(upbeat music) >> Today more than ever before, organizations are striving to gain a competitive advantage, deliver more value to customers, reduce risk, and respond more quickly to the needs of businesses. Now, to achieve these goals, organizations need easy access to a single view of accurate, consistent and very importantly, trusted data. If it's not trusted, nobody's going to use it and all in near real time. However, the growing volumes and complexities of data make this difficult to achieve in practice. Not to mention the organizational challenges that have evolved as data becomes increasingly important to winning in the marketplace. Specifically as data grows, so does the prevalence of data silos, making, integrating and leveraging data from internal and external sources a real challenge. Now, in this final segment, we'll hear from Joe Lichtenberg who's the global head of product and industry marketing, and he's going to discuss how smart data fabrics can be applied to different industries. And by way of these use cases, we'll probe Joe's vast knowledge base and ask him to highlight how InterSystems, which touts a next gen approach to Customer 360, how the company leverages a smart data fabric to provide organizations of varying sizes and sectors in financial services, supply chain, logistics and healthcare with a better, faster and easier way to deliver value to the business. Joe welcome, great to have you here. >> Thank you, it's great to be here. That was some intro. I could not have said it better myself, so thank you for that. >> Thank you. Well, we're happy to have you on this show now. I understand- >> It's great to be here. >> You you've made a career helping large businesses with technology solutions, small businesses, and then scale those solutions to meet whatever needs they had. And of course, you're a vocal advocate as is your company of data fabrics. We talked to Scott earlier about data fabrics, how it relates to data mesh big discussions in the industry. So tell us more about your perspective. >> Sure, so first I would say that I have been in this industry for a very long time so I've been like you, I'm sure, for decades working with customers and with technology, really to solve these same kinds of challenges. So for decades, companies have been working with lots and lots of data and trying to get business value to solve all sorts of different challenges. And I will tell you that I've seen many different approaches and different technologies over the years. So, early on, point to point connections with custom coding, and I've worked with integration platforms 20 years ago with the advent of web services and service-oriented architectures and exposing endpoints with wisdom and getting access to disparate data from across the organization. And more recently, obviously with data warehouses and data lakes and now moving workloads to the cloud with cloud-based data marts and data warehouses. Lots of approaches that I've seen over the years but yet still challenges remain in terms of getting access to a single trusted real-time view of data. And so, recently, we ran a survey of more than 500 different business users across different industries and 86% told us that they still lack confidence in using their data to make decisions. That's a huge number, right? And if you think about all of the work and all of the technology and approaches over the years, that is a surprising number and drilling into why that is, there were three main reasons. One is latency. So the amount of time that it takes to access the data and process the data and make it fit for purpose by the time the business has access to the data and the information that they need, the opportunity has passed. >> Elapsed time, not speed a light, right? But that too maybe. >> But it takes a long time if you think about these processes and you have to take the data and copy it and run ETL processes and prepare it. So that's one, one is just the amount of data that's disparate in data silos. So still struggling with data that is dispersed across different systems in different formats. And the third, is data democratization. So the business really wants to have access to the data so that they can drill into the data and ask ad hoc questions and the next question and drill into the information and see where it leads them rather than having sort of pre-structured data and pre-structured queries and having to go back to IT and put the request back on the queue again and waiting. >> So it takes too long, the data's too hard to get to 'cause it's in silos and the data lacks context because it's technical people that are serving up the data to the business people. >> Exactly. >> And there's a mismatch. >> Exactly right. So they call that data democratization or giving the business access to the data and the tools that they need to get the answers that they need in the moment. >> So the skeptic in me, 'cause you're right I have seen this story before and the problems seem like they keep coming up, year after year, decade after decade. But I'm an optimist and so. >> As am I. >> And so I sometimes say, okay, same wine new bottle, but it feels like it's different this time around with data fabrics. You guys talk about smart data fabrics from your perspective, what's different? >> Yeah, it's very exciting and it's a fundamentally different approach. So if you think about all of these prior approaches, and by the way, all of these prior approaches have added value, right? It's not like they were bad, but there's still limitations and the business still isn't getting access to all the data that they need in the moment, right? So data warehouses are terrific if you know the questions that you want answered and you take the data and you structure the data in advance. And so now you're serving the business with sort of pre-planned answers to pre-planned queries, right? The data fabric, what we call a smart data fabric is fundamentally different. It's a fundamentally different approach in that rather than sort of in batch mode, taking the data and making it fit for purpose with all the complexity and delays associated with it, with a data fabric where accessing the data on demand as it's needed, as it's requested, either by the business or by applications or by the data scientists directly from the source systems. >> So you're not copying it necessarily to that to make that you're not FTPing it, for instance. I've got it, you take it, you're basically using the same source. >> You're pulling the data on demand as it's being requested by the consumers. And then all of the data management processes that need to be applied for integration and transformation to get the data into a consistent format and business rules and analytic queries. And with Jess showed with machine learning, predictive prescriptive analytics all sorts of powerful capabilities are built into the fabric so that as you're pulling the data on demand, right, all of these processes are being applied and the net result is you're addressing these limitations around latency and silos that we've seen in the past. >> Okay, so you've talked about you have a lot of customers, InterSystems does in different industries supply chain, financial services, manufacturing. We heard from just healthcare. What are you seeing in terms of applications of smart data fabrics in the real world? >> Yeah, so we see it in every industry. So InterSystems, as you know, has been around now for 43 years, and we have tens of thousands of customers in every industry. And this architectural pattern now is providing value for really critical use cases in every industry. So I'm happy to talk to you about some that we're seeing. I could actually spend like three hours here and there but I'm very passionate about working with customers and there's all sorts of exciting. >> What are some of your favorites? >> So, obviously supply chain right now is going through a very challenging time. So the combination of what's happening with the pandemic and disruptions and now I understand eggs are difficult to come by I just heard on NPR. >> Yeah and it's in part a data problem and a big part of data problem, is that fair? >> Yeah and so, in supply chain, first there's supply chain visibility. So organizations want a real time or near real time expansive view of what's happening across the entire supply chain from a supply all the way through distribution, right? So that's only part of the issue but that's a huge sort of real-time data silos problem. So if you think about your extended supply chain, it's complicated enough with all the systems and silos inside your firewall, before all of your suppliers even just thinking about your tier one suppliers let alone tier two and tier three. And then building on top of real-time visibility is what the industry calls a control tower, what we call the ultimate control tower. And so it's built in analytics to be able to sense disruptions and exceptions as they occur and predict the likelihood of these disruptions occurring. And then having data driven and analytics driven guidance in terms of the best way to deal with these disruptions. So for example, an order is missing line items or a cargo ship is stuck off port somewhere. What do you do about it? Do you reroute a different cargo ship, right? Do you take an order that's en route to a different client and reroute that? What's the cost associated? What's the impact associated with it? So that's a huge issue right now around control towers for supply chain. So that's one. >> Can I ask you a question about that? Because you and I have both seen a lot but we've never seen, at least I haven't the economy completely shut down like it was in March of 2020, and now we're seeing this sort of slingshot effect almost like you're driving on the highway sometimes you don't know why, but all of a sudden you slow down and then you speed up, you think it's okay then you slow down again. Do you feel like you guys can help get a handle on that product because it goes on both sides. Sometimes you can't get the product, sometimes there's too much of a product as well and that's not good for business. >> Yeah, absolutely. You want to smooth out the peaks and valleys. >> Yeah. >> And that's a big business goal, business challenge for supply chain executives, right? So you want to make sure that you can respond to demand but you don't want to overstock because there's cost associated with that as well. So how do you optimize the supply chains and it's very much a data silo and a real time challenge. So it's a perfect fit for this new architectural pattern. >> All right, what else? >> So if we look at financial services, we have many, many customers in financial services and that's another industry where they have many different sources of data that all have information that organizations can use to really move the needle if they could just get to that single source of truth in real time. So we sort of bucket many different implementations and use cases that we do around what we call Business 360 and Customer 360. So Business 360, there's all sorts of ways to add business value in terms of having a real-time operational view across all of the different GOs and parts of the business, especially in these very large global financial services institutions like capital markets and investment firms and so forth. So around Business 360, having a realtime view of risk, operational performance regulatory compliance, things like that. Customer 360, there's a whole set of use cases around Customer 360 around hyper-personalization of customers and in realtime next best action looking to see how you can sell more increase share of wallet, cross-sell, upsell to customers. We also do a lot in terms of predicting customer churn. So if you have all the historical data and what's the likelihood of customers churning to be able to proactively intercede, right? It's much more cost effective to keep assets under management and keep clients rather than going and getting new clients to come to the firm. A very interesting use case from one of our customers in Latin America, so Banco do Brasil largest bank in all of Latin America and they have a very innovative CTO who's always looking for new ways to move the needle for the bank. And so one of their ideas and we're working with them to do this is how can they generate net new revenue streams by bringing in new business to the bank? And so they identified a large percentage of the population in Latin America that does no banking. So they have no banking history not only with Banco do Brasil, but with any bank. So there's a fair amount of risk associated with offering services to this segment of the population that's not associated with any banks or financial institutions. >> There is no historical data on them, there's no. >> So it's a data challenge. And so, they're bringing in data from a variety of different sources, social media, open source data that they find online and so forth. And with us running risk models to identify which are the citizens that there's acceptable risk to offer their services. >> It's going to be huge market of unbanked people in vision Latin America. >> Wow, that's interesting. >> Yeah, yeah, totally vision. >> And if you can lower the risk and you could tap that market and be first >> And they are, yeah. >> Yeah. >> So very exciting. Manufacturing, we know industry 4.0 which is about taking the OT data, so the data from the MES systems and the streaming data, real-time streaming data from the machine controllers and integrating it with the IT data, so your data warehouses and your ERP systems and so forth to have not only a real-time view of manufacturing from supply and source all the way through demand but also predictive maintenance and things like that. So that's very big right now in manufacturing. >> Kind of cool to hear these use cases beyond your healthcare, which is obviously, your wheelhouse, Scott defined this term of smart data fabrics, different than data fabrics, I guess. So when we think about these use cases what's the value add of so-called smart data fabrics? >> Yeah, it's a great question. So we did not define the term data fabric or enterprise data fabric. The analysts now are all over it. They're all saying it's the future of data management. It's a fundamentally different approach this architectural approach to be able to access the data on demand. The canonical definition of a data fabric is to access the data where it lies and apply a set of data management processes, but it does not include analytics, interestingly. And so we firmly believe that most of these use cases gain value from having analytics built directly into the fabric. So whether that's business rules or predictive analytics to predict the likelihood of a customer churn or a machine on the shop floor failing or prescriptive analytics. So if there's a problem in the supply chain, what's the guidance for the supply chain managers to take the best action, right? Prescriptive analytics based on data. So rather than taking the data and the data fabric and moving it to another environment to run those analytics where you have complexity and latency, having tall of those analytics capabilities built directly into the fabric, which is why we call it a smart data fabric, brings a lot of value to our customers. >> So simplifies the whole data lifecycle, data pipelining, the hyper-specialized roles that you have to have, you can really just focus on one platform, is that? >> Exactly, basically, yeah. And it's a simplicity of architecture and faster speed to production. So a big differentiator for our technology, for InterSystems, Iris, is most if not all of the capabilities that are needed are built into one engine, right? So you don't need to stitch together 10 or 15 or 20 different data management services for relational database in a non-relational database and a caching layer and a data warehouse and security and so forth. And so you can do that. There's many ways to build this data fabric architecture, right? InterSystems is not the only way. >> Right? >> But if you can speed and simplify the implementation of the fabric by having most of what you need in one engine, one product that gets you to where you need to go much, much faster. >> Joe, how can people learn more about smart data Fabric some of the use cases that you've presented here? >> Yeah, come to our website, intersystems.com. If you go to intersystems.com/smartdatafabric that'll take you there. >> I know that you have like probably dozens more examples but it would be cool- >> I do. >> If people reach out to you, how can they get in touch? >> Oh, I would love that. So feel free to reach out to me on LinkedIn. It's Joe Lichtenberg I think it's linkedin.com/joeLichtenberg and I'd love to connect. >> Awesome. Joe, thanks so much for your time. Really appreciate it. >> It was great to be here. Thank you, Dave. >> All right, I hope you've enjoyed our program today. You know, we heard Scott now he helped us understand this notion of data fabrics and smart data fabrics and how they can address the data challenges faced by the vast majority of organizations today. Jess Jody's demo was awesome. It was really a highlight of the program where she showed the smart data fabrics inaction and Joe Lichtenberg, we just heard from him dug in to some of the prominent use cases and proof points. We hope this content was educational and inspires you to action. Now, don't forget all these videos are available on Demand to watch, rewatch and share. Go to theCUBE.net, check out siliconangle.com for all the news and analysis and we'll summarize the highlights of this program and go to intersystems.com because there are a ton of resources there. In particular, there's a knowledge hub where you'll find some excellent educational content and online learning courses. There's a resource library with analyst reports, technical documentation videos, some great freebies. So check it out. This is Dave Vellante. On behalf of theCUBE and our supporter, InterSystems, thanks for watching and we'll see you next time. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

>>Hey everyone. Welcome back to Las Vegas. It's the Cube live at AWS Reinvent 2022. This is our fourth day of coverage. Lisa Martin here with Paul Gillen. Paul, we started Monday night, we filmed and streamed for about three hours. We have had shammed pack days, Tuesday, Wednesday, Thursday. What's your takeaway? >>We're routed final turn as we, as we head into the home stretch. Yeah. This is as it has been since the beginning, this show with a lot of energy. I'm amazed for the fourth day of a conference, how many people are still here I am too. And how, and how active they are and how full the sessions are. Huge. Proud for the keynote this morning. You don't see that at most of the day four conferences. Everyone's on their way home. So, so people come here to learn and they're, and they're still >>Learning. They are still learning. And we're gonna help continue that learning path. We have an alumni back with us, Toron joins us, the CPO and co-founder of Dremeo. Tomer, it's great to have you back on the program. >>Yeah, thanks for, for having me here. And thanks for keeping the, the best session for the fourth day. >>Yeah, you're right. I like that. That's a good mojo to come into this interview with Tomer. So last year, last time I saw you was a year ago here in Vegas at Reinvent 21. We talked about the growth of data lakes and the data lake houses. We talked about the need for open data architectures as opposed to data warehouses. And the headline of the Silicon Angle's article on the interview we did with you was, Dremio Predicts 2022 will be the year open data architectures replace the data warehouse. We're almost done with 2022. Has that prediction come true? >>Yeah, I think, I think we're seeing almost every company out there, certainly in the enterprise, adopting data lake, data lakehouse technology, embracing open source kind of file and table formats. And, and so I think that's definitely happening. Of course, nothing goes away. So, you know, data warehouses don't go away in, in a year and actually don't go away ever. We still have mainframes around, but certainly the trends are, are all pointing in that direction. >>Describe the data lakehouse for anybody who may not be really familiar with that and, and what it's, what it really means for organizations. >>Yeah. I think you could think of the data lakehouse as the evolution of the data lake, right? And so, you know, for, for, you know, the last decade we've had kind of these two options, data lakes and data warehouses and, you know, warehouses, you know, having good SQL support, but, and good performance. But you had to spend a lot of time and effort getting data into the warehouse. You got locked into them, very, very expensive. That's a big problem now. And data lakes, you know, more open, more scalable, but had all sorts of kind of limitations. And what we've done now as an industry with the Lake House, and especially with, you know, technologies like Apache Iceberg, is we've unlocked all the capabilities of the warehouse directly on object storage like s3. So you can insert and update and delete individual records. You can do transactions, you can do all the things you could do with a, a database directly in kind of open formats without getting locked in at a much lower cost. >>But you're still dealing with semi-structured data as opposed to structured data. And there's, there's work that has to be done to get that into a usable form. That's where Drio excels. What, what has been happening in that area to, to make, I mean, is it formats like j s o that are, are enabling this to happen? How, how we advancing the cause of making semi-structured data usable? Yeah, >>Well, I think first of all, you know, I think that's all changed. I think that was maybe true for the original data lakes, but now with the Lake house, you know, our bread and butter is actually structured data. It's all, it's all tables with the schema. And, you know, you can, you know, create table insert records. You know, it's, it's, it's really everything you can do with a data warehouse you can now do in the lakehouse. Now, that's not to say that there aren't like very advanced capabilities when it comes to, you know, j s O and nested data and kind of sparse data. You know, we excel in that as well. But we're really seeing kind of the lakehouse take over the, the bread and butter data warehouse use cases. >>You mentioned open a minute ago. Talk about why it's, why open is important and the value that it can deliver for customers. >>Yeah, well, I think if you look back in time and you see all the challenges that companies have had with kind of traditional data architectures, right? The, the, the, a lot of that comes from the, the, the problems with data warehouses. The fact that they are, you know, they're very expensive. The data is, you have to ingest it into the data warehouse in order to query it. And then it's almost impossible to get off of these systems, right? It takes an enormous effort, tremendous cost to get off of them. And so you're kinda locked in and that's a big problem, right? You also, you're dependent on that one data warehouse vendor, right? You can only do things with that data that the warehouse vendor supports. And if you contrast that to data lakehouse and open architectures where the data is stored in entirely open formats. >>So things like par files and Apache iceberg tables, that means you can use any engine on that data. You can use s SQL Query Engine, you can use Spark, you can use flin. You know, there's a dozen different engines that you can use on that, both at the same time. But also in the future, if you ever wanted to try something new that comes out, some new open source innovation, some new startup, you just take it and point out the same data. So that data's now at the core, at the center of the architecture as opposed to some, you know, vendors logo. Yeah. >>Amazon seems to be bought into the Lakehouse concept. It has big announcements on day two about eliminating the ETL stage between RDS and Redshift. Do you see the cloud vendors as pushing this concept forward? >>Yeah, a hundred percent. I mean, I'm, I'm Amazon's a great, great partner of ours. We work with, you know, probably 10 different teams there. Everything from, you know, the S3 team, the, the glue team, the click site team, you know, everything in between. And, you know, their embracement of the, the, the lake house architecture, the fact that they adopted Iceberg as their primary table format. I think that's exciting as an industry. We're all coming together around standard, standard ways to represent data so that at the end of the day, companies have this benefit of being able to, you know, have their own data in their own S3 account in open formats and be able to use all these different engines without losing any of the functionality that they need, right? The ability to do all these interactions with data that maybe in the past you would have to move the data into a database or, or warehouse in order to do, you just don't have to do that anymore. Speaking >>Of functionality, talk about what's new this year with drio since we've seen you last. >>Yeah, there's a lot of, a lot of new things with, with Drio. So yeah, we now have full Apache iceberg support, you know, with DML commands, you can do inserts, updates, deletes, you know, copy into all, all that kind of stuff is now, you know, fully supported native part of the platform. We, we now offer kind of two flavors of dr. We have, you know, Dr. Cloud, which is our SaaS version fully hosted. You sign up with your Google or, you know, Azure account and, and, and you're up in, you're up and running in, in, in a minute. And then dral software, which you can self host usually in the cloud, but even, even even outside of the cloud. And then we're also very excited about this new idea of data as code. And so we've introduced a new product that's now in preview called Dr. >>Arctic. And the idea there is to bring the concepts of GI or GitHub to the world of data. So things like being able to create a branch and work in isolation. If you're a data scientist, you wanna experiment on your own without impacting other people, or you're a data engineer and you're ingesting data, you want to transform it and test it before you expose it to others. You can do that in a branch. So all these ideas that, you know, we take for granted now in the world of source code and software development, we're bringing to the world of data with Jamar. And when you think about data mesh, a lot of people talking about data mesh now and wanting to kind of take advantage of, of those concepts and ideas, you know, thinking of data as a product. Well, when you think about data as a product, we think you have to manage it like code, right? You have to, and that's why we call it data as code, right? The, all those reasons that we use things like GI have to build products, you know, if we wanna think of data as a product, we need all those capabilities also with data. You know, also the ability to go back in time. The ability to undo mistakes, to see who changed my data and when did they change that table. All of those are, are part of this, this new catalog that we've created. >>Are you talk about data as a product that's sort of intrinsic to the data mesh concept. Are you, what's your opinion of data mesh? Is the, is the world ready for that radically different approach to data ownership? >>You know, we are now in dozens of, dozens of our customers that are using drio for to implement enterprise-wide kind of data mesh solutions. And at the end of the day, I think it's just, you know, what most people would consider common sense, right? In a large organization, it is very hard for a centralized single team to understand every piece of data, to manage all the data themselves, to, you know, make sure the quality is correct to make it accessible. And so what data mesh is first and foremost about is being able to kind of federate the, or distribute the, the ownership of data, the governance of the data still has to happen, right? And so that is, I think at the heart of the data mesh, but thinking of data as kind of allowing different teams, different domains to own their own data to really manage it like a product with all the best practices that that we have with that super important. >>So we we're doing a lot with data mesh, you know, the way that cloud has multiple projects and the way that Jamar allows you to have multiple catalogs and different groups can kind of interact and share data among each other. You know, the fact that we can connect to all these different data sources, even outside your data lake, you know, with Redshift, Oracle SQL Server, you know, all the different databases that are out there and join across different databases in addition to your data lake, that that's all stuff that companies want with their data mesh. >>What are some of your favorite customer stories that where you've really helped them accelerate that data mesh and drive business value from it so that more people in the organization kind of access to data so they can really make those data driven decisions that everybody wants to make? >>I mean, there's, there's so many of them, but, you know, one of the largest tech companies in the world creating a, a data mesh where you have all the different departments in the company that, you know, they, they, they were a big data warehouse user and it kinda hit the wall, right? The costs were so high and the ability for people to kind of use it for just experimentation, to try new things out to collaborate, they couldn't do it because it was so prohibitively expensive and difficult to use. And so what they said, well, we need a platform that different people can, they can collaborate, they can ex, they can experiment with the data, they can share data with others. And so at a big organization like that, the, their ability to kind of have a centralized platform but allow different groups to manage their own data, you know, several of the largest banks in the world are, are also doing data meshes with Dr you know, one of them has over over a dozen different business units that are using, using Dremio and that ability to have thousands of people on a platform and to be able to collaborate and share among each other that, that's super important to these >>Guys. Can you contrast your approach to the market, the snowflakes? Cause they have some of those same concepts. >>Snowflake's >>A very closed system at the end of the day, right? Closed and very expensive. Right? I think they, if I remember seeing, you know, a quarter ago in, in, in one of their earnings reports that the average customer spends 70% more every year, right? Well that's not sustainable. If you think about that in a decade, that's your cost is gonna increase 200 x, most companies not gonna be able to swallow that, right? So companies need, first of all, they need more cost efficient solutions that are, you know, just more approachable, right? And the second thing is, you know, you know, we talked about the open data architecture. I think most companies now realize that the, if you want to build a platform for the future, you need to have the data and open formats and not be locked into one vendor, right? And so that's kind of another important aspect beyond that's ability to connect to all your data, even outside the lake to your different databases, no sequel databases, relational databases, and drs semantic layer where we can accelerate queries. And so typically what you have, what happens with data warehouses and other data lake query engines is that because you can't get the performance that you want, you end up creating lots and lots of copies of data. You, for every use case, you're creating a, you know, a pre-joy copy of that data, a pre aggregated version of that data. And you know, then you have to redirect all your data. >>You've got a >>Governance problem, individual things. It's expensive. It's expensive, it's hard to secure that cuz permissions don't travel with the data. So you have all sorts of problems with that, right? And so what we've done because of our semantic layer that makes it easy to kind of expose data in a logical way. And then our query acceleration technology, which we call reflections, which transparently accelerates queries and gives you subsecond response times without data copies and also without extracts into the BI tools. Cause if you start doing bi extracts or imports, again, you have lots of copies of data in the organization, all sorts of refresh problems, security problems, it's, it's a nightmare, right? And that just collapsing all those copies and having a, a simple solution where data's stored in open formats and we can give you fast access to any of that data that's very different from what you get with like a snowflake or, or any of these other >>Companies. Right. That, that's a great explanation. I wanna ask you, early this year you announced that your Dr. Cloud service would be a free forever, the basic DR. Cloud service. How has that offer gone over? What's been the uptake on that offer? >>Yeah, it, I mean it is, and thousands of people have signed up and, and it's, I think it's a great service. It's, you know, it's very, very simple. People can go on the website, try it out. We now have a test drive as well. If, if you want to get started with just some sample public sample data sets and like a tutorial, we've made that increasingly easy as well. But yeah, we continue to, you know, take that approach of, you know, making it, you know, making it easy, democratizing these kind of cloud data platforms and, and kinda lowering the barriers to >>Adoption. How, how effective has it been in driving sales of the enterprise version? >>Yeah, a lot of, a lot of, a lot of business with, you know, that, that we do like when it comes to, to selling is, you know, folks that, you know, have educated themselves, right? They've started off, they've followed some tutorials. I think generally developers, they prefer the first interaction to be with a product, not with a salesperson. And so that's, that's basically the reason we did that. >>Before we ask you the last question, I wanna just, can you give us a speak peek into the product roadmap as we enter 2023? What can you share with us that we should be paying attention to where Drum is concerned? >>Yeah. You know, actually a couple, couple days ago here at the conference, we, we had a press release with all sorts of new capabilities that we, we we just released. And there's a lot more for, for the coming year. You know, we will shortly be releasing a variety of different performance enhancements. So we'll be in the next quarter or two. We'll be, you know, probably twice as fast just in terms of rock qu speed, you know, that's in addition to our reflections and our career acceleration, you know, support for all the major clouds is coming. You know, just a lot of capabilities in Inre that make it easier and easier to use the platform. >>Awesome. Tomer, thank you so much for joining us. My last question to you is, if you had a billboard in your desired location and it was going to really just be like a mic drop about why customers should be looking at Drio, what would that billboard say? >>Well, DRIO is the easy and open data lake house and, you know, open architectures. It's just a lot, a lot better, a lot more f a lot more future proof, a lot easier and a lot just a much safer choice for the future for, for companies. And so hard to argue with those people to take a look. Exactly. That wasn't the best. That wasn't the best, you know, billboards. >>Okay. I think it's a great billboard. Awesome. And thank you so much for joining Poly Me on the program, sharing with us what's new, what some of the exciting things are that are coming down the pipe. Quite soon we're gonna be keeping our eye Ono. >>Awesome. Always happy to be here. >>Thank you. Right. For our guest and for Paul Gillin, I'm Lisa Martin. You're watching The Cube, the leader in live and emerging tech coverage.

