(upbeat music) >> Good afternoon, everyone. Welcome back to the CUBE's day one coverage of VMware Explorer 22, live from San Francisco. I'm Lisa Martin. Dave Nicholson is back with me. Welcome back to the set. We're pleased to welcome William Bell as our next guest. The executive vice president of products at Phoenix NAP. William, welcome to the CUBE. Welcome back to the CUBE. >> Thank you, thank you so much. Happy to be here. >> Talk to us a little, and the audience a little bit about Phoenix NAP. What is it that you guys do? Your history, mission, value prop, all that good stuff. >> Absolutely, yeah. So we're global infrastructures as a service company, foundationally, we are trying to build pure play infrastructure as a service, so that customers that want to adopt cloud infrastructure but maybe don't want to adopt platform as a service and really just, you know, program themselves to a specific API can have that cloud adoption without that vendor lock in of a specific platform service. And we're doing this in 17 regions around the globe today. Yeah, so it's just flexible, easy. That's where we're at. >> I like flexible and easy. >> Flexible and easy. >> You guys started back in Phoenix. Hence the name. Talk to us a little bit about the evolution of the company in the last decade. >> Yeah, 100%. We built a data center in Phoenix expecting that we could build the centralized network access point of Phoenix, Arizona. And I am super proud to say that we've done that. 41 carriers, all three hyperscalers in the building today, getting ready to expand. However, that's not the whole story, right. And what a lot of people don't know is we founded an infrastructure as a service company, it's called Secured Servers no longer exists, but we founded that company the same time and we built it up kind of sidecar to Phoenix NAP and then we merged all of those together to form this kind of global infrastructure platform that customers can consume. >> Talk to us about the relationship with VMware. Obviously, here we are at VMware Explore. There's about seven... We're hearing 7,000 to 10,000 people here. People are ready to be back to hear from VMware and it's partner ecosystem. >> Yeah, I mean, I think that we have this huge history with VMware that maybe a lot of people don't know. We were one of the first six, the SPPs in 2011 at the end of the original kind of data center, whatever, vCloud data center infrastructure thing that they did. And so early on, there was only 10 of us, 11 of us. And most of those names don't exist anymore. We're talking, Terramark, Blue Lock, some of these guys. Good companies, but they've been bought or whatnot. And here's plucky Phoenix NAP, still, you know, offering great VMware cloud services for customers around the globe. >> What are some of the big trends that you're seeing in the market today where customers are in this multi-cloud world? You know this... I love the theme of this event. The center of the multi-cloud universe. Customers are in that by default. How do you help them navigate that and really unlock the value of it? >> Yeah, I think for us, it's about helping customers understand what applications belong where. We're very, very big believers both in the right home. But if you drill down on that right home for right applicator or right application, right home, it's more about the infrastructure choices that you're making for that application leads to just super exciting optimizations, right. If you, as an example, have a large media streaming business and you park it in a public called hyperscaler and you just eat those egress fees, like it's a big deal. Right? And there are other ways to do that, right. If you need a... If your application needs to scale from zero cores to 15,000 cores for an hour, you know, there are hyperscalers for that, right. And people need to learn how to make that choice. Right app, right home, right infrastructure. And that's kind of what we help them do. >> It's interesting that you mentioned the concept of being a pure play in infrastructure as a service. >> Yeah. >> At some point in the past, people would have argued that infrastructure as a service only exists because SaaS isn't good enough yet. In other words, if there's a good enough SaaS application then you don't want IaaS because who wants to mess around with IaaS, infrastructures as a service. Do you have customers who look at what they're developing as so much a core of what their value proposition is that they want to own it? I mean, is that a driving factor? >> I would challenge to say that we're seeing almost every enterprise become a SaaS company. And when that transition happens, SaaS companies actually care a lot about the cost basis, efficiency, uptime of their application. And ultimately, while they don't want to be in the data center business anymore, it doesn't mean that they want to pay someone else to do things that they feel wholly competent in doing. And we're seeing this exciting transition of open source technologies, open source platforms becoming good enough that they don't actually have to manage a lot of things. They can do it in software and the hardware's kind of abstracted. But that actually, I would say is a boon for infrastructure as a service, as an independent thing. It's been minimized over the years, right. People talk about hyperscalers as being cloud infrastructure companies and they're not. They're cloud platform companies, right. And the infrastructure is high quality. It is easy to access and scale, right, but it's ultimately, if you're just using one of those hyperscalers for that infrastructure, building VMs and doing a bunch of things yourself, you're not getting the value out of that hyperscaler. And ultimately that infrastructure's very expensive if you look at it that way. >> So it's interesting because if you look at what infrastructure consists of, which is hardware and software-- >> Yeah. >> People who said, eh, IaaS as is just a bridge to a bright SaaS future, people also will make the argument that the hardware doesn't matter anymore. I imagine that you are doing a lot of optimization with both hardware and stuff like the VMware cloud stack that you deploy as a VCPP partner. >> Absolutely, yeah. >> So to talk about that. >> Absolutely. >> I mean, you agree. I mean, if I were to just pose a question to you, does hardware still matter? Does infrastructure still matter? >> Way more than people think. >> Well, there you go. So what are you doing in that arena, specifically with VCPP? >> Yeah, absolutely. And so I think a good example of that, right, so last VMworld in person, 2019, we showcased a piece of technology that we had been working with Intel on for about two years at the time which was Intel persistent memory DC, persistent memory. Right? And we launched the first VMware cloud offering to have Intel DC persistent memory onboard. So that customers with the VMs that needed that technology could leverage it with the integrations in vSphere 6.7 and ultimately in seven more, right. Now I do think that was maybe a swing and a miss technology potentially but we're going to see it come back. And that specialized infrastructure deployment is a big part of our business, right. Helping people identify, you know, this application, if you'd have this accelerator, this piece of infrastructure, this quality of network can be better, faster, cheaper, right. That kind of mentality of optimization matters a lot. And VMware plays a critical role in that because it still gives the customer the operational excellence that they need without having to do everything themselves, right. And our customers rely on that a lot from VMware to get that whole story, operationally efficient, easy to manage, automated. All those things make a lot of difference to our VMware customers. >> Speaking of customers, what are you hearing, if anything, from customers, VMware customers that are your joint customers about the Broadcom acquisition? Are they excited about it? Are they concerned about it? And how do you talk about that? >> Yeah, I mean, I think that everyone that's in the infrastructure business is doing business with Broadcom, all right. And we've had so many businesses that we've been engaged with that have ultimately been a acquiree. I can say that this one feels different only in the size of the acquisition. VMware carries so much weight. VMware's brand exceeds Broadcom's brand, in my opinion. And I think ultimately, I don't know anything that's not public, right-- >> Well, they rebranded. By the way, on the point of brand, they rebranded their software business, VMware. >> Yeah. I mean, that's what I was going to say. That was the word on the street. I don't know if there's beneficial. Is that a-- >> Well, that's been-- >> But that's the word, right? >> That's what they've said. Well, but when a Avago acquired Broadcom they said, "we'll call ourselves Broadcom." >> Absolutely. Why wouldn't you? >> So yeah. So I imagine that what's been reported is likely-- >> Likely. Yeah, I 100% agree. I think that makes a ton of sense and we can start to see even more great intellectual property in software. That's where, you know, all of these businesses, CA, Symantec, VMware and all of the acquisitions that VMware has made, it's a great software intellectual property platform and they're going to be able to get so much more value out of the leadership team that VMware has here, is going to make a world of difference to the Broadcom software team. Yeah, so I'm very excited, you know. >> It's a lot of announcements this morning, a lot of technical product announcements. What did you hear in that excites you about the evolution of VMware as well as the partnership and the value in it for your customers? >> You know, one of our fastest growing parts of our business is this metal as a service infrastructure business and doing very, very... Using very specific technologies to do very interesting things, makes a big difference in our world and for our customers. So anything that's like smartNICs, disaggregated hypervisor, accelerators as a first class citizen in VMware, all that stuff makes the Phoenix NAP story better. So I'm super excited about that, right. Yeah. >> Well, it's interesting because VCPP is not a term that people who are not insiders know of. What they know is that there are services available in hyperscale cloud providers where you can deploy VMware. Well, you know, VMware cloud stack. Well, you can deploy those VMware cloud stacks with you. >> Absolutely. >> In exactly the same manner. However, to your point, all of this talk about disaggregation of CPU, GPU, DPU, I would argue with it, you're in a better position to deploy that in an agile way than a hyperscale cloud provider would be and foremost, I'm not trying to-- >> No, yeah. >> I'm not angling for a job in your PR department. >> Come on in. >> But the idea that when you start talking about something like metal as a service, as an adjunct or adjacent to a standard deployment of a VMware cloud, it makes a lot of sense. >> Yeah. >> Because there are people who can't do everything within the confines of what the STDC-- >> Yes. >> Consists of. >> Absolutely. >> So, I mean... Am I on the right track? >> No, you are 100% hitting it. I think that that point you made about agility to deliver new technology, right, is a key moment in our kind of delivery every single year, right. As a new chip comes out, Intel chip or Accelerator or something like that, we are likely going to be first to market by six months potentially and possibly ever. Persistent memory never launched in public cloud in any capacity but we have customers running on it today that is providing extreme value for their business, right. When, you know, the discreet GPUs coming from the just announced Flex series GPU from Intel, you're likely not going to see them in public cloud hyperscalers quickly, right. Over time, absolutely. We'll have them day one. Isolate came out, you could get it in our metal as a service platform the morning it launched on demand, right. Those types of agility points, they're not... Because they're hyperscale by nature. If they can't hyperscale it, they're not doing it, right. And I think that that is a very key point. Now, as it comes in towards VMware, we're driving this intersection of building that VCF or VMware cloud foundation which is going to be a key point of the VMware ecosystem. As you see this transition to core based licensing and some of the other things that have been talked about, VMware cloud foundation is going to be the stack that they expect their customers to adopt and deliver. And the fact that we can automate that, deliver it instantaneously in a couple of hours to hardware that you don't need to own, into networks you don't need to manage, but yet you are still in charge, keys to the kingdom, ready to go, just like you're doing it in your own data center, that's the message that we're driving for. >> Can you share a customer example that you think really just shines a big flashlight on the value that you guys are delivering? >> We definitely, you know, we had the pleasure of working with Make-A-Wish foundation for the last seven years. And ultimately, you know, we feel very compelled that every time we help them do something unique, different or what not, save money, that money's going into helping some child that's in need, right. And so we've done so many things together. VMware has stepped up as the plate over the years, done so many things with them. We've sponsored stuff. We've done grants, we've done all kinds of things. The other thing I would say is we are helping the City of Hope and Translational Genomics Research Institute on sequencing single cell RNA so that they can fight COVID, so that they can build cure, well, not cures but build therapies for colon cancer and things like that. And so I think that, you know, this is a driving light for us internally is helping people through efficiency and change. And that's what we're looking for. We're looking for more stories like that. We're looking... If you have a need, we're looking for people to come to us and say, "this is my problem. This is what this looks like. Let us see if we can find a solution that's a little bit different, a little bit out of the box and doesn't have to change your business dramatically." Yeah. >> And who are you talking to within customers? Is this a C level conversation? >> Yeah, I mean, I would say that we would love it to be... I think most companies would love to have that, you know, CFO conversation with every single customer. I would say VPs of engineering, increasingly, especially as we become more API centric, those guys are driving a lot of those purchasing decisions. Five years ago, I would've said director of IT, like director of IT. Now today, it's like VP of engineering, usually software oriented folks looking to deliver some type of application on top of a piece of hardware or in a cloud, right. And those guys are, you know, I guess, that's even another point, VMware's doing so much work on the API side that they don't get any credit for. Terraform, Ansible, all these integrations, VMware doing so much in this area and they just don't get any credit for it ever, right. It's just like, VMware's the dinosaur and they're just not, right. But that's the thing that people think of today because of the hype of the hyperscaler. I think that's... Yeah. >> When you're in customer conversations, maybe with prospects, are you seeing more customers that have gone all in on a hyperscaler and are having issues and coming to you guys saying help, this is getting way too expensive? >> Yeah, I think it's the unexpected growth problem or even the expected growth problem where they just thought it would be okay, but they've suffered some type of competitive pressure that they've had to optimize for and they just didn't really expect it. And so, I think that increasingly we are finding organizations that quickly adopted public cloud. If they did a full digital transformation of their business and then transformation of their applications, a lot of them now feel very locked in because every application is just reliant on x hyperscaler forever, or they didn't transform anything and they just migrated and parked it. And the bills that are coming in are just like, whoa like, how is that possible? We are typically never recommending get out of the public cloud. We are just... It's not... If I say the right home for the right application, it's by default saying that there are right applications for hyperscalers. Parking your VMware environment that you just migrated to a hyperscaler, not the right application. You know, I would love you to be with me but if you want to do that, at least go to VMC on AWS or go to OCVS or GCVE or any of those. If that's going to go with a Google or an Amazon and that's just the mandate and you're going to move your applications, don't just move them into native. Move them into a VMware solution and then if you still want to make that journey, that full transformation, go ahead and make it. I would still argue that that's not the most efficient way but, you know, if you're going to do anything, don't just dump it all into cloud, the native hyperscaler stuff. >> Good advice. >> So what do typical implementations look like with you guys when you're moving on premises environments into going back to the VCPP, STDC model? >> Absolutely. Do you have people moving and then transforming and re-platforming? What does that look like? What's the typical-- >> Yeah. I mean, I do not believe that anybody has fully made up their mind if exactly where they want to be. I'm only going to be in this cloud. It's an in the close story, right. And so even when we get customers, you know, we firmly believe that the right place to just pick up and migrate is to a VCPP cloud. Better cost effectiveness, typically better technology, you know service, right. Better service, right. We've been part of VMware for 12 years. We love the technology behind VMC's, now AWS is fantastic, but it's still just infrastructure without any help at all right, right. They're going to be there to support their technology but they're not going to help you with the other stuff. We can do some of those things. And if it's not us, it's another VCPP provider that has that expertise that you might need. So yes, we help you quickly, easily migrate everything to a VMware cloud. And then you have a decision point to make. You're happy where you are, you are leveraging public cloud for a certain applications. You're leveraging VMware cloud offerings for the standard applications that you've been running for years. Do you transform them? Do you keep them? What do you do? All those decisions can be made later. But I stress that repurchasing all your hardware again, staying inside your colo and doing everything yourself, it is for me, it's like a company telling me they're going to build a data center for themselves, single tenant data center. Like no one's doing that, right. But there are more options out there than just I'm going to go to Azure, right. Think about it. Take the time, assess the landscape. And VMware cloud providers as a whole, all 17,000 of us or whatever across the globe, people don't know that group of individuals of the companies is the third or fourth potentially largest cloud in the world. Right? That's the power of the VMware cloud provider ecosystem. >> Last question for you as we wrap up here. Where can the audience go to learn more about Phoenix NAP and really start test driving with you guys? >> Absolutely. Well, if you come to phoenixnap.com, I guarantee you that we will re-target you and you can click on a banner later if you don't want to stay there. (Lisa laughs) But yeah, phoenixnap.com has all the information that you need. We also put out tons of helpful content. So if you're looking for anything technology oriented and you're just, "I want to upgrade to Ubuntu," you're likely going to end up on a phoenixnap.com website looking for that. And then you can find out more about what we do. >> Awesome, phoenixnap.com. William, thank you very much for joining Dave and me, talking about what you guys are doing, what you're enabling customers to achieve as the world continues to evolve at a very dynamic pace. We appreciate your insights. >> Absolutely, thank you so much >> For our guest and Dave Nicholson, I'm Lisa Martin. You've been watching the CUBE live from VMware Explorer, 2022. Dave and I will be joined by a guest consultant for our keynote wrap at the end of the day in just a few minutes. So stick around. (upbeat music)

>>mhm. >>Good morning. Live from Las Vegas. That snowflake Summit 22. Lisa Martin With Day Volonte David's Great. We have three wall to wall days of coverage at Snowflake Summit 22 this year. >>Yeah, it's all about data and bringing data to applications. And we've got some big announcements coming this week. Super exciting >>collaboration around data. We are excited to welcome our first two guests before the keynote. We have seen Nielsen in S V. P of data and Analytics Service offering head at emphasis. And Chris Dignan alumni is back with us to chief revenue officer at stuff like guys. Great to have you on the programme. Thanks for having us. Thank you very much. So he'll tell us what's going on with emphasis and snowflake and the partnership. Give us all that good stuff. >>Yeah, No, I think with the convergence of, uh, data digital and computing economy, um, you know that convergence is creating so much possibilities for for customers, uh, snowflake and emphases working together to help our customers realise the vision and these possibilities that are getting driven. We share a very strategic partnership where we are thinking ahead for our customers in terms of what, uh, we can do together in order to build solutions in order to bring out the expertise that is needed for such transformations and also influencing the thinking, Um, and the and the point of view in the market together so that, you know there is there is cohesive approach to doing this transformation and getting to those business outcomes. So it's a It's a partnership that's very successful and its strategic for for our customers, and we continue to invest for the market. >>Got some great customer. Some of my favourite CVS, Nike, William Sanoma. Gotta love that one. Chris talked to us about the snowflake data cloud. What makes it so unique and compelling in the market? >>Well, I think our customers, really they are going through digital transformation today, and they're moving from on premise to the cloud and historically speaking, there just hasn't been the right tool set to help them do that. I think snowflake brings to the table an opportunity for them to take all of their data and take it and and allow it to go from one cloud to the other so they can sit on a W s it can sit on Azure can sit on G, C, P and I can move around from cloud to cloud, and they can do analytics on top of that. >>So data has been traditionally really hard. And we saw that in the big data movement. But we learned a lot. Uh, and AI has been, you know, challenging. So what are you seeing with with customers? What are they struggling with? And how are you guys helping them? >>Yeah. So if you look at the customer journey, they have invested in a number of technologies in the past and are now at a juncture where they need to transform that landscape. They have the challenges of legacy debt that they need to, you know, get rid of or transform. They have the challenges of really bringing, you know, a cohesive understanding within the enterprise as to what these possibilities are for their business. Given the strategy that they are pursuing, um, business and I t cycles are not necessarily aligned. Um, you have the challenge of very fragmented data landscape that they have created over a period of time. How do you, you know, put all these together and work with a specific outcome in mind so that you're not doing transformation for the purpose of transformation. But to be able to actually drive new business models, new data driven products and services ability for you to collaborate with your partners and create unique competitive advantage in the market. And how do you bring those purposes together with the transformation that that's really happening? And and that's where you know our our customers, um, you know, grapple with the challenges of bringing it together. So, >>Chris, how do you see? Because it was talking about, uh, legacy that I think technical debt. Um, you kind of started out making the data warehouse easier. Then this data cloud thing comes out. You're like, Oh, that's an interesting vision and all of a sudden it's way more than vision. You get this huge ecosystem you're extending, we're gonna hear the announcements this morning. We won't. We won't spill the beans, but but really expanding the data cloud. So it's hard to keep up with with where you're at. So I think modernisation, right? So how do you think about modernisation? How are your customers thinking about it? And what's the scope of Snowflake. >>Well, you know, I think historically, you asked about AI and Ml and, you know, in the A I world historically, they've lacked data, and I think because we're the data cloud, we're bringing data, you know, and making it available and democratising it for everybody. And then, you know, partners like emphasis are actually helping us bring, you know, applications and new business models to to the table to our customers and their innovating on top of the data that we already have in the Snowflake Data Club. >>Chris, can you talk about some of the verticals where you guys are successful with emphasis that the three that I mentioned are retailers, But I know that finance, healthcare and life sciences are are huge for smooth, like talk to me, give us a perspective of the verticals that are coming to you. Guys saying help us out with transport. >>You know, I'll give you just an example. So So in the in the retail space, for example, Kraft Heinz is a is a joint customer of ours. And, you know, they've been all in on on snowflakes, Data Cloud and one of our big customers as well it is is Albertsons, and Albertans realises, Oh my gosh, I have all this information around the consumer in in the grocery stores and Kraft Heinz. They want access to that, and they actually can make supply chain decisions a lot faster if they have access to it. So with snowflakes data sharing, we can actually allow them to share data. Albertans share data directly with Kraft, Heinz and Kraft. Heinz can actually make supply chain decisions in real time so that these are some of the stuff that emphasis and stuff like help our customers self. >>So traditionally, the data pipeline goes through some very highly specialised individuals, whether the data engineer, the data scientists and data analyst. So that example that you just gave our organisation you mentioned before democratisation. So democratisation needs to be as a businessperson, I actually can get access to the data. So in that example that you gave between Kraft, Heinz and and and Albertson, is it the the highly hyper specialised teams sharing that data? Or is it actually extending into the line of business focus? >>That's so that's the interesting part for us is I think, snowflake, we just recently reorganise my sales team this year into verticals, and the reason we did that is customers no longer want to talk to us about speeds and feeds of how fast my database goes. They want to actually talk about business outcomes. How do I solve for demand forecasting? How do I supply fix my supply chain issues? Those are things. Those are the. That's how we're aligning with emphasis. So well is they've been doing this for a long time, Can only we haven't. And so we need their help on getting us to the next level of of the sales motion and talking to our customers on solving these business challenges in >>terms of that next level. So no question for you. Where are the customer conversations happening? At what level? I mean, we've seen such dramatic changes in the market in the last couple of years. Now we're dealing with inflation rising interest rates. Ukraine. Are you seeing the conversations in terms of building data platforms rising up the C suite? As every company recognises, we're going to be a data company. We're not gonna be a business. >>Absolutely. And I think all the macroeconomic forces that you talked about that's working on the enterprises globally is actually leading them to think about how to future proof their business models. Right? And there are tonnes of learning that they've hired in the last two or three years and digitising in embracing more digital models. The conversation with the customers have really pivoted towards business outcome. It is a C suite conversation. It is no longer just an incremental change for the for the companies they recognise. That data has been touted as a strategic asset for a long time, but I think it's taking a purpose and a meaning as to what it does for for the customers, the conversations are around industry verticals. You know, what are the specific challenges and opportunities that the the enterprises have, uh, and how you realise those and these cuts across multiple different layers. You know, we're talking about how your democratised data, which in our point of view, is absolute, must in terms of putting a foundation that doesn't take super specialised people to be able to run every operation and every bit of data that you process we have invested in building autonomous data and a state that can process data as it comes in without any manual intervention and take it all the way to consumption but also investing in those industry solutions. Along with snowflake, we launched the healthcare and life Sciences solution. We launched the only channel for retail and CPG. And these are great examples of how Snowflake Foundation enables democratisation on one side but also help solve business problems. In fact, with Snowflake, we have a very, uh, special partnership because our point of view on data economy is about how you connect with the network partners externally, and snowflake brings native capabilities. On this, we leverage that to Dr Exchanges for our customers and one of the services company in the recycling business. Uh, we're actually building and in exchange, which will allow the data points from multiple different sources and partners to come together. So they have a better understanding of their customers, their operations, the field operations and things >>like building a data ecosystem. Yes. Alright, They they Is it a two sided market place where you guys are observers and providing the the technology and the process, you know, guidance. What's your role in that? >>Yeah. So, um, we were seeing their revolution coming? Uh, two stages. Maybe even more. Um, customers are comfortable building an ecosystem. That's kind of private for them. Which means that they know who they are sharing data with. They know what the data is getting used for. And how do you really put governance on this? So that on one side you can trust it on the other side. There is a good use of that data, Uh, and not, uh, you know, compromise on their quality or privacy and some of the other regulations. But we do see this opening up to the two sided market places as well. Uh, some of the industry's lend themselves extremely well for that kind of play. We have seen that happening in trading area. We've seen that happen. And, uh, you know, the credit checks and things like that which are usually open for, you know, those kind of ecosystem. But the conversations and the and the programmes are really leading towards towards that in the market. >>You know, Lisa, one of things I wrote about this weekend is I was decided to come to stuff like summit and and see one of the, you know, thesis I have is that we're going to move not just beyond analytics, including analytics, but also building data products that can be monetised and and I'm hoping we're going to see some of that here. Are you seeing that Christian in the customer? It's It's >>a great question, David. So So we have You know, I just thought of it as as he was talking about. We have a customer who's a very large customer of ours who's in the financial services space, and they handle roughly 40% of the credit card transactions that happen in the US and they're coming to us and saying they want to go from zero in data business today to a $2 billion business over the next five years, and they're leaning on us to help them do that. And one of the things that's exciting for me is they're coming to us not saying Hey, how do you do it? You know, they're saying, Hey, we want to build a consumption model on top of snowflake and we want to use you as the delivery mechanism and the billing mechanism to help us actually monetise that data. So yes, the answer is. You know, I I used to sell to, you know, chief Data Officers and and see IOS. Now I'm talking to VPs of sales and I'm talking to chief operating officers and I'm talking to CEOs about how do we actually create a new revenue stream? And that's just I mean, it's exhilarating to have those conversations. That's >>data products. They don't have to worry about the infrastructure that comes from the cloud. They don't have to worry about the governance, as Senior was saying, Just put >>it in stuff like Just >>put stuff like that. So I call it The super cloud is kind of a, you know, a funny little tongue in cheek. But it's happening. It's this layer. It's not just multiple clouds. You see a lot of your critical competitors adjacent competitors saying, Hey, we're now running in in Google or we're running in Azure. We've been running on AWS. This is different. This is different, isn't it? It's a cloud that floats above the The infrastructure of the hyper scale is, and that's that's a new era. I think >>it's a new error. I think they're you know, I think the hyper scholars want to, you know, keep us as a as a data warehouse and and we're not. The customers are not letting them so So I think that's you know where emphasis kind of saw the light early on. And they were our innovation partner of the year, uh, this past year and they're helping us in our customers innovate, >>but you're uniquely qualified to do that where? I don't think it's the hyper scholars agenda. At least I never say never with the hyper scale is, but yeah, they have focused on providing infrastructure. And, yeah, they have databases and other tools. But that that cross cloud that continuum to your point, talking to VPs of sales and how do you generate revenue? That maybe, is a conversation that they have, but not explicitly as to how to actually do it in a data >>cloud. That's right. I mean, those and those are the Those are the fun conversations because you're you're saying, Hey, we can actually create a new revenue stream. And how can we actually help you solve our joint customers problems? So, yes, it is. Well, >>that's competitive differentiation for businesses. I mean, this is, as I mentioned Every company has to be a data company. If they're not, they're probably not going to be around much longer. They've got to be able to to leverage a data platform like snowflake, to find insights, be able to act on them and create value new services, new products to stay competitive, to stay ahead of the competition. That's no longer nice to have >>100%. I mean, I think they're they're all scared. I mean, you know, like if you look in the financial services space, they look at some of the fintech, as you know, the giant £800 gorillas look at the small fintech has huge threats to the business, and they're coming to us and say, How can we innovate our business now? And they're looking at us as the the innovator, and they're looking at emphasis to help them do that. So I think these are These are incredible times. >>So the narrative on Wall Street, of course, this past earnings season was consumption and who has best visibility and and they they were able to snowflake had a couple of large customers dial down consumption, some consumer facing. Here's the thing. If you're selling a data product for more than it costs you to make. If you dial down consumption in the future, you're gonna dial down revenue. So that's it's going to become less and less discretionary over time. And that, to me, is the next error. That's really exciting. >>The key, The key there is understanding the unit of measure. I think that's the number. One question that we get from customers is what is the unit of measure that we care about, that we want to monetise because to your point, it costs you more to make the product. You're not going to sell it right? And so I think that those are the things that the energy that we're spending with customers today is advising them, jointly advising them on how to actually monetise the specific, you know, unit of measure that they care >>about because when they get the Amazon bill or the snowflake bill, the CFO starts knocking the door. The answer has to be well, look at all the revenue that we generated and all the operating profit and the free cash flow that we drove, and then it's like, Oh, I get it. Keep doing it well, if I'm >>if I'm going on sales calls with the VP of sales and his their sales team, fantastic, right generated helping them generate revenue, right? That's a great conversation >>dynamic. And I think the adoption is really driven through the value, uh, that they can drive in their ecosystem. Their products are similar to products and services that these companies sell. And if you're embedding data inside Syria into your products services, that makes you that much more competitive in the market and drive value for your stakeholders. And that's essentially the future business model that we're talking about. On one side, the other one is the agility. Things aren't remaining constant, they are constantly changing, and we talked about some of those forces earlier. All of this is changing. The landscape is changing the the needs in the economy and things like that, and how you adapt to those kind of models in the future and pivoted on data capabilities that lets you identify new opportunities and and create new value. >>Speaking of creating new value last question guys, before we wrap, what's the go to market approach here between the two companies working customers go to get engaged. I imagine both sides. >>Yeah. I mean, the way that partnership looks good to me is is sell with co selling. So So I think, you know, we look at developing joint solutions with emphasis. They've done a wonderful job of leading into our partnership. So, you know, Sue Neill and I have a regular cadence where we talked every quarter, and our sales teams and our partner teams are are all leaning in and co selling. I don't know if you >>have Absolutely, um, you know, we we proactively identify, you know, the opportunities for our customers. And we work together at all levels within, you know, between the two companies to be able to bring a cohesive solution and a proposition for the customers. Really help them understand how to, you know, what is it that they can, um, get to and how you get that journey actually executed. And it's a partnership that works very seamlessly through that entire process, not just upstream when we're selling, but also downstream and we're executing. And we've had tremendous success together and look forward to more. >>Congratulations on that success, guys. Thank you so much for coming on talking about new possibilities with data and AI and sharing some of the impact that the technologies are making. We appreciate your insights. >>Thank you. Thank >>you. Thank you So much >>for our guests and a Volonte. I'm Lisa Martin. You're watching the Cube live in Las Vegas from Snowflake Summit 22 back after the keynote with more breaking news. Mhm, mhm.

