>>Hey everyone. Welcome back to Miami, Miami Beach. Specifically, not a bad location to have a conference. Lisa Martin here with the Cube live at IFS Unleashed. We're gonna be having a great conversation next about Ization moments of Service Rules. Royces here, as is the C of IFS for aerospace and defense. Scott Camani. Nick Ward joins us as well, the VP of Digital Systems at Roll Royce. Guys, excited to have you on the program and welcome back. >>Thank you very much. Nice to be back. It's >>Been three years since the last IFS show. I love How's Scott? I was talking with Darren Roots earlier today and I said, Well, didn't it used to be IFS world? And he said, Yes. And I said, I love the name. I would love to, to unpack that with your cheek marketing officer because it, there's a lot of, of, of power behind Unleash. A lot of companies do such and such world or accelerate, but we're talking about unleashing the power of the technology to help customers deliver those moments of service. Yes. Love it. So Scott, start us off here. Talk about ization. That's a relatively new term to me. Sure. Help me understand what it means, because IFS is a pioneer in this sense. >>We are. So one of the things that IFS is always trying to do is to try to find a way to help our customers to realize a moment of service. And that moment of service is really when they found the ability to delight their customers. And when we look at the way in which we're trying to drive those business outcomes for our customers, ization seems to be at the core of it. So whether it's the ability for a company to use a product, a service, or an outcome, they're driving ization in a way where they're shaping their business. They're orchestrating their customers and their people and their assets behind a val value chain that helps them to provide a delightful experience for their customers. And with IFS being focused on Lifecycle asset management, we no longer have customers that have to choose from best of suite or best of breed. They can actually have both with ifs. And that's something we're really excited to provide to our customers and more excited for our customers to realize that value with their customers, their partners. Along the way. >>You, you mentioned customer delight and it's a term that we, we all use it, right? But there's so much power and, and capabilities and metrics behind that phrase, customer delight, which will unpack Nick bringing you into the conversation. Talk to us a little bit about what your role is at Rolls Royce. My first thought when I saw you was, oh, the fancy cars, but we're talking about aerospace and the fence, so give us a little bit of a history. >>Okay. So yes, we don't make cars is the first point. So we are, we are power, we do power as a service. So we are most well known, I guess for large aircraft airliners. You know, if you've, if you've flown here to Miami, there's probably a 50 50 chance you've flown on a Rod Roy powered aircraft. Our market segment is what we call wide bodied aircraft where you go on, there's two aisles. So the larger section of the market, and we, we provide power, so we provide the engines, but more importantly, we've been a ization company, a service company for at least two decades. We, we have a, a service relationship we call total care. And the whole idea of total care is, yes, I have my engine, it's on my aircraft, but I take care of it. I make sure it's available to fly when you need to fly it. And all of the things that have to come together to make that happen, it's a service company. >>Service company. Talk to me a little bit about, and I wanna get got your perspective as well, but the relationship that Roll Royce and IFS have this is a little bit unique. >>Well, I can start, but I I think Nick's gonna be better served to tell us about that as our customer. Nick and I actually started this journey about four years ago, and what we did was, is we were working closely with our perspective customer Rolls-Royce identified what they were looking for as a desired business outcome. And then we found a way through the technology and the software that we provide to all of our enterprise customers globally to find a solution that actually helped to provide a, an outcome not only to Rolls-Royce, but also to our collective downstream customers, commercial operators around the globe. So that's where we started the journey and we're continuing our discussions around other solutions, but that's how we started and it's been an incredible partnership. We're so happy and proud to have Nick as a customer and a advocate of all things ifs and I'll let him kind of continue from his point of view how he sees the partnership in the relationship. >>No, thank you Scott. I think we've, we've always, we've valued the kind of relationship that we have because I think IFS has always got Rolls Royce in terms of strategic direction. What do we try to do? I said, we're a service company. You know, we, we are, we have to have a service relationship with our, our customers, our airlines. To have a service relationship, you have to be able to connect to your service customer. And ifs is a big part of how we connect for data. That's how do we understand what the airline is doing with the engines, but it's also how we return data back into the airline. So we are, we're get a very close integrated relation between us, our airlines, through a bridge that, that ifs create through the maintenance product. Got it. So it works really well. >>I I think I'd make one other point. One of the things that we've always focused on is quantifiable business value. The only way a partnership like this could possibly work is if we have a desired business outcome, but if we're providing value, So the value work that we did in conjunction with Rolls Royce and really identifying that helped to support the business case that allowed this partnership to really begin and flourish. So I I, I'd be remiss if I didn't mention that business value element that's really core to everything we do and all the, the conversations that Nick and I have. >>Well, it's all about outcomes. Absolutely. It's all about outcomes. It >>Is, it has to be about, it's about moments of service, right? That's why we're here, right? So perhaps a moment of service for Robs Royce is every time you're a passenger, you're going through the terminal. You expect your aircraft to be there, ready, waiting for you to get on and depart on time. And our moment of service is every aircraft takes off on time, every time we live. When we die by the quality of that statement, how well we live up to that statement, I think I checked this morning, there's something alike, 600 aircraft in the sky right now with Rolls Royce power carrying passengers. All of those passengers have relied on that moment. Service happening regularly like clockwork. Every single time you don't get any forgiveness for a delay, you get very little forgiveness for a cancellation that has to happen. And then so many things have to come together for that to happen. >>Those 600 aircraft, that's maybe 200,000 people right now in the sky, Wow. Those 200,000 people are trying to connect, They're