(light corporate music) >> Welcome back, everyone, to VMware Explore 22. I'm John Furrier, host of theCUBE with Dave Vellante. Our 12th year covering VMware's User Conference, formerly known as VMworld, now rebranded as VMware Explore. Two great cube alumnus coming down the cube. Ricky Cooper, SVP, Worldwide Partner Commercials VMware, great to see you. Thanks for coming on. >> Thank you. >> We just had a great chat- >> Good to see you again. >> With the Discovery and, of course, Joseph George, vice president of Compute Industry Alliances. Great to have you on. Great to see you. >> Great to see you, John. >> So guys this year is very curious in VMware. A lot goin' on, the name change, the event. Big, big move. Bold move. And then they changed the name of the event. Then Broadcom buys them. A lot of speculation, but at the end of the day, this conference kind of, people were wondering what would be the barometer of the event. We're reporting this morning on the keynote analysis. Very good mojo in the keynote. Very transparent about the Broadcom relationship. The expo floor last night was buzzing. >> Mhm. >> I mean, this is not a show that's lookin' like it's going to be, ya' know, going down. >> Yeah. >> This is clearly a wave. We're calling it Super Cloud. Multi-Cloud's their theme. Clearly the cloud's happenin'. We not to date ourselves, but 2013 we were discussing on theCUBE- >> We talked about that. Yeah. Yeah. >> Discover about DevOps infrastructure as code- >> Mhm. >> We're full realization now of that. >> Yep. >> This is where we're at. You guys had a great partnership with VMware and HPE. Talk about where you guys see this coming together because customers are refactoring. They are lookin' at Cloud Native. The whole Broadcom visibility to the VMware customer bases activated them. They're here and they're leaning in. >> Yeah. >> What's going on? >> Yeah. Absolutely. We're seeing a renewed interest now as customers are looking at their entire infrastructure, bottoms up, all the way up the stack, and the notion of a hybrid cloud, where you've got some visibility and control of your data and your infrastructure and your applications, customers want to live in that sort of a cloud environment and so we're seeing a renewed interest. A lot of conversations we're having with customers now, a lot of customers committing to that model where they have applications and workloads running at the Edge, in their data center, and in the public cloud in a lot of cases, but having that mobility, having that control, being able to have security in their own, you know, in their control. There's a lot that you can do there and, obviously, partnering with VMware. We've been partners for so long. >> 20 years about. Yeah. Yeah. >> Yeah. At least 20 years, back when they invented stuff, they were inventing way- >> Yeah. Yeah. Yeah. >> VMware's got a very technical culture, but Ricky, I got to say that, you know, we commented earlier when Raghu was on, the CEO, now CEO, I mean, legendary product. I sent the trajectory to VMware. Everyone knows that. VMware, I can't know whether to tell it was VMware or HP, HP before HPE, coined hybrid- >> Yeah. >> 'Cause you guys were both on. I can't recall, Dave, which company coined it first, but it was either one of you guys. Nobody else was there. >> It was the partnership. >> Yes. I- (cross talking) >> They had a big thing with Pat Gelsinger. Dave, remember when he said, you know, he got in my grill on theCUBE live? But now you see- >> But if you focus on that Multi-Cloud aspect, right? So you've got a situation where our customers are looking at Multi-Cloud and they're looking at it not just as a flash in the pan. This is here for five years, 10 years, 20 years. Okay. So what does that mean then to our partners and to our distributors? You're seeing a whole seed change. You're seeing partners now looking at this. So, look at the OEMs, you know, the ones that have historically been vSphere customers are now saying, they're coming in droves saying, okay, what is the next step? Well, how can I be a Multi-Cloud partner with you? >> Yep. Right. >> How can I look at other aspects that we're driving here together? So, you know, GreenLake is a great example. We keep going back to GreenLake and we are partaking in GreenLake at the moment. The real big thing for us is going to be, right, let's make sure that we've got the agreements in place that support this SaaS and subscription motion going forward and then the sky's the limit for us. >> You're pluggin' that right into GreenLake, right? >> Well, here's why. Here's why. So customers are loving the fact that they can go to a public cloud and they can get an SLA. They come to a, you know, an On-Premise. You've got the hardware, you've got the software, you've got the, you know, the guys on board to maintain this through its life cycle. >> Right. I mean, this is complicated stuff. >> Yeah. >> Now we've got a situation where you can say, hey, we can get an SLA On-Premise. >> Yeah. And I think what you're seeing is it's very analogous to having a financial advisor just manage your portfolio. You're taking care of just submitting money. That's really a lot of what the customers have done with the public cloud, but now, a lot of these customers are getting savvy and they have been working with VMware Technologies and HPE for so long. They've got expertise. They know how they want their workloads architected. Now, we've given them a model where they can leverage the Cloud platform to be able to do this, whether it's On-Premise, The Edge, or in the public cloud, leveraging HPE GreenLake and VMware. >> Is it predominantly or exclusively a managed service or do you find some customers saying, hey, we want to manage ourself? How, what are you seeing is the mix there? >> It is not predominantly managed services right now. We're actually, as we are growing, last time we talked to HPE Discover we talked about a whole bunch of new services that we've added to our catalog. It's growing by leaps and bounds. A lot of folks are definitely interested in the pay as you go, obviously, the financial model, but are now getting exposed to all the other management that can happen. There are managed services capabilities, but actually running it as a service with your systems On-Prem is a phenomenal idea for all these customers and they're opening their eyes to some new ways to service their customers better. >> And another phenomenon we're seeing there is where partners, such as HPA, using other partners for various areas of their services implementation as well. So that's another phenomenon, you know? You're seeing the resale motion now going into a lot more of the services motion. >> It's interesting too, you know, I mean, the digital modernization that's goin' on. The transformation, whatever you want to call it, is complicated. >> Yeah. >> That's clear. One of the things I liked about the keynote today was the concept of cloud chaos. >> Yeah. >> Because we've been saying, you know, quoting Andy Grove at Intel, "Let chaos rain and rain in the chaos." >> Mhm. >> And when you have inflection points, complexity, which is the chaos, needs to be solved and whoever solves it kicks the inflection point, that's up into the right. So- >> Prime idea right here. Yeah. >> So GreenLake is- >> Well, also look at the distribution model and how that's changed. A couple of points on a deal. Now they're saying, "I'll be your aggregator. I'll take the strain and I'll give you scale." You know? "I'll give you VMware Scale for all, you know, for all of the various different partners, et cetera." >> Yeah. So let's break this down because this is, I think, a key point. So complexity is good, but the old model in the Enterprise market was- >> Sure. >> You solve complexity with more complexity. >> Yeah. >> And everybody wins. Oh, yeah! We're locked in! That's not what the market wants. They want some self-service. They want, as a service, they want easy. Developer first security data ops, DevOps, is already in the cycle, so they're going to want simpler. >> Yeah. >> Easier. Faster. >> And this is kind of why I'll say, for the big announcement today here at VMware Explore, around the VMware vSphere Distributed Services Engine, Project Monterey- >> Yeah. >> That we've talked about for so long, HPE and VMware and AMD, with the Pensando DPU, actually work together to engineer a solution for exactly that. The capabilities are fairly straightforward in terms of the technologies, but actually doing the work to do integration, joint engineering, make sure that this is simple and easy and able to be running HPE GreenLake, that's- >> That's invested in Pensando, right? >> We are. >> We're all investors. Yeah. >> What's the benefit of that? What's, that's a great point you made. What's the value to the customer, bottom line? That deep co-engineering, co-partnering, what does it deliver that others don't do? >> Yeah. Well, I think one example would be, you know, a lot of vendors can say we support it. >> Yep. >> That's great. That's actually a really good move, supporting it. It can be resold. That's another great move. I'm not mechanically inclined to where I would go build my own car. I'll go to a dealership and actually buy one that I can press the button and I can start it and I can do what I need to do with my car and that's really what this does is the engineering work that's gone on between our two companies and AMD Pensando, as well as the business work to make that simple and easy, that transaction to work, and then to be able to make it available as a service, is really what made, it's, that's why it's such a winner winner with our- >> But it's also a lower cost out of the box. >> Yep. >> Right. >> So you get in whatever. Let's call it 20%. Okay? But there's, it's nuanced because you're also on a new technology curve- >> Right. >> And you're able to absorb modern apps, like, you know, we use that term as a bromide, but when I say modern apps, I mean data-rich apps, you know, things that are more AI-driven not the conventional, not that people aren't doing, you know, SAP and CRM, they are, but there's a whole slew of new apps that are coming in that, you know, traditional architectures aren't well-suited to handle from a price performance standpoint. This changes that doesn't it? >> Well, you think also of, you know, going to the next stage, which is to go to market between the two organizations that before. At the moment, you know, HPE's running off doing various different things. We were running off to it again, it's that chaos that you're talking about. In cloud chaos, you got to go to market chaos. >> Yeah. >> But by simplifying four or five things, what are we going to do really well together? How do we embed those in GreenLake- >> Mhm. >> And be known in the marketplace for these solutions? Then you get a, you know, an organization that's really behind the go to market. You can help with sales activation the enablement, you know, and then we benefit from the scale of HPE. >> Yeah. >> What are those solutions I mean? Is it just, is it I.S.? Is it, you know, compute storage? >> Yeah. >> Is it, you know, specific, you know, SAP? Is it VDI? What are you seeing out there? >> So right now, for this specific technology, we're educating our customers on what that could be and, at its core, this solution allows customers to take services that normally and traditionally run on the compute system and run on a DPU now with Project Monterey, and this is now allowing customers to think about, okay, where are their use cases. So I'm, rather than going and, say, use it for this, we're allowing our customers to explore and say, okay, here's where it makes sense. Where do I have workloads that are using a lot of compute cycles on services at the compute level that could be somewhere else like networking as a great example, right? And allowing more of those compute cycles to be available. So where there are performance requirements for an application, where there is timely response that's needed for, you know, for results to be able to take action on, to be able to get insight from data really quick, those are places where we're starting to see those services moving onto something like a DPU and that's where this makes a whole lot more sense. >> Okay. So, to get this right, you got the hybrid cloud, right? >> [Ricky And Joseph] Yes. >> You got GreenLake and you got the distributed engine. What's that called the- >> For, it's HPE ProLiant- >> ProLiant with- >> The VMware- >> With vSphere. >> That's the compute- >> Distributed. >> Okay. So does the customer, how do you guys implement that with the customer? All three at the same time or they mix and match? What's that? How does that work? >> All three of those components. Yeah. So the beauty of the HP ProLiant with VMware vSphere-distributed services engine- >> Mhm. >> Also known as Project Monterey for those that are keeping notes at home- >> Mhm. >> It's, again, already pre-engineered. So we've already worked through all the mechanics of how you would have to do this. So it's not something you have to go figure out how you build, get deployment, you know, work through those details. That's already done. It is available through HPE GreenLake. So you can go and actually get it as a service in partnership with our customer, our friends here at VMware, and because, if you're familiar and comfortable with all the things that HP ProLiant has done from a security perspective, from a reliability perspective, trusted supply chain, all those sorts of things, you're getting all of that with this particular (indistinct). >> Sumit Dhawan had a great quote on theCUBE just an hour or so ago. He said you have to be early to be first. >> Yeah. (laughing) >> I love that quote. Okay. So you were- >> I fought the urge. >> You were first. You were probably a little early, but do you have a lead? I know you're going to say yes, okay. Let's just- >> Okay. >> Let's just assume that. >> Okay. Yeah. >> Relative to the competition, how do you know? How do you determine that? >> If we have a lead or not? >> Yeah. If you lead. If you're the best. >> We go to the source of the truth which is our customers. >> And what do they tell you? What do you look at and say, okay, now, I mean, when you have that honest conversation and say, okay, we are, we're first, we're early. We're keeping our lead. What are the things that you- >> I'll say it this way. I'll say it this way. We've been in a lot of businesses where there, where we do compete head-to-head in a lot of places. >> Mhm. >> And we know how that sales process normally works. We're seeing a different motion from our customers. When we talk about HPE GreenLake, there's not a lot of back and forth on, okay, well, let me go shop around. It is HP Green. Let's talk about how we actually build this solution. >> And I can tell you, from a VMware perspective, our customers are asking us for this the other way around. So that's a great sign is that, hey, we need to see this partnership come together in GreenLake. >> Yeah. >> It's the old adage that Amazon used to coin and Andy Jassy, you know, they do the undifferentiated heavy lifting. >> [Ricky And Joseph] Yeah. >> A lot of that's now Cloud operations. >> Mhm. >> Underneath it is infrastructure's code to the developer. >> That's right. >> That's at scale. >> That's right. >> And so you got a lot of heavy lifting being done with GreenLake- >> Right. >> Which is why there's no objections probably. >> Right. >> What's the choice? What are you going to shop? >> Yeah. >> There's nothing to shop around. >> Yeah, exactly. And then we've got, you know, that is really icing on the cake that we've, you know, that we've been building for quite some time and there is an understanding in the market that what we do with our infrastructure is hardened from a reliability and quality perspective. Like, times are tough right now. Supply chain issues, all that stuff. We've talked, all talked about it, but at HPE, we don't skimp on quality. We're going to spend the dollars and time on making sure we got reliability and security built in. It's really important to us. >> We had a great use case. The storage team, they were provisioning with containers. >> Yes. >> Storage is a service instantly we're seeing with you guys with VMware. Your customers' bringing in a lot of that into the mix as well. I got to ask 'cause every event we talk about AI and machine learning- >> Mhm. >> Automation and DevOps are now infiltrating in with the CICD pipeline. Security and data become a big conversation. >> [Ricky And Joseph] Agreed. >> Okay. So how do you guys look at that? Okay. You sold me on Green. Like, I've been a big fan from day one. Now, it's got maturity on it. I know it's going to get a lot more headroom to do. There's still a lot of work to do, but directionally it's pretty accurate, you know? It's going to be a success. There's still concern about security, the data layer. That's agnostic of environment, private cloud, hybrid, public, and Edge. So that's important and security- >> Great. >> Has got a huge service area. >> Yeah. >> These are on working progress. >> Yeah. Yeah. >> How do you guys view those? >> I think you've just hit the net on the head. I mean, I was in the press and journalist meetings yesterday and our answer was exactly the same. There is still so much work that can be done here and, you know, I don't think anybody is really emerging as a true leader. It's just a continuation of, you know, tryin' to get that right because it is what is the most important thing to our customers. >> Right. >> And the industry is really sort of catching up to that. >> And, you know, when you start talking about privacy and when you, it's not just about company information. It's about individuals' information. It's about, you know, information that, if exposed, actually could have real impact on people. >> Mhm. >> So it's more than just an I.T. problem. It is actually, and from HPE's perspective, security starts from when we're picking our suppliers for our components. Like, there are processes that we put into our entire trusted supply chain from the factory on the way up. I liken it to my golf swing. My golf swing. I slice right like you wouldn't believe. (John laughing) But when I go to the golf pros, they start me back at the mechanics, the foundational pieces. Here's where the problems are and start workin' on that. So my view is, our view is, if your infrastructure is not secure, you're goin' to have troubles with security as you go further up. >> Stay in the sandbox. >> Yeah. >> Yeah. So to speak, you know, they're driving range on the golf analogy there. I love that. Talk about supply chain security real quick because you mentioned supply chain on the hardware side. You're seeing a lot of open source and supply chain in software, trusted software. >> Yep. >> How does GreenLake look at that? How do you guys view that piece of it? That's an important part. >> Yeah. Security is one of the key pillars that we're actually driving as a company right now. As I said, it's important to our customers as they're making purchasing decisions and we're looking at it from the infrastructure all the way up to the actual service itself and that's the beauty of having something like HPE GreenLake. We don't have to pick, is the infrastructure or the middle where, or the top of stack application- >> It's (indistinct), right? >> It's all of it. >> Yeah. >> It's all of it. That matters. >> Quick question on the ecosystem posture. So- >> Sure. >> I remember when HP was, you know, one company and then the GSIs were a little weird with HP because of EDS, you know? You had data protector so we weren't really chatting up Veeam at the time, right? And as soon as the split happened, ecosystem exploded. Now you have a situation where you, Broadcom, is acquiring VMware. You guys, big Broadcom customer. Has your attitude changed or has it not because, oh, we meet with the customers already. Well, you've always said that, but have you have leaned in more? I mean, culturally, is HPE now saying, hmm, now we have some real opportunities to partner in new ways that we don't have to sleep with one eye open, maybe. (John laughing) >> So first of all, VMware and HPE, we've got a variety of different partners. We always have. >> Mhm. >> Well before any Broadcom announcement came along. >> Yeah, sure. >> We've been working with a variety of partners. >> And that hasn't changed. >> And that hasn't changed. And, if your question is, has our posture toward VMware changed at all, the answer's absolutely not. We believe in what VMware is doing. We believe in what our customers are doing with VMware and we're going to continue to work with VMware and partner with the (indistinct). >> And of course, you know, we had to spin out ourselves in November of last year, which I worked on, you know, the whole Dell thing. >> Yeah. We still had the same chairman. >> Yeah. There- (Dave chuckling) >> Yeah, but since then, I think what's really become very apparent and not, it's not just with HPE, but with many of our partners, many of the OEM partners, the opportunity in front of us is vast and we need to rely on each other to help us as, you know, solve the customer problems that are out there. So there's a willingness to overlook some things that, in the past, may have been, you know, barriers. >> But it's important to note also that it's not that we have not had history- >> Yeah. >> Right? Over, we've got over 200,000 customers join- >> Hundreds of millions of dollars of business- >> 100,000, over 10,000, or 100,000 channel partners that we all have in common. >> Yeah. Yeah. >> Yep. >> There's numerous- >> And independent of the whole Broadcom overhang there. >> Yeah. >> There's the ecosystem floor. >> Yeah. >> The expo floor. >> Right. >> I mean, it's vibrant. I mean, there's clearly a wave coming, Ricky. We talked about this briefly at HPE Discover. I want to get an update from your perspectives, both of you, if you don't mind weighing in on this. Clearly, the wave, we're calling it the Super Cloud, 'cause it's not just Multi-Cloud. It's completely different looking successes- >> Smart Cloud. >> It's not just vendors. It's also the customers turning into clouds themselves. You look at Goldman Sachs and- >> Yep. >> You know, I think every vertical will have its own power law of Cloud players in the future. We believe that to be true. We're still testing that assumption, but it's trending in when you got OPEX- >> [Ricky And Joseph] Right. >> Has to go to in-fund statement- >> Yeah. >> CapEx goes too. Thanks for the Cloud. All that's good, but there's a wave coming- >> Yeah. >> And we're trying to identify it. What do you guys see as this wave 'cause beyond Multi-Cloud and the obvious nature of that will end up happening as a state and what happens beyond that interoperability piece, that's a whole other story, and that's what everyone's fighting for, but everyone out in that ecosystem, it's a big wave coming. They've got their surfboards. They're ready to go. So what do you guys see? What is the next wave that everyone's jacked up about here? >> Well, I think that the Multi-Cloud is obviously at the epicenter. You know, if you look at the results that are coming in, a lot of our customers, this is what's leading the discussion and now we're in a position where, you know, we've brought many companies over the last few years. They're starting to come to fruition. They're starting to play a role in, you know, how we're moving forward. >> Yeah. >> Some of those are a bit more applicable to the commercial space. We're finding commercial customers that never bought from us before. Never. Hundreds and hundreds are coming through our partner networks every single quarter, you know? So brand new to VMware. The trick then is how do you nurture them? How do you encourage them? >> So new logos are comin' in. >> New logos are coming in all the time, all the time, from, you know, from across the ecosystem. It's not just the OEMs. It's all the way back- >> So the ecosystem's back of VMware. >> Unbelievably. So what are we doing to help that? There's two big things that we've announced in the recent weeks is that Partner Connect 2.0. When I talked to you about Multi-Cloud and what the (indistinct), you know, the customers are doing, you see that trend. Four, five different separate clouds that we've got here. The next piece is that they're changing their business models with the partners. Their services is becoming more and more apparent, et cetera, you know? And the use of other partners to do other services, deployment, or this stuff is becoming prevalent. Then you've got the distributors that I talked about with their, you know, their, then you route to market, then you route to business. So how do you encapsulate all of that and ensure your rewarding partners on all aspects of that? Whether it's deployment, whether it's test and depth, it's a points-based system we've put in place now- >> It's a big pie that's developing. The market's getting bigger. >> It's getting so much bigger. And then you help- >> I know you agree, obviously, with that. >> Yeah. Absolutely. In fact, I think for a long time we were asking the question of, is it going to be there or is it going to be here? Which was the wrong question. (indistinct cross talking) Now it's everything. >> Yeah. >> And what I think that, what we're seeing in the ecosystem, is that people are finding the spots that, where they're going to play. Am I going to be on the Edge? >> Yeah. >> Am I going to be on Analytics Play? Am I going to be, you know, Cloud Transition Play? There's a lot of players are now emerging and saying, we're- >> Yeah. >> We're, we now have a place, a part to play. And having that industry view not just of, you know, a commercial customer at that level, but the two of us are lookin' at Teleco, are looking at financial services, at healthcare, at manufacturing. How do these new ecosystem players fit into the- >> (indistinct) lifting. Everyone can see their position there. >> Right. >> We're now being asked for simplicity and talk to me about partner profitability. >> Yes. >> How do I know where to focus my efforts? Am I spread too thin? And, you know, that's, and my advice that the partner ecosystem out there is, hey, let's pick out spots together. Let's really go to, and then strategic solutions that we were talking about is a good example of that. >> Yeah. >> Sounds like composability to me, but not to go back- (laughing) Guys, thanks for comin' on. I think there's a big market there. I think the fog is lifted. People seeing their spot. There's value there. Value creation equals reward. >> Yeah. >> Simplicity. Ease of use. This is the new normal. Great job. Thanks for coming on and sharing. (cross talking) Okay. Back to live coverage after this short break with more day one coverage here from the blue set here in Moscone. (light corporate music)

