Upbeat music plays >> Voice Over: TheCUBE presents Ignite 22, brought to you by Palo Alto Networks. >> Good morning everyone. Welcome to theCUBE. Lisa Martin here with Dave Vellante. We are live at Palo Alto Networks Ignite. This is the 10th annual Ignite. There's about 3,000 people here, excited to really see where this powerhouse organization is taking security. Dave, it's great to be here. Our first time covering Ignite. People are ready to be back. They.. and security is top. It's a board level conversation. >> It is the other Ignite, I like to call it cuz of course there's another big company has a conference name Ignite, so I'm really excited to be here. Palo Alto Networks, a company we've covered for a number of years, as we just wrote in our recent breaking analysis, we've called them the gold standard but it's not just our opinion, we've backed it up with data. The company's on track. We think to do close to 7 billion in revenue by 2023. That's double it's 2020 revenue. You can measure it with execution, market cap M and A prowess. I'm super excited to have the CEO here. >> We have the CEO here, Nikesh Arora joins us from Palo Alto Networks. Nikesh, great to have you on theCube. Thank you for joining us. >> Well thank you very much for having me Lisa and Dave >> Lisa: It was great to see your keynote this morning. You said that, you know fundamentally security is a data problem. Well these days every company has to be a data company. Grocery stores, gas stations, car dealers. How is Palo Alto networks making customers, these data companies, more secure? >> Well Lisa, you know, (coughs) I've only done cybersecurity for about four, four and a half years so when I came to the industry I was amazed to see how security is so reactive as opposed to proactive. We should be able to stop bad threats, right? as they're happening. But I think a lot of threats get through because we don't have the right infrastructure and the right tooling and right products in there. So I think we've been working hard for the last four and a half years to turn it around so we can have consistent data flow across an enterprise and then mine that data for threats and anomalous behavior and try and protect our customers. >> You know the problem, I wrote this, this weekend, the problem in cybersecurity is well understood, you put up that Optiv graph and it's like 8,000 companies >> Yes >> and I think you mentioned your keynote on average, you know 30 to 40 tools, maybe 50, at least 20, >> Yes. >> from the folks that I talked to. So, okay, great, but actually solving that problem is not trivial. To be a consolidator, I mean, everybody wants to consolidate tools. So in your three to four years and security as you well know, it's, you can't fake security. It's a really, really challenging topic. So when you joined Palo Alto Networks and you heard that strategy, I know you guys have been thinking about this for some time, what did you see as the challenges to actually executing on that and how is it that you've been able to sort of get through that knot hole. >> So Dave, you know, it's interesting if you look at the history of cybersecurity, I call them the flavor of the decade, a flare, you know a new threat vector gets created, very large market gets created, a solution comes through, people flock, you get four or five companies will chase that opportunity, and then they become leaders in that space whether it's firewalls or endpoints or identity. And then people stick to their swim lane. The problem is that's a very product centric approach to security. It's not a customer-centric approach. The customer wants a more secure enterprise. They don't want to solve 20 different solutions.. problems with 20 different point solutions. But that's kind of how the industry's grown up, and it's been impossible for a large security company in one category, to actually have a substantive presence in the next category. Now what we've been able to do in the last four and a half years is, you know, from our firewall base we had resources, we had intellectual capability from a security perspective and we had cash. So we used that to pay off our technical debt. We acquired a bunch of companies, we created capability. In the last three years, four years we've created three incremental businesses which are all on track to hit a billion dollars the next 12 to 18 months. >> Yeah, so it's interesting on Twitter last night we had a little conversation about acquirers and who was a good, who was not so good. It was, there was Oracle, they came up actually very high, they'd done pretty, pretty good Job, VMware was on the list, IBM, Cisco, ServiceNow. And if you look at IBM and Cisco's strategy, they tend to be very services heavy, >> Mm >> right? How is it that you have been able to, you mentioned get rid of your technical debt, you invested in that. I wonder if you could, was it the, the Cloud, even though a lot of the Cloud was your own Cloud, was that a difference in terms of your ability to integrate? Because so many companies have tried it in the past. Oracle I think has done a good job, but it took 'em 10 to 12 years, you know, to, to get there. What was the sort of secret sauce? Is it culture, is it just great engineering? >> Dave it's a.. thank you for that. I think, look, it's, it's a mix of everything. First and foremost, you know, there are certain categories we didn't play in so there was nothing to integrate. We built a capability in a category in automation. We didn't have a product, we acquired a company. It's a net new capability in instant response. We didn't have a capability. It was net new capability. So there was, there was, other than integrating culturally and into the organization into our core to market processes there was no technical integration needed. Most of our technical integration was needed in our Cloud platform, which we bought five or six companies, we integrated then we just bought one recently called cyber security as well, which is going to get integrated in the Cloud platform. >> Dave: Yeah. >> And the thing is like, the Cloud platform is net new in the industry. We.. nobody's created a Cloud security platform yet, so we're working hard to create it because we don't want to replicate the mistakes of the past, that were made in enterprise security, in Cloud security. So it's a combination of cultural integration it's a combination of technical integration. The two things we do differently I think, than most people in the industry is look, we have no pride of, you know of innovations. Like, if somebody else has done it, we respect it and we'll acquire it, but we always want to acquire number one or number two in their category. I don't want number three or four. There's three or four for a reason and there still leaves one or two out there to compete with. So we've always acquired one or two, one. And the second thing, which is as important is most of these companies are in the early stage of development. So it's very important for the founding team to be around. So we spend a lot of time making sure they stick around. We actually make our people work for them. My principle is, listen, if they beat us in the open market with all our resources and our people, then they deserve to run this as opposed to us. So most of our new product categories are run by founders of companies required. >> So a little bit of Jack Welch, a little bit of Franks Lubens is a, you know always deference to the founders. But go ahead Lisa. >> Speaking of cultural transformation, you were mentioning your keynote this morning, there's been a significant workforce transformation at Palo Alto Networks. >> Yeah >> Talk a little bit about that, cause that's a big challenge, for many organizations to achieve. Sounds like you've done it pretty well. >> Well you know, my old boss, Eric Schmidt, used to say, 'revenue solves all known problems'. Which kind of, you know, it is a part joking, part true, but you know as Dave mentioned, we've doubled or two and a half time the revenues in the last four and a half years. That allows you to grow, that allows you to increase headcount. So we've gone from four and a half thousand people to 14,000 people. Good news is that's 9,500 people are net new to the company. So you can hire a whole new set of people who have new skills, new capabilities and there's some attrition four and a half thousand, some part of that turns over in four and a half years, so we effectively have 80% net new people, and the people we have, who are there from before, are amazing because they've built a phenomenal firewall business. So it's kind of been right sized across the board. It's very hard to do this if you're not growing. So you got to focus on growing. >> Dave: It's like winning in sports. So speaking of firewalls, I got to ask you does self-driving cars need brakes? So if I got a shout out to my friend Zeus Cararvela so like that's his line about why you need firewalls, right? >> Nikesh: Yes. >> I mean you mentioned it in your keynote today. You said it's the number one question that you get. >> and I don't get it why P industry observers don't go back and say that's, this is ridiculous. The network traffic is doubling or tripling. (clears throat) In fact, I gave an interesting example. We shut down our data centers, as I said, we are all on Google Cloud and Amazon Cloud and then, you know our internal team comes in, we'd want a bigger firewall. I'm like, why do you want a bigger firewall? We shut down our data centers as well. The traffic coming in and out of our campus is doubled. We need a bigger firewall. So you still need a firewall even if you're in the Cloud. >> So I'm going to come back to >> Nikesh: (coughs) >> the M and A strategy. My question is, can you be both best of breed and develop a comprehensive suite number.. part one and part one A of that is do you even have to, because generally sweets win out over best of breed. But what, how do you, how do you respond? >> Well, you know, this is this age old debate and people get trapped in that, I think in my mind, and let me try and expand the analogy which I tried to do up in my keynote. You know, let's assume that Oracle, Microsoft, Dynamics and Salesforce did not exist, okay? And you were running a large company of 50,000 people and your job was to manage the customer process which easier to understand than security. And I said, okay, guess what? I have a quoting system and a lead system but the lead system doesn't talk to my coding system. So I get leads, but I don't know who those customers. And I write codes for a whole new set of customers and I have a customer database. Then when they come as purchase orders, I have a new database with all the customers who've bought something from me, and then when I go get them licensing I have a new database and when I go have customer support, I have a fifth database and there are customers in all five databases. You'll say Nikesh you're crazy, you should have one customer database, otherwise you're never going to be able to make this work. But security is the same problem. >> Dave: Mm I should.. I need consistency in data from suit to nuts. If it's in Cloud, if you're writing code, I need to understand the security flaws before they go into deployment, before they go into production. We for somehow ridiculously have bought security like IT. Now the difference between IT and security is, IT is required to talk to each other, so a Dell server and HP server work very similarly but a Palo Alto firewall and a Checkpoint firewall Fortnight firewall work formally differently. And then how that transitions into endpoints is a whole different ball game. So you need consistency in data, as Lisa was saying earlier, it's a data problem. You need consistency as you traverse to the enterprise. And that's why that's the number one need. Now, when you say best of breed, (coughs) best of breed, if it's fine, if it's a specific problem that you're trying to solve. But if you're trying to make sure that's the data flow that happens, you need both best of breed, you know, technology that stops things and need integration on data. So what we are trying to do is we're trying to give people best to breed solutions in the categories they want because otherwise they won't buy us. But we're also trying to make sure we stitch the data. >> But that definition of best of breed is a little bit of nuance than different in security is what I'm hearing because that consistency >> Nikesh: (coughs) Yes, >> across products. What about across Cloud? You mentioned Google and Amazon. >> Yeah so that's great question. >> Dave: Are you building the security super Cloud, I call it, above the Cloud? >> It's, it's not, it's, less so a super Cloud, It's more like Switzerland and I used to work at Google for 10 years, not a secret. And we used to sell advertising and we decided to go into pub into display ads or publishing, right. Now we had no publishing platform so we had to be good at everybody else's publishing platform >> Dave: Mm >> but we never were able to search ads for everybody else because we only focus on our own platform. So part of it is when the Cloud guys they're busy solving security for their Cloud. Google is not doing anything about Amazon Cloud or Microsoft Cloud, Microsoft's Azure, right? AWS is not doing anything about Google Cloud or Azure. So what we do is we don't have a Cloud. Our job in providing Cloud securities, be Switzerland make sure it works consistently across every Cloud. Now if you try to replicate what we offer Prisma Cloud, by using AWS, Azure and GCP, you'd have to first of all, have three panes of glass for all three of them. But even within them they have four panes of glass for the capabilities we offer. So you could end up with 12 different interfaces to manage a development process, we give you one. Now you tell me which is better. >> Dave: Sounds like a super Cloud to me Lisa (laughing) >> He's big on super Cloud >> Uber Cloud, there you >> Hey I like that, Uber Cloud. Well, so I want to understand Nikesh, what's realistic. You mentioned in your keynote Dave, brought it up that the average organization has 30 to 50 tools, security tools. >> Nikesh: Yes, yes >> On their network. What is realistic for from a consolidation perspective where Palo Alto can come in and say, let me make this consistent and simple for you. >> Well, I'll give you your own example, right? (clears throat) We're probably sub 10 substantively, right? There may be small things here and there we do. But on a substantive protecting the enterprise perspective you be should be down to eight or 10 vendors, and that is not perfect but it's a lot better than 50, >> Lisa: Right? >> because don't forget 50 tools means you have to have capability to understand what those 50 tools are doing. You have to have the capability to upgrade them on a constant basis, learn about their new capabilities. And I just can't imagine why customers have two sets of firewalls right. Now you got to learn both the files on how to deploy both them. That's silly because that's why we need 7 million more people. You need people to understand, so all these tools, who work for companies. If you had less tools, we need less people. >> Do you think, you know I wrote about this as well, that the security industry is anomalous and that the leader has, you know, single digit, low single digit >> Yes >> market shares. Do you think that you can change that? >> Well, you know, when I started that was exactly the observation I had Dave, which you highlighted in your article. We were the largest by revenue, by small margin. And we were one and half percent of the industry. Now we're closer to three, three to four percent and we're still at, you know, like you said, going to be around $7 billion. So I see a path for us to double from here and then double from there, and hopefully as we keep doubling and some point in time, you know, I'd like to get to double digits to start with. >> One of the things that I think has to happen is this has to grow dramatically, the ecosystem. I wonder if you could talk about the ecosystem and your strategy there. >> Well, you know, it's a matter of perspective. I think we have to get more penetrated in our largest customers. So we have, you know, 1800 of the top 2000 customers in the world are Palo Alto customers. But we're not fully penetrated with all our capabilities and the same customers set, so yes the ecosystem needs to grow, but the pandemic has taught us the ecosystem can grow wherever they are without having to come to Vegas. Which I don't think is a bad thing to be honest. So the ecosystem is growing. You are seeing new players come to the ecosystem. Five years ago you didn't see a lot of systems integrators and security. You didn't see security offshoots of telecom companies. You didn't see the Optivs, the WWTs, the (indistinct) of the world (coughs) make a concerted shift towards consolidation or services and all that is happening >> Dave: Mm >> as we speak today in the audience you will find people from Google, Amazon Microsoft are sitting in the audience. People from telecom companies are sitting in the audience. These people weren't there five years ago. So you are seeing >> Dave: Mm >> the ecosystem's adapting. They're, they want to be front and center of solving the customer's problem around security and they want to consolidate capability, they need. They don't want to go work with a hundred vendors because you know, it's like, it's hard. >> And the global system integrators are key. I always say they like to eat at the trough and there's a lot of money in security. >> Yes. >> Dave: (laughs) >> Well speaking of the ecosystem, you had Thomas Curry and Google Cloud CEO in your fireside chat in the keynote. Talk a little bit about how Google Cloud plus Palo Alto Networks, the Zero Trust Partnership and what it's enable customers to achieve. >> Lisa, that's a great question. (clears his throat) Thank you for bringing it up. Look, you know the, one of the most fundamental shifts that is happening is obviously the shift to the Cloud. Now when that shift fully, sort of, takes shape you will realize if your network has changed and you're delivering everything to the Cloud you need to go figure out how to bring the traffic to the Cloud. You don't have to bring it back to your data center you can bring it straight to the Cloud. So in that context, you know we use Google Cloud and Amazon Cloud, to be able to carry our traffic. We're going from a product company to a services company in addition, right? Cuz when we go from firewalls to SASE we're not carrying your traffic. When we carry our traffic, we need to make sure we have underlying capability which is world class. We think GCP and AWS and Azure run some of the biggest and best networks in the world. So our partnership with Google is such that we use their public Cloud, we sit on top of their Cloud, they give us increased enhanced functionality so that our customers SASE traffic gets delivered in priority anywhere in the world. They give us tooling to make sure that there's high reliability. So you know, we partner, they have Beyond Corp which is their version of Zero Trust which allows you to take unmanaged devices with browsers. We have SASE, which allows you to have managed devices. So the combination gives our collective customers the ability for Zero Trust. >> Do you feel like there has to be more collaboration within the ecosystem, the security, you know, landscape even amongst competitors? I mean I think about Google acquires Mandiant. You guys have Unit 42. Should and will, like, Wendy Whitmore and maybe they already are, Kevin Mandia talk more and share more data. If security's a data problem is all this data >> Nikesh: Yeah look I think the industry shares threat data, both in private organizations as well as public and private context, so that's not a problem. You know the challenge with too much collaboration in security is you never know. Like you know, the moment you start sharing your stuff at third parties, you go out of Secure Zone. >> Lisa: Mm >> Our biggest challenge is, you know, I can't trust a third party competitor partner product. I have to treat it with as much suspicion as anything else out there because the only way I can deliver Zero Trust is to not trust anything. So collaboration in Zero Trust are a bit of odds with each other. >> Sounds like another problem you can solve >> (laughs) >> Nikesh last question for you. >> Yes >> Favorite customer or example that you think really articulates the value of what Palo Alto was delivering? >> Look you know, it's a great question, Lisa. I had this seminal conversation with a customer and I explained all those things we were talking about and the customer said to me, great, okay so what do I need to do? I said, fun, you got to trust me because you know, we are on a journey, because in the past, customers have had to take the onus on themselves of integrating everything because they weren't sure a small startup will be independent, be bought by another cybersecurity company or a large cybersecurity company won't get gobbled up and split into pieces by private equity because every one of the cybersecurity companies have had a shelf life. So you know, our aspiration is to be the evergreen cybersecurity company. We will always be around and we will always tackle innovation and be on the front line. So the customer understood what we're doing. Over the last three years we've been working on a transformation journey with them. We're trying to bring them, or we have brought them along the path of Zero Trust and we're trying to work with them to deliver this notion of reducing their meantime to remediate from days to minutes. Now that's an outcome based approach that's a partnership based approach and we'd like, love to have more and more customers of that kind. I think we weren't ready to be honest as a company four and a half years ago, but I think today we're ready. Hence my keynote was called The Perfect Storm. I think we're at the right time in the industry with the right capabilities and the right ecosystem to be able to deliver what the industry needs. >> The perfect storm, partners, customers, investors, employees. Nikesh, it's been such a pleasure having you on theCUBE. Thank you for coming to talk to Dave and me right after your keynote. We appreciate that and we look forward to two days of great coverage from your executives, your customers, and your partners. Thank you. >> Well, thank you for having me, Lisa and Dave and thank you >> Dave: Pleasure >> for what you guys do for our industry. >> Our pleasure. For Nikesh Arora and Dave Vellante, I'm Lisa Martin, you're watching theCUBE live at MGM Grand Hotel in Las Vegas, Palo Alto Ignite 22. Stick around Dave and I will be joined by our next guest in just a minute. (cheerful music plays out)

>>Set restaurants. And who says TEUs had got a little ass more skin in the game for us, in charge of his destiny? You guys are excited. Robert Worship is Chief Alumni. >>My name is Dave Ante, and I'm a long time industry analyst. So when you're as old as I am, you've seen a lot of transitions. Everybody talks about industry cycles and waves. I've seen many, many waves. Met a lot of industry executives and of a little bit of a, an industry historian. When you interview many thousands of people, probably five or 6,000 people as I have over the last half of a decade, you get to interact with a lot of people's knowledge and you begin to develop patterns. And so that's sort of what I bring is, is an ability to catalyze the conversation and, you know, share that knowledge with others in the community. Our philosophy is everybody's expert at something. Everybody's passionate about something and has real deep knowledge about that's something well, we wanna focus in on that area and extract that knowledge and share it with our communities. This is Dave Ante. Thanks for watching the Cube. >>Hello everyone and welcome back to the Cube where we are streaming live this week from CubeCon. I am Savannah Peterson and I am joined by an absolutely stellar lineup of cube brilliance this afternoon. To my left, a familiar face, Lisa Martin. Lisa, how you feeling? End of day two. >>Excellent. It was so much fun today. The buzz started yesterday, the momentum, the swell, and we only heard even more greatness today. >>Yeah, yeah, abs, absolutely. You know, I, I sometimes think we've hit an energy cliff, but it feels like the energy is just >>Continuous. Well, I think we're gonna, we're gonna slide right into tomorrow. >>Yeah, me too. I love it. And we've got two fantastic analysts with us today, Sarge and Keith. Thank you both for joining us. We feel so lucky today. >>Great being back on. >>Thanks for having us. Yeah, Yeah. It's nice to have you back on the show. We were, had you yesterday, but I miss hosting with you. It's been a while. >>It has been a while. We haven't done anything in since, Since pre >>Pandemic, right? Yeah, I think you're >>Right. Four times there >>Be four times back in the day. >>We, I always enjoy whole thing, Lisa, cuz she's so well prepared. I don't have to do any research when I come >>Home. >>Lisa will bring up some, Oh, sorry. Jeep, I see that in 2008 you won this award for Yeah. Being just excellent and I, I'm like, Oh >>Yeah. All right Keith. So, >>So did you do his analysis? >>Yeah, it's all done. Yeah. Great. He only part, he's not sitting next to me too. We can't see it, so it's gonna be like a magic crystal bell. Right. So a lot of people here. You got some stats in terms of the attendees compared >>To last year? Yeah, Priyanka told us we were double last year up to 8,000. We also got the scoop earlier that 2023 is gonna be in Chicago, which is very exciting. >>Oh, that is, is nice. Yeah, >>We got to break that here. >>Excellent. Keith, talk to us about what some of the things are that you've seen the last couple of days. The momentum. What's the vibe? I saw your tweet about the top three things you were being asked. Kubernetes was not one of them. >>Kubernetes were, was not one of 'em. This conference is starting to, it, it still feels very different than a vendor conference. The keynote is kind of, you know, kind of all over the place talking about projects, but the hallway track has been, you know, I've, this is maybe my fifth or sixth CU con in person. And the hallway track is different. It's less about projects and more about how, how do we adjust to the enterprise? How do we Yes. Actually do enterprise things. And it has been amazing watching this community grow. I'm gonna say grow up and mature. Yes. You know, you know, they're not wearing ties yet, but they are definitely understanding kind of the, the friction of implementing new technology in, in an enterprise. >>Yeah. So ge what's your, what's been your take, We were with you yesterday. What's been the take today to take aways? >>NOMA has changed since yesterday, but a few things I think I, I missed talking about that yesterday were that, first of all, let's just talk about Amazon. Amazon earnings came out, it spooked the market and I think it's relevant in this context as well, because they're number one cloud provider. Yeah. And all, I mean, almost all of these technologies on the back of us here, they are related to cloud, right? So it will have some impact on these. Like we have to analyze that. Like will it make the open source go faster or slower in, in lieu of the fact that the, the cloud growth is slowing. Right? So that's, that's one thing that's put that's put that aside. I've been thinking about the, the future of Kubernetes. What is the future of Kubernetes? And in that context, I was thinking like, you know, I think in, when I put a pointer there, I think in tangents, like, what else is around this thing? So I think CN CNCF has been writing the success of Kubernetes. They are, that was their number one flagship project, if you will. And it was mature enough to stand on its own. It it was Google, it's Google's Borg dub da Kubernetes. It's a genericized version of that. Right? So folks who do tech deep down, they know that, Right. So I think it's easier to stand with a solid, you know, project. But when the newer projects come in, then your medal will get tested at cncf. Right. >>And cncf, I mean they've got over 140 projects Yeah. Right now. So there's definitely much beyond >>Kubernetes. Yeah. So they, I have numbers there. 