trying to connect with friends, they're trying to connect with loved ones, family, colleagues, whatever the purpose is of that trip. It's really important to them. And we just have to make sure that that happens for us. We've had something like a million flights so far this year, 300 million people relying on that moment of so is happening. So I really resonate with, with the language that Scott users about the importance of sort of that focal point on when does it all come together? It comes together when as a passenger, I get on the plane and it goes and I get no issues. >>Right. Well people don't tolerate fragmented experiences anymore. No, no. I think one of the things that was in short supply during the pandemic was patience and tolerance. Sure. Not sure how much of that's gonna come back, right? But those integrated connected experiences, as you described so eloquently, Nick, those are table stakes for the customers, but also the brands behind them because of customers are unhappy, the churn rates go way up. And you see that reflected in obviously the success of the business and what you guys are doing together is seems to be quite powerful. Now then when you were on the cube with us three years ago in Boston at IFS back then you first introduced the intelligent engine and the Blue Data thread. Let's talk about the intelligent engine. Just give our audience a refresher of what that actually entails. >>So perhaps if we just step one one step back for that, just to understand how this fits in. So Roro is a service organization. We talked about that. What that means is we take a lot of the, the risk and the uncertainty away from our airline customers on the availability, the costs and maintenance effort associated with having a, having a chat engine. These are incredibly complicated and complex and sophisticated pieces of equipment. The most expensive, most sophisticated pieces of an aircraft. Managing that is, is difficult. And every airline does not want to have to focus on that. They wanna focus on being able to get the passenger on the air after, fly it, look after the airframe. So our role in that is to take that risk away, is to manage those engines, look after their health, look after their life, make sure they're available to fly whenever they need to fly. >>So for us to understand that, we then have to have data, we have to understand the state of every engine, where it is, the health of the engine, the life of that engine, what do we need to do next to that engine? And we can't do that unless we have data and that data flows into a digital platform. The intelligent engine, which is our cloud based ai, big data, all of the iot, all of the big buzzwords are there, right? So the data flows into that, that lets us run the models. It lets us understand, I can see something maybe it's a, it's a small issue, but if I leave it alone, it become a bigger issue. And maybe that will cause disruption further down the line. So we need to understand that we need to preempt it. So preemptive predictive maintenance is a, is a big part of the intelligent engine, but it's more than just that. >>It's also, we can understand how that engine is being flown. We can understand is it having a really intense flight? Is it having a more benign, gentle flight? Wow. That change time after the flight, typically after the flight. But what that means is we can then understand, actually we can keep that engine on the wing longer then you might otherwise have to do, If you have no data, you have to be conservative, safety rules, everything. Sure. So data allows you to say, actually I'm being overly conservative in this space. I can get more flying bios, flying hours from my product by extending the interval between maintenance and the intelligent engine has a large part to play in us justifying that we're able to do that. And then the final part that it does is eventually the engine is gonna have to come off from maintenance. >>These things fly 5 million miles between overhauls. You imagine you try to do that in your family car. It's, it doesn't happen. It's incredibly sophisticated thing can fly 5 million miles and then we take it off for a major overhaul. But there are thousands of these engines in the fleet. We have to understand which engine is going to come off when for what reason, and prepare our maintenance network to then receive the engine and deal with it and get it back to the customer. So the intelligent engine has a massive part to play in understanding the maintenance demand that the flying fleet is then creating. >>Wow, that's fascinating. And so you talked about that three years ago. What's next for that? I imagine there's only more evolution that's gonna happen. >>It keeps growing. It keeps growing. It's driven by the data. The more data we have, the more that we can do with that. I think as well that, you know, one of the big places that we've we've gone is you can do as much predictive analytics as you, like, there's a lot of people we'll talk about doing predictive analytics, but if you don't do the hard yards of turning predictive analytics into outcome Yeah. Then what did you get? You, you got a bit of smart advice. So we, we take that maintenance demand, we then have to understand how that drives the orchestration and the management of all the parts, the people, the work scope definition, the allocating an engine into a maintenance slot, exactly when it's gonna go. And what are we gonna do to, how do we control and manage our inventory to make sure that engine is gonna go through. >>How do we then actually execute the work inside our, our our overall shops? How do we get that engine back and and integrate our logistics process. So the intelligent engine is, if you like, the shiny front end of a process, it's all the buzzwords, but actually the hard yards behind the scene is just as if not more important to get right. And again, this is why I really like the moment of service concept. Because without that, the moment of service doesn't happen. The engine's not there, the part wasn't there. The field service maintenance guy wasn't there to go fix it. >>And brands are affected >>An, an aircraft on the ground earns no revenue for anybody. No. It's, it's a cost. It's it's a big sink of cost. It >>Is, it is. Absolutely. >>And you're helping aircraft only earn engines only earn when they fly. Yeah, >>Yeah. Absolutely. And what a fascinating, the intelligent engine. Scott, talk a little bit about, we talking about power, we can't not talk about sustainability. Yes, I understand that IFS has a new inaugural awards program that Rolls Roys was a recipient of the Change for Good sustainability awards. Congratulations. Thank you very much. And to Scott, talk to me a little bit about the Change for Good program sustainability program. What types of organizations across the industries of expertise are you looking for and why does Rules ROY really highlight what a winner embodies? >>So since Darren has joined IFS as the ceo, he's had a lot of intentional areas that we focused on. And sustainability has been one that's at the top of the list. IFS has a US ambassador Lewis Pew, who's our Chief