(soft joyful music) >> Welcome back everyone to the live CUBE coverage here in San Francisco for VMware Explore '22. I'm John Furrier with my host Dave Vellante. Three days of wall to wall live coverage. Two sets here at the CUBE, here on the ground floor in Moscone, and we got VMware and HPE back on the CUBE. Paul Turner, VP of products at vSphere and cloud infrastructure at VMware. Great to see you. And Mark Nickerson, Director of Go to Mark for Compute Solutions at Hewlett-Packard Enterprise. Great to see you guys. Thanks for coming on. >> Yeah. >> Thank you for having us. >> So we, we are seeing a lot of traction with GreenLake, congratulations over there at HPE. The customers changing their business model consumption, starting to see that accelerate. You guys have the deep partnership, we've had you guys on earlier yesterday. Talked about the technology partnership. Now, on the business side, where's the action at with the HP and you guys with the customer? Because, now as they go cloud native, third phase of the inflection point, >> Yep. >> Multi-cloud, hybrid-cloud, steady state. Where's the action at? >> So I think the action comes in a couple of places. Um, one, we see increased scrutiny around, kind of not only the cost model and the reasons for moving to GreenLake that we've all talked about there, but it's really the operational efficiencies as well. And, this is an area where the long term partnership with VMware has really been a huge benefit. We've actually done a lot of joint engineering over the years, continuing to do that co-development as we bring products like Project Monterey, or next generations of VCF solutions, to live in a GreenLake environment. That's an area where customers not only see the benefits of GreenLake from a business standpoint, um, on a consumption model, but also around the efficiency operationally as well. >> Paul, I want to, I want to bring up something that we always talk about on the CUBE, which is experience in the enterprise. Usually it's around, you know, technology strategy, making the right product market fit, but HPE and VMware, I mean, have exceptional depth and experience in the enterprise. You guys have a huge customer base, doesn't churn much, steady state there, you got vSphere, killer product, with a new release coming out, HP, unprecedented, great sales force. Everyone knows that you guys have great experience serving customers. And, it seems like now the fog is clearing, we're seeing clear line of sight into value proposition, you know, what it's worth, how do you make money with it, how do partners make money? So, it seems like the puzzle's coming together right now with consumption, self-service, developer focus. It just seems to be clicking. What's your take on all this because... >> Oh, absolutely. >> you got that engine there at VMware. >> Yeah. I think what customers are looking for, customers want that cloud kind of experience, but they want it on their terms. So, the work that we're actually doing with the GreenLake offerings that we've done, we've released, of course, our subscription offerings that go along with that. But, so, customers can now get cloud on their terms. They can get systems services. They know that they've got the confidence that we have integrated those services really well. We look at something like vSphere 8, we just released it, right? Well, immediately, day zero, we come out, we've got trusted integrated servers from HPE, Mark and his team have done a phenomenal job. We make sure that it's not just the vSphere releases but VSAN and we get VSAN ready nodes available. So, the customers get that trusted side of things. And, you know, just think about it. We've... 200,000 joined customers. >> Yeah, that's a lot. >> We've a hundred thousand kind of enabled partners out there. We've an enormous kind of install base of customers. But also, those customers want us to modernize. And, you know, the fact that we can do that with GreenLake, and then of course with our new features, and our new releases. >> Yeah. And it's nice that the products market fits going well on both sides. But can you guys share, both of you share, the cadence of the relationship? I mean, we're talking about vSphere, every two years, a major release. Now since 6, vSphere 6, you guys are doing three months' releases, which is amazing. So you guys got your act together there, doing great. But, you guys, so many joint customers, what's the cadence? As stuff comes out, how do you guys put that together? How tightly integrated? Can you share a quick... insight into that dynamic? >> Yeah, sure. So, I mean Mark can and add to this too, but the teams actually work very closely, where it's every release that we do is jointly qualified. So that's a really, really important thing. But it's more interesting is this... the innovation side of things. Right? If you just think about it, 'cause it's no use to just qualify. That's not that interesting. But, like I said, we've released with vSphere 8 you know... the new enhanced storage architecture. All right? The new, next generation of vSphere. We've got that immediately qualified, ready on HPE equipment. We built out new AI servers, actually with Invidia and with HPE. And, we're able to actually push the extremes of... AI and intelligence... on systems. So that's kind of work. And then, of course, our Project Monterey work. Project Monterey Distributed Services Engine. That's something we're really excited about, because we're not just building a new server anymore, we're actually going to change the way servers are built. Monterey gives us a new platform to build from that we're actually jointly working. >> So double click on that, and then to explain how HPE is taking advantage of it. I mean, obvious you have more diversity of XPU's, you've got isolation, you've got now better security, and confidential computing, all that stuff. Explain that in some detail, and how does HPE take advantage of that? >> Yeah, definitely. So, if you think about vSphere 8, vSphere 8 I can now virtualize anything. I can virtualize your CPU's, your GPU's, and now what we call DPU's, or data processing units. A data processing unit, it's... think of it as we're running, actually, effectively another version of ESX, sitting down on this processor. But, that gives us an ability to run applications, and some of the virtualization services, actually down on that DPU. It's separated away from where you run your application. So, all your applications get to consume all your CPU. It's all available to you. Your DPU is used for that virtualization and virtualization services. And that's what we've done. We've been working with HPE and HPE and Pensando. Maybe you can talk some of the new systems that we've built around this too. >> Yeah. So, I mean, that's one of the... you talked about the cadence and that... back to the cadence question real briefly. Paul hit on it. Yeah, there's a certain element of, "Let's make sure that we're certified, we're qualified, we're there day zero." But, that cadence goes a lot beyond it. And, I think Project Monterey is a great example of where that cadence expands into really understanding the solutioning that goes into what the customer's expecting from us. So, to Paul's point, yeah, we could have just qualified the ESX version to go run on a DPU and put that in the market and said, "Okay, great. Customers, We know that it works." We've actually worked very tightly with VMware to really understand the use case, what the customer needs out of that operating environment, and then provide, in the first instantiation, three very discrete product solutions aimed at different use cases, whether that's a more robust use case for customers who are looking at data intensive, analytic intensive, environments, other customers might be looking at VDI or even edge applications. And so, we've worked really closely with VMware to engineer solutions specific to those use cases, not just to a qualification of an operating environment, not just a qualification of certain software stack, but really into an understanding of the use case, the customer solution, and how we take that to market with a very distinct point of view alongside our partners. >> And you can configure the processors based on that workload. Is that right? And match the workload characteristics with the infrastructure is that what I'm getting? >> You do, and actually, well, you've got the same flexibility that we've actually built in why you love virtualization, why people love it, right? You've got the ability to kind of bring harness hardware towards your application needs in a very dynamic way. Right? So if you even think about what we built in vSphere 8 from an AI point of view, we're able to scale. We built the ability to actually take network device cards, and GPU cards, you're to able to build those into a kind of composed device. And, you're able to provision those as you're provisioning out VM's. And, the cool thing about that, is you want to be able to get extreme IO performance when you're doing deep learning applications, and you can now do that, and you can do it very dynamically, as part of the provisioning. So, that's the kind of stuff. You've got to really think, like, what's the use case? What's the applications? How do we build it? And, for the DPU side of things, yes, we've looked at how do we take some of our security services, some of our networking services, and we push those services down onto the SmartNIC. It frees up processors. I think the most interesting thing, that you probably saw on the keynote, was we did benchmarks with Reddit databases. We were seeing 20 plus, I'm sure the exact number, I think it was 27%, I have to get exact number, but a 27% latency improvement, to me... I came from the database background, latency's everything. Latency's king. It's not just... >> Well it's... it's number one conversation. >> I mean, we talk about multi-cloud, and as you start getting into hybrid. >> Right. >> Latency, data movement, efficiency, I mean, this is all in the workload mindset that the workhorses that you guys have been working at HPE with the compute, vSphere, this is heart center of the discussion. I mean, it is under the hood, and we're talking about the engine here, right? >> Sure. >> And people care about this stuff, Mark. This is like... Kubernetes only helps this better with containers. I mean, it's all kind of coming together. Where's that developer piece? 'Cause remember, infrastructure is code, what everybody wants. That's the reality. >> Right. Well, I think if you take a look at... at where the Genesis of the desire to have this capability came from, it came directly out of the fact that you take a look at the big cloud providers, and sure, the ability to have a part of that operating environment, separated out of the CPU, free up as much processing as you possibly can, but it was all in this very lockdown proprietary, can't touch it, can't develop on it. The big cloud guys owned it. VMware has come along and said, "Okay, we're going to democratize that. We're going to make this available for the masses. We're opening this up so that developers can optimize workloads, can optimize applications to run in this kind of environment." And so, really it's about bringing that cloud experience, that demand that customers have for that simplicity, that flexibility, that efficiency, and then marrying it with the agility and security of having your on premises or hybrid cloud environment. And VMware is kind of helping with that... >> That's resonating with the customer, I got to imagine. >> Yeah. >> What's the feedback you're hearing? When you talk to customers about that, the like, "Wait a minute, we'd have to like... How long is that going to take? 'Cause that sounds like a one off." >> Yeah. I'll tell you what... >> Everything is a one off now. You could do a one off. It scales. >> What I hear is give me more. We love where we're going in the first instantiation of what we can do with the Distributed Services Engine. We love what we're seeing. How do we do more? How do we drive more workloads in here? How do we get more efficiency? How can we take more of the overhead out of the CPU, free up more cores. And so, it's a tremendously positive response. And then, it's a response that's resonating with, "Love it. Give me more." >> Oh, if you're democratizing, I love that word because it means democratization, but someone's being democratized. Who's... What's... Something when... that means good things are happening, which means someone's not going to be winning out. Who's that? What... >> Well it, it's not necessarily that someone's not winning out. (laughs) What you read, it comes down to... Democratizing means you've got to look at it, making it widely available. It's available to all. And these things... >> No silos. No gatekeepers. Kind of that kind of thing. >> It's a little operationally difficult to use. You've got... Think about the DPU market. It was a divergent market with different vendors going into that market with different kind of operating systems, and that doesn't work. Right? You've got to actually go and virtualize those DPU's. So then, we can actually bring application innovation onto those DPU's. We can actually start using them in smart ways. We did the same thing with GPU's. We made them incredibly easy to use. We virtualized those GPU's, we're able to, you know, you can provision them in a very simple way. And, we did the same thing with Kubernetes. You mentioned about container based applications and modern apps in the one platform now, you can just set a cluster and you can just say, "Hey I want that as a modern apps enabled cluster." And boom. It's done. And, all of the configurations, set up, Kubernetes, it's done for you. >> But the thing that just GreenLake too, the democratization aspect of how that changed the business model unleashes... >> Right. >> ...efficiency and just simplicity. >> Oh yeah, absolutely. >> But the other thing was the 20% savings on the Reddit's benchmark, with no change required at the application level, correct? >> No change at the application level. In the vCenter, you have to set a little flag. >> Okay. You got to tick a box. >> You got to tick a little box... >> So I can live with that. But the point I'm making is that traditionally, we've had... We have an increasing amount of waste to do offloads, and now you're doing them much more efficiently, right? >> Yes. >> Instead of using the traditional x86 way of doing stuff, you're now doing purpose built, applying that to be much more efficient >> Totally agree. And I think it's becoming, it's going to become even more important. Look at, we are... our run times for our applications, We've got to move to a world where we're building completely confidential applications at all time. And that means that they are secured, encrypted, all traffic is encrypted, whether it's storage traffic, whether it's IO traffic, we've got to make sure we've got complete route of trust of the applications. And so, to do all of that is actually a... compute intensive. It just is. And so, I think as we move forward and people build much more complete, confidential, compute secured environments, you're going to be encrypting all traffic all the time. You're going to be doing micro-zoning and firewalling down at the VM level so that you've got the protection. You can take a VM, you can move it up to the cloud, it will inherit all of its policies, will move with it. All of that will take compute capacity. >> Yup. >> The great thing is that the DPU's give us this ability to offload and to use some of that spare compute capacity. >> And isolate so the application chance can't just tunnel in and get access to that >> You guys got so much going on. You can have your own CUBE show, just on the updating, what's going on between the two companies, and then the innovation. We got one minute left. Just quickly, what's the goal in the partnership? What's next? You guys going to be in the field together, doing joint customer work? Is there bigger plans? Is there events out there? What are some of your plans together in the marketplace? >> That's you. >> Yup. So, I think, Paul kind of alluded to it. Talk about the fact that you've got a hundred thousand partners in common. The venn diagram of looking at the HPE channel and the VMware channel, clearly there's an opportunity there to continue to drive a joint, go to market message, through both of our sales organizations, and through our shared channel. We have a 25,000 strong... solution architect... force that we can leverage. So as we get these exciting things to talk about, I mean, you talk about Project Monterey, the Distributed Services Engine. That's big news. There's big news around vSphere 8. And so, having those great things to go talk about with that strong sales team, with that strong channel organization, I think you're going to see a lot stronger partnership between VMware and HPE as we continue to do this joint development and joint selling >> Lots to get enthused about, pretty much there. >> Oh yeah! >> Yeah, I would just add in that we're actually in a very interesting point as well, where Intel's just coming out with Next Rev systems, we're building the next gen of these systems. I think this is a great time for customers to look at that aging infrastructure that they have in place. Now is a time we can look at upgrading it, but when they're moving it, they can move it also to a cloud subscription based model, you know can modernize not just what you have in terms of the capabilities and densify and get much better efficiency, but you can also modernize the way you buy from us and actually move to... >> Real positive change transformation. Checks the boxes there. And put some position for... >> You got it. >> ... cloud native development. >> Absolutely. >> Guys, thanks for coming on the CUBE. Really appreciate you coming out of that busy schedule and coming on and give us the up... But again, we can do a whole show some... all the moving parts and innovation going on with you guys. So thanks for coming on. Appreciate it. Thank you. I'm John Dave Vellante we're back with more live coverage day two, two sets, three days of wall to wall coverage. This is the CUBE at VMware Explorer. We'll be right back.

[Music] okay welcome back everyone it's thecube's coverage here in monaco i'm john furrier host of thecube monaco crypto summit presented by digital bits uh media partners coin telegraph in the cube a lot of great stuff going on here digital bits and the ecosystem around the world come together to talk about the next generation uh nft environments metaverse uh blockchain all the innovations going up and down the stack of the decentralized world that will be soon a reality for everybody we have a great guest david lutzkach here who's the co-founder of aftermath islands metaverse which i got a little sneak preview of but david thanks for joining me thanks john great to be here uh we had dinner the other night at nobu it's great to know you get to know your background you've got a stellar uh pedigree um you've run public companies you've been involved in tech media across the board again this is a ship we're seeing like we've never before perfect storm technology change cultural change business model transformation all around deep decentralization crypto token economics decentralized applications metaverse i mean come on we haven't digital identity there was identity which you're involved in take us through what are you working on take a minute to explain what you're working on and then we'll get into it so aftermath islands is is really a culmination of three things uh digital identity the ability to prove who you are because we think the internet and i think everyone would agree the internet's broken you know um nefarious actors bad actors can be anywhere um hacks fake spots so by being able to prove that you're a real person not necessarily verifying your identity but prove that you're a real person um can add a lot of benefits to everyone in the ecosync system second thing is we combine that with avatars nfts and credentials because i'd like to represent myself as a little more buff than i am and maybe a little taller and then the third thing is we put it in a unreal engine so real realistic photo realistic game engine metaverse that requires no downloading it's all pixel streaming just like you'd stream netflix you can stream the game i want to ask because this is i know it's a hard problem because i've asked a lot of people the same question the unreal engine is really powerful and the imagery is amazing like gaming we all know what it looks like it's hard it's not everyone's getting it right what makes it so special how are you guys cracking the code well i think it's our experience i mean we've worked for major entertainment companies major technology companies major sports companies so um as i just use your word because it being i want to be humbled by this but we do have a great pedigree we've also brought great people to the table so having a platform isn't enough we've got great creators and uh we've got great storytellers so we've got the anisiasa brothers one mariano is is a illustrator and former special editor uh project center at marvel and his brother fabian is our storyteller who's the co-creator of deadpool so we've got great people and with unreal engine 5 we've really taken it from the ground up we've looked at it and and we've really combined it with new gpu cloud serving and pixel streaming so that you're so the individual that's that's involved engaged immersed is now really playing it without having to download a graphics package yeah and also you drop some names there and some and some brands i know there's a lot more at dinner we've talked a lot about them you you know all the top creators and again i love the creator culture i mean that's the new buzzwords around but ultimately it's artists people building stuff application developers in the software world movies and film art art and code is kind of coming together it's the same kind of thing media and coding it's like the same mindset you know creative exactly crazy good smart in a good way in the blockchain it's harder because you've got all this underlying infrastructure and stuff to provision and build often created say oh man it's like doing chores it's like i just want to build cool stuff i don't want to get in the weeds of all the tech right this is like whoever cracks the code can unleash that heavy lifting so the artist can like feel good about kicking ass well i'm i'm being a slot a little sly here because we've sort of broken it into three areas and we've used blockchain to book and the platform so we still think that that gaming in the interactive platform has to have centralization it has to have decision making we have a great community um between twitter and discord we have over 30 000 people and we have organizations that have already um spawned um themselves up or spun up to manage our landowner ownership and some of our guilds for some of our professions but at the same time they're allowing us to make decisions based on what the community wants i mean i've heard recently um i don't want to say it's a horror story but it's been difficult that consensus-based models for development have to get consensus and not everybody agrees you still need the leadership i mean you still need sort of a captain on a ship to make sure that the dictatorships are work and well and linux um tried that and they've worked for a while but when they moved over to we're going to make some decisions have an opinion right whether it's centralization it's faster yeah consensus systems can be diverse and time-consuming well they can be political as well i mean you can you can it can become problems so at the front end we've got digital identity and that's all blockchain based and at the back end we have over 20 services including dids and did com which is decentralized identifier communication and all our services are blockchain based but in the middle um connected to nft's blockchain and everything else and to our teacher identity we have a game or a game platform or a open world platform that is centralized built in unreal engine so that we can make those decisions that spur on individual development it's an architecture it is i mean this is essentially an operating environment exactly you can have the benefits of the decentralized all your data on your identity okay and then have the middle be the playground and built right now that has to get done faster and you're constantly iterating exactly so you need to have that exactly so what are people saying about this to me i think that makes a lot of sense people are very intrigued um we're getting a lot of traction first of all unreal engine in the middle um brands love it because it provides a realistic view of a brand brands have spent you know hundreds of millions of dollars building brand equity and they don't necessarily want a cartoon representation of their brand so brands love it um uh we showed a video here at the monaco crypto summit of some and our videos available online on youtube but we're showing realistic we can create realistic avatars so people are really excited about what we're doing you know david i think one of the things i've had controversy statements in the past that got all the purists going back to 2018 you know throwing tomatoes at me but other halfs like loving it because at that time there was dogma around block change got to be done you know it was slow and gas so why i can use a database now we use the blockchain for smart contracts right which you that's what you want to do you want to have that locked in you want immutability so again this opportunity is to advance faster and not have to get stuck in the dogma but maybe get it back to it later database is a great example i agreed i think i think over time the community will take over the entire platform but i think at the beginning you have to have again you have to have a rudder on a ship to make it go somewhere it's called product market fit exactly you got to get to the market exactly with a product you've got that i want that exactly i mean unreal engine is hard i know what are some of the people you worked with because i think i think what i like about what you're working on is that you are and i think a great poster child of in terms of the organization of a group of people that are pros that want to do great work in a new world with the kind of experience and tools that they had in their old world right faster cheaper better more control when we were there at web one we're there at web two and now with web three we have the ability to fix some of the things that we thought were wrong with web one and two so and move into the ownership economy and and really um for us we've got a great team of people you know around the world that we work with and we're starting to bring in larger organizations to support us i mean our digital identity we're really working with the backbone at ibm and digital identity is very different in blockchain than is crypto and we're working with great people in crypto now we announced today that we're minting our native token dubs with digital bits so we're really excited about that yeah yeah let me ask you a question because i love the fact that you brought multiple ways of innovation again i've mentioned on that with shared experience there different different ride for different waves what have you learned and shared to folks who are going to dip their toe and get on their surfboard so to speak use the california metaphor for both californians what is web3 wave like how's it different from two what's the learnings can you share scar tissue experience observation anything around what you're doing now so they can get insight into this wave well you know web 1 and web 2 were broken i mean you could never go in i think we had this discussion you could never go into an electronic store in the real world write your information down on a piece of paper and expect that you'd walk out of the store with the purchase but we can type in information that is non-verified until i could take my friend's credit card know where they live and use it by using digital identity at a front end we create one user one account that user can have thousands of verifiable credentials around them and hundreds of avatars so i think what we've really learned is the ability to progress in a way that that really puts data back in the hands of consumers and makes them the owner of their identity by starting there we have a world in front of us that is valuable to marketers valuable to brands and valuables to individuals and whether it's education whether it's government services whether it's retail everything can be built on that simple premise that i am myself it's interesting there's a constant technology we're called presence you know you're present at an event you're present at a store you're present and some reality physically and you have credentials around that presence contextually exactly you're saying you can have one nft one digital identity or identity and have multiple identities that have contacts all stored i'll store it in an avatar it's like changing your suit hey i'm going into the apple store i'm now my apple john and and think of it this way um brands can now connect with you and give you promos give you product based on the information that you're willing to share with them about your real person and your avatar becomes your intermediary so your payment information stored within your digital identity and your avatar not at the retail level so this is a concept we've been working on for a long time i think we're talking about dinner but i want to bring this up for you for you to come and get a reaction to is that if what you just said is true that means if i'm the user and i have power to control my data the script flips now i'm brokering my data to the brand exactly not the other way around exactly or some intermediary i'm in control exactly and i could demand based on what my contextual relevance is to the brand and the brand is willing to pay for that because if you think about it today um social media unfortunately is plagued by fake accounts you know and issues and and so brands are spending all this money and they're getting slippage and breakage and that's spent if they know your real person they're more likely to want to give you an incentive to engage with them because it's a one-to-one transaction that creates value that's a great point you mentioned twitter earlier look at elon musk uncovered all the bots on twitter um and if they ever did the facebook i'm sure there's a ton of different accounts on facebook but you know it's out there these walled gardens have nefarious bad actors man it's not truth isn't what's the truth i mean gaming has this right now it's like you're anonymous you can go down or you got to go real name so we've got a hybrid you can do anonymously verified so because we use biometrics to verify that you're a real person so you can stay anonymous but we know you're a real person because your biometrics belong to you well david great to have you on thecube you got a great insight and experience thanks for sharing thank you john uh what's next for you guys you want to put a plug in for what you're working on you're looking for people funding more action what are you guys doing right well we've we've self-funded to date and we're we're finally going to be releasing um opportunities for people to engage with us in tokenomics and that's why we've we're working with digital bits but we're also looking for great people and great partners we're creating an interoperable open um uh world where we want to bring partners to the table so anyone who's interested reach out to us all right david guys thanks for going on thecube all right more coverage here on thecube we're all over this area going back to 2018 we brought thecube to all the events been covered on siliconangle.com since 2010 and watching this wave just get better the reality is here it's a metaverse world it is a decentralized world happening to everyone monaco crypto summit here in monaco thanks for watching we'll be right back with more after this short break you

