(gentle music) >> Good afternoon, cloud community and welcome back to fabulous Las Vegas, Nevada. We are at AWS re:Invent. It's our fourth day, it's in the afternoon. We've got two more segments left. This is a serious marathon, but it's so exciting, it's kept my brain super curious. I'm Savannah Peterson, joined by Paul Gillan today. Paul- >> Hello Savannah. >> Are you as excited about how much we've learned this week as I am? >> I am. It's just taking, my mind is just bursting with all the new information I've absorbed over the last three days. Amazing talking to all these smart people. >> It has really been so cool. >> And learning about all the permutations that we to think about cloud but there are so many businesses that have been built around the cloud, around making the cloud easier to use, supporting cloud as our next guest can talk about, that there's this whole ecosystem element that we don't hear about so much, but it's very much the foundation of the people who are here. >> Speaking of ecosystem, our next guest, please welcome Garrett to the show. Runs Ecosystem for Console Connect. How you doing Eric? >> I'm doing very well. >> Savannah: Garrett, sorry. Excuse me. >> No worries. >> Few names on the show today. >> Garrett: I'm sure. >> I do know your name, my mouth just doesn't want to, just doesn't want to participate today. Have you had a great show so far? >> It's been fantastic. You know, the AWS re:Invent show has always been a fantastic event, so. >> You're a veteran. You're also a CUBE alumni, which is great. >> Yes. Thank you for having me back. Thank you for your time. I most appreciated it. >> Yeah. We love having you. It's going to be great. We'll, we'll try and do even better each time we have you on the show. So just in case those listening are unfamiliar with Console Connect, give us the pitch. >> Okay, so Console Connect is our software defined interconnect platform. We also provide what we call network as a service. This allows our customers and partners to take advantage of our global private network on a pay as you go basis. Scalable and flexible. When you're not using the service, you can turn it off. So you only pay as you go. >> What a novel idea. >> Yes, yes. In the past you would have to have a year or multi-year contract. So we're making our services match cloud offerings around the world. The platform itself is in more than a thousand data centers all around the globe. >> Savannah: Just a couple. >> Yes, just a few. We have about 45 terabits of network behind it. It's all on our private network, so none of it's accessible via the public internet and we have a meeting place which allows our existing customers and partners to reach out across the platform and share services. So one customer needs to subscribe to another customer services, they can do so right across the platform on a pay as to go basis. So it's been very exciting for us. It's been very fast, it seems to me, for the past five or six years that we've had the service. >> At what point in their cloud journey do customers typically realize they need a service like yours? If the bandwidth they're getting, their native bandwidth they're getting is insufficient. >> Yeah, and I think that's a great question. I think the customers themselves have seen a serious disconnect between their direct connections to the cloud service providers where the cloud service providers are billing by the minute. And a traditional telecommunications connection is built by the year or multi years and then you really lose control over your cloud connection when you forget about it, right? Because service is always up. The connection's always up. >> Yeah. >> And a lot of individuals in a company may have access to the cloud, that cloud service, provider service. And next thing you know, you have a runaway group of services that are running that you're paying for and you don't really realize it 'cause the connection's up, you've already paid the connection the cloud service is up, you've already paid for it. >> So how do businesses get better control over that spend or how do you help them? >> Yeah, so how we help them is our service is able to be turned off when it's not in use. So in the event that you don't need the service over a weekend or over a month, you can just turn it off and you're not paying for that. >> It sounds so simple but it actually is kind of revolutionary in the industry which is why I keep coming back to it. It's great. So we've heard a lot about hybrid cloud, multicloud. How is this increasing the complexity for customers? >> Well I think the complexity for customers has increased due to the fact that you have a multicloud requirement or you have multiple teams accessing your cloud service provider and there's no one really managing it from a central perspective. >> Savannah: They can definitely get siloed really easy. >> Yeah, and then it runs away from you and the next thing you know, you start to look at the monthly bills. But generally that happens on an annual basis. If any companies like mine, you're doing your annual reconciliation of your bills and that's when you notice something's not right. >> Yeah, definitely. I can actually see a Slack message I got once, multiple times probably. Is anyone using this service? Why does it cost us that? That's exactly what you're talking about. >> Do you integrate with the Amazon Management Console or is it a separate service? >> It's, our service is a separate service. We are APId in with AWS. You do have a single console from our platform to manage your connections to the cloud. And then once you are connected in, you would still need to use the AWS console to manage your service. They're very, let's just say no one is offering a remote console third party console yet for AWS or any other cloud service for that matter. >> How about for hybrid cloud is obviously the way, you know, the way the industry is going. How do you enable companies to manage their hybrid cloud environments more intelligently? >> Yeah, and that's another great question. We allow that, you know, we're a global company. We have global access around the world. It includes not only traditional telecommunication services but also includes satellite service as well as 5G and LTE capability to the platform. So in the event that someone is in a hyper cloud situation, they have a lot of capability to enable their services. >> You talked about network as a service, and I, we haven't had a chance to dig into it. So tell me a little bit more. How does, how can this help reduce egress charges? How, are people excited when they hear network as a service? Where are we off at on that hype curve? >> Yeah, I think it's low on the excitement scale. >> Savannah: Yeah. >> You know, network has become somewhat of a commodity in the world, like electricity or water, you know, for the most of the world. And so network as a service, what it has enabled is it has enabled the customers more control over what they're doing. 'Cause in the past, you would need weeks, if not months to get services installed. And then if you needed to make a change to that service to increase it or decrease it in accordance to your requirements, that might take a couple of days at the soonest and you know, the Console Connect platform now changed that down to a few minutes. So within a few minutes, you can enable services, turn it up, turn it down, scale up, scale down. >> Savannah: Talk about time to value. >> There's no equipment installation required? >> No, it is our private network and so there must be a direct connection to it. It's not available over the public internet. Generally, a customer will connect to us via a cross connect at a data center or they can bring in a local loop. Or our existing customers, we just flip a little switch, so to speak, software wise, and we give them access to the platform from their existing services. >> Do you work with co-location interconnects as well? >> Exactly, yes. And in fact, you can purchase those services across our platform with a lot of the co-location service providers. >> So if I'm already using a co-lo, I can deploy your service directly from that co-lo. >> Yes. Yes. >> That's very convenient. >> That is very convenient. (laughs) >> You also mentioned the ability interconnect between customers. So your customers can actually connect to each other and conduct transactions or integrate their applications. Talk about how that works. >> Yeah, so for instance, let's say you are a customer that's taking advantage of our platform and you find your network is under a DDoS attack. You can go into our meeting place, connect to one of our cloud service providers who specializes in DDoS mitigation, spin up a connection to them within a few minutes, and immediately, you can start taking care of your DDoS problem. And once it's taken care of, you turn it down. Now those types of services that are subscription based are via API into our platform so we can settle the bill for our customer on behalf of that service provider or the service provider themselves can bill that customer depending on how they want to set it up. So it's very flexible. >> It's really clever, too. I mean, especially in an instance like you just mentioned in that example, that's a moment of panic and high stress and high tension. The last thing you want to be thinking about is what's the right service provider? How quickly can I get this up and running? If I can just couple clicks, couple lines of code perhaps, or even just through the portal, be able to do it, it's pretty powerful. You mentioned that Console Connect, and I want to talk about this 'cause it's clear you care about the user experience, the community and Console Connect came out of LinkedIn DNA and you mentioned there's a social component to the platform as well. Can you tell me a little bit more about that? >> Yes, thank you for that. Yeah, so you can, as a customer or a partner, you can market directly to others on the platform using our meeting place. And you have the ability to reach out directly to people across the platform, send them a message. You have the ability to post articles, blog in one of our sections. And then the other one, you can actually go in and see all the latest activity in the platform. You can see who's the newest companies to join Console Connect. >> Savannah: Oh wow, cool. >> How do I reach out to them? And then that gives you the ability to begin either marketing across the platform or direct marketing to someone or directly just reach out and connect with them and say hey, we want to set a bilateral partnership with you. You know, how do we do that? So it's very flexible. >> Savannah: Yeah. >> Can I connect my systems to others? So if I want to plug into their eCommerce system so I can fulfill orders taken through their eCommerce system, can I enable that kind of connection? >> Oh, we're not there yet. It is coming, but we're just not there yet. >> What are the complexities? >> A lot of that is a trust issue. >> Yeah. >> You know, when you're dealing with across the globe, there are regulations in every location that must be adhered to. A lot of that is security and privacy related. And we must make sure that we are adhering to all the local regulations wherever we are. >> So it's not the technology, it's a problem, really. It's the- >> It's a regulatory issue, yeah. So the technology is there and I would say that the rest is following, it's just, it's slow when you're dealing with permits and with compliance. >> I also want to ask you, our notes here mention egress charges, which are a niggling pain point for a lot of customers. They have to pay to get their data of the cloud. How do you help with that problem? >> So how we help with this is first, we get a discount from our partners, our cloud partners, including AWS, and we pass that on to the customers. The other way is you have a full visibility of which connections you have live into those partners and you can manage that much easier through the single, I would say view. Of all of your connections. >> Savannah: Yeah. >> You can see all of your cloud connections right in the one view. And then you can do a little more digging and say are we using these, you know? Because a lot of times, you have projects that spin up and then someone forgets to spin them back down. So this helps give you that single view. But again, we get the discount that we are happy to pass on as well. >> Which is a win-win for everyone. I've using a tab analogy all show, we all we want it in one place, one tab, not all the tabs. >> Yes. I think network management and service management in any enterprise or partnership company is a real drain on resources. >> Oh yeah. And it's a waste of money. >> Garrett: Yeah. And if you're not managing correctly, yeah, you get the thing on the money. >> Are you an alternative to the direct connect services from the major cloud providers or are you a compliment to them? >> We're not competing with them, we're partnered. And so we don't see ourselves as an alternative. A lot of times, our customers come to us and they want to direct connect in a location where perhaps AWS isn't. >> Paul: Doesn't have a point of presence. >> Exactly. Right. We give them that flexibility of, yes you can directly connect here. And then the other approach that we like to take is we like to give our customers the choice of not only data center, but also region. So a lot of times egress charges are can be calculated across regions as well and that can really add up for our customer. Whereas if you have multiple egress locations, you're not transferring data across a region on the AWS platform or another cloud service platform. You can egress at that location and then take it across your own network or take it across our network and then your egress charges will be more reasonable. >> That's, it's convenient. Smart! You're making people's jobs optimized and easier as well as their stack and all the tools that they're using. It's fantastic. All right Garrett, we've got a new challenge here on theCUBE at re:Invent. >> Garrett: All right. >> It's probably different from the last time you were on theCUBE. We're looking for your 30 second hot take, your thought leadership moment. What's the biggest theme coming out of the show or for you as we look into 2023? >> Well, for in 30 seconds- >> Savannah: Yeah, casual, right? >> No pressure. >> Savannah: No big deal. >> No, so with Console Connect, you know, we are around the globe. I know that a lot of companies at AWS are, some are regional, some are global. And we have the ability to cover both. We can do either regional or global or a hybrid of those. We also have a hybrid approach on different types of services. And so the flexibility, scalability, reliability, and the lowered cost of egress with Console Connect is a win all around. You can't lose with it. >> I love it. You're meeting customers where they are. Garrett, it was fantastic to have you back on theCUBE. We look forward to your third cameo. >> Thank you very much. I appreciate your time. Thank you for having Console Connect on. >> Hey, absolutely. We look forward to continuing to watch and hopefully tell that story as well. And thank all of you for tuning in to day four of AWS's re:Invent coverage in Las Vegas, Nevada. I'm starting to forget my own name. I am with Paul Gilland. I'm Savannah Peterson. This is theCUBE. We are the leading source for high tech coverage. (gentle music)

(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.

>>Okay, welcome back everyone. To the cubes coverage of AWS summit, 2022 in San Francisco, California. We're here, live on the floor at the Mosconi south events are back. I'm John fur, your host. Remember AWS summit 2022 in New York city is coming this summer. We'll be there with the live cube there as well. Look for us there, but of course, we're back in action with the cloud and AWS. Our next guest Garrett Miller is the general manager of navigation at Mapbox. I mean, it's been a Amazon customer for a long time, Garrett. Thanks for coming on the cube. >>Yeah. Thanks for having us, John. >>So you guys are in the middle of, I love the whole location base slash we developer integration. We've had many conversations on the cube around how engineers and developers are becoming embedded into the application, whether it's from a security standpoint, biometrics, all kinds of stuff, being built into the app and, and location navigation. That's right. Is huge from cars. Everyone knows their car, car map. That's right. GPS satellites, some space it's complicated. It sounds like it sounds easy, but I know it's hard. Yeah. You, you get the keynote going on today. Give us a quick update on Mapbox and we'll then we'll talk about the keynote. >>Yeah. You bet John that's right. So as you were saying, you know, it really is. It's all about location intelligence. And how does that get embedded into the applications? And to the point you made vehicles that are out there on the roads to today. So we target developers. Those are our key customers, and we've got over three and a half million registered on the platform today. They consume the modules that we build with APIs, SDKs, data sets, and more and more applications to accomplish whatever those location needs might be. >>Why we appreciate you coming on. You are featured keynote by presenter here at summit, which means Amazon thinks you're super important to share. I'll say your customer. So you, I know you've been a customer for a long time as a company, but what was your keynote about what was the main theme? The developers were all here. You got the builders. What was your content? What did you present this morning on the keynote? Yeah, >>Well, this morning we really talked a lot about logistics and the, this story that we told was know in the logistics industry, there is a massive movement to shorter and shorter delivery windows. And so the, the, the story that we told is really around a 10 minute delivery. Now, have you ever wondered how you get a 10 minute delivery? You, you place an order on your phone and all of a sudden somebody shows up at your front doorstep. You ever wonder about that? >><laugh> >>Some shows supply >>Chain. Someone's waiting in the wings from my call. >>Yeah. >>Yeah. Well, that's right. >>John's about to order sometime soon. That's right. You ready? That's right. Do all these assets. That's >>Right. They're all ready for you. But there's actually a tremendous amount that actually goes into that. And so it really starts with designing the right distribution system up front. And so we've got tools and, and applications and, and APIs that support that. And really it, every single step of the way, location is a critical aspect to making that delivery happen and getting it to a customer's doorstep in 10 minutes or less. And so how are you understanding the real time road graph that underlies a, a, a driver going from perhaps a dark store, dark kitchen to getting in, excuse me, in front of a customer in 10 minutes with hot food. >>I mean, this is a big point. I was just joking about waiting for me, you know, that, but the point is, is that it's not obvious, but it sounds really hard. I know it's hard because to have that delivery, a lot of things have to happen. It's not just knowing location. >>That's exactly >>Right. So can you just UN pull appeal back the covers on that? What's going on there? >>Yeah. So imagine this is, is, it really starts, as I was saying with designing that distribution system and it's putting in place where you might not expect it, it's actually putting in place a retail store, but these aren't any retail stores, right? These are dark stores. These are dark kitchens that are strategically placed as close as possible, the customer density, so that you can actually shorten that window as much as possible to get you whatever that order might be. But from there, it actually goes quite a bit further when an order actually comes in, you've gotta be able to understand how do I sign an, a driver to get that order to the customer in that, in that very short period of time, more often than not, it's getting it to the driver that can get there the fastest, once you've got the right driver identified, how are you actually then going to enable them to get from point a to B to get that order. >>And then perhaps from B to C to get to your front door, being able to do turn by turn navigation that reflects everything. That's how happening in the real world to be able to get there on a timely way is critical. And then wrapping around that actually the, the, the end customer's experience your experience with how are you placing that order? Yeah. How are you using Mapbox services to do that? How are you being able to track on your application and say, well, you know, great, I expect 10 minutes and they're five minutes away. Are you gonna show up our APIs and SDKs power? That experience, >>I wanna get into the product in a second, but you brought up something I think's important to highlight. One is dark kitchens, dark stores. That's right. Okay. Term people may or may not have heard of, we all have experience in COVID going to our favorite restaurant, which has been kind of downsized because of the COVID and we're waiting for our food. And someone comes in from another delivery ever standing in line next was just pick something up. I mean, they're going through the front door. That's like the, the, the branded store. So, so is it right to say that dark kitchens are essentially replicas of the store to minimize that traffic, but, but also to be efficient for something else that's right. >>It actually even goes further than that. There are many restaurant brands. Now, it only exists as a brand. They don't have a restaurant that you can go to and sit down and have that meal. They actually only operate dark kitchens to, to serve that demand of people wanting to order up, Hey, I want my food. I want it. Now, those brands exist to serve that need. >>All right. So great for the definition, we just define dark kitchens, dark stores, but also brings, I wanna get your reaction to this before we get into the product, cuz this is a trend that's right. This is not like a one off thing. That's right. It's not a pulled forward TA a market that was COVID enabled. This is actually a user experience inflection point. That's >>Right. >>Can you share your vision on what this means? Because there's mobile ordering, there's the dynamics of the kitchens as a supplier of something in stores. So that's content or a product that's being delivered to a consumer via of the web. So now there's gotta be a whole nother reef factoring of the operating environment. Now that's what's happening is that might get that >>Right? No, that's exactly right. And even if you step back, even further and you, you think about the, the journey that the logistics industry has been on, it used to be that two days was that really exciting delivery time. Right. And everybody got it super excited. Then it became next day. Then it became same day and now it's become 10 minutes. And even some companies are out there offering seven minute deliveries, right. And in order to do that, you've gotta completely retool your business. So you can think the logistics and industry really existing on two continuums, you've got pre-planned deliveries on one hand and on-demand deliveries on the other. And there are two parallel distribution systems and ecosystems and industries really springing up to serve those different types of demand. >>So you've been on Amazon web services customer for how many years, >>Since 2013 in our founding. And you know, actually we're really proud to say that we were born on Amazon and we have scaled on Amazon. >>How are they helping you scale? What are they doing to help you? >>Well, I'd say just about everything. And if you think about their, the, the services that Amazon provides for us, they power every single step of our business along the way. And so I'll give you an example. We can walk through that with some of the tech technology. I, if you think about again, how do you get 10 minutes? You gotta have a pretty precise understanding of what's going on in the real world. And so to do that, it, for us, it all starts with collecting billions and billions of data points from sensors that are out there in the world. We stream that into our technology stack, starting at the very beginning with Amazon ESIS. And so that's just the start. But then that feeds into our entire technology stack that all runs on site on top of AWS, to where we're running our own AI models that we use Amazon SageMaker to make, and then stream it back out to our AP, through our APIs, to our se Ks and applications that sit on the edge again, all leveraging Amazon technology. >>Well, I think this is a great use case and I'll get back into the, the Mapbox a second, but Amazon, you guys are executing what I call the super cloud vision, which is snowflake you guys building on their CapX leverage. You're building a super cloud on your own. It's your app, it's your cloud. >>That's right. That's right. So if you, again, if you think about it, you know, and actually just stepping back for a moment, tell about Mapbox for a second is what, what Mapbox can do is provide the most accurate digital representation of the physical world. Think about the Mapbox technology, delivering the most accurate digital twin of mother earth, right? That's what we do. And the way that we do that is to consume, as I said earlier, vast amounts of data, we've got powerful AI that structures that data, and then really robust and scalable infrastructure that underpins all of that. Now the benefit of working with a company like AWS is that they take care of that third point. Yeah. Which means we get to go focus on the first two, which is how we differentiate and build our >>Business. And that's exactly the model of how you win in the cloud. In my opinion, that's the go big piece, the go and there's tools that fit in white spaces. But that's the, I think that's the right formula. Let's get back to Mac boxer. I know you've got news. You got the, the, uh, Mapbox fleet SDK. You announced, I wanna hold on that we'll get to in a second, let's get back to what you got are providing that example as you have this new operating environment of how delivery and, and supply chain and that's example, I want to know how tech your technology is making all that work. Because I was just talking to someone last night about this web van was web 1.0 and crash never was successful. Instacart is kind of hurting. So maybe they're optimized. You could save them. I mean, cuz the economics gotta work. If you don't have the underlying system built, that might fail. So there'll be probably the third version that gets it. Right. Maybe at Mapbox again, I'm speculating, but I'll let you talk. Yeah. How does Mapbox solve the, that problem? >>You know, it's interesting if you come back to that, that, that analogy we're using with AWS and how do you use AWS to win in the cloud? It's the same story for Mapbox of how do you win in the location industry? And what we do is provide those same tool sets of APIs and SDKs, the thing go power, those logistics companies like an Instacart, who's a great customer of ours to run in their logistics business on top of it again, it's all about how do you provide technology that allows your customers yeah. To focus on what matters from a differentiation perspective as they focus on building their >>Business and you think your economics is gonna enable these people to be successful >>100%. That's >>The goal >>100%. >>All right. So another thing that I wanna bring up is the fleet SDK, what was the, that you announced they can, you just quickly share the news on what this >>Is? Yeah, yeah, absolutely. I appreciate that, John. Yeah. So today on the Eve of earth day, we're very excited to announce Mapbox fleet going into, uh, our beta launch and what Mapbox fleet is, is, uh, a set of tools and application that allows our customers to more efficiently route their vehicles, which means lowering their fuel consumption. And at the same time, more efficiently dispatching those vehicles, which means that you can get more done with fewer assets, essentially. How do you get more packages onto a single vehicle to get those to the customers? Now you may be watching the news and understanding, yeah, there's a tremendous explosion of delivery going. Yeah. And that's fantastic. Right? That's great business for our logistics customers. Good business for us too. What's happening though, is that as those volumes are ballooning, everybody's all of a sudden, really looking at their cost structures and trying to understand how do I manage this? >>Right. I have efficiency targets as a business. Maybe I've been really focused on customer acquisition. Now it's time to flip the model and really understand in the economics of profitable growth. We help with that, with that focus on efficiency, but the double edged sword with growth and, and you know, running a logistics business is that you actually have a tremendous amount of carbon emissions that are associated with that. Yeah. For a car to show up or a truck to show up, to deliver something to your house, their emissions associated with that. So what we find is that we're able to not only drive dollar savings for our customers, but also as part of that, with the efficiency angle, really help to drive down the overall carbon impact in the carbon footprint of what they do. And >>How do you do that? >>Well, it's the efficiency lens, right? So if somebody is driving 20%, fewer miles, they're going to emit 20% fewer. Okay. >>Gotcha. So it's a numbers game across the board with actual measurement. That's exactly right. Built in and say optimization paths, all kinds of navigation. >>That's exactly right. So embedded within Mapbox fleet application are those optimization algorithm. >>So you got a platform that's setting up for the next level delivery system slash new way to connect people to goods and services and other things getting from point a to point B, you got the sustainability check you're in the cloud, born in the cloud cloud scale. I gotta a, I can't go without asking if you're on Amazon, you do all this cool stuff. There's gotta be a machine learning an AI angle. So what is that? Yeah, absolutely. >>Absolutely. AB yeah. You know, <laugh> guilty as charged. >>I would say >>John. Uh, so look, I >>Think, I mean AI and, and sustainability are gonna be, I think filings in my, in the future we be talking about on the cube, if you're not an AI company or, and doing force for good stuff, I think there's gonna be mandatory requirements on those. >>I couldn't three more. I think the ESG agenda is an incredibly important one. One that's core to Mapbox has been since the founding of the company back in 2013. Uh, but if you look at how does AI and ML fit into Mapbox, it does that in a number of different ways. And really when we come back to this idea of Mapbox creating a digital twin of the earth, the way that we do that, it is through ingesting a tremendous amount of sensor data. Right? You can imagine, uh, Mapbox customers on any given week drive, billions of miles, we're capturing all of that telemetry data to understand and make sense of what does that mean for, for, for the world that allows us to push in any given day 700,000 updates to our underly, your location technology stack, and at the same time provide insights as to exactly what's happening. Are there roadside incidents? Are there, are there issues with traffic? So by collecting all of that data, we run incredibly powerful AI models on top of it that allow us to create the, the real world representation of what's happening. That's exactly how >>It works. What, what, as they say in the, um, big data AI world is you guys have a tremendous observation space. You're looking at a lot of surface area data that's exactly right. Across multiple workloads and apps. That's >>Exactly >>Right. You can connect those dots with the right AI. >>That's exactly right. That's exactly right. And I think I, you know, coming back to your point around sustainability, I do think that the AI and ML capabilities that are being delivered are going to be paramount to that. It being such a fundamental aspect to what am, to what Mapbox does as a business allows us to launch these game changing solutions like Mapbox fleet and staying on that, that kind of environmental and sustainable kick for a second. Just last week, we launched our, our EV routing API that powers the next generation of EVs. So AI ML sustainability. If it's not core business today, it's gotta very quickly become core. >>It's really interesting. I really think what we're teasing out here and it's fun to talk about it now because we'll look back at it later 10 years or more and say, wow, this is completely refactored the industry and lives and the planet ultimately. Right. So this is a, a kind of got force for good built into the system natively. That's >>Right. That's >>That's interesting, Garrett, thanks so much for sharing the story. Give you the last word, share with the audience, what you guys are up to, what you're promoting, what you're looking for. Are you hiring, uh, is there a call to action? You wanna share? Give the plug for the company? Yeah, >>Absolutely hiring like crazy come join Mapbox and BU build the future of geolocation and intelligent location services with us. Uh, the, thanks so much for the time, >>John. Thanks for coming on cube coverage here in San Francisco, California Mosconi center back at live events. I'm John for host cube stayed with us as day two wraps down. Remember New York city. This summer will be there as well. Cube coverage of more cloud coverage events are back. Thanks for watching.