18 graduated, right, 37 in incubation and then 81 in Sandbox stage. They have three stages, right. So it's, they have a lot to chew on and the more they take on, the less, you know, quality you get goes into it. Who is, who's putting the money behind it? Which vendors are sponsoring like cncf, like how they're getting funded up. I think it >>Something I pay attention to as well. Yeah. Yeah. Lisa, I know you've got >>Some insight. Those are the things I was thinking about today. >>I gotta ask you, what's your take on what Keith said? Are you also seeing the maturation of the enterprise here at at coupon? >>Yes, I am actually, when you say enterprise versus what's the other side? Startups, right? Yeah. So startups start using open source a lot more earlier or lot more than enterprises. The enterprise is what they need. Number one thing is the, for their production workloads, they want a vendor sporting them. I said that yesterday as well, right? So it depend depending on the size of the enterprise. If you're a big shop, definitely if you have one of the 500 or Fortune five hundreds and your tech savvy shop, then you can absorb the open source directly coming from the open source sort of universe right. Coming to you. But if you are the second tier of enterprise, you want to go to a provider which is managed service provider, or it can be cloud service provider in this case. Yep. Most of the cloud service providers have multiple versions of Kubernetes, for example. >>I'm not talking about Kubernetes only, but like, but that is one example, right? So at Amazon you can get five different flavors of Kubernetes, right? Fully manage, have, manage all kind of stuff. So people don't have bandwidth to manage that stuff locally. You have to patch it, you have to roll in the new, you know, updates and all that stuff. Like, it's a lot of work for many. So CNCF actually is formed for that reason. Like the, the charter is to bring the quality to open source. Like in other companies they have the release process and they, the stringent guidelines and QA and all that stuff. So is is something ready for production? That's the question when it comes to any software, right? So they do that kind of work and, and, and they have these buckets defined at high level, but it needs more >>Work. Yeah. So one of the things that, you know, kind of stood out to me, I have good friend in the community, Alex Ellis, who does open Fast. It's a serverless platform, great platform. Two years ago or in 2019, there was a serverless day date. And in serverless day you had K Native, you had Open Pass, you had Ws, which is supported by IBM completely, not CNCF platforms. K native came into the CNCF full when Google donated the project a few months ago or a couple of years ago, now all of a sudden there's a K native day. Yes. Not a serverless day, it's a K native day. And I asked the, the CNCF event folks like, what happened to Serverless Day? I missed having open at serverless day. And you know, they, they came out and said, you know what, K native got big enough. >>They came in and I think Red Hat and Google wanted to sponsor a K native day. So serverless day went away. So I think what what I'm interested in and over the next couple of years is, is they're gonna be pushback from the C against the cncf. Is the CNCF now too big? Is it now the gatekeeper for do I have to be one of those 147 projects, right? In order enough to get my project noticed the open, fast, great project. I don't think Al Alex has any desire to have his project hosted by cncf, but it probably deserves, you know, shoulder left recognition with that. So I'm pushing to happen to say, okay, if this is open community, this is open source. If CNC is the place to have the cloud native conversation, what about the projects that's not cncf? Like how do we have that conversation when we don't have the power of a Google right. Or a, or a Lenox, et cetera, or a Lenox Foundation. So GE what, >>What are your thoughts on that? Is, is CNC too big? >>I don't think it's too big. I think it's too small to handle the, what we are doing in open source, right? So it's a bottle. It can become a bottleneck. Okay. I think too big in a way that yeah, it has, it has, it has power from that point of view. It has that cloud, if you will. The people listen to it. If it's CNCF project or this must be good, it's like in, in incubators. Like if you are y white Combinator, you know, company, it must be good. You know, I mean, may not be >>True, but, >>Oh, I think there's a bold assumption there though. I mean, I think everyone's just trying to do the best they can. And when we're evaluating projects, a very different origin and background, it's incredibly hard. Very c and staff is a staff of 30 people. They've got 180,000 people that are contributing to these projects and a thousand maintainers that they're trying to uphold. I think the challenge is actually really great. And to me, I actually look at events as an illustration of, you know, what's the culture and the health of an organization. If I were to evaluate CNCF based on that, I'd say we're very healthy right now. I would say that we're in a good spot. There's a lot of momentum. >>Yeah. I, I think CNCF is very healthy. I'm, I'm appreciative for it being here. I love coupon. It's becoming the, the facto conference to have this conversation has >>A totally >>Different vibe to other, It's a totally different vibe. Yeah. There needs to be a conduit and truth be told, enterprise buyers, to subject's point, this is something that we do absolutely agree on, on enterprise buyers. We want someone to pick winners and losers. We do, we, we don't want a box of Lego dumped on our, the middle of our table. We want somebody to have sorted that out. So while there may be five or six different service mesh solutions, at least the cncf, I can go there and say, Oh, I'll pick between the three or four that are most popular. And it, it's a place to curate. But I think with that curation comes the other side of it. Of how do we, how, you know, without the big corporate sponsor, how do I get my project pushed up? Right? Elevated. Elevated, Yep. And, and put onto the show floor. You know, another way that projects get noticed is that startups will adopt them, Push them. They may not even be, I don't, my CNCF project may not, my product may not even be based on the CNCF product. But the new stack has a booth, Ford has a booth. Nothing to do with a individual prod up, but promoting open source. What happens when you're not sponsored? >>I gotta ask you guys, what do you disagree on? >>Oh, so what, what do we disagree on? So I'm of the mindset, I can, I can say this, I I believe hybrid infrastructure is the future of it. Bar none. If I built my infrastructure, if I built my application in the cloud 10 years ago and I'm still building net new applications, I have stuff that I built 10 years ago that looks a lot like on-prem, what do I do with it? I can't modernize it cuz I don't have the developers to do it. I need to stick that somewhere. And where I'm going to stick that at is probably a hybrid infrastructure. So colo, I'm not gonna go back to the data center, but I'm, I'm gonna look, pick up something that looks very much like the data center and I'm saying embrace that it's the future. And if you're Boeing and you have, and Boeing is a member, cncf, that's a whole nother topic. If you have as 400 s, hpu X, et cetera, stick that stuff. Colo, build new stuff, but, and, and continue to support OpenStack, et cetera, et cetera. Because that's the future. Hybrid is the future. >>And sub g agree, disagree. >>I okay. Hybrid. Nobody can deny that the hybrid is the reality, not the future. It's a reality right now. It's, it's a necessity right now you can't do without it. Right. And okay, hybrid is very relative term. You can be like 10% here, 90% still hybrid, right? So the data center is shrinking and it will keep shrinking. Right? And >>So if by whole is the data center shrinking? >>This is where >>Quick one quick getting guys for it. How is growing by a clip? Yeah, but there's no data supporting. David Lym just came out for a report I think last year that showed that the data center is holding steady, holding steady, not growing, but not shrinking. >>Who sponsored that study? Wait, hold on. So the, that's a question, right? So more than 1 million data centers have been closed. I have, I can dig that through number through somebody like some organizations we published that maybe they're cloud, you know, people only. So the, when you get these kind of statements like it, it can be very skewed statements, right. But if you have seen the, the scene out there, which you have, I know, but I have also seen a lot of data centers walk the floor of, you know, a hundred thousand servers in a data center. I cannot imagine us consuming the infrastructure the way we were going into the future of co Okay. With, with one caveat actually. I am not big fan of like broad strokes. Like make a blanket statement. Oh no, data center's dead. Or if you are, >>That's how you get those esty headlines now. Yeah, I know. >>I'm all about to >>Put a stake in the ground. >>Actually. The, I think that you get more intelligence from the new end, right? A small little details if you will. If you're golden gold manak or Bank of America, you have so many data centers and you will still have data centers because performance matters to you, right? Your late latency matters for applications. But if you are even a Fortune 500 company on the lower end and or a healthcare vertical, right? That your situation is different. If you are a high, you know, growth startup, your situation is different, right? You will be a hundred percent cloud. So cloud gives you velocity, the, the, the pace of change, the pace of experimentation that actually you are buying innovation through cloud. It's proxy for innovation. And that's how I see it. But if you have, if you're stuck with older applications, I totally understand. >>Yeah. So the >>We need that OnPrem. Yeah, >>Well I think the, the bring your fuel sober, what we agree is that cloud is the place where innovation happens. Okay? At some point innovation becomes legacy debt and you have thus hybrid, you are not going to keep your old applications up to date forever. The, the, the math just doesn't add up. And where I differ in opinion is that not everyone needs innovation to keep moving. They need innovation for a period of time and then they need steady state. So Sergeant, we >>Argue about this. I have a, I >>Love this debate though. I say it's efficiency and stability also plays an important role. I see exactly what you're talking about. No, it's >>Great. I have a counter to that. Let me tell you >>Why. Let's >>Hear it. Because if you look at the storage only, right? Just storage. Just take storage computer network for, for a minute. There three cost reps in, in infrastructure, right? So storage earlier, early on there was one tier of storage. You say pay the same price, then now there are like five storage tiers, right? What I'm trying to say is the market sets the price, the market will tell you where this whole thing will go, but I know their margins are high in cloud, 20 plus percent and margin will shrink as, as we go forward. That means the, the cloud will become cheaper relative to on-prem. It, it, in some cases it's already cheaper. But even if it's a stable workload, even in that case, we will have a lower tier of service. I mean, you, you can't argue with me that the cloud versus your data center, they are on the same tier of services. Like cloud is a better, you know, product than your data center. Hands off. >>I love it. We, we are gonna relish in the debates between the two of you. Mic drops. The energy is great. I love it. Perspective. It's not like any of us can quite see through the crystal ball that we have very informed opinions, which is super exciting. Yeah. Lisa, any last thoughts today? >>Just love, I love the debate as well. That, and that's, that's part of what being in this community is all about. So sharing about, sharing opinions, expressing opinions. That's how it grows. That's how, that's how we innovate. Yeah. Obviously we need the cloud, but that's how we innovate. That's how we grow. Yeah. And we've seen that demonstrated the last couple days and I and your, your takes here on the Cuban on Twitter. Brilliant. >>Thank you. I absolutely love it. I'm gonna close this out with a really important analysis on the swag of the show. Yes. And if you know, yesterday we were looking at what is the weirdest swag or most unique swag We had that bucket hat that took the grand prize. Today we're gonna focus on something that's actually quite cool. A lot of the vendors here have really dedicated their swag to being local to Detroit. Very specific in their sourcing. Sonotype here has COOs. They're beautiful. You can't quite feel this flannel, but it's very legit hand sound here in Michigan. I can't say that I've been to too many conferences, if any, where there was this kind of commitment to localizing and sourcing swag from around the corner. We also see this with the Intel booth. They've got screen printers out here doing custom hoodies on spot. >>Oh fun. They're even like appropriately sized. They had local artists do these designs and if you're like me and you care about what's on your wrist, you're familiar with Shinola. This is one of my favorite swags that's available. There is a contest. Oh going on. Hello here. Yeah, so if you are Atan, make sure that you go and check this out. The we, I talked about this on the show. We've had the founder on the show or the CEO and yeah, I mean Shine is just full of class as since we are in Detroit as well. One of the fun themes is cars. >>Yes. >>And Storm Forge, who are also on the show, is actually giving away an Aston Martin, which is very exciting. Not exactly manufactured in Detroit. However, still very cool on the car front and >>The double oh seven version named the best I >>Know in the sixties. It's love it. It's very cool. Two quick last things. We talk about it a lot on the show. Every company now wants to be a software company. Yep. On that vein, and keeping up with my hat theme, the Home Depot is here because they want everybody to know that they in fact are a technology company, which is very cool. They have over 500,000 employees. You can imagine there's a lot of technology that has to go into keeping Napa. Absolutely. Yep. Wild to think about. And then last, but not at least very quick, rapid fire, best t-shirt contest. If you've ever ran to one of these events, there are a ton of T-shirts out there. I rate them on two things. Wittiest line and softness. If you combine the two, you'll really be our grand champion for the year. I'm just gonna hold these up and set them down for your laughs. Not afraid to commit, which is pretty great. This is another one designed by locals here. Detroit Code City. Oh, love it. This one made me chuckle the most. Kiss my cash. >>Oh, that's >>Good. These are also really nice and soft, which is fantastic. Also high on the softness category is this Op Sarah one. I also like their bird logo. These guys, there's just, you know, just real nice touch. So unfortunately, if you have the fumble, you're not here with us, live in Detroit. At least you're gonna get taste of the swag. I taste of the stories and some smiles hear from those of us on the cube. Thank you both so much for being here with us. Lisa, thanks for another fabulous day. Got it, girl. My name's Savannah Peterson. Thank you for joining us from Detroit. We're the cube and we can't wait to see you tomorrow.

>>Good morning and welcome back to the Cube where we are excited to be broadcasting live all week from Detroit to Michigan at Cuban slash cloud Native con. Depending on who you're asking, Lisa, it's day two things are buzzing. How are you feeling? >>Good, excited. Ready for day two, ready to have more great conversations to see how this community is expanding, how it's evolving, and how it's really supporting it itself. >>Yeah, Yeah. This is a very supportive community. Something we talked a lot about. And speaking of community, we've got some very bold and brave folks over here. We've got this CTO and the head of product from Storm Forge, and they are on a mission to automate Kubernetes. Now automatic and Kubernetes are not words that go in the same sentence very often, so please welcome Patrick and Yasmin. Thank you both for being here. Hello. How you doing? >>Thanks for having us. >>Thanks for having us. >>Talk about what you guys are doing. Cause as you said, Kubernetes auto spelling is anything but auto. >>Yeah. >>The, what are some of the challenges? How do you help >>Eliminate this? Yeah, so the mission at Storm Forge is primarily automatic resource configuration and optimization essentially. So we started as a machine learning company first. And it's kind of an interesting story cuz we're one of those startups that has pivoted a few times. And so we were running our machine learning workloads. Most >>Have, I think, >>Right? Yeah. Yeah. We were, we started out running our machine learning workloads and moving them into Kubernetes. And then we weren't quite sure how to correctly adjust and size our containers. And so our ML team, we've got three PhDs and applied mathematics. They said, Well, hang on, we could write an algorithm for that. And so they did. And then, Oh, I love this. Yeah. And then we said, Well holy cow, that's actually really useful. I wonder if other people would like that. And that's kind of where we got our start. >>You solved your own problem and then you built a business >>Around it. Yeah, exactly. >>That is fantastic. Is, is that driving product development at Storm Forge still? That kind of attitude? >>I mean that kind of attitude definitely drives product development, but we're, you know, balancing that with what the users are, the challenges that they have, especially at large scale. We deal with a lot of large enterprises and for us as a startup, we can relate to the problems that come with Kubernetes when you're trying to scale it. But when you're talking about the scale of some of these larger enterprises, it's just a different mentality. So we're trying to balance that of how we take that input into how we build our product. Talk >>About that, like the, the end user input and how you're taking that in, because of course it's only going to be a, you know, more of a symbiotic relationship when that customer feedback is taken and >>Acted on. Yeah, totally. And for us, because we use machine learning, it's a lot of building confidence with our users. So making sure that they understand how we look at the data, how we come up with the recommendations, and actually deploy those changes in their environment. There's a lot of trust that needs to be built there. So being able to go back to our users and say, Okay, we're presenting you this type of data, give us your feedback and building it alongside them has helped a lot in these >>Relationships. Absolutely. You said the word trust, and that's something that we talk about at every >>Show. I was gonna jump on that too. It's >>Not, Yeah, it's not a buzzword. It's not, It shouldn't be. Yeah. It really should be, I wanna say lived and breathed, but that's probably grammatically incorrect. >>We're not a gram show. It's okay darling. Yeah, thank >>You. It should be truly embodied. >>Yeah. And I, I think it's, it's not even unique to just what we do, but across tech in general, right? Like when I talk about SRE and building SRE teams, one of the things I mentioned is you have to build that trust first. And with machine learning, I think it can be really difficult too for a couple different reasons. Like one, it tends to be a black box if it's actually true machine learning. Totally. Which ours is. But the other piece that we run into. Yeah. And the other piece we run into though is, is what I was an executive at United Health Group before I joined Storm Forge. And I would get companies that would come to me and try to sell me machine learning and I would kind of look at it and say, Well no, that's just a basic decision tree. Or like, that's a super basic whole winter forecast, right? Like that's not actually machine learning. And that's one of the things that we actually find ourselves kind of battling a little bit when we talk about what we do in building that trust. >>Talk a little bit about the latest release as you guys had a very active September. Here we are. And towards the, I think end of October. Yeah. What are some of the, the new things that have come out? New integrations, new partnerships. Give us a scoop on that. >>Yeah, well I guess I'll start and then I'll probably hand it over to you. But like the, the big thing for us is we talked about automating Kubernetes in the very beginning, right? Like Kubernetes has got a vpa it's >>A wild sentence anyway. Yeah, yeah. >>It it >>Has. We're not gonna get over at the whole show. Yeah. >>It as a VPA built in, it has an HPA built in and, and when you look at the data and even when you read the documentation from Google, it explicitly says never the two should meet. Right. Because you'll end up thrashing and they'll fight each other. Well the big release we just announced is with our machine learning, we can now do both. And so we vertically scale your pods to the correct up. Yeah. >>Follow status. I love that. >>Yeah, we can, we can scale your pods to the correct size and still allow you to enable the HPA and we'll make recommendations for your scaling points and your thresholds on the HPA as well so that they can work together to really truly maximize your efficiency that without sacrificing your performance and your reliability of the applications that you're running. That >>Sounds like a massive differentiator for >>Storm launch, which I would say it is. Yeah. I think as far as I know, we're the first in the industry that can do this. Yeah. >>And >>From very singularity vibes too. You know, the machines are learning, teaching themselves and doing it all automatically. Yep. Gets me very >>Excited. >>Yeah, absolutely. And from a customer demand perspective, what's the feedback been? Yeah, it's been a few >>Weeks. Yeah, it's been really great actually. And a lot of why we went down this path was user driven because they're doing horizontal scale and they want to be able to vertically size as they're scaling. So if you put yourself in the shoes of someone that's configuring Kubernetes, you're usually guessing on what you're setting your CPU requests and limits do. But horizontal scale makes sense. You're either adding more things or removing more things. And so once they actually are scaled out as a large environment and they have to rethink, how am I gonna resize this now? It's just not possible. It's so many thousands of settings across all the different environments and you're only thinking about CPU memory, You're not thinking about a lot of things. It's just, but once you scale that out, it's a big challenge. So they came to us and said, Okay, you're doing, cuz we were doing vertical scaling before and now we enable vertical and horizontal. And so they came to us and said, I love what you're doing about right sizing, but we wanna be able to do this while also horizontally scaling. And so the way that our software works is we give you the recommendations for what the setting should be and then allow Kubernetes to continue to add and remove replicas as needed. So it's not like we're going in and making changes to Kubernetes, but we make changes to the configuration settings so that it's the most optimal from a resource perspective. >>Efficiency has been a real big theme of the show. Yeah. And it's clear that that's a focus for you. Everyone here wants to do more faster Of course. And innovation, that's the thing to do that sometimes we need partners. You just announced an integration with Datadog. Tell us about that. Yeah, >>Absolutely. Yeah. So the way our platform works is we need data of course, right? So they're, they're a great partner for us and we use them both as an input and an output. So we pull in metrics from Datadog to provide recommendations and we'll actually display all those within the Datadog portal. Cause we have a lot of users that are like, Look, Datadog's my single pane of glass and I hate using that word, but they get all their insights there. They can see their recommendations and then actually go deploy those. Whether they wanna automatically have the recommendations deployed or go in and actually push a button. >>So give me an example of a customer that is using the, the new release and some of the business outcomes they're achieving. I imagine one of the things that you're enabling is just closing that ES skills gap. But from a business level perspective, how are they gaining like competitive advantages to be able to get products to market faster, for example? >>Yeah, so one of the customers that was actually part of our press release and launch and spoke about us at a webinar, they are a SaaS product and deal with really bursty workloads. And so their cloud costs have been growing 40% year over year. And their platform engineering team is basically enabled to provide the automation for developers and in their environment, but also to reduce those costs. So they want to, it's that trade off of resiliency and cost performance. And so they came to us and said, Look, we know we're over provisioned, but we don't know how to tackle that problem without throwing tons of humans at the problem. And so we worked with them and just on a single app found 60% savings and we're working now to kind of deploy that across their entire production workload. But that allows them to then go back and get more out of the, the budget that they already have and they can kind of reallocate that in other areas, >>Right? So there can be chop line and bottom >>Line impact. Yeah. And I, I think there's some really direct impact to the carbon emissions of an organization as well. That's a good point. When you can reduce your compute consumption by 60%. >>I love this. We haven't talked about this at all during the show. Yeah. And I'm really glad that you brought this up. All of the things that power this use energy. Yeah. >>What is it like seven to 8% of all electricity in the world is consumed by data centers. Like it's crazy. Yeah. Yeah. And so like that's wild. Yeah. Yeah. So being able to make a reduction in impact there too, especially with organizations that are trying to sign green pledges and everything else. >>It's hard. Yeah. ESG initiatives are huge. >>Absolut, >>It's >>A whole lot. A lot of companies have ESG initiatives where they can't even go out and do an RFP with a business, Right. If they don't have an actual active starting, impactful ESG program. Yes. Yeah. >>And the RFPs that we have to fill out, we have to tell them how they'll help. >>Yeah. Yes. It's so, yeah, I mean I was really struck when I looked on your website and I saw 54% average cost reduction for Yeah. For your cloud operations. I hadn't even thought about it from a power perspective. Yeah. I mean, imagine if we cut that to 3% of the world's power grid. That is just, that is very compelling. Speaking of compelling and exciting future things, talk to us about what's next? What's got you pumped for 2023 and and what lies >>Ahead? Oh man. Well that seems like a product conversation for sure. >>Well, we're super excited about extending what we do to other platforms, other metrics. So we optimize a lot right now around CPU and memory, but we can also give people insights into, you know, limiting kills, limiting CPU throttling, so extending the metrics. And when you look at hba and horizontal scale today, most of it is done with cpu, but there are some organizations out there that are scaling on custom metrics. So being able to take in more data to provide more recommendations and kind of extend what we can do from an optimization standpoint. >>That's, yeah, that's cool. And what house you most excited on the show floor? Anything? Anything that you've seen? Any keynotes? >>There's, Well, I haven't had a lot of time to go to the keynotes unfortunately, but it's, >>Well, I'm shock you've been busy or something, right? Much your time here. >>I can't imagine why. But no, there's, it's really interesting to see all the vendors that are popping up around Kubernetes focus specifically with security is always something that's really interesting to me. And automating CICD and how they continue to dive into that automation devs, SEC ops continues to be a big thing for a lot of organizations. Yeah. Yeah. >>I I do, I think it's interesting when we marry, Were you guys here last year? >>I was not here. >>No. So at, at the smaller version of this in Los Angeles. Yeah. I, I was really struck because there was still a conversation of whether or not we were all in on Kubernetes as, as kind of a community and a society this year. And I'm curious if you feel this way too. Everyone feels committed. Yeah. Yeah. I I I feel like there's no question that Kubernetes is the tool that we are gonna be using. >>Yeah. I I think so. And I think a lot of that is actually being unlocked by some of these vendors that are being partners and helping people get the most outta Kubernetes, you know, especially at the larger enterprise organizations. Like they want to do it, but the skills gap is a very real problem. Right. And so figuring out, like Jasmine talked about figuring out how do we, you know, optimize or set up the correct settings without throwing thousands of humans at it. Never mind the fact you'll never find a thousand people that wanna do that all day every day. >>I was gonna, It's a fold endeavor for those >>People study, right? Yeah. And, and being able to close some of those gaps, whether it's optimization, security, DevOps, C I C D. As we get more of those partners like I just talked about on the floor, then you see more and more enterprises being more open to leaning into Kubernetes a little bit. >>Yeah. Yeah. We've seen, we've had some great conversations the last day and, and today as well with organizations that are history companies like Ford Motor Companies for >>Example. Yeah. Right. >>Just right behind us. One of their EVs and, and it's, they're becoming technology companies that happen to do cars or home >>Here. I had a nice job with 'em this morning. Yes. With that storyline, honestly. >>Yes. That when we now have such a different lens into these organizations, how they're using technologies, advanced technologies, Kubernetes, et cetera, to really become data companies. Yeah. Because they have to be, well the consumers on the other end expect a Home Depot or a Ford or whomever or your bank Yeah. To know who you are. I want the information right here whenever I need it so I can do the transaction I need and I want you to also deliver me information that is relevant to me. Yeah. Because there, there's no patience anymore. Yeah. >>And we partner with a lot of big FinTech companies and it's, it's very much that. It's like how do we continue to optimize? But then as they look at transitioning off of older organizations and capabilities, whether that's, they have a physical data center that's racked to the gills and they can't do anything about that, so they wanna move to cloud or they're just dipping their toe into even private cloud with Kubernetes in their own instances. A lot of it is how do we do this right? Like how do we lean in and, Yeah. >>Yeah. Well I think you said it really well that the debate seems to be over in terms of do we go in on Kubernetes? That that was a theme that I think we felt that yesterday, even on on day one of the keynotes. The community seems to be just craving more. I think that was another thing that we felt yesterday was all of the contributors and the collaborators, people want to be able to help drive this community forward because it's, it's a flywheel of symbiosis for all of the vendors here. The maintainers and, and really businesses in any industry can benefit. >>Yeah. It's super validating. I mean if you just look at the floor, there's like 20 different booths that talk about cost reporting for Kubernetes. So not only have people moved, but now they're dealing with those challenges at scale. And I think for us it's very validating because there's so many vendors that are looking into the reporting of this and showing you the problem that you have. And then where we can help is, okay, now you know, you have a problem, here's how we can fix it for you. >>Yeah. Yeah. That, that sort of dealing with challenges at scale that you set, I think that's also what we're hearing. Yeah. And seeing and feeling on the show floor. >>Yeah, absolutely. >>What can folks see and, and touch and feel in your booth? >>We have some demos there you can play around with the product. We're giving away a Lego set so we've let >>Gotta gets >>Are right now we're gonna have to get some Lego, We do a swag segment at the end of the day every day. Now we've >>Some cool socks. >>Yep. Socks are hot. Let's, let's actually talk about scale internally as our closing question. What's going on at Storm Forge? If someone's watching right now, they're excited. Are you hiring? We are hiring. Yeah. How can they stalk you? What's the >>School? Absolutely. So you can check us out on Storm forge.io. We're certainly hiring across the engineering organization. We're hiring across the UX a product organization. We're dealing, like I said, we've got some really big customers that we're, we're working through with some really fun challenges. And we're looking to continue to build on what we do and do new innovative things like especially cuz like I said, we are a machine learning organization first. And so for me it's like how do I collect all the data that I can and then let's find out what's interesting in there that we can help people with. Whether that's cpu, memory, custom metrics, like as said, preventing kills, driving availability, reliability, What can we do to, to kind of make a little bit more transparent the stuff that's going on underneath the covers in Kubernetes for the decision makers in these organizations. >>Yes. Transparency is a goal of >>Many. >>Yeah, absolutely. Well, and you mentioned fun. If this conversation is any representation, it would be very fun to be working on both of your teams. We, we have a lot of fun Ya. Patrick, thank you so much for joining. Thanks for having us, Lisa, As usual, thanks for being here with me. My pleasure. And thank you to all of you for turning into the Cubes live show from Detroit. My name's Savannah Peterson and we'll be back in a few.