>> Announcer: theCUBE presents Kubecon and Cloudnativecon Europe, 2022. Brought to you by Red Hat, the cloud native computing foundation and its ecosystem partners. >> Welcome to Valencia, Spain in Kubecon, Cloudnativecon Europe 2022. I'm Keith Townsend and alongside Enrico senior IT analyst for (indistinct). Welcome back to the show Enrico. >> Thank you again for having me here. >> First impressions of Kubecon. >> Well, great show. As I mentioned before, I think that we are really in this very positive mood of talking with each other and people wanting to see the projects, people that build the projects and it's amazing. A lot of interesting conversation in the show floor and in the various sessions, very positive mood. >> So this is going to be a fun one, we have some amazing builders on the show this week and none other than William Morgan, CEO of Buoyant. What's your role in the Linkerd project? >> So I was one of the original creators of Linkerd, but at this point I'm just the beautiful face of the project. (all laughing) >> Speaking of beautiful face of the project Linkerd just graduated from as a CNCF project. >> Yeah, that's right so last year we became the first service mesh to graduate in the CNCF, very proud of that and that's thanks largely to the incredible community around Linkerd that is just excited about the project and wants to talk about it and wants to be involved. >> So let's talk about the significance of that. Linkerd not the only service mesh project out there. Talk to me about the level effort to get it to the point that it's graduated. You don't see too many projects graduating CNCF in general so let's talk about kind of the work needed to get Linkerd to this point. >> Yeah so the bar is high and it's mostly a measure, not necessarily of like the project being technically good or bad or anything but it's really a measure of maturity of the community around it so is it being adopted by organizations that are really relying on it in a critical way? Is it being adopted across industries? Is it having kind of a significant impact on the Cloudnative community? And so for us there was the work involved in that was really not any different from the work involved in kind of maintaining Linkerd and growing the community in the first place, which is you try and make it really useful. You try and make it really easy to get started with, you try and be supportive and to have a friendly and welcoming community. And if you do those things and you kind of naturally get yourself to the point where it's a really strong community full of people who are excited about it. >> So from the point of view of users adopting this technology, so we are talking about everybody or do you see really large organization, large Kubernetes clusters infrastructure adopting it? >> Yeah, so the answer to that is changed a little bit over time but at this point we see Linkerd adoption across industries, across verticals, and we see it from very small companies to very large ones so one of the talks I'm really excited about at this conference is from the folks at Xbox cloud gaming who are going to talk about how they deployed Linkerd across 22,000 pods around the world to serve basically on demand video games. Never a use case I would ever have imagined for Linkerd and at the previous Kubecon virtually Kubecon EU, we had a whole keynote about how Linkerd was used to combat COVID 19. So all sorts of uses and it really doesn't, whether it's a small cluster or large cluster it's equally applicable. >> Wow so as we talk about Linkerd service mesh we obviously are going to talk about security, application control, etcetera. But in this climate software supply chain is critical and you think about open source software supply chain, talk to us about the recent security audit of Linkerd. >> Yeah so one of the things that we do as part of a CNCF project and also as part of, I think our relationship with our community is we have regular security audits where we engage security professionals who are very thorough and dig into all the details. Of course the source code is all out there, so anyone can read through the code but they'll build threat model analysis and things like that. And then we take their report and we publish it. We say, "Hey look, here's the situation." So we have earlier reports online and this newest one was done by a company called Trail of Bits and they built a whole threat model and looked through all the different ways that Linkerd could go wrong and they always find issues of course, it would be very scary, I think, to get a report that was like, no, we didn't find- >> Yeah everything's clean. >> Yeah everything's fine, should be okay, I don't know. But they did not find anything critical. They found some issues that we rapidly addressed and then everything gets written up in the report and then we publish it, as part of an open source artifact. >> How do you, let's say, do they give you and adds up something? So if something happens so that you can act on the code before somebody else discovers the- >> Yeah, they'll give you a preview of what they found and then often it's not like you're going before the judge and the judge makes a judgment and then like off to jail, it's a dialogue because they don't necessarily understand the project. Well, they definitely don't understand it as well as you do. So you are helping them understand which parts are interesting to look at from the security perspective, which parts are not that interesting. They do their own investigation of course but it's a dialogue the entire time. So you do have an opportunity to say, "Oh you told me that was a a minor issue. "I actually think that's larger or vice versa." You think that's a big problem actually, we thought about that and it's not a big problem because of whatever. So it's a collaborative process. >> So Linkerd been around, like when I first learned about service mesh Linkerd was the project that I learned about. It's been there for a long time, just mentioned 22,000 clusters. That's just mind boggling- >> Pods, 22,000 pods. >> That's pods. >> Clusters would be great. >> Yeah, clusters would be great too but it filled 22,000 pods. >> It's a big deployment. >> That's a big deployment of Linkerd, but all the way down to the smallest set of pods as well. What are some of the recent project updates some of the learnings you bought back from the community and updated the project as a result? >> Yeah so a big one for us, on the topic of security, Linkerd, a big driver of Linkerd adoption is security and less on the supply chain side and more on the traffic, like live traffic security. So things like mutual TLS, so you can encrypt the communication between pods and make sure it's authenticated. One of the recent feature additions is authorization policy so you can lock down connections between services and you can say Service A is only allowed to talk to Service B and I want to do that not based on network identity, not based on like IP addresses, 'cause those are spoofable and we've kind of like as an industry moved, we've gotten a little more advanced from that but actually based on the workload identity as captured by the mutual TLS certificate exchange. So we give you the ability now to restrict the types of communication that are allowed to happen on your cluster. >> So, okay this is what happened. What about the future? Can you give us into suggestion on what is going to happen in the medium and long term? >> I think we're done you know we graduated, so we're just going to stop. (all laughing) What else is there to do? There's no grad school. No, so for us, there's a clear roadmap ahead continuing down the security realm, for sure. We've given you kind of the very first building block which at the service level, but coming up in the 2.12 release we'll have route based policy as well, as you can say this service is only allowed to call these three routes on this end point. And we'll be working later to do things like mesh expansions so we can run the data plane outside of Kubernetes, so the control plane will stay in Kubernetes but the data plane will, you'll be able to run that on Vms and things like that. And then of course in the, we're also starting to look at things like, I like to make a fun of (indistinct) a lot but we are actually starting to look at (indistinct) in the ways that that might actually be useful for Linkerd users. >> So we talk a lot about the flexibility of a project like Linkerd you can do amazing things with it from a security perspective but we're talking still to a DevOps type cloud of developers who are spread thin across their skillset. How do you help balance the need for the flexibility which usually comes with more nerd knobs and servicing a crowd that wants even higher levels of abstraction and simplicity. >> Yeah, that's a great question and this is what makes Linkerd so unique in the service mesh spaces. We have a laser focus on simplicity and especially on operational simplicity so our audience, we can make it easy to install Linkerd but what we really care about is when you're running it and you're on call for it and it's sitting in this critical, vulnerable part of your infrastructure, do you feel confident in that? Do you feel like you understand it? Do you feel like you can observe it? Do you feel like you can predict what it's going to do? And so every aspect of Linkerd is designed to be as operationally simple as possible. So when we deliver features, that's always our primary consideration, is we have to reject the urge, we have an urge as engineers to like want to build everything, it's an ultimate platform to solve all problems and we have to really be disciplined and say we're not going to do that, we're going to look at solving the minimum possible problem with a minimum set are features because we need to keep things simple and then we need to look at the human aspect to that. And I think that's been a part of Linkerd's success. And then on the Buoyant side, of course, I don't just work on Linkerd, I also work on Buoyant which helps organizations adopt Linkerd and increasingly large organizations that are not service mesh experts don't want to be service mesh experts, they want to spend their time and energy developing their business, right? And building the business logic that powers their company. So for them we have actually recently introduced, fully managed Linkerd where we can take on, even though Linkerd has to run on your cluster, the sidecar proxies has to be alongside your application. We can actually take on the operational burden of upgrades and trust income rotation, and installation. And you could effectively treat it as a utility, and have a hosted-like experience even though the actual bits, at least most of them not all of them, most of 'em have to live on your cluster. >> I love the focus of most CNCF projects, it's peanut butter or jelly, not peanut butter trying to be become jelly. What's the peanut butter to Linkerd's jelly? Like where does Linkerd stop? And some of the things that customers should really consider when looking at service mesh? >> Yeah, now that's a great way of looking at it and I actually think that philosophy comes from Kubernetes. I think Kubernetes itself, one of the reasons it was so successful is because it had some clearly delineated boundaries. It said, "This is what we're going to do. "And this is what we're not going to do. "So we're going to do layer three, four networking, "but we're going to stop there, "we're not going to do anything with layer seven." And that allowed the service mesh. So I guess if I were to go down the bread of the sandwich is Kubernetes, and then Linkerd is the peanut butter, I guess. And then the jelly, so I think the jelly is every other aspect of of building a platform. So if you are the audience for Linkerd most of the time is a platform owners. They're building a platform an internal platform for their developers to write code and so, as part of that, of course you've got Kubernetes, you've got Linkerd, but you've also got a CICD system. You've also got a code repository that's GitLab or or GitHub or whatever, you've got other kind of tools that are enforcing various other constraints. All of that is the jelly in the, this is analogy it's getting complicated now, and like the platform sandwich that you're serving. >> So talk to us about trans and service mesh from the, as we think of the macro. >> Yeah, so it's been an interesting space because, we were talking a little bit about this before the show but, there was so much buzz and then what we saw was basically it took two years for that buzz to become actual adoption and now a lot of the buzz is off on other exciting things and the people who remain in the Linkerd space are very focused on, "Oh, I actually have a real problem "that I need to solve "and I need to solve it now." So that's been great. So in terms of broader trends, I think one thing we've seen for sure is the service mesh space is kind of notorious for complexity, and a lot of what we've been doing on the Linkerd side has been trying to reverse that idea, because it doesn't actually have to be complex. There's interesting stuff you can do, especially when you get into the way we handle the sidecar model. It's actually really, it's a wonderful model operationally. It's really, it feels weird at first and then you're like, "Oh, actually this makes my operations a lot easier." So a lot of the trends that I see at least for Linkerd is doubling down on the sidecar model trying to make side cars as small and as thin as possible and try and make them kind of transparent to the rest of the application. >> Well, William Morgan, one of the coolest Twitter handles I've seen at WM on Twitter, that's actually a really cool Twitter handle. >> William: Thank you. >> CEO of Buoyant. Thank you for joining theCube again, Cube alum. From Valencia Spain, I'm Keith Towns, along with Enrico's (indistinct) and you're watching theCube, the leader in high tech coverage. (upbeat music)

>>The cube presents, Coon and cloud native con Europe 22, brought to you by the cloud native computing foundation. >>Welcome to vincia Spain in Coon cloud native con Europe, 2022. I'm Keith towns alongside en Rico senior. Etti senior it analyst for giong welcome back to the show en >>Rico. Thank you again for having me here. >>First impressions of QAN. >>Well, great show. As, as I mentioned before, I think that we are really in this very positive mode of talking with each other and people wanting to see, you know, the projects, people that build the projects at it's amazing. I mean, a lot of interesting conversation in the show floor and in the various sessions, very positive move. >>So this is gonna be a fun one. We have some amazing builders on the show this week, and none other than William Morgan, CEO of buoyant. What's your role in the link D project? >>So I was one of the original creators of link D but at this point I'm just the, the beautiful face of the project. >>Speaking of beautiful face of the project, linker D just graduated from as a CNCF project. >>Yeah, that's right. So last year we, we became the first service mesh to graduate in the CNCF. Very proud of that. And that's thanks, you know, largely to the incredible community around Linky that is just excited about the project and, you know, wants to talk about it and wants to be involved. >>So let's talk about the significance of that link D not the only service mesh project out there. Talk to me about the level effort to get it to the point that it's graduated. That's you don't see too many projects graduating CNCF in general. So let's talk about kind of the work needed to get Nier D to this point. >>Yeah. So, you know, the, the, the bar is high and it's mostly a measure, not necessarily of like the, the project being technically good or bad or anything, but it's really a measure of maturity of the community around it. So is it being adopted by organizations that are really relying on it in a critical way? Is it, you know, being adopted across industries, you know, is it having kind of a significant impact on the cloud native community? And so for us, you know, there was the, the work involved in that was really not any different from the work involved in, in kind of maintaining ity and growing the community in the first place, which is you try and make it really useful. You try and make it really easy to get started with you, try and be supportive and to, you know, have a, a friendly and welcoming community. And if you do those things and, you know, you kind of naturally get yourself to the point where it's a, it's a really strong community full of people who are excited about it. >>So from the of view of, you know, users adopting the, this technology, so we are talking about everybody, or do you see really, you know, large organization, large Kubernetes yeah. Clusters infrastructure adopting it. >>Yeah. So that's the answer to that is changed a little bit over time. But at this point we see Linky adoption across industries, across verticals, and we see it from very small companies to very large ones. So, you know, one of the talks I'm really excited about at this conference is from the folks at Xbox cloud gaming, who talked about, who are gonna talk about how they deployed Linky across, you know, 22,000 pods around the world to serve, you know, basically on demand video games, never a use case I would ever have imagined for Linky. And at the previous Kuan, you know, virtually Kuan EU, we had a whole keynote about how Linky was used to combat COVID 19. So all sorts of uses. And it really doesn't, you know, whether, whether it's a small cluster or large cluster it's equally applicable. >>Wow. So as we talk about link D service match, we obviously are gonna talk about security application control, etcetera. But in this climate Software supply chain is critical, right. And as we think about open source software supply chain, talk to us about the recent security audit of link dealer. >>Yeah. So one of the things that we do as part of a CNCF project, and also as part of, I, I think our relationship with our community is we have regular security audits, you know, where we, we engage security professionals who are very thorough and, you know, dig into all the details. Of course the source code is all out there, you know, so anyone can read through the code, but they'll build threat model analyses and things like that. And then we take their, their report and we publish it. We say, Hey, look, here's, you know, here's the situation. So we have earlier reports online, and this newest one was done by a company called trail of bits. And they built a whole threat model and looked through all the different ways that Linky could go wrong. And they always find issues. Of course, you know, it's, it would be very scary, I think, to get a report that was like, no, we didn't find yeah. Earth clean, you know? Yeah. Everything's fine. You know, should be okay. I don't know. Right. But they, you know, they did not find anything critical. They found some issues that we rapidly addressed and then, you know, everything gets written up in the report and, and then we publish it, you know, as part of an open source artifact >>Are, you let's say, you know, do they give you and add something? So if something happens so that you can act on the code before, you know, somebody else discovers the >>Yeah, yeah. They'll give you a preview of what they found. And then often, you know, it's not like you're going before the judge and the judge makes a judgment and then like off the jail, right. It's, it's a dialogue because they don't necessarily understand the project. Well, they definitely don't understand it as well as you do. So you are helping them, you know, understand which parts and, and your, you know, are, are interesting to look at from the security perspective, which parts are not that interesting. They do their own investigation of course, but it's a dialogue the entire time. So you do have an opportunity to say, oh, you told me that was a, a, a minor issue. I actually think that's larger or, or vice versa. You know, you, you think that's a big problem. Actually, we thought about that, and it's not a big problem because of whatever. So it's a collaborative process. >>So link D been around, like, when I first learned about service me link D was the project that I learned about. Yeah. It's been there for a long time, but just mentioned 22,000 clusters. That's just mind boggling pod, 22,000 pods, the pods. Okay. >>Clusters would be >>Great. Yeah. Yeah. Clusters would be great too, but filled 22 thousands pods, big deployment. That's the big deployment of link D but all the way down to the small, smallest set of pods as well. What are some of the recent project updates from of the learnings you bought back from the community and updated the, the project as a result? >>Yeah. So a big one for us, you know, on the topic of security link, a big driver of link adoption is security and, and less on the supply chain side and more on the traffic, like live traffic security. So things like mutual TLS. So you can encrypt the communication between pods and make sure it's authenticated. One of the recent feature additions is authorization policy. So you can lock down connections between services and you can say service a is only allowed to talk to service B. And I wanna do that. Not based on network identity, you know, and not based on like IP addresses, cuz those are spoof. And you know, we've kind of like as an industry moved, moved, we've gotten a little more advanced from that, but actually based on the workload identity, you know, as captured by the mutual TLS certificate exchange. So we give you the ability now to, to, to restrict the types of communication that are allowed to happen on your cluster. >>So, okay. This is what happened. What about the future? Can you give us, you know, into suggestion of what is going to happen in the medium and long term? >>I think we're done, you know, we graduated, so we're just gonna >>Stop there's >>What else is there to do? There's no grad school, you know? No, no. So for us, there's a clear roadmap ahead, continuing down the, the security realm, for sure. We've given you kind of the very first building block, which at the service level, but coming up in, in the two point 12 release, we'll have route based policy as well, as you can say, this service is only allowed to call these three, you know, routes on this end point and we'll be working later to do things like mesh expansion so we can run the data plane outside of Kubernetes. You know, so the control plane will stay in in Kubernetes, but the data plane will, you'll be able to run that on VMs and, and, and things like that. And then of course in the, you know, we're also starting to look at things like I like to make a fun of WAM a lot, but we are actually starting to look at WAM in, in the ways that that might actually be useful for Linky users. >>So we talk a lot about the flexibility of a project, like link D you can do amazing things with it from a security perspective, but we're talking still to a DevOps type cloud of, of, of developers who are spread thin across their skillset. How do you help balance the need for the flexibility, which usually becomes more nerd knobs and servicing a crowd that wants even higher levels of abstraction and simplicity. >>Yeah. Yeah. That's a great question. And this is, this is what makes Linky so unique in the service mesh spaces. We have a laser focus on simplicity and especially on operational simplicity. So our audience, you know, we can make it easy to install Linky, but what we really care about is when you're running it and you're on call for it and it's sitting in this critical, vulnerable part of your infrastructure, do you feel confident in that? Do you feel like you understand it? Do you feel like you can observe it? Do you feel like you can predict what it's gonna do? And so every aspect of Linky is designed to be as operationally simple as possible. So when we deliver features, you know, that's always our, our primary consideration is, you know, we have to reject the urge. You know, we have an urge as, as engineers to like want to build everything, you know, it's an ultimate platform to solve all problems and we have to really be disciplined and say, we're not gonna do that. >>We're gonna look at solving the minimum possible problem with a minimum set of features because we need to keep things simple. And, and then we need to look at the human aspect to that. And I think that's been a part of, of Link's success. And then on the buoyant side, of course, you know, I don't just work on link day. I also work on, on buoyant, which helps organizations adopt Linky and, and increasingly large organizations that are not service mesh experts don't wanna be service mesh experts that, you know, they wanna spend their time and energy developing their business, right. And, and building the business logic that powers their company. So for them, we have actually re recently introduced, fully managed. Linky where we can take on, even though Linky has to run on your cluster, right? The, the, the, the sidecar proxies has to be alongside your application. We can actually take on the operational burden of, of upgrades and trust, anchor rotation, and installation. And you can effectively treat it as a utility, right. And, and, and have a, a hosted, like, experience, even though the, the actual bits, at least most of them, not all of them, most of 'em have to live on your cluster. >>I love the focus of most CNCF projects, you know, it's, it's peanut butter or jelly, not peanut butter. Yeah. Trying to be become jelly. Right. What's the, what's the, what's the peanut butter to link D's jelly. Like where does link D stop and some of the things that customers should really consider yeah. When looking at service mesh. >>Yeah. No, that's a great way of looking at it. And I, I actually think that that philosophy comes from Kubernetes. I think Kubernetes itself, one of the reasons it was so successful is because it had some clearly delineated, it said, this is what we're gonna do. Right. And this is what we're not gonna do. So we're gonna do layer three, four networking. Right. But we're gonna stop there. We're not gonna do anything with layer seven. And that allowed the service mesh. So I guess if I were to go down the, the bread, the bread of the sandwich has Kubernetes, and then Linky is the, is the peanut butter, I guess, and then the jelly, you know, so I think the jelly is every other aspect of, of building a platform. Right. So if you are the, the audience for Linky, most of the time, it's a platform owners, right. They're building a platform, an internal platform for their developers to write code. And so, as part of that, of course, you've got Kubernetes, you've got Linky, but you've also got a C I CD system. You've also got a, you know, a code repository, if it's GitLab or, or GitHub or wherever you've got, you know, other kind of tools that are enforcing various other constraints. All of that is the jelly, you know, in the, this is, analogy's getting complicated now. And like the, the platform sandwich that, you know, that you're serving. >>So talk to us about trans and service mesh from the, from the, as we think of the macro. >>Yeah. Yeah. So, you know, it's been an interesting space because we were talking a little bit about, you know, about this before the show, but the, there was so much buzz, you know, and then what we, what we saw was basically it took two years for that buzz to become actual adoption, you know, and now a lot of the buzz is off on other exciting things. And the people who remain in the Linky space are, are very focused on, oh, I actually have a, a real problem that I need to solve and I need to solve it now. So that's been great. So in terms of broader trends, you know, I think one thing we've seen for sure is the service mesh space is kind of notorious for complexity, you know, and a lot of what we've been doing on the Linky side has been trying to, to reverse that, that, that idea, you know, because it doesn't actually have to be complex. There's interesting stuff you can do, especially when you get into the way we handle the sidecar model. It's actually really, it's a wonderful model operationally. It's really, it feels weird at first. And then you're like, oh, actually this makes my operations a lot easier. So a lot of the trends that I see at least for Linky is doubling down on the sidecar model, trying to make side cards as small and as thin as possible and try and make them, you know, kind of transparent to the rest of the application. So >>Well, William Morgan, one of the coolest Twitter handles I've seen at WM on Twitter, that's actually a really cool Twitter handle. Thank you, CEO of buoyant. Thank you for joining the cube again. Cube alum from Valencia Spain. I'm Keith towns, along with en Rico, and you're watching the cube, the leader in high tech coverage.