(upbeat music) >> Welcome back to Las Vegas everybody. You're watching theCUBE coverage of AWS reinvent 2021. I tell you this place is packed. It's quite amazing here, over 20,000 people, I'd say it's closer to 25, maybe 27,000, and it's whole overflow, lots going on in the evenings. It's quite remarkable and we're really happy to be part of this. Jay Turner is here, he's the Vice President of Development and Operations, at PCCW Global. He's joined by Garrett Lowell, Vice President of Ecosystem Partnerships for the Americas at PCCW Global. Guys, welcome to theCUBE. Thanks for coming on. >> Thank you. >> Thank you so much. Jay, maybe you could take us through, for those people who aren't familiar with your company, what do you guys do, what are you all about? >> PCCW Global is the international operating wing of Hong Kong telecom. If it's outside of Hong Kong, it's our network. We've got about 695,000 kilometers of diverse cable, we've got about 43, 44 terabit of capacity came into business in 2005, if my brain is serving me correctly right now. We have a very diverse and vast portfolio ranging all the way from satellite teleports, all the way to IP transit. We're a Tier 1 service provider from that perspective as well. We do one of everything when it comes to networking and that's really, what was the basis of Console Connect, was inventing a platform to really enable our users to capitalize on our network and our assets. >> Okay. 2005, obviously you predated Cloud, you laid a bunch of fibers struck it in the ocean, I mean, global networks. There was a big trend to do that you had to think, you had to go bigger, go home in that business, (laughing) all right. Console Connect is your platform, is that right? >> Jay: Yes. >> So explain- >> Yeah, sorry, Console Connect is a software defined interconnection platform. We built a user self-service portal. Users can allocate ports, they get the LOAs issued to them directly from the platform. And then once they've got an active port or they've come in via one of our partnerships, they can then provision connectivity across our platform. That may be extending to their data centers or extending to their branch office, or it could be building a circuit into the Cloud via direct connect, could be building a circuit into an internet exchange. All of those circuits are going to be across that 685,000 kilometers of diverse fiber rather than going across the public internet. >> When you started, it took some time obviously to build out that infrastructure and then the Cloud came into play, but it was still early days, but it sounds like you're taking the AWS Cloud model and applying that to your business, eliminate all that undifferentiated heavy lifting, if you will, like the visioning in management. >> Yeah, we've heard many people, and that's kind of the impetus of this was, I want to be directly connected to my end point. And how do I do that? AWS, yes, they had direct connect, but figuring out how to do that as an enterprise was challenging. So we said, hey, we'll automate that for you. Just tell us what region you want to connect to. And we'll do all the heavy lifting and we'll just hand you back a villain tag. You're good to go. So it's a classic case, okay. AWS has direct connect. People will go, oh, that's directly competitive, but it's now you're adding value on top of that. Right? >> Yeah. >> Describe where you fit, Garrett, inside of the AWS ecosystem. You look around this hall and it's just a huge growing ecosystem, where you fit inside of that ecosystem and then your ecosystem. What's that like? >> Where we fit into the AWS ecosystem, as Jay alluded to, we're adding value to our partners and customers where they can come in, not only are they able to access the AWS platform as well as other Cloud platforms, but they're also able to access each other. We have a marketplace in our platform, which allows our customers and partners to put a description of their services on the marketplace and advertise their capabilities out to the rest of the ecosystem of PCCW Global and Console Connect. >> And you're doing that inside of AWS, is that right or at least in part? >> No, that's not inside of AWS. >> So your platform is your platform. >> Yes. >> Your relationship with AWS is to superpower direct connect. Is that right or? >> So we're directly connected to AWS throughout the globe. And this allows our customers and partners to be able to utilize not only the PCCW global network, but also to expand that capability to the AWS platform in Cloud. >> So wherever there's a Cloud, you plug into it, okay? >> Garrett: That's correct. >> Jay: Yeah. And then another advantage, the customer, obviously doesn't have to be directly co-located with AWS. They don't have to be in the same geographical region. If for some reason you need to be connected to U.S. west, but you're in Frankfurt, fine, we'll back all the traffic for you. >> Dave: Does that happen a lot? >> It actually does. >> How come? What's the use case there. >> Global diversity is certainly one of them just being able to have multiple footprints. But the other thing that we're seeing more of late is these Cloud-based companies are beginning to be attracted to where their customers are located. So they'll start seeing these packets of views and they'll go, well, we're going to go into that region as well, stand up a VPC there. We want our customers then being able to directly connect to that asset that's closest to them. And then still be able to back call that traffic if necessary or take it wherever. >> What's the big macro trends in your business? Broadly you see cost per bit coming down, you see data consumption and usage going through the roof. How does that affect you? What are some of the big trends that you see? >> I think one of the biggest ones and one that we targeted with Console Connect, we were hearing a lot of customers going, the world's changing so dynamically. We don't know how to do a one-year forecast of bandwidth, much less a three-year, which is what a lot of contracts are asking us for. So we said, hey, how about one day? Can you do one day? (Dave laughs) Because that's what our granularity is. We allow for anything from one day up to three years right now, and then even within that term, we're dynamic. If something happens, if suddenly some product goes through the roof and you've suddenly got a spike in traffic, if a ship drags its anchor through a sub sea cable, and suddenly you're having to pivot, you just come into the platform, you click a couple of buttons, 20 seconds later, we've modified your bandwidth for you or we've provisioned a new circuit for you, we've got your backup going, whatever. Really at the end of the day, it's the customer paying for their network, so the customer should be the one making those decisions. >> How's that affect pricing? I presume or so, I can have one day to a three-year term, for example if I commit to three years, I get a better deal. Is that right, or? >> You do, but at the end of the day, it's actually pretty much a moderate, a better deal. We don't want to force the hand of the customer. If you signed a 12 month contract with us, we're going to give you a 3% discount. >> So it's not really, that's not a motivation to do it. It's just (indistinct) reduce the transaction complexity. And that's why you will sign up for a longer term not to get the big discount. >> Correct. And then, like I said, even within a longer contract, we're still going to allow you to flex and flow and modify if you need to, because it's your network. >> What kind of constraints do you put on that? Do I have to commit to a flow? And then everything above that is, I can flex up. Is that how it works? >> Yeah. >> Okay. And then, the more I commit to, the better the deal is, or not necessarily? >> No, it's pretty much flat rate. >> Okay, I'm going to commit and I'm going to say, all right, I know I'm going to use X, or sign up for that and anything over it, you're pretty flexible, I might get a few points if I sign up for more, somebody might want to optimize that if they're big enough. >> And another really neat advantage, the other complaint we heard from customers, they go, I need three different direct connect, I need to be connected to three different parties, but I don't want to run three different cross-connects and I don't want to have three different ports. That's just an expense and I don't want. And we, fine, take your one gig port run one gig of services on it. If that's 20 different services, we're fine. We allow you to multiplex your port and provision as- >> So awesome. I love that model. I know some software companies who I would recommend to take a look at that pricing model. So Garrett, how do you segment the ecosystem? How do you look at that? Maybe you could draw and paint a picture of the idea of partners and what they look like. I know there's not just one category, but, >> Sure. Our ideal partners are internet exchangers, Cloud partners and SAS providers, because a big piece of our business is migration to the Cloud, and the flexibility of our platform allows and encourages our SAS providers and SI partners to perform migration to the Cloud much easier in a flexible format for their customers. >> What can you tell us, any kind of metrics you can give us around your business to give a sense of the scope, the scale? >> Well, of our business, (Dave laughs) one of the driving factors here, Gardner says that about 2023, I think, 40% of the enterprise workloads will be deployed in the Cloud, which is all fine and dandy, except in my head, you're just trading one set of complexities for another. Instead of having everything in a glass house and being able to understand that, now you're going, it's in the Cloud, now I need to manage my connectivity there. wait a minute, are my security policies still the same? Do they apply if I'm going across the public internet? What exposure have I just bought into myself to try to run this? The platform really aims at normalizing that as much as possible. If you're directly connected to AWS, at the end of the day, that's a really long ethernet cable. So your a glass house just got a lot bigger, but you're still able to maintain and use the exact same policies and procedures that you've been using. That's really one of our guiding principles, is to reduce that complexity and make it very simple for the user. >> I understand that, cause in the early days of Cloud, a lot of enterprises, the CIOs, they were concerned about security, then I think they realized, ah, AWS has pretty good security. CIA is using it. But still people would say to me, it's not that it's best security, it's just different. You know, we move slow, Dave. How do you accommodate, there's that diversity, I mean, AWS is obviously matured, but are you suggesting that you can take my security edicts in my glass house and bring those into your networks and ultimately into the Cloud? Is that how it works? >> That's the goal. It's not going to be a panacea more than likely, but the more edicts that we can allow you to bring across and not have to go back and revamp and, the better for you as a customer and the better really for us, because it normalizes things, it makes it much easier for us to accommodate more and more users. >> And is it such now in the eco, is all the diversity in the ecosystem, is it such that there's enough common patterns you guys can accommodate most of those use cases? >> Yeah, absolutely. One of the key components is the fact that the platform runs on our MPLS network, which is inherently secure. It's not on the public internet anywhere. We do have internet on demand capability. So in the event that a customer wants access to the internet, no problem. We can accommodate this. And we also have 5G capability built into the platform to allow flexibility of location and flexibility of, I would say, standing up new customer locations. And then the other component of the security is the fact that the customers can bring their own security and apply anywhere. We're not blocking, we don't have any port filters or anything of this nature. >> If would think 5G actually, I could see people arguing both sides, but my sense is 5G is going to be a huge driver for your business cause it's going to just create so much more demand for your services, I think. I can see somebody arguing the counter about it. What's your point of view on that? >> No, I think that's a fair assessment. I think it's going to drive business for everyone here on the show floor and it's pushing those workloads more toward the edge, which is not an area that people were typically concerned with. The edge was just the door that they walked through. That's becoming much different now. We're also going to start seeing, and we're already seeing it, huge trends of moving that data at the edge rather than bringing it all the way back to a central warehouse and help ending it. The ability to have a dynamic platform where you can see exactly what your network's doing and in the push of a button, modify that, or provision new connectivity in response to how your business is performing. >> Yeah, ultimately it's all about the applications that are going to be driving demand for more data. That's just a tailwind for you guys. >> Yeah. You look at, some of the car companies are coming on, Tesla, you're drive around with like eight CPUs and I think communicating back over the air. >> Dave: Yeah, right. >> You start scaling that and you start getting into some some real bottlenecks. >> Amazing business you guys having obviously capital intensive, but once you get in there, you got a big moat. That is a matter of getting on a flywheel and innovating. Guys, congratulations on all the progress and so much for coming on theCUBE. >> Thanks for the time. >> Thank you very much. >> Great to meet you guys. Good luck. All right, thank you for watching. This is Dave Vellante for theCUBE, the leader in High-Tech Coverage. We'll be right back. (upbeat music)

(upbeat music) >> Welcome back to Las Vegas everybody. You are watching theCube's coverage of AWS reinvent 2021. I'll tell you this place is packed. It's quite amazing here over 20,000 people, I'd say it's closer to 25, maybe 27,000. And there's a little overflow, lots going on in the evenings. It's quite remarkable. And we're really happy to be part of this. Jay Turner is here, he's the vice president of development and ops at PCCW Global. He's joined by Garrett Lowell, vice-president of ecosystem partnerships for the Americas at PCCW Global. Guys, welcome to theCube. Thanks for coming on. >> Thank you so much. >> So, Jay, maybe you could take us through for those people who aren't familiar with your company, what do you guys do? What do you all about? >> Yes, so PCCW Global is the international operating wing of Hong Kong Telecom. So if it's outside of Hong Kong, it's our network. We've got about 695,000 kilometers of diverse cable. We've got about 43, 44 terabit of capacity. Came into business in 2005 if my brain is serving me correctly right now. So we have a very diverse and vast portfolio ranging all the way from satellite teleports, all the way to IP transit. We're a tier one service provider from that perspective as well. So we do one of everything when it comes to networking and that's really what was the basis of Console Connect, was inventing a platform to really enable our users to capitalize on that our network and our assets. >> Okay, so 2005, obviously you predated cloud, you laid a bunch of fibers, it's getting in the ocean, I mean, global networks, I mean, there was a big trend to do that and you had to think, you had to go bigger or go home and that business. >> Jay: Yes you had to do. >> So and Console Connect is your platform, is that right? So explain. >> Yeah, sorry. Yeah, Console Connect is our software defined interconnection platform. So we built a user self-service portal. Users can allocate ports, they get the LOAs issue to them directly from the platform. And then once they've got an active port or they've come in via one of our partnerships, they can then provision connectivity across our platform. And that may be extending to their data centers or extending or their branch office, or it could be building a circuit into the cloud via direct connect, could be building a circuit into an internet exchange. And all of those circuits are going to be across that 685,000 kilometers of diverse fiber rather than going across the public internet. >> So, when you started, it took some time obviously to build out that infrastructure and then the cloud came into play, but it was still early days, but it sounds like you're taking the cloud model, AWS Cloud model and applying that to your business, eliminate all that undifferentiated, heavy lifting, if you will, the visioning and management. >> Yeah, we've heard many people and that's kind of the impetus of this was, I want to be directly connected to my end point. And how do I do that? And AWS, yes, they had direct connect, but figuring out how to do that as an enterprise was challenging. So we said, hey, we'll automate that for you. Just tell us what region you want to connect to. And we'll do all the heavy lifting, and we'll just hand you back a villain tag. You're good to go. >> So it's a classic case of, okay, AWS has direct connect, people they go, "Ah, that's directly competitive, but it's not, you're adding value on top of that." Right. So describe where you fit Garrett inside of the AWS ecosystem. You look around this hall and it's just a huge growing ecosystem, where you fit inside of that ecosystem and then your ecosystem, what's that like? >> Okay, so where we fit into the AWS ecosystem, as Jay alluded to, we're adding value to our partners and customers where they can come in, not only are they able to access the AWS platform as well as other cloud platforms, but they're also able to access each other. So we have a marketplace in our platform, which allows our customers and partners to put a description of their services on the marketplace and advertise their capabilities out to the rest of the ecosystem of PCCW Global and Console Connect. >> Okay, so and you're doing that inside of AWS? I that right? Or at least in part? >> No, that's not inside of AWS. >> Okay, so your platform is your platform. >> Yes. >> And then, so your relationship with AWS is to sort of superpower direct connect, is that right or? >> So we're directly connected to AWS throughout the globe. And this allows our customers and partners to be able to utilize not only the PCCW Global network, but also to expand that capability to the AWS platform in clouds. >> Wherever there's a cloud you plug into it? Okay. >> That's correct. >> And then another advantage there is the customer, obviously doesn't have to be directly co-located with AWS. They don't have to be in the same geographic region. If for some reason you need to be connected to US West, but you're in Frankfurt, fine, we'll back all the traffic for you. >> Does that happen a lot? >> It actually does. >> How come? Why, what's the use case there? >> Global diversity is certainly one of them, just being able to have multiple footprints. But the other thing that we're seeing more of late is these cloud-based companies are beginning to kind of be attracted to where their customers are located. So they'll start seeing these pockets of use and they'll go, well, okay, we're going to go into that region as well, stand up a VPC there. And so then we want to our customers then being able to directly connect to that asset, that's closest to them. And then still be able to back call that traffic if necessary or take it wherever. >> What are the big, sort of macro trends in your business? I mean, broadly you see cost per bit coming down, you see data consumption and usage going through the roof. How does that affect you? What are some of the big trends that you see? >> I think one of the biggest ones and one that we targeted with Console Connect, we were hearing a lot of customers going, the world's changing so dynamically. We don't know how to do a one-year forecast of bandwidth, much less a three-year, which is what a lot of contracts are asking us for. So we said, hey, how about one day? Can you do one day? (Dave laughing) Because that's what our granularity is. So we allow for anything from one day up to three years right now, and then even within that term, we're dynamic. So if something happens, suddenly some product goes through the roof and you've suddenly got a spike in traffic. If a ship drags its anchor through a sub sea cable, and suddenly you're having to pivot, you just come into the platform, you click a couple of buttons, 20 seconds later, we've modified your bandwidth for you, or we've provisioned a new circuit for you. We've got your backup going whatever. Really at the end of the day, it's the customer paying for their network, so the customer should be the one making those decisions. >> How's that affect pricing? I presume, so I can have one date or a three-year term. Presume if I commit to three years, I get a better deal, is that right or? >> You do, but I mean, at the end of the day, it's actually pretty much a moderate, a better deal. We don't want to force the hand of the customer. So yeah, if you signed a 12 month contract with us, we're going to give you a 3% discount. >> Yeah, so it's not really, that's not a motivation to do it. Is just you want to reduce the transaction complexity. And that's why you would sign up for a longer term not to get the big discount. >> Correct. And then, like I said, even within a longer contract, we're still going to allow you to flex and flow and modify if you need to because it's your network. >> What kind of constraints do you put on that? Do I have to commit to a floor and then everything above that is I can flex up? Is that how it works? Okay. And then the more I commit to the better the deal is, or not necessarily? >> No, it's pretty much flat, right. >> So, okay. So I'm going to come in and I'm going to say, all right, I know I'm going to use X, I'll sign up for that and anything over it. You're pretty flexible, I might get a few points if I sign up for more, somebody might want to optimize that if they're big enough. >> And another really neat advantage, and the other complaint we heard from customers, they go, I need three different direct connect, or I need to be connected to three different parties, but I don't want to run three different cross-connects and I don't want to have three different ports. That's just an expense I don't want. And we say, fine, take your one gig port, run one gig of services on it, if that's 20 different services, we're fine. So we allow you to multiplex your port and provision- >> It's awesome. I love that model. I know some software companies who I would recommend take a look at that pricing model. So, Garrett, how do you segment the ecosystem? How do you look at that way? Maybe you could draw paint a picture sort of the, the ideal partners and what they look like. I know there's not just one category, but. >> Sure, so our ideal partners are internet exchanges, cloud partners, and SAS providers, because a big piece of our business is migration to the cloud. And the flexibility of our platform allows and encourages our SAS providers and SI partners to perform migration to the cloud much easier and flexible in a flexible format for their customers. >> Yeah, so what can you tell us, any kind of metrics you can give us around your business to give a sense of the the scope, the scale. >> Well, of our business, kind of one of the driving factors here, Gardner says that about 2023, I think 40% of the enterprise workloads will be deployed in the cloud, which is all fine and dandy, except in my head, you're just trading one set of complexities for another. So now, instead of having everything in a glass house and being able to kind of understand that now you're going, well, okay, so it's in the cloud now I need to manage my connectivity there. And, oh, well, wait a minute, are my security policies still the same? Do they apply if I'm going across the public internet? What exposure have I just, bought into myself to try to run this? So the platform really aims at normalizing that as much as possible. If you're directly connected to AWS, at the end of the day, that's a really long ethernet cable. So you're a glass house just got a lot bigger, but you're still able to maintain and use the exact same policies and procedures that you've been using. So that's really one of our guiding principles is to reduce that complexity and make it very simple for the user. >> Well, I don't understand, 'cause in the early days of cloud, a lot of enterprises, CIO they were concerned about security. And I think they realized that AWS has pretty good security, well, CIA is using it. But still people would say to me, it's not that it's bad security, it's just different. We move slow, Dave. So how do you accommodate, now I don't know, does that diversity, I mean, AWS has obviously matured, but are you suggesting that you can take my security edicts in my glass house and bring those into your networks and ultimately into the cloud? Is that kind of how it works? >> That's the goal. It's not going to be a panacea more than likely, but the more edicts that we can allow you to bring across and not have to go back and revamp and the better for you as a customer and the better really for us, because it normalizes things, it makes it much easier for us to accommodate more and more users. >> It is such now in the eco, it was all the diversity in the ecosystem. Is it such that there's enough common patterns that you you guys can kind of accommodate most of those use cases? >> Yeah, absolutely. I think the, one of the key components is the fact that the platform runs on our MPLS network, which is inherently secure. It's not on the public internet anywhere. Now we do have internet on demand capability. So in the event that a customer wants access to the internet, no problem, we can accommodate this. And we also have 5G capability built into the platform to allow flexibility of location and flexibility of... I would say, standing up new customer locations. And then the other component of the security is the fact that the customers can bring their own security and apply anywhere. So we're not blocking, we don't have any port filters or anything of this nature. >> Well, I would think 5G actually, I mean, I could see people arguing both sides, but my sense is 5G is going to be a huge driver for your business, 'cause it's going to just create so much more demand for your services I think, I could see somebody arguing the counter, but what's your point of view on that? >> No. I think that's a fair assessment. I think it's going to drive business for everyone here on the show floor. And it's pushing those workloads more toward the edge, which is not an area that people were typically concerned with. The edge was just the door that they walked through. That's becoming much different now. And we're also going to start seeing, and we're already seeing it, huge trends of moving that data at the edge, rather than bringing it all the way back to a central warehouse in Hare pending it. So, again, the ability to have a dynamic platform where you can see exactly what your network's doing and in the push of a button, modify that, or provision new connectivity in response to how your business is performing. >> Yeah, and ultimately it's all about the applications that are going to be driving demand for more data. And that's just a tailwind for you guys. >> Yeah, yeah and then you look at some of the car companies are coming on, you know, Tesla, you're driving around with like eight CPU's in that thing, communicating back over the air. >> Dave: Yeah right. >> You start scaling that, and you start getting into some real bottleneck. >> Amazing business you guys having, obviously capital intensive, but once you get in there, you've got a big moat, and then it's a matter of getting on a flywheel and innovating. Guys, congratulations on all the progress and thanks so much for coming on theCube. >> Yeah. No, thanks for the time. >> Thank you very much. >> Yeah, great to meet you guys. Good luck. All right. Thank you for watching. This is Dave Vellante for theCube, the leader in high-tech coverage, right back. (upbeat music)

