(upbeat music) >> Welcome to theCube's coverage of AWS Storage Day. We're here with a couple of AWS product experts. Covering AWS's migration and transfer services, Randy Boutin is the general manager of AWS DataSync, and Mat Matthews, GM of AWS Transfer Family. Guys, good to see you again. Thanks for coming on. >> Dave, thanks. >> So look, we saw during the pandemic, the acceleration to cloud migration. We've tracked that, we've quantified that. What's driving that today? >> Yeah, so Dave, great to be back here. Saw you last year at Storage Day. >> Nice to be in studio too, isn't it? Thanks, guys, for coming in. >> We've conquered COVID. >> So yeah, I mean, this is a great question. I think digital transformation is really what's driving a lot of the focus right now from companies, and it's really not about just driving down costs. It's also about what are the opportunities available once you get into the cloud in terms of, what does that unlock in terms of innovation? So companies are focused on the usual things, optimizing costs, but ensuring they have the right security and agility. You know, a lot has happened over the last year, and companies need to be able to react, right? They need to be able to react quickly, so cloud gives them a lot of these capabilities, but the real benefit that we see is that once your data's in the cloud, it opens up the power of the cloud for analytics, for new application development, and things of that sort, so what we're seeing is that companies are really just focused on understanding cloud migration strategy, and how they can get their data there, and then use that to unlock that data for the value. >> I mean, if I've said it once, I've said it 100 times, if you weren't a digital business during the pandemic, you were out of business. You know, migration historically is a bad word in IT. Your CIOs see it and go, "Ugh." So what's the playbook for taking years of data on-prem, and moving it into the cloud? What are you seeing as best practice there? >> Yeah, so as you said, the migration historically has been painful, right? And it's a daunting task for any business or any IT executive, but fortunately, AWS has a broad suite of capabilities to help enable these migrations. And by that, I mean, we have tools to help you understand your existing on-prem workloads, understand what services in the AWS offering align to those needs, but also help you estimate the cost, right? Cost is a big part of this move. We can help you estimate that cost, and predict that cost, and then use tools like DataSync to help you move that data when that time comes. >> So you're saying you help predict the cost of the migration, or the cost of running in the cloud? >> Running in the cloud, right. Yeah, we can help estimate the run time. Based on the performance that we assess on-prem, we can then project that into a cloud service, and estimate that cost. >> So can you guys explain DataSync? Sometimes I get confused, DataSync, what's the difference between DataSync and Storage Gateway? And I want to get into when we should use each, but let's start there if we could. >> Yeah, sure, I'll take that. So Storage Gateway is primarily a means for a customer to access their data in the cloud from on-prem. All right, so if you have an application that you want to keep on-prem, you're not ready yet to migrate that application to the cloud, Gateway is a strong solution, because you can move a lot of that data, a lot of your cold or long tail data into something like S3 or EFS, but still access it from your on-prem location. DataSync's all about data movement, so if you need to move your data from A to B, DataSync is your optimized solution to do that. >> Are you finding that people, that's ideally a one time move, or is it actually, sometimes you're seeing customers do it more? Again, moving data, if I don't- Move as much data as you need to, but no more, to paraphrase Einstein. >> What we're seeing in DataSync is that customers do use DataSync for their initial migration. They'll also, as Matt was mentioning earlier, once you get your data into the cloud, that flywheel of potential starts to take hold, and customers want to ultimately move that data within the cloud to optimize its value. So you might move from service to service. You might move from EFS to S3, et cetera, to enable the cloud flywheel to benefit you. DataSync does that as well, so customers use us to initially migrate, they use us to move within the cloud, and also we just recently announced service for other clouds, so you can actually bring data in now from Google and Azure as well. >> Oh, how convenient. So okay, so that's cool. So you helped us understand the use cases, but can we dig one more layer, like what protocols are supported? I'm trying to understand really the right fit for the right job. >> Yeah, so that's really important. So for transfer specifically, one of the things that we see with customers is you've got obviously a lot of internal data within your company, but today it's a very highly interconnected world, so companies deal with lots of business partners, and historically they've used, there's a big prevalence of using file transfer to exchange data with business partners, and as you can imagine, there's a lot of value in that data, right? Sometimes it's purchase orders, inventory data from suppliers, or things like that. So historically customers have had protocols like SFTP or FTP to help them interface with or exchange data or files with external partners. So for transfer, that's what we focus on is helping customers exchange data over those existing protocols that they've used for many years. And the real focus is it's one thing to migrate your own data into the cloud, but you can't force thousands or tens of thousands sometimes of partners to also work in a different way to get you their data, so we want to make that very seamless for customers using the same exact protocols like SFTP that they've used for years. We just announced AS2 protocol, which is very heavily used in supply chains to exchange inventory and information across multi-tiers of partners, and things of that nature. So we're really focused on letting customers not have to impact their partners, and how they work and how they exchange, but also take advantage of the data, so get that data into the cloud so they can immediately unlock the value with analytics. >> So AS2 is specifically in the context of supply chain, and I'm presuming it's secure, and kind of governed, and safe. Can you explain that a little bit? >> Yeah, so AS2 has a lot of really interesting features for transactional type of exchanges, so it has signing and encryption built in, and also has notification so you can basically say, "Hey, I sent you this purchase order," and to prove that you received it, it has capability called non-repudiation, which means it's actually a legal transaction. So those things are very important in transactional type of exchanges, and allows customers in supply chains, whether it's vendors dealing with their suppliers, or transportation partners, or things like that to leverage file transfer for those types of exchanges. >> So encryption, providence of transactions, am I correct, without having to use the blockchain, and all the overhead associated with that? >> It's got some built in capabilities. >> I mean, I love blockchain, but there's drawbacks. >> Exactly, and that's why it's been popular. >> That's really interesting, 'cause Andy Jassy one day, I was on a phone call with him and John Furrier, and we were talking up crypto and blockchain. He said, "Well, why do, explain to me." You know Jassy, right? He always wants to go deeper. "Explain why I can't do this with some other approach." And so I think he was recognizing some of the drawbacks. So that's kind of a cool thing, and it leads me- We're running this obviously today, August 10th. Yesterday we had our Supercloud event in Palo Alto on August 9th, and it's all about the ecosystem. One of the observations we made about the 2020s is the cloud is totally different now. People are building value on top of the infrastructure that you guys have built out over the last 15 years. And so once an organization's data gets into the cloud, how does it affect, and it relates to AS2 somewhat, how does it affect the workflows in terms of interacting with external partners, and other ecosystem players that are also in the cloud? >> Yeah, great, yeah, again, we want to try and not have to affect those workflows, take them as they are as much as possible, get the data exchange working. One of the things that we focus on a lot is, how do you process this data once it comes in? Every company has governance requirements, security requirements, and things like that, so they usually have a set of things that they need to automate and orchestrate for the data as it's coming in, and a lot of these companies use something called Managed File Transfer Solutions that allow them to automate and orchestrate those things. We also see that many times this is very customer specific, so a bank might have a certain set of processes they have to follow, and it needs to be customized. As you know, AWS is a great solution for building custom solutions, and actually today, we're just announcing a new set of of partners in a program called the Service Delivery Program with AWS Transfer Family that allows customers to work with partners that are very well versed in transfer family and related services to help build a very specific solution that allows them to build that automation orchestration, and keep their partners kind of unaware that they're interfacing in a different way. >> And once this data is in the cloud, or actually, maybe stays on-prem in some cases, but it basically plugs in to the AWS services portfolio, the whole security model, the governance model, shared responsibility comes in, is that right? It's all, sort of all in there? >> Yeah, that's right, that's exactly right, and we're working with it's all about the customer's needs, and making sure that their investment in AWS doesn't disrupt their existing workflows and their relationships with their customers and their partners, and that's exactly what Matt's been describing is we're taking a close look at how we can extend the value of AWS, integrate into our customer's workflows, and bring that value to them with minimal investment or disruption. >> So follow up on that. So I love that, because less disruption means it's easier, less friction, and I think of like, trying to think of examples. Think about data de-duplication like purpose-built backup appliances, right? Data domain won that battle, because they could just plug right in. Avamar, they were trying to get you to redo everything, okay, and so we saw that movie play out. At the same time, I've talked to CIOs that say, "I love that, but the cloud opens up all these cool new opportunities for me to change my operating model." So are you seeing that as well? Where okay, we make it easy to get in. We're not disrupting workflows, and then once they get in, they say, "Well if we did it this way, we'd take out a bunch of costs. We'd accelerate our business." What's that dynamic like? >> Exactly that, right. So that moved to the Cloud Continuum. We don't think it's going to be binary. There's always going to be something on-prem. We accept that, but there's a continuum there, so day one, they'll migrate a portion of that workload into the cloud, start to extract and see value there, but then they'll continue, as you said, they'll continue to see opportunities. With all of the various capabilities that AWS has to offer, all the value that represents, they'll start to see that opportunity, and then start to engage and consume more of those features over time. >> Great, all right, give us the bumper sticker. What's next in transfer services from your perspectives? >> Yeah, so we're obviously always going to listen to our customers, that's our focus. >> You guys say that a lot. (all laughing) We say it a lot. But yeah, so we're focused on helping customers again increase that level of automation orchestration, again that suite of capability, generally, in our industry, known as managed file transfer, when a file comes in, it needs to get maybe encrypted, or decrypted, or compressed, or decompressed, scanned for viruses, those kind of capabilities, make that easier for customers. If you remember last year at Storage Day, we announced a low code workflow framework that allows customers to kind of build those steps. We're continuing to add built-in capabilities to that so customers can easily just say, "Okay, I want these set of activities to happen when files come in and out." So that's really what's next for us. >> All right, Randy, we'll give you the last word. Bring us home. >> I'm going to surprise you with the customer theme. >> Oh, great, love it. >> Yeah, so we're listening to customers, and what they're asking for our support for more sources, so we'll be adding support for more cloud sources, more on-prem sources, and giving the customers more options, also performance and usability, right? So we want to make it easier, as the enterprise continues to consume the cloud, we want to make DataSync and the movement of their data as easy as possible. >> I've always said it starts with the data. S3, that was the first service, and the other thing I've said a lot is the cloud is expanding. We're seeing connections to on-prem. We're seeing connections out to the edge. It's just becoming this massive global system, as Werner Vogels talks about all the time. Thanks, guys, really appreciate it. >> Dave, thank you very much. >> Thanks, Dave. >> All right, keep it right there for more coverage of AWS Storage Day 2022. You're watching theCube. (upbeat music)

>>Welcome back to the cubes coverage of Dell tech world 2022. My name is Dave Volante and I'm here in our cube studios in Massachusetts getting ready for the first in person DT w since 2019, you know, Charles Phillips, the CEO of Infor and former Oracle ex once set on the cube friends, don't let friends build data centers anymore. It's just not the best use of capital for most companies, unless you happen to be in the data center business like Sexter organizations wanna make hybrid connections to the cloud. They need a partner that knows how to build and manage world class data centers that are both efficient and resilient. And in this segment, we're gonna talk about the importance of hybrid strategies for organizations, how they're approaching hybrid and why a partner strategy is important to support the next decade of digital transformation initiatives. And with me are Randy Roland. Who's the COO of six Tara and Holland Barry, who is the field CTO for the company. Gentlemen, welcome to the cube. Thanks for coming on. >>Thank you. >>Good to meet her. Thanks for having us. >>Hey, Randy, as a relatively new player, unlike a lot of data center operators, Cera, you're not shackled by decades of technical debt. Tell us more about the company. >>Yeah. So as you, uh, already discussed Ceras a data center company, and we're one of the few that can provide colocation globally. And so that allows our customers to scale, uh, across the globe, as our business scales, we operate in 28 markets. We have over 60 data centers and we continue to add more dots to the map based on customer demand. And the primary way we differentiate is that we've built a true global data center platform. And what do I mean by that is that we have a combination of 2300 customers, uh, enterprises, technology, service providers, government agencies, we're a leader in interconnection. Uh, we have a commitment to carry neutrality and to provide low latency access to all the different cloud platforms. And we've made major investments in developing our own technology in house. And this will come out. As we talk about hybrid cloud is to make our data centers easier to consume. Uh, we live in a cloud first world, and so we've got to be able to be responsive and be able to deliver capacity on demand and to allow our customer members to dynamically connect to each other so they can start to consume these valuable services. And so that's really what we're doing at Cera. >>You know, Randy, just a follow up is because when the cloud first came out, everybody said, oh, companies like, like yours, Dana data center operations are toast. And the exact opposite happened. It was like this rising tide lifted all boats. The, the business is, is booming. It's, uh, it's actually quite room, isn't it? >>Yeah, actually it's a good point. We actually lean into, uh, cloud consumption. I think, uh, if you remember, the cloud operates in four walls. And so when a company, um, actually starts to deploy and leverage more, they need a place to land their digital infrastructure hub, where they can make connections to all the different cloud solutions they're gonna consume. And they're using their own internal resources at the same time. And so the more that we adopt cloud, um, and lean into cloud, the more likely our customer gonna choose us. And back to your opening comment about, uh, the, the quote from the Oracle executive in, in my career, I've been in the data center business for a long time and it, it's definitely a generational thing. We have newer generation of it leaders when they think about their internal data center, their actual internal data center is ours. They're thinking about their own four walls sitting on their own property like they did historically. And so, uh, they view internal data centers as the contracts they have, uh, with six companies like six. >>Excellent. All right, Holland, let's bring you into the conversation. What are you seeing with, with hybrid cloud strategies? You, why are companies choosing hybrid? Give us some color there. >>Yeah, I think, you know, we, as a company sit in an interesting confluence of some workload movements, if you will. Um, so I think there's been, in some cases, an overcorrection in the public cloud, people thought that a cloud first strategy meant that you have to throw everything up in a public cloud. Uh, especially over the last couple years when we had, you know, the surprise of a large remote workforce. And as you mentioned at the top of the call, Dave, we also have folks with the shrinking appetite to own and operate their data centers, right? So the hybrid approach is a, um, a selective methodology to really look at the applications, uh, look at the strengths of each one of those venues, where you can run your applications and workloads, and really choosing the one that uses the strengths. And there's several, uh, drivers behind that. Uh, some of them are cost. Some of them are performance. Some of them might have to do a security or data sovereignty. Um, so you can really match those requirements and those business outcomes that you're looking to achieve, uh, and align them with that platform. That's that's best suited to serve it. >>So you mentioned a few of 'em, but I wanna sort of stay on that for a minute. Is it, is it, you know, egress cost, everybody talks about that, you know, latency proximity to the cloud. I mean, I think there's a lot of times, I think the ideal situation is you put your high performance, you know, transaction low latency stuff in one of your data centers. And, you know, a lot of the data is, is in the cloud that you might need access to. But is there other innovation, you know, talk a little bit more about the drivers that you're seeing with customers? >>Absolutely. We, I think, um, as it relates to data gravity and the potential relation to egress charges, that is a huge, uh, consideration, cuz there's a cost and a performance component to that. If you decide you want to take that data and move somewhere else, if it's in the public cloud, you're gonna pay some, uh, pretty large egres fees, but there's certainly other drivers, um, performance being another big one. Uh, if I've got a, a data lake or, or a big data analytics platform or maybe an AI platform that needs to live close to the data. Um, and especially if those workloads that are associated with crunching, the data are kind of high steady state, maybe even mission critical workloads that is certainly a workload profile. That's better suited to run within our four walls. You can have those CPU or GPU comput nodes sitting right next to those large data sets, operating with each other at land speed. Um, so in terms of the drivers behind, uh, making a, a venue change, if you will, I think cost is one of the biggest ones that we see and, and maybe performance and security following close after. >>So, so how are customers approaching hybrid? Can you paint a picture of kinda what that connection looks like and how, how they, you know, land on their strategies? >>Yeah, absolutely. So they're doing, uh, what I like to call a workload appropriateness, uh, exercise. And as they think about recalibrating where those workloads live, exactly what I said before, they're looking at the strengths of the platform and, uh, lining up those application profiles to live in, in the appropriate place. We have a unique advantage, uh, because of our interconnection profile and our adjacency to public cloud platforms, where if people want to have application tiers that may be sent on both sides of the fence, if you will, uh, we have super, super low latency connections. You can connect, you know, layer two, uh, maybe out to AWS, um, and, you know, have your VPC on one side, have, uh, you know, dedicated single tenant environments on our side and have those applications interact with each other. And then in a super low latency fashion, >>Hey, lemme just ask a follow up question on that. Because I remember the Y2K days, there was a, a lot of activity, a lot of spending and then CIOs wanted to look at their portfolio and, and rationalize that portfolio. When you talk about workload appropriateness, are you seeing a similar application rationalization exercise going on or is it just a Hey can spending, >>Uh, absolutely. We're seeing rationalization and I think what's happening is folks are getting a little more savvy about forecasting, the growth of their application, uh, the growth of the data associated with it, what the cost may be associated with needing to move them around to different venues. Um, and so we're, we're definitely seeing people look at those numbers and make decisions about workload placement based on that analytics and, and kind of knowledge of what it means down the road and also where the data might need to live locally too. We're seeing people, uh, being a little more cognizant geographically around data where it lives and how that relates to where the computer associated with that data is. >>Yeah. Hey Randy, can you tell us a little bit more from a business perspective about the Dell partnership? How did that come about, you know, who does, what, what are the swim lanes overlaps? Maybe you can help us understand that. >>Yeah, so we're very excited about, uh, our Dell partnership, as you can imagine, with as many customers and many data centers, as we've got deployed, we have Dell, uh, located it in a large percentage of our customer environments. And so it's just natural that we work together to figure out how we can continue to meet, uh, our customer's needs. And so the core idea that I'm excited about around Dell is that Dell has an excellent technology platform in all fronts, they've got great compute and storage and all types of software solutions. And what we want to do is help them make their platform more on demand. And so what do I mean by that? If you think about the historical, uh, time, it takes to deploy a traditional colo environment from the time you spec the cage, do you ship the equipment, you install the network, you rack and stack the equipment, unload the cloud stack. >>It takes weeks to months to deploy. And so what we're doing is working very closely with Dell to look at our existing customers and new prospects that are interested in their platform and how can we pre-provision that capacity in, in the data center make it so it's already plugged into the data center already is powered up. It's connected to the network and a customer can purchase it on demand. And so the idea behind this is how can we give our customers all the benefits of Kolo, which is what, uh, Holland was talking about a minute ago, but deliver that platform at the speed of cloud. And that's really the essence of the partnership we have with Dell. Uh, we think it could be explosive. Uh, we think there's a lot of opportunity, not only, uh, for us, but also for Dell as they continue to retain their customers and their customers go through tech refresh cycles, if they can have on demand technology that they're already familiar with, they can get the benefits that you get from co-location at the speed of cloud. And that that's what our, the, the basis of our, our relationship. >>Yeah. Thank you. So Holland, I mean, Randy was saying one of the pillars of Dell tech world this year is the whole as a service thrust. And, you know, essentially what it is, my, my viewpoint is Dell's building out its own cloud. That's, you know, it's, it's its aspiration I think, is to connect on-prem to, through hybrid, to public clouds across clouds, out to the edge extract that all that complexity and you guys would be a key part of that from a, from a CTO's perspective, that's a different mindset. I mean, it changes the way we manage, think about procure, you know, spend, uh, um, and, and maybe that even the technical configurations of, of how we deliver and consume it, you give us some thoughts on that. >>Absolutely. Look, I think what we're doing is we're laying the foundation for a truly hybrid experience. Um, Randy mentioned, uh, us going through great lengths with our technology partners like Dell and make the data center consumable in an automated fashion. And so as we increasingly move into technologies like containers and using coordinators managers like Kubernetes, we really now have the ability to make a true hybrid experience. And if you think about the experience of deploying, you know, in a data center, whether it's your own or a co like ours, that was, you know, a 60 to 90 day conversation to, to get that infrastructure spun up. And so now if you can consume public cloud resources, just like we've been used to doing where you can swipe a card and get access to infrastructure in a matter of minutes or hours have the same experience with us, we've kind of closed that last mile of infrastructure delivery. And the other neat thing about this is, uh, if you have a cloud first mandate, if some of those workloads are running a ter data center, uh, we check all those same boxes, right? Uh, we, we have infrastructure that sits off X. We have a global platform. Uh, we have, you know, highly automated environment. So you can really now start extracting yourself a little bit from the infrastructure and start focusing on the important stuff, which the applications that sit on top. >>So from a security standpoint, you have a similar, you know, the cloud guys talk about the shared responsibility model. Is that a similar model that, that you guys have? Can you describe that? >>Yeah, it's, it's, it's very analogous to this shared responsibility model and, and public cloud. We give a little bit more control to our customers, like things like, you know, dictate maintenance windows. Um, we give a little bit more control in terms of access to the infrastructure. Uh, it's one of the reasons that organizations like running infrastructure with us is because we can hand off control to these certain things that the lower levels of the infrastructure stack versus that higher level of abstraction that happens with public cloud. >>And what, what kind of skills are you after, uh, these days? Is it people that can squeeze, you know, more power and, you know, more efficient cooling, uh, is it infrastructure management? You mentioned Kubernetes before. What, what matters to a company like yours from a skill standpoint? >>Yeah. And to terms of our staff, it is at the lower, uh, levels of the stack, if you will. So maybe going, you know, up to, uh, layer two or three, if we think about the OSI model. So certainly power engineering, cooling engineering, the stuff that physically runs our, our data center, that's our meat and potatoes. That's important to us, but as you consider our digital platform, um, certainly the networking, uh, know how knowledge of the entire stack, knowing how things are architected, understanding how cloud works, how understanding how cloud connectivity works. These are all super, super important skill sets. So we span the spectrum a bit. Um, but it's less on the upper ends of it, you know, kind of going up to layer seven, >>Although I'd imagine that data center automation is obviously a big part of your, your IP, right. Is that something that you have guys bring to the table? Yes. >>Yeah, it's actually one of our key innovations is around how we've architected our software platform, how we do our automation, uh, how we run our network. Uh, we we've, uh, built a, a super, super innovative SDN fabric that powers all of our Metro regions that enables the delivery, the infrastructure that hangs off of it. Um, so yeah, a huge percentage of our I P is around that software innovation and, uh, networking automation. >>Great. Randy, I wonder if you could close it out for us. Uh, I'd love your thoughts on where you'd like to see the Dell partnership go and any other, you know, information you'd like to leave the audience with. >>Yeah. I think you've asked a couple questions about the perspective from a CTO and the way that we want to build our solutions is if you are a CTO or if you're a cloud architect, what we are trying to build is a set of Legos to allow you to assemble your ultimate hybrid it solution to use a combination of traditional colocation, where you have equipment that you own, that you manage on demand, bare metal from great partnerships, like where we have with Dell, that can augment what you have in colo have access to a rich ecosystem of technology providers that sit in the same data center markets so that you can start to, to actually augment your it architecture with a lot of our, um, uh, solution providers that sit within our, our, our markets access to cloud OnRamp. So you get low latency access to public cloud to start to leverage some of the technologies they have, and also have the ability to switch, right? If you start with one cloud cloud provider, and at some point you find something more cost efficient, or a little bit more architecturally, uh, built that we can, uh, uh, facilitate that switch. And then also to have connectivity to all the different network carriers that we have. And so, and, and also to do it globally, right? And so our mission is to give the CTO and the cloud architect, the ultimate Legos, uh, to build their custom solution, it's highly, um, cost effective and meets all the technology requirements. >>Yeah. Hedging that risk and having exit strategies, I think is huge. Every, every customer needs to think about that, uh, before they, they dive into the cloud. Okay, guys, we gotta leave it there. Thanks so much for coming in the cube. Great discussion. >>Thank you. Thanks for having us. >>And thank you for watching our ongoing coverage of Dell technologies, world 2022, the in-person live version where we insert great deep dive interviews like this one that focus on key customer topics. Keep it right there. You're watching the cube.