>>Hey everyone. Welcome back to the Cube's live coverage of snowflake summit 22. We are live at Caesar's forum in Vegas, Lisa Martin, with Dave ante, excited to welcome a VIP fresh from the keynote stage, the SAP, a product at snowflake Christian C Claman Christian. Thank you so much for joining us on the queue today. >>Thank you for having me very exciting. >>And thanks for bringing your energy, loved your keynote. I thought, wow. He is really excited about all of the announcements jam packed. We, and we didn't even get to see the entire keynote talk to us about, and, and for the audience, some of the things going on the product revenue in Q1 fiscal 23, 390 4 million, 85% growth, lot of momentum at snowflake. No doubt. >>So I think that the, the punch line is our innovation is if anything, gaining speed. Uh, we were over the moon excited to share many of these projects with customers and partners, cuz some of these efforts have been going on for multiple years. So, um, lots of interesting announcements across the board from making the existing workloads faster, but also we announced some new workloads getting into cyber security, getting into more transactional workloads with uni store. Um, so we're very excited. >>Well first time being back, this is the fourth summit, but the first time being back since 2019 a tremendous amount has changed for snowflake in that time, the IPO, the massive growth in customers, the massive growth in growth in customers with over 1 million in ARR, you talked about one of the things that clearly did not slow down during the last two years is innovation at snowflake. >>Yeah, that, that, that for, for sure, like, um, even though we, we had a, um, highly in the office culture, we did not miss a beat the moment that we said, Hey, let's all start doing zoom based calls. We, we did. So, uh, I dunno if you saw the, the first five minute minutes of my section in the keynote. Yeah. We, we originally talked about summarizing it and no we're gonna spend 40 minutes here. So we did a one minute clip and whatever gets flashed there. So no, the, the pace of innovation, I think it's second to none and maybe I'll highlight the something that we're very proud of. Snowflake is a single product, a single engine. So if we're making a query performance enhancement, it will help the cyber security workload and the low high concurrency, low latency workload. And eventually we're starting to see some of those enhancements all the way to uni store. So, so we get a lot of leverage out of our investments. What's >>Your favorite announcement? >>That's like picking children. Of course. Um, I think the native applications is the one that looks like, eh, I don't know about it on the surface, but it has the biggest potential to change everything like create an entire ecosystem of solutions for within a company or across companies that I don't know that we know what's possible. >>Well, I I've been saying for a while now that you have this application development stack over here, the database is kind of here and then you have the analytics and data pipeline stack. Those are those separate worlds. We, we talk about bringing data and AI and machine intelligence into applications. The only way that that is actually gonna move forward is if you bring those worlds together is a good example of that happening, um, within a proprietary framework, uh, it's probably gonna happen open source organically and you can sort of roll your own. Is that by design or is it just sort of happening? Well, >>The, the, they bring it all into a single platform obviously by design, cuz there is so much friction today on making all the pieces work together, which database do I use for transactions and how do I move data to my analytics system? And how do I keep system, uh, reference data in sync between the two? So, so it's complicated and our mission was remove all of this friction from, from, from the equation. Uh, the open source versus not the way we think about it is opensourcing open formats or even open APIs it's does it help us deliver the solution that we want for our customer? Does it help us solve their problems? In certain instances, it has done in the past and we've opened source frameworks in, in others. We mentioned at the keynote today, the, the integration of iceberg tables, that's an strong embrace of open technologies, but that does not mean that we want to continue to innovate in our formats. A lot of what you see in the open formats is because snowflake proprietary, uh, innovation. So, uh, we have a very clear philosophy around this. Well >>Like any cloud player, you have to bring open source tools in and make them available for your application developers. But take us through an example of, of uni store and specifically how you're embracing transaction data. What's a customer gonna actually do take us paint a picture >>For us. I I'm gonna give you a very simple use case, but I love it because it, it shows the power of the scenario today. When people are ingesting data into snowflake, you wanna do some book capping associating with those loads. So imagine I have, I dunno, a million files. How many of those files have I loaded? Imagine that one of those loads fail, how do you keep in sync? Whether the data made or not with your bookkeeping today, if you had to do it with a separate transactional database for the bookkeeping and the loading in, in snowflake, it is a lot of complexity for you to know what's where with uni store, you can just say, I'm gonna do the bookkeeping with these new table. It's called hybrid tables. The lows are transactional and all of this is a single transaction. So for, for anyone that has dealt with inconsistencies in database world, this is like a godsend. >>Okay. So my interpretation of that's all about what happens when something goes wrong >><laugh> which is a lot of the, everything about transactions. Yeah. It's what happens when goes wrong and goes wrong. Doesn't mean failures like goes wrong is when you're debiting money from your bank account, not having enough balance that counts as go wrong and the transactions should be aborted. So yes, transactions are all about conflict management and we're simplifying that in a broader set of use cases >>And, and in recovery. So you're, you're in fast recovery. So you're, you're the, the business impact of what you're doing is to sort of simplify that process. Is that the easy way to >>Boil down? Pretty much everything we do is about simplification. Like we, we we've seen organizations are large focusing on wrestling infrastructure as opposed to what are the business problems for a Frank who reference something that, that, that I believe very much in like, which is mission alignment. We are working on helping our customers achieve what they're set out to achieve, not giving them more technology for them to their goal to become, to wrestle the infrastructure. So it's all about ease of use all about simplification removal, friction, >>Just so if I may, so mission alignment, you know, you always hear about technology companies that, you know, provide infrastructure or a service, and then the customer takes that and, and, you know, monetizes it pretty much on their own. What the big change that I'm discerning from these announcements is you're talking about directly monetizing and participating in that monetization as a technology partner, but also the marketplace as well. >>Correct. And I would say in some ways this is not new. This has been happening for the last couple of years with data. Like if you just saw our industry data cloud launches, the financial services cloud, it comes with data providers that help you achieve specific outcomes on a specific industry. Mm-hmm <affirmative> what we're doing now is saying, it's not just data. Maybe it's some business logic, maybe it's some machine learning, maybe it's some user interface. So I think we're just turning the knob on collaboration and it's a continuation of what we've been doing. >>Talk a little bit more about mission alignment. When I heard Frank, Sweetman talk about that this morning. I always love that when I hear cultural alignment with organizations, but as you just said, it's really about enabling our customers to deliver outcomes to their customers as the SVP product. Can you, uh, talk a little bit about how the customers are influencing the product roadmap, the innovations and the speed with which things are coming out at snowflake? >>Yeah, so great question. We have several organizations at snowflake that are organized by vertical by industry. So the, the major sales organization is part of ed that the marketplace business development team is organized like that. We have a separate team that provides top leadership by industry vertical, um, globally. And then even within our solution engineering, there is verticals. So we have a longitudinal view of all the different functions and what do we need to do to achieve a set of use cases in a vertical? And all of those functions are in con constant communication with us on this is where the product is, um, seeing an opportunity or could do better for that vertical. So yeah, I can tell you, and obviously we love when, when there's alignment between those, but that's not always the case. You heard us talk about clean rooms now for some time, clean rooms are applicable to almost any industry, but it's red hot for media and advertising, third party, cookie deprecation, and all of that. So we, we get to, to see that lens, that our innovation is informed by industries. >>So we, we're seeing, obviously the evolution of snowflake we talked about in the keynotes today, you guys talked about 2019 and, you know, pre 2019, even it was to me anyway, your first phase was, Hey, we got a simpler EDW. You know, we're gonna pick that off and put it in the cloud and make it elastic and separate compute from storage, all that kind of cool stuff. And then during the pandemic, it was really IPO, but also the data cloud concept, you sort of laid that vision out. And now you're talking about application development, monetization, what I call the super cloud that layer. Right. Okay. So I, are >>You determin it best? >>Yes. You talk about this, uh, these announcements, how they fit into that larger vision where you're >>Going. Great question. The, the, the notion of the data cloud has not changed one bit. The data cloud thesis is that we want to provide amazing technology for our customers, but also facilitate collaboration and content exchange VR platform. And all that we did today is expand what that content can be. It's not just data or little helper function, it's entire applications, entire experiences. That is the, the summing up the, the, the impact of our announcements today. That, that that's the end of it. So it's still about the data cloud. >>So what is impressive to me is that you guys wouldn't couldn't have a company without the hyperscalers, right? It would be a lot different, right? So you built on top of that and, and now you have your customers building their own super clouds. I call it, I get a lot of grief for that term it's but the, the, the big area of criticism I get is, ah, that's just SAS. And I'm like, no, it's not, no, uh, I, I is everybody public who's announcing stuff. I, I better be careful, but you have customers that are actually building services, taking their data, their tooling, their proprietary information, and putting it on the snowflake data cloud and building their own clouds. Yeah. That's different. Then that's not multi-cloud, which is I can run on a different cloud and it's not, is it sass? If it feels like it's something new from a, from your perspective, is, is it different? >>I, I, I love that you called out that running on all clouds is not what we do right. This days, everyone is multi-cloud, you, you run on a VM or a container, and I multi-cloud check, no, we have a single platform that does multi-region multi-cloud but also cross region cross cloud globally, that that is the essence of what we're doing. So it, it is enabling new capabilities. >>I've I've also said, you know, in many respects, the super cloud hides, the underlying complexity, you think about things like exploiting graviton and a developer. Doesn't need to worry about that. You're gonna worry about that. Uh, but at the same time, they, the, as you get into the develop, the world of application development, some of your developers may want access to some of those cloud primitives. Are you providing both? What's the strategy there? >>Generally not in some areas, we, we, we, I would say bleed through some details that are material, but think of the reality of someone that wants to build a solution, it's really difficult to build an awesome solution in one cloud, Hey, you need to do this. What's the latest instance, and is gravity tank gonna help you or not all of that. Now do it for another one and then do it for another one. And I can tell you it's really difficult because we go through that exercise. Snowflake pouring to a new cloud is somewhere between one and two years of effort and not, not a small number of people because you're looking at security models and storage models. So that's the value that we give to anyone know, wants to build a solution and target customers in all three clouds. I >>Mean, people are still gonna do it themselves, but they're gonna spend a lot more and they're gonna lose their focus on what their real business is. And there'll still be that. I think that D DIY market is enormous for you guys, huge >>Opportunity. And there's also the question on what is the cost of that analysis and that effort. And can we amortize it on behalf of all of our customers? Like we talk about graviton, we have not talked about the many things that we evaluated that were not better price performance for our customers. That evaluation happened. That value was delivered by not moving there. >>And when you do it yourself, the curve looks like, okay, Hey, we can do it ourselves. We can make it pretty Inex. And then, and then the costs are gonna decline, but what really happens, like developing a mobile app, you gotta maintain it. And then if you don't have the scale and you don't have the engineering resources, you're just, the, the costs are gonna continue to go through the roof. I, >>I, I love that you compare it to mobile apps. Like, yeah. I still don't understand why every company that wants to build an app has to build two <laugh>. They got it. Yeah. There is no super cloud for the phone. >>Right. >>That's sort of our, our, our broad vision. Not yet. Not, not the phone, but the super cloud. Yeah, >>Yeah, absolutely. >>You >>Get it. This is, and you look out the ecosystem here. I mean, what a difference that you've been pointing this out, Lisa from, from, from 2019, a lot of buzz, it's all about innovation. You see this at, at thing at the reinvent is like the super bowl obviously. And you see that and it used to be, oh, how is, how is AWS gonna compete with snowflake and separate compute with stores? That's I, I feel like in a large way, that's all gone. It's like, okay, how do we like rise the whole, the whole industry? And that's really where the innovation is. >>We have an amazing partnership with AWS and they benefit from what we do. Yes. There's some competitive elements, but we're changing so many things creating so much opportunity that we're more aligned than not. Yeah. >>Last question for you is continuing on the part AWS partnership front, how does a partner like AWS and other partners, how do they fit into the data cloud narrative that you're talking about to customers? >>I would say that other than the one or two teams that are directly competitive, the rest of their teams are part of in data cloud. Like, uh, our relationship with SageMaker as an example is amazing. And a lot of what we wanna deliver to our customers is choice around machine learning, frameworks and tools. And they're part of the data cloud. We're working with them on how do you push down computation to avoid getting data out, to reinforce governance? So I, I would say that and, and go look at it that they have a hundred and something teams. So if two teams out of hundreds, uh, are, are the competitive element, we are largely aligned. And they're part of data cloud. >>Yeah. I mean, you, your customers consume a lot of compute and storage for, >>For a lot. Yes. >>AWS and, and also, you know, increasingly Azure and, and Google. I mean, it's, um, pretty amazing times, uh, Christian, I want to ask you about, um, couple of terms. Uh, one term that came up a couple of times today in Frank's keynote, he said, I'm not gonna call it a data mesh out kind of out of respect for the purists, which is cool, I thought, but then you had a customer stand up Geico and said, we're building a data. Mesh JPMC is, is speaking at this event, building a data mesh. And I look at things through that prism and say, okay, data mesh is about, you know, decentralization. Some, I I'd be curious as to whether or not you tick that box, but it's about building data products. It's about, uh, uh, self-service infrastructure. And it's about automated computational governance. You are actually tipping a lot of the ticking, a lot of those boxes and, and Mike, I guess the big one is, are, are you building a bigger walled garden? But I, I think you would say, no, it's a, it's a giant distributed network, but, but what, what, what do you say to that? We, >>The latter, the latter, yeah, giant distributed, open cloud and open in the sense that we want anyone to plug in and, and someone can say, well, but I cannot read your file formats. Sure. You can with what we announced today, but it's not about that. Our APIs are open. We have rest APIs. We have JDC ODC, probably most popular interfaces ever. Um, and we want everyone to be part of it. If anything, there's lots of areas that we would not want to go into ourselves cause we want partners and customers to go in there. So, no, we we're looking at a very broad ecosystem. We win based on the value created on top of the platform. Yeah. >>And I makes total sense to me. I mean, I think the imaculate conception of data mesh might be a purely open source version of snowflake. I just don't see that happening anytime soon. And so I, I think you're gonna, you are, I wrote about this creating a defacto standard and >>Exactly, and, and I don't like to get into the terminology that, oh, is the data measure? Not, no go look at the concepts like people used to say, but snowflake is not a data lake. Okay. What is the data lake? It's just a pattern. And if you follow the pattern and you can do it, that's fine. Then there's the, uh, emotional quasi-religious overlay open versus not, I think that's a choice. Not necessarily the concept, >>It's a moving target. I mean, I Unix used to be open. You know, that was the, I agree. Now, the reason why I do think the data mesh conversation is important is because Shaak Dani, when she defined data mesh, she pointed out in my view. Anyway, the problems of getting value outta data is that you go through these hyper specialized teams and they're they're blockers in the organization. And I think you in many respects are attacking that. And it's an organizational issue. >>The, the insights in the pattern are a hundred percent value and aligned with what we do, which is they, you want some amount of centralization, some amount of decentralization living in harmony. Uh, yeah. I have no problem with, with terminology. >>And the governance piece is, is, is massive. Especially it's the, the picture's becoming much more clear. Um, whatever's in the data cloud is a first class citizen, right? And you give all these wonderful benefits. I mean, the interesting thing, what you're doing with Dell and, and pure, I, I asked you that on the analyst call, it's a start. You know, I, I, I mean, >>And I said it briefly in, in, in the keynote this morning, we're publishing a set of standard conformance tests. So any storage system can plug into data cloud. >>Yeah. >>And by the way, it's based on S three APIs, another defect of standard. Like it's not a standard, but everyone is emulating that. And we're plugging >>Into that. Yeah. Nobody's complaining against, against S3 API >>About it is a, oh, it's not a Apache project. We shouldn't, who cares. Everyone has standard horizon net. That's it? >>Well, we've seen the mistakes of the past with this. I mean, look at, look at Hadoop, right? There was this huge battle between, you know, Cloudera and Horton works and map, oh, map bar is proprietary. Oh, Horton works is purely open. Cloudera is open. They're, they're all gone now. I mean, not gone, but they're just, they didn't have it. Right. You know, they, they got unfocused. I go back to Frank's book. They were trying to do too much to, to too many of those, the, the, the zoo animals and you can't fund it all >>To be effective for us. It's very important. I can give you, I don't know, 20 announcements or 50 announcements from the conference, but they're all going a singular goal. And it's, this do not trade off governance of data with the ability to get value out of data. That's everything we do. >>And that's critical for every company in every industry these days that has to be a data company to be, to survive, to be competitive, to be able to extract value from data. If data's currency, how do I leverage a tool like snowflake to be able to extract insights from it that I can act on and create value for my organization, Geico was on stage this morning. Everyone knows Geico and their beloved, um, gecko. Yeah. Is there another customer that you had that you think really articulates the value of the data cloud and to Dave's point how snowflake is becoming that defacto standard data platform? >>Well, we had Goldman Goldman Sachs on stage as well today. And he, he, he, he mentioned it that people think of Goldman as investment banking and all of that, but no, at the heart of what they do, there's a lot of data. And how do they make better decisions? So I think we could run through 20 different examples cuz your premise is the most important. Everything is a data problem. If it is not a data problem, you're not collecting the right data and getting the sense that you could be getting. >>These guys are public, right. >>Adobe. >>Yeah. Right. Adobe's doing it. Yeah. I dunno if the other one is, I don't wanna say, I'll have to ask you off camera, but the other financial firm building a super cloud, right. <laugh> yeah. I call it super cloud. So let be taking advantage of uni store. Yeah. To bring different data types in and monetize it. That's to me, that's the future of data. That's that's been the holy grail, right. >>We, we tried to emphasize that this is, is not a, Hey six, six months ago. We decided to do this. No, this is years in the making mm-hmm <affirmative>, which is why we were so excited to finally share it. Cuz you don't wanna say three years from now, we're gonna have something. No, it was the, now we have it. We have it in preview and it's working at it is as close to the holy grail as it gets. >>Yeah. I mean, look, pressure's on Kristin. Let's face it. Enterprise data warehouse failed to live up to the promises. Uh, certainly the data lakes fail to deliver master data management, all that's a Hadoop, all that stuff. There was a lot of hype around that. And a lot of us got really excited. Me included and then customers spent and they were underwhelmed. Yeah. So you know, you, you, you gotta deliver, you say it, you gotta do it. >>And correct. And then the, the other thing is I would say all of those waves of technology, there was no real better choice. >>Right. They added value. I wouldn't >>Debate that. You have to give it a shot. Like when you've bought 20 different appliances and you have all these silos and someone sells you, Hey, Hadoop will unify it. It sounds good. Just didn't do it. >>Yeah. And no debate that it brought some value for those that were agree. Sophisticated enough to deploy it. And I agree. Yeah. But, but this is a whole different ball game. >>Oh, everything we want to do is democratize and simplify mm-hmm <affirmative> yeah. We could go build something that I don't know. 10 companies in the world could use. That's not the sweet spot. Like how do we advance like the, the state of value generation in the world? That's the scale that we're talking about is go make it easy, accessible for everyone. >>Governed >>Governance and imperative this these days it's law. Yes. So >>Yeah, you have to, but it's not, it's, that's a, that's a ch really difficult challenge to create what I'll call automated or computational governance in a federated manner. That's not trivial. >>And that's our thesis. Everything we're doing is snow park, big announcement today. Python. I I've had people tell me well, but Python should be easy to host the Python run time. Like you can do it. Like I think in a week it took us years. Why? Oh, secure. Oh, details a lot. And <inaudible> mentioned it like securing. That is no easy, uh, feed >>Christian. Thank you so much for joining Dave and me bringing your energy from the keynote stage to the cube, set, breaking down some of the major announcements that have come out today. There's no doubt that the flywheel of innovation at snowflake is alive well and moving quickly, >>Innovation is, uh, at an all time hat snowflake. Thank you for having me. All >>Right. Our pleasure Christian from our guest, Dave ante, Lisa Martin here live in Las Vegas at Caesar's forum covering snowflake summit 22. We right back with our next guest.