>>From around the globe presenting the convergence of file and object brought to you by pure storage. Okay. >>We're back with the convergence of file and object and a power panel. This is a special content program made possible by pure storage. And co-created with the cube. Now in this series, what we're doing is we're exploring the coming together of file and object storage, trying to understand the trends that are driving this convergence, the architectural considerations that users should be aware of and which use cases make the most sense for so-called unified fast file in object storage. And with me are three great guests to unpack these issues. Garrett bell center is the data center solutions architect he's with CDW. Scott Sinclair is a senior analyst at enterprise strategy group. He's got deep experience on enterprise storage and brings that independent analyst perspective. And Matt Burr is back with us, gentlemen, welcome to the program. >>Thank you. >>Hey Scott, let me, let me start with you, uh, and get your perspective on what's going on in the market with, with object to cloud huge amount of unstructured data out there. It lives in files. Give us your independent view of the trends that you're seeing out there. >>Well, Dave, you know where to start, I mean, surprise, surprise data's growing. Um, but one of the big things that we've seen is that we've been talking about data growth for what decades now, but what's really fascinating is or changed is because of the digital economy, digital business, digital transformation, whatever you call it. Now, people are not just storing data. They actually have to use it. And so we see this in trends like analytics and artificial intelligence. And what that does is it's just increasing the demand for not only consolidation of massive amounts of storage that we've seen for awhile, but also the demand for incredibly low latency access to that storage. And I think that's one of the things that we're seeing, that's driving this need for convergence, as you put it of having multiple protocols can Solidated onto one platform, but also the need for high performance access to that data. >>Thank you for that. A great setup. I got, like I wrote down three topics that we're going to unpack as a result of that. So Garrett, let me, let me go to you. Maybe you can give us the perspective of what you see with customers is, is this, is this like a push where customers are saying, Hey, listen, I need to converge my file and object. Or is it more a story where they're saying, Garrett, I have this problem. And then you see unified file and object as a solution. >>Yeah, I think, I think for us, it's, you know, taking that consultative approach with our customers and really kind of hearing pain around some of the pipelines, the way that they're going to market with data today and kind of what are the problems that they're seeing. We're also seeing a lot of the change driven by the software vendors as well. So really being able to support a dis-aggregated design where you're not having to upgrade and maintain everything as a single block has been a place where we've seen a lot of customers pivot to where they have more flexibility as they need to maintain larger volumes of data and higher performance data, having the ability to do that separate from compute and cash. And some of those other layers are, is really critical. >>So, Matt, I wonder if you could follow up on that. So, so Gary was talking about this dis-aggregated design, so I like it, you know, distributed cloud, et cetera, but then we're talking about bringing things together in one place, right? So square that circle. How does this fit in with this hyper distributed cloud edge that's getting built out? >>Yeah. You know, I mean, I could give you the easy answer on that, but I can also pass it back to Garrett in the sense that, you know, Garrett, maybe it's important to talk about, um, elastic and Splunk and some of the things that you're seeing in, in that world and, and how that, I think the answer today, the question I think you can give, you can give a pretty qualified answer relative to what your customers are seeing. >>Oh, that'd be great, please. >>Yeah, absolutely. No, no problem at all. So, you know, I think with, um, Splunk kind of moving from its traditional design and classic design, whatever you want to, you want to call it up into smart store? Um, that was kind of one of the first that we saw kind of make that move towards kind of separating object out. And I think, you know, a lot of that comes from their own move to the cloud and updating their code to basically take advantage of object object in the cloud. Um, but we're starting to see, you know, with like Vertica Ian, for example, um, elastic other folks taking that same type of approach where in the past we were building out many to use servers. We were jamming them full of, uh, you know, SSDs and then DME drives. Um, that was great, but it doesn't really scale. >>And it kind of gets into that same problem that we see with hyperconvergence a little bit where it's, you know, you're all, you're always adding something maybe that you didn't want to add. Um, so I think it, you know, again, being driven by software is really kind of where we're seeing the world open up there. Um, but that whole idea of just having that as a hub and a central place where you can then leverage that out to other applications, whether that's out to the edge for machine learning or AI applications to take advantage of it. I think that's where that convergence really comes back in. Um, but I think like Scott mentioned earlier, it's really folks are now doing things with the data where before I think they were really storing and trying to figure out what are we going to actually do with it when we need to do something with it? So this is making it possible. >>Yeah. And Dave, if I could just sort of tack onto the end of the Garrett's answer there, you know, in particular verdict with beyond mode, the ability to leverage sharted sub clusters, give you, um, you know, sort of an advantage in terms of being able to isolate performance, hotspots you an advantage to that as being able to do that on a flash blade, for example. So, um, sharted, sub clusters allow you to sort of say, I am, you know, I am going to give prioritization to, you know, this particular element of my application in my dataset, but I can still share those, share that data across those, across those sub clusters. So, um, you know, as you see, you know, Vertica with the non-motor, >>You see Splunk advanced with, with smart store, um, you know, these are all sort of advancements that are, you know, it's a chicken and the egg thing. Um, they need faster storage, they need, you know, sort of a consolidated data storage data set. Um, and, and that's what sort of allows these things to drive forward. Yes, >>The verdict eon mode, there was a no, no, it's the ability to separate compute and storage and scale independently. I think, I think Vertica, if they're, if they're not the only one, they're one of the only ones I think they might even be the only one that does that in the cloud and on prem and that sort of plays into this distributed nature of this hyper distributed cloud. I sometimes call it and I'm interested in the, in the data pipeline. And I wonder Scott, if we can talk a little bit about that maybe where unified object and file fund. I mean, I'm envisioning this, this distributed mesh and then, you know, UFO is sort of a note on that, that I can tap when I need it. But, but Scott, what are you seeing as the state of infrastructure as it relates to the data pipeline and the trends there? >>Yeah, absolutely. Dave, so w when I think data pipeline, I immediately gravitate to analytics or, or machine learning initiatives. Right. And so one of the big things we see, and this is, it's an interesting trend. It seems, you know, we continue to see increased investment in AI, increase interest and people think, and as companies get started, they think, okay, well, what does that mean? Well, I gotta go hire a data scientist. Okay. Well that data scientist probably needs some infrastructure. And what they end, what often happens in these environments is where it ends up being a bespoke environment or a one-off environment. And then over time organizations run into challenges. And one of the big challenges is the data science team or people whose jobs are outside of it, spend way too much time trying to get the infrastructure, um, to, to keep up with their demands and predominantly around data performance. So one of the, one of the ways organizations that especially have artificial intelligence workloads in production, and we found this in our research have started mitigating that is by deploying flash all across the data pipe. We have. Yeah, >>We have data on this. Sorry to interrupt, but Pat, if you could bring up that, that chart, that would be great. Um, so take us through this, uh, Scott and, and share with us what we're looking at here. >>Yeah, absolutely. So, so Dave, I'm glad you brought this up. So we did this study. Um, I want to say late last year, uh, one of the things we looked at was across artificial intelligence environments. Now, one thing that you're not seeing on this slide is we went through and we asked all around the data pipeline and we saw flash everywhere. But I thought this was really telling because this is around data lakes. And when many people think about the idea of a data Lake, they think about it as a repository. It's a place where you keep maybe cold data. And what we see here is especially within production environments, a pervasive use of flash stores. So I think that 69% of organizations are saying their data Lake is mostly flash or all flash. And I think we had 0% that don't have any flash in that environment. So organizations are out that thing that flashes in essential technology to allow them to harness the value of their data. >>So Garrett, and then Matt, I wonder if you could chime in as well. We talk about digital transformation and I, I sometimes call it, you know, the COVID forced March to digital transformation. And, and I'm curious as to your perspective on things like machine learning and the adoption, um, and Scott, you may have a perspective on this as well. You know, we had to pivot, he had to get laptops. We had to secure the end points, you know, VDI, those became super high priorities. What happened to, you know, injecting AI into my applications and, and machine learning. Did that go in the back burner? Was that accelerated along with the need to digitally transform, uh, Garrett, I wonder if you could share with us what you saw with, with customers last year? >>Yeah. I mean, I think we definitely saw an acceleration. Um, I think folks are in, in my market are, are still kind of figuring out how they inject that into more of a widely distributed business use case. Um, but again, this data hub and allowing folks to now take advantage of this data that they've had in these data lakes for a long time. I agree with Scott. I mean, many of the data lakes that we have were somewhat flashing, accelerated, but they were typically really made up of large capacity, uh, slower spinning nearline drives, um, accelerated with some flash, but I'm really starting to see folks now look at some of those older Hadoop implementations and really leveraging new ways to look at how they consume data. And many of those redesigned customers are coming to us, wanting to look at all flash solutions. So we're definitely seeing it. And we're seeing an acceleration towards folks trying to figure out how to actually use it in more of a business sense now, or before I feel it goes a little bit more skunkworks kind of people dealing with, uh, you know, in a much smaller situation, maybe in the executive offices trying to do some testing and things. >>Scott you're nodding away. Anything you can add in here. >>Yeah. So, well, first off, it's great to get that confirmation that the stuff we're seeing in our research, Garrett seeing, you know, out in the field and in the real world, um, but you know, as it relates to really the past year, it's been really fascinating. So one of the things we, we studied at ESG is it buying intentions. What are things, what are initiatives that companies plan to invest in? And at the beginning of 2020, we saw heavy interest in machine learning initiatives. Then you transition to the middle of 2020 in the midst of COVID. Uh, some organizations continued on that path, but a lot of them had the pivot, right? How do we get laptops, everyone? How do we continue business in this new world? Well, now as we enter into 2021, and hopefully we're coming out of this, uh, you know, the, the pandemic era, um, we're getting into a world where organizations are pivoting back towards these strategic investments around how do I maximize the usage of data and actually accelerating those because they've seen the importance of, of digital business initiatives over the past >>Year. >>Yeah, Matt, I mean, when we exited 2019, we saw a narrowing of experimentation in our premise was, you know, that that organizations are going to start now operationalizing all their digital transformation experiments. And, and then we had a 10 month Petri dish on, on digital. So what are you, what are you seeing in this regard? >>It's 10 months, Petri dish is an interesting way to interesting way to describe it. Um, you know, we, we saw another, there's another, there's another candidate for pivot in there around ransomware as well. Right. Um, you know, security entered into the mix, uh, which took people's attention away from some of this as well. I mean, look, I I'd like to bring this up just a level or two, um, because what we're actually talking about here is progress, right? And, and progress is an, is an inevitability. Um, you know, whether it's whether, whether you believe that it's by 20, 25 or you, or you think it's 20, 35 or 2050, it doesn't matter. We're on a forced March to the eradication of desk. And that is happening in many ways. Uh, you know, in many ways, um, due to some of the things that Garrett was referring to and what Scott was referring to in terms of what our customer's demands for, how they're going to actually leverage the data that they have. >>And that brings me to kind of my final point on this, which is we see customers in three phases. There's the first phase where they say, Hey, I have this large data store, and I know there's value in there. I don't know how to get to it. Or I have this large data store and I've started a project to get value out of it. And we failed. Those could be customers that, um, you know, marched down the dupe, the Hadoop path early on. And they, they, they got some value out of it. Um, but they realized that, you know, HDFS, wasn't going to be a modern protocol going forward for any number of reasons. You know, the first being, Hey, if I have gold dot master, how do I know that I have gold dot four is consistent with my gold dot master? So data consistency matters. >>And then you have the sort of third group that says, I have these large datasets. I know how to extract value from them. And I'm already on to the Vertica is the elastics, you know, the Splunks et cetera. Um, I think those folks are the folks that, that latter group are the folks that kept their, their, their projects going because they were already extracting value from them. The first two groups we were seeing, sort of saying the second half of this year is when we're going to begin really being picking up on these, on these types of initiatives again. >>Well, thank you, Matt, by the way, for, for hitting the escape key, because I think value from data really is what this is all about. And there are some real blockers there that I kind of want to talk about. You've mentioned HDFS. I mean, we were very excited, of course, in the early days of a dupes, many of the concepts were profound, but at the end of the day, it was too complicated. We've got these hyper specialized roles that are, that are serving the business, but it still takes too long. It's, it's too hard to get value from data. And one of the blockers is infrastructure that the complexity of that infrastructure really needs to be abstracted taken up a level. We're starting to see this in, in cloud where you're seeing some of those abstraction layers being built from some of the cloud vendors, but more importantly, a lot of the vendors like pure, Hey, we can do that heavy lifting for you. Uh, and we, you know, we have expertise in engineering to do cloud native. So I'm wondering what you guys see. Maybe Garrett, you could start us off and the other salmon as some of the blockers, uh, to getting value from data and how we're going to address those in the coming decade. >>Yeah. I mean, I think part of it we're solving here obviously with, with pure bringing, uh, you know, flash to a market that traditionally was utilizing a much slower media. Um, you know, the other thing that I, that I see that's very nice with flash blade for example, is the ability to kind of do things, you know, once you get it set up a blade at a time. I mean, a lot of the things that we see from just kind of more of a simplistic approach to this, like a lot of these teams don't have big budgets and being able to kind of break them down into almost a blade type chunk, I think has really kind of allowed folks to get more projects and, and things off the ground because they don't have to buy a full expensive system to run these projects. Um, so that's helped a lot. >>I think the wider use cases have helped a lot. So, um, Matt mentioned ransomware, um, you know, using safe mode as a, as a place to help with ransomware has been a really big growth spot for us. We've got a lot of customers, very interested and excited about that. Um, and the other thing that I would say is bringing dev ops into data is another thing that we're seeing. So kind of that push towards data ops and really kind of using automation and infrastructure as code as a way to now kind of drive things through the system. The way that we've seen with automation through dev ops is, is really an area we're seeing a ton of growth with from a services perspective, >>Guys, any other thoughts on that? I mean, we're, I I'll, I'll tee it up there. I, we are seeing some bleeding edge, which is somewhat counterintuitive, especially from a cost standpoint, organizational changes at some, some companies, uh, think of some of the, the, the, the internet companies that do, uh, music, uh, for instance, and adding podcasts, et cetera. And those are different data products. We're seeing them actually reorganize their data architectures to make them more distributed, uh, and actually put the domain heads, the business heads in charge of the data and the data pipeline. And that is maybe less efficient, but, but it's, again, some of these bleeding edge. What else are you guys seeing out there that might be some harbinger of the next decade? >>Uh, I'll go first. Um, you know, I think specific to, um, the, the construct that you threw out, Dave, one of the things that we're seeing is, um, you know, the, the, the application owner, maybe it's the dev ops person, but it's, you know, maybe it's, it's, it's, it's the application owner through the dev ops person. They're, they're becoming more technical in their understanding of how infrastructure, um, interfaces with their, with their application. I think, um, you know, what, what we're seeing on the flash blade side is we're having a lot more conversations with application people than, um, just it people. It doesn't mean that the, it people aren't there, the it, people are still there for sure if they have to deliver the service, et cetera. Um, but you know, the days of, of it, you know, building up a catalog of services and a business owner subscribing to one of those services, you know, picking, you know, whatever sort of fits their need. >>Um, I don't think that constant, I think that's the construct that changes going forward. The application owner is becoming much more prescriptive about what they want the infrastructure to fit, how they want the infrastructure to fit into their application. Um, and that's a big change. And for, for, um, you know, certainly folks like, like Garrett and CDW, um, you know, they do a good job with this being able to sort of get to the application owner and bring those two sides together. There's a tremendous amount of value there, uh, for us to spend a little bit of a, of a retooling we've traditionally sold to the it side of the house. And, um, you know, we've had to teach ourselves how to go talk the language of, of applications. So, um, you know, I think you pointed out a good, a good, a good construct there, and you know, that that application owner tank playing a much bigger role in what they're expecting from the performance of it, infrastructure I think is, is, is a key, is a key change. >>Interesting. I mean, that definitely is a trend. That's puts you guys closer to the business where the infrastructure team is serving the business, as opposed to sometimes I talked to data experts and they're frustrated, uh, especially data owners or data, product builders who are frustrated that they feel like they have to beg, beg the, the data pipeline team to get, you know, new data sources or get data out. How about the edge? Um, you know, maybe Scott, you can kick us off. I mean, we're seeing, you know, the emergence of, of edge use cases, AI inferencing at the edge, lot of data at the edge. W what are you seeing there and how does this unified object I'll bring us back to that in file fit. >>Wow. Dave, how much time do we have, um, tell me, first of all, Scott, why don't you, why don't you just tell everybody what the edge is? Yeah. You got it all figured out. How much time do you have end of the day. And that's, that's a great question, right? Is if you take a step back and I think it comes back to Dave, something you mentioned it's about extracting value from data. And what that means is when you extract value from data, what it does is as Matt pointed out the, the influencers or the users of data, the application owners, they have more power because they're driving revenue now. And so what that means is from an it standpoint, it's not just, Hey, here are the services you get, use them or lose them, or, you know, don't throw a fit. It is no, I have to, I have to adapt. I have to follow what my application owners me. Now, when you bring that back to the edge, what it means is, is that data is not localized to the data center. I mean, we just went through a nearly 12 month period where >>The entire workforce for most of the companies in this country had went distributed and business continued. So if business is distributed, data is distributed. And that means, that means in the data center, that means at the edge, that means that the cloud, and that means in all other places and tons of places. And what it also means is you have to be able to extract and utilize data anywhere it may be. And I think that's something that we're going to continue to and continue to see. And I think it comes back to, you know, if you think about key characteristics, we've talked about, um, things like performance and scale for years, but we need to start rethinking it because on one hand, we need to get performance everywhere. But also in terms of scale, and this ties back to some of the other initiatives and getting value from data, it's something I call the, the massive success problem. One of the things we see, especially with, with workloads like machine learning is businesses find success with them. And as soon as they do they say, well, I need about 20 of these projects now will all of a sudden that overburdens it organizations, especially across, across core and edge and cloud environments. And so when you look at environments ability to meet performance and scale demands, wherever it needs to be is something that's really important. You know, >>Dave, I'd like to, um, just sort of tie together sort of two things that, um, I think that I heard from Scott and Garrett that I think are important and it's around this concept of scale. Um, you know, some of us are old enough to remember the day when kind of a 10 terabyte blast radius was too big of a blast radius for people to take on, or a terabyte of storage was considered to be, um, you know, uh, uh, an exemplary budget environment. Right. Um, now we sort of think as terabytes, kind of like we used to think of as gigabytes in some ways, um, petabyte, like you don't have to explain to anybody what a petabyte is anymore. Um, and you know, what's on the horizon and it's not far are our exabyte type dataset workloads. Um, and you start to think about what could be in that exabyte of data. >>We've talked about how you extract that value. And we've talked about sort of, um, how you start, but if the scale is big, not everybody's going to start at a petabyte or an exabyte to Garrett's point, the ability to start small and grow into these products, or excuse me, these projects, I think is a, is a really, um, fundamental concept here because you're not going to just go buy five. I'm going to go kick off a five petabyte project, whether you do that on disk or flash, it's going to be expensive, right. But if you could start at a couple of hundred terabytes, not just as a proof of concept, but as something that, you know, you could get predictable value out of that, then you could say, Hey, this either scales linearly, or non-linearly in a way that I can then go map my investments to how I can go dig deeper into this. That's how all of these things are going to, that's how these successful projects are going to start, because the people that are starting with these very large, you know, sort of, um, expansive, you know, Greenfield projects at multi petabyte scale, it's gonna be hard to realize near-term value. Excellent. Uh, >>We we're, we gotta wrap, but, but Garrett, I wonder if you could close it, when you look forward, you talk to customers, do you see this unification of file and object? Is it, is this an evolutionary trend? Is it something that is, that is, that is, that is going to be a lever that customers use. How do you see it evolving over the next two, three years and beyond? >>Yeah, I mean, I think from our perspective, I mean, just from what we're seeing from the numbers within the market, the amount of growth that's happening with unstructured data is really just starting to finally really kind of hit this data delusion or whatever you want to call it that we've been talking about for so many years. Um, it really does seem to now be becoming true, um, as we start to see things scale out and really folks settle into, okay, I'm going to use the cloud to start and maybe train my models, but now I'm going to get it back on prem because of latency or security or whatever the, the, the, um, decision points are there. Um, this is something that is not going to slow down. And I think, you know, folks like pure having the ability to have the tools that they give us, um, do use and bring to market with our customers are, are really key and critical for us. So I see it as a huge growth area and a big focus for us moving forward, >>Guys, great job unpacking a topic that, you know, it's covered a little bit, but I think we, we covered some ground. That is a, that is new. And so thank you so much for those insights and that data really appreciate your time. >>Thanks, Dave. Thanks. Yeah. Thanks, Dave. >>Okay. And thank you for watching the convergence of file and object. Keep it right there. Bright, bright back after the short break.