>>We'll go back to the queue. It's continuous coverage of AWS storage day. We're here in Seattle home with the Mariners home, with the Seahawks home of the Seattle storm. If you're a w NBA fan your cloud migration, according to our surveys and the ETR data that we use last year was number two initiative for it. Practitioners behind security. Welcome to this power panel on migration and transfer services. And I'm joined now by Matt Matthews. Who's the general manager of AWS transfer a family of services sitting. Roy is the GM of the snow family. And Randy boudin is the general manager of AWS data sync, gents. Welcome to good to see you. Thank you. So, Matt, you heard my narrative upfront, obviously it's top of mind for it. Pros, what are you seeing in the marketplace? >>Yeah, uh, certainly, um, many customers are currently executing on data migration strategies, uh, to the cloud. And AWS has been a primary choice for cloud storage for 15 years. Right. Um, but we still see many customers are evaluating, um, how to do their cloud migration strategies. And they're looking for, you know, um, uh, understanding what services can help them with those migrations. >>So said, well, why now? I mean, a lot of people might be feeling, you know, you got, you've got a hesitancy of taking a vaccine. What about hesitancy making a move? Maybe the best move is no movable. W why now? Why does it make sense? >>So AWS offers compelling, uh, cost savings to customers. I think with our global footprint that our 11 nines of durability are fully managed services. You're really getting the centralization benefits for the cloud, like all the resiliency and durability. And then besides that you are unlocking the on-prem data center and data store costs as well. So it's like a dual prong cost saving on both ends >>Follow up on that. If I may, I mean, again, the data was very clear cloud migration, top priority F for a lot of reasons, but at the same time migration, as you know, it's almost like a dirty word sometimes in it. So, so where do people even start? I mean, they've got so much data to migrate. How can they even handle >>That? Yeah. I'd recommend, uh, customers look at their cool and cold data. Like if they look at their backups and archives and they have not been used for long, I mean, it doesn't make sense to kind of keep them on prem, look at how you can move those and migrate those first and then slowly work your way up into like warm data and then hot data. >>Okay, great. Uh, so Randy, we know about the snow family of products. Of course, everybody's familiar with that, but what about online data migration? What can you tell us there? What's the, what are customers thinking >>About? Sure. So as you know, for many their journey to the cloud starts with data migration, right? That's right. So if you're, if you're starting that journey with, uh, an offline movement, you look to the snow family of products. If you, if you're looking for online, that's when you turn to data, sync data thinks that online data, movement, service data is it makes it fast and easy to move your data into AWS. The customers >>Figure out which services to use. Do you, how do you advise them on that? Or is it sort of word of mouth, peer to peer? How do they figure it out that that's squint through that? Yeah, >>So it comes down to a combination of things. So first is the amount of available bandwidth that you have, the amount of data that you're looking to move and the timeframe you have in which to do that. Right. So if you have a, high-speed say gigabit, uh, uh, network, uh, you can move data very quickly using data sync. If, if you have a slower network or perhaps you don't want to utilize your existing network for this purpose, then the snow family of products makes a lot of sense. Call said, that's it? Call center. That's >>My answer. Yeah, there you go. Oh, you'll >>Joke. Right. See Tam that's Chevy truck access method. You put it right on there and break it over. How about, you know, Matt, I wonder if we could talk maybe about some, some customer examples, any, any favorites that you see are ones that stand out in various industries? >>Yeah. So one of the things we're seeing is certainly getting your data to the cloud is, is important, but also customers want to migrate their applications to the cloud. And when they, when they do that, they, uh, the many applications still need ongoing data transfers from third parties, from ex partners and customers and, and whatnot. So, great example of this is, uh, FINRA and their partnership with AWS. So a FINRA is the single largest, um, uh, regulatory body for securities in the U S and they take in 335 billion market events per day, over 600,000 of their member brokers, registered brokers. So, uh, they use, um, AWS transfer family, uh, secure file transfers, uh, to get that data in an aggregated in, in S3, so they can, um, analyze it and, and, uh, really kind of, uh, understand that data so they can protect investors. So that's, that's a great example. >>So it's not just seeding the cloud, right? It's the ongoing population of it. How about, I mean, how do you guys see this shaping up the future? We all talk about storage silos. I see this as, you know, the cloud is in some ways a silo Buster. Okay. We've got all this data in the cloud now, but you know, you can not apply machine learning. There are other tooling, so what's the north star here. >>Yeah. It's really the north star of getting, you know, we want to unlock, uh, not only get the data in the cloud, but actually use it to unlock the benefits of the cloud has to offer. Right. That's really what you're getting at, aggregating all that data, uh, and using the power of the cloud to really, um, you know, harness that power to analyze the data. It's >>A big, big challenge that customers have. I mean, you guys are obsessed listening to customers, you know, w what kinds of things do you see in the future? Sid and Randy, maybe, maybe see if you can start, >>Uh, I'll start with the I'll kind of dovetail, on example, a Matthews, uh, I'll talk about a customer join, who moved 3.4 petabytes of data to the cloud joined was a streaming service provider out of Germany. They had prohibitive on-prem costs. They saved 500 K per year by moving to the cloud. And by moving to the cloud, they get much more of the data by being able to fine tune their content to local audiences and be more reactive and quicker, a reaction to business changes. So centralizing in the cloud had its benefits of access, flexibility, agility, and faster innovation, and faster time to market. Anything you'd add, right. >>Yeah, sure. So we have a customer Takara bio they're a biotech company. Uh, they're working with genome sequencing, right? So data rich information coming out of those sequencers, they're collecting and analyzing this data daily and sending it up into AWS for analysis, um, and, uh, by using data sync in order to do that, they've improved their data transfer rate by three times. And they've reduced their, uh, overhead six by 66% in terms of their process. >>Guys get, must be blown away by this. I mean, we've all sort of lived in this, so I'm prem world and you sort of lay it out infrastructure, and then you go onto the next one, but the use cases are so diverse. The industry, examples. Matt will give you the last >>Word here. Yeah, no, w w what are we looking to do? You know, we, we always want to listen to our customers, uh, but you know, collectively our, our services and working across other services, AWS, we really, uh, want to help customers not only move their data in the crowd, but also unlock the power of that data. And really, um, you know, uh, we think there's a big opportunity across their migration and transfer services to help customers choose, choose the right service, uh, based on their, where they are in their cloud migration, uh, and, and all the different things they're dealing with. >>I've said a number of times the next 10 years is not going to be like the last 10 years. It's like the cloud is growing up. You know, it's out of the infancy stage. Maybe it's an adolescent. So I don't really know exactly, but guys, thanks so much for coming to the cube and sharing your insights and information. Appreciate it. And thank you for watching everybody keep it right there. More great content from AWS storage day in Seattle.

>> From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Hello everyone, David Vellante here and welcome to the special CUBE conversation with a colleague and friend of mine, Randy Seidl is a accomplished CEO, he's an executive, sales pro, and he's a founder of the Sales Community, this newly formed social network, Randy, good to see you again, welcome. >> Hey, great to see you, it's been a lot of great years, great relationship with you and congratulations with all your success with SiliconANGLE and theCUBE. I was remembering back, I think it's been probably since 1985, so 35 years ago when we were both Cub Scouts, I was at EMC, and you were at IDC. >> Yeah, I mean, first of all, I love where you are, your man-cave there, we heard you held a great little networking event that you do periodically with some of our joint colleagues. And yeah, wow, we were both in our twenties, I was a young pop and Dicky Eagan, and Jack and Mike, and they would have me talk to you guys, you know, sort of brief you on the market, what little I knew now looking back. But wow, Randy, I mean. >> We knew! >> Right, I mean, and then just the whole thing just took off, but we had a good instinct, that storage was going to matter, everything back then was mainframe and IBM was the king of the world, and then you guys just crushed it. Wow, what a run, amazing. >> Yeah, absolutely. >> So tell me about Sales Community. What are you trying to accomplish with this new social network? >> Well, it was kind of really my COVID moment. I was talking to Peter Bell I know, you know well as well, and it was right in the beginning of COVID we were kind of comparing notes and long story short, he said, hey Randy, you do all this work with these technology companies, and channel partners, and use your customers, CIO, CTO, CSOs, but you're really not doing much for those that you know the best, which are really technology sales professionals, CROs, STRs kind of up and down the food chain. And that really got me thinking, then he introduced me to one of his companies that sells to CROs and I was going through with them and they were kind of calling me on the carpet saying, okay, do I really know these people? I'm like, oh my gosh! They basically just said, I'm a dope, I haven't really done anything here. So, one thing led to another and ended up developing a Sales Community, a big thing and big help for me was talking to probably 150 or so during the course of the summer, CROs, VPs of sales, Reps STRs to really kind of help get some feedback from them in terms of I caught now they call product-market fit, but kind of what they think it's missing, what's needed, what are their teams need, what do they want? So, it's kind of all a perfect storm, which to be honest without COVID probably wouldn't have created Sales Community. >> Well, I joined and it was a great onboarding experience and love participating with colleagues. I mean, sales is hard, I mean, you've got your ups and your downs and you just got to keep pressing on, but who's participating in Sales Community. >> We're targeting STRs on up to CROs and the kind of the tagline is learn more so you can sell more. We have a lot of great different kind of content areas and we're going to kind of bob and weave based on the feedback that we get, but we've got some great virtual events and interviews. We have an executive coach, Tony Jerry, who's doing nine sessions on designing your life. We did a recording, a live session last week on personal goal setting. We did one yesterday, it was a live session that'll be posted shortly on strategic health. Next one's on branding, so that's not necessarily specific to tech sales, but kind of adding value. We also have Dave Knorr, another executive coach doing a weekly interview series that we're calling tech sales insights with some of the leading CROs, CEOs, Jim Sullivan, who I know you know well, he's going to be the first one, it's going to be next Wednesday, he runs a NWN and he's done a lot of great things and a lot of other great leaders from there. Also still on the interview virtual events side, Michael Cotoia from Tech Target he's going to do a CMO insights series. His Tech Target International editors are also going to do regional ones. So CIO interviews from AMEA, Asia Pac, Latin America, Australia, also on the CSO side, we have somebody focused on doing a CSO interviews, Paul Salamanca of channel interviews, I think this channel, by and large gets missed a lot. CEO's and then Steve Duplessie, I know you know well as well is going to do and focus on CIO, sub-CIO insights, but basically creating virtual events and interview series that are really targeted at people that we sell to. So that covers the kind of virtual event and interview side. And I maybe more quickly go through some of the other key segments. So another one is a content library. There's the guy who's a STR at ServiceNow went through, send me note the other day that said, hey, I found out you have some great feedback on prospecting cold calling, I shared it with my team helped me a lot. So a lot of good things in terms of content library, also opportunity to network. So you could be say selling to Fidelity, you could send a note to the community and members and say anybody else trying to sell the Fidelity, let's network, let's compare notes, also great opportunities for channel partners. So channel partner could raise their hand and say, hey, I know Fidelity, let me help with you. A lot of sharing of best practices. And also just in terms of communication, slack channels, and then opportunities to create round tables. So you might have CROs from startups that want to have maybe six to 10 of them get together. So they can kind of commiserate, ask questions, you could have CROs, companies that are maybe transforming going from on-prem to kind of SAS model. So a lot of different great things, ultimately really to serve the folks in the tech Sales Community. >> Yeah, it sounds like, I mean, first of all tons of content, the other thing I like about it is we all read books on sales, some of them are so like gimmicky, some of them are inspirational. Some of them have really great suggestions. Some of them can be life changing, but what's always been missing in my opinion, is this notion of a network, a social network, if you will, where people can help each other, you just gave a ton of good examples. So you're really trying to differentiate from a lot of the things that have worked over the years, but have really sort of one way communication, some sales guru either training or you're reading his or her book. >> Yes, and we're also fortunate on the content side, we have some of the best kind of consulting sales methodology companies that love what we're doing. So they're likewise providing a lot of content and as you said, it's crazy. You think of any other industry, restaurant, hotel, lawyers, landscape, they have these big, kind of user groups, even technology companies user groups within the larger field of technology sales enterprise B2B sales, there's really nothing that looks like this that exists. So far the feedback's been great. >> Well, so just to what you're describing, I mean, I've known you for a long, long time, and one of the principles of great salespeople is, you help others, right? You make as many friends as you can, and you're the master of that. But essentially you're bringing a lot of the things that have worked, a lot of the principles that have worked in your career to this community. Maybe talk about that a little bit. >> Yeah, I mean, especially I think some of the younger sales folks, it's not kind of off the cuff as we know, but it's really kind of training, being disciplined, being prepared, what are you going to do, how are you going to do it in this COVID moment? You know, I'm seeing lots of friends where the companies that have great relationships, they can do really well and kind of lean in a lot. If you're kind of cold calling and this environment, and it's tough, so kind of, how can you be best prepared, how can you do the best homework? How can you have the kind of right agenda, when you're going to do the sales calls? And then it's not really as much follow up, but really follow through in terms of what you do afterwards. So kind of what is the training? What can you do, how can you do it? And, you know, it's crazy, a lot of companies spend lots of money on training, but if you think about it they're really tied in specifically to tech sales, hopefully this will be great. Plus being able to just kind of throw out questions here and there works out well as well. >> Well that's what I'm looking forward to, say, hey, I got some challenges, how do others deal with this? You know, one of the things that is, I think, paramount to being a great salesperson is the attitude you hear it all the time. How do you stay pumped up? (laughing) Like I said before, we've all been through ups and downs, and what do you tell people there? >> In terms of staying pumped up, interestingly enough, the session we did yesterday on strategic health, probably plays a key role. So yeah, there's the work aspects and how are you going to focus and wake up and get fired up. But ultimately, I think you really got to take several steps back and saying are you taking care of yourself? Are you sleeping, are you eating and drinking correctly? Are you drinking enough water, are you exercising? So, in this moment, I think that's probably something that gets missed a lot in terms of getting fired up. And then ultimately just being excited about kind of what you're doing, how are you doing it, taking care of the customers and serving those around you. And you had mentioned in terms of giving it back, but a lot of us that have been around, love the idea of kind of paying it forward, helping out others and seeing a lot of the great younger folks really rise up and become stars. >> I think that's one of the most exciting things is somebody has been around for awhile. Like (laughing) we all get cold calls and say, hey, how you doing today? You know, (laughing) you really had that dead air, and you actually want to reach out and help these individuals. A lot of times they'll call you, they have no idea what you do, well I've read your website, and I think we'd be a great fit for, you know, something that would not be a great fit. So, there's a level of preparation we always talk about in sales, you got to be prepared, but there's also sometimes... I was talking to a sales pro the other day, you know, sometimes you can over prepare he said, I've been on sales calls, I prepare for hours and hours and hours, and then they get there, and it was just a lot of wasted hours. I probably could have done it in 15 minutes. I mean, so there's a really a balance there. And it comes with experience, I guess. >> Yeah, I mean, I don't know how anybody could prepare hours and hours, so that's a whole different subject to think. >> Well, he said, my technique now is just 15 minutes before the call I'll jump on and just, you know, cram as much as I can. And it actually, it worked for him. So, different approaches, right? >> Yeah, absolutely. The other thing I'd like to mention is the advisory board I'm fortunate to have a work with, and be friends with several of the best in industry like you. So if anybody goes to the website, you can click on an advisory board and there's a 200 plus and haven't count them exactly. But you know, some of the best in technology, we've got them sorted on the sales side and the channel side, the consulting side, the coaching side, analyst side, but, really just such a tremendous each head of talent that can really help us continue to go and grow and pivot and you're making sure that we are serving our Sales Community and making sure everybody's learning more so they can sell more. And then I guess I should add onto that also, earning more and making more money. >> So I got to ask you where you land on this. I mean, you're a sports fan, I am too and for a while there once the "Moneyball" came out, you saw Billy Bean and it was this sort of formulaic approach. The guy, you know, we would joke the team with the best nerds would win. But it seems like there's an equilibrium. It used to be all gut feel and experience, and then it became the data nerds. And it seems like in our industry, it's following a similar pattern, the marketing ops, Martech, becoming very, very data driven. But it feels to me, Randy, especially in these COVID times that there really is this equilibrium, this balance between experience, and tribal knowledge, gut feel, network, which is something you're building and the data. How do you see that role, that CRO role, that sales role evolving, especially in the context of what I just talked about with the data nerds? (laughing) >> Yeah, absolutely, I think I heard two points there since you brought up Billy Bean, I forgot the guy's name, but in the movie is kind of nerd. I've got Jesse and Tucker who have been tremendously helpful for us putting together a Sales Community. But to answer the question on the CMOs side, the CMOs out there frankly not going to like this answer, but I think more and more, you see CMOs and CROs kind of separated and it's kind of different agendas, my belief is that eventually the CMO function or marketing is really going to come under sales and sales are really going to take a much more active role in driving and leveraging that marketing function in terms of what's the best bang for the buck, what are they doing, how are they doing it? And I've got a lot of friends, I won't name names, but they're not on the sales side and they're doing what they can, but they just see what I'd call it kind of wasted money or inefficiencies on the marketing side. So, if I maybe I spin that a different way, I think given kind of analytics and those companies that do have best practices, and I write things on the marketing side, you know, they're going to continue to go and grow, you know, on cert with the right sales team. So I think that you bring up a great point and that area is going to continue to evolve a lot. >> Does that principle apply to product marketing? In other words do you feel like product marketing should be more aligned with engineering or sales and maybe sales and finance, where do you land on that? >> Yeah, I mean, I'm kind of old school, so I go back to Dick and Jack and Roger and Mike Rutgers, and you all in terms of, hey, you have those silos, but you get everybody at the table, kind of what we're working well together. It is interesting though in today's world, the PLG, Product-Led Growth models, where a lot of companies now are trying to get in maybe almost like a VMware, maybe BMC did in the early days where you're kind of getting into the low level developers and then kind of things bubble up so that you think Product-Led Growth model, having a lower cost insight sales model, works when I'll say the kind of the product sells itself. But I would argue, that I think some of those PLG led companies really miss out on leveraging the high end enterprise relationships, to kind of turbocharge and supersize and expedite larger sales deals, larger (indistinct). >> Well, and you mentioned earlier a channel you said a lot of times that's overlooked and I couldn't agree more, channel increasingly important. That's where a lot of the relationships live, it gives you scale, it just gives you a lot of leverage, maybe you talk about the importance of channel and how it relates to Sales Community. >> Yeah, I mean, it's interesting they're really unto themselves, there's some things that are channel channel, but if you think about, you know, go to market tech sales, pick the company on average is probably half of the business goes through the channel. And it used to be way back when just kind of fulfillment, but now the best companies really are those that have the right relationships, that are adding value, that can help on the pre sales, that can help on the post sales, that can help kind of cross sale. You know, if I'm a customer, I don't want to deal with whatever five or 10 different vendors if I can have a one stop shop with one bar solution provider, partner, SI, or whatever you want to call them, you