>> Announcer: "theCUBE" presents KubeCon and CloudNativeCon Europe 2022 brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain and KubeCon and CloudNativeCon Europe 2022. I'm Keith Townsend, my co-host, Paul Gillin, Senior Editor Enterprise Architecture for SiliconANGLE. We're going to talk, or continue to talk to amazing people. The coverage has been amazing, but also the city of Valencia is beautiful. I have to eat a little crow, I landed and I saw the convention center, Paul, have you got out and explored the city at all? >> Absolutely, my first reaction to Valencia when we were out in this industrial section was, "This looks like Cincinnati." >> Yes. >> But then I got on the bus second day here, 10 minutes to downtown, another world, it's almost a middle ages flavor down there with these little winding streets and just absolutely gorgeous city. >> Beautiful city. I compared it to Charlotte, no disrespect to Charlotte, but this is an amazing city. Naina Singh, Principal Product Manager at Red Hat, and Roland Huss, also Principal Product Manager at Red Hat. We're going to talk a little serverless. I'm going to get this right off the bat. People get kind of feisty when we call things like Knative serverless. What's the difference between something like a Lambda and Knative? >> Okay, so I'll start. Lambda is, like a function as a server, right? Which is one of the definitions of serverless. Serverless is a deployment platform now. When we introduced serverless to containers through Knative, that's when the serverless got revolutionized, it democratized serverless. Lambda was proprietary-based, you write small snippets of code, run for a short duration of time on demand, and done. And then Knative which brought serverless to containers, where all those benefits of easy, practical, event-driven, running on demand, going up and down, all those came to containers. So that's where Knative comes into picture. >> Yeah, I would also say that Knative is based on containers from the very beginning, and so, it really allows you to run arbitrary workloads in your container, whereas with Lambda you have only a limited set of language that you can use and you have a runtime contract there which is much easier with Knative to run your applications, for example, if it's coming in a language that is not supported by Lambda. And of course the most important benefit of Knative is it's run on top of Kubernetes, which allows you- >> Yes. >> To run your serverless platform on any other Kubernetes installation, so I think this is one of the biggest thing. >> I think we saw about three years ago there was a burst of interest around serverless computing and really some very compelling cost arguments for using it, and then it seemed to die down, we haven't heard a lot about serverless, and maybe I'm just not listening to the right people, but what is it going to take for serverless to kind of break out and achieve its potential? >> Yeah, I would say that really the big advantage of course of Knative in that case is that you can scale down to zero. I think this is one of the big things that will really bring more people onto board because you really save a lot of money with that if your applications are not running when they're not used. Yeah, I think also that, because you don't have this vendor log in part thing, when people realize that you can run really on every Kubernete platform, then I think that the journey of serverless will continue. >> And I will add that the event-driven applications, there hasn't been enough buzz around them yet. There is, but serverless is going to bring a new lease on life on them, right? The other thing is the ease of use for developers. With Knative, we are introducing a new programming model, the functions, where you don't even have to create containers, it would do create containers for you. >> So you create the servers, but not the containers? >> Right now, you create the containers and then you deploy them in a serverless fashion using Knative. But the container creation was on the developers, and functions is going to be the third component of Knative that we are developing upstream, and Red Hat donated that project, is going to be where code to cloud capability. So you bring your code and everything else will be taken care of, so. >> So, I'd call a function or, it's funny, we're kind of circular with this. What used to be, I'd write a function and put it into a container, this server will provide that function not just call that function as if I'm developing kind of a low code no code, not no code, but a low code effort. So if there's a repetitive thing that the community wants to do, you'll provide that as a predefined function or as a server. >> Yeah, exactly. So functions really helps the developer to bring their code into the container, so it's really kind of a new (indistinct) on top of Knative- >> on top op. >> And of course, it's also a more opinionated approach. It's really more closer coming to Lambda now because it also comes with a programming model, which means that you have certain signature that you have to implement and other stuff. But you can also create your own templates, because at the end what matters is that you have a container at the end that you can run on Knative. >> What kind of applications is serverless really the ideal platform? >> Yeah, of course the ideal application is a HTTP-based web application that has no state and that has a very non-uniform traffic shape, which means that, for example, if you have a business where you only have spikes at certain times, like maybe for Super Bowl or Christmas, when selling some merchandise like that, then you can scale up from zero very quickly at a arbitrary high depending on the load. And this is, I think, the big benefit over, for example, Kubernetes Horizontal Pod Autoscaling where it's more like indirect measures of value scaling based on CPR memory, but here, it directly relates one to one to the traffic that is coming in to concurrent request. Yeah, so this helps a lot for non-uniform traffic shapes that I think this has become one of the ideal use case. >> Yeah. But I think that is one of the most used or defined one, but I do believe that you can write almost all applications. There are some, of course, that would not be the right load, but as long as you are handling state through external mechanism. Let's say, for example you're using database to save the state, or you're using physical volume amount to save the state, it increases the density of your cluster because when they're running, the containers would pop up, when your application is not running, the container would go down, and the resources can be used to run any other application that you want to us, right? >> So, when I'm thinking about Lambda, I kind of get the event-driven nature of Lambda. I have a S3 bucket, and if a S3 event is driven, then my functions as the server will start, and that's kind of the listening servers. How does that work with Knative or a Kubernetes-based thing? 'Cause I don't have an event-driven thing that I can think of that kicks off, like, how can I do that in Kubernetes? >> So I'll start. So it is exactly the same thing. In Knative world, it's the container that's going to come up and your servers in the container, that will do the processing of that same event that you are talking. So let's say the notification came from S3 server when the object got dropped, that would trigger an application. And in world of Kubernetes, Knative, it's the container that's going to come up with the servers in it, do the processing, either find another servers or whatever it needs to do. >> So Knative is listening for the event, and when the event happens, then Knative executes the container. >> Exactly. >> Basically. >> So the concept of Knative source which is kind of adapted to the external world, for example, for the S3 bucket. And as soon as there is an event coming in, Knative will wake up that server, will transmit this event as a cloud event, which is another standard from the CNCF, and then when the server is done, then the server spins down again to zero so that the server is only running when there are events, which is very cost effective and which people really actually like to have this kind of way of dynamic scaling up from zero to one and even higher like that. >> Lambda has been sort of synonymous with serverless in the early going here, is Knative a competitor to Lambda, is it complimentary? Would you use the two together? >> Yeah, I would say that Lambda is a offering from AWS, so it's a cloud server there. Knative itself is a platform, so you can run it in the cloud, and there are other cloud offerings like from IBM, but you can also run it on-premise for example, that's the alternative. So you can also have hybrid set scenarios where you really can put one part into the cloud, the other part on-prem, and I think there's a big difference in that you have a much more flexibility and you can avoid this kind of Windows login compared to AWS Lambda. >> Because Knative provides specifications and performance tests, so you can move from one server to another. If you are on IBM offering that's using Knative, and if you go to a Google offering- >> A google offering. >> That's on Knative, or a Red Hat offering on Knative, it should be seamless because they're both conforming to the same specifications of Knative. Whereas if you are in Lambda, there are custom deployments, so you are only going to be able to run those workloads only on AWS. >> So KnativeCon, co-located event as part of KubeCon, I'm curious as to the level of effort in the user interaction for deploying Knative. 'Cause when I think about Lambda or cloud-run or one of the other functions as a servers, there is no backend that I have to worry about. And I think this is where some of the debate becomes over serverless versus some other definition. What's the level of lifting that needs to be done to deploy Knative in my Kubernetes environment? >> So if you like... >> Is this something that comes as based part of the OpenShift install or do I have to like, you know, I have to... >> Go ahead, you answer first. >> Okay, so actually for OpenShift, it's a code layer product. So you have this catalog of operator that you can choose from, and OpenShift Serverless is one part of that. So it's really kind of a one click install where you have also get a default configuration, you can flexibly configure it as you like. Yeah, we think that's a good user experience and of course you can go to these cloud offerings like Google Cloud one or IBM Code Engine, they just have everything set up for you. And the idea of other different alternatives, you have (indistinct) charts, you can install Knative in different ways, you also have options for the backend systems. For example, we mentioned that when an event comes in, then there's a broker in the middle of something which dispatches all the events to the servers, and there you can have a different backend system like Kafka or AMQ. So you can have very production grade messaging system which really is responsible for delivering your events to your servers. >> Now, Knative has recently, I'm sorry, did I interrupt you? >> No, I was just going to say that Knative, when we talk about, we generally just talk about the serverless deployment model, right? And the Eventing gets eclipsed in. That Eventing which provides this infrastructure for producing and consuming event is inherent part of Knative, right? So you install Knative, you install Eventing, and then you are ready to connect all your disparate systems through Events. With CloudEvents, that's the specification we use for consistent and portable events. >> So Knative recently admitted to the, or accepted by the Cloud Native Computing Foundation, incubating there. Congratulations, it's a big step. >> Thank you. >> Thanks. >> How does that change the outlook for Knative adoption? >> So we get a lot of support now from the CNCF which is really great, so we could be part of this conference, for example which was not so easy before that. And we see really a lot of interest and we also heard before the move that many contributors were not, started into looking into Knative because of this kind of non being part of a mutual foundation, so they were kind of afraid that the project would go away anytime like that. And we see the adoption really increases, but slowly at the moment. So we are still ramping up there and we really hope for more contributors. Yeah, that's where we are. >> CNCF is almost synonymous with open source and trust. So, being in CNCF and then having this first KnativeCon event as part of KubeCon, we are hoping, and it's a recent addition to CNCF as well, right? So we are hoping that this events and these interviews, this will catapult more interest into serverless. So I'm really, really hopeful and I only see positive from here on out for Knative. >> Well, I can sense the excitement. KnativeCon sold out, congratulations on that. >> Thank you. >> I can talk about serverless all day, it's a topic that I really love, it's a fascinating way to build applications and manage applications, but we have a lot more coverage to do today on "theCUBE" from Spain. From Valencia, Spain, I'm Keith Townsend along with Paul Gillin, and you're watching "theCUBE," the leader in high-tech coverage. (gentle upbeat music)

(bright upbeat music) >> Welcome to theCUBE. Welcome to this CUBE Conversation. I'm Dave Nicholson and with me today, I have Jen Bennett, technical director out of the office of the CTO at Google. Jen, welcome to theCUBE. How are you? >> I'm doing great, Dave. Thanks for having me. >> It's great to have you here. Now, some estimates have 1% of global electrical production. So all of the electricity produced globally, 1% of that is being used currently for the category we call ICT or Information Communications Technology. By 2030, the estimate is that if that goes unchecked, unmeasured, unmitigated, we could be at between 8% and 20% consumption of all of the electricity generated globally, at that point. The question I have for you to start this off is, is that sustainable and if not, what are you and the folks at Google thinking about in this area? >> Yeah Dave, that is a great question. And I think one that's top of mind for many of us in the industry, and there's unfortunately not a simple answer, but for sure, I think that sustainability has been something that's been a core value of ours from the very beginning at Google. And we've really focused on the impact that we have throughout, you know, our computation on climate and on other aspects of the environment. And so I think this is something that's a really important topic that we need to discuss. And so, you know, I want to give you a little bit of a history from a Google perspective. You know, in 2007, we were the first major company to become carbon neutral. So today, you hear a lot about companies talking about carbon neutrality and how important that is to reach, you know, some of these targets that we've been talking about from the Paris Climate Agreement, et cetera. In 2017, you know, as we were looking at this target of how do we become more carbon free, we became the first company, first major company to match a hundred percent of our electricity use associated with our computation that you talked about earlier with renewable energy. So this was a really big push for us. So with the question around, is it sustainable, has to kind of go back to, well, where does the energy come from and how is it generated? And renewable energy is one of those big pieces of the puzzle here. And so we invested very heavily in what was called Power Purchase Agreements. This is, you know, creating the mechanisms, the financial instruments to, you know, enable energy companies to transition from maybe things that are less carbon friendly to more renewable energy. So that was a big emphasis that we put on that first decade of climate action. Since then, and you may be familiar that in 2020, we announced probably our most ambitious goal yet, which is to operate on carbon free 24 by seven. So one of the things that you'll appreciate is that renewable energy, the sun doesn't shine 24/7, wind doesn't blow 24/7. And so we need more to become carbon free, 24/7 around the clock. We need storage techniques. We need a lot of other potential, you know, technologies that are evolving. And so we're very committed to investing in making sure that we advance those technologies just like we did with renewable energy. And so this is a really ambitious goal. We don't know how to get there yet. And that's why we often referred to is as a moonshot. >> Yeah, so yeah, that is a moonshot. And it's interesting because it sounds like you've decided to use a metric that is more difficult than the metric you could use, which is aggregate neutrality. You mentioned the sun doesn't shine 24 hours a day. Well, of course it does somewhere on the planet, but not on an individual facility. So if you're... If you're measuring carbon neutral at a certain physical location, that's a higher bar. So you talk about storage with batteries and things like that. So it's admirable that you're not taking the sort of easy way out, and looking at it just from an aggregate perspective. >> Yeah. And I guess I would say, you know, I think it's a journey. So you referred to it as sort of easy way out. And, I know, I certainly... I think this is one of the challenges is that oftentimes, action... Climate action can seem overwhelming and we have to find ways to advance and to get to impact. And so I think, you for us and our journey, you know, we started with how can we best make the use of the energy that we have. And so we applied machine learning in our data centers to optimize the energy utilization so that we could really bring down, you know, or optimize how we used energy in the first place. Of course the most renewable energy is the energy you don't use. But then I think the next point was where do we go next and how do we continue to advance to a place where we do get to a carbon free future, at least for us with our energy use as well. And I think, just as importantly, the next step is, "And how do we enable others?" And that's where we're at today. And so, you know, we've made some really exciting announcements and we're hoping that that's just the start of many more to come. >> Well, let's talk about that. So how do you enable others on this journey? >> Yeah, it's great. So when we talked a little bit about carbon free and that idea of energy in 24 x 7, one of the things that we started to focus on was how do we look at energy on an hourly basis, not on an annual basis or on a monthly basis. And so, as we started to pull the, you know, gather that data instrument up, we realized that this information is extremely valuable to our customers as well, who leverage our cloud platform. And so one of the big announcements that we made as part of our suite of sustainability offerings is really... It's called carbon footprint. And it's really providing that information to customers that use our cloud technology to give them a sense of where, how carbon friendly, the energy that they're using. Of course, we are carbon neutral and so effectively the neutrality is zero. But for those who really want to make sure that they're selecting locations where there's clean energy, making sure that their digital infrastructure is running as efficiently as possible. This new tool carbon footprint will give them the opportunity to see that just like you might see on your billing, you know, how much you spend, how much carbon emission there is associated with that as well. So that's one of our big announcements and we've worked very closely with customers like HSBC and Twitter and Salesforce as we've developed that capability so that we know that it helps meet their needs as well. >> So right now the part of your carbon footprint that is managed by this capability would be say GCP consumption or the Google part of a organization's footprint. Any plans in the future to integrate other data sources into a centralized capability? >> Yeah. So I think we have a lot of other exciting news we shared as well. You know, we recognize that our customer's digital footprint is a growing part of their business. As we've seen, sort of the pandemic has accelerated this shift to digital, and we want to make sure that we're bringing the most climate friendly cloud platform, to enable that. But a lot of our customers also have other parts of their business that aren't digital. And so being able to bring sustainability offerings to them, to help them with data, as you mentioned, but also with other tooling is really important. And so the other exciting announcement that we made is that, we are bringing Google Earth Engine to Google Cloud for our customers and Google Earth Engine has been around for over a decade used by, climate researchers, NGOs, It's really a trusted platform for earth observation. And so we're really excited to bring this to our Google Cloud customers as a mechanism, to look at the impacts of climate on their business, as well as see how their business is impacting the environment. And so this is an amazing platform that we're really excited and have partnered very closely with customers like Unilever, to leverage this platform in their business. >> So what are some practical examples of data sources that come out of the Google Earth platform and how they integrate from a sustainability perspective? What are some insights that organizations can gain by leveraging this? >> Super question. So, within Earth Engine, there is, over 50 petabytes of data and over 700 curated data sets. It's the world's largest for earth observation. Things like satellite imagery to look at land cover and deforestation for example, soil moisture, water, and availability of water in flood zones. There's just a... It's a really rich catalog and has been, you know, really curated over a matter of time. It brings also not just historical data, but is constantly refreshed. And so for someone who wants to look at changes over a period of time, it's really the perfect platform for that. And so for example, with Unilever, we have been looking at deforestation and the association with their supply chain because of course, many companies like Unilever have committed to a zero deforestation, And pit land conversion as part of their commitments to climate action. And so this is a really powerful capability. It's sort been kept within the research community and the NGOs for such a long time, that we're really excited to start to now evolve that into applications where we can make a real difference. I think this is part of our mission is to say, "How do we extend our reach in our climate action to not only the billions of users that use our platform, but also our customers who also reach many, many users through their products." So we're really excited about that opportunity. >> So imagine five, 10 years in the future. How does this play out? Give us a view into the enterprise of the future and the kind of information they're going to have at their fingertips. You gave a great example of deforestation within a supply chain, and we're not talking software supply chain here, we're physical supply chains, >> Physical supply chain, yeah. >> If think about a modern enterprise having hundreds or thousands of connections with other enterprises when you're trying to understand what the impact is that you're having on the earth, you have to take all of those things into account. So, can you kind of walk us through a scenario of what that might look like in the not too distant future, the kinds of things they'll have access to? >> You know, I wish I had that, the vision of five to 10 years from now, but if I look at what has evolved even over the last few years, you know, we've been... As consumers, we have so much information at our fingertips, that's both a blessing and a curse in many ways. And I think our job as technology providers is to make sure that the technology that we bring enhances the ability to make decisions quickly and that's... And effectively. And I think that's really what the power of these tools is enabling. So if I look into the future and I look at a little bit of the past and say, you know, "How do we navigate?" We often navigate no longer by paper maps. We navigate by using digital maps. And that same capability is what I'm talking about with some of this geospatial capability is being able to see that information in a way that's very meaningful, very powerful, but also helps you make decisions right now. And so I think that capability is going to be really critical and it's going to bring the complexity of information in a way that I believe is going to help us make better decisions. So today, if we take that... if we continue to take that example that we talked about, you know, often we talk about a lot of decision-making in terms of, you know, pricing, I think in the future, you're going to start to see the complexity of decision making, you know, sort of, you know, becomes more complex, but with the capability and the tools and some of the AI capabilities, we're going to be able to make that very tangible for people so that the decision making is fairly straightforward, but enables us to take into consideration the complexity of the ecosystem. Really excited about the future. I also believe that the future involves a lot more collaboration than maybe we see today, because I think one of the challenges with climate change is, we need to come to an agreed, you know, a shared truth, a shared sense of truth. And that really means we have to break down some of these silos we've created, you know, whether it be in business, whether it be in collaboration with the ecosystem but we're going to start to see a lot more collaboration around data. >> Yeah. Well, Those other things, those other costs that are sometimes hidden and hard to fair it through, in economics terms we refer to those as externalities and may have always been a challenge, how do you account for those real costs of your activity? Jen, I have to say that your passion for this comes through, despite the technology dividing us, it must be a delight working in an environment where you have the support of your organization. And you've got a clear mission that you can wake up every day and pursue that. Talk a little bit about that from a personal perspective. >> Yeah, I wake up every day, well, wake up, I think about this all the time, and I'm reminded of it, everything that I do, you know, whether it be turning off the lights, whether it be running the water too long. I mean, we're now experiencing droughts like we never have you know, historically. And so I think all these things impact us on a personal level. It's really... I feel so fortunate to be able to be thinking about this, to be able to take on something that really is one of the most pressing issues of our time. But I will say I'm also truly inspired by the customers I get to work with and their passion for the same topic. And I really feel like we've crossed this point of really moving to action. So it's no longer just about debating, you know, the science, if you will, we've really started to move into and what action can we take? And I think that is really what is going to both help move the technology and the ability to leverage technology and push us to continue to develop solutions that help make those actions real. But I also am very inspired by the fact that we have these large commitments across organizations to really make change. And I think this is what we all need. >> Well, Jen, thanks for joining us today in this CUBE Conversation and sharing some of the insights that you have along with Google and your customers. We appreciate the work that you do, it's critically important. With that, this is Dave Nicholson. Thanks for joining us for this CUBE Conversation. Until next time, see you then. (bright upbeat music)