>>The cube presents, Coon and cloud native con Europe 22, brought to you by the cloud native computing foundation. >>Welcome to Melissa Spain. And we're at cuon cloud native con Europe, 2022. I'm Keith Townsend. And my co-host en Rico senior Etti en Rico's really proud of me. I've called him en Rico and said IK, every session, senior it analyst giga, O we're talking to fantastic builders at Cuban cloud native con about the projects and the efforts en Rico up to this point, it's been all about provisioning insecurity. What, what conversation have we been missing? >>Well, I mean, I, I think, I think that, uh, uh, we passed the point of having the conversation of deployment of provisioning. You know, everybody's very skilled, actually everything is done at day two. They are discovering that, well, there is a security problem. There is an observability problem. And in fact, we are meeting with a lot of people and there are a lot of conversation with people really needing to understand what is happening. I mean, in their classroom, what, why it is happening and all the, the questions that come with it. I mean, and, uh, the more I talk with, uh, people in the, in the show floor here, or even in the, you know, in the various sessions is about, you know, we are growing, the, our clusters are becoming bigger and bigger. Uh, applications are becoming, you know, bigger as well. So we need to know, understand better what is happening. It's not only, you know, about cost it's about everything at the >>End. So I think that's a great set up for our guests, max, Provo, founder, and CEO of storm for forge and Patrick Britton, Bergstrom, Brookstone. Yeah, I spelled it right. I didn't say it right. Berg storm CTO. We're at Q con cloud native con we're projects are discussed, built and storm forge. I I've heard the pitch before, so forgive me. And I'm, I'm, I'm, I'm, I'm, I'm kind of torn. I have service mesh. What do I need more like, what problem is storm for solving? >>You wanna take it? >>Sure, absolutely. So it it's interesting because, uh, my background is in the enterprise, right? I was an executive at United health group. Um, before that I worked at best buy. Um, and one of the issues that we always had was, especially as you migrate to the cloud, it seems like the CPU dial or the memory dial is your reliability dial. So it's like, oh, I just turned that all the way to the right and everything's hunky Dory. Right. Uh, but then we run into the issue like you and I were just talking about where it gets very, very expensive, very quickly. Uh, and so my first conversations with Matt and the storm forge group, and they were telling me about the product and, and what we're dealing with. I said, that is the problem statement that I have always struggled with. And I wish this existed 10 years ago when I was dealing with EC two costs, right? And now with Kubernetes, it's the same thing. It's so easy to provision. So realistically, what it is is we take your raw telemetry data and we essentially monitor the performance of your application. And then we can tell you using our machine learning algorithms, the exact configuration that you should be using for your application to achieve the results that you're looking for without over provisioning. So we reduce your consumption of CPU of memory and production, which ultimately nine times outta 10, actually I would say 10 out of 10 reduces your cost significantly without sacrificing reliability. >>So can your solution also help to optimize the application in the long run? Because yes, of course, yep. You know, the lowing fluid is, you know, optimize the deployment. Yeah. But actually the long term is optimizing the application. Yes. Which is the real problem. >>Yep. So we actually, um, we're fine with the, the former of what you just said, but we exist to do the latter. And so we're squarely and completely focused at the application layer. Um, we are, uh, as long as you can track or understand the metrics you care about for your application, uh, we can optimize against it. Um, we love that we don't know your application. We don't know what the SLA and SLO requirements are for your app. You do. And so in, in our world, it's about empowering the developer into the process, not automating them out of it. And I think sometimes AI and machine learning sort of gets a bad wrap from that standpoint. And so, uh, we've at this point, the company's been around, you know, since 2016, uh, kind of from the very early days of Kubernetes, we've always been, you know, squarely focused on Kubernetes using our core machine learning, uh, engine to optimize metrics at the application layer, uh, that people care about and, and need to need to go after. And the truth of the matter is today. And over time, you know, setting a cluster up on Kubernetes has largely been solved. Um, and yet the promise of, of Kubernetes around portability and flexibility, uh, downstream when you operationalize the complexity, smacks you in the face. And, uh, and that's where, where storm forge comes in. And so we're a vertical, you know, kind of vertically oriented solution. Um, that's, that's absolutely focused on solving that problem. >>Well, I don't want to play, actually. I want to play the, uh, devils advocate here and, you know, >>You wouldn't be a good analyst if you didn't. >>So the, the problem is when you talk with clients, users, they, there are many of them still working with Java with, you know, something that is really tough. Mm-hmm <affirmative>, I mean, we loved all of us loved Java. Yeah, absolutely. Maybe 20 years ago. Yeah. But not anymore, but still they have developers. They are porting applications, microservices. Yes. But not very optimized, etcetera. C cetera. So it's becoming tough. So how you can interact with these kind of yeah. Old hybrid or anyway, not well in generic applications. >>Yeah. We, we do that today. We actually, part of our platform is we offer performance testing in a lower environment and stage. And we like Matt was saying, we can use any metric that you care about and we can work with any configuration for that application. So the perfect example is Java, you know, you have to worry about your heap size, your garbage collection tuning. Um, and one of the things that really struck, struck me very early on about the storm forage product is because it is true machine learning. You remove the human bias from that. So like a lot of what I did in the past, especially around SRE and, and performance tuning, we were only as good as our humans were because of what they knew. And so we were, we kind of got stuck in these paths of making the same configuration adjustments, making the same changes to the application, hoping for different results. But then when you apply machine learning capability to that, the machine will recommend things you never would've dreamed of. And you get amazing results out of >>That. So both me and an Rico have been doing this for a long time. Like I have battled to my last breath, the, the argument when it's a bare metal or a VM. Yeah. Look, I cannot give you any more memory. Yeah. And the, the argument going all the way up to the CIO and the CIO basically saying, you know what, Keith you're cheap, my developer resources expensive, my bigger box. Yep. Uh, buying a bigger box in the cloud to your point is no longer a option because it's just expensive. Talk to me about the carrot or the stick as developers are realizing that they have to be more responsible. Where's the culture change coming from? So is it, that is that if it, is it the shift in responsibility? >>I think the center of the bullseye for us is within those sets of decisions, not in a static way, but in an ongoing way, especially, um, especially as the development of applications becomes more and more rapid. And the management of them, our, our charge and our belief wholeheartedly is that you shouldn't have to choose, you should not have to choose between costs or performance. You should not have to choose where your, you know, your applications live, uh, in a public private or, or hybrid cloud environment. And so we want to empower people to be able to sit in the middle of all of that chaos and for those trade-offs and those difficult interactions to no, no longer be a thing. You know, we're at, we're at a place now where we've done, you know, hundreds of deployments and never once have we met a developer who said, I'm really excited to get outta bed and come to work every day and manually tune my application. <laugh> One side, secondly, we've never met, uh, you know, uh, a manager or someone with budget that said, uh, please don't, you know, increase the value of my investment that I've made to lift and shift us over mm-hmm <affirmative>, you know, to the cloud or to Kubernetes or, or some combination of both. And so what we're seeing is the converging of these groups, um, at, you know, their happy place is the lack of needing to be able to, uh, make those trade offs. And that's been exciting for us. So, >>You know, I'm listening and looks like that your solution is right in the middle in application per performance management, observability. Yeah. And, uh, and monitoring. So it's a little bit of all of this. >>So we, we, we, we want to be, you know, the Intel inside of all of that, mm-hmm, <affirmative>, we don't, you know, we often get lumped into one of those categories. It used to be APM a lot. We sometimes get a, are you observability or, and we're really not any of those things in and of themselves, but we, instead of invested in deep integrations and partnerships with a lot of those, uh, with a lot of that tooling, cuz in a lot of ways, the, the tool chain is hardening, uh, in a cloud native and, and Kubernetes world. And so, you know, integrating in intelligently staying focused and great at what we solve for, but then seamlessly partnering and not requiring switching for, for our users who have already invested likely in a APM or observability. >>So to go a little bit deeper. Sure. What does it mean integration? I mean, do you provide data to this, you know, other applications in, in the environment or are they supporting you in the work that you >>Yeah, we're, we're a data consumer for the most part. Um, in fact, one of our big taglines is take your observability and turn it into actionability, right? Like how do you take the it's one thing to collect all of the data, but then how do you know what to do with it? Right. So to Matt's point, um, we integrate with folks like Datadog. Um, we integrate with Prometheus today. So we want to collect that telemetry data and then do something useful with it for you. >>But, but also we want Datadog customers. For example, we have a very close partnership with, with Datadog, so that in your existing data dog dashboard, now you have yeah. This, the storm for capability showing up in the same location. Yep. And so you don't have to switch out. >>So I was just gonna ask, is it a push pull? What is the developer experience? When you say you provide developer, this resolve ML, uh, learnings about performance mm-hmm <affirmative> how do they receive it? Like what, yeah, what's the, what's the, what's the developer experience >>They can receive it. So we have our own, we used to for a while we were CLI only like any good developer tool. Right. Uh, and you know, we have our own UI. And so it is a push in that, in, in a lot of cases where I can come to one spot, um, I've got my applications and every time I'm going to release or plan for a release or I have released, and I want to take, pull in, uh, observability data from a production standpoint, I can visualize all of that within the storm for UI and platform, make decisions. We allow you to, to set your, you know, kind of comfort level of automation that you're, you're okay with. You can be completely set and forget, or you can be somewhere along that spectrum. And you can say, as long as it's within, you know, these thresholds, go ahead and release the application or go ahead and apply the configuration. Um, but we also allow you to experience, uh, the same, a lot of the same functionality right now, you know, in Grafana in Datadog, uh, and a bunch of others that are coming. >>So I've talked to Tim Crawford who talks to a lot of CIOs and he's saying one of the biggest challenges, or if not, one of the biggest challenges CIOs are facing are resource constraints. Yeah. They cannot find the developers to begin with to get this feedback. How are you hoping to address this biggest pain point for CIOs? Yeah. >>Development? >>Just take that one. Yeah, absolutely. That's um, so like my background, like I said, at United health group, right. It's not always just about cost savings. In fact, um, the way that I look about at some of these tech challenges, especially when we talk about scalability, there's kind of three pillars that I consider, right? There's the tech scalability, how am I solving those challenges? There's the financial piece, cuz you can only throw money at a problem for so long. And it's the same thing with the human piece. I can only find so many bodies and right now that pool is very small. And so we are absolutely squarely in that footprint of, we enable your team to focus on the things that they matter, not manual tuning like Matt said. And then there are other resource constraints that I think that a lot of folks don't talk about too. >>Like we were, you were talking about private cloud for instance. And so having a physical data center, um, I've worked with physical data centers that companies I've worked for have owned where it is literally full wall to wall. You can't rack any more servers in it. And so their biggest option is, well, I could spend 1.2 billion to build a new one if I wanted to. Or if you had a capability to truly optimize your compute to what you needed and free up 30% of your capacity of that data center. So you can deploy additional name spaces into your cluster. Like that's a huge opportunity. >>So either out of question, I mean, may, maybe it, it doesn't sound very intelligent at this point, but so is it an ongoing process or is it something that you do at the very beginning mean you start deploying this. Yeah. And maybe as a service. Yep. Once in a year I say, okay, let's do it again and see if something changes. Sure. So one spot 1, 1, 1 single, you know? >>Yeah. Um, would you recommend somebody performance tests just once a year? >>Like, so that's my thing is, uh, previous at previous roles I had, uh, my role was you performance test, every single release. And that was at a minimum once a week. And if your thing did not get faster, you had to have an executive exception to get it into production. And that's the space that we wanna live in as well as part of your C I C D process. Like this should be continuous verification every time you deploy, we wanna make sure that we're recommending the perfect configuration for your application in the name space that you're deploying >>Into. And I would be as bold as to say that we believe that we can be a part of adding, actually adding a step in the C I C D process that's connected to optimization and that no application should be released monitored and sort of, uh, analyzed on an ongoing basis without optimization being a part of that. And again, not just from a cost perspective, yeah. Cost end performance, >>Almost a couple of hundred vendors on this floor. You know, you mentioned some of the big ones, data, dog, et cetera. But what happens when one of the up and comings out of nowhere, completely new data structure, some imaginable way to click to elementry data. Yeah. How do, how do you react to that? >>Yeah. To us it's zeros and ones. Yeah. Uh, and you know, we're, we're, we're really, we really are data agnostic from the standpoint of, um, we're not, we we're fortunate enough to, from the design of our algorithm standpoint, it doesn't get caught up on data structure issues. Um, you know, as long as you can capture it and make it available, uh, through, you know, one of a series of inputs, what one, one would be load or performance tests, uh, could be telemetry, could be observability if we have access to it. Um, honestly the messier, the, the better from time to time, uh, from a machine learning standpoint, um, it, it, it's pretty powerful to see we've, we've never had a deployment where we, uh, where we saved less than 30% while also improving performance by at least 10%. But the typical results for us are 40 to 60% savings and, you know, 30 to 40% improvement in performance. >>And what happens if the application is, I, I mean, yes, Kubernetes is the best thing of the world, but sometimes we have to, you know, external data sources or, or, you know, we have to connect with external services anyway. Mm-hmm <affirmative> yeah. So can you, you know, uh, can you provide an indication also on, on, on this particular application, like, you know, where the problem could >>Be? Yeah, yeah. And that, that's absolutely one of the things that we look at too, cuz it's um, especially when you talk about resource consumption, it's never a flat line, right? Like depending on your application, depending on the workloads that you're running, um, it varies from sometimes minute to minute, day to day, or it could be week to week even. Um, and so especially with some of the products that we have coming out with what we want to do, you know, partnering with, uh, you know, integrating heavily with the HPA and being able to handle some of those bumps and not necessarily bumps, but bursts and being able to do it in a way that's intelligent so that we can make sure that, like I said, it's the perfect configuration for the application regardless of the time of day that you're operating in or what your traffic patterns look like. Um, or you know, what your disc looks like, right? Like cuz with our, our low environment testing, any metric you throw at us, we can, we can optimize for. >>So Madden Patrick, thank you for stopping by. Yeah. Yes. We can go all day. Because day two is I think the biggest challenge right now. Yeah. Not just in Kubernetes, but application replatforming and re and transformation. Very, very difficult. Most CTOs and S that I talked to, this is the challenge space from Valencia Spain. I'm Keith Townsend, along with my host en Rico senior. And you're watching the queue, the leader in high tech coverage.

>>Hi everybody. This is Dave Volante. Welcome to this cube conversation where we're going to go back in time a little bit and explore the early days of Kubernetes. Talk about how it formed the improbable events, perhaps that led to it. And maybe how customers are taking advantage of containers and container orchestration today, and maybe where the industry is going. Matt Provo is here. He's the founder and CEO of storm forge and Chandler Huntington hoes. Hoisington is the general manager of EKS edge and hybrid AWS guys. Thanks for coming on. Good to see you. Thanks for having me. Thanks. So, Jenny, you were the vice president of engineering at miso sphere. Is that, is that correct? >>Well, uh, vice-president engineering basis, fear and then I ran product and engineering for DTQ masons. >>Yeah. Okay. Okay. So you were there in the early days of, of container orchestration and Matt, you, you were working at a S a S a Docker swarm shop, right? Yep. Okay. So I mean, a lot of people were, you know, using your platform was pretty novel at the time. Uh, it was, it was more sophisticated than what was happening with, with Kubernetes. Take us back. What was it like then? Did you guys, I mean, everybody was coming out. I remember there was, I think there was one Docker con and everybody was coming, the Kubernetes was announced, and then you guys were there, doc Docker swarm was, was announced and there were probably three or four other startups doing kind of container orchestration. And what, what were those days like? Yeah. >>Yeah. I wasn't actually atmosphere for those days, but I know them well, I know the story as well. Um, uh, I came right as we started to pivot towards Kubernetes there, but, um, it's a really interesting story. I mean, obviously they did a documentary on it and, uh, you know, people can watch that. It's pretty good. But, um, I think that, from my perspective, it was, it was really interesting how this happened. You had basically, uh, con you had this advent of containers coming out, right? So, so there's new novel technology and Solomon, and these folks started saying, Hey, you know, wait a second, wait if I put a UX around these couple of Linux features that got launched a couple of years ago, what does that look like? Oh, this is pretty cool. Um, so you have containers starting to crop up. And at the same time you had folks like ThoughtWorks and other kind of thought leaders in the space, uh, starting to talk about microservices and saying, Hey, monoliths are bad and you should break up these monoliths into smaller pieces. >>And any Greenfield application should be broken up into individuals, scalable units that a team can can own by themselves, and they can scale independent of each other. And you can write tests against them independently of other components. And you should break up these big, big mandalas. And now we are kind of going back to model this, but that's for another day. Um, so, so you had microservices coming out and then you also had containers coming out, same time. So there was like, oh, we need to put these microservices in something perfect. We'll put them in containers. And so at that point, you don't really, before that moment, you didn't really need container orchestration. You could just run a workload in a container and be done with it, right? You didn't need, you don't need Kubernetes to run Docker. Um, but all of a sudden you had tons and tons of containers and you had to manage these in some way. >>And so that's where container orchestration came, came from. And, and Ben Heineman, the founder of Mesa was actually helping schedule spark at the time at Berkeley. Um, and that was one of the first workloads with spark for Macy's. And then his friends at Twitter said, Hey, come over, can you help us do this with containers at Twitter? He said, okay. So when it helped them do it with containers at Twitter, and that's kinda how that branch of the container wars was started. And, um, you know, it was really, really great technology and it actually is still in production in a lot of shops today. Um, uh, more and more people are moving towards Kubernetes and Mesa sphere saw that trend. And at the end of the day, Mesa sphere was less concerned about, even though they named the company Mesa sphere, they were less concerned about helping customers with Mesa specifically. They really want to help customers with these distributed problems. And so it didn't make sense to, to just do Mesa. So they would took on Kubernetes as well. And I hope >>I don't do that. I remember, uh, my, my co-founder John furrier introduced me to Jerry Chen way back when Jerry is his first, uh, uh, VC investment with Greylock was Docker. And we were talking in these very, obviously very excited about it. And, and his Chandler was just saying, it said Solomon and the team simplified, you know, containers, you know, simple and brilliant. All right. So you guys saw the opportunity where you were Docker swarm shop. Why? Because you needed, you know, more sophisticated capabilities. Yeah. But then you, you switched why the switch, what was happening? What was the mindset back then? We ran >>And into some scale challenges in kind of operationalize or, or productizing our kind of our core machine learning. And, you know, we, we, we saw kind of the, the challenges, luckily a bit ahead of our time. And, um, we happen to have someone on the team that was also kind of moonlighting, uh, as one of the, the original core contributors to Kubernetes. And so as this sort of shift was taking place, um, we, we S we saw the flexibility, uh, of what was becoming Kubernetes. Um, and, uh, I'll never forget. I left on a Friday and came back on a Monday and we had lifted and shifted, uh, to Kubernetes. Uh, the challenge was, um, you know, you, at that time, you, you didn't have what you have today through EKS. And, uh, those kinds of services were, um, just getting that first cluster up and running was, was super, super difficult, even in a small environment. >>And so I remember we, you know, we, we finally got it up and running and it was like, nobody touch it, don't do anything. Uh, but obviously that doesn't, that doesn't scale either. And so that's really, you know, being kind of a data science focused shop at storm forge from the very beginning. And that's where our core IP is. Uh, our, our team looked at that problem. And then we looked at, okay, there are a bunch of parameters and ways that I can tune this application. And, uh, why are the configurations set the way that they are? And, you know, uh, is there room to explore? And that's really where, unfortunately, >>Because Mesa said much greater enterprise capabilities as the Docker swarm, at least they were heading in that direction, but you still saw that Kubernetes was, was attractive because even though it didn't have all the security features and enterprise features, because it was just so simple. I remember Jen Goldberg who was at Google at the time saying, no, we were focused on keeping it simple and we're going from mass adoption, but does that kind of what you said? >>Yeah. And we made a bet, honestly. Uh, we saw that the, uh, you know, the growing community was really starting to, you know, we had a little bit of an inside view because we had, we had someone that was very much in the, in the original part, but you also saw the, the tool chain itself start to, uh, start to come into place right. A little bit. And it's still hardening now, but, um, yeah, we, as any, uh, as any startup does, we, we made a pivot and we made a bet and, uh, this, this one paid off >>Well, it's interesting because, you know, we said at the time, I mean, you had, obviously Amazon invented the modern cloud. You know, Microsoft has the advantage of has got this huge software stays, Hey, just now run it into the cloud. Okay, great. So they had their entry point. Google didn't have an entry point. This is kind of a hail Mary against Amazon. And, and I, I wrote a piece, you know, the improbable, Verizon, who Kubernetes to become the O S you know, the cloud, but, but I asked, did it make sense for Google to do that? And it never made any money off of it, but I would argue they, they were kind of, they'd be irrelevant if they didn't have, they hadn't done that yet, but it didn't really hurt. It certainly didn't hurt Amazon EKS. And you do containers and your customers you've embraced it. Right. I mean, I, I don't know what it was like early days. I remember I've have talked to Amazon people about this. It's like, okay, we saw it and then talk to customers, what are they doing? Right. That's kind of what the mindset is, right? Yeah. >>That's, I, I, you know, I've, I've been at Amazon a couple of years now, and you hear the stories of all we're customer obsessed. We listened to our customers like, okay, okay. We have our company values, too. You get told them. And when you're, uh, when you get first hired in the first day, and you never really think about them again, but Amazon, that really is preached every day. It really is. Um, uh, and that we really do listen to our customers. So when customers start asking for communities, we said, okay, when we built it for them. So, I mean, it's, it's really that simple. Um, and, and we also, it's not as simple as just building them a Kubernetes service. Amazon has a big commitment now to start, you know, getting involved more in the community and working with folks like storm forage and, and really listening to customers and what they want. And they want us working with folks like storm florigen and that, and that's why we're doing things like this. So, well, >>It's interesting, because of course, everybody looks at the ecosystem, says, oh, Amazon's going to kill the ecosystem. And then we saw an article the other day in, um, I think it was CRN, did an article, great job by Amazon PR, but talk about snowflake and Amazon's relationship. And I've said many times snowflake probably drives more than any other ISV out there. And so, yeah, maybe the Redshift guys might not love snowflake, but Amazon in general, you know, they're doing great three things. And I remember Andy Jassy said to me, one time, look, we love the ecosystem. We need the ecosystem. They have to innovate too. If they don't, you know, keep pace, you know, they're going to be in trouble. So that's actually a healthy kind of a dynamic, I mean, as an ecosystem partner, how do you, >>Well, I'll go back to one thing without the work that Google did to open source Kubernetes, a storm forge wouldn't exist, but without the effort that AWS and, and EKS in particular, um, provides and opens up for, for developers to, to innovate and to continue, continue kind of operationalizing the shift to Kubernetes, um, you know, we wouldn't have nearly the opportunity that we do to actually listen to them as well, listen to the users and be able to say, w w w what do you want, right. Our entire reason for existence comes from asking users, like, how painful is this process? Uh, like how much confidence do you have in the, you know, out of the box, defaults that ship with your, you know, with your database or whatever it is. And, uh, and, and how much do you love, uh, manually tuning your application? >>And, and, uh, obviously nobody's said, I love that. And so I think as that ecosystem comes together and continues expanding, um, it's just, it opens up a huge opportunity, uh, not only for existing, you know, EKS and, uh, AWS users to continue innovating, but for companies like storm forge, to be able to provide that opportunity for them as well. And, and that's pretty powerful. So I think without a lot of the moves they've made, um, you know, th the door wouldn't be nearly as open for companies like, who are, you know, growing quickly, but are smaller to be able to, you know, to exist. >>Well, and I was saying earlier that, that you've, you're in, I wrote about this, you're going to get better capabilities. You're clearly seeing that cluster management we've talked about better, better automation, security, the whole shift left movement. Um, so obviously there's a lot of momentum right now for Kubernetes. When you think about bare metal servers and storage, and then you had VM virtualization, VMware really, and then containers, and then Kubernetes as another abstraction, I would expect we're not at the end of the road here. Uh, what's next? Is there another abstraction layer that you would think is coming? Yeah, >>I mean, w for awhile, it looked like, and I remember even with our like board members and some of our investors said, well, you know, well, what about serverless? And, you know, what's the next Kubernetes and nothing, we, as much as I love Kubernetes, um, which I do, and we do, um, nothing about what we particularly do. We are purpose built for Kubernetes, but from a core kind of machine learning and problem solving standpoint, um, we could apply this elsewhere, uh, if we went that direction and so time will tell what will be next, then there will be something, uh, you know, that will end up, you know, expanding beyond Kubernetes at some point. Um, but, you know, I think, um, without knowing what that is, you know, our job is to, to, to serve our, you know, to serve our customers and serve our users in the way that they are asking for that. >>Well, serverless obviously is exploding when you look again, and we tucked the ETR survey data, when you look at, at the services within Amazon and other cloud providers, you know, the functions off, off the charts. Uh, so that's kind of an interesting and notable now, of course, you've got Chandler, you've got edge in your title. You've got hybrid in, in your title. So, you know, this notion of the cloud expanding, it's not just a set of remote services, just only in the public cloud. Now it's, it's coming to on premises. You actually got Andy, Jesse, my head space. He said, one time we just look at it. The data centers is another edge location. Right. Okay. That's a way to look at it and then you've got edge. Um, so that cloud is expanding, isn't it? The definition of cloud is, is, is evolving. >>Yeah, that's right. I mean, customers one-on-one run workloads in lots of places. Um, and that's why we have things like, you know, local zones and wavelengths and outposts and EKS anywhere, um, EKS, distro, and obviously probably lots more things to come. And there's, I always think of like, Amazon's Kubernetes strategy on a manageability scale. We're on one far end of the spectrum, you have EKS distro, which is just a collection of the core Kubernetes packages. And you could, you could take those and stand them up yourself in a broom closet, in a, in a retail shop. And then on the other far in the spectrum, you have EKS far gate where you can just give us your container and we'll handle everything for you. Um, and then we kind of tried to solve everything in between for your data center and for the cloud. And so you can, you can really ask Amazon, I want you to manage my control plane. I want you to manage this much of my worker nodes, et cetera. And oh, I actually want help on prem. And so we're just trying to listen to customers and solve their problems where they're asking us to solve them. Cut, >>Go ahead. No, I would just add that in a more vertically focused, uh, kind of orientation for us. Like we, we believe that op you know, optimization capabilities should transcend the location itself. And, and, and so whether that's part public part, private cloud, you know, that's what I love part of what I love about EKS anywhere. Uh, it, you know, you shouldn't, you should still be able to achieve optimal results that connect to your business objectives, uh, wherever those workloads, uh, are, are living >>Well, don't wince. So John and I coined this term called Supercloud and people laugh about it, but it's different. It's, it's, you know, people talk about multi-cloud, but that was just really kind of vendor diversity. Right? I got to running here, I'm running their money anywhere. Uh, but, but individually, and so Supercloud is this concept of this abstraction layer that floats wherever you are, whether it's on prem, across clouds, and you're taking advantage of those native primitives, um, and then hiding that underlying complexity. And that's what, w re-invent the ecosystem was so excited and they didn't call it super cloud. We, we, we called it that, but they're clearly thinking differently about the value that they can add on top of Goldman Sachs. Right. That to me is an example of a Supercloud they're taking their on-prem data and their, their, their software tooling connecting it to AWS. They're running it on AWS, but they're, they're abstracting that complexity. And I think you're going to see a lot, a lot more of that. >>Yeah. So Kubernetes itself, in many cases is being abstracted away. Yeah. There's a disability of a disappearing act for Kubernetes. And I don't mean that in a, you know, in an, a, from an adoption standpoint, but, uh, you know, Kubernetes itself is increasingly being abstracted away, which I think is, is actually super interesting. Yeah. >>Um, communities doesn't really do anything for a company. Like we run Kubernetes, like, how does that help your bottom line? That at the end of the day, like companies don't care that they're running Kubernetes, they're trying to solve a problem, which is the, I need to be able to deploy my applications. I need to be able to scale them easily. I need to be able to update them easily. And those are the things they're trying to solve. So if you can give them some other way to do that, I'm sure you know, that that's what they want. It's not like, uh, you know, uh, a big bank is making more money because they're running Kubernetes. That's not, that's not the current, >>It gets subsumed. It's just become invisible. Right. Exactly. You guys back to the office yet. What's, uh, what's the situation, >>You know, I, I work for my house and I, you know, we go into the office a couple of times a week, so it's, it's, uh, yeah, it's, it's, it's a crazy time. It's a crazy time to be managing and hiring. And, um, you know, it's, it's, it's, it's definitely a challenge, but there's a lot of benefits of working home. I got two young kids, so I get to see them, uh, grow up a little bit more working, working out of my house. So it's >>Nice also. >>So we're in, even as a smaller startup, we're in 26, 27 states, uh, Canada, Germany, we've got a little bit of presence in Japan, so we're very much distributed. Um, we, uh, have not gone back and I'm not sure we will >>Permanently remote potentially. >>Yeah. I mean, w we made a, uh, pretty like for us, the timing of our series B funding, which was where we started hiring a lot, uh, was just before COVID started really picking up. So we, you know, thankfully made a, a pretty good strategic decision to say, we're going to go where the talent is. And yeah, it was harder to find for sure, especially in w we're competing, it's incredibly competitive. Uh, but yeah, we've, it was a good decision for us. Um, we are very about, you know, getting the teams together in person, you know, as often as possible and in the safest way possible, obviously. Um, but you know, it's been a, it's been a pretty interesting, uh, journey for us and something that I'm, I'm not sure I would, I would change to be honest with you. Yeah. >>Well, Frank Slootman, snowflakes HQ to Montana, and then can folks like Michael Dell saying, Hey, same thing as you, wherever they want to work, bring yourself and wherever you are as cool. And do you think that the hybrid mode for your team is kind of the, the, the operating mode for the, for the foreseeable future is a couple of, >>No, I think, I think there's a lot of benefits in both working from the office. I don't think you can deny like the face-to-face interactions. It feels good just doing this interview face to face. Right. And I can see your mouth move. So it's like, there's a lot of benefits to that, um, over a chime call or a zoom call or whatever, you know, that, that also has advantages, right. I mean, you can be more focused at home. And I think some version of hybrid is probably in the industry's future. I don't know what Amazon's exact plans are. That's above my pay grade, but, um, I know that like in general, the industry is definitely moving to some kind of hybrid model. And like Matt said, getting people I'm a big fan at Mesa sphere, we ran a very diverse, like remote workforce. We had a big office in Germany, but we'd get everybody together a couple of times a year for engineering week or, or something like this. And you'd get a hundred people, you know, just dedicated to spending time together at a hotel and, you know, Vegas or Hamburg or wherever. And it's a really good time. And I think that's a good model. >>Yeah. And I think just more ETR data, the current thinking now is that, uh, the hybrid is the number one sort of model, uh, 36% that the CIO is believe 36% of the workforce are going to be hybrid permanently is kind of their, their call a couple of days in a couple of days out. Um, and the, the percentage that is remote is significantly higher. It probably, you know, high twenties, whereas historically it's probably 15%. Yeah. So permanent changes. And that, that changes the infrastructure. You need to support it, the security models and everything, you know, how you communicate. So >>When COVID, you know, really started hitting and in 2020, um, the big banks for example, had to, I mean, you would want to talk about innovation and ability to, to shift quickly. Two of the bigger banks that have in, uh, in fact, adopted Kubernetes, uh, were able to shift pretty quickly, you know, systems and things that were, you know, historically, you know, it was in the office all the time. And some of that's obviously shifted back to a certain degree, but that ability, it was pretty remarkable actually to see that, uh, take place for some of the larger banks and others that are operating in super regulated environments. I mean, we saw that in government agencies and stuff as well. >>Well, without the cloud, no, this never would've happened. Yeah. >>And I think it's funny. I remember some of the more old school manager thing people are, aren't gonna work less when they're working from home, they're gonna be distracted. I think you're seeing the opposite where people are too much, they get burned out because you're just running your computer all day. And so I think that we're learning, I think everyone, the whole industry is learning. Like, what does it mean to work from home really? And, uh, it's, it's a fascinating thing is as a case study, we're all a part of right now. >>I was talking to my wife last night about this, and she's very thoughtful. And she w when she was in the workforce, she was at a PR firm and a guy came in a guest speaker and it might even be in the CEO of the company asking, you know, what, on average, what time who stays at the office until, you know, who leaves by five o'clock, you know, a few hands up, or who stays until like eight o'clock, you know, and enhancement. And then, so he, and he asked those people, like, why, why can't you get your work done in a, in an eight hour Workday? I go home. Why don't you go in? And I sit there. Well, that's interesting, you know, cause he's always looking at me like, why can't you do, you know, get it done? And I'm saying the world has changed. Yeah. It really has where people are just on all the time. I'm not sure it's sustainable, quite frankly. I mean, I think that we have to, you know, as organizations think about, and I see companies doing it, you guys probably do as well, you know, take a four day, you know, a week weekend, um, just for your head. Um, but it's, there's no playbook. >>Yeah. Like I said, we're a part of a case study. It's also hard because people are distributed now. So you have your meetings on the east coast, you can wake up at seven four, and then you have meetings on the west coast. You stay until seven o'clock therefore, so your day just stretches out. So you've got to manage this. And I think we're, I think we'll figure it out. I mean, we're good at figuring this stuff. >>There's a rise in asynchronous communication. So with things like slack and other tools, as, as helpful as they are in many cases, it's a, it, isn't always on mentality. And like, people look for that little green dot and you know, if you're on the you're online. So my kids, uh, you know, we have a term now for me, cause my office at home is upstairs and I'll come down. And if it's, if it's during the day, they'll say, oh dad, you're going for a walk and talk, you know, which is like, it was my way of getting away from the desk, getting away from zoom. And like, you know, even in Boston, uh, you know, getting outside, trying to at least, you know, get a little exercise or walk and get, you know, get my head away from the computer screen. Um, but even then it's often like, oh, I'll get a slack notification on my phone or someone will call me even if it's not a scheduled walk and talk. Um, uh, and so it is an interesting, >>A lot of ways to get in touch or productivity is presumably going to go through the roof. But now, all right, guys, I'll let you go. Thanks so much for coming to the cube. Really appreciate it. And thank you for watching this cube conversation. This is Dave Alante and we'll see you next time.

