from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape digital transformation is the operative watchword today but what does it mean from a cxos standpoint and how do you take those perspectives and bring them into an organization to affect its strategy and turn that strategy into action hi everybody this is Dave Allen say welcome to this cube conversations of CXO perspectives I'm here with Paul Lewis who's CTO of Americas from Hitachi ventaja Paul thanks for coming down from Toronto thanks very much I appreciate always great to be in Boston okay let's start with you in your background you're a CIO by trade been with Hitachi and now Hitachi Bonterra for a few years but tell us about your background yeah so I've been here about five years running the office of the CTO which is a highly vertical based organization prior to that I was a CIO CTO of a financial services organization for about 17 years operating technology sort of being a practitioner of what it means to create applications and operate IT and implement projects and worry about you know the blinking lights in a data centre so it's a very different world being on the manufacturer side but getting to see different verticals different industries and applying that it's been intellectually appealing so something I want to come back to exceed you were CIO and CTO which is not uncommon but often times that you know CIO is you know more in a strategy or a pure business role you had both so we'll come back to that when we talk about you know organizational issues but let's start with digital transformation as I said at the top it's the buzz word you go to every conference digital transformation you must you you must not get eaten by your competitors you must be the disrupter etc etc but what does digital transfer transformation mean to you as a CTO CIO from a customer's perspective so I see it much more as being having a customer perspective when you look at your business strategy so in as much as people say sort of customer 360 or you're taking a customer centric approach it's not really that it's it's saying how do I look at my business and evaluate it from the customers point of view so you know the three aspects of digital transformation is operational efficiency new business models and of course the new customer experience so operational efficiency says you if I'm doing a whole bunch of things or to deliver value a product or service but the only thing the customer sees is what's on the shelf and what's available to purchase then everything I do behind the scenes logistics is up for grabs maybe I do it's not an azimuth amia what's on the shelf so maybe somebody else can do it make that efficiency in terms of new business models if all my competitors especially those new digital disruptors have a new way of engaging with the client and the payment maybe it's a credit card versus cash you know capital versus op X maybe I need to diversify my portfolio to be equivalent to that to find customers that I'm currently not getting and then finally new customer experiences this is the customer point of view to say the customer wants to buy from you in a certain way so you better start to sell your products and service in the way to which they want to buy just because your products on the Shelf and the customer wants to buy from you online means you have to also be online and if your customer wants to buy from your competitor your product should be at your competitor right so you've got to think about how the customer buys not just how you sell so all that sort of business strategy so we could poke that a little bit so in a positive way so when you go back to pre-internet days the brand's had all the power right the retail companies knew what the pricing was you know the the the spreads in the stock market were really large we had Nasdaq on last week at Pentaho world all we talked about is how they're becoming basically a technology company to sell their services to others if they are transforming digitally so my my point and question to you is isn't a lot of digital transformation about how you use data to compete and actually maybe regain some of that you know market power or or or at least catch up to where the consumers are cuz the consumers today have all the advantage don't they well data certainly is a value producer versus sort of a side effect that it used to be but it is fair that the consumers have much more buying power than they have before and that's that's in many ways because of those disruptors those disruptors are creating new options for consumers and option and now consumers have that choice in fact the cut the consumerization as a whole as changing how consumers even perceive companies right so if I can download an app and if I don't like it an hour I can delete that up and download they can also choose your product in the same way they're gonna buy your product they don't like it they're gonna throw it away and buy somebody else's product they now have the ultimate choice to do anything they wish buy from anybody they want to locally or globally the globalization concept is changing the way you need to distribute your products and services to yes so the power actually in influence has gone to the consumer and it's only data that you can produce and you can consume externally that'll give you that insight to determine where I need to put my puck right where I need to hockey analogy where I need to ensure that I need to have my product and service and available before the customer wants it or even perceived to want it versus sort of waiting behind the scenes so the big difference between let's say being digital versus non digital is the data yeah but what does that mean to a CTO and a CIO so okay data that's the big difference not what I would say let's take it from the top so if the CEO now is focused on creating more value quicker they probably hire a chief digital officer that's focused on those three pillars if the organization is not that big they might have the CIO perform that function that means the CIO is less about order-taking and more about value creation the only way they're gonna be of value creators if they move from an application centric world of IT to a data centric world of IT and I use an analogy of applications infrastructure and applications I'm gonna go through that way yeah so here's your more about there's the difference between infrastructure applications and data if I look at infrastructure at lasts let's say three to five years I might be able to sweat it out any longer but if I do I'm gonna have performance scalability availability problems if I add more infrastructure to infrastructure it's gonna cost me more money I need more space I need more power and more rack right same kind of true on the application side if I that the last maybe seven to nine years maybe sweated out any longer I have seen performance of scalability problems if I add more applications to applications I have modernization as simplification and rationalization problems and it's not the number of applications that matter it's that I have the same function point recreated across five to ten different applications and five different 10 teams worrying about it same cost issue and and and data quality issue absolutely but data is in fact the opposite to that data is valuable to me from the point that I created the point that I deleted if I ever delete it in fact seeing data change over time is more valuable than seeing it static in its initial State if I add more data to data the bigger potential pot of gold I have and the Nuggets that I can find the more precise my algorithms become the more insightful I'll be able to create from a client's perspective for a firm product or transaction perspective in fact it is the value creator for IT versus the side effect that it's always been so if you remove the centricity from the CIO form application which is red green yellow projects to data being the value creator you start to be a major player in the digital transformation organization instead of sort of being the order taker project so there was a lot of things you said in there that made a lot of sense to me let me start with sort of the infrastructure that a lot of CIOs have spend have to spend their time keeping the lights on and that's not a value producing activity we can agree there were in still are many CIOs that sir were application-centric as you were saying and they would add a lot of value through those applications they have you know sharp application development team they could differentiate through those applications but increasingly when I talk to CIOs you see more sass coming into play and they're trying to avoid custom modifications so when I ask them well how do you differentiate the differentiation is the data the data and the IP that we build around that data the way that data helps us monetize whether it's directly or indirectly is our new differentiator but that's a big shift isn't it it's a large shift because they're they're completely application centric all their projects are about versioning of applications all their infrastructures creating highly available for applications so the big shift is say how do I create an organization that's data centric as a whole how to create a chief data officer and that data officer is elevated to be the peer of in many ways the VP of application the VP of M their organization has all the data centric responsibilities they have storage and protection and governance and analytics and stewardship they are the measured by the value they produce for the organization whether that's operational efficiency or revenue versus the projects to which they deliver on and that way the output of IT is not just projects it's not just spend but it's in fact revenue or profit let's talk about the organizational roles I said I wanted to come back to that and I do I you know you know the jokes CI o stands for career is over I was interviewing John haladki who was the CIO of Beth Israel Hospital a while back at MIT one of the shows we do and he was not optimistic about the role of the CIO Easter Day could disappear and the conversation it was a CDO conference chief data officer conference the conversation was well CIOs need to pick a path and you've got some experience here they either have to become CTOs or they have to become chief data officer x' now that was maybe two years ago I think the narrative has changed a little bit and people have calmed down about that but you've seen this these roles emerge chief data officer chief digital officer we just talked about how digital equals data so I actually see those two roles as you know more closely you know aligned or not depending on on the user but and the CIOs role I think you know and becoming more clear as as a business and strategy person but I wonder if you could weigh in as a former CI o-- / CTO current CTO you talk to a lot of customers how do you see organizations you know what's the right regime right regimes not the right that's not the proper term but what's the regime's that you see emerging I think the big shift determining what those organization roles are from standardization to verse2 diversification so it's less about single provider single process single implementation having a single set of IT services for all the potential workloads and more like what does the business and specific the line of business require and then how am I going to support that so it's now I'm going to have internal services I'm gonna have a private cloud I'm gonna use public cloud offerings I'm gonna have managed services I'm gonna go to third-party offerings I'm going to use a bunch of sass I'm going to consume a lot of cloud versions of ERP type products and that's the complexity of my environment and if that's the complexity of my environment that's the complexity and change of the shift of the roles the CIO now has to be less about project delivery in other words creating applications and more about managing an ecosystem of diverse deployments they have to manage relationships with public clouds they have to manage and create business offerings with the CFO and the CEO and the chief corporate officer in terms of creating new acquisitions or mergers right the CTO is focused on creating a highly secure framework of delivery so that not only the IT shop can deliver on value but all that shadow IT that's happening outs external to greet create a platform and a secure platform for them to deliver because the reality is of every hundred dollars of the CIO has there's $250 out in the business so why don't you make it 350 million it's $350 IT budget instead of 101 you do that by providing platforms and so therefore the CIO is part of the business leader versus being the IT leader the CTO is looking at platforms and therefore the chief data officer becomes the value producer they're the one focused almost entirely on creating revenue or creating so much efficiency in the organization that the profit margins dramatically increase so now business perspective business perspective business perspective and everything underlying is ecosystem it's not everything that I built it's things that I consume externally Wow okay so again a lot of things you said in there that make some sense that I want to better understand so the chief data officer as you described it sort of job one for her or him is to is understand how to essentially make money with data right all right and and again I don't want to say go sell your data because that's not always the answer but you're saying draw you can drive efficiencies and that the simplest form you can cut cost you can increase revenue or you can make better decisions right that's the whole champion in Channel your concept you can have a better understanding of your clients or your products and more importantly have a better understanding of clients - which currently don't purchase your products right how do I look at internal information and compared to external data to say oh how are those other consumers that are going to other my other disruptors what are they purchasing and why can't I produce something that's like or at least competitive in that world so you started off this conversation with three things operational efficiency new business models and the customer experience so there's certainly the chief data officer as you just mentioned can affect operational efficiency ways to cut cost you know through data and I guess they touch new business models as well hey if we're gonna monetize our data directly or a partner or bring in other data and you know did we talk about Nasdaq before that's a completely new before even working with the finance office to say if I were to make changes to my business here would be the net financial effect right okay now the customer experience is that the domain of the chief digital officer really more in that customer facing still still a combination but I would agree that the chief digital officer focusing on creating to matching the selling experience with the buy experience and that might be new mobile interfaces this might be creating omni-channel experiences or expanding upon that to say how do we ensure that we have an integrated channel experience it's not just that they can bribe you know a shoe and the website a shoe in a store it's that they can go online look at the shoes go to the store have those shoes be brought down automatically as soon as I walked in and then choose whether I buy it now take it home buy it online have it delivered to my house before I get home or it's $5 cheaper five stores down right so that experience will be chief digital officer but all of that requires data one can't deliver on all that unless they have a a deep understanding of their products a deep understanding of how the transactions the deep understanding how clients buy all of that experience data based whether it's mobile or human created or business data all combined together in fact that's actually a great jump into the sort of the IOT world the machine or the physical world where I now need to appreciate data that's happening the store in the kiosk and all of that experience data needs to be brought back and combined with the financial data to really appreciate with the transition of that digital experience money so those those roles do really span you know your three areas I can see just thinking here and hearing you speak the chief digital officer might go to the chief data officer and say hey I need this data so I can create a customer experience that gives us competitive advantage and I need that data to be accessible of high quality I maybe need you pulling some other data points exact I need real-time I need a blended I need it integrated with my ERP make it so exactly exactly that can't be too hard and then then that involves the CIO to actually provide the infrastructure and whatever SAS or internal execution but find a means to solve the problem and it's not gonna always be built it's likely gonna be consumed it's likely gonna be buy it's likely gonna be partner and so that's part of that historically it was the application kind of tail wagging the dog now it's the data that was really sort of the driver of the bus which is why you really need what we referred to as a data strategy for digital transformation creating a set of services or capabilities that are focused much more on data than IT like we're used to saying IT services make sure you have computer and storage and networking available to you but now it's saying you know what you have business data let's make sure you have services like store and manage and govern you have human sets of data that's blend and correlate and match and then you have machine data well that's much more about grid and point and and IOT related correlations and need to bring all that together as a series of data servers to which IT provides to the chief digital officer okay you talked about the edge before how do you see I mean we're seeing the pendulum now swing back from centralized you know cloud sort of decentralized this notion of edge to cloud is probably not gonna happen it's gonna be some stuff in between but how do you see let's follow the data how do you see in Itachi and Hitachi event ARRA has obviously a perspective on this you guys are an industrial you know giant how what's Itachi ventajas perspective on how the edge will evolve generally but specifically how the data model and the data flow will change so we see an Enterprise Information model has having sort of four legs to this table right and that one should keep data where it is because sometimes it's physically impossible to move data from where it was created to where it needs to be for analytics a train is example and we produce you know a high speed train that could be four or five seven terabytes per day well that's almost physically impossible to move to a server to be able to deal with right and when you look at larger machines like nuclear power plants and well treatment centers all of a sudden it's almost impossible so this four legs are you know you still need an enterprise data warehouse you still need a means to collect your business data and produce your thousands of Mis reports they actually run the business that is a ten million dollar machine - what you've created you then need a you need a content store an object store because you have all this human unstructured data - which in fairness a good portion of what might be dark a good portion of it like your twenty seven versions of your PowerPoint simply won't have any production nuggets of gold right but you still have lots of voice and video records and unstructured files that that could contain nuggets then you have your your Big Data Lake where you want to put your information that you want to do perform an analytics on right.you it's it's you don't want to worry about the data model you don't want to worry about how you're structuring the information until you actually do analytics on it and then finally the edge keeping data where it is have a federated distributed model and only when I want to do and perform specific analytics do I go collect that information bring it to the core perform the analytics produce visualization result we kind of refer to this as a as a data refinement mechanism where I'm searching for the appropriate information using those mathematical statistical algorithms in order to create you know visualizations that we can blend right back into the original sources so a lot of data will be created at the edge and and it'll stay at the edge and in fact a lot of data probably won't be even be persisted at the edge it'll be may be acted on thrown away and you'll save what you need to save is that exactly and you and you could say that there's going to be data that's at the edge that persist or not you'll might have data which might be referred to as the fog where you will collect it at the CEO or at the PIO right and you one or the pop and you want to be able to perform analytics with a little bit more compute you might bring some of that data centrally because you want to combine and blend with other information and then you might actually put it into the cloud because you want to combine other organizational related data and do very complex highly mathematical problem sets so we almost see it from sort of edge to outcome where there's edge processing fog processing core processing and then cloud processing okay so let's unpack that a little bit in the time we have remaining so you got the at least the three maybe even a four maybe it's a three in a three a tier model edge that that second tier gateway right aggregation point where you're doing some analytics and then the third tier and I guess maybe the fourth tier let's call it your own cloud private cloud or maybe the public cloud where you're doing the heavy modeling right and the training of the models and then maybe your ship in the model back down that's forever because it's now modifying the machine potentially or the machines understanding of data and then you're collecting new data based on that new algorithm to which you're now pushing out all right we don't have time but that just whole totally changes the whole security paradigm as well absolutely no had well Paul thanks very much for for coming on the cube and having this cube conversation really excellent work that you're doing congratulations and keep it up thank you very much you're welcome all right thanks for watching everybody this is Dave Volante and this is cube conversations we'll see you next time

>> Narrator: theCUBE presents Ignite 22. Brought to you by Palo Alto Networks. >> Hey, welcome back to Las Vegas. Lisa Martin here with Dave Vellante. This is day two of theCUBE's coverage of Palo Alto Ignite 2022. Dave we're just talking about how many times we're in Vegas. And we were here two weeks ago with our guest who's back in Alumni. And it's a blur, right? >> It's true, I lost count. Luckily I'm not flying red eye tonight. So that's good. >> I'm impressed. >> Excited about that. >> Yeah >> I'm actually going to enjoy the, nightlife here for a period of time. And, you know, we were at re-Invent. >> Yeah. >> And what a difference. This is nice and relaxed. You have time. You're not getting bumped in the hallway. >> Right. >> A lot of time for learning. So it's been great show. >> It's been great. And one of the things that we've been talking about is the supply chain. Securing the modern software supply chain is really complicated. We've got an Alumni back with us, to talk about what Palo Alto is doing in that respect. Ankur Shah joins us. The SVP and GM of Cloud Security at Palo Alto Networks. Welcome back. >> Yeah, happy to be back. Good to see you again. Dave and Lisa. >> It's been two long weeks. >> Ankur: I know. It's been two weeks, yeah >> Dave: It's kind of crazy. I mean, ReInvent really was a blur. And it's like you had everything coming at you. And there was obviously a big chunk of security, but you. It was just so much to absorb. >> Yeah. >> Right? >> Yeah, and I couldn't get into any of the sessions versus at Ignite. I mean, you could, you could learn a lot. To your point Dave. And 70,000 people versus 3000 in change. Big difference. >> Dave: Yeah. >> Lisa: Huge difference. >> Yeah. >> Lisa: Huge difference. So we touched on the Cider acquisition. >> Ankur: Yeah. >> Which was announced the intent to acquire last month. Let's dig into a little bit more of that, and then some of the great things that had been announced. >> Ankur: Yeah. >> In the last couple of days. >> Oh, absolutely. So, this is something that we have been marinating for last nine months. Thinking about how best to secure supply chain. And this is software supply chain. The modern application software is fairly complex. You know, back in the days when I was a developer, it was a simple three tier application. Ship the code once a year, et cetera. But now with microservices, new architectures, Kubernetes Public Cloud, we talked about this. It's getting super complicated, and the customers are really worried about securing their entire supply chain. Which is nothing but the software pipeline. And so we started looking at a whole bunch of companies and Cider really stood out. I mean, they had, they were the innovators in this space. Very early days, we've seen supply chain attack. But there hasn't been a really good and strong solution in that space. And Cider just delivered that incredible team. Great technology, super excited about what that integration will look like. in the coming quarters. >> What do we need to know about them? I mean, I'll be honest with you, I wasn't familiar with Cider until I saw you guys made the announcement of the intent to acquire them. What, what should we know about them? Why Cider? What was it that attracted you to them? >> Ankur: Yeah, so, you know, we have a history of technology acquisitions as you know, over the last four years, just in the public cloud. We acquire over half a a dozen companies, small and large. And typically we are always looking for companies who have the next gen technology available. Technology that is more in tune with how application software is going to look like in future. So we're not always going after companies that are making you know, tens of hundreds of millions of dollars in a year and all. We're looking for the right tech. The future. And that's what we found in Cider. Like they have a really strong application security background. And AppSec just broadly speaking, supply chain is part of it. But application security, just broadly speaking, is right for disruption. You've got a lot of vendors, who have been around for like last two decades. Old school stuff, lots and lots of false positives. So we've been bolstering, beefing up our portfolio in the application security space. And Cider really fits right nicely into it. Because it can like I said, secure a lot of technology and tooling, that software developers use as part of their software supply chain. So, great founding team, great technology. It was a perfect fit. >> Talk about integration. We spoke with Nikesh yesterday, with Nir, with a whole bunch of folks. Lee this morning. BJ yesterday as well. And one of the things that seems to stick out at me. With all the shows that we do, is the focus that Palo Alto has on ensuring that it's making the right acquisitions. But that it's the integration, is really seems to be like leading part of the strategy. That seems to be a little bit of a differentiator to me. >> Yeah, it absolutely is. There are two ways to integrate a technology into an existing platform. And Prisma Cloud is a platform as you know. Code-to-cloud, CNAPP platform as we call it. One is just kind of slotted in, put the whole thing in a box. And that's basically making one plus one equal to two. We're looking for high leverage in integrations, whereby once that integration comes along. It makes the rest of the platform even better and superior. It makes that technology look even better. So that's why there's a lot of focus on ensuring that we're delivering the right type of integration, that delivers instant customer value. And that makes the overall platform even superior. So customers don't feel like hey, like there's just one more add-on, on top of the other thing. >> Lisa: Right, not a bolt on. >> So that's why there's a lot of focus on that. Getting the strategy nailed. Because the founding teams generally have a preconceived notion about how the world looks like. Then they understand how Prisma cloud and Palo Alto Networks think about it. And then, we sort of merge the two ideas, and build something that's incredible. So I am, we're spending a lot of time in integration. That honeymoon phase of like, let's high five acquisitions done, that's over. Now it's the grinding work of actually getting this right. And you know, getting hundreds and thousands of customers. >> Well I like how you don't have the private equity mentality. It's not about EBITDA and cashflow. We'll take care of that. >> Ankur: Yeah. >> You know, it's about getting that integration. Getting that flywheel effect, inside the platform. You know, we said one plus one equals, maybe even more than two. Can you explain Prisma Cloud Secrets Security? What is that all about? What do we need to know about that? >> Ankur: Absolutely. So, the developers, you know generally store some stuff in the code repo for their automation work to build application. And that thing, the API keys or as Secrets are stored in code repo. It shouldn't be. Or even if they are, they should be encrypted, or locked down and things of that nature. But, you know, the need for speed trumps everything else. Developers want to go fast. And sometimes they're like, okay well. I guess my application needs this particular, you know API access token or secret. I'm just going to stick it in the code. Now the challenge with that is that, if somebody gets hold of your code repo. Now not only is your code repo, which has all your sensitive data. Your code is the life and blood of a technology company. That's in trouble. But also those secrets and API access keys can be used to log into your cloud accounts. And there you may have sensitive customer data. Everything that you have as a technology company stored in that public cloud accounts. So that's the worry. It's usually the initial access for the kill chain. Because that's where the attacks start. Let me get the secret, let me get the API access key. And let me see what I can do in public cloud. So we are now giving customers the visibility into where the secrets are stored. More importantly, it just right there on developer's face. In the code repo as they're checking in the code. They say why, hey, there's a secret here. Are you sure you want to, you want to keep it like this, no? Okay, well then you can either encrypt it, or just get rid of it. So we're making, we're bringing security where the developers are in their code repo, et cetera. >> So I can see a lot of developers saying, yeah, go ahead, encrypt it. So I don't have to do anything else, you know, extra. It's almost, the analogy is a very small you know, version of this. Its like, use a password manager. You store all your passwords in your contacts on your phone, right? I mean, somebody gets a hold of your contacts, you're screwed. >> Ankur: That's exactly right. >> And so, but I could still see a lot of developers say, check in the box. Say, yeah just encrypt it, leave it there. But you're saying best practice is to not to do that, right? >> Yeah, usually you're not supposed to, you know, store all your secrets, et cetera in code repo to begin with. But if you do, you know, you use a key wall like technology to really encrypt it and store it in a secret manner, yeah. >> Dave: There's an old saying, bad user behavior trump's great security every time. >> Ankur: Every time. >> But this is an example where, we know you're going to have bad behavior. So we're going to protect the bad behavior. >> Yeah, and actually, sorry Lisa, just to that point. The bad user behavior trumps good security. The classic example, this happened three weeks ago. Three, four weeks ago, where Dropbox, one of the file sharing companies there. 120 plus code repos were exposed. And the way their attack started, was a simple social engineering attack. Bad user behavior. There was an email, hey, like your passwords are updated for your, you know, this code plugin. Can you enter the password? And boom, now you have access to the code repo. And now if you have secrets inside of it, now, you know all bets are off. >> Are there hard-coded secrets versus like, I mean, like I think like, like you were saying, Dave. Like usernames and passwords and tokens, versus like soft coded secrets. >> Ankur: It's, I think it, this is more so two forms of it, you know. The most primary one is what we call the API access keys. And this keys are used to access cloud accounts, workloads and things of that nature. But there are actually secret secrets. Could be database login passwords, et cetera. The application is using it to spin up databases. Now, you know, you have access to the data stores. Any other application, there's a login password, all of that stuff. So it's less about the user password, but more the application and databases and things of that nature. >> Dave: So again, and, again, everybody should be using password managers. But when you use a password manager, it's going to give you a long list of passwords, that are either been compromised or are weak. And you just go uh, okay. So can you help? How do you help customers identify what the high risk? You know, API, you know, access are versus those ones that they may not have to worry about. >> Ankur: Yeah, look. You know, secrets aside. Risk prioritization is one of the biggest topics that our customers have across the board, in cloud security. All the security vendors are really, really good at one thing, generating alerts. Everybody does it. They generate an alert. You know, your ring camera, if you've got one. I mean this pop up every day, like every minute rather. Well like can you prioritize it for me? What should I really look at it? So that's a number one thing. What Prisma Cloud does is, you know, contextualize it. What the real risk is? They can tell you like, hey, here's the kill chain. If this thing, you know, goes to public internet. These are the potential exposures that you have. So we provide a prioritized risk of critical alerts that customers have to take care of before they can start taking care of more hygiene type of stuff, right? So that's how we do it. Like we leverage a lot of technology. We apply a lot of context. We tell you like, hey, this code repo is not protected by multifactor authentication. And then there's a secret inside. Are you sure, you know, you don't want to fix it? So that's what we do. But it's a great question. Top of mind for all our customers. And that's how we think about it across the board. Versus generating just alerts all the time. >> Dave: Is the strategy, Because we all know phishing is the sort of most, you know obvious way to. It's the top way in which people get hacked. >> Ankur: Yeah. >> Is your strategy essentially to say. Okay we know that's going to happen, so we're going to try to protect it at the back end. How much of the, maybe it's an industry question. more so than just a Palo Alto specifically, How much emphasis is do you think the industry is taking or should be taking on stopping that, you know that those phishing attacks? Because if that's the number one problem you know, maybe that's where we should be starting. >> Yeah, it's a great question. It's typically the initial vector, for a lot of attacks to your point. But there is one thing that technology and AI cannot solve. Which is the user behavior, to your point. Like we can't get into the heads of the user. I mean, you can train them, you can do everything. You can't prevent somebody from clicking a button. Of course there's technology out there for email security that does that. But your point is, right, it's going to happen. Now what do you do? How do you protect your applications, your crown jewel? You know, whether it's in the cloud or it's in the code repo. So a lot of what we are trying to do in code security, or cloud security, or in general at Palo Alto Networks. is to protect those crown jewel. Because we can't prevent somebody from doing something. User behavior is hard to change. >> Dave: So it's almost like, okay, you left your front door open. Somebody's going to walk in, but oh, they walk into a vault. And they don't know where to go. And there's nowhere they can- >> Ankur: Yeah. >> You know, nothing they can take. They can't get to the silverware or the jewelry. >> I think that's it, yeah. >> What are some of the things, like as we look at, we're wrapping up calendar year '22 heading into '23. That customers can look to Palo Alto Networks to help them achieve? One of the things that we talked about with Nikesh and Niri yesterday, is consolidation. Like, and you guys just did a recent, survey. >> Ankur: Yeah. >> About the state of Cyber, and organizations on average have 366 apps in their environment. 31 security tools, 30 to 50 security tools. >> Ankur: Yeah. >> Consolidation is really key there. What are some of the things that you are excited about to deliver to customers where consolidation is concerned? >> Ankur: Yeah. >> Where software supply chain security is concerned in the next year? >> Yeah, absolutely. Look, there are over 3000 security vendors. And this can be, I mean you talked about average customer having 300. I was talking to a CSO, this was last year for one of the largest financial institution I go, "How many security tools do you have?" He got 120. I said, why? He goes, we have a no vendor left behind policy. >> Wow. >> It's crazy. >> Dave: What? >> Obviously he was joking, but it's crazy, right? Like that's how the CSO's are. >> Dave: I mean, he was kidding. >> Yeah. >> Dave: But recognized that. Wow. >> Yeah, and, this is the state the security industry is in. And our mission has been, and Lee and Nikesh and Niri talked about it. Is just platforms, will platforms take moonshots, things long term. And especially the, macro headwinds that we're seeing. We're hearing more and more from the customers that, look we're not going to buy point product. Then we got to buy another product that stitches it all together. We need platforms, whether it's for zero trust, Prisma SaaS, whether it's cloud. Prisma cloud or for your sock transformation. You know XIM and Cortex line of products. So I think you're going to see more and more of that in 2023. I'm confident in that. >> We heard from Lee today, the world record's 400. >> Yes. >> Yeah. >> That's crazy. >> He's going for it. He's got a ways to go. 120 He's got to... >> Maybe he wasn't, that guy wasn't kidding about his no vendor left behind policy. (laughing) Do you have Ankur, a favorite customer story that really articulates the value of what Palo Alto delivers and continues to. You know, 'cause one of the things that Nikesh said in his keynote was that you know, security's a data problem. Well every company these days, in every industry has to be a data company. But really what they need to be able to be is a secured data company. >> Ankur: Yeah. >> How are you guys enabling that? >> Oh, absolutely. Look, many customer examples come to mind, but speaking of data. You know, one of, some of our largest customers who are protecting their PCI workers where they have sensitive data. They're using for example, Prisma Cloud, to ensure that malicious attacks don't happen. And those workloads are used for credit card processing. They're processing tens of thousands of credit card transactions a second. And make sure that nobody gets hold of that. And that's why they have to make sure that nobody is. No attacker is trying to get hold of the sensitive data, to your point, So we have customers across financial services, media and entertainment technology company. Where we are helping them go as fast as possible in public cloud. Go through digital transformation, by securing their applications. >> Dave: What's the T-shirt say? I see code. >> Oh yeah. >> Dave: Secure from Code to Cloud. >> Lisa: Shift Happens. >> Shift Happens, Secrets from Code to Cloud. >> I love that. I was looking at that, going back to that, what's next in cyber survey? >> Ankur: Yeah. >> It said 74% of respondents, and I believe there was 1300 CIO's, CXO's that were surveyed globally. Where they said security is slowing down DevOps. Can customers look to Palo Alto Networks to help them? >> Ankur: Be enablers? >> Yes. >> Yeah, hundred percent. Look, the conversation over the last few years have changed now. Security used to say like, oh, I don't know about these people who are building applications. The DevOps is like security slowing down. I think there's an opportunity for companies like Palo Alto Networks, to build the bridge between the two. And the way we do it is make the securities easy, simple and not super intrusive. Where developers have to do a natural thing. And one part of it, and I talked about it earlier, is bring security where the developers are. In their code repo, in their IDE. Make it super simple. Don't make them do unnatural things. And it just, this is no different from changing the behavior of our kids. Right? Like you make them do unnatural things, they're not going to do it. But if it is part of their regular, you know, day-to-day operating procedures. I think they're going to be more open to change. Yeah. So I think it's possible. And Palo Alto has a huge responsibility to bridge the divide between the apps team, or the DevOps and the security organization. >> Lisa: Lots of great stuff to come. We thank you so much for coming back, two weeks. Only being on two weeks ago. We appreciate your insights, learning more information. It's great to see you at Palo Alto Ignite. And we'll have to have you back on. 'Cause we know that there's so much more to follow with respect to what you're doing. And shifting left, shift happens. >> Awesome. Lisa, Dave, thank you so much. It's been a pleasure. >> Lisa: Thank you so much. For Ankur Shah and Dave Vellante. I'm Lisa Martin. You're watching theCUBE. The leader in live and emerging tech coverage.