(upbeat music) >> Narrator: From around the globe, it's theCUBE, with digital coverage of Postgres Vision 2021, brought to you by EDB. >> Well, good day, everybody. John Walls here on theCUBE, and continuing our CUBE conversation as part of Postgres Vision 2021, sponsored by EDB, with EDB Chief Technology Officer, Mr. Mark Linster. Mark, good morning to you. How are you doing today? >> I'm doing very fine, very good, sir. >> Excellent. Excellent. Glad you could join us. And we appreciate the time, chance, to look at what's going on in this world of data, which, as you know, continues to evolve quite rapidly. So let's just take that 30,000-foot perspective here to begin with here, and let's talk about data, and management, and what Postgres is doing in terms of accelerating all these innovative techniques, and solutions, and services that we're seeing these days. >> Yeah, so I think it's really... It's a fantastic confluence of factors that we've seen in Postgres, or are seeing in Postgres today, where Postgres has really, really matured over the last couple of years, where things like high availability, parallel processing, use of very high core counts, et cetera, have come together with the drive towards digital transformation, the enormous amounts of data that businesses are dealing with today, so, and then the third factor's really the embracing of open source, right? I mean, Linux has shown the way, and has shown that this is really, really possible. And now we're seeing Postgres as, I think, the next big open source innovation, after Linux, achieving the same type of transformation. So it's really, it's a maturing, it's an acceptance, and the big drive towards dealing with a lot more data as part of digital transformation. >> You know, part of that acceptance that you talk about is about kind of accepting the fact that you have a legacy system that maybe, if you're not going to completely overhaul, you still have to integrate, right? You've got to compliment and start this kind of migration. So in your perspective, or from your perspective, what kind of progress is Postgres allowing in the mindset of CTOs among your client base, or whatever, that their legacy systems can function in this new environment, that all is not lost, and while there is some, perhaps, catching up to do, or some patching you have to do here and there, that it's not as arduous, or not as complex, as might appear to be on the face. >> Well, I think there's, the maturing of Postgres that has really really opened this up, right? Where we're seeing that Postgres can handle these workloads, right? And at the same time, there's a growing number of success cases where companies across all industries, financial services, insurance, manufacturing, retail are using Postgres. So, so you're no longer, you're no longer the first leader who's taken a higher risk, right? Like, five or 10 years ago, Postgres knowledge was not readily available. So if you want Postgres, it was really hard to find somebody who could support you, right? Or find an employee that you could hire who would be the Postgres expert. That's no longer the case. There's plenty of books about Postgres. There's lots of conferences about Postgres. It's a big meetup topic. So, getting know how and getting acceptance amongst your team to use Postgres has become a lot easier, right? At the same time, over 90% of all enterprises today use open source in one way or the other. Which basically means they have open source policies. They have ways to bring open source into the development stream. So that makes it possible, right? Whereas before it was really hard, you had to have an individual who would be evangelized to go, get open source, et cetera, now open source is something that almost everybody is using. You know, from government to financing services, open sources use all over the place, right? So, so now you have something that really matured, right? There's a lot of references out there and then you have the policies that make it possible, right? You have the success stories and now all the pieces have come together to deal with this onslaught of data, right? And then maybe the last thing that that really plays a big role is the cloud. Postgres runs everywhere, right? I mean, it runs from an Arduino to Amazon. Everywhere. And so, which basically means if you want to drive agile business transformation, you call Postgres because you don't have to decide today where it's going to run. You're not locking into a vendor. You're not locking into a limited support system. You can run this thing anywhere. It'll run on your laptop. It'll run on every cloud in the world. You can have it managed, you can have it hosted. You can add have every flavor you want and there's lots of good Postgres support companies out there. So all of these factors together is really what makes us so interesting, right? >> Kubernetes and this marriage, this complimentary, you know relationship right now with Kubernetes, what has that done? You think in terms of providing additional services or at least providing perhaps a new approach or new philosophies, new concepts in terms of database management? >> Well, it's maybe the most the most surprising thing or surprising from the outside. Probably not from the inside, but you think that that Postgres this now 25 year old, database twenty-five year old open source project would be kind of like completely, you know, incompatible with Kubernetes, with containers. But what really happens is Postgres in containers today is the number one database, after Engine X. It is the number two software that is being deployed in containers. So it's really become the workhorse of the whole microservices transformation, right? A 25 year old software, well, it has a very small footprint. It has a lot of interesting features like GIS, document processing, now graph capabilities, common table expressions all those things that are really like cool for developers. And that's probably what leads it to be the number one database in containers. So it's absolutely compatible with Kubernetes. And the whole transformation towards microservices is is like, you know, there's nothing better out there. It runs everywhere and has the most innovative technologies in it. And that's what we're seeing. Also, you go to the annual stack overflow survey of developers, right? It's been consistently number one or number two most loved and most used database, right? So, so what's amazing is that it's this relatively old technology that is, you know, beating everybody else in this digital transformation and then the adoption by developers. >> Just like old dog new tricks, right? It's still winning, right? >> Yeah, yeah, and, and, you know, the elephant is the symbol and this elephant does dance. >> Still dancing that's right. You know, and this is kind of a loaded question but there are a lot of databases out there, a lot of options, obviously from your perspective, you know, Postgres is winning, right? And, and, and from the size of the marketplace it is certainly leading RA leader. In your opinion, you know, what, what is this confluence of factors that have influenced this, this market position if you will, of Postgres or market acceptance of Postgres? >> It's, I mean, it's the, it's a maturing of the core. As I said before, that the transaction rates et cetera, Postgres can handle, are growing every year and are growing dramatic, right? So that's one thing. And then you have it, that Postgres is really, I think, the most reliable and relational database out there as what is my opinion, I'm biased, I guess. And, and it's, it's super quality code but then you add to that the innovation drive. I mean, it was the first one out there with good JSONB support, right? And now it's brought in JSON Path as as part of the new SQL standard. So now you can address JSON data inside your database and the same way you do it inside your browser. And that's pretty cool for developers. Then you combine that with PostGIS, right, which is, I think the most advanced GIS system out there in database. Now, now you got relations, asset compliant, GIS and document. You may say what's so cool about that. Well, what's cool about it is I can do absolutely reliable asset compliant transactions. I can have a fantastic personalization engine through JSONB, and then all my applications need to know where is the transaction? Where is the next store? How far away I'm a form of the parking spot? Right? So now I got a really really nice recipe to put the applications of the future together. You add onto that movements toward supporting graph and supporting other capabilities inside the database. So now you got, you got capability, you've got reliability and you got fantastic innovation. I mean, there's nothing better out there. >> Let's hit the security angle here, 'cause you talked about the asset test, and certainly, you know, those, that criteria is being met. No question about that, whether it's isolation, durability, consistency, whatever, but, but security, I don't have to tell you what a growing concern this is. It's already paramount, but we're seeing every day write stories about, about intrusions and and invasions, if you will. So in terms of providing that layer of security that everybody's looking for right now, you know, this this ultra impenetrable force, if you will, what in your mind, what's Postgres allowing for, in that respect in terms of security, peace of mind, and maybe a little additional comfort that everybody in your space is looking for these? >> So, so look at, look at security with a database like, like multiple layers, right? There's not just, you don't do security only one place. It's like when you go into a bank branch, right? I mean, they do lock the door, they have a camera, there is a gate in front of the safe, there's a safe door. And inside the safe, there is still, again safety deposit boxes with individual locks. The same applies to Postgres, right? Where let's say we start at the heart of it where we can secure and protect tables and data. We're using access control lists and groups and usernames, et cetera. Right? So that's, that's at the heart of it. But then outside of that, we can encrypt the data when on disk or when it's in transit on disk. Most people use the Linux disc encryption systems but there's also good partners out there, like like more metric or others that we work with, that that provide security on disk. And then you go out from there and then you have the securing of the database itself again through the log-ins and the groups. You go out from there and now you have the securing of the hosts that the database is sitting on. Then you'll look at securing the data on the networks through SSL and certificates, et cetera. So that basically there's a multi-layer security model layer that positions Postgres extremely well. And then maybe the last thing is to say it certainly integrates very well with ELDAP, active directory, Kerberos, all the usual suspects that you would use to secure technology inside the enterprise or in an open network, like where people work from home, et cetera. >> You talked about the history about this 25 year old technology, you know, founded back at Cal Berkeley, you know, probably almost some 30 years ago and certainly has evolved. And, and as you have pointed out now as a very mature technology, what do you see though in terms of growth from here? Like, where does it go from here in the next 18 months, 24 months, what what do you think is that next barrier, that challenge that that you think the technology and this open source community wants to take on? >> Well, I think there's there's the continuous effort of making it faster, right? That always happens, right? Every database wants to be faster do more transactions per second, et cetera. And there's a lot of work that has been done there. I mean, just in the last couple of years, Postgres performance has increased by over 50%. Right? So, so transactions per second and that kind of scalability that is going to continue to be, to be a focus, right? And then the other one is leading the implementation of the SQL standards, right? So there'd be the most advanced database, the most innovative database, because, remember for many years now, Postgres has come up with a new release on an annual basis. Other database vendors are now catching up to that, but Postgres has done that for years. So innovation has always been at the heart of it. So we started with JSONB, Key value pair came even before that, PostGis has been around for a long time, graph extensions are going to be the next thing, ingestion of time series data is going to, is going to happen. So there's going to be an ongoing stream of innovations happening. But one thing that I can say is because Postgres is a pure open source project. There's not a hard roadmap, like where it's going to go but where it's going to go is always driven by what people want to have, right? There is no product management department. There's no, there's no great visionary that says, "Oh, this is where we're going to go." No, no. What's going to happen is what people want to have, right? If companies or contributors want to have a certain feature because they need it, well, that's how it's going to happen. And that's really been at the heart of this since Mike Stonebraker, who's an advisor to EDB today, invented it. And then, you know, the open source project got created. This has always been the movement to only focus on things that people actually want to have because if nobody wants to have it, we're just not going to build it because nobody wants it. Right? So when you asked me for the roadmap I believe it's going to be, you know, faster, obviously, always faster, right? Everybody wants faster. And then there's going to be innovation features like making the document stored even better, graph ingestion of large time series, et cetera. That's really what I believe is going to drive it forward. >> Wow. Yeah, the market has spoken and as you point out the market will continue to speak and, and drive that bus. So Mark, thank you for the time today. We certainly appreciate that. And wish EDB continued success at Postgres vision 2021. And thanks for the time. >> Thanks John, it was a pleasure. >> You bet. Mark Linster, joining us, the CTO at EDB. I'm John Walls, you've been watching theCUBE. (upbeat music)

(bright upbeat music) >> Hello everyone, and welcome to this exclusive Cube Conversation. We have the pleasure today to welcome, Wim Coekaerts, senior vice president of software development at Oracle. Wim, it's good to see you. How you been, sir? >> Good, it's been a while since we last talked but I'm excited to be here, as always. >> It was during COVID though and so I hope to see you face to face soon. But so Wim, since the Barron's Article declared Oracle a Cloud giant, we've really been sort of paying attention and amping up our coverage of Oracle and asking a lot of questions like, is Oracle really a Cloud giant? And I'll say this, we've always stressed that Oracle invests in R&D and of course there's a lot of D in that equation. And over the past year, we've seen, of course the autonomous database is ramping up, especially notable on Exadata Cloud@Customer, we've covered that extensively. We covered the autonomous data warehouse announcement, the blockchain piece, which of course got me excited 'cause I get to talk about crypto with Juan. Roving Edge, which for everybody who might not be familiar with that, it's an edge cloud service, dedicated regions that you guys announced, which is a managed cloud region. And so it's clear, you guys are serious about cloud. These are all cloud first services using second gen OCI. So, Oracle's making some moves but the question is, what are customers doing? Are they buying this stuff? Are they leaning into these new deployment models for the databases? What can you tell us? >> You know, definitely. And I think, you know, the reason that we have so many different services is that not every customer is the same, right? One of the things that people don't necessarily realize, I guess, is in the early days of cloud lots of startups went there because they had no local infrastructure. It was easy for them to get started in something completely new. Our customers are mostly enterprise customers that have huge data centers in many cases, they have lots of real estate local. And when they think about cloud they're wondering how can we create an environment that doesn't cause us to have two ops teams and two ways of managing things. And so, they're trying to figure out exactly what it means to take their real estate and either move it wholesale to the cloud over a period of years, or they say, "Hey, some of these things need to be local maybe even for regulatory purposes." Or just because they want to keep some data locally within their own data centers but then they have to move other things remotely. And so, there's many different ways of solving the problem. And you can't just say, "Here's one cloud, this is where you go and that's it." So, we basically say, if you're on prem, we provide you with cloud services on-premises, like dedicated regions or Oracle Exadata Cloud@Customer and so forth so that you get the benefits of what we built for cloud and spend a lot of time on, but you can run them in your own data center or people say, "No, no, no. I want to get rid of my data centers, I do it remotely." Okay, then you do it in Oracle cloud directly. Or you have a hybrid model where you say, "Some stays local, some is remote." The nice thing is you get the exact same API, the exact same way of managing things, no matter how you deploy it. And that's a big differentiator. >> So, is it fair to say that you guys have, I think of it as a purpose built club, 'cause I talk to a lot of customers. I mean, take an insurance app like Claims, and customers tell me, "I'm not putting that into the public cloud." But you're making a case that it actually might make sense in your cloud because you can support those mission critical applications with the exact same experience, same API, same... I can get, you know, take Rack for instance, I can't get, you know, real application clusters in an Amazon cloud but presumably I can get them in your cloud. So, is it fair to say you have a purpose built cloud specifically for the most demanding applications? Is that a right way to look at it or not necessarily? >> Well, it's interesting. I think the thing to be careful of is, I guess, purpose built cloud might for some people mean, "Oh, you can only do things if it's Oracle centric." Right, and so I think that fundamentally, Oracle cloud provides a generic cloud. You can run anything you want, any application, any deployment model that you have. Whether you're an Oracle customer or not, we provide you with a full cloud service, right? However, given that we know and have known, obviously for a long time, how our products run best, when we designed OCI gen two, when we designed the networking stack, the storage layer and all that stuff, we made sure that it would be capable of running our more complex environments because our advantage is, Oracle customers have a place where they can run Oracle the best. Right, and so obviously the context of purpose-built fits that model, where yes, we've made some design choices that allow us to run Rack inside OCI and allow us to deploy Exadatas inside OCI which you cannot do in other clouds. So yes, it's purpose built in that sense but I would caution on the side of that it sometimes might imply that it's unique to Oracle products and I guess one way to look at it is if you can run Oracle, you can run everything else, right? Because it's such a complex suite of products that if you can run that then it it'll support any other (mumbling). >> Right. Right, it's like New York city. You make it there, you can make it anywhere. If I can run the most demanding mission critical applications, well, then I can run a web app for instance, okay. I got a question on tooling 'cause there's a lot of tooling, like sometimes it makes my eyes bleed when I look at all this stuff and doesn't... Square the circle for me, doesn't autonomous, an autonomous database like Autonomous Linux, for instance, doesn't it eliminate the need for all these management tools? >> You know, it does. It eliminates the need for the management at the lower level, right. So, with the autonomous Linux, what we offer and what we do is, we automatically patch the operating system for you and make sure it's secure from a security patching point of view. We eliminate the downtime, so when we do it then you don't have to restart applications. However, we don't know necessarily what the app is that is installed on top of it. You know, people can deploy their own applications, they can run third party applications, they can use it for development environments and so forth. So, there's sort of the core operating system layer and on the database side, you know, we take care of database patching and upgrades and storage management and all that stuff. So the same thing, if you run your own application inside the database, we can manage the database portion but we don't manage the application portion just like on the operating system. And so, there's still a management level that's required, no matter what, a level above that. And the other thing and I think this is what a lot of the stuff we're doing is based on is, you still have tons of stuff on-premises that needs full management. You have applications that you migrate that are not running Autonomous Linux, could be a Windows application that's running or it could be something on a different Linux distribution or you could still have some databases installed that you manage yourself, you don't want to use the autonomous or you're on a third-party. And so we want to make sure that we can address all of them with a single set of tools, right. >> Okay, so I wonder, can you give us just an overview, just briefly of the products that comprise into the cloud services, your management solution, what's in that portfolio? How should we think about it? >> Yeah, so it basically starts with Enterprise Manager on-premises, right? Which has been the tool that our Oracle database customers in particular have been using for many years and is widely used by our customer base. And so you have those customers, most of their real estate is on-premises and they can use enterprise management with local. They have it running and they don't want to change. They can keep doing that and we keep enhancing as you know, with newer versions of Enterprise Manager getting better. So, then there's the transition to cloud and so what we've been doing over the last several years is basically, looking at the things, well, one aspect is looking at things people, likes of Enterprise Manager and make sure that we provide similar functionality in Oracle cloud. So, we have Performance Hub for looking at how the database performance is working. We have APM for Application Performance Monitoring, we have Logging Analytics that looks at all the different log files and helps make sense of it for you. We have Database Management. So, a lot of the functionality that people like in Enterprise Manager mentioned the database that we've built into Oracle cloud, and, you know, a number of other things that are coming Operations Insights, to look at how databases are performing and how we can potentially do consolidation and stuff. So we've basically looked at what people have been using on-premises, how we can replicate that in Oracle cloud and then also, when you're in a cloud, how you can make make use of all the base services that a cloud vendor provides, telemetry, logging and so forth. And so, it's a broad portfolio and what it allows us to do with our customers is say, "Look, if you're predominantly on-prem, you want to stay there, keep using Enterprise Manager. If you're starting to move to Oracle cloud, you can first use EM, look at what's happening in the cloud and then switch over, start using all the management products we have in the cloud and let go of the Enterprise Manager instance on-premise. So you can gradually shift, you can start using more and more. Maybe you start with analytics first and then you start with insights and then you switch to database management. So there's a whole suite of possibilities. >> (indistinct) you mentioned APM, I've been watching that space, it's really evolved. I mean, you saw, you know, years ago, Splunk came out with sort of log analytics, maybe simplified that a little bit, now you're seeing some open source stuff come out. You're seeing a lot of startups come out, you saw Cisco made an acquisition with AppD and that whole space is transforming it seems that the future is all about that end to end visibility, simplifying the ability to remediate problems. And I'm thinking, okay, you just mentioned, you guys have a lot of these capabilities, you got Autonomous, is that sort of where you're headed with your capabilities? >> It definitely is and in fact, one of the... So, you know, APM allows you to say, "Hey, here's my web browser and it's making a connection to the database, to a middle tier" and it's hard for operations people in companies to say, hey, the end user calls and says, "You know, my order entry system is slow. Is it the browser? Is it the middle tier that they connect to? Is it the database that's overloaded in the backend?" And so, APM helps you with tracing, you know, what happens from where to where, where the delays are. Now, once you know where the delay is, you need to drill down on it. And then you need to go look at log files. And that's where the logging piece comes in. And what happens very often is that these log files are very difficult to read. You have networking log files and you have database log files and you have reslog files and you almost have to be an expert in all of these things. And so, then with Logging Analytics, we basically provide sort of an expert dashboard system on top of that, that allows us to say, "Hey! When you look at logging for the network stack, here are the most important errors that we could find." So you don't have to go and learn all the details of these things. And so, the real advantages of saying, "Hey, we have APM, we have Logging Analytics, we can tie the two together." Right, and so we can provide a solution that actually helps solve the problem, rather than, you need to use APM for one vendor, you need to use Logging Analytics from another vendor and you know, that doesn't necessarily work very well. >> Yeah and that's why you're seeing with like the ELK Stack it's cool, you're an open source guy, it's cool as an open source, but it's complicated to set up all that that brings. So, that's kind of a cool approach that you guys are taking. You mentioned Enterprise Manager, you just made a recent announcement, a new release. What's new in that new release? >> So Enterprise Manager 13.5 just got released. And so EM keeps improving, right? We've made a lot of changes over over the years and one of the things we've done in recent years is do more frequent updates sort of the cloud model frequent updates that are not just bug fixes but also introduce new functionality so people get more stuff more frequently rather than you know, once a year. And that's certainly been very attractive because it shows that it's a lively evolving product. And one of the main focus areas of course is cloud. And so a lot of work that happens in Enterprise Manager is hybrid cloud, which basically means I run Enterprise Manager and I have some stuff in Oracle cloud, I might have some other stuff in another cloud vendors environment and so we can actually see which databases are where and provide you with one consolidated view and one tool, right? And of course it supports Autonomous Database and Exadata in cloud servers and so forth. So you can from EM see both your databases on-premises and also how it's doing in in Oracle cloud as you potentially migrate things over. So that's one aspect. And then the other one is in terms of operations and automation. One of the things that we started doing again with Enterprise Manager in the last few years is making sure that everything has a REST API. So we try to make the experience with Enterprise Manager be very similar to how people work with a cloud service. Most folks now writing automation tools are used to calling REST APIs. EM in the early days didn't have REST APIs, now we're making sure everything works that way. And one of the advantages is that we can do extensibility without having to rewrite the product, that we just add the API clause in the agent and it makes it a lot easier to become part of the modern system. Another thing that we introduced last year but that we're evolving with more dashboards and so forth is the Grafana plugin. So even though Enterprise Manager provides lots of cool tools, a lot of cloud operations folks use a tool called Grafana. And so we provide a plugin that allows customers to have Grafana dashboards but the data actually comes out of Enterprise Manager. So that allows us to integrate EM into a more cloudy world in a cloud environment. I think the other important part is making sure that again, Enterprise Manager has sort of a cloud feel to it. So when you do patching and upgrades, it's near zero downtime which basically means that we do all the upgrades for you without having to bring EM down. Because even though it's a management tool, it's used for operations. So if there were downtime for patching Enterprise Manager for an hour, then for that hour, it's a blackout window for all the monitoring we do. And so we want to avoid that from happening, so now EM is upgrading, even though all the events are still happening and being processed, and then we do a very short switch. So that help our operations people to be more available. >> Yes. I mean, I've been talking about Automated Operations since, you know, lights out data centers since the eighties back in (laughs). I remember (indistinct) data center one-time lights out there were storage tech libraries in there and so... But there were a lot of unintended consequences around, you know, automated ops, and so people were sort of scared to go there, at least lean in too much but now with all this machine intelligence... So you're talking about ops automation, you mentioned the REST APIs, the Grafana plugins, the Cloud feel, is that what you're bringing to the table that's unique, is that unique to Oracle? >> Well, the integration with Oracle in that sense is unique. So one example is you mentioned the word migration, right? And so database migration tends to be something, you know, customers obviously take very serious. We go from one place, you have to move all your data to another place that runs in a slightly different environment. And so how do you know whether that migration is going to work? And you can't migrate a thousand databases manually, right? So automation, again, it's not just... Automation is not just to say, "Hey, I can do an upgrade of a system or I can make sure that nothing is done by hand when you patch something." It's more about having a huge fleet of servers and a huge fleet of databases. How can you move something from one place to another and automate that? And so with EM, you know, we start with sort of the prerequisite phase. So we're looking at the existing environment, how much memory does it need? How much storage does it use? Which version of the database does it have? How much data is there to move? Then on the target side, we see whether the target can actually run in that environment. Then we go and look at, you know, how do you want to migrate? Do you want to migrate everything from a sort of a physical model or do you want to migrate it from a logical model? Do you want to do it while your environment is still running so that you start backing up the data to the target database while your existing production system is still running? Then we do a short switch afterwards, or you say, "No, I want to bring my database down. I want to do the migrate and then bring it back up." So there's different deployment models that we can let our customers pick. And then when the migration is done, we have a ton of health checks that can validate whether the target database will run through basically the exact same way. And then you can say, "I want to migrate 10 databases or 50 databases" and it'll work, It's all automated out of the box. >> So you're saying, I mean, you've looked at the prevailing way you've done migrations, historically you'd have to freeze the code and then migrate, and it would take forever, it was a function of the number of lines of code you had. And then a lot of times, you know, people would say, "We're not going to freeze the code" and then they would almost go out of business trying to merge the two. You're saying in 2021, you can give customers the choice, you can migrate, you could change the, you know, refuel the plane while you're in midair? Is that essentially what you're saying? >> That's a good way of describing it, yeah. So your existing database is running and we can do a logical backup and restore. So while transactions are happening we're still migrating it over and then you can do a cutoff. It makes the transition a lot easier. But the other thing is that in the past, migrations would typically be two things. One is one database version to the next, more upgrades than migration. Then the second one is that old hardware or a different CPU architecture are moving to newer hardware in a new CPU architecture. Those were sort of the typical migrations that you had prior to Cloud. And from a CIS admin point of view or a DBA it was all something you could touch, that you could physically touch the boxes. When you move to cloud, it's this nebulous thing somewhere in a data center that you have no access to. And that by itself creates a barrier to a lot of admins and DBA's from saying, "Oh, it'll be okay." There's a lot of concern. And so by baking in all these tests and the prerequisites and all the dashboards to say, you know, "This is what you use. These are the features you use. We know that they're available on the other side so you can do the migration." It helps solve some of these problems and remove the barriers. >> Well that was just kind of same same vision when you guys came up with it. I don't know, quite a while ago now. And it took a while to get there with, you know, you had gen one and then gen two but that is, I think, unique to Oracle. I know maybe some others that are trying to do that as well, but you were really the first to do that and so... I want to switch topics to talk about security. It's hot topic. You guys, you know, like many companies really focused on security. Does Enterprise Manager bring any of that over? I mean, the prevailing way to do security often times is to do scripts and write, you know, custom security policy scripts are fragile, they break, what can you tell us about security? >> Yeah. So there's really two things, you know. One is, we obviously have our own best security practices. How we run a database inside Oracle for our own world, we've learned about that over the years. And so we sort of baked that knowledge into Enterprise Manager. So we can say, "Hey, if you install this way, we do the install and the configuration based on our best practice." That's one thing. The other one is there's STIG, there's PCI and they're ShipBob, those are the main ones. And so customers can do their own way. They can download the documentation and do it manually. But what we've done is, and we've done this for a long time, is basically bake those policies into Enterprise Manager. So you can say, "Here's my database this needs to be PCI compliant or it needs to be HIPAA compliant and you push a button and then we validate the policies in those documents or in those prescript described files. And we make sure that the database is combined to that. And so we take that manual work and all that stuff basically out of the picture, we say, "Push this button and we'll take care of it." >> Now, Wim, but just quick sidebar here, last time we talked, it was under a year ago. It was definitely during COVID and it's still during COVID. We talked about the state of the penguin. So I'm wondering, you know, what's