know, that certainly makes life a lot easier. And I think a lot of companies almost been kind of a second class citizen, but I think those companies that really bring them into the fold as really partners at the table, whether it be an account planning sessions, whether you're doing sales calls, but kind of leveraging that I call it a variable cost kind of off balance sheet, sales force really is where the future is going to continue to go. >> So you've been a successful individual sales contributor. You've been a CEO, you've run large sales organizations. I mean, you basically ran sales at HP for Donna Telly, and so you've seen it all, and you've been helping startups. When you look at hiring sales people, what are the attributes that you look for? Is it intelligence, is it hard work, is it coach ability? What are some of the things that are most important to you, and do you apply different attributes in different situations? What are your thoughts on that? >> Great question in a little plug, maybe for a recruiting business, top talent recruiting, (laughing) but one of the key things that we do, which I think is different from others in the recruiting side is the relationships. So a lot of people don't dig in, when we're talking to candidates, they say, well, nobody really asked me this before. And I would argue a key differentiator, and this is way before COVID, but especially now with COVID is okay, who do you have relationships with? So I could be talking to a candidate that maybe somebody is hiring, wants to cover financial services in New York. And then I'll say, okay, well, who do you know what City JPB Bay and I'll know more people than they know. And I'll probably say, just so you know, that's weird me up in Boston. I know more than the council you probably know the best. So really trying to unearth, really kind of who has the right relationships and then separate from that in terms of a reference check, being able to reference checks sooner in the process with somebody that know well firsthand, as opposed to second hand. And a lot of times I've seen even some of the larger, more expensive recruiting firms, you're kind of wait until somebody is the final say, when do an offer, then they do a reference check and they do the reference check with somebody that they don't know. And to me, I mean, that's totally useless which quite with LinkedIn today, I could be say if we're looking at you for candidate, maybe a bad example, but I don't know, we probably have a 1000 in common, and from those, we probably have 200 that we both know, well, that I could check. And when you do reference checking, it's not a maybe it's either, hey, the person is a yes, or the person's a no. So trying to do that early in the process, I think is a big differentiator. And then last and probably third piece I'd highlight is, if it's a startup company, you can't get somebody that's just from a big company. If it's a big company role, you can't get somebody that just from a small company, you got to really make sure you kind of peel back the onions and see where they're from. And you could have somebody from a big company, but they were kind of wearing a smaller division. So again, you have to kind of, you can't judge a book by the cover. You got to kind of peel back the onion. >> So Randy, how do people learn more about Sales Community? Where do they go to engage, sign up, et cetera? >> Absolutely, it's salescommunity.com. So it should be pretty straight forward. A lot of great information there. You can go subscribe, and if you like it spread the word and a lot of great content and you can ping me there. And if not I'm randy@salescommunity.com. So love to get any feedback, help out in any way we can. >> Well, I think it's critical that you're putting this network together and you are probably the best networker that I know I've seen you in action at gatherings and you really have been a great inspiration and a friend. So, Randy, thanks so much for doing the Sales Community and coming on theCUBE and sharing your experience with us. >> Great, thanks Dave, appreciate it. >> All right you're very welcome and thank you for watching everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (upbeat music)

(upbeat music) >> Announcer: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Stu: Hi, I'm Stu Miniman and welcome to this special Cube presentation. We're talking with Pensando, and their event is "Future Proof Your Enterprise", to help us really understand where the company is, and the partnerships, what they're hearing from customers. Really happy to welcome back to our program Randy Pond, he's the Chief Financial Officer at Pensando. Randy, thanks so much for joining us. >> Randy: My pleasure, thanks for having me. >> All right, well Randy, obviously today, we're talking to people everywhere, they're remote so, not quite as plush as the last time we talked to you at the Goldman-Sachs office, in New York City, beautiful view in the background. That was a great backdrop, when you talk about bringing a company out of stealth, John Chambers there, your chairman, Antonio Neri >> Yeah Neri. >> Talking about the investment in the partnership. And Goldman-Sachs, an excellent customer there, here we are little bit more than six months later and that partnership with HPE is taking the next step. You've got the general availability, this month, of the HPE Proliant with Pensando Solutions. Bring us up to speed a little bit though, we'll talk about HPE maybe in a second but, your customers, your progress, you had, I believe it was up to your C round of funding, when you came out of stealth so, give us your viewpoint as to where the company is today. >> So today, I think, we're sort of, divide the conversation between financial and a business perspective. So financially, we're in great shape, the C round came together very well, we were way over subscribed. We raised our limits to secure additional funding, which has worked out really well, getting where we are currently with the pandemic. So financially, we're in great shape, our case burn has held steady and we've done a good job of forecasting, that's why I thing the Bird's pleased. From a business perspective, we've done a really good job delivering on our real maximum product perspective. So, the team has released the cloud production, we released the cloud to customers about a month or two ago. We just did a release to the enterprise space, through HPE. We got another release coming up the end of this month. There's releases scheduled for Q3 and Q4 of this year. Our second ASIC will come back, I think, the 15th of June, so we're going to get access to our new design, I think that's great news. You know our cloud customers are excited about that 'cause it provides a little more capability than the current device does. And we had a great Q1 and we're off to a great start on Q2. We overachieved in Q1, we look like we're going to overachieve again in Q2, both in terms of units and dollars, so we're in a pretty good place. >> Yeah, I'd like to see if we could break down say kind of the financial and the business piece. On the financial side piece, you've worked with this team for quite a long time, there's got to be a different financial model that you put in place when you know that you've got, really, your exit built in, add from the three spin-ins before, proof the product, get it out there and then, well, I've got an in-house feed with a full panel there, as opposed today. Is the model we should be thinking, what percentage of that is OEM? You talk about there's the cloud model, and the enterprise model and, how do you structure things a little bit differently for that type of model versus, maybe, what the spin-ins were or a traditional start-up. >> Sure. >> that might have a different, a few different models to choose from? >> So, we're much closer aligned to a traditional start-up environment. Now, the one unique point is the HPE relationship because they've been my partner, they are my primary go to market partner in the enterprise space today but, they're also a strategic investor. So, the reality is, in the enterprise space we have to sell the product through the OEMs, the average enterprise customer doesn't have the capacity to install themself. But that is a very different model than it is in the cloud side. So, it's an indirect sales model, most likely through HPE and other server providers, like Dell, Cisco possibly, and Super Micro. Every customer has their sort of, requested server manufacturer. On the cloud side, individuals build their own so, that's a, I ship to them and they install it themselves, it's a different software model, it's a different manufacturing model as in, we have a more traditional direct sales model on that side, but we've got a partner middle model on the enterprise side today. We've set 'em up as both, HPE sort of serves like a quasi Cisco environment for us, because we're depending on their engine to find our leads, and it's worked out really really well. >> Excellent, maybe bring us inside a little bit, where you are with (away from microphone) about customer acquisition leading up to now and what's the expectation now that HPE is fully ready to roll. >> So, we, I'm going to start the conversation again. There's the cloud side, so on the cloud side we have three committed customers today. One is in production, the other two are going into production later part of this year, they need the release we're going to give them in September/October timeframe but they've committed to us from a design perspective. And then there's a follow-on generational product in '21 where they really ramp hard. I already have a bind contract with two, I'm working on the third. And, on the enterprise side, we're modeling ourselves after the top 200 HPE customers right now. They normally align themselves around financial services, pharmaceuticals, transportation, sled, we're working through those customers. We have active talks with many of them today, they're in our sales pipeline, we manage that relationship together. Generally, HPE opens the door, we explain the technology to the technical team, they say they can see a place for us and they let us stand up a plat, and then we go from there. >> Excellent, so Randy we referenced the global pandemic going on right now. It's been a bit of a bifurcated model in the tech world. Though it's been definitely a tailwind, somewhat, from the cloud standpoint, there's many infrastructure pieces that have seen an immediate acceleration, things like work from home technology. So, there's certain devices and certain deployments. And there's other things that, of course, we put a pause button trying, too much uncertainty out there. What are you seeing at the market and how's that impacting you, as a relatively new start-up? >> Yeah, so in general, your point is well taken. The cloud players are telling us their demand is up dramatically and therefore the signal they're sending us is, they want to accelerate deployment and it's likely it's going to be bigger than we originally had estimated so, that's been great news for us. In the enterprise space it's really very different, you know we're not selling a lot of product to Walmart, or Gap, or the retail space, they're struggling mightily, any hotels, motels, Carnival Lines is not buying our product today. But, if you look at the financials, if you look at the pharmas, their demand's up quite a bit, they're both buying ahead a little bit to hedge their bets in the supply chain, for the situation today, and they're actually seeing the real demand go up. And, the banks especially have seen it go up 'cause their work from home has gone through the roof. So, it's been a good opportunity for us to sort of seize the moment and demonstrate how we can be part of their new implementations, and bring new services to 'em. >> Yeah, Randy, wonder if you can actually give us, a little bit, that voice of the customer and what is the problem you're solving? Because, we talked about, there's certain immediate initiatives that accompany the era, absolutely like, today, security is more important than ever. When people are working from home, the bad actors actually are trying even harder to get involved there, we talked a little bit about cloud, so what is that itch that Pensando scratches and, therefore, how do you fit into the current landscape? >> Sure, you know, with our customers today there's similar problems and dissimilar problems, between the cloud and the enterprise. The similar problems is that Pensando quickly solves things, like East West security inside of their environments, their computer environments, which is difficult to do today, it's expensive and difficult to do today. We've provided pervasively and wire rate, and that's sort of an easy sell, initially. Another one that's been pretty easy for everyone to look at is observability and telemetry because of where we're positioned, in the computer space, we see every packet, which provides us with a lot of knowledge about what's going on in their environment. So, that's been a pretty easy initial sell. In the case of the enterprise customers, we can sell other pieces of their solution that are either expensive, or introduce latency or management problems. Whether it's firewall technology, or load balancing technology, or micro segmentation technology, all of which we can do inside of our blade. And today it's done either through appliances or through virtual machines consuming CPUs. In the cloud space, we do all of that, plus we allow them to download their own image into our devices today, which is pretty powerful, we have a lot of memory and we have a lot of capacity, from an Arm core perspective. And we allow them to pick and choose the features and functionalities they want, and then run everything at wire speeds, at much faster speeds. The enterprise is running 10/25, the cloud partners are running 25/50 going to 100, where we're even more compelling, we think. >> Randy, want to get back to talk a little bit more about HPE. You spent long time working at Cisco, for a good part of that HPE was one of your bigger partners on that. So, tell us what it's like working with HPE, any compare/contrast would be welcome. >> You know, it's interesting, so the cultural environment of HPE, under Antonio Neri, is very similar to what we saw at Cisco. And he and John have a phenomenal relationship, it's a very collegial environment, it's a very bright environment. They move quickly, for a big business. Where it's vastly different is they are much tougher on the numbers side because they're under much more margin pressure, and compounded pressures, that we never had (chuckles) at Cisco, just in all fairness to them. But, if we look through the organization, like the executive that was assigned to our account, from a sales perspective, used to work at Cisco. I think one or two of his guys used to work with Cisco. There's program management people that used to work with Cisco, there're people in engineering that came from Cisco so, it's an environment that's similar enough that it's easy enough for us to navigate. And, we're connected sort of on all levels, which has really been useful, and we have a weekly standing dialog across all the different functions. So, we're pretty deeply embedded with HPE right now and it's gone very very well. >> Yeah, you said that, even with the global pandemic right now, that Pensando is a bit ahead of where you expected shipments to be. I'm curious always, when I talk to a CFO, how do you see macroeconomic impact of what is going on there? Any concerns on your end about supply chain, either for yourselves or for partners, like HPE? How do you see what we're currently going through and the recovery future? >> So, it's an interesting question. You know, getting this pandemic sort of processed through the supply chains like a pig through a python, there's just no way to get around it. I mean, you know we had the first breakdown when they closed the country of Malaysia and I just couldn't build final product. They literally just shut the place down so, it took us about 10 days to get ourselves up and running, from a skeleton perspective. The government worked with us, they let a small crew come into our manufacturing partner to get some finished goods off for one of our OEM customers. As we've come back up, we've seen lead times extend on some of the custom parts, it's just a fact of life. I think there's a little bit of an artificial demand that's driving the supply chain a little bit crazy right now because now people are panicked that what happens if it comes back, will I get caught again, can I get enough inventory to buffer myself for, you know, two weeks to three or four months, depending on how aggressive you want to be, or conservative you want to be in that space. And then, I think, as the supply chain trickles back online, you end up discovering that yes, I can build final product, and I can get the Asics, and the memory, but now I want to buy some, you know, RS232 devices and it turns out that sure he's got 'em but the magnetic, that goes inside of it, that comes from Western China, they aren't quite up and running just yet. But we're seeing legacy problems, nothing catastrophic, nothing that's been painful. We've had to move some work around to get an incremental volume for ourselves, we've added fab vendors, and a few other things. So, it's really made us focus on second sourcing everywhere we can because we thought we were small enough, and the volume perspective wasn't that big a deal, we'll just get second sourcing once we get the product to market. That's heated back up and we're doing all that work now. So, I think, knock on wood, our recovery has gone very well we don't see any big problems in the supply chain. Now, I think, the bigger the player, like an HPE, and the longer the window they were shut down, the harder they pull when they turn the supply chain back on. But I think the big players, Cisco, HPE, and others it's going to take them a longer time, I think, to really see how this trickles all the way through, 'cause you can't really get good visibility how much safety stock or buffer stock does everybody have, at every level of the chain. So, everybody pulls at once, you run dry in a week, a month? Is it fast enough to recover, from a production perspective? All those things, I think, they're still not quite resolved yet. >> Just one other related aspect of the pandemic, that I would love your viewpoint on. You know, work from home, obviously, is what everyone is doing right now. I'm curious if you think that, what the recovery would look like from that standpoint, is there anything from Pensando that makes you shift where you think about hiring it? I've been to the Cisco headquarters and the long street, with a lot of buildings, and a lot of people. And everybody's wondering, will that headquarters, and centralized structure, that we had before, is that forever changed? >> You know that's a great question. So, it's for certain changed, I think, in terms of therapeutic, or a vaccine, for the current covid virus. So, that's just a fact of life and we've been comparing notes with a lot of other companies about what they're doing to bring the workers back, who want it, who are comfortable and want to come back to work. 'Cause, even inside of Pensando, I've got some folks who're like, "Listen, I'm not comfortable coming back, "I've got kids at home , I don't want to take the chance." That's fine, we don't have a problem with that. And, quite frankly, we can make a case that, in some of our functional areas, we're more productive than we were before the pandemic. In India specifically, this has been a boon for us because they're not getting on and off buses, they're not spending three or four hours trying to get back and forth to work, they're happy working from home, we're happy having them at home. The guy who runs India for us says productivity's up, and employee satisfaction couldn't be higher. Our plans now is, we have to bring a small team back into our headquarters, in Milpitas, to bring up our new Asic. But, that's going to be 15 to 20 people, and not all at one time, we're going to spread them out. We're already articulating what parts of the building can and can't be used , one way hallways, masking, temperature taking, everything you would expect. The next phase for us is some sort of rotational work where we'll say, "We're going to bring 25% of the people in, "30% of the people in, you work the week, you're off "for two, you work the week you're off two." And so we can get through the back of this thing, it's unlikely, it's almost impossible, in my mind, we would bring back 100% of our employees in the building. Now, does that change the view longterm? It's a great question because, I think what it's forced us to do is to get more comfortable with remote work, so that we can truly make it an option of any one employee, in specific areas. Like, the lab guys have to be in the lab, and the IT guys got to be in the computer room, but if you're a software developer, or if you're a marketing guy, do you really have to be in the building? And I think it's pushed us to really learn to manage them more effectively, with remoteness. And I think it provides us, at least, with options going forward. When I hire the next 100, do I have to put 'em in a building someplace or do I just deal with them where they are and bring them into the fold? We've brought on dozens of people, since the pandemic started, and quite honestly, we onboard 'em , we train 'em, and we mainstream 'em remotely and it's worked out great. >> Excellent, all right Randy let's bring it back to the HPE partnership for the final question. >> Sure! >> Tell us what we should be looking at, through the rest of this year, what the general availability of this means to your business and the impact you expect it to have on your customer. >> So, from an HPE perspective, I think this is going to be great innovation that they're bringing to the marketplace, to their customer set. It allows them, I think, to separate themselves from the market, at least for some period of time, until the other players get pulled along by the end users. Their product has a pretty steep ramp, their front half and the back half of the year, for us, are dramatically different, in terms of size and ramp. And it really sets us up for a very large, we hope, fiscal '22, which , for us, will end in January 31st of '22. But we're going to know, I mean we go GA in just a few weeks and we're going to get a sense if we can turn these POCs into end customers. And we're also going to see the ramp of the cloud customers in Q4. So, you know, I really feel like, both for us and for HPE, the next three four months, as we start getting back to some regularity of interacting with customers physically, not just remotely, and we see the early benefits and some of the early profit ownership analysis on deployment erect technology. This could be dramatic for us and for them, quite honestly. >> All right, well Randy Pond, CFO of Pensando, thanks so much, really a pleasure catching up with you and getting to discuss about how Pensando's helping to future proof your enterprise. >> Thank you much, my pleasure, have a great day. >> All right, I'm Stu Miniman, check out theCUBE.net for all our coverage, thank you for watching, thank you. (soft music)