>> Announcer: Live from Las Vegas, it's theCUBE. Covering IBM Think 2018. Brought to you by IBM. >> Welcome back to theCUBE live at the inaugural IBM Think 2018 event. I'm Lisa Martin with Dave Vellante. Excited to be joined by a guest from down under, Garrett McDonald, the head of Enterprise Architecture at the Department of Human Services in Australia. Welcome to theCUBE. >> Thank you very much. >> Great to have you. So tell us about the Department of Human Services, DHS. You guys touch 99 percent of the Australian population. >> Yeah, we do. We sit within federal government, we're a large service delivery organization. So through a range of programs and services we touch pretty much every Australian citizen on an annual basis. And within our organization we're responsible for delivery of our national social welfare system, and that picks up people pretty much across the entire course of their lives at different points, we're also responsible for delivering the federally administered portion of our national health system, and that picks up pretty much every Australian every time you go to a doctor, a pharmacy, a hospital, a path lab, indirectly both the provider and the citizen are engaging with our services. We're responsible for running the child support system, but then we also provide IT services for other government departments, so we implement and operate for the Department of Veterans Affairs, and also the National Disability Insurance Agency. And then finally we also run Whole-of-government capabilities, so DHS we operate the myGov platform, that's a Whole-of-government capability for citizens who government authentication and within out program we have 12 million active users and that number continues to grow year on year, and that's the way that you access authenticated services for most of the major interactions that a citizen would have online with government. >> And your role is formerly CTO, right? >> Yep. >> You've got a new role. Can you explain it? >> Yeah, I'm a bit of a jack-of-all-trades within the senior executive at DHS, I've had roles in ICT infrastructure, the role of CTO, the role of national manager for Enterprise Architecture, and I've also had application delivery roles as well. >> Okay, so let's get into the healthcare talk because the drivers in that industry are so interesting, you've got privacy issues, in this country it's HIPAA, I'm sure you're got similar restrictions on data. Um, what's driving your business? You've got that regulation environment plus you've got the whole digital disruption thing going on. You've got cloud, private cloud, what's driving your organization from a technology perspective? >> I think there's two main factors there. We have changing citizen expectations, like we've got this continued explosion in the rate of changing technology, and through that people are becoming increasingly comfortable with the integration of technology in their lives, we've got people who are living their lives through social media platforms and have come to expect a particular user experience when engaging through those platforms, and they're now expecting the same experience when they interact with government. How do I get that slick user experience, how do I take the friction out of the engagement, and how do I take the burden out of having to interact with government? But at the same time, given we are a government agency and we do have data holdings across the entire Australian population, whether it's social welfare, whether it's health or a range of other services, there's this very very high focus on how do we maintain privacy and security of data. >> Yeah, I can't imagine the volumes of transactional data for 12 million people. What are some of the things that DHS is using or leveraging that relationship with IBM for to manage these massive volumes of data? You mentioned like different types of healthcare security requirements alone. What is that like? >> We've been using IBM as our dominant security partner for quite some years now, and it's been the use of data power appliances and ISM power appliances out at the edge to get the traffic into the organization. We're deploying Qradar as our Next Gen SIEM and we're slowly transitioning over to that. And then as we work out way through the mid-range platform through our investment in the power fleet and back to our System Z, we've been using Db2 on Z for quite some years in the health domain to provide that security, the reliability and the performance that we need to service the workloads that hit us on a day-to-day basis. >> So you got a little IoT thing going on. Right? You got the edge, you got the mainframe, you got Db2. Talk a little bit about how, because you've been a customer for a long time, talk about how that platform has evolved. Edge data, modernization of the mainframe, whether it's Linux, blockchain, AI, discuss that a little bit. >> Okay, so over the past three years we've been developing our Next Gen infrastructure strategy. And that really started off around about three years ago, we decided to converge on Enterprise Linux as our preferred operating system. We had probably five or six operating systems in use prior to that, and by converging down on Linux it's given us a, the ability to run same operating system whether it's on x86, on Power, or Z Linux, and that's allowed us to develop a broader range of people with deep skills in Linux, and that's really then given us a common platform upon which we can build an elastic private cloud to service our Next Gen application workloads. >> Now you've talked off-camera. No public cloud. Public cloud bad word (laughs) But you've chosen not to. Maybe discuss why and what you're doing to get cloud-like experiences. >> Yeah, so we are building out a private cloud and we do have a view towards public cloud at a point in the future, but given mandatory requirements we need to comply with within the Australian government around the use of the Cloud, given the sensitivity of the data that we hold. At this point we're holding all data on premise. >> Can we talk a little bit more about what you guys are doing with analytics and how you're using that to have a positive social impact for these 12 million Australians? >> Yeah, we've got a few initiatives on the go there. On how do we apply whether it's machine learning, AI, predictive analytics, or just Next Gen advanced analytics on how do we change the way we're delivering services to the citizens of Australia, how do we make it a more dynamic user experience, how do we make it more tailored? And on here that we're exploring at the moment is this considerable flexibility in our systems and how citizens can engage with them, so for example in the social welfare space we have a requirement for you to provide an estimate of the income you expect to learn over the next 12 months, and then based on what you actually earn through the year there can be an end-of-year true-up. Right, so that creates a situation where if you overestimate at the start of the year you can end up with an overpayment at the end of the year and we need to recover that. So what we're looking at doing is well how do we deploy predictive analytics so that we can take a look an an individual's circumstances and say well, what do we think the probability is that you may end up with an inadvertent overpayment, and how can we engage with you proactively throughout the year to help true that up so that you don't reach the end of the year and have an overpayment that we need to recover. >> So I wonder if we could talk about the data model. You talk about analytics, but what about the data model? As you get pressure from, you know, digital, let's call it. And healthcare is an industry that really hasn't been dramatically or radically transformed. It hasn't been Uberized. But the data model has largely been siloed, at least in my experience working with the healthcare industry. What's the situation in Australia, and specifically with regard to how do you get your data model in shape to be able to leverage it for this digital world? And I know you're coming at it from a standpoint of infrastructure, but maybe you could provide that context. >> Well, given for privacy reasons we continue to maintain a pretty strong degree of separation between categories of health data for a citizen, and we also have an initiative being deployed nationally around an electronic health record that the citizen is able to control, right, so when you create your citizen record, health record, there is a portion of data that is uploaded from our systems into that health record, and then a citizen can opt in around, well what information when you visit the general practitioner is available in that health record. When you go to a specialist you're able to control through privacy settings what information you're willing to share, so it's still a federated model, but there's a very, very strong focus on well how do we put controls in place so that the citizen is in control of their data. >> I want to follow up in that, this is really important, so okay, if I hear you correctly, the citizen essentially has access to and controls his or her own healthcare information. >> Yeah, that's right. And they're able to control what information are they willing to share with a given health practitioner. >> And it's pretty facile, it's easy for the citizen to do that. >> Yeah. >> And you are the trusted third party, is that right? Or -- >> It's a federated model, so we are a contributor to that service. We provide some of the functionality, we feed some of the data in, but we do have another entity that controls the overarching federation. >> Do you, is there a discussion going on around blockchain? I mean could you apply blockchain to sort of eliminate the need for that third party? And have a trustless sort of network? What's the discussion like there? >> We've been maintaining a watching brief on blockchain for a good couple of years now. We've been trying to explore, well how do we find an initial use case where we can potentially apply block chain where it provides a value and it meets the risk profile. And given it does need to be a distributed ledger, how do we find the right combination of parties where we can undertake a joint proof of technology to identify can we make this work. So not so much in HealthSpace, there are other areas where we're exploring at the moment. >> Okay, so you see the potential of just trying to figure out where it applies? >> Yeah, absolutely, and we're also watching the market to see well what's going to become the dominant distribution, how a regulatory framework's going to catch up and ensure that, you know apart from the technical implementation how do we make sure that it's governed, it's administered -- >> Do you own any Bitcoin? No, I'm just kidding. (laughter) How do you like in the Melbourne Cup? So, let's talk a little bit about the things that excite you as a technologist. We talked about a bunch of them, cloud, AI, blockchain, what gets you excited? >> I think the AI and machine learning is a wonderful area of emerging technology. So we've also been pushing quite hard with virtual assistants over the past two to three years, and we have six virtual assistants in the production environment. And those span both the unauthenticated citizen space, how do we assist them in finding information about the social welfare system, once you authenticate we have some additional virtual assistants that help guide you through the process, and then we've also been deploying virtual assistants into the staff-facing side. Now we have one there, she's been in production around about 18 months, and we've got very very complex social welfare legislation, policy, business rules, and when you're on the front line and you have a customer sitting in front of you those circumstances can be really quite complex. And you need to very quickly work through what areas of the policy are relevant, how do I apply them, how does this line up with the legislation, so what we've done is we've put a virtual assistant in place, it's a chat-based VA, and you can ask the virtual assistant some quite complex questions and we've had a 95 percent success rate on the virtual assistant answering a query on the first point of contact without the need to escalate to a subject matter expert and we figure that if we saved, we've had it round about a million questions answered in the last year, and if you think that each one of those probably saves around three minutes of time, engaging in SME, giving them the context and then sorting through to an answer, that's three million minutes of effort that our staff have been able to apply to ensuring that we get the best outcome for our citizen rather than working through how do I find the right answer. So that's a bit of a game-changer for us. >> What are some of the things that you're, related to AI, machine learning, cloud, that you're excited about learning this week at the inaugural IBM Think? And how it may really help your government as a service initiative, et cetera. >> Yeah, so I think I see a lot more potential in the space between say machine learning and predictive analytics. On based on what we know about an individual and based on what we know about similar individuals, how do we help guide that individual back to self-sufficiency? Right, so for many many years we've been highly effective and very efficient at the delivery of our services, but ultimately if we can get someone back to self-sufficiency, they're engaged in society, they're contributing to the economy, and I think that puts everyone in a pretty good place. >> Alright, so I got to ask you, I know again, architecture and infrastructure person, but I always ask everybody in your field. How long before machines are going to be able to make better diagnoses than doctors? >> Uh, not so sure about doctors, but within our space our focus has been on how do we use artificial intelligence and machine learning to augment human capability? Like, the focus is on within our business lines within our business lines we have room for discretion and human judgment. Right, so, we don't expect that the machines will be making the decisions, but given the complexity and the volume of the policy and legislation, we do think there's a considerable opportunity to use that technology to allow an individual to make the most informed and the most consistent and the most accurate decision. >> So then in your term you don't see that as a plausible scenario? >> No. >> Maybe not in our lifetime. >> As I said the focus is very much on, well, how do we augment human capability with emerging technology. >> So Garrett, last question and we've got about a minute left. What are some of the things that you are excited about in your new role as head of Enterprise Architecture for 2018 that you see by the end by the time we get to December, your summertime, that you will have wanted to achieve? >> Okay, so, over the last roughly two years I've been developing the future state technology design that will reshape out social welfare system for probably the next 30 years. This is a generational refresh we're undertaking in that space, so I think it's been a hard slog getting to this point, we're now starting to build on our new digital engagement layer, we've got a new enrichment layer starting to come to life where we do put that machine learning and AI in place and then we're also starting to rebuild the core of our social welfare system, so this is the year for me where we go from planning through to execution, and it brings me an immense sense of pleasure and pride to see the work that you've been pouring yourself into for many years start to come to fruition, start to engage with citizens, start to engage with other government agencies, and start to deliver the value that we know that it's capable of delivering. >> Well, sounds like a very exciting year ahead. We want to thank you so much, Garrett, for stopping by theCUBE and sharing the insights, what you guys are doing to help impact the lives of 12 million Australians. >> Thank you very much. >> Have a great event. >> Thank you. >> And for Dave Vellante I'm Lisa Martin. You're watching theCUBE's live coverage of the inaugural IBM Think 2018. Stick around, we'll be back with our next guest after a short break.

>>que presents on the ground. Wait. >>Hi. I'm Lisa Martin with the Cube, and we're on the ground at the Computer History Museum in Silicon Valley with the Association for Corporate Earth or a CG. Tonight is a CG 12th annual Growth Awards, and we're very fortunate to be joined by one of the longest sponsors of a CG Deloitte Gary Herbert from Delight. Welcome to the Cube. >>Thank you so much. >>So not only is a long time sponsor base did you get through the second biggest with the presumably a lot of options that Dylan has a sponsor and engage in communities like that. What next? A CG unique and warrant Deloitte sponsorship and active participation >>Delights been involved with a CG for over 10 years. And the reason is they collect a great group of senior leaders in Silicon Valley to talk about things that are really important. And a lot of great networks air here and make great things happen in the community. >>Excellent. And you can hear and feel the buzz of the innovation and the history of veterans in the room. We're here tonight to honor men who won the 2016 outstanding growth award, as well as Ambarella, who won the 2016 Emerging Growth Award in terms of the metrics used to select the winners, can you give us a little insight into what those metrics are and what this metrics and key criteria really mean for these types of award winners? >>One of the key metrics that we look at his revenue growth and Fitbit has had an incredible run over the last five years. But what's particularly amazing about Fitbit is they've been doing it very profitably, so it's really been a great testament to that. You can grow and grow in a profitable matter. >>And as we look at the next 2 to 3 years, in your perspective, what are some of the market drivers that you're going to see really influencing the fifth Mrs Your predictions there expect >>Fitbits and continue to be very successful. They've really done a great job from an execution perspective. They got great products and they define their brand. It's not just a just a tracker of steps. It is really a wellness brand. And that's why I think they're gonna continue to be successful. >>Same question for Amarillo in terms of emerging growth where some of the market drivers over the next two years, Amarilla will face. What are your >>predictions for them with Amber? I mean, since they're in the chip business, they they place themselves or have been very successful with getting successful with successful products, and that'll help their continued growth as well. Excellent. And >>what that said, Tell us what's next for Deloitte. >>Deloitte and we're diversified. Professional service is firm. I mean, people think of Deloitte as part of the Big Four, which is people think of audit Tax, I think people don't know is we're also actually were a consulting firm and an advisory firm. In fact, that makes up more than half of our revenues here. Look excellent. >>As we look forward to the future, we know tonight think that an emerald are in some great company with past winners. Lengthen Trulia Gopro What? Your predictions >>for the next class of candidates for 2017 grow awards. That's what's really exciting about this is you don't know who's successful. Companies are. If you told me three years ago is gonna be here today, I wouldn't have necessarily thought that. Um So what's exciting about this is you get to see what is next and who's who's being successful. And it really gets to celebrate the growth of those companies. Absolutely great closing to celebrate, not just the growth of these companies tonight fit, but an amber alert that we're here to celebrate, but >>also all of the >>leadership and expertise and sponsorship that we have here in Silicon Valley. Garrett, thank you so much for taking time to join us. It was a pleasure having you on the Cube. Thank you so much, Lisa. And with that said, Thank you for watching the Cube. I'm your host, Lisa Martin, and we'll see you next time.

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR, This is "Breaking Analysis with Dave Vellante". >> Black Hat 22 was held in Las Vegas last week, the same time as theCUBE Supercloud event. Unlike AWS re:Inforce where words are carefully chosen to put a positive spin on security, Black Hat exposes all the warts of cyber and openly discusses its hard truths. It's a conference that's attended by technical experts who proudly share some of the vulnerabilities they've discovered, and, of course, by numerous vendors marketing their products and services. Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this "Breaking Analysis", we summarize what we learned from discussions with several people who attended Black Hat and our analysis from reviewing dozens of keynotes, articles, sessions, and data from a recent Black Hat Attendees Survey conducted by Black Hat and Informa, and we'll end with the discussion of what it all means for the challenges around securing the supercloud. Now, I personally did not attend, but as I said at the top, we reviewed a lot of content from the event which is renowned for its hundreds of sessions, breakouts, and strong technical content that is, as they say, unvarnished. Chris Krebs, the former director of Us cybersecurity and infrastructure security agency, CISA, he gave the keynote, and he spoke about the increasing complexity of tech stacks and the ripple effects that that has on organizational risk. Risk was a big theme at the event. Where re:Inforce tends to emphasize, again, the positive state of cybersecurity, it could be said that Black Hat, as the name implies, focuses on the other end of the spectrum. Risk, as a major theme of the event at the show, got a lot of attention. Now, there was a lot of talk, as always, about the expanded threat service, you hear that at any event that's focused on cybersecurity, and tons of emphasis on supply chain risk as a relatively new threat that's come to the CISO's minds. Now, there was also plenty of discussion about hybrid work and how remote work has dramatically increased business risk. According to data from in Intel 471's Mark Arena, the previously mentioned Black Hat Attendee Survey showed that compromise credentials posed the number one source of risk followed by infrastructure vulnerabilities and supply chain risks, so a couple of surveys here that we're citing, and we'll come back to that in a moment. At an MIT cybersecurity conference earlier last decade, theCUBE had a hypothetical conversation with former Boston Globe war correspondent, Charles Sennott, about the future of war and the role of cyber. We had similar discussions with Dr. Robert Gates on theCUBE at a ServiceNow event in 2016. At Black Hat, these discussions went well beyond the theoretical with actual data from the war in Ukraine. It's clear that modern wars are and will be supported by cyber, but the takeaways are that they will be highly situational, targeted, and unpredictable because in combat scenarios, anything can happen. People aren't necessarily at their keyboards. Now, the role of AI was certainly discussed as it is at every conference, and particularly cyber conferences. You know, it was somewhat dissed as over hyped, not surprisingly, but while AI is not a panacea to cyber exposure, automation and machine intelligence can definitely augment, what appear to be and have been stressed out, security teams can do this by recommending actions and taking other helpful types of data and presenting it in a curated form that can streamline the job of the SecOps team. Now, most cyber defenses are still going to be based on tried and true monitoring and telemetry data and log analysis and curating known signatures and analyzing consolidated data, but increasingly, AI will help with the unknowns, i.e. zero-day threats and threat actor behaviors after infiltration. Now, finally, while much lip service was given to collaboration and public-private partnerships, especially after Stuxsnet was revealed early last decade, the real truth is that threat intelligence in the private sector is still evolving. In particular, the industry, mid decade, really tried to commercially exploit proprietary intelligence and, you know, do private things like private reporting and monetize that, but attitudes toward collaboration are trending in a positive direction was one of the sort of outcomes that we heard at Black Hat. Public-private partnerships are being both mandated by government, and there seems to be a willingness to work together to fight an increasingly capable adversary. These things are definitely on the rise. Now, without this type of collaboration, securing the supercloud is going to become much more challenging and confined to narrow solutions. and we're going to talk about that little later in the segment. Okay, let's look at some of the attendees survey data from Black Hat. Just under 200 really serious security pros took the survey, so not enough to slice and dice by hair color, eye color, height, weight, and favorite movie genre, but enough to extract high level takeaways. You know, these strongly agree or disagree survey responses can sometimes give vanilla outputs, but let's look for the ones where very few respondents strongly agree or disagree with a statement or those that overwhelmingly strongly agree or somewhat agree. So it's clear from this that the respondents believe the following, one, your credentials are out there and available to criminals. Very few people thought that that was, you know, unavoidable. Second, remote work is here to stay, and third, nobody was willing to really jinx their firms and say that they strongly disagree that they'll have to respond to a major cybersecurity incident within the next 12 months. Now, as we've reported extensively, COVID has permanently changed the cybersecurity landscape and the CISO's priorities and playbook. Check out this data that queries respondents on the pandemic's impact on cybersecurity, new requirements to secure remote workers, more cloud, more threats from remote systems and remote users, and a shift away from perimeter defenses that are no longer as effective, e.g. firewall appliances. Note, however, the fifth response that's down there highlighted in green. It shows a meaningful drop in the percentage of remote workers that are disregarding corporate security policy, still too many, but 10 percentage points down from 2021 survey. Now, as we've said many times, bad user behavior will trump good security technology virtually every time. Consistent with the commentary from Mark Arena's Intel 471 threat report, fishing for credentials is the number one concern cited in the Black Hat Attendees Survey. This is a people and process problem more than a technology issue. Yes, using multifactor authentication, changing passwords, you know, using unique passwords, using password managers, et cetera, they're all great things, but if it's too hard for users to implement these things, they won't do it, they'll remain exposed, and their organizations will remain exposed. Number two in the graphic, sophisticated attacks that could expose vulnerabilities in the security infrastructure, again, consistent with the Intel 471 data, and three, supply chain risks, again, consistent with Mark Arena's commentary. Ask most CISOs their number one problem, and they'll tell you, "It's a lack of talent." That'll be on the top of their list. So it's no surprise that 63% of survey respondents believe they don't have the security staff necessary to defend against cyber threats. This speaks to the rise of managed security service providers that we've talked about previously on "Breaking Analysis". We've seen estimates that less than 50% of organizations in the US have a SOC, and we see those firms as ripe for MSSP support as well as larger firms augmenting staff with managed service providers. Now, after re:Invent, we put forth this conceptual model that discussed how the cloud was becoming the first line of defense for CISOs, and DevOps was being asked to do more, things like securing the runtime, the containers, the platform, et cetera, and audit was kind of that last line of defense. So a couple things we picked up from Black Hat which are consistent with this shift and some that are somewhat new, first, is getting visibility across the expanded threat surface was a big theme at Black Hat. This makes it even harder to identify risk, of course, this being the expanded threat surface. It's one thing to know that there's a vulnerability somewhere. It's another thing to determine the severity of the risk, but understanding how easy or difficult it is to exploit that vulnerability and how to prioritize action around that. Vulnerability is increasingly complex for CISOs as the security landscape gets complexified. So what's happening is the SOC, if there even is one at the organization, is becoming federated. No longer can there be one ivory tower that's the magic god room of data and threat detection and analysis. Rather, the SOC is becoming distributed following the data, and as we just mentioned, the SOC is being augmented by the cloud provider and the managed service providers, the MSSPs. So there's a lot of critical security data that is decentralized and this will necessitate a new cyber data model where data can be synchronized and shared across a federation of SOCs, if you will, or mini SOCs or SOC capabilities that live in and/or embedded in an organization's ecosystem. Now, to this point about cloud being the first line of defense, let's turn to a story from ETR that came out of our colleague Eric Bradley's insight in a one-on-one he did with a senior IR person at a manufacturing firm. In a piece that ETR published called "Saved by Zscaler", check out this comment. Quote, "As the last layer, we are filtering all the outgoing internet traffic through Zscaler. And when an attacker is already on your network, and they're trying to communicate with the outside to exchange encryption keys, Zscaler is already blocking the traffic. It happened to us. It happened and we were saved by Zscaler." So that's pretty cool. So not only is the cloud the first line of defense, as we sort of depicted in that previous graphic, here's an example where it's also the last line of defense. Now, let's end on what this all means to securing the supercloud. At our Supercloud 22 event last week in our Palo Alto CUBE Studios, we had a session on this topic on supercloud, securing the supercloud. Security, in our view, is going to be one of the most important and difficult challenges for the idea of supercloud to become real. We reviewed in last week's "Breaking Analysis" a detailed discussion with Snowflake co-founder and president of products, Benoit Dageville, how his company approaches security in their data cloud, what we call a superdata cloud. Snowflake doesn't use the term supercloud. They use the term datacloud, but what if you don't have the focus, the engineering depth, and the bank roll that Snowflake has? Does that mean superclouds will only be developed by those companies with deep pockets and enormous resources? Well, that's certainly possible, but on the securing the supercloud panel, we had three technical experts, Gee Rittenhouse of Skyhigh Security, Piyush Sharrma who's the founder of Accurics who sold to Tenable, and Tony Kueh, who's the former Head of Product at VMware. Now, John Furrier asked each of them, "What is missing? What's it going to take to secure the supercloud? What has to happen?" Here's what they said. Play the clip. >> This is the final question. We have one minute left. I wish we had more time. This is a great panel. We'll bring you guys back for sure after the event. What one thing needs to happen to unify or get through the other side of this fragmentation and then the challenges for supercloud? Because remember, the enterprise equation is solve complexity with more complexity. Well, that's not what the market wants. They want simplicity. They want SaaS. They want ease of use. They want infrastructure risk code. What has to happen? What do you think, each of you? >> So I can start, and extending to the previous conversation, I think we need a consortium. We need a framework that defines that if you really want to operate on supercloud, these are the 10 things that you must follow. It doesn't matter whether you take AWS, Slash, or TCP or you have all, and you will have the on-prem also, which means that it has to follow a pattern, and that pattern is what is required for supercloud, in my opinion. Otherwise, security is going everywhere. They're like they have to fix everything, find everything, and so on and so forth. It's not going to be possible. So they need a framework. They need a consortium, and this consortium needs to be, I think, needs to led by the cloud providers because they're the ones who have these foundational infrastructure elements, and the security vendor should contribute on providing more severe detections or severe findings. So that's, in my opinion, should be the model. >> Great, well, thank you, Gee. >> Yeah, I would think it's more along the lines of a business model. We've seen in cloud that the scale matters, and once you're big, you get bigger. We haven't seen that coalesce around either a vendor, a business model, or whatnot to bring all of this and connect it all together yet. So that value proposition in the industry, I think, is missing, but there's elements of it already available. >> I think there needs to be a mindset. If you look, again, history repeating itself. The internet sort of came together around set of IETF, RSC standards. Everybody embraced and extended it, right? But still, there was, at least, a baseline, and I think at that time, the largest and most innovative vendors understood that they couldn't do it by themselves, right? And so I think what we need is a mindset where these big guys, like Google, let's take an example. They're not going to win at all, but they can have a substantial share. So how do they collaborate with the ecosystem around a set of standards so that they can bring their differentiation and then embrace everybody together. >> Okay, so Gee's point about a business model is, you know, business model being missing, it's broadly true, but perhaps Snowflake serves as a business model where they've just gone out and and done it, setting or trying to set a de facto standard by which data can be shared and monetized. They're certainly setting that standard and mandating that standard within the Snowflake ecosystem with its proprietary framework. You know, perhaps that is one answer, but Tony lays out a scenario where there's a collaboration mindset around a set of standards with an ecosystem. You know, intriguing is this idea of a consortium or a framework that Piyush was talking about, and that speaks to the collaboration or lack thereof that we spoke of earlier, and his and Tony's proposal that the cloud providers should lead with the security vendor ecosystem playing a supporting role is pretty compelling, but can you see AWS and Azure and Google in a kumbaya moment getting together to make that happen? It seems unlikely, but maybe a better partnership between the US government and big tech could be a starting point. Okay, that's it for today. I want to thank the many people who attended Black Hat, reported on it, wrote about it, gave talks, did videos, and some that spoke to me that had attended the event, Becky Bracken, who is the EIC at Dark Reading. They do a phenomenal job and the entire team at Dark Reading, the news desk there, Mark Arena, whom I mentioned, Garrett O'Hara, Nash Borges, Kelly Jackson, sorry, Kelly Jackson Higgins, Roya Gordon, Robert Lipovsky, Chris Krebs, and many others, thanks for the great, great commentary and the content that you put out there, and thanks to Alex Myerson, who's on production, and Alex manages the podcasts for us. Ken Schiffman is also in our Marlborough studio as well, outside of Boston. Kristen Martin and Cheryl Knight, they help get the word out on social media and in our newsletters, and Rob Hoff is our Editor-in-Chief at SiliconANGLE and does some great editing and helps with the titles of "Breaking Analysis" quite often. Remember these episodes, they're all available as podcasts, wherever you listen, just search for "Breaking Analysis Podcasts". I publish each on wikibon.com and siliconangle.com, and you could email me, get in touch with me at david.vellante@siliconangle.com or you can DM me @dvellante or comment on my LinkedIn posts, and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis". (upbeat music)

