used, how work gets institutionalized around your data, what does storage do in that context? To put smart to work. >> Well I think there's a couple of things. First we've gotta realize that it's not about storage, it's about the data and the information that happens to sit on the storage. So you have to have storage that's always available, always resilient, is incredibly fast, and as I said earlier, transparently moves things in and out of the cloud, automatically, so that the user doesn't have to do it. Second thing that's critical is the integration of AI, artificial intelligence. Both into the storage solution itself, of what the storage does, how you do it, and how it plays with the data, but also, if you're gonna do AI on a broad scale, and for example we're working with a customer right now and their AI configuration in 100 petabytes. Leveraging our storage underneath the hood of that big, giant AI analytics workload. So that's why they have to both think of it in the storage to make the storage better and more productive with the data and the information that it has, but then also as the undercurrent for any AI solution that anyone wants to employ, big, medium or small. >> So Bina, I want to pick up on that because there are gonna be some, there's some advanced technologies that are being exploited within storage right now, to achieve what Eric's talking about, but there's gonna be a lot more. And there's gonna be more intensive application utilizations of some of those technologies. What are some of the technologies that are becoming increasingly important, from a storage standpoint, that people have to think about as they try to achieve their digital transformation objectives. >> That's right, I mean Peter, in addition to some of the basics around making sure your infrastructure is enabled to handle the SLAs and the level of performance that's required by these AI workloads, when you think about what Eric said, this data's gonna reside, it's gonna reside on-premise, it's gonna be behind a firewall, potentially in the cloud, or multiple public clouds. How do you manage that data? How do you get visibility to that data? And then be able to leverage that data for your analytics. And so data management is going to be very important but also, being able to understand what that data contains and be able to run the analytics and be able to do things like tagging the metadata and then doing some specialized analytics around that is going to be very important. The fabric to move that data, data portability from on-prem into the cloud, and back and forth, bidirectionally, is gonna be very important as you look into the future. >> And obviously things like IOT's gonna mean bigger, more, more available. So a lot of technologies, in a big picture, are gonna become more closely associated with storage. I like to say that, at some point in time we've gotta stop thinking about calling stuff storage because it's gonna be so central to the fabric of how data works within a business. But Eric, I want to come back to you and say, those are some of the big picture technologies but what are some of the little picture technologies? That none-the-less are really central to being able to build up this vision over the course of the next few years? >> Well a couple of things. One is the move to NVMe, so we've integrated NVMe into our FLashSystem 9100, we have fabric support, we already announced back in February actually, fabric support for NVMe over an InfiniBand infrastructure with our FlashSystem 900 and we're extending that to all of the other inter-connects from a fabric perspective for NVMe, whether that be ethernet or whether that be fiber channel and we put NVMe in the system. We also have integrated our custom flash models, our FlashCore technology allows us to take raw flash and create, if you will, a custom SSD. Why does that matter? We can get better resiliency, we can get incredibly better performance, which is very tied in to your applications workloads and use cases, especially in data-driven multi-cloud environment. It's critical that the flash is incredibly fast and it really matters. And resilient, what do you do? You try to move it to the cloud and you lose your data. So if you don't have that resiliency and availability, that's a big issue. I think the third thing is, what I call the cloud-ification of software. All of IBM's storage software is cloud-ified. We can move things simultaneously into the cloud. It's all automated. We can move data around all over the place. Not only our data, not only to our boxes, we could actually move other people's array's data around for them and we can do it with our storage software. So it's really critical to have this cloud-ification. It's really cool to have this now technology, NVMe from an end-to-end perspective for fabric and then inside the system, to get the right resiliency, the right availability, the right performance for your applications, workloads and use cases, and you've gotta make sure that everything is cloud-ified and portable, and mobile, and we've done that with the solutions that are wrapped into our FlashSystem 9100 that we launched a couple of weeks ago. >> So you are both though leaders in the storage industry. I think that's very clear, and the whole notion of storage technology, and you work with a lot of customers, you see a lot of use cases. So I want to ask you one quick question, to close here. And that is, if there was one thing that you would tell a storage leader, a CIO or someone who things about storage in a broad way, one mindset change that they have to make, to start this journey