Sustainability officer, and he helps us to provide worldwide coverage of the efforts around sustainability. So it's not just about ifss ability to become a more sustainable organization, but it's the solutions that IFS is putting together in the five verticals that we focus on that can help those organizations achieve a level of sustainability for their, for their downstream customers, their partners, and for their enterprises themselves. So when we look at, you know, the social ability for us to be more conscientious about leaving the world a better place or trying to do our best to leave the world not as bad as we came into it, sustainability is a real focus for us. And, you know, the way in which we can support an organization like Rolls Royce and Nickel obviously share those areas of focus from Rolls Royce. It's a perfect fit. And congratulations again for the award. Thank you. We're, we're, we're so excited to, to have shared that with you. We have some other customers that have achieved it across different categories, but it's an area of current and continuous focus for ifs. >>Nick, talk to us, take us out here as our last question is the, the focus on sustainability at Rolls Royce. Talk to us a little bit about that and what some of the major efforts are that you've got underway. >>I think, you know, very similar as, as, as Scott taught there, the focus within Rolls Royce as a strategic group level is really high aviation particularly, I mean we're a, we're an engineering company. We're a power company. Power inherently consumes natural resources. It tends to generate climate affecting outcomes. But at the same time, we are an innovative organization and if anybody's gonna help solve climate challenges, it's gonna be organizations like Rolls Royce who are able to bring different technologies into the market. So we have a responsibility to manage and, and optimize the behavior of our, our existing product suite. But we also have a, a vested interest in trying to move aviation on into the next, the next phase. We talk about sustainable aviation. Aviation has to earn the right to exist. People have choices. We've come out of covid, people are used to doing zoom and not flying. >>People are used to doing things when they don't necessarily get on an aircraft and do something. The aviation business always has to earn the right from the public to exist. And increasingly people will make choices about how they fly when they fly, how far they fly based on the sustainability footprint. So it's really important to us to help both our customers operate the aircraft in as sustainable and climate friendly way as we can. It's really important to find those, those balance points between the cost of an operation and it's the impact of an operation. If you go all over and say, I am going to be net, well, not even net to, but zero carbon by almost inference, that means I'm not gonna operate. You have to operate to get to an outcome. But how do I do that? Why I manage my cost, I manage the, the profitability, the organization doing it, right? >>So it has to be financially sustainable, it has to be sustainable for the people operating within it. It has to be sustainable for the planet, right? So we do that in lots of different ways in small places and, and in big places. So small things we do is we help the operator understand if you change your flight profile, you'll generate fewer emissions. You may avoid controls if you flying a different way, maybe you create trails, you'll lose, you'll lose less fuel while you're doing that. So it's cost effective for you. There was always a balance point there between the wear and tear on the engine versus the, the, the environmental impact. And you find that optimum place. One of the first things we started doing with, with Scott is we have a, a way that we life our engine components. And one of the very simple outcomes of that is using that data, the blue data for connection to the customer. >>If we can see, effectively see inside the engine about how well it's wearing and we can extend those maintenance intervals as we talked about, what that eventually does is it reduces the need to take the engine off, ship it around the world. Probably on a great big 7, 4 7 or maybe year or two ago on an Anson off four big engines flying a long distance trek, shipping our engine to an overhaul facility. We're avoiding something like 200 of those shop visit overhauls a year. So every year that's 200 flights there and back again, which don't happen, right? Collectively that's around about 15,000 automobile equivalent emissions just don't happen. So simple things we can do just starts to have accumulative effect, >>Right? Simple things that you're doing that, that have a huge impact. We could talk for so much longer on stability, I'm sure we're out of time, but I can see why Roll Royce was, was the winner of the Inocular award. Congratulations. Well deserved. Well >>Deserved. I well >>Deserved. So interesting to hear about the intelligent engine. So you're gonna have to come back. Hopefully we'll be here next year and we can hear more of the evolution. Cuz I have a feeling there's never a dual moment in what you're doing. >>It's never a dull moment. There's never an end point. >>No. >>Okay, >>Going Scott, Nick, thank you so much for joining me on the program today. Thank you, Lisa. It's great to have you talk through what's going on at ifx and the partnership with Rolls Royce. We >>Appreciate, and again, Nick, Nick, thank you for your continued support in the partnership. >>I thank you, Scott. We appreciate it. Likewise, thank >>You. Kudos all around. All right, for my guests, I'm Lisa Martin, you're watching a Cube live from Miami. We're at IFS unleashed. We'll be back shortly after a break with our next guests. So stick around.

>>Yeah. Hey, everyone, Welcome to the cubes. Continuous coverage of AWS Re invent 2021. I'm Lisa Martin with John Furrier were running one of the industry's largest and most important hybrid tech events with AWS and massive ecosystem of partners. Right now there are two live cube sets to remote sets over 100 guests on the programme and we're pleased to welcome back one of our alum I to talk about the next generation and cloud innovation. Georgia Lisa is joins John to me, the director of product management for EC two edge at A. W S George. Welcome to the programme. >>Glad to be here in person. Thanks Great to be here in person. Awesome to be here in person. Finally, >>one of the things that is very clear is the US flywheel of innovation and there was no slowdown with what's happened in the last 22 months. Amazing announcements, new leadership. We talked a little bit about five g yesterday, but let's talk more about that. Everyone is excited about five g consumers businesses. What's going on? >>So, yeah, I wanted to talk to you today about the new service that we launched called AWS Private. Five g. Essentially, it's a service that allows any AWS customer to build their own private five g network and what we try to do with the services make it that simple and cost effective for anyone without any telco experience or expertise, really, to build their own