(upbeat music) >> Welcome back to theCUBE's coverage of AWS re:Invent 2021. I'm John Furrier, host of theCUBE. You're watching CUBE's worldwide leader in tech coverage. We're in person on the show floor. It's also a hybrid event, online as well. CUBE coverage online with Amazon re:Invent site. Great content all around, amazing announcements, transformation in all areas are exploding and in innovation, of course, we have innovation here with Sandy Carter, the worldwide public sector vice-president of partners and programs for Amazon Web Services. Sandy, welcome back, CUBE alumni. Great to see you. Thanks for coming on theCUBE. >> Great to see you and great to see you in person again. It's so exciting. The energy level, oh my God. >> Oh my God. It's so much. Thanks, great keynote. Good to see you again in person. A lot of action, give us the top announcements. What's going on? What are the top 10 AWS announcements? >> Yeah, so we, this year for 2022, as we frame it out, we decided on a 3D strategy, a three-dimensional strategy. So we started with destination then data and then delivery. So if I could do them in that order, does that sound good? >> Yeah. Destination. >> So let's start with destination. So I got this from one of the customers and he said to me, "look, Sandy, I thought it was all going to be about getting to the cloud. But when I got to the cloud, I realized it wasn't about just in the cloud, it was about what you do in the cloud." And so we made some announcements this morning, especially around migration, modernization, and optimization. So for migration, we have the mainframe announcement that Adam made, and then we also echoed it. Cause most of the mainframes today sit in public sector. So this is a managed service, it's working with Micro Focus, one of our partners. And Lockheed Martin one of our partners is one of the first into the mainframe migration, which is a service and services to help customers transform their business with the mainframe. And then as we compliment them, we look at that we also have modernization occurring. So for example, IoT. IDC tells us that IoT and that data has increased four times since COVID because now devices and sensors are tracking a lot of data. So we made an announcement around smart cities and we now have badging for our partners. We have 18 partners solutions now in smart cities. So working backwards from the partners they were talking about given now COVID is kind of in the midst of where it is smart cities and making those cities work better in public transportation and utility, it's just all where it's at. And then the final announcement in that category is containers. So 60% of our customers said that they're going to be using containers. So we announced a Rapid Adoption Assistance program for our partners to be able to help our customers move to containers overall. >> So mainframe migration, I saw that on stage, but Micro Focus, that was a good job. Get that legacy out of the way, move to the cloud. You've got smart cities, which is basically IoT, which brings cloud to the edge. And then containerization for the cloud native, either development or compatibility, interoperability kind of sets that table. That's the destination. >> That's right. That's right. Because all of those things, you know, you've got to get the mainframe to the cloud, but then it's about modernizing, right? Getting rid of all that COBOL code and then, you know, IoT and then making sure that you are ready to go with containers. It's the newest- >> So you've got the 3D, destination, data and delivery. >> That's right. >> Okay. Destination, check. Cloud. Cloud destination. >> Yeah. >> I'm putting dots together in real time. >> Destination cloud. There you go. You've got it. >> I'm still with it after all these interviews. >> Yeah, there you go. >> Data, I'll say killer Swami's onstage today, whole new data, multiple databases. What's the data focus in this area? >> So for our partners, first it's about getting the data to the cloud, which means that we need a way to really migrate it. So we announced an initiative to help get that data to the cloud. We had a set of partners that came on with us early on in this initiative to move that data to the cloud, it's called a Rapid Adoption Assistance, which helps you envision where you want to go with your data. Do you want to put it in a data lake? Do you want data stored as it is? What do you want to visualize? What do you want to do with analytics? So envision that and then get enablement. So all the new announcements, all the new services get enablement and then to pilot it. And then the second announcement in this area is a set of private offers in the marketplace. Our customers told us that they love to go after data, but that there's too many pieces and moving parts. So they need the assessment bundled with the managed service and everything bundled together so it's a solution for them. So those were our two announcements in the data area. >> So take me through the private marketplace thing, because this came up when I was talking with Stephen Orban who's now running the marketplace. What does that mean? So you're saying that this private offer is being enabling the suppliers and in government? >> Yeah. So available in the marketplace, a lot of our government agencies can buy from the marketplace. So if they have a contract, they can come and buy. But instead of having to go and say, okay, here's an assessment to tell me what I should do, now here's the offering, and now here's the managed service, they want it bundled together. So we have a set of offerings that have that bundled together today with the set of our great public sector partners. >> So tons of data action, where's the delivery fit in? >> So delivery. This one is very interesting because our customers are telling us that they no longer want just technology skills, they also need industry skills too. So they're looking for that total package. For example, you know, the state of New Jersey when hurricane Ida hit, category four storm, they wanted someone who obviously could leverage all the data, but they wanted someone who understood disaster response. And so Maxar fits that bill. They have that industry specialty along with the technology specialty. And so for our announcements here, we announced a new competency, which is an industry competency for energy. So think about renewables and sustainability and low carbon. These are the partners that do that. We have 32 different partners who met the needs of that energy competency. So we were able to GA that here today. The other really exciting announcement that we made was for small businesses to get extra training, it's called Think Big for Small Business communities. So we announced last year virtually, Think Big for Small Business. We now have about 200 companies who are part of that program, really getting extra help as diverse companies. Women owned, black owned, brown owned, veteran owned businesses, right? But now what they told us was in addition to the AWS help, what they loved is how we connected them together and we almost just stumbled upon it. I was hosting some meetings and I had Tia from Bellflower, I had Lisa from DLZP together and they got a lot of value just being connected. And we kept hearing that over and over and over again. So now we've programmatized that so it's more scalable than me introducing people to each other. We now have a program to introduce those small business leaders to each other. And then the last one that we announced is our AWS government competency is now the largest competency at AWS. So the government competency, which is pretty powerful. So now we're going to do a focus enhancement for federal. So all of our federal partners with all that opportunity can now take advantage of some private advisory council, some additional training that will go on there, additional go-to market support that they can use to help them. >> Okay. I feel like my brain is going to explode. Those are just the announcements here. There's a lot going. >> Yeah. There's a lot going on. >> I mean it's so much you've got to put them into buckets. Okay. What's the rationale around 3D? Delivery, data... I mean, destination, delivery, data. Destination, meaning cloud. Data, meeting data. And delivery meaning just new ways to get up and running- >> Skills. >> To get this delivery for the services. >> Yep. >> Okay. So is there a pattern emerging? What can you say? Cause remember we talked about this before a year ago, as well as in person at your public sector summit with your partners. Is there a pattern emerging that you're seeing here? Cause lots of the announcements are coming, done with the mainframes. Connect on your watch has been a big explosion. Adam Slansky told me personally, it's on fire. And public sector, we saw a lot of that. >> Well, in fact, you know, if you look at public sector, three factoids that we shared this morning in the keynote. Our public sector partners grew 54% this year, this is after last year we grew 45%. They grew the number of certifications that they had by 40% and the number of new customers by 32%. I mean, those are unreal numbers. Last year we did 28% new customers and we thought that was the cat's meow, now we're at 32%. So our partners are just exploding in this public sector space right now. >> It's almost as if they have an advantage because they dragged their feet for so long. >> It's true. It's true. COVID accelerated their movement to the cloud. >> A lot of slow moving verticals because of the legacy and whether it's regulation or government funding or skills- >> Or mainframes. >> All had to basically move fast, they had no excuses. And then the cloud kind of changes everyone's mindset. How about the culture? I want to ask you about the culture in the public sector, because this is coming up a lot. Again, a lot of your customers that I'm interviewing all talk... and I try to get them to talk about horizontally scalable and machine learning, and they're always, no, it's culture. >> Yeah. It's true. >> Culture is the number one thing. >> It is true. You know, culture eats strategy for lunch. So even if you have a great strategy around the cloud, if you don't have that right culture, you won't win in the marketplace. So we are seeing this a lot. In fact, one of our most popular programs is PTP, Partner Transformation Program. And it lays out a hundred day program on cloud best practices. And guess what's the number one topic? Culture. Culture, governance, technology, all of those things are so important right now. And I think because, you know, a lot of the agencies and governments and countries, they had moved to the cloud now that they're in the cloud, they went through that pain during COVID, now they're seeing all the impact of artificial intelligence and containers and blockchain and all of that, right? It's just crazy. >> That's a great insight. And I'll add to that because I think one of the things I've observed, especially with your partners is the fear of getting eliminated by technology or the fear of having a job change or fear of change in general went away once they started using it because they saw the criticality of the cloud and how it impacted their job, but then what it offered them as new opportunities. In fact, it actually increases more areas to innovate on and do more, whether it's job advancement or cross training or lateral moves, promotion, that's a huge retention piece. >> It really is. And I will tell you that the movement to the cloud enabled people to see it wasn't as scary as they thought it was going to be, and that they could still leverage a lot of the skills that they had and learn new ones. So I think it is. And this is one of the reasons why, I was just talking with Maureen launching that 29 million training program for the cloud, that really touches public sector because there is so many agencies, countries, governments that need to have that training. >> You're talking about Maureen Lonergan, she does the training. She's been working on that for years. >> Yeah. >> That's the only getting better and better. >> Yeah. >> Well Sandy, I've got to ask you, since you have a few minutes left, I want to ask you about your journey. >> Yeah. >> We've interviewed you going back a long time look where we are now. >> I know. It's incredible. >> Look at these two sets going on at CUBE. >> You've been an incredible voice on theCUBE. We really appreciate having you on because you're innovative. You're always moving like a shark. You can't sit still. You're always innovating. Still going on, you had the great women's luncheon from 20 to 200. >> Yeah, we grew. So we started out with 20 people back five years ago and now we had about 200 women and it was incredible because we do different topics. Our topic was around empathy and empathetic leadership. And you know how you can really leverage that today, back with the skills and your people. You know, given that Amazon just announced our new leadership principle about wanting to be the Earth's most employee centric company. It fits right in, empathetic leadership. And we had amazing women at that luncheon that told some great stories about empathy that I think will live in our hearts forever. >> And the other thing I want to point out, we had some of the guests on sitting on theCUBE. We had Linda Jojo from United airlines. >> Oh yeah. >> And a little factoid, yesterday in the keynote, 50% of the speakers were women. >> I know. The first time I did a blog post on it, like we had two amazing women in STEM and we had, you know, the black pilot that was highlighted. So it's showing more diversity. So I was just so excited. Thank you Adam, for doing that because I think that was an amazing, amazing focus here at the conference. >> I wanted to bring up a point. I had a note here to bring up to you. Public sector, you guys doubled the number of partners, large migrations this year. That's a big statoid. You've had 575,000 individuals hold active certifications. Okay. That grew 40% from August 2021, clearly a pandemic impact. A lot of people jumping back in getting their certs, migrating so if they're not... They're in between transitions where they have a tailwind or a headwind, whether you're United Airlines or whether you're Zoom, you got some companies were benefiting from the pandemic and some were retooling. That's something that we talked about actually at the beginning. >> That's right. Absolutely. And I do think that those certifications also demonstrate that customers have raised the bar on what they expect from a partner. It's no longer just like that technology input, it's also that industry side. And so you see the number of certifications going up because customers are demanding higher skill level. And by the way, for the partners we conducted a study with ESG and ESG said that more skilled partners, you drive more margin, profit margin, 42% more profit margin for a higher skilled partner. And we're seeing that really come to fruition with some of these really intense focus on getting more certifications and more training. >> I want to get your thoughts on the healthcare and life science. I just got a note here that tells me that the vertical is one of the fastest growing verticals with 105% year on year growth. Healthcare and life sciences, another important... Again, a lot of legacy, a lot of old silos, forced to expand and innovate with the pandemic growing. >> Yes. You know, government is our largest segment today, our largest competency. Healthcare is our fastest growing segment. So we have a big focus there. And like you said, it's not just around, you know, seeing things stay the same. It's about digital transformation. It's one of the reasons we're also seeing such an increase in our authority to operate program both on the government side and the healthcare side. So we do, you know, FedRAMP and IL5. We had six companies that got IL5, five of them in 2021, which is an amazing achievement. And then, you know, if you think about the healthcare side, our fastest growing compliance is HIPAA and HITRUST. And that ATO program really brings best practices and templates and stronger go to market for those partners too. >> Yeah. I mean, I think it's opportunity recognition and then capture during the pandemic with the cloud. More agility, more speed. >> That's right. >> Sandy, always great to have you on. In the last couple of seconds we have left, summarize the top 10 announcements in a bumper sticker. If you had to kind of put that bumper sticker on the car as it drives away from re:Invent this year, what's on that bumper sticker? What's it say? >> Partners that focus on destination, data and delivery will grow faster and add more value to their customers. >> There it is. The three dimension, DDD. Delivery... Destination, data and delivery. >> There you go. >> Here on theCUBE, bringing you all the data live on the ground here, CUBE studios, two sets wall-to-wall coverage. You're watching theCUBE, the leader in global tech coverage. I'm John Furrier your host. Thanks for watching. (soft techno music)

(calm techno music) >> Hey, welcome to this Cube Conversation. I'm Lisa Martin. I've got two guests here with me. Please Welcome Philipp Niemietz, the intermediate head of the department for the Laboratory of Machine Tools and Production Engineering or WZL. Philipp, welcome to the program. >> Thank you. >> And we have Russ Caldwell here as well, senior product manager at Dell Technologies. Russ, great to see you. >> Thanks for the invite. >> Absolutely. We're going to be talking about how the enhanced video capabilities of Dell EMC's streaming data platform are enabling manufacturing, anomaly detection, and quality control through the use of sensors, cameras, and x-ray cameras. We're going to go ahead, Philipp, and start with you. We're abbreviating the lab as you guys do as WZL. Talk to us about the lab. What types of problems are you solving? >> Yeah, thank you. In the laboratory for machine tools, we are looking at actually all the other problems that arise in production engineering in general. So that's from the actual manufacturing of work pieces and that's getting used in aerospace or automotive industries, and really dig into the specifics of how those metal parts are manufactured, how they are formed, what are the mechanics of this. So this is a very traditional area where we are coming from. We're also looking at like how to manage all those production systems, how to come up with decision-making processes that's moving those engineering environments forward. But in our department, we recently get... 10 years ago... This Industry 4.0 scenario is getting more and more pushed into authentic research. So more and more data is gathered. We have to deal with a lot of data coming from various sources, and how to actually include this in the research, how to derive new findings from this, or even maybe, even physical equations from all the data that we are gathering around this manufacturing technologies. And this is something that we're, from the research perspective, looking at. >> And talk to me about when you were founded. You're based in Germany, but when was the lab founded? >> The lab was founded 100 years ago, about 100 years ago. It's like a very long history. It is the largest institute for production engineering in Germany, or maybe even in Europe. >> Got it. Okay. Well, 100 years. Amazing innovation that I'm sure the lab has seen. Russ, let's go over to you. Talk to us about the Dell EMC streaming data platform or SDP is what referred to it. >> Yeah. Thanks Lisa. So it's interesting that Philipp brings up Industry 4.0 because this is a prime area where the streaming data platform comes into play. Industry 4.0 for manufacturing really kind of encompasses a few things. It's real-time data analysis. It's automation, machine learning. SDP pulls all that together. So it's a software solution from Dell EMC. And one of the ways we make it all happen is we've unified this concept of time in data. Historical data and real-time data are typically analyzed very, very differently. And so we're trying to support Industry 4.0 manufacturing use cases. That's really important, right? Looking at historical data and real-time data, so you can learn from the past, work you've done on the factory floor, and apply that in real-time analytics. And the platform is used to ingest store and analyze data of this real-time and historical data. It leverages a high availability and dynamic scaling with Kubernetes. So that makes it possible to have lot different projects on the platform. And it really offers a lot of methods to automate this high speed and high precision activities that Philipp's talking about here. There's a lot of examples where it comes into play. It's really exciting to work with Philipp and the team there in Germany. But what's great about it is it's a general purpose platform that supports things like construction where they're doing drones with video ingestion, tracking resources on the ground, and things like that. Predictive maintenance and safety for amusement parks, and many other use cases. But with Industry 4.0 and manufacturing, RWTH and Philipp's team has really kind of pushed the boundaries of what's possible to automate and analyze data for the manufacturing process. >> What a great background. So we understand about the lab. We understand about Dell EMC SDP. Philipp, let's go back to you. How was the lab using this technology? >> Yeah, good question. Maybe, going a little bit back to the details of the use case that we are presenting. We started maybe five, six years ago where all this Industry 4.0 was put into research where you wanted to get more data out of the process now. So we started to apply a little census to the machine, starting with the more traditional ones, like energy consumption and some control information that we get from the machine tool itself. But the sensor system are quite like not that complex. And we could deal with the amount of data fairly easy now using just a USB sticks and some local devices, just a storage. But as it's getting more sophisticated, we're getting more sensor data. We're applying new sensor systems with the tool where the extra process is taking place, throughout the year, like delicious information is hidden. So we're getting really close to the process, applying video data, bigger data streams, more sensor data, and even like are not something like an IoT scenarios. We usually have some data points per second, but we're talking here about census that have like maybe a million data points a second now. So every high frequencies that we have to deal with, and of course, then we had to come up with some system that actually have to do this, help to deal with this data. And yeah, use the classic big data stack that we then set up for ourselves in our research facility to deal with this amount of streaming data to then apply historical analysis. Like Russ just talked about on this classic Hadoop data stack where we used Kafka and Storm for ingestion, and then for streaming processing, and Spark for this traditional historical analysis. And actually, this is exactly where the streaming data platform came into play because we had a meeting with one of the techy account at the university. And we were like talking about this. We were having a chat about this problem. And he's like, "Oh, we have something going on in America, in USA with this a streaming data platform. It was still under a code name or something." And then actually, Russ and I got into contact then talking about the streaming data platform, and how we could actually use it, and get getting part. We were taking part in the alpha program, really working with the system with the developers. And it was really an amazing experience. >> Were you having scale problems with the original kind of traditional big data platform that you talked about with Hadoop, Apache, Kafka, Spark? Was that scale issues, performance issues? Is that why you looked to Dell EMC? >> Yeah. There were several issues, like one is the scaling option now. And when we were not always using all of the sensors, we are just using some of the sensors. We're thinking about account process to different manufacturing technologies, different machines that we have in our laboratory so that we can quickly add sensors. They are shut down sensors. Do not have to take care about setting up new workers or stuff so that the work balance is handled. But that's not the only thing. We also had a lot of issues with administrating this Hadoop stacks. It's quite error prone if you do it yourself, like we are still in the university even though we are very big level laboratory. We still have limited resources. So we spend a lot of time dealing with the dev ops of the system. And actually, this is something where on the streaming data platform actually helped us to reduce the time that we invested into this administration processes. We were able to take more time into the analytics, which is actually what we are interested in. And specifically, the point that Russ talked about this unified concept of time, we now can just apply one and that type of analysis on historical and streaming data, and do not have to separate domains that we have to deal with. Now we dealt with Kafka, and Storm on one side, and Spark on the other side. And now, we can just put it into one model and actually reduce the time now to maintain and handle and implement the code. >> The time reduction is critical for the overall laboratory, the workforce productivity of the folks that are using it. Russ, let's go back to you. Tell us about, first of all, how long has the Dell EMC SDP been around? And what are some of the key features that WZL is leveraging that you're also seeing benefit other industries? >> So the product actually officially launched in early 2020. So in the first quarter of 2020. But what Philipp was just talking about, his organization was actually in the alpha and the beta programs earlier than that in 2019. And that's actually where we had a cross-section of very different kinds of companies in all sorts of industries all over the world; in Japan, and Germany, in the US. And that's where we started to see this pattern of commonality of challenges, and how we could solve those. So one of those things we mentioned that unified concept of time is really powerful because with one line of code, you can actually jump to any point on the timeline of your data, whether it's the real-time data coming off of the sensors right now or something minutes, hours, years ago. And so it's really, really powerful for the developers. But we saw the common challenges that Philipp was just talking about everywhere. So the SDP, one of the great things about it is it's a single piece of software that will install, manage, secure, upgrade, and be supported of all the components that you just heard Philipp talking about. So all the pieces for the ingestion, the storage and the analytics are all in there. And that makes it easier to focus on the problem there. There was other common challenges that our customers were seeing as well. Things like this concept of derived streams, so that you can actually bring in raw streams of data, leave it in its raw form because many times, regulatory reasons, audit reasons, you want to not touch that data. But you can create parallel streams of that data that are called derived streams that are versions that you've altered for some consumption or reporting purposes without affecting the others. And that's powerful when you have multiple teams analyzing different data. And then finally, the thing that Philipp mentioned we saw everywhere, which was a unified way to interact with sensors all the same way because there's sensors for IoT sensors, telemetry log files, video, X-ray, infrared, all sorts of things. But being able to simplify that so that the developers and the data scientists can really build models to solve a business problem was really where we started to focus on how we wanted to bring to market the value of SDP. >> So you launched this, right? And you said early 2020, right before the pandemic and all of the chaos that has- >> Don't recommend that by the way. Don't recommend launching into a pandemic. But yes. >> I'm sure that a lot of lessons learned from silver linings, I'm sure. >> That's right. >> But obviously, big challenges there. I'm curious thought if you thought. One of the things that we've learned from the pandemic is that for so many industries, the access to real-time data is no longer just a nice to have. It is a critical differentiator for those that needed to pivot multiple times to survive in the early days to thrive to continue pivoting. I'm curious, what other industries you saw Russ that came to you saying, "All right, guys. We've got challenges here. Help us figure this out."