from New York City it's the cube covering welcome to the new edge brought to you by pensando systems hey welcome back here ready Jeff Rick here with the cube we are in downtown Manhattan at the top of goldman sachs it was a beautiful day now the clouds coming in but that's appropriate because we're talking about cloud we're talking about edge and the launch of a brand new company is pensando and their event it's called welcome to the new edge and we're happy to have since we're goldman the guys who have the money we're barry Eggers a founding partner of Lightspeed ventures and randy pond the CFO a pensando gentlemen welcome thank you thank you so Barry let's start with you you think you were involved at this early on why did you get involved what what kind of sparked your interest we got involved in this round and the reason we got involved were mainly because we've worked with this team before at Cisco we know they're fantastic they're probably the most prolific team and the enterprise and they're going after a big opportunity so we were pleased when the company said hey you guys want to work with us on this as a financial investor and we did some diligence and dug in and found you know everything to our liking and jump right in didn't anybody tell them this startup is a young man's game they mixed up the twenty-something I think yeah they sort of turned the startup on its head if you will no pun intended that's going right yeah yeah and Randy you've joined him a CFO you've known them for a while I mean what is it about this group of people that execute kind of forward-looking transformation transformational technologies time and time again that's not a very common trait it's a it's a great question so you know the key for these guys have been well they've been together since the 80s so Mario look and primitive this is the 80s I work with them at their previous startup before Christian two ladies and they're the combination of their skills are phenomenal together so you know one of them has some of the vision of where they want to go the second guy is a substantive sort of engineer takes it from concept first drawing and then the Prem takes over the execution perspective and then drives this thing and they've really been incredible together and then we added Sony at crescendo as a as a product marketing person and she's really stepped up and become integral part on the team so they work together so well it just makes a huge difference yeah it's it's it's amazing that that a that they keep doing it and B that they want to keep doing it right because they've got a few bucks in the bank and they don't really need to do it but still to take on a big challenge and then to keep it under wraps for two and a half years that's pretty pretty amazing so curious Barry from your point of view venture investing you guys kind of see the future you get pitched by smart people all day when you looked at John Chambers kind of conversation of these ten-year kind of big cycles you know what did you think of that how do you guys kind of slice and dice your opportunities and looking at these big Nick's yeah going back going back to the team a little bit they've been pretty good at identifying a lot of these cycles they brought us land switching a long time ago with crescendo they sort of redefined the data center several times and so there's another opportunity what's driving this opportunity really is the fact that explosion of applications in the network and of course east-west traffic in the network so networks were more designed north-south and they're slowly becoming more east-west but because the applications are closer to the edge and networks today mostly provide services in the core the idea for pensando is well why don't we bring the service deliver the services closer to the applications improve performance better security and better monitoring yeah and then just the just the hyper acceleration of you know the amount of data the amount of applications and then this age-old it's we're going to use the data to the computer do you move the compute to the data now the answer is yes all the above so you got some money to work with we do you got a round that he could be around you guys are closing the C round so I think 180 people approximately I think somebody told me close enough so as you put some of this capital to work what are some of your priorities going forward so we will continue to hire both in the engineering side but more importantly now we're hiring in sales and service we've been waiting for the product quite frankly so we've just got our first few sales guys hired we've got a pretty aggressive ramp especially with the HP relationship to put people out into the field we've hired a couple guys in New York will continue to hire at the sales team we're ramping the supply chain and we've got a relative complicated supply chain model but that has to react now that we're going to market all that might be pretty used to do that we're changing facilities we need to grow we're sort of cramped in a one-story building open up one floor of a building right now so the money is going to be used sort of critically to really scale the business down they can go to market okay but a pretty impressive list of both partners and customers on launch day you don't see Goldman HPE Equinix I think it was quite a slide some of that is the uniqueness of the way we went to market and did the original due diligence on the product and bringing customers in early and then converting them to investors you end up with a customer investment model so they stayed with us Goldman's been through all three rounds we've been about HP and last model we had NetApp has been um two rounds now so we've we've continued to develop as a business with this small core group of customers and investors that we could try to expand every time we move to the next round and as Barry said earlier this is the first time we had a traditional financial investor in our rounds the rest of them have all been customers they've been friends and family for the most part did you join the board too right I did yeah so what are you what are you excited about what what do you see is I mean just clearly your side you invested but is there something just extra special here you know react chambers put in a 10-year 10-year cycle yeah we've talked about it I mean I'm excited to work with the team right there best-in-class working closely with John again is a lot of fun a chance to not exhaust yeah yeah you know a chance to read redefine the data center and be part of the next way even as a VC you love waves and build my Connick company right and I think we have a real opportunity in front of us it it takes a lot of money to do this and do it right and I think we have the team that proven they can execute on this kind of opportunities from I'm excited to see what the next five years hold for this company good well it was funny John teased him a little bit about you know all the M&A stuff that he was famous for at Cisco he's like I don't do that anymore now I'm an investor I want IPOs all the way what's all 18 thinks it is 18 companies in his portfolio their routes they're going to IPO all the way yeah that's that's a good point actually this team has been prolific and they've delivered products that have generated fifty billion dollars and any walk into any data center in the world you're gonna see a product this team has built however this team has not taken a company public so that's really the opportunity I think that's what excites them Randy's here it's why Jon's here that's why I'm here we want to build a company that can be an independent company be a lasting leader in a new category yeah so last word Randy for you for people that aren't familiar with the team that aren't familiar with with with what they've done what would you tell them about why you came to this opportunity and why you're excited about it well this there is no higher quality engineering team in the world didn't these people so it's to get re-engaged with them again with an entirely new concept that's catching a transition and the market was just too good an opportunity to pass I mean I had retired for 15 months and I came out of retirement to join this team much to the chagrin of my wife but I just couldn't pass up the opportunity high caliber talent it's um every day is is interesting I have to say well thanks for for sharing the story with us and and congratulations on a great day and in a terrific event thank you thank you very much all right he's berry he's Randy I'm Jeff you're watching the cube from the top of goldman sachs in Manhattan thanks for watching we'll see you next time

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

>> Live from San Diego, California, it's the Cube. Covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. >> Hi, welcome back to Cisco Live from sunny San Diego. I'm Lisa Martin with Dave Vellante and David are joined by a couple of guests from DXC. To my right we've got Jake Sager, principal client executive TMT, Tech Media Telecom. Jake, great to have you on the program. >> Thank you. >> Now we're broadcasting from the sun. And Randy Redman, the director of security services Product Management. Randy welcome. >> Thank you very much. Glad to be here. >> So we're in the definite zone. You can imagine all of the exciting conversations going on behind us here. Guys, I just noticed that DXC, guys have been around for a couple of years IT services company with 25 billion in annual revenue, but you guys were just named, I think it's this morning, number three on CLUS 2019 solution provider list up from number 10 last year. Pretty good momentum. Jake, we'll start with you. What do you see in feed on the street, in the market with respect to digital transformation, what are customers pains and how is the DXC helping knock him out of the park? >> Well, I think you know, DXC has a long legacy history over 60 years of business together from CSC, EDS, and obviously HP heritage. So we've kind of seen it all and seen the business transform from a highly on the ground business to now a lot of things in the cloud. With that obviously customers are looking to do business in different ways. There's a lot of digital disruptors out there. So they're looking to find the new solution that's going to shade off the competition, kind of skirt it, find the newest best thing before they can and find customer driven solutions rather than just cost driven solutions and other things like that. >> So when you say customer driven solution, let's dig into that a little bit more. What does that mean? And how is it actually, how does it manifest? >> Well, I think the customer can be a lot of different things to a lot of different people. In retail, it can be somebody walking into your store and banking, it can be somebody using an app. But what does that end consumer want? What's going to make their life easier and make them go to you versus another company? And that's really what companies need to be looking at. There's no one answer to anything. But it's a lot of thought-lead leadership to try to come up with something brand new, that is not going to be disrupted by the next Airbnb or Uber. >> So you are a CEO, Michael, talks a lot about digital transformation. >> Right. >> Right here in the security side of things. So we going to dig into that a little bit. But in terms of the evolution of digital transformation, generally and specifically, how people are rethinking security as a result, because we often say, what's the difference between a business and a digital business? Well, it's how they use data. Okay, well and that opens up a whole can of worms on security. So what are you seeing in terms of the evolution of the so called digital transformation, but specifically how it's affecting their posture towards security? >> Yeah, absolutely, because in a digital environment, customers are completely rethinking both how their infrastructure is deployed and how their applications are deployed. And so really, it's opening up whole new avenues for security threats to enter their environments. At the same time, there are so many individual security technologies and customers are really struggling with what are the right technology choices to make and then more importantly how to operate them effectively, how to implement appropriate security policies, how to actually monitor effectively for threats across the environment. So digital transformation is changing their business environment, but it's really completely opening up the sphere on the security side of the house. >> So Jake, we were talking and I had asked you what your favorite topics are, you said, smart city, IoT and connected cars. Sounds like a security nightmare. >> Yeah. >> But it's an opportunity as well for you guys. >> Absolutely. >> So you go in, what's the customer conversation like? I mean, pick one or all three, if you can generalize, in terms of I mean, these are all new things, right? It's the Wild West right now. What's customers mindset? Like you said, they don't want to get disrupted. They're looking at new opportunities. What are they looking at? How are you guys helping them? >> Well, it depends industry by industry. You know, when it comes to healthcare, we can help with remote telemedicine, operating medical equipment remotely. But again, that's going to bring in a whole bunch of new security threats, which Randy is going to be more than equipped to talk about. But I think securing that is really a big problem. When you start talking about massive IoT, you're talking about thousands and thousands of sensors out there in a smart city or oil mining gas utility, like they were talking about earlier today. You're talking about tons of different entry points, lots of different vulnerabilities. So that's definitely a huge issue for them. It's also a ton of new data that they don't know how to manage, that they don't know how to make sense out of, through artificial intelligence or other means. So for a company like us that really has strength in security, artificial intelligence, machine learning, as well as a strong background of data center, data lake management, helping them kind of figure out what data to use and how to use it most effectively. That's really where we shine. Cause we're not necessarily the company providing the hardware. We're not the company writing the software. But we're really the glue that integrates it all together, and brings all those multi solutions together. 'Cause in IoT, it's an ecosystem. It's not solution in a box. >> Let's dig into the Smart City concept. It's so fascinating. I've read up on the Las Vegas city of Las Vegas, which is been on the Cube. Done a lot to really transform that city. But to your point take about data, I think Chuck Robbins said this morning in the keynote that organizations are only really getting insight from less than 1% of their data. >> Right. >> It must be one of those where do we start? >> Right. >> So you are talking about working with municipalities on becoming smart cities and being able to apply some of your expertise and AI. Where do you start that conversation? >> Well, I mean, the terms over abused, I think data is a new oil, right? So if you don't know which data you're getting it from and you're only getting 10%, you're not doing a very good job as an oil producer, right? So our company is very good at identifying where the data is. 'Cause a lot of times, that's half the problem, is finding where that data resides, getting it into a place where you can actually ingest it, and then actually analyze it and get something useful out of it. Companies typically don't know where all their data is, they don't know how to analyze it and they definitely don't know how to turn it into something useful. So that's something DXC does across the board. >> What about the partnership with Cisco? So Cisco, obviously, it's got the networks, it's got, you know, packets flying around. It's got to secure those. What's the partnership like? Are you leveraging their products? I'm sure you are. You guys use everybody's products. >> Right. >> What's the partnership like? And what specifically are you doing in the security area Randy? >> Yeah, so in terms of the partnership with Cisco, we're certainly looking in several areas frankly, because right, we're looking with our clients at a solution letter approach, right. And that's one of the things that we like with Cisco is the broad portfolio meshes with our broad portfolio. So certainly key areas of focus for us right now are in the Unified Communication space and how we're helping with collaboration for our clients, but also in the security area, technologies, such as Cisco stealth watch, which is helping provide more visibility to what's happening in networks today. Because more and more our view is that security as we were just talking about, even in the IoT space becomes more of an analytics exercise. It's less about really being able to detect what you already know, it's really about being able to drive detection from the unknown. And so the more data that we can get, the more visibility into network environments the better. >> How do you work with Cisco? 25% of Cisco's revenue is they called services. So, where do they leave off? I mean they're a product company. You guys are a services firm, but they have services. >> Right. >> How do you interact with them? You don't compete, I presume. At least there's maybe some overlap. But, where do they leave off and you guys pick up? >> Yeah, so certainly, we're not competing with Cisco from a services perspective. We're certainly relying on Cisco services for hardware and professional support around their technology. We're really there to provide overall solution design, architecture installation and we'll leverage Cisco professional services where that's appropriate. And then we provide managed services on the back end as well. >> So you're saying their role is to make sure it's architected properly and it's working, in the way it's promised. Your role is to say it my way and you can correct me is help the customer figure out how to apply those technologies to create business value. >> Well, exactly and also typically in a client solution. Cisco maybe one of several technologies that are involved in a broader solutions-- >> you got to make it all work together tomorrow-- >> And part of our role is to act as that integrator to bring the core Cisco elements with the DXC services and-- >> So your jobs getting harder and harder and harder. >> Fully it is. It's a security perspective. >> Dave: As a consumer things are getting easier, right? Oh, yeah, Google, Facebook, Instagram is so easy. But the back end with, you know, cloud and DevOps, the pace of change. How have you seen that affect your business? How are you dealing with that rapid change? >> Yeah, so I think that from a couple of perspectives here. One is that it's changing how we go about the process in terms of developing services and capabilities for our clients. Just as Agile has taken over actually in the application space, It's really driving how we think about actually developing offerings now around getting technology out into the market more quickly, evolving and growing capability from there. And so really, it's all about how we get proof of value for our clients quickly by getting technology into their hands as quickly as possible. >> Lisa: So let's talk about some of these waves of innovation Cisco was talking about this morning. Talking about this explosion of 5G, Wi-Fi 6 being able to have this access that works really well indoors outdoors, how that's changing even Jake you know, consumer demand. What opportunities, and Jake I'll start with you, what opportunities and some of the things that Cisco was talking about with respect to connectivity, AI with GPUs being everywhere, edge mobile, architectures becoming so a Morpheus opportunity for DXC to help customers really not just integrate the technologies but to excel and accelerate themselves to define new services, new business models. What's your differentiation point there? >> I mean, our main differentiation point from DXC is agnostic to the technology. We really specialize in being vendor agnostic, finding the best of breed companies out there and integrating it into our portfolio and offering it to our clients. If our client wants Azure, we're not going to try to sell them on Google Cloud. If they want one or the other, we're going to be hand in hand with the customer either way. With these new technologies that come around, it's just going to open the doors for so many new types of business, so many more disruptive businesses. No matter what comes along our goal is to have that portfolio in hand, which Cisco rounds out to be able to offer to our over 6000 enterprise clients. So we need to be able to manage every shape, size, variety, industry, anything you can think of. >> What's the trend? Is the trend, yeah, we want as you say, okay, we'll make it make it work for you or is the trend like, you guys figure it out. We're not sure what the right fit is. How much of that is going on? >> I'd say you probably see 50 50. (Jake laughs) >> I think we're seeing a lot of that. Certainly as clients are migrating applications to the cloud. They may be starting with a particular cloud platform, but clients are really frankly fairly agnostic in terms of the cloud platform they're migrating to. They're taking advantage of more and more SAS applications. So one of the trends that we're definitely seeing is how to address client security concerns in a hybrid cloud environment because that's more and more what we expect the future to be, even if clients are focusing on a particular cloud platform as their starting point today. >> So as data is traversing the network and one of the one of the things that I heard this morning from Chuck Robbins keynote was that the common denominator as all of these changes and waves in innovation are coming is the network. Data is traversing the network. Given that is a given and there's only going to be more and more data and more connected devices, more mobile data traffic. Randy question for you. How can DXC, how can you help customers leverage your expertise and say security and AI, as you mentioned, to extract more value from their data and allow them to become far more secure as the it's no longer acceptable, you can't just simply put a firewall around a perimeter that has so many a Morpheus points? >> Yeah and absolutely. And as we mentioned, with all of the data that's available today, it really becomes more of an analytics problem. And one of the investments that the DXC is making is specifically in our security platform that allows us to ingest data from pretty much any infrastructure data source and be able to leverage capabilities to provide analytics, machine learning and automation on top of that, to help clients leverage the power of the data and specifically from a security perspective, not just drive detection, because that's interesting. The question I get from clients is well now, what do I do about it? >> Right. >> And we're leveraging investment, our platform automation is actually to begin to take automated actions on behalf of our clients in order to solve security problems. >> Excellent, guys. Well, thank you so much, Jake, and Randy for stopping by the Cube and talking with Dave and me about what you guys are doing at DXC. The next time we'll have to talk about connected cars. >> Sure. >> Thank you. >> Alright. For Dave Vellante I'm Lisa Martin, you're watching the Cube live from Cisco Live in sunny San Diego. Thanks for watching. (techy music)