(intro music playing) >> Hello everyone, and welcome to the power of n where HPE Aruba and Pensando are changing the game, the way customers scale with the cloud, and what's next in the evolution in switching. Hey everyone, I'm John furrier with the cube, and I'm here with Shane Corbin, director of technical product management at Pensando, and William show vice president of product management, Aruba HPE. Gentlemen, thank you for coming on and doing a deep dive and, and going into the, the big news. So the first question I want to ask you guys is um, what do you guys see from a market customer perspective that kicked this project off? um, amazing um, results um, over the past year or so? Where did it all come from? >> No, it's a great question, John. So when we were doing our homework, there were actually three very clear customer challenges. First, security threats were largely spawn with on, within the perimeter. In fact, Forrester highlighted 80% of threats originate within the internal network. Secondly, workloads are largely distributed creating a ton of east-west traffic. And then lastly, network services such as firewalls, load balancers, VPN aggregators are expensive, they're centralized, and they ultimately result in service chaining complexity. >> John: So, so, >> John: Go ahead, Shane. >> Yeah. Additionally, when we spoke to our customers after launching initially the distributed services platform, these compliance challenges clearly became apparent to us and while they saw the architecture value of adopting what the largest public cloud providers have done by putting a smart NIC in each compute node to provide these stateful services. Enterprise customers were still, were struggling with the need to upgrade fleets and brown field servers and the associated per node cost of adding a smart NIC to every compute node. Typically the traffic volumes for on a per node basis within an enterprise data center are significantly lower than cloud. Thus, we saw an opportunity here to, in conjunction with Aruba, develop a new category of switching product um, to share the processing capabilities of our unique intellectual property around our DPU across a rack of servers that net net delivers the same set of services through a new category of platform, enabling a distributed services architecture, and ultimately addressing the compliance and TCO generating huge TCO and ROI for customers. >> You know, one of the things that we've been reporting on with you guys, as well as the cloud scale, this is the volume of data and just the performance and scale. I think the timing of the, of this partnership and the product development is right on point. And you've got the edge right around the corner, more, more distributed nature of cloud operations, huge, huge change in the marketplace. So great timing on the origination story there. Great stuff. Tell me more about the platform itself, the details, what's under the hood, the hardware OS, what are the specs? >> Yeah, so we started with a very familiar premise. Rubik customers are already leveraging CX with an edge to cloud common operating model, in deploying leaf and spine networks. Plus we're excited to introduce the industry's first distributed services switch, where the first configuration has 48-25 gig ports with a hundred gig couplings running Aruba CX cloud native operating system, Pensando Asic's software inside, enabling layer four through six, seven stateful services. Shane, do you want to elaborate on. >> Yeah, let me elaborate on that a little bit further, um, you know, as we spoke existing platforms and how customers were seeking to address these challenges were, are inherently limited by the ASIC dye size, and that does limit their scale and performance and ability in traditional switching platforms to deliver truly stateful functions in, in, in a switching platform, this was, you know, architecturally from the ground up, when we developed our DPU, first and second generation, we delivered it, or we, we built it with stateful services in mind from the get-go, we leveraged the clean state design with our P four program with DPU. We evolved to our seven nanometers based pro DPU right now, which is essentially enabling software and Silicon. And this has generated a new level of performance scale, flexibility and capability in terms of services. This serves as the foundation for our 200 gig card, were we taking the largest cloud providers into production for. And the DPU itself is, is designed inherently to process stage, track stateful connections, and stateful flow is at very, very large scale without impacting performance. And in fact, the two of these DPU components server disk, services foundation of the CX 10 K, and this is how we enable stateful functions in a switching platform functions like stateful network fire-walling, stateful segmentation, enhanced programmable telemetry, which we believe will bring a whole lot of value to our customers. And this is a platform that's inherently programmable from the ground up. We can, we can build and leverage this platform to build new use cases around encryption, enabling stateful load balancing, stateful NAT to name a few, but, but the key message here is, this is, this is a platform with the next generation of architecture's in mind, is programmed, but at all, there's the stack, and that's what makes it fundamentally different than anything else. >> I want to just double click on that if you don't mind, before we get to the competitive question, because I think you brought up the state thing. I think this is worth calling out, if you guys don't mind commenting more on this states issue, because this is big. Cloud native developers right now, want speed, they're shifting left at the CICD pipeline with programmability. So going down and having the programmability, and having state is a really big deal. Can you guys just expand on that a little bit more and why it's important and, and how hard it really is to pull off? >> I, I can start, I guess, um, it's very hard to pull off because of the sheer amount of connections you need to track when you're developing something like a stateful firewall or a stateful load balancer, a key component of that is managing the connections at very, very large scale and understanding what's happening with those connections at scale, without impacting application performance. And this is fundamentally different at traditional switching platform, regardless of how it's deployed today in Asics, don't typically process and manage state like this. Um, memory resources within the chip aren't sufficient, um, the policy scale that you can um, implement on a platform aren't sufficient to address and fundamentally enable deployable firewalling, or load balancing, or other stateful services. >> That's exactly right. And so the other kind of key point here is that, if you think about the sophistication of different security threats, it does really require you to be able to look at the entire packet, and, and more so be able to look at the entire flow and be able to log that history, so that you can get much better heuristics around different anomalies, security threats that are emerging today. >> That's a great, great point. Thanks for, for, um, bringing that extra, extra point out. I would just add to this, we're reporting this all the time on Silicon angle in the cube is that, you know, the, you know, the, the automation wave that's coming with around data, you know, it's a center of data, not data centers we heard earlier on with the, in, in, in the presentation. Data drives automation, having that enabled with the state is a real big deal. So, I think that's really worth calling out. Now, I've got to ask the competition question, how is this different? I mean, this is an evolution. I would say, it's a revolution. You guys are being being humble, um, but how is this different from what customers can deploy today? >> Architecturally, if you take a look at it. We've, we've spoken about the technology and fundamentally in the platform what's unique, in the architecture, but, foundationally when customers deploy stateful services they're typically deployed leveraging traditional big box appliances for east-west our workload based agents, which seek to implement stateful security for each east-west. Architecturally what we're enabling is stateful services like firewalling, segmentation, can scale with the fabric and are delivered at the optimal point for east west which is through leaf for access layer of the network. And we do this for any type of workload. Be it deployed on a virtualized compute node, be a deployed on a containerized worker node, be deployed on bare metal, agnostic up typology, it can be in the access layer of a three tier design and a data center. It can be in the leaf layer of a VX VPN based fabric, but the goal is an all centrally managed to a single point of orchestration and control of which William will talk about shortly. The goal of this is to drive down the TCO of your data center as a whole, by allowing you to retire legacy appliances that are deployed in an east-west roll, and not utilize host based agents, and thus save a whole lot of money and we've modeled on the order of 60 to 70% in terms of savings in terms of the traditional data center pod design of a thousand compute nodes which we'll be publishing. And as, as we go forward additional services, as we mentioned, like encryption, this platform has the capability to terminate up to 800 gigs of our line rates encryption, IP sec, VPN per platform, stateful Nat load balancing, and this is all functionality we'll be adding to this existing platform because it's programmable as we've mentioned from the ground up. >> What are some of the use cases lead? And what's the top use cases, what's the low hanging fruit and where does this go? You've got service providers, enterprises. What are the types of customers you guys see implementing? >> Yeah, that's, what's really exciting about the CX 10,000. We actually see customer interest from all types of different markets, whether it be higher education, service providers to financial services, basically all enterprises verticals with private cloud or edge data centers. For example, it could be a hospital, a big box retailer, or a colon such as Iniquinate So it's really the CX 10,000 that creates a new switching category, enabling stateful services in that leaf node right at the workload, unifying network and security automation policy management. Second, the CX 10,000 greatly improves security posture and eliminates the need for hair-pinning east-west traffic all the way back to the centralized deployments. Lastly, As Shane highlighted, there's a 70% TCO savings by eliminating that appliance sprawl and ultimately collapsing the network security operations. >> I love the category creation um, vibe here. Love it. And also the technical and the cloud alignment's great. But how do the customers manage all this? Okay, I got a new category. I just put the box in, throw away some other ones? I mean, how does this all get done? And how does the customers manage all this? >> Yeah, so we're, we're looking to build on top of the river fabric composer. It's another familiar site for our customers, and what's already provides for compute storage and network automation, with a broad ecosystem integrations, such as VMware vSphere Vcenter as with Nutanix prism and so aligned with the CX 10,000 FGA, now you have a fabric composer, unified security and policy orchestration, and management with the ability to find firewall policies efficiently and provide that telemetry to collect your such a Splunk. >> John: So the customer environments right now involve a lot of multi-vendor and new frameworks, obviously, cloud native. How does this fit into the customer's existing environment with the ecosystem? How do they get, get going here? >> Yeah, great question. Um, Our customers can get going as we, we've built a flexible platform that can be deployed in either Greenfield or brownfield. Obviously it's a best of breed architecture for distributed services we're building in conjunction with Aruba. But if customers want to gradually integrate this into their existing environments and they're using other vendors, spines or cores, this can be inserted seamlessly as, as a lead for an access, access tier switch to deliver the exact same set of services within that architecture. So it plugs seamlessly in because it supports all the standard control plan protocols, a VX 90 VPN, and a traditional attitude, three tier designs easily. Now, for any enterprise solution deployment, it's critical that you build a holistic ecosystem around it. It's clear that, this will get customer deployments and the ecosystem being diverse and rich is very, very important. And as part of our integrations with the controller, we're building a broad suite of integrations across threat detection, application dependency mapping, Siemens sooam, dev ops infrastructure as code tools. (inaudible) And it's clear if you look at these categories of integrations, you know, XDR or threat detection requires full telemetric from within the data center, it's been hard to accomplish to date because you typically need agents on, on your compute nodes to give you the visibility into what's going on or firewalls for east west fuels. Now, our platform can natively provide full visibility into all flows east- west in the data center. And this can become the source of telemetry truth that these MLX CR engines require to work. The other aspects of ecosystem around application dependency mapping, this single core challenge with deploying segmentation east west is understanding the rules to put in & Right, first is how do you insert the service, um, service device in such a way that it won't add more complexity? We don't add any complexity because we're in line natively. How you would understand it, would allow you to build the rules that are necessary to do segmentation. We integrate with tools like Guardi core, we provide our flogs as source of data, and they can provide room recommendations and policy recommendations for customers. Around, we're building integrations around Siemen soam with, with tools like Splunk and elastic, elastic search that will allow NetOps and SecOps teams to visualize trend and manage the services delivered by the CX 10 K. And the other aspect of ecosystem, from a security standpoint is clearly how do I get policy for these traditional appliances and enforce them on this next generation architecture that you've built, that can enable stateful services. So we're building integrations with tools like turf and an algo sec third-party sources of policy that we can ingest and enforce on the infrastructure, allowing you to gradually, um, migrate to this new architecture over time. >> John: It's really a cloud native switch. I mean, you solve people's problems, pin- points, but yet positioned for growth. I mean, it sounds that's my takeaway, but I got to ask you guys both, what's the takeaway for the customers because it's not that simple for them, I mean it's, we a have complicated environment. (all giggling) >> Yeah, I think it's, I think it's really simple, um, you know, every 10 years or so, we see major evolutions in the data center and the switching environment, but we do believe we've created a new category with the distributed services, distributed services switch, delivering cloud scale distributed services, where the local, where the workloads reside greatly, simplifying network, security provisioning, and operations with the urban fabric composer while improving security posture and the TCO. But that's not all the folks, it's a journey, right Shane? >> Yeah, it's absolutely a journey. And this is the first step in a long journey with a great partner like Aruba. There's other platforms, hundred or 400 gig hardware platforms where we're looking at and then this additional services that we can enable over time, allowing customers to drive even more TCO value out of the platform of the architecture services like encryption for securing the cloud on-ramp, services like stateful load balancing to deploy east-west in the data center and, you know, holistically that's, that's the goal, deliver value for customers. And we believe we have an architecture and a platform, and this is a first step in a long journey. >> It's a great way of, I just ask one final, final question for both of you as product leaders, you got to be excited having a category creation product here in this market, this big wave, but what's your thoughts? >> Yeah, exactly right, it doesn't happen that often, and so we're, we're all in it's, it's exciting to be able to work with a great team like Pensando and Shane here. Um, so we're really, really excited about this launch. >> Yeah, it's awesome. The team is great. It's a great partnership between Pensando and Aruba. You know, we, we look forward to delivering value for our joint customers. >> John: Thank you both for sharing under the hood and more details on the product. Thanks for coming on. >> [William And Shane] Thank you. >> Okay. The next evolution in switching, I'm John Furrier here with the power of nHPE Aruba and Pensando changing the game, the way customers scale up in the cloud and networking. Thanks for watching. (music playing)

>>Hello and welcome to the power of and where H P E Aruba and Pensando are changing the game the way customers scale at the cloud and what's next in the evolution in switching everyone. I'm john ferrier with the Cuban. I'm here with Shane Corbyn, Director of Technical Product management. Pensando Williams show vice president Product management, Aruba HP Gentlemen, thank you for coming on and doing a deep dive and and going into the big news. So the first question I want to ask you guys is um, what do you guys see from a market customer perspective that kicked this project off? Amazing results over the past year or so. Where did it all come from? >>It's a great question, John So when we were doing our homework, there were actually three very clear customer challenges. First, security threats were largely spawned with from within the perimeter. In fact, four star highlights that 80% of threats originate within the internal network. Secondly, workloads are largely distributed, creating a ton of east west traffic and then lastly, network services such as firewalls load balancers. VPN aggregators are expensive. They're centralized and then ultimately result in service changing complexity. So everyone, >>so go ahead. Change. >>Yeah. Additionally, when we spoke to our customers after launching initially the distributed services platform, these compliance challenges clearly became apparent to us and while they saw the architectural value of adopting what the largest public cloud providers have done by putting a smart making each compute note to provide these state full services. Enterprise customers were still were struggling with the need to upgrade fleets and Brownfield servers and the associated per node cost of adding a spark nick to every compute node. Typically the traffic volumes for on a personal basis within an enterprise data center are significantly lower than cloud. Thus we saw an opportunity here to in conjunction with Aruba developed a new category of switching product um, to share the crossing capabilities of our unique intellectual property around our DPU across a rack of servers that Net Net delivers the same set of services through a new category of platform, enabling a distributed services architecture and ultimately addressing the compliance and uh, TCO generating huge TCO and ri for customers. >>You know, one of the things that we've been reporting on with you guys as well as the cloud scale, this is the volume of data and just the performance and scale I think the timing of the, of this partnership and the product development is right on point. You got the edge right around the corner more, more distributed nature of cloud operations, huge, huge change in the marketplace. So great timing on the origination story there. Great stuff. Tell me more about the platform itself. The details what's under the hood, the hardware. Os, what are the specs? >>Yeah, so we started with a very familiar premise, Ruba customers are already leveraging C X with an edge to cloud, common operating model and deploying Leaf and spy networks. Plus we're excited to introduce the industry's first distributed services switch where the first configuration has 48 25 gig ports with 100 gig uplinks running Aruba C X cloud native operating system. Pensando A six and software inside enabling layer four through seven staple services you want to elaborate on. >>Let me elaborate on that a little further. Um, you know, as we spoke, existing platforms and how customers were seeking to address these challenges were inherently limited by the diocese and that thus limited their scale and performance and ability in traditional switching platforms to deliver truly stable functions in in a switching platform. This was, you know, architecturally from the ground up. When we developed our DPU 1st and 2nd generation, we delivered it or we we we built it with staples services in in mind from the Gecko. We we leverage to clean state designed with RP four program with GPU, we evolved to our seven nanometer based DPU right now, which is essentially enabling software and silicon and this has generated a new level of performance scale flexibility and capability in terms of services this serves as the foundation for or 200 gig card where we're taking the largest cloud providers into production for. And the DPU itself is designed inherently to process state track state connections and state will flow is a very, very large scale without impacting performance. And in fact, the two of these deep you component service, their services foundation of the C X 10-K And this is how we enable states of functions in a switching platform. Functions like stable network network fire walling, stable segmentation, enhance programmable telemetry. Which we believe will bring a whole lot of value to our customers. And this is a, a platform that's inherently programmable from the ground up. We can we can build and and leverages platform to build new use cases around encryption, enabling state for load balancing, stable nash to name a few. But the key message here is this is this is a platform with the next generation of architecture is in mind is programmed but at all levels of the stack and that's what makes it fundamentally different than anything else. >>I want to just double click on that if you don't mind before we get to the competitive question because I think you brought up the state thing, I think this is worth calling out if you guys don't mind commenting more on this state issue because this is big cloud. Native developers right now want speed, they're shifting left at the Ci cd pipeline with program ability. So going down and having the program ability and having state is a really big deal. Can you guys just expand on that a little bit more and why it's important and how hard it really is to pull off. >>I I can start I guess. Well um it's very hard to pull off because of the sheer amount of connections you need to track when you're developing something like a state, full firewall or state from load balancer. A key component of that is managing the connections at very, very large scale and understanding what's happening with those connections at scale without impacting application performance. And this is fundamentally different. A traditional switching platform regardless of how it's deployed today in a six don't typically process and manage state like this. Memory resources within the shape aren't sufficient. Um the policy scale that you can implement on a platform aren't sufficient to address and fundamentally enable deployable fire walling or load balancing or other state services. >>That's exactly right. So the other kind of key point here is that if you think about the sophistication of different security threats, it does really require you to be able to look at the entire packet and more so be able to look at the entire flow and be able to log that history so that you can get much better heuristics around different anomalies. Security threats that are emerging today. >>That's a great great point. Thanks for bringing that extra extra point out, I would just add to this, we're reporting this all the time when silicon angle in the cube is that you know, the you know, the the automation wave that's coming with around data, you know, it's the center of data now, not date as soon as we heard earlier on with the presentation data drives automation having that enabled with state is a real big deal. So I think that's really worth calling out now. I got to ask the competition question, how is this different? I mean this is an evolution, I would say it's a revolution you guys are being humble um but how is this different from what customers can deploy today >>architecturally, if you take a look at it? So we've, we've spoken about the technology and fundamentally in the platform, what's unique in the architecture but foundational e when customers deploy stable services, they're typically deployed leveraging traditional big box appliances for east west or workload based agents which seek to implement stable security for each East west architectural, what we're enabling is staples services like fire walling, segmentation can scale with the fabric and are delivered at the optimal point for east west which is through the Leaf for access their of the network and we do this for any type of workload. Being deployed on a virtualized compute node being deployed on a containerized, our worker node being deployed on bare metal agnostic of topology. It can be in the access layer of a three tier design and a data center. It can be in the leaf layer of the excellent VPN based fabric. But the goal is an all centrally managed to a single point of orchestration control which William we'll talk about shortly. The goal of this is to to drive down the TCO of your data center as a whole by allowing you to retire legacy appliances that are deployed in in east west role, not utilized host based agents and thus save a whole lot of money. And we've modeled on the order of 60 to 70% in terms of savings in terms of the traditional data center pod design of 1000 compute nodes which will be publishing and as as we go forward, additional services as we mentioned like encryption, this platform has the capability to terminate up to 800 gigs of line, right encryption, I P sec VPN per platform state will not load balancing and this is all functionality will be adding to this existing platform because it's programmable as we mentioned from the ground up. >>What are some of the use cases lead and one of the top use case. What's the low hanging fruit? And where does this go? Service providers enterprise, what are the types of customers you guys see implementing? >>Yeah, that's what's really exciting about the C X 10,000 we actually see customer interest from all types of different markets, whether it be higher education service providers to financial services, basically all enterprises verticals with private cloud or edge data centers for example, could be a hospital, a big box retailer or Coehlo. Such as an equity. It's so it's really the 6 10,000 that creates a new switching category enabling staple services in that leaf node, right at the workload, unifying network and security automation policy management. Second, the C X 10,000 greatly improved security posture and eliminates the need for hair pinning east west traffic all the way back to the centralized plants. Lastly, a Shane highlighted there's a 70% Tco savings by eliminating that appliance brawl and ultimately collapsing the network security operations. >>I love the category creation vibe here. Love it. And obviously the technical and the cloud line is great. But how do the customers manage all this? Okay. You got a new category. I just put the box in, throw away some other one. I mean how does this all get down? How does the customers manage all this? >>Yeah. So we're looking to build on top of the ribbon fabric composer. It's another familiar sight for our customers which already provides for compute storage and network automation with a broad ecosystem integrations such as being where the sphere be center as with Nutanix prison And so aligned with the c. x. 10,000 at G. A. now the aruba fabric composer unifies security and policy orchestration and management with the ability to find firewall policies efficiently and provide that telemetry to collectors such a slump. >>So the customer environments right now involve a lot of multi vendor and new frameworks cloud native. How does this fit into the customer's existing environment? The ecosystem. How do they get that get going here? >>Yeah, great question. Um our customers can get going is we we built a flexible platform that can be deployed in either Greenfield or brownfield. Obviously it's a best of breed architecture for distributed services were building in conjunction with the ruble but if customers want to gradually integrate this into their existing environments and they're using other vendors, spines or course this can be inserted seamlessly as a leaf or an access access to your switch to deliver the exact same set of services within that architecture. So it plugs seamlessly in because it supports all the standard control playing protocols, VX, Lenny, VPN and traditional attitude three tier designs easily. Now for any enterprise solution deployment, it's critical that you build a holistic ecosystem around it. It's clear that this will get customer deployments and the ecosystem being diverse and rich is very, very important and as part of our integrations with the controller, we're building a broad suite of integrations across threat detection application dependency mapping, Semen sore develops infrastructure as code tools like ants, Poland to answer the entire form. Um, it's clear if you look at these categories of integrations, you know XDR or threat detection requires full telemetry from within the data center. It's been hard to accomplish to date because you typically need agents on, on your compute nodes to give you the visibility into what's going on or firewalls for east west flaws. Now our platform can natively provide full visibility in dolphins, East west in the data center and this can become the source of telemetry truth that these Ml XT or engines required to work. The other aspects of ecosystem are around application dependency mapping the single core challenge with deploying segmentation. East West is understanding the rules to put in place right first, is how do you insert the service uh service device in such a way that it won't add more complexity. We don't add any complexity because we're in line natively. How do we understand that allow you to build the rules are necessary to do segmentation. We integrate with tools like guard corps, we provide our flow logs a source of data and they can provide rural recommendations and policy recommendations for customers around. We're building integrations around steve and soar with tools like Splunk and elastic elastic search that will allow net hops and sec ops teams to visualize, train and manage the services delivered by the C X 10-K. And the other aspect of ecosystem from a security standpoint is clearly how do I get policy from these traditional appliances and enforce them on this next generation architecture that you've built that can enable state health services. So we're building integrations with tools like toughen analgesic third party sources of policy that we can ingest and enforcing the infrastructure allowing you to gradually migrate to this new architecture over time >>it's really a cloud native switch, you solve people's problems pain points but yet positioned for growth. I mean it sounds that's my takeaway. But I gotta ask you guys both what's the takeaway for the customers because it's not that simple for that. We have a complicated >>Environment. I think, I think it's really simple every 10 years or so. We see major evolutions in the data center in the switching environment. We do believe we've created a new category with the distributed services, distributed services, switch, delivering cloud scale distribute services where the local where the workloads were side greatly simplifying network security provisions and operations with the Yoruba fabric composer while improving security posture and the TCO. But that's not all folks. It's a journey. Right. >>Yeah, it's absolutely a journey. And this is the first step in in a long journey with a great partner like Aruba, there's other platforms, 100 or four gig hardware platforms we're looking at and then there's additional services that we can enable over time allowing customers to drive even more Tco value out of the platform and the architectural services like encryption for securing the cloud on ramp services like state for load balancing to deploy east west in the data center and you know, holistically that's that's the goal, deliver value for customers and we believe we have an architecture and a platform and this is the first step in a long journey. It's >>a great way. I just ask one final final question for both of you. As product leaders, you've got to be excited having a category creation product here in this market, this big wave. What's what's your thoughts? >>Yeah, exactly. Right. It doesn't happen that often. And so we're all in, it's it's exciting to be able to work with a great team like Sandu and chain here. And so we're really excited about this launch. >>Yeah, it's awesome. The team is great. It's a great partnership between and santo and Aruba and you know, we we look forward to delivering value for john customers. >>Thank you both for sharing under the hood and more details on the product. Thanks for coming on. >>Thank you. Okay, >>the next evolution of switching, I'm john furrier here with the power of An HP, Aruba and Pensando, changing the game the way customers scale up in the cloud and networking. Thanks for watching. Mhm.