? Give me a snapshot of some of the other industries that were sort of leading Edge last year. >> Sure. There was some surprising ones. I've mentioned it a little bit, but it's interesting you give me a chance to talk about them. 'cause what was also shocking about this was not only that the same problems that I just mentioned happened in multiple industries. It was actually the prevalence of certain kinds of data. So for example, the construction example I gave you where a company was using drones to ingest streaming video as well as Telemetry of all the equipment on the ground. Drones are in all sorts of industries. So it turns out that's a pattern. But even a lower level than just drone data is actually video data or any kind of media data. And so Philipp talked about they're using that kind of data as well in manufacturing. We're seeing video data in every industry combined with other sensor data. And that's what's really surprised us in the beta program. So working with Philipp, we actually altered our roadmap after we launched to realize that we needed to escalate even more features about video analysis and actually be able to take the process even closer to the Edge where the data's being generated. So the other industries, including construction, logistics, medicine, network traffic, all sorts of data, that is a continuous unbounded stream of data falls into the category of being able to be analyzed, stored, playback like a DVR with SDP. >> Playback like a DVR. I like that. Philipp, back over to you. Talk to us about what's next. Obviously, a tremendous amount of innovation in the first 100 years of WZL. Talk to me about what some of the lab's plans are for the future from a streaming data perspective, got a great foundation infrastructure there with Dell EMC. What's next? >> Like we are working together with a large industry consortium, and then we get a lot of information. Not information, but they really want to see that all this big data stuff that's coming into Industry 4.0. And Russ already talked about it. And then, I'm pretty satisfied in having all the data and the data centers that they have, but they want to push it to the Edge. So all the analytics, it's getting more and more to the Edge because they see that the more data you gather, the more data has to be transferred via the network. So we have to come up with ways on, of course, deploy all the model on the Edge, maybe do some analytics on the Edge. I don't know, something like federated learning to see. Maybe you don't even need to transfer the data to the data center. You can start learning approaches on the Edge and combine them with different data sources that are actually sharing the data, which is the specific point in like corporations that want to corporate using the different data sources, but have some privacy issues. So this is something that we are looking into. And also, working like low-code or no-code environments, like different framework that we use here just in our laboratory, but this is also something that we see in the industry. And more and more people have to interact with the data management systems. So they have to somehow get a lower access point than just some pile from script that they need to write. Maybe, they just need drag and drop environment where they can modify some ingestion or some transformation to the data. So they're not always the people and all the data engineers or the computer science experts have to deal with those kind of stuff, and other people can do as well. So this is something that we are looking into this in the next future. But, yeah. But there are a lot of different things, and there's not enough time to talk about all of them. >> So it sounds like an idea to democratize that data to allow more data citizens to leverage that, analyze it and extract value from it because we all know data is oil, it's gold, but only if you can actually get those analysis quickly and make decisions that really affect and drive the business. Russ, last question for you. Talk to us about what you see next coming in the industry. Obviously, launching this technology at a very interesting time, a lot of things have changed in the last year. You've learned a lot. You said you modified the technology based on the WZL implementation. But what are some of the things that you see coming next? >> So it's really interesting 'cause my colleague at Dell constantly reminds me that people develop solutions with the technology they have at the time, right? It's a really obvious statement, but it's really powerful to realize what customers of ours have been doing so far. It's been based on batch tools and storage tools that were available at the time, but weren't necessarily the best match for the problem that we're trying to solve. And the world is moving completely to a real-time view of their data. If you can understand that answer sooner, there's higher value for higher revenue, lower costs, safety, all sorts of reasons, right? To do that, everyone's realizing you can't really count on... Like Philipp, he can't count on moving all the data somewhere else to make that decision, that latency; or sometimes, rules around controlling what data can go. Really, we'll keep it from that. So being able to move code closer to the data is where we see things are really happening. This is actually why the streaming data platform has really focused heavily on Edge implementations. We have SDP Core for the core data center. We also have SDP Edge that runs on single node in three node configurations for a headless environments for all sorts of use cases where you need to move the code and make the decisions right when the data is generated at the sensors. The other things we see happening in the industry that are really important is everything's moving to a fully software-defined solution. This idea of being able to have software-defined stream ingestion, analytics and storage. You can deploy the solution you want in the form factor that you have available at your location is important, right? And so, fully software-defined solutions is really going to be where things are at, and which gives you this kind of cloud-like experience, but you can deploy it anywhere at the Edge, Core or cloud, right? And that's really, really powerful. Philipp picked up on the one that we see a lot of this idea of low-code, no-code whether it's things like node red in the IoT world, where you're being able to stitch together a sequence of functions to answer questions in real time or other more sophisticated tools. That ability to, like you said, democratize what people can do with the data in real time is going to be extremely valuable as things move forward. And then the biggest thing we see that we're really focused on is we need to make it as easy as possible to ingest any kind of data. The more data types that you can bring in, the more problems you can solve. And so bringing on as many on-ramps and connectivity into other solutions is really, really important. And for all that, SDP's team is really focused on trying to prioritize the customers like Philipp's team in the RWTH WZL labs there. But finding those common patterns everywhere so that we can actually kind of make it the norm to be analyzing streaming data, not just historical batch data. >> Right. That's outstanding. As you said, the world is moving to real-time analytics. Real-time data ingestion is absolutely critical on there. Just think of the problems that we don't even know about that we could solve. Guys, thank you for joining me today, talking about what WZL is doing with the Dell EMC streaming data platform, and all the innovations you've done so far, and what's coming in the future. We'll have to catch up in the next six months or so, and see what great progress you've made. Thank you for your time. >> Thanks, Lisa. >> Thank you. >> For my guests, I'm Lisa Martin. You're watching a Cube Conversation. (calm techno music)

>> Welcome back to Los Angeles. The cube is live. It feels so good to say that. I'm going to say that again. The cube is alive in Los Angeles. We are a coop con cloud native con 21. Lisa Martin with Dave Nicholson. We're talking to storm forge next. Cool name, right? We're going to get to the bottom of that. Please welcome Matt Provo, the founder and CEO of storm forge and Tom Ellery, the SVP of revenue storm forge, guys, welcome to the program. Thanks for having us. So storm forge, you have to say it like that. Like I feel like do you guys wear Storm trooper outfits on Halloween. >> Sometimes Storm trooper? The colors are black. You know, we hit anvils from time to time. >> I thought I, I thought they, that I saw >> Or may not be a heavy metal band that might be infringing on our name. It's all good. That's where we come from. >> I see. So you, so you started the company in 2015. Talk to me about the Genesis of the company. What were some of the gaps in the market that you saw that said we got to come in here and solve this? >> Yeah, so I was fortunate to always know. I think when you start a company, sometimes you, you know exactly the set of problems that you want to go after and potentially why you might be uniquely set up to solve it. What we knew at the beginning was we had a number of really talented data scientists. I was frustrated by the buzzwords around AI and machine learning when under the hood, this really a lot of vaporware. And so at the outset, really the, the point was build something real at the core, connect that to a set of problems that could drive value. And when we looked at really the beginnings of Kubernetes and containerization five, six years ago at its Genesis, we saw just a bunch of opportunity for machine learning, to play the right kind of role if we could build it correctly. And so at the outset it was what's going on. Why are people are people moving content workloads over to containers in the first place? And, you know, because of the flexibility and the portability around Kubernetes, we then ran into quickly its complexity. And within that complexity was really the foundation to set up the company and the solution for prob a set of problems uniquely and most beneficially solved by using machine learning. And so when we sort of brought that together and designed out some ideas, we, we did what any, any founder with a product background would do. We went and talked to a bunch of potential users and kind of tried to validate the problems themselves and, and got a really positive response. So. >> So Tom, from a business perspective, what, what attracted you to this? >> Well, initially I wasn't attracted just, I'll say that just from a startup standpoint. So I've been in the industry for 30 years, I've done six or seven pre IPO companies. I was exiting a private company. I did not want to go do another startup company, but being in the largest enterprise companies for the last 20 years, you see Kubernetes like wildfire in these places. And you knew there was huge amount of complexity and sophistication when they deployed it. So I started talking to Matt early on. He explained what they were doing and how unique the offer was around machine learning. I already knew the problems that customers had at scale with Kubernetes. So it was for me, I said, all right, I'm going to take one more run at this with Matt. I think we're, we're in a great position to differentiate ourselves. So that was really the launch pad for me, was really the technology and the market space. Those, those two things in combination are very exciting for us as a business. >> And, you know, a couple of bottles of amazing wine and a number of dinners that. >> Helps as well. >> That definitely helped twist his arm? >> Now tell us, just really kind of get into the technology. What does it do? How does it help facilitate the Kubernetes environment? >> Yeah, absolutely. So when organizations start moving workloads over to Kubernetes and get their applications up and running, there's a number of amazing organizations, whether it's through cloud providers or otherwise that that sort of solved that day one problem, those challenges. And as I was mentioning, you know, they moved because of flexibility and so developers love it and it starts to create a great experience, but there's these set of expectations. >> Where, where typically are these moving from? What you, what, what are the, what are the top three environments these are, that these are moving out of? >> Yeah. I mean, of course, non containerized environments, more generally. They could be coming from, you know, bare metal environment and it could be coming from kind of a VM driven environment. >> Okay. >> So when you look back at kind of the, the growth and Genesis and of VMs, you see a lot of parallels to what we're seeing now with, with containerization. And so as you move, it's, it's exciting. And then you get smacked in the face with the complexity, for all of the knobs that are able to be turned within a Kubernetes environment. It gives developers a lot of flexibility. These knobs, as you turn them, you have no visibility into how into the impact on the application itself. And so often organizations are become, you know, becoming more agile shipping, you know, shipping code more quickly, but then all of a sudden the, the cloud bill comes and they've, over-provisioned by 80, 90%, the, they didn't need nearly as many resources. And so what we do is we help understand the unique goals and requirements for each of the applications that are running in Kubernetes. And we have machine learning capabilities that can predict very accurately what organizations will need from a resource standpoint, in order to meet their goals, not just from a cost standpoint, but also from a performance standpoint. And so we allow organizations to typically save usually between 40 and 60% off their cloud bill and usually increased performance between 30 and 50%. Historically developers had to choose between cost and performance and their worldview on the application environment was very limited to a small set of what we would call parameters or metrics that they could choose from. And machine learning allows that world to just be blown open and not many humans are, are sophisticated in the way we think about multidimensional math to be able to make those kinds of predictions. You're talking about billions and billions of combinations, not just in a static environment, but an ongoing basis. So our technology sits in the middle of all that chaos and, and allows it to allows organizations just to re reap a whole lot of benefits that they otherwise may not ever find. >> Those numbers that you mentioned were, were big from a cost savings perspective than a performance increased perspective, which is so critical these days is in the last 18 months, we've seen so much change. We've seen massive pivots from companies in every industry to survive first of all, and then to be able to thrive and be able to iterate quickly enough to develop new products and services and get them to market to be competitive. >> Yeah. >> Yeah. Sorry. I mean, the thing that's interesting, there was an article by Andreessen Horowitz. I don't know if you've taken to the cloud paradox. So we actually, if you start looking at that great example would be some of these cloud companies that are growing like astronomical rates, snowflakes, like phenomenal what they're doing, but go look at their cogs and what it's doing. Also, it's growing almost proportionately as the revenues growing. So you need to be able to solve that problem in a way that is sophisticated enough with machine learning algorithms, that people don't have to be in the loop to do it. And that the math can prove out the solution as you go out and scale your environments. And a lot of companies now are all transitioning over SAS based platforms, and they're going to start running into these problems that they go as they go to scale. And those are the areas that we're really focused and concentrating on as an organization. >> As the leader of sales, talk to me about the voice of the customer. What are some- you've been there six months or so we heard, we heard about the wine and the dinners is obvious. >> We haven't done a lot of that over the last 18 months. >> You'll have to make for lost time then >> As soon as he closes more business. >> Oh, oh there we go, we got that on camera! >> There's, there's been three, a market spaces that we've had some really good success in that. So we talked about a SAS marketplace. So there's a company that does Drupal and Matt knows very well up in Boston, Aquia. And they have every customer is a unique snowflake customer. So they need to optimize each of their customers in order to ensure the cost as well as performance for that customer on their site works appropriately. So that's one example of a SAS based company that where we can go in and help them optimize without humans doing the optimization and the math and the machine learning from storm forge doing that. So that's an area, the other area that we've seen some really good traction Cantonese with GSI. So part of our go to market model is with GSI. So if you think about what a GSI does, a lot of times customers are struggling either initially deploying Kubernetes or putting it in for 12, 18 months and realizing we're starting to scale, we got all kinds of performance issues. How do I solve it? A lot of these people go to the Accentures, the cognizance and other ones, and start flying their ninjas into kind of solve the problem. So we're getting a lot of traction with them because they're using our tool as a way to help solve the customer's problems. And they're in the largest enterprise customers as possible. >> So if I'm hearing what you're saying correctly, you're saying that when I deploy server less applications, I may in fact, get a bill for servers that are being used? Is it, is that what you're telling us? >> They're there in fact may be a bill for what was coined as server less. That is very difficult to understand, by the way, >> That's crazy talk, Matt. >> And connect back. >> Yeah. But absolutely we deal with that all the time. It's a, it's a painful process from time to time. >> Have you, have you, have you seen the statistics that's going on with how people, I mean, there was huge inertia from every CIO that you had have a cloud strategy in place. Everyone ran out and had a cloud strategy in place. And then they started deploying on Kubernetes. Now they're realizing, oh wow, we can run it, but it's costing us more than it ever costs us on prem and the operational complexity associated with that. So there's not enough people in the industry to help solve that problem, especially at the grass roots, that's where you need sophisticated solutions like storm forge and machine learning to help solve this at scale problem in a way that humans could never solve. >> And I would, I would just add to that, that the, the same humans managing the Kubernetes application environments today are likely the same humans that we're managing it in a, in a BM world. So there's a huge skills gap. I love what Castin announced at KU KU con this year around their learning environment where it's free. Come learn Kubernetes and this, and we need more of that. There's an enormous skills gap and, and the problems are complex enough in and of themselves. But when we have, when you add that to the skills gap, it it's, it presents a lot of challenges for organizations. >> What are some the ways in which you think that gap can start to be made smaller. >> Yeah. I mean, I think as more workloads get moved over, over, you know, over time, you see, you see more and more people becoming comfortable in an environment where scale is a part of what they have to manage and take care of. I love what the Linux foundation and the CNCF are doing around Kubernetes certifications, you know, more and more training. I think you're going to see training, you know, availability for more and more developers and practitioners be adopted more widely. You know, and I think that, you know, as the tool chain itself hardens within a CCD world in a containerized world, as that hardens, you're going to, you're going to start seeing more and more individuals who are comfortable across all these different tools. If you look at the CNCF landscape, I mean, today compared to four or five years ago, it's growing like crazy. And so, but, but there's also consolidation taking place within the tools. And people have an opportunity to, to learn and gain expertise within us. Which is very marketable by the way, >> Absolutely >> My employees often show me their LinkedIn profiles and remind me of how , how much they're getting recruited, but they've been loyal. So it's been a fantastic. >> Are there are so many parallels when you look at a VM in virtualization and what's happening with covers, obviously all the abstractions and stuff, but there was this whole concept of VM sprawl, you know, maybe 10 years in, if you think about the Kubernetes environment, that is exponentially bigger problem because of how many they're spitting up versus how, how many you spun up in VM. So those things ultimately need to be solved. It's not just going to be solved with people. It needs to be solved with sophisticated software. That's the only way you're going to solve a problem at scale like that. No matter how many people you have in the industry, it's just never going to solve the problem. >> So when you're in customer conversations, Tom, what are you say are like the top three differentiators that really set storm forage apart? >> Well, so the first one is we're very focused on Kubernetes only. So that's all we do is just Kubernetes environment. So we understand not just the applications that run in Kubernetes, but we understand the underlying architectures and techniques, which we think is really important. From a solution standpoint, >> So you're specialists? >> We are absolutely specialists. The other areas obviously are machine learning and the sophistication of our machine learning. And Matt said this really well, early on, I mean, the buzzwords are all out there. You can read them all up, all over the place for the last five to seven year AI and ML. And a lot of them are very hollow, but our whole foundation was based on machine learning and PhDs from Harvard. That's where we came out of from a technology background. So we were solving more, we weren't just solving the Kubernetes problems. We were solving machine learning problems. And so that's another really big area of differential for us. And I think the ability to actually scale and not just deal with small problems, but very large problems, because our focus is the fortune 2000 companies. And most of them have been deploying like financial services and stuff, Kubernetes for three, four or five years. And so they have had scale challenges that they're trying to solve. >> Yeah. It's Lisa and I talk about this concept of machine learning and looking under the covers and trying to find out is the machine really learning? Is it really learning or is it people are telling the machine, you need to do this. If you see that Where's the machine actually making those correlations and doing something intelligently. So can you give us an example of something that is actually happening that's intelligent? >> Well, so the, the, if this, then that problem is actually a huge source of my original frustration for starting the company, because you, you, you tag AI as a buzzword onto a lot of stuff. And we see that growing like crazy. And so I literally at the beginning said, if we can't actually build something real, that solves problems, like we're going to hang it up. And, you know, as Tom said, we came out of Harvard and, you know, there was a challenge initially of, are we just going to build like a really amazing algorithm? That's so heavy, it can never be productized or commercialized and it really should have just stayed in academia. And, you know, I the I, I will say a couple of things. One is I do not believe that that black box AI is a thing. We believe in what we would call human, augmented AI. So we want to empower practitioners and developers into the process instead of automate them out. We just want to give them the information and we want to save time for them and make their lives easier. But there's a kill switch on the technology. They can intervene at any point in time. They can direct the technology as they see fit. And what's really, really interesting is because their worldview of this application environment gets opened up by all the predictions and all of the learning that actually is taking place and, you know, give it because that worldview is open, they then get into a kind of a tinkering or experimental mindset with the technology. And they start thinking about all these other scenarios that they never were able to explore previously with the application. And, and so the machine learning itself is on an ongoing basis. Understanding changes in traffic, understanding and changes, changes in workloads for the application or demand. If you thought about like surge pricing for Uber, you know, because of a, a big game that took place. And you know, that, that change in peaks and valleys in demand, our, our technology not only understands those reactively, but it starts to build models and predict proactively in advance of the events that are going to take place on, on what ne- what kind of resources need to be allocated. And why that's the other piece around it is often solutions are giving you a little bit of a what, but they certainly are not giving you any explanation of the why. So the holy grail really like in our world is kind of truly explainable AI, which we're not there yet. Nobody's there yet. But human augmented AI with, with actual intelligence that's taking place that also is relevant to business outcomes is, is pretty exciting. So that's why where try to operate. >> Very exciting guys. Thanks for joining us, talking to us about storm forage, to feel like we need some store in forge. T-shirts what do you think? >> (unintelligible) >> See, I'm not even asking for the bottle of wine. I liked that idea. I thank Matt and Tom, thank you so much for joining us exciting company. Congratulations on your success. And we look forward to seeing what great things are to come from storm forage. >> Thanks so much for the time. >> Our pleasure. For Dave Nicholson. I'm Lisa Martin. We are alive in Los Angeles, the cube covering Kube con and cloud native con 21 stick around. Dave and I will be right back with our next guest.