(upbeat music) >> From the Bellagio Hotel in Las Vegas, It's theCUBE. Covering UiPath FORWARD IV. Brought to you by UiPath. >> Welcome back to theCUBE's coverage of UiPath FORWARD IV. Live from the Bellagio, in Las Vegas. I'm Lisa Martin with Dave Vellante. We're here all day today and tomorrow. We're going to talk about process mining next. We've got two guests here. Mike Engel is here, intelligent automation and process intelligence leader at PWC. And Ryan McMahon, the SVP of growth at UiPath. Gentlemen, welcome to the program. >> Thank you, Lisa. >> Thank you. >> So Ryan, I'm going to start with you. Talk to us about process mining. How does UiPath do it differently and what are some of the things being unveiled at this event? >> So look, I would tell you it's actually more than process mining and hopefully, not only you but others saw this this morning with Param. It's really about the full capabilities of that discovery suite. In which, obviously, process mining is part of. But it starts with task capture. So, going out and actually working with subject matter experts on a process. Accounts payable, accounts receivable, order to cash, digitally capturing that process or how they believe it should work or execute across one's environment. Right Mike? And then from there, actually validating or verifying with things or capabilities like process mining. Giving you a full digital x-ray of actually how that process is being executed in the enterprise. Showing you process bottlenecks. For things like accounts payable, showing you days outstanding, maverick buying, so you can actually pin point and do a few things. Fix your process, right? Where process should be fixed. Fix your application because it's probably not doing what you think it is, and then third, and where the value comes, is in our platform of which process mining is a capability, our PA platform. Really moving directly to automations, right? And then, having the ability with even task mining to drill into a specific bottleneck. Capturing keystrokes, clicks, and then moving to, with both of those, process mining and task mining, into Automation Hub, as part of our discovery platform as well. Being able to crowdsource, prioritize, all of those potential, if you will, just capabilities of automations, and saying, "Okay, let's go and prioritize these. These deliver to the greatest value," and executing across them. So, as much as it is about process mining, it's actually the whole entire discovery suite of capabilities that differentiates UiPath from other RPA vendors, as the only RPA vendor that delivers process mining, task mining and this discovery suite as part of our enterprise automation platform. >> Such a critical point, Ryan. I mean, it's multi-dimensional. It's not just one component. It's not just process mining or task mining, it's the combination that's really impactful. Agree with you a hundred percent. >> So, one of the things that people who watch our shows know, I'm like a broken record on this, the early days of RPA, I called it paving the cow path. And that was good because somebody knew the process, they just repeat it. But the problem was, the process wasn't necessarily the best process. As you just described. So, when you guys made the acquisition of ProcessGold, I said, "Okay, now I'm starting to connect the dots," and now a couple years on, we're starting to see that come together. This is what I think is most misunderstood about UiPath, and I wonder, from a practitioner's perspective, if you can sort of fill in some of those gaps. It's that, it's different from a point tool, it's different from a productivity tool. Like Power Automate, I'll just say it, that's running in Azure Cloud, that's cool or a vertically integrated part of some ERP Stack. This is a horizontal play that is end to end. Which is a bigger automation agenda, it's bold but it's potentially huge. $60 billion dollar TAM, I think that's understated. Maybe you could, from a practitioner's perspective, share with us the old way, >> Yeah. >> And kind of, the new way. >> Well obviously, we all made a lot of investments in this space, early on, to determine what should we be automating in the first place? We even went so far as, we have platforms that will transcribe these kind of surveys and discussions that we're having with our clients, right. But at the end of the day all we're learning is what they know about the process. What they as individuals know about the process. And that's problematic. Once we get into the next phase of actually developing something, we miss something, right? Because we're trying to do this rapidly. So, I think what we have now is really this opportunity to have data driven insights and our clients are really grabbing onto that idea, that it's good to have a sense of what they think they do but it's more important to have a sense of what they actually do. >> Are you seeing, in the last year in a half we've seen the acceleration of a lot of things, there's some silver linings but we've also seen the acceleration in automation as a mandate. Where is it? In terms of a priority, that you're seeing with customers, and are there any industries that you're seeing that are really leading the edge here? >> Well I do see it as a priority and of course, in the role that I have, obviously everybody I talk to, it's a priority for them. But I think it's kind of changing. People are understanding that it's not just a sense of, as Ryan was pointing out, it's not just a sense of getting an understanding of what we do today, it's really driving it to that next step of actually getting something impactful out the other end. Clients are starting to understand that. I like to categorize them, there's three types of clients, there's starters, there's stall-ers and those that want to scale. >> Right? So we're seeing a lot more on the other ends of this now, where clients are really getting started and they're getting a good sense that this is important for them because they know that identifying the opportunities in the first place is the most difficult part of automation. That's what's stalling the programs. Then on the other end of the spectrum, we've got these clients that are saying, "Hey, I want to do this really at scale, can you help us do that?" >> (Ryan) Right. >> And it's quite a challenge. >> How do I build a pipeline of automations? So I've had success in finance and accounting, fantastic. How do I take this to operations? How do I take this this to supply chain? How do I take this to HR? And when I do that, it all starts with, as Wendy Batchelder, Chief Data Officer at VMware, would say and as a customer, "It starts with data but more importantly, process." So focusing on process and where we can actually deliver automation. So it's not just about those insights, it's about moving from insights to actionable next steps. >> Right. >> And that is where we're seeing this convergence, if you will, take place. As we've seen it many times before. I mentioned I worked at Cisco in the past, we saw this with Voice Over IP converging on the network. We saw this at VMware, who I know you guys have spoken to multiple times. When a move from a hypervisor to including NSX with the network, to including cloud management and also VSAN for storage, and converging in software. We're seeing it too with process, really. Instead of kids and clipboards, as they used to call it, and many Six Sigma and Lean workshops, with whiteboards and sticky papers, to actually showing people within, really, days how a process is being executed within their organization. And then, suggesting here's where there's automation capabilities, go execute against them. >> So Ryan, this is why sometimes I scoff at the TAM analysis. I get you've got to do the TAM analysis, you've got to communicate to Wall Street. But basically what you do is you pull out IDC or Gartner data, which is very stovepipe, and you kind of say, "Okay we're in this market." It's the convergence of these markets. It's cloud, it's containers, it's IS, it's PaaS, it's Saas, it's blockchain, it's automation. They're all coming together to form this, it sound like a buzzword but this digital matrix, if you will. And it's how well you leverage that digital matrix, which defines your digital business. So, talk about the role that automation, generally, RPA specifically, process mining specifically, play in a digital business. >> Do you want to take that Mike or do you want me to take it? >> We can both do it? How about that? >> Yeah, perfect. >> So I'll start with it. I mean all this is about convergence at this point, right? There are a number of platform providers out there, including UiPath, that are kind of teaching us that. Often times led by the software vendors in terms of how we think of it but what we know is that there's no one solution. We went down the RPA path, lots of clients and got a lot of excitement and a lot of impact but if you really want to drive it broader, what clients are looking at now, is what is the ecosystem of tools that we need to have in place to make that happen? And from our perspective, it's got to start with really, process intelligence. >> What I would say too, if you look at digital transformation, it was usually driven from an application. Right? Really. And what I think customers found was that, "Hey," I'm going to name some folks here, "Put everything in SAP and we'll solve all your problems." Larry Ellison will tell you, "Put everything into Oracle and we'll solve all your problems." Salesforce, now, I'm a salesperson, I've never used an out of the box Salesforce dashboard in my life, to run my business because I want to run it the way I want to run it. Having said that though, they would say the same thing, "Put everything into our platform and we'll make sure that we can access it and you can use it everywhere and we'll solve all of your problems." I think what customers found is that that's not the case. So they said, "Okay, where are there other ways. Yes, I've got my application doing what it's doing, I've improved my process but hang on. There's things that are repeatable here that I can remove to actually focus on higher level orders." And that's where UiPath comes in. We've kind of had a bottom up swell but I would tell you that as we deliver ROI within days or weeks, versus potentially years and with a heavy, heavy investment up front. We're able to do it. We're able to then work with our partners like PWC, to then demonstrate with business process modeling, the ability to do it across all those, as I call, Silo's of excellence in an organization, to deliver true value, in a timeline, with integrated services from our partner, to execute and deliver on ROI. >> You mentioned some of the great software companies that have been created over the years. One you didn't mention but I want you to comment on it is Service Now. Because essentially McDermott's trying to create the platform of platforms. All about workflow and service management. They bought an RPA company, "Hey we got this too." But it's still a walled garden. It's still the same concept is put everything in here. My question is, how are you different? Yeah look, we're going to integrate with customers who want to integrate because we're an open platform and that's the right approach. We believe there will be some overlap and there'll be some choices to be made. Instead of that top down different approach, which may be a little bit heavy and a large investment up front, with varied results, as far as what that looks like, ours is really a bottoms up. I would tell you too, if you look at our community, which is a million and a half, I believe, strong now and growing, it's really about that practitioner and those people that have embraced it from the bottom up that really change how it gets implemented. And you don't have what I used to call the white blood cells, pushing back when you're trying to say, "Hey, let's take it from this finance and accounting to HR, to the supply chain, to the other sides of the organization," saying, "Hey look, be part of this," instead of, "No, you will do." >> Yeah, there's no, at least that I know of, there's no SAP or Salesforce freemium. You can't try it before you buy. And the entry price is way higher. I mean generally. I guess Salesforce not necessarily but I could taste automation for well under $100,000. I could get in for, I bet you most of your customers started at 25 of $50,000 departmental deployments. >> It's a bottoms up ground swell, that's exactly right. And it's really that approach. Which is much more like an Atlassian, I will tell you and it's really getting to the point where we obviously, and I'm saying this, I work at UiPath, we make really good software. And so, out of the box, it's getting easier and easier to use. It all integrates. Which makes it seamless. The reason people move to RPA first was because they got tired of bouncing between applications to do a task. Now we deliver this enterprise automation platform where you can go from process discovery to crowd sourcing and prioritizing your automations with your pipeline of automations, into Studio, into creating those automations, into testing them and back again, right? We give you the opportunity not to leave the platform and extract the most value out of our, what we call enterprise automation platform. Inclusive of process mining. Inclusive of testing and all those capabilities, document understanding, which is also mine, and it's fantastic. It's very differentiated from others that are out there. >> Well it's about having the right framework in place. >> That's it. From an automation perspective. I think that's a little bit different from what you would expect from the SAP's of the world. Mike, where are you seeing, in the large organizations that you work with, we think of what you describe as the automation pipeline, where are some of the key priorities that you're finding in large organizations? What's in that pipeline and in what order? >> It's interesting because every time we have a conversation whether it's internal or with our clients, we come up with another use case for this type of technology. Obviously, when we're having the initial conversations, what we're talking about is really automation. How do we stuff that pipe with automation. But you know, we have clients that are saying, "Hey listen, I'm trying to carve out of a parent company and what I need to do is document all of my processes in a meaningful way, that I can, at some point, take action on, so there's meaningful outcomes." Whether it be a shared services organization that's looking to outsource, all different types of use cases. So, prioritizing is, I think, it's about impact and the quickest way to impact seems to be automation. >> Is it fair to say, can I look at you UiPath as automation infrastructure? Is that okay or do you guys want to say, "Oh, we're an application." The reason I ask, so then you can answer, is if you look at the great infrastructure plays, they all had a role. The DBA, the CCIE from Cisco, the Cloud Architect, the VMware admin, you've been at all of them, Ryan. So, is there a role emerging here and if it's not plumbing or infrastructure, I know, okay that's cool but course correct me on the infrastructure comment and then, is there a role emerging? >> You know, I think the difference between UiPath and some of the infrastructure companies is, it used to take, Dave, years to give an ROI, really. You'd invest in infrastructure and it's like, if we build it they will come. In fact, we've seen this with Cloud, where we kind of started doing some of that on prem, right? We can do this but then you had Amazon, Azure and others kind of take it and say, "Look, we can do it better, faster and cheaper." It's that simple. So, I would say that we are an application and that we reference it as an enterprise automation platform. It's more than infrastructure. Now, are we going to, as I mentioned, integrate to an open platform, to other capabilities? Absolutely. I think, as you see with our investments and as we continue to build this out, starting in core RPA, buying ProcessGold and getting into our discovery suite of capabilities I covered, getting into, what I see next is, as you start launching many bots into your organization, you're touching multiple applications, so you got to test it. Any time you would launch an application you're going to test it before you go live, right? We see another convergence with testing and I know you had Garrett on and Matt, earlier, with testing, application testing, which has been a legacy, kind of dinosaur market, converging with RPA, where you can deliver automations to do it better, faster and cheaper. >> Thank you for that clarification but now Mike, is that role, I know roles are emerging in RPA and automation but is there, I mean, we're seeing centers of excellence pop up, is there an analogy there or sort of a similar- >> Yeah, I think the new role, if you will, it's not super new but it's really that sense of an automation solution architect. It's a whole different thing. We're talking about now more about recombinant innovation. >> Mike: Yeah. >> Than we are about build it from scratch. Because of the convergence of these low-code, no-code types of solutions. It's a different skill set. >> And we see it at PWC. You have somebody who is potentially a process expert but then also somebody who understands automations. It's the convergences of those two, as well, that's a different skill set. It really is. And it's actually bringing those together to get the most value. And we see this across multiple organizations. It starts with a COE. We've done great with our community, so we have that upswell going and then people are saying, "Hang on, I understand process but I also understand automations. let me put the two together," and that's where we get our true value. >> Bringing in the education and training. >> No question. >> That's a huge thing. >> The traditional components of it still need to exist but I think there are new roles that are emerging, for sure. >> It's a big cultural shift. >> Oh absolutely, yeah. >> How do you guys, how does PWC and UiPath, and maybe you each can answer this in the last minute or so, how do you help facilitate that cultural shift in a business that's growing at warp speed, in a market that is very tumultuous? How do you do that? >> Want to go first or I can go? >> I'll go ahead and go first. It's working with great partners like Mike because they see it and they're converging two different practices within their organization to actually bring this value to customers and also that executive relevance. But even on our side, when we're meeting with customers, just in general, we're actually talking about, how do we deal with, there's what? 13 and a half million job openings, I guess, right now and there's 8500 people that are unemployed, is the last number that I heard. We couldn't even fill all of those jobs if we wanted to. So it's like, okay, what is it that we could potentially automate so maybe we don't need all those jobs. And that's not a negative, it's just saying, we couldn't fill them anyway. So let's focus on where we can and where, there again, can extract the most value in working with our partners but create this new domain that's not networking or virtualization but it's actually, potentially, process and automation. It's testing and automation. It might even be security and automation. Which, I will tell you, is probably coming next, having come out of the security space. You know, I sit there and listen to all these threats and I see these people chasing, really, automated threats. It's like, guys a threat hunter that's really good goes through the same 15 steps that they would when they're chasing a false positive, as if a bot would do that for them. >> I mean, I've written about the productivity declines over the past several decades in western countries, it's not universal around the world and maybe we have a productivity boost because of Covid but it's like this perpetual workday now. That's not sustainable. So we're not going to be able to solve the worlds great problems. Whether it's climate change, diversity, massive deaths, on and on and on, unless we deal with that labor gap. >> That's right. >> And the only way to do that is automation. It's so clear to me that that's the answer. Part of the answer. >> It is part of the answer and I think, to your point Lisa, it's a cultural shift that's going to happen whether we want it to or not. When you think about people that are coming into the work force, it's an expectation now. So if you want to retain or you know, attract and retain the right people, you'd better be prepared for it as an organization. >> Yeah, remember the old, proficient in Word and Excel. Makes it almost trivial. It's trivial compared to that. I think if you don't have automation chops, going forward, it's going to be an issue. Hey, we have whatever, 5000 bots running at our company, how could you help? Huh? What's a bot? >> That's right. You're right. We see this too. I'll give you an example at Cisco. One of their financial analysts, junior starter, he says, "Part of our training program, is creating automations. Why? Because it's not just about finance anymore. It's about what can I automate in my role to actually focus on higher level orders and this for me, is just amazing." And you know, it's Rajiv Ramaswamy's son who's over there at Cisco now as a financial analyst. I was sitting on my couch on a Saturday, no kidding, right Dave? And I get a text from Rajiv, who's now CEO at Nutanix, and he says, "I can't believe I just created a bot." And I said, "I'm at the right place." Really. >> That's cool, I mean hey, you're right too. You want to work for Amazon, you got to know how to provision a EC2 instance or you don't get the job. >> Yeah. >> You got to train for that. And these are the types of skills that are expected- >> That's right. >> For the future. >> Awesome. Guys- >> I'm glad I'm older. >> Are you no longer proficient in Word is the question. >> Guys, thanks for joining us, talking about what you guys are doing together, how you're really facilitating this massive growth trajectory. It's great to be back in person and we look forward to hearing from some of your customers later today. >> Terrific. >> Great. >> Thank you for the opportunity. >> Thank you for having us. >> Thank you guys. >> Our pleasure. For Dave Vellante, I'm Lisa Martin, you're watching theCUBE live from the Bellagio in Las Vegas, at UiPath FORWARD IV. Stick around. We'll be back after a short break. (upbeat music)