>>Okay, welcome back everyone. To the cubes coverage here, coop con cloud native con 2021 in person. The Cuba's here. I'm John farrier hosted the queue with Dave Nicholson, my cohost and cloud analyst, man. It's great to be back, uh, in person. We also have a hybrid event. We've got two great guests here, the founders of deep fence, sham, Krista Swami, C co-founder and CTO, and said deep line founder. It's great to have you on. This is a super important topic. As cloud native is crossed over. Everyone's talking about it mainstream, blah, blah, blah. But security is driving the agenda. You guys are in the middle of it. Cutting edge approach and news >>Like, like we were talking about John, we had operating at the intersection of the awesome desk, right? Open source security and cloud cloud native, essentially. Absolutely. And today's a super exciting day for us. We're launching something called track pepper, Apache V2, completely open source. Think of it as an x-ray or MRI scan for your cloud scan, you know, visualize this cloud at scale, all of the modalities, essentially, we look at cloud as a continuum. It's not a single modality it's containers. It's communities, it's William to settle we'll list all of them. Co-exist side by side. That's how we look at it and threat map. It essentially allows you to visualize all of this in real time, think of fed map, but as something that you, that, that takes over the Baton from the CIS unit, when the lift shift left gets over, that's when the threat pepper comes into picture. So yeah, super excited. >>It's like really gives that developer and the teams ops teams visibility into kind of health statistics of the cloud. But also, as you said, it's not just software mechanisms. The cloud is evolving, new sources being turned on and off. No one even knows what's going on. Sometimes this is a really hidden problem, right? Yeah, >>Absolutely. The basic problem is, I mean, I would just talk to, you know, a gentleman 70 of this morning is two 70 billion. Plus public cloud spent John two 70 billion plus even 3 billion, 30 billion they're saying right. Uh, projected revenue. And there is not even a single community tool to visualize all the clouds and all the cloud modalities at scale, let's start there. That's what we sort of decided, you know what, let's start with utilizing everything else there. And then look for known badness, which is the vulnerabilities, which still remains the biggest attack vector. >>Sure. Tell us about some of the hood. How does this all work cloud scale? Is it a cloud service managed service it's code? Take us out, take us through product. Absolutely. >>So, so, but before that, right, there's one small point that Sandeep mentioned. And Richard, I'd like to elaborate here, right? He spoke about the whole cloud spending such a large volume, right? If you look at the way people look at applications today, it's not just single clone anymore. It's multicloud multi regions across diverse plants, right? What does the solution to look at what my interests are to this point? That is a missing piece here. And that is what we're trying to tackle. And that is where we are going as open source. Coming back to your question, right? How does this whole thing work? So we have a completely on-prem model, right? Where customers can download the code today, install it. It can bill, we give binary stool and Shockley just as the exciting announcement that came out today, you're going to see somewhat exciting entrepreneurs. That's going to make a lot more easy for folks out there all day. Yeah, that's fine. >>So how does this, how does this all fit into security as a micro service and your, your vision of that? >>Absolutely. Absolutely. You know, I'll tell you, this has to do with the one of the continual conferences I would sort of when I was trying to get an idea, trying to shape the whole vision really? Right. Hey, what about syncretism? Microservice? I would go and ask people. They mentioned that sounds, that makes sense. Everything is becoming a microservice. Really. So what you're saying is you're going to deploy one more microservice, just like I deploy all of my other microservices. And that's going to look after my microservices. That compute back makes logical sense, essentially. That was the Genesis of that terminology. So defense essentially is deployed as a microservice. You go to scale, it's deployed, operated just like you to your microservices. So no code changes, no other tool chain changes. It just is yet another microservice. That's going to look after you talk about >>The, >>So there's one point I would like to add here, which is something very interesting, right? The whole concept of microservice came from, if you remember the memo from Jeff Bezos, that everybody's going to go, Microsoft would be fired. That gave rise to a very conventional unconditionally of thinking about their applications. Our deep friends, we believe that security should be. Now. You should bring the same unconventional way of thinking to security. Your security is all bottom up. No, it has to start popping up. So your applications on microservice, your security should also be a micro. >>So you need a microservice for a microservice security for the security. You're starting to get into a paradigm shift where you starting to see the API economy that bayzos and Amazon philosophy and their approach go Beanstream. So when I got to ask you, because this is a trend we've been watching and reporting on the actual application development processes, changing from the old school, you know, life cycle, software defined life cycle to now you've got machine learning and bots. You have AI. Now you have people are building apps differently. And the speed of which they want to code is high. And then other teams are slowing them down. So I've heard security teams just screw people over a couple of days. Oh my God, I can wait five days. No, it used to be five weeks. Now it's five days. They think that's progress. They want five minutes, the developers in real time. So this is a real deal optimum. >>Well, you know what? Shift left was a good thing. Instill a good thing. It helps you sort of figure out the issues early on in the development life cycle, essentially. Right? And so you started weaving in security early on and it stays with you. The problem is we are hydrating. So frequently you end up with a few hundred vulnerabilities every time you scan oftentimes few thousand and then you go to runtime and you can't really fix all these thousand one. You know? So this is where, so there is a little bit of a gap there. If you're saying, if look at the CIC cycle, the in financial cycle that they show you, right. You've got the far left, which is where you have the SAS tools, snake and all of that. And then you've got the center where, which is where you hand off this to ops. >>And then on the right side, you've got tech ops defense essentially starts in the middle and says, look, I know you've had thousand one abilities. Okay. But at run time, I see only one of those packages is loaded in memory. And only that is getting traffic. You go and fix that one because that's going to heart. You see what I'm saying? So that gap is what we're doing. So you start with the left, we come in in the middle and stay with you throughout, you know, till the whole, uh, she asks me. Yeah, well that >>Th that, that touches on a subject. What are the, what are the changes that we're seeing? What are the new threats that are associated with containerization and kind of coupled with that, look back on traditional security methods and how are our traditional security methods failing us with those new requirements that come out of the microservices and containerized world. And so, >>So having, having been at FireEye, I'll tell you I've worked on their windows products and Juniper, >>And very, very deeply involved in. >>And in fact, you know what I mean, at the company, we even sold a product to Palo Alto. So having been around the space, really, I think it's, it's, it's a, it's a foregone conclusion to say that attackers have become more sophisticated. Of course they have. Yeah. It's not a single attack vector, which gets you down anymore. It's not a script getting somewhere shooting who just sending one malicious HTP request exploiting, no, these are multi-vector multi-stage attacks. They, they evolve over time in space, you know? And then what happens is I could have shot a revolving with time and space, one notable cause of piling up. Right? And on the other side, you've got the infrastructure, which is getting fragmented. What I mean by fragmented is it's not one data center where everything would look and feel and smell similar it's containers and tuberosities and several lessons. All of that stuff is hackable, right? So you've got that big shift happening there. You've got attackers, how do you build visibility? So, in fact, initially we used to, we would go and speak with, uh, DevSecOps practitioner say, Hey, what is the coalition? Is it that you don't have enough scanners to scan? Is it that at runtime? What is the main problem? It's the lack of visibility, lack of observability throughout the life cycle, as well as through outage, it was an issue with allegation. >>And the fact that the attackers know that too, they're exploiting the fact that they can't see they're blind. And it's like, you know what? Trying to land a plane that flew yesterday and you think it's landing tomorrow. It's all like lagging. Right? Exactly. So I got to ask you, because this has comes up a lot, because remember when we're in our 11th season with the cube, and I remember conversations going back to 2010, a cloud's not secure. You know, this is before everyone realized shit, the club's better than on premises if you have it. Right. So a trend is emerged. I want to get your thoughts on this. What percentage of the hacks are because the attackers are lazier than the more sophisticated ones, because you see two buckets I'm going to get, I'm going to work hard to get this, or I'm going to go for the easy low-hanging fruit. Most people have just a setup that's just low hanging fruit for the hackers versus some sort of complex or thought through programmatic cloud system, because now is actually better if you do it. Right. So the more sophisticated the environment, the harder it is for the hackers, AK Bob wire, whatever you wanna call it, what level do we cross over? >>When does it go from the script periods to the, the, >>Katie's kind of like, okay, I want to go get the S3 bucket or whatever. There's like levels of like laziness. Yeah. Okay. I, yeah. Versus I'm really going to orchestrate Spearfish social engineer, the more sophisticated economy driven ones. Yeah. >>I think, you know what, this attackers, the hacks aren't being conducted the way they worked in the 10, five years ago, isn't saying that they been outsourced, there are sophisticated teams for building exploiters. This is the whole industry up there. Even the nation, it's an economy really. Right. So, um, the known badness or the known attacks, I think we have had tools. We have had their own tools, signature based tools, which would know, look for certain payloads and say, this is that I know it. Right. You get the stuff really starts sort of, uh, getting out of control when you have so many sort of different modalities running side by side. So much, so much moving attack surfaces, they will evolve. And you never know that you've scanned enough because you never happened because we just pushed the code. >>Yeah. So we've been covering the iron debt. Kim retired general, Keith Alexander, his company. They have this iron dome concept where there's more collective sharing. Um, how do you see that trend? Because I can almost imagine that the open-source man is going to love what you guys got. You're going to probably feed on it, like it's nobody's business, but then you start thinking, okay, we're going to be open. And you have a platform approach, not so much a tool based approach. So just give me tools. We all know that when does it, we cross over to the Nirvana of like real security sharing. Real-time telemetry data. >>And I want to answer this in two parts. The first part is really a lot of this wisdom is only in the community. It's a tribal knowledge. It's their informal feeds in from get up tickets. And you know, a lot of these things, what we're really doing with threat map, but as we are consolidating that and giving it out as a sort of platform that you can use, I like to go for free. This is the part you will never go to monetize this. And we are certain about disaster. What we are monetizing instead is you have, like I said, the x-ray or MRI scan of the cloud, which tells you what the pain points are. This is feel free. This is public collective good. This is a Patrick reader. This is for free. It's shocking. >>I took this long to get to that point, by the way, in this discussion. >>Yeah, >>This is this timing's perfect. >>Security is collective good. Right? And if you're doing open source, community-based, you know, programs like this is for the collector group. What we do look, this whole other set map is going to be open source. We going to make it a platform and our commercial version, which is called fetch Stryker, which is where we have our core IP, which is basically think about this way, right? If you figured out all the pain points and using tech map, or this was a free, and now you wanted the remedy for that pain feed to target a defense, we targeted quarantining of those statin workloads and all that stuff. And that's what our IP is. What we really do there is we said, look, you figured out the attack surface using tech fabric. Now I'm going to use threat Stryker to protect their attacks and stress >>Free. Not free to, or is that going to be Fort bang? >>Oh, that's for, okay. >>That's awesome. So you bring the goodness to the party, the goods to the party, again, share that collective, see where that goes. And the Stryker on top is how you guys monetize. >>And that's where we do some uniquely normal things. I would want to talk about that. If, if, if, if you know public probably for 30 seconds or so unique things we do in industry, which is basically being able to monitor what comes in, what goes out and what changes across time and space, because look, most of the modern attacks evolve over time and space, right? So you go to be able to see things like this. Here's a party structure, which has a vulnerability threats. Mapper told you that to strike. And what it does is it tells you a bunch of stress has a vulnerable again, know that somebody is sending a Melissa's HTP request, which has a malicious payload. And you know what, tomorrow there's a file system change. And there is outbound connection going to some funny place. That is the part that we're wanting this. >>Yeah. And you give away the tool to identify the threats and sell the hammer. >>That's giving you protection. >>Yeah. Yeah. Awesome. I love you guys love this product. I love how you're doing it. I got to ask you to define what is security as a microservice. >>So security is a microservice is a deployment modality for us. So defense, what defense has is one console. So defense is currently self posted by the customers within the infrastructure going forward. We'll also be launching a SAS version, the cloud version of it. But what happens as part of this deployment is they're running the management console, which is the gooey, and then a tiny sensor, which is collecting telemetric that is deployed as a microservice is what I'm saying. So you've got 10 containers running defenses level of container. That's, that's an eight or the Microsoft risk. And it utilizes, uh, EDP F you know, for tracing and all that stuff. Yeah. >>Awesome. Well, I think this is the beginning of a shift in the industry. You start to see dev ops and cloud native technologies become the operating model, not just dev dev ops are now in play and infrastructure as code, which is the ethos of a cloud generation is security is code. That's true. That's what you guys are doing. Thanks for coming on. Really appreciate it. Absolutely breaking news here in the queue, obviously great stuff. Open source continues to grow and win in the new model. Collaboration is the cube bringing you all the cover day one, the three days. I'm Jennifer, your host with Dave Nicholson. Thanks for watching.

>>Welcome back to the cubes coverage of AWS public sector summit live in Washington D. C. A face to face event were on the ground here is to keep coverage. I'm john Kerry, your hosts got two great guests. Both cuba alumni Shannon Kellogg VP of public policy for the Americas and john would ceo tell us congratulations on some announcement on stage and congressional john being a public company. Last time I saw you in person, you are private. Now your I. P. O. Congratulations >>totally virtually didn't meet one investor, lawyer, accountant or banker in person. It's all done over zoom. What's amazing. >>We'll go back to that and a great great to see you had great props here earlier. You guys got some good stuff going on in the policy side, a core max on stage talking about this Virginia deal. Give us the update. >>Yeah. Hey thanks john, it's great to be back. I always like to be on the cube. Uh, so we made an announcement today regarding our economic impact study, uh, for the commonwealth of Virginia. And this is around the amazon web services business and our presence in Virginia or a WS as we all, uh, call, uh, amazon web services. And um, basically the data that we released today shows over the last decade the magnitude of investment that we're making and I think reflects just the overall investments that are going into Virginia in the data center industry of which john and I have been very involved with over the years. But the numbers are quite um, uh, >>just clever. This is not part of the whole H. 20. H. Q. Or whatever they call HQ >>To HQ two. It's so Virginia Amazon is investing uh in Virginia as part of our HQ two initiative. And so Arlington Virginia will be the second headquarters in the U. S. In addition to that, AWS has been in Virginia for now many years, investing in both data center infrastructure and also other corporate facilities where we house AWS employees uh in other parts of Virginia, particularly out in what's known as the dullest technology corridor. But our data centers are actually spread throughout three counties in Fairfax County, Loudoun County in Prince William County. >>So this is the maxim now. So it wasn't anything any kind of course this is Virginia impact. What was, what did he what did he announce? What did he say? >>Yeah. So there were a few things that we highlighted in this economic impact study. One is that over the last decade, if you can believe it, we've invested $35 billion 2020 alone. The AWS investment in construction and these data centers. uh it was actually $1.3 billion 2020. And this has created over 13,500 jobs in the Commonwealth of Virginia. So it's a really great story of investment and job creation and many people don't know John in this Sort of came through in your question too about HQ two, But aws itself has over 8000 employees in Virginia today. Uh, and so we've had this very significant presence for a number of years now in Virginia over the last, you know, 15 years has become really the cloud capital of the country, if not the world. Uh, and you see all this data center infrastructure that's going in there, >>John What's your take on this? You've been very active in the county there. Um, you've been a legend in the area and tech, you've seen this many years, you've been doing so I think the longest running company doing cyber my 31st year, 31st year. So you've been on the ground. What does this all mean to you? >>Well, you know, it goes way back to, it was roughly 2005 when I served on the Economic Development Commission, Loudon County as the chairman. And at the time we were the fastest-growing county in America in Loudon County. But our residential real property taxes were going up stratospherically because when you look at it, every dollar real property tax that came into residential, we lose $2 because we had to fund schools and police and fire departments and so forth. And we realized for every dollar of commercial real property tax that came in, We made $97 in profit, but only 13% of the money that was coming into the county was coming in commercially. So a small group got together from within the county to try and figure out what were the assets that we had to offer to companies like Amazon and we realized we had a lot of land, we had water and then we had, you know this enormous amount of dark fiber, unused fibre optic. And so basically the county made it appealing to companies like amazon to come out to Loudon County and other places in northern Virginia and the rest is history. If you look today, we're Loudon County is Loudon County generates a couple $100 million surplus every year. It's real property taxes have come down in in real dollars and the percentage of revenue that comes from commercials like 33 34%. That's really largely driven by the data center ecosystem that my friend over here Shannon was talking. So >>the formula basically is look at the assets resources available that may align with the kind of commercial entities that good. How's their domicile there >>that could benefit. >>So what about power? Because the data centers need power, fiber fiber is great. The main, the main >>power you can build power but the main point is is water for cooling. So I think I think we had an abundance of water which allowed us to build power sources and allowed companies like amazon to build their own power sources. So I think it was really a sort of a uh uh better what do they say? Better lucky than good. So we had a bunch of assets come together that helps. Made us, made us pretty lucky as a, as a region. >>Thanks area too. >>It is nice and >>john, it's really interesting because the vision that john Wood and several of his colleagues had on that economic development board has truly come through and it was reaffirmed in the numbers that we released this week. Um, aws paid $220 million 2020 alone for our data centers in those three counties, including loud >>so amazon's contribution to >>The county. $220 million 2020 alone. And that actually makes up 20% of overall property tax revenues in these counties in 2020. So, you know, the vision that they had 15 years ago, 15, 16 years ago has really come true today. And that's just reaffirmed in these numbers. >>I mean, he's for the amazon. So I'll ask you the question. I mean, there's a lot of like for misinformation going around around corporate reputation. This is clearly an example of the corporation contributing to the, to the society. >>No, no doubt. And you think >>About it like that's some good numbers, 20 million, 30 >>$5 million dollar capital investment. You know, 10, it's, what is it? 8000 9000 >>Jobs. jobs, a W. S. jobs in the Commonwealth alone. >>And then you look at the economic impact on each of those counties financially. It really benefits everybody at the end of the day. >>It's good infrastructure across the board. How do you replicate that? Not everyone's an amazon though. So how do you take the formula? What's your take on best practice? How does this rollout? And that's the amazon will continue to grow, but that, you know, this one company, is there a lesson here for the rest of us? >>I think I think all the data center companies in the cloud companies out there see value in this region. That's why so much of the internet traffic comes through northern Virginia. I mean it's I've heard 70%, I've heard much higher than that too. So I think everybody realizes this is a strategic asset at a national level. But I think the main point to bring out is that every state across America should be thinking about investments from companies like amazon. There are, there are really significant benefits that helps the entire community. So it helps build schools, police departments, fire departments, etcetera, >>jobs opportunities. What's the what's the vision though? Beyond data center gets solar sustainability. >>We do. We have actually a number of renewable energy projects, which I want to talk about. But just one other quick on the data center industry. So I also serve on the data center coalition which is a national organization of data center and cloud providers. And we look at uh states all over this country were very active in multiple states and we work with governors and state governments as they put together different frameworks and policies to incent investment in their states and Virginia is doing it right. Virginia has historically been very forward looking, very forward thinking and how they're trying to attract these data center investments. They have the right uh tax incentives in place. Um and then you know, back to your point about renewable energy over the last several years, Virginia is also really made some statutory changes and other policy changes to drive forward renewable energy in Virginia. Six years ago this week, john I was in a coma at county in Virginia, which is the eastern shore. It's a very rural area where we helped build our first solar farm amazon solar farm in Virginia in 2015 is when we made this announcement with the governor six years ago this week, it was 88 megawatts, which basically at the time quadruple the virginias solar output in one project. So since that first project we at Amazon have gone from building that one facility, quadrupling at the time, the solar output in Virginia to now we're by the end of 2023 going to be 1430 MW of solar power in Virginia with 15 projects which is the equivalent of enough power to actually Enough electricity to power 225,000 households, which is the equivalent of Prince William county Virginia. So just to give you the scale of what we're doing here in Virginia on renewable energy. >>So to me, I mean this comes down to not to put my opinion out there because I never hold back on the cube. It's a posture, we >>count on that. It's a >>posture issue of how people approach business. I mean it's the two schools of thought on the extreme true business. The government pays for everything or business friendly. So this is called, this is a modern story about friendly business kind of collaborative posture. >>Yeah, it's putting money to very specific use which has a very specific return in this case. It's for everybody that lives in the northern Virginia region benefits everybody. >>And these policies have not just attracted companies like amazon and data center building builders and renewable energy investments. These policies are also leading to rapid growth in the cybersecurity industry in Virginia as well. You know john founded his company decades ago and you have all of these cybersecurity companies now located in Virginia. Many of them are partners like >>that. I know john and I both have contributed heavily to a lot of the systems in place in America here. So congratulations on that. But I got to ask you guys, well I got you for the last minute or two cybersecurity has become the big issue. I mean there's a lot of these policies all over the place. But cyber is super critical right now. I mean, where's the red line Shannon? Where's you know, things are happening? You guys bring security to the table, businesses are out there fending for themselves. There's no militia. Where's the, where's the, where's the support for the commercial businesses. People are nervous >>so you want to try it? >>Well, I'm happy to take the first shot because this is and then we'll leave john with the last word because he is the true cyber expert. But I had the privilege of hosting a panel this morning with the director of the cybersecurity and Infrastructure Security agency at the department, Homeland Security, Jenness easterly and the agency is relatively new and she laid out a number of initiatives that the DHS organization that she runs is working on with industry and so they're leaning in their partnering with industry and a number of areas including, you know, making sure that we have the right information sharing framework and tools in place, so the government and, and we in industry can act on information that we get in real time, making sure that we're investing for the future and the workforce development and cyber skills, but also as we enter national cybersecurity month, making sure that we're all doing our part in cyber security awareness and training, for example, one of the things that are amazon ceo Andy Jassy recently announced as he was participating in a White house summit, the president biden hosted in late august was that we were going to at amazon make a tool that we've developed for information and security awareness for our employees free, available to the public. And in addition to that we announced that we were going to provide free uh strong authentication tokens for AWS customers as part of that announcement going into national cybersecurity months. So what I like about what this administration is doing is they're reaching out there looking for ways to work with industry bringing us together in these summits but also looking for actionable things that we can do together to make a difference. >>So my, my perspective echoing on some of Shannon's points are really the following. Uh the key in general is automation and there are three components to automation that are important in today's environment. One is cyber hygiene and education is a piece of that. The second is around mis attribution meaning if the bad guy can't see you, you can't be hacked. And the third one is really more or less around what's called attribution, meaning I can figure out actually who the bad guy is and then report that bad guys actions to the appropriate law enforcement and military types and then they take it from there >>unless he's not attributed either. So >>well over the basic point is we can't as industry hat back, it's illegal, but what we can do is provide the tools and methods necessary to our government counterparts at that point about information sharing, where they can take the actions necessary and try and find those bad guys. >>I just feel like we're not moving fast enough. Businesses should be able to hack back. In my opinion. I'm a hawk on this one item. So like I believe that because if people dropped on our shores with troops, the government will protect us. >>So your your point is directly taken when cyber command was formed uh before that as airlines seeing space physical domains, each of those physical domains have about 100 and $50 billion they spend per year when cyber command was formed, it was spending less than Jpmorgan chase to defend the nation. So, you know, we do have a ways to go. I do agree with you that there needs to be more uh flexibility given the industry to help help with the fight. You know, in this case. Andy Jassy has offered a couple of tools which are, I think really good strong tokens training those >>are all really good. >>We've been working with amazon for a long time, you know, ever since, uh, really, ever since the CIA embrace the cloud, which was sort of the shot heard around the world for cloud computing. We do the security compliance automation for that air gap region for amazon as well as other aspects >>were all needs more. Tell us faster, keep cranking up that software because tell you right now people are getting hit >>and people are getting scared. You know, the colonial pipeline hack that affected everybody started going wait a minute, I can't get gas. >>But again in this area of the line and jenny easterly said this this morning here at the summit is that this truly has to be about industry working with government, making sure that we're working together, you know, government has a role, but so does the private sector and I've been working cyber issues for a long time to and you know, kind of seeing where we are this year in this recent cyber summit that the president held, I really see just a tremendous commitment coming from the private sector to be an effective partner in securing the nation this >>full circle to our original conversation around the Virginia data that you guys are looking at the Loudon County amazon contribution. The success former is really commercial public sector. I mean, the government has to recognize that technology is now lingua franca for all things everything society >>well. And one quick thing here that segues into the fact that Virginia is the cloud center of the nation. Um uh the president issued a cybersecurity executive order earlier this year that really emphasizes the migration of federal systems into cloud in the modernization that jOHN has worked on, johN had a group called the Alliance for Digital Innovation and they're very active in the I. T. Modernization world and we remember as well. Um but you know, the federal government is really emphasizing this, this migration to cloud and that was reiterated in that cybersecurity executive order >>from the, well we'll definitely get you guys back on the show, we're gonna say something. >>Just all I'd say about about the executive order is that I think one of the main reasons why the president thought was important is that the legacy systems that are out there are mainly written on kobol. There aren't a lot of kids graduating with degrees in COBOL. So COBOL was designed in 1955. I think so I think it's very imperative that we move has made these workloads as we can, >>they teach it anymore. >>They don't. So from a security point of view, the amount of threats and vulnerabilities are through the >>roof awesome. Well john I want to get you on the show our next cyber security event. You have you come into a fireside chat and unpack all the awesome stuff that you're doing. But also the challenges. Yes. And there are many, you have to keep up the good work on the policy. I still say we got to remove that red line and identified new rules of engagement relative to what's on our sovereign virtual land. So a whole nother Ballgame, thanks so much for coming. I appreciate it. Thank you appreciate it. Okay, cute coverage here at eight of public sector seven Washington john ferrier. Thanks for watching. Mhm. Mhm.