(uplifting music) >> Hello and welcome to The Cube, here in Palo Alto, California for a special program on cloud-native at scale, enabling next generation cloud or SuperCloud for modern application cloud-native developers. I'm John Furrier, host of The Cube. My pleasure to have here Madhura Maskasky, co-founder and VP of Product at Platform9. Thanks for coming in today for this cloud-native at scale conversation. >> Thank you for having me. >> So, cloud-native at scale, something that we're talking about because we're seeing the next level of mainstream success of containers, Kubernetes and cloud-native developers, basically DevOps in the CICD pipeline. It's changing the landscape of infrastructure as code, it's accelerating the value proposition and the SuperCloud as we call it, has been getting a lot of traction because this next generation cloud is looking a lot different, but kind of the same as the first generation. What's your view on SuperCloud as it fits to cloud-native as scales up? >> Yeah, you know, I think what's interesting, and I think the reason why SuperCloud is a really good and a really fit term for this, and I think, I know my CEO was chatting with you as well, and he was mentioning this as well, but I think there needs to be a different term than just multi-cloud or cloud. And the reason is because as cloud-native and cloud deployments have scaled, I think we've reached a point now where, instead of having the traditional data center style model where you have a few large distributors of infrastructure and workload at a few locations, I think the model is kind of flipped around, right, where you have a large number of micro sites. These micro sites could be your public cloud deployment, your private, on-prem infrastructure deployments, or it could be your edge environment, right? And every single enterprise, every single industry is moving that direction. And so you got to refer that with a terminology that indicates the scale and complexity of it. And so I think SuperCloud is an appropriate term for that. >> So, you brought a couple things I want to dig into. You mentioned edge nodes. We're seeing not only edge nodes being the next kind of area of innovation, mainly because it's just popping up everywhere. And that's just the beginning. What even know what's around the corner. You got buildings, you got IOT, OT and IT kind of coming together, but you also got this idea of regions, global infrastructure is a big part of it. I just saw some news around CloudFlare shutting down a site here. There's policies being made at scale. These new challenges there. Can you share, because you got to have edge. So, hybrid cloud is a winning formula. Everybody knows that it's a steady state. >> Madhura: Yeah. >> But across multiple clouds brings in this new un-engineered area, yet it hasn't been done yet. Spanning clouds. People say they're doing it, but you start to see the toe in the water, it's happening, it's going to happen. It's only going to get accelerated with the edge and beyond globally. So I have to ask you, what is the technical challenges in doing this? Because it's something business consequences as well, but there are technical challenges. Can you share your view on what the technical challenges are for the SuperCloud or across multiple edges and regions? >> Yeah, absolutely. So, I think, you know, in the context of this, this term of SuperCloud, I think, it's sometimes easier to visualize things in terms of two axes, right? I think on one end you can think of the scale in terms of just pure number of nodes that you have, deploy number of clusters in the Kubernetes space. And then, on the other access you would have your distribution factor, right? Which is, do you have these tens of thousands of nodes in one site or do you have them distributed across tens of thousands of sites with one node at each site? Right? And if you have just one flavor of this, there is enough complexity but potentially manageable. But when you are expanding on both these axes you really get to a point where that scale really needs some well thought out, well structured solutions to address it. Right? A combination of homegrown tooling along with your, you know, favorite distribution of Kubernetes is not a strategy that can help you in this environment. It may help you when you have one of this or when your scale is not at the level. >> Can you scope the complexity? Because I mean, I hear a lot of moving parts going on there, the technology's also getting better. We're seeing cloud-native becomes successful. There's a lot to configure, there's a lot to install. Can you scope the scale of the problem? Because about at scale, >> Madhura: Yeah. >> Challenges here. >> Yeah. Absolutely. And I think, you know, I like to call it, you know, the problem that the scale creates, you know, there's various problems, but I think one problem, one way to think about it is you know, it works on my cluster problem, right? So, you know, I come from engineering background and there's a, you know, there's a famous saying between engineers and QA and the support folks, right. Which is, it works on my laptop, which is I tested this change, everything was fantastic, it worked flawlessly on my machine, on production, it's not working. And the exact same problem now happens in these distributed environments, but at massive scale, right. Which is that, you know, developers test their applications, et cetera within the sanctity of their sandbox environments. But once you expose that change in the wild world of your production deployment, right. And the production deployment could be going at the radio cell tower at the edge location where a cluster is running there, or it could be sending, you know, these applications and having them run at my customer site where they might not have configured that cluster exactly the same way as I configured it, or they configured the cluster right. But maybe they didn't deploy the security policies or they didn't deploy the other infrastructure plugins that my app relies on. All of these various factors add their own layer of complexity. And there really isn't a simple way to solve that today. And that is just, you know, one example of an issue that happens. I think another, you know, whole new ballgame of issues come in the context of security, right? Because when you are deploying applications at scale in a distributed manner, you got to make sure someone's job is on the line to ensure that the right security policies are enforced regardless of that scale factor. So, I think that's another example of problems that occur. >> Okay. So, I have to ask about scale because there are a lot of multiple steps involved when you see the success of cloud native. You know, you see some, you know, some experimentation. They set up a cluster, say, it's containers and Kubernetes, and then you say, okay, we got this, we configure it. And then, they do it again and again, they call it day two. Some people call it day one, day two operation, whatever you call it. Once you get past the first initial thing, then you got to scale it. Then you're seeing security breaches, you're seeing configuration errors. This seems to be where the hotspot is. And when companies transition from, I got this to, oh no, it's harder than I thought at scale. Can you share your reaction to that and how you see this playing out? >> Yeah, so, you know, I think it's interesting. There's multiple problems that occur when, you know, the two factors of scale, as we talked about start expanding. I think, one of them is what I like to call the, you know, it works fine on my cluster problem, which is back in, when I was a developer, we used to call this, it works on my laptop problem, which is, you know, you have your perfectly written code that is operating just fine on your machine, your sandbox environment. But the moment it runs production, it comes back with P zeros and P ones from support teams, et cetera. And those issues can be really difficult to triage. Right. And so, in the Kubernetes environment, this problem kind of multi-folds, it goes, you know, escalates to a higher degree because you have your sandbox developer environments, they have their clusters and things work perfectly fine in those clusters because these clusters are typically handcrafted or a combination of some scripting and handcrafting. And so, as you give that change to then run at your production edge location, like say your radio cell tower site or you hand it over to a customer to run it on their cluster, they might not have configured that cluster exactly how you did, or they might not have configured some of the infrastructure plugins. And so the things don't work. And when things don't work, triaging them becomes like (indistinct) hard, right? It's just one of the examples of the problem. Another whole bucket of issues is security, which is you have these distributed clusters at scale, you got to ensure someone's job is on the line to make sure that the security policies are configured properly. >> So, this is a huge problem. I love that comment. That's not happening on my system. It's the classic, you know, debugging mentality. >> Madhura: Yeah. >> But at scale it's hard to do that with error prone. I can see that being a problem. And you guys have a solution you're launching. Can you share what Arlon is this new product? What is it all about? Talk about this new introduction. >> Yeah, absolutely. I'm very, very excited. You know, it's one of the projects that we've been working on for some time now because we are very passionate about this problem and just solving problems at scale in on-prem or at in the cloud or at edge environments. And what Arlon is, it's an open source project and it is a tool, it's a Kubernetes native tool for a complete end-to-end management of not just your clusters, but your clusters, all of the infrastructure that goes within and along the sites of those clusters, security policies, your middleware plugins, and finally your applications. So, what Arlon lets you do in a nutshell is in a declarative way, it lets you handle the configuration and management of all of these components in at scale. >> So, what's the elevator pitch simply put for what dissolves in terms of the chaos you guys are reigning in, what's the bumper sticker? >> Yeah. >> What would it do? >> There's a perfect analogy that I love to reference in this context, which is think of your assembly line, you know, in a traditional, let's say, you know, an auto manufacturing factory or et cetera, and the level of efficiency at scale that assembly line brings, right? Arlon, and if you look at the logo we've designed, it's this funny little robot, and it's because when we think of Arlon, we think of these enterprise large scale environments, you know, sprawling at scale creating chaos because there isn't necessarily a well thought through, well-structured solution that's similar to an assembly line, which is taking each component, you know, addressing them, manufacturing, processing them in a standardized way, then handing to the next stage where again, it gets, you know, processed in a standardized way. And that's what Arlon really does. That's like deliver the pitch. If you have problems of scale of managing your infrastructure, you know, that is distributed. Arlon brings the assembly line level of efficiency and consistency for those. >> So keeping it smooth, the assembly line, things are flowing, CICD, pipelining. >> Madhura: Exactly. >> So, that's what you're trying to simplify that OPS piece for the developer. I mean, it's not really OPS, it's their OPS, it's coding. >> Yeah. Not just developer, the OPS, the operations folks as well, right? Because developers, you know, there is, developers are responsible for one picture of that layer, which is my apps, and then maybe that middle layer of applications that they interface with, but then they hand it over to someone else who's then responsible to ensure that these apps are secured properly, that they are logging, logs are being collected properly, monitoring and observability is integrated. And so, it solves problems for both those teams. >> Yeah, it's DevOps. So, the DevOps is the cloud-needed developer. The option teams have to kind of set policies. Is that where the declarative piece comes in? Is that why that's important? >> Absolutely. Yeah. And, you know, Kubernetes really introduced or elevated this declarative management, right? Because you know, Kubernetes clusters are, or your, yeah, you know, specifications of components that go in Kubernetes are defined in declarative way, and Kubernetes always keeps that state consistent with your defined state. But when you go outside of that world of a single cluster, and when you actually talk about defining the clusters or defining everything that's around it, there really isn't a solution that does that today. And so Arlon addresses that problem at the heart of it, and it does that using existing open source, well-known solutions. >> And, I want get into the benefits, what's in it for me as the customer, developer, but I want to finish this out real quick and get your thoughts. You mentioned open source. Why open source? What's the current state of the product? You run the product group over there, Platform9, is it open source? And you guys have a product that's commercial. Can you explain the open-source dynamic? And first of all, why open source? >> Madhura: Yeah. >> And what is the consumption? I mean, open source is great, people want open source, they can download it, look up the code, but you know, maybe want to buy the commercial. So, I'm assuming you have that thought through, can you share? >> Madhura: Yeah. >> Open source and commercial relationship. >> Yeah. I think, you know, starting with why open source, I think, it's, you know, we as a company, we have, you know, one of the things that's absolutely critical to us is that we take mainstream open-source technologies components, and then we, you know, make them available to our customers at scale through either a SaaS model or on-prem model, right? But, so as we are a company or startup or a company that benefits, you know, in a massive way by this open-source economy, it's only right, I think in my mind that, we do our part of the duty, right? And contribute back to the community that feeds us. And so, you know, we have always held that strongly as one of our principles. And we have, you know, created and built independent products starting all the way with Fission, which was a serverless product, you know, that we had built to various other, you know, examples that I can give. But that's one of the main reasons why open source and also open source because we want the community to really firsthand engage with us on this problem, which is very difficult to achieve if your product is behind a wall, you know, behind a block box. >> Well, and that's what the developers want too. I mean, what we're seeing in reporting with SuperCloud is the new model of consumption is I want to look at the code and see what's in there. >> Madhura: That's right. >> And then also, if I want to use it, I'll do it. Great. That's open source, that's the value. But then at the end of the day, if I want to move fast, that's when people buy in. So it's a new kind of freemium, I guess, business model. I guess that's the way is, well, but that's the benefit of open source. This is why standards and open source growing so fast, you have that confluence of, you know, a way for us to try before they buy, but also actually kind of date the application, if you will. We, you know, Adrian (indistinct) uses the dating metaphor, you know, hey, you know, I want to check it out first before I get married. >> Madhura: Right. >> And that's what open source. So, this is the new, this is how people are selling. This is not just open source, this is how companies are selling. >> Absolutely. Yeah. Yeah. You know, I think in, you know, two things, I think one is just, you know, this cloud-native space is so vast that if you're building a close flow solution, sometimes there's also a risk that it may not apply to every single enterprise's use cases. And so having it open source gives them an opportunity to extend it, expand it, to make it proper to their use case if they choose to do so. Right? But at the same time, what's also critical to us is we are able to provide a supported version of it with an SLA that we, you know, that's backed by us, a Saas-hosted version of it as well, for those customers who choose to go that route, you know, once they have used the open-source version and loved it and want to take it at scale and in production and need a partner to collaborate with, who can, you know, support them for that production environment. >> I have to ask you. Now, let's get into what's in it for the customer. I'm a customer, why should I be enthused about Arlon? What's in it for me? You know. 'Cause if I'm not enthused about it, I'm not going to be confident and it's going to be hard for me to get behind this. Can you share your enthusiastic view of, you know, why I should be enthused about Arlon? I'm a customer. >> Yeah, absolutely. And so, and there's multiple, you know, enterprises that we talk to, many of them, you know, our customers, where this is a very kind of typical story that you hear, which is we have, you know, a Kubernetes distribution. It could be on premise, it could be public cloud-native Kubernetes, and then, we have our CICD pipelines that are automating the deployment of applications, et cetera. And then, there's this gray zone. And the gray zone is well before you can, your CICD pipelines can deploy the apps, somebody needs to do all of that groundwork of, you know, defining those clusters and yeah, you know, properly configuring them. And as these things start by being done hand grown. And then, as you scale, what typically enterprises would do today is they will have their homegrown DIY solutions for this. I mean, a number of folks that I talk to that have built Terraform automation, and then, you know, some of those key developers leave. So, it's a typical open source or typical, you know, DIY challenge. And the reason that they're writing it themselves is not because they want to. I mean, of course, technology is always interesting to everybody, but it's because they can't find a solution that's out there that perfectly fits the problem. And so that's that pitch. I think, (indistinct) would be delighted. The folks that we've talk, you know, spoken with, have been absolutely excited and have, you know, shared that this is a major challenge we have today because we have, you know, few hundreds of clusters on EKS Amazon, and we want to scale them to few thousands, but we don't think we are ready to do that. And this will give us the ability to, >> Yeah, I think, people are scared. I won't say scare, that's a bad word. Maybe I should say that they feel nervous because, you know, at scale, small mistakes can become large mistakes. This is something that is concerning to enterprises. And I think, this is going to come up at (indistinct) this year where enterprises are going to say, okay, I need to see SLAs. I want to see track record, I want to see other companies that have used it. >> Madhura: Yeah. >> How would you answer that question to, or challenge, you know, hey, I love this, but is there any guarantees? Is there any, what's the SLA, I'm an enterprise, I got tight, you know, I love the open source trying to free fast and loose, but I need hardened code. >> Yeah, absolutely. So, two parts to that, right? One is Arlon leverages existing open-source components, products that are extremely popular. Two specifically. One is Arlon uses ArgoCD, which is probably one of the highest rated and used CD open-source tools that's out there, right? It's created by folks that are as part of into team now, you know, really brilliant team. And it's used at scale across enterprises. That's one. Second is Arlon also makes use of cluster API (indistinct), which is a Kubernetes' sub-component, right? For life cycle management of clusters. So, there is enough of, you know, community users, et cetera, around these two products, right? Or open-source projects that will find Arlon to be right up in their alley because they're already comfortable, familiar with ArgoCD. Now, Arlon just extends the scope of what ArgoCD can do. And so, that's one. And then, the second part is going back to your point of the comfort. And that's where, you know, Platform9 has a role to play, which is when you are ready to deploy Arlon at scale, because you've been, you know, playing with it in your (indistinct) test environments, you're happy with what you get with it, then Platform9 will stand behind it and provide that SLA. >> And what's been the reaction from customers you've talked to Platform9 customers with, that are familiar with Argo and then Arlon? What's been some of the feedback? >> Yeah, I think, the feedback's been fantastic. I mean, I can give examples of customers where, you know, initially, you know, when you are telling them about your entire portfolio of solutions, it might not strike a card right away. But then we start talking about Arlon, and we talk about the fact that it uses ArgoCD they start opening up, they say, we have standardized on Argo and we have built these components, homegrown, we would be very interested. Can we co-develop? Does it support these use cases? So, we've had that kind of validation. We've had validation all the way at the beginning of Arlon before we even wrote a single line of code saying, this is something we plan on doing. And the customer said, if you had it today, I would've purchased it. So, it's been really great validation. >> All right. So, next question is, what is the solution to the customer? If I asked you, look at, I have, I'm so busy, my team's overworked. I got a skills gap, I don't need another project that's so I'm so tied up right now, and I'm just chasing my tail. How does Platform9 help me? >> Yeah, absolutely. So I think, you know, one of the core tenants of Platform9 has always been that, we try to bring that public cloud like simplicity by hosting, you know, this in a lot of such similar tools in a SaaS-hosted manner for our customers, right? So, our goal behind doing that is taking away or trying to take away all of that complexity from customer's hands and offloading it to our hands, right? And giving them that full white glove treatment as we call it. And so, from a customer's perspective, one, something like Arlon will integrate with what they have, so, they don't have to rip and replace anything. In fact, it will, even in the next versions, it may even discover your clusters that you have today, and, you know, give you an inventory. And then, >> So, customers have clusters that are growing, that's a sign, >> Correct. >> Call you guys. >> Absolutely. Either they have massive large clusters. Right. That they want to split into smaller clusters, but they're not comfortable doing that today, or they've done that already on say, public cloud or otherwise. And now, they have management challenges. >> So, especially, operationalizing the clusters, whether they want to kind of reset everything and remove things around and reconfigure >> Madhura: Yeah. >> And or scale out. >> That's right. Exactly. >> And you provide that layer of policy. >> Absolutely. Yes. >> That's the key value here. >> That's right. >> So, policy-based configuration for cluster scale up. >> Profile and policy-based, declarative configuration and life cycle management for clusters. >> If I asked you how this enables SuperCloud, what would you say to that? >> I think, this is one of the key ingredients to SuperCloud, right? If you think about a SuperCloud environment, there is at least few key ingredients that come to my mind that are really critical. Like they are, you know, life-saving ingredients at that scale. One is having a really good strategy for managing that scale. You know, in a, going back to assembly line in a very consistent, predictable way. So, that Arlon solves, then you need to compliment that with the right kind of observability and monitoring tools at scale, right? Because ultimately issues are going to happen and you're going to have to figure out, you know, how to solve them fast. And Arlon by the way, also helps in that direction, but you also need observability tools. And then, especially if you're running at on the public cloud, you need some cost management tools. In my mind, these three things are like the most necessary ingredients to make SuperCloud successful. And you know, Arlon flows in one, >> Okay, so now, the next level is, okay, that makes sense. It's under the covers kind of speak under the hood. >> Madhura: Yeah. >> How does that impact the app developers of the cloud-native modern application workflows? Because the impact to me seems the apps are going to be impacted. Are they going to be faster, stronger? I mean, what's the impact, if you do all those things as you mentioned, what's the impact of the apps? >> Yeah, the impact is that your apps are more likely to operate in production the way you expect them to, because the right checks and balances have gone through, and any discrepancies have been identified prior to those apps, prior to your customer running into them, right? Because developers run into this challenge today where there's a split responsibility, right? I'm responsible for my code, I'm responsible for some of these other plugins, but I don't own the stack end to end. I have to rely on my OPS counterpart to do their part, right? And so, this really gives them, you know, the right tooling for that. >> So, this is actually a great kind of relevant point, you know, as cloud becomes more scalable, you're starting to see this fragmentation gone of the days of the full-stack developer to the more specialized role. But this is a key point, and I have to ask you because if this Arlon solution takes place, as you say, and the apps are going to be (indistinct), they're designed to do, the question is, what does the current pain look like? Are the apps breaking? What is the signals to the customer, >> Madhura: Yeah. >> That they should be calling you guys up into implementing Arlon, Argo, and on all the other goodness to automate, what does some of the signals, is it downtime? Is it failed apps, is it latency? What are some of the things that, >> Madhura: Yeah, absolutely. >> Would be indications of things are F'ed up a little bit. >> Yeah. More frequent down times, down times that are, that take longer to triage. And so your, you know, your mean times on resolution, et cetera, are escalating or growing larger, right? Like we have environments of customers where they have a number of folks on in the field that have to take these apps and run them at customer sites. And that's one of our partners, and they're extremely interested in this because the rate of failures they're encountering for this, you know, the field when they're running these apps on site, because the field is automating their clusters that are running on sites using their own scripts. So, these are the kinds of challenges, and those are the pain points, which is, you know, if you're looking to reduce your mean time to resolution, if you're looking to reduce the number of failures that occur on your production site, that's one. And second, if you're looking to manage these at scale environments with a relatively small, focused, nimble OPS team, which has an immediate impact on your budget. So, those are the signals. >> This is the cloud-native at scale situation, the innovation going on. Final thought is your reaction to the idea that, if the world goes digital, which it is, and the confluence of physical and digital coming together, and cloud continues to do its thing, the company becomes the application, not where IT used to be supporting the business, you know, the back office and the (indistinct) terminals and some PCs and handhelds. Now, if technology's running, the business is the business. >> Yeah. >> Company is the application. >> Yeah. >> So, it can't be down. So, there's a lot of pressure on CSOs and CIOs now and boards is saying, how is technology driving the top-line revenue? That's the number one conversation. >> Yeah. >> Do you see the same thing? >> Yeah, it's interesting. I think there's multiple pressures at the CXO, CIO level, right? One is that there needs to be that visibility and clarity and guarantee almost that, you know, the technology that's, you know, that's going to drive your top line is going to drive that in a consistent, reliable, predictable manner. And then second, there is the constant pressure to do that while always lowering your costs of doing it, right? Especially, when you're talking about, let's say, retailers or those kinds of large-scale vendors, they many times make money by lowering the amount that they spend on, you know, providing those goods to their end customers. So, I think those, both those factors kind of come into play and the solution to all of them is usually in a very structured strategy around automation. >> Final question. What does cloud-native at scale look like to you? If all the things happen the way we want them to happen, the magic wand, the magic dust, what does it look like? >> What that looks like to me is a CIO sipping at his desk on coffee, production is running absolutely smooth. And he's running that at a nimble, nimble team size of at the most, a handful of folks that are just looking after things, but things are just taking care of themselves. >> John: And the CIO doesn't exist and there's no CISO, there at the beach. >> (laughs) Yeah. >> Thank you for coming on, sharing the cloud-native at scale here on The Cube. Thank you for your time. >> Fantastic. Thanks for having me. >> Okay. I'm John Furrier here, for special program presentation, special programming cloud-native at scale, enabling SuperCloud modern applications with Platform9. Thanks for watching. (gentle music)