>> Live from Las Vegas, it's theCUBE, covering Informatica World 2019. Brought to you by Informatica. >> Welcome back, everyone, to theCUBE's live coverage of Informatica World 2019. I'm your host, Rebecca Knight, along with my cohost, John Furrier. We have two guests for this segment. We have Charlie Emer. He is the senior director data management and governance strategy at Honeywell. Thanks for joining us. >> Thank you. >> And Randy Mickey, senior vice president global professional services at Informatica. Thanks for coming on theCUBE. >> Thank you. >> Charlie, I want to start with you. Honeywell is a household name, but tell us a little bit about the business now and about your role at Honeywell. >> Think about it this way. When I joined Honeywell, even before I knew Honeywell, all I thought was thermostats. That's what people would think about Honeywell. >> That's what I thought. >> But Honeywell's much bigger than that. Look, if you go back to the Industrial Revolution, back in, I think, '20s, we talked about new things. Honeywell was involved from the beginning making things. But we think this year and moving forward in this age, Honeywell is looking at it as the new Industrial Revolution. What is that? Because Honeywell makes things. We make aircraft engines, we make aircraft parts. We make everything, household goods, sensors, all types of sensors. We make things. So when we say the new Industrial Revolution is about the Internet of Things, who best to participate because we make those things. So what we are doing now is what we call IIOT, Industrial Internet of Things. Now, that is what Honeywell is about, and that's the direction we are heading, connecting those things that we make and making them more advancing, sort of making life easier for people, including people's quality of life by making those things that we make more usable for them and durable. >> Now, you're a broad platform customer of Informatica. I'd love to hear a little bit from both of you about the relationship and how it's evolved over the years. >> Look, we look at Informatica as supporting our fundamentals, our data fundamentals. For us to be successful in what we do, we need to have good quality data, well governed, well managed, and secure. Not only that, and also accessible. And we using Informatica almost end to end. We are using Informatica for our data movement ETL platform. We're using Informatica for our data quality. We're using Informatica for our master data management. And we have Informatica beginning now to explore and to use Informatica big data management capabilities. And more to that, we also utilize Informatica professional services to help us realize those values from the platforms that we are deploying. IIoT, Industrial IoT has really been a hot trend. Industrial implies factories building big things, planes, wind farms, we've heard that before. But what's interesting is these are pre-existing physical things, these plants and all this manufacturing. When you add digital connectivity to it and power, it's going to change what they were used to be doing to new things. So how do you see Industrial IoT changing or creating a builder culture of new things? Because this connect first, got to have power and connectivity. 5G's coming around, Wi-Fi 6 is around the corner. This is going to light up all these devices that might have had battery power or older databases. What's the modernization of these industrial environments going to look like in your view? First of all, let me give you an example of the value that is coming with this connectivity. Think of it, if you are an aircraft engineer. Back in the day, a plane landed in Las Vegas. You went and inspected it, physically, and checked in your manual when to replace a part. But now Honeywell is telling you, we're connecting directly to the mechanic who is going to inspect the plane, and there will be sort of in their palms they can see and say wait a minute. This part, one more flight and I should replace this part. Now, we are advising you now, doing some predictive analytics, and telling you when this part could even fail. We're telling you when to replace it. So we're saying okay, the plane is going to fly from here to California. Prepare the mechanics in California when it lands with the part so they can replace it. That's already safety 101. So guaranteeing safety, sort of improving the equity or the viability of the products that we produce. When we're moving away from continue to build things because people still need those things built, safety products, but we're just making them more. We've heard supply chain's a real low-hanging fruit on this, managing the efficiency so there's no waste. Having someone ready at the plane is efficient. That's kind of low-hanging fruit. Any ideas on some of the creativity of new applications that's going to come from the data? Because now you start getting historical data from the connections, that's where I think the thing can get interesting here. Maybe new jobs, new types of planes, new passenger types. >> We are not only using the data to improve on the products and help us improve customer needs, design new products, create new products, but we also monitorizing that data, allowing our partners to also get some insights from that data to develop their own products. So creating sort of an environment where there is a partnership between those who use our products. And guess what, most of the people who use our products, our products actually input into their products. So we are a lot more business-to-business company than a B2C. So I see a lot of value in us being able to share that intelligence, that insight, in our data at a level of scientific discovery for our partners. >> Randy, I want to bring you into the conversation a little bit here (laughs). >> Thanks. >> So you lead Informatica's professional services. I'm interested to hear your work with Honeywell, and then how it translates to the other companies that you engage with. Honeywell is such a unique company, 130 years of innovation, inventor of so many important things that we use in our everyday lives. That's not your average company, but talk a little bit about their journey and how it translates to other clients. >> Sure, well, you could tell, listening to Charlie, how strategic data is, as well as our relationship. And it's not just about evolution from their perspective, but also you mentioned the historicals and taking advantage of where you've been and where you need to go. So Charlie's made it very clear that we need to be more than just a partner with products. We need to be a partner with outcomes for their business. So hence, a professional services relationship with Honeywell and Charlie and the organization started off more straightforward. You mentioned ETL, and we started off 2000, I believe, so 19 years ago. So it's been a journey already, and a lot more to go. But over the years you can kind of tell, using data in different ways within the organization, delivering business outcomes has been at the forefront, and we're viewed strategically, not just with the products, but professional services as well, to make sure that we can continue to be there, both in an advisory capacity, but also in driving the right outcomes. And something that Charlie even said this morning was that we were kind of in the fabric. We have a couple of team members that are just like Honeywell team members. We're in the fabric of the organization. I think that's really critically important for us to really derive the outcomes that Charlie and the business need. >> And data is so critical to their business. You have to be, not only from professional services, but as a platform. Yes. This is kind of where the value comes from. Now, I can't help but just conjure up images of space because I watch my kids that watch, space is now hot. People love space. You see SpaceX landing their rocket boosters to the finest precision. You got Blue Origin out there with Amazon. And they are Honeywell sensors either. Honeywell's in every manned NASA mission. You have a renaissance of activity going on in a modern way. This is exciting, this is critical. Without data, you can't do it. >> Absolutely, I mean, also sometimes we take a break. I'm a fundamentalist. I tell everybody that excitement is great, but let's take a break. Let's make sure the fundamentals are in place. And we actually know what is it, what are those critical data that we need to be tracking and managing? Because you don't just have to manage a whole world of data. There's so much of it, and believe me, there's not all value in everything. You have to be critical about it and strategic about it. What are the critical data that we need to manage, govern, and actually, because it's expensive to manage the critical data. So we look at a value tree as well, and say, okay, if we, as Honeywell, want to be able to be also an efficient business enabler, we have to be efficient inside. So there's looking out, and there's also looking inside to make sure that we are in the right place, we are understanding our data, our people understand data. Talking about our relationship with IPS, Informatica Professional Services, one of the things that we're looking at is getting the right people, the engineers, the people to actually realize that okay, we have the platform, we've heard of Clare, We heard of all those stuff. But where are the people to actually go and do the real stuff, like actually programming, writing the code, connecting things and making it work? It's not easy because the technology's going faster than the capabilities in terms of people, skills. So the partnership we're building with Informatica professional services, and we're beginning to nurture, inside that, we want to be in a position were Honeywell doesn't have to worry so much about the churn in terms of getting people and retraining and retraining and retraining. We want to have a reliable partner who is also moving with the certain development and the progress around the products that we bought so we can have that success. So the partnership with IPS is for the-- >> The skill gaps we've been talking about, I know she's going to ask next, but I'll just jump in because I know there's two threads here. One is there's a new generation coming into the workforce, okay, and they're all data-full. They've been experiencing the digital lifestyle, the engineering programs. To data, it's all changing. What are some of the new expertise that really stand out when evaluating candidates, both from the Informatica side and also Honeywell? What's the ideal candidate look like, because there's no real four-year degree anymore? Well, Berkeley just had their first class of data analytics. That's new two-generation. But what are some of those skills? There's no degree out there. You can't really get a degree in data yet. >> Do you want to talk about that? >> Sure, I can just kick off with what we're looking at and how we're evolving. First of all, the new graduates are extremely innovative and exciting to bring on. We've been in business for 26 years, so we have a lot of folks that have done some great work. Our retention is through the roof, so it's fun to meld the folks that have been doing things for over 10, 15 years, to see what the folks have new ideas about how to leverage data. The thing I can underscore is it's business and technology, and I think the new grads get that really, really well in terms of data. To them, data's not something that's stored somewhere in the cloud or in a box. It's something that's practically applied for business outcomes, and I think they get that right out of school, and I think they're getting that message loud and clear. Lot of hybrid programs. We do hire direct from college, but we also hire experienced hires. And we look for people that have had degrees that are balanced. So the traditional just CS-only degrees, still very relevant, but we're seeing a lot of people do hybrids because they know they want to understand supply chain along with CS and data. And there are programs around just data, how organizations can really capitalize on that. >> And also we're hearing, too, that having domain expertise is actually just as important as having the coding skills because you got to know what an outcome looks like before you collect the data. You got to know what checkmate is if you're going to play chess. That's the old expression, right? >> I think people with the domain, both the hybrid experience or expertise, are more valuable to the company because maybe from the product perspective, from building products, you could be just a scientist, code the code. But when you come to Honeywell, for example, we want you to be able to understand, think about materials. Want you to be able to understand what are the products, what are the materials that we use. What are the inputs that we have to put into these products? Now a simple thing like a data scientist deciding what the right correct value of what an attribute should be, that's not something that because you know code you can determine. You have to understand the domain, the domain you're dealing with. You have to understand the context. So that comes, the question of context management, understanding the context and bringing it together. That is a big challenge, and I can tell you that's a big gap there. >> Big gap indeed, and understand the business and the data too. >> Yes. >> Charles, Randy, thank you both so much for coming on theCUBE. It's been a great conversation. >> Thank you. >> Thank you. >> I'm Rebecca Knight for John Furrier. You are watching theCUBE. (funky techno music)

>> Announcer: Live, from Vancouver, Canada it's the CUBE, covering OpenStack Summit North America 2018, brought to you by Red Hat, the Open Stack Foundation, and it's ecosystem partners. >> Welcome back, I'm Stu Miniman and my cohost John Troyer and you're watching the CUBE, the worldwide leader in tech coverage. Happy to welcome back to the program long time friend of the CUBE back from the earliest days, Randy Bias, Vice President with Juniper, Randy, great to see you. >> Absolutely, great to be back with you guys. >> All right, so Randy, we've been talking about, you know, community, and everything's going good and attendance might be down a little bit but how we fit in with containers and kubernetes, and everything, so we expect you to tear everything up for us and tell us the reality of what's happening in this community. >> I'll do my best (laughing). >> All right, so before we get to the kubernetic stuff, you're working on, we used to call it OpenContrail? Which you were involved in before Juniper acquired it, went through a rebranding recently, Tungsten, which I was looking up, came from the word heavy stone, give us the update from the networking side. >> Yeah, so the short history is that there was a company called Contrail, and they created a software defined networking controller, it was acquired by Juniper in 2012, 2013, and then that was open sourced, so Juniper for a long time was running with sort of two editions, Contrail which was the commercial offering, and OpenContrail which was the open source, and then shortly after I joined Juniper, identified that, you know, we really needed to go back to the drawing board on the way that we had organized the community, and transition it from being Juniper-led to community led, and so over the past year, I spearheaded that effort, and then that culminated in us announcing at the end of March at ONS that, you know, OpenContrail was now Tungsten Fabric. We renamed it, we moved it into the Linux foundation, under its governance, and now Juniper is one of many people of the community that have a seat at the table for the management, both from a business and technical perspective, and we're moving forward with a new reinvigorated community. >> Yeah, so networking sits at really the intersection of this multi-cloud world that we're living in. There's so many players trying to be there, you know Cisco, really moving to become more of a software company, when I interviewed their number two guy at their show, he's like, when you think of Cisco in the future, we're not even going to be a networking company, we'll be a software company. VMware, of course, pushed heavy through, then the Nicira acquisition, where does Tungsten fit, kind of compare and contrast for us, where it fits among some of these other offerings out there in the marketplace. >> Yeah, I mean, I think most enterprise vendors are in a similar transition from being a hardware to software companies. We're no different than any of the rest. I think we have a pretty significant advantage in that we have a lot of growth in the cloud sector, so a lot of the large public clouds are our customers and we're selling a tremendous amount of hardwaring to them, so I think we've got a lot longer runway. But, you know, we just recently hired CTO, Bikash Koley, out of Google, and we're starting to see some additional folks out of Google, like my new boss, Morgan, and what that's bringing with it is a very much a software first type perspective. So Bikash and Morgan really built everything for the Google network from the topper rack all the way out to the win and it's almost all software-based, disaggregated, hardware, software, opensource software running on top of white boxes, and so that kind of perspective is now really deep, start beginning to become embedded in Juniper. And at the head of that is Tungsten. So we see Tungsten Fabric as being sort of a tool that we use to create, you know, a global ubiquitous network fabric, that anybody can use anywhere, without talking to Juniper at all, without knowing that Juniper's part of Tungsten, and then as they grow up and they get to a point where they need multi-cloud, they need federation, or they need kind of day two enterprise operations, you know, we have a commercial version and a commercial distribution that they can use. >> Randy, we talked a little bit about OpenContrail and last year, at OpenStack Summit and moving it to a more of a community based governance model, and now that's happened with the Linux Foundation, can you talk a little bit about the role of opensource governance, and corporate governance, and then foundations, and just going forward, you know, what's an effective model for 2018 going forward, for a foundation-led project and maybe in the context of Tungsten Fabric, and how is that looking? >> Yeah, so again, OpenContrail's now Tungsten Fabrics, might be new for some of the viewers, lot of people still coming to terms with that. And so one of the things that we noticed is that, and when many people go and they say, hey, we want opensource first, the AT&T's of this world, part of what they're saying, one of the aspects of being opensource versus we want to be one of many around the table, we want to have a seat at the table, we want to have the option to contribute code back, and we want to feel like it's a group effort. And so that was a big factor, right? It was an opensource project, but it was largely the governance was carried by Juniper, all the testing infrastructure was Juniper, you know, all of the people who made architectural decisions were Juniper, all of the lead contributors were Juniper, and so, going to Linux Foundation was critical to us having a legal framework, for the trademarks, the code, the licenses, the contributor license agreements, are all owned and operated by the Linux Foundation and not by Juniper, so we basically have a trusted third party who can mediate all those things and create a structure, a governance small structure where Juniper has one seat at the table, and all the other community members do as well. So it was really key to getting, to moving to that model to increase people's interest in the project and to really go the next level. There just wasn't any way to do it without doing this. >> All right, so, Randy, let's talk about OpenStack. You were watching the keynote yesterday, you were, you know, in the Twitter stream, >> Randy: I don't usually watch keynotes, man. >> Stu: But you know this community, so-- >> I do know this community (laughing). >> Give us kind of the good, the bad, and the ugly from your standpoint as to, you know, where we've gone, you know, what's doing well, and what you're frustrated as heck that we still haven't fixed yet. >> Well, I mean, it's great that we have so much inroads amongst the carriers, it's great that, you know, that there's a segment that OpenStack has been able to land in. I mean, at some points when I was feeling particularly pessimistic on some days, I was like, oh man, this thing's never going to go anywhere, so that's great. On the other hand, you know, the promise that we had of sort of being the Linux operating center, operating system of the data center, and you know, really gaining inroads into private cloud and enterprise, that just hasn't materialized and I don't see a path to that. A lot of that has to do with history, I'm not sure how much of that I want to go into here, but I see those as being bright lights. I see the Ocata containers effort and sort of having this alternative structure that's more or less like the umbrella structure that I lobbied for while I was on the board. So for several years on the board, I said we need to really look more like the Apache Software Foundation, we need to look less like the Linux Operating System in terms of how we think about things. Not this big integrated monolithic release, you need more competition between projects and that just wasn't really embraced. And I think that that, in a way, that was one of several things that really kind of limited our ability to capture the market that we really wanted, which is the enterprise market. >> Yeah, well, I know, and one of those sticking points there that I've talked to you many times over the years about is how do I actually deploy this? You know, getting a base configuration and scaling this out, simplicity is tough, getting to those environments, you know, getting it up in two weeks, is good for some environments, but maybe not for others. >> Yeah, I mean I think there's sort of a spectrum, right? At one end of the spectrum, you say hey, I'm going to have a very opinionated approach like kubernetes does, and we're going to limit what we say we can do, you know, we're not all things to all people. And I think that opinionated approach, like the Linux operating system worked very, very well. And then other end of the spectrum is we've got no opinion like the Apache Software Foundation, and then it's up to vendors to go and cherry pick the pieces they want and turn that into some kind of commercial offering, whether it's Hortonworks, or Thi-dare or Du-per or whatever it is, the problem is that OpenStack wound up in the middle where it had the sort of integrated monolithic release cycle which it still does, which started to be all things to all people, and it was never as great as it could be, so it's like we got to support Hyper-V, we got to support VMware, and as the laundry list of all things we have to support grew longer, it became more and more difficult to have a compelling, easy to use, easy to scale offering that any enterprise could consume. >> Randy, a lot of talk this week about edge computing, with several different definitions, right? But it does strike me that, you know, there's a certain set of apps, that you write 'em and that they live fine in a big public cloud, and a big data center somewhere. But there's a lot of hardware that's going to be living out in the world, whether that's at the base of a radio tower, or in a wall, or in my shoe, that is going to be running hardware, and is going to be running something, and sometimes that something can be OpenStack, and we're seeing some examples of it, many examples of that already. Is that an area of growth for OpenStack? Is that an interesting part of how this fabric is going to expand? >> Well, I probably have a contrarian view here. So, I spent a bunch of time at Juniper, one of the things I worked on for a while was edge computing and we're still trying to decide what we want to do there and you know, kind of to the first point you made is everybody's edge is different, right? Is it on the mobile phone, is it back in the data center, the difference is that the real estate gets more expensive as you move out, right? And it's in terms of latency, and it's in terms of bandwidth and it's also in terms of cost of storage and compute. There's a move closer to the mobile device that becomes progressively more expensive, and so that's why a lot of people sort of look and say hey, wouldn't it be nice if we can get you out the closer lower latency and bandwidth and so on but as we looked at it, a lot of the different use cases it became really interesting in that, it wasn't clear if there was that much value between 5 milliseconds and 20 milliseconds, right? I mean, that's pretty, either one's pretty close, sure there's a lot of difference between 20 and a 100, but maybe not so much between 5 and 20. And so we kind of came to the conclusion that at least for right now, probably, the bulk of use cases are fine with 20 milliseconds, and what that means is that regional systems like AWS's Lambda at the Edge, they're in metro, those are probably good for most cases. I don't know that you need to be on the tower, I don't know that you need to be in the central office, so I think edge computing is still nascent, we don't know exactly what all those use cases are, but I think you might be able to service most of them from regional data centers, and then the question really becomes what does that stack need to be and if you have a regional data center that's got plenty of power, plenty of space, then it might be that OpenStack is a good solution, but if you're trying to scale down onto the tower, I got to have some doubts about whether OpenStack can really scale down that far. >> Randy, analytics is something we've been seeing, the networking people used for many years, at this show, starting to hear a lot of discussion about AI and ML, would love your view point as to what you're seeing in that space. >> You know I have some friends who started off in AI in very early days and he had a very pessimistic view. He said, you know this stuff comes and goes, but I'm actually very positive and optimistic about it because the way I look at this is there's a renaissance happening which is that, you know, now ML is really available to masses and you're seeing people do really interesting things like, we have a product called AppFormix, and what they do is they take ML and they apply it to