(upbeat music) >> Hey, we're back here in theCube. This is day three of our coverage right here in the middle of all the action of Cloud City at Mobile World Congress. This is the hit of the entire show in Barcelona, not only in person, but out on the interwebs virtually. This is a hybrid event. This is back to real life, and theCube is here. I'm John Furrier with Dave Vellante and D. R. is here, Danielle Royston. >> Totally. >> Welcome back to theCube for fourth time. now at the anchor desk, coming back. >> I don't know. It's been a busy day. It's been a busy week. It's been an awesome week. >> Dave: Feeling good? >> Oh, my god. >> You made the call. >> I made the call. You finished your podcast, what months ago? >> Yeah. >> Made the call. >> Made the call. You're on the right side of history. >> Right? And people were like, "It's going to be canceled. COVID won't be handled." Blahbity blah. >> She's crazy. >> And I'm like, nope. She's crazy. I'm okay with that. Right? But I'm like... >> Crazy good. >> Right, I'm like, I'm forward-looking in a lot of ways. And we were looking towards June, and we're like, "I think this is going to be the first event back. We're going to be able to do it." >> You know, the crazy one's commercial that Apple ran, probably one of the best commercials of all time. You can't ignore the crazy ones in a good way. You can't ignore what you're doing. And I think to me, what I'm so excited about is, 'cause we've been covering cloud. We're cloud bigots. We love the cloud, public cloud. We've been on that train from day one. But when you hear the interviews we did here on theCube and interviews that we talked about with the top people, Google, Amazon Web Services. We're talking about the top people, both technology leaders like Bill Vass and the people who run the Telecom Verticals like Alf, Alfonzo. >> Danielle: Yeah. >> Adolfo, I mean, Hernandez. >> Danielle: Yeah. >> We had Google's top networking executive. We had their industry leader in the telecom, Microsoft, and the Silicon. All are validating, and it's like surround sound to what you're saying here. And it cannot be ignored. >> I mean, we are coming to a big moment in Telco, right? And I mean, I've been saying that it's coming. I called 2021, the year of public cloud and Telco. It helped that Ericcson bailed. So thank you, Ericcson people. >> Dave: It was a gift. >> It was a gift. >> John: It really was. >> It really was a gift. And it was not just for me, but I think also for the vendors in the booth. I mean, we have a Cloud City army, right? Here we go. Let's start marching. And it's awesome. >> He reminds me of that baseball player that took a break 'cause he had a hangover and Cal Ripken. >> Cal Ripken, right, yeah, yeah. What was that guy's name? >> Did it really happen? >> Yeah, he took a break and... >> The new guy stepped in? >> Yeah, and so we'll go to Cal Ripken. >> No, no, so before it was it? Lou Gehrig. >> Lou Gehrig, yeah. >> Right, so Lou Gehrig was nobody. And we can't remember the guy's name. Nobody knows the guy's name. >> Danielle: Yeah, yeah. >> What was that guy's name? Nobody knows. Oh, 'cause Lou Garrett, he got hurt. >> Danielle: And Lou Gehrig stepped in. >> He sat out, and Lou Gehrig replaced him. >> Danielle: Love it. >> And never heard of him again. >> Danielle: I'll take that. >> Never missed a game. Never missed a game for his entire career. So again, this is what Ericcson did. They just okay, take a break and... >> But I mean, it's been great. Again, I had a great day yesterday. My keynote was delivered. Things are going well with the booth. We had Jon Bon Jovi. I mean, that was just epic, and it was acoustic, and it was right after lockdown. I think everyone was really excited to be there. But I was talking to a vendor that said we'd been able to accomplish in three days what normally it would take three years from a sales funnel perspective. I mean, that is, that's big, and that's not me. That's not my organization. That's other organizations that are benefiting from this energy. Oh, that's awesome. >> The post-isolation economy has become a living metaphor for transformation. And I've been trying to sort of grok and put the pieces together as to how this thing progresses. And my interview with Portaone, in particular, >> Danielle: Yeah. >> really brought it into focus for me, anyway. I'd love to get your thoughts. One of the things we haven't talked much about is public policy. And I think about all the time, all the discussion in the United States about infrastructure, this is critical infrastructure, right? >> Danielle: Yeah. >> And the spectrum is a country like South Africa saying, "Come on in. We want to open up." >> Danielle: Yeah. >> "We want to innovate." And to me that's to me, that's the model for these tier two and tier three telcos that are just going to disrupt the big guys. Whereas, you know, China, may be using the other end of the spectrum, very controlling, but it's the former that is going to adopt the cloud sooner. It's going to completely transform the next decade. >> Yeah, I think this is a great technology for a smaller challenger CSP that still is a large successful company to challenge the incumbents that are, they are dinosaurs too. They move a little bit slow. And maybe if you're a little bit faster, quicker dinosaur you'll survive longer. Maybe it will be able to transform and a public cloud enables that. And I think, you know, I'm playing the long game here, right? >> Dave: Yeah. >> Is public cloud ready for every telco in every corner of the world? No. And there's a couple of things that are barriers to that. We don't really talk about the downsides, and so maybe we sort of wrap up with, there are challenges, and I acknowledge there are challenges. You know, in some cases there are data regulations and issues, right? And you can't, right? There's not a hyperscaler in your country, right? And so you're having a little bit of challenges, but you trend this out over 10 years and then pace it with the hyperscalers are building new data centers. They're each at 25 plus each, plus or minus a few, right? They're marching along, and you trend this out over 10 years, I think one of two things happens. Your data regulations are eased or you a hyperscaler appears in a place you can use it. And those points converge, and hopefully the software's there, and that's my effort. And, yeah. >> You know what's an interesting trend, D. R., John? That is maybe a harbinger to this. You just mentioned something. If the hyperscalers might not have a presence in a country, you know what they're doing? And our data shows this, I do that weekly series "Breaking Analysis," and the data, OpenStack was popping up. >> Danielle: Yeah. >> Like where does OpenStack come from? Well, guess what. When you cut the data, it was telcos using open source to build clouds in regions where there was no hyperscaler. >> Where it didn't exist, yeah. >> So it's a-- >> Gap-filler. >> Yeah, it's a gap-filler. It's a Band-aid. >> But I think this is where like Outpost is such a great idea, right? Like getting Outposts, and I think Microsoft has the ability to do this as well, Google less so, right. They're not providing the staff. They're doing Anthos, so you're still managing this, the rack, but they're giving you the ability to tap into those services. But I was talking to a CE, a CTO in Bolivia. He was like, "We have data privacy issues in our country. There's no hyperscaler." Not sure Bolivia is like next on the list for AWS, right? But he's like, "I'm going to build my own public cloud." And I'm like, "Why would you do that when you can just use Outposts?" And then when your data regulations release or there's a, they get to Bolivia, you can switch and you're on the stack and you're ready to go. I think that's what you should do. You should totally do that. >> Yeah, and one of the things that's come up here on the interviews and theCube and here, the show, is that there are risk takers and innovators and there's operators. And this has been the consistent theme around, yeah, the on-premises world. You mentioned this regulation reasons and/or some workflows just have to be on premise for security reasons, whatever. That's the corner case. >> Danielle: Yeah. >> But the operating model of the technology architecture is shifted. >> Danielle: Yep. >> And that reality, I don't think, is debatable. So I find it. I've got to ask you this because I'm really curious. I know you get a lot of people steering 'ya, oh the public cloud's just a hosting, but why aren't people getting this architectural shift? I mean, you mentioned Outpost, and Wavelength, which Amazon has, is a game changer. It's Amazon Cloud at the hub. >> Yeah, at the edge, yeah. >> Okay, that's a low latency again, low-hanging fruit applications, robotics, whatnot. I mean, that's an architectural dot that's been connected. >> Yeah. >> Why aren't people getting it? >> In our industry, I think it is a lot of not invented here syndrome, right? And that's a very sort of nineties thought, and I have been advocating stand on the shoulders of the greatest technologists in the world. Right? And you know, there is a geopolitical US thing. I think we lived through a presidency that had a sort of nationalistic approach and a lot of those conversations pop up, but I've also looked to these guys and I'm like, you still have your Huawei kit installed, and there's concerns with that, too. So, and you picked it because of cost. And it's really hard to switch off of. >> John: Yeah. >> So give me a break with your public cloud USA stuff, right? You can use it. You're just making excuses. You're just afraid. What are you afraid of? The HR implications? Let's talk about that, right? And the minute I take it there, conversation changes. >> I talked to Teresa Carlson when she was running the public sector at AWS. She's now president of Splunk. I call her a Renaissance woman. She's been a great leader. In public sector there's been this weird little pocket of AWS where it's, I guess, a sales division, but it's still its own company. >> Danielle: Yeah. >> And she just did the CIA deal. The DOD and the public sector partnerships are now private, a lot more private relationships. So it's not like just governments. You mentioned government and national security and these things. You start to see the ecosystem, not, not just be about companies, government and private sector. So this whole vibe of the telecomm being regulated, unregulated, unbundled is an interesting kind of theory. What's your thoughts and reactions to this kind melting pot of ecosystem change and evolution? >> Yeah, I mean, I think there's a very nationalistic approach by the telcos, right? They sort of think about the countries that they operate in. There's a couple of groups that go across multiple countries, but can there be a global telco? Can that happen, right? Just like we say, you were saying it earlier, Netflix. Right? You didn't say Netflix, UK, right? And so can we have a global telco, right? That is challenging on a lot of different levels. But think about that in a public cloud starts to enable that idea. Right? Elon Musk is going to get Mars. >> Dave: Yep. >> John: Yeah. >> You need a planetary level telco, and I think that day is, I mean, I don't think it's tomorrow, but I think that's like 10, 20 years away. >> You're done. We're going to see it start this decade. It's already starting. >> Danielle: Yeah. >> But we're going to see the fruits of that dividend. >> Danielle: Right, yeah. >> I got to ask you. You're a student of the industry and you got so much experience. It's great to have you on theCube and chat about, riff about, these things, but the the classic "Who's ready for disruption?" question comes up. And I think there's no doubt that the telcos, as an industry, has been slow moving, and the role and the importance has changed. People need the need to have the internet access. They need to access. >> Danielle: Yeah. >> So and you've got the Edge. Now applications are now running on a, since the iPhone 14 years ago, as you pointed out, people now are interested in how packets move. >> Danielle: Yeah. >> That's fast, whether it's a doctor or an emergency worker or someone. >> What would we have done in 2020 without the internet and broadband and our mobile phones? I mean. >> Dave: We would have been miserable. >> You know, I think about 1920 when the Spanish flu pandemic hit a hundred years ago. Those guys did not have mobile phones, and they must have been bored, right? I mean, what are you going to do? Right? And so, yeah, I think, I think last year really moved a lot of thinking forward in this respect, so. >> Yeah, it's always like that animal out in the Serengeti that gets taken down, you know, by the cheetah or the lion. How do you know when someone is going to be disrupted? What's the, what's the tell sign in your mind? You look at the telco landscape, what is someone waiting to be disrupted or replaced look like? >> Know what? They're ostriches. Ostriches, how do you say that word right? They stick their head in the sand. Like they don't want to talk about it. La, la, la, I don't want to. I don't want to think about it. You know, they bring up all these like roadblocks, and I'm like, okay, I'm going to come visit you in another six months to a year, and let's see what happens when the guys that are moving fast that are open-minded to this. And it's, I mean, when you start to use the public cloud, you don't like turn it on overnight. You start experimenting, right? You start. You take an application that is non-threatening. You have, I mean, these guys are running thousands of apps inside their data centers. Pick some boring ones. Pick some old ones that no one likes. Move that to the public cloud. Play with it, right? I'm not talking about moving your whole network overnight tomorrow. You got to learn. You have no, I mean, very little talent in the telco that know how to program against the AWS stack. Start hiring. Start doing it. And you're going to start to learn about the compensation. And I used to do compensation, right? I spent a lot of time in HR, right? The compensation points and structures, and they can bear AWS and Google versus a telco. You want Telco stock? Do you want Google stock? >> John: Right, where do you want to go? >> Right? Right? And so you need to start. Like that's going to challenge the HR organization in terms of compensate. How do we compensate our people when they're learning these new, valuable skills? >> When you think about disruption, you know, the master or the professor of disruption, Clay Christensen, one of the best lectures he ever gave is we were at Cambridge, and he gave a lecture on the steel industry and he was describing it. It was like four layers of value in the steel industry, the value chain. It started with rebar, like the lowest end. Right? >> Danielle: Yeah, yeah. >> And the telco's actually the opposite. So, you know, when the international companies came in, they went after rebar, and the higher end steel companies said, "Nah, let them have it." >> Danielle: Let it go. >> "That's the low margin stuff." And then eventually when they got up to the high end, they all got killed. >> Danielle: It was over, yeah. >> The telcos are the opposite. They're like, you know, in the connectivity, and they're hanging on to that because it's so big, but all the high value stuff, it's already gone to the over-the-top players, right? >> It's being eaten away. And I'm like, "What is going to wake you guys up to realize those are your competitors?" That's where the battle is, right? >> Dave: That's really where the value is. >> The battle of the bastards. You're there by yourself, the Game of Thrones, and they're coming at you. >> John: You need a dragon. >> What are you doing about it? >> I need a dragon. I need a dragon to compete in this market. Riding on the dragon would be a good strategy. >> I know. I was just watching. 'Cause I have a podcast. I have a podcast called "Telco in 20," and we always put like little nuggets in the show notes. I personally review them. I was just reviewing the one for the keynote that we're putting out. And I had a dragon in my keynote, right? It was a really great moment. It was really fun to do. But there's, I don't know if you guys are Game of Thrones fans. >> Dave: Oh, yeah. >> John: For sure. >> Right? But there's a great moment when Daenerys guts her dragons, the baby dragons, and she takes over the Unsullied Army. Right? And it's just this, right? Like all of a sudden, the tables turn in an instant where she has nothing, and she's like on her quest, right? I'm on a quest. >> John: Comes out of the fire. >> Right, comes out of the fire. The unburnt, right? She has her dragons, right? She has them hatch. She takes over the Unsullied Army, right? Slays and starts her march, right? And I'm like, we're putting that clip into the show notes because I think that's where we are. I think I've hatched some dragons, right? The Cloud City Army, let's go, let's go take on Telco. >> John: Well, I mean to me... >> Easy. >> I definitely have made it happen because I heard many people talking about cloud. This is turning into a cloud show. The question is, when does this be, going to be a cloud show? You know it's just Cloud City is a big section of the show. I mean, all the big players are behind it. >> Danielle: Yeah, yeah. >> Amazon Web Services, Google, Azure, Ecosystem, startups thinking differently, but everyone's agreeing, "Why aren't we doing this?" >> I think, like I said, I mean, people are like, you're such a visionary. And how did, why do you think this will work? I'm like, it's worked in every other industry. Am I really that visionary? And like, these are the three best tech companies in the world. Like, are you kidding me? And so I think we've shown the momentum here. I think we're looking forward to 2022, you know? And do we see 2022, you get to start planning this the minute we get back. Right? >> John: Yeah. >> Like I wouldn't recommend doing this in a hundred days again. That was a very painful, but you know, February, I was, there's a sign inside NWC, February 28th, right? We're talking seven months. You got to get going now. >> John: Let's get on the phone. (John and Dave talking at the same time) >> I mean, I think you're right on. I mean, you know, remember Skype in the early days? >> Danielle: Yeah, yeah, yeah, yeah. >> It wasn't regional. >> Danielle: Yeah. >> It was just plug into the internet, right? >> Danielle: It was just Skype. It was just WhatsApp. >> Well, this great location, and if you can get a shot, guys, of the people behind us. I don't know if you can. If you're watching, check out the scene here. It's winding down. A lot of people having happy hour now. This is a social construct here at Cloud City. Not only is it chock full of information, reporting that we're doing and getting all the data and with the presentations on the main stage with Adam and the studio and the team. This is a place where people are meeting and there's deals being done face to face, intimate relationships. The best of the best are here. They make the trek, so there's been a successful formula. Of course theCube is in the middle of all the action, which we love. We're excited to be back. I want to thank you personally while we have you on stage here. >> I want to thank you guys and the crew. The crew has been amazing turning out videos on short order. We have all these crews in different cities. It's our own show has been virtual. You know, Adam's at Bristol, right? We're here. This was an experiment. We talked about this a hundred days ago, 90 days ago. Could we get theCube there and do the show, but also theCube. >> You are a visionary. And you said, made for TV hybrid event with your team, reduced television shows, theCube. We're digital. We love you guys. Great alignment, but it's magical because the content doesn't end here. The show might end. They might break down the beautiful plants and the exhibits, but the community is going to continue. The content and the conversations. >> Yeah. >> So. >> We are looking forward to it and. >> Yeah, super-glad, super-glad we did this. >> Awesome. Well, any final moments that you would like to share? And the last two minutes we have, favorite moments, observations, funny things that have happened to you, weird things that have happened to you. Share something that people might not know or a favorite moment. >> I think, I mean I don't know that people know we have a 3D printer in the coffee shops, and so you can upload any picture, and there are three 3D printing coffee art, right? So I've been seeing lots of social posts around people uploading their, their logos and things like that. I think Jon Bon Jovi, he was super-thankful to be back. He thanked me personally two different times of like, I'm just glad to be out in front of people. And I think just even just the people walking around, thank you for being brave, thank you for coming back. You've helped Barcelona, and we're happy to be together even if it is with masks. It's hard to do business with masks on. Everyone's happy and psyched. >> The one thing that people cannot do relative to you is they cannot ignore you. You are making a great big waves. >> Danielle: I shout pretty loud. It's kind of hard to ignore me. >> Okay, you're making a great big wave. You're on the right side, we believe, of history. Public cloud is driving the bus down main street of Cloud City, and if people don't get out of the way, they will be under the bus. >> And like I said, in my keynote, it's go time. Let's do it. >> Okay, thank you so much for all your tension and mission behind the cloud and the success of... >> Danielle: We'll do it again. We're going to do it again soon. >> Ketogi's hundred million dollar investment. Be the CEO of Togi as we follow that progress. And of course, Telco D. R. Danielle Royston, the digital revolution. Thanks for coming on theCube. >> Thank you, guys. It was super-fun. Thank you so much. >> This is theCube. I'm John Furrier with Dave Vellante. We're going to send it back to Adam in the studio. Thanks the team here. (Danielle clapping and cheering) I want to thank the team, everyone here. Adam is great. Chloe, great working with you guys. Awesome. And what a great crew. >> So great. >> Thank you everybody. That's it for theCube here on the last day, Wednesday, of theCube. Stay tuned for tomorrow, more action on the main stage here in Cloud City. Thanks for watching.

>>Hi, my name is Debbie Mangus and I am the global lead for IBM Garrett for IBM Services and I am most inspired by change about when it becomes real for our clients and making that change real and seeing Camera has been one of the biggest challenges for me with this, with this pandemic, is not being able to be there on client side with my teams. But one of the things I'm most excited to share about with you through think is some of the incredible stories. Despite Covid and how IBM Garrett has risen up to be the ultimate transformation accelerator, bringing innovation and transformation together to deliver your outcomes at scale. And I look forward to seeing you there. >>Mhm.

>>Welcome to the convergence of file and object, a special program made possible by pure storage and co-created with the cube we're running. What I would call a little mini series and we're exploring the conversions of file and object storage. What are the key trends? Why would you want to converge file and object? What are the use cases and architectural considerations and importantly, what are the business drivers of U F F O so-called unified fast file and object in this program, you'll hear from Matt Burr, who was the GM of pure flash blade business. And then we'll bring in the perspectives of a solutions architect, Garrett who's from CDW, and then the analyst angle with Scott St. Claire of the enterprise strategy group ESG. And then we'll wrap with a really interesting technical conversation with Chris and bond CB bond, who is a lead data architect at Microfocus. And he's got a really cool use case to share with us. So sit back and enjoy the pros.