private five g network. So you just have to go to your AWS console. Um, describe the parameters for network simple stuff like, Where do you want it to be located? The throughput, the number of devices and AWS will build a plan for your network and seep you everything that you need. Just plug it together. Uh, turn it on and the network automatically configures itself. All you got to do is popular sim cards that we send you into your mobile devices and you have a private five g network working in your your premise is >>one of the things that we know and love about AWS is its customer obsession. It's focused on the customer's that whole flywheel of all the innovation that comes out as Adam was saying yesterday to the customers, we deliver this, but but you wanted more. We said we deliver this, but you wanted more. Talk to me a little bit about some of the customer catalysts for private five G. >>Actually, one of the good examples is where we are right now. More and more AWS customers need to connect an increased number of devices, and these devices become more data hungry. You know they need to push data around. They also become more and more wireless, right? Uh, so when you are trying to connect devices in the manufacturing floor, bit sensors, you know, connect the tracks, forklifts or in a convention centre. You look at how many devices there are around us. When you're trying to connect these devices with a wired network, you quickly run into physical problems like it's. It's hard to lay cable anywhere, and customers try to use for many of these use cases. But as a number of devices grows into the thousands and you know you need to put more and more data around, you quickly reach the limitations of what the WiFi technology and also WiFi is not really great at covering really open, large space. So that's where these customers, you know, think of college campuses, convention centres, manufacturing floors, all of these customers. Really? What they need to be able to do is to level the power of the mobile networks. However, doing that by yourself is pretty hard. So that's what we aim to to enable here we are waiting to enable these customers to build very easily and cost effectively their own. Uh, >>Okay, George. So I have to ask. I'm truly curious. I love this announcement. Um, because it brings together kind of the edge story. But also, I'm a band with love. I love more broad. Give me more broadband. Faster, cheaper and more broadband. How does it work? So take me through the use case of what do I need to deploy? Do I need to have a back haul connection? What does that look like? Is there a certain band with requirements? How big is the footprint? What's the radius? Just walk me through. How do I roll this out? >>Yeah, sure. Some of that stuff actually depends on your requirements, right. How How big? How much of a space do you want to cover? Basically, what we see, if you were in preview right now, so we're sipping you. The simplest configuration, which is basically these things called small cells there, you know, radio units and antennas. And all you have to do is connect them to your local. The network has Internet access. These things connect and automatically had, you know, connect home to the cloud and basically integrate and build up your whole network. All all you need is that Internet connection, and I don't know what to do. Now, how big is the network? You can You can make it pretty big. You can cover hundreds of thousands of square feet with with cellular networks with mobile networks. Um, you know, the bigger you they especially want to cover the more of these radio units. We're gonna stop you, uh, >>classic wireless radios. >>Yes. You >>light up the area with five g connected to the network. That's your choke point. The big of the pipe >>took the bigger pipe. That toxic. I mean, well, there, there's two. There's two things to consider here. There is local connectivity. So devices talking to each other, and there was connectivity back to somewhere else, like the Internet or the cloud. There are use cases, for example. Let's say data video feeds that you want to push up to do some inference in the cloud. In these use cases, you're basically pushing all of the data up. There is no left. There's no East West connectivity locally, and that's where our simplest configuration works best. There are other, uh, use cases where there is a lot of connectivity and devices talk to each other locally, like in this place, for example, right in this. In these cases, we can sip you that second configuration where we actually see Pew, a managed hardware WS managed hardware on premises, and that runs the smart of the network and allows all of your data traffic to remain local. That's >>wavelength Outpost, or both. >>A different configuration of A. W s private five G. It's a managed service. We take. We take care of it. You basically it's very It has a pricing model, which is very customer friendly because you like multi W services. You can start with no upfront fees. You can scale and pay as you scale because >>it's designed to deploy easily. >>Yep, deploys the >>footprint. Just I'm just curious if the poll is it like, it's like an antenna. Is it like so and >>yeah, well, the antenna is, you know, the small cell. They call them small cells in, you know, in in cellular land there, this big. And you can you can hide this. There is actually a demo in the Venetian of the private service. So you can you can actually see it in action, but yeah, that thing can cover 10,000 square feet, just one of them. So you can >>go out and put a five g network downtown and be like the king. >>You could Yes. You could have your own private network. You can monetise that next >>on the Q. >>Great stuff. >>So in terms of industries adopting this, you gave us some examples. Obviously. Convention centres, campuses, universities. I'm just curious, given the amount of acceleration that we've seen in every industry the last 22 months where organisations must become digital. They depend on that for their livelihood. And we saw this all these pivots, right? 22 months ago. How do we survive this? How do we thrive? Are consumers now are whether it's an injury or consumer or enterprise. Have this expectation that we're gonna be able to communicate no matter where we are 24 by seven. Whether it's health care, financial services. I'm just curious if you're seeing any industries in particular that you think are really prime for this private five >>G. Yeah. So manufacturing is a is a really great example because you have to cover large spaces. You have thousands of devices, sensors, etcetera and using other solutions like WiFi does not provide you the depth of capabilities like, for example, you know, advanced security capabilities or even capabilities to prioritise traffic from some devices over others, which is what a five G network can do for you. But also, you know, it involves large spaces both indoors and outdoors. We, you know, actually, Amazon is a really great example of you know of using this. We're working with Amazon fulfilment centres. These are the warehouses that fulfil your orders when you order online. Um, and they are