>>Hi, everyone. My name is my uncle. My uncle Poor I worked with Geo reminds you in India. We call ourselves Geo Platforms. Now on. We've been recently in the news. You've raised a lot off funding from one of the largest, most of the largest tech companies in the world. And I'm here to talk about Geos Cloud Journey, Onda Mantis Partnership. I've titled it the story often, Underdog becoming the largest telecom company in India within four years, which is really special. And we're, of course, held by the cloud. So quick disclaimer. Right. The content shared here is only for informational purposes. Um, it's only for this event. And if you want to share it outside, especially on social media platforms, we need permission from Geo Platforms limited. Okay, quick intro about myself. I am a VP of engineering a geo. I lead the Cloud Services and Platforms team with NGO Andi. I mean the geo since the beginning, since it started, and I've seen our cloud footprint grow from a handful of their models to now eight large application data centers across three regions in India. And we'll talk about how we went here. All right, Let's give you an introduction on Geo, right? Giorgio is on how we became the largest telecom campaign, India within four years from 0 to 400 million subscribers. And I think there are There are a lot of events that defined Geo and that will give you an understanding off. How do you things and what you did to overcome massive problems in India. So the slide that I want to talkto is this one and, uh, I The headline I've given is, It's the Geo is the fastest growing tech company in the world, which is not a new understatement. It's eggs, actually, quite literally true, because very few companies in the world have grown from zero to 400 million subscribers within four years paying subscribers. And I consider Geo Geos growth in three phases, which I have shown on top. The first phase we'll talk about is how geo grew in the smartphone market in India, right? And what we did to, um to really disrupt the telecom space in India in that market. Then we'll talk about the feature phone phase in India and how Geo grew there in the future for market in India. and then we'll talk about what we're doing now, which we call the Geo Platforms phase. Right. So Geo is a default four g lt. Network. Right. So there's no to geo three g networks that Joe has, Um it's a state of the art four g lt voiceover lt Network and because it was designed fresh right without any two D and three G um, legacy technologies, there were also a lot of challenges Lawn geo when we were starting up. One of the main challenges waas that all the smart phones being sold in India NGOs launching right in 2000 and 16. They did not have the voice or lt chip set embedded in the smartphone because the chips it's far costlier to embed in smartphones and India is a very price and central market. So none of the manufacturers were embedding the four g will teach upset in the smartphones. But geos are on Lee a volte in network, right for the all the network. So we faced a massive problem where we said, Look there no smartphones that can support geo. So how will we grow Geo? So in order to solve that problem, we launched our own brand of smartphones called the Life um, smartphones. And those phones were really high value devices. So there were $50 and for $50 you get you You At that time, you got a four g B storage space. A nice big display for inch display. Dual cameras, Andi. Most importantly, they had volte chip sets embedded in them. Right? And that got us our initial customers the initial for the launch customers when we launched. But more importantly, what that enabled other oh, EMS. What that forced the audience to do is that they also had to launch similar smartphones competing smartphones with voltage upset embedded in the same price range. Right. So within a few months, 3 to 4 months, um, all the other way EMS, all the other smartphone manufacturers, the Samsung's the Micromax is Micromax in India, they all had volte smartphones out in the market, right? And I think that was one key step We took off, launching our own brand of smartphone life that helped us to overcome this problem that no smartphone had. We'll teach upsets in India and then in order. So when when we were launching there were about 13 telecom companies in India. It was a very crowded space on demand. In order to gain a foothold in that market, we really made a few decisions. Ah, phew. Key product announcement that really disrupted this entire industry. Right? So, um, Geo is a default for GLT network itself. All I p network Internet protocol in everything. All data. It's an all data network and everything from voice to data to Internet traffic. Everything goes over this. I'll goes over Internet protocol, and the cost to carry voice on our smartphone network is very low, right? The bandwidth voice consumes is very low in the entire Lt band. Right? So what we did Waas In order to gain a foothold in the market, we made voice completely free, right? He said you will not pay anything for boys and across India, we will not charge any roaming charges across India. Right? So we made voice free completely and we offer the lowest data rates in the world. We could do that because we had the largest capacity or to carry data in India off all the other telecom operators. And these data rates were unheard off in the world, right? So when we launched, we offered a $2 per month or $3 per month plan with unlimited data, you could consume 10 gigabytes of data all day if you wanted to, and some of our subscriber day. Right? So that's the first phase off the overgrowth and smartphones and that really disorders. We hit 100 million subscribers in 170 days, which was very, very fast. And then after the smartphone faith, we found that India still has 500 million feature phones. And in order to grow in that market, we launched our own phone, the geo phone, and we made it free. Right? So if you take if you took a geo subscription and you carried you stayed with us for three years, we would make this phone tree for your refund. The initial deposit that you paid for this phone and this phone had also had quite a few innovations tailored for the Indian market. It had all of our digital services for free, which I will talk about soon. And for example, you could plug in. You could use a cable right on RCR HDMI cable plug into the geo phone and you could watch TV on your big screen TV from the geophones. You didn't need a separate cable subscription toe watch TV, right? So that really helped us grow. And Geo Phone is now the largest selling feature phone in India on it. 100 million feature phones in India now. So now now we're in what I call the geo platforms phase. We're growing of a geo fiber fiber to the home fiber toe the office, um, space. And we've also launched our new commerce initiatives over e commerce initiatives and were steadily building platforms that other companies can leverage other companies can use in the Jeon o'clock. Right? So this is how a small startup not a small start, but a start of nonetheless least 400 million subscribers within four years the fastest growing tech company in the world. Next, Geo also helped a systemic change in India, and this is massive. A lot of startups are building on this India stack, as people call it, and I consider this India stack has made up off three things, and the acronym I use is jam. Trinity, right. So, um, in India, systemic change happened recently because the Indian government made bank accounts free for all one billion Indians. There were no service charges to store money in bank accounts. This is called the Jonathan. The J. GenDyn Bank accounts. The J out off the jam, then India is one of the few countries in the world toe have a digital biometric identity, which can be used to verify anyone online, which is huge. So you can simply go online and say, I am my ankle poor on duh. I verify that this is indeed me who's doing this transaction. This is the A in the jam and the last M stands for Mobil's, which which were held by Geo Mobile Internet in a plus. It is also it is. It also stands for something called the U. P I. The United Unified Payments Interface. This was launched by the Indian government, where you can carry digital transactions for free. You can transfer money from one person to the to another, essentially for free for no fee, right so I can transfer one group, even Indian rupee to my friend without paying any charges. That is huge, right? So you have a country now, which, with a with a billion people who are bank accounts, money in the bank, who you can verify online, right and who can pay online without any problems through their mobile connections held by G right. So suddenly our market, our Internet market, exploded from a few million users to now 506 106 100 million mobile Internet users. So that that I think, was a massive such a systemic change that happened in India. There are some really large hail, um, numbers for this India stack, right? In one month. There were 1.6 billion nuclear transactions in the last month, which is phenomenal. So next What is the impact of geo in India before you started, we were 155th in the world in terms off mobile in terms of broadband data consumption. Right. But after geo, India went from one 55th to the first in the world in terms of broadband data, largely consumed on mobile devices were a mobile first country, right? We have a habit off skipping technology generation, so we skip fixed line broadband and basically consuming Internet on our mobile phones. On average, Geo subscribers consumed 12 gigabytes of data per month, which is one of the highest rates in the world. So Geo has a huge role to play in making India the number one country in terms off broad banded consumption and geo responsible for quite a few industry first in the telecom space and in fact, in the India space, I would say so before Geo. To get a SIM card, you had to fill a form off the physical paper form. It used to go toe Ah, local distributor. And that local distributor is to check the farm that you feel incorrectly for your SIM card and then that used to go to the head office and everything took about 48 hours or so, um, to get your SIM card. And sometimes there were problems there also with a hard biometric authentication. We enable something, uh, India enable something called E K Y C Elektronik. Know your customer? We took a fingerprint scan at our point of Sale Reliance Digital stores, and within 15 minutes we could verify within a few minutes. Within a few seconds we could verify that person is indeed my hunk, right, buying the same car, Elektronik Lee on we activated the SIM card in 15 minutes. That was a massive deal for our growth. Initially right toe onboard 100 million customers. Within our and 70 days. We couldn't have done it without be K. I see that was a massive deal for us and that is huge for any company starting a business or start up in India. We also made voice free, no roaming charges and the lowest data rates in the world. Plus, we gave a full suite of cloud services for free toe all geo customers. For example, we give goTV essentially for free. We give GOTV it'll law for free, which people, when we have a launching, told us that no one would see no one would use because the Indians like watching TV in the living rooms, um, with the family on a big screen television. But when we actually launched, they found that GOTV is one off our most used app. It's like 70,000,080 million monthly active users, and now we've basically been changing culture in India where culture is on demand. You can watch TV on the goal and you can pause it and you can resume whenever you have some free time. So really changed culture in India, India on we help people liver, digital life online. Right, So that was massive. So >>I'm now I'd like to talk about our cloud >>journey on board Animal Minorities Partnership. We've been partners that since 2014 since the beginning. So Geo has been using open stack since 2014 when we started with 14 note luster. I'll be one production environment One right? And that was I call it the first wave off our cloud where we're just understanding open stack, understanding the capabilities, understanding what it could do. Now we're in our second wave. Where were about 4000 bare metal servers in our open stack cloud multiple regions, Um, on that around 100,000 CPU cores, right. So it's a which is one of the bigger clouds in the world, I would say on almost all teams, with Ngor leveraging the cloud and soon I think we're going to hit about 10,000 Bama tools in our cloud, which is massive and just to give you a scale off our network, our in French, our data center footprint. Our network introduction is about 30 network data centers that carry just network traffic across there are there across India and we're about eight application data centers across three regions. Data Center is like a five story building filled with servers. So we're talking really significant scale in India. And we had to do this because when we were launching, there are the government regulation and try it. They've gotten regulatory authority of India, mandates that any telecom company they have to store customer data inside India and none of the other cloud providers were big enough to host our clothes. Right. So we we made all this intellectual for ourselves, and we're still growing next. I love to show you how we grown with together with Moran says we started in 2014 with the fuel deployment pipelines, right? And then we went on to the NK deployment. Pipelines are cloud started growing. We started understanding the clouds and we picked up M C p, which has really been a game changer for us in automation, right on DNA. Now we are in the latest release, ofem CPM CPI $2019 to on open stack queens, which on we've just upgraded all of our clouds or the last few months. Couple of months, 2 to 3 months. So we've done about nine production clouds and there are about 50 internal, um, teams consuming cloud. We call as our tenants, right. We have open stack clouds and we have communities clusters running on top of open stack. There are several production grade will close that run on this cloud. The Geo phone, for example, runs on our cloud private cloud Geo Cloud, which is a backup service like Google Drive and collaboration service. It runs out of a cloud. Geo adds G o g S t, which is a tax filing system for small and medium enterprises, our retail post service. There are all these production services running on our private clouds. We're also empaneled with the government off India to provide cloud services to the government to any State Department that needs cloud services. So we were empaneled by Maiti right in their ego initiative. And our clouds are also Easter. 20,000 certified 20,000 Colin one certified for software processes on 27,001 and said 27,017 slash 18 certified for security processes. Our clouds are also P our data centers Alsop a 942 be certified. So significant effort and investment have gone toe These data centers next. So this is where I think we've really valued the partnership with Morantes. Morantes has has trained us on using the concepts of get offs and in fries cold, right, an automated deployments and the tool change that come with the M C P Morantes product. Right? So, um, one of the key things that has happened from a couple of years ago to today is that the deployment time to deploy a new 100 north production cloud has decreased for us from about 55 days to do it in 2015 to now, we're down to about five days to deploy a cloud after the bear metals a racked and stacked. And the network is also the physical network is also configured, right? So after that, our automated pipelines can deploy 100 0 clock in five days flight, which is a massive deal for someone for a company that there's adding bear metals to their infrastructure so fast, right? It helps us utilize our investment, our assets really well. By the time it takes to deploy a cloud control plane for us is about 19 hours. It takes us two hours to deploy a compu track and it takes us three hours to deploy a storage rack. Right? And we really leverage the re class model off M C. P. We've configured re class model to suit almost every type of cloud that we have, right, and we've kept it fairly generous. It can be, um, Taylor to deploy any type of cloud, any type of story, nor any type of compute north. Andi. It just helps us automate our deployments by putting every configuration everything that we have in to get into using infra introduction at school, right plus M. C. P also comes with pipelines that help us run automated tests, automated validation pipelines on our cloud. We also have tempest pipelines running every few hours every three hours. If I recall correctly which run integration test on our clouds to make sure the clouds are running properly right, that that is also automated. The re class model and the pipelines helpers automate day to operations and changes as well. There are very few seventh now, compared toa a few years ago. It very rare. It's actually the exception and that may be because off mainly some user letter as opposed to a cloud problem. We also have contributed auto healing, Prometheus and Manager, and we integrate parameters and manager with our even driven automation framework. Currently, we're using Stack Storm, but you could use anyone or any event driven automation framework out there so that it indicates really well. So it helps us step away from constantly monitoring our cloud control control planes and clothes. So this has been very fruitful for us and it has actually apps killed our engineers also to use these best in class practices like get off like in France cord. So just to give you a flavor on what stacks our internal teams are running on these clouds, Um, we have a multi data center open stack cloud, and on >>top of that, >>teams use automation tools like terra form to create the environments. They also create their own Cuba these clusters and you'll see you'll see in the next slide also that we have our own community that the service platform that we built on top of open stack to give developers development teams NGO um, easy to create an easy to destroy Cuban. It is environment and sometimes leverage the Murano application catalog to deploy using heats templates to deploy their own stacks. Geo is largely a micro services driven, Um um company. So all of our applications are micro services, multiple micro services talking to each other, and the leverage develops. Two sets, like danceable Prometheus, Stack stone from for Otto Healing and driven, not commission. Big Data's tax are already there Kafka, Patches, Park Cassandra and other other tools as well. We're also now using service meshes. Almost everything now uses service mesh, sometimes use link. Erred sometimes are experimenting. This is Theo. So So this is where we are and we have multiple clients with NGO, so our products and services are available on Android IOS, our own Geo phone, Windows Macs, Web, Mobile Web based off them. So any client you can use our services and there's no lock in. It's always often with geo, so our sources have to be really good to compete in the open Internet. And last but not least, I think I love toe talk to you about our container journey. So a couple of years ago, almost every team started experimenting with containers and communities and they were demand for as a platform team. They were demanding community that the service from us a manage service. Right? So we built for us, it was much more comfortable, much more easier toe build on top of open stack with cloud FBI s as opposed to doing this on bare metal. So we built a fully managed community that a service which was, ah, self service portal, where you could click a button and get a community cluster deployed in your own tenant on Do the >>things that we did are quite interesting. We also handle some geo specific use cases. So we have because it was a >>manage service. We deployed the city notes in our own management tenant, right? We didn't give access to the customer to the city. Notes. We deployed the master control plane notes in the tenant's tenant and our customers tenant, but we didn't give them access to the Masters. We didn't give them the ssh key the workers that the our customers had full access to. And because people in Genova learning and experimenting, we gave them full admin rights to communities customers as well. So that way that really helped on board communities with NGO. And now we have, like 15 different teams running multiple communities clusters on top, off our open stack clouds. We even handle the fact that there are non profiting. I people separate non profiting I peoples and separate production 49 p pools NGO. So you could create these clusters in whatever environment that non prod environment with more open access or a prod environment with more limited access. So we had to handle these geo specific cases as well in this communities as a service. So on the whole, I think open stack because of the isolation it provides. I think it made a lot of sense for us to do communities our service on top off open stack. We even did it on bare metal, but that not many people use the Cuban, indeed a service environmental, because it is just so much easier to work with. Cloud FBI STO provision much of machines and covering these clusters. That's it from me. I think I've said a mouthful, and now I love for you toe. I'd love to have your questions. If you want to reach out to me. My email is mine dot capulet r l dot com. I'm also you can also message me on Twitter at my uncouple. So thank you. And it was a pleasure talking to you, Andre. Let let me hear your questions.

>> From the SiliconANGLE Media office in Boston, Massachusetts. It's theCUBE. (upbeat music) Now, here's your host Dave Vellante. >> Hi everybody, welcome to this Cube Conversation on data protection. You know, I've been reporting for the last several months that spending on storage is reverting back to pre-2018 levels, but at the same time, it's not falling off a cliff. Now, one area of storage that is still very, very strong is the data protection segment. In the past 18 months, we've seen about a half a billion dollars in venture funding come into the market. We've just seen a big multi-billion dollar exit. And backup specifically in data protection, data management generally is where all the action is right now. And one of the leaders in data protection is Dell EMC. The company has the largest share of the market and the new entrants, believe me, want a piece of their pie. But anyone who follows this company knows that the firm is not likely to give up it's turf very easily. So much is changing in the market today. And I want to understand how Dell EMC's data protection division is responding to both the competitive threats and the changing market dynamics. With me are two experts from Dell EMC to address these issues. Nelson Hsu is Director of Solutions, Product Marketing for the data protection division at Dell EMC, and Colm Keegan is Senior Consultant, Product Marketing at Dell EMC. Gents, welcome to theCUBE. Great to see you again. >> Thank you for having us. >> Thanks, Dave. >> So you heard my intro. You guys are the leader. You got the biggest market share. You got all the upstarts coming at ya. What's your response? >> Want me to take that? >> Sure. >> Yeah. It's interesting, so we were talking about this before we came on set, you know and often times they want to poke holes at us 'cause you know we're perceived as being the old timers, or the stodgy ones of the group out there. And play a little jiu jitsu, you move in say you know well time in market counts for something. You know we've been solving data protection challenges for customers for literally decades now. You know and so, water under the boat and knowing the experience that we've derived from that allows us to bring solutions that are mature, that are proven. What we're doing is we're taking those proven solutions and pairing them with modern capabilities. So that, you know we look at it and say, hey, look, Mr. Customer. You have significant data protection challenges today because, as you said, the world's changing. It's changing rapidly. We can help you address those while also sowing the seeds for the foundation for the future. So we think that's a compelling message and we think that while some of our competitors, in particular the upstarts, have had some interesting things to say, big picture-wise, they don't know what they don't know. 'Cause they just don't have the time in the market. Their solutions are also largely absent upmarket, you know, when you look at the enterprise. So we're comfortable. We think we're in a very good spot right now. >> So cloud obviously was the huge mega trend of the past decade. You guys said from the beginning, it's going to be a hybrid world. Some of that was we hope it's going to be a hybrid world. Well you were right, it's a hybrid world. So how is cloud, hybrid cloud affecting your customer decisions around data protection, and how are you responding? >> Well, you know, there's no doubt that the growth in cloud and the growth in hybrid cloud is real. And it's there today. As we look, and as Colm mentioned, we've been protecting data across the enterprise, across the edge and in the cloud, and that growth continues. So today, we have over 1,000 customers that we're protecting their data in the cloud. To the tone of over 2.7 exabytes of data protected in the cloud by Dell EMC data protection. So there is absolutely no doubt that that growth is there. We have a lot of innovation that we're driving on, both in various ares of cloud native, cyber security and deep integration. >> Okay, so that's good, 1,000 customers. That's a pretty good observation space. But when you think about hybrid, what I think when I talk to customers is they want that same exact cloud experience. They don't want to have to context switch. They don't want to have to buy different platforms. So how are you specifically addressing that customer requirement? >> So there's a couple ways we look at that, right? For our customers, simplicity is very key in ease of use. So that's one of our core tenants as we go across both the edge, the core and the cloud. And the other aspect of that is consistency. So giving them and allowing them to use the tools that they know today to be able to protect their data, wherever that data resides. So with the cloud, with cloud native, your data becomes very, very distributed. And you have to be able to see all that data, and control and manage that data. So the whole aspect around cloud data management has now risen to the top as a major concern. We do that in a great way in a sense that we both have a hybrid strategy and a lot of that is working with Dell Technologies cloud. And it's based upon VMware. And so we have a very good deep relationship with VMware to utilize their tools that our customers use today. Whether it be vSphere or vcontrol that they can manage their data protection from one console, from one environment itself. >> Yeah, Dave, I think when you look at the split today, the latest cut of research is that roughly 52% of VM's are in the cloud, and 48 percent are on-prems so it's already hybrid, and as Nelson said, it's largely predicated on VMware. So as organizations start consuming cloud they're going to go with the platform that they've been operating under for years now. So it'll be VMware. We've always had very tight integration with VMware. We have a very strong partnership with them. And that's both on the existing portfolio as well as the agile portfolio that we're building out today under PowerProtect. So as that hybrid world evolves for the customers obviously we want to make sure they're protected from a virtual machine standpoint. And make that, as Nelson said, very simple for them because the last thing customers need is complexity particularly as their environments are becoming inherently more complex. Because now you look at most enterprises today, they're going to have a mix of workloads. It's physical, it's virtual, containers are unaccounted for. It's cloud native apps, it's SaaS. You know we were talking earlier about multi-clouds. Oftentimes it just kind of came up organically and now you've got this huge distribution of workloads and oftentimes, customers have been just sort of reactive to that. In other words, let me find a way to protect that and I'll worry about the details later. We're looking at that and saying, we have the portfolio to help you protect all your workloads, and as importantly, we'll help consolidate the management in that environment. It's going to start with VMware, but then longer term we're planning for things like a SaaS control plane so that we can give you a complete view of that environment and allow you to assign the policies you need in terms of SLA's, in terms of compliance. You're basically hitting all the security, hitting all the key things that you need and so directionally we think starting with VMware and building from there is probably the most realistic way we can get customers protected from a hyper cloud. >> So the vision is a single point of control that is SaaS based that lives in the cloud or lives wherever you want it to live? >> Right, it can be either. >> So one of our core tendencies here, right, is that we want and deliver the ability to protect our customer's data wherever it resides. Whether it's edge, core or cloud. >> So sticking on cloud for a second, and then sort of segue into the VMware conversation that I want to have is VMware is the sort of linchpin of your multi-cloud strategy. That makes a lot of sense. VMware is going to be a leader, if not the leader in multi-cloud. We'll see how that all shakes out. It's kind of jump ball right now but VMware is in pretty good position with 500,000 customers. But your perspective on cloud is different than say, take an AWS cloud provider, it's a place. Put your data in my cloud. You guys are talking about the experience. And that's really what you're trying to drive with VMware, whether is Ron-prem, whether it's in Google, Azure, AWS, wherever. The cloud, you name it. Is that the right way to think about your strategy? Specifically as it relates to multi-cloud. >> Yeah, so I think on the area of multi-cloud, it is a multi-cloud world. Years ago I was in a SaaS startup and we had customers that were looking to deploy to the cloud. And then that was the question. Okay, do we hedge on multi-cloud or not? As a SaaS provider, we actually implemented on both AWS and Azure at the time. Which became relevant, because now our customers are asking us, yes, my primary is with this particular hyper scaler. But do you also support this second hyper scaler? So the reality started to evolve. And so for us, yes, VMware is a very strategic aspect and partner with us, especially with Dell Technologies cloud. But we also have a multi-cloud relationship with AWS, with Azure and with Google. >> Yes, so the compatibility matrix, if you will, applies now to the cloud. >> Absolutely, absolutely. So now it's having that feature and functionality across multiple clouds. >> One of the things we obviously paid attention to is Project Tanzu with inside of VMware. All around bringing kind of Kubernetes and VMware together. How does that affect data protection? >> Well, I think it affects data protection in the sense that addressing the entire aspect of still your data is distributed now. And it's going to grow that way. I think that we've seen numbers upwards of 70% of applications will be container based. Some of that will be going forward to 2022 where there'll be multiple production applications that will be container based. I think what Tanzu will bring to the table is a cohesive way to manage and control that environment itself. >> Okay, and so maybe we could sort of drill into that a little bit. Containers, it's becoming more obvious that people want to persist some of that data. It's largely stateless, but you've got to figure out how to recover. So do you have solutions in that space, is that sort of more road mapping? You can talk about that a little bit. >> No, absolutely. So definitely we have concrete solutions with our Dell EMC PowerProtect data manager for Kubernetes. It's actually one of the first that was in the market to support cloud native environments. >> It is the first. >> Yeah, the first offering out there to support Kubernetes. And so the aspect there is that as cloud native has moved from DevOps, and now into production in the mission critical applications, now becomes the aspect of originally the DNA of DevOps was my data doesn't have to be persistent. Now when you move into a mission critical environment, you're entire environment needs to be protected. And to be able to bring those workloads back up should anything happen and to be able to protect that data that is critical to those workloads. >> Okay, and so you're saying you're first, and you see this as a differentiator in the marketplace, or is everybody going to have this, or it's one of these confusing ice cream cone of solutions. So why you guys? What's your big differentiation? Let's stick to containers. I have the same questions sort of overall come back to that. >> So great question, and the matter of fact is that with our experience across the edge, core and cloud, Kubernetes and containers will be prevalent throughout. And it'll be the way that applications will be developed. It's meeting the demands of the business and being agile. And I think that with our ability internally that would move to that agile emotion. We have that ability to address the customer's needs especially in the cloud native Kubernetes space. >> I think going back to what you said too about VMware, certainly our partnership there is differentiated. We even heard some echos of that during Vmworld. Pat Gelsinger usually doesn't give call outs on the main stage very frequently. And he said that they were working with us as a best-in-class partner for data protection with Tanzu. And so there is a very tight partnership there, so if I'm a customer and I'm looking at containers, I'm probably going to want to do it within the framework of VMware to start with. But it's important to point out that we're also not dependent on VMware. So we can still deliver protection for Kubernetes containers outside of say the VMware management domain. But I would say from a differentiation standpoint there are some real tight partnering going on to make these capabilities mature. >> Well it helps that your CEO owns 80% of the company. (laughing) But it's an interesting point you're making because again, dial back 10 years ago, VMware had much more of a Switzerland strategy under Maritz, almost to, at the time, EMC's detriment. I think Michael Dell is very clearly, as is Jeff Clarke, said look, we're going to do more integration. And Pat Gelsinger has been, look, I love all my partners. It's true but we're entering sort of a new era. And that integration is key, you know, again, because of the ownership structure, and your long history there. It's got to confer some advantages in the marketplace. >> Yeah, and he's also got to remove some of the headwinds to adoption of VMware cloud. And data protection, as we discussed often times can be a headwind if customers are concerned that they're not going to be able to protect their data, chances are they're going to stand pat for a while. So I mean you need to find ways to take some of those objections off the table. >> Yeah, and not to take anything away from your competitors. Look, it's an open API world, and again, people are going to compete. But at the end of the day this stuff is still really complex and if you can do some core engineering together it's definitely an advantage. Let's talk a little bit about cyber. I often say it's become a board level topic. It's not a matter of if, it's a matter of when. SecOps teams are overtaxed. I think I put out a stat lately, I got it from Robert Herjavec actually. He said think about this. The worldwide economy is 86 trillion and we spend .014% on cyber, that's it. We're barely scratching the surface. And that's part of the problem. Okay, but with that limited resource we have to be as smart as possible. You've got this ransomware coming in. So what are your customers asking you for and how are you responding? >> So it's interesting, right, because it is top of mind, cyber and cyber attacks, and