we're running what i would call a little mini series and we're exploring the convergence of file and object storage what are the key trends why would you want to converge file an object what are the use cases and architectural considerations and importantly what are the business drivers of uffo so-called unified fast file and object in this program you'll hear from matt burr who is the gm of pure's flashblade business and then we'll bring in the perspectives of a solutions architect garrett belsner who's from cdw and then the analyst angle with scott sinclair of the enterprise strategy group esg he'll share some cool data on our power panel and then we'll wrap with a really interesting technical conversation with chris bond cb bond who is a lead data architect at microfocus and he's got a really cool use case to share with us so sit back and enjoy the program from around the globe it's thecube presenting the convergence of file and object brought to you by pure storage we're back with the convergence of file and object a special program made possible by pure storage and co-created with the cube so in this series we're exploring that convergence between file and object storage we're digging into the trends the architectures and some of the use cases for unified fast file and object storage uffo with me is matt burr who's the vice president and general manager of flashblade at pure storage hello matt how you doing i'm doing great morning dave how are you good thank you hey let's start with a little 101 you know kind of the basics what is unified fast file and object yeah so look i mean i think you got to start with first principles talking about the rise of unstructured data so um when we think about unstructured data you sort of think about the projections 80 of data by 2025 is going to be unstructured data whether that's machine generated data or um you know ai and ml type workloads uh you start to sort of see this um i don't want to say it's a boom uh but it's sort of a renaissance for unstructured data if you will we move away from you know what we've traditionally thought of as general purpose nas and and file shares to you know really things that focus on uh fast object taking advantage of s3 cloud native applications that need to integrate with applications on site um you know ai workloads ml workloads tend to look to share data across you know multiple data sets and you really need to have a platform that can deliver both highly performant and scalable fast file and object from one system so talk a little bit more about some of the drivers that you know bring forth that need to unify file an object yeah i mean look you know there's a there's there's a real challenge um in managing you know bespoke uh bespoke infrastructure or architectures around general purpose nas and daz etc so um if you think about how a an architect sort of looks at an application they might say well okay i need to have um you know fast daz storage proximal to the application um but that's going to require a tremendous amount of dams which is a tremendous amount of drives right hard drives are you know historically pretty pretty pretty unwieldy to manage because you're replacing them relatively consistently at multi-petabyte scale um so you start to look at things like the complexity of daz you start to look at the complexity of general purpose nas and you start to just look at quite frankly something that a lot of people don't really want to talk about anymore but actual data center space right like consolidation matters the ability to take you know something that's the size of a microwave like a modern flash blade or a modern um you know uffo device uh replaces something that might be you know the size of three or four or five refrigerators so matt what why is is now the right time for this i mean for years nobody really paid much attention to object s3 already obviously changed you know that course most of the world's data is still stored in file formats and you get there with nfs or smb why is now the time to think about unifying object and file well because we're moving to things like a contactless society um you know the the things that we're going to do are going to just require a tremendous amount more compute power network um and quite frankly storage throughput and you know i can give you two sort of real primary examples here right you know warehouses are being you know taken over by robots if you will um it's not a war it's a it's a it's sort of a friendly advancement in you know how do i how do i store a box in a warehouse and you know we have we have a customer who focuses on large sort of big box distribution warehousing and you know a box that carried a an object two weeks ago might have a different box size two weeks later well that robot needs to know where the space is in the data center in order to put it but also needs to be able to process hey i don't want to put the thing that i'm going to access the most in the back of the warehouse i'm going to put that thing in the front of the warehouse all of those types of data you know sort of real time you can think of the robot as almost an edge device is processing in real time unstructured data in its object right so it's sort of the emergence of these new types of workloads and i give you the opposite example the other end of the spectrum is ransomware right you know today you know we'll talk to customers and they'll say quite commonly hey if you know anybody can sell me a backup device i need something that can restore quickly um if you had the ability to restore something in 270 terabytes an hour or 250 terabytes an hour uh that's much faster when you're dealing with a ransomware attack you want to get your data back quickly you know so i want to add i was going to ask you about that later but since you brought it up what is the right i guess call it architecture for for for ransomware i mean how and explain like how unified object and file which appointment i get the fast recovery but how how would you recommend a customer uh go about architecting a ransomware proof you know system yeah well you know with with flashblade and and with flasharray there's an actual feature called called safe mode and that safe mode actually protects uh the snapshots and and the data from uh sort of being a part of the of the ransomware event and so if you're in a type of ransomware situation like this you're able to leverage safe mode and you say okay what happens in a ransomware attack is you can't get access to your data and so you know the bad guy the perpetrator is basically saying hey i'm not going to give you access to your data until you pay me you know x in bitcoin or whatever it might be right um with with safe mode those snapshots are actually protected outside of the ransomware blast zone and you can bring back those snapshots because what's your alternative if you're not doing something like that your alternative is either to pay and unlock your data or you have to start retouring restoring excuse me from tape or slow disk that could take you days or weeks to get your data back so leveraging safe mode um you know in either the flash for the flash blade product uh is a great way to go about architecting against ransomware i got to put my my i'm thinking like a customer now so safe mode so that's an immutable mode right can't change the data um is it can can an administrator go in and change that mode can you turn it off do i still need an air gap for example what would you recommend there yeah so there there are still um uh you know sort of our back or roll back role-based access control policies uh around who can access that safe mode and who can right okay so uh anyway subject for a different day i want to i want to actually bring up uh if you don't object a topic that i think used to be really front and center and it now be is becoming front and center again i mean wikibon just produced a research note forecasting the future of flash and hard drives and those of you who follow us know we've done this for quite some time and you can if you could bring up the chart here you you could and we see this happening again it was originally we forecast the the the death of of quote-unquote high spin speed disc drives which is kind of an oxymoron but you can see on here on this chart this hard disk had a magnificent journey but they peaked in volume in manufacturing volume in 2010 and the reason why that is is so important is that volumes now are steadily dropping you can see that and we use wright's law to explain why this is a problem and wright's law essentially says that as you your cumulative manufacturing volume doubles your cost to manufacture decline by a constant percentage now i won't go too much detail on that but suffice it to say that flash volumes are growing very rapidly hdd volumes aren't and so flash because of consumer volumes can take advantage of wright's law and that constant reduction and that's what's really important for the next generation which is always more expensive to build uh and so this kind of marks the beginning of the end matt what do you think what what's the future hold for spinning disc in your view uh well i can give you the answer on two levels on a personal level uh it's why i come to work every day uh you know the the eradication or or extinction of an inefficient thing um you know i like to say that uh inefficiency is the bane of my existence uh and i think hard drives are largely inefficient and i'm willing to accept the sort of long-standing argument that um you know we've seen this transition in block right and we're starting to see it repeat itself in in unstructured data and i'm going to accept the argument that cost is a vector here and it most certainly is right hdds have been considerably cheaper uh than than than flash storage um you know even to this day uh you know up up to this point right but we're starting to approach the point where you sort of reach a a 3x sort of um you know differentiator between the cost of an hdd and an std and you know that really is that point in time when uh you begin to pick up a lot of volume and velocity and so you know that tends to map directly to you know what you're seeing here which is you know a a slow decline uh which i think is going to become even more rapid kind of probably starting around next year um where you start to see sds excuse me ssds uh you know really replacing hdds uh at a much more rapid clip particularly on the unstructured data side and it's largely around cost the the workloads that we talked about robots and warehouses or you know other types of advanced machine learning and artificial intelligence type applications and workflows you know they require a degree of performance that a hard drive just can't deliver we are we are seeing sort of the um creative innovative uh disruption of an entire industry right before our eyes it's a fun thing to live through yeah and and we would agree i mean it doesn't the premise there is that it doesn't have to be less expensive we think it will be by you know the second half or early second half of this decade but even if it's a we think around a 3x delta the value of of ssd relative to spinning disk is going to overwhelm just like with your laptop you know it got to the point where you said why would i ever have a spinning disc in my laptop we see the same thing happening here um and and so and we're talking about you know raw capacity you know put in compression and d-dupe and everything else that you really can't do with spinning discs because of the performance issues you can do with flash okay let's come back to uffo can we dig into the challenges specifically that that this solves for customers give me give us some examples yeah so you know i mean if we if we think about the examples um you know the the robotic one um i think is is is the one that i think is the marker for you know kind of of of the the modern side of of of what we see here um but what we're you know what we're what we're seeing from a trend perspective which you know not everybody's deploying robots right um you know there's there's many companies that are you know that aren't going to be in either the robotic business uh or or even thinking about you know sort of future type oriented type things but what they are doing is green field applications are being built on object um generally not on not on file and and not on block and so you know the rise of of object as sort of the the sort of let's call it the the next great protocol for um you know for uh for for modern workloads right this is this is that that modern application coming to the forefront and that could be anything from you know financial institutions you know right down through um you we've even see it and seen it in oil and gas uh we're also seeing it across across healthcare uh so you know as as as companies take the opportunity as industries to take this opportunity to modernize you know they're modernizing not on things that are are leveraging you know um you know sort of archaic disk technology they're they're they're really focusing on on object but they still have file workflows that they need to that they need to be able to support and so having the ability to be able to deliver those things from one device in a capacity orientation or a performance orientation uh while at the same time dramatically simplifying uh the overall administration of your environment both physically and non-physically is a key driver so the great thing about object is it's simple it's a kind of a get put metaphor um it's it scales out you know because it's got metadata associated with the data uh and and it's cheap uh the drawback is you don't necessarily associate it with high performance and and and as well most applications don't you know speak in that language they speak in the language of file you know or as you mentioned block so i i see real opportunities here if i have some some data that's not necessarily frequently accessed you know every day but yet i want to then whether end of quarter or whatever it is i want to i want to or machine learning i want to apply some ai to that data i want to bring it in and then apply a file format uh because for performance reasons is that right maybe you could unpack that a little bit yeah so um you know we see i mean i think you described it well right um but i don't think object necessarily has to be slow um and nor does it have to be um you know because when you think about you brought up a good point with metadata right being able to scale to a billions of objects being able to scale to billions of objects excuse me is of value right um and i think people do traditionally associate object with slow but it's not necessarily slow anymore right we we did a sort of unofficial survey of of of our of our customers and our employee base and when people described object they thought of it as like law firms and storing a word doc if you will um and that that's just you know i think that there's a lack of understanding or a misnomer around what modern what modern object has become and perform an object particularly at scale when we're talking about billions of objects you know that's the next frontier right um is it at pace performance wise with you know the other protocols no uh but it's making leaps and grounds so you talked a little bit more about some of the verticals that you see i mean i think when i think of financial services i think transaction processing but of course they have a lot of tons of unstructured data are there any patterns you're seeing by by vertical market um we're you know we're not that's the interesting thing um and you know um as a as a as a as a company with a with a block heritage or a block dna those patterns were pretty easy to spot right there were a certain number of databases that you really needed to support oracle sql some postgres work et cetera then kind of the modern databases around cassandra and things like that you knew that there were going to be vmware environments you know you could you could sort of see the trends and where things were going unstructured data is such a broader horizontal thing right so you know inside of oil and gas for example you have you know um you have specific applications and bespoke infrastructures for those applications um you know inside of media entertainment you know the same thing the the trend that we're seeing the commonality that we're seeing is the modernization of you know object as a starting point for all the all the net new workloads within within those industry verticals right that's the most common request we see is what's your object roadmap what's your you know what's your what's your object strategy you know where do you think where do you think object is going so um there isn't any um you know sort of uh there's no there's no path uh it's really just kind of a wide open field in front of us with common requests across all industries so the amazing thing about pure just as a kind of a little you know quasi you know armchair historian the industry is pure was really the only company in many many years to be able to achieve escape velocity break through a billion dollars i mean three part couldn't do it isilon couldn't do it compellent couldn't do it i could go on but pure was able to achieve that as an independent company and so you become a leader you look at the gartner magic quadrant you're a leader in there i mean if you've made it this far you've got to have some chops and so of course it's very competitive there are a number of other storage suppliers that have announced products that unify object and file so i'm interested in how pure differentiates why pure um it's a great question um and it's one that uh you know having been a long time puritan uh you know i take pride in answering um and it's actually a really simple answer um it's it's business model innovation and technology right the the technology that goes behind how we do what we do right and i don't mean the product right innovation is product but having a better support model for example um or having on the business model side you know evergreen storage right where we sort of look at your relationship to us as a subscription right um you know we're going to sort of take the thing that that you've had and we're going to modernize that thing in place over time such that you're not rebuying that same you know terabyte or you know petabyte of storage that you've that you that you've paid for over time so um you know sort of three legs of the stool uh that that have made you know pure clearly differentiated i think the market has has recognized that um you're right it's it's hard to break through to a billion dollars um but i look forward to the day that you know we we have two billion dollar products and i think with uh you know that rise in in unstructured data growing to 80 by 2025 and you know the massive transition that you know you guys have noted in in in your hdd slide i think it's a huge opportunity for us on you know the other unstructured data side of the house you know the other thing i'd add matt i've talked to cause about this is is it's simplicity first i've asked them why don't you do this why don't you do it and the answer is always the same is that adds complexity and we we put simplicity for the customer ahead of everything else and i think that served you very very well what about the economics of of unified file an object i mean if you bring in additional value presumably there's a there there's a cost to that but there's got to be also a business case behind it what kind of impact have you seen uh with customers yeah i mean look i'll i'll i'll go back to something i mentioned earlier which is just the reclamation of floor space and power and cooling right um you know there's a you know there's people people people want to search for kind of the the sexier element if you will when it comes to looking at how we how you derive value from something but the reality is if you're reducing your power consumption by you know by by a material percentage power bills matter in big in big data centers um you know customers typically are are facing you know a paradigm of well i i want to go to the cloud but you know the clouds are not being more expensive than i thought it was going to be or you know i figured out what i can use in the cloud i thought it was going to be everything but it's not going to be everything so hybrid's where we're landing but i want to be out of the data center business and i don't want to have a team of 20 storage people to match you know to administer my storage um you know so there's sort of this this very tangible value around you know hey if i could manage um you know multiple petabytes with one full-time engineer uh because the system uh to yoran kaz's point was radically simpler to administer didn't require someone to be running around swapping drives all the time would that be a value the answer is yes 100 of the time right and then you start to look at okay all right well on the uffo side from a product perspective hey if i have to manage a you know bespoke environment for this application if i have to manage a bespoke environment for this application and a bespoke environment for this application and this book environment for this application i'm managing four different things and can i actually share data across those four different things there's ways to share data but most customers it just gets too complex how do you even know what your what your gold.master copy is of data if you have it in four different places or you try to have it in four different places and it's four different siloed infrastructures so when you get to the sort of the side of you know how do we how do you measure value in uffo it's actually being able to have all of that data concentrated in one place so that you can share it from application to application got it i'm interested we use a couple minutes left i'm interested in the the update on flashblade you know generally but also i have a specific question i mean look getting file right is hard enough uh you just announced smb support for flashblade i'm interested in you know how that fits in i think it's kind of obvious with file and object converging but give us the update on on flashblade and maybe you could address that specific question yeah so um look i mean we're we're um you know tremendously excited about the growth of flashblade uh you know we we we found workloads we never expected to find um you know the rapid restore workload was one that was actually brought to us from from from a customer actually and has become you know one of our one of our top two three four you know workloads so um you know we're really happy with the trend we've seen in it um and you know mapping back to you know thinking about hdds and ssds you know we're well on a path to building a billion dollar business here so you know we're very excited about that um but to your point you know you don't just snap your fingers and get there right um you know we've learned that doing file and object uh is is harder than block um because there's more things that you have to go do for one you're basically focused on three protocols s b nfs and s3 not necessarily in that order um but to your point about smb uh you know we we are uh on the path through to releasing um you know smb uh full full native smb support in in the system that will allow us to uh service customers we have a limitation with some customers today where they'll have an s b portion of their nfs workflow um and we do great on the nfs side um but you know we didn't we didn't have the ability to plug into the s p component of their workflow so that's going to open up a lot of opportunity for us um on on that front um and you know we continue to you know invest significantly across the board in in areas like security which is you know become more than just a hot button you know today security's always been there but it feels like it's blazing hot today um and so you know going through the next couple years we'll be looking at uh you know developing some some um you know pretty material security elements of the product as well so uh well on a path to a billion dollars is the net on that and uh you know we're we're fortunate to have have smb here and we're looking forward to introducing that to to those customers that have you know nfs workloads today with an s p component yeah nice tailwind good tam expansion strategy matt thanks so much really appreciate you coming on the program we appreciate you having us and uh thanks much dave good to see you [Music] okay we're back with the convergence of file and object in a power panel this is a special content program made possible by pure storage and co-created with the cube now in this series what we're doing is we're exploring the coming together of file and object storage trying to understand the trends that are driving this convergence the architectural considerations that users should be aware of and which use cases make the most sense for so-called unified fast file in object storage and with me are three great guests to unpack these issues garrett belsner is the data center solutions architect he's with cdw scott sinclair is a senior analyst at enterprise strategy group he's got deep experience on enterprise storage and brings that independent analyst perspective and matt burr is back with us gentlemen welcome to the program thank you hey scott let me let me start with you uh and get your perspective on what's going on the market with with object the cloud a huge amount of unstructured data out there that lives in files give us your independent view of the trends that you're seeing out there well dave you know where to start i mean surprise surprise date is growing um but one of the big things that we've seen is we've been talking about data growth for what decades now but what's really fascinating is or changed is because of the digital economy digital business digital transformation whatever you call it now people are not just storing data they actually have to use it and so we see this in trends like analytics and artificial intelligence and what that does is it's just increasing the demand for not only consolidation of massive amounts of storage that we've seen for a while but also the demand for incredibly low latency access to that storage and i think that's one of the things that we're seeing that's driving this need for convergence as you put it of having multiple protocols consolidated onto one platform but also the need for high performance access to that data thank you for that a great setup i got like i wrote down three topics that we're going to unpack as a result of that so garrett let me let me go to you maybe you can give us the perspective of what you see with customers is is this is this like a push where customers are saying hey listen i need to converge my file and object or is it more a story where they're saying garrett i have this problem and then you see unified file and object as a solution yeah i think i think for us it's you know taking that consultative approach with our customers and really kind of hearing pain around some of the pipelines the way that they're going to market with data today and kind of what are the problems that they're seeing we're also seeing a lot of the change driven by the software vendors as well so really being able to support a disaggregated design where you're not having to upgrade and maintain everything as a single block has really been a place where we've seen a lot of customers pivot to where they have more flexibility as they need to maintain larger volumes of data and higher performance data having the ability to do that separate from compute and cache and those other layers are is really critical so matt i wonder if if you could you know follow up on that so so gary was talking about this disaggregated design so i like it you know distributed cloud etc but then we're talking about bringing things together in in one place right so square that circle how does this fit in with this hyper-distributed cloud edge that's getting built out yeah you know i mean i i could give you the easy answer on that but i could also pass it back to garrett in the sense that you know garrett maybe it's important to talk about um elastic and splunk and some of the things that you're seeing in in that world and and how that i think the answer to dave's question i think you can give you can give a pretty qualified answer relative what your customers are seeing oh that'd be great please yeah absolutely no no problem at all so you know i think with um splunk kind of moving from its traditional design and classic design whatever you want you want to call it up into smart store um that was kind of one of the first that we saw kind of make that move towards kind of separating object out and i think you know a lot of that comes from their own move to the cloud and updating their code to basically take advantage of object object in the cloud uh but we're starting to see you know with like vertica eon for example um elastic other folks taking that same type of approach where in the past we were building out many 2u servers we were jamming them full of uh you know ssds and nvme drives that was great but it doesn't really scale and it kind of gets into that same problem that we see with you know hyper convergence a little bit where it's you know you're all you're always adding something maybe that you didn't want to add um so i think it you know again being driven by software is really kind of where we're seeing the world open up there but that whole idea of just having that as a hub and a central place where you can then leverage that out to other applications whether that's out to the edge for machine learning or ai applications to take advantage of it i think that's where that convergence really comes back in but i think like scott mentioned earlier it's really folks are now doing things with the data where before i think they were really storing it trying to figure out what are we going to actually do with it when we need to do something with it so this is making it possible yeah and dave if i could just sort of tack on to the end of garrett's answer there you know in particular vertica with neon mode the ability to leverage sharded subclusters give you um you know sort of an advantage in terms of being able to isolate performance hot spots you an advantage to that is being able to do that on a flashblade for example so um sharded subclusters allow you to sort of say i'm you know i'm going to give prioritization to you know this particular element of my application and my data set but i can still share those share that data across those across those subclusters so um you know as you see you know vertica advance with eon mode or you see splunk advance with with smart store you know these are all sort of advancements that are you know it's a chicken in the egg thing um they need faster storage they need you know sort of a consolidated data storage data set um and and that's what sort of allows these things to drive forward yeah so vertica eon mode for those who don't know it's the ability to separate compute and storage and scale independently i think i think vertica if they're if they're not the only one they're one of the only ones i think they might even be the only one that does that in the cloud and on-prem and that sort of plays into this distributed you know nature of this hyper-distributed cloud i sometimes call it and and i'm interested in the in the data pipeline and i wonder scott if we could talk a little bit about that maybe we're unified object and file i mean i'm envisioning this this distributed mesh and then you know uffo is sort of a node on that that i i can tap when i need it but but scott what are you seeing as the state of infrastructure as it relates to the data pipeline and the trends there yeah absolutely dave so when i think data pipeline i immediately gravitate to analytics or or machine learning initiatives right and so one of the big things we see and this is it's an interesting trend it seems you know we continue to see increased investment in ai increased interest and people think and as companies get started they think okay well what does that mean well i got to go hire a data scientist okay well that data scientist probably needs some infrastructure and what they end what often happens in these environments is where it ends up being a bespoke environment or a one-off environment and then over time organizations run into challenges and one of the big challenges is the data science team or people whose jobs are outside of it spend way too much time trying to get the infrastructure to to keep up with their demands and predominantly around data performance so one of the one of the ways organizations that especially have artificial intelligence workloads in production and we found this in our research have started mitigating that is by deploying flash all across the data pipeline we have we have data on this sorry interrupt but yeah if you could bring up that that chart that would be great um so take us through this uh uh scott and share with us what we're looking at here yeah absolutely so so dave i'm glad you brought this up so we did this study um i want to say late last year uh one of the things we looked at was across artificial intelligence environments now one thing that you're not seeing on this slide is we went through and we asked all around the data pipeline and we saw flash everywhere but i thought this was really telling because this is around data lakes and when when or many people think about the idea of a data lake they think about it as a repository it's a place where you keep maybe cold data and what we see here is especially within production environments a pervasive use of flash storage so i think that 69 of organizations are saying their data lake is mostly flash or all flash and i think we have zero percent that don't have any flash in that environment so organizations are finding out that they that flash is an essential technology to allow them to harness the value of their data so garrett and then matt i wonder if you could chime in as well we talk about digital transformation and i sometimes call it you know the coveted forced march to digital transformation and and i'm curious as to your perspective on things like machine learning and the adoption and scott you may have a perspective on this as well you know we had to pivot we had to get laptops we had to secure the end points you know and vdi those became super high priorities what happened to you know injecting ai into my applications and and machine learning did that go in the back burner was that accelerated along with the need to digitally transform garrett i wonder if you could share with us what you saw with with customers last year yeah i mean i think we definitely saw an acceleration um i think folks are in in my market are still kind of figuring out how they inject that into more of a widely distributed business use case but again this data hub and allowing folks to now take advantage of this data that they've had in these data lakes for a long time i agree with scott i mean many of the data lakes that we have were somewhat flash accelerated but they were typically really made up of you know large capacity slower spinning near-line drive accelerated with some flash but i'm really starting to see folks now look at some of those older hadoop implementations and really leveraging new ways to look at how they consume data and many of those redesigned customers are coming to us wanting to look at all flash solutions so we're definitely seeing it we're seeing an acceleration towards folks trying to figure out how to actually use it in more of a business sense now or before i feel it goes a little bit more skunk works kind of people dealing with uh you know in a much smaller situation maybe in the executive offices trying to do some testing and things scott you're nodding away anything you can add in here yeah so first off it's great to get that confirmation that the stuff we're seeing in our research garrett's seeing you know out in the field and in the real world um but you know as it relates to really the past year it's been really fascinating so one of the things we study at esg is i.t buying intentions what are things what are initiatives that companies plan to invest in and at the beginning of 2020 we saw a heavy interest in machine learning initiatives then you transition to the middle of 2020 in the midst of covid some organizations continued on that path but a lot of them had the pivot right how do we get laptops to everyone how do we continue business in this new world well now as we enter into 2021 and hopefully we're coming out of this uh you know the pandemic era um we're getting into a world where organizations are pivoting back towards these strategic investments around how do i maximize the usage of data and actually accelerating those because they've seen the importance of of digital business initiatives over the past year yeah matt i mean when we exited 2019 we saw a narrowing of experimentation and our premise was you know that that organizations are going to start now operationalizing all their digital transformation experiments and and then we had a you know 10 month petri dish on on digital so what do you what are you seeing in this regard a 10 month petri dish is an interesting way to interesting way to describe it um you know we saw another there's another there's another candidate for pivot in there around ransomware as well right um you know security entered into the mix which took people's attention away from some of this as well i mean look i'd like to bring this up just a level or two um because what we're actually talking about here is progress right and and progress isn't is an inevitability um you know whether it's whether whether you believe that it's by 2025 or you or you think it's 2035 or 2050 it doesn't matter we're on a forced march to the eradication of disk and that is happening in many ways uh you know in many ways um due to some of the things that garrett was referring to and what scott was referring to in terms of what are customers demands for how they're going to actually leverage the data that they have and that brings me to kind of my final point on this which is we see customers in three phases there's the first phase where they say hey i have this large data store and i know there's value in there i don't know how to get to it or i have this large data store and i've started a project to get value out of it and we failed those could be customers that um you know marched down the hadoop path early on and they they got some value out of it um but they realized that you know hdfs wasn't going to be a modern protocol going forward for any number of reasons you know the first being hey if i have gold.master how do i know that i have gold.4 is consistent with my gold.master so data consistency matters and then you have the sort of third group that says i have these large data sets i know how to extract value from them and i'm already on to the verticas the elastics you know the splunks etc um i think those folks are the folks that that ladder group are the folks that kept their their their projects going because they were already extracting value from them the first two groups we we're seeing sort of saying the second half of this year is when we're going to begin really being picking up on these on these types of initiatives again well thank you matt by the way for for hitting the escape key because i think value from data really is what this is all about and there are some real blockers there that i kind of want to talk about you mentioned hdfs i mean we were very excited of course in the early days of hadoop many of the concepts were profound but at the end of the day it was too complicated we've got these hyper-specialized roles that are that are you know serving the business but it still takes too long it's it's too hard to get value from data and one of the blockers is infrastructure that the complexity of that infrastructure really needs to be abstracted taking up a level we're starting to see this in in cloud where you're seeing some of those abstraction layers being built from some of the cloud vendors but more importantly a lot of the vendors like pew are saying hey we can do that heavy lifting for you uh and we you know we have expertise in engineering to do cloud native so i'm wondering what you guys see uh maybe garrett you could start us off and other students as some of the blockers uh to getting value from data and and how we're going to address those in the coming decade yeah i mean i i think part of it we're solving here obviously with with pure bringing uh you know flash to a market that traditionally was utilizing uh much slower media um you know the other thing that i that i see that's very nice with flashblade for example is the ability to kind of do things you know once you get it set up a blade at a time i mean a lot of the things that we see from just kind of more of a you know simplistic approach to this like a lot of these teams don't have big budgets and being able to kind of break them down into almost a blade type chunk i think has really kind of allowed folks to get more projects and and things off the ground because they don't have to buy a full expensive system to run these projects so that's helped a lot i think the wider use cases have helped a lot so matt mentioned ransomware you know using safe mode as a place to help with ransomware has been a really big growth spot for us we've got a lot of customers very interested and excited about that and the other thing that i would say is bringing devops into data is another thing that we're seeing so kind of that push towards data ops and really kind of using automation and infrastructure as code as a way to now kind of drive things through the system the way that we've seen with automation through devops is really an area we're seeing a ton of growth with from a services perspective guys any other thoughts on that i mean we're i'll tee it up there we are seeing some bleeding edge which is somewhat counterintuitive especially from a cost standpoint organizational changes at some some companies uh think of some of the the the internet companies that do uh music uh for instance and adding podcasts etc and those are different data products we're seeing them actually reorganize their data architectures to make them more distributed uh and actually put the domain heads the business heads in charge of the the data and the data pipeline and that is maybe less efficient but but it's again some of these bleeding edge what else are you guys seeing out there that might be yes some harbingers of the next decade uh i'll go first um you know i think specific to um the the construct that you threw out dave one of the things that we're seeing is um you know the the application owner maybe it's the devops person but it's you know maybe it's it's it's the application owner through the devops person they're they're becoming more technical in their understanding of how infrastructure um interfaces with their with their application i think um you know what what we're seeing on the flashblade side is we're having a lot more conversations with application people than um just i.t people it doesn't mean that the it people aren't there the it people are still there for sure they have to deliver the service etc um but you know the days of of i.t you know building up a catalog of services and a business owner subscribing to one of those services you know picking you know whatever sort of fits their need um i don't think that constru i think that's the construct that changes going forward the application owner is becoming much more prescriptive about what they want the infrastructure to fit how they want the infrastructure to fit into their application and that's a big change and and for for um you know certainly folks like like garrett and cdw um you know they do a good job with this being able to sort of get to the application owner and bring those two sides together there's a tremendous amount of value there for us it's been a little bit of a retooling we've traditionally sold to the i.t side of the house and um you know we've had to teach ourselves how to go talk the language of of applications so um you know i think you pointed out a good a good a good construct there and and you know that that application owner taking playing a much bigger role in what they're expecting uh from the performance of it infrastructure i think is is is a key is a key change interesting i mean that definitely is a trend that's put you guys closer to the business where the the infrastructure team is is serving the business as opposed to sometimes i talk to data experts and they're frustrated uh especially data owners or or data product builders who are frustrated that they feel like they have to beg beg the the data pipeline team to get you know new data sources or get data out how about the edge um you know maybe scott you can kick us off i mean we're seeing you know the emergence of edge use cases ai inferencing at the edge a lot of data at the edge what are you seeing there and and how does this unified object i'll bring us back to that and file fit wow dave how much time do we have um two minutes first of all scott why don't you why don't you just tell everybody what the edge is yeah you got it figured out all right how much time do you have matt at the end of the day and that that's that's a great question right is if you take a step back and i think it comes back today of something you mentioned it's about extracting value from data and what that means is when you extract value from data what it does is as matt pointed out the the influencers or the users of data the application owners they have more power because they're driving revenue now and so what that means is from an i.t standpoint it's not just hey here are the services you get use them or lose them or you know don't throw a fit it is no i have to i have to adapt i have to follow what my application owners mean now when you bring that back to the edge what it means is is that data is not localized to the data center i mean we just went through a nearly 12-month period where the entire workforce for most of the companies in this country had went distributed and business continued so if business is distributed data is distributed and that means that means in the data center that means at the edge that means that the cloud that means in all other places in tons of places and what it also means is you have to be able to extract and utilize data anywhere it may be and i think that's something that we're going to continue to and continue to see and i think it comes back to you know if you think about key characteristics we've talked about things like performance and scale for years but we need to start rethinking it because on one hand we need to get performance everywhere but also in terms of scale and this ties back to some of the other initiatives and getting value from data it's something i call that the massive success problem one of the things we see especially with with workloads like machine learning is businesses find success with them and as soon as they do they say well i need about 20 of these projects now all of a sudden that overburdens it organizations especially across across core and edge and cloud environments and so when you look at environments ability to meet performance and scale demands wherever it needs to be is something that's really important you know so dave i'd like to um just sort of tie together sort of two things that um i think that i heard from scott and garrett that i think are important and it's around this concept of scale um you know some of us are old enough to remember the day when kind of a 10 terabyte blast radius was too big of a blast radius for people to take on or a terabyte of storage was considered to be um you know an exemplary budget environment right um now we sort of think as terabytes kind of like we used to think of as gigabytes in some ways um petabyte like you don't have to explain anybody what a petabyte is anymore um and you know what's on the horizon and it's not far are our exabyte type data set workloads um and you start to think about what could be in that exabyte of data we've talked about how you extract that value we've talked about sort of um how you start but if the scale is big not everybody's going to start at a petabyte or an exabyte to garrett's point the ability to start small and grow into these products or excuse me these projects i think a is a really um fundamental concept here because you're not going to just go by i'm going to kick off a five petabyte project whether you do that on disk or flash it's going to be expensive right but if you could start at a couple hundred terabytes not just as a proof of concept but as something that you know you could get predictable value out of that then you could say hey this either scales linearly or non-linearly in a way that i can then go map my investments to how i can go dig deeper into this that's how all of these things are gonna that's how these successful projects are going to start because the people that are starting with these very large you know sort of um expansive you know greenfield projects at multi-petabyte scale it's gonna be hard to realize near-term value excellent we gotta wrap but but garrett i wonder if you could close when you look forward you talk to customers do you see this unification of of file and object is it is this an evolutionary trend is it something that is that that is that is that is going to be a lever that customers use how do you see it evolving over the next two three years and beyond yeah i mean i think from our perspective i mean just from what we're seeing from the numbers within the market the amount of growth that's happening with unstructured data is really just starting to finally really kind of hit this data deluge or whatever you want to call it that we've been talking about for so many years it really does seem to now be becoming true as we start to see things scale out and really folks settle into okay i'm going to use the cloud to to start and maybe train my models but now i'm going to get it back on prem because of latency or security or whatever the the um decision points are there this is something that is not going to slow down and i think you know folks like pure having the ability to have the tools that they give us um to use and bring to market with our customers are really key and critical for us so i see it as a huge growth area and a big focus for us moving forward guys great job unpacking a topic that you know it's covered a little bit but i think we we covered some ground that is uh that is new and so thank you so much for those insights and that data really appreciate your time thanks steve thanks yeah thanks dave okay and thank you for watching the convergence of file and object keep it right there right back after this short break innovation impact influence welcome to the cube disruptors developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe enjoy the best this community has to offer on the cube your global leader in high-tech digital coverage [Music] okay now we're going to get the customer perspective on object and we'll talk about the convergence of file and object but really focusing on the object piece this is a content program that's being made possible by pure storage and it's co-created with the cube christopher cb bond is here he's a lead architect for microfocus the enterprise data warehouse and principal data engineer at microfocus cb welcome good to see you thanks dave good to be here so tell us more about your role at microfocus it's a pan microfocus role of course we know the company is a multinational software firm and acquired the software assets of hp of course including vertica tell us where you fit yeah so microfocus is uh you know it's like i said wide worldwide uh company that uh sells a lot of software products all over the place to governments and so forth and um it also grows often by acquiring other companies so there is the problem of of integrating new companies and their data and so what's happened over the years is that they've had a a number of different discrete data systems so you've got this data spread all over the place and they've never been able to get a full complete introspection on the entire business because of that so my role was come in design a central data repository an enterprise data warehouse that all reporting could be generated against and so that's what we're doing and we selected vertica as the edw system and pure storage flashblade as the communal repository okay so you obviously had experience with with vertica in your in your previous role so it's not like you were starting from scratch but but paint a picture of what life was like before you embarked on this sort of consolidated a approach to your your data warehouse what was it just disparate data all over the place a lot of m a going on where did the data live right so again the data was all over the place including under people's desks in just dedicated you know their their own private uh sql servers it a lot of data in in um microfocus is run on sql server which has pros and cons because that's a great uh transactional database but it's not really good for analytics in my opinion so uh but a lot of stuff was running on that they had one vertica instance that was doing some select uh reporting wasn't a very uh powerful system and it was what they call vertica enterprise mode where had dedicated nodes which um had the compute and storage um in the same locus on each uh server okay so vertica eon mode is a whole new world because it separates compute from storage you mentioned eon mode uh and the ability to to to scale storage and compute independently we wanted to have the uh analytics olap stuff close to the oltp stuff right so that's why they're co-located very close to each other and so uh we could what's nice about this situation is that these s3 objects it's an s3 object store on the pure flash plate we could copy those over if we needed to uh aws and we could spin up um a version of vertica there and keep going it's it's like a tertiary dr strategy because we actually have a we're setting up a second flashblade vertica system geo-located elsewhere for backup and we can get into it if you want to talk about how the latest version of the pure software for the flashblade allows synchronization across network boundaries of those flash plays which is really nice because if uh you know there's a giant sinkhole opens up under our colo facility and we lose that thing then we just have to switch the dns and we were back in business off the dr and then if that one was to go we could copy those objects over to aws and be up and running there so we're feeling pretty confident about being able to weather whatever comes along so you're using the the pure flash blade as an object store um most people think oh object simple but slow uh not the case for you is that right not the case at all it's ripping um well you have to understand about vertica and the way it stores data it stores data in what they call storage containers and those are immutable okay on disk whether it's on aws or if you had a enterprise mode vertica if you do an update or delete it actually has to go and retrieve that object container from disk and it destroys it and rebuilds it okay which is why you don't you want to avoid updates and deletes with vertica because the way it gets its speed is by sorting and ordering and encoding the data on disk so it can read it really fast but if you do an operation where you're deleting or updating a record in the middle of that then you've got to rebuild that entire thing so that actually matches up really well with s3 object storage because it's kind of the same way uh it gets destroyed and rebuilt too okay so that matches up very well with vertica and we were able to design this system so that it's append only now we had some reports that were running in sql server okay uh which were taking seven days so we moved that to uh to vertica from sql server and uh we rewrote the queries which were which had been written in t sql with a bunch of loops and so forth and we were to get this is amazing it went from seven days to two seconds to generate this report which has tremendous value uh to the company because it would have to have this long cycle of seven days to get a new introspection in what they call their knowledge base and now all of a sudden it's almost on demand two seconds to generate it that's great and that's because of the way the data is stored and uh the s3 you asked about oh you know is it slow well not in that context because what happens really with vertica eon mode is that it can they have um when you set up your compute nodes they have local storage also which is called the depot it's kind of a cache okay so the data will be drawn from the flash and cached locally uh and that was it was thought when they designed that oh you know it's that'll cut down on the latency okay but it turns out that if you have your compute nodes close meaning minimal hops to the flashblade that you can actually uh tell vertica you know don't even bother caching that stuff just read it directly on the fly from the from the flashblade and the performance is still really good it depends on your situation but i know for example a major telecom company that uh uses the same topology as we're talking about here they did the same thing they just they just dropped the cache because the flash player was able to to deliver the the data fast enough so that's you're talking about that that's speed of light issues and just the overhead of of of switching infrastructure is that that gets eliminated and so as a result you can go directly to the storage array that's correct yeah it's it's like it's fast enough that it's it's almost as if it's local to the compute node uh but every situation is different depending on your uh your knees if you've got like a few tables that are heavily used uh then yeah put them um put them in the cash because that'll be probably a little bit faster but if you have a lot of ad hoc queries that are going on you know you may exceed the storage of the local cache and then you're better off having it uh just read directly from the uh from the flash blade got it look it pure's a fit i mean i sound like a fanboy but pure is all about simplicity so is object so that means you don't have to you know worry about wrangling storage and worrying about luns and all that other you know nonsense and and file i've been burned by hardware in the past you know where oh okay they're building to a price and so they cheap out on stuff like fans or other things and these these components fail and the whole thing goes down but this hardware is super super good quality and uh so i'm i'm happy with the quality that we're getting so cb last question what's next for you where do you want to take this uh this this initiative well we are in the process now of we um when so i i designed this system to combine the best of the kimball approach to data warehousing and the inland approach okay and what we do is we bring over all the data we've got and we put it into a pristine staging layer okay like i said it's uh because it's append only it's essentially a log of all the transactions that are happening in this company just they appear okay and then from the the kimball side of things we're designing the data marts now so that that's what the end users actually interact with and so we're we're taking uh the we're examining the transactional systems to say how are these business objects created what's what's the logic there and we're recreating those logical models in uh in vertica so we've done a handful of them so far and it's working out really well so going forward we've got a lot of work to do to uh create just about every object that that the company needs cb you're an awesome guest to really always a pleasure talking to you and uh thank you congratulations and and good luck going forward stay safe thank you [Music] okay let's summarize the convergence of file and object first i want to thank our guests matt burr scott sinclair garrett belsener and c.b bohn i'm your host dave vellante and please allow me to briefly share some of the key takeaways from today's program so first as scott sinclair of esg stated surprise surprise data's growing and matt burr he helped us understand the growth of unstructured data i mean estimates indicate that the vast majority of data will be considered unstructured by mid-decade 80 or so and obviously unstructured data is growing very very rapidly now of course your definition of unstructured data and that may vary across across a wide spectrum i mean there's video there's audio there's documents there's spreadsheets there's chat i mean these are generally considered unstructured data but of course they all have some type of structure to them you know perhaps it's not as strict as a relational database but there's certainly metadata and certain structure to these types of use cases that i just mentioned now the key to what pure is promoting is this idea of unified fast file and object uffo look object is great it's inexpensive it's simple but historically it's been less performant so good for archiving or cheap and deep types of examples organizations often use file for higher performance workloads and let's face it most of the world's data lives in file formats what pure is doing is bringing together file and object by for example supporting multiple protocols ie nfs smb and s3 s3 of course has really given new life to object over the past decade now the key here is to essentially enable customers to have the best of both worlds not having to trade off performance for object simplicity and a key discussion point that we've had on the program has been the impact of flash on the long slow death of spinning disk look hard disk drives they had a great run but hdd volumes they peaked in 2010 and flash as you well know has seen tremendous volume growth thanks to the consumption of flash in mobile devices and then of course its application into the enterprise and that's volume is just going to keep growing and growing and growing the price declines of flash are coming down faster than those of hdd so it's the writing's on the wall it's just a matter of time so flash is riding down that cost curve very very aggressively and hdd has essentially become you know a managed decline business now by bringing flash to object as part of the flashblade portfolio and allowing for multiple protocols pure hopes to eliminate the dissonance between file and object and simplify the choice in other words let the workload decide if you have data in a file format no problem pure can still bring the benefits of simplicity of object at scale to the table so again let the workload inform what the right strategy is not the technical infrastructure now pure course is not alone there are others supporting this multi-protocol strategy and so we asked matt burr why pure or what's so special about you and not surprisingly in addition to the product innovation he went right to pure's business model advantages i mean for example with its evergreen support model which was very disruptive in the marketplace you know frankly pure's entire business disrupted the traditional disk array model which was fundamentally was flawed pure forced the industry to respond and when it achieved escape velocity velocity and pure went public the entire industry had to react and a big part of the pure value prop in addition to this business model innovation that we just discussed is simplicity pure's keep its simple approach coincided perfectly with the ascendancy of cloud where technology organizations needed cloud-like simplicity for certain workloads that were never going to move into the cloud they're going to stay on-prem now i'm going to come back to this but allow me to bring in another concept that garrett and cb really highlighted and that is the complexity of the data pipeline and what do you mean what do i mean by that and why is this important so scott sinclair articulated he implied that the big challenge is organizations their data full but insights are scarce scarce a lot of data not as much insights it takes time too much time to get to those insights so we heard from our guests that the complexity of the data pipeline was a barrier to getting to faster insights now cb bonds shared how he streamlined his data architecture using vertica's eon mode which allowed him to scale compute independently of storage so that brought critical flexibility and improved economics at scale and flashblade of course was the back-end storage for his data warehouse efforts now the reason i think this is so important is that organizations are struggling to get insights from data and the complexity associated with the data pipeline and data life cycles let's face it it's overwhelming organizations and there the answer to this problem is a much longer and different discussion than unifying object and file that's you know i can spend all day talking about that but let's focus narrowly on the part of the issue that is related to file and object so the situation here is that technology has not been serving the business the way it should rather the formula is twisted in the world of data and big data and data architectures the data team is mired in complex technical issues that impact the time to insights now part of the answer is to abstract the underlying infrastructure complexity and create a layer with which the business can interact that accelerates instead of impedes innovation and unifying file and object is a simple example of this where the business team is not blocked by infrastructure nuance like does this data reside in a file or object format can i get to it quickly and inexpensively in a logical way or is the infrastructure in a stovepipe and blocking me so if you think about the prevailing sentiment of how the cloud is evolving to incorporate on premises workloads that are hybrid and configurations that are working across clouds and now out to the edge this idea of an abstraction layer that essentially hides the underlying infrastructure is a trend we're going to see evolve this decade now is uffo the be all end-all answer to solving all of our data pipeline challenges no no of course not but by bringing the simplicity and economics of object together with the ubiquity and performance of file uffo makes it a lot easier it simplifies life organizations that are evolving into digital businesses which by the way is every business so we see this as an evolutionary trend that further simplifies the underlying technology infrastructure and does a better job supporting the data flows for organizations so they don't have to spend so much time worrying about the technology details that add a little value to the business okay so thanks for watching the convergence of file and object and thanks to pure storage for making this program possible this is dave vellante for the cube we'll see you next time [Music] you