a mix of indoor space and outer space, and you can think of, you know, I don't know if you've seen pictures or videos. There's robots running around their sensors everywhere. There is packing lines, etcetera, all of these things in order to operate performantly, but also securely and safely for the people that are around. You need to be well connected at a very high reliability rate. Right? So, uh, Amazon for two networks is actually using private A W s private five G to connect all of these devices. The really key thing here is you don't have to go drop 1000 of these access points we're talking about you. Can you can. You can probably cover your space with 5 10 of these. So your operational expenses, your maintenance goes down and there is less interruption of your normal operations like you can't. You don't have to stop your manufacturing line for someone to come in and fix your WiFi access. >>It's great for campuses like college campuses, college >>campuses, a great one. We you know, we've worked with college campuses, including the CME University in the past two, you know, with some of our partners to, uh, to to deploy. So >>that's how close you have these distribution, gas systems, distribution, whatever they call it accelerate whatever amplifies into get extra coverage, this seems to be a good fit. Um, for that how you mentioned in the preview? How do people get involved? Is there like a criteria. How was it going to >>be available to get priority? Don't get you >>tell them ready to jump in. Take us through the programme. What's the plants? >>So currently we're you know, we're in that preview mode. So we're keeping you this small configuration, the simpler configuration. You can sign up on the AWS website and you know, we, as we scale our operations are supply chain. Because this involves also, you know, hardware, etcetera. We're gonna go to general availability g A over the next few months and we have both configurations open. So I I encourage everyone who is interested go to the W s website and sign up. We're asking to get that in customers' hands because we're getting overwhelmingly positive feedback on what we built. >>This is transformative. I mean, clearly what you're talking about here is going to transform industry and help organisations transform themselves and outpaced the competitors that are in the rear view mirror Aren't going to be able to take advantage of this were on the show floor. We've got lots of people here. Where can people actually go and see this preview tested up? >>There is an actual demo in the Venetian. I can't remember. Sorry, I can't remember the room. I think it's on the Yes, actually, it's on the floor on the third floor where the meeting rooms are on outside 35 or one. If anyone wants to go, we're >>going to start buying lunch time. >>Yes. Yeah, you can see it in action. And, you know, you could You could see a future where everything, You know, you look around. There's thousands of devices here. You could power all of these devices with a single cell and, you know, really scaled throughput >>in the five G. Just curious, um on the range is better than wifi >>ranges. Better outdoors, >>obviously, or factories. What's the throughput on the >>depending on the spectrum that you choose? And that's actually a really good save way. The device, the service that we built, its spectrum agnostic so it can be used on right now. We're using it on what we call C BRS spectrum, which is the free for all you can. You know, you can you can use it yourself. But also, customers can bring their own spectrum. And we're working with a batch of, uh, CSP operators to build advanced bundles where you can work this on licence spectrum. So if you're going up the spectrum in what they called millimetre wave >>spectrum owner to bring your own licence, >>you could So telco right? You could be a telco, bring your, you know, and work with us as a partner or some actually, actually, manufacturing customers have purchased rights to small spectrum bands so they can use those in combination with this service to deploy. So to your original question, as you're going back up the spectrum, you can drive more and more throughput. You it's not. It's not unheard of to drive one gig. You know what's so >>The low hanging fruit is the the use cases that have critical need for edge connectivity manufacturing? Um, certainly the retail or whatever that they help do the deployment >>we can. We can. We can see this being applicable because because you can start super small. You can see this being applicable even to branch offices, right? Like, uh, let's say I was talking to a customer yesterday. They were thinking or have all these branch offices. I don't even I don't even want to have I thought either he just wants something that's very quickly and easily. You know, I can manage centrally and it just connects. >>Can I should have fixed wireless shot to the wavelength order to have back all with wire >>too. Oh, they actually we are planning to. You know, I talked about where the smarts of the network live in the they can live in a region, they can live in the locals, and they can live in a wave election. So we're combining more and more of these products as well. And it's computing, obviously, is a is an obvious thing that, you know, we should be working on >>incredible work, George, that you and the team have done transforming industries. And I don't know if a feeling there might be a cube to Is it? Would it be too dot >>Oh, John, >>he's ready. Big George, Thank you so much for joining joining me today. It's great >>to be here. Thanks for having that >>for John Ferrier. I'm Lisa Martin. You're watching the Cube, the global leader in live coverage. Mhm

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

>>Hello, everyone. My name is Rick Pew. I'm a senior product manager at Mirant. This and I have been working on the Doctor Enterprise Container Cloud for the last eight months. Today we're gonna be talking about multi cloud kubernetes. So the first thing to kind of look at is, you know, is multi cloud rial. You know, the terms thrown around a lot and by the way, I should mention that in this presentation, we use the term multi cloud to mean both multi cloud, which you know in the technical sense, really means multiple public clouds and hybrid cloud means public clouds. And on Prem, uh, we use in this presentation will use the term multi cloud to refer to all different types of multiple clouds, whether it's all public cloud or a mixture of on Prem and Public Cloud or, for that matter, multiple on Prem clouds as doctor and price container. Cloud supports all of those scenarios. So it really well, let's look at some research that came out of flex era in their 2020 State of the cloud report. You'll notice that ah, 33% state that they've got multiple public and one private cloud. 