(upbeat music) >> Hello, welcome everyone to "theCUBE" presentation of the AWS Startup Showcase, this is Season Two, Episode Four of the ongoing series covering exciting startups from the AWS ecosystem. Here to talk about Cyber Security. I'm your host John Furrier here joined by two great "CUBE" alumnus, Liz Rice who's the chief open source officer at Isovalent, and Mark Nunnikhoven who's the distinguished cloud strategist at Lacework. Folks, thanks for joining me today. >> Hi. Pleasure. >> You're in the U.K. Mark, welcome back to the U.S, I know you were overseas as well. Thanks for joining in this panel to talk about set the table for the Cybersecurity Showcase. You guys are experts out in the field. Liz we've had many conversations with the rise of open source, and all the innovations coming from out in the open source community. Mark, we've been going and covering the events, looking at all the announcements we're kind of on this next generation security conversation. It's kind of a do over in progress, happening every time we talk security in the cloud, is what people are are talking about. Amazon Web Services had reinforced, which was more of a positive vibe of, Hey, we're all on it together. Let's participate, share information. And they talk about incidents, not breaches. And then, you got Black Hat just happened, and they're like, everyone's getting hacked. It's really interesting as we report that. So, this is a new market that we're in. People are starting to think differently, but still have to solve the same problems. How do you guys see the security in the cloud era unfolding? >> Well, I guess it's always going to be an arms race. Isn't it? Everything that we do to defend cloud workloads, it becomes a new target for the bad guys, so this is never going to end. We're never going to reach a point where everything is completely safe. But I think there's been a lot of really interesting innovations in the last year or two. There's been a ton of work looking into the security of the supply chain. There's been a ton of new tooling that takes advantage of technology that I'm really involved with and very excited about called eBPF. There's been a continuation of this new generation of tooling that can help us observe when security issues are happening, and also prevent malicious activities. >> And it's on to of open source activity. Mark, scale is a big factor now, it's becoming a competitive advantage on one hand. APIs have made the cloud great. Now, you've got APIs being hacked. So, all the goodness of cloud has been great, but now we've got next level scale, it's hard to keep up with everything. And so, you start to see new ways of doing things. What's your take? >> Yeah, it is. And everything that's old is new again. And so, as you start to see data and business workloads move into new areas, you're going to see a cyber crime and security activity move with them. And I love, Liz calling out eBPF and open source efforts because what we've really seen to contrast that sort of positive and negative attitude, is that as more people come to the security table, as more developers, as more executives are aware, and the accessibility of these great open source tools, we're seeing that shift in approach of like, Hey, we know we need to find a balance, so let's figure out where we can have a nice security outcome and still meet our business needs, as opposed to the more, let's say to be polite, traditional security view that you see at some other events where it's like, it's this way or no way. And so, I love to see that positivity and that collaboration happening. >> You know, Liz, this brings up a good point. We were talking at our Super Cloud Event we had here when we were discussing the future of how cloud's emerging. One of the conversations that Adrian Cockcroft brought up, who's now retired from AWS, former with Netflix. Adrian being open source fan as well. He was pointing out that every CIO or CISO will buy an abstraction layer. They love the dream. And vendors sell the dream, so to speak. But the reality it's not a lot of uptake because it's complex, And there's a lot of non-standard things per vendor. Now, we're in an era where people are looking for some standardization, some clean, safe ways to deploy. So, what's the message to CSOs, and CIOs, and CXOs out there around eBPF, things like that, that are emerging? Because it's almost top down, was the old way, now as bottoms up with open source, you're seeing the shift. I mean, it's complete flipping the script of how companies are buying? >> Yeah. I mean, we've seen with the whole cloud native movement, how people are rather than having like ETF standards, we have more of a defacto collaborative, kind of standardization process going on. So, that things like Kubernetes become the defacto standard that we're all using. And then, that's helping enterprises be able to run their workloads in different clouds, potentially in their own data centers as well. We see things like EKS anywhere, which is allowing people to run their workloads in their data center in exactly the same way as they're running it in AWS. That sort of leveling of the playing field, if you like, can help enterprises apply the same tooling, and that's going to always help with security if you can have a consistent approach wherever you are running your workload. >> Well, Liz's take a minute to explain eBPF. The Berkeley packet filtering technology, people know from Trace Dumps and whatnot. It's kind of been around for a while, but what is it specifically? Can you take a minute to explain eBPF, and what does that mean for the customer? >> Yeah. So, you mentioned the packet filtering acronym. And honestly, these days, I tell people to just forget that, because it means so much more for. What eBPF allows you to do now, is to run custom programs inside the kernel. So, we can use that to change the way that the kernel behaves. And because the kernel has visibility over every process that's running across a machine, a virtual machine or a bare metal machine, having security tooling and observability tooling that's written using eBPF and sitting inside the kernel. It has this great perspective and ability to observe and secure what's happening across that entire machine. This is like a step change in the capabilities really of security tooling. And it means we don't have to rely on things like kernel modules, which traditionally people have been quite worried about with good reason. eBPF is- >> From a vulnerability standpoint, you mean, right? From a reliability. >> From a vulnerability standpoint, but even just from the point of view that kernel modules, if they have bugs in them, a bug in the kernel will bring the machine to a halt. And one of the things that's different with eBPF, is eBPF programs go through a verification process that ensures that they're safe to run that, but happens dynamically and ensures that the program cannot crash, will definitely run to completion. All the memory access is safe. It gives us this very sort of reassuring platform to use for building these kernel-based tools. >> And what's the bottom line for the customer and the benefit to the organization? >> I think the bottom line is this new generation of really powerful tools that are very high performance. That have this perspective across the whole set of workloads on a machine. That don't need to rely on things like a CCAR model, which can add to a lot of complexity that was perfectly rational choice for a lot of security tools and observability tools. But if you can use an abstraction that lives in the kernel, things are much more efficient and much easier to deploy. So, I think that's really what that enterprise is gaining, simpler to deploy, easier to manage, lower overhead set of tools. >> That's the dream they want. That's what they want. Mark, this is whether the trade offs that comes up. We were talking about the supercloud, and all kinds. Even at AWS, you're going to have supercloud, but you got super hackers as well. As innovation happens on one side, the hackers are innovating on the other. And you start to see a lot of advances in the lower level, AWS with their Silicon and strategies are continuing to happen and be stronger, faster, cheaper, better down the lower levels at the network lay. All these things are innovating, but this is where the hackers are going too, right? So, it's a double edge sword? >> Yeah, and it always will be. And that's the challenge of technology, is sort of the advancement for one, is an advancement for all. But I think, while Liz hit the technical aspects of the eBPF spot on, what I'm seeing with enterprises, and in general with the market movement, is all of those technical advantages are increasing the confidence in some of this security tooling. So, the long sort of anecdote or warning in security has always been things like intrusion prevention systems where they will look at network traffic and drop things they think bad. Well, for decades, people have always deployed them in detect-only mode. And that's always a horrible conversation to have with the board saying, "Well, I had this tool in place that could have stopped the attack, but I wasn't really confident that it was stable enough to turn on. So, it just warned me that it had happened after the fact." And with the stability and the performance that we're seeing out of things based on technologies like eBPF, we're seeing that confidence increase. So, people are not only deploying this new level of tooling, but they're confident that it's actually providing the security it promised. And that's giving, not necessarily a leg up, but at least that level of parody with that push forward that we're seeing, similar on the attack side. Because attackers are always advancing as well. And I think that confidence and that reliability on the tooling, can't be underestimated because that's really what's pushing things forward for security outcomes. >> Well, one of the things I want get your both perspective on real quick. And you kind of segue into this next set of conversations, is with DevOps success, Dev and Ops, it's kind of done, right? We're all happy. We're seeing DevOps being so now DevSecOps. So, CSOs were like kind of old school. Buy a bunch of tools, we have a vendor. And with cloud native, Liz, you mentioned this earlier, accelerating the developers are even driving the standards more and more. So, shifting left is a security paradigm. So, tooling, Mark, you're on top of this too, it's tooling versus how do I organize my team? What are the processes? How do I keep the CICD pipeline going, higher velocity? How can I keep my app developers programming faster? And as Adrian Cockcroft said, they don't really care about locking, they want to go faster. It's the ops teams that have to deal with everything. So, and now security teams have to deal with the speed and velocity. So, you're seeing a new kind of step function, ratchet game where ops and security teams who are living DevOps, are still having to serve the devs, and the devs need more help here. So, how do you guys see that dynamic in security? Because this is clearly the shift left's, cloud native trend impacting the companies. 'Cause now it's not just shifting left for developers, it has a ripple effect into the organization and the security posture. >> We see a lot of organizations who now have what they would call a platform team. Which is something similar to maybe what would've been an ops team and a security team, where really their role is to provide that platform that developers can use. So, they can concentrate on the business function that they don't have to really think about the underlying infrastructure. Ideally, they're using whatever common definition for their applications. And then, they just roll it out to a cloud somewhere, and they don't have to think about where that's operating. And then, that platform team may have remit that covers, not just the compute, but also the networking, the common set of tooling that allows people to debug their applications, as well as securing them. >> Mark, this is a big discussion because one, I love the team, process collaboration. But where's the team? We've got a skills gap going on too, right? So, in all this, there's a lot of action happening. What's your take on this dynamic of tooling versus process collaboration for security success? >> Yeah, it's tough. And I think what we're starting to see, and you called it out spot on, is that the developers are all about dynamic change and rapid change, and operations, and security tend to like stability, and considered change in advance. And the business needs that needle to be threaded. And what we're seeing is sort of, with these new technologies, and with the ideas of finally moving past multicloud, into, as you guys call supercloud, which I absolutely love is a term. Let's get the advantage of all these things. What we're seeing, is people have a higher demand for the outputs from their tooling, and to find that balance of the process. I think it's acknowledged now that you're not going to have complete security. We've gotten past that, it's not a yes or no binary thing. It's, let's find that balance in risk. So, if we are deploying tooling, whether that's open source, or commercial, or something we built ourselves, what is the output? And who is best to take action on that output? And sometimes that's going to be the developers, because maybe they can just fix their architecture so that it doesn't have a particular issue. Sometimes that's going to be those platform teams saying like, "Hey, this is what we're going to apply for everybody, so that's a baseline standard." But the good news, is that those discussions are happening. And I think people are realizing that it's not a one size-fits-all. 10 years ago was sort of like, "Hey, we've got a blueprint and everyone does this." That doesn't work. And I think that being out in the open, really helps deliver these better outcomes. And because it isn't simple, it's always going to be an ongoing discussion. 'Cause what we decide today, isn't going to be the same thing in a week from now when we're sprint ahead, and we've made a whole bunch of changes on the platform and in our code. >> I think the cultural change is real. And I think this is hard for security because you got so much current action happening that's really important to the business. That's hard to just kind of do a reset without having any collateral damage. So, you kind of got to mitigate and manage all the current situation, and then try to build a blueprint for the future and transform into a kind of the next level. And it kind of reminds me of, I'm dating myself. But back in the days, you had open source was new. And the common enemy was proprietary, non-innovative old guard, kind of mainframe mini computer kind of proprietary analysis, proprietary everything. Here, there is no enemy. The clouds are doing great, right? They're leaning in open source is at all time high and not stopping, it's it's now standard. So, open is not a rebel. It's not the rebel anymore, it's the standard. So, you have the innovation happening in open source, Liz, and now you have large scale cloud. And this is a cultural shift, right? How people are buying, evaluating product, and implementing solutions. And I when I say new, I mean like new within the decades or a couple decades. And it's not like open source is not been around. But like we're seeing new things emerge that are pretty super cool in the sense that you have projects defining standards, new things are emerging. So, the CIO decision making process on how to structure teams and how to tackle security is changing. Why IT department? I mean, just have a security department and a Dev team. >> I think the fact that we are using so much more open source software is a big part of this cultural shift where there are still a huge ecosystem of vendors involved in security tools and observability tools. And Mark and I both represent vendors in those spaces. But the rise of open source tools, means that you can start with something pretty powerful that you can grow with. As you are experimenting with the security tooling that works for you, you don't have to pay a giant sum to get a sort of black box. You can actually understand the open source elements of the tooling that you are going to use. And then build on that and get the enterprise features when you need those. And I think that cultural change makes it much easier for people to work security in from the get go, and really, do that shift left that we've been talking about for the last few years. >> And I think one of the things to your point, and not only can you figure out what's in the open source code, and then build on top of it, you can also leave it too. You can go to something better, faster. So, the switching costs are a lot lower than a lock in from a vendor, where you do all the big POCs and the pilots. And, Mark, this is changing the game. I mean, I would just be bold enough to say, IT is going to be irrelevant in the sense of, if you got DevOps and it works, and you got security teams, do you really need IT 'cause the DevOps is the IT? So, if everyone goes to the cloud operations, what does IT even mean? >> Yeah, and it's a very valid point. And I think what we're seeing, is where IT is still being successful, especially in large companies, is sort of the economy of scale. If you have enough of the small teams doing the same thing, it makes sense to maybe take one tool and scale it up because you've got 20 teams that are using it. So, instead of having 20 teams run it, you get one team to run it. On the economic side, you can negotiate one contract if it's a purchase tool. There is still a place for it, but I think what we're seeing and in a very positive way, is that smaller works better when it comes to this. Because really what the cloud has done and what open source continues to do, is reduce the barrier to entry. So, a team of 10 people can build something that it took a 1000 people, a decade ago. And that's wonderful. And that opens up all these new possibilities. We can work faster. But we do need to rethink it at reinforce from AWS. They had a great track about how they're approaching it from people side of things with their security champion's idea. And it's exactly about this, is embedding high end security talent in the teams who are building it. So, that changes the central role, and the central people get called in for big things like an incident response, right? Or a massive auditor reviews. But the day-to-day work is being done in context. And I think that's the real key, is they've got the context to make smarter security decisions, just like the developers and the operational work is better done by the people who are actually working on the thing, as opposed to somebody else. Because that centralized thing, it's just communication overhead most of the time. >> Yeah. I love chatting with you guys because here's are so much experts on the field. To put my positive hat on around IT, remember the old argument of, "Oh, automation's, technology's going to kill the bank teller." There's actually more tellers now than ever before. So, the ATM machine didn't kill that. So, I think IT will probably reform from a human resource perspective. And I think this is kind of where the CSO conversation comes full circle, Liz and Mark, because, okay, let's assume that this continues the trajectory to open source, DevOps, cloud scale, hybrid. It's a refactoring of personnel. So, you're going to have DevOps driving everything. So, now the IT team becomes a team. So, most CSOs we talk to are CXOs, is how do I deploy my teams? How do I structure things, my investment in people, and machines and software in a way that I get my return? At the end of the day, that's what they live for, and do it securely. So, this is the CISO's kind of thought process. How do you guys react to that? What's the message to CISOs? 'Cause they have a lot of companies to look at here. And in the marketplace, they got to spend some money, they got to get a return, they got to reconfigure. What's your advice? Liz, what's your take? Then we'll go to Mark. >> That's a really great question. I think cloud skills, cloud engineering skills, cloud security skills have never been more highly valued. And I think investing in training people to understand cloud that there are tons of really great resources out there to help ramp people up on these skills. The CNCF, AWS, there's tons of organizations who have really great courses and exams, and things that people can do to really level up their skills, which is fantastic right from a grassroots level, through to the most widely deployed global enterprise. I think we're seeing a lot of people are very excited, develop these skills. >> Mark, what's your take for the CSO, the CXO out there? They're scratching their head, they're going, "Okay, I need to invest. DevOps is happening. I see the open source, I'm now got to change over. Yeah, I lift and shift some stuff, now I got to refactor my business or I'm dead." What's your advice? >> I think the key is longer term thinking. So, I think where people fell down previously, was, okay, I've got money, I can buy tools, roll 'em out. Every tool you roll out, has not just an economic cost, but a people cost. As Liz said, those people with those skills are in high demand. And so, you want to make sure that you're getting the most value out of your people, but your tooling. So, as you're investing in your people, you will need to roll out tools. But they're not the answer. The answer is the people to get the value out of the tools. So, hold your tools to a higher standard, whether that's commercial, open source, or something from the CSP, to make sure that you're getting actionable insights and value out of them that your people can actually use to move forward. And it's that balance between the two. But I love the fact that we're finally rotating back to focus more on the people. Because really, at the end of the day, that's what's going to make it all work. >> Yeah. The hybrid work, people processes. The key, the supercloud brings up the conversation of where we're starting to see maturation into OPEX models where CapEx is a gift from the clouds. But it's not the end of bilk. Companies are still responsible for their own security. At the end of the day, you can't lean on AWS or Azure. They have infrastructure and software, but at the end of the day, every company has to maintain their own. Certainly, with hybrid and edge coming, it's here. So, this whole concept of IT, CXO, CIO, CSO, CSO, I mean, this is hotter than ever in terms of like real change. What's your reaction to that? >> I was just reading this morning that the cost of ensuring against data breaches is getting dramatically more expensive. So, organizations are going to have to take steps to implement security. You can't just sort of throw money at the problem, you're going to actually have to throw people and technology at the problem, and take security really seriously. There is this whole ecosystem of companies and folks who are really excited about security and here to help. There's a lot of people interested in having that conversation to help those CSOs secure their deployments. >> Mark, your reaction? >> Yeah. I think, anything that causes us to question what we're doing is always a positive thing. And I think everything you brought up really comes down to remembering that no matter what, and no matter where, your data is always your data. And so, you have some level of responsibility, and that just changes depending on what system you're using. And I think that's really shifting, especially in the CSO or the CSO mindset, to go back to the basics where it used to be information security and not just cyber security. So, whether that information and that data is sitting on my desk physically, in a system in our data center, or in the cloud somewhere. Looking holistically, and that's why we could keep coming back to people. That's what it's all about. And when you step back there, you start to realize there's a lot more trade offs. There's a lot more levers that you can work on, to deliver the outcome you want, to find that balance that works for you. 'Cause at the end of the day, security is just all about making sure that whatever you built and the systems you're working with, do what you want them to do, and only what you want them to do. >> Well, Liz and Mark, thank you so much for your expert perspective. You're in the trenches, and really appreciate your time and contributing with "theCUBE," and being part of our Showcase. For the last couple of minutes, let's dig into some of the things you're working on. I know network policies around Kubernetes, Liz, EKS anywhere has been fabulous with Lambda and Serverless, you seeing some cool things go on there. Mark, you're at Lacework, very successful company. And looking at a large scale observability, signaling and management, all kinds of cool things around native cloud services and microservices. Liz, give us an update. What's going on over there at Isovalent? >> Yeah. So, Isovalent is the company behind Cilium Networking Project. Its best known as a Kubernetes networking plugin. But we've seen huge amount of adoption of cilium, it's really skyrocketed since we became an incubating project in the CNCF. And now, we are extending to using eBPF to not just do networking, but incredibly in depth observability and security observability have a new sub project called Tetragon, that gives you this amazing ability to see out of policy behavior. And again, because it's using eBPF, we've got the perspective of everything that's happening across the whole machine. So, I'm really excited about the innovations that are happening here. >> Well, they're lucky to have you. You've been a great contributor to the community. We've been following your career for very, very long time. And thanks for everything that you do, really appreciate it. Thanks. >> Thank you. >> Mark, Lacework, we we've following you guys. What are you up to these days? You know, we see you're on Twitter, you're very prolific. You're also live tweeting all the events, and with us as well. What's going on over there at Lacework? And what's going on in your world? >> Yeah. Lacework, we're still focusing on the customer, helping deliver good outcomes across cloud when it comes to security. Really looking at their environments and helping them understand, from their data that they're generating off their systems, and from the cloud usage as to what's actually happening. And that pairs directly into the work that I'm doing, the community looking at just security as a practice. So, a lot of that pulling people out of the technology, and looking at the process and saying, "Hey, we have this tech for a reason." So, that people understand what they need in place from a skill set, to take advantage of the great work that folks like Liz and the community are doing. 'Cause we've got these great tools, they're outputting all this great insights. You need to be able to take actions on top of that. So, it's always exciting. More people come into security with a security mindset, love it. >> Well, thanks so much for this great conversation. Every board should watch this video, every CSO, CIO, CSO. Great conversation, thanks for unpacking and making something very difficult, clear to understand. Thanks for your time. >> Pleasure. >> Thank you. >> Okay, this is the AWS Startup Showcase, Season Two, Episode Four of the ongoing series covering the exciting startups from the AWS ecosystem. We're talking about cybersecurity, this segment. Every quarter episode, we do a segment around a category and we go deep, we feature some companies, and talk to the best people in the industry to help you understand that. I'm John Furrier your host. Thanks for watching. (upbeat music)