and get it going so that it's gonna be successful. What would that one mindset change be? Bina, what do you think? >> You know, I think it's really around, there's a lot of capabilities out there. It's really around simplifying your environment and making sure that, as you're deploying these new solutions or new capabilities, that you've really got a partnership with a vendor that's gonna help you make it easier. Take those complex tasks, make them easier, deliver those step-by-step instructions and documentation and be right there when you need their assistance. So I think that's gonna be really important. >> So look at it from a portfolio perspective, where best of breed is still important, but it's gotta work together because it leverages itself. >> It's gotta work together, absolutely. >> Eric, what would you say? >> Well I think the key thing is, people think storage is storage. All storage is not the same and one of the central tenets at IBM storage is to make sure that we're integrated with the cloud. We can move data around transparently, easily, simply, Bina pointed out the simplicity. If you can't support the cloud, then you're really just a storage box, and that's not what IBM does. Over 40% of what we sell is actually storage software and all that software works with all of our competitors' gear. And in fact our Spectrum Virtualize for Public Cloud, for example, can simultaneously have datasets sitting in a cloud instantiation, and sitting on premises, and then we can use our copy data management to take advantage of that secondary copy. That's all because we're so cloud-ified from a software perspective, so all storage is not the same, and you can't think of storage as, I need the cheapest storage. It's gotta be, how does it drive business value for my oceans of data? That's what matters most, and by the way, we're very cost-effective anyway, especially because of our custom flash model which allows us to have a real price advantage. >> You ain't doing business at a level of 100 petabytes if you're not cost effective. >> Right, so those are the things that we see as really critical, is storage is not storage. Storage is about data and information. >> So let me summarize your point then, if I can really quickly. That in other words, that we have to think about storage as the first step to great data management. >> Absolutely, absolutely Peter. >> Eric, Bina, great conversation. >> Thank you. >> So we've heard a lot of great thought leaderships comments on the data-driven journey with multi-cloud and some great product announcements. But now, let's do the crowd chat. This is your opportunity to participate in this proceedings. It's the centerpiece of the digital community event. What questions do you have? What comments do you have? What answers might you provide to your peers? This is an opportunity for all of us collectively to engage and have those crucial conversations that are gonna allow you to, from a storage perspective, drive business value in your digital business transformations. So, let's get straight to the crowd chat. (bright music)

>> From Orlando, Florida it's theCUBE! Covering SAP SAPPHIRE NOW 2018, brought to you by NetApp. >> Welcome to theCUBE I'm Lisa Martin with Keith Townsend and we are in Orlando at SAP SAPPHIRE NOW 2018, where we're in the NetApp booth and talking with lots of partners and we're excited to welcome back to theCUBE, distinguished alumni Jim McHugh from NVIDIA, you are the VP and GM of Deep Learnings and "other stuff" as you said in the keynote. (all laugh) >> Yeah, and other stuff. That's a lot of responsibility! That other stuff, that, you know, that can really pile up! >> That can kill ya. Yeah, exactly. >> So here we are at SAPPHIRE you've been working with SAP in various forms for a long time, this event is enormous, lots of momentum at NVIDIA, what is NVIDIA doing with SAP? >> We're really helping SAP figure out and drive the development of their SAP Leonardo machine learning services so, machine learning, as we saw in the keynote today, with Haaso as a key component of it, and really what it's doing is it's automating a lot of the standard processes that people did, in the interactions, so whether it's closing your invoices at the end of the quarter, and that can take weeks to go through it manually, you can actually do machine learning and deep learning and do that instantaneously, so you can get a continuous close. Things like service ticketing, so when a service ticket comes in, you know, we all know, you pick up the phone, you call 'em and they collect your information, and then they pass you on to someone else that wants to confirm the information, all that can be handled just in a email, because now I know a lot about you when you send me an email I know who you are, know what company you're with, I know your problem 'cause you stated it, and I can route it, using machine learning, to the appropriate person. I can not only route it to the appropriate person I can look up in a knowledge database and say hey, have we seen this answer a question before feed that to the customer service representative, and when they start interacting with the customer they already have a lot of information about them and it's already well underway. >> So from a practical technology perspective we hear a lot about AI, machine learning, NVIDIA obviously leading the way with GPUs and enabling development frameworks to take advantage of machine learning and that compute power. But the enterprise, we'll at that and we're like you know that, we see obvious value, but I need a data scientist, I need a programmer, I need all this capability, from a technical staff perspective, to take advantage of it. How is NVIDIA, SAP, making that easier to consume? >> So most enterprises, if you're just jumpin' in and tryin' to figure it out, you would need all these people, you'd need a data scientist and someone to go through the process. 