it takes many forms. The attacks can be malware, they could be encryption, they could be deletion. Which is ultimately the worst case scenario. And I think as you go forward and you look at it cyber is the number one concern for any CIO, CISO or anyone that's worried about their security infrastructure. >> Which is everybody >> Which is everybody, right, exactly. I think that we have delivered for the cloud data protection area a first and best offering with an air gap data protection solution. So inherently, we can insulate and protect our customer's data from cyber threats. So when a ransom event occurs you can recover your data without having to pay that ransom. Or not be concerned that in most severe cases your data gets deleted. I think most recently there was a healthcare provider who was threatened about their data being deleted. And that was the worst case. We were able to protect their data in the sense that with our cyber recovery offering they protected their data in an air gap vaulted solution. And they didn't have to pay for that ransom. >> So what I'm hearing from you guys is okay, cloud, very important. Hybrid cloud, multi-cloud, fundamental to our strategy. VMware, they say bet on sure things. VMware is pretty much a sure thing. Large customer base, leader in the space. And then cyber as a key concern of customers, you want to expand the notion of backup and data protection to really point it at cyber as well. >> Absolutely, in fact with this recent research, it's called the Global Data Protection Index Survey and we just refreshed it. And what customers identified as the most compelling reasons to adopt cloud is for better performance, better data protection, and better security. Not necessarily in that order but those were the top three. So we look at that and say, you know we've got plays there. Certainly we have capabilities protecting workloads in the cloud whether they be virtual machines, cloud native, containers. But the security aspect of it is huge. Because oftentimes customers, and Dave, you and I were talking about this, they make some broader assumptions about once data is in the clouds they can kind of wash their hands and walk away. Not so fast, because certainly there is a shared responsibility model that extends not only to data protection, but also to security. Look, don't get me wrong, the cloud service providers have fantastic security capabilities, have a great perimeter. But as you said, it's not a question of if, it's a question of when. And when something happens, are you ready for it? So these solutions extend not only to on-prem but into the cloud. So it's that ability wherever the workload lives that you can get the right protection and what we're really now referring to as safeguarding data. Because it's a combination of data protection and security that's embedded and doing it wherever the workload resides. >> I'm glad you brought that up Colm. I have a follow up on that, but Nelson, did you want to add something? >> Well, I just want to mention that one of the biggest concerns is making sure that that data you vaulted is actually clean and safe. So we have a cyber sense capability within our cyber recovery product, that when you vault that data it does about 100 analytics on that data to make sure that there's no malware. That it's not infected. And it does it automatically and even on incremental using machine learning. >> That's really important because mistakes happen really fast. (laughing) So if you're vaulting corrupted data, >> What do you do? >> Oops. >> Yeah, exactly. >> I want to come back, I think the shared responsibility model is not well understand and there's a lot of confusion in the industry. At a conference this year, AWS' CISO Stephen Schmidt was saying, look all this talk about security is broken it's not really productive. The state of security in the cloud is actually really good and to your point Colm, yeah, he's right about that. Then you hear Pat Gelsinger saying, he's told me many times in theCUBE security is a do-over. To my point, you know the 86 trillion. And so I kind of lean, when I talk to IT people what Pat is saying. So you say okay, where is the dissidence there? Well, the reality is is the cloud service providers and the shared security model, they'll secure the physical infrastructure. But it's up to the customer to be responsible for everything else. You know, the edicts of the organization are applied. We were talking to the CISO of a large insurance company and she said to us, oh no, shared responsibility means it's our responsibility. So you're not going to go after the cloud service provider, you're going to go after the insurance company, or the financial service institution. Their brand is the one that's going to get hurt. So that's misunderstood. My question, very long winded rant, but what role do you guys play in that shared responsibility model? >> Well, ultimately it comes down to the customer. And the shared responsibility model really is admissible, as you mentioned, right? And so at the end of the day, you as the customer own and are responsible to protect that data. So your data protection strategy, your cyber resilience strategy has to be sound. And it has to be secured by those that can actually do it across multiple distribution models and platforms, whether it's edge, core or cloud. Whether it's VM's, containers. It doesn't change. You're still ultimately responsible for it. >> I think maybe what you might be driving at the question, Dave, is empowering the customers to maintain control of their data. And having the tools in place so that they feel comfortable. And part of it too is moving more towards automation. Because as their applications grow, and as Nelson said, become more distributed, as the data grows exponentially, this just fundamentally isn't a task that humans can manage very much longer. >> I'm glad you brought that up, because you ask a CISO, what's your number one problem? And he or she will tell you the skill sets to keep up with all this complexity. And that's where automation comes in. >> Correct, it does. So that's where we're taking it. Is trying to make things more automated and take tasks away from humans that they just can't keep up with. >> All right guys, I'll give you the last word. We go back a decade or so ago and backup was a whole different situation. And we saw the rise of virtualization and now cloud and all these other things that we have been talking about. Edge, the cyber threats, et cetera. So bring us home, where do you see the future and how does Dell EMC data protection fit in? >> It's an exciting time, it really is. It's kind of like the coming of that second storm as you mentioned. Businesses have that demand of needing more services to load more quickly in an agile fashion. And as they pair that with the growth of their data which is distributed, they really have that challenge overall of how do I manage this environment? So you have to have the observability to understand where your data is and to be able to monitor it. You have to be able to orchestrate your workloads so that they're automated, and the data protection of those workloads are automated as well. And so the imperative that aspects like Tanzu are addressing with cloud native, that Kubernetes brings to the table to deliver containerized applications. That's really quite honestly is the biggest evolution I've seen in my last 20 to 30 years. This is definitely a different paradigm shift. >> Yeah, you know, six months ago I was with a competitor and was taking a look at EMC, sorry, I should say Dell EMC, and I was wondering, should I make a move over here? And really what convinced me was the fact that the company was willing to basically solve internally the innovator's dilemma. You're making so much money on your existing portfolio, now you're going to start investing in what appears to be almost internal competition to your portfolio. It's not, it's complimentary. So that's what drove the decision for me to come here, but I will also say it's great to be a part of an organization that has a long-term vision. You remember, I think the phrase that was being used, being held captive to the 90-day shot clock. You know, the earnings reports and stuff. And that drives behavior. Well, if your organization is looking at decade-long goals, that means that you can actually plan to do things that over time are going to actually bring real value to customers. So I think we're doing the right things. We're obviously innovating, we're on this agile software development cadence gives us the ability to solve the problems incrementally over time so customers can see that value instead of waiting for large batch releases. But is also gives us the ability to say, hey, when we've made mistakes or when we hadn't seen certain things come around the corner, we're agile enough to change with that. So I think the combination of having that vision and putting in the investments, and we've kind of likened ourselves to the biggest startup in the industry with the backing of a Fortune 50. And so from a customer standpoint you got to look at that and think, you know, that's interesting, because I need to solve my current problems today. I need to have a path forward for the future. And who am I betting on to deliver that? And the other thing I'll leave on is customers are trying to work with fewer suppliers, not more suppliers. Because they want to reduce the complexity. Well who has the ability to not only bring data protection to bear, but a whole portfolio of technology is really end to end. That can snap into those environments to again reduce complexity and drive more business value. >> That's a really interesting point you make about consolidations. Ever since I've been in this industry people want to deal with less suppliers and reduce the complexity. But you still see startups and VC's funding things. And what's happened is this consolidation, the big guys, you guys are the biggest consolidator. And I always say the rich get richer. There's always this tension between sort of, do I go out and buy the spoke, best of breed tools, or do I get them from somebody who can help me across the portfolio? That's really where your strength is. Guys, thank you so much. This is really a very important topic. Data protection is one of the most important areas that we've been covering. I've been reporting on it a lot. As I said, a lot of venture money has been flowing in. So I really appreciate you guys coming in, sharing your perspectives. And best of luck in the marketplace. >> Appreciate it, Dave. >> Thanks, this was great. >> You're welcome. All right, and thank you for watching, everybody. This is Dave Vellante for theCUBE. We'll see you next time. (upbeat music)

>> Live from Boston, Massachusetts. It's theCube. Covering AWS Reinforce 2019. Brought to you by Amazon Web Services and its ecosystem partners. >> Hello everyone. Welcome back to the live Cube coverage here in Boston, Massachusetts for AWS, Amazon Web Services Reinforce with their inaugural conference around security, I'm (mumbles). We've got two great guests, from Splunk, Cube alumnis, and also, we do the Cube coverage Dot Conf., their annual conference, Haiyan Song, SVP, General Manager Security Market, Oliver Freidrichs, Vice President of Security Products, formerly with a company you sold to Splunk, doing Security Phantom, which was mentioned in the partner summit, so congratulations. Great to see you guys. >> Thank you. >> Thank you for having us. >> So you guys are a really great example of a company that's been constantly innovating, on top of AWS, as a partner, differentiating, continuing to do business, and been successful. All the talk about Amazon could compete with partners, there's always been that myth. You guys have been operating successfully, got great customers on AWS, now you have the security conference, so now it's like a whole new party for you guys. 'Cause you don't go off to reinvent anymore, certainly, the big event, what do you guys think about all this Reinforce focus? >> First of all, I'm just super impressed. The size, the scale, and the engagement from the ecosystem that they have over here, and I think, you know you mentioned we've been really partnering and being successful. I think the secret is really about, just be very customer-focused. It's about what the customer needs, it's not what does each of us need, and when we have that focus, we know how to partner, we know how to engage. One of the examples that we have here is we're partnering up as the capture the flag exercise and it's powered by Splunk, it's put up by AWS Reinforce, and we wanted to bring the best user engagement, gamification of learning to this audience. >> And there's a demand for a security conference because a new breed, a new generation of engineering and enterprises as they move to DevOps, with security, all those same principals now apply, but the stakes are higher because you got to share data, you got to get the data, it's the data-driven problem. You guys are thinking outside-- I think four years ago at Dot Conf, the cyber security focus front and center, mainstream. >> Very much so. And I think for us, security is a big part of our user conference, too. But we're getting inspirations from this event and how we can further, really implify that message for our customers. But we're just so glad we're part of this, thank you for having us. >> We're glad, big love covering you, big success story. Oliver, I want to get to you on the Phantom. Yesterday it was mentioned in a great demo of the security hub, security hub's the big news here, it's one of their major announcements, what is a security hub? >> Yeah, so security hub, and you're right it was just announced that it reached general availability, which means it's available now to the rest of the world. It's a place to centralize a lot of your security management in AWS. So when you have detections, or Amazon calls them findings, coming from other security servers so they're centralized in security hub, where you can then inspect them, take action, investigate them. And one of the reasons we're here, is we've established an integration with security hub, where you can now take a finding coming from security hub, pull it into Splunk Phantom, and run an automation playbook to be able to, at machine speed, take action on a threat. So typically, you know if you're a human, you're looking at an event, and you're deciding what do I do, well I might want to go an suspend an AMI or go and move that AMI or change the access control group to a different access control group so that AMI can only communicate with a certain protected network if it's infected. Automation lets you do that instantaneously, so if you have an attacker who unfortunately may have gained control of your AMI, this allows you to react immediately, very very quickly to take action in that environment. >> And this is where the holes are in the network, and its administrative errors and (mumbles) sittin' out there that someone just configure it, now they're like, they could be out there, no one knows. >> Exactly. >> Could be just tired, I didn't configure it properly. But you guys were in the demos, I want to get your reaction that, because I was sittin' in the room, they highlighted Phantom in the demo. >> That's right. >> And so that was super important. Talk about that integration. What's actually going on under the covers there. >> Yeah, so at a basic level, we're pulling findings through the security hub API, into the automation platform. And then at that point, a playbook kicks off. And a playbook is basically, think of it as a big if this/then that statement. You see a threat, and you go and take a number of actions. You might go and block a port, you might go an suspend that AMI, you might go and disable a user, but you basically build that logic up based on a known threat, and you decide, here's what I'm going to do when I see this threat, and I'm going to turn that into a codified playbook that you can then run very rapidly. On the back end, we've had to integrate with a dozen other APIs like EC2, S3, Guard Duty and others to be able to take action in the environment as well to remediate threats, like changing the access control list or group on a resource. So it's closing that end-to-end loop. >> Hold on, Dave , one quick question on that followup. Then the SISO came in from Capital One and was off the record with this comment, was not really a sensitive comment, but I want to highlight and your both reaction to this. He says in terms of workforce and talent, mentality, 'cause the question came up about talent and whatnot, he sees a shift from better detection to better alerts, because of some of the demos, and implying, kind of connecting the dots, that the trend is to automate the threat detections the way you guys had demoed with Phantom, and then he was tying it back to, from a resource perspective, it frees his team up to do other things. This is a real trend. You agree with that statement? >> Absolutely. >> What's your thoughts? >> Honestly, we believe that we can be automating up to 90% of the level one analysts. There's a lot of routine route work that's done today in the SOC, and it's unforgiving, nobody wants to be a Tier One analyst, they all want to get promoted or go somewhere else, because it's literally a rat race. >> It's boring and it's repetitive, you just automate it. >> Who wants to do that, so we can automate that, we can free up about 50% of the analysts' time to actually focus on proactive activities, things that actually matter, like hunting, research and other development, writing counter-measures, versus the continually keeping up and drinking from a fire hose. >> So I wonder if we could talk about how Splunk has evolved. You guys started before cloud, which came in 2006 and then really took off later, before the sort of big data craze, and you guys mopped up in big data. You never really use that term in your marketing, but you kind of became the big data leader defacto, you got an IPO with actually relatively, by today's comparisons, small raises, >> Compared to today, yeah, yeah (laughs). >> Incredibly successful story, very capital-efficient. But then the cloud comes in, you mopped up on prem, how would you describe how the cloud has changed your strategy, obviously you go out an acquire companies heavily focused on automation, but how would you describe your cloud strategy and how has that changed Splunk? >> That's a great question. I think the fact that you have so many people here, just tells you that the whole industry is going through this transformation. Not only the digital transformation, the cloud transformation. And I'm glad you mentioned our root, it's all about big data, and nowadays security, in many ways, is actually more about data than anything else. 'Cause the data represents your business, and you protect your data, how do you leverage the data, represents your security strategy. The evolution for us, when you zero that into cloud is, we have really been a very early adopter of cloud, we've been providing cloud services for our customers from the very beginning, at least six years ago when we introduced a product called Storm and we continued to evolve that as the technology evolved, we evolved that with customers. So nowadays you probably know cloud is one of our fastest-growing segments of our business. The technology team has been really innovating, really really fast. How do we take a technology that we built for on-prem, how do we rebuilt it to be cloud-native, to be elastic, to be secure in the new way of DevOps. Those are some of the super exciting things we're doing as a company, and on the security side we're also, how do we help customers secure a hybrid world? 'Cause we truly believe the world going to stay hybrid for a long long time and we have companies like AWS really sort of pioneering and focusing and doing things great for the cloud, we still have a lot of customers who need companies and technologies and solutions like what Splunk bring in to bridge the world. >> I want to get you guys' thoughts on some comments we've had with some SISOs in the past, and I really can't say the names probably, but one of them, she was very adamant around integration. And now when you're dealing with an ecosystem, integration's been a big part of the conversation, and the quote was, on integration, "have APIs and "don't have it suck." And we evaluate peoples' integration based upon the qualities of their APIs. Implying that APIs are an integration point. You guys have a lot of experience with APIs, your thoughts on this importance of integration and the roles that APIs play, because that's, again, feeds automation, again it's a key, central component of the conversations these days. Integration, your reaction to that. >> So, maybe I'll start. I'd say we would not have had the success of Phantom Cyber or the Soar market, if not for having those APIs. 'Cause automation was not a new concept. It's been tried and probably not succeeded for many times, and the reason that we've been experiencing this great adoption and success with Phantom technology is because the availability of APIs. I think the other thing I would just add, I'm sure he has lot of experience in working that, Splunk was always positioned ourself as we want to be the neutral party, to bring everything together. And nowadays we're so glad we're doin' the integration, not only on the data side, which is still important. Bring the data, bring the dark data and shining a light on top of that, but also turning that into action through this type of API integration. >> So good investment, betting on integration years ago. >> Absolutely. >> Early on. >> We also change our culture. We previously say how many apps we have in our Splunk base. Now with Oliver being part of the team, Phantom being part of the portfolio, we say how many apps and how many APIs we had to integrate. That a change of metrics. >> All right, Oliver. It's up to you now. I'm sure you know I know where you stand on this, APIs being, a renaissance of APIs going to the next level, 'cause a lot of new things goin' on with Kubernetes and other things. You've got State now, you got Stateless, which is classic rest APIs, but now you got State data that's going to play a big role. Your thoughts on that, don't make the APIs suck, and we're going to evaluate vendors based upon how good their API is. >> Yeah, I think, look it's a buying decision today. It's a procurement decision whether or not you have open APIs. I think buyers are forcing us as an industry, as vendors, to have APIs that don't suck. We're highly motivated to have APIs that work well. >> That sounds like a t-shirt ready to come out (laughs) >> That's a great idea. >> The Cube API's coming, by the way. >> What does that mean, to have APIs that don't suck? >> So the, a great definition I heard recently was, the API that you use as a vendor to interface with your product should be the same API that customers can use to interface with your product. And if all of a sudden they're different, and you're offering a lesser API to customers, that's when they start sucking. As long as you're eating your own dog food, I think that's a good definition. >> So it's not neutered, it's as robust, and as granular. >> Exactly, exactly. And I think what, 20 years ago there were no APIs in security. To do what we do today, to automate all of this security response techniques that we do today, it wasn't even possible. We had to get to a certain level of API availability to even get to this stage. And today, again, unless, if you're a black box, people aren't going to buy your product anymore. >> Yeah, so, again, go the next level is visibility's another topic. So if you open the APIs up, the data's gettin' better, so therefore you can automate the level one alert, threat detections, move people up to better alerting, better creativity, then begs the question, at what point does the visibility increase? What has to happen in the industry to have that total shared environment around data sharing, because open APIs implies sharing of data. Where visibility could be benefited greatly . >> Yeah, I think visibility is really the key. You can't measure what you can't, you can't manage what you can't measure, and you can't, you have to see everything in your environment, your assets, users, devices, and all of your data. So visibility is essential. And it comes in a number of forms. One is getting access to your policy data, your configuration data, seeing how are my things configured? What assets do I have? Where are my S3 buckets? How many AMIs do I have? Who owns them? How many accounts do I have? I think that was one of the challenges before, probably the last three to four years, before that period, enterprises were setting up a lot of these shadow cloud environments, 'cause you could buy Amazon with your credit card, essentially. So that was one of the problems that we would see in the enterprise, when a developer would go and create their own Amazon environment. So getting visibility into that is really been a big advancement in the last few years. Finding those things. >> The birth of multi-cloud. Go ahead John. >> Doesn't make it easier. >> We were talking earlier in our intro Dave and I on the keynote analysis around you can configure it, you can secure it, and then we were riffing on the DevOps movement, which essentially decimated the configuration management landscape. Which was at that time a provisioning issue around developers. They'd have to essentially stand up and manage the network, and go and make sure the ports are all there, and they got load balances are in place, and that was a developer's job. Infrastructure as code took that away. That was a major bottom, hierarchical needs, that was the lowest need. Now with security, if DevOps can take away the configuration management and infrastructure as code, it's time for security to take away a lot of the configuration or security provisioning, if you will. So the question is, what are some of those security provisioning, heavy liftings, tasks that are going to be taken away when developers don't have to worry about security? So as this continues with cloud native, it becomes security native. As a developer, and I don't want to get in and start configuring stuff. I want the security team to magically, security as code, as Dave said. Where are we on that? What's your guys' thoughts on getting to that point? Is it coming soon? Is it here now? What are some of those provisioning tasks that are going to be automated away? >> I think we made a lot of progress in that area already. The ability to simply configure your environment, that Amazon has continued to add layers of check boxes and compliance that allow you to configure the environment far more seamlessly than having to go down into the granular access control list and defining a granular access control policy on your network ports or AMIs, for example. So I think the simplification of that has improved pretty dramatically. And even some of the announcements today in terms of adding more capabilities to do that. Encryption by default. I don't have to go configure my encryption on my data at rest. It's there. And I don't even have to think about it. So if someone steals a physical hard drive, which is very difficult to begin with, out of an Amazon data center, my data's encrypted, and nobody can get access to that. I don't even have to worry about that. So that's one of the benefits that I think the cloud adds, is there's a lot of default security built in that ends up normalizing security and actually making the cloud far more secure than traditional corporate environments and data centers. >> Well I still think you have to opt in, though. Isn't that what I heard? >> Opt in, yes. I would just add to that, I think it's like a rising tides. So the cloud is making lot of the infrastructure side more secure, more native, and then that means we need to pay more attention to the upper level applications and APIs, and identities, and access controls. I think the security team continue to have lot of jobs. Even yesterday they said well, not only we need to do what we need to do to secure the AWS, we also now get involved in every decision, all the other compa-- you know, like functions are doing, taking new sort of SASS services. So I guess message is the security professional continue to have jobs, and your job going to be more and more sophisticated, but more and more relevant to the business, so that I think is the change. >> So question. Oliver, you described what a good API experience is, from a customer perspective, Haiyan, you talked about hybrid. Can you compare the on prem experience with the cloud experience for your customers and how and they coming together? >> You want me to try that first? >> Sure. >> Okay. So, I think lot of the things that people have learned to protect or defend, or do detection response in the on prem world, is still very relevant in the cloud world. It's just the cloud world, I think it's just now really transforming to become more DevOps-centric. How you should design security from the get-go, versus in the on prem world was more okay, let's try to figure out how to monitor this thing, because we didn't really give lot of thoughts to security at the very beginning. So I think that is probably the biggest sort of mentality or paradigm shift, but on the other hand, people don't go and just flip into one side versus the other, and they still need to have a way of connecting what's happening in the current world, the current business, the one that's bring home the bacon, to the new world that's going to bring home the bacon in the future. So they're both really important for them. And I think having a technology as AWS and their whole ecosystem, that all embracing that hybrid world and ecosystem plate no one sort of single vendor going to do all of them, and pick the right solutions to do what you do. So in security, I think it's, you going to continue to evolve, to become more, when the security's built in, what is the rising tide that's going to dictate the rest of the security vendors do. You cannot just think as 10 years ago, five years ago, even two years ago. >> So that bolt-on mentality in the first decade of the millennium was a boon for Splunk. It was beautiful. 'Cause we got to figure out what happened, and you provided the data to show that. How does Splunk differentiate from all the guys that are saying "oh yeah, Splunk, they're on prem, we're the cloud guys." What's your story there? >> Our story is you can't really sort of secure something if you don't have experience yourself. Splunk cloud is probably one of the top, say 10 customers of AWS. We live in the cloud, we experience the cloud, we use the word drink, you know, like eat our own dog food, we like to say we drink our own champagne, if you will, so that's really driving lot of our technology development and understanding the market and really built that into our data platform, build that into our monitoring capabilities, and build that into the new technologies. How, you know, it's all about streaming, it's not about just somebody sending you information. It's about, in a hybrid world, how do you do it in a way that you, we have a term called the distributed data fabric search, because data is never going to be in one place, or even sort of in one cloud. How do we enable that access so you can get value? From a security perspective, how do we integrate with companies and solutions that's so native into the cloud, so you have the visibility not and the Bodong, but from the very beginning. >> So you're saying that cloud is not magic for a software company, it's commitment and it's a cultural mindset. >> Absolutely. >> Guys, thanks so much for comin' on, great to see you, we'll see you at Dot Conf, the Cube will be there this year again, I think for the seventh straight year. Oliver, congratulations on your product success, and mention as part of the AWS security hub presentation. >> Thank you. >> Good stuff from Splunk. Splunk is inside the Cube, explaining, extracting the signal from the noise, from one of the market-leading companies in the data business, now cyber security, I'm with (mumbles), we'll be back with more Cube coverage after this short break. (techno music)