the latest update for Linux, any Linux developments that we should be aware of? >> Linux, we're still working very hard on Autonomous Linux and that's something where we can really differentiate and solve a problem. Of course, one of the things to mention is that Enterprise Manager can can do HIPAA compliance on Oracle Linux as well. So the security practices are not just for the database it can also go down to the operating system. Anyway, so on the Autonomous Linux side, you know, management in an Oracle Cloud's OS management is evolving. We're spending a lot of time on integrating log capturing, and if something were to go wrong that we can analyze a log file on the fly and send you a notification saying, "Hey, you know there was this bug and here's the cause." And it was potentially a fix for it to Autonomous Linux and we're putting a lot of effort into that. And then also sort of IT/operation management where we can look at the different applications that are running. So you're running a web server on a Linux environment or you're running some Java processes, we can see what's running. We can say, "Hey, here's the CPU utilization over the past week or the past year." And then how is this evolving? Say, if something suddenly spikes we can say, "Well, that's normal, because every Monday morning at 10 o'clock there's a spike or this is abnormal." And then you can start drilling this down. And this comes back to overtime integration with whether it's APM or Logging Analytics, we can tie the dots, right? We can connect them, we can say, "Push this thing, then click on that link." We give you the information. So it's that integration with the entire cloud platform that's really happening now >> Integration, there's that theme again. I want to come back to migration and I think you did a good job of explaining how you sort of make that non-disruptive and you know, your customers, I think, you know, generally you're pushing you know, that experience which makes people more comfortable. But my question is, why do people want to migrate if it works and it's on prem, are they doing it just because they want to get out of the data center business? Or is it a better experience in the cloud? What can you tell us there? >> You know, it's a little bit of everything. You know, one is, of course the idea that data center maintenance costs are very high. The other one is that when you run your own data center, you know, we obviously have this problem but when you're a cloud vendor, you have these problems but we're in this business. But if you buy a server, then in three years that server basically is depreciated by new versions and they have to do migration stuff. And so one of the advantages with cloud is you push a button, you have a new version of the hardware, basically, right? So the refreshes happen on a regular basis. You don't have to go and recycle that yourself. Then the other part is the subscription model. It's a lot easier to pay for what you use rather than you have a data center whether it's used or not, you pay for it. So there's the cost advantages and predictability of what you need, you pay for, you can say, "Oh next year we need to get x more of EMs." And it's easier to scale that, right? We take care of dealing with capacity planning. You don't have to deal with capacity planning of hardware, we do that as the cloud vendor. So there's all these practical advantages you get from doing it remotely and that's really what the appeal is. >> Right. So, as it relates to Enterprise Manager, did you guys have to like tear down the code and rebuild it? Was it entire like redo? How did you achieve that? >> No, no, no. So, Enterprise Manager keeps evolving and you know, we changed the underlying technologies here and there, piecemeal, not sort of a wholesale replacement. And so in talking about five, there's a lot of new stuff but it's built on the existing EM core. And so we're just, you know, improving certain areas. One of the things is, stability is important for our customers, obviously. And so by picking things piecemeal, we replace one engine rather than the whole thing. It allows us to introduce change more slowly, right. And then it's well-tested as a unit and then when we go on to the next thing. And then the other one is I mentioned earlier, a lot of the automation and extensibility comes from REST APIs. And so instead of basically re-writing everything we just provide a REST endpoint and we make all the new features that we built automatically be REST enabled. So that makes it a lot easier for us to introduce new stuff. >> Got it. So if I want to poke around with this new version of Enterprise Manager, can I do that? Is there a place I can go, do I have to call a rep? How does that work? >> Yeah, so for information you can just go to oracle.com/enterprise manager. That's the website that has all the data. The other thing is if you're already playing with Oracle Cloud or you use Oracle Cloud, we have Enterprise Manager images in the marketplace. So if you have never used EM, you can go to Oracle Cloud, push a button in the marketplace and you get a full Enterprise Manager installation in a matter of minutes. And then you can just start using that as well. >> Awesome. Hey, I wanted to ask you about, you know, people forget that you guys are the stewards of MySQL and we've been looking at MySQL Database Cloud service with HeatWave Did you name that? And so I wonder if you could talk about what you're doing with regard to managing HeatWave environments? >> So, HeatWave is the MySQL option that helps with analytics, right? And it really accelerates MySQL usage by 100 x and in some cases more and it's transparent to the customer. So as a MySQL user, you connect with standard MySQL applications and APIs and SQL and everything. And the HeatWave part is all done within the MySQL server. The engine itself says, "Oh, this SQL query, we can offload to the backend HeatWave cluster," which then goes in memory operations and blazingly fast returns it to you. And so the nice thing is that it turns every single MySQL database into also a data warehouse without any change whatsoever in your application. So it's been widely popular and it's quite exciting. I didn't personally name it, HeatWave, that was not my decision, but it sounds very cool. >> That's very cool. >> Yeah, It's a very cool name. >> We love MySQL, we started our company on the lamp stack, so like many >> Oh? >> Yeah, yeah. >> Yeah, yeah. That's great. So, yeah. And so with HeatWave or MySQL in general we're basically doing the same thing as we have done for the Oracle Database. So we're going to add more functionality in our database management tools to also look at HeatWave. So whether it's doing things like performance hub or generic database management and monitoring tools, we'll expand that in, you know, in the near future, in the future. >> That's great. Well, Wim, it's always a pleasure. Thank you so much for coming back in "The Cube" and letting me ask all my Colombo questions. It was really a pleasure having you. (mumbling) >> It's good be here. Thank you so much. >> You're welcome. And thank you for watching, everybody, this is Dave Vellante. We'll see you next time. (bright music)

>>Yeah. >>All right. Welcome back to our third session, which is all about administering analytics at Global Scale. We're gonna be discussing how you can implement security data compliance and governance across the globe at for large numbers of users to ensure thoughts. What is open for everyone across your organization? So coming right up is Cheryl Zang, who is a senior director of product management of Thought spot, and Kendrick. He threw the sports sports director of Systems Engineering. So, Cheryl and Kendrick, the floor is yours. >>Thank you, Tina, for the introduction. So let's talk about analytics scale on. Let's understand what that is. It's really three components. It's the access to not only data but its technology, and we start looking at the intersection of that is the value that you get as an organization. When you start thinking about analytics scale, a lot of times we think of analysts at scale and we look at the cloud as the A seven m for it, and that's a That's an accurate statement because people are moving towards the cloud for a variety of reasons. And if you think about what's been driving, it has been the applications like Salesforce, Forcados, Mongo, DB, among others. And it's actually part of where we're seeing our market go where 64% of the company's air planning to move their analytics to the cloud. And if you think of stock spotted specifically, we see that vast majority of our customers are already in the cloud with one of the Big Four Cloud Data warehouses, or they're evaluated. And what we found, though, is that even though companies are moving their analytics to the cloud, we have not solved. The problem of accessing the data is a matter of fact. Our customers. They're telling us that 10 to 25% of that data warehouse that they're leveraging, they've moved and I'm utilizing. And if you look at in General, Forrester says that 60 to 73% of data that you have is not being leveraged, and if we think about why you go through, you have this process of taking enterprise data, moving it into these cubes and aggregates and building these reports dashboards. And there's this bottleneck typically of that be I to and at the end of the day, the people that are getting that data on the right hand side or on Lee. Anywhere from 20 to 30% of the population when companies want to be data driven is 20 to 30% of the population. Really what you're looking for now it's something north of that. And if you think of Cloud data, warehouse is being the the process and you bring Cloud Data Warehouse and it's still within the same framework. You know? Why invest? Why invest and truly not fix the problem? And if you take that out and your leverage okay, you don't necessarily have the You could go directly against the warehouse, but you're still not solving the reports and dashboards. Why investing truly not scale? It's the three pillars. It's technology, it's data, and it's a accessibility. So if we look at analytics at scale, it truly is being able to get to that north of the 20 to 30% have that be I team become enablers, often organization. Have them be ableto work with the data in the Cloud Data warehouse and allow the cells marking finding supplies and then hr get direct access to that. Ask their own questions to be able to leverage that to be able to do that. You really have to look at your modern data architecture and figure out where you are in this maturity, and then they'll be able to build that out. So you look at this from the left to right and sources. It's ingestion transformation. It's the storage that the technology brains e. It's the data from a historical predictive perspective. And then it's the accessibility. So it's technology. It's data accessibility. And how do you build that? Well, if you look at for a thought to spot perspective, it truly is taking and driving and leveraging the cloud data warehouse architectures, interrogated, essay behind it. And then the accessibility is the search answers pen boards and embedded analytics. If you take that and extend it where you want to augment it, it's adding our partners from E T L R E L t. Perspective like al tricks talent Matile Ian Streaming data from data brings or if you wanna leverage your cloud, data warehouses of Data Lake and then leverage the Martin capability of your child data warehouse. The augmentation leveraging out through its data bricks and data robot. And that's where your data side of that pillar gets stronger, the technologies are enabling it. And then the accessibility from the output. This thought spot. Now, if you look at the hot spots, why and how do we make this technology accessible? What's the user experience we are? We allow an organization to go from 20 to 30% population, having access to data to what it means to be truly data driven by our users. That user experience is enabled by our ability to lead a person through the search process. There are search index and rankings. This is built for search for corporate data on top of the Cloud Data Warehouse. On top of the data that you need to be able to allow a person who doesn't understand analytics to get access to the data and the questions they need to answer, Arcuri Engine makes it simple for customers to take. Ask those questions and what you might think are not complex business questions. But they turn into complex queries in the back end that someone who typically needs to know that's that power user needs to know are very engine. Isolate that from an end user and allows them to ask that question and drive that query. And it's built on an architecture that allows us to change and adapt to the types of things. It's micro services architecture, that we've not only gone from a non grim system to our cloud offering, in a matter of of really true these 23 years. And it's amazing the reason why we can do that, do that and in a sense, future proof your investment. It's because of the way we've developed this. It's wild. First, it's Michael Services. It's able to drive. So what this architecture ER that we've talked about. We've seen different conversations of beyond its thought spot everywhere, which allows us to take that spot. One. Our ability to for search for search data for auto analyzed the Monitor with that govern security in the background and being able to leverage that not only internally but externally and then being able to take thought spot modeling language for that analysts and that person who just really good at creating and let them create these models that it could be deployed anywhere very, very quickly and then taking advantage off the Cloud Data warehouse or the technology that you have and really give you accessibility the technology that you need as well as the data that you need. That's what you need to be able to administer, uh, to take analytics at scale. So what I'm gonna do now is I'm gonna turn it over to Cheryl and she's gonna talk about administration in thought spot. Cheryl, >>thank you very much Can take. Today. I'm going to show you how you can administrator and manage South Spot for your organization >>covering >>streaming topics, the user management >>data management and >>also user adoption and performance monitoring. Let's jump into the demo. >>I think the Southport Application The Admin Council provides all the core functions needed for system level administration. Let's start with user management and authentication. With the user tab. You can add or delete a user, or you can modify the setting for an existing user. For example, user name, password email. Or you can add the user toe a different group with the group's tab. You can add or delete group, or you can manage the group setting. For example, Privileges associated with all the group members, for example, can administrate a soft spot can share data with all users or can manage data this can manage data privilege is very important. It grants a user the privileges to add data source added table and worksheet, manage data for different organizations or use cases without being an at me. There is also a field called Default Pin Board. You can select a set of PIN board that will be shown toe all of the users in that group on their homepage in terms off authentication. Currently, we support three different methods local active directory and samel By default. Local authentication is enabled and you can also choose to have several integration with an external identity provider. Currently, we support actor Ping Identity, Seaside Minor or a T. F. S. The third method is integration with active directory. You can configure integration with L DAP through active directory, allowing you to authenticate users against an elder up server. Once the users and groups are added to the system, we can share pin board wisdom or they can search to ask and answer their own questions. To create a searchable data, we first need to connect to our data warehouses with embraced. You can directly query the data as it exists in the data warehouse without having to move or transfer the data. In this page, you can add a connection to any off the six supported data warehouses. Today we will be focusing on the administrative aspect off the data management. So I will close the tap here and we will be using the connections that are already being set up. Under the Data Objects tab, we can see all of the tables from the connections. Sometimes there are a lot of tables, and it may be overwhelming for the administrator to manage the data as a best practice. We recommend using stickers toe organize your data sets here, we're going to select the Salesforce sticker. This will refined a list off tables coming from Salesforce only. This helps with data, lineage and the traceability because worksheets are curated data that's based on those tables. Let's take a look at this worksheet. Here we can see the joints between tables that created a schema. Once the data analyst created the table and worksheet, the data is searchable by end users. Let's go to search first, let's select the data source here. We can see all of the data that we have been granted access to see Let's choose the Salesforce sticker and we will see all of the tables and work ship that's available to us as a data source. Let's choose this worksheet as a data source. Now we're ready to search the search Insight can be saved either into a PIN board or an answer. Okay, it's important to know that the sticker actually persist with PIN board and answers. So when the user logging, they will be able to see all of the content that's available to them. Let's go to the Admin Council and check out the User Adoption Pin board. The User Adoption Pin board contains essential information about your soft spot users and their adoption off the platform. Here, you can see daily active user, weekly, active user and monthly active user. Count that in the last 30 days you can also see the total count off the pin board and answers that saved in the system. Here, you can see that unique count off users. Now. You can also find out the top 10 users in the last 30 days. The top 10 PIN board consumers and top 10 ad hoc searchers here, you can see that trending off weekly, active users, daily, active users and hourly active users over time. You can also get information about popular pin boards and user actions in the last one month. Now let's zoom in into this chart. With this chart, you can see weekly active users and how they're using soft spot. In this example, you can see 60% of the time people are doing at Hawk search. If you would like to see what people are searching, you can do a simple drill down on quarry tax. Here we can find out the most popular credit tax that's being used is number off the opportunities. At last, I would like to show you assistant performance Tracking PIN board that's available to the ad means this PIN board contains essential information about your soft spot. Instance performance You this pimple. To understand the query, Leighton see user traffic, how users are interacting with soft spot, most frequently loaded tables and so on. The last component toe scowling hundreds of users, is a great on boarding experience. A new feature we call Search Assist helps automate on boarding while ensuring new users have the foundation. They need to be successful on Day one, when new users logging for the first time, they're presented with personalized sample searches that are specific to their data set. In this example, someone in a sales organization would see questions like What were sales by product? Type in 2020. From there are guided step by step process helps introduce new users with search ensuring a successful on boarding experience. The search assist. The coach is a customized in product Walk through that uses your own data and your own business vocabulary to take your business users from unfamiliar to near fluent in minutes. Instead of showing the entire end user experience today, I will focus on the set up and administration side off the search assist. Search Assist is easy to set up at worksheet level with flexible options for multiple guided lessons. Using preview template, we help you create multiple learning path based on department or based on your business. Users needs to set up a learning path. You're simply feeling the template with relevant search examples while previewing what the end user will see and then increase the complexity with each additional question toe. Help your users progress >>in summary. It is easy to administrator user management, data management, management and the user adoption at scale Using soft spot Admin Council Back to you, Kendrick. >>Thank you, Cheryl. That was great. Appreciate the demo there. It's awesome. It's real life data, real life software. You know what? Enclosing here? I want to talk a little bit about what we've seen out in the marketplace and some of them when we're talking through prospects and customers, what they talk a little bit about. Well, I'm not quite area either. My data is not ready or I've got I don't have a file data warehouse. That's this process. In this thinking on, we have examples and three different examples. We have a company that actually had never I hadn't even thought about analytics at scale. We come in, we talked to them in less than a week. They're able to move their data thought spot and ask questions of the billion rose in less than a week now. We've also had customers that are early adoption. They're sticking their toes in the water around the technology, so they have a lot of data warehouse and they put some data at it, and with 11 minute within 11 minutes, we were able to search on a billion rows of their data. Now they're adding more data to combine to, to be able to work with. And then we have customers that are more mature in their process. Uh, they put large volumes of data within nine minutes. We're asking questions of their data, their business users air understanding. What's going on? A second question we get sometimes is my data is not clean. We'll talk Spot is very, very good at finding that type of data. If you take, you start moving and becomes an inner door process, and we can help with that again. Within a week, we could take data, get it into your system, start asking business questions of that and be ready to go. You know, I'm gonna turn it back to you and thank you for your time. >>Kendrick and Carol thank you for joining us today and bringing all of that amazing inside for our audience at home. Let's do a couple of stretches and then join us in a few minutes for our last session of the track. Insides for all about how Canadian Tire is delivering Korean making business outcomes would certainly not in a I. So you're there

>> Voiceover: From around the globe, it's theCUBE, with coverage of Kubecon and CloudNativeCon, North America, 2020, virtual brought to you by Red Hat, the Cloud Native Computing Foundation and Ecosystem Partners. >> Welcome back to theCUBE's coverage, virtual coverage of Kubecon and CloudNativeCon 2020. We're not in person this year, normally we're there in person. We have to do remote because of the pandemic, but hey, it opens up more conversations. And this is theCUBE virtual. I'm John Furrier, your host. And you'll see a lot of interviews. We've got some great guests, Talking to the leaders, the developers, the end users, as well as the vendors with the CNCF, we got two great guests, Priyanka Sharma, the General Manager of the CNCF, great to see you and Stephen Augustus OSS Engineer at VMware. He's also the KubeCon co-chair back on the cube. Thanks for coming on folks. I appreciate it. >> Thank you for having us. So, thanks for coming on, actually, remote and virtual. We're doing a lot of interviews, we're getting some perspectives, people are chatting in Slack. It's still got the hallway vibe feel, a lot of talks, a lot of action, keynotes happening, but I think the big story for me, and I would like to talk about, I want to get your perspective is this new working group that's out there. So I know there's some news around it. Could you take a minute to explain kind of what this is all about? >> Sure. I'll give a little bit of context for those who may have missed my keynote which... very bad. (Priyanka laughs) As I announced, I'm so proud to be working with the likes of Stephen Augustus here, and a bunch of other folks from different companies, different open source projects, et cetera, to bring inclusive naming to code. I think it's been a forever issue. Quite frankly. We've had many problematic terms in software out there. The most obvious one being master-slave. That really shouldn't be there. That have no place in an inclusive world, inclusive software, inclusive community with the help of amazing people like Stephen, folks from IBM, Red Hat, and many, many others. We came together because while there's a lot of positive enthusiasm and excitement for people to make the changes that are necessary to make the community welcome for all, there's a lot of different work streams happening. And we really wanted to make sure there is a centralized place for guidelines and discussion for everybody in a very non...pan-organizational kind of way. And so that's the working group that John is talking about. With that said, Stephen, I think you can do the best justice to speak to the overall initiative. >> Yeah, absolutely. So I think that's to Priyanka's point, there are lots of people who are interested in this work and again, lots of work where this is already happening, which is very exciting to say, but as any good engineer, I think that's it's important to not duplicate your work. It's important to recognize the efforts that are happening elsewhere and work towards bringing people together. So part of this is providing, being able to provide a forum for discussion for a variety of companies, for a variety of associations that... and foundations that are involved in inclusive naming efforts. And then to also provide a framework for walking people through how we evaluate language and how we make these kinds of changes. As an example, for Kubernetes, we started off the Kubernetes working group naming and the hope for the working group naming was that it was going to evolve into hopefully an effort like this, where we could bring a lot of people on and not just talk about Kubernetes. So since we formed that back in, I want to say, June-ish, we've done some work on about of providing a language evaluation framework, providing templates for recommendations, providing a workflow for moving from just a suggestion into kind of actuating those ideas right and removing that language where it gets tricky and code is thinking about, thinking about, say a Kubernetes API. And in fact that we have API deprecation policies. And that's something that we have to if offensive language is in one of our APIs, we have to work through our deprecation policy to get that done. So lots of moving parts, I'm very excited about the overall effort. >> Yeah, I mean, your mind can explode if you just think about all the complications involved, but I think this is super important. I think the world has voted on this, I think it's pretty obvious and Priyanka, you hit some of the key top-line points, inclusive software. This is kind of the high order bit, but when you get down to it, it's hard as hell to do, because if you want to get ne new namings and/or changing namings accepted by the community and code owners, you're dealing with two things, a polarizing environment around the world today, and two, the hassles involved, which includes duplicate efforts. So you've got kind of a juggling act going on between two forces. So it's a hard problem. So how are you tackling this? Because it's certainly the right thing to do. There's no debate there. How do you make it happen? How do you go in without kind of blowing things up, if you will? And do it in a way that's elegant and clean and accept it. 