'Cause AIs, it's a new way of writing software, and you're using data to train the software, so we don't have, we don't put programmers in a room anymore and let 'em code for nine months and out pops software, you know, eventually. We give 'em more and more data, and the data scientist is training it. Well the good news is we're working with SAP and they have the data scientists, they know how SAP apps work, they know how the integration works, they know the workflows of their customers, so they're building the models and then making it available as a service, right? So when you go to the SAP cloud, you're saying I wanna actually take advantage of the SAP service for service ticketing or, you know, I wanna figure out how I can do my invoice processing better, or I'm an HR representative, and I don't wanna spend 60% of my time reading resumes, I wanna actually have an AI do it for me, and then it's a service that you can consume. There, that we do make it possible, like if you have a developer in your enterprise and you say you know what, I'm a big SAP user but I actually wanna develop a custom app or other some things I might do, then SAP makes available the Leonardo machine learning foundation and you can take advantage of that and develop a custom app. And if you have a really big problem and you wanna take it off, NVIDIA's happy to work with you directly and figure out how to solve different problems. And most of our customers are in all three of those, Right? They're consuming the services 'cause they automate things today, they're figuring out, what are the custom apps they need to build around SAP and then they're, you know, they're figuring out some of the product building products or something else that's a much bigger machine learning, deep learning problem. >> So yesterday during Bill McDermott's keynote he talked about tech for good, now there's been a lot of news recently of tech for not-so-good and data privacy, GDPR, you know, compliance going into affect last week, NVIDIA really has been an integral part of this AI renaissance, you talked about, you know, you can help loads of different customers there's so much potential with AI, as Bill McDermott said yesterday, AI to augment humanity. I can imagine, you know, life and death situations like in healthcare, can you give us an example of what you guys are doing with SAP that, you know, maybe is transforming healthcare at a particular hospital? >> Yeah, so one of the great examples I was just talking about is, what Massachusetts General is doing. Massachusetts General is one of the largest research hospitals in the United States, and they're doing a lot of work in AI, to really automate processes that, you know, when you would take your child in to figure out the bone density scan, which basically tells you the bone age of your child, and they compare it to your biological age, and that can tell you a lot of things, is it just a, you know, a growth problem, or is there something more serious to be concerned about. Well, they would do these MRIs, and then you would have to wait for days while the, the technician and the doctor would flip through a textbook from the 1950's, to determine it. Well Massachusetts General automated all that where they actually trained a neural network on all these different scans and all these different components and now you find out in minutes. So it greatly reduces the stress, right? And there's plenty of other project going on and you can see it in determination if that's a cancer cell, or, you know, so many different aspects of it, your retina happens to be an incredible venue into whether you have hypertension, whether you have Malaria, Dengue fever, so things like, you know what, maybe you shouldn't be around anywhere where you're gonna get bit by a mosquito and it's gonna pass it to your family, all that can now be handled, and you don't need expensive healthcare, you can actually take it to a clinician out in the field. So, we love all that. But if you think about the world of SAP which is the, you know, controls the data records of most companies, right? Their supply chain information, their resource information about, you know, what they have available, all that's being automated. So if we think from the production of food where we're having tractors now that they have the ability to go over a plant and say you know what, that needs insecticide or that needs weeds to be removed 'cause it's just bad for the whole component, or that's a diseased plant and I'm gonna remove it, or it just needs water so it can grow, right? That is increasing the production of food in an organic way, then we improve the distribution centers so it doesn't sit as long, right, so that we can actually have drones flying through the warehouses and knowing what needs to be moved first, go from there, we're moving to autonomous driving vehicles and, where deliveries can happen at night when there's not so much traffic, and then we can get the food as fresh as possible and deliver it. So if you think that whole distribution center and just being in the pipeline as being automated, it's doing an incredible amount of good. And then, jumping into the world of autonomous driving vehicles, it's a 10 trillion dollar business that's being changed, radically. >> So as we think about these super