(upbeat music) >> Hey everyone and welcome back to The Cube. We are covering VMware Explore live in San Francisco. This is our third day of wall to wall coverage. And John Furrier is here with me, Lisa Martin. We are excited to welcome two guests from Kasten by Veeam, please welcome Tom Laden, VP of marketing and Matt LeBlanc, not Joey from friends, Matt LeBlanc, the systems engineer from North America at Kasten by Veeam. Welcome guys, great to have you. >> Thank you. >> Thank you for having us. >> Tom-- >> Great, go ahead. >> Oh, I was going to say, Tom, talk to us about some of the key challenges customers are coming to you with. >> Key challenges that they have at this point is getting up to speed with Kubernetes. So everybody has it on their list. We want to do Kubernetes, but where are they going to start? Back when VMware came on the market, I was switching from Windows to Mac and I needed to run a Windows application on my Mac and someone told me, "Run a VM." Went to the internet, I downloaded it. And in a half hour I was done. That's not how it works with Kubernetes. So that's a bit of a challenge. >> I mean, Kubernetes, Lisa, remember the early days of The Cube Open Stack was kind of transitioning, Cloud was booming and then Kubernetes was the paper that became the thing that pulled everybody together. It's now de facto in my mind. So that's clear, but there's a lot of different versions of it and you hear VMware, they call it the dial tone. Usually, remember, Pat Gelter, it's a dial tone. Turns out that came from Kit Colbert or no, I think AJ kind of coined the term here, but it's since been there, it's been adopted by everyone. There's different versions. It's open source. AWS is involved. How do you guys look at the relationship with Kubernetes here and VMware Explore with Kubernetes and the customers because they have choices. They can go do it on their own. They can add a little bit with Lambda, Serverless. They can do more here. It's not easy. It's not as easy as people think it is. And then this is a skill gaps problem too. We're seeing a lot of these problems out there. What's your take? >> I'll let Matt talk to that. But what I want to say first is this is also the power of the cloud native ecosystem. The days are gone where companies were selecting one enterprise application and they were building their stack with that. Today they're building applications using dozens, if not hundreds of different components from different vendors or open source platforms. And that is really what creates opportunities for those cloud native developers. So maybe you want to... >> Yeah, we're seeing a lot of hybrid solutions out there. So it's not just choosing one vendor, AKS, EKS, or Tanzu. We're seeing all the above. I had a call this morning with a large healthcare provider and they have a hundred clusters and that's spread across AKS, EKS and GKE. So it is covering everything. Plus the need to have a on-prem solution manage it all. >> I got a stat, I got to share that I want to get your reactions and you can laugh or comment, whatever you want to say. Talk to big CSO, CXO, executive, big company, I won't say the name. We got a thousand developers, a hundred of them have heard of Kubernetes, okay. 10 have touched it and used it and one's good at it. And so his point is that there's a lot of Kubernetes need that people are getting aware. So it shows that there's more and more adoption around. You see a lot of managed services out there. So it's clear it's happening and I'm over exaggerating the ratio probably. But the point is the numbers kind of make sense as a thousand developers. You start to see people getting adoption to it. They're aware of the value, but being good at it is what we're hearing is one of those things. Can you guys share your reaction to that? Is that, I mean, it's hyperbole at some level, but it does point to the fact of adoption trends. You got to get good at it, you got to know how to use it. >> It's very accurate, actually. It's what we're seeing in the market. We've been doing some research of our own, and we have some interesting numbers that we're going to be sharing soon. Analysts don't have a whole lot of numbers these days. So where we're trying to run our own surveys to get a grasp of the market. One simple survey or research element that I've done myself is I used Google trends. And in Google trends, if you go back to 2004 and you compare VMware against Kubernetes, you get a very interesting graph. What you're going to see is that VMware, the adoption curve is practically complete and Kubernetes is clearly taking off. And the volume of searches for Kubernetes today is almost as big as VMware. So that's a big sign that this is starting to happen. But in this process, we have to get those companies to have all of their engineers to be up to speed on Kubernetes. And that's one of the community efforts that we're helping with. We built a website called learning.kasten.io We're going to rebrand it soon at CubeCon, so stay tuned, but we're offering hands on labs there for people to actually come learn Kubernetes with us. Because for us, the faster the adoption goes, the better for our business. >> I was just going to ask you about the learning. So there's a big focus here on educating customers to help dial down the complexity and really get them, these numbers up as John was mentioning. >> And we're really breaking it down to the very beginning. So at this point we have almost 10 labs as we call them up and they start really from install a Kubernetes Cluster and people really hands on are going to install a Kubernetes Cluster. They learn to build an application. They learn obviously to back up the application in the safest way. And then there is how to tune storage, how to implement security, and we're really building it up so that people can step by step in a hands on way learn Kubernetes. >> It's interesting, this VMware Explore, their first new name change, but VMWorld prior, big community, a lot of customers, loyal customers, but they're classic and they're foundational in enterprises and let's face it. Some of 'em aren't going to rip out VMware anytime soon because the workloads are running on it. So in Broadcom we'll have some good action to maybe increase prices or whatnot. So we'll see how that goes. But the personas here are definitely going cloud native. They did with Tanzu, was a great thing. Some stuff was coming off, the fruit's coming off the tree now, you're starting to see it. CNCF has been on this for a long, long time, CubeCon's coming up in Detroit. And so that's just always been great, 'cause you had the day zero event and you got all kinds of community activity, tons of developer action. So here they're talking, let's connect to the developer. There the developers are at CubeCon. So the personas are kind of connecting or overlapping. I'd love to get your thoughts, Matt on? >> So from the personnel that we're talking to, there really is a split between the traditional IT ops and a lot of the people that are here today at VMWare Explore, but we're also talking with the SREs and the dev ops folks. What really needs to happen is we need to get a little bit more experience, some more training and we need to get these two groups to really start to coordinate and work together 'cause you're basically moving from that traditional on-prem environment to a lot of these traditional workloads and the only way to get that experience is to get your hands dirty. >> Right. >> So how would you describe the persona specifically here versus say CubeCon? IT ops? >> Very, very different, well-- >> They still go ahead. Explain. >> Well, I mean, from this perspective, this is all about VMware and everything that they have to offer. So we're dealing with a lot of administrators from that regard. On the Kubernetes side, we have site reliability engineers and their goal is exactly as their title describes. They want to architect arch applications that are very resilient and reliable and it is a different way of working. >> I was on a Twitter spaces about SREs and dev ops and there was people saying their title's called dev ops. Like, no, no, you do dev ops, you don't really, you're not the dev ops person-- >> Right, right. >> But they become the dev ops person because you're the developer running operations. So it's been weird how dev ops been co-opted as a position. >> And that is really interesting. One person told me earlier when I started Kasten, we have this new persona. It's the dev ops person. That is the person that we're going after. But then talking to a few other people who were like, "They're not falling from space." It's people who used to do other jobs who now have a more dev ops approach to what they're doing. It's not a new-- >> And then the SRE conversation was in site, reliable engineer comes from Google, from one person managing multiple clusters to how that's evolved into being the dev ops. So it's been interesting and this is really the growth of scale, the 10X developer going to more of the cloud native, which is okay, you got to run ops and make the developer go faster. If you look at the stuff we've been covering on The Cube, the trends have been cloud native developers, which I call dev ops like developers. They want to go faster. They want self-service and they don't want to slow down. They don't want to deal with BS, which is go checking security code, wait for the ops team to do something. So data and security seem to be the new ops. Not so much IT ops 'cause that's now cloud. So how do you guys see that in, because Kubernetes is rationalizing this, certainly on the compute side, not so much on storage yet but it seems to be making things better in that grinding area between dev and these complicated ops areas like security data, where it's constantly changing. What do you think about that? >> Well there are still a lot of specialty folks in that area in regards to security operations. The whole idea is be able to script and automate as much as possible and not have to create a ticket to request a VM to be billed or an operating system or an application deployed. They're really empowered to automatically deploy those applications and keep them up. >> And that was the old dev ops role or person. That was what dev ops was called. So again, that is standard. I think at CubeCon, that is something that's expected. >> Yes. >> You would agree with that. >> Yeah. >> Okay. So now translating VM World, VMware Explore to CubeCon, what do you guys see as happening between now and then? Obviously got re:Invent right at the end in that first week of December coming. So that's going to be two major shows coming in now back to back that're going to be super interesting for this ecosystem. >> Quite frankly, if you compare the persona, maybe you have to step away from comparing the personas, but really compare the conversations that we're having. The conversations that you're having at a CubeCon are really deep dives. We will have people coming into our booth and taking 45 minutes, one hour of the time of the people who are supposed to do 10 minute demos because they're asking more and more questions 'cause they want to know every little detail, how things work. The conversations here are more like, why should I learn Kubernetes? Why should I start using Kubernetes? So it's really early day. Now, I'm not saying that in a bad way. This is really exciting 'cause when you hear CNCF say that 97% of enterprises are using Kubernetes, that's obviously that small part of their world. Those are their members. We now want to see that grow to the entire ecosystem, the larger ecosystem. >> Well, it's actually a great thing, actually. It's not a bad thing, but I will counter that by saying I am hearing the conversation here, you guys'll like this on the Veeam side, the other side of the Veeam, there's deep dives on ransomware and air gap and configuration errors on backup and recovery and it's all about Veeam on the other side. Those are the guys here talking deep dive on, making sure that they don't get screwed up on ransomware, not Kubernete, but they're going to Kub, but they're now leaning into Kubernetes. They're crossing into the new era because that's the apps'll end up writing the code for that. >> So the funny part is all of those concepts, ransomware and recovery, they're all, there are similar concepts in the world of Kubernetes and both on the Veeam side as well as the Kasten side, we are supporting a lot of those air gap solutions and providing a ransomware recovery solution and from a air gap perspective, there are a many use cases where you do need to live. It's not just the government entity, but we have customers that are cruise lines in Europe, for example, and they're disconnected. So they need to live in that disconnected world or military as well. >> Well, let's talk about the adoption of customers. I mean this is the customer side. What's accelerating their, what's the conversation with the customer at base, not just here but in the industry with Kubernetes, how would you guys categorize that? And how does that get accelerated? What's the customer situation? >> A big drive to Kubernetes is really about the automation, self-service and reliability. We're seeing the drive to and reduction of resources, being able to do more with less, right? This is ongoing the way it's always been. But I was talking to a large university in Western Canada and they're a huge Veeam customer worth 7000 VMs and three months ago, they said, "Over the next few years, we plan on moving all those workloads to Kubernetes." And the reason for it is really to reduce their workload, both from administration side, cost perspective as well as on-prem resources as well. So there's a lot of good business reasons to do that in addition to the technical reliability concerns. >> So what is those specific reasons? This is where now you start to see the rubber hit the road on acceleration. >> So I would say scale and flexibility that ecosystem, that opportunity to choose any application from that or any tool from that cloud native ecosystem is a big driver. I wanted to add to the adoption. Another area where I see a lot of interest is everything AI, machine learning. One example is also a customer coming from Veeam. We're seeing a lot of that and that's a great thing. It's an AI company that is doing software for automated driving. They decided that VMs alone were not going to be good enough for all of their workloads. And then for select workloads, the more scalable one where scalability was more of a topic, would move to Kubernetes. I think at this point they have like 20% of their workloads on Kubernetes and they're not planning to do away with VMs. VMs are always going to be there just like mainframes still exist. >> Yeah, oh yeah. They're accelerating actually. >> We're projecting over the next few years that we're going to go to a 50/50 and eventually lean towards more Kubernetes than VMs, but it was going to be a mix. >> Do you have a favorite customer example, Tom, that you think really articulates the value of what Kubernetes can deliver to customers where you guys are really coming in and help to demystify it? >> I would think SuperStereo is a really great example and you know the details about it. >> I love the SuperStereo story. They were a AWS customer and they're running OpenShift version three and they need to move to OpenShift version four. There is no upgrade in place. You have to migrate all your apps. Now SuperStereo is a large French IT firm. They have over 700 developers in their environment and it was by their estimation that this was going to take a few months to get that migration done. We're able to go in there and help them with the automation of that migration and Kasten was able to help them architect that migration and we did it in the course of a weekend with two people. >> A weekend? >> A weekend. >> That's a hackathon. I mean, that's not real come on. >> Compared to thousands of man hours and a few months not to mention since they were able to retire that old OpenShift cluster, the OpenShift three, they were able to stop paying Jeff Bezos for a couple of those months, which is tens of thousands of dollars per month. >> Don't tell anyone, keep that down low. You're going to get shot when you leave this place. No, seriously. This is why I think the multi-cloud hybrid is interesting because these kinds of examples are going to be more than less coming down the road. You're going to see, you're going to hear more of these stories than not hear them because what containerization now Kubernetes doing, what Dockers doing now and the role of containers not being such a land grab is allowing Kubernetes to be more versatile in its approach. So I got to ask you, you can almost apply that concept to agility, to other scenarios like spanning data across clouds. >> Yes, and that is what we're seeing. So the call I had this morning with a large insurance provider, you may have that insurance provider, healthcare provider, they're across three of the major hyperscalers clouds and they do that for reliability. Last year, AWS went down, I think three times in Q4 and to have a plan of being able to recover somewhere else, you can actually plan your, it's DR, it's a planned migration. You can do that in a few hours. >> It's interesting, just the sidebar here for a second. We had a couple chats earlier today. We had the influences on and all the super cloud conversations and trying to get more data to share with the audience across multiple areas. One of them was Amazon and that super, the hyper clouds like Amazon, as your Google and the rest are out there, Oracle, IBM and everyone else. There's almost a consensus that maybe there's time for some peace amongst the cloud vendors. Like, "Hey, you've already won." (Tom laughs) Everyone's won, now let's just like, we know where everyone is. Let's go peace time and everyone, then 'cause the relationship's not going to change between public cloud and the new world. So there's a consensus, like what does peace look like? I mean, first of all, the pie's getting bigger. You're seeing ecosystems forming around all the big new areas and that's good thing. That's the tides rise and the pie's getting bigger, there's bigger market out there now so people can share and share. >> I've never worked for any of these big players. So I would have to agree with you, but peace would not drive innovation. And in my heart is with tech innovation. I love it when vendors come up with new solutions that will make things better for customers and if that means that we're moving from on-prem to cloud and back to on-prem, I'm fine with that. >> What excites me is really having the flexibility of being able to choose any provider you want because you do have open standards, being cloud native in the world of Kubernetes. I've recently discovered that the Canadian federal government had mandated to their financial institutions that, "Yes, you may have started all of your on cloud presence in Azure, you need to have an option to be elsewhere." So it's not like-- >> Well, the sovereign cloud is one of those big initiatives, but also going back to Java, we heard another guest earlier, we were thinking about Java, right once ran anywhere, right? So you can't do that today in a cloud, but now with containers-- >> You can. >> Again, this is, again, this is the point that's happening. Explain. >> So when you have, Kubernetes is a strict standard and all of the applications are written to that. So whether you are deploying MongoDB or Postgres or Cassandra or any of the other cloud native apps, you can deploy them pretty much the same, whether they're in AKS, EKS or on Tanzu and it makes it much easier. The world became just a lot less for proprietary. >> So that's the story that everybody wants to hear. How does that happen in a way that is, doesn't stall the innovation and the developer growth 'cause the developers are driving a lot of change. I mean, for all the talk in the industry, the developers are doing pretty good right now. They've got a lot of open source, plentiful, open source growing like crazy. You got shifting left in the CICD pipeline. You got tools coming out with Kubernetes. Infrastructure has code is almost a 100% reality right now. So there's a lot of good things going on for developers. That's not an issue. The issue is just underneath. >> It's a skillset and that is really one of the biggest challenges I see in our deployments is a lack of experience. And it's not everyone. There are some folks that have been playing around for the last couple of years with it and they do have that experience, but there are many people that are still young at this. >> Okay, let's do, as we wrap up, let's do a lead into CubeCon, it's coming up and obviously re:Invent's right behind it. Lisa, we're going to have a lot of pre CubeCon interviews. We'll interview all the committee chairs, program chairs. We'll get the scoop on that, we do that every year. But while we got you guys here, let's do a little pre-pre-preview of CubeCon. What can we expect? What do you guys think is going to happen this year? What does CubeCon look? You guys our big sponsor of CubeCon. You guys do a great job there. Thanks for doing that. The community really recognizes that. But as Kubernetes comes in now for this year, you're looking at probably the what third year now that I would say Kubernetes has been on the front burner, where do you see it on the hockey stick growth? Have we kicked the curve yet? What's going to be the level of intensity for Kubernetes this year? How's that going to impact CubeCon in a way that people may or may not think it will? >> So I think first of all, CubeCon is going to be back at the level where it was before the pandemic, because the show, as many other shows, has been suffering from, I mean, virtual events are not like the in-person events. CubeCon LA was super exciting for all the vendors last year, but the attendees were not really there yet. Valencia was a huge bump already and I think Detroit, it's a very exciting city I heard. So it's going to be a blast and it's going to be a huge attendance, that's what I'm expecting. Second I can, so this is going to be my third personally, in-person CubeCon, comparing how vendors evolved between the previous two. There's going to be a lot of interesting stories from vendors, a lot of new innovation coming onto the market. And I think the conversations that we're going to be having will yet, again, be much more about live applications and people using Kubernetes in production rather than those at the first in-person CubeCon for me in LA where it was a lot about learning still, we're going to continue to help people learn 'cause it's really important for us but the exciting part about CubeCon is you're talking to people who are using Kubernetes in production and that's really cool. >> And users contributing projects too. >> Also. >> I mean Lyft is a poster child there and you've got a lot more. Of course you got the stealth recruiting going on there, Apple, all the big guys are there. They have a booth and no one's attending you like, "Oh come on." Matt, what's your take on CubeCon? Going in, what do you see? And obviously a lot of dynamic new projects. >> I'm going to see much, much deeper tech conversations. As experience increases, the more you learn, the more you realize you have to learn more. >> And the sharing's going to increase too. >> And the sharing, yeah. So I see a lot of deep conversations. It's no longer the, "Why do I need Kubernetes?" It's more, "How do I architect this for my solution or for my environment?" And yeah, I think there's a lot more depth involved and the size of CubeCon is going to be much larger than we've seen in the past. >> And to finish off what I think from the vendor's point of view, what we're going to see is a lot of applications that will be a lot more enterprise-ready because that is the part that was missing so far. It was a lot about the what's new and enabling Kubernetes. But now that adoption is going up, a lot of features for different components still need to be added to have them enterprise-ready. >> And what can the audience expect from you guys at CubeCon? Any teasers you can give us from a marketing perspective? >> Yes. We have a rebranding sitting ready for learning website. It's going to be bigger and better. So we're not no longer going to call it, learning.kasten.io but I'll be happy to come back with you guys and present a new name at CubeCon. >> All right. >> All right. That sounds like a deal. Guys, thank you so much for joining John and me breaking down all things Kubernetes, talking about customer adoption, the challenges, but also what you're doing to demystify it. We appreciate your insights and your time. >> Thank you so much. >> Thank you very much. >> Our pleasure. >> Thanks Matt. >> For our guests and John Furrier, I'm Lisa Martin. You've been watching The Cube's live coverage of VMware Explore 2022. Thanks for joining us. Stay safe. (gentle music)

>>Welcome back everyone to the cubes coverage here live in San Francisco for VMware Explorer. Formerly got it. World. We've been to every world since 2010. Now is VMware Explorer. I'm John furier host with Dave ante with Dave lium here. He's the chief cloud strategy officer at Deloitte. Welcome to the cube. Thanks for coming on. Appreciate your time. >>Thanks for having me. It's >>Epic keynote today on stage all seven minutes of your great seven minutes >>Performance discussion. Yes. Very, very, very, very quick to the order. I brought everybody up to speed and left. >>Well, Dave's great to have you on the cube one. We follow your work. We've been following for a long time. Thank you. A lot of web services, a lot of SOA, kind of in your background, kind of the old web services, AI, you know, samples, RSS, web services, all that good stuff. Now it's, it's now we're in kind of web services on steroids. Cloud came it's here. We're NextGen. You wrote a great story on Metacloud. You've been following the Supercloud with Dave. Does VMware have it right? >>Yeah, they do. Because I'll tell you what the market is turning toward. Anything that sit above and between the clouds. So things that don't exist in the hyperscaler, things that provide common services above the cloud providers are where the growth's gonna happen. We haven't really solved that problem yet. And so there's lots of operational aspects, security aspects, and the ability to have some sort of a brokering service that'll scale. So multi-cloud, which is their strategy here is not about cloud it's about things that exist in between cloud and making those things work. So getting to another layer of abstraction and automation to finally allow us to make use out of all these hyperscaler services that we're signing on today. Dave, >>Remember the old days back in the eighties, when we were young bucks coming into the business, the interoperability wave was coming. Remember that? Oh yeah, I got a deck mini computer. I got an IBM was gonna solve that unex. And then, you know, this other thing over here and lands and all and everything started getting into this whole, okay. Networking. Wasn't just coax. You started to see segment segments. Interoperability was a huge, what 10 year run. It feels like that's kind of like the vibe going on here. >>Yeah. We're not focused on having these things interop operate onto themselves. So what we're doing is putting a layer of things which allows them to interop operate. That's a different, that's a different problem to solve. And it's also solvable. We were talking about getting all these very distinct proprietary systems to communicate one to another and interate one to another. And that never really happened. Right? Cause you gotta get them to agree on interfaces and protocols. But if you put a layer above it, they can talk down to whatever native interfaces that are there and deal with the differences between the heterogeneity and abstract yourself in the complexity. And that's, that's kind of the different that works. The ability to kind of get everybody, you know, clunk their heads together and make them work together. That doesn't seem to scale couple >>And, and people gotta be motivated for that. Not many people might not >>Has me money. In other words has to be a business for them in doing so. >>A couple things I wanna follow up on from work, you know, this morning they used the term cloud chaos. When you talk to customers, you know, when they have multiple clouds, do they, are they saying to you, Hey, we have cloud chaos are, do they have cloud chaos? And they don't know it or do they not have cloud chaos? What's the mix. >>Yeah. I don't think the word chaos is used that much, but they do tell me they're hitting a complexity wall, which you do here out there as a term. So in other words, they're getting to a point where they can't scale operations to deal with a complexity and heterogeneity that they're, that they're bringing into the organization because using multiple clouds. So that is chaotic. So I guess that, you know, it is another way to name complexity. So there's so many services are moving from a thousand cloud services, under management to 3000 cloud services under management. They don't have the operational team, the skill, skill levels to do it. They don't have the tooling to do it. That's a wall. And you have to be able to figure out how to get beyond that wall to make those things work. So >>When, when we had our conversation about Metacloud and Supercloud, we we've, I think very much aligned in our thinking. And so now you've got this situation where you've got these abstraction layers, but, and there, but my question is, are we gonna have multiple abstraction layers? And will they talk to each other or are standards emerging? Will they be able to, >>No, we can't have multiple abstraction layers else. We just, we don't solve the problem. We go from complexity of exists at the native cloud levels to complexity of exists, that this thing we're dealing with to deal with complexity. So if you do that, we're screwing up. We have to go back and fix it. So ultimately this is about having common services, common security, layers, common operational layers, and things like that that are really reduced redundancy within the system. So instead of having a, you know, five different security layers and five different cloud providers, we're layering one and providing management and orchestration capabilities to make that happen. If we don't do that, we're not succeeding. >>What do you think about the marketplace? I know there's a lot of things going on that are happening around this. Wanna get your thoughts on obviously the industry dynamics, vendors preserving their future. And then you've got customers who have been leveraging the CapEx, goodness of say Amazon and then have to solve their whole distributed environment problem. So when you look at this, is it really solving? Is it is the order of operations first common layer abstraction because you know, it seems like the vendor, I won't say desperation move, but like their first move is we're gonna be the control plane or, you know, I think Cisco has a vision in their mind that no, no we're gonna have that management plane. I've heard a lot of people talking about, we're gonna be the management interface into something. How do you see that playing out? Because the order of operations to do the abstraction is to get consensus, right, right. First not competition. Right. So how do you see that? What's your reaction to that? And what's your observation. >>I think it's gonna be tough for the people who are supplying the underlying services to also be the orchestration and abstraction layers, because they're, they're kind of conflicted in making that happen. In other words, it's not in their best interest to make all these things work and interoperate one to another, but it's their best interest to provide, provide a service that everybody's going to leverage. So I see the layers here. I'm certainly the hyperscalers are gonna play in those layers and then they're welcome to play in those layers. They may come up with a solution that everybody picks, but ultimately it's about independence and your ability to have an objective way of, of allowing all these things to communicate together and driving this, driving this stuff together, to reduce the complexity again, to reduce. >>So a network box, for instance, maybe have hooks into it, but not try to dominate it >>Or that's right. Yeah, that's right. I think if you're trying to own everything and I get that a lot when I write about Supercloud and, and Metacloud they go, well, we're the Metacloud, we're the Supercloud you can't be other ones. That's a huge problem to solve. I know you don't have a solution for that. Okay. It's gonna be many different products to make that happen. And the reality is people who actually make that work are gonna have to be interdependent independent of the various underlying services. They're gonna, they can support them, but they really can't be them. They have to be an interate interop. They have to interoperate with those services. >>Do you, do you see like a w three C model, like the worldwide web consortium, remember that came out around 96, came to the us and MIT and then helped for some of those early standards in, in, in the internet, not DNS, but like the web, but DNS was already there and internet was already there, but like the web standards HTML kind of had, I think wasn't really hardcore get you in the headlock, but at least it was some sort of group that said, Hey, intellectually be honest, you see that happening in this area. >>I hope not. And here's >>Why not. >>Yeah. >>Here's, here's why the reality is is that when these consortiums come into play, it freezes the market. Everybody waits for the consortium to come up with some sort of a solution that's gonna save the world. And that solution never comes because you can't get these organizations through committee to figure out some sort of a technology stack that's gonna be working. So I'd rather see the market figure that out. Not a consortium when >>I, you mean the ecosystem, not some burning Bush. >>Yeah. Not some burning Bush. And it just hasn't worked. I mean, if it worked, it'd be great. And >>We had a, an event on August 9th, it was super cloud 22 and we had a security securing the super cloud panel. And one of my was a great conversation as you remember, John, but it was kind of depressing in that, like we're never gonna solve this problem. So what are you seeing in the security front? You know, it seems to like that's a main blocker to the Metacloud the Supercloud >>Yeah. The reality is you can't build all the security services in, in the Metacloud. You have to basically leverage the security services on the native cloud and leverage them as they exist. So this idea that we're gonna replace all of these security services with one layer of abstraction, that's gonna provide the services. So you don't need these underlying security systems that won't work. You have to leverage the native security systems, native governance, native operating interfaces, native APIs of all the various native clouds using the terms that they're looking to leverage. And that's the mistake. I think people are going to make, you don't need to replace something that's working. You just may need to make it easier to >>Use. Let's ask Dave about the, sort of the discussion that was on Twitter this morning. So when VMware announced their, you know, cross cloud services and, and the whole new Tansu one, three, and, and, and, and aria, there was a little chatter on Twitter basically saying, yeah, but VMware they'll never win the developers. And John came and said, well, hi, hang on. You know, if, if you've got open tools and you're embracing those, it's really about the ops and having standards on the op side. And so my question to you is, does VMware, that's >>Not exactly what I said, but close enough, >>Sorry. I mean, I'm paraphrasing. You can fine tune it, but, but does VMware have to win the developers or are they focused on kind of the right areas that whole, you know, op side of DevOps >>Focused on the op side, cuz that's the harder problem to solve. Developers are gonna use whatever tools they need to use to build these applications and roll them out. And they're gonna change all the time. In other words, they're gonna change the tools and technologies to do it in the supply chain. The ops problem is the harder problem to solve the ability to get these things working together and, and running at a certain point of reliability where the failure's not gonna be there. And I think that's gonna be the harder issue and doing that without complexity. >>Yeah. That's the multi-cloud challenge right there. I agree. The question I want to also pivot on that is, is that as we look at some of the reporting we've done and interviews, data and security really are hard areas. People are tune tuning up DevOps in the developer S booming, everyone's going fast, fast and loose. Shifting left, all that stuff's happening. Open source, booming Toga party. Everyone's partying ops is struggling to level up. So I guess the question is what's the order of operations from a customer. So a lot of customers have lifted and shift. The, some are going all in on say, AWS, yeah, I got a little hedge with Azure, but I'm not gonna do a full development team. As you talk to customers, cuz they're the ones deploying the clouds that want to get there, right? What's the order of operations to do it properly in your mind. And what's your advice as you look at as a strategy to, to do it, right? I mean, is there a playbook or some sort of situational, you know, sequence, >>Yes. One that works consistently is number one, you think about operations up front and if you can't solve operations, you have no business rolling out other applications and other databases that quite frankly can't be operated and that's how people are getting into trouble. So in other words, if you get into these very complex architectures, which is what a multicloud is, complex distributed system. Yeah. And you don't have an understanding of how you're gonna operationalize that system at scale, then you have no business in building the system. You have no business of going in a multicloud because you are going to run into that wall and it's gonna lead to a, an outage it's gonna lead to a breach or something that's gonna be company killing. >>So a lot of that's cultural, right. Having, having the cultural fortitude to say, we're gonna start there. We're gonna enforce these standards. >>That's what John CLE said. Yeah. CLE is famous line. >>Yeah, you're right. You're right. So, so, so what happens if the, if that as a consultant, if you, you probably have to insist on that first, right? Or, I mean, I don't know, you probably still do the engagement, but you, you're gonna be careful about promising an outcome aren't you, >>You're gonna have to insist on the fact they're gonna have to do some advanced planning and come up with a very rigorous way in which they're gonna roll it out. And the reality is if they're not doing that, then the advice would be you're gonna fail. So it's not a matter of when it's, when it's gonna happen. We're gonna, but at some point you're gonna fail either. Number one, you're gonna actually fail in some sort of a big disastrous event or more likely or not. You're gonna end up building something that's gonna cost you $10 million more a month to run and it's gonna be underoptimized. And is >>That effective when you, when you say that to a client or they say, okay, but, or do they say yes, you're >>Right. I view my role as a, someone like a doctor and a lawyer. You may not want to hear what I'm telling you. But the thing is, if I don't tell you the truth and I'm not doing my job as a trusted advisor. And so they'll never get anything but that from us, you know, as a firm and the reality is they can make their own decisions and will have to help them, whatever path they want to go. But we're making the warnings in place to make. >>And, and also also situationally it's IQ driven. Are they ready? What's their makeup. Are they have the kind of talent to execute. And there's a lot of unbeliev me. I totally think agree with on the op side, I think that's right on the money. The question I want to ask you is, okay, assume that someone has the right makeup of team. They got some badass people in there, coding away, DevOps, SREs, you name it. Everyone lined up platform teams, as they said today on stage, all that stuff. What's the CXO conversation at the boardroom that you, you have around business strategy. Cuz if you assume that cloud is here and you do things right and you get the right advisors in the next step is what does it transform my business into? Because you're talking about a fully digitalized business that converges it's not just, it helps you run an app back office with some terminal it's full blown business edge app business model innovation is it that the company becomes a cloud on their own and they have scale. And they're the super cloud of their category servicing a power law of second place, third place, SMB market. So I mean, Goldman Sachs could be the service provider cloud for financial services maybe. Or is that the dream? What, what's the dream for the, the, the CXO staff take us through the, >>What they're trying to do is get a level of automation with every able to leverage best breed technology to be as innovative as they possibly can. Using an architecture that's near a hundred percent optimized. It'll never be a hundred percent optimized. Therefore it's able to run, bring the best value to the business for the least amount of money. That's the big thing. If they want to become a cloud, that's, that's not a, not necessarily a good idea. If they're finance company be a finance company, just build these innovations around how to make a finance company be innovative and different for them. So they can be a disruptor without being disrupted. I see where see a lot of companies right now, they're gonna be exposed in the next 10 years because a lot of these smaller companies are able to weaponize technology to bring them to the next level, digital transformations, whatever, to create a business value. That's gonna be more compelling than the existing player >>Because they're on the CapEx back of Amazon or some technical innovation. Is that what the smaller guys, what's the, what's the lever that beats the >>It's the ability to use whatever technology you need to solve your issues. So in other words, I can use anything that exists on the cloud because it's part of the multi-cloud I'm I able to find the services that I need, the best AI system, the best database systems, the fastest transaction processing system, and assemble these syncs together to solve more innovative problems in my competitor. If I'm able to do that, I'm gonna win the game. So >>It's a buffet of technology. Pick your yes, your meal, come on, >>Case spray something, this operations, first thing in my head, remember Alan NA, when he came in the Cub and he said, listen, if you're gonna do cloud, you better change the operating model or you you're gonna make, you know, you'll drop millions to the bottom line. He was at CIO of Phillips at the time. You're not gonna drop billions. And it's all about, you know, the zeros, right? So do you find yourself in a lot of cases, sort of helping people rearchitect their operating model as a function of, of, of what cloud can, can enable? >>Yeah. Every, every engagement that we go into has operating model change op model changes, and typically it's gonna be major surgery. And so it's re reevaluating the skill sets, reevaluating, the operating model, reevaluating the culture. In fact, we have a team of people who come in and that's all they focus on. And so it used to be just kind of an afterthought. We'd put this together, oh, by the way, I think you need to do this and this and this. And here's what we recommend you do. But people who can go in and get cultural changes going get the operating models systems, going to get to the folks where they're gonna be successful with it. Reality. If you don't do that, you're gonna fail because you're not gonna have the ability to adapt to a cloud-based a cloud-based infrastructure. You can leverage this scale. >>David's like a masterclass here on the cube at VMware explore. Thanks for coming on. Thanks for spending the valuable time. Just what's going on in your world right now, take a quick minute to plug what's going on with you. What are you working on? What are you excited about? What what's happening, >>Loving life. I'm just running around doing, doing things like this, doing a lot of speaking, you know, still have the blog on in info world and have that for the last 12 years and just loving the fact that we're innovating and changing the world. And I'm trying to help as many people as I can, as quickly as I can. What's >>The coolest thing you've seen this year in terms of cloud kind of either weirdness coolness or something that made you fall outta your chair. Wow. That >>Was cool. I think the AI capabilities and application of AI, I'm just seeing use cases in there that we never would've thought about the ability to identify patterns that we couldn't identify in the past and do so for, for the good, I've been an AI analyst. It was my first job outta college and I'm 60 years old. So it's, it's matured enough where it actually impresses me. And so we're seeing applications >>Right now. That's NLP anymore. Is it? >>No, no, not list. That's what I was doing, but it's, we're able to take this technology to the next level and do, do a lot of good with it. And I think that's what just kind of blows me on the wall. >>Ah, I wish we had 20 more minutes, >>You know, one, one more masterclass sound bite. So we all kind of have kids in college, David and I both do young ones in college. If you're coming outta college, CS degree or any kind of smart degree, and you have the plethora of now what's coming tools and unlimited ways to kind of clean canvas up application, start something. What would you do if you were like 22? Right now, >>I would focus on being a multi-cloud architect. And I would learn a little about everything. Learn a little about at the various cloud providers. And I would focus on building complex distributed systems and architecting those systems. I would learn about how all these things kind of kind of run together. Don't learn a particular technology because that technology will ultimately go away. It'll be displaced by something else, learn holistically what the technologies is able to do and become the orchestrator of that technology. It's a harder problem to solve, but you'll get paid more for it. And it'll be more fun job. >>Just thinking big picture, big >>Picture, how everything comes together. True architecture >>Problems. All right, Dave is on the queue masterclass here on the cube. Bucha for Dave ante Explorer, 2022. Live back with our next segment. After this short break.