(upbeat music) >> Live, from Washington DC. It's theCUBE. Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to theCUBE's live coverage of the AWS Public Sector Summit here in Washington DC. I'm your host Rebecca Knight, co-hosting alongside of John Furrier. We are excited to welcome to the program, General Keith Alexander former NSA Director, the first Commander to lead the US Cyber Command, Four-star General with a 40 year career. Thank you so much for coming theCUBE, we are honored, we are honored to have you. >> It is an honor to be here. Thank you. >> So let's talk about cyber threats. Let's start there and have you just give us your observations, your thoughts on what are the most pressing cyber threats that keep you up at night? >> Well, so, when you think about threats, you think about Nation States, so you can go to Iran, Russia, China, North Korea. And then you think about criminal threats, well all the things like ransomware. Some of the Nation State actors are also criminals at night so they can use Nation State tools. And my concern about all the evolution of cyber-threats, is that the attacks are getting more destructive, the malware has more legs with worms and the impact on our commercial sector and our nation, increasingly bigger. So you have all those from cyber. And then I think the biggest impact to our country is the theft of intellectual property, right. That's our future. So you look out on this floor here, think about all the technical talent. Now imagine that every idea that we have, somebody else is stealing, making a product out of it, competing with us, and beating us. That's kind of what Huawei did, taking CISCO code to make Huawei, and now they're racing down that road. So we have a couple of big issues here to solve, protect our future, that intellectual property, stop the theft of money and other ideas, and protect our nation. So when you think about cyber, that's what I think about going to. Often times I'll talk about the Nation State threat. The most prevalent threats is this criminal threat and the most, I think, right now, important for us strategically is the theft of intellectual property. >> So why don't we just have a digital force to counter all this? Why doesn't, you know, we take the same approach we did when we, you know, we celebrated the 75th anniversary D-day, okay, World War II, okay, that was just recently in the news. That's a physical war, okay. We have a digital war happening whether you call it or not. I think it is, personally my opinion. I think it is. You're seeing the misinformation campaigns, financial institutions leaving England, like it's nobody's business. I mean it crippled the entire UK, that like a big hack. Who knows? But its happening digitally. Where's the forces? Is that Cyber Command? What do you do? >> So that's Cyber Command. You bring out an important issue. And protecting the nation, the reason we set up Cyber Command not just to get me promoted, but that was a good outcome. (laughing) But it was actually how do we defend the country? How do we defend ourselves in cyber? So you need a force to do it. So you're right, you need a force. That force is Cyber Command. There's an issue though. Cyber Command cannot see today, attacks on our country. So they're left to try to go after the offense, but all the offense has to do is hit over here. They're looking at these sets of targets. They don't see the attacks. So they wouldn't have seen the attack on Sony. They don't see these devastating attacks. They don't see the thefts. So the real solution to what you bring up is make it visible, make it so our nation can defend itself from cyber by seeing the attacks that are hitting us. That should help us protect companies in sectors and help us share that information. It has to be at speed. So we talk about sharing, but it's senseless for me to send you for air traffic control, a letter, that a plane is located overhead. You get it in the mail seven days later, you think, well-- >> Too late. >> That's too late. >> Or fighting blindfolded. >> That's right. >> I mean-- >> So you can't do either. And so what it gets you to, is we have to create the new norm for visibility in cyber space. This does a whole host of things and you were good to bring out, it's also fake news. It's also deception. It's all these other things that are going on. We have to make that visible. >> How do you do that, though? >> What do you do? I do that. (laughing) So the way you do it, I think, is start at the beginning. What's happening to the network? So, on building a defensible framework, you've got to be able to see the attacks. Not what you expect, but all the attacks. So that's anomaly detection. So that's one of the things we have to do. And then you have to share that at network speed. And then you have to have a machine-learning expert system AI to help you go at the speeds the attacker's going to go at. On fake-news, this is a big problem. >> Yeah. >> You know. This has, been throughout time. Somebody pointed out about, you know, George Washington, right, seven fake letters, written to say, "Oh no, I think the King's good." He never wrote that. And the reason that countries do it, like Russia, in the elections, is to change something to more beneficial for them. Or at least what they believe is more beneficial. It is interesting, MIT has done some studies, so I've heard, on this. And that people are 70% more like to re-Tweet, re-Tweet fake news than they are the facts. So. >> Because it's more sensational, because it's-- >> That's food. It's good for you, in a way. But it's tasty. >> Look at this. It's kind of something that you want to talk about. "Can you believe what these guys are doing? "That's outrageous, retweet." >> Not true. >> Not true. Oh, yeah, but it makes me mad just thinking about it. >> Right, right. >> And so, you get people going, and you think, You know, it's like going into a bar and you know, you go to him, "He thinks you're ugly." and you go to me, and you go, "He thinks you're ugly." (laughs) And so we get going and you started it and we didn't even talk. >> Right, right. >> And so that's what Russia does. >> At scale too. >> At scale. >> At the scale point. >> So part of the solution to that is understanding where information is coming from, being able to see the see the environment like you do the physical environment at speed. I think step one, if I were to pick out the logical sequence of what'll happen, we'll get to a defensible architecture over the next year or two. We're already starting to see that with other sectors, so I think we can get there. As soon as you do that, now you're into, how do I know that this news is real. It's kind of like a block-chain for facts. How do we now do that in this way. We've got to figure that out. >> We're doing our part there. But I want to get back to this topic of infrastructure, because digital, okay, there's roads, there's digital roads, there's packets moving round. You mentioned Huawei ripping off CISCO, which takes their R and D and puts it in their pockets. They have to get that. But we let fake news and other things, you've got payload, content or payload, and then you've got infrastructure distribution. Right, so, we're getting at here as that there are literally roads and bridges and digital construction apparatus, infrastructure, that needs to be understood, addressed, monitored, or reset, because you've had email that's been around for awhile. But these are new kinds of infrastructure, but the payload, malware, fake news, whatever it is. There's an interaction between payload and infrastructure. Your thoughts and reaction to that as a Commander, thinking about how to combat all this? >> I, my gut reaction, is that you're going to have to change, we will have to change, how we think about that. It's not any more roads and avenues in. It's all the environment. You know, it's like this whole thing. Now the whole world is opened up. It's like the Matrix. You open it up and there it is. It's everything. So what we have to do is think about is if it's everything, how do we now operate in a world where you have both truths and fiction? That's the harder problem. So that's where I say, if we solve the first problem, we're so far along in establishing perhaps the level so it raises us up to a level where we're now securing it, where we can begin to see now the ideas for the pedigree of information I think will come out. If you think about the amount of unique information created every year, there are digital videos that claim it's doubling every year or more. If that's true, that half of, 75% of it is fiction, we've got a big road to go. And you know there is a lot of fiction out there, so we've got to fix it. And the unfortunate part is both sides of that, both the fiction and the finding the fiction, has consequences because somebody says that "A wasn't true, "That person, you know, they're saying, he was a rapist, "he was a robber, he was a drugger," and then they find out it was all fake, but he still has that stigma. And then the person over here says, "See, they accused me of that. "They're out to get me in other areas. "They can exclaim what they want." >> But sometimes the person saying that is also a person who has a lot of power in our government, who is saying that it's fake news, when it's not fake news, or, you know what, I-- >> So that's part of the issue. >> It's a very different climate >> Some of it is fake. Some of it's not. And that's what makes it so difficult for the public. So you could say, "That piece was fake, "maybe not the other six." But the reality is, and I think this is where the media can really help. This is where you can help. How do we set up the facts? And I think that's the hardest part. >> It's the truth. >> Yeah, yeah. >> It's a data problem. And you know, we've talked about this off camera in the past. Data is critical for the systems to work. The visibility of the data. Having contextual data, the behavioral data. This gets a lot of the consequences. There's real consequences to this one. Theft, IP, freedom, lives. My son was video-gaming the other day and I could hear his friends all talking, "What's your ping start word? "What's your ping time? "I got lag, I'm dead." And this is a video game. Military, lagging, is not a game. People are losing their lives, potentially if they don't have the right tactical edge, access to technology. I know this is near and dear to your heart. I want to get your reaction. The Department of Defense is deploying strategies to make our military in the field, which represents 85% infantry, I believe, some statistic around that number, is relying on equipment. Technology can help, you know, that. Your thoughts on, the same direction. >> Going to the Cloud. Their effort to go to the Cloud is a great step forward, because it addresses just what you're saying. You know, everybody used to have their own data centers. But a data center has a fixed amount of computational capability. Once you reach it, you have to get another data center, or you just live with what you've got. In the Cloud if the problem's bigger, elasticity. Just add more corridors. And you can do things now that we could never do before. Perhaps even more importantly, you can make the Clouds global. And you can see around the world. Now you're talking about encrypted data. You're talking about ensuring that you have a level of encryption that you need, accesses and stuff. For mobile forces, that's the future. You don't carry a data center around with an infantry battalion. So you want that elasticity and you need the connectivity and you need the training to go with it. And the training gets you to what we were just talking about. When somebody serves up something wrong, and this happened to me in combat, in Desert Storm. We were launched on, everybody was getting ready to launch on something, and I said, "This doesn't sound right." And I told the Division Commander, "I don't agree. "I think this is crazy. "The Iraqis are not attacking us down this line. "I think it's old news. "I think somebody's taken an old report that we had "and re-read it and said oh my God, they're coming." And when we found out that was a JSTARS, remember how the JSTARS MTI thing would off of a wire, would look like a convoy. And that's what it was. So you have to have both. >> So you were on the cusp of an attack, deploying troops. >> That's right. >> On fake information, or misinformation, not accurate-- >> Old information. >> Old information. >> Old information. >> Old, fake, it's all not relevant. >> Well what happens is somebody interprets that to be true. So it gets back to you, how do you interpret the information? So there's training. It's a healthy dose of skepticism, you know. There are aliens in this room. Well, maybe not. (laughing) >> As far as we know. >> That's what everybody. >> But what a fascinating anecdote that you just told, about being in Desert Storm and having this report come and you saying, "Guys, this doesn't sound right." I mean, how often do you harken back to your experience in the military and when you were actually in combat, versus what you are doing today in terms of thinking about these threats? >> A lot. Because in the military, when you have troops in danger your first thought is how can I do more, how can I do better, what can I do to get them the intelligence they need? And you can innovate, and pressure is great innovator. (crunching sound) And it was amazing. And our Division Commander, General Griffith, was all into that. He said, "I trust you. "Do whatever you want." And we, it was amazing. So, I think that's a good thing. Note that when you go back and look at military campaigns, there's always this thing, the victor writes the history. (laughing) So you know, hopefully, the victor will write the truthful history. But that's not always the case. Sometimes history is re-written to be more like what they would like it to be. So, this fake news isn't new. This is something where I think journalists, historians, and others, can come together and say, "You know, that don't make sense. "Let's get the facts." >> But there's so much pressure on journalists today in this 24-hour news cycle, where you're not only expected to write the story, but you're expected to be Tweeting about it, or do a podcast about it later, to get that first draft of history right. >> So it may be part of that is as the reporter is saying it, step back and say, "Here's what we've been told." You know, we used to call those a certain type of sandwich, not a good-- (laughing) If memory serves it's a sandwich. One of these sandwiches. You're getting fed that, you're thinking, "You know, this doesn't make sense. "This time and day that this would occur." "So while we've heard this report. "It's sensational. "We need to go with the facts." And that's one of the areas that I think we really got to work. >> Journalism's changing too. I can tell you, from we've talked, data drives us. We've no advertising. Completely different model. In-depth interviews. The truth is out there. The key is how do you get the truth in context to real-time information for those right opportunities. Well, I want to get before we go, and thanks for coming on, and spending the time, General, I really appreciate it. Your company that you've formed, IronNet, okay, you're applying a lot of your discipline and knowledge in military cyber and cutting-edge tech. Tell us about your company. >> So one of the things that you, we brought up, and discussed here. When I had Cyber Command, one of the frustrations that I discussed with both Secretary Gates and Secretary Panetta, we can't see attacks on our country. And that's the commercial sector needs to help go fix that. The government can't fix that. So my thought was now that I'm in the commercial sector, I'll help fix the ability to see attacks on the commercial sector so we can share it with the government. What that entails is creating a behavioral analytic system that creates events, anomalies, an expert system with machine-learning and AI, that helps you understand what's going on and the ability to correlate and then give that to the government, so they can see that picture, so they have a chance of defending our country. So step one is doing that. Now, truth and lending, it's a lot harder than I thought it would be. (laughing) You know, I had this great saying, "Nothing is too hard "for those of us who don't have to do it." "How hard can this be?" Those were two of my favorite sayings. Now that I have to do it, I can say that it's hard, but it's doable. We can do this. And it's going to take some time. We are getting traction. The energy sector has been great to work with in this area. I think within a year, what we deploy with the companies, and what we push up to the Cloud and the ability to now start sharing that with government will change the way we think about cyber security. I think it's a disruptor. And we have to do that because that's the way they're going to attack us, with AI. We have to have a fast system to defend. >> I know you got to go, tight schedule here, but I want to get one quick question in. I know you're not a policy, you know, wonk, as they say, or expert. Well, you probably are an expert on policy, but if we can get a re-do on reshaping policy to enable these hard problems to be solved by entrepreneurs like yourself expertise that are coming into the space, quickly, with ideas to solve these big problems, whether it's fake news or understanding attacks. What do the policy makers need to do? Is it get out of the way? Do they rip up everything? Do they reshape it? What's your vision on this? What's your opinion? >> I think and I think the acting Secretary of Defense is taking this on and others. We've got to have a way of quickly going, this technology changes every two years or better. Our acquisition cycle is in many years. Continue to streamline the acquisition process. Break through that. Trust that the military and civilian leaders will do the right thing. Hold 'em accountable. You know, making the mistake, Amazon, Jeff Bezos, says a great thing, "Go quickly to failure so we can get "to success." And we in the military say, "If you fail, you're a dummy." No, no, try it. If it doesn't work, go on to success. So don't crush somebody because they failed, because they're going to succeed at some point. Try and try again. Persevere. The, so, I think a couple of things, ensure we fix the acquisition process. Streamline it. And allow Commanders and thought leaders the flexibility and agility to bring in the technology and ideas we need to make this a better military, a better intelligence community, and a better country. We can do this. >> All right. All right, I'm thinking Rosie the Riveter. We can do this. (laughing) >> We can do it. Just did it. >> General Alexander, thank you so much for coming on the show. >> Thank you. >> I'm Rebecca Knight for John Furrier. Stay tuned for more of theCUBE. (electronic music)

>> Narrator: Live from Boston, Massachusetts. It's the Cube, covering ZertoCON 2018. Brought to you by Zerto. >> This is the Cube, I'm Paul Gillin, we're on the ground here in Boston for ZertoCON 2018 and joining me is Bill Manning who's in infrastructure operations at Woodforest National Bank. Now I was not familiar with Woodforest National Bank but I understand that regular visitors to WalMart in the south probably are. You're the WalMart bank I understand. >> That's what a lot of people like to call us. >> Your many branches are located in WalMarts in other words. And based in Houston, which has been no stranger to disasters lately >> Correct. >> The topic of IT resilience very much fresh on your mind. What is IT resilience mean in terms of your operations at Woodforest? >> We need to be very resilient in terms of natural disasters, hurricanes mostly. So, in order to prepare ourselves for that we migrate, 70% of our infrastructure between data centers every six months. When hurricane season starts we migrate away from Houston. When it's done, we migrate back. >> Now, why the migration strategy? Why move between data centers? Why not just settle on one data center that's out of harm's way if you will. >> Well there's no one data center that's out of 100% harm's way, so you need to make sure that if one data center goes down, you can always come up at your backup, or your primary data center. >> Now how did you become a Zerto customer? I understand you were one of their first, their first customer? >> We were their first customer we had Kashya before them and then RecoverPoint. Kashya was the precursor to Zerto. And whenever we were having issues with our replication appliance, we decided to look into Zerto, and we bought, implemented, and turned on Zerto fairly quickly. So we were the first customer and then we were the first customer that was using it. We actively utilized it to run a migration. And so far everything's going great. We love the product. And it works very well for us. >> Now being the first customer of a product is typically thought of as a risky proposition. What pushed you over the tipping point? >> We had an appliance that kept failing on us and the last failure was the straw, that broke the back. So we already had Zerto in a, I believe it was an alpha, possibly a beta test implementation, and when that straw finally broke, we turned off the appliance and we turned on Zerto. And it was very seamless. And yes there were headaches. We had issues with it. But a lot of the support tickets, all of the enhancement requests, a lot of those have our name on it. Because we utilized it. >> So you're doing the cloud migration every six months. What are some of the operational issues that you have to take into account when you're moving that size of processing load a couple hundred miles away? Or maybe Austin, maybe 100 miles away. >> We do it so often it's kind of second nature to us now. But we know the pain points of if you do it regularly, you know what happened last time. Hopefully you documented it. And you know what can happen this time. And a lot of times it's Firewall rules, it's what did we do at our current data center that we forgot to do at our other data center, in preparation for migration. So our biggest pain point is making sure we don't forget, oh hey we did something here, let's make sure to replicate it over and do the same thing over at our other data center. >> How has the role of backup changed over the time you've been using Zerto? It's not really, you don't have the luxury of point in time backups anymore. It's a continuous process, isn't it? >> Well we don't utilize Zerto for backups. We utilize another product for our primary backup system and we are a bank. We have seven year retention policies. So there are certain things that we have to keep on tape or on disk for a certain number of years. And Zerto doesn't immediately offer that to us. However we do utilize Zerto in a kind of pseudo backup process. If we need to recover a file that got deleted accidentally, I can either spend an hour using our other process or 10 minutes using Zerto. So we just pop into Zerto, use the journal file level recovery and there you go. >> You had, being in Houston you had a number of major storms in recent years. Are there any stories you can share with us about how you have managed to stay up and running during those storms? >> Our first storm, our first big storm right after Katrina was Rita. And when Rita came through, we didn't have what we have today. We ended up powering down non-critical items and making sure our critical applications were up and running. And luckily we didn't lose much power. We didn't lose any networking. Where as, during Harvey, we lost some networking for a week or two. The difference was we already moved everything to our secondary data center well away from the hurricane. And sure, one of our redundant paths was down. Our other one was up. We still had connectivity and we were doing great. So in terms of where we progress, hurricane season is what we are mainly concerned with. So we utilize Zerto, we move everything over. So if our data center, our primary data center in Houston goes down, we're mildly affected and customers shouldn't even notice. >> How does this make your business more resilient? I mean is this actually, is there business benefits to your, for your customers? >> Of course. >> Of the business being this resilient? >> If we're a bank and our ATMs go down, and we can't get them back up for a few days, our customers notice. If we're a bank and our primary systems go down and you can't take money out of your account for I believe the timeframe is 72 hours, the Federal government comes in and they own us now. We are no longer a bank. Because we didn't, we failed at providing services for our customers, for an extended period of time. And that's unacceptable. So to mitigate that we use a DR strategy. We use a business continuity plan. And we make sure that if something were to happen, even if it were outside of hurricane season, or if we were during hurricane season, and we had an issue at our other data center, Zerto allows us to bring everything back up within minutes. And because we do it regularly, if we're not going to have as many headaches as someone that just says, "Oh, well we've implemented Zerto but we don't utilize it." We run a few test failovers to make sure that we can actually migrate, but we don't bring anything up and run production load. We run production load every six months using Zerto. So that's how we get around making sure that we're highly available and we don't get taken over by the government. >> I hear a lot of talk, Bill, these days about digital transformation. How real is that to what Woodforest is doing? How are you changing the way you do business? >> I think it's already hard for us. I mean we've already gone digital. When I first started, we had couriers picking up paperwork from the branches and taking them to centralized processing locations, and running everything manually. Now it's all digitally. And that was partially thanks to 9/11. There was proof work they couldn't run for weeks because airports were down. And because of that banks started already going digital. So we already have digital transactions. Now if you write a check at WalMart, instead of taking a few days or a week or two to clear, it clears that day or the next day. Because it's all digital. WalMart went digital, we went digital. Most banks are already going digital or have already gone digital. So we just kind of, people ask, we're mostly already there. We're already digital. >> How about cloud? What's your road map when it comes to using multiple cloud providers? >> We're definitely looking into it, they give us a lot of benefit. They give us a lot of service that we can... >> You got a lot of flexibility. >> Flexibility, sure. Flexibility in doing things that we can't necessarily do ourselves. Right now we're taking baby steps. We're not throwing full production load into the cloud. We're looking at, let's put our development environment up there and see what it can provide for our developers. And so far they're enjoying what the opportunities or the possibilities can be. So we're looking forward to hopefully this year getting them up and running and in the cloud and enjoying all of the benefits from there. And after that once we get some development done in there, then we'll probably start seeing some production applications being put into the cloud. Some sort of probably SAS server offering. >> Well hurricane season is coming up in just a couple of months. I wish you the best >> Thank you so much. >> this season. Bill Manning thanks very much for joining us. >> Thank you very much, I appreciate it. >> We'll be right back from ZertoCON, I'm Paul Gillin, this is the Cube. (upbeat tech beats)

(upbeat music) >> Announcer: From Berlin, Germany, it's The Cube, covering DataWorks Summit Europe 2018. Brought to you by Hortonworks. >> Hi, welcome to The Cube, we're separating the signal from the noise and tuning into the trends in data and analytics. Here at DataWorks Summit 2018 in Berlin, Germany. This is the sixth year, I believe, that DataWorks has been held in Europe. Last year I believe it was at Munich, now it's in Berlin. It's a great show. The host is Hortonworks and our first interviewee today is Scott Gnau, who is the chief technology officer of Hortonworks. Of course Hortonworks got established themselves about seven years ago as one of the up and coming start ups commercializing a then brand new technology called Hadoop and MapReduce. They've moved well beyond that in terms of their go to market strategy, their product portfolio, their partnerships. So Scott, this morning, it's great to have ya'. How are you doing? >> Glad to be back and good to see you. It's been awhile. >> You know, yes, I mean, you're an industry veteran. We've both been around the block a few times but I remember you years ago. You were at Teradata and I was at another analyst firm. And now you're with Hortonworks. And Hortonworks is really on a roll. I know you're not Rob Bearden, so I'm not going to go into the financials, but your financials look pretty good, your latest. You're growing, your deal sizes are growing. Your customer base is continuing to deepen. So you guys are on a roll. So we're here in Europe, we're here in Berlin in particular. It's five weeks--you did the keynote this morning, It's five weeks until GDPR. The sword of Damacles, the GDPR sword of Damacles. It's not just affecting European based companies, but it's affecting North American companies and others who do business in Europe. So your keynote this morning, your core theme was that, if you're in enterprise, your business strategy is equated with your cloud strategy now, is really equated with your data strategy. And you got to a lot of that. It was a really good discussion. And where GDPR comes into the picture is the fact that protecting data, personal data of your customers is absolutely important, in fact it's imperative and mandatory, and will be in five weeks or you'll face a significant penalty if you're not managing that data and providing customers with the right to have it erased, or the right to withdraw consent to have it profiled, and so forth. So enterprises all over the world, especially in Europe, are racing as fast as they can to get compliant with GDPR by the May 25th deadline time. So, one of the things you discussed this morning, you had an announcement overnight that Hortonworks has released a new solution in technical preview called The Data Steward Studio. And I'm wondering if you can tie that announcement to GDPR? It seems like data stewardship would have a strong value for your customers. >> Yeah, there's definitely a big tie-in. GDPR is certainly creating a milestone, kind of a trigger, for people to really think about their data assets. But it's certainly even larger than that, because when you even think about driving digitization of a business, driving new business models and connecting data and finding new use cases, it's all about finding the data you have, understanding what it is, where it came from, what's the lineage of it, who had access to it, what did they do to it? These are all governance kinds of things, which are also now mandated by laws like GDPR. And so it's all really coming together in the context of the new modern data architecture era that we live in, where a lot of data that we have access to, we didn't create. And so it was created outside the firewall by a device, by some application running with some customer, and so capturing and interpreting and governing that data is very different than taking derivative transactions from an ERP system, which are already adjudicated and understood, and governing that kind of a data structure. And so this is a need that's driven from many different perspectives, it's driven from the new architecture, the way IoT devices are connecting and just creating a data bomb, that's one thing. It's driven by business use cases, just saying what are the assets that I have access to, and how can I try to determine patterns between those assets where I didn't even create some of them, so how do I adjudicate that? >> Discovering and cataloging your data-- >> Discovering it, cataloging it, actually even... When I even think about data, just think the files on my laptop, that I created, and I don't remember what half of them are. So creating the metadata, creating that trail of bread crumbs that lets you piece together what's there, what's the relevance of it, and how, then, you might use it for some correlation. And then you get in, obviously, to the regulatory piece that says sure, if I'm a new customer and I ask to be forgotten, the only way that you can guarantee to forget me is to know where all of my data is. >> If you remember that they are your customer in the first place and you know where all that data is, if you're even aware that it exists, that's the first and foremost thing for an enterprise to be able to assess their degree of exposure to GDPR. >> So, right. It's like a whole new use case. It's a microcosm of all of these really big things that are going on. And so what we've been trying to do is really leverage our expertise in metadata management using the Apache Atlas project. >> Interviewer: You and IBM have done some major work-- >> We work with IBM and the community on Apache Atlas. You know, metadata tagging is not the most interesting topic for some people, but in the context that I just described, it's kind of important. And so I think one of the areas where we can really add value for the industry is leveraging our lowest common denominator, open source, open community kind of development to really create a standard infrastructure, a standard open infrastructure for metadata tagging, into which all of these use cases can now plug. Whether it's I want to discover data and create metadata about the data based on patterns that I see in the data, or I've inherited data and I want to ensure that the metadata stay with that data through its life cycle, so that I can guarantee the lineage of the data, and be compliant with GDPR-- >> And in fact, tomorrow we will have Mandy Chessell from IBM, a key Hortonworks partner, discussing the open metadata framework you're describing and what you're doing. >> And that was part of this morning's keynote close also. It all really flowed nicely together. Anyway, it is really a perfect storm. So what we've done is we've said, let's leverage this lowest common denominator, standard metadata tagging, Apache Atlas, and uplevel it, and not have it be part of a cluster, but actually have it be a cloud service that can be in force across multiple data stores, whether they're in the cloud or whether they're on prem. >> Interviewer: That's the Data Steward Studio? >> Well, Data Plane and Data Steward Studio really enable those things to come together. >> So the Data Steward Studio is the second service >> Like an app. >> under the Hortonworks DataPlane service. >> Yeah, so the whole idea is to be able to tie those things together, and when you think about it in today's hybrid world, and this is where I really started, where your data strategy is your cloud strategy, they can't be separate, because if they're separate, just think about what would happen. So I've copied a bunch of data out to the cloud. All memory of any lineage is gone. Or I've got to go set up manually another set of lineage that may not be the same as the lineage it came with. And so being able to provide that common service across footprint, whether it's multiple data centers, whether it's multiple clouds, or both, is a really huge value, because now you can sit back and through that single pane, see all of your data assets and understand how they interact. That obviously has the ability then to provide value like with Data Steward Studio, to discover assets, maybe to discover assets and discover duplicate assets, where, hey, I can save some money if I get rid of this cloud instance, 'cause it's over here already. Or to be compliant and say yeah, I've got these assets here, here, and here, I am now compelled to do whatever: delete, protect, encrypt. I can now go do that and keep a record through the metadata that I did it. >> Yes, in fact that is very much at the heart of compliance, you got to know what assets there are out there. And so it seems to me that Hortonworks is increasingly... the H-word rarely comes up these days. >> Scott: Not Hortonworks, you're talking about Hadoop. >> Hadoop rarely comes up these days. When the industry talks about you guys, it's known that's your core, that's your base, that's where HDP and so forth, great product, great distro. In fact, in your partnership with IBM, a year or more ago, I think it was IBM standardized on HDP in lieu of their distro, 'cause it's so well-established, so mature. But going forward, you guys in many ways, Hortonworks, you have positioned yourselves now. Wikibon sees you as being the premier solution provider of big data governance solutions specifically focused on multi-cloud, on structured data, and so forth. So the announcement today of the Data Steward Studio very much builds on that capability you already have there. So going forward, can you give us a sense to your roadmap in terms of building out DataPlane's service? 'Cause this is the second of these services under the DataPlane umbrella. Give us a sense for how you'll continue to deepen your governance portfolio in DataPlane. >> Really the way to think about it, there are a couple of things that you touched on that I think are really critical, certainly for me, and for us at Hortonworks to continue to repeat, just to make sure the message got there. Number one, Hadoop is definitely at the core of what we've done, and was kind of the secret sauce. Some very different stuff in the technology, also the fact that it's open source and community, all those kinds of things. But that really created a foundation that allowed us to build the whole beginning of big data data management. And we added and expanded to the traditional Hadoop stack by adding Data in Motion. And so what we've done is-- >> Interviewer: NiFi, I believe, you made a major investment. >> Yeah, so we made a large investment in Apache NiFi, as well as Storm and Kafka as kind of a group of technologies. And the whole idea behind doing that was to expand our footprint so that we would enable our customers to manage their data through its entire lifecycle, from being created at the edge, all the way through streaming technologies, to landing, to analytics, and then even analytics being pushed back out to the edge. So it's really about having that common management infrastructure for the lifecycle of all the data, including Hadoop and many other things. And then in that, obviously as we discuss whether it be regulation, whether it be, frankly, future functionality, there's an opportunity to uplevel those services from an overall security and governance perspective. And just like Hadoop kind of upended traditional thinking... and what I mean by that was not the economics of it, specifically, but just the fact that you could land data without describing it. That seemed so unimportant at one time, and now it's like the key thing that drives the difference. Think about sensors that are sending in data that reconfigure firmware, and those streams change. Being able to acquire data and then assess the data is a big deal. So the same thing applies, then, to how we apply governance. I said this morning, traditional governance was hey, I started this employee, I have access to this file, this file, this file, and nothing else. I don't know what else is out there. I only have access to what my job title describes. And that's traditional data governance. In the new world, that doesn't work. Data scientists need access to all of the data. Now, that doesn't mean we need to give away PII. We can encrypt it, we can tokenize it, but we keep referential integrity. We keep the integrity of the original structures, and those who have a need to actually see the PII can get the token and see the PII. But it's governance thought inversely as it's been thought about for 30 years. >> It's so great you've worked governance into an increasingly streaming, real-time in motion data environment. Scott, this has been great. It's been great to have you on The Cube. You're an alum of The Cube. I think we've had you at least two or three times over the last few years. >> It feels like 35. Nah, it's pretty fun.. >> Yeah, you've been great. So we are here at Dataworks Summit in Berlin. (upbeat music)