complex systems that we're trying to improve, we start to break them down into small components, smaller components, you end up with these scenarios, these edge scenarios, use cases where, you know, whether it's data frequency, data value, or data latency, we have to push to compute out to the edge. Can you talk about use cases where NVIDIA has pushed the technology far out to the edge to take in massive amounts of data, that effectively can't be sent back to the core or to the data center for processing, what are some of these use cases solutions? >> So it's, the world of IOT is changing as well, right, the compute power has to be where it's needed, right, and in any form, so whether that's cloud based, data center based, or at the edge and we have a great customer that is actually doing inspection, oil refineries, bridges, you know, where they spot a crack or some sort of mark where they have to go look at it, well traditionally what you do is you send out a whole team and they build up scaffolding, or they have people repel down to try to inspect it. Well now what we're doing is flying drones and sending wall crawlers up. So they find something, they get data, and then, instead of actually, like you said, putting it, you know, on a truck and taking it back to your data center or trying to figure out how to have enough bandwidth to get there, they're taking one of our products, which is a DGX station, it's basically the equivalent of a half a row of servers, but it's in a single box, water cooled, and they're putting it in vans sitting out in remote areas of Alaska, and retraining the model there on site. So, they get the latest model, they get more intelligence and they just collect it, and they can resend the drones up and then discover more about it. So it really, really is saving, and that saves a lot of money, so you have a group of really smart you know, technicians and people who understand it and a guy who can do the neural network capability instead of a whole team coming up and setting up scaffolding that would cost millions of dollars. >> That reminds me of that commercial that they showed yesterday during general session SAP commercial with Clive Owen the actor, talking about, you mentioned, you know, cracks in oil wells and things like that it just reminded me of that, and what they talked about in that video was really how invisible software, like SAP, is transforming industries, saving lives, I think I saw on their website an example of how they're leveraging AI and technology to reduce water scarcity in India or save the rhino conservation and what you just described with NVIDIA seems to be quite in alignment with the direction that SAP is going. >> Oh absolutely, yeah, I mean we believe in SAP's view of the intelligent enterprise and people gotta remember, enterprise isn't just like the corporate office whatever, enterprises are many different things, alright. Public safety, if you can think about that, that's a big thing we focus on. A really amazing thing that's going on, thinking about using drones for first responders they actually can know what's going on at the scene and when the other people are showing up they know what kind of area they're going into. Or for search and rescue, drones can cover a lot of territory and detect a human faster than a human can, right? And if you can actually find someone within the first 24 hours, chance of survival is so much higher. All of that is, you know, leveraging the exact same technology that we do for looking at our business processes, right, and it's not as, you know, dramatic, it's not gonna show up on the evening news, but honestly, streamlining our business processes, making it happen so much faster and more efficient makes businesses more efficient, you know, it's better for the company, it's better for the employees as well. >> So let's talk about, something that's, that's taboo, financial services, making money with data, or with analytics or machine learning from data, again we have to, John Furrier is here, and we have someone from NVIDIA here, and if we don't bring up blockchain in some type of way he's gonna throw something at his team, so, >> Let's give a shout out to John Furrier. (laughing) >> Give a shout out to John. But from a practical sense, let's subtract the digital currency part of machine, of blockchain, do you see applications for blockchain from a machine learning perspective? >> Yeah, I mean well, if you just boil blockchain down or for trusted networks, right? And you know you heard Bill McDermott say that on stage he called his marketplaces, or areas that he could do for an exchange, it makes total sense. If I can have a trusted way of doing things where I have a common ledger between companies and we know that it's valid, that we can each interchange with, yeah it makes complete sense, right, now we gotta get to the practical imitation of that and we have to build the trust of the companies to understand, okay this technology can take you there, and that's where I think, you know, where we come in with our technology capabilities, ensuring to people that it's reliable and work, SAP comes in with the customer relationships and trusted in what they've been doing in helping people run their business for years, and then it becomes cultural. Like all things, we can kid ourselves in technology that we'll just solve everything, it's a cultural change. I'm gonna share that common ledger, I'm gonna share that common network and feel confident in it, it's something that people have to do and, you know, my take on that always is when the accuracy is so much better, when the