>> Thank you, sir. All right, you ready to roll? >> Ready. >> All right, we'll go ahead and go in five, four, three, two. >> Okay, let's summarize the convergence of file and object. First, I want to thank our guests, Matt Burr, Scott Sinclair, Garrett Belsner, and CB Bonne. I'm your host, Dave Vellante, and please allow me to briefly share some of the key takeaways from today's program. So first, as Scott Sinclair of ESG stated surprise, surprise, data's growing. And Matt Burr, he helped us understand the growth of unstructured data. I mean, estimates indicate that the vast majority of data will be considered unstructured by mid decade, 80% or so. And obviously, unstructured data is growing very, very rapidly. Now, of course, your definition of unstructured data, now that may vary across a wide spectrum. I mean, there's video, there's audio, there's documents, there's spreadsheets, there's chat. I mean, these are generally considered unstructured data but of course they all have some type of structure to them. You know, perhaps it's not as strict as a relational database, but there's certainly metadata and certain structure to these types of use cases that I just mentioned. Now, the key to what Pure is promoting is this idea of unified fast file and object, U-F-F-O. Look, object is great, it's inexpensive, it's simple, but historically, it's been less performant, so good for archiving, or cheap and deep types of examples. Organizations often use file for higher performance workloads and let's face it, most of the world's data lives in file formats. What Pure is doing is bringing together file and object by, for example, supporting multiple protocols, ie, NFS, SMB, and S3. S3, of course, has really given a new life to object over the past decade. Now, the key here is to essentially enable customers to have the best of both worlds, not having to trade off performance for object simplicity. And a key discussion point that we've had in the program has been the impact of Flash on the long, slow, death of spinning disk. Look, hard disk drives, they had a great run, but HDD volumes, they peaked in 2010, and Flash, as you well know, has seen tremendous volume growth thanks to the consumption of Flash in mobile devices and then of course, its application into the enterprise. And as volume is just going to keep growing and growing, and growing. the price declines of Flash are coming down faster than those of HDD. So it's, the writing's on the wall. It's just a matter of time. So Flash is riding down that cost curve very, very aggressively and HDD has essentially become a managed decline business. Now, by bringing Flash to object as part of the FlashBlade portfolio and allowing for multiple protocols, Pure hopes to eliminate the dissonance between file and object and simplify the choice. In other words, let the workload decide. If you have data in a file format, no problem. Pure can still bring the benefits of simplicity of object at scale to the table. So again, let the workload inform what the right strategy is not the technical infrastructure. Now Pure, of course, is not alone. There are others supporting this multi-protocol strategy. And so we asked Matt Burr why Pure, what's so special about you? And not surprisingly, in addition to the product innovation, he went right to Pure's business model advantages. I mean, for example, with its Evergreen support model which was very disruptive in the marketplace. You know, frankly, Pure's entire business disrupted the traditional disk array model which was, fundamentally, it was flawed. Pure forced the industry to respond. And when it achieved escape velocity and Pure went public, the entire industry had to react. And a big part of the Pure value prop in addition to this business model innovation that we just discussed is simplicity. Pure's keep it simple approach coincided perfectly with the ascendancy of cloud where technology organizations needed cloud-like simplicity for certain workloads that were never going to move into the cloud. They were going to stay on-prem. Now I'm going to come back to this but allow me to bring in another concept that Garrett and CB really highlighted, and that is the complexity of the data pipeline. And what do I mean, what do I mean by that, and why is this important? So Scott Sinclair articulated or he implied that the big challenge is organizations, they're data full, but insights are scarce; a lot of data, not as much insights, and it takes time, too much time to get to those insights. So we heard from our guests that the complexity of the data pipeline was a barrier to getting to faster insights. Now, CB Bonne shared how he streamlined his data architecture using Vertica's Eon Mode which allowed him to scale, compute, independently of storage, so that brought critical flexibility and improved economics at scale. And FlashBlade, of course, was the backend storage for his data warehouse efforts. Now, the reason I think this is so important is that organizations are struggling to get insights from data and the complexity associated with the data pipeline and data lifecycles, let's face it, it's overwhelming organizations. And there, the answer to this problem is a much longer and different discussion than unifying object and file. That's, you know, I could spend all day talking about that, but let's focus narrowly on the part of the issue that is related to file and object. So the situation here is the technology has not been serving the business the way it should. Rather, the formula is twisted in the world of data and big data, and data architectures. The data team is mired in complex technical issues that impact the time to insights. Now, part of the answer is to abstract the underlying infrastructure complexity and create a layer with which the business can interact that accelerates instead of impedes innovation. And unifying file and object is a simple example of this where the business team is not blocked by infrastructure nuance, like does this data reside in the file or object format? Can I get to it quickly and inexpensively in a logical way or is the infrastructure in a stovepipe and blocking me? So if you think about the prevailing sentiment of how the cloud is evolving to incorporate on premises, workloads that are hybrid, and configurations that are working across clouds, and now out to the edge, this idea of an abstraction layer that essentially hides the underlying infrastructure is a trend we're going to see evolve this decade. Now, is UFFO the be-all end-all answer to solving all of our data pipeline challenges? No, no, of course not. But by bringing the simplicity and economics of object together with the ubiquity and performance of file, UFFO makes it a lot easier. It simplifies a life organizations that are evolving into digital businesses, which by the way, is every business. So, we see this as an evolutionary trend that further simplifies the underlying technology infrastructure and does a better job supporting the data flows for organizations so they didn't have to spend so much time worrying about the technology details that add little value to the business. Okay, so thanks for watching the convergence of file and object and thanks to Pure Storage for making this program possible. This is Dave Vellante for theCUBE. We'll see you next time.

live from Stanford University it's the hue covering Stanford women in data science 2020 brought to you by Silicon angle media hi and welcome to the cube I'm your host Sonia - Garrett and we're live at Stanford University covering wigs women in data science conference the fifth annual one and joining us today is Daphne Koller who is the co-founder who sari is the CEO and founder of in seat row that Daphne welcome to the cube nice to be here Sonia thank you for having me so tell us a little bit about in seat row how you how it you got it founded and more about your role so I've been working in the intersection of machine learning and biology and health for quite a while and it was always a bit of a an interesting journey in that the data sets were quite small and limited we're now in a different world where there's tools that are allowing us to create massive biological data sets that I think can help us solve really significant societal problems and one of those problems that I think is really important is drug discovery development where despite many important advancements the costs just keep going up and up and up and the question is can we use machine learning to solve that problem better and you talk about this more in your keynote so give us a few highlights of what you talked about so in the last you can think of drug discovery and development in the last 50 to 70 years as being a bit of a glass half-full glass half-empty the glass half-full is the fact that there's diseases that used to be a death sentence or of the sentence still a life long of pain and suffering that are now addressed by some of the modern-day medicines and I think that's absolutely amazing the other side of it is that the cost of developing new drugs has been growing exponentially in what's come to be known as Arun was law being the inverse of Moore's Law which is the one we're all familiar with because the number of drugs approved per billion u.s. dollars just keeps going down exponentially so the question is can we change that curve and you talked in your keynote about the interdisciplinary cold to tell us more about that I think in order to address some of the critical problems that were facing one needs to really build a culture of people who work together at from different disciplines each bringing their own insights and their own ideas into the mix so and in seat row we actually have a company that's half-life scientists many of whom are producing data for the purpose of driving machine learning models and the other half are machine learning people and data scientists who are working on those but it's not a handoff where one group produces the data and the other one consumes and interpreted but really they start from the very beginning to understand what are the problems that one could solve together how do you design the experiment how do you build the model and how do you derive insights from that that can help us make better medicines for people and I also wanted to ask you you co-founded Coursera so tell us a little bit more about that platform so I founded Coursera as a result of work that I'd been doing at Stanford working on how technology can make education better and more accessible this was a project that I did here a number of my colleagues as well and at some point in the fall of 2011 there was an experiment let's take some of the content that we've been we've been developing within it's within Stanford and put it out there for people to just benefit from and we didn't know what would happen would it be a few thousand people but within a matter of weeks with minimal advertising other than one New York Times article that went viral we had a hundred thousand people in each of those courses and that was a moment in time where you know we looked at this and said can we just go back to writing more papers or is there an incredible opportunity to transform access to education to people all over the world and so I ended up taking a what was supposed to be a teary leave of absence from Stanford to go and co-found Coursera and I thought I'd go back after two years but the but at the end of that two-year period the there was just so much more to be done and so much more impact that we could bring to people all over the world people of both genders people of the different social economic status every single country around the world we I just felt like this was something that I couldn't not do and how did you why did you decide to go from an educational platform to then going into machine learning and biomedicine so I've been doing Coursera for about five years in 2016 and the company was on a great trajectory but it's primarily a Content company and around me machine learning was transforming the world and I wanted to come back and be part of that and when I looked around I saw machine learning being applied to ecommerce and the natural language and to self-driving cars but there really wasn't a lot of impact being made on the life science area and I wanted to be part of making that happen partly because I felt like coming back to our earlier comment that in order to really have that impact you need to have someone who speaks both languages and while there's a new generation of researchers who are bilingual in biology and in machine learning there's still a small group and there very few of those in kind of my age cohort and I thought that I would be able to have a real impact by building and company in the space so it sounds like your background is pretty varied what advice would you give to women who are just starting college now who may be interested in a similar field would you tell them they have to major in math or or do you think that maybe like there are some other majors that may be influential as well I think there's a lot of ways to get into data science math is one of them but there's also statistics or physics and I would say that especially for the field that I'm currently in which is at the intersection of machine learning data science on the one hand and biology and health on the other one can get there from biology or medicine as well but what I think is important is not to shy away from the more mathematically oriented courses in whatever major you're in because that found the is a really strong one there's a lot of people out there who are basically lightweight consumers of data science and they don't really understand how the methods that they're deploying how they work and that limits them in their ability to advance the field and come up with new methods that are better suited perhaps to the problems that they're tackling so I think it's totally fine and in fact there's a lot of value to coming into data science from fields other than a third computer science but I think taking courses in those fields even while you're majoring in whatever field you're interested in is going to make you a much better person who lives at that intersection and how do you think having a technology background has helped you in in founding your companies and has helped you become a successful CEO in companies that are very strongly Rd focused like like in C tro and others having a technical co-founder is absolutely essential because it's fine to have an understanding of whatever the user needs and so on and come from the business side of it and a lot of companies have a business co-founder but not understanding what the technology can actually do is highly limiting because you end up hallucinating oh if we could only do this and yet that would be great but you can't and people end up oftentimes making ridiculous promises about what technology will or will not do because they just don't understand where the land mines sit and and where you're gonna hit real obstacles and in the path so I think it's really important to have a strong technical foundation in these companies and that being said where do you see an teacher in the future and and how do you see it solving say Nash that you talked about in your keynote so we hope that in seat row we'll be a fully integrated drug discovery and development company that is based on a slightly different foundation than a traditional pharma company where they grew up in the old approach of that is very much bespoke scientific analysis of the biology of different diseases and then going after targets or our ways of dealing with the disease that are driven by human intuition where I think we have the opportunity to go today is to build a very data-driven approach that collects massive amounts of data and then let analysis of those data really reveal new hypotheses that might not be the ones that the cord with people's preconceptions of what matters and what doesn't and so hopefully we'll be able to over time create enough data and apply machine learning to address key bottlenecks in the drug discovery development process so we can bring better drugs to people and we can do it faster and hopefully at much lower cost that's great and you also mentioned in your keynote that you think that 2020s is like a digital biology era so tell us more about that so I think if you look if you take a historical perspective on science and think back you realize that there's periods in history where one discipline has made a tremendous amount of progress in a relatively short amount of time because of a new technology or a new way of looking at things in the 1870s that discipline was chemistry was the understanding of the periodic table and that you actually couldn't turn lead into gold in the 1900s that was physics with understanding the connection between matter and energy and between space and time in the 1950s that was computing where silicon chips were suddenly able to perform calculations that up until that point only people have been able to do and then in 1990s there was an interesting bifurcation one was the era of data which is related to computing but also involves elements statistics and optimization of neuroscience and the other one was quantitative biology in which biology moved from a descriptive science of techsan amaizing phenomena to really probing and measuring biology in a very detailed and a high-throughput way using techniques like microarrays that measure the activity of 20,000 genes at once Oh the human genome sequencing of the human genome and many others but these two feels kind of evolved in parallel and what I think is coming now 30 years later is the convergence of those two fields into one field that I like to think of as digital biology where we are able using the tools that have and continue to be developed measure biology in entirely new levels of detail of fidelity of scale we can use the techniques of machine learning and data science to interpret what we're seeing and then use some of the technologies that are also emerging to engineer biology to do things that it otherwise wouldn't do and that will have implications in biomaterials in energy in the environment in agriculture and I think also in human health and it's an incredibly exciting space to be in right now because just so much is happening and the opportunities to make a difference and make the world a better place are just so large that sounds awesome Daphne thank you for your insight and thank you for being on cute thank you I'm so neat agario thanks for watching stay tuned for more great