(air whooshing) (cymbal crashing) >> Hello everybody, I'm John Furrier, host of theCUBE. Join us for the season two, episode four of the ongoing series, The AWS Startup Showcase. For this episode, it's all about cybersecurity, hackers, super hackers, super cloud, all 10 companies presenting are the latest, hottest companies in cybersecurity startups. Of course, John Ramsey will be keynoting. He's the vice president of AWS, a security team. And of course, we've got great expert panels with the heroes, Liz Rice from Open Source, talking about kernaling in Linux kernal, security programming to best practices for CSOs. If you're a CSO or CXO, check it out.

>>The cube presents, Coon and cloud native con Europe 22, brought to you by the cloud native computing foundation. >>Welcome to Valencia Spain and coverage of Q con cloud native con Europe, 2022. I'm Keith Townsend. You're a host of the cube along with Paul Gillum, senior editor, enterprise architecture for Silicon angle, ENCO, senior ready, senior it analyst for giga own. Uh, this has been a full day, 7,500 attendees. I might have seen them run out of food. This is just unexpected. I mean, they, the, it escalated from what understand it went from four, capping it off to 4,000 gold, 5,000 gold in and off. Finally at 7,500 people. I'm super excited for, you know, today's been a great day of coverage. I'm super excited for tomorrow's coverage, uh, from the cube. But first off, we'll let the, the new person on stage take the, the first question of, of the wrap up of the day of coverage, UN Rico on Rico. What's different about this year versus other Q coupons or cloud native conversations. >>I, I think in general, it's the maturity. So we talk it a lot about day two operations, uh, observability monitoring, uh, going deeper and deeper in the security aspects of the application. So this means that for many enterprises, Kubernetes is becoming real critical. They want to, to get more control of it. And of course you have the discussion around Phen op around, you know, uh, cost control because we are deploying Kubernetes everywhere. And, and if you don't have everything optimized control, monitor it, you know, uh, cost to the roof and think about, uh, deploying the public cloud. If your application is not optimized, you're paying more, but also in the on premises, if you are not optimiz, you don't have the clear idea of what is going to happen. So capacity planning become the nightmare that we know from the past. So there is a lot of going on around these topics, uh, really exciting, actually less infrastructure, more replication. That is what Kubernetes is India. >>Paul help me separate some of the signal from the noise. Uh, there is a lot going on a lot of overlap. What are some of the big themes of takeaways for day one that enterprise architects executives need to take home and really chew >>On? Well, the Kubernetes was a turning point. You know, Docker was introduced nine years ago and for the first three or four years, it was an interesting technology that was not very widely adopted. Kubernetes came along and gave developers a reason to use containers. What strikes me about this conference is that this is a developer event, you know, ordinarily you go to conferences and it's geared toward it managers towards CIOs. This is very much geared toward developers when you have the hearts and minds of developers, the rest of the industry is sort of pulled along with it. So this is ground zero for the hottest, uh, the, the hottest area of the entire computing industry. Right now, I is in this area building distributed services, BA microservices based cloud native applications. And it's the developers who are leading the way. I think that's, that's a significant shift. I don't see the managers here, the CIOs here, these are the people who are, uh, who are pulling this industry into the next generation. >>Um, one of the interesting things that I've seen when we, you know, we've always said, Kubernetes is for the developers, but we talk with, uh, an icon from, uh, MoneyGram. Who's a end user, he's an enterprise architect. And he brought Kubernetes to his front end developers and they, they, they kind of rejected it. They said, what is this? I just wanna develop cold. So when we say Kubernetes is for developers, or the developers are here, where, how do we reconcile that mismatch of experience? We have enterprise architecture. I hear constantly that, that the, uh, Kubernetes is for developers, but is it a certain kind of developer that Kubernetes is for? >>Well, yes and no. I mean, so the paradigm is changing. Okay. So, and maybe a few years back, it was tough to understand how, you know, uh, uh, make your application different. So microservices, everything was new for everybody, but actually, so everything is changed to a point. Now, the developer understands, you know, it is neural. So, you know, going through the application APIs automation, because the complexity of this application is, is huge. And you have, you know, 7 24 kind of development, uh, sort of deployment. So you have to stay always on cetera, et cetera. And actually to the point of, you know, developers, uh, you know, bringing this new generation of, uh, decision makers in India. So they are actually decision, they are adopting technology. Maybe it's a sort of shadow it at the very beginning. So they're adopting it, they're using it. And they're starting to use a lot of open source stuff. And then somebody upper in the stack, the executive says, what are, yeah, they, they discover that the technology is already in place is, uh, is a critical component. And then it's, uh, you know, uh, transformed in something enterprise, meaning, you know, paying enterprise services on top of it to be sure con uh, contract and so on. So it's a real journey. And these are, these guys are the real decision makers. Oh, they are at the base of the decision making process. At least >>Cloud native is something we're gonna learn to take for granted. You know, when you remember back, remember the fail whale in the early days of Twitter, when periodically the service would just would just, uh, um, crash from, uh, from, uh, traffic or Amazon went through the same thing. Facebook went through the same thing. We don't see that anymore because we are now learning to take cloud native for granted. We assume applications are gonna be available. They're gonna be performant. They're gonna scale. They're gonna handle anything. We throw at them that is cloud native at work. And I think we, we forget sometimes how refreshing it is to have, uh, an internet that really works for you. >>Yeah. I, I think we're much earlier in the journey. You know, we have Microsoft, uh, on the Xbox team talked about 22,000 pods running ni D some of the initial problems and pain points of, uh, around those challenges. Uh, much of my hallway track conversation has been centered around as we talk about kind of the decision makers, the platform teams. And this is what I'm getting excited to talk about in tomorrow's coverage. Who's on the ground doing this stuff. Is it developers as we are, as, as we see or hear or told, or is it what we're seeing from the Microsoft example, the MoneyGram example where central it is kind of getting it, and not only are they getting it, they're enabling developers to, to simply write code, build it. And Kubernetes is invisible. It seems like that's become the holy grill to make Kubernetes invisible cloud native invisible, and the experience is much closer to cloud. >>So I, I think that, uh, um, it's an interesting, I mean, I had a lot of conversation in the past year is that it's not that the original, you know, traditional it operations are disappearing. So it's just that, uh, traditional it operation are giving resources to these new developers. Okay. So it's a, it's a sort of walled garden. You don't see the wall, but it's a walled garden. So they are giving you resources and you use these resources like an internal cloud. So a few years back, we were talking about private cloud, the private cloud, as, you know, as a, let's say, uh, the same identical paradigm of, of the public cloud. This is not possible because there are no infinite resources or, well, whatever we, we think are infinite resources. So what you're doing today is giving these developers enough resources to think that they are unlimited and they can, uh, do automatic provisioning and do all these kind of things. So they don't think about infrastructure at all, but actually it's there. So it operation are still there providing resources to let developers be more free and agile and everything. So we are still in a, I think in an interesting time for all of it, >>Kubernetes and cloud native in general, I think are blurring the lines, traditional lines development and operations always were separate entities, obviously through with DevOps. Those two are emerging, but now we're moving. When you add in shift left testing shift, right? Testing, uh, dev SecOps, you see the developers become much more involved in the infrastructure and they want to be involved in infrastructure because that's what makes their applications perform. So this is gonna, cause I think it organizations to have, do some rethinking about what those traditional lines are, maybe break down those walls and have these teams work, work much closer together. And that should be a good thing because the people who are developing applications should also have intimate knowledge of the infrastructure they're gonna run on. >>So Paul, another recurring theme that we've heard here is the impact of funding on resources. What have you, what have your discussions been around founders and creators when it comes to sourcing talent and the impact of the markets on just their day to day? >>Well, the sourcing talent has been a huge issue for the last year. Of course, really ever since the pandemic started interesting. We, uh, one of our, our guests earlier today said that with the meltdown in the tech stock market, actually talent has become more available because people who were tied to their companies because of their, their stock options are now seeing those options are underwater. And suddenly they're not as loyal to the companies they joined. So that's certainly for the, for the startups. Uh, there are many small startups here. Um, they're seeing a bit of a windfall now from the, uh, from the tech stock, uh, bust, um, nevertheless skills are a long term problem. The us, uh, educational system is turning out about 10% of the skilled people that the industry needs every year. And no one I know, sees an end to that issue anytime soon. >>So ENGO, last question to you, let's talk about what that means to the practitioner. There's a lot of opportunity out >>There. >>200 plus sponsors I hear here I think is, or the projects is 200 plus, where are the big opportunities as a practitioner, as I'm thinking about the next thing that I'm going to learn to help me survive the next 10 or 15 years of my career? Where, where do you think the focus should be? Should it be that low level, uh, cloud builder, or should it be at those Le levels of extraction that we're seeing and reading about? >>I, I think, I think that, uh, you know, it's, uh, it's a good question. The, the answer is not that easy. I mean, uh, being a developer today, for sure grants, you, you know, uh, a salary at the end of the month, I mean, there is high demand, but actually there are a lot of other technical, uh, figures in, in the, in, uh, in the data center in the cloud that could, you know, really find easily a job today. So developers is the first in my mind also because they are more, uh, they, they can serve multiple roles. It means you can be a developer, but actually you can be also, you know, with the new roles that we have, especially now with the DevOps, you can be, uh, somebody that supports operation because, you know, automation, you know, a few other things. So you can be a C admin of the next generation, even if you're a developer, even if when you start as a developer, >>Cuan 20, 22 is exciting. I don't care if you're a developer practitioner, a investor, a, uh, it decision maker is CIO CXO. They're so much to learn and absorb here and we're going to be covering it for the next two days. Me and Paul will be shoulder to shoulder. We will, you, I'm not gonna say you're gonna get sick of this because it's just, you know, it's all great information. We'll, we'll, we'll help sort all of this from Valencia Spain. I'm Keith Townsend, along with my host ENCO senior, the Paul Gillon. And you're watching the, you, the leader in high tech coverage.

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

>> Welcome back to theCUBE's covering of AWS Public Sector Summit. In-person here in Washington, DC. I'm John Furrier, your host, great to be back face to face. We've got a great, special guest Clint Crosier, who is the Director of AWS' Aerospace & Satellite. Major General of The Air Force/Space Force. Retired. Great to see you in person again. Thanks for coming on theCUBE. >> Thank you for having me. I appreciate that. >> First of all, props to you for doing a great job at Amazon, bringing all your knowledge from Space Force and Air Force into the cloud. >> Thank you. >> So that's great, historical context. >> It's been valuable and it's provided a whole lot of insight into what we're building with the AWS space team, for sure. >> So number one question I get a lot is: We want more space content. What's the coolest thing going on in space? Is there a really a satellite behind the moon there, hidden there somewhere? What's the coolest thing going on in space? >> Well, the coolest thing that's going on in space, I think is you're seeing the rapid growth of the space industry, I mean, to me. I've been in the space industry for 34 years now, and there have been periods where we projected lots of growth and activity and it just didn't really come about, especially in the 80's and the 90's. But what we're seeing today is that growth is taking place. Whether it's the numbers of satellites that are being launched around the globe every year, there's some 3,000 objects on orbit today. Estimates are that there'll be 30,000 objects at the end of the decade, or the number of new companies, or the number of global spinning. It is just happening right now, and it's really exciting. >> So, when people say or hear space, there's a lot of economic changes in terms of the cost structures of how to get things deployed into space. That brings up the question of: Is space an opportunity? Is it a threat vector? What about congestion and security? >> Yeah, well three great things, absolutely an opportunity. We're seeing the rapid growth of the space industry, and we're seeing more commercialization than ever before. In my whole career, The Air Force or, NASA, or the NRO would sort of, hold things and do them themselves Today, you're seeing commercial contracts going out from the National Reconnaissance Office, NASA, from The Air Force, from the Space Force. So lots of opportunity for commercial companies. Security. Absolutely, priority number one should be security is baked into everything we do at AWS. And our customers, our Government classified customers tell us the reason they came to AWS is our security is top notch and certified for all their workloads. And as you well know, we have from unclassified all the way up to top secret capabilities on the AWS cloud. So just powerful opportunities for our customers. >> Yeah. And a lot of competitors will throw foot on that. I know, I've reported on some of that and not a lot of people have that same credential. >> Sure. >> Compared to the competition. >> Sure. >> Now I have to ask you, now that you have the top secret, all these clouds that are very tailorable, flexible with space: How are you helping customers with this Aerospace Division? Is it is a commercial? In the public sector together? What's the... >> All of the above. >> Take us through the value proposition. >> Yeah, happy to do this. So what we recognized over the last two years or so we, at AWS, recognized all this rapid growth that we're talking about within the space industry. Every sector from launch to on-orbit activities, to space exploration, all of it. And so AWS saw that and we looked at ourselves and said: "Do we have the right organization and expertise in place really to help our customers lean into that?" And the answer was: we decided to build a team that had deep experience in space, and that was the team that we grew because our thesis was: If you have a deep experience in space, a deep experience in cloud, you bring those two together and it's a powerful contribution. And so we've assembled a team with more than 500 years of collective hands-on experience, flying satellites, launching rockets. And when we sit down with our customers to innovate on their behalf, we're able to come up with some incredible solutions and I'm happy to talk about those. >> I'd love to, but tell you what, first of all, there's a lot of space nerds out there. I love space. I love space geeking out on the technology, but take us through the year you had, you've had a pretty incredible year with some results. You have that brain trust there. I know you're hiring. I know that people want to work for you. I'm sure the resumes are flying in, a lot of action. >> There is. >> What are the highlights from this year? >> So the highlights I think is, we've built a team that the industry is telling us was needed. Again, there was no organization that really served the space cloud industry. And so we're kind of building this industry within the industry, the space cloud industry. And so number one, just establishing that team and leaning into that industry has been valuable. The other thing that we're real proud of is we built a global team, because space is a global enterprise. We have teams in Europe and in Asia and South America here in the U.S., so we built a global team. One of the things that we did right up front, we weren't even six months old, when we envisioned the idea of doing the AWS Space Accelerator. And some of the folks told me: "Clint, six months under your belt, maybe you ought to get your feet under you." And I said: "No, no. We move fast to support our customers." And so we made a call for any space startup that wanted to come on board with AWS and go through our four week Space Accelerator. We partnered with Sarah from Capital. And the idea was: if you're a small company that wants to grow and build and learn how you can use the cloud to gain competitive advantage, come with us. And so John, I would have been happy if we had 50 companies applied, we had 194 companies across 44 countries that applied to our accelerator. We had to down select a 10, but that was a tremendous accomplishment, two of those are speaking this afternoon, where they met each other at our accelerator and now have formed a partnership: Ursa Space and HawkEye 360 on how they build on the cloud together. Fascinating. >> Well, I love that story. First of all, I love the military mindset. No, we're not going to wait. >> Move it out. >> It's not take that hill, it's take that planet. >> Our customers won't wait, innovation, doesn't wait, the future doesn't wait. We have to move out. >> So, this brings up the entrepreneurship angle. We got there a little early, but I want to talk about it because it's super important. There's an entrepreneurial culture happening right now in the space community >> There is. At large, and it's getting bigger and wider. >> Bigger every day. >> What is that? What if someone says: "Hey, what's going on with entrepreneurship in this space? What are the key dynamics? What's the power dynamics?" It's not money, there's money out there, but like what's the structural thing happening? >> The key dynamic, I think, is we're seeing that we can unlock things that we could never do before. And one of our goals is: the more space data we can make more accessible to more people around the world. It unlocks things we couldn't do. We're working with space companies who are using space data to track endangered whales off the coast of California. We're working with companies that are using space data to measure thermal and greenhouse emissions for climate change and climate management. We're working with one company, Edgybees, who has a small satellite constellation, and they're using it to build satellite based, augmented reality, to provide it to first responders as they go into a disaster response area. And they get a 3D-view of what they're going into. None of those workloads were possible five years ago. And the cloud and cloud-based technologies are really what opens those kinds of workloads up. >> What kind of higher level services do you see emerging from space cloud? Because you know, obviously you have to have some infrastructure. >> Absolutely. Got to put some stuff into space. That's a supply chain, reliability, also threat. I mean, I can have a satellite attack, another satellite, or I'm just making that up, but I'm sure there's other scenarios that the generals are thinking about. >> So space security and cyberspace security is critical. And as I said, it's built into everything we do in all of our platforms, so you're absolutely right about that, but when we think about the entrepreneurship, you know, what we're seeing is, and I'll give you a good example of why the industry is growing so fast and why cloud. So one company we work with, LeoLabs. So Leo identified the growth in the LEO: Low Earth Orbit segment. 3,000 objects on orbit today, 30,000 tomorrow. Who's going to do the space traffic management for 30,000 objects in space that are all in the same orbital regime? And so LeoLabs built a process to do space traffic management, collision avoidance. They were running it on premises. It took them eight hours to do a single run for a single satellite conjunction. We got them to help understand how to use the cloud. They moved all that to AWS. Now that same run they do in 10 seconds. Eight hours to 10 seconds. Those are the kind of workloads as space proliferates in and we grow, that we just can't execute without cloud and cloud-based technologies. >> It's interesting, you know, the cloud has that same kind of line: move your workloads to the cloud and then refactor. >> Yeah. So space workloads are coming to the cloud. >> They are. >> Just changing the culture. So I have to ask you, I know there's a lot of young people out there looking for careers and interests. I mean, Cal poly is going into the high school now offering classes. >> Yeah So high school, there's so much interest in space and technology. What is the cultural mindset to be successful? Andy Jassy last year, reading and talk about the mindset of the builder and the enterprise CXO: "Get off your butt and start building" There's a space ethos going on. What is the mindset? Would you share your view on it? >> The mindset is innovation and moving fast, right? We, we lived, most of my career, in the time where we had an unlimited amount of money and unlimited amount of time. And so we were really slow and deliberate about how we built things. The future won't wait, whether it's commercial application, or military application, we have to move fast. And so the culture is: the faster we can move, The more we'll succeed, and there's no way to move faster than when you're building on the AWS cloud. Ground station is a good example. You know, the proposition of the cloud is: Don't invest your limited resources in your own infrastructure that doesn't differentiate your capability. And so we did that same thing with ground station. And we've said to companies: "Don't spend millions of dollars on developing your own ground station infrastructure, pay by the minute to use AWS's and focus your limited resources back in your product, which differentiate your space mission." and that's just been power. >> How is that going from customer perspective? >> Great. It's going great. We continue to grow. We added another location recently. And just in the last week we announced a licensed accelerator. One of the things our customers told us is it takes too long to work with global governments to get licensed, to operate around the world. And we know that's been the case. So we put together a team that leaned in to solve that problem, and we just announced the licensed accelerator, where we will work with companies to walk them through that process, and we can shave an 18 month process into a three or four month process. And that's been... we've gotten great response on that from our company. >> I've always said: >> I remember when you were hired and the whole space thing was happening. I remember saying to myself: "Man, if democratization can bring, come to space" >> And we're seeing that happening >> You guys started it and you guys, props to your team. >> Making space available to more and more people, and they'll dazzle us with the innovative ways we use space. 10 years ago, we couldn't have envisioned those things I told you about earlier. Now, we're opening up all sorts of workloads and John, real quick, one of the reasons is, in the past, you had to have a specific forte or expertise in working with space data, 'cause it was so unique and formatted and in pipeline systems. We're making that democratized. So it's just like any other data, like apps on your phone. If you can build apps for your phone and manage data, we want to make it that easy to operate with space data, and that's going to change the way the industry operates. >> And that's fundamentally, that's great innovation because you're enabling that. That's why I have to ask you on that note Of the innovation trends that you see or activities: What excites you the most? >> So a lot of things, but I'll give you two examples very quickly: One is high-performance compute. We're seeing more and more companies really lean in to understanding how fast they can go on AWS. I told you about LeoLabs, eight hours to 10 seconds. But that high-performance computes going to be a game changer. The other thing is: oh, and real quick, I want to tell you, Descartes Labs. So Descartes Labs came to us and said: "We want to compete in the Annual Global Top 500 supercomputer challenge" And so we worked with them for a couple of weeks. We built a workload on the AWS standard platform. We came in number 40 in the globe for the Top 500 super computer lists, just by building some workloads on our standard platform. That's powerful, high-performance compute. But the second example I wanted to give you is: digital modeling, digital simulation, digital engineering. Boom Aerospace is a company, Boom, that we work with. Boom decided to build their entire supersonic commercial, supersonic aircraft, digital engineering on the AWS cloud. In the last three years, John, they've executed 6,000 years of high-performance compute in the last three years. How do you do 6,000 years in compute in three years? You spin up thousands of AWS servers simultaneously, let them do your digital management, digital analysis, digital design, bring back a million different perturbations of a wing structure and then pick the one that's best and then come back tomorrow and run it again. That's powerful. >> And that was not even possible, years ago. >> Not at that speed, no, not at that speed. And that's what it's really opening up in terms of innovation. >> So now you've done it so much in your career, okay? Now you're here with Amazon. Looking back on this past year or so, What's the learnings for you? >> The learning is, truly how valuable cloud can be to the space industry, I'll admit to you most people in the space industry and especially in the government space industry. If you ask us a year ago, two years ago: "Hey, what do you think about cloud?" We would have said: "Well, you know, I hear people talk about the cloud. There's probably some value. We should probably look at that" And I was in the same boat, but now that I've dug deeply into the cloud and understand the value of artificial intelligence, machine learning, advanced data analytics, a ground station infrastructure, all those things, I'm more excited than ever before about what the space industry can benefit from cloud computing, and so bringing that, customer by customer is just a really fulfilling way to continue to be part of the space industry. Even though I retired from government service. >> Is there a... I'm just curious because you brought it up. Is there a lot of people coming in from the old, the space industry from public sector? Are they coming into commercial? >> Absolutely. >> Commercial rising up and there's, I mean, I know there's a lot of public/private partnerships, What's the current situation? >> Yeah, lots of partnerships, but we're seeing an interesting trend. You know, it used to be that NASA led the way in science and technology, or the military led the way in science and technology, and they still do in some areas. And then the commercial industry would follow along. We're seeing that's reversed. There's so much growth in the commercial industry. So much money, venture capital being poured in and so many innovative solutions being built, for instance, on the cloud that now the commercial industry is leading technology and building new technology trends that the military and the DOD and their government are trying to take advantage of. And that's why you're seeing all these commercial contracts being led from Air Force, Space Force, NASA, and NRO. To take advantage of that commercialization. >> You like your job. >> I love my job. (laughing) -I can tell, >> I love my job. >> I mean, it is a cool job. I kind of want to work for you. >> So John, space is cool. That's our tagline: space is cool. >> Space is cool. Space equals ratings in the digital TV realm, it is really, super exciting a lot of young people are interested, I mean, robotics clubs in high schools are now varsity sports, eSports, all blend together. >> Space, robotics, artificial intelligence, machine learning, advanced analytics. It's all becoming a singular sector today and it's open to more people than ever before, for the reasons we talked about. >> Big wave and you guys are building the surf boards, everyone a ride it, congratulations. Great to see you in person. >> Thank you. Again, thanks for coming on theCUBE, appreciate that. >> Thanks for having us. >> Clint Crosier is the Director of AWS Aerospace & Satellite. Legend in the industry. Now at AWS. I'm John Furrier with theCUBE. Thanks for watching.