53% say they've got multiple public and multiple private cloud. So if you have those two up, you get 86% of the people say that they're in multiple public clowns and at least one private cloud. So I think at this stage we could say that multi cloud is a reality. According to 4 51 research, you know, a number of CEO stated that the strong driver their desire was to optimize cost savings across their private and public clouds. Um, they also wanted to avoid vendor lock in by operating in multiple clouds and try to dissuade their teams from taking too much advantage of a given providers proprietary infrastructure. But they also indicated that there the complexity of using multiple clouds hindered the rate of adoption of doing it doesn't mean they're not doing it. It just means that they don't go assed fast as they would like to go in many cases because of the complexity. And here it Miranda's. We surveyed our customers as well, and they're telling us similar things, you know. Risk management, through the diversification of providers, is key on their list cost optimization and the democratization of allowing their development teams, uh, to create kubernetes clusters without having to file a nightie ticket. But to give them a self service, uh, cloud like environment, even if it's on prem or multi cloud to give them the ability to create their own clusters, resize their own clusters and delete their own clusters without needing to have I t. Or of their operations teams involved at all. But there are some challenges with this, with the different clouds you know require different automation. Thio provisioned the underlying infrastructure or deploy and operating system or deployed kubernetes, for that matter, in a given cloud. You could say that they're not that complicated. They all have, you know, very powerful consoles and a P I s to do that. But did you get across three or four or five different clouds? Then you have to learn three or four or five different AP ice and Web consoles in order to make that happen on in. That scenario is difficult to provide self service for developers across all the cloud options, which is what you want to really accelerate your application innovation. So what's in it for me? You know We've got a number of roles and their prizes developers, operators and business leaders, and they have somewhat different needs. So when the developer side the need is flexibility to meet their development schedules, Number one you know they're under constant pressure to produce, and in order to do that, they need flexibility and in this case, the flexibility to create kubernetes clusters and use them across multiple clouds. Now they also have C I C D tools, and they want them to be able to be normalized on automated across all of the the on prim and public clouds that they're using. You know, in many cases they'll have a test and deployment scenario where they'll want to create a cluster, deploy their software, run their test, score the tests and then delete that cluster because the only point of that cluster, perhaps, was to test ah pipeline of delivery. So they need that kind of flexibility. From the operator's perspective, you know, they always want to be able to customize the control of their infrastructure and deployment. Uh, they certainly have the desire to optimize their optics and Capex fans. They also want to support their develops teams who many times their their customers through a p I access for on Prem and public clouds burst. Scaling is something operators are interested in, and something public clouds can provide eso the ability to scale out into public clouds, perhaps from there on prem infrastructure in a seamless manner. And many times they need to support geographic distribution of applications either for compliance or performance reasons. So having you know, data centers all across the world and be able to specifically target a given region, uh, is high on their list. Business leaders want flexibility and confidence to know that you know, they're on prim and public cloud uh, deployments. Air fully supported. They want to be able, like the operator, optimize their cloud, spends business leaders, think about disaster recovery. So having the applications running and living in different data centers gives them the opportunity to have disaster recovery. And they really want the flexibility of keeping private data under their control. On on Prem In certain applications may access that on Prem. Other applications may be able to fully run in the cloud. So what should I look for in a container cloud? So you really want something that fully automates these cluster deployments for virtual machine or bare metal. The operating system, uh, and kubernetes eso It's not just deploying kubernetes. It's, you know, how do I create my underlying infrastructure of a VM or bare metal? How do I deploy the operating system? And then, on top of all that, I want to be able to deploy kubernetes. Uh, you also want one that gives a unified cluster lifecycle management across all the clouds. So these clusters air running software gets updated. Cooper Netease has a new release cycle. Uh, they come out with something new. It's available, you know, How do you get that across all of your clusters? That air running in multiple clouds. We also need a container cloud that can provide you the visibility through logging, monitoring and alerting again across all the clouds. You know, many offerings have these for a particular cloud, but getting that across multiple clouds, uh, becomes a little more difficult. The Doctor Enterprise Container cloud, you know, is a very strong solution and really meets many of these, uh, dimensions along the left or kind of the dimensions we went through in the last slide we've got on Prem and public clouds as of RG A Today we're supporting open stack and bare metal for the on Prem Solutions and AWS in the public cloud. We'll be adding VM ware very soon for another on Prem uh, solution as well as azure and G C P. So thank you very much. Uh, look forward, Thio answering any questions you might have and we'll call that a rap. Thank you. >>Hi, Rick. Thanks very much for that. For that talk, I I am John James. You've probably seen me in other sessions. I do marketing here in Miran Tous on. I wanted to to take this opportunity while we had Rick to ask some more questions about about multi cloud. It's ah, potentially a pretty big topic, isn't it, Rick? >>Yeah. I mean, you know, the devil's in the details and there's, uh, lots of details that we could go through if you'd like, be happy to answer any questions that you have. >>Well, we've been talking about hybrid cloud for literally years. Um, this is something that I think you know, several generations of folks in the in the I. A s space doing on premise. I s, for example, with open stack the way Miran Tous Uh does, um, found, um, you know, thought that that it had a lot of potential. A lot of enterprises believed that, but there were There were things stopping people from from making it. Really, In many cases, um, it required a very, ah, very high degree of willingness to create homogeneous platforms in the cloud and on the premise. Um, and that was often very challenging. Um, but it seems like with things like kubernetes and with the isolation provided by containers, that this is beginning to shift, that that people are actually looking for some degree of application portability between their own Prem and there and their cloud environments. And