>>Have you ever wondered how we sequence the human genome, how your smartphone is so well smart, how we will ever analyze all the patient data for the new vaccines or even how we plan to send humans to Mars? Well, at Cloudera, we believe that data can make what is impossible today possible tomorrow we are the enterprise data cloud company. In fact, we provide analytics and machine learning technology that does everything from making your smartphone smarter, to helping scientists ensure that new vaccines are both safe and effective, big data, no problem out era, the enterprise data cloud company. >>So I think for a long time in this country, we've known that there's a great disparity between minority populations and the majority of population in terms of disease burden. And depending on where you live, your zip code has more to do with your health than almost anything else. But there are a lot of smaller, um, safety net facilities, as well as small academic medical colleges within the United States. And those in those smaller environments don't have the access, you know, to the technologies that the larger ones have. And, you know, I call that, uh, digital disparity. So I'm, Harry's in academic scientist center and our mission is to train diverse health care providers and researchers, but also provide services to underserved populations. As part of the reason that I think is so important for me hearing medical college, to do data science. One of the things that, you know, both Cloudera and Claire sensor very passionate about is bringing those height in technologies to, um, to the smaller organizations. >>It's very expensive to go to the cloud for these small organizations. So now with the partnership with Cloudera and Claire sets a clear sense, clients now enjoy those same technologies and really honestly have a technological advantage over some of the larger organizations. The reason being is they can move fast. So we were able to do this on our own without having to, um, hire data scientists. Uh, we probably cut three to five years off of our studies. I grew up in a small town in Arkansas and is one of those towns where the railroad tracks divided the blacks and the whites. My father died without getting much healthcare at all. And as an 11 year old, I did not understand why my father could not get medical attention because he was very sick. >>Since we come at my Harry are looking to serve populations that reflect themselves or affect the population. He came from. A lot of the data you find or research you find health is usually based on white men. And obviously not everybody who needs a medical provider is going to be a white male. >>One of the things that we're concerned about in healthcare is that there's bias in treatment already. We want to make sure those same biases do not enter into the algorithms. >>The issue is how do we get ahead of them to try to prevent these disparities? >>One of the great things about our dataset is that it contains a very diverse group of patients. >>Instead of just saying, everyone will have these results. You can break it down by race, class, cholesterol, level, other kinds of factors that play a role. So you can make the treatments in the long run. More specifically, >>Researchers are now able to use these technologies and really take those hypotheses from, from bench to bedside. >>We're able to overall improve the health of not just the person in front of you, but the population that, yeah, >>Well, the future is now. I love a quote by William Gibson who said the future is already here. It's just not evenly distributed. If we think hard enough and we apply things properly, uh, we can again take these technologies to, you know, underserved environments, um, in healthcare. Nobody should be technologically disadvantage. >>When is a car not just a car when it's a connected data driven ecosystem, dozens of sensors and edge devices gathering up data from just about anything road, infrastructure, other vehicles, and even pedestrians to create safer vehicles, smarter logistics, and more actionable insights. All the data from the connected car supports an entire ecosystem from manufacturers, building safer vehicles and fleet managers, tracking assets to insurers monitoring, driving behaviors to make roads safer. Now you can control the data journey from edge to AI. With Cloudera in the connected car, data is captured, consolidated and enriched with Cloudera data flow cloud Dara's data engineering, operational database and data warehouse provide the foundation to develop service center applications, sales reports, and engineering dashboards. With data science workbench data scientists can continuously train AI models and use data flow to push the models back to the edge, to enhance the car's performance as the industry's first enterprise data cloud Cloudera supports on-premise public and multi-cloud deployments delivering multifunction analytics on data anywhere with common security governance and metadata management powered by Cloudera SDX, an open platform built on open source, working with open compute architectures and open data stores all the way from edge to AI powering the connected car. >>The future has arrived. >>The Dawn of a retail Renaissance is here and shopping will never be the same again. Today's connected. Consumers are always on and didn't control. It's the era of smart retail, smart shelves, digital signage, and smart mirrors offer an immersive customer experience while delivering product information, personalized offers and recommendations, video analytics, capture customer emotions and gestures to better understand and respond to in-store shopping experiences. Beacons sensors, and streaming video provide valuable data into in-store traffic patterns, hotspots and dwell times. This helps retailers build visual heat maps to better understand custom journeys, conversion rates, and promotional effectiveness in our robots automate routine tasks like capturing inventory levels, identifying out of stocks and alerting in store personnel to replenish shelves. When it comes to checking out automated e-commerce pickup stations and frictionless checkouts will soon be the norm making standing in line. A thing of the past data and analytics are truly reshaping. >>The everyday shopping experience outside the store, smart trucks connect the supply chain, providing new levels of inventory visibility, not just into the precise location, but also the condition of those goods. All in real time, convenience is key and customers today have the power to get their goods delivered at the curbside to their doorstep, or even to their refrigerators. Smart retail is indeed here. And Cloudera makes all of this possible using Cloudera data can be captured from a variety of sources, then stored, processed, and analyzed to drive insights and action. In real time, data scientists can continuously build and train new machine learning models and put these models back to the edge for delivering those moment of truth customer experiences. This is the enterprise data cloud powered by Cloudera enabling smart retail from the edge to AI. The future has arrived >>For is a global automotive supplier. We have three business groups, automotive seating in studios, and then emission control technologies or biggest automotive customers are Volkswagen for the NPSA. And we have, uh, more than 300 sites. And in 75 countries >>Today, we are generating tons of data, more and more data on the manufacturing intelligence. We are trying to reduce the, the defective parts or anticipate the detection of the, of the defective part. And this is where we can get savings. I would say our goal in manufacturing is zero defects. The cost of downtime in a plant could be around the a hundred thousand euros. So with predictive maintenance, we are identifying correlations and patterns and try to anticipate, and maybe to replace a component before the machine is broken. We are in the range of about 2000 machines and we can have up to 300 different variables from pressure from vibration and temperatures. And the real-time data collection is key, and this is something we cannot achieve in a classical data warehouse approach. So with the be data and with clouded approach, what we are able to use really to put all the data, all the sources together in the classical way of working with that at our house, we need to spend weeks or months to set up the model with the Cloudera data lake. We can start working on from days to weeks. We think that predictive or machine learning could also improve on the estimation or NTC patient forecasting of what we'll need to brilliance with all this knowledge around internet of things and data collection. We are applying into the predictive convene and the cockpit of the future. So we can work in the self driving car and provide a better experience for the driver in the car. >>The Cloudera data platform makes it easy to say yes to any analytic workload from the edge to AI, yes. To enterprise grade security and governance, yes. To the analytics your people want to use yes. To operating on any cloud. Your business requires yes to the future with a cloud native platform that flexes to meet your needs today and tomorrow say yes to CDP and say goodbye to shadow it, take a tour of CDP and see how it's an easier, faster and safer enterprise analytics and data management platform with a new approach to data. Finally, a data platform that lets you say yes, >>Welcome to transforming ideas into insights, presented with the cube and made possible by cloud era. My name is Dave Volante from the cube, and I'll be your host for today. And the next hundred minutes, you're going to hear how to turn your best ideas into action using data. And we're going to share the real world examples and 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing, efficiencies, better forecast, retail demand, transform analytics, improve public sector service, and so much more how we use data is rapidly evolving as is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to rather we use terms like digital transformation and digital business, but you think about it. What is a digital business? How is that different from just a business? >>Well, digital business is a data business and it differentiates itself by the way, it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings. But increasingly insights are leading to the development of data, products and services that can be monetized, or as you'll hear in our industry, examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real-time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. >>Self-service investing, filing insurance claims and our smart phones. And so many examples, IOT systems that communicate and act machine and machine real-time pricing actions. These are all examples of products and services that drive revenue cut costs or create other value. And they all rely on data. Now while many business leaders sometimes express frustration that their investments in data, people, and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data, transformation and leadership. One thing is certain the next 10 years of data and digital transformation, won't be like the last 10. So let's get into it. Please join us in the chat. >>You can ask questions. You can share your comments, hit us up on Twitter right now. It's my pleasure to welcome Mick Holliston in he's the president of Cloudera mic. Great to see you. Great to see you as well, Dave, Hey, so I call it the new abnormal, right? The world is kind of out of whack offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations line cooks at restaurants. Everything that we consumers have missed, but here's the one thing. It seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling their pricing algorithms, you know, commodity prices we don't know is inflation. Transitory. Is it a long-term threat trying to forecast GDP? It's just seems like we have to reset all of our assumptions and make a feel a quality data is going to be a key here. How do you see the current state of the industry and the role data plays to get us into a more predictable and stable future? Well, I >>Can sure tell you this, Dave, uh, out of whack is definitely right. I don't know if you know or not, but I happen to be coming to you live today from Atlanta and, uh, as a native of Atlanta, I can, I can tell you there's a lot to be known about the airport here. It's often said that, uh, whether you're going to heaven or hell, you got to change planes in Atlanta and, uh, after 40 minutes waiting on algorithm to be right for baggage claim when I was not, I finally managed to get some bag and to be able to show up dressed appropriately for you today. Um, here's one thing that I know for sure though, Dave, clean, consistent, and safe data will be essential to getting the world and businesses as we know it back on track again, um, without well-managed data, we're certain to get very inconsistent outcomes, quality data will the normalizing factor because one thing really hasn't changed about computing since the Dawn of time. Back when I was taking computer classes at Georgia tech here in Atlanta, and that's what we used to refer to as garbage in garbage out. In other words, you'll never get quality data-driven insights from a poor data set. This is especially important today for machine learning and AI, you can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid as AI is increasingly used in every business app, you must build a solid data foundation mic. Let's >>Talk about hybrid. Every CXO that I talked to, they're trying to get hybrid, right? Whether it's hybrid work hybrid events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything, what's your point of view with >>All those descriptions of hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. >>Oh yeah, you're right. Mick. I did miss that. What, what do you mean by hybrid data? Well, >>David in cloud era, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises in a private cloud and public cloud, or perhaps even in a new open data exchange. Now this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud, but either way security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch her read a recent news story. Data breaches are at an all time high. And the ethics of AI applications are being called into question every day and understanding the lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know Dave? That's the business cloud era? Is it on a serious note from cloud era's perspective? Adopting a hybrid data strategy is central to every business's digital transformation. It will enable rapid adoption of new technologies and optimize economic models while ensuring the security and privacy of every bit of data. What can >>Make, I'm glad you brought in that notion of hybrid data, because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You've got the economics, the physics, the local laws come into play. So what about the rest of hybrid? Yeah, >>It's a great question, Dave and certainly cloud era itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office. Uh, ether net may not be happening quite so fast in somebody's rural home in, uh, in, in the middle of Nebraska somewhere. Right? So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it. Uh, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, uh, involve us kind of slowly coming back to work, begin in this fall. And we're looking forward to being able to shake hands and see one another again for the first time in many cases for more than a year and a half, but, uh, yes, hybrid work, uh, and hybrid data are playing an increasingly important role for every kind of business. >>Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, and the case. Here's how I think about it. It makes, I mean, some industries have transformed. You think about retail, for example, it's pretty clear, although although every physical retail brand I know has, you know, not only peaked up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence, uh, and ended up reverse. We see Amazon building out physical assets so that there's more hybrid going on. But when you look at healthcare, for example, it's just starting, you know, with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control, mint control of payment systems in manufacturing, you know, the pandemic highlighted America's reliance on China as a manufacturing partner and, and supply chain. Uh it's so my point is it seems that different industries they're in different stages of transformation, but two things look really clear. One, you've got to put data at the core of the business model that's compulsory. It seems like embedding AI into the applications, the data, the business process that's going to become increasingly important. So how do you see that? >>Wow, there's a lot packed into that question there, Dave, but, uh, yeah, we, we, uh, you know, at Cloudera I happened to be leading our own digital transformation as a technology company and what I would, what I would tell you there that's been arresting for us is the shift from being largely a subscription-based, uh, model to a consumption-based model requires a completely different level of instrumentation and our products and data collection that takes place in real, both for billing, for our, uh, for our customers. And to be able to check on the health and wellness, if you will, of their cloud era implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed, the rate and pace of getting vaccines, uh, to market, uh, or we've been assisting with testing process. >>That's taken place because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and, and healthy and safe outcomes for everyone. And cloud era has been underneath a great deal of that type of work and the financial services industry you pointed out. Uh, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are really helping those kinds of organizations get through those difficult challenges. You, you also happened to mention, uh, you know, public sector and in public sector. We're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. >>Um, and while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, can't grow, build great ML apps, unless you've got a strong data foundation underneath is back to that garbage in garbage out comment that I made previously. And so in order to do that, you've got to have a great hybrid dated management platform at your disposal to ensure that your data is clean and organized and up to date. Uh, just as importantly from that, that's kind of the freedom side of things on the security side of things. You've got to ensure that you can see who just touched, not just the data itself, Dave, but actually the machine learning models and organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage. >>In addition to data lineage. In other words, who's had access to the machine learning models when and where, and at what time and what decisions were made perhaps by the humans, perhaps by the machines that may have led to a particular outcome. So every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models just as they can track the lineage of data. So lots going on there across industries, lots going on as those various industries think about how AI can be applied to their businesses. Pretty >>Interesting concepts. You bring it into the discussion, the hybrid data, uh, sort of new, I think, new to a lot of people. And th this idea of model lineage is a great point because people want to talk about AI, ethics, transparency of AI. When you start putting those models into, into machines to do real time inferencing at the edge, it starts to get really complicated. I wonder if we could talk about you still on that theme of industry transformation? I felt like coming into the pandemic pre pandemic, there was just a lot of complacency. Yeah. Digital transformation and a lot of buzz words. And then we had this forced March to digital, um, and it's, but, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? It definitely >>Is a lot of a POC limbo or a, I think some of us internally have referred to as POC purgatory, just getting stuck in that phase, not being able to get from point a to point B in digital transformation and, um, you know, for every industry transformation, uh, change in general is difficult and it takes time and money and thoughtfulness, but like with all things, what we found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts set. Another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts as it relates to the underlying technology here. And to bring it home a little bit more practically, I guess I would say at cloud era, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. >>And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, uh, right close to home in place. They can kind of experiment a little bit more safely and economically, and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplish, but kind of starting small and then drawing fast from there on customer's journey to the we'll make we've >>Covered a lot of ground. Uh, last question. Uh, w what, what do you want people to leave this event, the session with, and thinking about sort of the next era of data that we're entering? >>Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. I want them to think about a hybrid data, uh, strategy. So, uh, you know, really hybrid data is a concept that we're bringing forward on this show really for the, for the first time, arguably, and we really do think that it enables customers to experience what we refer to Dave as the power of, and that is freedom, uh, and security, and in a world where we're all still trying to decide whether each day when we walk out each building, we walk into, uh, whether we're free to come in and out with a mask without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe, uh, for ourselves and for others. And the same is true of organizations. It strategies. They want the freedom to choose, to run workloads and applications and the best and most economical place possible. But they also want to do that with certainty, that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole, >>Nick, thanks so much great conversation and really appreciate the insights that you're bringing to this event into the industry. Really thank you for your time. >>You bet Dave pleasure being with you. Okay. >>We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid, right? So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manny veer, DAS. Who's the head of enterprise computing at Nvidia. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise, and it's being driven by the emergence of data, intensive applications and workloads no longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like Nvidia. So let's learn more about this collaboration and what it means to your data business. Rob, thanks, >>Mick and Dave, that was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy and accelerating the path to value and hybrid environments. And I want to drill down on this aspect today. Every business is facing accelerating everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor. Now, every engagement with coworkers, customers and partners is virtual from website metrics to customer service records, and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? A cloud era? We believe this onslaught of data offers an opportunity to make better business decisions faster. >>And we want to make that easier for everyone, whether it's fraud, detection, demand, forecasting, preventative maintenance, or customer churn, whether the goal is to save money or produce income every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit they cloud provides and with security and edge to AI data intimacy. That's why the partnership between cloud air and Nvidia together means so much. And it starts with the shared vision making data-driven, decision-making a reality for every business and our customers will now be able to leverage virtually unlimited quantities of varieties, of data, to power, an order of magnitude faster decision-making and together we turbo charge the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. >>We're joined today by NVIDIA's Mandy veer dos, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, man, you're veer. Thank you for joining us over the unit. >>Thank you, Rob, for having me. It's a pleasure to be here on behalf of Nvidia. We are so excited about this partnership with Cloudera. Uh, you know, when, when, uh, when Nvidia started many years ago, we started as a chip company focused on graphics, but as you know, over the last decade, we've really become a full stack accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, uh, AI being a prime example. And when we think about Cloudera, uh, and your company, a great company, there's three things we see Rob. Uh, the first one is that for the companies that will already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. >>And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about in various mission, going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies today who have been the early adopters, uh, using the power acceleration by changing the technology in their stacks. But more and more, we see the opportunity of meeting customers, where they are with tools that they're familiar with with partners that they trust. And of course, Cloudera being a great example of that. Uh, the second, uh, part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through, but as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. >>And so again, the power of your platform, uh, is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute the machine learning compute needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where literally they took the workflow. They had, they took the servers, they had, they added GPS into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >>My name's Joanne salty. I'm the branch chief of the technical branch and RAs. It's actually the research division research and statistical division of the IRS. Basically the mission that RAs has is we do statistical and research on all things related to taxes, compliance issues, uh, fraud issues, you know, anything that you can think of. Basically we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So it's our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those Agra algorithms, the of parameters each of those algorithms have. >>So that's, that's really been our challenge. Now the expectation was that with Nvidia in cloud, there is help. And with the cluster, we actually build out the test this on the actual fraud, a fraud detection algorithm on our expectation was we were definitely going to see some speed up in prom, computational processing times. And just to give you context, the size of the data set that we were, uh, the SMI was actually working, um, the algorithm against Liz around four terabytes. If I recall correctly, we'd had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them? It was really, really quick. Uh, the definite now term short term what's next is going to be the subject matter expert is actually going to take our algorithm run with that. >>So that's definitely the now term thing we want to do going down, go looking forward, maybe out a couple of months, we're also looking at curing some, a 100 cards to actually test those out. As you guys can guess our datasets are just getting bigger and bigger and bigger, and it demands, um, to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward. And then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run them, you know, come onto our art's desire, wherever imagination takes our skis to actually develop solutions, know how the platforms to run them on just kind of the close out. >>I rarely would be very missed. I've worked with a lot of, you know, companies through the year and most of them been spectacular. And, uh, you guys are definitely in that category. The, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't. Thank you guys. So thank you for the opportunity to, and fantastic. And I'd have to also, I want to thank my guys. My, uh, my staff, David worked on this Richie worked on this Lex and Tony just, they did a fantastic job and I want to publicly thank him for all the work they did with you guys and Chev, obviously also. Who's fantastic. So thank you everyone. >>Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and Nvidia? Is it primarily go to market or you do an engineering work? What's the story there? >>It's really both. It's both go to market and engineering and engineering focus is to optimize and take advantage of invidious platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both >>Great. Thank you. Many of Eric, maybe you could talk a little bit more about why can't we just existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do Nvidia and cloud era bring to the table that goes beyond the conventional systems that we've known for many years? >>Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now Nvidia has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform. So that regardless of the technique, the customer's using to get insight from that data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >>So I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going toward doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive, uh, things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start, you think about the AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems and real time, AI inference, at least even at the edge, huge potential for business value and a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the like, and so you're putting AI into these data intensive apps within the enterprise. >>The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >>Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint and new platforms like these being developed by cloud air and Nvidia will dramatically lower the cost, uh, of enabling this type of workload to be done. Um, and what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation, engine chain management, drug province, and increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots that AR VR and manufacturing. So driving quality, better quality in the power grid management, automated retail IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >>I mean, this is like your wheelhouse. Maybe you could add something to that. >>Yeah. I mean, I agree with Rob. I mean he listed some really good use cases. You know, the way we see this at Nvidia, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled, uh, use cases, particular use cases like a chat bot, uh, uh, from the ground up with the hardware and the software almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. I think we are in the first phase of the democratization, uh, for example, the work we did with Cloudera, which is, uh, for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. >>And you still come home and assemble it, but all the parts are there. The instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought, bought a table and it showed up and somebody placed it in the right spot. Right. And they didn't really have to learn, uh, how to do AI. So these are the phases. And I think they're very excited to be going there. Yeah. You know, >>Rob, the great thing about for, for your customers is they don't have to build out the AI. They can, they can buy it. And, and just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations and Mick and I talked about this, the guy go problem that we've all studied in college, uh, you know, garbage in, garbage out. Uh, but, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob over the next several years? >>So yeah, the combination of massive amounts of data that have been gathered across the enterprise in the past 10 years with an open API APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency, you know, and that's allowing us as an industry to democratize the data access while at the same time, delivering the federated governance and security models and hybrid technologies are playing a key role in making this a reality and enabling data access to be hybridized, meaning access and treated in a substantially similar way, your respect to the physical location of where that data actually resides. >>That's great. That is really the value layer that you guys are building out on top of that, all this great infrastructure that the hyperscalers have have given us, I mean, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you can go first and then manufacture. You could bring us home. Where do you guys want to see the relationship go between cloud era and Nvidia? In other words, how should we, as outside observers be, be thinking about and measuring your project specifically and in the industry's progress generally? >>Yeah, I think we're very aligned on this and for cloud era, it's all about helping companies move forward, leverage every bit of their data and all the places that it may, uh, be hosted and partnering with our customers, working closely with our technology ecosystem of partners means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >>Yeah. And I agree with Robin and for us at Nvidia, you know, we, this partnership started, uh, with data analytics, um, as you know, a spark is a very powerful technology for data analytics, uh, people who use spark rely on Cloudera for that. And the first thing we did together was to really accelerate spark in a seamless manner, but we're accelerating machine learning. We accelerating artificial intelligence together. And I think for Nvidia it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity. >>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got particular expertise in, in data and finance and insurance. I mean, you know, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We talk more about digital, you know, or, or, or data driven when you think about sort of where we've come from and where we're going. What are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third party, real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we, we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That day. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, is it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? Absolutely. >>I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of the, having multiple distributors, what did they have in stock? So there are millions of data points that you need to drill down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of it, like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their business >>Is performing good, the ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration. W where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Nicolson about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict that they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, what do you see in that regard? Yeah, I think it's, >>I mean, we're definitely not at a point where, when I talked to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? You can get machines to solve general knowledge problems, where they can solve one problem and then a distinctly different problem, right? That's still many years away, but narrow why AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience in pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this a address actually, you know, a business that's a restaurant with indoor dining, does it have a bar? Is it outdoor dining? And it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do even with narrow AI that can really drive top line of business results. >>Yeah. I liked that term, narrow AI, because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. I mean, I think for most right, most >>Fortune 500 companies, they can't just snap their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're have, they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh on-premise and, um, public as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought of? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. And then the salespeople, they know the CRM data and, you know, logistics folks there they're very much in tune with ERP, almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership, if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. I >>Mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience and that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a, a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really >>Important. I think data as a product is a very powerful concept and I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data and that's not necessarily what you mean, thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my data architecture. Is that kind of thinking starting to really hit the marketplace? Absolutely. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware. And is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies, you're doing great examples >>Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss and exactly. Then it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight. >>Yeah. So, um, I, I'm in the executive sponsor for, um, the Accenture Cloudera partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud era is the right data platform for that. So, um, >>Having a cloud Cloudera ushered in the modern big data era, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, absolutely. >>Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role to play. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Yes. Thank you so much. Okay. We continue now with the theme of turning ideas into insights. So ultimately you can take action. We heard earlier that public cloud first doesn't mean public cloud only, and a winning strategy comprises data, irrespective of physical location on prem, across multiple clouds at the edge where real time inference is going to drive a lot of incremental value. Data is going to help the world come back to normal. We heard, or at least semi normal as we begin to better understand and forecast demand and supply and balances and economic forces. AI is becoming embedded into every aspect of our business, our people, our processes, and applications. And now we're going to get into some of the foundational principles that support the data and insights centric processes, which are fundamental to digital transformation initiatives. And it's my pleasure to welcome two great guests, Michelle Goetz. Who's a Kuba woman, VP and principal analyst at Forrester, and doing some groundbreaking work in this area. And Cindy, Mikey, who is the vice president of industry solutions and value management at Cloudera. Welcome to both of >>You. Welcome. Thank you. Thanks Dave. >>All right, Michelle, let's get into it. Maybe you could talk about your foundational core principles. You start with data. What are the important aspects of this first principle that are achievable today? >>It's really about democratization. If you can't make your data accessible, um, it's not usable. Nobody's able to understand what's happening in the business and they don't understand, um, what insights can be gained or what are the signals that are occurring that are going to help them with decisions, create stronger value or create deeper relationships, their customers, um, due to their experiences. So it really begins with how do you make data available and bring it to where the consumer of the data is rather than trying to hunt and Peck around within your ecosystem to find what it is that's important. Great. >>Thank you for that. So, Cindy, I wonder in hearing what Michelle just said, what are your thoughts on this? And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody the fundamentals that Michelle just shared? >>Yeah, there's, there's quite a few. And especially as we look across, um, all the industries that we're actually working with customers in, you know, a few that stand out in top of mind for me is one is IQ via and what they're doing with real-world evidence and bringing together data across the entire, um, healthcare and life sciences ecosystems, bringing it together in different shapes and formats, making the ed accessible by both internally, as well as for their, um, the entire extended ecosystem. And then for SIA, who's working to solve some predictive maintenance issues within, there are a European car manufacturer and how do they make sure that they have, you know, efficient and effective processes when it comes to, uh, fixing equipment and so forth. And then also, um, there's, uh, an Indonesian based, um, uh, telecommunications company tech, the smell, um, who's bringing together, um, over the last five years, all their data about their customers and how do they enhance our customer experience? How do they make information accessible, especially in these pandemic and post pandemic times, um, uh, you know, just getting better insights into what customers need and when do they need it? >>Cindy platform is another core principle. How should we be thinking about data platforms in this day and age? I mean, where does, where do things like hybrid fit in? Um, what's cloud era's point >>Of view platforms are truly an enabler, um, and data needs to be accessible in many different fashions. Um, and also what's right for the business. When, you know, I want it in a cost and efficient and effective manner. So, you know, data needs to be, um, data resides everywhere. Data is developed and it's brought together. So you need to be able to balance both real time, you know, our batch historical information. It all depends upon what your analytical workloads are. Um, and what types of analytical methods you're going to use to drive those business insights. So putting and placing data, um, landing it, making it accessible, analyzing it needs to be done in any accessible platform, whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're seeing, being the most successful. >>Great. Thank you, Michelle. Let's move on a little bit and talk about practices and practices and processes as the next core principles. Maybe you could provide some insight as to how you think about balancing practices and processes while at the same time managing agility. >>Yeah, it's a really great question because it's pretty complex. When you have to start to connect your data to your business, the first thing to really gravitate towards is what are you trying to do? And what Cindy was describing with those customer examples is that they're all based off of business goals off of very specific use cases that helps kind of set the agenda about what is the data and what are the data domains that are important to really understanding and recognizing what's happening within that business activity and the way that you can affect that either in, you know, near time or real time, or later on, as you're doing your strategic planning, what that's balancing against is also being able to not only see how that business is evolving, but also be able to go back and say, well, can I also measure the outcomes from those processes and using data and using insight? >>Can I also get intelligence about the data to know that it's actually satisfying my objectives to influence my customers in my market? Or is there some sort of data drift or detraction in my, um, analytic capabilities that are allowing me to be effective in those environments, but everything else revolves around that and really thinking succinctly about a strategy that isn't just data aware, what data do I have and how do I use it, but coming in more from that business perspective to then start to be, data-driven recognizing that every activity you do from a business perspective leads to thinking about information that supports that and supports your decisions, and ultimately getting to the point of being insight driven, where you're able to both, uh, describe what you want your business to be with your data, using analytics, to then execute on that fluidly and in real time. And then ultimately bringing that back with linking to business outcomes and doing that in a continuous cycle where you can test and you can learn, you can improve, you can optimize, and you can innovate because you can see your business as it's happening. And you have the right signals and intelligence that allow you to make great decisions. >>I like how you said near time or real time, because it is a spectrum. And you know, one of the spectrum, autonomous vehicles, you've got to make a decision in real time, but, but, but near real-time, or real-time, it's, it's in the eyes of the holder, if you will, it's it might be before you lose the customer before the market changes. So it's really defined on a case by case basis. Um, I wonder Michelle, if you could talk about in working with a number of organizations, I see folks, they sometimes get twisted up and understanding the dependencies that technology generally, and the technologies around data specifically can have on critical business processes. Can you maybe give some guidance as to where customers should start, where, you know, where can we find some of the quick wins and high return, it >>Comes first down to how does your business operate? So you're going to take a look at the business processes and value stream itself. And if you can understand how people and customers, partners, and automation are driving that step by step approach to your business activities, to realize those business outcomes, it's way easier to start thinking about what is the information necessary to see that particular step in the process, and then take the next step of saying what information is necessary to make a decision at that current point in the process, or are you collecting information asking for information that is going to help satisfy a downstream process step or a downstream decision. So constantly making sure that you are mapping out your business processes and activities, aligning your data process to that helps you now rationalize. Do you need that real time near real time, or do you want to start grading greater consistency by bringing all of those signals together, um, in a centralized area to eventually oversee the entire operations and outcomes as they happen? It's the process and the decision points and acting on those decision points for the best outcome that really determines are you going to move in more of a real-time, uh, streaming capacity, or are you going to push back into more of a batch oriented approach? Because it depends on the amount of information and the aggregate of which provides the best insight from that. >>Got it. Let's, let's bring Cindy back into the conversation in your city. We often talk about people process and technology and the roles they play in creating a data strategy. That's that's logical and sound. Can you speak to the broader ecosystem and the importance of creating both internal and external partners within an organization? Yeah. >>And that's, uh, you know, kind of building upon what Michelle was talking about. If you think about datas and I hate to use the phrase almost, but you know, the fuel behind the process, um, and how do you actually become insight-driven? And, you know, you look at the capabilities that you're needing to enable from that business process, that insight process, um, you're extended ecosystem on, on how do I make that happen? You know, partners, um, and, and picking the right partner is important because a partner is one that actually helps under or helps you implement what your decisions are. Um, so, um, looking for a partner that has the capability that believes in being insight-driven and making sure that when you're leveraging data, um, you know, for within process on that, if you need to do it in a time fashion, that they can actually meet those needs of the business, um, and enabling on those, those process activities. So the ecosystem looking at how you, um, look at, you know, your vendors are, and fundamentally they need to be that trusted partner. Um, do they bring those same principles of value of being insight driven? So they have to have those core values themselves in order to help you as a, um, an end of business person enable those capabilities. So, so yeah, I'm >>Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, right? You're never going to run out. So Michelle, let's talk about leadership. W w who leads, what does so-called leadership look like in an organization that's insight driven? >>So I think the really interesting thing that is starting to evolve as late is that organizations enterprises are really recognizing that not just that data is an asset and data has value, but exactly what we're talking about here, data really does drive what your business outcomes are going to be data driving into the insight or the raw data itself has the ability to set in motion. What's going to happen in your business processes and your customer experiences. And so, as you kind of think about that, you're now starting to see your CEO, your CMO, um, your CRO coming back and saying, I need better data. I need information. That's representative of what's happening in my business. I need to be better adaptive to what's going on with my customers. And ultimately that means I need to be smarter and have clearer forecasting into what's about ready to come, not just, you know, one month, two months, three months or a year from now, but in a week or tomorrow. >>And so that's, how is having a trickle down effect to then looking at two other types of roles that are elevating from technical capacity to more business capacity, you have your chief data officer that is shaping the exp the experiences, uh, with data and with insight and reconciling, what type of information is necessary with it within the context of answering these questions and creating a future fit organization that is adaptive and resilient to things that are happening. And you also have a chief digital officer who is participating because they're providing the experience and shaping the information and the way that you're going to interact and execute on those business activities, and either running that autonomously or as part of an assistance for your employees and for your customers. So really to go from not just data aware to data driven, but ultimately to be insight driven, you're seeing way more, um, participation, uh, and leadership at that C-suite level. And just underneath, because that's where the subject matter expertise is coming in to know how to create a data strategy that is tightly connected to your business strategy. >>Right. Thank you. Let's wrap. And I've got a question for both of you, maybe Cindy, you could start and then Michelle bring us home. You know, a lot of customers, they want to understand what's achievable. So it's helpful to paint a picture of a, of a maturity model. Uh, you know, I'd love to go there, but I'm not going to get there anytime soon, but I want to take some baby steps. So when you're performing an analysis on, on insight driven organization, city, what do you see as the major characteristics that define the differences between sort of the, the early, you know, beginners, the sort of fat middle, if you will, and then the more advanced, uh, constituents. >>Yeah, I'm going to build upon, you know, what Michelle was talking about as data as an asset. And I think, you know, also being data where, and, you know, trying to actually become, you know, insight driven, um, companies can also have data and they can have data as a liability. And so when you're data aware, sometimes data can still be a liability to your organization. If you're not making business decisions on the most recent and relevant data, um, you know, you're not going to be insight driven. So you've got to move beyond that, that data awareness, where you're looking at data just from an operational reporting, but data's fundamentally driving the decisions that you make. Um, as a business, you're using data in real time. You're, um, you're, you know, leveraging data to actually help you make and drive those decisions. So when we use the term you're, data-driven, you can't just use the term, you know, tongue in cheek. It actually means that I'm using the recent, the relevant and the accuracy of data to actually make the decisions for me, because we're all advancing upon. We're talking about, you know, artificial intelligence and so forth. Being able to do that, if you're just data where I would not be embracing on leveraging artificial intelligence, because that means I probably haven't embedded data into my processes. It's data could very well still be a liability in your organization. So how do you actually make it an asset? Yeah, I think data >>Where it's like cable ready. So, so Michelle, maybe you could, you could, you could, uh, add to what Cindy just said and maybe add as well, any advice that you have around creating and defining a data strategy. >>So every data strategy has a component of being data aware. This is like building the data museum. How do you capture everything that's available to you? How do you maintain that memory of your business? You know, bringing in data from your applications, your partners, third parties, wherever that information is available, you want to ensure that you're capturing and you're managing and you're maintaining it. And this is really where you're starting to think about the fact that it is an asset. It has value, but you may not necessarily know what that value is. Yet. If you move into a category of data driven, what starts to shift and change there is you're starting to classify label, organize the information in context of how you're making decisions and how you do business. It could start from being more, um, proficient from an analytic purpose. You also might start to introduce some early stages of data science in there. >>So you can do some predictions and some data mining to start to weed out some of those signals. And you might have some simple types of algorithms that you're deploying to do a next next best action for example. And that's what data-driven is really about. You're starting to get value out of it. The data itself is starting to make sense in context of your business, but what you haven't done quite yet, which is what insight driven businesses are, is really starting to take away. Um, the gap between when you see it, know it and then get the most value and really exploit what that insight is at the time when it's right. So in the moment we talk about this in terms of perishable insights, data and insights are ephemeral. And we want to ensure that the way that we're managing that and delivering on that data and insights is in time with our decisions and the highest value outcome we're going to have, that that insight can provide us. >>So are we just introducing it as data-driven organizations where we could see, you know, spreadsheets and PowerPoint presentations and lots of mapping to help make sort of longer strategic decisions, or are those insights coming up and being activated in an automated fashion within our business processes that are either assisting those human decisions at the point when they're needed, or an automated decisions for the types of digital experiences and capabilities that we're driving in our organization. So it's going from, I'm a data hoarder. If I'm data aware to I'm interested in what's happening as a data-driven organization and understanding my data. And then lastly being insight driven is really where light between business, data and insight. There is none it's all coming together for the best outcomes, >>Right? So people are acting on perfect or near perfect information or machines or, or, uh, doing so with a high degree of confidence, great advice and insights. And thank you both for sharing your thoughts with our audience today. It's great to have you. Thank you. Thank you. Okay. Now we're going to go into our industry. Deep dives. There are six industry breakouts, financial services, insurance, manufacturing, retail communications, and public sector. Now each breakout is going to cover two distinct use cases for a total of essentially 12 really detailed segments that each of these is going to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout session for choice of choice or for more information, click on the agenda page and take a look to see which session is the best fit for you. And then dive in, join the chat and feel free to ask questions or contribute your knowledge, opinions, and data. Thanks so much for being part of the community and enjoy the rest of the day.

>>Good day. And thanks for joining us as we continue our series here on the Coupa, the AWS startup showcase featuring today, big ID and what this is, will Murphy was the vice president of business development and alliances at big idea. Well, good day to you. How are you going today? Thanks John. I'm doing well. I'm glad to be here. That's great. And acute belong to, I might add, so it's nice to have you back. Um, let's first off, let's share the big ID story. Uh, you've been around for just a handful of years accolades coming from every which direction. So obviously, uh, what you're doing, you're doing very well, but for our viewers who might not be too familiar with big ID, just give us a 30,000 foot level of your core competence. Yeah, absolutely. So actually we just had our five-year anniversary for big ID, uh, which we're quite excited about. >>Um, and that five-year comes with some pretty big red marks. We've raised over $200 million for a unicorn now. Um, but where that comes to and how that came about was that, um, we're dealing with, um, longstanding problems with modern data landscape security governance, privacy initiatives, um, and starting in 2016 with the, uh, authorship of GDPR, the European privacy law organizations, how to treat data differently than they did before they couldn't afford to just sit on all this data that was collected for a couple of reasons, right? Uh, one of them being that it's expensive. So you're constantly storing data, whether that's on-prem or in the cloud is we're going to talk about there's expense that you have to pay to secure the data and keep it from being leaked. You have to pay for access control. It's paid for a lot of different things and you're not getting any value out of that. >>And then there's the idea of like the customer trust piece, which is like, if anything happens to that data, um, your reputational, uh, your reputation as a company and the trust you have between your customers and your organization is broken. So big ID. What we did is we decided that there was a foundation that needed to be built. The foundation was data discovery. If you even an organization knows where its data is, whose data it is, where it is, um, and what it is, and also who has access to it, they can start to make actionable decisions based on the data and based on this new data intelligence. So we're trying to help organizations keep up with modern data initiatives and we're empowering organizations to handle their data sensitive, personal regulated. And what's actually quite interesting is we allow organizations to define what's sensitive to them because like people, organizations are all different. >>And so what's sensitive to one organization might not be to another, it goes beyond the wall. And so we're giving organizations that new power and flexibility, and this is what I still find striking is that obviously with this exponential growth of data and machine learning, just bringing billions of inputs, it seems like right. All of a sudden you have this fast reservoir data, is that the companies in large part, um, don't know a lot about the data that they're harvest state and where it is. And so it's not actionable, it's kind of dark data, right. Just out there reciting. >>Um, and so as I understand it, this, this is your focus basically is tell people, Hey, here's your landscape. Uh, here's how you can better put it to action, why it's valuable and we're going to help them protect it. Um, and they're not aware of these things, which I still find a little striking in this day and age, >>And it goes even further. So, you know, when you start to, when you start to reveal the truth and what's going on with data, there's a couple things that some organizations do. Uh, and I think human instincts, some organizations want to bury their head in the sand. I'm like, everything's fine. Uh, which is, as we know, and we've seen the news frequently, not a sustainable approach. Uh, there's the, there's the, like, let's be a, we're overwhelmed. We don't, we don't even know. We don't even know where to start. Then there's the natural reaction, which is okay. We have to centralize and control everything which defeats the purpose of having, um, shared drives and collaboration and, um, geographically disparate workforces, which we've seen particularly over the last year, how important that resiliency within organizations is to be able to work in different areas. And so, um, it really restricts the value that, um, organizations can get from their data, which is important. And it's important in a ton of ways. Um, and for customers that have allowed their, their data to be, to be stored and harvested by these organizations, they're not getting value out of it either. It's just risk. And we've got to move data from the liability side of the balance sheet, um, to the assets out of the balance sheet. And that comes first and foremost with knowledge. >>So everybody's vote cloud, right? Everybody was on prem and also we build a bigger house and build a bigger house, better security, right in front of us, got it, got to grow. And that's where I assume AWS has come in with you. And, and this was a two year partnership that you've been engaged with in AWS. So maybe shine a little light on that, about the partnership that you've created with AWS, and then how you then in turn transition that, to leverage that for the betterment of your >>Customer base. Yeah. So AWS has been a great partner. Um, they are very forward-looking for an organization, as large as they are very forward looking that they can't do everything that their customers need. And it's better for the ecosystem as a whole to enable small companies like us. And we were very small when we started our relationship with them, uh, to, to join their partner organization. So we're an advanced partner. Now we're part of ISV accelerate. So it's a slightly more lead partner organization. Um, and we're there because our customers are there and AWS like us, but we both have a customer obsessed culture. Um, but organizations are embracing the cloud and there's fear of the cloud. There's there really shouldn't be in the, in the way that we thought of it, maybe five or 10 years ago. And that, um, companies like AWS are spending a lot more money on security than most organizations can. >>So like they have huge security teams, they're building massive infrastructure. And then on top of that, companies themselves can do, can use, uh, products like big ID and other products to make themselves more secure, um, from outside threats and from, from inside threats as well. So, um, we are trying to with them approach modern data challenge as well. So even within AWS, if you put all the information in, like, let's say S3 buckets, that doesn't really tell you anything. It's like, you know, I, I make this analogy. Sometimes I live in Manhattan. If I were to collect all the keys of everybody that lived in a 10 block radius around me and put it into a dumpster, uh, and keep doing that, I would theoretically know where all the keys were there in the dumpster. Now, if somebody asked me, I'd like my keys back, uh, I'd have a really hard time giving them that because I've got to sort through, you know, 10,000 people's keys. >>And I don't really know a lot about it, but those key sale a lot, you know, it says, are you in an old building, are you in a new building? You have a bike, do you have a car? Do you have a gym locker? There's all sorts of information. And I think this analogy holds up for data because of the way you store your data is important, but, um, you can gain a lot of theoretically innocuous, but valuable information from the data that's there while not compromising the sensitive data. And as an AWS has been a fabulous partner in this, they've helped us build a AWS security, have integration out of the box. Um, we now work with over 12 different AWS native, uh, applications from anything like S3 Redshift and Sienna, uh, Kinesis, as well as, um, apps built on AWS like snowflake and Databricks that we, that we connect to. >>And AWS, the technical team of department teams have been an enormous part of our success there. We're very proud of joining the marketplace to be where our customers want to buy enterprise software more and more. Um, and that's another area that we're collaborating, uh, in, in, in joint accounts now to bring more value in simplicity to our joint customers. What's your process in terms of your customer and, uh, evaluating their needs because you just talked about earlier, you had different approaches to security. Some people put their head in the sand, right? Some people admit that there's a problem. Some people fully engaged. So I assume there's also different levels of sophistication in terms of whatever you have in place and then what their needs are. So if you would shine a little light on that, you know, where they are in terms of their data landscape and AWS and its tools, but you just touched them on multiple tools you have in your service. >>Now, all that comes together to develop what would be, I guess, a unique program for a company's specific needs. It is. We started talking to the largest enterprise accounts when we were founded and we still have a real proclivity and expertise in that area. So the issues with the large enterprise accounts and the uniqueness there is scale. They have a tremendous amount of data, HR data, financial data, customer data, you name it, right? Like, we'll go. We can, we can go dry mouth talking about how many you're saying data. So many times with, with these large customers, um, freight Ws scale, wasn't an issue. They can store it, they can analyze it. They can do tons. It where we were helping is that we could make that safer. So if you want to perform data analytics, you want to ensure that sensitive data is not being, or that you want to make sure you're not violating local, not national or industry specific regulations. >>Financial services is a great example. There's dozens of regulations at the federal level in the United States and each state has their own regulations. This becomes increasingly complex. So AWS handles this by, by allowing an amazing amount of customization for their customers. They have data centers in the right places. They have experts on, on, uh, vertical, specific issues. Big ID handles this similarly in some ways, but we handle it through ostensive ability. So one of our big things is we have to be able to connect to every everywhere where our customers have data. So we want to build a foundation of like, let's say first let's understand the goals is the goal compliance with the law, which it should be for everybody that should just be like, we need to, we need to comply with the law. Like that's, that's easy. Yeah. Then as the next piece, like, are we dealing with something legacy? >>Was there a breach? Do we need to understand what happened? Are we trying to be forward-looking and understanding? We want to make sure we can lock down our most sensitive data, tier our storage tier, our security tier are our analytics efforts, which also is cost-effective. So you don't have to do, uh, everything everywhere, um, or is the goal a little bit like we needed to get a return on investment faster, and we can't do that without de-risking some of that. So we've taken those lessons from the enterprise where it's exceedingly difficult, uh, to work because of the strict requirements, because the customers expect more. And I think like AWS, we're bringing a down market. Uh, we have some, a new product coming out. Uh, it's exclusive for, uh, AWS now called small ID, which is a cloud native, a smaller version, lighter weight version of our product for customers in the more commercial space in the SMB space where they can start to build a foundation of understanding their data or, um, protection for security for, for, for privacy. >>And, and before I let you go here, what I'd like to hear about is practical application. You know, somebody that, that you've, you know, that you were able to help and assist you evaluated. Cause you've talked about the format here. You've talked about your process and talk about some future, I guess, challenges, opportunities, but, but just to give our viewers an idea of maybe the kind of success you've already had to, uh, give them a perspective on that, this share a couple stories. If you wouldn't mind with some work that you guys did and rolled up your sleeves and, and, uh, created that additional value >>For your customers. Yeah, absolutely. So I'll give a couple examples. I'm going to, I'm going to keep everyone anonymized, uh, as a privacy based company, in many ways, what we, we try to respect colors. Um, but let's talk about different types of sensitive data. So we have customers that, um, intellectual property is their biggest concern. So they, they do care about compliance. They want to comply with all local and national laws where they, where they, their company resides all their offices are, but they were very concerned about sensitive data sprawl around intellectual property. They have a lot of patents. They have a lot of sensitive data that way. So one of the things we did is we were able to provide custom tags and classifications for their sensitive data based on intellectual property. And they could see across their cloud environment, across their on-premise environment across shared drives, et cetera. >>We're sensitive data had sprawl where it had moved, who's having access to it. And they were able to start realigning their storage strategy and their content management strategy, data governance strategy, based on that, and start to, uh, move sensitive data back to certain locations, lock that down on a higher level could create more access control there, um, but also proliferate and, uh, share data that more teams needed access to. Um, and so that's an example of a use case that I don't think we imagined necessarily in 2016 when we were focused on privacy, but we've seen that the value can come from it. Um, so yeah, no, I mean, the other piece is, so we've worked with some of the largest AWS customers in the world. Their concern is how do we even start to scan the Tedder, terabytes and petabytes of data in any reasonable fashion? >>Uh, without it being out of date, if we create this data map, if we prayed this data inventory, uh, it's going to be out of date day one, as soon as we say, it's complete, we've already added more. That's where our scalability fit Sam. We were able to do a full scan of their entire AWS environment and, uh, months, and then keep up with the new data that was going into their AWS environment. This is a, this is huge. This was groundbreaking for them. So our hyper scan capability, uh, that we've wrote, brought out that we rolled out to AWS first, um, was a game changer for them to understand what data they had and where it is who's it is et cetera at a way that they never thought they could keep up with. You know, I I'm, I brought back to the beginning of code when the British government was keeping track of all the COVID cases on spreadsheets and spreadsheet broke. >>Um, it was also out of date, as soon as they entered something else. It was already out of date. They couldn't keep up with them. Like there's better ways to do that. Uh, luckily they think they've moved on from, from that, uh, manual system, but automation using the correct human inputs when necessary, then let, let machine learning, let, uh, big data take care of things that it can, uh, don't waste human hours that are precious and expensive unnecessarily and make better decisions based on that data. You know, you raised a great point too, which I hadn't thought of about the fact is you do your snapshot today and you start evaluating all their needs for today. And by the time you're going to get that done, their needs have now exponentially grown. It's like painting the golden gate bridge, right. You get that year and now you've got to pay it again. I said it got bigger, but anyway, they will. Thanks for the time. We certainly appreciate it. Thanks for joining us here on the sort of showcase and just remind me that if you ever asked for my keys, keep them out of that dumpster to be here.