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

(upbeat music) >> Hello, welcome to this CUBE conversation. I'm John Furrier your host of theCUBE here in our Palo Alto studio. We got a great conversation with the CEO of Lacework, David Hatfield. Who's in on theCUBE remote. David great to see you guys, a security platform at Lacework, you're at the helm as CEO. Welcome to theCUBE conversation. >> Thank you, John. Great to see you congrats to you and the team and all the success. I think what you guys are doing is really important so happy to be part of it. >> Great to have you in the community and you guys are doing great work. I know about Lacework I've done some due diligence on you guys. I love your business model, but for the folks who don't know what you guys do, take a minute to explain who is Lacework? What do you guys do? What's your positioning? And what's your focus? >> Yeah, well, we're a modern data security platform for the cloud. And so I think data science meets cloud security ultimately. The company has been around since 2015. We received one of the largest financing rounds that we're aware of I think in history in security business, $525 million in January. Led by Sutter Hill Ventures which many people may know about they founded PureStorage with the notion that we're going to go fundamentally change and revamp the ownership model for a high speed data storage using flash versus using spinning disc drives. I spent eight years with that company. Love with what we built there. Then Mike Speiser considered an investment in a company called Snowflake computing. I think you're aware of what Snowflake does which is bringing data warehousing into the cloud. And the third big investment that Sutter Hill made is really to help disrupt security, and that's in Lacework. So north of a billion dollar valuation a 300% year over year growth and have a ton of momentum. So at the core of what we do, it's really trying to merge, when we look at we look at security as a data problem, security and compliance the data problem. And when you apply that to the cloud, it's a massive data problem. you literally have trillions of data points across shared infrastructure that we need to be able to ingest and capture and then you need to be able to process efficiently and provide context back to the end-user. And so we approached it very differently than how legacy approaches have been in place, you know largely rules-based engines that are written to be able to try and stop the bad guys. And they miss a lot of things. And so our data-driven approach that we patented is called a polygraph. It's a, it's a security architecture and there are three primary benefits. It does a lot of things, but the three things that we think are most profound first is it eliminates the need for, you know dozens of point solutions. I was shocked when I, you know kind of learned about security. I was at Symantec back in the day. And just to see how fragmented this market is, it's one of the biggest markets in tech. $124 billion in annual spend growing at, to $300 billion in the next three years. And it's massively fragmented. And the average number of point solutions that customers have to deal with is dozens. Like literally 75 is the average number. And so we wanted to take a platform approach to solve this problem where the larger the attack surface that you put in the more data that you put into our machine learning algorithms the smarter it gets and the higher, the efficacy. So eliminating point solutions is his value proposition one. Point two is that we have to be 10 X better than everybody else in the business. Otherwise the merchant companies don't get a breakout and become long and during companies. And so there's a number of different dimensions. The first dimension that I think is probably the most important is efficacy, you know in anomaly detection or in, you know threat detection where you're trying to identify what risks we have in the business. It's, it's generally a very noisy activity. And so rules-based approaches on average will produce a hundred alerts to our one or two. Those, the signal to noise ratio, is, is, you know is a massive a 100x, but call it 10x a reduction. And so we're actually delivering the needle versus the haystack for security administrators and dev developers to actually solve the problem. So it's 10x, higher efficacy it's 10x faster to be able to resolve the problems. And obviously the ROI is, is a no-brainer because you're eliminating all these points which is in having to manage it. And the third, and probably the thing that I'm most excited about what we're doing and what our customers are already realizing is that we're transforming security and compliance teams from kind of compliance into business enablers. when you automate all these processes and you build it into, you know the CICD platforms for the developers you actually enable the developers to write code to differentiate their business, you know to create new customer experiences to get competitive advantage and drive revenue for their businesses. And, and you know that's not what security has done up to this point. We oftentimes, they're the ones we're the ones having to say, no, you know we're slow down or it's too risky, etc. But when you automate that and you increase the efficacy you can enable the developers to do their thing. And it allows the CSOs and allows the security professionals to up level their responsibility into selling and driving revenue. And that is increasingly going to become more and more important for supply chains and partners of these cloud native businesses of how secure am I working with you, etc. And so we think that that transformation of the role of security is going to be as, as meaningful as the technology that we're providing the business. So we're super excited about it. >> I could tell you have so much going on this investment team Sutter Hill, you mentioned big time players huge success track record. Just saw them written up in the wall street journal as one of the best venture capital firms and returns. It's just that the bets are all coming home, but their bet strategy is simple. Disrupting the market that's growing and changing PureStorage, you mentioned company you've worked for, you know people were saying, oh, they'll never get escape velocity. They disrupted an existing, boring storage market changed the game there, security, right for change. A lot of tools, a lot of people have buying tools off the shelf, you know and everyone fighting for the platform. That seems to be the conversation. So I have to ask you, you guys want to be the player that that platform you are, that platform what's different in this platform where everyone's trying to be a security platform, what's makes you different. >> Yeah. So I mean, I think the platform wars are, are clearly, upon us, you know I think what's different about our approach is that we were built on the cloud, for the cloud so we're a cloud native business that, you know runs our business on AWS and everything that we do. We don't have hardware, we don't own data centers. we don't have any of the legacy elements that are there. we use software run on the cloud to enable this. So that's point number one point number two is we did the hard work of mapping the data elements that are out there and adjusting them in and then have this polygraph, you know behavioral anomaly detection, that is it can be applied to today. It's being applied to vulnerability and discovery management and containers and Kubernetes. But over time we believe it extends very naturally to a larger part of the attack server. So we don't have to rewrite the data engine to develop solutions across broader attack services. We already have that, you know so I think our time to develop and innovate will be profound. And I think the third thing that we're seeing companies do and largely the legacy bigger companies is that they're just acquiring their way there. And, it's very, very difficult to acquire 8 to 10 to 20, 30 companies, 30 different CTOs 30 different code bases and try and integrate them to provide a delightful customer experience. And, the parallels, you know in the storage business are, are are pretty similar actually, Dell bought EMC, EMC bought a hundred companies. And, we went after a platform approach to be able to go attack them with a unified file system in a in a unified customer experience that was native for the media that we're working with. We're doing the same playbook here, you know which is you have to have the hard work of the foundation elements in place to be cloud native to deliver great outcomes, great efficacy and and a really great customer experience. So when we get head to head with any of these points coming out and trying to solve something for containers or Kubernetes, or just vulnerability discovery and management, etc, or we're competing with the legacy companies that have, a hodgepodge of acquisitions that they're trying to pull together we went North of 95% of the time. our POC win rates are phenomenal better than anything I've ever seen. We had a pretty good one to appear too. And the, the product and the experience and the efficacy kind of stand on their own once we're in those fights. So part of why we enjoy working with AWS and are really focused on building the partnership together is that it creates awareness of what could be and what possibilities all we want is a shot. And, our approach is such that you can be up and running in minutes, you know and every single one of our customers does a POC. So we'll stand behind our technology as our real differentiator compared to anybody else that's out there. >> Great. You guys had great traction going on with the company certainly saw the investment news that you mentioned earlier at the top. Why did you come on as CEO? And when did you come on and join the team? And what was the reason? What, what, what attracted you to join as the CEO of Lacework? >> Well, I've been involved in the company for since the beginning actually I invested in the early rounds participated on the board and I've always bought into this. The thesis that security is fundamentally a data problem. And if we can get the data problem and the data processing right, you know you can fundamentally change the industry but you need to have a major inflection. And that inflection is people moving to the cloud. And we all have seen it during the pandemic. things are accelerating. AWS just did their earnings yesterday. I think they increased their top-line guidance from 46 billion to 56 billion this year. I mean, it's a machine that is continuing to move forward. They have 30% market share. Azure's investing at 20% GCP still investing people are moving their businesses online aggressively. And as they shift to the cloud the rules-based approach just doesn't work. It doesn't scale. And so a new approach needs to be done. And so by being cloud native and best of breed and solving the thorny problem of this data processing problem first, you know it gives us an opportunity to use that to then extend and build a business, you know at an enduring level over the next 10 to 20 years. And that's Sutter's model, that's their playbook. They don't invest in 400 companies and kind of spray and pray, which is what most venture funds do. And I love them. They're great. And we appreciate the investment in tech, but Sutter's focus is find a really big market find a catalyst for change. In our case, it's moving to the cloud and then build a modern approach. that is 10x better in every dimension. And that attracted to me. I mean, it's, it's a, it's one of the biggest markets in tech and it's one of the most important things that we can do is a digital business is to ensure that we're secure and we're safe and the threats are becoming much more skilled much more deliberate, much better funded. And so the importance for us to ensure that company's security is really tight is, is increasingly critical. So the combination of those factors, and then as I dove back into it and talked to a bunch of customers and talk to partners and seeing the outcomes and enthusiasm that they had and the, the team is phenomenal. And so talking to them, and I just kind of got energized by the opportunity to go build a really important company that really delivers great outcomes. So I'm having a ball great to be back into it. >> Yeah. It's great to have leadership that has experienced that you have and go to the next level because this is classic next level. When you talk about Amazon's earnings and cloud scale and hybrid and edge right around the corner at scale as well. So you start to see that transformation really hit the tipping point, which is changing the landscape on the developer side, which I think is super valuable. I think you hit that. You mentioned core problem. You guys look at that through the lens of data problem. How does this trend of everything going hybrid and soon to be, you know edge core to edge impact your businesses of tailwind? How do you see you capturing that next level of scale from a business perspective for lease work? >> Well, I think that the trend, you know from core to edge, you know, hybrid and, you know ultimately cloud a hundred percent, there we've started with the cloud native businesses. Like, we've been focusing on those companies that are already there, you know and so now we're we just had finished a phenomenal record-breaking Q1 and multiple seven figure deals, you know with very complex global environments where they do have a hybrid environment and they are leveraging the edge. And we're perfect for that. I mean, as you think about what we deliver in its most simplistic context, you know we're effectively delivering a security solution from the container to control plane, right. You know we want to be able to have a granular understanding of operated trillions of data points coming in and those can be collected in the core. They can be collected on-prem. They can be collected in the cloud. Ultimately they need to be collected and then contextualized so, you know and this is where our behavioral polygraph technology transitions data into information that's useful via the polygraph. And so we think that, the complexity that's added with environments that are hybrid environments that are leveraging the edge environments that are leveraging the cloud native all need a control plane to run across that to deliver efficacy, you know, for our customers. And, we work with, you know AWS has their own security tools. Azure has some security tools UCPs security tools, but ultimately, our, our challenge and opportunity is to be best of breed to deliver incremental value on top of that and that horizontal value across it. so customers have choice but they know that their security posture is, is, is secure. And so we, we see it as a tailwind for our businesses as we go forward. >> I always said the companies that have the horizontal scalability with cloud and then have that vertical AI kind of vibe where you can get in the context of the data is there to win it all. And I think that you guys have a great solution potentially there. I want to get more information if you don't mind double clicking on that with me, this is kind of a different take on cloud security because you've got the scalability, which gives you the observation space. And then you got to get the context to get the right patterns or whatever magic you guys have in the, in the secret sauce. But you doing that on top of massive exponential velocity. >> Yeah. >> Where's that secret sauce? Is it in the compute? Is it in the software? What's different about what you guys have in security to give us a- >> It's all in the, it's all in the software. Ultimately, it's the intelligence of how you capture it how you ingest it, how you, you process it but then ultimately how you, how you contextualize it and then how you apply it to different problems. and so the attack surface area and security is a very broad, that's why there's so many point solutions that are out there. And so the breadth of solutions, you know we just want to continue to add solutions and capabilities on top of this polygraph security architecture that allows for the same kind of simple experience, the same kind of 10x value proposition, but, but, but wider. And so we can eliminate more and more of those of those point solutions. So, our, our thinking on it is that, you know we can participate once we have a customer the land and expand motion of what we have. We want to make it really really frictionless for customers to try our technology. And so that's why we do POC. That's why it only takes a couple of minutes and you can do it for just Kubernetes or just containers or just vulnerability discovery and managed like wherever your specific pain point is. We want to help identify what that is, you know give you a chance to try it. And then once we prove ourselves it's very easy to extend that across the board. So we get natural growth in velocity from people moving to cloud and just, you know more usage of, of compute and storage and sort of etc, but breadth of actually the security or posture or a tax service that they have as well. So, you know so I think we have an opportunity to benefit from, from both the depth and the breadth, you know but the value that we're delivering is ultimately the software that we're running on top of the infrastructure. And you mentioned observability, there's a number of companies that are leveraging the data and insights collected in different ways to converge security and observability over time. And, we see that, you know that ultimately there's a very very big security company that needs to be built. That really is best of breed, but the data and the insights that we're providing to our primary customer, which is really DevOps. I mean, it's really the development communities and the builders or who we're changing security for and enabling, in addition to the security teams, you know we think that we're going to continue to drive software that adds value on that data set and it can be applied to multiple problems in the future. So today security is a massive market. We're going to focus there, but it does. It does extend pretty naturally to other markets >> It's a hot market security. Everyone needs to have the latest and greatest and also has to be effective. I got to ask you specifically around startup transition to a rapidly growing company to now you're going to the next level where you're starting to having to get into some serious, big complex enterprise go to market sales motions. So what's in it for the customer. What's the, what's the pain point? What's the customer orientation. What do you marketing into as a solution? Is it the developer? Is it the CSO? Is it the CXO, what's in it for the enterprise? Why Lacework, why are they engaging? You guys get record numbers. What's the, what's in it for them. What's the, if I'm the customer what's in it for me? >> Ultimately efficacy, which is your security posture is it goes up significantly, simplicity, which is makes it easier for you to do your other jobs, you know and I'll have to look for those needles in a haystack and ROI, you know which is it's just compelling, and much, much more efficient than what, what you're doing today. So that that's a pretty universal value proposition and applies to cloud native businesses that are high growth that applies to government agencies. It applies to a large complex enterprises. We have a wonderful kind of go to market motion right now. I think Andy Byron and the team who've been here have really done a wonderful job of really making the customer buying experience and the journey really efficient, you know and help them quantify the impact and the risks and then deliver value. And I think, that that applies in sort of the commercial mid-market and cloud native space. And like I mentioned, we had, a number of deals in the quarter that were seven figure deals, you know in very complex organizations with massive demands. And, you know it ultimately selling is a team sport and, you know and still having the process and the rigor, that's there fine tuning that to make sure you have the people and the partnerships, you know, that deliver solutions in the way that customers want to buy them and then ultimately deliver a value proposition that is just unquestionably better. And I think we have all of those elements, you know we'll be entering the, the large enterprise very aggressively in the quarters to come. I that's where I've come from, you know running a multi-tool, you know, kind of go to market engines where you've got mid-market commercial enterprise large enterprise government across all geographies is, is really fun to expand. And, we're we're hiring as fast as we can maintain quality, you know? And so we're out of that startup phase now and entering into real scale. And, I think that, you know in the AWS marketplace I think we're the number one startup vendor. If I, if I got my facts, right. for, for private offers, we're one of the top security players and top 50 ISBs in the marketplace overall. And so in order for us to get the motion we need to make sure that we're delivering our value in the context of how companies want to buy it. And people want to use AWS credits, you know to apply to their solutions. And so it's really important for us to make that frictionless buying experience occur. And so we're excited about it. I think we've got a really nice start and it's the fun part of building companies, which is how do you attune things to make sure you're making it really really easy for the market to absorb your technology. And then once you're there, delight the hell out of them and just make sure that, that there's that they're excited in our, our net retention rates are the best I've seen in the marketplace. Our net promoter scores, you know, are in the high fifties low sixties, which, which is fantastic in this space. I think it's best in class by order of magnitude some players, big SIM players that are out there, you know have a customer in net promoter score of four. You know that means 96% of the people or 96 boats that says they wouldn't recommend the solution to their, to their peers. So, at pure, we've got this at scale. So from 70 to, in the, in the low eighties I think we have the opportunity to do the same thing here. So, combination of tailoring the motion that we have making it really easy for the buyer to buy what they want with whom they want from whom they want, you know and then just spreading a value proposition. That is a no brainer is, is I think the secret recipe >> If anything, it's interesting, you know you're so much experience in the enterprise and tech with cloud native you're basically laying out the success formula, which is if you have a value proposition you should be able to get it in quickly. You don't need the top down. win everything you can have a value proposition that can be enabled for usage and then grow rapidly when it's successful and that's cloud, that's the cloud business model. So it's not so much about organic versus this. It's really what the preferred motion is. >> It's speed, and I think developers in particular it's why the cloud happened, right? I.T wasn't delivering services in, in the speed and the efficacy that, that, that the developers wanted. And so in order to appeal to the developer community you need to deliver something that's frictionless and easy and fits into JIRA and fits into their workflow processes and speaks their language. And so we built our platform and our solutions for builders because that's where the money is. That's where the pain point is and that's and they want to build secure code. They just don't want to be told no. And so, we want to automate that process and make code secure and do that, you know in the build phase and then do it in the runtime. And then across the CICD pipeline we want to continuously be adding value across that. And, and the developers, candidly when pure bought the solution, many years ago and I introduced him to the company, it was it was the general manager of our software business unit that bought it not the security team. And I think that's a trend that is continuing that we're going to focus on. >> A lot of people realize that security and compliance and automation kind of all go together where you don't want to disrupt developers to kind of engineer something just to do an integration, for instance. So there's a real business model impact that you're hitting on here. That's not just a technical solution. It's really how the business is operating. And I think that to me is super interesting use case. What's your reaction to that? Do you see this as a, as a- >> No it's, that's that's that third part that I was talking about, you know which is that's most exciting is that, you know people are calling shift left, right. so moving, you know security into the development pipeline as it's happening and in integrating security architects as value added into the development organizations themselves and leveraging automated machine learning tools like ours to be able to simplify and automate the process versus slowing it down. So we think that shift left is, is super exciting and, and will continue. And we actually think we're the leaders in that space. We want to continue to be the leaders in that. >> Congratulations, great insight. Awesome to have you on and to hear from your experience and also the great venture that your scaling up and to the next level. Lacework, David thanks for coming on, but I'll give you the last minute to close us out. Give us a quick plug for the company vitals, what you're working on now, what you're looking for, you're obviously hiring give a quick plug for Lacework. What you, what are you working on? >> So, number one, we love our partnership with AWS. And so we're going to continue to invest, invest there. Two the businesses growing North of 300% year over year. That means that we've got record breaking growth and lots of hiring. So we're hiring across all functions. And three give us an opportunity. I, I think that, you know, you can fundamentally we want to be the bar of what you define all other security companies and all the technology companies. So it's a high bar. We want to make it frictionless, frictionless to try give us a shot, give us some feedback. And I'm grateful and privileged to be part of this, this wonderful team. So look forward to spending more time with you, John, in the future. >> Man, looking forward to a lot lots of talk about David Hatfield CEO of Lacework great company scaling up again. Another success story in cloud, cloud native as Po, COVID comes to a close, if you will for this phase and people get back to real life. The scale of cloud is going to be leading it and a new technology is going to be powering it. This is theCube conversation. I'm John Furrier. Thanks for watching. (soft music playing) (music fades)