operations and I love this because as an operations guy, you know, I used to have these problems in production where something would go out and the first thing I'd do, is I'm trying to do correlation and then root cause analysis, like, what was the actual failure? Like I can see the symptom on this end and now I have to get all the way back to what caused it, and the reality is that machine learning, AI techniques and protocols can do all the heavy lifting for operators very, very quickly and basically surface a problem for somebody to do the final analysis on. And so I do think that ML and AI apply to very specific vertical problems, it is just a place where we're going to see a tremendous amount of revolution in the next couple years. >> All right, and that hits right at really that intersection between kind of the developers and the operators there-- >> Absolutely. >> What are you seeing from an organizational standpoint, companies you're talking to these days, how are they doing adopting that change, dealing with that, you know, often schism or are they bringing those groups together? >> Well, I think you remember that like in the early days, I used bring my deck along and I would talk about assembly line IT versus the robotics spectrum all of IT and I would sort of make that sort of analogy to sort of the car manufacturing process, and I think what machine learning is really going to do is take us to that next level past that right? So we had the assembly line where we have all the specialists, we had the robotics factory where we had people who know how to build a robots and software, and it's really sort of like, just churning out with a lot of people on the line, and I think the next level after that is, you know, completely fully automated applications driving themselves, you know, self-driving applications, and I think that's when things get really interesting, and maybe we start to remove the traditional operator out of the equation and it really becomes about empowering developers with tools that are comfortable and that leverage all the cloud era and stuff that we built. >> All right, so Randy, you're credited with the pets versus cattle analogy, what's the latest, you were talking about some of the previous slide decks, what's Randy Bias looking on down the road? >> I mean, the stuff just comes to me, man. I can't like predict, but the thing I've been talking about a lot lately is services of platform, I think we might've talked about that last time, which is just this notion that if we look at where Amazon's invested and what's interesting, it's certainly not at the infrastructure layer and it's really not at the PAS layer, it's that thick layer in between with like database as a service and NoSQL as a service, and messaging service, and DNS and so on, where you can kind of cherry pick those things as you're assembling your own PAS for your application, and I still think that's the area that is under-discussed, and the reason is is the people back into basically doing that, building kind of the service as a platform system, but they're not like going into it, kind of like eyes wide open. >> Yeah, so just following up on that last piece, one of the criticisms I have this week is when you talk about multi-cloud, most of the people talk about, oh well people are clawing things back to their data centers. Juniper plays across the board, strong partnership with Amazon, yet you're here, what are you hearing from customers, you know, what do you see as kind of the balance there and, you know, the public cloud's role in the world? >> I mean, they're still winning, right? I don't think there's any doubt, I haven't seen a decline back here talking about, but we are starting to enter into the era of, okay, this stuff is out there, and it's running, but I need to find my governance model, I need to understand who's using what, I need to understand what it's costing me, and that's the sign of the maturation process. And so I think that, you know, we saw in the early days of cloud, people jumping the gun, creating compliance services, and you know, SAS products that would basically measure how much you're spending and think that it's time for that stuff to come back in vogue again, because the tool needs to be there for people to manage these extended supply chain of IT vendors which include the public cloud. And I think that the idea that would claw them back as opposed to like just see that as holistic part of what we're trying to accomplish doesn't make any sense. >> Well learned. Well, Randy Bias, always a pleasure to catch up with you. >> John. >> John Troyer, I'm Stu Miniman, getting towards the end of two days of three days of live coverage. Thanks for staying with the CUBE. (bubbly electronic music)

(upbeat music) >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're in our Palo Alto studio this morning for a CUBE Conversation talking about content marketing, attention economy, a lot of really interesting topics that should be top of mind for marketers, that we're in very interesting times on the B2C side and even more, I think, on the B2B side. So we're excited to have Randy Wootton, he's the CEO of Percolate. Randy, great to see you. >> Thanks very much for having me. A real pleasure to be here. >> Absolutely, so for those who aren't familiar, give us kind of the quick and dirty on Percolate. >> Percolate has been around for about seven years. It started as a social media marketing platform. So helping people, helping brands, build their brands on the social landscape, and integrating campaigns to deploy across the different social channels. Over the last couple of years, it's been moving more into the space called content marketing, which is really an interesting new area that marketers are coming to terms with. How do you put together content and orchestrate it across all the different channels. >> And it's interesting, a lot of vocabulary on the website around experiences and content not a lot about products. So how should marketers think and how does experience and content ultimately map back to the products and services you're trying to sell. >> Well, I do think that's a great point. And the distinction between modern brands, who are trying to create relationships with their consumers, rather than pushing products, especially if you're B2B, or technology pushing speeds and feeds. Instead, you are trying to figure out what is going to enable you to create a brand that consumers pull through versus getting pushed at. And so I think the idea around content marketing is that in some ways advertising isn't working anymore. People aren't paying attention to display ads, they're not clicking, they aren't processing the information. But, they are still buying. So the idea for marketers is, how do you get the appropriate content at the right time, to the right person, in their purchase journey. >> Right, and there's so many different examples of people doing new things. There's more conversations kind of, of the persona of the company, of the purpose, purpose driven things, really trying to appeal to their younger employees as well as a younger customer. You have just crazy off the wall things, which never fail to entertain. Like Geico, who seems to break every rule of advertising by having a different theme every time you see a Geico ad. So people are trying humor, they're trying theater, they're trying a lot of things to get through because the tough thing today is getting people's attention. >> I think so, and they talk a lot about the attention economy. That we live in a world of exponential fragmentation. All the information that we are processing across all these different devices. And a brand trying to break through, there's a couple of challenges, one is you have to create a really authentic voice, one that resonates with who you are and how you show up. And then, I think the second point is you recognize that you are co-building the brand with the consumers. It's no longer you build the Super Bowl ad and transmit it on T.V., and people experience your brand. You have this whole unfolding experience in real time. You've seen some of the airlines, for example, that have struggled with the social media downside of brand building. And so how do control, not control, but engage with consumers in a way that feels very authentic and it continues to build a relationship with your consumers. >> Yeah, it's interesting, a lot of things have changed. The other thing that has changed now is that you can have a direct relationship with that consumer whether you want it or not, via social media touches, maybe you were before, that was hidden through your distribution, or you didn't have that, that direct connect. So, you know, being able to respond to this kind of micro-segmentation, it's one thing to talk about micro-segmentation on the marketing side, it's a whole different thing with that one individual, with the relatively loud voice, is screaming "Hey, I need help." >> That's right, and I think there are a couple of things on that point. One is, I've been in technology for 20 years. I've been at Microsoft, I was at Salesforce, I was at AdReady, Avenue A, and Quantive. And now, Rocket Fuel before I came to Percolate. And I've always been wrestling with two dimensions of the digital marketing challenge. One is around consumer identity, and really understanding who the consumer is, and where they've been and what they've done. The second piece is around the context. That is, where they are in the moment, and which device they're on. And so, those are two dimensions of the triangle. The third is the content, or in advertising it's the creative. And that's always been the constraint. You never have enough creative to be able to really deliver on the promise of personalization, of getting the right message to the right person at the right time. And that now is the blockade. That now is the bottleneck, and that now is what brands are really trying to come to terms with. Is how do we create enough content so that you can create a compelling experience for each person, and then if there's someone who is engaging in a very loud voice, how do you know, and how do you engage to sort of address that, but not loose connections with all your other consumers. >> Right, it's interesting, you bring up something, in some of the research, in micro-moments. And in the old days, I controlled all of the information, you had to come for me for the information, and it was a very different world. And now, as you said, the information is out there, there's too much information. Who's my trusted conduit for the information. So by the time they actually get to me, or I'm going to try to leverage these micro-moments, it's not about, necessarily direct information exchange. What are some of these kind of micro-moments, and how are they game changers? >> Well, I think the fact that we can make decisions in near real time. And when I was at Rocket Fuel, we were making decisions in less than 20 milliseconds, processing something like 200 billion bid transactions a day, and so I just think people are not yet aware of the amount, the volume and the velocity of data that is being processed each and every day. And, to make decisions about specific moments. So the two moments I give as examples are: One, I'm sitting at home watching the Oakland Raiders with my two boys, I'm back on the couch and we're watching the game, and Disney makes an advertisement. I'm probably open to a Disney advertisement with my boys next to me, who are probably getting an advertisement at the same time by Disney. I'm a very different person in that moment, or that micro-moment than when I'm commuting in from Oakland to San Francisco on BART, reading the New York Times. I'm not open to a Disney ad at that moment, because I'm concentrating on work, I'm concentrating on the commute. And I think the thing that brands are coming to terms with is, how much am I willing to pay to engage with me sitting on the couch versus me sitting on BART. And that is where the real value comes from, is understanding which moments are the valuable ones. >> So there's so much we can learn from Ad Tech. And I don't think Ad Tech gets enough kind of credit for operating these really large, really hyper speed, really sophisticated marketplaces that are serving up I don't even know how many billions of transactions per unit time. A lot of activity going on. So, you've been in that world for a while. As you've seen them shift from kind of people driving, and buyers driving to more automation, what are some of the lessons learned, and what should learn more from a B2B side from this automated marketplace. >> Well, a couple of things, one is the machines are not our enemies, they are there to enable or enhance our capabilities. Though I do think it's going to require people to re-think work, specifically at agencies, in terms of, you don't need people to do media mixed modeling on the front end in Excel files, instead, you need capacity on the back end after the data has come out, and to really understand the insights. So there is some re-training or re-skilling that's needed. But, the machines make us smarter. It's not artificial intelligence, it's augmented intelligence. I think for B2B in particular what you're finding is, all the research shows that B2B purchasers spend something like 70 or 80% of their time in making the purchase decision before they even engage with the sales rep. And as a B2B company ourselves, we know how expensive our field reps are. And so to make sure that they are engaging with people at the right time, understanding the information that they would have had, before our sales cycle starts, super important. And I think that goes back to the content orchestration, or content marketing revolution that we are seeing now. And, you know, I that there is, when you think about it, most marketers today, use PowerPoint and Excel to have their marketing calendar and run their campaigns. And we're the only function left where you don't have an automated system, like a sales force for marketers, or a service now for marketers. Where a chief of marketing or a SVP of marketing, has, on their phone the tool of record, they system of record that they want to be able to oversee the campaigns. >> Right, although on the other hand, you're using super sophisticated A/B testing across multiple, multiple data sets, rather than doing that purchase price, right. You can test for colors, and fonts, and locations. And it's so different than trying to figure out the answer, make the investment, blast the answer, than this kind of DevOps way, test, test, test, test, test, adjust, test, test, test, test, adjust. >> You're absolutely right, and that's what, at Rocket Fuel, and any real AI powered system, they're using artificial intelligence as the higher order, underneath that you have different categories, like neural networks, deep learning and machine learning. We were using a logistic regression analysis. And we were running algorithms 27 models a day, every single day, that would test multiple features. So it wasn't just A/B testing, it was multi variant analysis happening in real time. Again, the volume and velocity of data is beyond human comprehension, and you need the machine learning to help you make sense of all that data. Otherwise, you just get overwhelmed, and you drown in the data. >> Right, so I want to talk a little bit about PNG. >> I know they're close and dear to your heart. In the old days, but more recently, I just want to bring up, they obviously wield a ton of power in the advertising spin campaign. And they recently tried to bring a little bit more discipline and said, hey we want tighter controls, tighter reporting, more independent third party reporting. There's this interesting thing going now where before, you know, you went for a big in, 'causethen you timed it by some conversion rating you had customers at the end. But now people it seems like, are so focused on the in kind of forgetting necessarily about the conversion because you can drive promoted campaigns in the social media, that now there's the specter of hmm, are we really getting, where we're getting. So again, the PNG, and the consumer side, are really leading kind of this next revolution of audit control and really closer monitoring to what's happening in these automated ad marketplaces. >> Well, I think what you're finding is, there's digital transformation happening across all functions, all industries. And, I think that in the media space in particular, you're also having an agency business model transformation. And what they used to provide for brands has to change as you move forward. PNG has really been driving that. PNG because of how much money they spend on media, has the biggest stick in the fight, and they've brought a lot of accountability. Mark Pritchard, in particular, has laid down these gauntlets the last couple of years, in terms of saying, I want more accountability, more visibility. Part of the challenge with the digital ecosystem is the propensity for fraud and lack of transparency, 'cause things are moving so quickly. So, the fact, that on one side the machines are working really well for ya, on the other side it's hard to audit it. But PNG is really bringing that level of discipline there. I think the thing that PNG is also doing really well, is they're really starting to re-think about how CPG brands can create relationships with their consumers and customers, much like we were talking about before. Primarily, before, CPG brands would work through distributors and retailers, and not really have a relationship with the end consumer. But now as they've started to build up their first party profiles, through clubs and loyalty programs, they're starting to better understand, the soccer mom. But it's not just the soccer mom, it's the soccer mom in Oakland at 4 o'clock in the afternoon, as she goes to Starbucks, when she's picked up her kids from school. All of those are features that better help PNG understand who that person is, in that context, and what's the appropriate engagement to create a compelling experience. That's really hard to do at the individual level. And when you think about the myriad of brands, that PNG has, they have to coordinate their stories and conversations across all of those brands, to drive market share. >> Yeah, it's a really interesting transformation, as we were talking earlier, I used to joke always, that we should have the underground railroad, from Cincinnati to Silicone Valley to get good product managers, right. 'Cause back in the day you still were doing PRD's and MRD's and those companies have been data driven for a long time and work with massive shares and small shifts in market percentages. But, as you said, they now, they're having to transform still data driven, but it's a completely different set of data, and much more direct set of data from the people that actually consume our products. >> And it's been a long journey, I remember when I was at Microsoft, gosh this would have been back in 2004 or 2005, we were working with PNG and they brought their brands to Microsoft. And we did digital immersions for them, to help them understand how they could engage consumers across the entire Microsoft network, and that would include X-Box, Hotmail at the time, MSN, and the brands were just coming to terms with what their digital strategy was and how they would work with Portal versus how they would work with other digital touchpoints. And I think that has just continued to evolve, with the rise of Facebook, with the rise of Twitter, and how do brands maintain relationships in that context, is something that every brand manager of today is having to do. My father, I think we were chatting a little earlier, started his career in 1968 as a brand manager for PNG. And, I remember him telling the stories about how the disciplined approach to brand building, and the structure and the framework hasn't changed, the execution has, over the last 50 years. >> So, just to bring it full circle before we close out, there's always a segment of marketing that's driven to just get me leads, right, give me leads, I need barcode scans at the conference et cetera. And then there's always been kind of the category of kind of thought leadership. Which isn't necessarily tied directly back to some campaign, but we want to be upfront, and show that we're a leading brand. Content marketing is kind of in-between, so, how much content marketing lead towards kind of thought leadership, how much lead kind of towards, actually lead conversions that I can track, and how much of it is something completely different. >> That's a great question, I think this is where people are trying to come to terms, what is content, long form, short form video. I think of content as being applied across all three dimensions of marketing. One is thought leadership, number two is demand gen, and number three is actualization or enablement in a B2B for your sales folks. And how do you have the right set of content along each of those dimensions. And I don't think they're necessarily, I fundamentally think the marketing funnel is broken. It's not you jump in at the top, and you go all the way to the bottom and you buy. You have this sort of webbed touch of experiences. So the idea is, going back to our earlier conversation, is, who is that consumer, what do you know about him, what is the context, and what's the appropriate form of content for them, where they are in their own buyer journey. So, a UGC video on YouTube may be okay for one consumer in a specific moment, but a short form video may be better for someone else, and a white paper may be better. And I think that people don't necessarily go down the funnel and purchase because they click on a search ad, they instead may be looking at a white paper at the end of the purchase, and so the big challenge, is the attribution of value, and that's one of the things that we're looking at Percolate. Is almost around thinking about it as content insight. Which content is working for whom. 'Cause right now you don't know, and I think the really interesting thing is you have a lot of people producing a lot of content. And, they don't know if it's working. And I think when we talk to marketers, that we hear their teams are producing content, and they want to know, they don't want to create content that doesn't work. They just want a better understanding of what's working, and that's the last challenge in the digital marketing transformation to solve. >> And how do you measure it? >> How do you measure, how do you define it? And categorize it, so that's one of the challenges, we were chatting a little bit before, about what you guys are doing at CUBE, and your clipper technology and how you're able to dis-aggregate videos, to these component pieces, or what in an AI world, you'd call features, that then can be loaded as unstructured data, and you can apply AI against it and really come up with interesting insights. So I think there's, as much as I say, the transformation of the internet has been huge, AI is going to transform our world more than we even can conceive of today. And I think content eventually will be impacted materially by AI. >> I still can't help but think of the original marketing quote, I've wasted half of my marketing budget, I'm just not sure which half. But, really it's not so much the waste as we have to continue to find better ways to measure the impact of all these kind of disparate non-traditional funnel things. >> I think you're right, I think it was Wanamaker who said that. I think your point is spot on, it's something we've always wrestled with, and as you move more into the branding media, they struggle more with the accountability. That's one of the reasons why direct response in the internet has been such a great mechanism, is because it's data based, you can show results. The challenge there is the attribution. But I think as we get into video, and you can get to digital video assets, and you can break it down into its component pieces, and all the different dimensions, all of that's fair game for better understanding what's working. >> Randy, really enjoyed the conversation, and thanks for taking a minute out of your busy day. >> My pleasure, always enjoy it. >> Alright, he's Randy, I'm Jeff, you're watching theCUBE from Palo Alto Studios, thanks for watching. (digital music)