that this is opening up, Uh, you know, investment on interest in pursuing this stuff. Is that the right perception? >>Yeah. So let's let's break that down a little bit. So what's nice about kubernetes is through the a. P. I s are the same. Regardless of whether it's something that Google or or a W s is offering as a platform as a service or whether you've taken the upstream open source project and deploy it yourself on parameter in a public cloud or whatever the scenario might be or could be a competitor of Frances's product, the Kubernetes A. P I is the same, which is the thing that really gives you that application portability. So you know, the container itself is contained arising, obviously your application and minimizing any kind of dependency issues that you might have And then the ability to deploy that to any of the coup bernetti clusters you know, is the same regardless of where it's running, the complexity comes and how doe I actually spend up a cluster in AWS and open stack and D M Where and gp An azure. How do I build that infrastructure and and spin that up and then, you know, used the ubiquitous kubernetes a p I toe actually deploy my application and get it to run. So you know what we've done is we've we've unified and created A I use the word normalized. But a lot of times people think that normalization means that you're kind of going to a lowest common denominator, which really isn't the case and how we've attacked the the enabling of multi cloud. Uh, you know, what we've done is that we've looked at each one of the providers and are basically providing an AP that allows you to utilize. You know, whatever the best of you know, that particular breed of provider has and not, uh, you know, going to at least common denominator. But, you know, still giving you a ah single ap by which you can, you know, create the infrastructure and the infrastructure could be on Prem is a bare metal infrastructure. It could be on preeminent open stack or VM ware infrastructure. Any of the public clouds, you know, used to have a a napi I that works for all of them. And we've implemented that a p i as an extension to kubernetes itself. So all of the developers, Dev ops and operators that air already familiar operating within the, uh, within the aapi of kubernetes. It's very, very natural. Extension toe actually be able to spend up these clusters and deploy them >>Now that's interesting. Without giving away, obviously what? Maybe special sauce. Um, are you actually using operators to do this in the Cooper 90? Sense of the word? >>Yes. Yeah, we've extended it with with C R D s, uh, and and operators and controllers, you know in the way that it was meant to be extended. So Kubernetes has a recipe on how you extend their A P I on that. That's what we used as our model. >>That, at least to me, makes enormous sense. Nick Chase, My colleague and I were digging into operators a couple of weeks ago, and that's a very elegant technology. Obviously, it's a it's evolving very fast, but it's remarkably unintimidating once you start trying to write them. We were able toe to compose operators around Cron and other simple processes and just, >>you know, >>a couple of minutes on day worked, which I found pretty astonishing. >>Yeah, I mean, you know, Kubernetes does a lot of things and they spent a lot of effort, um, in being able, you know, knowing that their a p I was gonna be ubiquitous and knowing that people wanted to extend it, uh, they spent a lot of effort in the early development days of being able to define that a p I to find what an operator was, what a controller was, how they interact. How a third party who doesn't know anything about the internals of kubernetes could add whatever it is that they wanted, you know, and follow the model that makes it work. Exactly. Aziz, the native kubernetes ap CSTO >>What's also fascinating to me? And, you know, I've I've had a little perspective on this over the past, uh, several weeks or a month or so working with various stakeholders inside the company around sessions related to this event that the understanding of how things work is by no means evenly distributed, even in a company as sort of tightly knit as Moran Tous. Um, some people who shall remain nameless have represented to me that Dr Underprice Container Cloud basically works. Uh, if you handed some of the EMS, it will make things for you, you know, and this is clearly not what's going on that that what's going on is a lot more nuanced that you are using, um, optimal resource is from each provider to provide, uh, you know, really coherent architected solutions. Um, the load balancing the d. N s. The storage that this that that right? Um all of which would ultimately be. And, you know, you've probably tried this. I certainly have hard to script by yourself in answerable or cloud formation or whatever. Um, this is, you know, this is not easy work. I I wrote a about the middle of last year for my prior employer. I wrote a dip lawyer in no Js against the raw aws a piece for deployment and configuration of virtual networks and servers. Um, and that was not a trivial project. Um, it took a long time to get thio. Uh, you know, a dependable result. And to do it in parallel and do other things that you need to do in order to maintain speed. One of the things, in fact, that I've noticed in working with Dr Enterprise Container Cloud recently, is how much parallelism it's capable of within single platforms. It's It's pretty powerful. I mean, if you want to clusters to be deployed simultaneously, that's not hard for Doc. Aerated price container cloud to dio on. I found it pretty remarkable because I have sat in front of a single laptop trying to churn out of cluster under answerable, for example, and just on >>you get into that serial nature, your >>poor little devil, every you know, it's it's going out and it's ssh, Indian Terminals and it's pretending it's a person and it's doing all that stuff. This is much more magical. Um, so So that's all built into the system to, isn't it? >>Yeah. Interesting, Really Interesting point on that. Is that you know, the complexity isn't not necessarily and just creating a virtual machine because all of these companies have, you know, spend a lot of effort to try to make that as easy as possible. But when you get into networking, load balancing, routing, storage and hooking those up, you know, two containers automating that if you were to do that in terror form or answerable or something like that is many, many, many lines of code, you know, people have to experiment. Could you never get it right the first or second or the third time? Uh, you know, and then you have to maintain that. So one of the things that we've heard from customers that have looked a container cloud was that they just can't wait to throw away their answerable or their terror form that they've been maintaining for a couple of years. The kind of enables them to do this. It's very brittle. If if the clouds change something, you know on the network side, let's say that's really buried. And it's not something that's kind of top of mind. Uh, you know, your your thing fails or maybe worse, you think that it works. And