>> Well, thank you, Gary. Well, you know, reasonable people could debate when the so-called big data era started. But for me it was in the fall of 2010 when I was sleepwalking through this conference in Dallas. And the conference was focused on data being a liability. And the whole conversation was about, how do you mitigate the risks of things like work in process and smoking-gun emails. I got a call from my business partner, John Fard, he said to me, "get to New York and come and see the future of data. We're doing theCUBE at Hadoop World tomorrow." I subsequently I canceled about a dozen meetings that I had scheduled for the week. And with only one exception, every one of the folks I was scheduled to meet said, "what's a Hadoop?" Well, I flew through an ice storm across country. I got to the New York Hilton around 3:00 AM, and I met John in the Dark Bar. If any of you remember that little facility. And I caught a little shut eye. And then the next day I met some of the most interesting people in tech during that time. They were thinking a lot differently than we were used to. They looked at data through a prism of value. And they were finding new ways to do things like deal with fraud, they were building out social networks, they were finding novel marketing vectors and identifying new investment strategies. The other thing they were doing is, they were taking these little tiny bits of code and bring it to really large sets of data. And they were doing things that I hadn't really heard of like no schema-on-write. And they were transforming their organizations by looking at data not as a liability, but as a monetization opportunity. And that opened my eyes and theCUBE, like a lot of others bet its business on data. Now over the past decade, customers have built up infrastructure and have been accommodating a lot of different use cases. Things like offloading ETL, data protection, mining data, analyzing data, visualizing. And as you know, you no doubt realize this was at a time when the cloud was, you know, really kind of nascent. And it was really about startups and experimentation. But today, we've evolved from the wild west of 2010, and many of these customers they're leveraging the cloud for of course, ease of use and flexibility it brings, but also they're finding out it brings complexity and risk. I want to tell you a quick story. Recently it was interviewing a CIO in theCUBE and he said to me, "if you just shove all your workloads into the cloud, you might get some benefit, but you're also going to miss the forest to the trees. You have to change your operating model and expand your mind as to what is cloud and create a cloud light experience that spans your on premises, workloads, multiple public clouds, and even the edge. And you have to re-imagine your business and the possibilities that this new architecture this new platform can bring." So we're going to talk about some of this today in a little bit more detail and specifically how we can better navigate the data storm. And what's the role of hybrid cloud. I'm really excited to have two great guests. Manish Dasaur is the managing director in the North America lead for analytics and artificial intelligence at Accenture. Anupam Singh is the chief customer officer for Cloudera. Gentlemen, welcome to theCUBE, great to see you. >> Hi Dave good to see you again. >> All right, guys, Anupam and Manish, you heard my little monologue upfront Anupam we'll start with you. What would you? Anything you'd add, amend, emphasize? You know, share a quick story. >> Yeah, Dave thank you for that introduction. It takes me back to the days when I was an article employee and went to this 14 people meet up. Just a couple of pizza talking about this thing called Hadoop. And I'm just amazed to see that today we are now at 2000 customers, who are using petabytes of data to make extremely critical decisions. Reminds me of the fact that this week, a lot of our customers are busy thinking about elections and what effect it would have on their data pipeline. Will it be more data? Will it be more stressful? So, totally agree with you. And also agree that cloud, is almost still in early days in times of the culture of IT on how to use the cloud. And I'm sure we'll talk about that today in greater detail. >> Yeah most definitely Manish I wonder if we could get your perspective on this. I mean, back when Anupam was at Oracle you'd shove a bunch of, you know, data, maybe you could attach a big honking disc drive, you'd buy some Oracle licenses, you know, it was a Unix box. Everything went into this, you know, this God box and then things changed quite dramatically, which was awesome, but also complex. And you guys have been there from the beginning. What's your perspective on all this? >> Yeah, it's been fascinating just to watch the market and the technology evolve. And I think the urgency to innovate is really just getting started. We're seeing companies drive growth from 20% in cloud today, to 80% cloud in the next few years. And I think the emergence of capabilities like hybrid cloud, we really get upfront a lot of flexibility for companies who need the ability to keep some data in a private setting, but be able to share the rest of the data in a public setting. I think we're just starting to scratch the surface of it. >> So let's talk a little bit about what is a hybrid cloud Anupam I wonder if you could take this one let's start with you and then Manish we come back to you and to get the customer perspective as well. I mean, it is a lot of things to a lot of people, but what is it? Why do we need it? And you know, what's the value? >> Yeah, I could speak poetic about Kubernetes and containers et cetera. But given that, you know, we talk to customers a lot, all three of us from the customer's perspective, hybrid cloud is a lot about collaboration and ease of procurement. A lot of our customers, whether they're in healthcare, banking or telco, are being asked to make the data available to regulatory authority, to subsidiaries outside of their geography. When you need that data to be available in other settings, taking a from on-prem and making it available in public cloud, enables extreme collaboration, extreme shared data experience if you will, inside the company. So we think about hybrid like that. >> Manish anything you'd add? How are your customers thinking about it? >> I mean, in a very simple way, it's a structure that where we are allowing mixed computing storage and service environments that's made of on-prem structures, private cloud structures, and public cloud structures. We're often calling it multicloud or mixcloud. And I think the really big advantage is, this model of cloud computing is enabling our clients to gain the benefits of public cloud setting, while maintaining your own private cloud for sensitive and mission critical and highly regulated computing services. That's also allowing our clients and organizations to leverage the pay-as-you-go model, which is really quite impressive and attractive to them because then they can scale their investments accordingly. Clients can combine one or more public cloud providers together in a private cloud, multicloud platform. The cloud can operate independently of each other, communicate over an encrypted connection. This dynamic solution offers a lot of flexibility and scalability which I think is really important to our clients. >> So Manish I wonder if we would stay there. How do they, how do your customers decide? How do you help them decide, you know, what the right mix is? What the equilibrium is? How much should it be in on-prem? How much should be in public or across clouds? Or, you know, eventually, well the edge will I guess decide for us. But, how do you go through, what are the decision points there? >> Yeah, I think that's a great question Dave. I would say there's several factors to consider when developing a cloud strategy that's the right strategy for you. Some of the factors that come to my mind when contemplating it, one would be security. Are there data sets that are highly sensitive that you don't want leaving the premise, versus data sets that need to be in a more shareable solution. Another factor I'd consider is speed and flexibility. Is there a need to stand up and stand down capabilities based on the seasonality of the business or some short-term demands? Is there a need to add and remove scale from the infrastructure and that quick pivot and that quick reaction is another factor they should consider. The third one I'd probably put out there is cost. Large data sets and large computing capacities often much more scalable and cost effective than a cloud infrastructure so there's lots of advantages to think through there. And maybe lastly I'd share is the native services. A lot of the cloud providers enable a set of native services for ingestion, for processing, of modeling, for machine learning, that organizations can really take advantage of. I would say if you're contemplating your strategy right now, my coaching would be, get help. It's a team sport. So definitely leverage your partners and think through the pros and cons of the strategy. Establish a primary hyperscaler, I think that's going to be super key and maximize your value through optimizing the workload, the data placement and really scaling the running operations. And lastly, maybe Dave move quickly right? Each day that you wait, you're incurring technical debt in your legacy environment, that's going to increase the cost and barrier to entry when moving to the new cloud hybrid driver. >> Thank you for that. Anupam I wonder if we could talk a little bit about the business impact. I mean, in the early days of big data, yes, it was a heavy lift, but it was really transformative. When you go to hybrid cloud, is it really about governance and compliance and security and getting the right mix in terms of latency? Are there other, you know, business impacts that are potentially as transformative as we saw in the early days? What are your thoughts on that? >> Absolutely. It's the other business impacts that are interesting. And you know, Dave, let's say you're in the line of business and I come to you and say, oh, there's cost, there's all these other security governance benefits. It doesn't ring the bell for you. But if I say, Dave used to wait 32 weeks, 32 weeks to procure hardware and install software, but I can give you the same thing in 30 minutes. It's literally that transformative, right? Even on-prem, if I use cloud native technology, I can give something today within days versus weeks. So we have banks, we have a bank in Ohio that would take 32 weeks to rack up a 42 node server. Yes, it's very powerful, you have 42 nodes on it, 42 things stacked on it, but still it's taking too much time. So when you get cloud native technologies in your data center, you start behaving like the cloud and you're responsive to the business. The responsiveness is very important. >> That's a great point. I mean, in fact, you know, there's always this debate about is the cloud public cloud probably cost more expensive? Is it more expensive to rent than it is to own? And you get debates back and forth based on your perspective. But I think at the end of the day, what, Anupam you just talked about, it may oftentimes could dwarf, you know, any cost factors, if you can actually, you know, move that fast. Now cost is always a consideration. But I want to talk about the migration path if we can Manish. Where do, how should customers think about migrating to the cloud migration's a, an evil word. How should they think about migrating to the cloud? What's the strategy there? Where should they start? >> No I think you should start with kind of a use case in mind. I think you should start with a particular data set in mind as well. I think starting with what you're really seeking to achieve from a business value perspective is always the right lens in my mind. This is the decade of time technology and cloud to the fitness value, right? So if you start with, I'm seeking to make a dramatic upsell or dramatic change to my top line or bottom line, start with the use case in mind and migrate the data sets and elements that are relevant to that use case, relevant to that value, relevant to that unlock that you're trying to create, that I think is the way to prioritize it. Most of our clients are going to have tons and tons of data in their legacy environment. I don't think the right way to start is to start with a strategy that's going to be focused on migrating all of that. I think the strategy is start with the prioritized items that are tied to the specific value or the use case you're seeking to drive and focus your transformation and your migration on that. >> So guys I've been around a long time in this business and been an observer for awhile. And back in the mainframe days, we used to have a joke called CTAM. When we talk about moving data, it was called the Chevy truck access method. So I want to ask you Anupam, how do you move the data? Do you, it's like an Einstein saying, right? Move as much data as you need to, but no more. So what's going on in that front? what's happening with data movement, and, you know, do you have to make changes to the applications when you move data to the cloud? >> So there's two design patterns, but I love your service story because you know, when you have a 30 petabyte system and you tell the customer, hey, just make a copy of the data and everything will be fine. That will take you one and a half years to make the copies aligned with each other. Instead, what we are seeing is the biggest magic is workload analysis. You analyze the workload, you analyze the behavior of the users, and say so let's say Dave runs dashboards that are very complicated and Manish waits for compute when Dave is running his dashboard. If you're able to gather that information, you can actually take some of the noise out of the system. So you take selected sets of hot data, and you move it to public cloud, process it in public cloud maybe even bring it back. Sounds like science fiction, but the good news is you don't need a Chevy to take all that data into public cloud. It's a small amount of data. That's one reason the other pattern that we have seen is, let's say Manish needs something as a data scientist. And he needs some really specific type of GPUs that are only available in the cloud. So you pull the data sets out that Manish needs so that he can get the new silicone, the new library in the cloud. Those are the two patterns that if you have a new type of compute requirement, you go to public cloud, or if you have a really noisy tenant, you take the hot data out into public cloud and process it there. Does that make sense? >> Yeah it does and it sort of sets up this notion I was sort of describing upfront that the cloud is not just, you know, the public cloud, it's the spans on-prem and multicloud and even the edge. And it seems to me that you've got a metadata opportunity I'll call it and a challenge as well. I mean, there's got to be a lot of R and D going on right now. You hear people talking about cloud native and I wonder on Anupam if you could stay on that, I mean, what's your sense as to how, what the journey is going to look like? I mean, we're not going to get there overnight. People have laid out a vision of this sort of expanding cloud and I'm saying it's a metadata opportunity, but I, you know, how do you, the system has to know what workload to put where based on a lot of those factors that you guys were talking about. The governance, the laws of the land, the latency issues, the cost issues is, you know, how is the industry Anupam sort of approaching this problem and solving this problem? >> I think the biggest thing is to reflect all your security governance across every cloud, as well as on-prem. So let's say, you know, a particular user named Manish cannot access financial data, revenue data. It's important that that data as it goes around the cloud, if it gets copied from on-prem to the cloud, it should carry that quality with it. A big danger is you copy it into some optic storage, and you're absolutely right Dave metadata is the goal there. If you copy the data into an object storage and you lose all metadata, you lose all security, you lose all authorization. So we have invested heavily in something called shared data experience. Which reflects policies from on-prem all the way to the cloud and back. We've seen customers needing to invest in that, but some customers went all hog on the cloud and they realize that putting data just in these buckets of optic storage, you lose all the metadata, and then you're exposing yourself to some breach and security issues. >> Manish I wonder if we could talk about, thank you for that Anupam. Manish I wonder if we could talk about, you know, I've imagined a project, okay? Wherever I am in my journey, maybe you can pick your sort of sweet spot in the market today. You know, what's the fat middle if you will. What does a project look like when I'm migrating to the cloud? I mean, what are some of the, who are the stakeholders? What are some of the outer scope maybe expectations that I better be thinking about? What kind of timeframe? How should I tackle this and so it's not like a, you know, a big, giant expensive? Can I take it in pieces? What's the state-of-the-art of a project look like today? >> Yeah, lots of thoughts come to mind, Dave, when you ask that question. So there's lots to pack. As far as who the buyer is or what the project is for, this is out of migration is directly relevant to every officer in the C-suite in my mind. It's very relevant for the CIO and CTO obviously it's going to be their infrastructure of the future, and certainly something that they're going to need to migrate to. It's very important for the CFO as well. These things require a significant migration and a significant investment from enterprises, different kind of position there. And it's very relevant all the way up to the CEO. Because if you get it right, the truly the power it unlocks is illuminates parts of your business that allow you to capture more value, capture a higher share of wallet, allows you to pivot. A lot of our clients right now are making a pivot from going from a products organization to an as a service organization and really using the capabilities of the cloud to make that pivot happen. So it's really relevant kind of across the C-suite. As far as what a typical program looks like, I always coach my clients just like I said, to start with the value case in mind. So typically, what I'll ask them to do is kind of prioritize their top three or five use cases that they really want to drive, and then we'll land a project team that will help them make that migration and really scale out data and analytics on the cloud that are focused on those use cases. >> Great, thank you for that. I'm glad you mentioned the shift in the mindset from product to as a service. We're seeing that across the board now, even infrastructure players are jumping on the bandwagon and borrowing some sort of best practices from the SaaS vendors. And I wanted to ask you guys about, I mean, as you move to the cloud, one of the other things that strikes me is that you actually get greater scale, but there's a broader ecosystem as well. So we're kind of moving from a product centric world and with SaaS we've got this sort of platform centric, and now it seems like ecosystems are really where the innovation is coming from. I wonder if you guys could comment on that, maybe Anupam you could start. >> Yeah, many of our customers as I said right? Are all about sharing data with more and more lines of businesses. So whenever we talk to our CXO partners, our CRO partners, they are being asked to open up the big data system to more tenants. The fear is, of course, if you add more tenants to a system, it could get, you know, the operational actually might get violated. So I think that's a very important part as more and more collaboration across the company, more and more collaboration across industries. So we have customers who create sandboxes. These are healthcare customers who create sandbox environments for other pharma companies to come in and look at clinical trial data. In that case, you need to be able to create these fenced environments that can be run in public cloud, but with the same security that you expect up. >> Yeah thank you. So Manish this is your wheelhouse as Accenture. You guys are one of the top, you know, two or three or four organizations in the world in terms of dealing with complexity, you've got deep industry expertise, and it seems like some of these ecosystems as Anupam was just sort of describing it in a form are around industries, whether it's healthcare, government, financial services and the like. Maybe your thoughts on the power of ecosystems versus the, you know, the power of many versus the resources of one. >> Yeah, listen, I always talk about this is a team sport right? And it's not about doing it alone. It's about developing as ecosystem partners and really leveraging the power of that collective group. And I've been for as my clients to start thinking about, you know, the key thing you want to think about is how you migrate to becoming a data driven enterprise. And in order for you to get there, you're going to need ecosystem partners to go along the journey with you, to help you drive that innovation. You're going to need to adopt a pervasive mindset to data and democratization of that data everywhere in your enterprise. And you're going to need to refocus your decision-making based on that data, right? So I think partner ecosystem partnerships are here to stay. I think what we're going to see Dave is, you know, at the beginning of the maturity cycle, you're going to see the ecosystem expand with lots of different players and technologies kind of focused on industry. And then I think you'll get to a point where it starts to mature and starts to consolidate as ecosystem partners start to join together through acquisitions and mergers and things like that. So I think ecosystem is just starting to change. I think the key message that I would give to our clients is take advantage of that. There's too much complexity for any one person to kind of navigate through on your own. It's a team sport, so take advantage of all the partnerships you can create. >> Well, Manish one of the things you just said that it kind of reminds me, you said data data-driven, you know, organizations and, you know, if you look at the pre-COVID narrative around digital transformation, certainly there was a lot of digital transformation going on, but there was a lot of complacency too. I talked to a lot of folks, companies that say, "you know, we're doing pretty well, our banks kicking butt right now, we're making a ton of money." Or you know, all that stuff that's kind of not on my watch. I'll be retired before then. And then it was the old, "if it ain't broke, don't fix it." And then COVID breaks everything. And now if you're not digital, you're out of business. And so Anupam I'll start with you. I mean, to build a data-driven culture, what does that mean? That means putting data at the center of your organization, as opposed to around in stove pipes. And this, again, we talked about this, it sort of started in there before even the early parts of last decade. And so it seems that there's cultural aspects there's obviously technology, but there's skillsets, there's processes, you've got a data lifecycle and a data, what I sometimes call a data pipeline, meaning an end to end cycle. And organizations are having to rethink really putting data at the core. What are you seeing? And specifically as it relates to this notion of data-driven organization and data culture, what's working? >> Yeah three favorite stories, and you're a 100% right. Digital transformation has been hyperaccelerated with COVID right? So our telco customers for example, you know, Manish had some technical problems with bandwidth just 10 minutes ago. Most likely is going to call his ISP. The ISP will most likely load up a dashboard in his zip code and the reason it gives me stress, this entire story is because most likely it's starting on a big data system that has to collect data every 15 minutes, and make it available. Because you'll have a very angry Manish on the other end, if you can't explain when is the internet coming back, right? So, as you said this is accelerated. Our telco providers, our telco customers ability to ingest data, because they have to get it in 15 minute increments, not in 24 hour increments. So that's one. On the banking sector what we have seen is uncertainty has created more needs for data. So next week is going to be very uncertain all of us know elections are upcoming. We have customers who are preparing for that additional variable capacity, elastic capacity, so that if investment bankers start running hundreds and thousands of reports, they better be ready. So it's changing the culture at a very fundamental level, right? And my last story is healthcare. You're running clinical trials, but everybody wants access to the data. Your partners, the government wants access to the data, manufacturers wants access to the data. So again, you have to actualize digital transformation on how do you share very sensitive, private healthcare data without violating any policy. But you have to do it quick. That's what COVID has started. >> Thank you for that. So I want to come back to hybrid cloud. I know a lot of people in the audience are, want to learn more about that. And they have a mandate really to go to cloud generally but hybrid specifically. So Manish I wonder if you could share with us, maybe there's some challenges, I mean what's the dark side of hybrid. What should people be thinking about that they, you know, they don't want to venture into, you know, this way, they want to go that way. What are some of the challenges that you're seeing with customers? And how are they mitigating them? >> Yeah, Dave it's a great question. I think there's a few items that I would coach my clients to prioritize and really get right when thinking about making the migration happen. First of all, I would say integration. Between your private and public components that can be complex, it can be challenging. It can be complicated based on the data itself, the organizational structure of the company, the number of touches and authors we have on that data and several other factors. So I think it's really important to get this integration right, with some clear accountabilities build automation where you can and really establish some consistent governance that allows you to maintain these assets. The second one I would say is security. When it comes to hybrid cloud management, any transfers of data you need to handle the strict policies and procedures, especially in industries where that's really relevant like healthcare and financial services. So using these policies in a way that's consistent across your environment and really well understood with anyone who's touching your environment is really important. And the third I would say is cost management. All the executives that I talk about have to have a cost management angle to it. Cloud migration provides ample opportunities for cost reduction. However many migration projects can go over budget when all the costs aren't factored in, right? So your cloud vendors. You've got to be mindful of kind of the charges on accessing on premise applications and scaling costs that maybe need to be budgeted for and where if possible anticipated and really plan for. >> Excellent. So Anupam I wonder if we could go a little deeper on, we talked a little bit about this, but kind of what you put where, which workloads. What are you seeing? I mean, how are people making the choice? Are they saying, okay, this cloud is good for analytics. This cloud is good. Well, I'm a customer of their software so I'm going to use this cloud or this one is the best infrastructure and they got, you know, the most features. How are people deciding really what to put where? Or is it, "hey, I don't want to be locked in to one cloud. I want to spread my risk around. What are you seeing specifically? >> I think the biggest thing is just to echo what Manish said. Is business comes in and as a complaint. So most projects that we see on digital transformation and on public cloud adoption is because businesses complaining about something. It's not architectural goodness, it is not for just innovation for innovation's sake. So, the biggest thing that we see is what we call noisy neighbors. A lot of dashboards, you know, because business has become so intense, click, click, click, click, you're actually putting a lot of load on the system. So isolating noisy neighbors into a cloud is one of the biggest patterns that you've seen. It takes the noisiest tenant on your cluster, noisiest workload and you take them to public cloud. The other one is data scientists. They want new libraries, they want to work with GPU's. And to your point Dave, that's where you select a particular cloud. Let's say there's a particular type silicone that is available only in that cloud. That GPU is available only in that cloud or that particular artificial intelligence library is available only in a particular cloud. That's when customers say, Hey miss, they decided, why don't you go to this cloud while the main workload might still be running on them, right? That's the two patterns that we are seeing. >> Right thank you. And I wonder if we can end on a little bit of looking to the future. Maybe how this is all going to evolve over the next several years. I mean, I like to look at it at a spectrum at a journey. It's not going to all come at once. I do think the edge is part of that. But it feels like today we've got, you know, multi clouds are loosely coupled and hybrid is also loosely coupled, but we're moving very quickly to a much more integrated, I think we Manish you talked about integration. Where you've got state, you've got the control plane, you've got the data plane. And all this stuff is really becoming native to the respective clouds and even bring that on-prem and you've got now hybrid applications and much much tighter integration and build this, build out of this massively distributed, maybe going from it's a hyper-converged to hyper-distributed again including the edge. So I wonder Manish we could start with you. How are your customers thinking about the future? How are they thinking about, you know, making sure that they're not going down a path where that's going to, they're going to incur a lot of technical debt? I know there's sort of infrastructure is code and containers and that seems it seems necessary, but insufficient there's a lot of talk about, well maybe we start with a functions based or a serverless architecture. There's some bets that have to be made to make sure that you can future proof yourself. What are you recommending there Manish? >> Yeah, I, listen I think we're just getting started in this journey. And like I said, it's really exciting time and I think there's a lot of evolution in front of us that we're going to see. I, you know, I think for example, I think we're going to see hybrid technologies evolve from public and private thinking to dedicated and shared thinking instead. And I think we're going to see advances in capabilities around automation and computer federation and evolution of consumption models of that data. But I think we've got a lot of kind of technology modifications and enhancements ahead of us. As far as companies and how they future proof themselves. I would offer the following. First of all, I think it's a time for action, right? So I would encourage all my class to take action now. Every day spent in legacy adds to the technical debt that you're going to incur, and it increases your barrier to entry. The second one would be move with agility and flexibility. That's the underlying value of hybrid cloud structures. So organizations really need to learn how to operate in that way and take advantage of that agility and that flexibility. We've talked about creating partnerships in ecosystems I think that's going to be really important. Gathering partners and thought leaders to help you navigate through that complexity. And lastly I would say monetizing your data. Making a value led approach to how you viewed your data assets and force a function where each decision in your enterprise is tied to the value that it creates and is backed by the data that supports it. And I think if you get those things right, the technology and the infrastructure will serve. >> Excellent and Anupam why don't you bring us home, I mean you've got a unique combination of technical acumen and business knowledge. How do you see this evolving over the next three to five years? >> Oh, thank you Dave. So technically speaking, adoption of containers is going to steadily make sure that you're not aware even of what cloud you're running on that day. So the multicloud will not be a requirement even, it will just be obviated when you have that abstraction there. Contrarily, it's going to be a bigger challenge. I would echo what Manish said start today, especially on the cultural side. It is great that you don't have to procure hardware anymore, but that also means that many of us don't know what our cloud bill is going to be next month. It is a very scary feeling for your CIO and your CFO that you don't know how much you're going to to spend next month forget next year, right? So you have to be agile in your financial planning as much you have to be agile in your technical planning. And finally I think you hit on it. Ecosystems are what makes data great. And so you have to start from day one that if I am going on this cloud solution, is the data shareable? Am I able to create an ecosystem around that data? Because without that, it's just somebody running a report may or may not have value to the business. >> That's awesome, guys. Thanks so much for a great conversation. We're at a time and I want to wish everybody a terrific event. Let me now hand it back to Vanita. She's going to take you through the rest of the day. This is Dave Vellante for theCUBE, thanks. (smooth calm music)

(melodic music) >> Narrator: From around the globe, it's theCUBE. With digital coverage of AnsibleFest 2020. Brought to you by Red Hat. >> Hey, welcome back. Get ready, Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of AnsibleFest 2020, it's virtual this year. But we've had a lot of great interviews and just coming off the keynotes, want to invite John Furrier in, he's been doing a lot of the keynotes and attending this thing for years. So John, first off, get your impressions of AnsibleFest 2020. >> Hey Jeff, great to cover this event. It's too bad we're not in person, we're virtual, theCUBE virtual AnsibleFest is virtual. Last year was in person, it's a really intimate event last year. And again with that theme, a similar vibe here for 2020 again, not face-to-face, but the content has that same kind of community vibe. Just some notable things just of the Keynote and some of the news is obviously last year they launched the Ansible Automation Platform. They've grown their collections community from five supported platforms to 50. And they launched the automation services catalog. So, you starting to see from the Keynotes, the positioning of Red Hat and Ansible. Just a series of announcements at AnsibleFest that include a lot integrations. Okay, and I think that's the key thing, obviously Kubernetes we heard at VMworld continued to take center stage in cloud native and CI/CD Pipeline. So yeah, with that, that's the vibe collections, collections, collections, and some new terminology, which could be confused depending on where you come from, but the word 'content' means something here and content is code and there's a collaboration aspect. And so, overall you seeing that positioning of agile, DevOps, security network automation and obviously community, a big part of Red Hat and Ansible is the core community and this future development environment of easy to consume, easy to code, easy to troubleshoot and built-in security and make it collaborative. That's the open-source ethos. And that's really the focus of AnsibleFest 2020 virtual. >> Yeah, I thought it was interesting. Richard Henshaw you know came out with, and it really reinforced the theme that automate and connect. And it's pretty interesting 'cause he talks about Ansible being the language of collaboration and how important collaboration is. And as we know with COVID and everybody working from home, now kind of the traditional methods of development teams getting together and a DevOps culture and doing daily stand-ups and having this kind of co-mingling of people isn't available anymore really as an option. So the pressure to collaborate is harder than ever before. So really an interesting twist for Ansible taking that tack that they are the language of collaboration. >> I liked his philosophy and some of his narrative around, he used to be a developer. They had a different group from their network-op brethren and they had different kind of siloed bill work together, it's all IT back in the day. But as things have become more cloud native, they have to integrate more and work together. And so this notion of collections is a big deal at Ansible. It's the idea of having these, these playbooks and having people be responsible for their playbooks and share those playbooks. They have a thing called content, which is how you can share these playbooks as content to be consumed and also collaborated and built on and with. But ultimately the theme around Ansible has always been a tool for automation. And now as a platform, the focus is making that automation platform wide across multiple environments, not just public cloud or on premises, it's edge, it's multicloud. So this idea of network automation has moved resources across the environments. And security is a big part of it. The automation platform for instance has a new 2.10 release, which brings back a huge amount of change releases where you don't have to be tied to the local host where you have this module updates are not directly tied to release cycles. Now this means that there's more availability of code. So network automation and updates, synchronous updates are huge. They talked about the VMware collection, IBM Z collections, all these things point to integrations. And that's really the focus of this integrate, this cloud native is, can I play well with others? This is again an extension to the community theme of open source. And if you're not integrating well in cloud native, you probably not going to be around longer. And that's a good theme for them. >> Yeah. So John, I wonder if you can unpack it a little bit, Robyn Bergeron and her Keynote went through this concept of the collection that I'm checking my notes here. They actually have three different types, they've got playbooks, roles, modules, PES, docks and plugins. And she talked about this is a way to basically aggregate information and share it in a bundle that other people can take full advantage of. >> Yeah, and I think that's the key of these collections. And I asked each of them when I was talking to them on camera prior to the event. And I say, what's the big theme for AnsibleFest this year? And they all said, Robyn was like collections, collections, collections. But the idea of writing code in a collection is all about Integry, so the VMware for instance is a great example. IBM Z, which is their mainframe piece. Ansible now part of Red Hat, and now Red Hat's part of IBM, you seeing that they now have more innovation going on with let's say mainframes. So the IBM Z integration allows Ansible to be compatible and bring a modern error to the mainframes. And this speaks to how people are working with these new roles and can leverage code in a new way. So, I think that's a real big thing about providing that last mile innovation and bringing it in other environments. Not just being on Ansible, but really integrating in with others. >> The other piece getting a lot attention John is OpenShift and the rule of OpenShift and the play of OpenShift. So how should people think about how OpenShift fits in this whole puzzle? >> I think OpenShift brings the Red Hat, a hybrid cloud automation piece to it, to Ansible, which is the, where the developers are playing with the CI/CD Pipeline. So the combination of, if you remember back in the days of OpenStack when we covered Red Hat and when OpenShift kind of really hit the scene, that was around private cloud. And then OpenShift adopted Kubernetes and that kind of cloud native vibe. And then since then the growth has been phenomenal. So when you take Red Hat's OpenShift, which is the cloud platform and you bring it to the automation platform of Ansible, it allows customers to have an easy to use capability to do hybrid and multicloud automation. And where this matters is where containers are getting traction. IDC was reporting numbers where only five to 15% of the enterprise, depending upon how you look at it are containerized, which means there's a huge surge of opportunity in these enterprises to bring containers into the cloud model. So for lift and shift and for modern workloads. So the OpenShift provides that path. So it's a nice compliment for the two together to work. So when we heard customers talking about the game system, one customer we talked about using Ansible Tower and the entire cloud, private cloud environment across data centers. So it's a good fit, automation with cloud. And honestly that's where the magic is. >> Right, right. The other piece that we keep hearing about over and over and over, and there's a play here as well as the edge, right. And really moving the compute closer to the place the data is generated and closer to the place that the data is consumed. But where do you see kind of the edge, the edge play here at AnsibleFest? (deep breath) >> Well this kind of ties into the earlier question about OpenShift and Ansible, that kind of automation meets hybrid cloud and addressing this like last mile aspect that Ansible provides in terms of load balancing, configuration, applications, application servers, pushing the apps to the edge. That's a big deal. And as 5G comes out and as edge becomes more, more important, you're going to need to have automation, the surface area of things (chuckles) to automate becomes critical. So the whole discussion is, it's larger scale, more devices, more code being shipped. This is where the engineers got to get involved early, bake security in from the beginning. But also have that automation capability, so it's not context switching between I ship some code, I got to troubleshoot it. They can all do it from within the Ansible platform. (hands rubs together) And that's where the traction with developers is. And this notion, this was the notion of sharing and collections and content become important because you have more people involved. And the betterment of the, of the collections and the crowd and the developers make sense. So edge is real and you got to have a software defined operational model. And you got to have a cloud piece like OpenShift, and you got to have an automation component like Ansible. So, this is a critical, whether you're talking space or 5G or inside an office or on a person, software defined operations will be the key. And that is a big trend that we're seeing right now. >> Yeah, so final question, John, what are you hoping to get out of this show, AnsibleFest 2020? Are there any open questions that you're hoping to get, get kind of answered or closed? Or what are you hoping to walk away with at the end of this event? >> Well, I'm curious to see how they handle the virtual event. Obviously the face to face is a very important intimate part of their community model. So I want to see how that goes. I want to see, I want to hear and look and squint through and connect the dots on the relationship with the Red Hat IBM acquisition, because Ansible is part of Red Hat and Red Hat is now (chuckles) part of IBM. So I think that's going to be a huge lift for Ansible, because once Ansible gets into the slipstream of IBM sales channels, that acceptance is going to be a really important factor for their growth. And then ultimately what's the developer trend? What new things are developers doing with automation that help customers have modern applications so that more, better apps can be deployed coming out of COVID, and as CXO's and the ivory tower of businesses change their business models, what new things are developers doing and how did that scale? So that's my, my key focus. >> All right, well that's great. Well, John, thanks for sharing your thoughts, your insight. And enough of us talking. Let's get to the tech athletes at AnsibleFest 2020. >> Awesome, thanks. >> Alright, he's John I'm Jeff. You're watching theCUBE with ongoing coverage of AnsibleFest 2020. Thanks for watching. We'll see you next time. (melodic music)