>> Announcer: Live from Madrid, Spain, it's the Cube, covering HPE Discover Madrid 2017, brought to you by Hewlett Packard Enterprise. >> Welcome back to Madrid, Spain everybody, this is the Cube, the leader in live tech coverage. We're here covering HPE Discover 2017. I'm Dave Vellante with my cohost for the week, Peter Burris, Randy Meyer is back, he's the vice president and general manager Synergy and Mission Critical Solutions at Hewlett Packard Enterprise and Paul Shellerd is here, the director of the Center for Theoretical Cosmology at Cambridge University, thank you very much for coming on the Cube. >> It's a pleasure. >> Good to see you again. >> Yeah good to be back for the second time this week. I think that's, day stay outlets play too. >> Talking about computing meets the cosmos. >> Well it's exciting, yesterday we talked about Superdome Flex that we announced, we talked about it in the commercial space, where it's taking HANA and Orcale databases to the next level but there's a whole different side to what you can do with in memory compute. It's all in this high performance computing space. You think about the problems people want to solve in fluid dynamics, in forecasting, in all sorts of analytics problems, high performance compute, one of the things it does is it generates massive amounts of data that people then want to do things with. They want to compare that data to what their model said, okay can I run that against, they want to take that data and visualize it, okay how do I go do that. The more you can do that in memory, it means it's just faster to deal with because you're not going and writing this stuff off the disk, you're not moving it to another cluster back and forth, so we're seeing this burgeoning, the HPC guys would call it fat nodes, where you want to put lots of memory and eliminate the IO to go make their jobs easier and Professor Shallard will talk about a lot of that in terms of what they're doing at the Cosmos Institute, but this is a trend, you don't have to be a university. We're seeing this inside of oil and gas companies, aerospace engineering companies, anybody that's solving these complex computational problems that have an analytical element to whether it's comparative model, visualize, do something with that once you've done that. >> Paul, explain more about what it is you do. >> Well in the Cosmos Group, of which I'm the head, we're interested in two things, cosmology, which is trying to understand where the universe comes from, the whole big bang and then we're interested in black holes, particularly their collisions which produce gravitational waves, so they're the two main areas, relativity and cosmology. >> That's a big topic. I don't even know where to start, I just want to know okay what have you learned and can you summarize it for a lay person, where are you today, what can you share with us that we can understand? >> What we do is we take our mathematical models and we make predictions about the real universe and so we try and compare those to the latest observational data. We're in a particularly exciting period of time at the moment because of a flood of new data about the universe and about black holes and in the last two years, gravitational waves were discovered, there's a Nobel prize this year so lots of things are happening. It's a very data driven science so we have to try and keep up with this flood of new data which is getting larger and larger and also with new types of data, because suddenly gravitational waves are the latest thing to look at. >> What are the sources of data and new sources of data that you're tapping? >> Well, in cosmology we're mainly interested in the cosmic microwave background. >> Peter: Yeah the sources of data are the cosmos. >> Yeah right, so this is relic radiation left over from the big bang fireball, it's like a photograph of the universe, a blueprint and then also in the distribution of galaxies, so 3D maps of the universe and we've only, we're in a new age of exploration, we've only got a tiny fraction of the universe mapped so far and we're trying to extract new information about the origin of the universe from that data. In relativity, we've got these gravitational waves, these ripples in space time, they're traversing across the universe, they're essentially earthquakes in the universe and they're sound waves or seismic waves that propagate to us from these very violent events. >> I want to take you to the gravitational waves because in many respects, it's an example of a lot of what's here in action. Here's what I mean, that the experiment and correct me if I'm wrong, but it's basically, you create a, have two lasers perpendicular to each other, shooting a signal about two or three miles in that direction and it is the most precise experiment ever undertaken because what you're doing is you're measuring the time it takes for one laser versus another laser and that time is a function of the slight stretching that comes from the gravitational rays. That is an unbelievable example of edge computing, where you have just the tolerances to do that, that's not something you can send back to the cloud, you gotta do a lot of the compute right there, right? >> That's right, yes so a gravitational wave comes by and you shrink one way and you stretch the other. >> Peter: It distorts the space time. >> Yeah you become thinner and these tiny, tiny changes are what's measured and nobody expected gravitational waves to be discovered in 2015, we all thought, oh another five years, another five years, they've always been saying, we'll discover them, we'll discover them, but it happened. >> And since then, it's been used two or three times to discover new types of things and there's now a whole, I'm sure this is very centric to what you're doing, there's now a whole concept of gravitational information, can in fact becomes an entirely new branch of cosmology, have I got that right? >> Yeah you have, it's called multimessenger astronomy now because you don't just see the universe in electromagnetic waves, in light, you hear the universe. This is qualitatively different, it's sound waves coming across the universe and so combining these two, the latest event was where they heard the event first, then they turned their telescope and they saw it. So much information came out of that, even information about cosmology, because these signals are traveling hundreds of billions of light years across to us, we're getting a picture of the whole universe as they propagate all that way, so we're able to measure the expansion rate of the universe from that point. >> The techniques for the observational, the technology for observation, what is that, how has that evolved? >> Well you've got the wrong guy here. I'm from the theory group, we're doing the predictions and these guys with their incredible technology, are seeing the data, seeing and it's imagined, the whole point is you've gotta get the predictions and then you've gotta look in the data for a needle in the haystack which is this signature of these black holes colliding. >> You think about that, I have a model, I'm looking for the needle in the haystack, that's a different way to describe an in memory analytic search pattern recognition problem, that's really what it is. This is the world's largest pattern recognition problem. >> Most precise, and literally. >> And that's an observation that confirms your theory right? >> Confirms the theory, maybe it was your theory. >> I'm actually a cosmologist, so in my group we have relativists who are actively working on the black hole collisions and making predictions about this stuff. >> But they're dampening vibration from passing trucks and these things and correcting it, it's unbelievable. But coming back to the technology, the technology is, one of the reasons why this becomes so exciting and becomes practical is because for the first time, the technology has gotten to the point where you can assume that the problem you're trying to solve, that you're focused on and you don't have to translate it in technology terms, so talk a little bit about, because in many respects, that's where business is. Business wants to be able to focus on the problem and how to think the problem differently and have the technology to just respond. They don't want to have to start with the technology and then imagine what they can do with it. >> I think from our point of view, it's a very fast moving field, things are changing, new data's coming in. The data's getting bigger and bigger because instruments are getting packed tighter and tighter, there's more information, so we've got a computational problem as well, so we've got to get more computational power but there's new types of data, like suddenly there's gravitational waves. There's new types of analysis that we want to do so we want to be able to look at this data in a very flexible way and ingest it and explore new ideas more quickly because things are happening so fast, so that's why we've adopted this in memory paradigm for a number of years now and the latest incarnation of this is the HP Superdome flex and that's a shared memory system, so you can just pull in all your data and explore it without carefully programming how the memory is distributed around. We find this is very easy for our users to develop data analytic pipelines to develop their new theoretical models and to compare the two on the single system. It's also very easy for new users to use. You don't have to be an advanced programmer to get going, you can just stay with the science in a sense. >> You gotta have a PhD in Physics to do great in Physics, you don't have to have a PhD in Physics and technology. >> That's right, yeah it's a very flexible program. A flexible architecture with which to program so you can more or less take your laptop pipeline, develop your pipeline on a laptop, take it to the Superdome and then scale it up to these huge memory problems. >> And get it done fast and you can iterate. >> You know these are the most brilliant scientists in the world, bar none, I made the analogy the other day. >> Oh, thanks. >> You're supposed to say aw, chucks. >> Peter: Aw, chucks. >> Present company excepted. >> Oh yeah, that's right. >> I made the analogy of, imagine I.M. Pei or Frank Lloyd Wright or someone had to be their own general contractor, right? No, they're brilliant at designing architectures and imagining things that no one else could imagine and then they had people to go do that. This allows the people to focus on the brilliance of the science without having to go become the expert programmer, we see that in business too. Parallel programming techniques are difficult, spoken like an old tandem guy, parallelism is hard but to the extent that you can free yourself up and focus on the problem and not have to mess around with that, it makes life easier. Some problems parallelize well, but a lot of them don't need to be and you can allow the data to shine, you can allow the science to shine. >> Is it correct that the barrier in your ability to reach a conclusion or make a discovery is the ability to find that needle in a haystack or maybe there are many, but. >> Well, if you're talking about obstacles to progress, I would say computational power isn't the obstacle, it's developing the software pipelines and it's the human personnel, the smart people writing the codes that can look for the needle in the haystack who have the efficient algorithms to do that and if they're cobbled by having to think very hard about the hardware and the architecture they're working with and how they've parallelized the problem, our philosophy is much more that you solve the problem, you validate it, it can be quite inefficient if you like, but as long as it's a working program that gets you to where you want, then your second stage you worry about making it efficient, putting it on accelerators, putting it on GPUs, making it go really fast and that's, for many years now we've bought these very flexible shared memory or in memory is the new word for it, in memory architectures which allow new users, graduate students to come straight in without a Master's degree in high performance computing, they can start to tackle problems straight away. >> It's interesting, we hear the same, you talk about it at the outer reaches of the universe, I hear it at the inner reaches of the universe from the life sciences companies, we want to map the genome and we want to understand the interaction of various drug combinations with that genetic structure to say can I tune exactly a vaccine or a drug or something else for that patient's genetic makeup to improve medical outcomes? The same kind of problem, I want to have all this data that I have to run against a complex genome sequence to find the one that gets me to the answer. From the macro to the micro, we hear this problem in all different sorts of languages. >> One of the things we have our clients, mainly in business asking us all the time, is with each, let me step back, as analysts, not the smartest people in the world, as you'll attest I'm sure for real, as analysts, we like to talk about change and we always talked about mainframe being replaced by minicomputer being replaced by this or that. I like to talk in terms of the problems that computing's been able to take on, it's been able to take on increasingly complex, challenging, more difficult problems as a consequence of the advance of technology, very much like you're saying, the advance of technology allows us to focus increasingly on the problem. What kinds of problems do you think physicists are gonna be able to attack in the next five years or so as we think about the combination of increasingly powerful computing and an increasingly simple approach to use it? >> I think the simplification you're indicating here is really going to more memory. Holding your whole workload in memory, so that you, one of the biggest bottlenecks we find is ingesting the data and then writing it out, but if you can do everything at once, then that's the key element, so one of the things we've been working on a great deal is in situ visualization for example, so that you see the black holes coming together and you see that you've set the right parameters, they haven't missed each other or something's gone wrong with your simulation, so that you do the post-processing at the same time, you never need the intermediate data products, so larger and larger memory and the computational power that balances with that large memory. It's all very well to get a fat node, but you don't have the computational power to use all those terrabytes, so that's why this in memory architecture of the Superdome Flex is much more balanced between the two. What are the problems that we're looking forward to in terms of physics? Well, in cosmology we're looking for these hints about the origin of the universe and we've made a lot of progress analyzing the Plank satellite data about the cosmic microwave background. We're honing in on theories of inflation, which is where all the structure in the universe comes from, from Heisenberg's uncertainty principle, rapid period of expansion just like inflation in the financial markets in the very early universe, okay and so we're trying to identify can we distinguish between different types and are they gonna tell us whether the universe comes from a higher dimensional theory, ten dimensions, gets reduced to three plus one or lots of clues like that, we're looking for statistical fingerprints of these different models. In gravitational waves of course, this whole new area, we think of the cosmic microwave background as a photograph of the early universe, well in fact gravitational waves look right back to the earliest moment, fractions of a nanosecond after the big bang and so it may be that the answers, the clues that we're looking for come from gravitational waves and of course there's so much in astrophysics that we'll learn about compact objects, about neutron stars, about the most energetic events there are in the whole universe. >> I never thought about the idea, because cosmic radiation background goes back what, about 300,000 years if that's right. >> Yeah that's right, you're very well informed, 400,000 years because 300 is. >> Not that well informed. >> 370,000. >> I never thought about the idea of gravitational waves as being noise from the big bang and you make sense with that. >> Well with the cosmic microwave background, we're actually looking for a primordial signal from the big bang, from inflation, so it's yeah. Well anyway, what were you gonna say Randy? >> No, I just, it's amazing the frontiers we're heading down, it's kind of an honor to be able to enable some of these things, I've spent 30 years in the technology business and heard customers tell me you transformed by business or you helped me save costs, you helped me enter a new market. Never before in 30 plus years of being in this business have I had somebody tell me the things that you're providing are helping me understand the origins of the universe. It's an honor to be affiliated with you guys. >> Oh no, the honor's mine Randy, you're producing the hardware, the tools that allow us to do this work. >> Well now the honor's ours for coming onto the Cube. >> That's right, how do we learn more about your work and your discoveries, inclusions. >> In terms of looking at. >> Are there popular authors we could read other than Stephen Hawking? >> Well, read Stephen's books, they're very good, he's got a new one called A Briefer History of Time so it's more accessible than the Brief History of Time. >> So your website is. >> Yeah our website is ctc.cam.ac.uk, the center for theoretical cosmology and we've got some popular pages there, we've got some news stories about the latest things that have happened like the HP partnership that we're developing and some nice videos about the work that we're doing actually, very nice videos of that. >> Certainly, there were several videos run here this week that if people haven't seen them, go out, they're available on Youtube, they're available at your website, they're on Stephen's Facebook page also I think. >> Can you share that website again? >> Well, actually you can get the beautiful videos of Stephen and the rest of his group on the Discover website, is that right? >> I believe so. >> So that's at HP Discover website, but your website is? >> Is ctc.cam.ac.uk and we're just about to upload those videos ourselves. >> Can I make a marketing suggestion. >> Yeah. >> Simplify that. >> Ctc.cam.ac.uk. >> Yeah right, thank you. >> We gotta get the Cube at one of these conferences, one of these physics conferences and talk about gravitational waves. >> Bone up a little bit, you're kind of embarrassing us here, 100,000 years off. >> He's better informed than you are. >> You didn't need to remind me sir. Thanks very much for coming on the Cube, great pleasure having you today. >> Thank you. >> Keep it right there everybody, Mr. Universe and I will be back after this short break. (upbeat techno music)

>> Announcer: Live from Madrid, Spain. It's the Cube. Covering HP Discover Madrid 2017. Brought to you by Hewlett Packard Enterprise. >> Good afternoon from Madrid everybody. Good morning on the East Coast. Good really early morning on the West Coast. This is the Cube, the leader in live tech coverage. We're here day one at HPE Discover Madrid 2017. My name is Dave Velonte, I'm here with my cohost Peter Berse. Randy Meyers here is the Vice President and General Manager of the Mission Critical business unit at Hewlett Packard Enterprise. And he's joined by Alexander Zhuk, who is the SAP practice lead at Eldorado. Welcome to the Cube, thanks for coming on. >> Thanks for having us. >> Thank you. >> Randy we were just reminiscing about the number of times you've been on the Cube, consecutive years, it's like the Patriots winning the AFC East it just keeps happening. >> Or Cal Ripkin would probably be you. >> Me and Tom Brady. >> You're the Cal Ripken of the Cube. So give us the update, what's happening in the Mission Critical Business unit. What's going on here at Discover. >> Well, actually just lots of exciting things going on, in fact we just finished the main general session keynote. And that was the coming out party for our new Superdome Flex product. So, we've been in the Mission Critical space for quite some time now. Driving the HANA business, we've got 2500 customers around the world, small, large. And with out acquisition last year of SGI, we got this fabulous technology, that not only scales up to the biggest and most baddest thing that you can imagine to the point where we're talking about Stephen Hawking using that to explore the universe. But it scales down, four sockets, one terabyte, for lots of customers doing various things. So I look at that part of the Mission Critical business, and it's just so exciting to take technology, and watch it scale both directions, to the biggest problems that are out there, whether they are commercial and enterprise, and Alexander will talk about lots of things we're doing in that space. Or even high performance computing now, so we've kind of expanded into that arena. So, that's really the big news Super Dome Flex coming out, and really expanding that customer base. >> Yeah, Super Dome Flex, any memory in that baby? (laughing) >> 32 sockets, 48 terabyte if you want to go that big, and it will get bigger and bigger and bigger over time as we get more density that's there. And we really do have customers in the commercial space using that. I've got customers that are building massive ERP systems, massive data warehouses to address that kind of memory. >> Alright, let's hear from the customer. Alexander, first of all, tell us about your role, and tell us about Eldorado. >> I'm responsible for SAP basis and infrastructure. I'm working in Eldorado who is one of the largest consumer electronics network in Russia. We have more than 600 shops all over the country in more than 200 cities and towns, and have more than 16,000 employees. We have more than 50,000 stock keeping units, and proceeding over three and a half million orders with our international primarily. >> SAP practice lead, obviously this is a HANA story, so can you take us through your HANA journey, what led to the decision for HANA, maybe give us the before, during and after. Leading up to the decision to move to HANA, what was life like, and why HANA? >> We first moved our business warehouse system to HANA back in 2011. It's a time we got strong business requirements to have weak reporting. So, retail business, it's a business whose needs and very rapid decision making. So after we moved to HANA, we get the speed increasing of reports giving at 15 times. We got stock replenishment reports nine times faster. We got 50 minute sales reports every hour, instead of two hours. May I repeat this? >> No, it makes sense. So, the move to HANA was really precipitated by a need to get more data faster, so in memory allows you to do that. What about the infrastructure platform underneath, was it always HP at the time, that was 2011. What's HP's role, HPE's role in that, HANA? >> Initially we were on our business system in Germany, primarily on IBM solutions. But then according to the law requirements, we intended to go to Russia. And here we choose HP solutions as the main platform for our HANA database and traditional data bases. >> Okay Data residency forced you to move this whole solution back to Russia. If I may, Dave, one of the things that we're talking about and I want to test this with you, Alexander, is businesses not only have to be able to scale, but we talk about plastic infrastructure, where they have to be able to change their work loads. They have to be able to go up and down, but they also have to be able to add quickly. As you went through the migration process, how were you able to use the technology to introduce new capabilities into the systems to help your business to grow even faster? >> At that time, before migration, we had strong business requirements for our business growing and had some forecasts how HANA will grow. So we represented to our possible partners, our needs, for example, our main requirement was the possibility to scale up our CRM system up to nine terabytes memory. So, at that time, there was only HP who could provide that kind of solution. >> So, you migrated from a traditional RDBMS environment, your data warehouse previously was a traditional data base, is that right? And then you moved to HANA? >> Not all systems, but the most critical, the most speed critical system, it's our business warehouse and our CRM system. >> How hard was that? So, the EDW and the CRM, how difficult was that migration, did you