efficiency is so much better, when the return is so much better, we get a lot more comfortable. People used to be nervous about giving the grocery store their phone number, right, 'cause they would track their food, right? And today we're just like okay yeah here's my phone number. (Keith laughing) >> So. (laughs) >> Give you a 30 cent discount, here's my number. >> Exactly. We're so cheap. (laughing) >> So we're in the NetApp booth and you guys recently announced a reference, combined reference, AI reference architecture with NetApp, tell us a little bit more about that. >> Yeah, well the little secret behind all the things we just talked about, there's an incredible amount of data, right, and as you collect this data it's really important to store it in a way that it's accessible when you need it. And when you're doing trainings, I have a product that's called DGX-1, DGX-1 takes an incredible amount of data that helps us train these neural networks, and it's fast, and it has an insatiable desire for data. So what we've worked with NetApp is actually pool together reference architecture so that when a data scientist, who is a very valuable resource, is working on this, he's ensured that the infrastructures are gonna work together seamlessly and deliver that data to the training process. And then when you create that model, we use something that's called inference, you put it in production, and again same time, when you're having that inference running you wanna make sure that data can get to it and can interact with the data seamlessly and the reference architectures play out there as well. So our goal is, start knocking off one by one, what do the customers need to be successful? And we put a lot of effort into the GPUs, we put a lot of effort into the deep learning software that runs on top of that, we put a lot of effort into, you know, what's the models they need to use, etc. And now we have to spend a lot more time of what's their infrastructure? And make sure that's reliable because, you would hate to do all that work only to find that your infrastructure had a hiccup, and took your job down. So we're working really hard to make sure that never happens >> So I have this theory that, well I don't have the theory, David Curry came out with this theory of data has gravity, but I've come up with this additional theory, now that we look at AI, and the capability of AI and what people are and what the hyper scalers are doing in their data center is that individual companies think, have a challenge replicating in their own data center, this AI and compute now has gravity. You know, I can't well, at least before today I didn't think well I can take my data center, put it on the road, and do these massive pieces of injection on the edge, sounds like we're pushin' back on that a little bit and saying that you know what sure if it's, I don't know what the limits are, and I guess that's the question. What are the limits of what we can do on the edge when it comes to the amount of data, and portable AI to that edge? >> Well so, there's again the two aspects of it, the training takes an incredible amount of data that's why they would have to take a super computer and put it there so they could do the retraining, but, when you think about when you can have the pro-- something the size of a credit card, which is our Jetson solution, and you can install it in a drone or you can put in cameras for public safety, etc. Which is, has incredible, think about looking for a lost child or parents with Alzheimer's, you can scan through video real quick and find them, right? All because of a credit card sized processor, that's pretty impressive. But that's what's happening at the edge, we're now writing applications that are much more intelligent using AI, there are AI applications sitting at the edge that, instead of just processing the data in a way where I'm getting a average, average number of people who walked into my store, right, that's what we used to do five years ago, now we're actually using intelligent applications that are making calculated decisions, it's understanding who's coming in a store, understanding their buying/purchasing power, etc. That's extremely important in retail, because, if you wanna interact with someone and give them that, you know when they're doing self checkout, try to sell 'em one more thing, you know, did you forget the batteries that go with that, or whatever you want it to be, you only have a few seconds, right? And so you must be able to process that and have something really intelligent doing that instead of just trying to do the law of average and get a directionally correct-- and we've known this, anytime you've been on your webpage or whatever and someone recommends something you're like that doesn't have anything to do with me and then all of a sudden it started getting really good that's where they're getting more intelligent. >> When I walk into the store with my White Sox hat and then they recommend the matching jersey. I'm gonna look, gonna come lookin' for you guys at NVIDIA like wa-hey! I don't have money for a jersey, but things like that, yeah. >> We're just behind the scenes somewhere. >> Well, you title VP and GM of Deep Learning and stuff, there's a lot of stuff. (all laugh) Jim thanks so much for coming back on theCUBE sharing with us what's new at NVIDIA it sounds like the world of possibilities is endless, so exciting! >> Yeah, it is an exciting time, thank you. >> Thanks for your time, we wanna thank you for watching theCUBE, Lisa Martin with Keith Townsend from SAP SAPPHIRE 2018, thanks for watching. (bubbly music)