>> From around the globe, its theCUBE, covering the UPGRADE 2020, the NTT Research Summit presented by NTT research. >> Welcome back. I'm Stu Miniman and this is theCUBE's coverage of UPGRADE 2020. Of course, it's the NTT Research Summit and happy to welcome to the program, someone that's watched theCUBE for a long time, but first time on the program, Simon Walsh, he is the new CEO of NTT Americas. Simon, great to see you, and thanks so much for joining us. >> Thanks very much Stu, good to be here, nice to see you. >> As I mentioned, your previous companies that you've worked for are that theCUBE and theCUBE audience are well aware of. As a matter of fact, when I worked for some of those companies, NTT is one of the large global companies that I had the pleasure to interact with over the years. But if you could, maybe, let's start with just a bit of your background. And as I said, it's only been a few months that you've been the CEO. So, what's it like coming into a role like this, during the the situation that we're all faced with in 2020? >> Yeah. Thank you. My background is really in the platforms that enable the customers to run their technologies. And, I've spent some of my time in Europe and India and then lastly the last five plus years in the Americas, I have to say, I really enjoy it. It's a much better environment. And if I think about it from a GDP and an economy perspective, it's a really dynamic place to work. I've worked with companies, headquartered from Europe, running in Americas. And I've worked with companies that were headquartered in the Americas, running some of the European businesses. So, I've crossed the continents if you like. And I recently joined NTT and I have to say, it was a pretty lengthy process to explore, but that was partly, interviews and due diligence. Cause you want to make sure that, you're buying into a company that, number one, you can have a cultural compatibility with, but also somebody who you see really investing in technology that consult for the business agenda of the markets. So, that's really a bit about my background and then joining. I mean, I literally joined the last week of June, so, my whole time has been through lockdown in terms of employment. It's been very unique taking on a new post, exclusively remote, and I was a bit worried, at a human level, just, how do you connect with people? But what I would comment is I've actually had the ability to really meet a lot more people in person cause you can physically get to people's schedules a lot easier. So, that's certainly helped. And I've done my activities of meeting up clients. So, they've been very amenable to connecting, talking to our business partners and spending considerable amount of time with my colleagues in the Americas and around the world. And it's actually been very rewarding. I think, funnily enough, you probably physically closer because you're on a screen, and you're probably like 24 inches away from each other. Whereas in a meeting room you'd be the other side of a table. So, it's been unique, but so far so good. >> Oh yeah, absolutely. The new abnormal, as we've sometimes say we're all used to looking in the screens all day, talking to various people there. The impact on business though has been, obviously a lot of different things depending on the company, but that discussion of digital transformation a few years ago, it was like, "Oh, I don't know if it's real, is it a buzz word?" But that the spotlight that's been shown here in 2020 is what is real and what is not? Leveraging cloud services, giving people agility, being able to react fast because buoyant 2020th, we needed to react fast. So, help bring us inside a bit, and your time there, the discussions you're having with customers that adoption, moving along that journey for digital transformation, the impact that you're seeing and how's NTT helping its customers as they need to accelerate and respond to the realities that we see today. >> Yeah. So you're right Stu. I mean, digital disruption has been on varying for multiple years and we used to call it, technology and change and now we call it digital disruption or digital transformation. So, it's not necessarily new. I think the thing that's really accelerated in 2020, as a consequence of the pandemic is really the word distributed in that customers are undertaking their digital transformations, understanding what it is to modernize processes, modernize the customer experience. And then they're finding that actually they don't meet in a boardroom and discuss, the performance of the business. So, they now need to have distributed access to data. And I think that the topics that we see very prevalent is the distributed nature of the workforce. And obviously there's always been a field workforce and we've had systems. CRM systems and other systems that were built for a distributed workforce. But now we have to think about how supply chain management systems and our HR systems, the PNL, and, all of the activities that our business undertakes with an entirely distributed workforce. And it's quite abnormal. What I think what we've learned is where is the data and how do I amalgamate data from distributed systems? And so I see, we're doing a lot of work with our clients relating to digital transformation, but really about how do I join data from system A to System F in a distributed manner? And most importantly, securely, timely and in an interface that is usable. And it sounds really easy. It's like, Oh great. Yeah, it's just two different data points, connect them together, make it secure, make it visible, create transparency. But we all know that the world is full of technical debt, legacy systems and platforms, very expensive and significant historical investments. And those things don't modernize themselves overnight. And quite often the dollars to modernize them don't justify themselves. So, we then end up layering on new technology. So, what I'm seeing in digital transformation is really about how do we handle distributed data, distributed decision making, and how do we do that in a secure manner and through an interface that is user friendly. >> Yeah, we obviously know that there's had to be some prioritization. The joke I've had, everybody came into 2020 with, "Okay, here's what I'm going to do for the first half of the year. Here's the objectives that I have." And we kind of throw those in the shredder rather early on. Number one priority I still hear it was probably that the number one priority coming into the year and it stays there and you've mentioned it multiple times, it's security, it is absolutely front and center still. How overall though, how are your customers, the CXO suite, how are they adjusting their priorities? Are there certain projects that just go on hold? Are there certain ones that get front and center, obviously, you know, that distributed work from anywhere telemedicine, teach and learn from anywhere, have been top of mind. But any other key learnings you're finding or prioritization changes, some of which are going to probably stay with us, for the longterm. >> Absolutely. We've definitely seen customers reprioritizing. And I think there is obviously an inevitability to this as a consequence of the pandemic. I mean, if you were undertaking a campus upgrade, you might just put that on pause for the moment. And we've absolutely seen that. But what we've really seen as a prioritization has been, how do we get our information to our users, whether the user is a customer or whether the user is an employee? There's examples where there's lots of companies who say they've got like online e-tail, right? But now they've got to do curbside pickup because they've actually got inventory in the stores, but the stores couldn't open. So, what you've seen is a re-prioritization to say, well when we look at inventory management and the supply chain systems, are we factoring in the inventory we have in a store could also be seen as inventory across the stores? And in fact, what we've really got now is a distributed warehouse. We've got inventory in the warehouse like wholesale ready for distribution. And then we've got inventory in a store, retail ready for consumer consumption. What don't want that to be separate inventory. We want that to be holistic. And then how do we enable any consumer anywhere to be able to arrange for curbside pickup, which we didn't use to do because we would come into the store or arrange for mail order. But the inventory may come from you know, I may send something from San Francisco to somebody in Boston because it was in a store inventory in San Francisco. Now, sure, it's got some freight cost, but I've also got some other efficiency savings and I'm reducing my working capital or my inventory expense. So, we've seen prioritization for really how to take advantage of this. I come back to it, this word distributed is very simple in principal, but everything is now working on a new dynamic. So, that's some of the prioritization we've seen. >> You mentioned one of the things that might get put on hold is, wait if I was doing a corporate network update, that might not be the first thing, we absolutely, we've gotten some great data on just the changing traffic patterns of the internet, but the network is so critically important. Everybody from home is dealing with, you know, children doing their Zoom classrooms while we're trying to do video meetings. NTT obviously has a strong network component to what its business is. So, help us understand the services that are important there, what you're working with customers and how has this kind of transformed some of those activities? >> Yeah. Yeah, sure. Thank you. You're so right. I mean and I have to say, I just like to pay my respects to colleagues and fellow workers around the world who are not just working from home, but also homeschooling in parallel. Our kids fled the nest, either they're working for themselves now, so, we don't have the extra activity of homeschooling, but I can really have a lot of respect for colleagues who are trying to do both, it's a real fine art. And we've seen a lot of actually just talking of re-prioritization. We've seen a lot of companies including ourselves, say to our colleagues, look after your children, homeschool them, do everything you can to support your families and then get to your work. So, that re-prioritization just in behavior has been a key change that we've seen a lot of people do. That flexibility to, you know, work is something you do, not somewhere you go. And therefore, as long as the work is done, we can flex around, you know your needs as a family. So, that's one prioritization we've seen active actually. But to your point on the network, it's quite amusing to me that we've been for years now talking about cloud, on-demand subscription services. And actually the one asset that you need to really enable cloud is the network. And it's historically been the least cloud-like that you could possibly imagine because you still need to specify a physical connection. You still need to specify a bandwidth value. You still need to specify, the number of devices you've got to attach to it. I think this is really a monstrous change that we're going to experience and really are experiencing, the network as a service. I mean, we talk about IAS, PAS SAS, but what happened to NAS? I mean, really did we just think that everything was about computer and software? The networker is the underpinner. And so really we see a big change and this is where we've been very busy in the network as a service enabling customers to have, dynamic reallocation of resources on the network so that they can prioritize traffic, prioritize content, prioritize events. A lot of customers and are doing activities such as hosting their own event, their own digital conference. And you want to prioritize what the user experience is when you host one of those events over perhaps back office process that can quite frankly wait a few days. So, we see a significant opportunity. This is where we've been very busy the last few months in really building out much more dynamic network as a service solutions, the cloud network. And I think the whole software defined network agenda has materially accelerated. That's one major area. And then the other area has just been the phenomenal shift to IP voice and software and actually almost the deletion of the phone in its entirety. Everybody using, Teams or Skype or Google Hangouts to really use as their collaboration mechanism. And then, we're providing all the underlying transportation layer, but as IP voices, that creates a much more integrated collaboration experience, and it creates a cost saving cause you're taking away the classic voice services. >> Yeah. So Simon boy, I'm excited for that. I tell you, I remember when I got my first Blackberry and they were trying to sell me some things, I'm like, "Wait, this is an internet endpoint. I can do all of these things there." And of course, you know, it's taken me the last dozen years. If gone a certain far, but, and we always joke. It's like smartphones, we don't use them for phones anymore. We use them for all the messaging and all those services. So, the data and the network are so critically important. Simon, I want to turn to UPGRADE 2020, you know what I'm excited about this, we've talked about the major impacts of what's happened in 2020. And we're looking at the here and now, but it's great in technology when we get to be able to look forward and look at some of the opportunities out there. So, would love to hear from your standpoint, some of the areas, what's exciting you, what's exciting that we can look forward to some of the areas and pockets of research that we see at the event. >> Yeah, I think he's Stu. I think what I like about our event is the investment that we make to work with the scientific community, academia, and really invest in, forward-looking, future-proofing, how physics and different technologies might play a role in the future. And, some of these investments and some of this research yields, commercial products and some of it doesn't, but it's still a very valuable opportunity for us to really look at where technology is going. I think the areas that are particularly appealing to me on a personal level, just the whole thing of Quantum computing. This is, I know we're already exploring the capabilities of Quantum computing in some labs, and some academia centers and really to understanding how can we take advantage of that. But I think if you then say, and you take another area that we're exploring through the event, Biosciences. If you then take the two together and you think, okay, how do we take Quantum computing, and we take Biosciences and you think about healthcare, and then you think about the pandemic, are there things that we can do with simulations and technologies in the future that really would give us greater comprehension and ability to accelerate, understanding, accelerate testing, and then really contribute to the health and welfare of society. And I think that's really quite an exciting area for us. So, that's a specific topic that I'm particularly interested in. I'm glad to see us doing a lot in that space, Quantum computing, as well as the Biosciences. And I'd say one other area where I still think we're all trying to ascertain, how it serves the business is really the area of blockchain. I think this is intriguing. I'm still mentally trying to master the subject. No amount of white papers has managed to overcome the topic in my brain yet. So I'm still working on it. And then I think cryptography, I come back to the same subject security. I mean, we are dependent as citizens, businesses and nations on technology now, and our data is available how we secure it, how we make sure that it's encrypted is absolutely going to be critical. You see an increasing push nationally and globally to ensure that there is security of data. And I think the subject of cryptography, and how we go forward with, beyond 128 bit is going to be a very difficult and critical subject. So these are the areas I'm very impressed with. >> Wonderful. Simon, I want to give you the final word from UPGRADE 2020. >> Yeah. Thanks, Stu Just thanks very much to anybody that's attending. What you'll find through various workshops is lots of insight, from our strategic partners, from research scientists, from academia, from ourselves. So thank you very much for participating. We always value your feedback. So, please tell us what we could do to improve the content, to help you with your businesses. And we look forward and hope that everybody stays safe. Thank you for connecting with us virtually. >> Well, Simon Walsh. Thank you so much. Great having a conversation and glad to have you in our Cube alumni now. >> Thank you very much Stu. Have a good day. >> All right. And stay tuned more coverage from UPGRADE 2020 I'm Stu Miniman, and thanks as always for watching theCUBE. (upbeat music)

>> Advertiser: From theCUBE Studios in Palo Alto, in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Hi, everybody, this is Dave Vellante and welcome to our ongoing CXO series, Charlie Giancarlo season, chief executive officer of Pure Storage. Charlie, always a pleasure. Thanks so much for taking the time. >> Thanks, Dave. And like you said, always a pleasure, thank you. >> Well, I got to start asking you, the last time we talked, you were recovering from COVID. How are you doing? >> Yeah, I'm doing great actually. I seem to have fully recovered. I've been on 17 mile hikes at 10,000 feet. I've been doing a lot of biking, so it looks like other than my wife telling me that maybe I'm not all there, but she did that before COVID. So I'm used to it. >> Well, that's awesome to hear. Well, of course, just yesterday, you guys announced your quarter. I want to start there. You beat expectations, although revenue growth was a little less robust than we're used to from Pure, but you clearly had some activity regarding COVID in the US. International, very strong, but again, we'll talk about this US customers kind of reevaluating was your other key point. I got a lot of takeaways from the call that I want to ask you about. But the big thing was you had set a very confident tone on the Earnings Call. So I kind of want to start there. Well, give us your summary. >> Yeah, no, thank you for that. So first of all, we feel like we're operating really with all of our cylinders going. We have operational discipline. We've been adding to our R&D capabilities. We've hired people this year. and we showed a profit this quarter. So we're operating, I think very well. We've introduced a boatload of new products continuously over the last couple of quarters, including, FlashArray//C, the first and only all-flash product that competes at second Tier disc levels. We introduced our file services on FlashArray//C, which really allows us to go into the general purpose of file market. And we picked up a huge amount of share as you well know in Q1. We believe we're going to pick up significant share in Q2 as well, well above our competitors. So we feel like given everything we can control, we're doing very well. As you said, in Q2, what we saw was Europe, which came out of the crisis for the most part recover very, very nicely. The US, that's still in the crisis. Of course, we're seeing some slowness and especially among what we call the mid tier or the commercial market. They've been hurt very badly by the lockdown in the economy. And they have our sympathies, but we definitely saw some slow down there. >> Yeah, so I want to talk about the market share and maybe unpack some of that data. I mean, you guys gave a cautious outlook. It kind of gave no formal guidance, but you did informally guide flat, so you kind of gave some visibility there. So actually I appreciated it. I think some of the analysts were a little bit concerned there, but I think that's prudent. And they're really the expectations are a function of your expectations around the COVID recovery. I think you mentioned your account almost state by state and very clearly the international where you've seen comebacks have been very, very strong. >> Right, so I think our customers' data continues to grow if anything, growing faster under a lockdown environment and the move to more digital engagement with everyone, their customers, their employees, et cetera. So digital continues to grow, which generally creates more demand. However, of course, as you know, in storage customers generally always have a buffer. And what we saw on Q2 was customers starting to reconsider how they're going to spend their IT budget. And whenever you have a reconsideration, you have a slowdown. And that's what we experienced. And especially in the US where the effects of the pandemic, of the economy have been much more severe than in other parts of the world. >> Yeah, so I want to talk about some data. I often, as you know, like to share some data from our partner ETR every quarter we do the survey. So guys bring up that chart. And what it shows here, let's just set it up for the audience and Charlie for you as well. That this is essentially net score, which is a measure of spending velocity for the major primary guys. So we show Pure at the top in orange, that's just a coincidence guys. And then HPE, NetApp, Dell, and IBM. And you can see the net score, and then I've super imposed there in that table, in the upper left. And you can see Pure Storage is really the only one of these majors in the green. Everybody else is in the red, which is either the lower or high teens. And you can see a little bit of a COVID impact, last quarter, but holding strong at about a 40% net score where everybody else is, as I say, in the mid teens. And so that's a real positive. I point out, this is a forward looking survey. So we're asking people, what are you planning on spending in the second half relative to what you spent in the first half. And again, we see Pure with consistent momentum. I'll add, just if you looked at the past quarter, you guys announced plus 2% growth. IBM was plus 3% growth and we know why, they have the mainframe tailwind. HPE played a little hide, the growth ball. I don't know Charlie, how closely you looked at it, but they said 4% growth sequentially. Now, the last quarter they were down 16%. The same quarter last year, they were flat. So it looks to me like they were down this quarter. So we appreciate when you have clear guidance. >> Their storage, by the way, was down 10% year over year. >> Yeah, okay, great, thank you. I didn't pick up on that. And so, yeah, that seemed like that to me. And then NetApp happens tonight and we get Dell tomorrow. But so you were saying that you gained share, what gives you that confidence? >> Well, several, you mean for Q2? We know we gained Q1, right? We were 15 points above the industry average and maybe about 20 points ahead of our competitors. We saw a similar momentum from our partner. Remember, we're 100% partner fulfilled, right? And so in conversations with our partners, we have a general sense of how we're doing vis-a-vis competitive environments. We also know that our win rates have held very nicely and in quarters, almost every quarter, we're used to about a 20% per annum higher growth rate than our competitors. So when all of our metrics, that is our relative metrics. Things like win rates and so forth continue unabated, we generally expect to have the same outcome. >> Great, and then so let me go through some of the takeaways that I have from the quarter. I'll just run through them and we can go wherever you like. But the COVID snapback obviously is a key indicator. We saw that in international versus the US. >> Charlie: Right. >> New opportunities for growth. I want to talk about that, at some length the FlashArray//C object, the Cohesity pieces and other TAM expansion. The pipeline is very encouraging, but there's some uncertainty leading to your tepid guidance. Very strong, gross margins as usual. The subscription model is growing nicely. I want to hit on that. And the RPO, the remaining performance obligations grew to almost a billion dollars. That's a big number. New logo, solid at 20%. No real change in the competitive, but you called out, you'll see more PowerMax than PowerStore. That was really interesting. You're still hiring pretty aggressively, last quarter. And your technology investments continue. And I'll throw in the seven nines, which I think is another industry first, but where do you want to go there? >> Yeah, well, seven nines is a reliability figure for those of your audience that doesn't know. It relates to how much uptime or availability a product has or in our case, fleet of products. We have tens of thousands of arrays in the field. And last quarter we achieved what's called seven nines, which is the equivalent across the fleet of only three seconds of downtime per array per year. Which is, most other vendors had struggled to stay to five nines. And that's typically without even counting what they call scheduled downtime for upgrades. We don't even count that. We count all downtime of any type. So we're clearly, I think with no doubt, we're the most reliable product on the these days. >> So I want to come back to the TAM discussion because you, I inferred many opportunities for you guys to continue to grow. I mean, it's Flash, it's still about flash. flash is gaining share relative to spinning disk and relative to hybrid, you guys made that point a lot. FlashArray//C, you sound pretty happy with that, again, going after hybrid. And then this notion of bringing file services and object that unify play. kind of the man made great strides years ago with that capability. And then the data protection piece, the recovery with Cohesity, the faster recovery. That's another TAM expansion. So really, I identified four points of potential growth area for you over the next several years. I wonder if you could talk about that? >> Absolutely, we do feel very positive about all these areas. These areas open up a huge amount of the TAM that we didn't play in before. So FlashArray//C for example, as you say, flash was always a primary workload environment for flash 'cause it was very expensive compared to disc. Higher performance, better ecological footprint, denser, faster, cheaper, are more expensive though. So it only went after primary workload, but the vast majority of data storage is secondary workload. Things that don't require the high performance and therefore customers want it less expensive. And of course there were even more bits there. But FlashArray//C now competes very well with low cost disc, which is amazing. And of course it's 10 times lower footprint and 10 times more reliable. So this is the first and literally today only product that has all-flash in that secondary workload market. So just opens up a huge amount for us. And then, yes, I love talking about data protection for the following reason, customers actually don't want to do a backup, right? If you think about it, what they really want is recovery. Backup is what you have to do in order to get recovery. And these backup systems have been very good at backup, but usually can take 24 or 48 or even more hours to be able to recover from a failure. And now with ransomware, you don't want your website to be down for days before it comes back up. You don't want your traders not trading for days. It costs a lot of money. And with what we call rapid recovery and now flash recover, we can have companies come back within an hour or two at most, with a rapid recovery solution. And so the integrated solution that we've put together with Cohesity, allows customers to very quickly get up and running with an anti ransomware solution that allows them to get back up and operating in no time at all. >> Well, was interesting to see you choosing the partner route. I mean, you could have, if you remember EMC in the day. They bought in, data protection and it had actually worked out pretty well for them. You look at a company like NetApp, they've chosen not to vertically integrate with backup. You're choosing the same path. What's the thinking there? Stick to your knitting and partner up and add value where you can? >> Yeah, we have strong partnerships actually with all of the data backup players, Veritas Veeam, with Rubrik and others. In many cases, customers have already made their decision who their backup player is. Also, backup is actually a very relatively fragmented market. There's backup for different types of applications and different vendors have strengths and weaknesses in each one of those. And so our partnership across the backup board is very important to us. We did see however customers wanting an integrated solution, which we have, let's say initiated with Cohesity. But we believe it's the first of what will be multiple pure validated designs. Not all of which will be OEM, but all of which will be available as integrated systems in the market, through our channel partners. And so you can expect to see more of these as we go forward. >> So kind of the PVDs okay. I want to ask you about your subscription model. I mean, it's growing very nicely. Are there nuances there just in terms of understanding the income statement ie, product revenue was down, subscriptions growing. Are you going through that transition and having to sort of educate people on the impact on the income statement? You didn't make a big deal out of that on the Earnings Call and I thought, well, maybe I'm overstating that, but I wonder if you could talk about that dynamic? >> No, no, you're absolutely correct. And there is some of that going on on the earning statement. The bigger part, though, of let's say the lower growth this quarter was due, and the forecast was due to the pandemic. No doubt and especially in the US, especially hard hit in the US. But simultaneously we are going through the transition that many companies have had to go through in the past where a larger proportion over time of our sales are going to be what we call Pure as-a-Service and our unified subscription. So moving to subscription from CapEx. And whenever you do that, it takes a while, even though your sales, as in bookings, can stay in the growth path. The revenue takes a while to catch up as your subscription bookings grow. So there is some of that going on on our P and L as well. >> Yeah, well, it's the nirvana to the extent you can get that model. And of course your RPO is a good indication of you got a nice backlog that's yielding, that's certainty in revenue. >> That's correct. And the RPO is very nice and it reflects the fact that we have multi-year contracts going in with customers who are choosing Pure as-a-Service in Evergreen. And of course, the billing only reflects what we've actually built them for. >> I was struck by your comments regarding your main competitor, which is Dell, Dell EMC. Now, of course, in the early days of Pure, I've always said you guys drove a truck through the old VNX and symmetrics base. You said you're seeing PowerMax more than you're seeing PowerStore. That was interesting and somewhat surprising to me. >> Yeah, well, a standard play of Dell is to offer VMAX because it's less expensive versus our FlashArray. And then when the customer clearly says, well, it's just not performance enough or it just can't do the work that we need, then they'll offer PowerMax at a supposedly a deep discount to be able to compete with a FlashArray. So that's been a favorite tactic of theirs for quite some time. We maintain our win rates against that. PowerStore on the other hand, remember, it's a forklift upgrade with a new product on four different Dell existing products, right? And two things. One, is customers are just reluctant right now to try new things, right? They don't have the time to be able to test them properly. But I also think there's some reluctance even on Dell's part to put those properties up for grabs right now, when customers are more risk adverse. So, we continue, as I said, we are not seeing it as much as we had thought we might going into this. >> Yeah, we'll definitely find out more tomorrow. And I would expect that, to the extent that you're having more and more success in file, you're going to obviously run into NetApp more. >> Yeah, and that's what we're expecting. The file services on FlashArray//C really allow us to start to penetrate the general purpose file market. Clearly not on the very small, and we're not going after the very small market. We're going after the data center file share market on this and the Tier 2 workloads. >> Well, what's the early returns there? I mean, you saw the NetApp did the SolidFire acquisition to shore up NetApp kind of missed flash, and then bought SolidFire but that is obviously a good play. Do you feel like it's a tougher road than perhaps the old EMC install base or what are you seeing early on? >> Well, there's a lot of maturity obviously in files. And it will take us a while to be able to get up to full levels of maturity in files. But what customers love about us is our simplicity. And our file services on FlashArray is just as simple as our block services on FlashArray. And I think what customers are going to find is a very performant product that requires very little maintenance, very little tuning to meet their needs. And I think they're just going to appreciate the fact that it's a true fully capable block product with a fully capable set of file services. And that they'll be able to consolidate more and more of their use cases onto smaller and smaller footprint. So I think that's what they're going to appreciate about what we do. >> That's ironic, outsimplifying NetApp, which of course made its name, taken on guys like ASPEX for those of you remember that or even even the early day. So that's good. And I'd be remiss if I didn't ask you about cloud. Thinking on cloud, I know it's early days and I know most of your subscriptions of course are still with on-prem, but you made an interesting announcement last year to accelerate with Cloud Block Store running on AWS. How's the uptake been there? What can you tell us about that? >> Yeah, we're seeing a good uptake there. I'd say more of it is in the DevOps environment than in the actual NDR, disaster recovery, more than it is in transition of primary workloads into the cloud. And we're just seeing a bit less of that than one would expect given all the press around it. I don't think it's us. I think customers are just taking a while. They're focusing their new activities in the cloud and much less about transitioning existing environments. But we are seeing work done there. What we are seeing is a huge uptake in what we call our unified subscription, which is a Pure as-a-Service on-prem where we deliver to our customers, basically cloud, the equivalent from their point of view of cloud storage on-prem, where we manage the entire environment plus the unified subscription is that plus Cloud Block Store. So regardless of where our customers want to place their data, either on-prem or in the cloud, it's the same price and the same contract, same interface, same management to them. So we've seen a huge, I mean, literally an incredible spike in uptake in that. >> Great, thank you for that. And then I got to end with, I asked you last time about networking. You have a, a very wide observation space and a lot of expertise in a lot of different areas. So I want to ask you about, we've seen the spate of IPOs this week. Snowflake came , Palantir, UniFi, JFrog, number of others. Very interesting to see that in the Valley, you're in the Valley. Of course you shot in the Valley like everybody else these days, but what do you make of that? Is it kind of everybody trying to get in before the election? Or is it just a really good time? What's your take on that? >> I think a lot of it is getting in before the election, but a lot of stock market movements as you well know, has to do with cash flows more than it has to do with the prospects of individual companies and just given the amount of stimulus that's taking place, not just in US but worldwide. There's a lot of money floating around, which is boiling stock market prices. And so it's a great, an old colleague of mine had a saying, "When Monday's on sale, take it." And that seems to be the case right now, at least as far as the stock market is concerned. And I've stood there for a good time for IPOs. >> Well, the Palantir IPO took a swipe at Silicon Valley broadly, really targeting, I think Facebook and Google. It really doesn't have anything to do with your business, but I mean, I think as an executive in Silicon Valley, you see the innovation and the software development that's going into so many good things. I was struck by that though. I thought it was a little bit of a cheap shot at Silicon Valley. It really was aimed at Google and Facebook because there's so many companies from you guys, Cisco, Palo Alto Networks, it'll work on and on and on. They are just doing some great software work. And we're seeing that with COVID, where would we be without Big Tech? >> Well, thank you, Dave. I think the press tends to focus on the consumer companies. And we all have maybe our own individual opinions about the way they operate, but you're correct. I mean, I think the good foundational work that many companies in Silicon Valley are doing to make our lives easier every day, just continues to really impress. >> Well, Charles Giancarlo it's always a pleasure. Thanks so much. You're generous with your time. I really appreciate you coming on theCUBE. >> Thank you, Dave. Again, as you said, always a pleasure to speak with you and look forward to doing it next quarter. >> All right, us as well. And thank you for watching everybody. This is Dave Vellante for theCUBE. We'll see you next time, we're out. (bright upbeat music)