(upbeat music) >> Well, good day and thank you for joining us as we continue our series here on theCUBE of the AWS Startup Showcase featuring today BigID. And with us is Will Murphy, who's the Vice President of the Business Development and Alliances at BigID. Will, good day to you, how are you doing today? >> Thanks John, I'm doing well. I'm glad to be here. >> Yeah, that's great. And theCUBE alum too, I might add so it's nice to have you back. Let's first off, let's share the BigID story. You've been around for just a handful of years. Accolades coming from every which direction so obviously what you're doing, you're doing very well. But for our viewers who might not be too familiar with BigID, just give us a 30,000 foot level of your core competence. >> Yeah absolutely. So actually we just had our five-year anniversary for BigID, which we're quite excited about. And that five year comes with some pretty big red marks. We've raised over $200 million for a unicorn now. But where that comes to and how that came about was that we're dealing with longstanding problems with modern data landscapes, security governance, privacy initiatives. And starting in 2016 with the authorship of GDPR, the European privacy law organizations had to treat data differently than they did before. They couldn't afford to just sit on all this data that was collected. For a couple reasons, right? One of them being that it's expensive. So you're constantly storing data whether that's on-prem or in the cloud as we're going to talk about. There's expense to that. You have to pay to secure the data and keep it from being leaked, You have to pay for access control, you have to pay for a lot of different things. And you're not getting any value out of that. And then there's the idea of the customer trust piece, which is like if anything happens to that data, your reputation as a company and the trust you have between your customers and your organization is broken. So BigID, what we did is we decided that there was a foundation that needed to be built. The foundation was data discovery. If an organization knows where its data is, whose data it is, where it is, and what it is and also who has access to it, they can start to make actionable decisions based on the data and based on this new data intelligence. So, we're trying to help organizations keep up with modern data initiatives. And we're empowering organizations to handle their data, sensitive, personal regulated. What's actually quite interesting is we allow organizations to define what's sensitive to them because like people, organizations are all different. And so what's sensitive to one organization might not be to another. It goes beyond the wall. And so we're giving organizations that new power and flexibility. >> And this is what I still find striking is that obviously with this exponential growth of data you got machine learning, just bringing billions of inputs. It seems like right now. Also you had this vast reservoir of data. Is that the companies in large part don't know a lot about the data that they're harvesting and where it is, and so it's not actionable. It's kind of dark data, right? Just out there residing. And so as I understand it, this is your focus basically is to tell people, hey here's your landscape, here's how you can better put it to action why it's valuable and we're going to help you protect it. And they're not aware of these things which I still find a little striking in this day and age >> And it goes even further. So you know, when you start to reveal the truth and what's going on with data, there's a couple things that some organizations do. And enter the human instincts. Some organizations want to bury their head in the sand like everything's fine. Which is as we know and we've seen the news frequently not a sustainable approach. There's the like let's be we're overwhelmed. Yeah. We don't even know where to start. Then there's the unnatural reaction, which is okay, we have to centralize and control everything. Which defeats the purpose of having shared drives and collaboration in geographically disparate workforces, which we've seen in particularly over the last year, how important that resiliency within organizations is to be able to work in different areas. And so it really restricts the value that organizations can get from their data, which is important. And it's important in a ton of ways. And for customers that have allowed their data to be stored and harvested by these organizations, like they're not getting value out of it neither. It's just risk. And we've got to move data from the liability side of the balance sheet to the assets side of the balance sheet. And that comes first and foremost with knowledge. >> So everybody's going cloud, right? Used to be, you know, everybody's on prem. And all of a sudden we build a bigger house. And so because you build a bigger house, you need better security, right? Your perimeter's got to grow. And that's where I assume AWS has come in with you. And this is a two year partnership that you've been engaged with in AWS. So maybe shine a little light on that. About the partnership that you've created with AWS and then how you then in turn transition that to leverage that for the benefit of your customer base. >> Yeah. So AWS has been a great partner. They are very forward-looking for an organization as large as they are. Very forward looking that they can't do everything that their customers need. And it's better for the ecosystem as a whole to enable small companies like us, and we were very small when we started our relationship with them, to join their partner organization. So we're an advanced partner now. We're part of ISV Accelerate. So it's a slightly more lead partner organization. And we're there because our customers are there. And AWS like us, we both have a customer obsessed culture. But organizations are embracing the cloud. And there's fear of the cloud, but there really shouldn't be in the way that we thought of it maybe five or 10 years ago. And that companies like AWS are spending a lot more money on security than most organizations can. So like they have huge security teams, they're building massive infrastructure. And then on top of that, companies themselves can can use products like big ID and other products to make themselves more secure from outside threats and from inside threats as well. So we are trying to with them approach modern data challenges well. So even within AWS, if you put all the information in like let's say S3 buckets, it doesn't really tell you anything. It's like, you know, I make this analogy sometimes. I live in Manhattan and if I were to collect all the keys of everybody that lived in a 10 block radius around me and put it into a dumpster and keep doing that, I would theoretically know where all the keys were. They're in the dumpster. Now, if somebody asked me, I'd like my keys back, I'd have a really hard time giving them that. Because I've got to sort through, you know, 10,000 people's keys. And I don't really know a lot about it. But those key say a lot, you know? It says like, are you in an old building? Are you in a new building? Do you have a bike? Do you have a car? Do you have a gym locker? There's all sorts of information. And I think that this analogy holds up for data but ifs of the way you store your data is important. But you can gain a lot of theoretically innocuous but valuable information from the data that's there, while not compromising the sensitive data. And as an AWS has been a fabulous partner in this. They've helped us build a AWS security, have integration out of the box. We now work with over 12 different AWS native applications from anything like S3, Redshift, Athena, Kinesis, as well as apps built on AWS, like Snowflake and Databricks that we connect to. And in AWS, the technical teams, department teams have been an enormous part of our success there. We're very proud to have joined the marketplace, to be where our customers want to buy enterprise software more and more. And that's another area that we're collaborating in joint accounts now to bring more value and simplicity to our joint customers. >> So what's your process in terms of your customer and evaluating their needs? 'Cause you just talked about it earlier that you had different approaches to security. Some people put their head in the sand, right? Some people admit that there's a problem. Some people fully are engaged. So I assume there's also a different level of sophistication in terms of what they already have in place and then what their needs are. So if you were to shine a little light on that, about assessing where they are in terms of their data landscape. And now AWS and its tools, which you just touched on. You know, the multiple tools you have in your service. Now, all that comes together to develop what would be I guess, a unique program for a company's specific needs. >> It is. We started talking to the largest enterprise accounts when we were founded and we still have a real proclivity and expertise in that area. So the issues with the large enterprise accounts and the uniqueness there is scale. They have a tremendous amount of data: HR data financial data, customer data, you name it. Right? Like, we could go dry mouth talking about how many insane data so many times with these large customers. For AWS, scale wasn't an issue. They can store it. They can analyze it. They can do tons with it. Where we were helping is that we could make that safer. So if you want to perform data analytics, you want to ensure that sensitive data is not being part of that. You want to make sure you're not violating local, national or industry specific regulations. Financial services is a great example. There's dozens of regulations at the federal level in United States. And each state has their own regulations. This becomes increasingly complex. So AWS handles this by allowing an amazing amount of customization for their customers. They have data centers in the right places. They have experts on vertical specific issues. BigID handles this similarly in some ways, but we handle it through extensibility. So one of our big things is we have to be able to connect to everywhere where our customers have data. So we want to build a foundation of like let's say first, let's understand the goals. Is the goal compliant with the law? Which it should be for everybody. That should just be like, we need to comply with the law. Like that's easy. Yeah. Then there's the next piece, like are we dealing with something legacy? Was there a breach? Do we need to understand what happened? Are we trying to be forward-looking and understanding? We want to make sure we can lock down our most sensitive data. Tier our storage, tier our security, tier are our analytics efforts which also is cost-effective. So you don't have to do everything everywhere. Or is the goal a little bit like we needed to get our return on investment faster. And we can't do that without de-risking some of that. So we've taken those lessons from the enterprise where it's exceedingly difficult to work because of the strict requirements because the customers expect more. And I think like AWS, we're bringing it down market. We have some new product coming out. It's exclusive for AWS now called SmallID, which is a cloud native. A smaller version, lighter weight version of our product for customers in the more commercial space. In the SMB space where they can start to build a foundation of understanding their data for protection and for security, for privacy. >> Will, and before I let you go here what I'd like to hear about is practical application. You know, somebody that you've, you know, that you were able to help and assist, you evaluated. 'Cause you've talked about the format here. You talked about your process and talked about some future, I guess, challenges, opportunities. But just to give our viewers an idea of maybe the kind of success you've already had. To give them a perspective on that. Just share a couple of stories, if you wouldn't mind. Whether there's some work that you guys did and rolled up your sleeves and created that additional value for your customers. >> Yeah, absolutely. So I'll give a couple examples. I'm going to keep everyone anonymized. As a privacy based company, in many ways, we try to respect-- >> Probably a good idea, right? (Will chuckles) >> But let's talk about different types of sensitive data. So we have customers that intellectual property is their biggest concern. So they do care about compliance. They want to comply with all the local and national laws where their company resides and all their offices are. But they were very concerned about sensitive data sprawl around intellectual property. They have a lot of patents. They have a lot of sensitive data that way. So one of the things we did is we were able to provide custom tags and classifications for their sensitive data based on intellectual property. And they could see across their cloud environment, across their on-premise environment, across shared drives et cetera, where sensitive data had sprawl. Where it had moved, who's having access to it. And they were able to start realigning their storage strategy and their content management strategy, data governance strategy, based on that. And start to move sensitive data back to certain locations, lock that down on a higher level. Could create more access control there, but also proliferate and share data that more teams needed access to. And so that's an example of a use case that I don't think we imagined necessarily in 2016 when we were focused on privacy but we've seen that the value can come from it. Yeah. >> So it's a good... Please, yeah, go ahead. >> No, I mean, the other (mumbles). So we've worked with some of the largest AWS customers in the world. Their concern is how do we even start to scan the Tedder terabytes and petabytes of data in any reasonable fashion without it being out of date. If we create this data map, if we create this data inventory, it's going to be out of date day one. As soon as we say, it's complete, we've already added more. >> John: Right. >> That's where our scalability fits in. We were able to do a full scan of their entire AWS environment in months. And then keep up with the new data that was going into their AWS environment. This is huge. This was groundbreaking for them. So our hyper scan capability that we brought out, that we rolled out to AWS first, was a game changer for them. To understand what data they had, where it is, who's it is et cetera, at a way that they never thought they could keep up with. You know, I brought back to the beginning of code when the British government was keeping track of all the COVID cases on spreadsheets and spreadsheets broke. It was also out of date. As soon as they entered something else it was already out of date. They couldn't keep up with it. Like there's better ways to do that. Luckily they think they've moved on from that manual system. But automation using the correct human inputs when necessary. Then let machine learning, let big data take care of things that it can. Don't waste human hours that are precious and expensive unnecessarily. And make better decisions based on that data. >> Yeah. You raised a great point too which I hadn't thought of about. The fact is, you do your snapshot today and you start evaluating all their needs for today. And by the time you're able to get that done their needs have now exponentially grown. It's like painting the golden gate bridge. Right? You get done and now you got to paint it again, except it got bigger. We added lanes, but anyway. Hey, Will. Thanks for the time. We certainly appreciate it. Thanks for joining us here on the startup showcase. And just remind me that if you ever asked for my keys keep them out of that dumpster. Okay? (Will chuckles) >> Thanks, John. Glad to be here. >> Pleasure. (soft music)

(bright music) >> Announcer: From around the globe, it's theCUBE, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Global Partner Network. >> Okay, welcome back everyone to theCUBE Virtual Experience here for re:Invent coverage 2020 virtual. Normally we're in person doing interviews face to face, but we're remote this year because of the pandemic. We're here for the APN partner experience, kickoff coverage with two great guests, Rima Olinger, of global lead for VMware cloud on AWS. And Aarthi Raju, Senior Manager Solutions Architecture for Amazon Web Services. Thanks for coming on, appreciate it. >> Good to be with you John, thank you. >> So I got, want to get it out there this partner network experience, it's really about the ecosystem. And VMware has been one of the biggest success stories. They've been around for a long time, and not one of the earliest ecosystem partners, but a big success. 2016, when that announcement happened, a lot of people were like, whoa, we VMware is giving into Amazon. And Amazon was like, no, that's not how it works. So turns out everyone was been proven wrong, it's been hugely successful beneficial to both. What's the momentum, share an update this year on the AWS VMware momentum. >> So John, as you know, we're into our third anniversary, and the relationship cannot be any stronger. We see customers are leaning into the service very heavily. We see great adoption across multiple industries. As some data points for you, if we look at October of this year to October prior year, we're seeing the number of active nodes, or the number of consuming host and active VMS, nearly doubled year over year. we also continue to see greater partner interest in the solution, we have over 300 ISVs that have validated the services on VMC. And we see over 600 plus partners that continue to take the competencies and build practices around it. So the momentum is very strong, for years still today. >> One of the comments I made when the naysayers were like kind of pooh-poohing the deal, I was like, no, no, the cloud growth is going to be a factor at that time, then, the trendy thing was software's eating the world, was a big trend there. If you look at the growth of cloud scale, and software innovation, and the operating side of it, 'cause VMware runs IT, they let operators running IT. There's no conflict because Amazon's growing and now the operator roles growing and changing. So you have two dynamics going on. I think this is a really nuanced point for the VMware, AWS relationship around, how they both fit together. Because it's a win win better together scenario, and it is on AWS, which is a distinction. Can you guys share your reaction to kind of that dynamic of operating software at scale, and how this translates for customers? >> Absolutely, we see a lot of benefits that this service is bringing to the customers. Because what it's doing is providing them with this consistent infrastructure and operations across hybrid cloud environments. And in this way, they have the choice of where to place their applications on-prem or in the cloud, specifically. And this is one of the reasons why AWS is a VMware's preferred cloud provider for all vSphere workloads. We see the customers gravitate towards it and be receptive to it specifically because they say I accelerate my path towards migrating and modernizing my application. It provides me with consistent as I mentioned, operations and infrastructure. And it also helps them with factoring, and helps us scale their business and very fast, very seamless fashion. Aarthi what is your perspective, maybe additional things. >> Yeah. >> Yeah, from a technical innovation perspective, the momentum, John has been very strong, especially, listening to what customers have been asking us the past couple of years. 2020 has been a big year for us in terms of launching some giant innovations. A couple of things to call out is, we launched the VMware Transit Connect. This was announced during VMworld this year and customers have been telling us, hey, we are migrating workloads from on premises to the cloud, we need a simplified way of connecting all these resources on-prem resources, resources on VMware cloud on AWS, and their AWS native resources as well. So, the VMware Transit Connect, uses the AWS transit gateway that we launched at re:Invent two years back to provide that simplified connectivity model for our customers. The next big thing this year was, we introduced a new instance type i3en.metal, So customers have been telling us they want denser nodes for especially storage heavy workload. So we launched this i3en, that comes with approximately, like 45 terabytes of storage per node. So that's a lot of storage for individual nodes. So customers have been taking advantage of these dense nodes as well. There was other areas that we kind of focused on from a lower entry point for our customers. When we initially started the service, John, you know that we had, the minimum entry point as four nodes, we've scaled that down to three, and now we've come to two nodes, giving the same production SLA for customers. The other big launch this year was the acquisition of Datrium by VMware and how we introduce the VMware cloud disaster recovery. Datrium uses the eight native AWS services like S3 and EC2, providing customers this low cost TR options. We're talking about the APN here and for partners, we launched the VMware cloud Director Service, which delivers multi-tenancy to our managed service providers, so that they can cater to small, to medium sized enterprises. >> What are some of the other use cases that are the key in these migrations, because this becomes a big benefit we're hearing, certainly, during the partner day, here at re:Invent, is, migration, cloud SaaSification, getting to a SaaS, but not losing the business model. Either was on premises or born in the cloud, this done new operating models, the key thing, what are some of the key use cases for partners? >> The most widely adopted use case that John, which you rightfully touched on, is really the cloud migration. We see around 41% of customers use the service just for cloud migrations. Now, this could be an application migration, like SAP, SQL server or Oracle Applications, or it could be a complete data center evacuation. And we see that with some customers who have a cloud mandate, or they have refresh cycles that are coming up, or maybe they're in a colo, and they're not happy with their SLA. I could use the example of William Hill, is one of the customers largest betting and gaming companies that are in the UK. And what's the use case was, a combination of a data center extension as well as a capacity expansion specifically. And what William Hill was able to do is, move 800 on-premise servers, and they decommission them in the first 12 months. And they also migrated 3000 VM. So that is cloud migrations is a big use case. The second big use case, as I mentioned earlier, is the data center extension that includes also VDI, the combination of both is around 42% of the use cases, with around 26%, I would say for data center extension and 16% for VDI. Why, customers want to expand their footprint, they want to go to a new region, and they want to meet on demand, cyclical capacity needs, or sometimes temporary needs for some events or some seasonal spikes. So we see that as a second big use case. A third one equally important, tend to be disaster recovery. Now, this is either to augment an existing DR. Replace a DR that is already in place, or start a new DR, and that constitutes around 17% of the use cases that we see. Because customers want to reduce their DR, avert some cost by moving to the cloud. And one example that comes to mind is Pennsylvania Lumbers Men's Mutual Insurance, it was a DR use Case. They worked with an external storage partner of ours faction in order to put that in place. So overall a great use cases across the board. And I know a big one is application modernization, Aarthi, I know you work with your teams on that, if there's any feedback from you on that. >> Yeah, the next generation applications or application modernization comes a lot. We talk to like AWS customers who are migrating from on-premises to the cloud using VMware cloud on AWS. And three or four years back as we were building the service and architecting, one thing was very evident, like we wanted to make sure that as we were building the service, we wanted to ensure that customers can take advantage of the native AWS services. We've got 175 plus services and new services launching at re:Invent, So we wanted to make sure that there is this, seamless mechanism and seamless path for customers to modernize using native AWS services. So what we've done as part of like onboarding for customers and as customers built on VMware cloud on AWS, is provide them both the network path and data path. So they can as your into the same availability zone or region, they're like, hey, I can use S3 for backups. I can use EFS, for file shares, etcetera. So we're seeing a wide range of next generation application use cases that customers are building on. >> Why would I get at the reasons why customers are continuing to adopt VMware cloud on AWS? Can you guys share an update, I'll show you the obvious reasons, the beginning was nice strategy for VMware, it's proven to be clear. But where's the innovation coming from? What's the key drivers for the adoption of VMware cloud on AWS? >> So one of the key patterns that we are seeing is, customers who used to be risk averse, customers will be invested a lot in VMware. And at the point, they did not want to move their workloads or applications to the cloud because of the risk involved, or sometimes they didn't want to refactor, or they were worried about the investment in tools, resources, they tend to gravitate towards this solution. The fact that you could provide your customers with this consistent infrastructure and operations across on premise, as well as on the cloud environment. The fact that you do not need to do an application refactoring. You could optimize your workload placement, based on your business needs, you could move your workloads bidirectionally, you could either leave it on-prem, or move it to the cloud, and vice versa. We've also noticed that there is a lower TCO associated with the use of the service. We know from a study that VMware commissioned Forrester in 2019, for that study, that 59%, there is a recurring savings in terms of infrastructure, and operational savings that is related to that. Customers tell us that, this consistency in infrastructure is translating it, into zero refactoring. This consistency in operations, is leading them to use their existing skill sets. And with the ability to relocate the workload skill into the environment that best suits them, that is providing customers with maximum flexibility. So I would say it is delivering on the promise of accelerating the migration and the modernization of our customers applications so that they can continue to respond to their business needs and continue to be competitive in the marketplace. >> Aarthi I want you to weigh in and get reaction to that. Because again, I've talked publicly and also privately with Ragu, for instance, at VMware, when this was all going down. It's a joint integration, so there's a lot of things going on under the hood that are important, what are the most important things that people should pay attention to around this partnership? Could you share your opinion? >> Yeah, sure, John. So one of the most common questions that we get from customers is, hey, this is giant integration, we can take use of make use of native AWS services, but what are some of the use cases that we should be targeting, right? As we talk to customers, some of the common use cases to think about is, it also depends on the audience. Remember, admin scoring example, who might not be familiar with the AWS side of services, they can start with something simple like backing up. So S3, which is our simple storage service, we see that use case way more often with our VMware cloud on AWS customers. This also ties with that Datrium integration that I talked about with the VCD or the VMware cloud disaster recovery, providing that low cost TR option. We are also starting to see customers offload database management, for example, with Amazon RDS, and taking advantage of the manage database service. As we talk to more customers, some of the use cases that comes up are like, hey, how do I build this data lake architecture? I've migrated to the cloud, I want to make use of the data that I have in the cloud now, how do I build my data lake architecture or perform analytics or build this operation resiliency across both these environments, their VMware cloud on AWS, as well as their native AWS environments? So we've got that seamless connectivity that they can take advantage of with VMware Transit Connect, we've got the cross account ENI model that we built, that they can take advantage of. And he talks about this one, and talks about the security is always job zero for us. And we're also seeing customers that take advantage of the AWS services like the web application firewall or shield, and integrating it with the VMware cloud on AWS environment. And that provides a seamless access right? You now have all these security services that AWS provides, that allows you to build a secure environment on VMware cloud on AWS. So providing customers the choice has always been a priority, right? We're talking about like infrastructure level services. As we move up the stack, and as customers are going through this modernization journey, like VMware provides containerization option using VMware Tanzu, that came out at VMworld. And then they also have the native options, we provide a EKS, which is our Kubernetes as a managed service. And then we also have other services that enables customers to take that jump into that modernization journey. One customer we've been working very recently with is PennyMac. They migrated their VDI infrastructure into VMware cloud on AWS. And that's allowed them to scale their environment for the remote workers. But what they are doing as part of their modernization journey, is now we're helping them build this completely serverless architecture, using Lambda on the AWS cloud. >> Yeah, that's really where they see that, the value is high level services, the old expression prima, they use the hockey from Wayne Gretzky skate to where the puck is going to be, or, get to where the ball will be in the field. This is kind of what's happening, and I'm kind of smiling, when Aarthi was talking because, I've been saying it's been, going to, IT operations, and IT serviceman's is going to change radically so years ago. But you're really talking about here is the operating side of IT coming together with cloud. VMware, I think is a leading indicator of, you still got to operate IT, you still got to operate stuff. Software needs to be operated apps need to be operated. So this new operating model is being shown here with cloud, this is the theme with and without IT. With automation, this is the big trend from re:Invent this year. Obviously AI machine learning, you still got to operate the stuff. It's IT, depends on, we got lammed in automation doesn't go away, the game is still the same, isn't it what's happening here? >> Absolutely, so what we're saying is, once there's that you're absolutely right about the fact that they needed to, worry about the operations, once they migrate their workloads, they're taking their data, they're saying, how do I make sure that I put in place operational excellence, and this is where, AWS comes in, and we provide them with the tools needed to do that. And then step number two, say, what can I do with this data? How do I translate it into a business benefit? And this is where the AI ML tools come in place, and so forth. And then the third step, which is all right, what can I do to modernize these applications further. So you're spot on, John, in saying that this is like a transformation, it is no longer a discussion about, migration anymore, it is more of a discussion about modernizing what you have in place. And this is, again, where this brilliancy between the collaboration, between VMware and AWS, is bringing to the table, sets of tools and framework for customers, whether it's security framework or networking framework, to make the pieces fit together. So I'm very excited about this partnership. And we continue to innovate, as you heard in prior discussions with our executives on behalf of our customers, we spoke about the RDS Amazon, relational database service on vSphere. We spoke about how to post on VMware cloud on AWS, to bring the cloud to the customers data center for specific needs that they have in spite. And we're not stopping here. We are continuing not to make more joint engineering and more announcements, hopefully in the future to come. >> That's great insight. And a lot of people who were commenting, three, four years ago, when this is all going down, they're on the wrong side of history, that the data is undeniable, refutable, it's a success. Aarthi give us the final word, modern applications, modern infrastructure, what does that mean, these days? What's the bottom line when you talk to people out there? When you're at a party or friends or on zoom, or a Jime, in conference? What do you tell people when they say, what's a modern application infrastructure look like? >> Yes, the word modern application, the good or bad thing is it's going to, what I said yesterday could be different from what I'm saying today. But in general, I think modern application is where we enable our customers to focus more on their business priorities using our services, versus worrying about the infrastructure or worrying about like, hey, should I be worrying about capacity? Should I be worrying about my operational needs or monitoring? I think we want to abstract all that. We want to take that heavy lifting off of customers and help them focus on their business. >> Horizontally scalable and leveraging software in the application, can't go wrong with that formula in the cloud. Thanks for coming on, and thanks for the awesome conversation. Thanks for coming on. >> Thank you John. >> Thank you >> Okay, it's theCUBE Virtual for re:Invent Experience 2020, this is virtual, not in person this year. I'm John Furrier, your host from the theCUBE, thanks for watching. (bright music)

>>from around the globe. It's the Cube with digital coverage of VM World 2020 brought to you by VM Ware and its ecosystem partners. Welcome back. I'm stupid a man. And this is the cubes coverage of VM World 2020 our 11th year at VM World. And of course, we've been watching VM where they're doing a lot more in the cloud the last few years. Big partnership with A W s. And part of that is they bring their ecosystem with them. So Justus, they've had hundreds of companies working with them in the data center. When they do VM ware cloud on AWS in azure oracle, all the cloud service fighters, the data protection companies can come along and continue to partner with them. That's part of what we're gonna be discussing. Happened. Welcome back to the program. It's been a few years. Deepak Mohan. He's the executive vice president of products organization at Veritas. Deepak, thank you so much for joining us. You've got a beautiful veritas facility behind you there. >>Yeah. Nice to meet you. Stew. Yeah. We're really excited about the way in world event and a happy to be on the show. with you? >>Yes. So? So? So let's before we dig in tow data, resiliency and all the other pieces, you know, the Veritas VM relationship goes, goes way back. I mean, I think back to the early oughts, uh, you know, talk about the software companies. You know, Veritas was the, you know, software company in the industry that really got a lot of it started. Yeah, a little company that you and I both know knee M c picked up VM where the rest is history there. But veritas that that partnership has been there since the early early days off from VM ware. So just free refresh our viewers a little bit on on that partnership. >>Yeah, So we, um we're and Veritas have bean partners for, like 20 years. In fact, I'll say, both companies were founded about the same time. We, uh, neighbors in Silicon Valley and Veritas was actually one of the first companies to have introduced the concept off software defined data center software, defined storage. In fact, even before, you know, visa and all came into the picture. But as we and we're progressed with, the virtual is ations off the infrastructure. It was really important for enterprise customers to ensure that both their applications stay resilient and highly available, and all that data remains protected. So at 87% off the global fortune 500 customers are veritas customers. They're all using we and we're in their infrastructures. So any time we, um we're introduces a technology we have to ensure it is available, it's protected eso that partnership goes along a long way where every remember platform has way supported on day one for the Veritas solution. So very tight partnership. We get to see each other frequently and make sure that our solutions are joined at the hip. >>Yeah, Deepak, the term we hear from Veritas, we talked about data resiliency. And as you laid out there, you know, some things have changed. You know, 20 years ago, we weren't talking about cloud native environments, and you know all of these various pieces. Uh, it was really multi vendor heterogeneous environments that veritas lived in. Um, but even in all of these environments of, of course, you know, data resiliency, you know, making sure my data is protected, making sure things they're secure. Um, is still, you know, top of mine and so important for organizations. So, you know, talk to us a little bit about you know what that means here in 2020. With Veritas? Yes. >>So I'll say. 20 years ago, uh, we had one application. One server. Life was very fairly simple. Um, you know? Then came William where? You know, now we have the hybrid private clouds, public clouds, hybrid clouds. So the infrastructure is shifting into these other models, but the need for application resiliency and data resiliency is getting more and more complex because now we have applications that are running on Prem. They're running in virtual machines. They're running in hybrid environments. They're running in private clouds. They're running in infrastructure as a service. SAAS applications. So they're all over the place now, think about the job off the CEO. First, you have to make sure all these applications are up and running 24 by seven. Second, these applications have to be protected, which means, in case off a disaster in case often issue, you have to be ableto recover them a third. How do you be compliant with regulations with things? So so customers now have to have visibility into their infrastructure. So the job of the CEO is becoming super complex to keep in handle on everything. And that's where, uh, the companies like Veritas who are doing application resiliency data resiliency has become really important. I mean, as an example, last year at VM World Show floor, I actually counted the number off backup vendors compared to storage vendors. And there was actually more data protection and resiliency vendors on the floor. Then they were actually storage. Wentz. >>Yeah, Deepak here. You're absolutely right. We saw that, you know, for for years we used to call it storage world because they had all come in partner with VM Ware. But data protection. So So eso important here when one of the big conversations this year, of course, is that rollout of Project Pacific with VCR 77 update one just right, right ahead of the M world. Uh, I'm assuming Veritas is just keeping in lockstep with vm ware, but, you know, talk a bit about you know how that fits into the portfolio. >>Oh, absolutely. So, uh so one off the keys for veritas success over the last 20 years, uh, is that we have kept up with all the technology transformations and all the technology disruptions that happened. And as these hybrid cloud disruption that happening with you mentioned Project Pacific. But you know that it's the 10 zoo platform we are. We are one off the design partners with VM ware for to ensure the data protection layers are done correctly. Eso So we are definitely working with VM ware on the on the Chenzhou uh, resiliency as well as leveraging the Valero platform. So we'll make sure that as a customers are deploying these new solutions the Veritas Solutions out there