'Cause that's the... end of the day, it's acceptance and putting it code owners. >> Absolutely. I think so, as you said, we live in a polarizing environment right now. Most of us here though know that this is the right thing to do. Team CloudNative is for everyone. And that is the biggest takeaway I hope people get from our work in this initiative. Open source belongs to everybody and it was built for the problems of today. That's why I've been working on this. Now, when it goes into actual execution, as you said, there are many moving parts, Stephen and the Kubernetes working group, is our shining example and a really good blueprint for many folks to utilize. In addition to that, we have to bring in diverse organizations. It's not just open source projects. It's not just companies. It's also standards organizations. It's also folks who think about language in books, who have literally done PhDs in this subject. And then there are folks who are really struggling through making the changes today and tomorrow and giving them hope and excitement. So that at the end of this journey, not only do you know you've done the right thing, but you'd be recognized for it. And more people will be encouraged by your own experience. So we and the LF have been thinking at it from a holistic perspective, let's bring in the standards bodies, let's bring in the vendors, let's bring in the open source projects, give them guidelines and blueprints that we are lucky that our projects are able to generate, combine it with learnings from other people, because many people are doing great work so that there is one cohesive place where people can go and learn from each other. Eventually, what we hope to do is also have like a recognition program so that it's like, hey, this open source project did this. They are now certified X or there's like an awards program. They're still figuring that piece out, but more to come on that space. That's my part. But Stephen can tell you about all the heavy lifting that they've been doing. >> Before we get to Steve, I just want to say congratulations to you. That's great leadership. And I think you're taking a pragmatic approach and you putting the stake in the ground. And that's the number one thing, and I want to take my hat off to you guys and Priyanka, thank you for that leadership. All right, Stephen, let's talk about how this gets done because you guys open sources is what it's all about is about the people, it's about building on the successes of others, standing on the shoulders of others, you guys are used to sitting in rooms now virtually and squabbling over things like, code reviews and you got governing bodies. This is not a new thing in collaboration. So this is also a collaboration test. What are you seeing as the playbook to get this going? Can you share your insights into what the Kubernetes group's doing and how you see this. What are the few first few steps you see happening? So people can either understand it, understand the context and get involved? >> So I think it comes down to a lot of it is scope, right? So as a new contributor, as a current contributor, maybe you are one of those language experts, that is interested in getting involved as a co-chair myself for SIG Release. A lot of the things that we do, we have to consider scope. If we make this change, how is it affecting an end user? And maybe you work in contributor experience. Maybe you work in release, maybe you work in architecture. But you may not have the entire scope that you need to make a change. So I think that first it's amazing to see all of the thought that has gone through making certain changes, like discussing master and slave, discussing how we name control plane members, doing the... having the discussion around a whitelist and blacklist. What's hard about it is, is when people start making those changes. We've already seen several instances of an invigorated contributor, and maybe the new contributor coming in and starting to kind of like search and replace words. And it... I wish it was that simple, it's a discussion that has to be heard, you need buy-in from the code owners, if it's an API that you're touching, it's a conversation that you need to have with the SIG Architecture, as well as say SIG Docs. If it's something that's happening in Release, then it's a easier 'cause you can come and talk to me, but, overall I think it's getting people to the point where they can clearly understand how a change affects the community. So we kind of in this language evaluation framework, we have this idea of like first, second and third order concerns. And as you go through those concerns, there are like diminishing impacts of potential harm that a piece of language might be causing to people. So first order concerns are the ones that we want to eliminate immediately. And the ones that we commonly hear this discussion framed around. So master-slave and whitelist, blacklist. So those are ones that we know that are kind of like on the track to be removed. The next portion of that it's kind of like understanding what it means to provide a recommendation and who actually approves the recommendation. Because this group is, we have several language aficionados in this group, but we are by now means experts. And we also want to make sure that we do not make decisions entirely for the community. So, discussing that workflow from a turning a recommendation into actuating a solution for that is something that we would also do with the steering committee. So Kubernetes kind of like top governing body. Making sure that the decision is made from the top level and kind of filtered out to all of the places where people may own code or documentation around it is I think is really the biggest thing. And having a framework to make it easy to make, do those evaluations, is what we've been craving and now have. >> Well, congratulations. That's awesome. I think it's always... it's easier said than done. I mean, it's a system when you have systems and code, it's like, there's always consequences in systems architecture, you know that you do in large scales OSS. You guys know what that means. And I think the low hanging fruit, obviously master, slave, blacklist, whitelist, that's just got to get done. I mean, to me, if that just doesn't get done, that's just like a stake in the ground that must happen. But I think this idea of it takes a village, kind of is a play here. People just buy into it. That so it's a little bit of a PR thing going on too, for get buy-in, this is again a classic, getting people on board, Priyanka, isn't it? It's the obvious and then there's like, okay, let's just do this. And then what's the framework? What's the process? What's the scope? >> Yeah, absolutely agree. And many people are midway through the journey. That's one of the big challenges. Some people are on different phases of the journey, and that was one of the big reasons we started this working group, because we want to be able to provide a place of conversation for people at different stages. So we get align now rather than a year later, where everybody has their own terms as replacements and nothing works. And maybe the downstream projects that are affected, like who knows, right? It can go pretty bad. And it's very complex and it's large-scale opensource or coasters, anywhere, large software. And so because team CloudNative belongs to everyone because open source belongs to everyone. We got up, get people on the same page. For those who are eager to learn more, as I said in my keynote, please do join the two sessions that we have planned. One is going to happen, which is about inclusive naming in general, it's an hour and a half session happening on Thursday. I'm pretty sure. And there we will talk about all the various artists who are involved. Everybody will have a seat at the table and we'll have documentation and a presentation to share on how we recommend the all move, move together as an ecosystem, and then second is a presentation by Celeste in the Kubernetes working group about how Kubernetes specifically has done naming. And I feel like Stephen, you and your peers have done such amazing work that many can benefit from it. >> Well, I think engineers, you got two things going to work in for you, which is one, it's a mission. And that's... There's certainly societal benefits for this code, code is for the people. Love that, that's always been the marching orders, but also engineers are efficient. If you have duplicate efforts. I mean, it's like you think about people just doing it on their own, why not do it now, do it together, more efficient, fixing bugs over stuff, you could have solved now. I mean, this is a huge issue. So totally believe it. I know we got to go, but I want to get the news and Priyanka, you guys had some new stuff coming out from the CNCF, new things, survey, certifications, all kinds of new reports. Give us the quick highlights on the news. >> Yes, absolutely. So much news. So many talking points. Well, and that's a good thing, why? Because the CloudNative Ecosystem is thriving. There is so many people doing so much awesome stuff that I have a lot to share with you. And what does that tell us about our spirit? It tells you about the spirit of resilience. You heard about that briefly in the conversation we just had with Stephen about our working group to align various parties and initiatives together, to bring inclusive naming to code. It's about resilience because we did not get demoralized. We did not say, "oh, it's a pandemic. I can't meet anyone. So this isn't happening." No, we kept going. And that is happening in inclusive naming that is happening in the CloudNative series we're doing, that's happening in the new members that are joining, as you may have seen Volcano Engine just joined as platinum member and that's super exciting. They come from China. They're part of the larger organization that builds Tik Tok, which is pretty cool as a frequent bruiser I can say that, in addition, on a more serious note, security is really key and as I was talking to someone just minutes ago, security is not something that's a fad. Security is something that as we keep innovating, as cloud native keeps being the ground zero, for all future innovation, it keeps evolving. The problems keep getting more complex and we have to keep solving them. So in that spirit, we in CNCF see it as our job, our duty, to enable the ecosystem to be better conversant in the security needs of our code. So to that end, we are launching the CKS program, which is a certification for our Kubernetes security specialist. And it's been in the works for awhile as many of you may know, and today we are able to accept registrations. So that's a really exciting piece of news, I recommend you go ahead and do that as part of the KubeCon registration folks have a discount to get started, and I think they should do it now because as I said, the security problems keep getting worse, keep getting more complicated. And this is a great baseline for folks to start when they are thinking about this. it's also a great boon for any company out there, whether they're end users, vendors, it's all sometimes a blurry line between the two, which is all healthy. Everybody needs developers who are security conversant I would say, and this certification help you helps you achieve that. So send all of your people to go take it. So that's sort of the announcements. Then other things I would like to share are as you go, sorry, were you saying something? >> No. Go ahead. >> No, as you know, we talked about the whole thing of team CloudNative is for everyone. Open source is for everyone And I'm really proud that CNCF has offered over 1000 diversity scholarships since 2016 to traditionally under-representing our marginalized groups. And I think that is so nice, and, but just the very, very beginning. As we grow into 2021, you will see more and more of these initiatives. Every member I talked to was so excited that we put our money where our mouth is, and we support people with scholarships, mentorships, and this is only going to grow. And it just so like at almost 17%, the CNCF mentors in our program are women. So for folks who are looking for that inspiration, for folks who want to see someone who looks like them in these places, they have more diverse people to look up to. And so overall, I think our DEI focus is something I'm very proud of and something you may hear about in other news items. And then finally, I would like to say is that CloudNative continues to grow. The cloud native wave is strong. The 2.0 for team CloudNative is going very well. For the CloudNative annual survey, 2020, we found an astonishing number of places where CloudNative technologies are in production. You heard some stories that I told in my keynote of people using multiple CNCF projects together. And these are amazing and users who have this running in production. So our ecosystem has matured. And today I can tell you that Kubernetes is used in production, by at about 83% of the places out there. And this is up by 5% from 78% last year. And just so much strength in this ecosystem. I mean, now at 92% of people are using containers. So at this point we are ubiquitous. And as you've heard from us in various times, our 70 plus project portfolio shows that we are the ground zero of innovation in cloud native. So if you asked me to summarize the news, it's number one, team CloudNative and open source is for everyone. Number two, we take pride in our diversity and over 1000 scholarships have been given out since 2016 to recipients from underrepresented groups. Number three, this is the home base for innovation with 83% of folks using Kubernetes in production and 70 plus projects that deliver a wide variety of support to enterprises as they modernize their software and utilize containers. >> Awesome. That was a great summary. First of all, you're a great host. You should be hosting theCUBE with us. Great keynote, love the virtual events that you guys have been doing, love the innovation. I think I would just say just from my perspective and being from there from the beginning is it's always been inclusive and the experience of the events and the community have been top-notch. People squabble, people talk, people have conversations, but at the end of the day, it is a great community and it's fun, memorable, and people are accepting, it's a great job. Stephen, good job as co-chair this year. Well done. Congratulations. >> Thank you very much. >> Okay. Thanks for coming on, I appreciate it. >> Take it easy. >> Okay, this is theCUBE virtual, we wish we were there in person, but we're not, we're remote. This is the virtual Cube. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital experience Brought to you by Dell Technologies. Hello, everyone. And welcome back to the cubes Coverage of Del Tech World 2020. With me is Jeff Boudreau, the president general manager of Infrastructure Solutions group Deltek. Jeff, always good to see you, my friend. How you doing? >>Good. Good to see you. >>I wish we were hanging out a Sox game or a pat's game, but, uh, I guess this will dio But, you know, it was about a year ago when you took over leadership of I s G. I actually had way had that sort of brief conversation. You were in the room with Jeff Clark. I thought it was a great, great choice. How you doing? How you feeling Any sort of key moments the past 12 months that you you feel like sharing? >>Sure. So I first I want to say, I do remember that about a year ago. So thank you for reminding me. Yeah, it's, uh it's been a very interesting year, right? It's been it's been one year. It was in September was one year since I took over I s G. But I'm feeling great. So thank you for asking. I hope you're doing the same. And I'm really optimistic about where we are and where we're heading. Aziz, you know, it's been an extremely challenging year in a very unpredictable year, as we've all experienced. And I'd say for the, you know, the first part of the year, especially starting in March on I've been really focused on the health and safety of our, you know, the families, our customers and our team members of the team on a lot of it's been shifting, you know, in regards to helping our customers around, you know, work from home or education and learn from home. And, you know, during all this time, though, I'll tell you, as a team, we've accomplished a lot. There's a handful of things that I'm very proud of, you know, first and foremost, that states around the customer experience we have delivered on our best quality in our product. NPS scores in our entire history. So something I'm extremely proud of during this time around our innovation and innovation engine, we part of the entire portfolio which you're well aware of. We had nine launches in nine weeks back in that May in June. Timeframe. So something I'm really proud of the team on, uh, on. Then last, I'd say it's around the team and right, we shifted about 90% of our workforce from the office tow home, you know, from an engineering team. That could be, you know, 85% of my team is engineers and writing code. And so, you know, people were concerned about that. But we didn't skip a beat, so, you know, pretty impressed by the team and what they've done there. So, you know, the strategy remains unchanged. Uh, you know, we're focused on our customers integrating across the entire portfolio and the businesses like VM ware and really focused on getting share. So despite all the uncertainty in the market, I'm pretty pleased with the team and everything that's been going on. So uh, yeah, it's it's been it's been an interesting year, but it's really great. I'm really optimistic about what we have in front of us. >>Yeah, I mean, there's not much you could do a control about the macro condition on it, you know it. Z dealt to us and we have to deal with it. I mean, in your space. It's the sort of countervailing things here one is. Look, you're not selling laptops and endpoint security. That's not your business right in the data center. Eso. But the flip side of that is you mentioned your portfolio refresh. You know, things like Power Store. You got product cycles now kicking in. So that could be, you know, a buffer. What are you seeing with Power Store and what's the uptake look like? They're >>sure. Well, specifically, let me take a step back and the regards the portfolio. So first, you know, the portfolio itself is a direct reflection in the feedback from all our partners and our customers over the last couple of years on Day two, ramp up that innovation. I spent a lot of time in the last few years simplifying under the power brands, which you're well aware of, right? So we had a lot of for a legacy EMC and Legacy dollars. Really? How do we simplify under a set of brands really over delivering innovation on a fewer set of products that really accelerating in exceeding customer needs? And we did that across the board. So from power edge servers, you know, power Max, the high end storage, the Powerball, all that we didn't hear one. And just most recently. And, you know, it's part of the big launches. We had power scale. We have power flex for software to find. And, of course, the new flagship offer for the mid range, which is power store. Um, Specifically, the policy of the momentum has been building since our launch back in May. And the feedback from our partners and our customers has been fantastic. And we've had a lot of big wins against, you know, a lot of a lot of our core competitors. A couple examples one is Arrow Electronics SAA, Fortune 500 Global Elektronik supplier. They leverage power Store to provide, you know, basically both, you know, enterprise computing and storage needs for their for their broader bases around the world on there, really taking advantage of the 41 data reduction, really helping them simplify their capacity planning and really improve operational efficiencies specifically without impacting performance. So it's it's one. We're given the data reductions, but there's no impact on performance, which is a huge value proffer for arrow another big customers tickets and write a global law firm on their reporting to us that over 90 they've had a 90% reduction in their rack space, and they've had over five times two performance over a core competitors storage systems azi. They've deployed power store around the world, really, and it's really been helping them. Thio easily migrate workloads across, so the feedback from the customers and partners has been extremely positive. Um, there really citing benefits around the architecture, the flexibility architecture around the micro services, the containers they're loving, the D M or integration. They're loving the height of the predictable data reduction capabilities in line with in line performance or no performance penalties with data efficiencies, the workload support, I'd say the other big things around the anytime upgrades is another big thing that customers we're really talking about so very excited and optimistic in regards as we continue to re empower store the second half of the year into next year really is the full full year for power store. >>So can I ask you about that? That in line data reduction with no performance hit is that new ipe? I mean, you're not doing some kind of batch data reduction, right? >>No, it's It's new, I p. It's all patented. We've actually done a lot of work in regards to our technologies. There's some of the things we talk about GPS and deep use and smart Knicks and things like that. We've used some offload engines to help with that. So between the software and the hardware, we've had leverage new I. P. So we can actually provide that predictable data reduction. But right with the performance customers need, So we're not gonna have a trade off in regards. You get more efficiencies and less performance or more performance and less efficiency. >>That's interesting. Yeah, when I talked to the chip guys, they talk about this sort of the storage offloads and other offloads we're seeing. These alternative processors really start to hit the market videos. The obvious one. But you're seeing others. Aziz. Well, you're really it sounds like you're taking advantage of that. >>Yeah, it's a huge benefit. I mean, we should, you know, with our partners, if it's Intel's and in videos and folks like that broad comes, it's really leveraging the great innovation that they do, plus our innovation. So if you know the sum of the parts, can you know equal Mauritz a benefit to our customers in the other day? That's what it's all about. >>So it sounds like Cove. It hasn't changed your strategy. I was talking toe Dennis Hoffman and he was saying, Look, you know, fundamentally, we're executing on the same strategy. You know, tactically, there's things that we do differently. But what's your summarize your strategy coming in tow 2021. You know, we're still early in this decade. What are you seeing is the trends that you're trying to take advantage of? What do you excited about? Maybe some things that keep you up at night? >>Yeah, so I'd say, you know, I'll stay with what Dennis said. You know, it's our strategy is not changing its a company. You probably got that from Michael and from job, obviously, Dennis just recently. But for me, it's a two pronged approach. One's all about winning the consolidation in the core infrastructure markets that we could just paid in today. So I think Service Storage Network, we're already clear leader across all those segments that we serve in our you know, we'll continue to innovate within our existing product categories. And you saw that with the nine launches in the nine weeks in my point on that one is we're gonna always make sure that we have best debris offers. If it's a three tier, two tier or converge or hyper converged offer, we wanna make sure that we serve that and have the best innovation possible. In addition to that, though, the secondary piece of the strategy really is around. How do we differentiate value across or innovating across I S G? You know, Dell Technologies and even the broader ecosystems and some of the examples I'll give you right now that we're doing is if you think about innovating across icy, that's all about providing improved customer experience, a set of solutions and offers that really helped simplify customer operations, right? And really give them better T CEOs or better. S L. A. An example of something like that's cloud like it's a SAS based off of that we have. That really helps provide great insights and telemetry to our customers. That helps them simplify their I T operations, and it's a major step forward towards, you know, autonomous infrastructure which is really what they're asking for. Customers of a very happy with the work we've done around Day one, you know, faster, time to value. But now it's like Day two and beyond. How do you really helped me Kinda accelerate the operations and really take that away from a three other big pieces innovating across all technologies. And you know, we do this with VM Ware now live today, and that's just writing. So things like VX rail is an example where we work together and where the clear leader in H C I. Things like Delta Cloud Uh, when we built in V M V C F A, B, M or cloud foundation in Tan Xue delivering an industry leading hybrid cloud platform just recently a VM world. I'm sure you heard about it, but Project Monterey was just announced, and that's an effort we're doing with VM Ware and some other partners. They're really about the next generation of infrastructure. Um, you know, I guess taking it up a notch out of the infrastructure and I've g phase, you know, some of the areas that we're gonna be looking at the end to end solutions to help our customers around six key areas. I'm sure John Rose talking about the past, but things like cloud Edge five g A i m l data management security. So those will be the big things. You'll see us lean into a Z strategies consistent. Some big themes that you'll see us lean into going into next year. >>Yeah, I mean, it is consistent, right? You guys have always tried to ride the waves, vector your portfolio into those waves and add value. I'm particularly impressed with your focus on customer experience, and I think that's a huge deal. You know, in the past, a lot of companies yours included your predecessor. You see, Hey, throwing so many products at me, I can't I don't understand the portfolio. So I mean, focusing on that I think is huge right now because people want that experience, you know, to be mawr cloudlike. And that's that's what you got to deliver. What about any news from from Dell Tech world? Any any announcements that you you wanna highlight that we could talk about? >>Sure. And actually, just touching back on the point you had no about the simplification that is a major 10 of my in regards the organization. So there's three key components that I drive once around customer focus, and that's keeping customers first and foremost. And everything we do to is around axillary that innovation. Engine three is really bringing everything together as one team. So we provide a better outcome to our customers. You know, in that simplification after that you talk about is court toe what we're driving. So I want to do less things, I guess better in the notion of how we do that. What that means to me is, as I make decisions that want to move away from other technologies and really leverage our best of breed type shared type, that's technology. I p people I p I can, you know, e can exceed customer needs in those markets that were serving. So it's actually allows me to x Sorry, my innovation engine, because I shift more and more resource is onto the newer stock now for Del Tech world. Yes, We got some cool stuff coming. You probably heard about a few of them. Uh, we're gonna be announcing a project project Apex. Hopefully you've been briefed on that already. This isn't new news or I'll be in trouble. But that's really around. Our strategy about delivering, simple, consistent as a service experiences for our customers bringing together are dealt technology as a service offering and our cloud strategy together. Onda also our technology offerings in our go to market all under a single unified effort, which Ellison do would be leading. Um, you know, on behalf of our executive leadership team s, that's one big area. And there is also another big one that I'll talk about a sui expand our as a service offers. And we think there's a big power to that in regards to our Dell Technologies. Cloud console solving will be launching a new cloud console that will provide uniformed experience across all the resources and give users and ability toe instantly managed every aspect of their cloud journey with just a few clicks. So going back to your broader point, it's all about simplicity. >>Yeah, we definitely all over Apex. That's something I wanted to ask you about this notion of as a service, really requiring it could have a new mindset, certainly from a pricing and how you talk about the customer experience that it's a whole new customer experience. Your you're basically giving them access. Thio What I would consider more of a platform on giving them some greater flexibility. Yeah, there's some constraints in there, but of course, you know the physical only put so much capacity and before him. But the idea of being ableto dial up, dial down within certain commitments is, I think, a powerful one. How does it change the way in which you you think about how you go about developing products just in terms of you know, this AP economy Infrastructure is code. How how you converse about those products internally and externally. How would you see that shaking >>out Dave? That's an awesome question. And it's actually for its front center. For everything we do, obviously, customers one choice and flexibility what they do. And to your point as we evolved warm or as a service, no specific product and product brands and logos on probably the way of the future. It's the services. It's the experience that you provide in regards to how we do that. So if you think about me, you know, in in infrastructure making infrastructure as a service, you really want to define what that customer experiences. That s L. A. That they're trying toe realize. And then how do we make sure that we build the right solutions? Products feature functions to enable that a law that goes back to the core engineering stuff that we need to dio right now, a lot of that stuff is about making sure that we have the right things around. If it's around developer community. If it's around AP rich, it's around. SdK is it's all about how do we leverage if it's internal source or external open source, if you will. It's regards to How do we do that? No. A thing that I think we all you know what you're well aware but we ought to keep in mind is that the cloud native applications are really relevant. Toe both the on premises, wealthy off premise. So think about things around portability reusability. You know, those are some great examples of just kind of how we think about this as we go forward. But those modern applications were required modern infrastructure, and regardless of how that infrastructure is abstracted now, just think about things like this. Aggregation or compose ability or Internet based computing. It's just it's a huge trend that we have to make sure we're thinking of. So is we. We just aggregate between the physical layers to the software layers and how we provide that to a service that could be think of a modern container based asset that could be repurposed. Either could be on a purpose built thing. It could be deployed in a converge or hyper converged. Or it could be two points a software feature in a cloud. Now, that's really how we're thinking about that, regards that we go forward. So we're talking about building modern assets or components That could be you right once we used many type model, and we can deploy that wherever you want because of some of the abstraction of desegregation that we're gonna do. >>E could see customers in the in the near term saying, I don't care so much about the product. I want the fast one all right with the cheaper one e. >>It's kind of what you talking about, that I talked about the ways. If you think about that regards, you know, maybe it's on a specific brand or portfolio. You look into and you say, Hey, what's the service level that I'd wanted to your point like Hey, for compute or for storage, it's really gonna end up being the specific S l A. And that's around performance or Leighton see, or cost or resiliency they want. They want that experience in that that you know, And that's why they're gonna be looking for the end of the end state. That's what we have to deliver is an engineering. >>So there's an opportunity here for you guys that I wonder if you could comment on. And that's the storage admin E. M. C essentially created. You know, you get this army of people that you know pretty good of provisioning lungs, although that's not really that's a great career path for folks. But program ability is, and this notion of infrastructure is code as you as you make your systems more programmable. Is there a skill set opportunity to take that army of constituents that you guys helped train and grow and over their careers and bring them along into sort of the next decade? This new era? >>I think the the easy answer is yes, I obviously that's a hard thing to do and you go forward. But I think embracing the change in the evolution of change, I think is a great opportunity. And I think there is e mean if you look step back and you think about data management, right? And you think about all the you know all data is not created equal and you know, and it has a life cycle, if you will. And so if it's on edge to Korda, Cloward, depending think about data vaults and data mobility and all that stuff. There's gonna be a bunch of different personas and people touching data along the way. I think the I T advance and the storage admin. They're just one of those personas that we have to help serve and way talk about How do we make them heroes, if you will, in regards to their broader environment. So if they're providing, if they evolve and really helped provide a modern infrastructure that really enables, you know infrastructure is a code or infrastructure as a service, they become a nightie hero, if you will for the rest of team. So I think there's a huge opportunity for them to evolve as the technology evolves. >>Yeah, you talked about you know, your families, your employees, your team s o. You obviously focused on them. You got your products going hitting all the marks. How are you spending your time these days? >>Thes days right now? Well, we're in. We're in our cycle for fiscal 22 planning. Right? And right now, a lot of that's above the specific markets were serving. It's gonna be about the strategy and making sure that we have people focused on those things. So it really comes back to some of the strategy tents were driving for next year. Now, as I said, our focus big time. Well, I guess for the for this year is one is consolidation of the core markets. Major focus for May 2 is going to be around winning in storage, and I want to be very specific. It's winning midrange storage. And that was one of the big reasons why Power Store came. That's gonna be a big focus on Bennett's really making sure that we're delivering on the as a service stuff that we just talked about in regards to all the technology innovation that's required to really provide the customer experience. And then, lastly, it's making sure that we take advantage of some of these growth factors. So you're going to see a dentist. Probably talked a lot about Telco, but telco on edge and as a service and cloud those things, they're just gonna be key to everything I do. So if you think about from poor infrastructure to some of these emerging opportunities Z, I'm spending all my time. >>Well, it's a It's a big business and a really important one for Fidel. Jeff Boudreau. Thanks so much for coming back in the Cube. Really a pleasure seeing you. I hope we can see each other face to face soon. >>You too. Thank you for having me. >>You're very welcome. And thank you for watching everybody keep it right there. This is Dave Volonte for the Cube. Our continuing coverage of Del Tech World 2020. We'll be right back right after this short break