have to freeze code, was it a painful migration? >> Yes, from the application point of view it was very painful, because we had to change everything, some our reports they had to be completely changed, reviewed, they had to adopt some abap code for the new data base. Also, we got some HANA level troubles, because it was very elaborate. >> Early days of HANA, I think it was announced in 2011. Maybe 2012... (laughing) >> That's one of the things for most customers that we talk to, it's a journey. You're moving from a tried and true environment that you've run for years, but you want the benefits in memory of speed, of massive data that you can use to change your business. But you have to plan that. It was a great point. You have to plan it's gonna scale up, some things might have to scale out, and at the same time you have to think about the application migration, the data migration, the data residency rules, different countries have different rules on what has to be there. And I think that's one of the things we try to take into account as HPE when we're designing systems. I want to let you partition them. I want to let you scale them up or down depending on the work load that's there. Because you don't just have one, you have BW and CRM, you have development environments, test environments, staging environments. The more we can help that look similar, and give you flexibility, the easier that is for customers. And then I think it's incumbent on us also to make sure we support our customers with knowledge, service, expertise, because it really is a journey, but you're right, 2011 it was the Wild West. >> So, give us the HPE HANA commercial. Everybody always tells us, we're great at HANA, we're best at HANA. What makes HPE best at HANA, different with HANA? >> What makes us best at HANA, one, we're all in on this, we have a partnership with SAP, we're designing for the large scale, as you said, that nobody else is building up into this space. Lots of people are building one terabyte things, okay. But when you really want to get real, when you want to get to 12 terabytes, when you want to get to 24 to 48. We're not only building systems capable of that, we're doing co-engineering and co-innovation work with SAP to make that work, to test that. I put systems on site in Waldorf, Germany, to allow them to go do that. We'll go diagnose software issues in the HANA code jointly, and say, here's where you're stressing that, and how we can go leverage that. You couple that with our services capability, and our move towards, you'll consume HANA in a lot of different ways. There will be some of it that you want on premise, in house, there will be some things that you say, that part of it might want to be in the Cloud. Yes, my answer to all of those things is yes. How do I make it easy to fit your business model, your business requirements, and the way you want to consume things economically? How do I alow you to say yes to that? 2500 customers, more than half of the installed base of all HANA systems worldwide reside on Hewlett Packard Enterprise. I think we're doing a pretty good job of enabling customers to say, that's a real choice that we can go forward with, not just today, but tomorrow. >> Alexander, are you doing things in the Cloud? I'm sure you are, what are you doing in the Cloud? Are you doing HANA in the Cloud? >> We have not traditional Cloud, as to use it to say, now we have a private Cloud. We have during some circumstance, we got all the hardware into our property. Now, it's operating by our partner. Between two company they are responsible for all those layers from hardware layer, service contracts, hardware maintenance, to the basic operation systems support, SEP support. >> So, if you had to do it all over again, what might you do differently? What advice would you give to other customers going down this journey? >> My advice is to at first, choose the right team and the right service provider. Because when you go to solution, some technical overview, architectural overview, you should get some confirmation from vendor. At first, it should be confirmed by HP. It should be confirmed by SEP. Also, there is a financial question, how to sponsor all this thing. And we got all these things from HP and our service partner. >> Right, give you the last word. >> So, one, it's an exciting time. We're watching this explosion of data happening. I believe we've only just scratched the surface. Today, we're looking at tens of thousands of skews for a customer, and looking at the velocity of that going through a retail chain. But every device that we have, is gonna have a sensor in it, it's gonna be connected all the time. It's gonna be generating data to the point where you say, I'm gonna keep it, and I'm gonna use it, because it's gonna let me take real time action. Some day they will be able to know that the mobile phone they care about is in their store, and pop up an offer to a customer that's exactly meaningful to do that. That confluence of sensor data, location data, all the things that we will generate over time. The ability to take action on that in real time, whether it's fix a part before it fails, create a marketing offer to the person that's already in the store, that allows them to buy more. That allows us to search the universe, in search for how did we all get here. That's what's happening with data. It is exploding. We are at the very front edge of what I think is gonna be transformative for businesses and organizations everywhere. It is cool. I think the advent of in memory, data analytics, real time, it's gonna change how we work, it's gonna change how we play. Frankly, it's gonna change human kind when we watch some of these researchers doing things on a massive level. It's pretty cool. >> Yeah, and the key is being able to do that wherever the data lives. >> Randy: Absolutely >> Gentlemen, thanks very much for coming on the Cube. >> Thank you for having us. >> Your welcome, great to see you guys again. Alright, keep it right there everybody, Peter and I will be back with our next guest, right after this short break. This is the Cube, we're live from HPE Discover Madrid 2017. We'll be right back. (upbeat music)

>> Live from Las Vegas, it's theCube. Covering VMworld 2017. Brought to you by vmware and it's ecosystem partner. (techno beat) >> I'm Stu Miniman and this is theCube. Happy to welcome back to the program two guests we've had on a few times. Randy Arseneau, who's the CMO of Inifindat, and Bryan Carmody who's the CTO at Inifinidat. Gentlemen, thanks so much for joining us. >> Hey, Stu, what's going on? >> Thanks, Stu, good to be here. >> Alright, so, it's Vmworld time again, a lot going on. We set, kind of a vibe of the show already. It's about the same attendance as last year, but the vibe feels good. Pat is actually hitting the stride on the keynote, talking about Amazon, talking about momentum that they have. You guys have had some announcements recently. Randy, why don't you start us off. Tell us about, you know, the update of Inifinidat, how many customers you've got, what can you share? >> So, thanks, Stu, thanks for having us again, it's great to, great to be back on theCube. So, yeah, we've, over the last few years, three and a half years that we've been shipping our product, we've been able to sustain a really good, consistent cadence of growth, and that's continued into this year. So, a few weeks ago, a couple weeks ago, we announced our most recent performance, financial performance. We're continuing to more than double each quarter year over year. We are profitable from a gap revenue perspective, which is kind of unheard of in our industry, so we think we're breaking the trend of a lot of the storage startups, and even some established storage players that are having a really difficult time making their financial and business model and go to market work. Ours is clearly working, we're generating revenue, we're growing our customer base. We now have over two exabytes of storage in service world wide. We figured out about 80-ish, 80 percent, plus or minus a couple of percentage points of that is running vmware. So, we think this is kind of an obvious place for us to be in terms of the affinities of our customer base. And about 50 percent of our systems are actually dedicated to vmware, so they're running huge vmware farms. So, the financial performance has continued to be really solid, we're bucking the trend in the industry in terms of being profitable, and continuing to grow the business at a really aggressive rate. Because the solution works, I mean it's not rocket science, right, we have a product. >> I hear you have trouble raising money if you're profitable, so that's challenging. Yeah, and congratulations on the momentum. The joke a few years ago have been Vmworld became storage world, and you know, we spent years talking about, oh it's, you know flash is there, and then the software to find data center. The only mention of like, storage that I really heard in the keynote this morning was Pat talking about "Oh, they've got about 10,000 customers running vsand." So, Bryan, a lot of waves going on, we've had a number of conversations about where you fit, bring us up to speed as to, you know, what are the conversations you're having with customers, you know, what are the important trends to them, and where your technology, how do you position yourselves there? >> Oh, sure, so I mean, I think from customers perspectives it's all just storage, they're all data stores, and the different architectures, and the different delivery models are, they don't really matter at the end of the day. What your CIO, which he cares about, is what is the acquisition cost, what's the operational cost? What's the performance that it delivers, the latency in through put? And what's the availability of the data store? And, you know, what we're seeing, especially with the software defined storage systems, and vsands, is they work, but they work for small capacities, when you try to scale them, what every customer, without exception, sees is that they add three dollars in server cost for every dollar in storage array cost avoidance. So, you know, these projects tend to not be very, they tend to be career limiting, you know, and that's why what we're hearing, especially at Wall Street, is that it's vscam, not vsand. >> Stu: Wow. >> Yeah, but for small workloads where, and environments where you're looking to get a, you have a single person who needs to do storage, and manage the hyper visors, it absolutely works. I think it's a, it's a killer robome and small business solution. >> Yeah, it's interesting, cos there's this growth of solutions that use storage, but they aren't in a position to storage, and vsands, and a lot of hyper conversions like that. >> I like the virtualization admin, I've got some app, I just want a management, I don't have to want a, you know, God, that storage stuff's hard. You know, so they'll kind of do that pieces, versus, you know, real storage, you know, like care about reliability. >> Go ask Pat what the average size of those customers are. Like, my grandmother is one of those customers, you know, she uses it. But, yeah, so I >> You come from a heavy technology family, though, so. >> Yes, exactly. She was the first vm certified person I probably know. So, clearly the part of the market that we're going after is very different from that. Our systems start at, well they get interesting at a petabyte of usable capacity. By far our most popular model is a petabyte and a half of effective capacity. Our largest system scales up to ten petabytes in a single system manage, in a single rack. So, these are big monster cloud scale vmware environments. That's where, you know, our customers are having awesome success. And you know, it's not just limited to vmware, though. You know, you can take the same system, the same skew, and you can use it to replace data domain systems for backup to disc. The largest splunk insulation in the world is running at one of the US, big US telecoms and is running the same skew that our customers are using for their big petabyte scale vmware environments. Analytics, which is probably the biggest growing thing, one area that Randy is working pretty heavily in, it's absolutely exploding. >> Yeah, it's, which is cool in a sense, because we've been, you know, and I kind of use the tongue in cheek term "accidental tourists." I mean, we sell this system into an incredibly wide range of workload environments, and enterprise environments. Which is why we have a really strong presence in every vertical, I mean we're strong in health care and life sciences, we're strong in financial services, we're strong in retail and manufacturing, we're strong in utilities, we're strong in cloud providers. And it's exactly because of the fact that the system is designed and architected expressly to be very flexible and very adaptable. So, we never shy away from the concept of general purpose storage, I mean that became very unfashionable about five or six years ago, when everything had to be hyper-specialized and fit for purpose. But, when we can walk into an environment, and as Bryan said, most of our customers tend to be fairly, you know, midsize and large enterprises, they don't have one particular type or class of workload, they've got 100. And they're running 100 different storage systems. So we can go in as a consolidation play and say "Look, let's take all of that vmware environment, all of that, you know, take your data domain and your backup protection environment, your analytic workload environments, and move them off of these disparate platforms onto this one, you know, very capable, very flexible system. They all peacefully coexist, they all perform phenomenally well. It's immensely easy. We have a customer presentation that's going to be talking about exactly how easy it is. We have another Cube session where another one of our customers is going to share the beauty of integration and orchestration automation using our API. So, we kind of have a large enterprise class, extremely flexible, fully composable storage system that you can really plugin anywhere. I mean, we've talked before about how in some environments, there might be one or two little fringe applications somewhere that require some weird configuration of flash, or you know, in memory database or something that's five terabytes, that's running on some strange system, and that's fine, like, we're happy to leave that there. We will go after the other 95 percent of the workloads in your environments and we'll take them all, and do so very happily. >> Yeah, it's interesting, we tracked kind of that wave of big data, and especially like hadoop, and I went to all of these shows and they'd be like "Oh, you know, hgfs, you know, don't put it on a storage array because it's too expensive!" And when you dug into it, it was, you know, a couple of servers sitting under somebody's desk. >> Right. >> So, it wasn't real storage, like you said, but it was cost, and it was there, but what I'm excited about is when I'm hearing about the new kind of analytics things. When you start talking about, you know, AI and machine learning, and everything like that, you've got to have, you've got real storage issues, and how are you attacking the price, and how are you architecting to be ready for those types of applications? >> Yeah, and to Bryan's point the telecoms we've got the one running the largest splunk environment of the world, we've got another that's running a huge elk environment, the architect presented at elasticon this year, that's all running on Inifinibox. So, again, we haven't specifically architected the solution necessarily for those, but our customers, you know, God bless 'em, bring it in, plug it in, try it, because it's so simple, there's really no downside to experimenting with it, and they discover "Wow, this actually works exceptionally well." >> Yeah, and I think if, if you kind of step back from specific workloads, analytics or vmware, or whatever, what customers for the next decade are asking for is pretty consistent. And it's pretty easy to understand. They want to be able to do sub-millisecond response times. They want to do very high multi-gigabyte per second, throughput. They want to do it over petabyte scale datacents, and they want to do it at a vastly lower cost per gigabyte than the kind of traditional enterprise storage products. And if you build that, they will come. And I think that's what we did, and I think it's a huge part of, you know, the success that our customers are having. And the momentum that kind of our company has right now, is just doing all of those things simultaneously. >> Alright, so, from a price standpoint, I mean, price and simplicity, kind of been the things that we've been beaten on for the storage industry. You know, what, how do you position that, you know, what is kind of the killer, you know, thing that makes the customers come to you and say, you know, "Wow, you guys are different and that's going to solve." >> You know, so, we unabashedly, in every business school, you know, whatever, they tell you "Don't sell on price, sell on value," and we have kind of been doing the opposite of that. Since day one, since day one. The first communication to a potential customer is we put a number out there. That number will be a tenth, on a cost per gig basis, of, you know, of what they're paying today. And it's a, it's something that nobody can say no to, it's a demonstration that we're really serious about what we're capable of doing. So, then that only works if you back it up, then, when the customer does an evaluation, and the bake offs, and the competitive stuff. You have to absolutely destroy everything else out there, or else you get pigeonholed as a tier two, a tier three. And I think a lot of the, a lot of the newer companies are kind of falling into that, where they're, they have traction, but they're really not getting into enterprise accounts, they're not getting life safety and mission critical workloads put on them. So, we unabashedly lead with price, and, you know, at the end of the day, every time you instantiate a cost function reduction, in storage, it makes new types of computing possible. You put that storage in the hands of developers, and they tell their management teams "Here's what we can do with this." We are trying to make storage less expensive. >> Yeah, and although, you know, you're not supposed to sell on price, you sell on value, the problem is nobody buys on value, so you still have to be price sensitive. And you have to have a solution that is economically feasible, and viable, and attractive. So, we've got a very, very attractive TCO structure and model that we've used in just about every of our major sales campaigns. And we have to monstroubly, significantly lower cost, not just of acquisition, but of ongoing operation. So, when you layer all those things together, you can sell to the pure technologists who love the kind of robustness and the feature richness of the capability, and where they can apply it, and how they can apply it, but it also has a very attractive financial story, so when you're selling it to the business owners and the kind of, you know, other constituencies, it's a story that everybody likes, so. >> Yeah, lot of people in the storage industry, it's always, you know, that next thing, flash was a wavy road for a while, you know, when I go talk to the storage geeks, it's the "Oh, nvme over fabric." It's going to dramatically change everything. >> Bryan: It is. >> What's your take? >> Oh, yeah, yeah, it's huge, it's huge. You know, it's always a catch up game between the network and the transport technologies, and then the storage media. So, you know, nvme over fabric's is huge, but you know, you have to use it the right way, and I think that it's not being used correctly by the marketers, you know, who are running you know. A lot of the storage companies, they're using it as a way to justify their pricing. They're using it as a way to make storage expensive. And it's kind of the, again, it's the opposite of our strategy. What every customer is demanding from their vendors, is "I need my storage next quarter to be less expensive than it is, this quarter next year needs to be cheaper than this year, how are you going to do that for me?" So, advanced technologies, like, nvme and nvme over fabrics, and optane and three d crosspoint, these things all have, they're incredibly strategic technologies. But, you have to use them the right way, you have to always keep an eye on the bottom line, and be very suspicious of technologists that are trying to make infrastructure more expensive, rather than less. >> Yeah, and I mean, it's always, it's not just the technology, it's the application, and I think a lot of vendors in our space have a tendency to focus exclusively on the technology, and how to build an architecture around it, or repurpose an existing architecture, more commonly, without really thinking about the application of that technology. Where is it going to be used, how is it going to be used, what's the cost structure have to look like, what's the use-case environment look like, what verticals am I going to sell it to, what's the channel ecosystem look like? They kind of tend to save that for the last, so they develop this whiz bang, you know, solution, which is again, typically, an aging architecture that maybe has some new foundational layers of technology or media built into it, without really thinking about the end game. So, that's one of the many things that I think Moshe Yanai does better than anybody, is he looks at the problem from the outside in. He meets with customers on a daily basis, I mean, he's kind of a maniac in terms of traveling around and meeting with customers. He has a phenomenal reputation, for obvious reasons, and he listens. He listens to their problems, he listens to what they confront and what they fight with every day, to kind of make a solution that works for them, and then he adapts that to his design ethos. Not, it's not the other way around. So, we don't develop something and then go try to force fit it into a market or into an environment. >> Yeah, last thing I wanted to ask you is; users coming to a show like this, they love to be able to hear from their peers, you've got a whole bunch of customers telling their stories, what are some of the key takeaways that, you know, peers talking to peers, that they're going to be hearing this week at the show? >> Yeah, so, there's, it's a lot of the same things we've been talking about here, you know. It's cost takeout, frankly, I mean, first and foremost, these are customers that are under tremendous cost pressure. They have used us as a consolidation platform to take costs out, but deliver a higher quality of service. We have, so we have a breakfast we organize, we've got a bunch of our customers. The other thing I love about our customers is they have a tendency to be kind of groupies, and I use that term you know, very favorably, because they're immensely loyal to the system, because it simply makes their life better and easier and allows them to focus on other tasks. So, they're talking about cost reduction and consolidation, they're talking about delivering higher performance. Very, very simply, they're talking about the ease of integration and orchestration and automation using our API. So, plugging our system in and just, it becomes a magnet for workloads. They bring it in for a particular project, and as other growth occurs, in insularly areas, it just gets moved on to the infinibox because it's incredibly easy, and it's a painless, seamless, frictionless process, so. >> Bryan, I'm going to give you a final word, takeaways for the show that you want people to have from Infinidat. >> Oh, I just, I really want everybody to have a great time, come by, check out the booth, we have an espresso machine, we'll talk a little bit about some of the computer science behind the system, and, but more than anything, I want everybody to have a really good time at the event. >> Well, great point, everybody, Vmworld, always a great community, lots of great conversations, everybody geeking out on the technology, and getting some caffeine to help them through what is a very long week. So, we're at the beginning of three days of live coverage here, double set. Thank you, Randy Arseneau, Bryan Carmody. >> Thanks, Stu, if you chroma key my shirt, just be gentle, that's all I ask, thank you. >> Alright, we'll be back with lots more coverage. Thanks for watching theCube. (techno music)