or or to offer them the resiliency and data protection needed >>Deepak, we've watched that that real maturation of what VM was doing in the cloud, of course, the partnership, you know, first with IBM at VM World a few years ago, right after VM world, it was with a W s. And there was a lot of interest. But we are seeing that customer adoption. I wonder if you talk about how closely you worked with them. Do you have any, you know, maybe anonymous customers that you talk about? You know what they're seeing in the cloud? Why vm ware and Veritas went when they go to this environment. >>Yes. So I'll we have several customers who are moving into the cloud space, uh, leveraging VMC or now with the azure reimburse solutions. So what happens is when these customers we have large financials, for example, who are using now we anywhere and migrating their workloads into the cloud have eso. So they may be deploying virtual machines there. But the need for H A and data resilience in backup actually gets a little bit more complex because the old environments are still there on prime. Some workloads are now moving to the cloud, and they're leveraging The Veritas Solutions want to support the migration. Second, to offer the resiliency, leveraging the Veritas resiliency platform or net backup overeaters input scale. An example is I'll use an example of an air one airline customer reservation systems now moving to KWS within two availability zones. The application availability comes with the Veritas solution. So Veritas is Prue is on their journey to the cloud helping enterprise customers work in these hybrid use cases. >>Deepak, since you've got so many customers and they're going through their cloud journeys, uh, Veritas works across all the environment. You get a good view point as to where we are. One of the things we're really trying to help clarify people. We throw out these terms Hybrid cloud and multi cloud. Most customers I talked to we have a cloud strategy and you use more than one cloud. Yes. Is portability the big concern? Well, no, I'm not moving things all over the time. I don't wake up and say, you know, I'm checking the stock market and therefore I'm gonna, you know, move toe one of the other, but I need tohave my multiple environment. It's difficult on them with different skill sets. Uh, and you know, we're seeing, you know, companies like Veritas and VM where, you know, living where the customer is. So give us a little insight as toe what you're seeing from the customers, this whole hybrid, multi cloud environment. What? What does it mean to to your customers? >>Eso what? What? And says, You know, we have a variety of customers and, you know, invariably, when we talked to them, each one of them has, ah, little bit different journey to the cloud. I you know, some customers I'd say maybe more mid market. Want to move completely towards ah platform as a service approach and leverage either azure or a W s. Uh, but I'll say most of the enterprise customers are looking at, uh, taking workloads. It could be one of the applications. Some are further ahead in the journey, and they're taking now a mission Critical application. Okay, You know, it could be and s a p workload. It could be a thumb mission critical, you know, building system reservation systems and then using VM ware as the mechanism to go into the cloud with it and and and And when they do that, they're looking for the same level and same level of tools for both availability and data protection. Eso I'll say that we have lots of different examples between utilities, healthcare companies, financials, government. Yeah, who are ill say the common theme is now they're moving towards. I'll say the harder workloads are now moving to the cloud. And now they're absolutely leveraging tools from where eaters. They want to make sure that our solutions actually support those complex and highly scalable use cases. And we're absolutely doing that with the solutions. >>Deepak, you talk about some of the challenges that customers have. You know, some things have changed in 2021 thing that has not changed eyes that security is top of mind. We often see the, you know, data protection and security. Some of those pieces go hand in hand. I remember years ago talking at at the Veritas conference, it was G, D, p. R. And Ransom. Where were the big things that we talked about with every single customer as to how they were defending and preparing for that? So give us, give us the state of your environment. We know that even when everybody's working from home, unfortunately, the bad actors they're actually working over telling >>No. Yes. So I'll see the problem off. Ran somewhere has actually gotten a whole lot worse over the last couple of years. Uh, so, Aziz, we think about ransom where, uh, we have the security layer, which means, you know, first is you have to make sure your infrastructure is protected. You know, the second layer is detection. Which means how do you know if there's ransomware sitting in your environment? Because it could have come in and it may actually click in at a much later time, and the third is recovery. And to be able to recover, you need really good data protection and back up policies within the companies were able to recover it. So, of course, uh, most companies invest a lot in the security software, but we know that ransomware still get sent. It can get into a phishing attack. It can get into email some one off the employees at home clicks on something. You know, Ransomware is in eso the backup, and the data protection is the last line of defense from to be able to recover. So now you have it. You're stuck. What do you do? You want to find the last best copy, uh, be able to recover very, very quickly, and and the problem is is really serious. I was actually talking to my one off our tech support leaders, and we get at least one color day with one of our customers that have been hit with ransom er and we helped them through the recovery process s Oh, that's a heavy investment area for Veritas. Without that backup software backup exact software, but also with the hardened very terse appliances. We provide a very solid way for our customers to be able to protect and recover from Ransomware. The only thing I suggest is you know, once you have been hit at and if you don't have a good backup you know, I talked about that huge. Just state that entire state has to be protected also from ransomware, which means standardization is key. So when something happens, are you going to look at nine products to recover from or you want all your catalogs, all your data, all your insights in one place, so you can then go quickly, come back online and not have to pay the ransom? >>All right. Well, Deepak, let's let's bring it home. We're here at VM World. We we talked at the beginning about the long partnership. You were there, you know, Day zero with the VCR seven activity. What do you want people to take away from VM World 2020. When it comes to Veritas, >>I'm a key message. Tow our mutual customers as that veritas is here to support your journey to the hybrid cloud to the cloud. We are investing heavily in the solutions we Our goal is to continue providing today zero support for all we end where solutions and releases. And we're working very closely with VM ware on the 10 zoo platform rollout. We have a design partner with me and were there as well as leveraging the right AP eyes, whether to be a d. P. V i o P sent were certified on every latest versions off the VM Ware portfolio. We have several 100 engineers that work the just to make sure that we support these platforms, you know, in additional say's as the women were connects toe aws and to azure. Those solutions are also extremely well certified. So where it'll works very closely with AWS we were the first to be certified on the the AWS solutions. >>Uh, you're you're you're talking about like outposts, I believe. >>Oh, yes. Outpost. Yeah, so we just got the outpost ready. Certification, you know, works extremely well with the reimburse solutions. A swell Aziz A V s, uh, azure reimburse solutions so heavy areas off investment for us. So the same way that our customers have depended on us over the last 20 years. We are writing the technology disruptions to help our customers into the next wave with the same set off solutions working both on prime hybrid and clouds. >>Yeah, Deepak, I'm having flashbacks. You and I remember the things when it was the V x f s and the Vieques VM. And now we've got the, uh you know, uh, you know all the very the VM Ware versions on A V s and Google Cloud VM Ware engine. It gets a little confusing out there. But, hey, I really appreciate you giving us some clarity as to how you're helping customers with their their data resiliency supporting and ransomware and the deepen long partnership that Veritas and VM Ware have. Thanks so much for joining us. >>Thank you. Thank you. Stew. >>Alright, Stay tuned. Lots more coverage from VM World 2020. I'm stew minimum and thank you for watching the Cube

>>from around the globe. It's the Cube with digital coverage of Miranda's launchpad 2020 brought to you by more antis. >>Hi, I'm stupid man. And this is the cubes coverage of Miran Tous Launchpad 2020. Happy to welcome to the program First time guest William Do places. He's the head of customer success in operations with Miran Tous William. Thanks so much for joining us, >>Steve. Thanks for two. Thanks for having me. >>Yeah, why don't we start with a little bit? You know, customer success operations. Tell us what that's entail, What's what's under your purview, Right? >>So is everything basically, you know, post sales, right? So after a customer has portions, their their subscription, we basically take it from there Going forward, you know, looking after the relationship with the customer, ensure they you know, the whole, you know, subscription fulfillment element off it. Whether that is just bored with that is to cut the relationship management from a post sales perspective and so on, so forth. So that is basically into end from the point off purchase to the renewal face. Would would would fall with any supporting operations. >>Well, that's such an important piece of the whole cloud conversation. Of course, people, you know, we talked for such a long time cap ex op X. We talk about descriptions and manage services. Of course, has been a riel. You know, growth segment of the market place. Love to hear a little bit, you know, What are you hearing from your customers? And, you know, give us the lay of the land As to the various options that that that Miranda is offering today and we'll get into any of the new pieces also. >>Yeah. So the the the options that we're making available for our customers primary called Prod Care, which is a 24 7 mission critical support subscription. Andi Ops Care, which is a fully managed service offering. Um, what we hear from our customers is is, you know, the the the notion of having a development environment and a production environment with different, you know, sls and entitlements and so on. You know that that that notion is disappearing because your divots chain or pipeline is all connected. So you could just think for yourself. If you have a group of developers like 50 or 100 or 1000 developers that are basically standing there still, because they cannot push code because there's a problem or a new issue on the development cloud. But the development cloud is not. Beings is not seen or is treated as a mission critical platform. You know, those developers are standing date stole, so that is a very expensive problem for a customer at that point in time, so that the whole chain, the whole pipeline that makes part off your your develop cycle, should be seen as one entity. And that's what we've seen in the market at the moment that we're realizing with a large customers that are really embracing the kind of the approach to modern applications. Andi. This is why we're making these options available. Thio, our Doctor Enterprise customers We've been running with them for quite a while on the on the Miranda's cloud platform, which is our Infrastructures service offering on. We've had some great success with that, and we now in a position to make that available to our customers. So it's really providing a customer that true enterprise mission critical regardless of time off they the day of the week availability off support whether that is a my question or whether that is really an outage or a failure. You know, you know, you've got that safety net that is that is online and available for you. Thio to sort Whatever problem you have about, you know, that is from the support perspective, you know. And if we go over into the manage service offering we have for on up Skate that is a really hardened Eitel based, um infrastructure or platform as a service offering that we provide eso. We've had some great success. Like I said on the on the Miranda's cloud platform Peace. And we're now making that available for Doc Enterprise customers as well. So that is taking the whole the whole chain through. We look after the the whole platform for the customer and allow the customer to get on with what is important to them. You know, how do they develop their applications? You know, optimize that for their business instead, off spending their times and keep spending their time on keeping the lights on, so to speak, you know? So we take care of all of that. They have that responsibility over to us on DWI. We manage that as our own and we basically could become an extension of their business. So we have a fully integrated into the environment, the whole logging and not monitoring piece we take over the whole life cycle. Management off the environment. We take over, we do the whole change Management piece Incident Management Incident Management piece on. This whole process is truly transparent to the customer. At no point are they, you know, in the dark what's going on where we're going and we have the and the whole pieces wrapped around Bio customer success Manager which is bringing this whole sense off ownership Onda priority. That customer, you've got a single point of contact that is your business partner and that the only piece, the only metric that that individuals measured on is the success off that customer with our our product. So that in a nutshell, at a very high level what these are. But these offerings are all about >>well, we all know these days how important it is toe, you know, make your developers productive. It's funny listening to you, I think back to the Times where you talked about making sure that it's mission critical environment You know, years ago it was like, Oh, well, the developer just gets whatever old hardware we have, and they do it on their own. Now, of course, you know you want Dev in production toe have a very similar environment. And as you said, those manage services offering and be, you know, so important because we want to be able to shift left, let my platform let my vendors take care of some of the things that's gonna be able to enable me to build my new applications toe, respond to the business and do. In fact, I don't want my developers getting bogged down. So do you have any, You know, what are some of the successes there? How do your customers measure that? They Hey, I'm getting great value for going to manage service. Obviously, you know, you talked about that, That technical manager that helps them there. Anybody that's used, you know, enterprise offerings. There's certain times where it's like, Hey, I use it a lot. Other times it's it's just nice to be there, but, you know, why do you bring us in a little bit? Some of the customers, obviously anonymous. You need Teoh you know, how do they say, You know, this is phenomenal value for my business. >>Yes, it's all. It's all about the focus, right? So you're the customer. 100% focus on what is like I said, important to them, they are not being distracted at any point for, you know, on spending time on infrastructure related or platform related issues they purely focused on. Like I said, that is, that is important to their business. Andi, The successes that we see from that it is, is that we have this integration into into our customers like a seamless approach. We work with them is a true, transparent approach to work with our customers. There's a there's an active dialogue off what they developers want to see from the environment, what the customers want to see from from from the environment, what is working well, what we need to optimize. And that is really seeing ah, really good a approach from from from us and we're seeing some some great successes in it. But it all comes down to the customer is focusing on one thing, and that is on what is important to them on. But is there business instead off. You know, like you said, focusing on the stuff that shoot me, that that should be shift left. >>Yeah. And will, um, is there anything that really stands out when you talk about that? The monitoring that you in the reporting that you give the customers Is it all self serve? You know, how did they set that up and make sure that I'm getting valuable data. That's what what my company needs. >>Yes. So that is where your custom success manager comes in is really how to customize that approach to what fit for the customers. So we've got it in the background, very much automated, but we do the tweaks Thio customize it for for the customer that makes sense for them. Some customers want to see very granular details. Other customers just want a glance over it and look at the the high level metrics what they find important. So it is finding that balance and and understanding what your customer find important, and then put that in a way that makes sense for them Now. That might sound might sound kind of obvious, but it's more difficult than you think to put data from the customer That makes sense to them, uh, in their in their context. And then, you know, be in a position where you can take the information that you receive and give your customer the the runway to plan their the application. You know, where are they trending? So be able. Dutilleux. Look. 3452 quarters 345 months to quarters ahead to say this is where you're going to be. If you continue down this path, we might need to look at shifting direction or shift workload around or at Resource is or or, you know, depending on the situation. But it's all about having that insight going forward, looking forward. Rather, um, instead off, you know, playing things by year end, looking, looking at the year. And now because then that ISS that is done and dusted, really. So it's all about what is coming down the line for us and then be able to to plan for it and have an educated conversation of with with with your customer where they want to go. >>You mentioned that part of this offering is making this available for the Docker Enterprise base. Uh, maybe, if you could explain a little bit as to you know, what's gonna be compelling for for those customers. You know what Laurentis is has built specifically for that base? >>Yeah. So, like I said, this is an offering we have available on our Miranda's cloud platform for quite a while. You've seen some great success from it. Um, we're making it now available for the Doctor Enterprise customers. So it is really a true platform as a service offering, um, on your infrastructure of choice, whether that is on prim or whether that is on public cloud, we don't really care. We'll work with customers whichever way it is. And yeah, Like I said, just give that true platform as a service experience for our customers, Onda allow them to to focus on what's important to them. >>Alright, let me let you have the final word. Will tell us what you want your customers to understand about Iran tous when they leave launchpad this year. >>Yeah, So the main thing the main theme that I want to leave with is is that you know, the the we've made significant progress over the last 62 229 months on the doc enterprise side on. We're now in a position where we're taking the next step in making these offerings available for our customers, and we're really for the customers. That's the handful of custom that we have already. My greater to these offerings with getting some really good feedback from them on it is really helping them just thio thio just to expedite. They they, you know, wherever they're gonna go, whatever they want to want to achieve the, you know, expedite, think goals on bond. It is really there to ensure that we provide a customer or customers a true, um, you know, mission critical feeling, uh, giving them the support they need when they needed at the priority or the severity or the intensity that they need as well as they provide them. The ability to to focus on what is important to them on board. Let us look after the infrastructure and platform for them. >>Well, well, okay. Congratulations on Although the work that the team's done and definitely look forward to hearing more in the future. >>Excellent. Thank you very much for your time. >>Be sure to check out all the tracks for Miranda's launchpad 2020 of course. Powered by Cuba 3. 65. Got the infrastructure. The developers Lots of good content. Both live and on demand. And I'm still minimum. Thank you for watching. Thank you.

>> From theCUBE studios in Palo Alto in Boston, connecting with thought leaders around the globe, these are cloud native insights. >> Welcome to another episode of Cloud Native Insights. I'm your host Stu Miniman and of course with Cloud Native Insights will really help understand you know, where we have gone from cloud, how we are taking advantage of innovation, a real driver for what happens in the spaces of course developers. You think back to the early days, it was often developers that were grabbing a credit card, using cloud services and then it had to be integrated into what was being done and the rest of the organization saw the large rise of DevOps and all the other pieces around that, that help bring in things like security and finance and the like. Happy to welcome to the program first time guest, William Janssen. He is the CEO of DeltaBlue. Deep in this discussion of cloud native DeltaBlue is a European company helping with continuous deployment across cross cloud providers in the space. William, thanks so much for joining us, nice to see you. >> Glad to be on the show, thank you Stu. >> All right, so one of the reasons I'm glad to have you on is because of some of the early episodes here, you know we were discussing really what cloud native is and what it should be. I had my first interview on the program, Joep Piscaer, who you know, had given the analogy and said when you talked about DevOps, DevOps isn't something you could buy. But it's something that lots of vendors would try to sell you. And we're trying to dispel, lots of companies out there, they're like, "Oh, cloud native, well we support Kubernetes. "And we have this tool and you should buy our cloud native, "you know, A, B, C or D." So, want to start a little first with what you see out there and what you think the ultimate goal and outcome of cloud native should be? >> I think cloud native, to start with your last question, I think cloud native should make life fun again. We have a lot of technical problems, we solve them in technical things. You mentioned Kubernetes but Kubernetes is solving a technical problem. And introducing another technical problem. So what I think cloud native should do is focus on what you're actually good at. So a developer should develop. Someone from the infrastructure, an operator, should focus on their key points and not try to mix it up. So, not Kubernetes, Kubernetes is again introducing another technical issue. Our view on cloud native is that people should have fun again and should be focusing on what they're good at. And so it's not about technology, it's about getting the procedures right and focusing on the things you love to do. And not to talk to the cross border, talk to a lot of developers and solve operational kind of things. That's what we try to solve and that's our view of cloud native. >> Yeah, I'll poke that a little bit because one thing you say, people should do what they're good at. It's really what is important for the business, what do we need to get done? There's often new skills that we need to do. So it's really great if we could just keep doing the same thing we're doing. We know how to do it. We optimize it, we play with all of our geek knobs. But the drumbeat that I hear is, we need to be agile, we need to be able to create new applications. IT needs to be responsive for the business and rather than in the past it was about, building this beautiful stack that we could optimize and build these pieces together. Today, the analogy I hear more is, there's layers out there, there's lots of different tooling, especially if you look at the developer world. There is just too many options out there. So, maybe bring us a little bit as to you know, what DeltaBlue does. How you look at allowing developers to build what they, new things that they need but not be, I guess the word, locked into a certain place or certain technology. >> Yes, I've been on IT for 20 years. So I've seen a lot of things go around. And when we started out with DeltaBlue, the only thing we had in mind is how could we make the lifecycle of applications and all the things you had to do, the government around applications way more easy. Back in the days, we already saw that containerization solved some of the issues. But it solves technical issues. So like when you start coding, you don't need to go to the network card anymore. We took the same approach to our cloud native approach. So we started on the top level. We started with applications in mind. And the things back in the day you had Bitnami already had the option to have a VM or standard installation of an application. So what we see is that nowadays, many developers and many organizations try to focus on that specific part, how to get your code into some kind of under configuration solution. We take that for granted. There are so many great solutions out there, already tried to solve that problem. So instead of reinventing that wheel again, we take that for granted. But we take another approach. We think that if the application is there, you need to test it. You need to take it into production. You want to have several versions of a specific application into the production environment. So what we've tried to solve with our platform is to make that part of the life cycle, let's call it horizontal version of your application lifecycle, not getting an application built or running up different stuff, we take that for granted. We take the horizontal approach. How to get your traditional application from your development environment to your testing, acceptance. That's a different kind of people test your application, security testing before you take it into production. And that should be all be done from a logical point of view. So we built one web interface, a logical portal. And you can simply drag and drop any type of application, not just a more than micro service oriented or Kubernetes based application but any type of application from your acceptance environment to your production environment. That's going to solve the real problem. So now, any business can have 10 different acceptance environments for even your old legacy SAP or your Intershop environment. That's going to get your business value. So going back to your definition of cloud native, getting that kind of abstraction between getting your and code your application and get it get somewhere up and running and all the stuff that's needs to be done from your development environment into the production environment. That's going to add to your business value. That's going to speed up your time to market, that's going to make sure that you have a better cloud quality because now you can test even your legacy application from 10 different points of view and 10 different types of different branches, all in a parallel environment. So, when we started with DeltaBlue, we took a different approach, took the technical stuff for granted, and focus on all the government around applications and the governance that's the thing, I think that's the most important part in the cloud native discussion. >> So governance, especially in Europe, has a lot of importance there. If you could, bring us inside a little bit, customers you're talking to, where they are in this journey. If you've got an example of something you're doing specifically we'd love to hear how that happens in real world. >> Yes we have many different customers but I think one of our best examples, for example is Wunderman Thompson, a big eCommerce party across the globe but also here in the Netherlands. And we made a blueprint of their development environment the way they develop application and the way they host applications. So, now they started a new project, 40 developers go to the new big eCommerce application. In the past, everyone had to install their own Intershop environment on their own laptop, Java, Oracle, that kind of stuff. It took me a day and a half. Since we abstracted that into like a simple cell, like you would do in any serverless environment nowadays, they can now simply click on a button. And since they made their laptop or their development environment part of our platform, they can now simply drag and drop the complete initial environment to the laptop and they can send development in 10 minutes instead of a day and a half. That's just the first step that makes their life easier. But also imagine, we have an application up and running for two, three months and our security patch, we all know the trouble of getting a patch installed in production but also then install it into the acceptance environment, test environment, development environment, all those kind of different versions. With our platform, since we have the application in mind, we can, with simple one simple click of the button, we can propagate that security patch across all the different environments. So from a developer point of view, there's no need to have any kind of knowledge of course they need to configure a port or something like that but no need of knowledge of any type of infrastructure anymore. We have made the same blueprint for the complete development environment. So with a single click of the button, they have a complete detail environment, known over the need to go to their infrastructure to get the service to their operating guys, they have them installed, industrial Nexus, very book of repository, all that kind of stuff. It's all within one blueprint. So again, we think that the application should come first. That should be abstracted, and not abstracted just in a single spin up a container or spinning up a VM. Now, the complete business case, application, complete environment should be up and running with a single click of a button. So now they can start if they have a demo tomorrow, for example, and they want to have a demo setup. With a single click, they have a complete environment up and running, instead of having to wait three weeks, four weeks before they can start coding. And the same comes with a production environment. We now have an intelligent proxy in front of it. So they can have three different versions of the same shot in their production environment. And based on business rules, we can spread the load against the different versions of a business application, eCommerce application. We signed a new contract with New Relic last week. And the next thing we're going to do, and it's going to be there in two weeks, is fit New Relic data, I mean, an eCommerce application is about performance. A longer response time of a page page load time will drop your drop your revenue. So what we're going to do with New Relic is feed it's performance data back into that the intelligent proxy in front of their application. So now they're going to drop the new version of their intershop application on a Thursday evening, they go to sleep. Friday morning, they wake up and from the three versions, and the best performing website will be up and running. That's the kind of intelligence and that's the kind of feedback we can put into our platform since we started with applications in mind first. It's getting better quality, because you can do better testing. I mean, we all want to test, but we never want to wait for those different kinds of setups, they want to have fast development cycles. That kind of flexibility where you do the functional deployment, the functional release, not the technical stuff. What we now see in the market is that most people, when they go to the cloud, try to solve the technical release problems of getting the application up and running in a technical way into the production time, we try to focus on the functional level. >> So, William, being data driven, a very important piece of what you talked about there. What I want to help our audience understand is concerns about if you talk about abstractions, or if you want to be able to live across different environments, is can you take advantage of the full capabilities of the underlying platform? Because, that is, one of the reasons we go to cloud isn't just because it's got limitless compute Pricing comes down. But there's only new features coming out, or I want to be able to go to, a cloud provider and take advantage of some specific feature. So help us understand how I can live across these environments, but still take advantage of those cloud native features and innovations as they come out. >> Great. There are actually two ways. For most alternatives, we also have an alternative component in our platform as well. We have complete marketplace with all kinds of functionality like AWS has, but I can imagine that people want to develop an AWS and get our AWS lambda functions or s3 buckets or that that kind of specific functionality. And going back to the Intershop example, they run their application as a CaaS solution on Azure. So when you went to Azure DevOps, or that kind of specific functionality included, our platform connects over 130 different data centers across the globe and Azure and AWS, and Oviedo Digital Ocean are all part of the huge mix of different cloud providers. For every provider, we have what we call gateway components. We deploy natively, mostly bare metal or equivalents of bare metal within those cloud providers. And we made an abstraction layer on the network layer. So now we can include those kind of specific services like they were part of our platform natively. Because if we would have just build a layer and couldn't use the specific components of an AWS or an Azure or that kind of stuff, we would just be another hosting provider. I haven't liked VMware. So that kind of stuff. We want to and we are aware that we need to include a specific stuff, functionality. And what we do with this with what we call gateway components. So we have AWS, gay components, educators, but also for IBM, or Google specific environment. So we can combine the network of AWS, with our specific network. And that's possible, because we made a complete abstraction layer between the network of the infrastructure provider and our network. So we can complete IP subnets DNS resolver as if it was running on their local environment. And thereby, since we have that abstraction layer, we can even move the workloads on AWS to Azure. And since we have the abstraction layer network, we can even make sure that you don't need to reconfigure your application. I think that's the flexibility that people are looking for. And if they have a specific workload and Azure and it's getting too expensive, for the ones that includes AWS stuff, they want to shift the workload to different kind of cloud providers based on the characteristics of a specific worker, or even if you want to have the cheapest option, you can even use your on premise data center. >> William, do that there absolutely is interest in doing that. One of the barriers to being able to just go between environments is of course that the skills required to do this. So, there's something to be said about, if I use a single provider, I understand how to do it, I understand how to optimize it, I understand the finances of it. And while there may be very similar things in another cloud, or in my own data center, the management tools are different and everything. So how do we overcome, that skill set challenge, between different environments. >> We had a different approach the same as we do it on application level, we took it also in data center level, so we're going to handle most cannot say all because there's always specific components. But from our interface, you can simply go to a specific application and select the type of data center you want to run on your application. And if your application is running on an AWS, you get the gateway components with the components, like an s3 bucket or a lambda or an RDS, based on the data center you're running in. So we took that abstraction layer even on that level. But I got to be honest, I think 80% of our customers is not interested in the data center, they run their application in unless they have specific functionality, and which is not available on our platform, or they have a long running application, or use a specific or they bought a specific application. Otherwise, they don't care. Because from a traditional application, there is no difference between running on Azure or Google Cloud or an IBM cloud or whatever. The main difference is that we can make a guarantee about the SLA. I mean, IBM has a better uptime guarantee. A better performance and a better network compared to let's say, digitalocean. Kind of set this up. But there is a huge difference. But it's more like the guarantee that we can give them. So we have this abstraction layers, and we try to put as many as possible as much as possible into our portal interface. There will no way that we're going to redesign and we work about the complete AWS interface, or we're not going to include 100% of their functionality. That's not possible. We're, small company. AWS is somewhat more developers in place. But the main components and people are asking for like RDS or these kind of specific setups, that's where we have the gateway components for available and they can include them into their own application. But we also going to advise them why they were looking for those specific AWS components. Is it within the application architecture or is it something gauges right? Isn't there a better solution or an other solution? And I think, since we have that objection that one of the biggest benefits is, and what we see our customers also do is we incorporate that data center into our platform. And we have one huge network across all the cloud providers and including their own data center. So in the past, they had to have two different development teams, one specialized in AWS development, with all that kind of specific stuff. And all one development team which had more like a traditional point of view, because their internal system and data which was not allowed to go outside the company or had to stay within the firewall. And since we have now one big network, which is transparent to them, we can make sure that their code for their internal systems stays internal and is running on internal systems. But we could still use some kind of functionality from the outside. We do it all unencrypted today, and we have one big platform available. So with our gateway components, we can make sure that that data and application data is really staying internally. And only is allowed to grow internal data access and that kind of stuff, but still use external functionality or price. But again, I would say 80% of our customers, they don't care because they just want to get rid of the burden. I think going back to what we think cloud native means is just getting rid of the burden. And you shouldn't be concerned about what type of cloud we're actually using. >> Absolutely, William, the goal of infrastructure support, my applications and my data and we want companies to be able to focus on what is important for the business and not get bogged down and certain technical arguments introduction. So William, thank you so much for joining us. Really great to hear about Delta blue. Looking forward to hearing more in the future. >> Thank you. >> I'm Stu Miniman. And look forward to hearing more of your cloud native insights.