it's not until you actually go to use it that you notice that you can't get any of your containers. So you know, it's really great the way that we've simplified that for the users and again democratizing it. So the developers and Dev ops people can create these clusters, you know, with ease and not worry about all the complexities of networking and storage. >>Another thing that amazed me as I was digging into my first, uh, Dr Price container Cloud Management cluster deployment was how, uh, I want I don't want to use the word nuanced again, but I can't think of a better word. Nuanced. The the security thinking is in how things air set up. How, um, really delicate the thinking about about how much credential power you give to the deploy. Er the to the seed server that deploys your management cluster as opposed thio Um uh or rather the how much how much administrative access you give to the to the administrator who owns the entire implementation around a given provider versus how much power the seed server gets because that gets its own user right? It gets a bootstrap user specifically created so that it's not your administrator, you know, more limited visibility and permissions. And this whole hierarchy of permissions is then extended down into the child clusters that this management cluster will ultimately create. So that Dev's who request clusters will get appropriate permissions granted within. Ah, you know, a corporate schema of permissions. But they don't get the keys to the kingdom. They don't have access to anything they don't you know they're not supposed to have access to, but within their own scope, they're safe. They could do anything they want, so it's like a It's a It's a really neat kind of elegant way of protecting organizations against, for example, resource over use. Um, you know, give people the power to deploy clusters, and basically you're giving them the power toe. Make sure that a big bill hits you know, your corporate accounting office at the end of the billing cycle, um so there have to be controls and those controls exist in this, you know, in this. >>Yeah, And there's kind of two flavors of that. One is kind of the day one that you're doing the deployment you mentioned the seed servers, you know, And then it creates a bastion server, and then it creates, you know, the management cluster and so forth, you know, and how all those permissions air handled. And then once the system is running, you know, then you have full access to going into key cloak, which is a very powerful open source identity management tool on you have dozens of, you know, granular permissions that you can give to an individual user that gives them permission to do certain things and not others within the context of kubernetes eso. It's really well thought out. And the defaults, you know, our 80% right. You know, there's very few people are gonna have to go in and sort of change those defaults. You mentioned the corporate directory. You know, hooks right upto l bap or active directory can suck everybody down. So there's no kind of work from a day. One perspective of having to go add. You know everybody that you can think of different teams and groupings of of people. Uh, you know, that's kind of all given from the three interface to the corporate directory. And so it just makes kind of managing the users and and controlling who can do what? Uh, really easy. And, you know, you know, day one day two it's really almost like our one hour to write because it's just all the defaults were really well thought out. You can deploy, you know, very powerful doctor and price container cloud, you know, within an hour, and then you could just start using it. And you know, you can create users if you want. You can use the default users. That air set up a time goes on, you can fine tune that, and it's a really, really nice model again for the whole frictionless democratization of giving developers the ability to go in and get it out of, you know, kind of their way and doing what they want to do. And I t is happy to do that because they don't like dozens of tickets and saying, you know, create a cluster for this team created cluster for that team. You know, here's the size of these guys. Want to resize when you know let's move all that into a self service model and really fulfill the prophecy of, you know, speeding up application development. >>It strikes me is extremely ironic that one of the things that public cloud providers bless them, uh, have always claimed, is that their products provide this democratization when in the experience, I think my own experience and the experience of most of the AWS developers, for example, not toe you know, name names, um, that I've encountered is that an initial experience of trying to start start a virtual machine and figuring out how to log into it? A. W s could take the better part of an afternoon. It's just it's not familiar once you have it in your fingers. Boom. Two seconds, right. But, wow, that learning curve is steep and precipitous, and you slip back and you make stupid mistakes your first couple 1000 times through the loop. Um, by letting people skip that and letting them skip it potentially on multiple providers, in a sense, I would think products like this are actually doing the public cloud industry is, you know, a real surface Hide as much of that as you can without without taking the power away. Because ultimately people want, you know, to control their destiny. They want choice for a reason. Um, and and they want access to the infinite services And, uh, and, uh, innovation that AWS and Azure and Google are all doing on their platforms. >>Yeah, you know, and they're solving, uh, very broad problems in the public clouds, you know, here were saying, you know, this is a world of containers, right? This is a world of orchestration of these containers. And why should I have to worry about the underlying infrastructure, whether it's a virtual machine or bare metal? You know, I shouldn't care if I'm an application developer developing some database application. You know, the last thing I wanna worry about is how do I go in and create a virtual machine? Oh, this is running. And Google. It's totally different than the one I was creating. An AWS I can't find. You know where I get the I P address in Google. It's not like it was an eight of us, you know, and you have to relearn the whole thing. And that's really not what your job is. Anyways, your job is to write data base coat, for example. And what you really want to do is just push a button, deploy a nor kiss traitor, get your app on it and start debugging it and getting it >>to work. Yep. Yeah, it's It's powerful. I've been really excited to work with the product the past week or so, and, uh, I hope that folks will look at the links at the bottoms of our thank you slides and, uh, and, uh, avail themselves of of free trial downloads of both Dr Enterprise Container, Cloud and Lens. Thank you very much for spending this extra time with me. Rick. I I think we've produced some added value here for for attendees. >>Well, thank you, John. I appreciate your help. >>Have a great rest of your session by bike. >>Okay, Thanks. Bye.